ALBERT

Description: In recent years, the rapid increase in CO2 concentration has accelerated global warming. As a result, sea levels rise, glaciers melt, extreme weather occurs, and species become extinct. As the world’s largest CO2 emission rights trading market, EU Emissions Trading System (EU-ETS) has reached 1.855 billion tons of quotas by 2019, influencing the development of the global carbon emission market. Crude oil, as one of the major fossil energy sources in the world, its price fluctuation is bound to affect the price of carbon emission rights. Therefore, this paper aims to reveal the correlation between crude oil futures prices and carbon emission rights futures prices by studying the price fluctuation. In this paper, the linkage between West Texas Intermediate (WTI) crude oil futures prices and European carbon futures prices was investigated. In addition, this paper selects continuous data of WTI crude oil futures prices and spot prices with European carbon futures prices from January 8, 2018 to November 27, 2020, and builds a smooth transformation regression (STR) model. The relationship between crude oil futures and carbon futures prices is studied in both forward and reversal linkage through empirical analysis. The results show that crude oil futures prices and carbon futures prices have a mutual effect on each other, and both linear and nonlinear correlations between the two prices exist. Based on the results of this research, some suggestions are provided.

Description: We present a high-efficiency method for simulating seawater intrusion (SWI), with mixing, in confined coastal aquifers based on uncoupled equations in the through-flow region of the aquifer. The flow field is calculated analytically and the tracer transport numerically, via spatial splitting along the principal directions (PD) of transport. Advection-dispersion processes along streamlines are simulated with the very efficient matched artificial dispersivity (MAD) method of Syriopoulou and Koussis and the system of discretized transverse-dispersion equations is solved with the Thomas algorithm. These concepts are embedded in the 2D-MADPD-SWI model, yielding comparable solutions to those of the uncoupled SWI equations with the state-of-the-art FEFLOW code, but faster, while 2D-MADPD-SWI achieves an at least hundredfold faster solution than a variable-density flow model. We demonstrate the utility of the 2D-MADPD-SWI model in stochastic Monte Carlo simulations by assessing the uncertainty on the advance of the 1,500 ppm TDS line (limit of tolerable salinity for irrigation) due to randomly variable hydraulic conductivity and freshwater flow rate.

Description: Wastewater stabilization ponds (WSPs) are commonly used to treat municipal wastewater in the Canadian Arctic. Bacterial community structure and functionality remain mostly uncharacterized for arctic WSPs, yet are presumed important for treatment outcomes during the 3-month summer treatment season with open water in the WSPs. The objective of this study was to investigate treatment performance and related temporal and spatial changes in the structure and putative function of bacterial communities during treatment of municipal wastewater in the WSPs of Pond Inlet and Clyde River, Nunavut over two consecutive summer treatment seasons. Influent raw wastewater contained a high organic load and large bacterial communities (~9 log 16S rRNA copies/mL) belonging mainly to Proteobacteria. Although designed to be facultative ponds, both WSPs remained anaerobic with neutral pH values (7.5–7.8) throughout the summer treatment season. Water quality data showed that nutrients [measured as carbonaceous biological oxygen demand (CBOD5)], total suspended solids, and total ammonia nitrogen were progressively reduced during treatment in the ponds as the summer progressed. The pond bacterial population size and species richness depended on the pond temperature (2–18°C), with 8.5 log 16S rRNA copies/mL and the largest alpha diversities (Shannon-Wiener index of 4-4.5) observed mid-season (late July). While the phylogenetic beta diversity in raw wastewater from the two locations remained similar, pond bacterial communities underwent significant (p 〈 0.05) changes to dominance of Comamonadaceae, Geobacteracea, and Porphyromonadaceae. Multivariate distance based redundancy analysis and predicted gene functionalities in the microbiota agreed with water quality results that microbial removal of nutrients (e.g., CBOD5) peaked in the middle of the summer coinciding with the treatment period with the highest pond temperatures. Information from this study will be useful for further development of models to predict biological treatment outcomes, which could be used to size and assess the feasibility of WSPs in extreme climates. Higher pond temperatures resulted in optimal biological processes and nutrient removal in the middle of the summer. While it is challenging to control environmental factors in a passive wastewater treatment system there are some design considerations that could be used to optimize temperature regimes, such as the depth of the pond.

Description: In this study, we demonstrated generation and transmission of 114 Gbaud and 126 Gbaud faster-than-Nyquist (FTN) discrete Fourier transform-spread (DFT-spread) quadrature phase shift keying orthogonal frequency division multiplexing (QPSK-OFDM) with 88-Gsa/s sampling rate digital-to-analog converters (DACs) experimentally. It is the first time to realize 400G FTN DFT-spread QPSK-OFDM signal per optical carrier for metro and regional applications, which will be a solution for network operators to address the issue of increasing bandwidth derived from the rapid popularization of mobile Internet and the wide application of IoT (Internet of Things technology). Delay-and-add filter (DAF) is adopted to realize frequency shaping at the transmitter to keep higher portions of energy of signal at low frequencies, which makes the OFDM much more robust to strong filtering effect. After pre-equalization, bit error rate (BER) performance of 114 GBaud and 126 GBaud FTN DFT-spread QPSK-OFDM has been significantly improved, and maximum-likelihood sequence estimation (MLSE) shows a better effect than binary decoding in the aspect of against the inter symbol interference (ISI) introduced by spectrum compression. The effective bit rate of dual polarization 126 Gbaud FTN DFT-spread QPSK-OFDM which is generated with 88 GSa/s sampling rate is 410.08 Gb/s, to the exclusion of all overhead including TSs, cyclic prefix (CP), and 20% forward error correction (FEC) coding. We successfully transmit 8 × 400 Gbit/s FTN DFT-spread QPSK-OFDM signal generated from 88 Gsa/s sampling rate DAC over 420 km single mode fiber (SMF) with the BER under 2.4 × 10−2.

Description: The impact of heat-absorbing viscoelastic nanofluidic flow along with a convectively heated porous Riga plate with Cattaneo-Christov double flux was analytically investigated. The Buongiorno model nanofluid was implemented with the diversity of Brownian motion and thermophoresis. Making use of the transformations; the PDE systems are altered into an ODE system. We use the homotopy analysis method to solve these systems analytically. The reaction of the apposite parameters on fluid velocity, fluid temperature, nanoparticle volume fraction skin friction coefficients (SFC), local Nusselt number and local Sherwood number are shown with vividly explicit details. It is found that the fluid velocities reflect a declining nature for the development of viscoelastic and porosity parameters. The liquid heat becomes rich when escalating the radiation parameter. In addition, the nanoparticle volume fraction displays a declining nature towards the higher amount of thermophoresis parameter, whereas the inverse trend was obtained for the Brownian motion parameter. We also found that the fluid temperature is increased in viscoelastic nanofluid compared to the viscous nanofluid. When we change the fluid nature from heat absorption to heat generation, the liquid temperature also rises. In addition, the fluid heat is suppressed when we change the flow medium from a stationary plate to a Riga plate for heat absorption/generation cases.

Description: Occurrences and exposure to high levels of microbial bioaerosols such as pathogenic bacteria, fungi, fungal spores, and viruses can be linked to the deterioration of the environment and public health. This study aimed to review the results available for the unusual bioaerosol distribution scenario in the Asian regions. The amount of bioaerosol load and their environmental behavior in the atmosphere is heavily influenced by air pollution such as haze, fog, dust, and particulate matter (PM) and thus strongly affect the air quality index (AQI). Human factors such as heavy traffic, overcrowds, and biomass burning also affected the prevalence or occurrences of bioaerosols in the atmosphere. Seasonal/temporal and diurnal variation was significantly observed from these studies and in the case of South Asia, post-monsoon and winter months were incredibly concentrated with pathogenic bioaerosols. Many human infections, for example, pneumonia, tuberculosis, brucellosis, anthrax, and query fever (Q-fever), are linked to pathogenic bacterial bioaerosols. Respiratory diseases such as asthma and chronic pulmonary obstructiveness are related to fungal bioaerosols, spores, and viral infections. To facilitate the testing and monitoring appraisal of airborne bioaerosols, artificial intelligence, deep neural networks, and machine learning can be used to develop real-time PCR-based bioaerosol sensors. Moreover, mobile apps and compatible electronic gadgets can be developed for the city dwellers to real-time monitor the concentration of bioaerosols in the air they are breathing.

Description: In the context of the energy crisis and environmental deterioration, the integrated energy system (IES) based on multi-energy complementarity and cascaded utilization of energy is considered as an effective way to solve these problems. Due to the different energy forms and the various characteristics in the IES, the coupling relationships among various energy forms are complicated which enlarges the difficulty of energy efficiency evaluation of the IES. In order to flexibly analyze the energy efficiency of the IES, an operation efficiency evaluation model for the IES is established. First, energy utilization efficiency (EUE) and exergy efficiency (EXE) are proposed based on the first/second law of thermodynamics. Second, the energy efficiency models for five processes and four subsystems of the IES are formed. Lastly, an actual commercial-industrial park with integrated energy is employed to validate the proposed method.

Description: The cascades prediction aims to predict the possible information diffusion path in the future based on cascades of the social network. Recently, the existing researches based on deep learning have achieved remarkable results, which indicates the great potential to support cascade prediction task. However, most prior arts only considered either cascade features or user relationship network to predict cascade, which leads to the performance limitation because of the lack of unified modeling for the potential relationship between them. To that end, in this paper, we propose a recurrent neural network model with graph attention mechanism, which constructs a seq2seq framework to learn the spatial-temporal cascade features. Specifically, for user spatial feature, we learn potential relationship among users based on social network through graph attention network. Then, for temporal feature, a recurrent neural network is built to learn their structural context in several different time intervals based on timestamp with a time-decay attention. Finally, we predict the next user with the latest cascade representation which obtained by above method. Experimental results on two real-world datasets show that our model achieves better performance than the baselines on the both evaluation metrics of HITS and mean average precision.

Description: Flows with chemical reactions in porous media are fundamental phenomena encountered in many natural, industrial, and scientific areas. For such flows, most existing studies use continuum assumptions and focus on volume-averaged properties on macroscopic scales. Considering the complex porous structures and fluid–solid interactions in realistic situations, this study develops a sophisticated lattice Boltzmann (LB) model for simulating reactive flows in porous media on the pore scale. In the present model, separate LB equations are built for multicomponent flows and chemical species evolutions, source terms are derived for heat and mass transfer, boundary schemes are formulated for surface reaction, and correction terms are introduced for temperature-dependent density. Thus, the present LB model offers a capability to capture pore-scale information of compressible/incompressible fluid motions, homogeneous reaction between miscible fluids, and heterogeneous reaction at the fluid–solid interface in porous media. Different scenarios of density fingering with homogeneous reaction are investigated, with effects of viscosity contrast being clarified. Furthermore, by introducing thermal flows, the solid coke combustion is modeled in porous media. During coke combustion, fluid viscosity is affected by heat and mass transfer, which results in unstable combustion fronts.

Description: This paper investigates the thermophysical properties and heat transfer performance of graphene nanoplatelet (GNP) and alumina hybrid nanofluids at different mixing ratios. The electrical conductivity and viscosity of the nanofluids were obtained at temperatures between 15–55°C. The thermal conductivity was measured at temperatures between 20–40°C. The natural convection properties, including Nusselt number, Rayleigh number, and heat transfer coefficient, were experimentally obtained at different temperature gradients (20, 25, 30, and 35°C) in a rectangular cavity. The Mouromtseff number was used to theoretically estimate all the nanofluids’ forced convective performance at temperatures between 20–40°C. The results indicated that the thermal conductivity and viscosity of water are increased with the hybrid nanomaterial. On the other hand, the viscosity and thermal conductivity of the hybrid nanofluids are lesser than that of mono-GNP nanofluids. Notwithstanding, of all the hybrid nanofluids, GNP-alumina hybrid nanofluid with a mixing ratio of 50:50 and 75:25 were found to have the highest thermal conductivity and viscosity, enhancing thermal conductivity by 4.23% and increasing viscosity by 15.79%, compared to water. Further, the addition of the hybrid nanomaterials improved the natural convective performance of water while it deteriorates with mono-GNP. The maximum augmentation of 6.44 and 10.48% were obtained for Nuaverage and haverage of GNP-Alumina (50:50) hybrid nanofluid compared to water, respectively. This study shows that hybrid nanofluids are more effective for heat transfer than water and mono-GNP nanofluid.

Description: From the observed datasets, we should be able to produce curve surfaces that have the same characteristics as the original datasets. For instance, if the given data are positive, then the resulting curve or surface must be positive on entire given intervals, i.e., everywhere. In this study, a new partial blended rational bi-quartic spline with C1 continuity is constructed through the partially blended scheme. This rational spline is defined on four corners of the rectangular meshes. The sufficient condition for the positivity of rational bi-quartic spline is derived on four boundary curve networks. There are eight free parameters that can be used for shape modification. The first-order partial derivatives are estimated by using numerical techniques. We also show that the proposed scheme is local quadratic reproducing such that it can exactly reproduce the quadratic surface. We test the proposed scheme to interpolate various types of positive surface data. Based on statistical indicators such as the root mean square error (RMSE) and coefficient of determination (R2), we found that the proposed scheme is on par with some established schemes. In fact, it requires less CPU times (in seconds) to generate the interpolating surface on rectangular meshes. Furthermore, by combining the statistical indicators’ result and graphically visualizing the test functions, the proposed method has the capability to reconstruct very comparable smoothing interpolating positive surfaces compared to some existing schemes. This finding is significant in producing a better interpolating surface for computer graphics applications since the proposed scheme has a smaller error compared with existing schemes.

