ALBERT

Description: Carbonate reservoirs are highly heterogeneous. During waterflooding stage, the channeling phenomenon of displacing fluid in high-permeability layers easily leads to early water breakthrough and high water-cut with low recovery rate. To quantitatively characterize the inter-well connectivity parameters (including conductivity and connected volume), we developed an inter-well connectivity model based on the principle of inter-well connectivity and the geological data and development performance of carbonate reservoirs. Thus, the planar water injection allocation factors and water injection utilization rate of different layers can be obtained. In addition, when the proposed model is integrated with automatic history matching method and production optimization algorithm, the real-time oil and water production can be optimized and predicted. Field application demonstrates that adjusting injection parameters based on the model outputs results in a 1.5% increase in annual oil production, which offers significant guidance for the efficient development of similar oil reservoirs. In this study, the connectivity method was applied to multi-layer real reservoirs for the first time, and the injection and production volume of injection-production wells were repeatedly updated based on multiple iterations of water injection efficiency. The correctness of the method was verified by conceptual calculations and then applied to real reservoirs. So that the oil field can increase production in a short time, and has good application value.

Description: This paper analyzes the small cosmopolitan and stability of the industrial coupling symbiotic network of eco-industrial parks of oil and gas resource-based cities. Taking Daqing A Ecological Industrial Park as an example, we constructed the characteristic index system and calculated the topological parameters such as the agglomeration coefficient and the average shortest path length of the industrial coupling symbiotic network. Based on the complex network theory we analyzed the characteristics of the scaled world, constructed the adjacency matrix of material and information transfers between enterprises, drew the network topology diagram. We simulated the system analysis and analyzed the stability of the industrial coupling symbiotic network of the eco-industrial park using the network efficiency and node load and maximum connected subgraph. The analysis results are as follows: the small world degree δ of Daqing A Eco-industrial Park is 0.891, which indicates that the industrial coupled symbiotic network has strong small world characteristics; the average path is 1.268, and the agglomeration coefficient is 0.631. The probability of edge connection between two nodes in a symbiotic network is 63.1%, which has a relatively high degree of aggregation, indicating that energy and material exchanges are frequent among all enterprises in the network, the degree of network aggregation is high, and the dependence between nodes is high; when the tolerance parameter is 0 to 0.3, the network efficiency and the maximum connected subgraphs show a sharp change trend, indicating that the topology of the industrial coupling symbiotic network of the eco-industrial park changes drastically when the network is subjected to deliberate attacks. It is easy to cause the breakage of material flow and energy flow in the industrial park, which leads to the decline of the stability of the industrial coupling symbiotic network of the eco-industrial park.

Description: The study was conducted in 2 urbanized areas of the Baikal region of Russia. These are the cities of Shelekhov and Tayshet with their suburbs. Aluminum production has been carried out in Shelekhov for over 60 years and in Tayshet for 5 years. The purpose of the study was to determine the pollution of urban soils with toxic elements—Al, F, Be, Li, as well as Cr, Ni, Pb, and so on under the influence of industrial enterprises (aluminum and cable plants, thermal power plants). Also, the purpose of the research was to determine the effect of increased fluorite (F) in the environment on children’s health. Pure aluminum is used much less frequently than in alloys. The addition of various elements (Be, B, Li, Fe, Si, Mg, Mn, Zr, Ag, Pb, Cu, Ni, and others) increases the hardness, density, thermal conductivity, and other properties of the alloys. The area of high F content in urban soil is 15 times higher than the regional context. The maximum content of Na, Be, and Al is 2 to 4 times higher than the regional background. An increased Li content is marked only near aluminum smelters. The F content in urine samples from children living in areas with long-term pollution exposure (Shelekhov) is 1.5 to 2 times higher than in the group of children with a short exposure period (Tayshet).

Description: Multi-frequency signals have been accessible for most Global Navigation Satellite Systems . Existing studies have verified that using multi-frequency extra-wide-lane and wide-lane observations can realize decimeter, sub-decimeter and even centimeter rapid positioning. In this paper, a tightly combined wide-lane real-time kinematic positioning method using triple-frequency GPS and BDS is proposed. The differential inter-system bias is taken into consideration so that an inter-system differencing model is formed. Due to the influence of different frequencies between GPS and BDS, the double-difference wide-lane ambiguity between GPS and BDS reference satellites and the single-difference ambiguity of the BDS reference satellite are estimated jointly with the wide-lane differential inter-system bias. Thus, a full-rank model can be obtained without any external calibration. Using the stability of wide-lane differential inter-system bias in the estimation from epoch to epoch, redundant observations can be introduced, therefore the strength of the positioning model can be enhanced. Positioning performance under simulated obstructed environments is evaluated. The results show that the inter-system model can effectively improve the positioning compared with the conventional intra-system model for the severely obstructed situations.

Description: This article focuses on how to effectively make full use of the storage resources in vehicular cloud. A trust mechanism called DI-Trust (Trust Model Based on Dynamic Incentive Mechanism) is proposed to schedule vehicular cloud storage resource. The discussion is under the scenario of the parking lot where vehicle nodes are in static state. The model can reasonably arrange the suitable scheduling algorithm according to the attribute characteristics of different kind of service requirements. The trust value of a vehicle is updated according to the model to fully utilize the vehicle idle storage resources. The simulation experiment results show that the model can work effectively. It can objectively evaluate trust values of vehicle nodes, and construct the effective resource schedule of the vehicular cloud storage resource to meet needs from users.

Description: As an important type of unconventional hydrocarbon, tight sandstone oil has great present and future resource potential. Reservoir quality evaluation is the basis of tight sandstone oil development. A comprehensive evaluation approach based on the gray correlation algorithm is established to effectively assess tight sandstone reservoir quality. Seven tight sandstone samples from the Chang 6 reservoir in the W area of the AS oilfield in the Ordos Basin are employed. First, the petrological and physical characteristics of the study area reservoir are briefly discussed through thin section observations, electron microscopy analysis, core physical property tests, and whole-rock and clay mineral content experiments. Second, the pore type, throat type and pore and throat combination characteristics are described from casting thin sections and scanning electron microscopy. Third, high-pressure mercury injection and nitrogen adsorption experiments are optimized to evaluate the characteristic parameters of pore throat distribution, micro- and nanopore throat frequency, permeability contribution and volume continuous distribution characteristics to quantitatively characterize the reservoir micro- and nanopores and throats. Then, the effective pore throat frequency specific gravity parameter of movable oil and the irreducible oil pore throat volume specific gravity parameter are introduced and combined with the reservoir physical properties, multipoint Brunauer-Emmett-Teller (BET) specific surface area, displacement pressure, maximum mercury saturation and mercury withdrawal efficiency parameters as the basic parameters for evaluation of tight sandstone reservoir quality. Finally, the weight coefficient of each parameter is calculated by the gray correlation method, and a reservoir comprehensive evaluation indicator (RCEI) is designed. The results show that the study area is dominated by types II and III tight sandstone reservoirs. In addition, the research method in this paper can be further extended to the evaluation of shale gas and other unconventional reservoirs after appropriate modification.

Description: Fog computing is viewed as an extended technique of cloud computing. In Internet of things–based collaborative fog computing systems, a fog node aggregating lots of data from Internet of things devices has to transmit the information to distributed cloud servers that will collaboratively verify it based on some predefined auditing policy. However, compromised fog nodes controlled by an adversary might inject bogus data to cheat or confuse remote servers. It also causes the waste of communication and computation resources. To further control the lifetime of signing capability for fog nodes, an appropriate mechanism is crucial. In this article, the author proposes a time-constrained strong multi-designated verifier signature scheme to meet the above requirement. In particular, a conventional non-delegatable strong multi-designated verifier signature scheme with low computation is first given. Based on its constructions, we show how to transform it into a time-constrained variant. The unforgeability of the proposed schemes is formally proved based on the famous elliptic curve discrete logarithm assumption. The security requirement of strong signer ambiguity for our substantial constructions is also analyzed by utilizing the intractable assumption of decisional Diffie–Hellman. Moreover, some comparisons in terms of the signature size and computational costs for involved entities among related mechanisms are made.

Description: Coalbed gas (CBG) has been widely used as an important energy source. However, its utilization and allocation system is imperfect in mining areas. During the utilization process, a large amount of CBG is discharged into the air, causing environmental pollution. In this study, we proposed a “full spectrum-domain-time” CBG utilization model. In this model, by combining high methane concentration gas power generation, low methane concentration gas purification, and ultra-low methane concentration gas thermal storage and oxidation utilization, we were able to utilize CBG with full-spectrum of methane concentrations. In addition, by establishing CBG transportation and storage system in mining area, we were able to realize CBG supply in the entire network domain. Furthermore, based on the time series prediction algorithm, the CBG demand of different mining areas is predicted and regulatorily met by real time allocation. Through these three steps, an efficient “full spectrum-domain-time” CBG utilization system was formed and practically applied in Yangquan mining area. The application results showed that under the comprehensive control of “full spectrum-domain-time” CBG utilization model, CBG with methane concentration ≥0.2% could be used in the mining area and its utilization rate increased year by year, reaching the highest of 77.15%. Overall, our study provided a reference for the efficient CBG utilization in the mining area.

Description: Low-pressure N2 adsorption (LPNA) could provide quantitative data for characterizing the pores in gas shale. However, the inconsistencies of outgas temperature have caused significant deviations in LPNA experiments. To explore the effects of outgas temperature on pore characteristics, two shale samples of Lower Cambrian Niutitang formation from Northern Guizhou, China, were collected for LPNA experiments and thermogravimetry-fourier transform infrared (TG-FTIR) spectroscopy. The samples were outgassed at six temperatures: 80°C, 100°C, 150°C, 200°C, 250°C, 300°C. Larger adsorbed volumes were presented in the isotherms at higher outgas temperatures. Similar regularity is obtained from the relationship between specific surface area, micropore volume and outgas temperature. Comprehensive analysis of TG-FTIR and LPNA at different outgas temperature indicated that at lower outgas temperatures (from 80°C to 100°C), the free water was unlikely to be removed completely, and resulted in large amounts of micropores couldn’t be accessed. An excessive outgas temperature might expulse liquid hydrocarbons or decompose organic matter (from 200°C to 300°C), and could lead to the generation of micropores. When the sample were outgassed at 150°C, TG-FTIR analysis indicated that the sample composition unchanged and a better removal of free water happened. Therefore, 150°C should be a suitable outgas temperature for shale in LPNA experiments. The findings in this research not only provide reliable evidence for the selection of outgas procedure in LPNA for shale, but clarify the important effects of free water and volatile materials on pore accessibility in shale.

Description: Time series have broad usage in the wireless Internet of Things. This article proposes a nonlinear time series prediction algorithm based on the Small-World Scale-Free Network after the AIC-Optimized Subtractive Clustering Algorithm (AIC-DSCA-SSNET, AD-SSNET) to predict the nonlinear and unstable time series, which improves the prediction accuracy. The AD-SSNET is introduced as a reservoir based on the echo state network to improve the predictive capability of nonlinear time series, and combined with artificial intelligence method to construct the prediction model training samples. First, the optimal clustering scheme of randomly distributed neurons in the network is adaptively obtained by the AIC-DSCA, then the AD-SSNET is constructed according to the intra-cluster priority connection algorithm. Finally, the reservoir synaptic matrix is calculated according to the synaptic information. Experimental results show that the proposed nonlinear time series prediction algorithm extends the feasible range of spectral radii of the reservoir, improves the prediction accuracy of nonlinear time series, and has great significance to time series analysis in the era of wireless Internet of Things.

Description: This study investigates the causal relationship between renewable energy sources and clean environmental economic growth among South Asian economies. This study comprises the panel data sets for eight (8) South Asian countries, and data start from 2003 to 2017. This study implies a Hausman test to identify which particular tests are more suitable and selected a fixed effect test and granger causality test for effective analysis perspective. Moreover, this study further relies on the panel vector error correction model (PVECM) test to suggest for long-run relationship existence among variables. Furthermore, the evaluation of the panel and the dynamic ordinary least squares regression shows that the production of renewable energy has compelled an effect on economic growth. While other sources of energy for instance, hydropower, geothermal, wind, and solar, have valuable and considerable influence on the economic growth of South Asian economies. The results reveal with these remarks the existence of positive associations among productions of renewable energies, energy dependence, and gross domestic product per capita. The obtained results reveal that renewable energy sources show a momentous effect on the economic growth of South Asian economies.

