As one of the critical state parameters of the battery management system, lithium battery state of charge (SOC) can provide an essential reference for battery safety management, charge/discharge control, and energy management of electric vehicles. To analyze the application of deep learning in electric vehicle power battery SOC estimation, this study reviewed the technical process, common public datasets, and the neural networks used, structural characteristics, advantages and disadvantages of lithium battery SOC estimation in deep learning method. First, the specific technical processes of the deep learning method for SOC estimation were analyzed, including data collection, data preprocessing, feature engineering, model training, and model evaluation. Secondly, the current commonly and publicly used lithium battery dataset was summarized. Then, the input variables, data sets, errors, and advantages and disadvantages of four types of deep learning methods, were concluded using the structure of neural network used for training as the classification criterion. Finally, the challenges and future development directions of lithium battery SOC estimation in deep learning method were explained.

Both in lung adenocarcinoma (LUAD) and severe acute respiratory syndromes (SARS) uncontrolled inflammation could be detected in lung tissue. Whether the similarity mechanism exists is still unknown. PDZ-binding motif (PBM) in SARS-CoV E protein has been demonstrated as virulence factor induce inflammation storm. Study function of PBM in LUAD is significant for mechanism exploration of carcinogenesis mediated by SARS-CoV. To identify gene expression fluctuation induced by PBM, a microarray sequencing data of lung tissue infected by wild type (SARS-CoV-E-wt) and recombinant virus (SARS-CoV-E-mutPBM) was analysis followed by functional enrichment analysis. To understand the role of screened specific genes in LUAD, overall survival and immune correlation were calculated. A total of 12 genes (MAPK1, PRKCA, FGFR4, KDR, PTPRD, BCL2L15, UBD, MAMDC2, LTBP4, PTPRB, LGI3 and ITGA8) might participate in initial and development stage of LUAD through expression variation and mutation. Meanwhile, a total of 12 genes (CARHSP1, EIF4E2, HMGA1, IL1R2, MAGOHB, PVR, ADCY9, ELF5, ESYT3, SCML4, SECL14L4 and THRA) could lead to poorer prognosis via dysregulation. In addition, MAMDC2 and ITGA8 down-regulated by PBM could also alter prognosis. Though the conservative PBM (-D-L-L-V-) could be found at the end of carboxyl terminal in multi E proteins of coronaviruses, the specific function of each one depend on the whole amino acid sequence simultaneously. In conclusion, PBM of SARS-CoV E protein could promote carcinogenesis of LUAD by dysregulating important gene expression profiles followed by influence immune response and overall prognosis. The results in present study also provided reference for the therapy of SARS-CoV-2 in LUAD patients.

3,4-Dihydroquinolin-2(1H)-ones represent a class of valuable bioactive compounds with six-membered nitrogen-containing heterocyclic structures. The development of simple, mild and efficient synthetic methods has been widely concerned by synthetic chemists. In this review, we have summarized a series of different synthetic strategies for the synthesis of dihydroquinoline-2(1H)-ones via catalytic annulation of α,β-unsaturated N-arylamides in the past decade, including covering electrophilic cyclization, radical initiated cyclization and photochemical cyclization reactions. Besides, the substrate scope and mechanistic details are also discussed. This paper will provide a useful reference for the development of diverse synthesis methodologies of 3,4-dihydroquinolin-2(1H)-ones.

MoS2 lithium-based grease is suitable for lubrication protection between bearings at high temperatures and loads due to its excellent tribological properties. However, there is little research on the influence of different addition methods of MoS2 additive on the tribology and corrosion properties of lithium grease. In this work, vegetable oil with low toxicity, high biodegradation rate, and low cost was selected as the base oil, lithium 12-hydroxystearate as the thickener, and MoS2 as the additive. The effects of different adding modes of MoS2 on the tribology and corrosion properties of lithium grease were studied. The experimental results showed that adding 0.01wt% MoS2 before thickening was more conducive to improving the tribological properties of lithium grease. The average friction coefficient was 0.034, and the average spot diameter was reduced by 0.16mm. After grinding and adding 0.01wt% MoS2, the corrosion inhibition efficiency of the steel sheet was as high as 96.97%. The main reason was that the longer stirring and grinding were conducive to the uniform distribution of MoS2 in the grease, and the protective film formed by MoS2 and GCr15-bearing steel improved the lubrication performance and corrosion inhibition performance of the friction system.

Pneumonia remains a major cause of morbidity and mortality worldwide, especially during COVID-19 pandemic. With the significant global health burden that pneumonia poses, it is es-sential to improve therapeutic and management strategies. The increasing emergence of antibiotic resistant bacterial strains limits options for effective antibiotic use. New antibiotics for treatment of pneumonia may address deficits in current antimicrobial drugs, with an ability to cover both typical, atypical, and resistance pathogen. Several of these newer drugs also have structural characteristics that allow for a decreased propensity in development of bacterial resistance. Po-tential use of stem cell therapies in place of corticosteroid treatments may also offer an im-provement in patient outcomes. Human mesenchymal stem cell treatments have shown efficacy and safety in treating COVID-19 induced pneumonia. Combined treatment with both stem cells and antibiotics in pneumonia in a rabbit model has also shown significantly increased efficacy in comparison to antibiotic treatment alone, presenting yet another possible route for a novel strategy in treating pneumonia, though additional future studies are necessary before clinical implementation. While pneumonia remains a major disease of concern, having newer approved antibiotics as well as novel therapies such as stem cell treatments in the pipeline offers clinicians more options in effectively treating pneumonia.