Description: We study theoretically the properties of local heat originated from energy exchange between electrons passing through a quantum dot (QD) coupled to a phonon bath. The dot is sandwiched between two normal metal leads and also side-coupled to Majorana bound states (MBSs) formed at opposite ends of a topological superconductor nanowire. We find that in addition to the negative differential of heat generation (NDHG) in the Coulomb blockade regime, another NDHG emerges near the leads’ Fermi level due to the dot-MBS coupling. This dual NDHG effect is robust against the variation of intradot Coulomb interaction strength, and disappears if the QD is coupled to regular Fermions. Direct hybridization between the MBSs reduces their impacts on the electronic transport processes, and eliminates the dual NDHG effect. Our results show that the dual NDHG effect is quite efficient for inferring the existence of MBSs, and may remedy some limitations of the detection schemes relying on tunneling spectroscopy technique.

Description: We numerically calculate the quasinormal frequencies of the Klein-Gordon and Dirac fields propagating in a two-dimensional asymptotically anti-de Sitter black hole of the dilaton gravity theory. For the Klein-Gordon field we use the Horowitz-Hubeny method and the asymptotic iteration method for second order differential equations. For the Dirac field we first exploit the Horowitz-Hubeny method. As a second method, instead of using the asymptotic iteration method for second order differential equations, we propose to take as a basis its formulation for coupled systems of first order differential equations. For the two fields we find that the results that produce the two numerical methods are consistent. Furthermore for both fields we obtain that their quasinormal modes are stable and we compare their quasinormal frequencies to analyze whether their spectra are isospectral. Finally we discuss the main results.

Description: The ongoing urbanization requires enhanced understanding of the local meteorological and climatological conditions within the urban environment for multiple applications, concerning energy demand, human health, and spatial planning. Identifying areas with harmful meteorological conditions enables citizens and local authorities to take actions to optimize quality of life for urban dwellers. At the moment cities have (in general) limited networks of meteorological monitoring stations. To overcome this lack of observations, the use of non-traditional data sources is rapidly increasing. However, the use of such data sources without enough prior verification has become a controversial topic in the scientific community. This study aims to verify and assess one of the main non-traditional data sources, i.e. smartphones. The goal is to research the potential of smartphones (using the Samsung Galaxy S4 as an example phone model) to correctly sense air temperature, relative humidity, and solar radiation, and to determine to what extent environmental conditions negatively affect their performance. The smartphone readings were evaluated against observations from reference instrumentation at a weather station and a mobile measurement platform. We test the response time of the smartphone thermometer and hygrometer, and the light sensor’s cosine response. In a lab setting, we find that a smartphone can provide reliable temperature information when it is not exposed to direct solar radiation. The smartphone’s hygrometer performs better at low relative humidity levels while it can over-saturate at higher levels. The light sensor records show substantial correlation with global radiation observations, and short response times. Measurements along an urban transect of 10 km show the smartphone’s ability to react to fast changes of temperature in the field, both in time and space. However, a bias correction (dependent on wind speed and radiation) is required to represent the reference temperature. Finally we show that after such a bias correction, a smartphone record can successfully capture spatial variability over a transect as well.

Description: In this review, we report on recent progress in the generation and application of multichromatic polarization-tailored pulse sequences for the coherent control of multiphoton ionization (MPI) dynamics and present unpublished experimental results that complement our previous findings. Specifically, we utilize single-color, bichromatic, and trichromatic polarization-controlled pulse sequences generated by spectral amplitude, phase and polarization modulation of a carrier-envelope phase (CEP)-stable white light supercontinuum for MPI. The analysis of the number of ionization pathways and the number of distinct final free electron states shows that both increase significantly, but scale differently with the number of absorbed photons and the number of pulses in the sequence. In our experiments, ultrafast polarization shaping is combined with high-resolution photoelectron tomography to generate, control, and reconstruct three-dimensional photoelectron momentum distributions from atomic and molecular MPI. We discuss the use of polarization-controlled single-color and bichromatic pulse sequences in perturbative and non-perturbative coherent control of coupled electron-nuclear dynamics in molecules, atomic spin-orbit wave packet dynamics and the directional photoemission from atoms and chiral molecules. We compare the coherent control of CEP-insensitive intraband multipath interference in the MPI with a fixed number of photons with CEP-sensitive interband multipath interference in the ionization with a different number of photons. The generation and control of free electron vortices with even-numbered rotational symmetry by MPI with single-color pulse sequences is contrasted with the bichromatic control of CEP-sensitive electron vortices with odd-numbered rotational symmetry. To illustrate the potential of multichromatic pulse sequences for coherent control, we present a trichromatic scheme for shaper-based quantum state holography.

Description: Global food and water insecurity could be serious problems in the upcoming decades with growing demands from the increasing global population and more frequent effect of climatic extremes. As the available water resources are diminishing and facing continuous stress, it is crucial to monitor water demand and water availability to understand the associated water stresses. This study assessed the water stress by applying the water supply stress index (WaSSI) in relation to green (WaSSIG) and blue (WaSSIB) water resources across six major cropland basins including the Mississippi (North America), San Francisco (South America), Nile (Africa), Danube (Europe), Ganges-Brahmaputra (Asia), and Murray-Darling (Australia) for the past 17-years (2003–2019). The WaSSIG and WaSSIB results indicated that the Murray-Darling Basin experienced the most severe (maximum WaSSIG and WaSSIB anomalies) green and blue water stresses and the Mississippi Basin had the least. All basins had both green and blue water stresses for at least 35% (6 out of 17 years) of the study period. The interannual variations in green water stress were driven by both crop water demand and green water supply, whereas the blue water stress variations were primarily driven by blue water supply. The WaSSIG and WaSSIB provided a better understanding of water stress (blue or green) and their drivers (demand or supply driven) across cropland basins. This information can be useful for basin-specific resource mobilization and interventions to ensure food and water security.

Description: This study evaluated the agricultural eco-efficiency (AEE) of 77 counties and districts in Jiangsu Province from 1999 to 2018 using the slack-based measure (SBM) of efficiency in data envelopment analysis (DEA) (SBM-DEA) and analyzed its spatiotemporal evolution characteristics and influencing factors. We found that 1) the overall AEE, pure technology efficiency (PTE), and scale efficiency (SE) exhibited a fluctuating downward trend. AEE exhibited a significantly positive spatial association and an increasingly widening regional inequality. 2) AEE featured the “high south” and “low north” spatial pattern, with the high-value regions concentrated around the Taihu Lake plain region in southern Jiangsu Province (Sunan) and low-value regions scattered across most of the northern Jiangsu Province (Subei) cities. The high-high and low-low spatial association types further confirmed the existence of the north–south agglomeration pattern. 3) PTE and SE exhibited a similar “high south” and “low north” spatial pattern to that of AEE. The areas with the growth trends of AEE, PTE, and SE were clustered in Xuzhou and Nanjing city and in the bordering regions between Yangzhou and the Huai’an city, and also between Changzhou and the Wuxi city. 4) Excessive redundant input and use of pesticides, chemical fertilizers, agricultural diesel, labor, land, and agricultural carbon emissions, all have been the primary factors affecting Jiangsu’s AEE. Irrigation also considerably affected AEE, while mechanical power and agricultural film have minimal effects. The majority of counties and districts in the Subei, central Jiangsu Province (Suzhong), and Ningzhen Yang Hilly region experienced excessive usage of chemical fertilizers, pesticides, chemical fertilizers, agricultural diesel, labor, and land. The findings can improve understanding of the spatial association effect and underlying impediment of AEE and can further help policymakers promoting agricultural eco-efficiency.

Description: Water-soluble species constitute a significant fraction (up to 60–70%) of the total aerosol loading in the marine atmospheric boundary layer (MABL). The “indirect” effects, that is, climate forcing due to modification of cloud properties depend on the water-soluble composition of aerosols. Thus, the characterization of aerosols over the MABL is of greater relevance. Here, we present 1-year long aerosol chemical composition data of PM10 and PM2.5 at a costal location in the northeastern Arabian Sea (Goa; 15.45°N, 73.20°E, 56 m above the sea level). Average water-soluble ionic concentration (sum of anion and cation) is highest (25.5 ± 6.9 and 19.6 ± 5.8 μg·m−3 for PM10 and PM2.5, respectively) during winter season and lowest during post-monsoon (17.3 ± 9.1 and 14.4 ± 8.1 μg·m−3 for PM10 and PM2.5, respectively). Among water-soluble ionic spices, SO42- ion was found to be dominant species in anions and NH4+ is dominant in cations, for both PM10 and PM2.5 during all the seasons. These observations clearly hint to the contribution from anthropogenic emission and significant secondary inorganic species formation. Sea-salt (calculated based on Na+ and Cl−) concentration shows significant temporal variability with highest contribution during summer seasons in both fractions. Sea-salt corrected Ca2+, an indicator of mineral dust is found mostly during summer months, particularly in PM10 samples, indicates contribution from mineral dust emissions from arid/semiarid regions located in the north/northwestern India and southwest Asia. These observations are corroborated with back-trajectory analyses, wherein air parcels were found to derive from the desert area in summer and Indo-Gangetic Plains (a hot spot for anthropogenic emissions) during winter. In addition, we also observe the presence of nss-K+ (sea-salt corrected), for PM2.5, particularly during winter months, indicating influence of biomass burning emissions. The impact on aerosol chemistry is further assessed based on chloride depletion. Chloride depletion is observed very significant during post-monsoon months (October and November), wherein more than 80 up to 100% depletion is found, mediated by excess sulfates highlighting the role of secondary species in atmospheric chemistry. Regional scale characterization of atmospheric aerosols is important for their better parameterization in chemical transport model and estimation of radiative forcing.

Description: Atmospheric gravity waves (GWs) are generated in the lower atmosphere by various weather phenomena. They propagate upward, carry energy and momentum to higher altitudes, and appreciably influence the general circulation upon depositing them in the middle and upper atmosphere. We use a three-dimensional first-principle general circulation model (GCM) with implemented nonlinear whole atmosphere GW parameterization to study the global climatology of wave activity and produced effects at altitudes up to the upper thermosphere. The numerical experiments were guided by the GW momentum fluxes and temperature variances as measured in 2010 by the SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) instrument onboard NASA’s TIMED (Thermosphere Ionosphere Mesosphere Energetics Dynamics) satellite. This includes the latitudinal dependence and magnitude of GW activity in the lower stratosphere for the boreal summer season. The modeling results were compared to the SABER temperature and total absolute momentum flux and Upper Atmosphere Research Satellite (UARS) data in the mesosphere and lower thermosphere. Simulations suggest that, in order to reproduce the observed circulation and wave activity in the middle atmosphere, GW fluxes that are smaller than observed fluxes have to be used at the source level in the lower atmosphere. This is because observations contain a broader spectrum of GWs, while parameterizations capture only a portion relevant to the middle and upper atmosphere dynamics. Accounting for the latitudinal variations of the source appreciably improves simulations.

Description: Large-scale disturbances such as ice storms may increase in frequency and intensity as climate changes. While disturbances are a natural component of forest ecosystems, climatically driven alteration to historical patterns may impart fundamental change to ecosystem function. At Hubbard Brook Experimental Forest, NH, experimental ice storms of varying severity were applied to replicate plots of mature northern hardwoods to quantify their effects on forested ecosystems. We assessed ice storm treatment effects on insectivorous foliage-gleaning birds and evaluated insectivore predation on model caterpillars in the understory vegetation. These birds are charismatic, of conservation concern, and are major predators of caterpillars. In turn, lepidopterans are the dominant herbivores in temperate forests and are integral to ecosystem function. We predicted that avian abundance would increase due to additional structural heterogeneity caused by ice treatments, with a concomitant increase in caterpillar predation. Point counts were used to measure insectivorous bird activity in the ice storm experiment plots and additional control plots before and after treatments. We deployed and retrieved plasticine model caterpillars and estimated predation from characteristic marks to these surrogates. Abundance of foliage-gleaning birds was higher in the ice storm plots and birds responded to treatments as a single diffuse disturbance rather than on an individual plot level. All species except one were observed both before and after the ice treatments. Surprisingly, predation on caterpillar models was unaffected by ice storm treatments but rather was a function of caterpillar density. The increase in avian abundance in the ice storm treatment plots corroborates other studies of bird responses to relatively small-scale disturbances in forests and the limited change in species composition was expected given the plot size. We conclude that ice storms may provide beneficial changes for foliage-gleaning birds in the growing season following the disturbance.

