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Shale gas, mainly consisting of adsorbed gas and free gas, has served a critical role of supplying the growing global natural gas demand in the past decades. Considering that the adsorbed methane has contributed up to 80% of the total gas in place (GIP), understanding the methane adsorption behaviors is imperative to an accurate estimation of total GIP. Historically, the single-site Langmuir model, with the assumption of a homogeneous surface, is commonly applied to estimate the adsorbed gas amount. However, this assumption cannot depict the methane adsorption characteristics due to various compositions and pore sizes of shales. In this work, a multi-site model integrating the energetic heterogeneity in adsorption is derived to predict methane adsorption on shale. Our results show that the multi-site model is capable of addressing the heterogeneity of shales by a wide range of adsorption energy distributions (owing to the complex compositions and different pore sizes), which is different from the single-site model only characterized by single adsorption energy. Consequently, the multi-site model results have better accuracy against the experimental data. Therefore, applying the multi-site Langmuir model for estimating GIP in shales can achieve more accurate results compared with using the traditionally single-site model.

Expansive soil is widely distributed and often needs to be improved for engineering and construction needs. Using blast furnace slag and fly ash as precursors and NaOH as an alkali activator, a geopolymer was prepared to solidify expansive soil, and the effect of nano-SiO2 on the compressive strength and water stability of the geopolymer-solidified expansive soil was further studied. The effects of alkali addition ratio, nano-SiO2 addition ratio, and curing agent addition ratio on the unconfined compressive strength and water stability of the cured soil were studied through unconfined compressive strength tests, and the curing mechanism was analyzed by electron microscopy scanning. The experimental results showed that the unconfined compressive strength and water stability of geopolymer-stabilized soil first increased and then decreased with an increase in alkali activator dosage. The optimal dosage of alkali activator was found to be 12.5%. Furthermore, it was found that adding nano-SiO2 can further enhance the strength and water stability of solidified soil. When the content of nano-SiO2 was 3%, the unconfined compressive strength was increased by 15%. With an increase in the content of nano-SiO2 doped polymer (GFNS), the unconfined compressive strength and water stability of the solidified soil showed a trend of first increasing and then decreasing, reaching a peak at a content of 20%. The cementitious materials, such as hydrated calcium silicate and hydrated calcium silicate aluminate, generated by the reaction between nano-SiO2 and geopolymer played a role in bonding and filling in the solidified soil. Under the joint action of the two, the structural arrangement between the solidified soil particles became more compact, which improved the strength of the solidified soil.

The annual co-circulation of two influenza A subtypes, H1N1 and H3N2, viruses in humans poses significant public health threats worldwide. However, the continuous antigenic drift and shift of influenza viruses limited the effectiveness of current seasonal influenza vaccines, necessitating the development of new vaccines against both seasonal and pandemic viruses. One potential solution to this challenge is to improve inactivated vaccines by including multiple T-cell epitopes. In this study, we designed stabilized trimeric recombinant mosaic HA proteins named HAm, which contain the most potential HA T-cell epitopes of seasonal influenza A virus. We further evaluated the antigenicity, hemagglutinin activity, and structural integrity of HAm and compared its immunogenicity and efficacy to a commercial quadrivalent inactivated influenza vaccine (QIV) in mice. Our results demonstrated that the HAm vaccine was able to induce broadly cross-reactive antibodies and T-cell responses against homologous, heterologous, and heterosubtypic influenza-naive mice. Additionally, the HAm antigens outperformed QIV vaccine antigens by eliciting protective antibodies against panels of antigenically drifted influenza vaccine strains from 2009 to 2024 and protecting against ancestral viruses’ lethal challenge. These results suggest that the HAm vaccine is a promising potential candidate for future universal seasonal and pandemic influenza vaccine development.