Description: In view of the uncertainty and volatility of wind power generation and the inability to provide stable and continuous power, this paper proposes a hydrogen storage wind-gas complementary power generation system, using Matlab/Simulink to simulate and model wind generators and gas turbines. Considering the economy and power supply reliability of the wind-gas complementary power generation system, and taking the economic and environmental cost of the system as the objective function, the capacity optimization model of the wind-gas complementary power generation system is established. The brain storming algorithm (BSO) is used to solve the optimization problem, and the BSO algorithm is used to optimize the BP neural network, which improves the accuracy of the BP neural network for load forecasting. Finally, a simulation is carried out with load data in a certain area, and the simulation verification verifies that BSO-BP can improve the accuracy of load forecasting and reduce the error of load forecasting. Multi-objective optimization of system economic cost and environmental cost through BSO algorithm can make the system cost reach the most reasonable level. Through the analysis of the calculation examples, it is verified that gas-fired power generation can effectively alleviate the volatility of wind power generation, showing the role and advantages of energy complementary power generation. Therefore, the wind-gas complementary system can effectively increase energy utilization and reduce wind curtailment.

Description: This article identifies the potential environmental effects large-scale indoor farming may have on air, water, and soil. We begin with an overview of what indoor farming is with a focus on greenhouses and indoor vertical farms (eg, plant factories). Next, the differences between these 2 primary methods of indoor farming are presented based on their structural requirements, methods of growing, media, nutrient sources, lighting requirements, facility capacity, and methods of climate control. We also highlight the benefits and challenges facing indoor farming. In the next section, an overview of research and the knowledge domain of indoor and vertical farming is provided. Various authors and topics for research are highlighted. In the next section, the transformative environmental effects that indoor farming may have on air, soil, and water are discussed. This article closes with suggestions for additional research on indoor farming and its influence on the environment.

Description: Vehicular Ad hoc NETwork is a promising technology providing important facilities for modern transportation systems. It has garnered much interest from researchers studying the mitigation of attacks including distributed denial of service attacks. Machine learning techniques, which mainly rely on the quality of the datasets used, play a role in detecting many attacks with a high level of accuracy. We conducted a comprehensive literature review and found many limitations on the datasets available for distributed denial of service attacks on Vehicular Ad hoc NETwork including the following: unavailability of online versions, an absence of distributed denial of service traffic, unrepresentative of Vehicular Ad hoc NETwork, and no information regarding the network configurations. Therefore, in this article, we proposed a novel simulation technique to generate a valid dataset called Vehicular Ad hoc NETwork distributed denial of service dataset, which is dedicated to Vehicular Ad hoc NETworks. Vehicular Ad hoc NETwork distributed denial of service dataset holds information on distributed denial of service attack traffic considering Vehicular Ad hoc NETwork architecture, traffic density, attack intensity, and nodes mobility. Well-known simulation tools such as SUMO, OMNeT++, Veins, and INET were used to ensure that all the properties of Vehicular Ad hoc NETwork have been captured. We then compared Vehicular Ad hoc NETwork distributed denial of service dataset with several studies to prove its novelty and evaluated the dataset using several machine learning models. We confirmed that studied models using this dataset achieved high accuracy above 99.5% except support-vector machine that achieved 97.3%.

Description: The role of pyrogenic carbon (PyC) in the global carbon cycle is still incompletely characterized. Much work has been done to characterize PyC on landforms and in soils where it originates or in “terminal” reservoirs such as marine sediments. Less is known about intermediate reservoirs such as streams and rivers, and few studies have characterized hillslope and in-stream erosion control structures (ECS) designed to capture soils and sediments destabilized by wildfire. In this preliminary study, organic carbon (OC), total nitrogen (N), and stable isotope parameters, δ13C and δ15N, were compared to assess opportunities for carbon and nitrogen sequestration in postwildfire sediments (fluvents) deposited upgradient of ECS in ephemeral- and intermittent-stream channels. The variability of OC, N, δ13C, and δ15N were analyzed in conjunction with fire history, age of captured sediments, topographic position, and land cover. Comparison of samples in 2 watersheds indicates higher OC and N in ECS with more recently captured sediments located downstream of areas with higher burn severity. This is likely a consequence of (1) higher burn severity causing greater runoff, erosion, and transport of OC (organic matter) to ECS and (2) greater cumulative loss of OC and N in older sediments stored behind older ECS. In addition, C/N, δ13C, and δ15N results suggest that organic matter in sediments stored at older ECS are enriched in microbially processed biomass relative to those at newer ECS. We conservatively estimated the potential mean annual capture of OC by ECS, using values from the watershed with lower levels of OC, to be 3 to 4 metric tons, with a total potential storage of 293 to 368 metric tons in a watershed of 7.7 km2 and total area of 2000 ECS estimated at 2.6 ha (203-255 metric tons/ha). We extrapolated the OC results to the regional level (southwest USA) to estimate the potential for carbon sequestration using these practices. We estimated a potential of 0.01 Pg, which is significant in terms of ecosystem services and regional efforts to promote carbon storage.

Description: Aiming at the problems existing in existing steganalysis algorithms, this article proposes Motion Vector Coding Cost Change video steganalysis features based on Improved Motion Vector Reversion-Based features and Subtractive Probability of Coding Cost Optimal Matching features based on Subtractive Probability of Optimal Matching features from the perspective of the change of coding cost. Motion Vector Coding Cost Change features can be well consistent with the coding cost before recoding by analyzing the sub-pixel coding cost of recoding. By counting the sub-pixel coding costs of motion vectors before and after video recoding, the Sum of Absolute Difference values of motion vectors instead of predicted residuals are applied to steganalysis and detection, and the steganographic algorithm based on motion vectors is effectively detected. Experiments show that Motion Vector Coding Cost Change features have higher detection accuracy than Add-or-Subtract-One, Improved Motion Vector Reversion-Based, and other typical features in various steganography methods, and Subtractive Probability of Coding Cost Optimal Matching features have higher detection effect and better robustness than Subtractive Probability of Optimal Matching features.

Description: In this study, an interval extension method of a bi-iterative is proposed to determine a moving source. This method is developed by utilising the time difference of arrival and frequency difference of arrival measurements of a signals received from several receivers. Unlike the standard Gaussian noise model, the time difference of arrival - frequency difference of arrival measurements are obtained by interval enclosing, which avoids convergence and initialisation problems in the conventional Taylor-series method. Using the bi-iterative strategy, the algorithm can alternately calculate the position and velocity of the moving source in interval vector form. Simulation results indicate that the proposed scheme significantly outperforms other methods, and approaches the Cramer-Rao lower bound at a sufficiently high noise level before the threshold effect occurs. Moreover, the interval widths of the results provide the confidence degree of the estimate.

Description: Aiming at the shortcomings of the research on individual identification technology of emitters, which is primarily based on theoretical simulation and lack of verification equipment to conduct external field measurements, an emitter individual identification system based on Automatic Dependent Surveillance–Broadcast is designed. On one hand, the system completes the individual feature extraction of the signal preamble. On the other hand, it realizes decoding of the transmitter’s individual identity information and generates an individual recognition training data set, on which we can train the recognition network to achieve individual signal recognition. For the collected signals, six parameters were extracted as individual features. To reduce the feature dimensions, a Bessel curve fitting method is used for four of the features. The spatial distribution of the Bezier curve control points after fitting is taken as an individual feature. The processed features are classified with multiple classifiers, and the classification results are fused using the improved Dempster–Shafer evidence theory. Field measurements show that the average individual recognition accuracy of the system reaches 88.3%, which essentially meets the requirements.

Description: Suppressing the trajectory data to be released can effectively reduce the risk of user privacy leakage. However, the global suppression of the data set to meet the traditional privacy model method reduces the availability of trajectory data. Therefore, we propose a trajectory data differential privacy protection algorithm based on local suppression Trajectory privacy protection based on local suppression (TPLS) to provide the user with the ability and flexibility of protecting data through local suppression. The main contributions of this article include as follows: (1) introducing privacy protection method in trajectory data release, (2) performing effective local suppression judgment on the points in the minimum violation sequence of the trajectory data set, and (3) proposing a differential privacy protection algorithm based on local suppression. In the algorithm, we achieve the purpose Maximal frequent sequence (MFS) sequence loss rate in the trajectory data set by effective local inhibition judgment and updating the minimum violation sequence set, and then establish a classification tree and add noise to the leaf nodes to improve the security of the data to be published. Simulation results show that the proposed algorithm is effective, which can reduce the data loss rate and improve data availability while reducing the risk of user privacy leakage.

Description: Mobile edge computing is a new computing paradigm, which pushes cloud computing capabilities away from the centralized cloud to the network edge to satisfy the increasing amounts of low-latency tasks. However, challenges such as service interruption caused by user mobility occur. In order to address this problem, in this article, we first propose a multiple service placement algorithm, which initializes the placement of each service according to the user’s initial location and their service requests. Furthermore, we build a network model and propose a based on Lyapunov optimization method with long-term cost constraints. Considering the importance of user mobility, we use the Kalman filter to correct the user’s location to improve the success rate of communication between the device and the server. Compared with the traditional scheme, extensive simulation results show that the dynamic service migration strategy can effectively improve the service efficiency of mobile edge computing in the user’s mobile scene, reduce the delay of requesting terminal nodes, and reduce the service interruption caused by frequent user movement.

Description: The healthcare budget is increasing day-by-day as the population of the world increases. The same is the case regarding the workload of health care workers, that is, doctors and other practitioners. Under such a scenario where workload and cost are increasing drastically, there is a dire need of integrating recent technological enhancements with the said domain. Since the last decade, a lot of work is in the process considering the said integration bringing revolutionary changes. For remote monitoring, existing systems use different types of Internet of things devices that measure different health parameters. One of the major problems in such a system is to find an optimum routing approach that can resolve energy and thermal issues that are taking the limelight in the research arena. In this article, a dynamic routing technique is proposed which is keen to connect multiple in vivo/ex vivo Internet of things devices and a sink (focusing thermal and energy problem) and then forwarding data from sink to remote location for monitoring. Performance parameters are kept energy efficiency and thermal awareness and analytical results show that the proposed protocol supersedes existing approaches in said metrics.

Description: In order to reduce the restroom envelope energy consumption, one optimization method on basis of analyzing the influence of heat transfer coefficient on the performance of a prefabricated restroom envelope in a hot summer and cold winter zone was proposed. An energy-consuming model of prefabricated restroom in Nanjing is initially built based on Designer's Simulation Toolkit software. Subsequently, the effect of external walls, rooftops, external windows with various thermal characteristics on the building envelope is analyzed respectively. Simultaneously, a method that only changes the heat transfer coefficient of the prefabricated restroom envelope while keeping other parameters unchanged is adopted. Results show that, for a prefabricated restroom, the optimal range of heat transfer coefficient of the external wall, rooftop, and external window in hot summer and cold winter zone is 0.199∼0.22, 0.16∼0.19, and 3.0∼3.1 W/(m2·K), respectively. When the window-to-wall ratio is less than 0.2, the priority of the wall heat transfer coefficient on building energy consumption is higher than that of the rooftop heat transfer coefficient, simultaneously, the rooftop heat transfer coefficient has priority higher than window heat transfer coefficient. Thus, it is of great significance to optimize the design of the prefabricated restroom envelope in a hot summer and cold winter zone, which provides relative reference for thermal performance improvement of prefabricated restrooms.

Description: In order to ensure the strong real-time information sharing of Aerial Ad hoc Network, a low-delay information sharing algorithm for multiple-radio-per-platform networking is proposed based on the directional transmission capability of phased-array antenna. The algorithm introduces virtual nodes and virtual links in the process of topology generation first. By extracting topology information and choosing link grouping, it can effectively reduce redundant transmission and transmission latency of information sharing. Then, it is verified through simulation that the algorithm can reduce the latency by up to 49.8% and eliminate transmission redundancy. In addition, a direction selection algorithm is proposed for the variation of antenna beam direction. Simulation results show that the algorithm can further reduce the latency of information sharing and ensure the real time of information sharing, thus further improving the network performance.