Description: The thermodynamic properties of the parabolic-well fluid are considered. The intermolecular interaction potential of this model, which belongs to the class of the so-called van Hove potentials, shares with the square-well and the triangular well potentials the inclusion of a hard-core and an attractive well of relatively short range. The analytic second virial coefficient for this fluid is computed explicitly and an equation of state is derived with the aid of the second-order thermodynamic perturbation theory in the macroscopic compressibility approximation and taking the hard-sphere fluid as the reference system. For this latter, the fully analytical expression of the radial distribution function, consistent with the Carnahan-Starling equation of state as derived within the rational function approximation method, is employed. The results for the reduced pressure of the parabolic-well fluid as a function of the packing fraction and two values of the range of the parabolic-well potential at different temperatures are compared with Monte Carlo and Event‐driven molecular dynamics simulation data. Estimates of the values of the critical temperature are also provided.

Description: Strategies for the use of amendments on agricultural soils are needed to help build resilience against potential soil threats. Gypsum is commonly applied to improve soil quality and nutrient supply. However, the sustainability and environmental safety of some gypsum sources is uncertain. This study aims to i. characterize a new by-product, lacto-gypsum, derived from a dairy whey side stream over a 1 year pilot production cycle and ii. assess the temporal variability of the raw form of lacto-gypsum and the stability of its physico-chemical and compositional properties when stored under three potential storage regimes. Results showed that lacto-gypsum compares favorably with conventional equivalents in terms of nutrient and trace element concentrations and represents an environmentally safe material free of contaminants. Storage form did not affect its main physico-chemical characteristics over time and the raw lacto-gypsum remained stable up to 20 days when stored at 4°C. In contrast to conventional gypsum, the lacto-gypsum had very low pH. In general this new lacto-gypsum shows potential as a suitable product for use as a soil amendment or as an acidification agent for animal slurry to reduce ammonia gas emissions during storage. However, further evaluation of this by-product in real life scenarios is required.

Description: We report the crystal structure and superconducting properties of new V5+2xNb35−xMo35−xIr10Pt15 high-entropy alloys (HEAs) for x in the range of 0 ≤x≤ 10. These HEAs are found to crystallize in a cubic A15-type structure and have a weakly coupled, fully gapped superconducting state. A maximum Tc of 5.18 K and zero-temperature upper critical field Bc2(0) of 6.4 T are observed at x = 0, and both quantities decrease monotonically with the increase of V content x. In addition, Tc shows an increase with increasing valence electron concentration from 6.4 to 6.5, which is compared with other A15-type HEA and binary superconductors.

Description: We investigate here the magnetic properties of a large-scale magnetic flux rope related to a coronal mass ejection (CME) that erupted from the Sun on September 12, 2014 and produced a well-defined flux rope in interplanetary space on September 14–15, 2014. We apply a fully data-driven and time-dependent magnetofrictional method (TMFM) using Solar Dynamics Observatory (SDO) magnetograms as the lower boundary condition. The simulation self-consistently produces a coherent flux rope and its ejection from the simulation domain. This paper describes the identification of the flux rope from the simulation data and defining its key parameters (e.g., twist and magnetic flux). We define the axial magnetic flux of the flux rope and the magnetic field time series from at the apex and at different distances from the apex of the flux rope. Our analysis shows that TMFM yields axial magnetic flux values that are in agreement with several observational proxies. The extracted magnetic field time series do not match well with in-situ components in direct comparison presumably due to interplanetary evolution and northward propagation of the CME. The study emphasizes also that magnetic field time-series are strongly dependent on how the flux rope is intercepted which presents a challenge for space weather forecasting.

Description: The Mpemba effect refers to systems whose thermal relaxation time is a non-monotonic function of the initial temperature. Thus, a system that is initially hot cools to a bath temperature more quickly than the same system, initially warm. In the special case where the system dynamics can be described by a double-well potential with metastable and stable states, dynamics occurs in two stages: a fast relaxation to local equilibrium followed by a slow equilibration of populations in each coarse-grained state. We have recently observed the Mpemba effect experimentally in such a setting, for a colloidal particle immersed in water. Here, we show that this metastable Mpemba effect arises from a non-monotonic temperature dependence of the maximum amount of work that can be extracted from the local-equilibrium state at the end of Stage 1.

Description: Theory and observations of Langmuir waves and turbulence induced in the auroral ionosphere by electron beams of magnetospheric-origin are reviewed. The theoretical discussions include a brief description of the electrostatic dispersion relation, excitation of Langmuir waves by electron beams, and the stability of beam distributions. The theory of Langmuir turbulence—including the parametric decay instability and wave collapse—is also briefly discussed. The main focus of the review, however, is on the observations of Langmuir waves and turbulence in the ionosphere by in-situ and ground-based sensors. A summary of five decades of in-situ wave and particle observations is presented and combined with a collection of more recent results from ground-based instruments. The ground-based observations include signatures of Langmuir turbulence in the form of coherent echoes in incoherent scatter radar measurements; signatures of electron beams in the form of auroral morphologies recorded by high-speed, high-resolution optical imagers; and electromagnetic emissions received on the ground at high latitudes. Uniting the various observations obtained by the vastly different sensors is shown to provide further insight into the micro-scale processes that occur in the ionosphere. Also discussed in this review is the potential of the ground-based sensors to provide a broader spatial and temporal context for single-point in-situ measurements of such processes.

Description: With the fossil energy crisis and environmental pollution, wind energy and other renewable energy have been booming. However, the strong intermittence and volatility of wind power make difficult of its integration into grid. To solve this problem, this study proposes a complementary power generation model of wind-hydropower-pumped storage systems, which uses hydropower and pumped storage to adjust the fluctuation of wind power. How to consider the uncertainty and unpredictability of wind power output and make more reliable hydropower generation plan and pumped storage generation plan is the key problem to be solved in the grid with the high proportion of renewable energy. The martingale model of forecast evolution is used to describe the uncertainty evolution of wind power in different regions. According to the flexible load in the region, the flexibility index is used to quantify flexibility, and the transaction price is set to be proportional to flexibility. The two-stage framework of day-ahead and real-time dispatching model is then developed. In the day-ahead stage, different regions trade with each other. If the power after trading is imbalanced, it will be supplemented by hydropower and the grid to meet the power demand. In the real-time stage, the pumped storage is added to quickly balance the deviation of wind power and load between the real-time and day-ahead stages. Finally, considering the positive effect of hydropower on wind power consumption in the grid, a benefit allocation method based on improved Shapley value method is proposed. Test cases are simulated to verify the rationality of the proposed dispatching model and the benefit allocation method. After the cooperation of hydropower and pumped storage, the average revenue growth is 3.02%. The improved benefit allocation scheme makes more benefit of hydropower and pumped storage and promotes the cooperation of multi-participants.

Description: The development of efficient and cost-effective solar photocatalysts capable of producing hydrogen from formic acid as a hydrogen storage medium is still a challenging issue. Herein, we report that iron minerals, ferric iron hydroxy sulfates (FHS), immobilized on a natural layered silicate, magadiite, can be used as a photocatalyst to produce hydrogen from formic acid under irradiation with solar simulator. The material exhibits the hydrogen production rate of 470 μmol g−1 h−1, which is considerably higher than that obtained on other iron minerals and comparable to that obtained on precious metal-based photocatalyst ever reported. The present result may open a way to design efficient photocatalyst for hydrogen production from formic acid in an economically and environmentally friendly way.

Description: Our research aims to analyze how the uncertainties and risks of the overseas oil & gas investment environment change over time and reveal the specific occurrence probabilities of risk on different levels. In the process of long-drawn overseas oil & gas investment that can last for 30 years or longer, it is difficult for investment decision-makers to grasp the occurrence probabilities and trends of some specific risks accurately and in a timely manner. The overseas risk assessment system has made great progress; however, it has remained elusive due to the challenge of too many complex and interweaved factors. With the advent of big data and artificial intelligence, more precise and specific risk evaluations can be conducted. Our research selects 25 indicators from six dimensions and applies a Cloud parameter Bayesian network algorithm to dynamically assess the oil and gas overseas investment risk of 10 countries. The results reveal how risk dynamics have changed over the past two decades. Our research may serve as a reference in future overseas oil & gas investment risk decision-making, and is also significant to outbound investing, engineering, and service projects. The proper use of risk assessment results can be conducive to potential investors who may invest in potential countries in the future.

Description: In an emergency evacuation, people almost always come in close proximity as they quickly leave a built environment under a potential threat. With COVID19, this situation presents yet another challenge: that of getting unintentionally exposed to an infected individual. To assess the epidemiological consequences of an emergency evacuation, we expanded a popular pedestrian dynamic model to enable social distancing during a normal exit and analyze the effect of possible transmission through respiratory droplets and aerosol. Computer simulations point to a troubling outcome, whereby the benefits of a quick exit could be outweighed by the risk of infection.

Description: This study constructed a comprehensive index system and employed a coupling coordination degree model, global spatial autocorrelation models, and local spatial autocorrelation models to quantitatively investigate the spatiotemporal characteristics and dynamic mechanism of the coupling coordination relationship between green urbanization and green finance in China during 2010–2017. The results showed that the level of green urbanization and green finance improved over the study period, but the development of green finance lagged behind the pace of green urbanization and the comprehensive score was still low. The coupling coordination degree presented a trend of continuous optimization, with coordination in eastern China being clearly higher than in central, western, and northeastern China. Furthermore, there was both spatial dependency and spatial heterogeneity in the coupling coordination degree between green urbanization and green finance. Provinces with a high-high clustering mode were mainly distributed in the eastern region, while provinces in western and northeastern China mainly had a low-low clustering mode in 2010. The high-high clustering mode gradually expanded from eastern to central China, while most provinces in western and northeastern China still exhibited low-low clustering in 2017. This indicates that the coupling coordination degree between green urbanization and green finance had strong spatial agglomeration and spatial spillover effects in central and eastern China, while in western and northeastern China its development was still poor.

Description: Molecular simulations such as Molecular Dynamics (MD) and Monte Carlo (MC) have gained increasing importance in the explanation of various physicochemical and biochemical phenomena in soft matter and help elucidate processes that often cannot be understood by experimental techniques alone. While there is a large number of computational studies and developments in MD, MC simulations are less widely used, but they offer a powerful alternative approach to explore the potential energy surface of complex systems in a way that is not feasible for atomistic MD, which still remains fundamentally constrained by the femtosecond timestep, limiting investigations of many essential processes. This paper provides a review of the current developments of a MC based code, SIMONA, which is an efficient and versatile tool to perform large-scale conformational sampling of different kinds of (macro)molecules. We provide an overview of the approach, and an application to soft-matter problems, such as protocols for protein and polymer folding, physical vapor deposition of functional organic molecules and complex oligomer modeling. SIMONA offers solutions to different levels of programming expertise (basic, expert and developer level) through the usage of a designed Graphical Interface pre-processor, a convenient coding environment using XML and the development of new algorithms using Python/C++. We believe that the development of versatile codes which can be used in different fields, along with related protocols and data analysis, paves the way for wider use of MC methods. SIMONA is available for download under http://int.kit.edu/nanosim/simona.

Description: Pull-in instability was an important phenomenon in microelectromechanical systems (MEMS). In the past, MEMS were usually assumed to work in an ideal environment. But in the real circumstances, MEMS often work in dust-filled air, which is equivalent to working in porous media, that's mean fractal space. In this paper, we studied MEMS in fractal space and established the corresponding model. At the same time, we can control the occurrence time and stable time of pull-in by adjusting the value of the fractal index, and obtain a stable pull-in phenomenon.

Description: This work presents an optimized probabilistic modeling methodology that facilitates the modeling of photovoltaic (PV) modules with measured data over a range of environmental conditions. The method applies cuckoo search to optimize kernel parameters, followed by electrical characteristics estimation via relevance vector machine. Unlike analytical modeling techniques, the proposed cuckoo search-relevance vector machine (CS-RVM) takes advantages of no required knowledge of internal PV parameters, more accurate estimation capability and less computational effort. A comparative study has been done among the electrical characteristics predicted by back-propagation neural network (BPNN), radial basis function neural network (RBFNN), support vector machine (SVM), Villalva's model, relevance vector machine (RVM), and the CS-RVM. Experimental results show that the proposed CS-RVM provides the best prediction in most scenarios.

Description: The study of the use of nanotechnology for drug delivery has been extensive. Nanomedical approaches for therapeutics; drug delivery in particular is superior to conventional methods in that it allows for controlled targeted delivery and release, higher stability, extended circulation time, minimal side-effects, and improved pharmacokinetic clearance (of the drug) form the body, to name a few. The magnitude of COVID-19, the current ongoing pandemic has been severe; it has caused widespread the loss of human life. In individuals with severe COVID-19, immune dysregulation and a rampant state of hyperinflammation is observed. This kind of an immunopathological response is detrimental and results in rapid disease progression, development of secondary infections, sepsis and can be fatal. Several studies have pin-pointed the reason for this immune dysregulation; deviations in the signaling pathways involved in the mediation and control of immune responses. In severe COVID-19 patients, many signaling cascades including JAK/STAT, NF-κB, MAPK/ERK, TGF beta, VEGF, and Notch signaling were found to be either upregulated or inactivated. Targeting these aberrant signaling pathways in conjunction with antiviral therapy will effectuate mitigation of the hyperinflammation, hypercytokinemia, and promote faster recovery. The science of the use of nanocarriers as delivery agents to modulate these signaling pathways is not new; it has already been explored for other inflammatory diseases and in particular, cancer therapy. Numerous studies have evaluated the efficacy and potential of nanomedical approaches to modulate these signaling pathways and have been met with positive results. A treatment regime, that includes nanotherapeutics and antiviral therapies will prove effective and holds great promise for the successful treatment of COVID-19. In this article, we review different nanomedical approaches already studied for targeting aberrant signaling pathways, the host immune response to SARS-CoV-2, immunopathology and the dysregulated signaling pathways observed in severe COVID-19 and the current treatment methods in use for targeting signaling cascades in COVID-19. We then conclude by suggesting that the use of nanomedical drug delivery systems for targeting signaling pathways can be extended to effectively target the aberrant signaling pathways in COVID-19 for best treatment results.

