ALBERT

Description: The influence of size effect on the hydromechanical behavior of rock mass has long been recognized. As a result, analysis of the rock mass size effect has been developed. However, when conducting size effect studies, the representativeness of the sample is less considered. Therefore, combining the existing statistical methods and sampling methods, a comprehensive representative sampling method for rock mass is present. In this method, a large number of sample statistics of different sizes are provided in the progressive coverage method; then, the plane density of the track length is defined as the value of stratification to perform stratified sampling for representative samples. Furthermore, it is applied to a joint network model generated in accordance with the actual situation and compared with those of other methods. The sampling results show that the proposed method can provide a certain reference value for studying the scale-dependent behavior of rock mass mechanical parameters.

Description: The Linxing area is located in the north of the eastern margin of the Ordos Basin, which has great resource potential for tight gas. In this paper, fluid inclusion analysis and basin modeling are the main means to clarify the gas accumulation mechanism of the Upper Paleozoic in the Linxing area. Petrographic analysis shows that fluid inclusions can be classified into 5 types: aqueous inclusions, hydrocarbon-bearing aqueous inclusions, hydrocarbon inclusions, crystal-bearing aqueous inclusions, and aqueous-carbonic inclusions. According to the statistical analysis of homogenization temperature and salinity of fluid inclusions, combined with the burial-thermal evolution, the study area was divided into 3 areas: the inner-magma baking area, the middle-anomal thermal area, and the outer-normal thermal area. The gas accumulation characteristics are differences among the 3 areas, the closer to Zijinshan magmatic pluton, the earlier gas accumulation period; and the vertical gas accumulation in the inner-magma baking area and the middle-anomal thermal area was not a slow and gradual process from bottom to top. The period from the Middle Jurassic to the Early Cretaceous is the key period for rapid pressure accumulation in the Upper Paleozoic reservoirs, which is consistent with the period of natural gas accumulation. The area near the Zijinshan magmatic pluton was the high fluid potential area during the gas accumulation period, which indicates that natural gas and other fluids migrated from Zijinshan magmatic pluton to the surrounding area. It is concluded that in the Linxing area, the Zijinshan magmatic pluton had a significant impact on natural gas accumulation, and the natural gas accumulation model under the control of magmatic thermal-tectonic effect was proposed.

Description: With the increasingly close relations between cities in China, it is of great significance to explore the regular characteristics of the intercity connection. Through Tencent’s population migration heat and Baidu map big data, this paper analyzes the regular characteristics of the relations between complex cities based on such index as the rich node propensity index, preference level index, and relative heat index and also investigates the influence of geographical proximity factors on the external relations of different cities. The research has the following results. Firstly, the relations between cities have obvious club characteristics. The rich nodes tend to connect with the rich nodes, while the nonrich nodes tend to connect with the nonrich nodes. Secondly, the connection between cities has the effect of hierarchical proximity, and cities mainly establish spatial connections with cities of the same level and adjacent level. Thirdly, the relations between cities also have the effect of geographical proximity, and the degree of influence of geographical proximity in low-level cities is greater than that in high-level cities. Fourthly, the external connection mode of high-level cities is to establish close contact with high-level cities adjacent to the level, with strong attraction to low-level cities adjacent to the location at the same time. The low-level cities are closely related to the high-level cities adjacent to the location and other cities of geographical proximity or adjacent level. This study helps to further understand the complex characteristics and laws of intercity connections and urban networks.

Description: The seepage of gas-liquid two-phase flow in fracture is a commonly found phenomenon in nature. To reveal the underlying mechanism and the critical condition of the chaos occurrence, a stochastic gas-liquid two-phase flow seepage model is established, and then investigated through a numerical simulation and a horizontal Hele-Shaw experiment. The numerical simulation and laboratory experiment results show that the seepage chaos of gas-liquid two-phase flow takes place when the relative saturation is in the range of gas relative saturation 44%-70%, and the occurrence probability can be expressed in polynomials. The chaos probability exceeds 80% when the relative saturation of gas is 47%-65%, and the chaos probability is 100% when the relative gas saturation is 57%-60%. It is found that the stochastic variation of gas connection cluster and the compressibility of gas lead to a remarkable change of pressure gradient of the gas-liquid flow both in magnitude and direction. Therefore, the turbulent flow is formed, the kinetic energy of fluid transport decreases gradually, and the flow is stopped at last.

Description: An effective porosity is defined as the ratio of volume of interconnected pore space to total volume of a porous sample. It controls the magnitude of fluid flow and is a key parameter in the assessment of recoverable resources. However, its accurate measurement in tight formations is challenging, due to their complex pore structure and lithofacies heterogeneity. In this study, porosities of sixteen lacustrine shale samples from the second Member of the Kongdian Formation (Ek2) in the Cangdong Sag, Bohai Bay Basin were measured and compared using multiple methods and sample sizes to compare and contrast the effective porosity results. The methods included helium pycnometry (HP; cubes of 1 cm3 and grains at 500-841 μm), water immersion porosimetry (WIP; cubes), mercury intrusion porosimetry (MIP; cubes), and nuclear magnetic resonance (NMR; cubes). Finally, samples were completely sealed using paraffin for bulk density measurements to evaluate the extent of potential clay swelling in shale samples involving probing fluids. Results from the HP, WIP, and MIP methods for skeletal density, bulk density, and effective porosity with cubic samples were compared. While very similar skeletal densities were found for all three methods, a lower bulk density, and therefore lower porosity, from the MIP approach can be attributed to the experimental conditions (e.g., vacuum efficiency, applied pressure, wettability of water/helium vs. mercury) and the probable presence of pores with diameters larger than 50 μm not measurable by MIP. Furthermore, the HP porosity of granular samples with 500-841 μm grain sizes can be regarded as approaching the total porosity. The complicated relationship between WIP and NMR porosities may result from the heat-induced volatilization of moisture in pores during NMR tests, and countercurrent imbibition of water replacing the residual hydrocarbons during the saturation process for sample preparation in both tests. The swelling behavior of the lacustrine Ek2 shale with water is not significant because of the low content of expansive clay minerals. In summary, the WIP and HP methods are recommended for effective porosity measurement, whereas the NMR and MIP methods are invaluable for the measurement of pore-size distribution, with additional information on the effective porosity.

Description: The lower Silurian Longmaxi Formation hosts a highly productive shale gas play in the Zhaotong region of southern China. According to core observation, X-ray diffraction analyses, and scanning electron microscopy (SEM) observations, the shale comprises primarily quartz, carbonate minerals, and clay minerals, with minor amounts of plagioclase, K-feldspar, and pyrite. The clay mineral content ranges from 15.0% to 46.1%, with an average of 29.3% in the Zhaotong region. Organic geochemical analyses show that the Longmaxi Formation has good potential for shale gas resources by calculating total organic carbon, vitrinite reflectance, and gas content. Scanning electron microscope images demonstrate that reservoir pore types in the Longmaxi shale include organic pores, interparticle pores, intercrystalline pores, intraparticle pores, and fractures. Reservoir distribution is controlled by lithofacies, mineral composition, and geochemical factors. In addition, we investigated the relationships between reservoir parameters and production from 15 individual wells in the Zhaotong region by correlation coefficients. As a result, the brittleness index, total organic carbon (TOC), porosity, and gas content were used to define high-quality reservoirs in the Longmaxi shale. Based on these criteria, we mapped the thickness and distribution of high-quality reservoirs in the Longmaxi Formation and selected highlighted several key sites for future exploration and development.

Description: When mine water inrush accidents occur, timely and accurately identifying the water inrush source plays an important role in determining the cause of water inrush and making a solution to a disaster. According to the differences of water chemical composition in each water sources of mine, eight kinds of indicators of water chemical composition were selected as sample variables for water inrush source identification. On this basis, an identification model of water inrush source was established by using principal component analysis (PCA) and Fisher discriminant analysis (FDA) combined. The model was used to identify the water inrush source of 14 groups of training samples and 12 groups of samples to be judged in different water sources of the Xiandewang coal mine, and it was compared with the results of the conventional identification model which used the FDA method. Results of this study showed that having processed data by using the PCA method can effectively eliminate the effects of information superposition between sample indicators, and the identification accuracy of mine water inrush source was significantly increased. Related study in this paper can provide some basis and reference for the study of mine water inrush source identification technology.

Description: The abundance of organic matter in shales, which has a direct effect on the hydrocarbon generation potential of shales, is an important organic geochemical parameter for evaluating shale gas reservoirs. The total organic carbon content (TOC content) in shale is controlled by the abundance of original sedimentary organic matter. Therefore, it is very important to study the mechanism of organic matter enrichment in shale. In this paper, the Lower Cambrian marine shales from the Lower Yangtze region are selected as the research subject, most of which originate from a typical area well called Well JXY1. The degree of pyritization (DOP) is used to characterize the redox environment of the water body, while the P/Al ratio is used to analyze the biological productivity of paleoseawater. The paleosalinity of seawater is calculated via carbon and oxygen isotope analysis. In addition, the early Cambrian hydrothermal activities were studied by using core description; Si, Al, Fe, and Mn elemental analysis; and oxygen isotope calculations. The results show that during the early Cambrian Wangyinpu sedimentary period, the seawater was an anaerobic water body with H2S, and the oxygen concentration was approximately 0 mL/L. In the middle stages of the Wangyinpu sedimentary period, the water body had the strongest reducibility and the highest biological productivity. Moreover, the paleoocean in this period between the Yangtze plate and the Cathaysian plate was greatly affected by hydrothermal activities, with temperatures ranging from 90°C to 120°C. Active hydrothermal activities promoted high biological productivity and an anaerobic environment, both of which were conducive to the preservation and enrichment of organic matter, resulting in extremely high TOC content in the Wangyinpu shales (from 6.5% to approximately 16%).

Description: Electroencephalography-(EEG-) based control is a noninvasive technique which employs brain signals to control electrical devices/circuits. Currently, the brain-computer interface (BCI) systems provide two types of signals, raw signals and logic state signals. The latter signals are used to turn on/off the devices. In this paper, the capabilities of BCI systems are explored, and a survey is conducted how to extend and enhance the reliability and accuracy of the BCI systems. A structured overview was provided which consists of the data acquisition, feature extraction, and classification algorithm methods used by different researchers in the past few years. Some classification algorithms for EEG-based BCI systems are adaptive classifiers, tensor classifiers, transfer learning approach, and deep learning, as well as some miscellaneous techniques. Based on our assessment, we generally concluded that, through adaptive classifiers, accurate results are acquired as compared to the static classification techniques. Deep learning techniques were developed to achieve the desired objectives and their real-time implementation as compared to other algorithms.

Description: As the externalized carrier of intrinsic value, value decision-making is an important factor affecting the social value system. As an old Chinese saying goes, “A friend in need is a friend indeed,” crisis environment provides the background for the conflicts of multiple values, while individual social value orientation (SVO) determines the ranking of the value states. This paper defined the SVO types by means of Slider Measure method on the basis of environment description, constructed a decision-making game model in accordance with SVO differences, and finally analysed the mechanism of people’s decision-making. Taking the epidemic situation as the background, this paper conducted an empirical analysis with the sample of college students. The results showed that the most SVO types of college students were prosocial orientation, followed by individualistic orientation, altruistic orientation, and competitive orientation. In the crisis environment, individual SVO type and decision-making constituted a mapping relationship. There was an equilibrium point in the decision of prosocial orientation, and the dominant decision of altruistic orientation or individualistic orientation is relatively stable.

Description: High heterogeneity and nonuniformly distributed multiscale pore systems are two characteristics of the unconventional reservoirs, which lead to very complex transport mechanisms. Limited by inadequate computational capability and imaging field of view, flow simulation cannot be directly performed on complex pore structures. The traditional methods usually coarsen the grid to reduce the computational load but will lead to the missing microstructure information and inaccurate simulation results. To develop a better understanding of flow properties in unconventional reservoirs, this study proposed a new upscaling method integrated gray lattice Boltzmann method (GLBM) and pore network model (PNM), accounting for the fluid flow in heterogeneous porous media. This method can reasonably reduce the computational loads while preserving certain micropore characteristics. Verifications are conducted by comparing the simulation and experimental results on tight sandstones, and good agreements are achieved. The proposed method is proven to be capable of estimating bulk properties in highly heterogenous unconventional reservoirs. This method could contribute to the development of multiscale pore structure characterizations and enhance the understandings of fluid flow mechanisms in unconventional reservoirs.