Description: For wireless sensor network, the localization algorithm based on Voronoi diagram has been applied. However, the location accuracy node position in wireless sensor network needs to be optimized by the analysis of the literature, a node location algorithm based on Voronoi diagram and support vector machine is proposed in this article. The basic idea of the algorithm is to first divide the region into several parts using Voronoi diagram and anchor node in the localization region. The range of the initial position of the target node is obtained by locating the target node in each region and then the support vector machine is used to optimize the position of the target node accurately. The localization performance of the localization algorithm is analyzed by simulation and real-world experiments. The experimental results show that the localization algorithm proposed in this article is better than the optimal region selection strategy based on Voronoi diagram-based localization scheme and Weighted Voronoi diagram-based localization scheme localization algorithms in terms of localization accuracy. Therefore, the performance of the localization algorithm proposed in this article is verified.

Description: The objective of this study was to evaluate the treatment efficiency of a coupled stillage anaerobic digestion, which was performed in scoria-packed continuous reactors and following aerobic degradation. The optimum organic loading rate was determined for the continuous anaerobic digestion of a molasses ethanol distillery stillage with and without wet air feed pretreatment. The pretreatment of the molasses ethanol distillery stillage brought a significantly higher chemical oxygen demand removal in anaerobic digestion with an increased loading rate of 2000 mg/L d when compared with the raw stillage. The results also showed a complete removal of the biological oxygen demand following the coupling of anaerobic digestion with aerobic degradation. During the later stillage aerobic treatment, 68% of the chemical oxygen demand was removed within 8 hours of retention time. Despite the color, the removal of organics in stillage due to integrating wet air pretreatment, continuous anaerobic digestion, and aerobic degradation was successful. The pretreatment and hybrid technique also appears as a promising technique toward the sustainable management of stillage, thereby meeting discharge limit set for the ethanol industry by regulators.

Description: Clustering technology is one of the crucial technologies to prolong the lifetime in wireless sensor networks. However, most cluster schemes choose cluster head randomly to send data without considering load balancing and security. In addition, some cluster heads in the highly active area may be overloaded, while others in the low active area may be overloaded, which may easily lead to extreme imbalance in task allocation. Our research on relevant literature shows that the existing authentication schemes do not fully consider the load balancing of cluster heads, while the load balancing schemes ignore the security authentication of cluster heads. Therefore, this article effectively combines load balancing and security verification, and proposes a lightweight load balancing and verification scheme (secure load and energy balancing) based on clustered wireless sensor networks. Secure load and energy balancing implements cluster head’s authentication and confidentiality and integrity of all messages in load balancing. This scheme not only effectively maintains the energy balance of the whole network but also successfully improves the security overhead, thus prolonging the network lifetime. The simulation results show that compared with other similar schemes, this scheme has higher packet forwarding rate, longer network life, and lower overhead. This further proves that the scheme is energy-saving, safe, dynamic, stable, and sustainable.

Description: Soil erosion is 1 of the most important environmental problems that pose serious challenges to food security and the future development prospects of Ethiopia. Climate change influences soil erosion and is critical for the planning and management of soil and water resources. This study aimed to assess the current and future climate change impact on soil loss rate for the near future (2011-2040), middle future (2041-2070), and far future (2071-2100) periods relative to the reference period (1989-2018) in the Agewmariam watershed, Northern Ethiopia. The 20 models of Coupled Model Intercomparison Project phase 5 global climate models (GCMs) under Representative Concentration Pathway (RCP) 4.5 (intermediate scenario) and 8.5 (high emissions scenario) scenarios were used for climate projection. The statistical bias correction method was used to downscale GCMs. Universal Soil Loss Equation integrated with geographic information system was used to estimate soil loss. The results showed that the current average annual soil loss rate and the annual total soil loss on the study area were found to be 25 t ha−1 year−1 and 51 403.13 tons, respectively. The soil loss has increased by 3.0%, 4.7%, and 5.2% under RCP 4.5 scenarios and 6.0%, 9.52%, and 14.32% under RCP 8.5 scenarios in the 2020s, 2050s, and 2080s, respectively, from the current soil loss rate. Thus, the soil loss rate is expected to increase on all future periods (the 2020s, 2050s, and 2080s) under both scenarios (RCP 4.5 and RCP 8.5) due to the higher erosive power of the future intense rainfall. Thus, climate change will exacerbate the existing soil erosion problem and would need for vigorous new conservation policies and investments to mitigate the negative impacts of climate change on soil loss.

Description: This review assessed the effects of environmental labels on consumers’ demand for more sustainable food products. Six electronic databases were searched for experimental studies of ecolabels and food choices. We followed standard Cochrane methods and results were synthesized using vote counting. Fifty-six studies ( N = 42,768 participants, 76 interventions) were included. Outcomes comprised selection ( n = 14), purchase ( n = 40) and consumption ( n = 2). The ecolabel was presented as text ( n = 36), logo ( n = 13) or combination ( n = 27). Message types included: organic ( n = 25), environmentally sustainable ( n = 27), greenhouse gas emissions ( n = 17), and assorted “other” message types ( n = 7). Ecolabels were tested in actual ( n = 15) and hypothetical ( n = 41) environments. Thirty-nine studies received an unclear or high RoB rating. Sixty comparisons favored the intervention and 16 favored control. Ecolabeling with a variety of messages and formats was associated with the selection and purchase of more sustainable food products.

Description: Climate change will ultimately result in higher surface temperature and more variable precipitation, negatively affecting agricultural productivity. To sustain the agricultural production in the face of climate change, adaptive agricultural management or best management practices (BMPs) are needed. The currently practiced BMPs include crop rotation, early planting, conservation tillage, cover crops, effective fertilizer use, and so on. This research investigated the agricultural production of BMPs in response to climate change for a Hydrologic Unit Code12 sub-watershed of Choctawhatchee Watershed in Alabama, USA. The dominating soil type of this region was sandy loam and loamy sand soil. Agricultural Production Systems sIMulator and Cropping Systems Simulation Model were used to estimate the agricultural production. Representative Concentration Pathway (RCP) 4.5 and RCP8.5 that projected a temperature increase of 2.3℃ and 4.7℃ were used as climate scenarios. The research demonstrated that crop rotation had positive response to climate change. With peanuts in the rotation, a production increase of 105% was observed for cotton. There was no consistent impact on crop yields by early planting. With selected peanut-cotton rotations, 50% reduced nitrogen fertilizer use was observed to achieve comparable crop yields. In response to climate change, crop rotation with legume incorporation is thus suggested, which increased crop production and reduced fertilizer use.

Description: Basin-scale simulation is fundamental to understand the hydrological cycle, and in identifying information essential for water management. Accordingly, the Soil and Water Assessment Tool (SWAT) model is applied to simulate runoff in the semi-arid Tambo River Basin in southern Peru, where economic activities are driven by the availability of water. The SWAT model was calibrated using the Sequential Uncertainty Fitting Ver-2 (SUFI-2) algorithm and two objective functions namely the Nash-Sutcliffe simulation efficiency (NSE), and coefficient of determination ( R2) for the period 1994 to 2001 which includes an initial warm-up period of 3 years; it was then validated for 2002 to 2016 using daily river discharge values. The best results were obtained using the objective function R2; a comparison of results of the daily and monthly performance evaluation between the calibration period and validation period showed close correspondence in the values for NSE and R2, and those for percent bias (PBIAS) and ratio of standard deviation of the observation to the root mean square error (RSR). The results thus show that the SWAT model can effectively predict runoff within the Tambo River basin. The model can also serve as a guideline for hydrology modellers, acting as a reliable tool.

Description: Ultrasonic computerized tomography is a promising technique for damage detection by enabling ultrasonic waves via multiple measurement paths leading to accurate localization of structural damage. Unlike traditional ultrasonic computerized tomography that requires numerous measurements and costly computation, a compressive sampling advancing both the measuring phase and the imaging phase is proposed in this study to achieve accurate identification with no low-speed traditional ultrasonic computerized tomography technique measurements or costly computation in real-world applications. The proposed rapid ultrasonic computerized tomography approach advances both the measuring phase and the imaging phase. In the measuring phase, far few ultrasonic measurement paths are randomly selected to capture the characteristics of the ultrasonic waves carrying the underlying damaged information. And in the imaging phase, ℓ1-norm minimization optimization algorithm is used to reconstruct the internal damage, rendering the sparest solution related to the physical damages. The functionality of the proposed approach is validated by both numerical simulation and experimental testing. The results indicate that the improved ultrasonic computerized tomography technique in compressive sampling framework has a great potential for rapid damage detection, which is a game-changing technique for accurate and cost-efficient damage detection in real-world applications.

Description: Many studies in air, soil, and water research involve observations and sampling of a specific location. Knowing where studies have been previously undertaken can be a valuable addition to future research, including understanding the geographical context of previously published literature and selecting future study sites. Here, we introduce Literature Mapper, a Python QGIS plugin that provides a method for creating a spatial bibliography manager as well as a specification for storing spatial data in a bibliography manager. Literature Mapper uses QGIS’ spatial capabilities to allow users to digitize and add location information to a Zotero library, a free and open-source bibliography manager on basemaps or other geographic data of the user’s choice. Literature Mapper enhances the citations in a user’s online Zotero database with geo-locations by storing spatial coordinates as part of traditional citation entries. Literature Mapper receives data from and sends data to the user’s online database via Zotero’s web API. Using Zotero as the backend data storage, Literature Mapper benefits from all of its features including shared citation Collections, public sharing, and an open web API usable by additional applications, such as web mapping libraries. To evaluate Literature Mapper’s ability to provide insights into the spatial distribution of published literature, we provide a case study using the tool to map the study sites described in academic publications related to the biogeomorphology of California’s coastal strand vegetation, a line of research in which air movement, soil, and water are all driving factors. The results of this exercise are presented in static and web map form. The source code for Literature Mapper is available in the corresponding author’s GitHub repository: https://github.com/MicheleTobias/LiteratureMapper

Description: This paper examines a broad spectrum of challenges plaguing electric power supply in Africa. The challenges have lingered very long that policymakers, energy companies, and government agencies have shown docility in tackling the problem headlong. The increasing human population and technological innovations are evidence that the more the problem lingers, the more it becomes insurmountable. In this paper, it was proposed the lingering challenges can be solved using the standalone system of power generation. The renewable energy option and its adaptability were highlighted to guide standalone users on the way forward. The growing population in Africa can be advantageous in generating biogas from human feaces. It was discovered that renewable energy devices are quite expensive; hence, the biogas option for cooking and powering gas generators seem to be sustainable as its technology can be modified to suit the users' financial base. Therefore, it is projected that if the human excretal biogas can be adopted, Africa will soon overcome its energy crisis through the doggedness of its standalone users.

Description: To better evaluate the spatial steering effect of directional perforation hydraulic fractures, evaluation indexes for the spatial steering effect are first proposed in this paper. Then, these indexes are used to quantitatively evaluate existing physical experimental results. Finally, with the help of RFPA2D-Flow software, the influence of perforation length and azimuth on the spatial steering process of hydraulic fracture are quantitatively analysed using four evaluation indexes. It is shown by the results that the spatial deflection trajectory, deflection distance, deflection angle and initiation pressure of hydraulic fractures can be used as quantitative evaluation indexes for the spatial steering effect of hydraulic fractures. The deflection paths of directional perforation hydraulic fractures are basically the same. They all gradually deflect to the maximum horizontal principal stress direction from the perforation hole and finally represent a double-wing bending fracture. The deflection distance, deflection angle and initiation pressure of hydraulic fractures increase gradually with increasing perforation azimuth, and the sensitivity of the deflection angle to the perforation azimuth of hydraulic fractures also increases. With increasing perforation length, the deflection distance of hydraulic fractures increases gradually. However, the deflection angle and initiation pressure decrease gradually, as does the sensitivity.

Description: Aiming at the key optimization problems of wireless sensor networks in complex industrial application environments, such as the optimum coverage and the reliability of the network, a novel topology optimization of coverage-oriented strategy for wireless sensor networks based on the wolf pack algorithm is proposed. Combining the characteristics of topology structure of wireless sensor networks and the optimization idea of the wolf pack algorithm redefines the group’s wandering and surprise behavior. A novel head wolf mutation strategy is proposed, which increases the neighborhood search range of the optimal solution, enhances the uniformity of wolf pack distribution and the ergodicity ability of the wolf pack search, and greatly improves the calculation speed and the accuracy of the wolf pack algorithm. With the same probability, the cluster heads are randomly selected periodically, and the overall energy consumption of wireless sensor networks is evenly distributed to the sensor node to realize the balanced distribution of the data of the member nodes in the cluster and complete the design of the topology optimization of wireless sensor networks. Through algorithm simulation and result analysis, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the wolf swarm algorithm shows its advantages in terms of the residual energy of the sensor node, the average transmission delay, the average packet delivery rate, and the coverage of the network. Among them, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the remaining energy of nodes has increased by 9.5% and 15.5% and the average coverage of the network has increased by 10.5% and 5.6%, respectively.