Description: This paper introduces a novel linked structure-content representation of federal statutory law in the United States and analyzes and quantifies its structure using tools and concepts drawn from network analysis and complexity studies. The organizational component of our representation is based on the explicit hierarchical organization within the United States Code (USC) as well an embedded cross-reference citation network. We couple this structure with a layer of content-based similarity derived from the application of a “topic model” to the USC. The resulting representation is the first that explicitly models the USC as a “multinetwork” or “multilayered network” incorporating hierarchical structure, cross-references, and content. We report several novel descriptive statistics of this multinetwork. These include the results of this first application of the machine learning technique of topic modeling to the USC as well as multiple measures articulating the relationships between the organizational and content network layers. We find a high degree of assortativity of “titles” (the highest level hierarchy within the USC) with related topics. We also present a link prediction task and show that machine learning techniques are able to recover information about structure from content. Success in this prediction task has a natural interpretation as indicating a form of mutual information. We connect the relational findings between organization and content to a measure of “ease of search” in this large hyperlinked document that has implications for the ways in which the structure of the USC supports (or doesn’t support) broad useful access to the law. The measures developed in this paper have the potential to enable comparative work in the study of statutory networks that ranges across time and geography.

Description: LixFePO4 orthophosphates and fluorite- and pyrochlore-type zirconate materials are widely considered as functional compounds in energy storage devices, either as electrode or solid state electrolyte. These ceramic materials show enhanced cation exchange and anion conductivity properties that makes them attractive for various energy applications. In this contribution we discuss thermodynamic properties of LixFePO4 and yttria-stabilized zirconia compounds, including formation enthalpies, stability, and solubility limits. We found that at ambient conditions LixFePO4 has a large miscibility gap, which is consistent with existing experimental evidence. We show that cubic zirconia becomes stabilized with Y content of ~8%, which is in line with experimental observations. The computed activation energy of 0.92eV and ionic conductivity for oxygen diffusion in yttria-stabilized zirconia are also in line with the measured data, which shows that atomistic modeling can be applied for accurate prediction of key materials properties. We discuss these results with the existing simulation-based data on these materials produced by our group over the last decade. Last, but not least, we discuss similarities of the considered compounds in considering them as materials for energy storage and radiation damage resistant matrices for immobilization of radionuclides.

Description: Nuclear reaction rates are one of the most important ingredients in describing how stars evolve. The study of the nuclear reactions involved in different astrophysical sites is thus mandatory to address most questions in nuclear astrophysics. Direct measurements of the cross-sections at stellar energies are very challenging–if at all possible. This is essentially due to the very low cross-sections of the reactions of interest (especially when it involves charged particles), and/or to the radioactive nature of many key nuclei. In order to overcome these difficulties, various indirect methods such as the transfer reaction method at energies above or near the Coulomb barrier are used to measure the spectroscopic properties of the involved compound nucleus that are needed to calculate cross-sections or reaction rates of astrophysical interest. In this review, the basic features of the transfer reaction method and the theoretical concept behind are first discussed, then the method is illustrated with recent performed experimental studies of key reactions in nuclear astrophysics.

Description: Revegetation is regarded as an effective means to improve the ecological environment in deserts and profoundly influences the potential ecological functions of the soil fungal community. Therefore, Illumina high-throughput sequencing was performed to characterize the soil fungal diversity and community composition at two soil depths (0–10 cm and 10–20 cm) with four revegetation durations (natural grassland, half-mature, nearly mature, and mature Pinus. sylvestris var. mongolica plantations) in the Mu Us Sandy Land, China. The effects of soil properties on soil fungal communities were also examined to reveal the connection between fungal function and soil environment. The results indicated that 1) soil nutrient content and enzyme activity showed significant differences through the restoration durations, 2) there was no significant effect of soil depth on soil fungal diversity, while the Shannon diversity index of all fungal communities was significantly different among different revegetation durations, 3) compared with grassland, ectomycorrhizal fungi (notably, Inocybe, Tuber, and Calostoma) were abundant in plantations. The endophyte fungus Mortierella was among the top 10 genera in all soil samples and arbuscular mycorrhizal fungus Diversispora was the indicator genus of the grassland, and 4) catalase and total nitrogen were the main factors affecting fungal community composition and were closely related to saprotrophs and pathotrophs, respectively. This new information indicates the variation of soil fungal communities along revegetation durations and highlights the interaction between fungal functions and desert ecosystems.

Description: After the launch of STEREO twin spacecraft, and most recently of Solar Orbiter and Parker Solar Probe spacecraft, the next mission that will explore Sun-Earth interactions and how the Sun modulates the Heliosphere will be the “Lagrange” mission, which will consist of two satellites placed in orbit around L1 and L5 Sun-Earth Lagrangian points. Despite the significant novelties that will be provided by such a double vantage point, there will be also missing information, that are briefly discussed here. For future heliospheric missions, an alternative advantageous approach that has not been considered so far would be to place two twin spacecraft not in L1 and L5, but in L4 and L5 Lagrangian points. If these two spacecraft will be equipped with in situ instruments, and also remote sensing instruments measuring not only photospheric but also coronal magnetic fields, significant advancing will be possible. In particular, data provided by such a twin mission will allow to follow the evolution of magnetic fields from inside the Sun (with stereoscopic helioseismology), to its surface (with classical photospheric magnetometers), and its atmosphere (with spectro-polarimeters); this will provide a tremendous improvement in our physical understanding of solar activity. Moreover, the L4-L5 twin satellites will take different interesting configurations, such as relative quadrature, and quasi-quadrature with the Earth, providing a baseline for monitoring the Sun-to-Earth propagation of solar disturbances.

Description: Using the SDSS spectroscopy, we have carried out fine optical spectral classification for activity types for 710 AGN candidates. These objects come from a larger sample of some 2,500 candidate AGN using pre-selection by various samples; bright objects of the Catalog of Quasars and Active Galactic Nuclei, AGN candidates among X-ray sources, optically variable radio sources, IRAS extragalactic objects, etc. A number of papers have been published with the results of this spectral classification. More than 800 QSOs have been identified and classified, including 710 QSOs, Seyferts and Composites. The fine classification shows that many QSOs show the same features as Seyferts, i.e., subtypes between S1 and S2 (S1.2, S1.5, S1.8 and S1.9). We have introduced subtypes for the QSOs: QSO1.2, QSO1.5, QSO1.8, QSO1.9, though the last subtype does not appear in SDSS wavelength range due to mostly highly redshifted Hα (the main line for identification of the 1.9 subtype). Thus, independent of the luminosity (which serves as a separator between QSOs and Seyferts), AGN show the same features. We also have classified many objects as Composites, spectra having composite characteristics between Sy and LINERs, Sy and HII or LINERs and HII; in some cases all three characteristics appear together resulting as Sy/LINER/HII subtype. The QSOs subtypes together with Seyfert ones allow to follow AGN properties along larger redshift range expanding our knowledge on the evolution of AGN to more distant Universe represented by QSOs.

Description: In semi-arid to arid regions, both anthropogenic sources (urban and agriculture) and deeper Critical Zone (groundwater with long flow paths and water residence times) may play an important role in controlling chemical exports to rivers. Here, we combined two anthropogenic isotope tracers: uranium isotope ratios (234U/238U) and boron isotope ratios (δ11B), with the 87Sr/86Sr ratios to identify and quantify multiple solute (salinity) sources in the Rio Grande river in southern New Mexico and western Texas. The Rio Grande river is a major source of freshwater for irrigation and municipal uses in southwestern United States. There has been a large disagreement about the dominant salinity sources to the Rio Grande and particularly significant sources are of anthropogenic (agriculture practices and shallow groundwater flows, groundwater pumping, and urban developments) and/or geological (natural groundwater upwelling) origins. Between 2014 and 2016, we collected monthly river samples at 15 locations along a 200-km stretch of the Rio Grande river from Elephant Butte Reservoir, New Mexico to El Paso, Texas, as well as water samples from agricultural canals and drains, urban effluents and drains, and groundwater wells. Our study shows that due to the presence of localized and multiple salinity inputs, total dissolved solids (TDS) and isotope ratios of U, B, and Sr in the Rio Grande river show high spatial and temporal variability. Several agricultural, urban, and geological sources of salinity in the Rio Grande watershed have characteristic and distinguishable U, Sr, and B isotope signatures. However, due to the common issue of overlapping signatures as identified by previous tracer studies (such as δ18O, δD, δ34S), no single isotope tracer of U, Sr, or B isotopes was powerful enough to distinguish multiple salinity sources. Here, combining the multiple U, Sr, and B isotope and elemental signatures, we applied a multi-tracer mass balance approach to quantify the relative contributions of water mass from the identified various salinity end members along the 200-km stretch of the Rio Grande during different river flow seasons. Our results show that during irrigation (high river flow) seasons, the Rio Grande had uniform chemical and isotopic compositions, similar to the Elephant Butte reservoir where water is stored and well-mixed, reflecting the dominant contribution from shallow Critical Zone in headwater regions in temperate southern Colorado and northern New Mexico. In non-irrigation (low flow) seasons when the river water is stored at Elephant Butte reservoir, the Rio Grande river at many downstream locations showed heterogeneous chemical and isotopic compositions, reflecting variable inputs from upwelling of groundwater (deeper CZ), displacement of shallow groundwater, agricultural return flows, and urban effluents. Our study highlights the needs of using multi-tracer approach to investigate multiple solutes and salinity sources in rivers with complex geology and human impacts.

Description: A fast and automatically controlled frequency-tunable radiofrequency (rf) system is installed in an rf plasma thruster consisting of a stepped-diameter insulator source tube wound by a single-turn loop antenna and a solenoid providing a magnetic nozzle, and immersed in vacuum. The frequency and the output power are controlled so as to minimize the reflection coefficient and to maintain the net power corresponding to the forward minus reflected powers at a constant level. The reproducibility of the impedance matching and the stability of the net rf power are assessed, showing the fast impedance matching within about 10 msec and the long and stable delivery of the rf power to the thruster. When increasing the rf power up to 500 W, discontinuous changes in the source plasma density, the imparted thrust, and the signal intensity of the ion beam downstream of the thruster are observed, indicating effects of the discharge mode on the thruster performance and the ion energy distribution.

Description: We demonstrate a new memristive device (IL-Memristor), in which an ionic liquid (IL) serve as a material to control the volatility of the resistance. ILs are ultra-low vapor pressure liquids consisting of cations and anions at room temperature, and their introduction into solid-state processes can provide new avenues in electronic device fabrication. Because the device resistance change in IL-Memristor is governed by a Cu filament formation/rupture in IL, we considered that the Cu filament stability affects the data retention characteristics. Therefore, we controlled the data retention time by clarifying the corrosion mechanism and performing the IL material design based on the results. It was found out that the corrosion of Cu filaments in the IL was ruled by the comproportionation reaction, and that the data retention characteristics of the devices varied depending on the valence of Cu ions added to the IL. Actually, IL-Memristors involving Cu(II) and Cu(I) show volatile and non-volatile nature with respect to the programmed resistance value, respectively. Our results showed that data volatility can be controlled through the metal ion species added to the IL. The present work indicates that IL-memristor is suitable for unique applications such as artificial neuron with tunable fading characteristics that is applicable to phenomena with a wide range of timescale.

Description: Pinoresinol is a high-value monolignol-derived lignan used in plant defense and with human health-supporting effects. The synthetic yield and isolation efficiency of racemic pinoresinol from coniferyl alcohol by conventional radical coupling methods is sub-optimal. In this work, a facile and efficient synthetic approach was developed to synthesize pinoresinol with much higher yield. By using 5-bromoconiferyl alcohol, which was synthesized in high yield from 5-bromovanillin, to make 5,5′-bromopinoresinol via a peroxidase-mediated radical coupling reaction takes advantage of the smaller variety of radical coupling products from the 5-substituted monolignol, producing simpler product mixtures from which 5,5′-bromopinoresinol may be readily crystalized with good yield (total yield of 44.1% by NMR; isolated crystalline yield of 24.6%). Hydro-debromination of the crystalline 5,5′-bromopinoresinol to pinoresinol was essentially quantitative. Gram quantities of pinoresinol were conveniently synthesized by using this approach. This simple alternative pathway to make pinoresinol will impact pinoresinol-related research including structural characterization and modification of lignins, as well as clinical applications of pinoresinol and its derivatives.