Description: To solve the problems of current short-term forecasting methods for metro passenger flow, such as unclear influencing factors, low accuracy, and high time-space complexity, a method for metro passenger flow based on ST-LightGBM after considering transfer passenger flow is proposed. Firstly, using historical data as the training set to transform the problem into a data-driven multi-input single-output regression prediction problem, the problem of the short-term prediction of metro passenger flow is formalized and the difficulties of the problem are identified. Secondly, we extract the candidate temporal and spatial features that may affect passenger flow at a metro station from passenger travel data based on the spatial transfer and spatial similarity of passenger flow. Thirdly, we use a maximal information coefficient (MIC) feature selection algorithm to select the significant impact features as the input. Finally, a short-term forecasting model for metro passenger flow based on the light gradient boosting machine (LightGBM) model is established. Taking transfer passenger flow into account, this method has a low space-time cost and high accuracy. The experimental results on the dataset of Lianban metro station in Xiamen city show that the proposed method obtains higher prediction accuracy than SARIMA, SVR, and BP network.

Description: People are the most important factors of economy and the primary carriers of social culture. Cross-border migration brings economic and cultural impacts to the origin and destination and is also a key to reflect the international relations of related countries. In fact, the migration relationships of countries are complex and multilateral, but most traditional migration models are bilateral. Network theories could provide a better description of global migration to show the structure and statistical characteristics more clearly. Based on the estimated migration data and disparity filter algorithm, the networks describing the global multilateral migration relationships have been extracted among 200 countries over fifty years. The results show that the global migration networks during 1960–2015 exhibit a clustering and disassortative feature, implying globalized and multipolarized changes of migration during these years. The networks were embed into a Poincaré disk, yielding a typical and hierarchical “core-periphery” structure, which is associated with angular density distribution, and has been used to describe the “multicentering” trend since 1990s. Analysis on correlation and evolution of communities indicates the stability of most communities, yet some structural changes still exist since 1990s, which reflect that the important historical events are contributable to regional and even global migration patterns.

Description: Most of the existing knowledge graph embedding models are supervised methods and largely relying on the quality and quantity of obtainable labelled training data. The cost of obtaining high quality triples is high and the data sources are facing a serious problem of data sparsity, which may result in insufficient training of long-tail entities. However, unstructured text encoding entities and relational knowledge can be obtained anywhere in large quantities. Word vectors of entity names estimated from the unlabelled raw text using natural language model encode syntax and semantic properties of entities. Yet since these feature vectors are estimated through minimizing prediction error on unsupervised entity names, they may not be the best for knowledge graphs. We propose a two-phase approach to adapt unsupervised entity name embeddings to a knowledge graph subspace and jointly learn the adaptive matrix and knowledge representation. Experiments on Freebase show that our method can rely less on the labelled data and outperforms the baselines when the labelled data is relatively less. Especially, it is applicable to zero-shot scenario.

Description: Portfolio investment is adopted by the venture capital to diversify those risks involved in project selection, investing or operating so that the venture capitalist can expect a relatively stable income and lower financing risks. Based on the design of portfolio investment contract with unlimited funds developed by Kanniainen and Keuschnigg, and Inderst et al., this article makes a modification and presents a model given the limitation of funds available for the venture capitalist. It is demonstrated that the marginal benefit of efforts paid by the entrepreneurs exceeds the marginal cost, given the limitation of funds available, which will conduce to a high-level engagement of the entrepreneurs. Thus, by adopting the design of renegotiation contract, the venture capitalist can manage to stimulate the entrepreneurs to make efforts, which is to result in moral hazard reduction.

Description: Huge data on the web come from discussion forums, which contain millions of threads. Discussion threads are a valuable source of knowledge for Internet users, as they have information about numerous topics. The discussion thread related to single topic comprises a huge number of reply posts, which makes it hard for the forum users to scan all the replies and determine the most relevant replies in the thread. At the same time, it is also hard for the forum users to manually summarize the bulk of reply posts in order to get the gist of discussion thread. Thus, automatically extracting the most relevant replies from discussion thread and combining them to form a summary are a challenging task. With this motivation behind, this study has proposed a sentence embedding based clustering approach for discussion thread summarization. The proposed approach works in the following fashion: At first, word2vec model is employed to represent reply sentences in the discussion thread through sentence embeddings/sentence vectors. Next, K-medoid clustering algorithm is applied to group semantically similar reply sentences in order to reduce the overlapping reply sentences. Finally, different quality text features are utilized to rank the reply sentences in different clusters, and then the high-ranked reply sentences are picked out from all clusters to form the thread summary. Two standard forum datasets are used to assess the effectiveness of the suggested approach. Empirical results confirm that the proposed sentence based clustering approach performed superior in comparison to other summarization methods in the context of mean precision, recall, and F-measure.

Description: Low-permeability reservoirs have tiny pores with winding and complicated pore throats. The oil recovery efficiency of low-permeability reservoirs can be enhanced through the displacement of reservoir oil through imbibition. In the present study, experiments were conducted to investigate variations in the imbibition height of hydrophilic and weakly-hydrophilic rock samples under different interfacial tensions. An imbibition model considering imbibition resistance and bending of pore throats was established based on fractal theory. According to the experimental results, variations in the imbibition height of low-permeability rock samples with time can be divided into three stages. In the first stage, the capillary force plays a dominant role, while the viscous force and gravity have very slight effects. The imbibition height first increases rapidly and then levels off to a constant rate. With the increase in interfacial tension, the imbibition rate in the first stage increases, the ultimate imbibition height increases initially and then decreases, and the contribution of the imbibition height in the first stage to the ultimate imbibition height becomes greater. There is an optimal interfacial tension that causes the ultimate imbibition height to reach its maximum. The calculated results obtained from the proposed imbibition model are consistent with the experimental results, indicating that the model can accurately reflect the change in the imbibition height in low-permeability reservoirs in the first stage.

Description: The Otago Schist in the South Island of New Zealand represents an exhumed Mesozoic accretionary prism. Two coastal areas (Akatore Creek and Bruce Rocks) south of Dunedin preserve structural and geochemical evidence for the development of postmetamorphic hydrothermal systems that involved widespread fluid-rock reaction at shallow crustal depths. The Jurassic to Triassic pumpellyite-actinolite (Akatore Creek) to upper greenschist facies (Bruce Rocks) metamorphic fabrics were crosscut by sets of regionally extensive Cretaceous exhumation joints. Many of the joints were subsequently reactivated to form networks of small-displacement (

Description: This paper considers the two-player location game in a closed-loop market with quantity competition. Based on the Cournot and Hotelling models, a circle model is established for a closed-loop market in which two players (firms) play a location game under quantity competition. Using a two-stage (location-then-quantity) pattern and backward induction method, the existence of subgame-perfect Nash equilibria is proved for the location game in the circle model with a minimum distance transportation cost function. In addition, sales strategies are proposed for the two players for every local market on the circle when the players are in the equilibrium positions. Finally, an algorithm for simulating the competitive dynamics of the closed-loop market is designed, and two numerical simulations are provided to substantiate the effectiveness of the obtained results.

Description: Widely distributed in North China, Ordovician karst is characterized by having high thickness, nonuniform aquosity, and significant water pressure-bearing properties. Deep mining in North China is threatened by associated water hazards; hence, research on the hydrogeological characteristics of deep Ordovician karst is needed. In this study, the Weibei coalfield in Shaanxi Province, China, was selected as the study area, especially mines in the Hancheng and Chenghe mining areas. In situ experiments, including water pumping, water drainage, water injecting and water pressure, and laboratory experiments, were conducted to study the hydrogeological characteristics of the Ordovician karst top in the study area. A comprehensive analysis was conducted on controlling factors for the development of the Ordovician karst top in the study area, and a method for evaluating the water inrush risk in coal mining areas based on karst hydrogeological characteristics was proposed. The research results indicated that the Ordovician karst top in the study area was characterized by heterogeneity, vertical zonation, and partially filled properties, which were mainly controlled by two factors: sedimentation and tectonism. The hydrogeological conditions of the Ordovician karst could be divided into three types: nonfilled and nonsignificant tectonism, filled and nonsignificant tectonism, and significant tectonism. Among them, the filled and nonsignificant tectonism type Ordovician karst top type had a filling thickness of 20 m. Based on karst hydrogeological characteristics, the methods were proposed to evaluate the water inrush risk in the coal mining floor. The practical tests verified the methods.

Description: It is critical to select an optimized sand control method for an interbedded sandstone and mudstone reservoir (ISMR) due to its serious sand production hazards. However, currently, most general sand control methods cannot meet the requirements of sand control in interbedded sandstone and mudstone reservoirs (e.g., Bohai Bay oil and gas fields from China). Ensuring efficiency of sand control and increasing the oil and gas production rate in this interbedded sandstone and mudstone become more and more important. In this paper, a “multilayer rotatable sand control experimental device” for the interbedded sandstone and mudstone reservoir was developed. A series of sand control experimental studies were conducted by using the proposed device. The net-to-gross ratio (NTG) and well inclinations are two major factors considered in the experimental analysis. In addition, a sensitivity analysis regarding formation particle size distribution (PSD), clay content, and mineral compositions is performed in the experiment under a moderate sand control mode. With systematic experimental test results in this work, combined with numerous existing sand control models, a set of optimum sand control design and the associated optimization template for ISMR were developed, which have been successfully applied in Bohai Bay. Field application results show that NTG and well inclination are two critical parameters in the design of sand control in ISMR. The optimal indexes of a sand control mode are determined as NTG of 0.4 and well inclination of 45°. The introduction of these two key factors in sand control design broadens the application range of moderate sand production.

Description: The scale dependence of surface roughness is critical in characterising the hydromechanical properties of field-scale rock joints but is still not well understood, particularly when different orders of roughness are considered. We experimentally reveal the scale dependence of two-order roughness, i.e., waviness and unevenness through fractal parameters using the triangular prism surface area method (TPM). The surfaces of three natural joints of granite with the same dimension of 1000 mm×1000 mm are digitised using a 3D laser scanner at three different measurement resolutions. Waviness and unevenness are quantitatively separated by considering the area variation of joint surface as grid size changes. The corresponding fractal dimensions of waviness and unevenness in sampling window sizes ranging from 100 mm×100 mm to 1000 mm×1000 mm at an interval of 100 mm×100 mm are determined. We find that both the fractal dimensions of waviness and unevenness vary as the window size increases. No obvious stationarity threshold has been found for the three rock joint samples, indicating the surface roughness of natural rock joints should be quantified at the scale of the rock mass in the field.

Description: A novel posture motion-based spatiotemporal fused graph convolutional network (PM-STGCN) is presented for skeleton-based action recognition. Existing methods on skeleton-based action recognition focus on independently calculating the joint information in single frame and motion information of joints between adjacent frames from the human body skeleton structure and then combine the classification results. However, that does not take into consideration of the complicated temporal and spatial relationship of the human body action sequence, so they are not very efficient in distinguishing similar actions. In this work, we enhance the ability of distinguishing similar actions by focusing on spatiotemporal fusion and adaptive feature extraction for high discrimination information. Firstly, the local posture motion-based attention (LPM-TAM) module is proposed for the purpose of suppressing the skeleton sequence data with a low amount of motion in the temporal domain, and the representation of motion posture features is concentrated. Besides, the local posture motion-based channel attention module (LPM-CAM) is introduced to make use of the strongly discriminative representation between different action classes of similarity. Finally, the posture motion-based spatiotemporal fusion (PM-STF) module is constructed which fuses the spatiotemporal skeleton data by filtering out the low-information sequence and enhances the posture motion features adaptively with high discrimination. Extensive experiments have been conducted, and the results demonstrate that the proposed model is superior to the commonly used action recognition methods. The designed human-robot interaction system based on action recognition has competitive performance compared with the speech interaction system.