Description: In order to mine the coal seam under super-thick hard roof, improve the utilization rate of resources and prolong the remaining service life of the mine, a case study of the Gaozhuang Coal Mine in the Zaozhuang Mining Area has been performed in this paper. Based on the specific mining geological conditions of ultra-close coal seams (#3up and #3low coal seams), their joint systematic analysis has been performed, with the focus made in the following three aspects: (i) prevention of rock burst under super-thick hard roof, (ii) deformation control of surrounding rock of roadways in the lower coal seam, and (iii) fire prevention in the goaf of working face. Given the strong bursting tendency observed in upper coal seam and lower coal seam, the technology of preventing rock burst under super-thick hard roof was proposed, which involved setting of narrow section coal pillars to protect roadways and interleaving layout of working faces. The specific supporting scheme of surrounding rock of roadways in the #3low1101 working face was determined, and the grouting reinforcement method of local fractured zones through Marithan was further proposed, to ensure the deformation control of surrounding rock of roadways in lower coal seams. The proposed fire prevention technology envisaged goaf grouting and spraying to plug leaks, which reduced the hazard of spontaneous combustion of residual coals in mined ultra-close coal seams. The technical and economic improvements with a direct economic benefit of 5.55 million yuan were achieved by the application of the proposed comprehensive technical support. The research results obtained provide a theoretical guidance and technical support of safe mining strategies of close coal seams in other mining areas.

Description: This article describes the implementation of a multiple-input multiple-output acoustic communication link in shallow water conditions to enable a software-defined acoustic modem with a maximum transmission rate of 20 kbps in a 5-kHz bandwidth. The reliability improvement of a low-complexity Alamouti space–time block code is evaluated to improve the diversity in a high-rate transmission mode using single carrier modulation, as well as in a low-rate transmission mode relying on continuous-phase frequency-shift keying. Using measurements in realistic subsea conditions, the effect of the spatial channel correlation is demonstrated. It is found that for the space–time block code/continuous-phase frequency-shift keying, the spatial diversity is significantly degraded due to the high spatial correlation. In contrast, for the high-mode transmission rate, space–time block code with single carrier modulation offers a bit error rate improvement by a factor over hundred, in comparison to a single transmit element, demonstrating that the multiple-input multiple-output optimal code depends on the software-defined acoustic modem transmission mode.

Description: Long-term watershed management in Ethiopia was evaluated in various agro-ecologies starting in the 1980s. Our research was carried out to investigate the effects of long-term watershed management on soil macronutrient status and crop production in the Maybar subwatershed terrace positioning system, which has a long-term data set on various aspects, such as hydroclimatology, agriculture, and social studies. Crop yield data were collected from 40 fixed plots of that data set, and soil samples were collected by topo-sequencing of the catchment from the cultivation field based on different terrace position plot arrangements. The results showed higher crop yield and production of biomass in the upper section or deposition zone of soil and water conservation structure than below the structure or loss zone, but did not vary significantly from the annual production potential. The annual production of cereals was marginally decreased, but not pulse crops, reducing the wheat harvest production from the middle to the loss zone (23.8%) rather than the deposition zone to middle portion of the terrace (8.0%). In comparison, to increase the slope position of the terrace, the redaction percentage of pulse crops (field pea and lentil) is greater, because in the first terrace location (upper to middle) and in the second terrace, the output capacity of field pea was reduced by 22.4%. The condition of soil fertility between the 2 consecutive systems for soil and water protection differed from the upper to the lower land positions. Improvement in soil chemical and physical properties relatively increased toward the upper land position. Soil organic matter, available phosphorus, bulk density, and soil moisture content were significantly affected by soil and water conservation structures ( P ⩽ .05). Long-term terrace growth typically has a positive effect on improvements in onsite soil resources and the capacity for crop production. It therefore has a beneficial impact on onsite natural resources, such as enhancing soil macronutrients and increasing productivity in crop yields.

Description: Partial discharges are the major cause of deterioration in the insulation characteristics of switchgears. Therefore, timely detection of partial discharge in switchgear and potential insulation faults is an urgent problem that needs to be addressed in the power supervision industry. In this study, a device was proposed for online monitoring of high-voltage switchgears based on pulse current method and ozone (O3) detection. The pulse current method obtains the PD signal by monitoring the phase holes on the switch indicator. Occurrence of a partial discharge in a certain phase leads to the production of a discharge pulse, which can be coupled out by a capacitive sensor. The current spectrum and the O3 produced by partial discharge were processed via fast Fourier transform for accurate diagnosis of the occurrence of partial discharge and its severity in switchgears. The proposed method allows for convenient acquisition of the partial discharge signal, simple installation of the device, and realization with inexpensive sensors.

Description: When gob side entry retaining is carried out in backfill mining, the roof will show different subsidence morphology due to the difference of compactness and supporting force of the backfill body at different positions. This paper analyzed the immediate roof subsidence structure under two extreme conditions, constructed the roof segmented subsidence structure and the mechanical model of roadside backfill body, and used FLAC3D software to investigate the roof migration and the force law of the roadside backfill body under the conditions of different goaf backfilled rates, different width and strength of roadside backfill body. Finally, the backfill practice of a mine in Shandong Province of China is taken as an example for analysis. The results show that the segmented subsidence structure of the immediate roof is related to the mechanical properties of the roadside backfill body and the goaf backfill body. When the backfilled rate of goaf decreases from 95% to 70%, the width of roadside backfill body decreases from 5 m to 1 m, and the elastic modulus decreases from 10 GPa to 0.5 GPa, the greater difference in the subsidence and inclination of the immediate roof on both sides of the roadside backfill body is, the more obvious the segmented subsidence structure characteristics of the immediate roof are, and the greater force on the roadside backfill body will be, the more unfavorable it is to maintain the stability of the roadway surrounding rock and the roadway backfill body. Therefore, when gob side entry retaining is carried out in backfill mining, the surrounding rock structure and the force on roadside backfill body should be considered comprehensively.

Description: It is the most important and challenging problem to share the data safely in cloud computing. Some so-called trusted third parties may also infringe users’ data privacy. It is an urgent problem for data owners to share data safely with the designated users rather than the third party or other users. Traditional encryption schemes utilize different keys to produce multiple encrypted copies of the same data for users. It is no longer applicable for cloud data sharing security. Attribute-based encryption can solve above problems, but it needs to rely on trusted third parties to protect the users’ privacy. In this article, in order to address the above problems, we propose a blockchain-based ciphertext-policy attribute-based encryption scheme for cloud data secure sharing without relying on any trusted third parties. Blockchain-based ciphertext-policy attribute-based encryption scheme can protect the rights and security of data owner. Compared with existing cloud security schemes, the proposed scheme has more advantages in terms of the six aspects: (1) data owners have the authority to decide who can decrypt the data; (2) the operations of users are retained permanently, and all records are tamper-proof; (3) our proposed scheme has the characteristic of “one-to-many” encryption, and data is encrypted only once; (4) our scheme does not rely on any trusted third party; (5) in terms of the discrete logarithm problem and decisional q parallel-bilinear Diffie–Hellman exponent problem, we prove that our proposed scheme is secure; and (6) experiment shows that our proposed scheme is more efficient than the comparative scheme.

Description: The availability of cost-effective and environmentally friendly electricity to the entire population is a prime concern of the South African government. It has brought attention to microgrid projects, especially when rural population is considered properly. To address the energy needs of any country, the focus line should be the cost and availability of local resources. Due to the abundance of coal reserves and lack of alternative resources, coal dependence cannot be overlooked in the near future. This paper focuses not only on microgrid needs in South Africa but also on the possible use of hydrogen extracted from coal as a fuel in Proton Exchange Membrane Fuel Cell (PEMFC) in microgrids. The complete assembly of PEMFC and its use in the microgrid are discussed. To make the H2 extraction process eco-friendly and hence worth considering, Carbon capture and sequestration process is discoursed. Furthermore, cost benefit analysis and the long term benefit of the use of PEMFC in microgrids with coal-based hydrogen production are presented in this research.

Description: Understanding the microheterogeneity of tight sandstone is the basis of reservoir science, and quantitative characterization of the reservoir’s microheterogeneity is key to reservoir evaluation. In this study, an image-processing analysis method to study the heterogeneity of tight reservoirs is established. A modified Image J plugin is used to accurately identify the surface porosity of a thin casting sheet; the heterogeneity of the microscopic pores in a reservoir is then abstracted into discrete values of the surface porosity. A new parameter for quantitative characterization of the microscopic heterogeneity of tight sandstone, that is, the heterogeneity index Q, is proposed. The fractal dimension calculated via a liquid nitrogen adsorption experiment is used to test the new parameter, and the geological significance of Q is discussed. The results show that Q has a good positive correlation with the fractal dimension, which is beneficial in determining the heterogeneity of the reservoir, pore throat distribution, and roughness of the pore surface. Q has a good correlation with physical parameters such as the specific surface area, average pore diameter, and total pore volume of the sample, indicating that this index can effectively characterize and quantitatively evaluate the reservoir. Therefore, this parameter provides a new basis for reservoir evaluation and classification and provides a new direction for delineating advantageous horizons as well as guiding development and mining.

Description: Low-permeability to ultralow-permeability reservoirs of the China National Petroleum Corporation are crucial to increase the reserve volumes and the production of crude oil in the present and future times. This study aimed to address the two major technical bottlenecks faced by the low-permeability to ultralow-permeability reservoirs by a comprehensive use of technologies and methods such as rate-controlled mercury injection, nuclear magnetic resonance, conventional logging, physical simulation, numerical simulation, and field practices. The reservoir characteristics of low-permeability to ultralow-permeability reservoirs were first analyzed. The water flooding development adjustment mode in the middle and high water-cut stages for the low-permeability to ultralow-permeability reservoirs, where water is injected along the fracture zone and lateral displacement were established. The formation mechanism and distribution principles of dynamic fractures, residual oil description, and expanding sweep volume were studied. The development mode for Type II ultralow-permeability reservoirs with a combination of horizontal well and volume fracturing was determined; this led to a significant improvement in the initial stages of single-well production. The volume fracturing core theory and optimization design, horizontal well trajectory optimization adjustment, horizontal well injection-production well pattern optimization, and horizontal well staged fracturing suitable for reservoirs with different characteristics were developed. This understanding of the reservoir characteristics and the breakthrough of key technologies for effective development will substantially support the oil-gas valent weight of the Changqing Oilfield to exceed 50 million tons per year, the stable production of the Daqing Oilfield with 40 million tons per year (oil-gas valent weight), and the realization of 20 million tons per year (oil-gas valent weight) in the Xinjiang Oilfield.

Description: The impact of neglected well bore pressure losses due to fluid accumulation and kinetic energy in the fundamental energy equation used for derivation of flowing bottom-hole pressure in horizontal well have been conceived to be a considerable reason for the discrepancy between computed rates from the existing models and actual rates got from production tests. In the study, a new model that investigate all possible well bore pressure losses effect on the production rate of a horizontal oil well have been established. The newly developed model has been validated using the field data obtained from the literature and outcome got from the new model yields more satisfactory results. A more realistic results that evident all flow phenomena in petroleum production well include the initial unsteady, pseudo-steady and steady state flow condition hence flow rate at any given production time has been established for flow of oil along horizontal production well. The concept is useful to estimate flowing bottom-hole pressure and analyze its effect on production rate value of a horizontal oil well without ignoring any pressure resisting terms in the governing thermodynamic equation. The unsteadiness fluid flow period that generally observed after shut in a well have also been demonstrated. Closer agreement between the results obtained using the newly developed model and real life field measurement was observed when compared with the previous model in the literature. The study gives reservoir engineer an exact and helpful device for estimating and assessing horizontal oil well production rate.