Description: Mirror modes in collisionless high-temperature plasmas represent macroscopic high-temperature quasi-superconductors with bouncing electrons in discrete-particle resonance with thermal ion-sound noise contributing to the ion-mode growth beyond quasilinear stability. In the semi-classical Ginzburg-Landau approximation the conditions for phase transition are reviewed. The quasi-superconducting state is of second kind causing a magnetically perforated plasma texture. Focussing on the interaction of mirror bubbles we apply semi-classical Josephson conditions and show that a mirror perforated plasma emits weak electromagnetic radiation which in the magnetosheath should be in the sub-millimeter, respectively, infrared range. This effect might be of astrophysical importance.

Description: Monocyclic aromatic hydrocarbons such as benzene, toluene and xylene are thought to play an important role as precursors to the formation of polycyclic aromatic hydrocarbons (PAHs) and their methylated counterparts in a range of astrophysical environments. Benzene has been detected in two carbon rich objects and models have predicted that it could also be present in the interstellar medium (ISM). It has hence been speculated that small aromatic molecules are present in molecular clouds in the ISM, although they have not been detected to date. If they are present in the ISM, they are likely to exist in water-ice dominated icy mantles on the surface of dust grains.We present a laboratory study of benzene, toluene and two xylene isomers (ortho- and para-xylene) in the presence of water ice on a carbonaceous model dust grain surface (highly oriented pyrolytic graphite, HOPG). Temperature programmed desorption (TPD) shows how the desorption of the molecules is affected by the presence of water ice. The importance of these data for astrophysical situations is demonstrated by the use of TPD-derived kinetic parameters to generate a simple model of desorption in dense molecular clouds on an astrophysical timescale. Since benzene, toluene and xylene have not been detected in water-dominated icy mantles to date, desorption has been simulated in a range of different water-containing environments to show the different behaviour expected depending on ice composition. The simulations demonstrate how future observations of aromatic molecules in dense molecular clouds at known temperatures could reveal which environments the molecules are in. Data from these experiments are also used to predict the behaviour of other, larger, aromatic molecules such as PAHs. Reflection absorption infrared spectroscopy (RAIRS) is also used to record the infrared spectra of the small molecules in different water ice configurations. These spectra can be used to aid identification of these icy aromatics in future observations, such as those that will be possible with the James Webb Space Telescope (JWST). In all cases, spectra of mixed ices consisting of the aromatic molecule and amorphous water ice show evidence of interactions between the water ice and the aromatic species.

Description: Folding, kinking, curling and vortical optical forms are distinctive features of most bright auroral displays. These forms are symptomatic of non-linear forcing of the plasma above auroral arcs resulting from the intensification of electrical currents and Alfvén waves along high-latitude geomagnetic field-lines during periods of disturbed space weather. Electrons accelerated to energies sufficient to carry these currents impact the atmosphere and drive visible emission with spatial structure and dynamics that replicate the morphology and time evolution of the plasma region where the acceleration occurs. Movies of active auroral displays, particularly when combined with conjugate in-situ fields and plasma measurements, therefore capture the physics of a driven, non-linearly evolving space plasma system. Here a perspective emphasizing the utility of combining in-situ measurements through the auroral acceleration region with high time and spatial resolution auroral imaging for the study of space plasma turbulence is presented. It is demonstrated how this special capacity reveals the operation of a cascade of vortical flows and currents through the auroral acceleration region regulated by the physics of Alfvén waves similar to that thought to operate in the Solar wind.

Description: The aim of the paper is to identify the consequence of the Constructal Principle in the field of Thermoeconomics of (energy) production systems. This Principle has been recently formulated as an extension of the Maximum Entropy Production Principle and it has been used in literature to explain the shape and structure of all kind of flowing systems. First, the concept of Thermoeconomic Environment is defined consistently with the consumption of environmental resources and residual emissions, which inherently characterize every kind of production system. This approach allows to infer that the evolution of any energy system is strictly related to the exploitation of resources from the Thermoeconomic Environment. Moreover, the widely accepted assumption that energy systems have to be optimized by minimizing the specific resource (exergy) cost of products, has to be regarded as a consequence of a physical principle that tells us which energy systems can persist in time (to survive) and which others would be selected for extinction. The paper shows how the creation of a recycle may allow a reduction of the unit exergy cost of the product, obtaining a more sustainable behavior of the macro-system, made up by the production process together with its supply chains, consistently with the Constructal Principle. Finally, the definition of the Thermoeconomic Environment allows (at least in principle) to properly identify the resource (exergy) cost of disposing off residues and sub-products directly in the environment, without any kind of additional operation. As a consequence, residues and sub-products have to be generally converted into some kind of product by different (new) production processes, supporting the paradigm of the Circular Economy and highlighting the importance of recycling not only for system efficiency, but for system surviving. More generally, the results obtained may be regarded as the physical justifications of the evolutionary tendency toward the more and more complex and highly circular pathways that can be observed in both natural and artificial (energy) production systems.

Description: With the objective of better understanding the sources and dynamics of carbonaceous fractions of the aerosols present in the atmosphere of Montreal, we implemented here an online wet oxidation/isotope ratio mass spectrometry (IRMS) method to simultaneously measure both water-soluble organic carbon (WSOC) content and the corresponding δ13C of aerosol samples collected at four monitoring stations over a 1-year period representing distinct types of environmental conditions (i.e., background, road traffic, industrial, and downtown). We coupled these data with the corresponding concentrations of other carbon fractions: total carbon (TC), elemental carbon plus organic carbon (EC + OC), and carbonates. Results show that TC (6.64 ± 2.88 μg m–3), EC + OC (4.98 ± 2.23 μg m–3), and carbonates (1.71 ± 1.09 μg m–3) were characterized by lower concentrations in winter and higher ones between spring and early autumn, with all fractions expectedly showing significantly lower concentrations for aerosols collected at the background station. We observed a seasonal dependence of the δ13CEC+OC (−25.31 ± 0.94‰) with the EC + OC/total suspended particles (TSP) ratio: (i) an increase of the ratio during late spring, summer and early autumn associated to road traffic emissions characterized by a δ13C of ∼−25‰ and (ii) lower ratios during the winter months indicating the influence of two distinct emission sources, a first one with a δ13C ∼−27‰, suggesting the local influence of combined biomass burning from residential heating and of fossil fuel combustion, and a second one with a δ13C ∼−21‰, likely related to more regional emissions. WSOC (1.14 ± 0.67 μg m–3) presented a similar seasonal pattern for all monitoring stations, with low concentrations in winter, early spring and late autumn that rapidly increased until summer. Our results indicate that this seasonality is controlled by higher anthropogenic contributions from southern Canada and northeastern United States regions and probably from biogenic emissions during the warm months. Moreover, δ13CWSOC (−25.08 ± 1.47‰) showed a 13C-depletion in summer, indicating higher fossil fuel and biogenic contributions, whereas the higher isotope compositions observed in winter may result from the photochemical aging of regional aerosols. Ultimately, we identified the influence of local industrial emissions late in 2013 as well as the impact of aerosol emissions associated to the Lac-Mégantic rail disaster that occurred on July 6, ∼200 km east of Montreal.

Description: Planning for the research and development (R&D) of renewable energy resources (RERs) has not received enough attention. This paper aims to study the planning for the R&D of RERs in order to avoid bottlenecks and ensure sustainable development in developing marine economies. We have established a triple difference model (DDD) model and a wise pig game model between the theoretical government and enterprise. The data on RERs come from the World Bank and International Energy Agency databases. We have three contributions on the basis of distinguishing between mature and immature marine RERs technologies. First, it emphasizes the importance of developing R&D planning for marine RERs immature technology in the future. Second, the DDD model is used to empirically establish whether RERs planning has a significant positive impact on RERs’ output, which explains the importance of existing RERs planning. Third, the wise pig game model is used to analyze the welfare benefits to the government brought by the R&D planning of marine RERs which proves the importance of future RERs R&D planning.

Description: Hydroelectric facilities often release water at variable rates over the day to match electricity demand, resulting in short-term variability in downstream discharge and water levels. This sub-daily variability, known as hydropeaking, has mostly been studied at large facilities. The ongoing global proliferation of small hydropower (SHP) facilities, which in Brazil are defined as having installed capacities between 5 and 30 MW, raises the question of how these facilities may alter downstream flow regimes by hydropeaking. This study examines the individual and cumulative effects of hydropower facilities on tributaries in the upland watershed of the Pantanal, a vast floodplain wetland system located on the upper Paraguay River, mostly in Brazil. Simultaneous hourly discharge measurements from publicly available reference and downstream gage stations were analyzed for 11 reaches containing 24 hydropower facilities. Most of the facilities are SHPs and half are run-of-river designs, often with diversion channels (headraces). Comparison of daily data over an annual period, summarized by indicators of hydrological alteration (HA) that describe the magnitude, frequency, rate of change, and duration of flows, revealed differences at sub-daily scales attributable to hydropeaking by the hydropower facilities. Results showed statistically significant sub-daily HA in all 11 reaches containing hydropower facilities in all months. Discharge indicators that showed the highest percentage of days with increased variability were the mean rates of rise and fall, amplitude, duration of high pulses, maximum discharge, and number of reversals. Those that showed higher percentages of decreased variability included minimum discharge, number of high pulses, duration of stability, and number of low pulses. There was no correlation between HA values and physical characteristics of rivers or hydropower facilities (including installed capacity), and reaches with multiple facilities did not differ in HA from those with single facilities. This study demonstrates that SHPs as well as larger hydropower facilities cause hydrological alterations attributable to hydropeaking. Considering the rapid expansion of SHPs in tropical river systems, there is an urgent need to understand whether the ecological impacts of hydropeaking documented in temperate biomes also apply to these systems.

Description: The Sustainable Development Goals (SDG) have become the international framework for sustainability policy. Its legacy is linked with the Millennium Development Goals (MDG), established in 2000. In this paper a scientometric analysis was conducted to: (1) Present a new methodological approach to identify the research output related to both SDGs and MDGs (M&SDGs) from 2000 to 2017, with the aim of mapping the global research related to M&SDGs; (2) Describe the thematic specialization based on keyword co-occurrence analysis and citation bursts; and (3) Classify the scientific output into individual SDGs (based on an ad-hoc glossary) and assess SDGs interconnections. Publications conceptually related to M&SDGs (defined by the set of M&SDG core publications and a scientometric expansion based on direct citations) were identified in the in-house CWTS Web of Science database. A total of 25,299 publications were analyzed, of which 21,653 (85.59%) were authored by Higher Education Institutions (HEIs) or academic research centers (RCs). The findings reveal the increasing participation of these organizations in this research (660 institutions in 2000–2005 to 1,744 institutions involved in 2012–2017). Some institutions present both a high production and specialization on M&SDG topics (e.g., London School of Hygiene & Tropical Medicine and World Health Organization); and others with a very high specialization although lower production levels (e.g., Stockholm Environment Institute). Regarding the specific topics of research, health (especially in developing countries), women, and socio-economic issues are the most salient. Moreover, it has been observed an important interlinkage in the research outputs of some SDGs (e.g., SDG11 “Sustainable Cities and Communities” and SDG3 “Good Health and Well-Being”). This study provides first evidence of such interconnections, and the results of this study could be useful for policymakers in order to promote a more evidenced-based setting for their research agendas on SDGs.

Description: Resources and environment management have always been a research hotspot. In the context of sustainable development and environmental governance, scholars and policy makers have been increasing their research efforts on natural resource utilization and its environmental impact. By using the Web of Science Core Collection database, this article applies the bibliometric method to accomplish a systematic review about studies on accounting and management of natural resource consumption based on input-output method. The results indicate that both in terms of the quantity and quality of academic achievements and international cooperation, China is in high academic position and has made great contributions to the development in this research field. While energy and water account for a large proportion of the study objects, more attention is paid on the other kinds of natural resources, such as land, metal, and ocean. International trade is an eternal hot topic in this field. With the continuous progress of the multi-regional input-output model, the importance and feasibility in the analysis of sub-national level or region in the global supply chain gradually emerged. Combining input-output model with other methods can obtain more comprehensive and accurate results for scientific decision-making. Meanwhile, the uncertainty and limitations inherent in such models clearly need further attention.

Description: The southern Amazonia is undergoing a major biophysical transition, involving changes in land use and regional climate. This study provides new insights on the relationship between hydroclimatic variables and vegetation conditions in the upper Madeira Basin (~1 × 106 km2). Vegetative dynamics are characterised using the normalized difference vegetation index (NDVI) while hydroclimatic variability is analysed using satellite-based precipitation, observed river discharge, satellite measurements of terrestrial water storage (TWS) and downward shortwave radiation (DSR). We show that the vegetation in this region varies from energy-limited to water-limited throughout the year. During the peak of the wet season (January-February), rainfall, discharge and TWS are negatively correlated with NDVI in February-April (r = −0.48 to −0.65; p 〈 0.05). In addition, DSR is positively correlated with NDVI (r = 0.47–0.54; p 〈 0.05), suggesting that the vegetation is mainly energy-limited during this period. Outside this period, these correlations are positive for rainfall, discharge and TWS (r = 0.55–0.88; p 〈 0.05), and negative for DSR (r = −0.47 to −0.54; p 〈 0.05), suggesting that vegetation depends mainly on water availability, particularly during the vegetation dry season (VDS; late June to late October). Accordantly, the total rainfall during the dry season explains around 80% of the VDS NDVI interannual variance. Considering the predominant land cover types, differences in the hydroclimate-NDVI relationship are observed. Evergreen forests (531,350 km2) remain energy-limited during the beginning of the dry season, but they become water-limited at the end of the VDS. In savannas and flooded savannas (162,850 km2), water dependence occurs months before the onset of the VDS. These differences are more evident during extreme drought years (2007, 2010, and 2011), where regional impacts on NDVI were stronger in savannas and flooded savannas (55% of the entire surface of savannas) than in evergreen forests (40%). A spatial analysis reveals that two specific areas do not show significant hydroclimatic-NDVI correlations during the dry season: (i) the eastern flank of the Andes, characterised by very wet conditions, therefore the vegetation is not water-limited, and (ii) recent deforested areas (~42,500 km2) that break the natural response in the hydroclimate-vegetation system. These findings are particularly relevant given the increasing rates of deforestation in this region.