Description: Karst collapse pillars (KCPs) frequently cause severe groundwater inrush disasters in coal mining above a confined aquifer. An accurate understanding of the damage and fracture evolution, permeability enhancement, and seepage changes in KCPs under the combined action of mining-induced stress and confined hydraulic pressure is of great significance for the early prediction and prevention of groundwater inrush from KCPs in coal seam floors. In this study, a micromechanics-based coupled stress-seepage-damage (SSD) modeling approach, in which the macroscopic mechanical and hydraulic properties of the rock are explicitly related to the microcrack kinetics, is proposed to simulate the fracture evolution and the associated groundwater flow in KCPs. An in situ high-precision microseismic monitoring technology is used to verify the micromechanical modeling results, which indicate that the numerical model successfully reproduces the damage and fracture evolution in a coal seam floor with a KCP during the mining process. The presented model also provides a visual representation of the complex process of KCP activation and groundwater inrush channel formation. A numerical study shows that the damage and activation of a KCP start from the edge of the KCP, gradually develop toward the interior of the KCP, and eventually connect with the damage fracture zone of the floor, forming a primary water-conducting channel in the KCP, causing the confined groundwater to flow into the working face. Groundwater inrush from a KCP is a gradual process instead of a mutation process. A reduction in the distance between the working face and a KCP and increases in the confined hydraulic pressure and the initial water-conducting height of the KCP can significantly increase the risk of groundwater inrush from the KCP.

Description: In this paper, a delayed control strategy for a class of nonlinear underactuated fourth-order systems is developed. The proposal is based on the implementation of the tangent linearization technique, differential flatness, and a study of the σ-stabilization of the characteristic equation of the closed-loop system. The tangent linearization technique allows obtaining a local controllability property for the analyzed class of systems. Also, it can reduce the complexity of the global control design, through the use of a cascade connection of two second-order controllers instead of designing a global controller of the fourth-order system. The stabilizing behavior of the delayed controller design is supported by the σ-stability criterion, which provides the controller parameter selection to reach the maximum exponential decay rate on the system response. To illustrate the efficiency of the theoretical results, the proposal is experimentally assessed in two cases of study: a flexible joint system and a pendubot.

Description: Recently, knowledge graph embedding methods have attracted numerous researchers’ interest due to their outstanding effectiveness and robustness in knowledge representation. However, there are still some limitations in the existing methods. On the one hand, translation-based representation models focus on conceiving translation principles to represent knowledge from a global perspective, while they fail to learn various types of relational facts discriminatively. It is prone to make the entity congestion of complex relational facts in the embedding space reducing the precision of representation vectors associating with entities. On the other hand, parallel subgraphs extracted from the original graph are used to learn local relational facts discriminatively. However, it probably causes the relational fact damage of the original knowledge graph to some degree during the subgraph extraction. Thus, previous methods are unable to learn local and global knowledge representation uniformly. To that end, we propose a multiview translation learning model, named MvTransE, which learns relational facts from global-view and local-view perspectives, respectively. Specifically, we first construct multiple parallel subgraphs from an original knowledge graph by considering entity semantic and structural features simultaneously. Then, we embed the original graph and construct subgraphs into the corresponding global and local feature spaces. Finally, we propose a multiview fusion strategy to integrate multiview representations of relational facts. Extensive experiments on four public datasets demonstrate the superiority of our model in knowledge graph representation tasks compared to state-of-the-art methods.

Description: The aerosol size distribution and cloud condensation nuclei (CCN) number concentration were measured using a wide-range particle spectrometer (WPS) and a cloud condensation nuclei counter (CCNC) on Mt. Tian from 31 July to 9 September, 2019. Combined with meteorological data, distribution characteristics of aerosol size and CCN and their influencing factors were analyzed. The results indicated that the mean aerosol number concentration was 5475.6 ± 5636.5 cm−3. The mean CCN concentrations were 183.7 ± 114.5 cm−3, 729.8 ± 376.1 cm−3, 1630.5 ± 980.5 cm−3, 2162.5 ± 1345.3 cm−3, and 2575.7 ± 1632.9 cm−3 at supersaturation levels of 0.1%, 0.2%, 0.4%, 0.6%, and 0.8%, respectively. The aerosol number size distribution is unimodal, and the dominant particle size is 30–60 nm. Affected by the height of the boundary layer and the valley wind, the diurnal variation in aerosol number concentration shows a unimodal distribution with a peak at 17:00, and the CCN number concentration showed a bimodal distribution with peaks at 18:00 and 21:00. The particle size distribution and supersaturation have a major impact on the activation of the aerosol into CCN. At 0.1% supersaturation (S), the 300–500 nm particles are most likely to activate to CCN. Particles of 100–300 nm are most easily activated at 0.2% (S), while particles of 60–80 nm are most likely activated at high supersaturation (≥0.4%). The concentrations of aerosol and CCN are higher in the northerly wind. Ambient relative humidity (RH) has little relationship with the aerosol activation under high supersaturation. According to N = CSk fitting the CCN spectrum, C = 3297 and k = 0.90 on Mt. Tian, characteristic of the clean continental type.

Description: The atmospheric boundary layer height is important for constraining air pollution and meteorological models. This study attempted to validate the MODIS-estimated atmospheric boundary layer height (ABLH), and variation in the ABLH in Uganda was evaluated. The ABLH was estimated from MODIS data using the mixing ratio profile gradient method and compared to the ABLH estimated from radiosonde data using three different methods. Unlike in studies in other regions of the world, correlations between ABLH estimated using MODIS and radiosonde data were weak, implying limited usefulness of MODIS data for determining ABLH. However, the diurnal variation in MODIS-derived ABLH and particulate matter (PM10) was consistent with the expected inverse relationship between PM10 mass concentration and ABLH, and the mean MODIS-derived ABLH values were significantly lower during wet seasons than dry seasons, as expected.

Description: In our previous studies, we investigated the performance of a novel pneumatic planar magnetic separator (PMS) for the dry beneficiation of a selected magnetite ore. In the present study, we have extended the studies on the PMS with the focus on investigating how various PMS processing flowsheet configurations influence its performance. The outcomes were subsequently compared with those of a Davis tube recovery (DTR) tester. The study demonstrated that the use of PMS in the dry beneficiation of magnetite ores is feasible, and operating the PMS in different flowsheet configurations positively influences the magnetite concentrate grade and purity. Finally, the study showed that the PMS performance compares well with that of DTR and can potentially replace DTR in operations that are carried out in arid regions.

Description: Festivals are experiential products heavily depending on the recommendations of previous visitors. With the power of social media growing, understanding the antecedents of positive electronic word-of-mouth (eWOM) intentions of festival attendees is immensely beneficial for festival organizers to better promote their festivals and control negative publicity. However, there is still limited research regarding eWOM intentions in the festival context. Thus, this study aims to fill such a gap by investigating the relationships among festival attendees’ enjoyment seeking motivation, perceived value, visitor satisfaction, and eWOM intention in a local festival setting. Additionally, the moderating role of gender was tested as it is one of the most important demographic variables to show individual differences in behavioral intentions. The results of structural equation modeling showed a positive effect of enjoyment seeking motivation on perceived value, visitor satisfaction, and eWOM intention. Moreover, gender differences in eWOM intention and a full mediating effect of visitor satisfaction between perceived value and eWOM intention for female respondents were revealed. The findings of this study extend the existing festival literature and provide insights for strategically organizing and promoting festivals to generate more positive eWOM which can be utilized as an effective marketing tool and a feedback channel.

Description: Geospatial data is urgently needed in decision-making processes to achieve Sustainable Development Goals (SDGs) at global, national, regional and local scales. While the advancement of geo-technologies to obtain or produce geospatial data has become faster and more affordable, many countries in the global south still experience a geospatial data scarcity at the rural level due to complex geographical terrains, weak coordination among institutions and a lack of knowledge and technologies to produce visualised geospatial data like maps. We proposed a collaborative spatial learning framework that integrates the spatial knowledge of stakeholders to obtain geospatial data. By conducting participatory mapping workshops in three villages in the Deli Serdang district in Indonesia, we tested the framework in terms of facilitating communication and collaboration of the village stakeholders while also supporting knowledge co-production and social learning among them. Satellite images were used in digital and non-digital mapping workshops to support village stakeholders to produce proper village maps while fulfilling the SDGs’ emphasis to make geospatial data available through a participatory approach.

Description: In this study, the flotation behavior of malachite was investigated using hydrophobic talc nanoparticles (TNs) as collectors. To improve the floatability of TN-deposited malachite, various experimental parameters were systematically investigated. We found that the floatability sharply increased as the size of the TNs decreased. The floatability of malachite was enhanced in the presence of smaller TNs, since higher amounts of smaller TNs were deposited on the surface of the malachite, thus rendering the surface more hydrophobic. Moreover, the floatability of the TN-deposited malachite increased as the pH decreased, likely due to the more favorable interaction between TNs and malachite by means of electrostatic attraction. Furthermore, the floatability became more enhanced as the TN concentration increased, likely associated with increases in the amount of TNs deposited on the surface of the malachite, thus enhancing the floatability by altering the hydrophobicity of the surface. Our findings suggest that the application of natural hydrophobic TNs as collectors in malachite flotation should be introduced as a new concept.

Description: Access and use of seed of improved varieties of groundnut among farmers can improve farmers’ livelihoods and contribute to the potential of crop production in Tanzania. This paper analyzes factors underpinning the adoption of improved groundnut varieties among farmers to pave the way for upscaling quality seed used for increased production and commodity business in farming communities. A four-stage stratified sampling was used to collect data from 300 groundnut farmers in seven agro-ecological zones through individual interviews. Secondary data were collected from the literature and the Tanzania Agricultural Research Institute at Naliendele centre (TARI–Naliendele). Descriptive statistics and Probit regression model were used for data analysis. The empirical results showed that Johari 1985, Pendo 1998, Naliendele 2009, Mnanje 2009, Mangaka 2009 and Nachi 2015, are the main six improved groundnut varieties used by farmers, with Pendo 1998 having the highest adoption rate (17.1%). In the grain market, four varieties, namely Pendo 1998, Mnanje 2009, Nachi 2015 and Johari 1985, were observed to be highly preferred by grain off-takers. Furthermore, among the adopted improved varieties, Nachi 2015, is observed to be the most consistent high yielding variety, ranging from 1100 kg/ha to 1500 kg/ha in all agro-ecological zones. A farmer’s decision to adopt new varieties is affected by age and gender, farmer group membership, availability of improved seed and seed cost. Overall, male farmers are more likely to adopt improved varieties of groundnut than female farmers. The implications of these findings are also discussed, in particular in the area of policy support.

Description: Green bonds are similar to conventional bonds but are specifically earmarked to raise money to finance climate or environmental projects. There have been anecdotes of green bonds being priced tighter than similar conventional bonds by the same issuers. Our survey of academic literature indicates that most papers show the yield of a green bond is lower than that of the equivalent conventional bond at issuance (also known as green premium or greenium). However, green bond pricing studies by Climate Bonds Initiative produce mixed results. The conflicting results are likely explained by differences in sample selections, time periods, methodologies, and the properties of the respective issuing entity and the bond. In addition, we examine investment returns from select green bond funds and green bond indexes. The assets under management of those funds are still small and they underperform their benchmark indexes.

Description: Protected areas are the backbone of biodiversity conservation but are fixed in space and vulnerable to anthropogenic climate change. Myanmar is exceptionally rich in biodiversity but has a small protected area system. This study aimed to assess the potential vulnerability of this system to climate change. In the absence of good biodiversity data, we used a spatial modeling approach based on a statistically derived bioclimatic stratification (the Global Environmental Stratification, GEnS) to understand the spatial implications of projected climate change for Myanmar’s protected area system by 2050 and 2070. Nine bioclimatic zones and 41 strata were recognized in Myanmar, but their representation in the protected area system varied greatly, with the driest zones especially underrepresented. Under climate change, most zones will shift upslope, with some protected areas projected to change entirely to a new bioclimate. Potential impacts on biodiversity include mountaintop extinctions of species endemic to isolated peaks, loss of climate specialists from small protected areas and those with little elevational range, and woody encroachment into savannas and open forests as a result of both climate change and rising atmospheric CO2. Myanmar needs larger, better connected, and more representative protected areas, but political, social, and economic problems make this difficult.