Description: Hydrodesulfurization reaction, as the last step of hydrothermal cracking reaction, is of great significance for the reduction of viscosity and desulfurization of heavy oil. Based on Density Functional Theory and using Dmol3 module of Materials Studio, this research simulated the adsorption and hydrodesulfurization of thiophene on Ni2P (001) surface, and discussed the hydrodesulfurization reaction mechanism of thiophene on Ni2P (001) surface. It was found that the direct hydrodesulfurization of thiophene had more advantages than the indirect hydrodesulfurization of thiophene. Finally, the optimal reaction path was determined: C4H4S+H2→C4H6.

Description: Carbon dioxide (CO2) flooding is an effective method to enhance oil recovery in low-permeability reservoirs. Studying key geological factors controlling oil displacement efficiency is of great significance to the CO2 injection scheme design in low-permeability reservoirs. Focusing on low-permeable H reservoir in Songliao Basin, China, this paper describes the contact and connection of sand bodies, natural fractures and high-permeability zones with core samples, log data and experiment firstly. After that, the impact of interaction of sand body connection, natural fracture and high-permeability zone on oil displacement efficiency is determined by using geological and dynamic data in CO2 injection area. Results indicate that the connection of single sand bodies between injectors and producters wells primarily controls CO2 flooding in low-permeability reservoirs. Furthermore, coupling of sand body connection, natural fractures and high-permeability zones is the key geological factor governing oil displacement efficiency of CO2 injection in low-permeability reservoirs, where well or generally-connected sand bodies can improve the efficiency significantly. Meanwhile, the dominant seepage channels in other directions have no influence on producers, which is beneficial to improve CO2 flooding efficiency.

Description: In this study, we analyse the impact of oil price uncertainty (as measured by an observable measure of oil price volatility, i.e. realised volatility) on United States state-level real consumption by accounting for oil dependency. We account for both the long- and short-run dynamics of the state-level consumption function using the panel Pooled Mean Group estimator. The analysis makes use of a novel dataset including housing and stock market wealth at the state level covering the quarterly period 1975:Q1 to 2012:Q2, supplemented with an annual dataset up to 2018. We simultaneously estimate the long-run relationship and short-run impact of oil price volatility at the state-level conditional upon their oil dependency. We find that the negative impact of volatility is most severe for the states of Wyoming, Alaska and New Mexico, while the negative impact is least for Illinois, New York and Nebraska. States with lower per capita income and consumption expenditure, notably in the Southeast and Southwest region of the country are exposed to be more vulnerable to the negative impact of adverse developments and uncertainty in the oil market, as they may have less access to a stock of wealth and other means as recourse. Heterogenous responses, therefore, necessitate additional state-level response besides the national response to oil uncertainty.

Description: Generating electricity through renewable energies is growing increasingly to reduce the huge demand on electricity and the impact of fossil energies on the environment, the most common sources forms used are: the wind, the sun, the photovoltaic and the thermal, without forgetting hydropower by the bays of dams. Fortunately, 70% of our planet is covered by the seas and oceans, this area constitutes a huge potential for electricity production to be exploited. The scientific advances of recent years allow a better exploitation of these resources especially the marine current due to its reliability and predictability. The marine current energy is extracted using a hydrokinetic turbine (HKT) which transform the kinetic energy of water into an electrical energy. The exploitation of this resource needs in the first step the assessment of marine currents in the study area for implementing the HKT, and the second step is designing an adequate technology. The main goal of this study is the assessment of the marine current resource on the Moroccan Mediterranean coast to evaluate the suitable area to implement the HKT, and to determine the marine current speed intensities at different depths. As well as, to estimate an average potential existing in the site. Moreover, we will conduct a study based on the results of the assessment that was made to design a horizontal axis marine current turbine (HAMCT). Two hydrofoil profile were considered to design a HAMCT using the Blade Element Theory (BEM) and calculating their performances adapted to the site conditions Naca4415 and s8052. In addition, a comparison was made between this two HAMCT hydrofoil profile for deciding the best one for implementing in the studied area.

Description: Aiming at the problems of low data transmission efficiency and uneven energy consumption caused by unreliable link communication in the routing process of wireless sensor networks, this article designs a routing game algorithm based on link quality. In this article, the index for evaluating link quality is defined first. Then, the link quality, node residual energy, and minimum jump transmission strategy are integrated into the utility function to establish a game model to determine the best next hop transmission node. Finally, the routing optimal transmission path is obtained according to the analysis of the existence of Nash equilibrium in the game. In the simulation experiment, the influence of the change of link quality parameters on the performance of the algorithm is analyzed, and the proposed algorithm is compared with non-linear weight particle swarm optimization (NWPSO) algorithm and Low Energy Adaptive Clustering Hierarchy-Improvement (LEACH-IMPT) algorithm in three aspects: the number of surviving nodes, network lifetime, and network energy consumption. The results show that the network lifetime of this method is 16.8% longer than that of LEACH-IMPT algorithm and 7.5% longer than that of NWPSO algorithm. This shows that the algorithm can effectively balance the network energy consumption and prolong the network life cycle. In addition, according to the routing path obtained in the simulation experiment, the optimality of its link quality is verified in the real experimental environment, and the experimental results prove the feasibility of the method in this article in practice.

Description: Cloud computing is a well-known technology that provides flexible, efficient, and cost-effective information technology solutions for multinationals to offer improved and enhanced quality of business services to end-users. The cloud computing paradigm is instigated from grid and parallel computing models as it uses virtualization, server consolidation, utility computing, and other computing technologies and models for providing better information technology solutions for large-scale computational data centers. The recent intensifying computational demands from multinationals enterprises have motivated the magnification for large complicated cloud data centers to handle business, monetary, Internet, and commercial applications of different enterprises. A cloud data center encompasses thousands of millions of physical server machines arranged in racks along with network, storage, and other equipment that entails an extensive amount of power to process different processes and amenities required by business firms to run their business applications. This data center infrastructure leads to different challenges like enormous power consumption, underutilization of installed equipment especially physical server machines, CO2 emission causing global warming, and so on. In this article, we highlight the data center issues in the context of Pakistan where the data center industry is facing huge power deficits and shortcomings to fulfill the power demands to provide data and operational services to business enterprises. The research investigates these challenges and provides solutions to reduce the number of installed physical server machines and their related device equipment. In this article, we proposed server consolidation technique to increase the utilization of already existing server machines and their workloads by migrating them to virtual server machines to implement green energy-efficient cloud data centers. To achieve this objective, we also introduced a novel Virtualized Task Scheduling Algorithm to manage and properly distribute the physical server machine workloads onto virtual server machines. The results are generated from a case study performed in Pakistan where the proposed server consolidation technique and virtualized task scheduling algorithm are applied on a tier-level data center. The results obtained from the case study demonstrate that there are annual power savings of 23,600 W and overall cost savings of US$78,362. The results also highlight that the utilization ratio of already existing physical server machines has increased to 30% compared to 10%, whereas the number of server machines has reduced to 50% contributing enormously toward huge power savings.

Description: While it is well understood that the emerging Social Internet of Things offers the capability of effectively integrating and managing massive heterogeneous IoT objects, it also presents new challenges for suggesting useful objects with certain service for users due to complex relationships in Social Internet of Things, such as user’s object usage pattern and various social relationships among Social Internet of Things objects. In this study, we focus on the problem of service recommendation in Social Internet of Things, which is very important for many applications such as urban computing, smart cities, and health care. We propose a graph-based service recommendation framework by jointly considering social relationships of heterogeneous objects in Social Internet of Things and user’s preferences. More exactly, we learn user’s preference from his or her object usage events with a latent variable model. Then, we model users, objects, and their relationships with a knowledge graph and regard Social Internet of Things service recommendation as a knowledge graph completion problem, where the “like” property that connects users to services needs to be predicted. To demonstrate the utility of the proposed model, we have built a Social Internet of Things testbed to validate our approach and the experimental results demonstrate its feasibility and effectiveness.

Description: A routing-benefited deployment algorithm combining static and dynamic layouts is proposed, and its comprehensive performance evaluation is given in this article. The proposed routing-benefited deployment algorithm is intended to provide a suitable network deployment and subsequent data transmission approach for underwater optical networking and communication. Static nodes are anchored for long-term monitoring, and movable nodes can adjust their depths based on the virtual force and move with the variation of area-of-interest changing. Then, nodes begin to collect data that they can monitor and transmit to sink nodes. Here, the underwater wireless optical communication model is described to actualize the real environment, and the vector-based forwarding protocol is particularly considered to compare the impact of different deployment algorithms on routing. It is shown by simulation experiment results that routing-benefited deployment algorithm outperforms several existing traditional virtual force deployment algorithms in terms of coverage, lifetime, energy consumption balance, packet-loss rate, and time-delay.

Description: With resource crisis and environmental crisis increasingly grim, many countries turn the focus to pollution-free and renewable wind energy resources, which are mainly used for offshore wind power generation, seawater desalination and heating, etc., on the premise that the characteristics of resources are fully grasped. In this study, the evaluation of offshore wind energy in offshore waters in China, as well as the advantages and disadvantages of existing studies were overviewed from four aspects: the spatial-temporal characteristics of wind energy, wind energy classification, the short-term forecast of wind energy and the long-term projection of wind energy, according to the research content and the future considerations about wind energy evaluation (evaluation of wind energy on islands and reefs, the impact of wind energy development on human health) were envisaged, in the hope of providing a scientific basis for the site selection and business operation ‘or military applications’ here (after business operation), etc. of wind energy development, ‘aritime navigation against environmental construction,’ here and also contributing to the sustainable development and health of human beings.

Description: An important node identification algorithm based on an improved structural hole and K-shell decomposition algorithm is proposed to identify important nodes that affect security in complex networks. We consider the global structure of a network and propose a network security evaluation index of important nodes that is free of prior knowledge of network organization based on the degree of nodes and nearest neighborhood information. A node information control ability index is proposed according to the structural hole characteristics of nodes. An algorithm ranks the importance of nodes based on the above two indices and the nodes’ local propagation ability. The influence of nodes on network security and their own propagation ability are analyzed by experiments through the evaluation indices of network efficiency, network maximum connectivity coefficient, and Kendall coefficient. Experimental results show that the proposed algorithm can improve the accuracy of important node identification; this analysis has applications in monitoring network security.

Description: The Sky Island Restoration Collaborative (SIRC) is a growing partnership between government agencies, nonprofit organizations, and private landowners in southeast Arizona, the United States, and northern Sonora, Mexico. Starting in 2014 as an experiment to cultivate restoration efforts by connecting people across vocations and nations, SIRC has evolved over 5 years into a flourishing landscape-restoration initiative. The group is founded on the concept of developing a restoration economy, where ecological and socioeconomic benefits are interconnected and complimentary. The variety of ideas, people, field sites, administration, and organizations promote learning and increase project success through iterative adaptive management, transparency, and sharing. The collaborative seeks to make restoration self-sustaining and improve quality of life for citizens living along the US-Mexico border. Research and experiments are developed between scientists and practitioners to test hypotheses, qualify procedures, and quantify impacts on shared projects. Simultaneously, partners encourage and facilitate connecting more people to the landscape—via volunteerism, internships, training, and mentoring. Through this history, SIRC’s evolution is pioneering the integration of community and ecological restoration to protect biodiversity in the Madrean Archipelago Ecoregion. This editorial introduces SIRC as a unique opportunity for scientists and practitioners looking to engage in binational partnerships and segues into this special journal issue we have assembled that relates new findings in the field of restoration ecology.

Description: In the past decades, emerging technologies such as unmanned driving and indoor navigation have developed rapidly, and simultaneous localization and mapping has played unparalleled roles as core technologies. However, dynamic objects in complex environments will affect the positioning accuracy. In order to reduce the influence of dynamic objects, this article proposes an improved simultaneous localization and mapping algorithm combined with semantic segmentation model. First, in the pre-processing stage, in order to reduce the influence of dynamic features, fully convolutional network model is used to find the dynamic object, and then the output image is masked and fused to obtain the final image without dynamic object features. Second, in the feature-processing stage, three parts are improved to reduce the computing complexity, which are extracting, matching, and eliminating mismatching feature points. Experiments show that the absolute trajectory accuracy in high dynamic scene is improved by 48.58% on average. Meanwhile, the average processing time is also reduced by 21.84%.