Description: Agriculture is the major user of water resources, accounting for 70% of global freshwater demand. As the demand for clean water increases, so does the need to implement more efficient strategies for water management in irrigated agriculture. While the benefits of precision irrigation in high-value crops, such as cannabis, tomatoes, and potatoes, are fully recognized, there is still need to investigate and implement cheap and efficient irrigation strategies for widespread low-value crops such as maize. In this study, the soil moisture dynamics in a sprinkler-irrigated maize field in Veneto (Northeastern Italy) was monitored using six time domain reflectometry (TDR) probes for the entire growing season. The TDR sensors were positioned at different depths into two separate sites: an Uninformed Site irrigated based on the farmer's experience and an Informed Site in which a water balance irrigation strategy was applied based on soil moisture measurements. A parsimonious hydrological model was then implemented and calibrated to quantify the different water balance terms (precipitation, evapotranspiration, lateral fluxes, and deep percolation). The comparison between the water budget terms in the two sites highlights that soil moisture monitoring during agriculture activities leads to substantial savings in terms of irrigation water volumes requirements and cost, without compromising the productivity of the crop field. A simplified upscaling of the results at the regional scale, assuming average conditions as in this study site and growing season, reveals that potentially significant economic savings, compared to the total profits linked to maize crops, could be possible.

Description: The possible influence of MHD turbulence on the energy distributions of ions in the Earth's plasma sheet was studied using data taken by the THEMIS satellites. Turbulence levels were traced using eddy diffusion coefficients (D), of which we measured one for each Geocentric Solar Magnetospheric (GSM) coordinates every 12 min. Ion fluxes between 1.75 and 210.5 keV during the same time windows that correspond to mainly suprathermal populations were fitted to Kappa distribution functions, which approximate a Maxwellian distribution when the κ-index (κ) is large. We found that the distribution of the eddy diffusion coefficients is bimodal, independently of both the eddy diffusion component and the plasma beta (β) parameter, which is defined as the ratio between plasma and magnetic pressures. The main peak corresponds to turbulent plasma flows with D 〉 103 km2 s−1. In such cases, the impact of turbulence on the κ index depends on the value of β and also on the direction of the turbulent transport. For eddy diffusion perpendicular to the neutral sheet, the values of κ decrease as Dzz increases for β 〈 2; while for higher values of β, κ increases with Dzz. For the other two directions, the values of κ decrease as D increases. This last tendency is stronger for β ~ 1 but almost null for β ~ 10. The secondary peak in the distribution of D values might represent quasi-laminar flows forming part of very large vortices, correct detection and description of which is beyond the scope of this study.

Description: Response time is the key index of on-line monitoring system. To improve the response speed of traditional bead thermal conductivity CO2 sensor, this paper proposes to use multi-walled carbon nanotubes (MWCNTs) to improve the performance of gas sensor carrier. Nano-sized γ-Al2O3/CeO2 powder was synthesized by chemical precipitation method under the action of ultrasonic wave. SEM morphology reveals a particle size of 20–50 nm. MWCNTs were hydroxylated and the solution was then prepared by adding a certain amount of dispersant under ultrasonic wave. The composite support of γ- Al2O3/CeO2/MWCNTs was prepared by wet mixing carbon nanotube solution into the above support materials. Using dynamic resistance matching and black component technology, the influence of radiation heat and environmental temperature and humidity is reduced. Results show that the designed thermal conductivity sensor has consistent response and recovery time to different concentrations of CO2, with a T90 response time of 9 s and a T90 recovery time of 13 s, which is faster compared to major commercial Carbon dioxide sensors. The average sensitivity of the sensor is 0.0075 V/10% CO2. Therefore, the high thermal conductivity and pore characteristics of carbon nanotubes can effectively improve the response speed of the thermal conductivity sensor.

Description: A total of 94 soil samples from different soil depths (0∼25 cm, 25∼50 cm) were collected of farmland soil around the plain of Beijing, and the concentrations of five heavy metal elements (Cd, Cr, Pb, As, and Hg) were measured using standard methods. The safety utilization evaluation method of heavy metals was based on three different evaluation methods. Then, the governance principles and specific management control strategy were determined in detail according to the core pollution source analysis of each safety grade zone. The results show that there are four different comprehensive safe utilization areas: safe, low-risk, medium-risk, and high-risk utilization. Among them, the study area was dominated by low-risk utilization areas, and the risk trend was gradually weakening from the center of the city to the periphery. Based on the characteristics of different security zones, this study puts on the governance principles of priority protection, long-term monitoring and moderate optimization, strengthens early warning, and cooperates with effective repair and priority governance. And then it puts forward practical control strategies according to the core pollution sources of each safety utilization zone. Our findings may provide a clear direction for rational utilization of land resources and renovation in the future.

Description: To investigate the nexus between natural gas consumption, global carbon dioxide (CO2) emissions, and technological innovation, this study employs a balanced panel dataset of 73 countries for the period 1990–2019 based on the fixed effect and random effect estimation methods. Considering potential heterogeneity in the natural gas-CO2 nexus, this study divides the 73 countries into regional comprehensive economic partnership (RCEP) countries and non-RCEP countries for comparative analysis. The main findings indicate that natural gas consumption can significantly promote CO2 emissions for the full sample and non-RCEP countries, and improved technological innovation can help alleviate CO2 emissions from natural gas consumption. In the RCEP countries, technological innovation can improve the carbon emission reduction effect of natural gas. Furthermore, economic growth and global CO2 emissions show an inverted U-shaped relationship, which confirms the environmental Kuznets curve hypothesis. Finally, several policy implications are provided to reduce global CO2 emissions and promote green recovery in the post-epidemic era.

Description: The rapid development of artificial intelligence (AI), big data analytics, cloud computing, and Internet of Things applications expect the emerging memristor devices and their hardware systems to solve massive data calculation with low power consumption and small chip area. This paper provides an overview of memristor device characteristics, models, synapse circuits, and neural network applications, especially for artificial neural networks and spiking neural networks. It also provides research summaries, comparisons, limitations, challenges, and future work opportunities.

Description: Most European cities have air pollution levels that exceed the threshold for human health protection. Children are sensitive to air pollution and thus it is important to ensure they are not exposed to high concentrations of air pollutants. In order to make a positive change toward cleaner air, a joint effort is needed, involving all civil society actors. Schools and local communities have a decisive role, and can, for example, become engaged in citizen science initiatives and knowledge coproduction. In 2019, with the aim of raising awareness for air quality, NILU developed a citizen science toolbox to engage primary schools in monitoring air quality using a simple and affordable measuring method based on paper and petroleum jelly. This is a very visual method, where the students can clearly see differences from polluted and non-polluted places by looking at “how dirty” is the paper. In addition to the qualitative analysis, we have developed an air meter scale making possible for the students to obtain an indicative measurement of the air pollution level. The comparison between the paper and petroleum jelly method against reference PM10 data collected at two official air quality stations showed a good agreement. The method is a strong candidate for dust monitoring in citizen science projects, making participation possible and empowering people with simple tools at hand. The toolbox is targeted at primary schools and children aged 6–12 years, although it can easily be adapted to other age groups. The main objective of the toolbox is to involve young children who are usually not targeted in air quality citizen science activities, to develop research skills and critical thinking, as well as increase their awareness about the air they breathe. The toolbox is designed to engage students in hands-on activities, that challenge them to create hypotheses, design scientific experiments, draw conclusions and find creative solutions to the air pollution problem. The toolbox includes all the necessary material for the teachers, including guidance, background information and templates facilitating the incorporation in the school curricula. The toolbox was launched as part of the Oslo European Green Capital in March 2019 and was later included as part of the European Clean Air Day initiative coordinated by the European Citizen Science Association (ECSA) working group on air quality. A total of 30 schools and 60 4th grade classes (aged 8–9 years) participated in the Oslo campaign. The citizen science approach employed in the schools, combined the four key elements that promote knowledge integration: elicit ideas, add new ideas, distinguish among ideas and reflect and sort out ideas. Although the main goal of the study was to provide simple but robust tools for engaging young children in air quality monitoring, we also carried out ex-ante and ex-post evaluations in 12 of the participating classes using a 10-question multiple choice test to have an indication of the contribution of the activity to knowledge integration. The results show that there is an increase in the number of correct answers, as well as a reduction in the misconceptions after conducting the activity. These results indicate that applying a citizen science approach improved science instruction and helped knowledge integration by including students' views and taking advantage of the diverse ideas students generated. Citizen science gives learners an insight into the ways that scientists generate solutions for societal problems. But more important, citizen science provides a way to differ from the classic view of the learner as an absorber of information, by considering the social context of instruction and making the topic personally relevant.

Description: Bismuth ferrite (BFO) nanoparticle with general formula Bi1-xNdxFe1-yCoyO3 (x=0, 0.05; y=0, 0.05, 0.10, 0.15, 0.20) were prepared using a two-solvent sol-gel method. Interestingly, most of the samples exhibited a cellular architecture. Bandgap engineering of BFO nanoparticles was achieved by co-doping with Nd and Co. Under illumination with ultraviolet light, the concentration of methylene orange increased. The sample of Bi0.95Nd0.05Fe0.85Co0.15O3 produced a small amount of hydrogen (8.88molg-1 after 1.5;h), but the other samples did not produce detectable levels of hydrogen. In this research, the production of hydrogen occurred under illumination by ultraviolet light, demonstrating the splitting of pure water without the use of a sacrificial reagent. A possible reason for this is that the conduction and valence band edges of BiFeO3 straddle the water redox potential. Consequently, it is possible to realize unassisted water splitting using BFO. The ferromagnetism of all samples increased linearly with the increase of dopant concentration, and the residual magnetization of the Bi0.95Nd0.05Fe0.80Co0.20O3 sample reached to 0.679 emu g−1. Moreover, the magnetic properties of bismuth ferrite and Nd/Co Co-doped bismuth ferrite photocatalyst were also investigated to show the simple separation. These results demonstrate that BFO nanoparticles have potential applications in photocatalytic hydrogen production without the use of a sacrificial reagent.

Description: Immune checkpoint inhibitors (ICIs) are designed to reinvigorate antitumor immune responses by interrupting inhibitory signaling pathways and promote the immune-mediated elimination of malignant cells. Although ICI therapy has transformed the landscape of cancer treatment, only a subset of patients achieve a complete response. Focused ultrasound (FUS) is a noninvasive, nonionizing, deep penetrating focal therapy that has great potential to improve the efficacy of ICIs in solid tumors. Five FUS modalities have been incorporated with ICIs to explore their antitumor effects in preclinical studies, namely, high-intensity focused ultrasound (HIFU) thermal ablation, HIFU hyperthermia, HIFU mechanical ablation, ultrasound-targeted microbubble destruction (UTMD), and sonodynamic therapy (SDT). The enhancement of the antitumor immune responses by these FUS modalities demonstrates the great promise of FUS as a transformative cancer treatment modality to improve ICI therapy. Here, this review summarizes these emerging applications of FUS modalities in combination with ICIs. It discusses each FUS modality, the experimental protocol for each combination strategy, the induced immune effects, and therapeutic outcomes.

Description: The response of the scientific community to the global health emergency caused by the COVID-19 pandemic has produced an unprecedented number of manuscripts in a short period of time, the vast majority of which have been shared in the form of preprints posted on online preprint repositories before peer review. This surge in preprint publications has in itself attracted considerable attention, although mostly in the bibliometrics literature. In the present study we apply a mathematical growth model, known as the generalized Richards model, to describe the time evolution of the cumulative number of COVID-19 related preprints. This mathematical approach allows us to infer several important aspects concerning the underlying growth dynamics, such as its current stage and its possible evolution in the near future. We also analyze the rank-frequency distribution of preprints servers, ordered by the number of COVID-19 preprints they host, and find that it follows a power law in the low rank (high frequency) region, with the high rank (low frequency) tail being better described by a q-exponential function. The Zipf-like law in the high frequency regime indicates the presence of a cumulative advantage effect, whereby servers that already have more preprints receive more submissions.