Description: Information and communication technologies transform modern education into a more available learning matrix. One of the unexplored aspects of open education is the constant communicative interaction within the student group by using social media. The aim of the study was to determine principal functions of student-led communication in the educational process, the method for assessing its strong points and the disadvantages disrupting traditional learning. For the primary study of the phenomenon, we used methods that made it possible to propose approaches to further analysis. Netnography is the main research method defining the essence and characteristics of the student-led peer-communication. In our research, we applied data visualization, analytical and quantitative methods and developed a set of quantitative indicators that can be used to assess various aspects of student communication in chats. The elaborated visual model can serve as a simple tool for diagnosing group communication processes. We revealed that online group chats perform a support function in learning. They provide constant informational resource on educational and organizational issues and create emotional comfort. Identified features serve to define shortcomings (e.g., lack of students’ readiness to freely exchange answers to assignments) and significant factors (e.g., underutilized opportunities for self-organization) that exist in the modern system of higher education.

Description: Sugarcane is an important industrial crop because it is the major source of white sugar. It is also one of the crops for the alcohol and biofuel industries. Disease-causing organisms can significantly decrease the productivity of sugarcane plants and sugar quality. Among the disease-causing organisms, Colletotrichum falcatum Went causes the most significant economic loss (5–50%) in the sugarcane production due to red rot disease. This loss results in only 31% sugar recovery. It is reported that C. falcatum can kill sugarcane plants. Currently, there is no sustainable way of preventing red rot disease from spreading in sugarcane plantations. Many popular sugarcane varieties are no longer used in sugarcane cultivation because of their susceptibility to C. falcatum. The objectives of this manuscript were to: (i) summarize existing approaches for the early detection of red rot disease and controlling techniques of red rot disease in the field and laboratory and (ii) assess red rot disease control effectiveness so as to propose better methods for mitigating the spread C. falcatum. If our proposition is adopted or practiced, it could significantly contribute to the mitigation of C. falcatum infection in the sugarcane industry. This could enable achieving sustainable cultivation of sugarcanes to guarantee the sustainability of the sugar industry in the tropics and the subtropics.

Description: Minerals from mantle xenoliths in the Zapolyarnaya pipe in the Upper Muna field, Russia and from mineral separates from other large diamondiferous kimberlite pipes in this field (Deimos, Novinka and Komsomolskaya-Magnitnaya) were studied with EPMA and LA-ICP-MS. All pipes contain very high proportions of sub-calcic garnets. Zapolyarnaya contains mainly dunitic xenoliths with veinlets of garnets, phlogopites and Fe-rich pyroxenes similar in composition to those from sheared peridotites. PT estimates for the clinopyroxenes trace the convective inflection of the geotherm (40–45 mW·m−2) to 8 GPa, inflected at 6 GPa and overlapping with PT estimates for ilmenites derived from protokimberlites. The Upper Muna mantle lithosphere includes dunite channels from 8 to 2 GPa, which were favorable for melt movement. The primary layering deduced from the fluctuations of CaO in garnets was smoothed by the refertilization events, which formed additional pyroxenes. Clinopyroxenes from the Novinka and Komsomolskaya-Magnitnaya pipes show a more linear geotherm and three branches in the P-Fe# plot from the lithosphere base to the Moho, suggesting several episodes of pervasive melt percolation. Clinopyroxenes from Zapolyarnaya are divided into four groups according to thermobarometry and trace element patterns, which show a stepwise increase of REE and incompatible elements. Lower pressure groups including dunitic garnets have elevated REE with peaks in Rb, Th, Nb, Sr, Zr, and U, suggesting mixing of the parental protokimberlitic melts with partially melted metasomatic veins of ancient subduction origin. At least two stages of melt percolation formed the inclined PT paths: (1) an ancient garnet semi-advective geotherm (35–45 mW·m−2) formed by volatile-rich melts during the major late Archean event of lithosphere growth; and (2) a hotter megacrystic PT path (Cpx-Ilm) formed by feeding systems for kimberlite eruptions (40–45 mW·m−2). Ilmenite PT estimates trace three separate PT trajectories, suggesting a multistage process associated with metasomatism and formation of the Cpx-Phl veinlets in dunites. Heating associated with intrusions of protokimberlite caused reactivation of the mantle metasomatites rich in H2O and alkali metals and possibly favored the growth of large megacrystalline diamonds.

Description: The transition from intensive conventional agriculture to sustainable agriculture has become a global priority. This is due to the need for environmentally friendly agriculture to ensure sufficient food for a rapidly growing population. The bioeconomy is essential to progress in the field of sustainable agriculture. It contributes to the conservation of biological resources through circular and comprehensive management. The bioeconomy prioritizes the reduction and reuse of materials and products. The focus of this study is the use of biodegradable/compostable raffia in protected horticultural crops in the Province of Almería (Spain). The analysis and evaluations, based on an extensive literature review and information given by stakeholders, determined that biodegradable raffia use significantly improves the management of residual biomass in Almería. However, biodegradable raffia is only used in a small percentage of crops even though it is a sustainable alternative and profitable for farmers. The economic analysis incorporates the higher cost of recycling non-biodegradable raffia.

Description: Sustainable agricultural production is endangered by several ecological factors, such as drought, extreme temperatures, excessive salts, parasitic ailments, and insect pest infestation. These challenging environmental factors may have adverse effects on future agriculture production in many countries. In modern agriculture, conventional crop-breeding techniques alone are inadequate for achieving the increasing population’s food demand on a sustainable basis. The advancement of molecular genetics and related technologies are promising tools for the selection of new crop species. Gene pyramiding through marker-assisted selection (MAS) and other techniques have accelerated the development of durable resistant/tolerant lines with high accuracy in the shortest period of time for agricultural sustainability. Gene stacking has not been fully utilized for biotic stress resistance development and quality improvement in most of the major cultivated crops. This review emphasizes on gene pyramiding techniques that are being successfully deployed in modern agriculture for improving crop tolerance to biotic and abiotic stresses for sustainable crop improvement.

Description: People spend most of their time in indoors and, as a result, indoor air quality has become an issue of increasing concern. Due to the use of coal and heavy transportation in Beijing, China, concentrations of polycyclic aromatic hydrocarbons (PAHs) bound to PM2.5 have risen and caused concerns about health risk, both outdoors and indoors. This study carried out quantitative investigation of PM2.5-bound PAHs in middle school classrooms and estimated the health risk to adolescents. According to the results, indoor PM2.5 concentrations ranged from 20.9 μg/m3 to 257.6 μg/m3, indoor PAH concentrations ranged from 8.0 ng/m3 to 83.0 ng/m3, and both were statistically correlated with outdoor concentrations. Results of diagnostic ratios (DR) and the PMF (positive matrix factorization) model indicated that coal combustion was the main source of PAHs in the classroom environment. The average value of incremental lifetime cancer risk (ILCR) was estimated to be 1.49 × 10−6, which indicated a potential health risk to students according to USEPA standards. Predictions showed that by 2021–2022, the risk will be reduced to an acceptable level. Results of this study could provide useful information for air pollution control in Beijing and proposing targeted solution against indoor air pollution.

Description: A multimode resource-constrained project scheduling problem (MRCPSP) may have multifeasible solutions, due to its nature of targeting multiobjectives. Given the NP-hard MRCPSP and intricate multiobjective algorithms, finding the optimized result among those solutions seems impossible. This paper adopts data envelopment analysis (DEA) to evaluate a series of solutions of an MRCPSP and to find an appropriate choice in an objective way. Our approach is applied to a typical MRCPSP in practice, and the results validate that DEA is an effective and objective method for MRCPSP solution selection.

Description: Based on the oligopoly game theory and the intellectual property rights protection policy, we investigate the complex dynamical behaviors of a mixed duopoly game with quadratic cost. In the new system, a few parameters are improved by considering intellectual property rights protection and the stability conditions of the Nash equilibrium point are discussed in detail. A set of the two-dimensional bifurcation diagrams is demonstrated by using numerical modeling, and these diagrams show abundant complex dynamical behaviors, such as coexistence of attractors, different bifurcation, and fractal structures. These dynamical properties can present the long-run effects of strengthening intellectual property protection.

Description: Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way bridge connects environments where deep learning resources are plentiful with those where they are scarce. The paper describes several unique features offered by FKB, such as customizable layers, loss functions, and network ensembles. The paper concludes with a case study that applies FKB to address open questions about the robustness of an experimental approach to global climate simulation, in which subgrid physics are outsourced to deep neural network emulators. In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to be transferred and used in Fortran. Such a process allows the model’s emergent behavior to be assessed, i.e., when fit imperfections are coupled to explicit planetary-scale fluid dynamics. The results reveal a previously unrecognized strong relationship between offline validation error and online performance, in which the choice of the optimizer proves unexpectedly critical. This in turn reveals many new neural network architectures that produce considerable improvements in climate model stability including some with reduced error, for an especially challenging training dataset.

Description: Social networks are a complex system that members communicate, create new connections or destroy existing connections, and further deliver major impacts on each member’s life. Given the spread of the Internet and increased academic pressure, sedentary and prescreen behaviors are very common among adolescents; meanwhile, sports behaviors are gradually decreasing. This situation has had an adverse effect on health. This paper used a questionnaire survey to investigate the influence of social networks on adolescent sports behavior, including the intermediary role of social efficacy and moderating effect of self-presentation. The questionnaire survey was conducted on 568 students from 6 high schools in Shaanxi, Henan, and Shandong Provinces. After this, factor analysis and weighted least squares method were used for the empirical test. Based on theoretical and empirical analysis, this paper found the following: (1) Social networks of adolescents have obvious positive predictive effects on their sports behavior. A single online social network and an offline social network, instrumental network, emotional network, and mixed network have obvious positive predictive effects on adolescent sports behaviors. However, under the influence of multiple types of social networks, an offline social network has a negative predictive effect, while a mixed network has effects that are not as obvious. (2) Social efficacy plays an intermediary role in the relationship between social network and adolescent sports behavior. (3) The moderating effect of self-presentation is not significant.

Description: The aim of the study was to evaluate the changes in glomalin-related soil proteins (GRSP) content, microbial diversity and soil physical quality depending on the type of soil measures of soil improvement and changes in soil health. The study was based on a 100-year stationary field microplot experiment where the soil profiles were collected with preserving the natural soil horizons. The microplot experiment was carried out on eight different soil types: Brunic Arenosol (Dystric I), Rendzic Leptosol, Fluvic Cambisol, Haplic Cambisol (Eutric), Gleyic Phaeozem, Brunic Arenosol (Dystric II), Haplic Cambisol (Eutric II) and Haplic Cambisol (Dystric). These soils are the most common types of agricultural soils in Poland. Relatively significant correlations with the soil quality, physical parameters and the glomalin-related soil proteins have been found. The study determined the total GRSP (T-GRSP) and easily extractable GRSP (EE-GRSP) levels in soils as well as the soil physical quality index and soil’s microbial biodiversity. The GRSP depended on the type of soil and correlated with S-Index and also was responsible for the unique chemical and physical properties of soils. Soils characterized by the highest T-GRSP content belonged to the group of very good and good soil physical quality characterized also by high biological activity, for which there were strong correlations with such parameters as dehydrogenase activity (DHA), microbial biomass content (MBC), microbial nitrogen content (MBN) and total bacteria number (B). The highest T-GRSP content and higher microbial diversity were found in Gleyic Phaeozem, Rendzic Leptosol and Fluvic Cambisol. The T-GRSP and EE-GRSP content were additionally correlated with the number of AMF spores. Very poor and poor soil physical quality according to S-Index characterized Brunic Arenosol (Dystric I) and Haplic Cambisol (Dystric). This research indicates that a specific edaphone of soil microorganisms and GRSP content may be of great importance when assessing a soil’s quality and improvements in soil health. The abundance of glomalin-producing fungi significantly affects the quality of the soil. This effect is particularly important for agricultural soils are threatened by ongoing land degradation.