Description: In this article, based on wavelet reconstruction and fractal dimension, a medical image authentication method is implemented. According to the local and global methods, the regularity of the mutation structure in the carrier information is analyzed through a measurement defined in the medical image transformation domain. To eliminate the redundancy of the reconstructed data, the fractal dimension is used to reduce the attributes of the reconstructed wavelet coefficients. According to the singularity of the fractal dimension of the block information, the key features are extracted and the fractal feature is constructed as the authentication feature of the images. The experimental results show that the authentication scheme has good robustness against attacks, such as JPEG compression, multiplicative noise, salt and pepper noise, Gaussian noise, image rotation, scaling attack, sharpening, clipping attack, median filtering, contrast enhancement, and brightness enhancement.

Description: In order to solve the problem of difficult gas extraction in coal mine, a method of gas extraction from coal seam by interval hydraulic flushing is put forward. Based on the coal seam gas occurrence conditions of 7609 working face in Wuyang Coal Mine, the numerical simulation research on gas drainage by ordinary drilling and hydraulic flushing drilling was carried out by using COMSOL numerical simulation software. The results show that with the increase of hydraulic flushing coal quantity, the effective gas drainage radius also increases. The effective extraction radius of ordinary drilling is 0.5 m, and the effective extraction radius is 1.0 m, 1.2 m and 1.3 m respectively when the coal flushing quantity is 0.5t/m, 1.0t/m and 1.5t/m. As multiple boreholes are drained at the same time, the boreholes will affect each other, which will reduce the gas pressure and increase the effective drainage radius, the spacing between boreholes can be greater than twice the effective drainage radius of a single borehole when arranging boreholes. And the smaller the flushing interval, the more uniform the gas pressure reduction area. According to the numerical simulation results, the ordinary drilling and 1.0t/m interval hydraulic flushing test were carried out in the field. Through observation and analysis, the gas concentration of the interval hydraulic flushing drilling module was increased by 31.2% and the drainage purity was increased by 5.77 times compared with the ordinary drilling module. It shows that the interval hydraulic flushing drilling can effectively improve the gas drainage effect.

Description: To clarify the influence of pore pressure gradient on hydraulic fracture propagation, the stress distribution in and around the borehole is explained by theoretical analysis method in this paper. A mechanical model of hydraulic fracture initiation under the action of pore pressure gradient is established. Then coupled seepage-stress-damage software is used to simulate the initiation and propagation of hydraulic fractures in rock samples under the action of pore pressure gradient. Finally, the influence of the number and spatial position of the induction holes on the initiation and propagation of hydraulic fractures is analyzed. It is shown that: (1) Pore pressure gradient can effectively reduce the initiation pressure of hydraulic fractures. (2) The greater the pore pressure gradient is, the easier the hydraulic fracture is to spread to the region with high pore pressure. (3) With the action of pore pressure gradient, the hydraulic fracture is shaped as ‘丨’, ‘丿’ and ‘S’ types and can be represented by the four abstract conceptual models.

Description: To study the influence of vibration on gas desorption and diffusion in particle coal, gas desorption experiments on soft coal with outburst risk under different frequency vibrations were carried out by using a self-designed gas adsorption and desorption platform under vibration conditions, and the influence of different frequency vibrations on the diffusion kinetic parameters was quantitatively analyzed by using a dynamic diffusion coefficient model. The influence mechanism of vibration on gas desorption and diffusion in coal was further analyzed from the three aspects of gas molecules, energy conversion and pore structure through theoretical analysis and mercury injection experiments. The results showed that with increasing vibration frequency, the gas desorption of the coal samples first increases and then decreases. The initial diffusion coefficient of gas in the coal samples increases linearly with increasing vibration frequency, but the attenuation coefficient of the diffusion coefficient decreases first and then increases with increasing vibration frequency. The "throwing effect" and thermal effect of vibration on the gas molecules are both conducive to the desorption of gas molecules. In addition, vibration causes changes in the pore structure in coal, increasing gas diffusion paths and reducing diffusion resistance.

Description: In this article, a comprehensive parameter analysis for the polling-based medium access control protocol is executed. The theoretical expressions of the relationship between network parameters and performance including delay and energy consumption are given for the first time. The specific conclusions in this article are as follows: (1) awake duration is the parameter that has the greatest impact on delay and energy consumption. Increasing the duty cycle (awake duration) will effectively reduce the delay, but will also increase the energy consumption within a certain range; (2) increasing polling duration can reduce the delay, but it will also increase the energy consumption; and (3) more forwarding nodes cause a smaller delay, and it can save the energy with modest increase of delay by reducing the polling duration. An adaptive parameter optimization polling-based medium access control protocol is proposed to optimize network performance. In this protocol, the residual energy gets fully used to increase awake duration and polling duration, which makes the delay smaller, and the network maintains a long lifetime meanwhile. Based on the results of the analysis, the adaptive parameter optimization polling-based medium access control protocol proposed in this article reduces the delay by 22.40% and increases the energy efficiency by 23.25%.

Description: The existing equipment of civil aircraft cargo fire detection mainly uses photoelectric smoke detectors, which has a high false alarm rate. According to Federal Aviation Agency’s statistics, the false alarm rate is as high as 99%. Since, in the cargo of civil aircraft, visible image processing technology cannot be used to detect smoke in the event of a fire due to the closed dark environment, a novel smoke detection method using infrared image processing technology is presented. Experiments were conducted under different environment pressures in the full-size cargo of civil aircraft. The results show that the proposed method can effectively detect smoke at the early stage of fire which is applicable for fire detection in civil aircraft cargoes.

Description: In recent years an increasing number of organizations have started to rethink their physical work environments and recognized the value of having activity-based workspaces (ABWs). This allows employees to choose freely between several work environments based on their specific task. There is growing debate amongst researchers about the effects of ABWs on employee behavior, but companies are still not aware of the options available or the consequences of moving to an ABW layout. This single-case, exploratory study uses 36 interviews and multiple data sources in a German organization leading in use of ABWs to generate insight into this topic. We develop a taxonomy of ABWs and analyze how various design parameters affect how people perform in ABWs regarding communication, leadership, working style, and work performance. We relate these findings to previous research and develop a cause-effects framework of ABWs. Against these findings, we generate recommendations for future research and practice.

Description: For aircrafts equipped with BeiDou Navigation Satellite System/Strapdown Inertial Navigation System integrated navigation system, BeiDou Navigation Satellite System information can be used to achieve autonomous alignment. However, due to the complex polar environment and multipath effect, BeiDou Navigation Satellite System measurement noise often exhibits a non-Gaussian distribution that will severely degrade the estimation accuracy of standard Kalman filter. To address this problem, a new polar alignment algorithm based on the Huber estimation filter is proposed in this article. Considering the special geographical conditions in the polar regions, the dynamic model and the measurement model of BeiDou Navigation Satellite System/Strapdown Inertial Navigation System integrated alignment system in the grid frame are derived in this article. The BeiDou Navigation Satellite System measurement noise characteristics in the polar regions are analyzed and heavy-tailed characteristics are simulated, respectively. Since the estimation accuracy of standard Kalman filter can be severely degraded under non-Gaussian noise, a Kalman filter based on the Huber estimation is designed combining grid navigation system and generalized maximum likelihood estimation. The simulation and experiment results demonstrate that the proposed algorithm has better robustness under non-Gaussian noise, and it is effective in the polar regions. By employing the proposed algorithm, the rapidity and accuracy of the alignment process can be improved.

Description: Petrological analysis, thin-section observation and laboratory analysis data were selected to systematically study the physical and diagenetic features of the first member of the Paleogene Shahejie Formation (Es1) in the No. 3 structural belt of the Nanpu Sag, Bohai Bay Basin. The intensities of different diagenetic processes were determined, the diagenetic evolution sequence was reconstructed, the typical diagenetic facies were identified and the effects of different diageneses on the reservoir were quantitatively analyzed. The results show that the main intergranular fillings include authigenic-quartz, quartz secondary enlargement, clay minerals, carbonate cement and matrix. The pore types include intergranular porosity, dissolution porosity and microfractures. The reservoir has experienced compaction, early cementation, dissolution and late cementation, among which compaction is the most important porosity reducer. Compaction was the main diagenetic process involved in porosity reduction, accounting for about 24.4% of the loss of thin-section porosity. The dissolution process clearly improved the porosity, increasing thin-section porosity by 2.7%. Five diagenetic facies were identified on the basis of petrographic analyses, namely, (a) strongly compacted-weakly cemented-weakly dissolved facies; (b) weakly compacted-strongly cemented-weakly dissolved facies; (c) moderately compacted-moderately cemented-weakly dissolved facies; (d) strongly compacted-weakly cemented-moderately dissolved facies; and (e) strongly compacted-weakly cemented-strongly dissolved facies. According to the analysis of diagenesis intensity, the porosity evolution model of various diagenetic facies was reconstructed, and the reservoir quality of various diagenetic facies was quantitatively predicted. The reservoir quality of different diagenetic facies clearly changed with depth. The best reservoir quality was in strongly compacted–weakly cemented–strongly dissolution facies, which have good sorting, contain a large amount of feldspar and soluble debris, and are mainly developed in the main part of the river channel. Our study can provide a reference for the subsequent exploration and development of deep petroleum systems.

Description: One optimization method of hourly heat load calculation model for heat storage air-conditioning heating system in different climate zones was proposed. A building model is initially built in six different climate zones. Subsequently, the hourly heat load and steady-state design heat load in different climate zones were analyzed. Simultaneously, the hourly heat load additional coefficient of the air-conditioning system with different heating modes on a typical day was compared. It can be found that steady-state design heat load on a typical day is mostly between the peak load and average load of the air-conditioning heating system. Simultaneously, results indicate that the hourly heat load additional coefficient in each climate zone can be fitted to different exponential functions. When the heat storage capacity of building components was changed, the maximum increase of the hourly heat load additional coefficient of the air-conditioning system with intermittent heating was 5%. Thus, the research of the optimal design of hourly heat load calculation method provides a relative reference for performance improvement of the heat storage air-conditioning heating system.

Description: The low-frequency pulse wave makes the velocity of the fluid in the reservoir fluctuate dramatically, which results in a remarkable inertia force. The Darcy’s law was inapplicable to the pulse flow with strong effect of inertial force. In this paper, the non-Darcy flow equation and the calculation method of capillary number of pressure pulse displacement are established. The pressure pulse experiments of single-phase and two- phase flow are carried out. The results show that the periodic change of velocity can decrease the seepage resistance and enhance apparent permeability by generating the inertial force. The higher the pulse frequency improves the apparent permeability by enhancing influence of inertial force. The increase of apparent permeability of high permeability core is larger than that of low permeability core, which indicates that inertial force is more prominent in high permeability reservoir. For the water-oil two-phase flow, inertia force makes the relative permeability curve move towards right, and the equal permeability point becomes higher. In other words, with the increase of capillary number, part of residual oil is activated, and the displacement efficiency is improved.

Description: Climate change is one of the greatest threats that our civilization is facing because increases in extreme temperatures severely affect humans, the economy, and ecosystems. General circulation models, which adequately predict climate change around the world, are less accurate at regional levels. Therefore, trends must be locally assessed, particularly in regions such as the Baja California Peninsula, which is a thin mass of land surrounded by the Pacific Ocean and the Gulf of California. Herein, we discuss extreme temperature trends in the Baja California Peninsula and whether they are statistically significant based on the Spearman’s nonparametric statistical test. For these purposes, 18 weather stations covering the entire region were analyzed, revealing that maximum temperatures for the hottest months are rising at a rate that is consistent with the RCP 8.5 scenario. Changes in minimum temperatures were also analyzed.

Description: Effective scheduling of limited communication resources is one of the critical methods for data transmission in the Internet of things. However, the time slot utilization rate of many existing resource scheduling methods of Internet of things is not high. This article proposes a new efficient resource scheduling based on routing tree and detection matrix for Internet of things. In heterogeneous Internet of things, according to the different working modes and functions, the nodes are divided into Internet of things devices, routing nodes, and base station. We use time slot multiplexing to improve the time slot utilization of continuous transmission in Internet of things. First, the time slot allocation table in a round is obtained by the time slot scheduling based on the routing tree. Then, the collision matrix and the transmission matrix are established based on the time slot allocation table in a round. Finally, the minimum time slot scheduling in continuous rounds is determined based on the routing tree and the detection matrix. The experimental results show that the resource scheduling based on routing tree and detection matrix effectively improves the utilization of time slots and improves the throughput of the Internet of things.