Description: Modeling is essential for modern science, and science-based policies are directly affected by the reliability of model outputs. Artificial intelligence has improved the accuracy and capability of model simulations, but often at the expense of a rational understanding of the systems involved. The lack of transparency in black box models, artificial intelligence based ones among them, can potentially affect the trust in science driven policy making. Here, we suggest that a broader discussion is needed to address the implications of black box approaches on the reliability of scientific advice used for policy making. We argue that participatory methods can bridge the gap between increasingly complex scientific methods and the people affected by their interpretations

Description: Many late-type stars across the Milky Way exhibit observable pulsations similar to our Sun that open up a window into stellar interiors. The NASA Kepler mission, a space-based photometric telescope, measured the micro-magnitude luminosity fluctuations caused by solar-like oscillations of tens of thousands of stars for almost 10 years. Detailed stellar structure, evolution, and oscillation theoretical work established in the decades before, such as predictions about mode mixing in the interior of red-giant stars, among many others, now had voluminous precision data against which it could be tested. The overwhelming result is the general validation of the theory of stellar oscillations as well as stellar-structure models; however, important gaps in our understanding of interior physics was also revealed by Kepler. For example, interior rotation, convection, and mixing processes are complex phenomena not fully captured by standard models. This review explores some of the important impacts Kepler observations of solar-like oscillations across the cool end of the H-R diagram has had on stellar astrophysics through the use of asteroseismology.

Description: We propose a scheme to realize the storage and retrieval of optical Peregrine solitons in a coherent atomic gas via electromagnetically induced transparency (EIT). We show that optical Peregrine solitons with very small propagation loss, ultraslow motional velocity, and extremely low generation power can be created in the system via EIT. We also show that such solitons can be stored, retrieved, split, and routed with high efficiency and fidelity through the manipulation of control laser fields. The results reported here are useful for the active control of optical Peregrine solitons and promising for applications in optical information processing and transmission.

Description: Lithium-ion batteries (LIBs) have been one of the most predominant rechargeable power sources due to their high energy/power density and long cycle life. As one of the most promising candidates for the new generation negative electrode materials in LIBs, silicon has the advantages of high specific capacity, a lithiation potential range close to that of lithium deposition, and rich abundance in the earth’s crust. However, the commercial use of silicon in LIBs is still limited by the short cycle life and poor rate performance due to the severe volume change during Li++ insertion/extraction, as well as the unsatisfactory conduction of electron and Li+ through silicon matrix. Therefore, many efforts have been made to control and stabilize the structures of silicon. Magnesiothermic reduction has been extensively demonstrated as a promising process for making porous silicon with micro- or nanosized structures for better electrochemical performance in LIBs. This article provides a brief but critical overview of magnesiothermic reduction under various conditions in several aspects, including the thermodynamics and mechanism of the reaction, the influences of the precursor and reaction conditions on the dynamics of the reduction, and the interface control and its effect on the morphology as well as the final performance of the silicon. These outcomes will bring about a clearer vision and better understanding on the production of silicon by magnesiothermic reduction for LIBs application.

Description: A Poincaré sphere is a powerful prescription to describe a polarized state of coherent photons, oscillating along certain directions. The polarized state is described by a vector in the sphere, and various passive optical components, such as polarization plates and quartz rotators are able to rotate the vectorial state by changing the phase and the amplitude among two orthogonal basis states. The polarization is originated from spin of photons, and recently, significant attentions have been made for optical Orbital Angular Momentum (OAM) as another fundamental degree of freedom for photons. The beam shape of photons with OAM is a vortex with a topological charge at the core, and the state of vortexed photons can be described by a hyper-Poincaré sphere. Here, we propose a compact Poincaré rotator, which controls a vortexed state of photons in a silicon photonic platform, based on Finite-Difference Time-Domain (FDTD) simulations. A ring-shaped gear is evanescently coupled to two silicon photonic waveguides, which convert optical momentum to OAM with both left and right vortexed states. By controlling the relative phase and the amplitude of two traveling waves in input ports, we can control the vortexed states in the hyper-Poincaré sphere for photons out of the gear. The impact of the geometrical Pancharatnam-Berry-Guoy's phase and the conservation law of spin and OAM for vortexed photons out of the gear are discussed.

Description: Auto-thermal operation of biomass torrefaction can help avoid additional heat investment and the associated costs to the system. This work provides a general method for relating the feedstock-specific parameters to the energy balance and pre-diagnosing the potential of auto-thermal for different biomass torrefaction and pyrolysis systems. Both solid and gas thermal properties under various torrefaction conditions and their influences to the torrefaction system energy balances are considered. Key parameters that influence the process auto-thermal operation are analyzed, which include torrefaction reaction heat, torrefaction conditions, drying method, biomass species, and inert N2 flowrate. Equations of torgas and biomass higher heating values (HHVs), as well as the torrefaction reaction heat at different operating conditions are developed. It is found that torgas and biomass HHVs increase with torrefaction temperature and biomass weight loss. Torrefaction reaction heat has a linear relationship with the biomass weight loss, with a positive slope at 250–260°C, and a negative slope at 270–300°C, which indicates that torrefaction shifts from endothermic to exothermic at ∼270°C. Applying advanced drying technology and avoiding the use of N2 can help the system achieve auto-thermal operation at lower torrefaction temperature and residence time, thus leading to a higher process energy efficiency and product yield. This is the first work to relate the micro level element changes of biomass to the macro level process energy balances of the torrefaction system. This work is important in design and operation of the torrefaction system in both pilot and industrial scales to improve process efficiency and predict product quality in a reliable and economic manner.

Description: There is a vast amount of evidence that suggests that the geomagnetic tail is like a turbulent wake behind an obstacle. Large-scale vortices in the wake are able to generate turbulent transport that takes place both along the plasma sheet, in the X and Y directions, and across the plasma sheet, in the Z direction. Thus, turbulent fluctuations in all directions should be taken into consideration when analyzing plasma transport in the plasma sheet, and stability of the plasma sheet configurations. In this review, we summarize and discuss the main results of large and middle scale magnetospheric turbulence yielded by data analysis and modeling. We also identify changes in the description of the magnetospheric dynamics connected with the existence of turbulent fluctuations in the tail.

Description: In this paper, we study the effect of dark energy on the extended thermodynamic structure and interacting microstructures of black holes in AdS, through an analysis of thermodynamic geometry. Considering various limiting cases of the novel equation of state obtained in charged rotating black holes with quintessence, and taking enthalpy H as the key potential in the extended phase space, we scrutinize the behavior of the Ruppeiner curvature scalar R in the entropy-pressure (S,P)-plane (or equivalently in the temperature-volume (T,V)-plane). Analysis of R empirically reveals that dark energy parameterized by α, significantly alters the dominant interactions of neutral, charged and slowly rotating black hole microstructures. In the Schwarzschild-AdS case: black holes smaller than a certain size continue to have attractive interactions whereas larger black holes are completely dominated by repulsive interactions which arise to due dark energy. For charged or rotating AdS black holes with quintessence, R can change sign at multiple points depending upon the relation between α and charge q or angular momentum J. In particular, above a threshold value of α, R is never negative at all, suggesting heuristically that the repulsive interactions due to quintessence are long ranged as opposed to the previously known short ranged repulsion in charged AdS black holes. A mean field interaction potential is proposed whose extrema effectively capture the points where the curvature R changes sign.

Description: Citizen science is an important vehicle for democratizing science and promoting the goal of universal and equitable access to scientific data and information. Data generated by citizen science groups have become an increasingly important source for scientists, applied users and those pursuing the 2030 Agenda for Sustainable Development. Citizen science data are used extensively in studies of biodiversity and pollution; crowdsourced data are being used by UN operational agencies for humanitarian activities; and citizen scientists are providing data relevant to monitoring the sustainable development goals (SDGs). This article provides an International Science Council (ISC) perspective on citizen science data generating activities in support of the 2030 Agenda and on needed improvements to the citizen science community's data stewardship practices for the benefit of science and society by presenting results of research undertaken by an ISC-sponsored Task Group.

Description: Long-hole blasting in mines is likely to cause strong vibration of surficial infrastructure, greatly damage the rock mass surrounding goaf near explosion center, and possibly induce blast vibration disasters. In this article, an improved method for multihole blasting seismic wave prediction is proposed to estimate far-field blast vibration. In this method, the fundamental vibration waveforms are firstly measured through the field blast with a single deck at an underground pilot area. The fundamental vibration waveforms are then used to simulate the vibration waveforms for a single-deck case in the production blast by considering the difference of the equivalent distances from the production blast site and the pilot area to the surface measuring point. The vibration waveforms for the single-deck case are linearly superposed to predict the possible vibration waveforms in production blast with multiple long holes and decks according to the designed delay time between decks. Based on these predicted waveforms, the blast vibration can be estimated and the blast design can be optimized to determine a rational delay time in accordance with the vibration limit. The proposed method was applied in pillar recovery of Hongling Polymetallic Mine to optimize the long-hole blast design to manage blast vibration. The rational delay time for the 716 production blast design was recommended as 26 ms. The practice showed that the blast vibration induced by the 716 production blast has been managed, and the predicted and the measured waveforms agree well. It provides an effective method for multihole blast design to control blast vibration.

Description: Isoelectronic substitution is an ideal tuning parameter to alter electronic states and correlations in iron-based superconductors. As this substitution takes place outside the conducting Fe planes, the electronic behaviour is less affected by the impurity scattering experimentally and relevant key electronic parameters can be accessed. In this short review, I present the experimental progress made in understanding the electronic behaviour of the nematic electronic superconductors, FeSe1−xSx. A direct signature of the nematic electronic state is in-plane anisotropic distortion of the Fermi surface triggered by orbital ordering effects and electronic interactions that result in multi-band shifts detected by ARPES. Upon sulphur substitution, the electronic correlations and the Fermi velocities decrease in the tetragonal phase. Quantum oscillations are observed for the whole series in ultra-high magnetic fields and show a complex spectra due to the presence of many small orbits. Effective masses associated to the largest orbit display non-divergent behaviour at the nematic end point (x ∼ 0.175(5)), as opposed to critical spin-fluctuations in other iron pnictides. Magnetotransport behaviour has a strong deviation from the Fermi liquid behaviour and linear T resistivity is detected at low temperatures inside the nematic phase, where scattering from low energy spin-fluctuations are likely to be present. The superconductivity is not enhanced in FeSe1−xSx and there are no divergent electronic correlations at the nematic end point. These manifestations indicate a strong coupling with the lattice in FeSe1−xSx and a pairing mechanism likely promoted by spin fluctuations.

Description: With the growing population, solid waste management (SWM) is becoming a significant environmental challenge and an emerging issue, especially in the eco-sensitive Indian Himalayan region (IHR). Though IHR does not host high local inhabitants, growing tourist footfall in the IHR increases solid wastes significantly. The lack of appropriate SWM facilities has posed a serious threat to the mountain-dwelling communities. SWM is challenging in the highlands due to the remoteness, topographical configuration, increasing urbanization, and harsh climate compared to plain areas. Difficulty in managing SWM has led to improper disposal methods, like open dumping and open burning of waste, that are adversely affecting the fragile IHR ecosystem. Open dumping of unsegregated waste pollutes the freshwater streams, and burning releases major pollutants often linked to the glacier melt. Processes like composting, vermicomposting, and anaerobic digestion to treat biodegradable wastes are inefficient due to the regions' extreme cold conditions. IHR specific SWM rules were revised in 2016 to deal with the rising problem of SWM, providing detailed criteria for setting up solid waste treatment facilities and promoting waste-to-energy (WtE). Despite governments' effort to revise SWM; measures like proper collection, segregation, treatment, and solid waste disposal needs more attention in the IHR. Door-to-door collection, segregation at source, covered transportation, proper treatment, and disposal are the primary steps to resource recovery across the IHR. Approaches such as waste recycling, composting, anaerobic digestion, refuse-derived fuel (RDF), and gas recovery from landfills are essential for waste alteration into valuable products initiatives like 'ban on single-use plastic' and 'polluters to pay' have a potential role in proper SWM in the IHR. Research and technology, capacity building, mass awareness programs, and initiatives like ‘ban on single-use plastic’ and ‘polluters to pay’ have a potential role in proper SWM in the IHR. This review highlights the current status of waste generation, the current SWM practices, and SWM challenges in the IHR. The review also discusses the possible resource recovery from waste in the IHR, corrective measures introduced by the government specific to IHR and, the way forward for improved SWM for achieving sustainable development of the IHR.

Description: An analysis model of wind power consumption capacity is established with the multi-fractal theory. Firstly, the fluctuation characteristics of wind power are described through multi-fractal parameters, and the correlation between wind power fluctuation characteristics and consumption capacity are analyzed. Afterwards, the swinging door algorithm (SDA) is applied to divide the wind power curve in the evaluation period, and the fluctuation process with similar characteristics is clustered. Further, a functional analysis model to evaluate wind power consumption capacity is mentioned based on the fluctuation clustering results. Finally, the effectiveness of the method is verified by an example of a regional power grid in China, and the influence of adjustable parameters in the model on the consumption capacity is quantitatively analyzed.