Description: An experimental product study of the reactions of furfural with the main tropospheric oxidants (Cl, OH and NO3) has been carried out using a Fourier Transform Infrared spectrophotometer (FTIR) and a gas chromatograph–mass spectrometer with a time of flight detector (GC–TOFMS). The main gas-phase products detected were 5-chloro-2(5H)-furanone, maleic anhydride, 2-nitrofuran and CO. Molar yields were quantified for the detected products in these reactions, thus suggesting the existence of nongaseous products that could not be observed with the analytical techniques employed. The formation of Secondary Organic Aerosol (SOA) from the oxidation of furfural with Cl atoms, OH, NO3 and ozone was investigated in a smog chamber in the absence of inorganic seed aerosols. The experimental results show the formation of ultrafine particles (less than 1 µm in diameter) for all of the studied reactions except for the nitrate radical. Given their small size, these ultrafine particles (

Description: Precise exposure assessment of air pollutants is crucial in epidemiologic studies to ensure valid estimates of health effects. We conducted a longitudinal study to evaluate the role of air quality monitoring (AQM) measurements and high-resolution modeling outcomes focusing on nitrogen dioxide (NO2) exposure and atopic dermatitis (AD). A total of 128 young children with AD in Seoul Metropolitan Area, Korea, were recruited as a panel. We estimated the participants’ exposure to NO2 for four months, from 1 April through 31 July 2014 based on (1) monitored levels from 60 AQM stations located at varying distances from residential areas (AQM station-based NO2, AQM-NO2) and (2) estimates from a community multi-scale air quality (CMAQ) modeling system with a high-resolution (1 × 1 km) (CMAQ-NO2). We then compared the effect of AQM-NO2 on AD symptoms with that of CMAQ-NO2. The average distance between the participants’ residences and the nearest AQM station was 2.03 ± 1.06 km, ranging from 0.28 km to 5.73 km. Based on AQM-NO2, the AD symptoms increased by 10.28% (95% confidence interval (CI): 3.24, 17.79) with an increase of 10 ppb of NO2. The effect estimates of CMAQ-NO2 were similar to those of AQM-NO2 when assessed in patients living within 3 km from the nearest AQM station. Even within 1 km, the CI estimate obtained from the CMAQ was much narrower than from AQM (44.18–49.54 vs. 7.02–64.75). However, the association of AQM-NO2 with AD symptoms of patients living beyond 3 km was not positive, whereas that of CMAQ-NO2 maintained positive. In conclusion, exposure to ambient NO2 is significantly associated with aggravation of AD symptoms in young children. In addition, our study suggests that exposure assessment of NO2 using measurement data obtained from monitoring stations far from residential locations can lead to misclassification bias.

Description: Reducing plastic pollution in rivers, lakes, and oceans is beneficial to aquatic animals and human livelihood. To achieve this, reliable observations of the abundance, spatiotemporal variation, and composition of plastics in aquatic ecosystems are crucial. Current efforts mainly focus on collecting data on the open ocean, on beaches and coastlines, and in river systems. Urban areas are the main source of plastic leakage into the natural environment, yet data on plastic pollution in urban water systems are scarce. In this paper, we present a simple method for plastic hotspot mapping in urban water systems. Through visual observations, macroplastic abundance and polymer categories are determined. Due to its simplicity, this method is suitable for citizen science data collection. A first application in the Dutch cities of Leiden and Wageningen showed similar mean plastic densities (111–133 items/km canal) and composition (75–80% soft plastics), but different spatial distributions. These observations emphasize the importance of long-term data collection to further understand and quantify spatiotemporal variations of plastics in urban water systems. In turn, this will support improved estimates of the contribution of urban areas to the plastic pollution of rivers and oceans.

Description: Leaf rust (LR) and stem rust (SR) pose serious challenges to wheat production in Kazakhstan. In recent years, the susceptibility of local wheat cultivars has substantially decreased grain yield and quality. Therefore, local breeding projects must be adjusted toward the improvement of LR and SR disease resistances, including genetic approaches. In this study, a spring wheat segregating population of Pamyati Azieva (PA) × Paragon (Par), consisting of 98 recombinant inbred lines (RILs), was analyzed for the resistance to LR and SR at the seedling and adult plant-growth stages. In total, 24 quantitative trait loci (QTLs) for resistance to rust diseases at the seedling and adult plant stages were identified, including 11 QTLs for LR and 13 QTLs for SR resistances. Fourteen QTLs were in similar locations to QTLs and major genes detected in previous linkage mapping and genome-wide association studies. The remaining 10 QTLs are potentially new genetic factors for LR and SR resistance in wheat. Overall, the QTLs revealed in this study may play an important role in the improvement of wheat resistance to LR and SR per the marker-assisted selection approach.

Description: Black carbon (BC), organic carbon (OC), and total carbon (TC) in snow are important for their climatic and cryospheric effects. They are also part of the global carbon cycle. Atmospheric black and organic carbon (including brown carbon) may deposit and darken snow surfaces. Currently, there are no standardized methods for sampling, filtering, and analysis protocols to detect carbon in snow. Here, we describe our current methods and protocols to detect carbon in seasonal snow using the OCEC thermal optical method, a European standard for atmospheric elemental carbon (EC). We analyzed snow collected within and around the urban background SMEARIII (Station for Measuring Ecosystem-Atmosphere Relations) at Kumpula (60° N) and the Arctic GAW (Global Atmospheric Watch) station at Sodankylä (67° N). The median BC, OC, and TC in snow samples (ntot = 30) in Kumpula were 1118, 5279, and 6396 ppb, and in Sodankylä, they were 19, 1751, and 629 ppb. Laboratory experiments showed that error due to carbon attached to a sampling bag (n = 11) was

Description: Height measurement for moving pedestrians is quite significant in many scenarios, such as pedestrian positioning, criminal suspect tracking, and virtual reality. Although some existing height measurement methods can detect the height of the static people, it is hard to measure height accurately for moving pedestrians. Considering the height fluctuations in dynamic situation, this paper proposes a real-time height measurement based on the Time-of-Flight (TOF) camera. Depth images in a continuous sequence are addressed to obtain the real-time height of the pedestrian with moving. Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. Thirdly, a segmentation algorithm based on the maximally stable extremal regions (MSERs) is introduced to extract the pedestrian head region. Then, a novel multilayer iterative average algorithm (MLIA) is developed for obtaining the height of dynamic pedestrians. Finally, Kalman filtering is used to improve the measurement accuracy by combining the current measurement and the height at the last moment. In addition, the VICON system is adopted as the ground truth to verify the proposed method, and the result shows that our method can accurately measure the real-time height of moving pedestrians.

Description: Since China’s first stock index futures, China Securities Index 300 (CSI300) stock index futures were published in 2010, and China’s stock index futures market is now in a period of rapid development and play a key role in price discovery. During 2014 to 2015, China’s stock index futures market fluctuated abnormally, and the overuse of high-frequency trading (HFT) strategies in the stock index futures market was blamed as the main reason of the abnormal volatility. To lower down market fluctuation, the regulatory institute then announced a series of trade restriction policy to prevent the overuse of HFT behaviour. However, until now, the impact of such trade restriction policy for HFT remains uncertain. To tackle this issue, based on minute-level HFT data from the CSI 300 index futures market, this paper aims to investigate the relationship between HFT and the exogenous liquidity risk and how HFT affects China’s stock index futures market on its liquidity using the liquidity-adjusted value at risk (LVaR) model. The findings indicate that HFT improves the return of the liquidity provider and reduces the exogenous liquidity risk significantly.

Description: Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019–2020. The PM2.5 sensor output correlates strongly with reference measurements (R2 = 0.87 against a beta attenuation monitor and R2 = 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor’s response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating.

Description: Due to the growing success of neural machine translation (NMT), many have started to question its applicability within the field of literary translation. In order to grasp the possibilities of NMT, we studied the output of the neural machine system of Google Translate (GNMT) and DeepL when applied to four classic novels translated from English into Dutch. The quality of the NMT systems is discussed by focusing on manual annotations, and we also employed various metrics in order to get an insight into lexical richness, local cohesion, syntactic, and stylistic difference. Firstly, we discovered that a large proportion of the translated sentences contained errors. We also observed a lower level of lexical richness and local cohesion in the NMTs compared to the human translations. In addition, NMTs are more likely to follow the syntactic structure of a source sentence, whereas human translations can differ. Lastly, the human translations deviate from the machine translations in style.

Description: The article is devoted to a reconstruction of the sedimentation processes in Kamyshovoye Lake (the Kaliningrad Region, Russia) during the Late Glacial and Holocene. The results of the geochemical analysis of Kamyshovoye Lake’s bottom sediments, accompanied by statistical processing and detailed radiocarbon dating, are presented. It was established that a high proportion of mineral matter dominated in the intervals between 15,000 and 11,400 and between 1400 and 600 cal y BP; enrichment with carbonates was noted between 11,400 and 5200 cal y BP and during the past 600 years; and a high percentage of organic matter was recorded between 7800 and 600 cal y BP. We conclude that the increase in mineral matter was influenced by such factors as reduced vegetation cover due to natural and anthropogenic processes, aeolian transfer, and dead-ice melting during the Late Glacial. The increase in carbonate matter was mainly associated with humidity and the reduction conditions of the lake ecosystem. Organogenic matter content was affected by the autochthonic (biological) productivity of the lake, which directly depends on more favorable climatic conditions.

Description: Fertilized agricultural soils serve as a primary source of anthropogenic N2O emissions. In South Africa, there is a paucity of data on N2O emissions from fertilized, irrigated dairy-pasture systems and emission factors (EF) associated with the amount of N applied. A first study aiming to quantify direct N2O emissions and associated EFs of intensive pasture-based dairy systems in sub-Sahara Africa was conducted in South Africa. Field trials were conducted to evaluate fertilizer rates (0, 220, 440, 660, and 880 kg N ha−1 year−1) on N2O emissions from irrigated kikuyu–perennial ryegrass (Pennisetum clandestinum–Lolium perenne) pastures. The static chamber method was used to collect weekly N2O samples for one year. The highest daily N2O fluxes occurred in spring (0.99 kg ha−1 day−1) and summer (1.52 kg ha−1 day−1). Accumulated N2O emissions ranged between 2.45 and 15.5 kg N2O-N ha−1 year−1 and EFs for mineral fertilizers applied had an average of 0.9%. Nitrogen in yielded herbage varied between 582 and 900 kg N ha−1. There was no positive effect on growth of pasture herbage from adding N at high rates. The relationship between N balance and annual N2O emissions was exponential, which indicated that excessive fertilization of N will add directly to N2O emissions from the pastures. Results from this study could update South Africa’s greenhouse gas inventory more accurately to facilitate Tier 3 estimates.

Description: Achieving sustainable zero-waste and carbon neutral solutions that contribute to a circular economy is critically important for the long-term prosperity and continuity of traditional carbon-based energy industries. The Estonian oil shale (OS) sector is an example where such solutions are more than welcome. The combustion of OS generates a continuous flow of ashes destined to landfills. In this study, the technical feasibility of producing monolith building materials incorporating different OS ashes from Estonia was evaluated. Three binder systems were studied: self-cementation of the ashes, ceramic sintering in clay brick production and accelerated carbonation of OS ash (OSA) compacts. Results showed that most of the OSAs studied have low self-cementitious properties and these properties were affected by ash fineness and mineralogical composition. In case of clay bricks, OSA addition resulted in a higher porosity and improved insulation properties. The carbonated OSA compacts showed promising compressive strength. Accelerated carbonation of compacted samples was found to be the most promising way for the future utilization of OSAs as sustainable zero-waste and carbon neutral solution.