Description: During horizontal well staged fracturing, there is stress interference between multiple transverse fractures in the same perforation cluster. Theoretical analysis and numerical calculation methods are applied in this study. We analysed the mechanism of induced stress interference in a single fracture under different fracture spacings and principal stress ratios. We also investigated the hydraulic fracture morphology and synchronous expansion process under different fracture spacings and principal stress ratios. The results show that the essence of induced stress is the stress increment in the area around the hydraulic fracture. Induced stress had a dual role in the fracturing process. It created favourable ground stress conditions for the diversion of hydraulic fractures and the formation of complex fracture network systems, inhibited fracture expansion in local areas, stopped hydraulic fractures, and prevented the formation of effective fractures. The curves of the maximum principal stress, minimum principal stress, and induced principal stress difference with distance under different fracture lengths, different fracture spacings, and different principal stress ratios were consistent overall. With a small fracture spacing and a small principal stress ratio, intermediate hydraulic fractures were difficult to initiate or arrest soon after initiation, fractures did not expand easily, and the expansion speed of lateral hydraulic fractures was fast. Moreover, with a smaller fracture spacing and a smaller principal stress ratio, hydraulic fractures were more prone to steering, and even new fractures were produced in the minimum principal stress direction, which was beneficial to the fracture network communication in the reservoir. When the local stress and fracture spacing were appropriate, the intermediate fracture could expand normally, which could effectively increase the reservoir permeability.

Description: Power management in wireless sensor networks is very important due to the limited energy of batteries. Sensor nodes with harvesters can extract energy from environmental sources as supplemental energy to break this limitation. In a clustered solar-powered sensor network where nodes in the network are grouped into clusters, data collected by cluster members are sent to their cluster head and finally transmitted to the base station. The goal of the whole network is to maintain an energy neutrality state and to maximize the effective data throughput of the network. This article proposes an adaptive power manager based on cooperative reinforcement learning methods for the solar-powered wireless sensor networks to keep harvested energy more balanced among the whole clustered network. The cooperative strategy of Q-learning and SARSA( λ) is applied in this multi-agent environment based on the node residual energy, the predicted harvested energy for the next time slot, and cluster head energy information. The node takes action accordingly to adjust its operating duty cycle. Experiments show that cooperative reinforcement learning methods can achieve the overall goal of maximizing network throughput and cooperative approaches outperform tuned static and non-cooperative approaches in clustered wireless sensor network applications. Experiments also show that the approach is effective in response to changes in the environment, changes in its parameters, and application-level quality of service requirements.

Description: Due to the complex environments in real fields, it is challenging to conduct identification modeling and diagnosis of plant leaf diseases by directly utilizing in-situ images from the system of agricultural Internet of things. To overcome this shortcoming, one approach, based on small sample size and deep convolutional neural network, was proposed for conducting the recognition of cucumber leaf diseases under field conditions. One two-stage segmentation method was presented to acquire the lesion images by extracting the disease spots from cucumber leaves. Subsequently, after implementing rotation and translation, the lesion images were fed into the activation reconstruction generative adversarial networks for data augmentation to generate new training samples. Finally, to improve the identification accuracy of cucumber leaf diseases, we proposed dilated and inception convolutional neural network that was trained using the generated training samples. Experimental results showed that the proposed approach achieved the average identification accuracy of 96.11% and 90.67% when implemented on the data sets of lesion and raw field diseased leaf images with three different diseases of anthracnose, downy mildew, and powdery mildew, significantly outperforming those existing counterparts, indicating that it offered good potential of serving field application of agricultural Internet of things.

Description: Flue gas assisted steam assisted gravity drainage (SAGD) is a frontier technology to enhance oil recovery for heavy oil reservoirs. The carbon dioxide generated from the thermal recovery of heavy oil can be utilized and consumed to mitigate climate warming for the world. However, most studies are limited to merely use numerical simulation or small physical simulation device and hardly focus on large scale three-dimensions experiment, which cannot fully investigate the enhanced oil recovery (EOR) mechanism of flue gas assisted SAGD, thus the effect of flue gas on SAGD production performance is still not very clear. In this paper, large-scaled and high temperature and pressure resistant 3D physical simulation experiment was conducted, where simulated the real reservoir to a maximum extent, and systematically explored the EOR mechanisms of the flue gas assisted SAGD. Furthermore, the differences between the steam huff and puff, SAGD and flue gas assisted SAGD are discussed. The experimental result showed that the production effect of SAGD was improved by injecting flue gas, with the oil recovery was increased by 5.7%. With the help of thermocouple temperature measuring sensors, changes of temperature field display that flue gas can promote lateral re-development of the steam chamber, and the degree of reservoir exploitation around the horizontal wells has been increased particularly. What’s more, the addition of flue gas further increased the content of light components and decreased the content of heavy by comparing the content of heavy oil components produced in different production times.

Description: Although new energy has been widely used in our lives, oil is still one of the main energy sources in the world. After the application of traditional oil recovery methods, there are still a large number of oil layers that have not been exploited, and there is still a need to further increase oil recovery to meet the urgent need for oil in the world economic development. Chemically enhanced oil recovery (CEOR) is considered to be a kind of effective enhanced oil recovery technology, which has achieved good results in the field, but these technologies cannot simultaneously effectively improve oil sweep efficiency, oil washing efficiency, good injectability, and reservoir environment adaptability. Viscoelastic surfactants (VES) have unique micelle structure and aggregation behavior, high efficiency in reducing the interfacial tension of oil and water, and the most important and unique viscoelasticity, etc., which has attracted the attention of academics and field experts and introduced into the technical research of enhanced oil recovery. In this paper, the mechanism and research status of viscoelastic surfactant flooding are discussed in detail and focused, and the results of viscoelastic surfactant flooding experiments under different conditions are summarized. Finally, the problems to be solved by viscoelastic surfactant flooding are introduced, and the countermeasures to solve the problems are put forward. This overview presents extensive information about viscoelastic surfactant flooding used for EOR, and is intended to help researchers and professionals in this field understand the current situation.

Description: The COVID-19 pandemic has hit humanity globally. Besides its obvious threats to our physical health and economic stability, one can only speculate about the pandemic’s and its countermeasures’ psychosocial impacts. Here, we took advantage of a sample of healthy male participants who had completed psychosocial measures on mental health, environmental concern, and prejudice against asylum-seekers just before and during the nationwide lockdown in Germany in spring 2020. A follow-up assessment of 140 participants during the lockdown provided a unique opportunity to track psychosocial changes in a prospective longitudinal study design. In comparison to before the lockdown (1) mental health worsened, (2) environmental concern increased, and (3) prejudice against asylum-seekers decreased. Our study demonstrates psychosocial “side effects” of the pandemic that bring both challenges and opportunities for our society with regard to the handling of psychological reactions to this pandemic and further global crises, including climate change and mass migration.

Description: The spatiotemporal dynamic changes of forest biomass can provide scientific reference and scheme for improving the quality of forest resources and the ecological environment in karst areas. In this article, the China’s National Forest Continuous Inventory data (from 1984 to 2015) was used to analyze the dynamic changes of forest biomass with the univariate linear slope k, barycenter trajectory, improved hot spots detection which was applied in the analysis of forest biomass dynamic change, and geospatial detector method in Guizhou in the first time. The results showed that the total forest biomass had a steady upward trend, 29.3% unit biomass of the forest had significantly increased, while 1.4% decreased dramatically. The forest biomass gravity center shifted from Qiandongnan to Qiannan, with a total distance of 54.1 km. Thus, the following conclusions were drawn: (1) benefiting from the effective implementation of forestry-related policies, the forest biomass had significant increased in a long time series, especially for the artificial shelter forest; (2) the gravity center shifted to the northwest and the number of level 1 forest biomass hot spots increased year by year, which showed a generalized symmetric pattern along the Wujiang River mainstream; and (3) the results of geographical survey showed that the change of forest biomass was greatly affected by topography, climate and human activities, among which terrain factors had the greatest impact.

Description: Low-power lossy networks performance relies heavily on the wireless node battery status. Furthermore, Routing Protocol for Low-Power and Lossy Network routing protocol was not optimally designed with sustainable energy consumption in mind to suit these networks. Prolonging the lifespan of these networks is of utmost priority. This article introduces a solar energy harvesting module to power energy-constrained network devices and quantifies the effect of using harvested energy on prolonging their network lifetime when Routing Protocol for Low-Power and Lossy Network routing protocol is used. Simulation of the new developed module is conducted in three different scenarios using Contiki Cooja simulator sporting Zolertia Z1 motes. Furthermore, the harvested energy used was fed from a Cooja-based Simulation model of actual PV supercapacitor circuit design. All battery levels were set to 1% of their total capacity for all nodes in the network to speed up observing the energy harvesting effect. The performance evaluation results showed that the network with no-energy harvesting operated for time duration of 4:08:04 time units (i.e. hour:minute:second) with a dramatic decrease in connection between nodes in the network. However, the same network, when using the harvested energy to back up the battery operation, lasted for 6:40:01 in time units with improved connectivity, a total extended network lifetime of 2:31:97-time units. Furthermore, for the Routing Protocol for Low-Power and Lossy Network routing metrics, OF0 outperformed ETX in term of throughput, packet delivery ratio, energy consumption, and network connectivity. Results indicate that the developed harvested energy module fits perfectly for any Cooja-based simulation and mimics actual photovoltaic-based supercapacitor battery. It should also help researchers introduce and quantify accurately new energy consumption-based routing metrics for Routing Protocol for Low-Power and Lossy Network.

Description: Research in the physical sciences is critical to the development of new materials technologies for clean energy. Aims in the present work are to synthesise and characterise three-dimensional architectures composed of two-dimensional atomic layer molybdenum disulphide for solar cells and self-powered photodetectors with improved performance. Nanostructured molybdenum disulphide was prepared by using a spin coating method with controlled process times. Prior to each deposition, the layer was dried with hot air for 5 min. A rough, irregular and clustered surface type was generated when the number of spin coating runs was increased. This type of surface was consistent with the morphologies expected for two-dimensional atomic layer molybdenum disulphide in three-dimensional architectures. The nanoscale morphologies, composites, and electronic properties of molybdenum disulphide were examined using scanning electron microscopy, energy-dispersive X-ray spectroscopy, and micro-Raman scattering spectroscopy, respectively. Moreover, three-dimensional architecture-based prototypes for solar cells and self-powered photodetectors were designed, fabricated and tested. In photovoltaic mode, the obtained responsivity and response speed were almost 10 times larger and 20 times faster, respectively, than those recently reported for a single monolayer molybdenum disulphide-based self-powered prototype. In addition, the effects of bias, heat, humidity and a static field on the generated photocurrent and the response time were evaluated. It is expected that the newly designed prototype will exhibit exceptional properties: a broadband spectral response, a high signal-to-noise ratio and excellent stability.

Description: Wireless body area network can be employed to collect patient’s electronic health data. To guarantee the reliability and confidentiality of the collected data, secure data transmission in wireless body area network is required. In wireless body area network, a mutual authentication process has to be carried out between the controller and sensors to ensure their legitimacy, and a key distribution mechanism is required to secure communication after successful mutual authentication. Li et al. proposed a cryptographic solution, which allows group device pairing authentication and key agreement but has low authentication efficiency and key leakage problems. To address these issues, a group authentication and key distribution scheme is proposed in this article. It enables effectively mutual authentication between controller and sensors, supports all signatures of sensors in the group to be checked by the controller through aggregation verification to achieve efficient authentication, and allows key distribution during authentication to improve the computation efficiency. Security analysis indicates that the proposed scheme enjoys existentially unforgeability, and theoretical and experimental comparison demonstrates its practicality in terms of computation and communication cost.