Understanding the mechanisms of snap-off during gas–liquid immiscible displacement is of great significance in the petroleum industry to enhance oil and gas recovery. In this work, based on the original pseudo-potential lattice Boltzmann method, we improved the fluid–fluid force and fluid–solid force scheme. Additionally, we integrated the Redlich–Kwong equation of state into the lattice Boltzmann model and employed the exact difference method to incorporate external forces within the lattice Boltzmann framework. Based on this model, a pore–throat–pore system was built, enabling gas–liquid to flow through it to investigate the snap-off phenomenon. The results showed the following: (1) The snap-off phenomenon is related to three key factors: the displacement pressure, the pore–throat length ratio, and the pore–throat width ratio. (2) The snap-off phenomenon occurs only when the displacement pressure is within a certain range. When the displacement pressure is larger than the upper limit, the snap-off will be inhibited, and when the pressure is less than the lower limit, the gas–liquid interface cannot overcome the pore–throat and results in a “pinning” effect. (3) The snap-off phenomenon is controlled using the pore–throat structures: e.g., length ratio and the width ratio between pore and throat. It is found that the snap-off phenomenon could easily occur in a “long-narrow” pore–throat system, and yet hardly in a “short-wide” pore–throat system.

Stable communication technologies in complex waters are a prerequisite for underwater operations. Underwater acoustic communication is susceptible to multipath interference, while underwater optical communication is susceptible to environmental impact. The underwater electric field communication established based on the weak electric fish perception mechanism is not susceptible to environmental interference, and the communication is stable. It is a new type of underwater communication technology. To address issues like short communication distances and high bit error rates in existing underwater electric field communication systems, this study focuses on underwater electric field communication systems based on direct sequence spread spectrum (DSSS) and binary phase shift keying (BPSK) modulation techniques. To verify the feasibility of the established spread spectrum electric field communication system, static communication experiments were carried out in a swimming pool using the DSSS-based system. The experimental results show that in fresh water with a conductivity of 739 μS/cm, the system can achieve underwater current electric field communication within a 11.2 m range with 10−6 bit errors. This paper validates the feasibility of DSSS BPSK in short-range underwater communication, and compact communication devices are expected to be deployed on underwater robots for underwater operations.

The rise of omics research, spanning genomics, transcriptomics, proteomics, and epigenomics, has revolutionized our understanding of biological systems [...]

At present, the traditional control strategy of heating systems is still unable to achieve building heating on demand, which enhances the energy consumption of heating and affects the thermal comfort of buildings. Therefore, this study puts forward a novel data-driven MPC for building thermal inlet, which allows the optimal operation of the district heating system and has been verified by simulation with three public buildings. In this method, the indoor temperature at the next moment reaches the temperature set value by changing the current flow rate. First, based on the energy consumption monitoring platform and the measured data of the buildings, the building indoor temperature prediction model at the next moment is established by using long short-term memory (LSTM). Compared with subspace model identification (SMI), LSTM has higher prediction accuracy, and the R2 was about 0.9 in three buildings. Second, the particle generated by particle swarm optimization, which represents the flow variation, is input to the trained LSTM to predict the indoor temperature. By minimizing the objective function, the optimal flow change at the current time can be calculated. The results showed that the MPC based on a data-driven model can adjust the flow rate in time to maintain a stable indoor temperature with ±0.5 °C error. In addition, when the temperature setting needs to be changed, the indoor temperature can reach the new set value in 3 h, which outperforms the PID control. The method proposed in this paper can greatly reduce the influence of regulation lag by adjusting the flow in advance.

Rapid urbanization with unreasonable human disturbances has caused a serious ecological crisis. By constructing an ecological-security pattern (ESP), key landscape elements can be effectively identified. ESP optimization helps to improve a city’s ecosystem services and achieve the harmonious development between man and nature. Therefore, it is crucial to construct an accurate ESP and propose practical ESP optimization strategies. Taking Liyang City as an example, this paper first constructed the ESP with a combination methodology of circuit theory, graph theory, the granularity-reverse method, and the comprehensive-evaluation method. Then, strategies for ESP optimization were proposed in terms of ecological restoration and ecological source promotion. Finally, the optimized ESP was verified by quantitative assessment involving landscape connectivity and network structure. Research results show that the current ESP includes 24 ecological sources, 41 ecological corridors, and 50 ecological nodes that need ecological restoration. In the optimized ESP, 31.5 km2 of ecological land is added, 3 ecological sources are added, 55 ecological corridors are generated, and the number of nodes in the ecological network is increased by 4. By comparing the evaluation results before and after optimization, it can be seen that the optimization scheme has a positive effect on landscape connectivity and ecological coordination of the whole region.