Description: The emergence and outbreak of the novel coronavirus (COVID-19) had a devasting effect on global health, the economy, and individuals’ daily lives. Timely diagnosis of COVID-19 is a crucial task, as it reduces the risk of pandemic spread, and early treatment will save patients’ life. Due to the time-consuming, complex nature, and high false-negative rate of the gold-standard RT-PCR test used for the diagnosis of COVID-19, the need for an additional diagnosis method has increased. Studies have proved the significance of X-ray images for the diagnosis of COVID-19. The dissemination of deep-learning techniques on X-ray images can automate the diagnosis process and serve as an assistive tool for radiologists. In this study, we used four deep-learning models—DenseNet121, ResNet50, VGG16, and VGG19—using the transfer-learning concept for the diagnosis of X-ray images as COVID-19 or normal. In the proposed study, VGG16 and VGG19 outperformed the other two deep-learning models. The study achieved an overall classification accuracy of 99.3%.

Description: This paper presents a review and analysis of large-scale air convection tests and the establishment of intrinsic permeability in coarse open-graded materials. Natural air convection can make a significant contribution to heat transfer during cooling periods. In seasonally freezing environments this can result in excessive frost penetration and subsequent frost-related problems. Intrinsic permeability largely defines the onset of convective heat transfer in granular materials. Conventional methods for measuring intrinsic permeability cannot be applied to very coarse materials. Large-scale laboratory experiments on natural air convection can serve as an alternative method for determining this crucial parameter. This paper gives an overview of four different experimental test setups for measuring natural air convection, all differing in physical shape, boundary conditions and heat flux/temperature measurement devices. Comparison between these is difficult because the air convection pattern can differ and in some cases the shape and number of convection cells cannot be validated. Most of the studies available in the literature use theoretical equations to approximate intrinsic permeability. A method based on the analytical Nu-Ra number relationship is employed to establish the values of intrinsic permeability. Tests that provide enough data to enable the use of the Nu-Ra relationship are very limited. The overall results show a reasonable correlation between experiment-based intrinsic permeability and theoretical approximation. However, several issues must be addressed: first, differences may exist between the intrinsic permeability of natural and of crushed materials due to the shape effect. Second, the method used is in theory valid only for two-dimensional air convection within a square enclosure heated from below. Yet the results show that this method could be extended to other conditions with a certain degree of confidence. Third, a good estimate of intrinsic permeability is possible only with accurate experimental measurement.

Description: Community is the core spatial unit for evaluating sustainable development. However, single data and method seem inadequate for conducting a scientific, effective, and innovative sustainable evaluation of complex community units. In this study, we perform a sustainable-oriented land use scheme using multisource remote sensing, machine learning, and object-based postclassification refinement. Furthermore, we assess the sustainability of the traffic community by data-driven and combined housing, ecosystem services, and landscape configuration. The results indicated that (1) the relationship between housing, ecosystem services, and landscape pattern has obvious synergistic effects, although with dissimilar importance in different sustainability levels. High sustainability level is intensely coordinated with landscape configuration, medium sustainability level is more affected by ecosystem services, and low sustainability level is more related to housing. (2) Community sustainability presents a significant spatial distribution. The communities of high sustainability level are mainly located in both sides of the Pearl River and emerging urban areas, while those of medium sustainability level are distributed sporadically in the study area and those of low sustainability level are concentrated in old towns. (3) Community transformation cannot be accomplished at one step. Along with the continuous optimization of landscape configuration, the priority should be given to housing reconstruction and improvement of ecosystem services further. We provide scientific and effective data-based evidence for urban decision-makers by integrating the advantages of the Earth Observation System and multifactor analysis.

Description: Practically, supply disruption may lead production process to entirely halt (completely disrupted) or the output to differ in the order size (partially disrupted), which makes it more difficult for the retailer to satisfy stochastic market demand. Under the circumstance, the retailer is likely to procure products from two suppliers to effectively alleviate the demand-supply mismatches. Thus, under supply disruption and stochastic demand, this paper develops both backup sourcing and simultaneous sourcing (SS) strategies to analyze the retailer’s performance, where backup sourcing includes wholesale price priority (WPP) and supply reliability priority (SRP). Specifically, (1) under WPP, when the selling price is relatively lower (higher), the retailer is suggested to activate the reliable backup supplier after the realization of supply disruption (demand uncertainty). (2) Under SRP, two scenarios including minor disruption and major disruption can be identified, where the retailer’s order quantity from the reliable (unreliable) supplier under minor disruption scenario is more (less) than that under major. (3) Finally, this paper systematically compares the retailer’s preferences among WPP, SRP, and SS via theoretical results and numerical examples. That is, when the unreliable supplier is more likely to work normally or shortage cost (selling price) is relatively lower, the retailer prefers SPR regarding the unreliable supplier as backup sourcing due to its lower wholesale price and acceptable supply disruption. Otherwise, the retailer is inclined to WPP regarding the reliable supplier as backup sourcing for ensuring all market demand to be satisfied. In addition, unless the emergency prices of two suppliers are extremely higher, backup sourcing strategies could perform better than simultaneous sourcing strategy.

Description: This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

Description: Single image super-resolution (SISR) is a traditional image restoration problem. Given an image with low resolution (LR), the task of SISR is to find the homologous high-resolution (HR) image. As an ill-posed problem, there are works for SISR problem from different points of view. Recently, deep learning has shown its amazing performance in different image processing tasks. There are works for image super-resolution based on convolutional neural network (CNN). In this paper, we propose an adaptive residual channel attention network for image super-resolution. We first analyze the limitation of residual connection structure and propose an adaptive design for suitable feature fusion. Besides the adaptive connection, channel attention is proposed to adjust the importance distribution among different channels. A novel adaptive residual channel attention block (ARCB) is proposed in this paper with channel attention and adaptive connection. Then, a simple but effective upscale block design is proposed for different scales. We build our adaptive residual channel attention network (ARCN) with proposed ARCBs and upscale block. Experimental results show that our network could not only achieve better PSNR/SSIM performances on several testing benchmarks but also recover structural textures more effectively.

Description: A floor aquifuge usually bends and fails when mining above a confined aquifer, which may lead to water inrush disaster. The floor aquifuge was simplified as a thin disc model in this paper, and a series of coupled bending-seepage tests of sandstone were carried out by a patent test system. The variation characteristics of load-displacement, load-time, and permeability-time were analyzed. The deflection and stress in the thin disc rock samples were deduced; the initiation and propagation of cracks were analyzed. The failure behavior of the thin disc rock samples was described. It shows the following: (1) The bending failure behavior relates to the stress distribution and crack evolution inside the thin disc. (2) The main cause of crack initiation is a tension-shear failure. (3) The 5 mm thickness thin discs form petal-shaped cracks, due to tensile stress, while petal-shaped cracks only appear at the cap block of the 10 mm discs, which are sheared into two pieces along the conical surface with an inclination about 45°. (4) Water inrush occurs after bending failure in the floor aquifuge, and it is an opportune moment to grout along the crack propagation trend lines to prevent the water inrush disasters.

Description: Evapotranspiration (ET) is an essential component of watershed hydrological cycle. Spatial-temporal variations analyses of evapotranspiration and potential evapotranspiration (PET) have remarkable theoretical and practical significances for understanding the interaction between climate changes and hydrological cycle and optimal allocation of water resources under global warming background. The MODIS-estimated ET agreed well with basin evapotranspiration from water balance principle methods in the study. The spatiotemporal variations results based on MOD16 ET data showed the following: (1) multiyear mean ET and PET were 464.2 mm and 1192.2 mm, and annual ET showed an upward trend at a rate of 3.48 mm/a, while PET decreased significantly at a rate of −8.18 mm/a. The annual ET trend showed a complemental relationship with PET; (2) at the seasonal scale, ET was highest in summer and least in winter, while PET was higher in spring and summer. The change of ET and PET in spring and summer had a great contribution to the annual variations; (3) ET and PET in the northern part were significantly stronger than those in the western and southern parts; (4) ET in cropland increased significantly, while PET decreased obviously in grass and forest; (5) changes of ET and PET were closely related to climatic factors. The rise in temperature caused the increase in ET and the decrease of wind speed contributed more to the decrease in PET. The results can provide a scientific basis for water resources planning and management.

Description: With the gestation and development of new technologies, new products, new formats, and new models, venture capital investment, as one of the most important forms of open innovation in large companies, plays an increasingly important role in the innovation of mature large companies and entrepreneurial enterprises. To deal with the complex and dynamic environment, the niche of Corporate Venture Capital (CVC) ecological community is investigated from the perspective of the innovation ecosystem. By analyzing the innovation of CVC ecological community with the use of the logistic expansion model, this paper analyzes the stability of evolution game through the replicator dynamic equation and discusses ten parameters of niche state. In the end, we conclude that there are four optimization strategies in the coevolution of major corporations and entrepreneurial firms, namely, niche separation, niche expansion, niche K-R, and niche alliance.

Description: Multiobject detection tasks in complex scenes have become an important research topic, which is the basis of other computer vision tasks. Considering the defects of the traditional single shot multibox detector (SSD) algorithm, such as poor small object detection effect, reliance on manual setting for default box generation, and insufficient semantic information of the low detection layer, the detection effect in complex scenes was not ideal. Aiming at the shortcomings of the SSD algorithm, an improved algorithm based on the adaptive default box mechanism (ADB) is proposed. The algorithm introduces the adaptive default box mechanism, which can improve the imbalance of positive and negative samples and avoid manually set default box super parameters. Experimental results show that, compared with the traditional SSD algorithm, the improved algorithm has a better detection effect and higher accuracy in complex scenes.

Description: The nonlinear resonant responses, mode interactions, and multitime periodic and chaotic oscillations of the cantilevered pipe conveying pulsating fluid are studied under the harmonic external force in this research. According to the nonlinear dynamic model of the cantilevered beam derived using Hamilton’s principle under the uniformly distributed external harmonic excitation, we combine Galerkin technique and the method of multiple scales together to obtain the average equation of the cantilevered pipe conveying pulsating fluid under 1 : 3 internal resonance and principal parametric resonance. Based on the average equation in the polar form, several amplitude-frequency response curves are obtained corresponding to the certain parameters. It is found that there exist the hardening-spring type behaviors and jumping phenomena in the cantilevered pipe conveying pulsating fluid. The nonlinear oscillations of the cantilevered pipe conveying pulsating fluid can be excited more easily with the increase of the flow velocity, external excitation, and coupling degree of two order modes. Numerical simulations are performed to study the chaos of the cantilevered pipe conveying pulsating fluid with the external harmonic excitation. The simulation results exhibit the existence of the period, multiperiod, and chaotic responses with the variations of the fluid velocity or excitation. It is found that, in the cantilevered pipe conveying pulsating fluid, there are the multitime nonlinear vibrations around the left-mode and the right-mode positions, respectively. We also observe that there exist alternately the periodic and chaotic vibrations of the cantilevered pipe conveying pulsating fluid in the certain range.

Description: A remarkable exposure of tubular authigenic carbonates was found on the seafloor in the Dongsha area of the South China Sea (SCS). The tubular carbonates, around 2–3 cm in diameter and usually less than 10 cm in length, represent broken fragments of once-larger pipes that now protrude from muddy sediments. The morphology, carbon and oxygen stable isotope compositions, and trace and rare earth element contents of the carbonates were analyzed to decipher the mode of carbonate formation. The tubular carbonates exhibit a dark brown coating of iron and manganese hydrous oxides, indicating prolonged exposure to oxic bottom waters. The carbonate content of the micritic pipes falls between 12.5 and 67.3 wt.% with an average of 42.0 wt.%, suggesting formation within the sediment. This inference is supported by trace and rare earth element patterns including a moderate enrichment of middle rare earth elements. Low δ13C values (as low as −50.3‰, Vienna Pee Dee Belemnite (VPDB)) suggest that carbonate precipitation was induced by the anaerobic oxidation of methane. The unusually positive δ18O values of the carbonates (as high as +5.3‰, VPDB) are believed to reflect the destabilization of locally abundant gas hydrate. Taken together, it is suggested that pipe formation was initiated by sediment-dwelling organisms, such as crustaceans or bivalves. The burrows subsequently acted as conduits for upward fluid migration. The lithification of the sediment directly surrounding the conduits and the partial filling of the conduits with carbonate cement resulted in the formation of tubular carbonates. Turbidity currents, sediment slumps, or the vigorous emission of fluids probably induced the fragmentation of tubular carbonates within the sediment. The carbonate fragments had been further subjected to winnowing by bottom currents. This study provides insight into the interaction of megafauna burrowing with fluid migration and carbonate formation at hydrocarbon seeps, highlighting the role of bottom currents and mass wasting on the formation of fragmented tubular carbonates.