Description: Authigenic albites occur widely in clastic reservoirs with important implications for diagenesis and reservoir formation. The middle Permian Lucaogou Formation in the Jimusaer Sag (Junggar Basin, NW China), where major exploration breakthroughs in shale oil have been achieved, reveals a new phenomenon that authigenic albites are abundant in unique mixed carbonate–volcanic–clastic sequences. This has not been reported in the literatures. To fill the knowledge gap, the origin of these authigenic albites and their relationship with dissolution pores (i.e. diagenesis implications) were investigated. Results show that two types (I and II) of authigenic albite were identified within the shale oil reservoirs. Euhedral Type I authigenic albites with 3–10 μm only occur in dolarenite intraclasts and are symbiotic with amorphous dolomite minerals with a pure chemical composition of 〉99% albite-end-member content. Larger Type II authigenic albites with 10–50 μm are widely distributed in reservoirs, primarily in dissolution pores, and coexist with authigenic dolomite minerals or dolomite overgrowths. Their chemical composition is less pure with anorthite-end-member contents that range from undetectable to 9.77%, with an average of 1.34%. A symbiotic relationship, pure chemical composition, size, and euhedral morphology indicate that Type I authigenic albites precipitated during syngenetic hydrothermal action. However, the morphology of dissolution pores, residual symbiotic “orthoclase”, impure chemical composition and carbon–oxygen isotope indicate that Type II were the products of the dissolution and reprecipitation of “perthite” crystal pyroclasts influenced by acid organic fluids in latter diagenesis. The differential dissolution of “orthoclase” and “albite” components in “perthite” crystal pyroclasts formed enormous intergranular secondary pores in the presence of dolomite minerals in the shale oil reservoirs.

Description: Residents in US cities are exposed to high levels of stress and violent crime. At the same time, a number of cities have put forward “greening” efforts which may promote nature’s calming effects and reduce stressful stimuli. Previous research has shown that greening may lower aggressive behaviors and violent crime. In this study we examined, for the first time, the longitudinal effects over a 30-year period of average city greenness on homicide rates across 290 major cities in the US, using multilevel linear growth curve modeling. Overall, homicide rates in US cities decreased over this time-period (52.1–33.5 per 100,000 population) while the average greenness increased slightly (0.41–0.43 NDVI). Change in average city greenness was negatively associated with homicide, controlling for a range of variables (β = −.30, p-value = .02). The results of this study suggest that efforts to increase urban greenness may have small but significant violence-reduction benefits.

Description: Dezhou City is located in northwestern Shandong Province, China, and is rich in geothermal resources. Approximately 30% of the geothermal wells and geothermal heating areas of Shandong Province are located in Dezhou. A doublet-well layout geothermal system was completed by the Lubei Geo-engineering Exploration Institute for local winter heating, which has been in operation for 4 years. The wellbores penetrated the Guantao Formation with a well spacing of 180 m. This study aims to assess the heat extraction performance of the current well layout and predict the temperature evolution and lifespan. Furthermore, larger well spacing schemes were used in a simulation to test the heat supply potential and sustainability. In this study, the thermal conductivity and permeability were calibrated using in situ measured data from a field production test. A relatively high permeability layer was found between the depths of 1468 and 1536 m. The temperature remained stable in the first 6 years and then started to decrease. The recharging (injection) water tended to concentrate along the bottom highly permeable layer and accounted for over 64% of the outflow in the 100th year of the simulation test. The outflow temperature decreased from 53.9°C to 50°C in the 32nd year, making it less viable for subsequent sustainable exploitation. Hence, a larger well spacing is required for long-term operation based on the same geothermal reservoir. It was found that a spacing of 400 m could guarantee an outflow temperature above 50°C over a 100-year lifespan with an 80 m3/h pumping (production) rate. Moreover, the sustainability of the 600-m spacing was almost 2.5 times that of the 400 m case. The modeling and analysis method can be useful for the development and optimization of a doublet-well geothermal system under similar conditions.

Description: The sandstone reservoirs in the Upper Paleozoic He 8 Member in the northern Tianhuan depression of the Ordos Basin are vastly different and feature particularly complex gas–water distributions. Scanning electron microscopy, fluorescence, Raman spectroscopy inclusions, relative permeability analysis, and nuclear magnetic resonance were utilized in this study based on core data, identification statistics, and various thin-section microscope measurements. Samples from the Upper Paleozoic He 8 Member in the northern Tianhuan depression were collected to study the characteristics of reservoir heterogeneity and gas–water distribution, which were controlled by differential diagenesis. The results indicate that compaction and dissolution are the two most important factors controlling reservoir heterogeneity. Large differences in diagenesis–accumulation sequences and pore structure characteristics affect reservoir wettability, irreducible water saturation, and gas displacement efficiency, thereby controlling the gas–water distribution. The He 8 Member is a gas reservoir that is densified because of accumulation. Reservoirs can be divided into three types based on the relationship between diagenetic facies and gas–water distribution. Type I is characterized by weak compaction, precipitate or altered kaolinite cementation, strong dissolution of diagenetic facies, and high porosity and permeability. This type is dominated by grain-mold pores and intergranular dissolution pores and produces gas reservoirs with high gas yield. Type II is characterized by medium-strength compaction, altered kaolinite or chlorite cementation, weak dissolution of diagenetic facies, and medium porosity and permeability. This type is dominated by residual intergranular pores, a few residual intergranular pores, and dispersed dissolution pores, producing gas reservoirs with low gas yield. Type III is characterized by medium-strength compaction, altered kaolinite cementation, and medium-strength dissolution of diagenetic facies. This type is dominated by kaolinite intercrystal pores and dispersed dissolution pores, producing gas reservoirs with high water yield.

Description: Complex fracture networks are easily developed along the horizontal wellbore during hydraulic fracturing. The water phase increases the seepage resistance of oil in natural fractured reservoir. The flow regimes become more intricate due to the complex fractures and the occurrence of two-phase flow. Therefore, a semi-analytical two-phase flow model is developed based on the assumption of orthogonal fracture networks to describe the complicate flow regimes. The natural micro-fractures are treated as a dual-porosity system and the hydraulic fracture with complex fracture networks are characterized explicitly by discretizing the fracture networks into multiple fracture segments. The model is solved according to Laplace transformation and Duhamel superposition principle. Results show that seven possible flow regimes are described according to the typical curves. The major difference between the vertical fractures and the fracture networks along the horizontal wellbore is the fluid “feed flow” behavior from the secondary fracture to the main fracture. A natural fracture pseudo-radial flow stage is added in the proposed model comparing with the conventional dual-porosity model. The water content has a major effect on the fluid total mobility and flow capacity in dual-porosity system and complex fracture networks. With the increase of the main fracture number, the interference of the fractures increases and the linear flow characteristics in the fracture become more obvious. The secondary fracture number has major influence on the fluid feed capacity from the secondary fracture to the main fracture. The elastic storativity ratio mainly influences the fracture flow period and inter-porosity flow period in the dual-porosity system. The inter-porosity flow coefficient corresponds to the inter-porosity flow period of the pressure curves. This work is significantly important for the hydraulic fracture characterization and performance prediction of the fractured horizontal well with complex fracture networks in natural fractured reservoirs.

Description: It is crucial to obtain the representative relative permeability curves for related numerical simulation and oilfield development. The influence of temperature on the relative permeability curve remains unclear. An unsteady method was adopted to investigate the influence of temperature (range from 25–130 °C) on the oil–water relative permeability curve of sandstone reservoirs in different blocks. Then, the experimental data was analyzed by using an improved Johnson–Bossler–Naumann method. Results reveal that with the increase in temperature within a certain temperature range: (1) the relative permeability of the oil and water phases increases; (2) the irreducible water saturation increases linearly, whereas the residual oil saturation decreases nonlinearly, and the oil recovery factor increases; and (3) the saturation of two equal permeability points moves to the right, and hydrophilicity becomes stronger. The findings will aid future numerical simulation studies, thus leading to the improvement of oil displacement efficiency.

Description: The traditional stress arch hypothesis during longwall mining fails to elucidate the formation mechanism of stress arch, and the morphological characteristics and evolution of stress arch are indefinite. To solve these problems, a mechanical model was established for elucidating the formation mechanism of stress arch in overlaying strata. The influencing of key strata on the morphological characteristics of the stress arch was studied. Finally, the evolution of the stress arch during longwall mining was studied through numerical simulation. The results show that the bearing structure of the overlying strata served as the key strata, and the stress arch was formed when the key strata were subjected to deflection after playing a bearing structure role. This was the result of coordination and redistribution of major principal stress in the key strata. The morphological characteristics of the stress arch changed accordingly with the change in key strata. When the thickness of key strata and the distance between key strata and coal seam were gradually increased, the height and width of the stress arch increased accordingly; however, its height was always terminated at the top interface of key strata. At this time, the peak value of the abutment pressure of the working face gradually decreased while the influencing range gradually increased. During longwall mining, the stress arch developed upward by leaps and bounds with the bearing and fracture of key strata. When the overlying key strata were completely fractured, the stress arch disappeared. The results were verified using the field measurement data on the abutment pressure of the Y485 longwall face in Tangshan Mine.

Description: Automatic mining technology is the ideal path and the inevitable way to improve production efficiency, reduce labour intensity and ensure safety for thin coal seam. Recently, while automatic mining technology is increasingly applied in China for thin seams, the corresponding automatic cutting technology has made new advances. Among them, mnemonic cutting technology has been fruitful industrial tested with suitable conditions. Simultaneously, another one called cutting trace pre-set technology of the shearer has been put forward. Using this method, the cutting trace in the area with coal thickness changed and geological structures can be preset. What's more, self-adaptive regulation strategy of cutting trace based on coal-rock recognition by monitoring current of cutting motor was discussed. Then, the main problems and development trends of automatic mining in China was also proposed.

Description: In this study, Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) platforms were successfully applied to quantify the annual soil loss for the protection of soil erosion in Fincha catchment, Ethiopia. The key physical factors such as rainfall erosivity ( R-factor), soil erodibility ( K-factor), topographic condition (LS-factor), cover management ( C-factor), and support practice ( P-factor) were prepared in GIS environment from rainfall, soil, Digital Elevation Model (DEM), Land use/Land cover (LULC) respectively. The RUSLE equation was used in raster calculator of ArcGIS spatial tool analyst. The individual map of the derived factors was multiplied in the raster calculator and an average annual soil loss ranges from 0.0 to 76.5 t ha−1 yr−1 was estimated. The estimated annual soil loss was categorized based on the qualitative and quantitative classifications as Very Low (0–15 t ha−1 yr−1), Low (15–45 t ha−1 yr−1), Moderate (45–75 t ha−1 yr−1), and High (〉75 t ha−1 yr−1). It was found from the generated soil erosion severity map that about 45% of the catchment area was vulnerable to the erosion with an annual soil loss of (〉75 t ha−1 yr−1), and this demonstrates that the erosion reduction actions are immediately required to ensure the sustainable soil resources in the study area. The soil erosion severity map generated based on RUSLE model and GIS platforms have a paramount role to alert all stakeholders in controlling the effects of the erosion. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss protection practices.

Description: Source localisation is an important component in the application of wireless sensor networks, and plays a key role in environmental monitoring, healthcare and battlefield surveillance and so on. In this article, the source localisation problem based on time-of-arrival measurements in asynchronous sensor networks is studied. Because of imperfect time synchronisation between the anchor nodes and the signal source node, the unknown parameter of start transmission time of signal source makes the localisation problem further sophisticated. The derived maximum-likelihood estimator cost function with multiple local minimum is non-linear and non-convex. A novel two-step method which can solve the global minimum is proposed. First, by leveraging dimensionality reduction, the maximum (minimum) distance maximum (minimum) time-of-arrival matching-based second-order Monte Carlo method is applied to find a rough initial position of the signal source with low computational complexity. Then, the rough initial position value is refined using trust region method to obtain the final positioning result. Comparative analysis with state-of-the-art semidefinite programming and min–max criterion-based algorithms are conducted. Simulations show that the proposed method is superior in terms of localisation accuracy and computational complexity, and can reach the optimality benchmark of Cramér–Rao Lower Bound even in high signal-to-noise ratio environments.

Description: Climate change brings many changes in a physical environment like plants and leaves. The flowers and plants get affected by natural climate and local weather extremes. However, the projected increase in the frost event causes sensitivity in plant reproduction and plant structure vegetation. The timing of growing and reproduction might be an essential tactic by which plant life can avoid frost. Flowers are more sensitive to hoarfrost than leaves but more sensitive to frost in most cases. In most cases, frost affects the size of the plant, its growth, and the production of seeds. In this article, we examined that how frost affects plants and flowers? How it affects the roots and prevents the growth of plants, vegetables, and fruits? Furthermore, we predicted how the frost will grow and how we should take early precautions to protect our crops? We presented the convolutional neural network model framework and used the conv1d algorithm to evaluate one-dimensional data for frost event prediction. Then, as part of our model contribution, we preprocessed the data set. The results were comparable to four weather stations in the United States. The results showed that our convolutional neural network model configuration is reliable.