Description: Identifying governance schemes that promote cooperation among urban stakeholders is a priority in a context where rapid urbanization poses multiple and complex challenges for ensuring the sustainability of cities. Smart cities offer promising governance approaches, especially in the framework of the concept of Urban Living Labs (ULLs), as an enabling environment for so-called user-centric co-creation processes. While embedding a potential to promote solutions that tackle the challenges of urbanization, especially in relation to the energy transition, it is not yet clear how ULLs can effectively involve all relevant actors nor the extent of their impact, especially regarding behaviors. The study first analyzes the interplay between the challenge of urban energy transition and local governance schemes. Then, it explores how findings from behavioral sciences can inform the design of ULLs to effectively promote active engagement in the urban energy transition. Finally, it reviews the theoretical findings in relation to the ULL that has been taking shape in the city of Trento, Italy.

Description: In southern Mediterranean areas, vineyards are facing the combination of increasing air temperature, drought and frequency of extreme events (e.g., heat waves) due to climate change. Since most of the berry growth and ripening phases occur during the aridity period, such environmental constraints are responsible for limitations in yield and berry quality. Within this scenario, to achieve vineyard sustainability, renewed approaches in vineyard management have been proposed and the use of plant biostimulants seems a prominent and environmental friendly practice. The aim of this study was to test four combinations of a tropical plant extract and conventional chemicals for disease control on morpho-anatomical, physiological, biochemical and berry quality in Vitis vinifera L. subsp. vinifera “Aglianico.” In particular, we aimed to evaluate the possibility to counteract the negative effects of the reductions in copper distribution, by applying the tropical plant extract enriched with: micronutrients, enzymes involved in the activation of natural defense, aminoacids, and vitamins. The halved dose of Cu in combination with the tropical plant extract allowed maintaining a reduced vegetative vigor. In the second year of treatment, the addition of the plant extract significantly improved leaf gas exchanges and photochemistry as well as the synthesis of photosynthetic pigments. At berry level, the plant extract induced an increase in phenolics accompanied by a decrease in soluble sugars. The overall results showed that the expected differences in growth performance and productivity in vines are linked to different eco-physiological and structural properties induced by the various treatments. The tropical plant extract also primed plant defenses at the leaf and fruit levels, mainly due to modifications of some structural and biochemical traits, respectively.

Description: Carbon dioxide removal (CDR) from the atmosphere is likely to be needed to limit global warming to 1.5 or 2°C and thereby for meeting the Paris Agreement. There is a debate which methods are most suitable and cost-effective for this goal and thus deeper understanding of system effects related to CDR are needed for effective governance of these technologies. Bio-Energy with Carbon Capture and Storage (BECCS) and Direct Air Carbon Capture and Storage (DACCS) are two CDR methods, that have a direct relation to the electricity system—BECCS via producing it and DACCS via consuming. In this work, we investigate how BECCS and DACCS interact with an intermittent electricity system to achieve net negative emissions in the sector using an energy system model and two regions with different wind and solar resource conditions. The analysis shows that DACCS has a higher levelized cost of carbon (LCOC) than BECCS, implying that it is less costly to capture CO2 using BECCS under the assumptions made in this study. However, due to a high levelized cost of electricity (LCOE) produced by BECCS, the total system cost is lower using DACCS as negative emission provider as it is more flexible and enables cheaper electricity production from wind and solar PV. We also find that the replacement effect outweighs the flexibility effect. Since variations in solar-based systems are more regular and shorter (daily cycles), one could assume that DACCS is better suited for such systems, whereas our results point in the opposite direction showing that DACCS is more competitive in the wind-based systems. The result is sensitive to the price of biomass and to the amount of negative emissions required from the electricity sector. Our results show that the use of the LCOC as often presented in the literature as a main indicator for choosing between different CDR options might be misleading and that broader system effects need to be considered for well-grounded decisions.

Description: Wildland research, management, and policy in western democracies have long relied on concepts of equilibrium: succession, sustained yield, stable age or species compositions, fire return intervals, and historical range of variability critically depend on equilibrium assumptions. Not surprisingly, these largely static concepts form the basis for societal expectations, dominant management paradigms, and environmental legislation. Knowledge generation has also assumed high levels of stasis, concentrating on correlational patterns with the expectation that these patterns would be reliably transferrable. Changes in climate, the introduction of large numbers of exotic organisms, and anthropogenic land conversion are leading to unprecedented changes in disturbance regimes and landscape composition. Importantly, these changes are largely non-reversable; once introduced exotic species are seldom eradicated, climates will continue to warm for the foreseeable future, and many types of land conversion cannot be easily undone. Due to their effects on extant infrastructure and expectations for ecosystem services, these changes are, and will be, viewed by western societies as overwhelmingly negative. The continued acceleration of change will generate increasingly novel systems for which the transferability of correlational relationships will prove unreliable. Our abilities to predict system trajectories will therefore necessarily decrease. In this environment, top-down, expert dominated approaches to environmental decision making are unlikely to produce results that meet broader societal expectations. To be successful we need to embrace a more inclusive paradigm of collaborative governance and multiple forms of knowledge for adapting to constant change, including indigenous epistemological systems. By increasing public and stakeholder participation, we can encourage collaborative social learning allowing all parties to more fully understand the complexities and tradeoffs associated with wildland management and the technical limits of models that seek to quantify those tradeoffs. System novelty will necessarily make forecasting more dependent on predictive modeling and will require better models. Data collection should therefore be strongly influenced by model input requirements and validation; research will need to focus on fundamental and causal relationships to a much greater degree than is done currently.

Description: The measurement of rock joint parameters is a hotly debated and difficult problem in rock mechanics. Joints have great influence on the propagation of stress waves in rock mass. Since the multiple reflections of stress waves propagating inside the joints is not considered accurately, the reflection wave shape cannot be obtained by using a discontinuous displacement model to describe the deformation characteristics of joints. A joint is regarded as a rock using the first analysis of the stress wave transmission in the course of a single joint and the propagation law of a reflection wave. For rocks orientated in the same direction with the same type of wave superposition, stress wave parameters can be established through the multiple reflection effect of a single-joint analysis model. Further to this, analysis using an extended single-joint model can estimate a stress wave under the condition of a vertical incidence group parallel strata analysis model. Taking a single macro-joint as an example, a measuring line is arranged in the normal direction of the joint, and two measuring points on both sides of the joint are arranged in a line to record the waveforms of the incident and transmitted waves. According to the established single-joint analysis model, the calculated waveform of the incident side measuring point is calculated by using the measured waveform of the transmission side measuring point, and the measured waveform of the incident side measuring point is compared with the measured waveform of the incident side measuring point, and the joint elastic parameters with the minimum error are obtained by using the principle of least square method. Six tests were carried out through joints with a thickness of 0.04 m. The results show that the primary wave (P-wave) and secondary vertical wave (SV wave) velocity of joints obtained from many tests have good consistency, which indicates that the joint analysis model has good stability, and the test solution of joint elastic parameters based on the model is reliable.

Description: We present a general method for solving the modified Helmholtz equation without shape approximation for an arbitrary periodic charge distribution, whose solution is known as the Yukawa potential or the screened Coulomb potential. The method is an extension of Weinert’s pseudo-charge method [Weinert M, J Math Phys, 1981, 22:2433–2439] for solving the Poisson equation for the same class of charge density distributions. The inherent differences between the Poisson and the modified Helmholtz equation are in their respective radial solutions. These are polynomial functions, for the Poisson equation, and modified spherical Bessel functions, for the modified Helmholtz equation. This leads to a definition of a modified pseudo-charge density and modified multipole moments. We have shown that Weinert’s convergence analysis of an absolutely and uniformly convergent Fourier series of the pseudo-charge density is transferred to the modified pseudo-charge density. We conclude by illustrating the algorithmic changes necessary to turn an available implementation of the Poisson solver into a solver for the modified Helmholtz equation.

Description: We present in detail a set of algorithms for a dynamic pore-network model of immiscible two-phase flow in porous media to carry out fluid displacements in pores. The algorithms are universal for regular and irregular pore networks in two or three dimensions and can be applied to simulate both drainage displacements and steady-state flow. They execute the mixing of incoming fluids at the network nodes, then distribute them to the outgoing links and perform the coalescence of bubbles. Implementing these algorithms in a dynamic pore-network model, we reproduce some of the fundamental results of transient and steady-state two-phase flow in porous media. For drainage displacements, we show that the model can reproduce the flow patterns corresponding to viscous fingering, capillary fingering and stable displacement by varying the capillary number and viscosity ratio. For steady-state flow, we verify non-linear rheological properties and transition to linear Darcy behavior while increasing the flow rate. Finally we verify the relations between seepage velocities of two-phase flow in porous media considering both disordered regular networks and irregular networks reconstructed from real samples.

Description: The rapid development of wind energy has brought a lot of uncertainty to the power system. The accurate ultra-short-term wind power prediction is the key issue to ensure the stable and economical operation of the power system. It is also the foundation of the intraday and real-time electricity market. However, most researches use one prediction model for all the scenarios which cannot take the time-variant and non-stationary property of wind power time series into consideration. In this paper, a Markov regime switching method is proposed to predict the ultra-short-term wind power of multiple wind farms. In the regime switching model, the time series is divided into several regimes that represent different hidden patterns and one specific prediction model can be designed for each regime. The Toeplitz inverse covariance clustering (TICC) is utilized to divide the wind power time series into several hidden regimes and each regime describes one special spatiotemporal relationship among wind farms. To represent the operation state of the wind farms, a graph autoencoder neural network is designed to transform the high-dimensional measurement variable into a low-dimensional space which is more appropriate for the TICC method. The spatiotemporal pattern evolution of wind power time series can be described in the regime switching process. Markov chain Monte Carlo (MCMC) is used to generate the time series of several possible regime numbers. The Kullback-Leibler (KL) divergence criterion is used to determine the optimal number. Then, the spatiotemporal graph convolutional network is adopted to predict the wind power for each regime. Finally, our Markov regime switching method based on TICC is compared with the classical one-state prediction model and other Markov regime switching models. Tests on wind farms located in Northeast China verified the effectiveness of the proposed method.

Description: This study aimed to understand post-agricultural natural forest regeneration in the Southern Brazilian Atlantic Forest and its possible role as a cost-effective, passive approach to forest restoration. The study characterized vegetation structure, floristic composition, and the dynamics of secondary forest chronosequences. Data were collected from 159 plots (10 × 10 m each) across forest remnants in Santa Catarina State, covering forest ages that ranged from 2 to 60 years of regeneration after swidden agriculture. Only areas with no signs of degradation were sampled in order to provide a description of vegetation characteristics that could be used to identify and monitor natural regeneration. A total of 11,455 woody plants were identified and classified into 334 species representing 71 families. As the succession process unfolds, the continuous turnover of species makes forests more diverse and structurally complex. Floristic similarity among forest types is observed during the early stages of succession, but decreases over time. Pioneer species dominate young secondary forests, representing about 40% of the basal area up to 10 years of regeneration. Shade-tolerant species start colonizing the sites at early ages; however, they become more important structural elements only after 30 years of succession. The observed patterns of forest structure and species diversity largely conform to the post-agricultural succession seen in many tropical forests. The high species diversity found in this study highlights the importance of natural regeneration as a strategy to restore ecosystems. Floristic data can be used as a reference for choosing suitable species for active restoration, as well as contributing to the design of integrated restoration strategies. We herein reinforce the potential of natural regeneration as part of large-scale restoration programs, which would be particularly attractive to family farmers by the low cost of supplies and labor.

Description: A novel rugged two-section driving NIR TDLAS scheme was implemented to reduce temperature and pressure sensitivity of methane carbon isotope measurement during oil and natural gas drilling operations. Isotope spectra line groups with same lower energy levels were selected to derive the concentration of 13CH4 and 12CH4. Dynamic pressure linewidth broadening was introduced in the absorbance curve fitting. Various uncontrollable factors such as spectra shift, stretching, and baseline trending were incorporated in the comprehensive multi-peak fitting. The results showed that the sensitivity of isotope ratios to temperature and pressure variation was greatly suppressed. The δ13CH4 uncertainty in the temperature test was 2.8‰ with fitted δ13CH4-T slope of 0.021‰/°C in 25 ± 5°C range. The δ13CH4 uncertainty in the pressure test was 1.4‰ with fitted δ13CH4-P slope of

Description: Microgrids have been emerging and playing valuable roles in several parts of society, from academia of scholars to the energy supply industry of professional practitioners. A microgrid policy appeared in the Thailand 2015 energy development plan. There are many microgrids in Thailand. The first smart microgrid in Thailand is in active operation. Some microgrids are no longer functioning. Other microgrids continue to serve their customers. The remaining microgrid projects are in the process of development. Most present microgrids in Thailand are driven by public policy and legal flexibility. The objective of this research is to investigate the compatible microgrid technology in Thailand and explore the key drivers of microgrid policies in Thailand. The research methodology applied in this research includes data collection (i.e., a document study, interview, group discussion, and microgrid project participation and observation), as well as data analysis and conclusion. The findings of the research show that: in Thailand, the desired microgrid technologies are compatible with 1) inputs of potential local renewable energy resources of solar, wind, biomass, and mini-hydro, and 2) small gaps of human resource capabilities to deal with the technology utilization. The key drivers of the Thailand microgrid policy are 1) electricity access, 2) wealth creation and distribution, 3) environmental protection, and 4) technology development.