Description: In November 2019, the Supreme Court of India issued a notification to all the states in the National Capital Region of Delhi to install smog towers for clean air and allocated INR 36 crores (~USD 5.2 million) for a pilot. Can we vacuum our air pollution problem using smog towers? The short answer is “no”. Atmospheric science defines the air pollution problem as (a) a dynamic situation where the air is moving at various speeds with no boundaries and (b) a complex mixture of chemical compounds constantly forming and transforming into other compounds. With no boundaries, it is unscientific to assume that one can trap air, clean it, and release into the same atmosphere simultaneously. In this paper, we outline the basics of atmospheric science to describe why the idea of vacuuming outdoor air pollution is unrealistic, and the long view on air quality management in Indian cities.

Description: In this work, we demonstrate how the blockchain and the off-chain storage interact via Oracle-based mechanisms, which build an effective connection between a distributed database and real assets. For demonstration purposes, smart contracts were drawn up to deal with two different applications. Due to the characteristics of the blockchain, we may still encounter severe privacy issues, since the data stored on the blockchain are exposed to the public. The proposed scheme provides a general solution for resolving the above-mentioned privacy issue; that is, we try to protect the on-chain privacy of the sensitive data by using homomorphic encryption techniques. Specifically, we constructed a secure comparison protocol that can check the correctness of a logic function directly in the encrypted domain. By using the proposed access control contract and the secure comparison protocol, one can carry out sensitive data-dependent smart contract operations without revealing the data themselves.

Description: Healthcare facilities are constantly deteriorating due to tight budgets allocated to the upkeep of building assets. This entails the need for improved deterioration modeling of such buildings in order to enforce a predictive maintenance approach that decreases the unexpected occurrence of failures and the corresponding downtime elapsed to repair or replace the faulty asset components. Currently, hospitals utilize subjective deterioration prediction methodologies that mostly rely on age as the sole indicator of degradation to forecast the useful lives of the building components. Thus, this paper aims at formulating a more efficient stochastic deterioration prediction model that integrates the latest observed condition into the forecasting procedure to overcome the subjectivity and uncertainties associated with the currently employed methods. This is achieved by means of developing a hybrid genetic algorithm-based fuzzy Markovian model that simulates the deterioration process given the scarcity of available data demonstrating the condition assessment and evaluation for such critical facilities. A nonhomogeneous transition probability matrix (TPM) based on fuzzy membership functions representing the condition, age and relative deterioration rate of the hospital systems is utilized to address the inherited uncertainties. The TPM is further calibrated by means of a genetic algorithm to circumvent the drawbacks of the expert-based models. A sensitivity analysis was carried out to analyze the possible changes in the output resulting from predefined modifications to the input parameters in order to ensure the robustness of the model. The performance of the deterioration prediction model developed is then validated through a comparison with a state-of-art stochastic model in contrast to real hospital datasets, and the results obtained from the developed model significantly outperformed the long-established Weibull distribution-based deterioration prediction methodology with mean absolute errors of 1.405 and 9.852, respectively. Therefore, the developed model is expected to assist decision-makers in creating more efficient maintenance programs as well as more data-driven capital renewal plans.

Description: The problem of wave identification is formulated as applied to the results of measurements of the temperature and the density of the neutral atmosphere in the range height 90–120 km by the artificial periodic irregularities (APIs) technique. The technique is based on the resonant scattering of radio waves by artificial periodic irregularities of the ionospheric plasma emerging in the field of a standing wave arising from the interference of the incident and reflected waves from the ionosphere. APIs were created using SURA heating facility (named as SURA experiment). The acoustic wave theory is reformulated on the base of data which can be observed in the given experimental setup. The basic system of equations is reduced so that it accounts only upward and downward directed waves, ignoring entropy mode. The algorithm of wave identification based on usage of dynamic projection operators for such a reduced case is proposed and explicit form of projection operators is derived. Its application to finite number dataset via Discrete Fourier Transform (DFT) is described and results of its application to the DFT-transformed set of experimental observation of the temperature and density perturbations are presented. The result yields hybrid amplitudes, that allow us to calculate energy of the directed waves that enter the observed superposition. The problem of entropy mode detection is discussed, the corresponding projecting operators for the full evolution system are built and a way to apply the method to quantification of it is proposed.

Description: Organic amendments can reportedly sustain and increase lowland rice productivity in smallholder systems. Few studies have assessed locally-available substrates in hydrologically variable floodplain environments. We investigated the effects of green and farmyard manures on rice yields, and total soil C and N in the Kilombero floodplain, Tanzania. At both the fringe and the middle positions, five treatments were applied in 2016 and 2017, comprising (1) non-amended control, (2) farmyard manure, (3) pre-rice legumes, (4) post-rice legumes and (5) a combination of green and farmyard manures. Residual treatment effects were assessed in 2018 when rice plots were uniformly non-amended. Depending on the year and the position, organic amendments increased rice grain yields by 0.7–3.1 Mg ha–1 above the non-amended control. Sole green and farmyard manure applications had similar effects on grain yield, while a combination of green and farmyard manure led to a significant increase in grain yield above both the control and sole applications of organic amendments in both years. The contribution from biological N2 fixation by legumes ranged from 4 to 61 kg N ha–1. Despite partial N balances being mostly negative, we observed positive residual effects on the yield of the non-amended rice in the third year. Such effects reached up to 4 Mg ha−1 and were largest with post-rice legumes, sole or combined with farmyard manure. Irrespective of the position in the floodplain, manures significantly increased soil C and N contents after two years, hence enhancing soil fertility and resulting in increased rice grain yields. Comparable benefits may be obtained along the hydrological gradients of other large river floodplains of the region and beyond.

Description: The aim of this study was to analyse the genetic and phenotypic differentiation of bacteria isolated from root nodules of Trifolium rubens, a rare clover species. The symbiotic compatibility of selected isolates was investigated using two agronomically important plants, red clover (Trifolium pratense L.) and pea (Pisum sativum L.). A high genetic diversity of analysed strains was shown using the Enterobacterial Repetitive Intergenic Consensus Polymerase Chain Reaction (ERIC-PCR) method. Most of the strains showed a high similarity to R. leguminosarum in the 16S rRNA sequence. Two strains were identified as Agrobacterium spp. There was a strong positive correlation between fresh clover weight and the number of root nodules and a statistically significant increase in the number of the root nodules in selected strains compared to the negative control. Phenotypic tests and BIOLOG analysis showed the ability of the analysed strains to grow in different experimental conditions (pH = 6–10, 0.5–3% NaCl, different carbon and nitrogen sources), which makes them suitable for application as an agronomically important factor.

Description: Ecuador Andean purple corn (Zea mays L.) was subjected to a germination process at 15–40 °C for 24–168 incubation hours. Purple corn protein concentrates (PCPCs) were obtained by alkaline extraction at pH 8.0 and pH 10.0, followed by an isoelectric precipitation process at pH 4.0, pH 5.0 and pH 6.0. Proteins and phenolic content of PCPCs was calculated. PCPC antioxidant properties were determined by the ferric-reducing antioxidant power (FRAP) in vitro method and by the 2,2-azinobis, 3-ethyl-benzothiazoline-6-sulfonic acid, (ABTS) in vitro method. Andean purple corn seeds were able to germinate under the germination conditions tested in this study. The higher percentage of germination was of 63.33% at 168 h/25 °C. The PCPCs protein profile was characterized for the presence of six bands with molecular weights of 14.50 kDa, 20.12 kDa, 25.18 kDa, 41.85 kDa, 59.59 kDa, and 65.87 kDa. Germinated PCPC presented a high TPC content with ranges of 605.71–1820.00 mg gallic acid equivalents (GAE)/g PCPC dry weight (DW), germinated PCPC/72 h/25 °C presented a higher value of 1820.00 mg GAE/g PCPC, DW. All germinated PCPCs samples assayed presented strong antioxidant activity when measured by the ABTS and FRAP methods. Germinated PCPC/144 h/35 °C presented high antioxidant activity by ABTS with 804.35 µmol Trolox equivalents (TE)/g PCPC DW and germinated PCPC/144 h/30 °C presented a high value by the FRAP method, 987.83 µmol TE/g PCPC DW.

Description: Weedy rice is one of the most common weeds in rice cultivation in many rice areas throughout the world and it is able to cause significant yield reductions. Weedy rice is characterized by a high biological diversity that permits different populations to be identified on the basis of their morphological and physiological traits. This variability contributes to its success in different environments and allows different abiotic stresses, which are intensified by climate change, to be faced. Taller plants, enhanced tillering, seed shattering and the presence of red pericarp, variable hull coloration and awn morphology, linked to a deeper seed dormancy, are some of the traits that help weedy rice to spread in changing environments. The higher phenotypic plasticity and genetic variability of weedy rice make it more able to cope with temperature variations, intermittent water availability, soil salinity, drought conditions and increased CO2 concentrations than cultivated rice. As these abiotic stresses will become more frequent in the future, weedy rice competitiveness may be higher, with a spread of infestations. Thus, the control of weedy rice should be based on an integration of different preventive and agronomic techniques, a sensible use of herbicides and the use of suitable rice varieties.

Description: Ventilator is important equipment for mines as it safeguards the lives under the shaft and ensures other equipment’s proper functioning by providing fresh air. Therefore, how to effectively control the ventilator system becomes more significant. In order to acquire the commonly used model and control strategy for ventilator systems, a new universal ventilator model is established based on the blast capacity differential pressure in the ventilating duct and the ventilator motor model. Then, an adaptive Chebyshev neural network (ACNN) controller is proposed to effectively control the ventilator system where the unknown load torque and the unknown disturbance caused by the complex environment under the shaft are approximated by the Chebyshev neural network (CNN). Afterwards, an appropriate Lyapunov function candidate is designed to guarantee the stability of the proposed controller and the closed-loop ventilator system. Finally, the ACNN controller has been demonstrated to be effective in terms of validity and precision for the new proposed ventilator model through the simulations.

Description: Nonlinear evolution equations widely describe phenomena in various fields of science, such as plasma, nuclear physics, chemical reactions, optics, shallow water waves, fluid dynamics, signal processing, and image processing. In the present work, the derivation and analysis of Lie symmetries are presented for the time-fractional Benjamin–Bona–Mahony equation (FBBM) with the Riemann–Liouville derivatives. The time FBBM equation is reduced to a nonlinear fractional ordinary differential equation (NLFODE) using its Lie symmetries. These symmetries are derivations using the prolongation theorem. Applying the subequation method, we then use the integrating factor property to solve the NLFODE to obtain a few travelling wave solutions to the time FBBM.

Description: The Cloud Computing paradigm is focused on the provisioning of reliable and scalable virtual infrastructures that deliver execution and storage services. This paradigm is particularly suitable to solve resource-greedy scientific computing applications such as parameter sweep experiments (PSEs). Through the implementation of autoscalers, the virtual infrastructure can be scaled up and down by acquiring or terminating instances of virtual machines (VMs) at the time that application tasks are being scheduled. In this paper, we extend an existing study centered in a state-of-the-art autoscaler called multiobjective evolutionary autoscaler (MOEA). MOEA uses a multiobjective optimization algorithm to determine the set of possible virtual infrastructure settings. In this context, the performance of MOEA is greatly influenced by the underlying optimization algorithm used and its tuning. Therefore, we analyze two well-known multiobjective evolutionary algorithms (NSGA-II and NSGA-III) and how they impact on the performance of the MOEA autoscaler. Simulated experiments with three real-world PSEs show that MOEA gets significantly improved when using NSGA-III instead of NSGA-II due to the former provides a better exploitation versus exploration trade-off.