The imbibition phenomenon widely exists in nature and industrial applications. It is of great significance to study the mechanism of imbibition and the influence laws of related factors. In this paper, based on the assumption of interacting capillaries, a capillary bundle model of counter-current imbibition is established. In addition, the characteristics of imbibition and the influences of capillary size and fluid viscosity are analyzed. The results show that water is imbibed into the smaller capillaries and expelled from the larger capillaries. The rate of the meniscus in water-imbibition capillaries is proportional to the square root of time. In the interacting capillaries, oil production by counter-current imbibition decreases and then increases gradually with the increase of the capillary diameter difference. When the total cross-sectional area of the capillary remains unchanged, the cross-sectional area of the total water-imbibition capillaries is affected by the size distribution of the capillaries. The larger the viscosity of the non-wetting phase, the more uneven the imbibition front, the lower the imbibition efficiency. The higher the viscosity of the wetting phase, the more uniform the imbibition front, and the higher the imbibition efficiency.

Recently, the spatial contradiction in rural construction has intensified. Production–living–ecological (PLE) spaces, as important load-bearing spatial patterns of rural revitalization, have become a research focus of territorial space planning. Because of the lack of studies on the scale and accuracy at the township level in rural PLE spaces, the objective of this study is to quantify the subfunctional and functional areas of PLE spaces, weigh the relationship between PLE functions, and conduct feature identification and strategy formulation of the PLE synergistic functional areas. Combined with multitype measurement methods, the study constructed a township-level PLE space evaluation system composed of 12 subfunctional indicators. Taking Guli Street in Nanjing city as an example, Spearman correlation analysis, spatial local autocorrelation analysis, and cold/hot spot identification were used to analyze the synergies and tradeoffs between PLE functions. On this basis, the evaluation model of the PLE synergies area was constructed. The results showed that the production function showed a fragmented distribution pattern. The proportion of high-intensity living function areas was very small. The ecological function area had good patch integrity. In the PLE functions, obvious synergies exist between any two functions, and the tradeoff between the third one and any of the two functions. The seven types of PLE synergistic potential areas were dominated by the dual-function high synergistic zone (DF-H-Z). The zoning scheme and governance strategy proposed in this paper have important practical value for solving the contradiction of sustainable and coordinated development of township-scale spatial resources.

Shale reservoirs are rich in nanoscale pore-microfractures, and generally contain water (especially inorganic pores) under reservoir conditions. Therefore, evaluating gas flow capacity under water-bearing conditions is of great significance for analyzing reservoir capacity and forecasting production. Based on the single-phase gas transfer theory in nanopores, we established a gas transport model in both circular pores and slit pores by considering pore-fracture patterns of actual samples. As will be shown, inorganic pore fractures are mostly slit-type, while organic pores are mostly circular. This gas transport model also uses weighting coefficients superimposed on slip flow and molecular free flow. Further, the effect of water saturation on gas flow is quantified by considering the distribution characteristics of inorganic and organic pores in shale and also by combining the pore distribution characteristics of actual samples. The flow characteristics of gas in organic and inorganic pores under water-bearing conditions in the reservoir are further compared. The study lays a theoretical foundation for the reasonable evaluation and prediction of shale gas well capacity under reservoir water conditions.

In recent years, the “coal to electricity” project (CTEP) using clean energy instead of coal for heating has been implemented by Beijing government to cope with air pollution. However, VOC pollution after CTEP was rarely studied in suburbs of Beijing. To fill this exigency, 116 volatile organic compounds (VOCs) were observed during nonheating (P1) and heating (P2) periods in suburban Beijing. The results showed that the total of VOCs (TVOCs) was positively correlated with PM2.5, PM10, NO2, CO, and SO2 but negatively correlated with O3 and wind speed. The average TVOCs concentration was 19.43 ± 12.41 ppbv in P1 and 16.25 ± 8.01 ppbv in P2. Aromatics and oxygenated VOCs (OVOCs) were the main contributors to ozone formation potential (OFP). Seven sources of VOCs identified by the positive matrix factorization (PMF) model were industrial source, coal combustion, fuel evaporation, gasoline vehicle exhaust, diesel vehicle exhaust, background and biogenic sources, and solvent usage. The contribution of coal combustion to VOCs increased significantly during P2, whereas industrial sources, fuel evaporation, and solvent usage exhibited opposite trends. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were used to analyze the source distributions. The results showed that VOC pollution was caused mainly by air mass from southern Hebei during P1 but by local emissions during P2. Therefore, although the contribution of coal combustion after heating increased, TVOCs concentration during P2 was lower than that during P1. Chronic noncarcinogenic risks of all selected VOC species were below the safe level, while the carcinogenic risks of most selected VOC species were above the acceptable risk level, especially for tetrachloromethane and 1,2-dichloroethane. The cancer risks posed by gasoline vehicle emissions, industrial enterprises, and coal combustion should be paid more attention.