Description: There is a large amount of information and maintenance data in the aviation industry that could be used to obtain meaningful results in forecasting future actions. This study aims to introduce machine learning models based on feature selection and data elimination to predict failures of aircraft systems. Maintenance and failure data for aircraft equipment across a period of two years were collected, and nine input and one output variables were meticulously identified. A hybrid data preparation model is proposed to improve the success of failure count prediction in two stages. In the first stage, ReliefF, a feature selection method for attribute evaluation, is used to find the most effective and ineffective parameters. In the second stage, a K-means algorithm is modified to eliminate noisy or inconsistent data. Performance of the hybrid data preparation model on the maintenance dataset of the equipment is evaluated by Multilayer Perceptron (MLP) as Artificial Neural network (ANN), Support Vector Regression (SVR), and Linear Regression (LR) as machine learning algorithms. Moreover, performance criteria such as the Correlation Coefficient (CC), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) are used to evaluate the models. The results indicate that the hybrid data preparation model is successful in predicting the failure count of the equipment.

Description: The optical images collected by remotely operated vehicles (ROV) contain a lot of information about underwater (such as distributions of underwater creatures and minerals), which plays an important role in ocean exploration. However, due to the absorption and scattering characteristics of the water medium, some of the images suffer from serious color distortion. These distorted color images usually need to be enhanced so that we can analyze them further. However, at present, no image enhancement algorithm performs well in any scene. Therefore, in order to monitor image quality in the display module of ROV, a no-reference image quality predictor (NIPQ) is proposed in this paper. A unique property that differentiates the proposed NIPQ metric from existing works is the consideration of the viewing behavior of the human visual system and imaging characteristics of the underwater image in different water types. The experimental results based on the underwater optical image quality database (UOQ) show that the proposed metric can provide an accurate prediction for the quality of the enhanced image.

Description: Identification of community structures and the underlying semantic characteristics of communities are essential tasks in complex network analysis. However, most methods proposed so far are typically only applicable to assortative community structures, that is, more links within communities and fewer links between different communities, which ignore the rich diversity of community regularities in real networks. In addition, the node attributes that provide rich semantics information of communities and networks can facilitate in-depth community detection of structural information. In this paper, we propose a novel unified Bayesian generative model to detect generalized communities and provide semantic descriptions simultaneously by combining network topology and node attributes. The proposed model is composed of two closely correlated parts by a transition matrix; we first apply the concept of a mixture model to describe network regularities and then adjust the classic Latent Dirichlet Allocation (LDA) topic model to identify community semantically. Thus, the model can detect broad types of network structure regularities, including assortative structures, disassortative structures, and mixture structures and provide multiple semantic descriptions for the communities. To optimize the objective function of the model, we use an effective Gibbs sampling algorithm. Experiments on a number of synthetic and real networks show that our model has superior performance compared with some baselines on community detection.

Description: This work investigates a decentralized state feedback scheme of neural network control for an interconnected system. The completely unknown associated terms are estimated directly by the neural structure. A modified approach is proposed to deal with the state feedback format. By combining the Lyapunov function and backstepping technology together, an adaptive decentralized controller is established, and we can construct the boundedness of all signals in the closed-loop structure through the controller, which can drive the formation of a given reference signal. In the end, the effectiveness of the presented strategy is referred to a simulation example.

Description: Testing Fusarium resistance to ear rots in maize requires a well-supported methodology and tests for toxin responses. In this study, commercial hybrids were tested for resistance to Fusarium graminearum, Fusarium culmorum, and Fusarium verticillioides (kernel and silk channel), as well as their toxin response. One third of the hybrids tested showed a similar resistance or susceptibility to the three pathogens and their toxin response, but there is no proof for their genetic background being the same or different. The performance of the remaining hybrids was highly variable and supports the idea of different genetic regulation. The mean ear rot severity of the kernel resistance was doubled compared with the silk channel resistance data. The ear rot and toxin tests displayed significant positive correlations, verifying the decisive role of resistance in toxin regulation. Several hybrids, termed toxigenic hybrids, showed significant extra toxin production, indicating an additional food safety risk. The toothpick method gave more reliable results and a better differentiation of genotypes. The resistance to different Fusarium spp. in a specific growing region should be analyzed separately in independent resistance tests. Through this, the food safety risks could be better identified. Susceptible hybrids should not be used for commercial production.

Description: This study is focused on a barian titanian phlogopite found in an alkaline ultramafic dyke transecting Mesozoic limestones of the Gargano Promontory (Apulia, Italy). The rock containing the barian titanian phlogopite, an olivine-clinopyroxene-rich lamprophyre with nepheline and free of feldspars, has been classified as monchiquite. The present study combines chemical analyses, single crystal X-ray diffraction and Raman spectroscopy. Chemical variations suggest that the entry of Ba into the phlogopite structure can be explained by the exchange Ba + Al = K + Si. The crystal structure refinement indicates that the Ti uptake is consistent with the Ti–oxy exchange mechanism. The structural parameters associated with the oxy substitution mechanism are extremely enhanced and rarely reported in natural phlogopite: (a) displacement of M2 cation toward the O4 site (~0.7); (b) M2 octahedron bond-length distortion (~2.5); (c) very short c cell parameter (~10.14 Å). Raman analysis showed most prominent features in the 800–200 cm−1 region with the strongest peaks occurring at 773 and 735 cm−1. Only a weak, broad band was observed to occur in the OH-stretching region. As concerns the origin of the barian titanian phlogopite, the rock textural features clearly indicate that it crystallized from pockets of the interstitial melt. Here, Ba and Ti enrichment took place after major crystallization of olivine under fast-cooling conditions, close to the dyke margin.

Description: The harmonic closeness centrality measure associates, to each node of a graph, the average of the inverse of its distances from all the other nodes (by assuming that unreachable nodes are at infinite distance). This notion has been adapted to temporal graphs (that is, graphs in which edges can appear and disappear during time) and in this paper we address the question of finding the top-k nodes for this metric. Computing the temporal closeness for one node can be done in O(m) time, where m is the number of temporal edges. Therefore computing exactly the closeness for all nodes, in order to find the ones with top closeness, would require O(nm) time, where n is the number of nodes. This time complexity is intractable for large temporal graphs. Instead, we show how this measure can be efficiently approximated by using a “backward” temporal breadth-first search algorithm and a classical sampling technique. Our experimental results show that the approximation is excellent for nodes with high closeness, allowing us to detect them in practice in a fraction of the time needed for computing the exact closeness of all nodes. We validate our approach with an extensive set of experiments.

Description: The study’s objective was to evaluate the influence of thinning on the quality and regularity of yield of ‘Regina’ cherries grown on a dwarf Gisela 5 rootstock. The experiments were conducted in the years 2009–2012 in Western Poland. Trees were thinned using a chemical agent, ammonium thiosulphate (ATS), at doses of 20 g ATS L−1, 30 g ATS L−1 and 40 g ATS L−1, and by hand, and the results of chemical and hand thinning were compared with those obtained for unthinned trees. The course of weather conditions in winter and during flowering had a significant impact on yield. Chemical thinning is known to be an effective method to regulate fruiting of pome trees, but it can also be successful if applied to cherry trees, as reflected by the alternate bearing index, which was the lowest after applying ATS at a dose of 40 g. ATS treatment improved fruit quality in full crop years. Thinning resulted in, among other things, larger and darker fruit and higher content of total soluble solids and titratable acidity. Treatment with 40 g ATS L−1 significantly stimulated the vegetative growth of trees.

Description: The lithobiont community encrusting an early Pleistocene palaeocliff cropping out north of Augusta (SE Sicily, Italy) was investigated based on field observations and laboratory inspection of two rocky samples. Bryozoans, serpulids, brachiopods and bivalves encrusted part of the exposed surfaces that were bored mostly by clionaid sponges. Bryozoans, with at least 25 species detected on the rocky samples, are the most diversified skeletonized lithobionts also accounting for the highest number of colonies/specimens and highest coverage. Brachiopods, with the only species Novocrania anomala and a few but large cemented valves, cover wide surfaces. Serpulids, with two species identified on the sampled rocks and further two on the outcrop, were intermediate. A multiphase colonization is present, including a final epilithobiont community locally formed on eroded surfaces exposing a network of pervasive borings. The co-occurrence of very sciaphilic species having circalittoral to bathyal distributions suggests that the studied community thrived on a rocky substratum located near or at the shelf break, probably belonging to the shelf break (or RL) biocoenosis, also in agreement with observations on the fossil content of neighboring marly sediments. The observed relationships among colonizers largely represent mere superimpositions, and real interactions are not enough to state species competitiveness.

Description: A novel four-dimensional energy, economic, and environmental (3E) under energy reduction constraints chaotic system is proposed. The acquisition of environmental quality data is the key to this paper. During the course of the study, we used Bayesian estimation algorithm to calibrate the environmental quality. Based on the official data, the Levenberg–Marquardt backpropagation neural network method was optimized by genetic algorithm to effectively identify the parameters in the 3E system. The research results show that although increasing energy reduction inputs can improve environmental quality, the effect on energy intensity and overall stability of the system is not obvious. When polluting input in the ecological environment system affects its maximum capacity, the environmental system collapses (i.e., the ecological system can no longer purify the environment through the self-circulation process and will eventually die out). Therefore, it is necessary to correctly grasp the ecological environment protection and the relationship between economic developments and explore synergies to promote ecological priorities and green development new ideas.

Description: Computer programmers require various instructive information during coding and development. Such information is dispersed in different sources like language documentation, wikis, and forums. As an information exchange platform, programmers broadly utilize Stack Overflow, a Web-based Question Answering site. In this paper, we propose a recommender system which uses a supervised machine learning approach to investigate Stack Overflow posts to present instructive information for the programmers. This might be helpful for the programmers to solve programming problems that they confront with in their daily life. We analyzed posts related to two most popular programming languages—Python and PHP. We performed a few trials and found that the supervised approach could effectively manifold valuable information from our corpus. We validated the performance of our system from human perception which showed an accuracy of 71%. We also presented an interactive interface for the users that satisfied the users’ query with the matching sentences with most instructive information.

Description: Since 2006, an increasing number of French vineyards have chosen to convert to organic farming. One major change in vineyard practices includes replacing chemical pesticides with copper and sulfur-based products in line with Council Regulation (EC) No. 834/2007. This change can make overall management and pest and disease control more difficult and potentially lead to yield losses. From 2013 to 2016, a network of 48 vineyard plots, in southern France, under conventional management and in conversion to organic farming were monitored throughout the three-year conversion phase to investigate the grapevine phytosanitary management of four major pests and diseases and variations in control efficiency. The severity of downy and powdery mildew, grape berry moths, and Botrytis bunch rot were assessed and linked to the protection strategy. The findings showed that pests and diseases were controlled in the third year of conversion at similar efficiency levels as in conventional farming. However, the first two years of conversion were a transitional and less successful period during which higher incidences of cryptogamic diseases were observed. This demonstrates a need for winegrowers to receive more in-depth technical advice and support, especially on pest and disease control, during this critical transition period.

Description: The sugarcane (Saccharum spp. L.) mechanical harvesting system leaves a large amount of straw mulch on the soil surface. The straw mulch may affect soil conditions, root regrowth, and sugarcane yield. Thus, this study assessed the response of sugarcane root system growth and stalk yield to different rates of straw removal. An experiment was conducted in a Rhodic Kandiudox with sand clay loam texture to test the impact of four rates of straw removal: no removal (18.9 Mg ha−1 of dry mass); moderate removal (8.7 Mg ha−1); high removal (4.2 Mg ha−1) and total removal on sugarcane root system and stalk yield. Higher concentrations of roots (60%) were found in the first 40 cm of soil. Moderate straw removal resulted in higher root mass (3.6 Mg ha−1) and stalk production (23 Mg ha−1 of dry mass). However, no straw removal reduced root mass by 20% (105 Mg ha−1). Through regression analysis, it was estimated that retaining between 8.5 and 13 Mg ha−1 of straw resulted in the highest root mass and stalk yield. Managing straw removal to retain a moderate amount enables producers to sustain suitable soil conditions for sugarcane root growth and stalk production while providing straw for industrial use.