Permanent magnet torque motor (PMTM) is widely used in aerospace, computer numerical control (CNC) machine tools, and industrial robots with many advantages such as high torque density, strong overload capacity, and low torque ripple. With the upgrading of industrial manufacturing, the requirements for the performance of torque motors have become more stringent. At present, how to achieve high output torque and low torque ripple has become a research hotspot of torque motors. In the optimization process, it is necessary to increase the output torque while the torque ripple can be reduced, and it is difficult to get a good result with the single-objective optimization. In this paper, a multi-objective optimization method based on the combination of design parameter stratification and support vector machine (SVM) is proposed. By analyzing the causes of torque ripple, the output torque, efficiency, cogging torque, and total harmonic distortion (THD) of back electromotive force (EMF) are selected as the optimization objectives. In order to solve the coupling problem between the motor parameters, the calculation formula of Pearson correlation coefficient is used to analyze the relationship between the design parameters and the optimization objectives, and the design parameters are layered ac-cording to the sensitivity. In order to shorten the optimization cycle of the motor, SVM is used as a fitting method of the mathematical model. The performance between initial and optimal motors is compared, and it can be found that the optimized motor has a higher torque and lower torque ripple. The simulation results verify the effectiveness of the proposed optimization method.

Semantic Web has recently gained traction with the use of Linked Open Data (LOD) on the Web. Although numerous state-of-the-art methodologies, standards, and technologies are applicable to the LOD cloud, many issues persist. Because the LOD cloud is based on graph-based resource description framework (RDF) triples and the SPARQL query language, we cannot directly adopt traditional techniques employed for database management systems or distributed computing systems. This paper addresses how the LOD cloud can be efficiently organized, retrieved, and evaluated. We propose a novel hybrid approach that combines the index and live exploration approaches for improved LOD join query performance. Using a two-step index structure combining a disk-based 3D R*-tree with the extended multidimensional histogram and flash memory-based k-d trees, we can efficiently discover interlinked data distributed across multiple resources. Because this method rapidly prunes numerous false hits, the performance of join query processing is remarkably improved. We also propose a hot-cold segment identification algorithm to identify regions of high interest. The proposed method is compared with existing popular methods on real RDF datasets. Results indicate that our method outperforms the existing methods because it can quickly obtain target results by reducing unnecessary data scanning and reduce the amount of main memory required to load filtering results.

Among sub-items of energy consumption in public buildings, lighting sockets play an important role in energy-saving analysis. So, the energy consumption data quality of lighting sockets is important. However, limited by the initial cost of energy monitoring platform, it is difficult to install electricity meters covering all branches and to retrofit the incompact classification electricity branches, which results in a mixture of the lighting socket energy consumption and other components. In this study, a separation methodology is proposed. First, the abnormal data in the energy monitoring platform are cleaned and screened using a clustering algorithm. Second, the average outdoor air temperature partitioning model (OATPM) method and the k-nearest neighbor (KNN) clustering algorithm method are proposed for identifying and separating the abnormal data. These two methods have complementary advantages in the best applicable scenarios, including calculation accuracy and other aspects. The verification results for three buildings show that the relative error of this separation methodology is less than 15%. Finally, this paper presents the optimization parameters of the KNN method. Through this methodology, building managers need only historical data in an energy monitoring platform to separate the combined power consumption of the lighting sockets and air-conditioning online, independent of detailed information statistics.