Both lung adenocarcinoma and SARS-CoV-2 infection could cause pulmonary inflammation. Angiotensin-converting enzyme 2, not only as the functional receptor of SARS-CoV-2 but also play key role in lung adenocarcinoma. To study the risk of SARS-CoV-2 infection in lung adenocarcinoma patients, mRNA and miRNA profiles were obtained from TCGA and GEO databases followed by bioinformatics analysis. A regulatory network which regards angiotensin-converting enzyme 2 as the center would be structured. In addition, via immunological analysis about key factors in lung adenocarcinoma patients, to explore the essential reasons for the susceptibility of SARS-CoV-2. Compared with normal tissue, angiotensin-converting enzyme 2 was increased in lung adenocarcinoma patients. Furthermore, a total of 7 differently expressed correlated mRNAs (ACE2, CXCL9, MMP12, IL6, AZU1, FCN3, HYAL1 and IRAK3) and 5 differently expressed correlated miRNAs (miR-125b-5p, miR-9-5p, miR-130b-5p, miR-381-3p and miR-421) were screened followed by enrichment analysis. Interestingly, toll-like receptor signaling pathway with the most frequent occurrence was enriched by mRNA (IL6) and miRNA (miR-125b-5p) sets simultaneously. Finally through comprehensive analysis, it was assumed that miR-125b-5p-ACE2-IL6 axis in the structured regulatory network could alter risk of SARS-CoV-2 infection in lung adenocarcinoma patients.

In this study, three new demountable joints consisting of reinforced concrete columns and steel beams were proposed and their seismic performance was investigated using cyclic loading tests. The test results demonstrated that the three demountable RCS joints had good seismic performance. Using the finite element software ABAQUS, the influence of parameters such as beam flange thickness, bolt strength, and connector steel strength on the seismic performance of each joint was analyzed, and the influence of different parameters on the seismic behavior of the joint was determined. The results also showed that the three demountable RCS joints were sensitive to changes in the thickness of the steel beam flange, while the connector steel strength and bolt type had little impact on the joint's capacity. Additionally, shear capacity calculation formulas for the joint core area provided by different codes and researchers were compared with test and finite element results. The results showed that the calculation results of the ASCE guidance method, the Nishiyama method, and the CECS 347-2013 method were higher than the test values, while the calculation results of the Para method were lower because it did not consider the contribution of the cylindrical steel plate to the shear capacity of the joint core area.

Flaviviruses cause a significant amount of mortality and morbidity, especially in the area where they are endemic. A recent example is the outbreak of Zika virus though out the world. Development of antiviral drugs against different viral targets is as important as development of vaccine. During viral replication, the flavivirus genome is translated as a single polyprotein precursor, which must be cleaved into individual proteins by a complex of the viral protease, NS3, and its cofactor, NS2B. Flavivirus protease is the most attractive target for development of therapeutic antivirals because it is essential for processing of viral polyprotein precursor and generation of functional viral proteins. In this review, we have summarized recent development in drug discovery targeting NS3-NS2B protease of flaviviruses, especially Zika, dengue and West Nile virus.

The development of U.S. Army and NATO data link systems is introduced first, and then the development trend of future intelligent data link is summarized into integration, generalization, multifunctionality and high security. A unit-level combat system architecture based on the global combat cloud, which is capable of realizing the flexible scheduling of global combat resources and maximizing the overall combat effectiveness, is proposed. Intelligent data link is an important part of this solution, providing strong information support for future urban unit-level warfare.

Drug-target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited, failing to delve into the structural nuances of interactions. With increasingly accurate and accessible structure prediction of targets, we developed a novel deep learning model, named S2DTA, to accurately predict DTA by fusing sequence and structural knowledge of drugs, targets, and pockets using heterogeneous models based on graph and semantic networks. Experimental findings underscored that complex feature representations imparted negligible enhancements to the model’s performance. However, the integration of heterogeneous models demonstrably bolstered predictive accuracy. In comparison to three state-of-the-art methodologies, the supremacy of S2DTA became strikingly apparent. It showcased a noteworthy 25.2% reduction in Mean Absolute Error (MAE) and an impressive 20.1% decrease in Root Mean Square Error (RMSE). Furthermore, S2DTA exhibited substantial advancements in other pivotal metrics, including Pearson Correlation Coefficient (PCC), Spearman, Concordance Index (CI), and R2. These metrics experienced remarkable increments of at least 19.6%, 17.5%, 8.1%, and a remarkable 49.4%, respectively. Finally, we conducted interpretability analysis on the effectiveness of S2DTA by bidirectional self-attention mechanism, fully proving that S2DTA is a valuable and accurate tool for predicting DTA. For further exploration, the source data and code repository can be accessed at https://github.com/dldxzx/S2DTA.

Amid the swift progression of the global automobile industry, the aspiration for lightweight vehicle design has surfaced as a crucial approach to boost fuel efficiency and curtail environmental impact. The objective of this study revolves around achieving holistic optimization of vehicle structure via detailed scrutiny of vehicle process characteristics, amalgamated with a Back Propagation neural network (BPNN) optimized by a genetic algorithm (GA) and a topology optimization (TO) method.The process initiates with an examination of the vehicle's technical characteristics, succeeded by an optimization protocol that couples GA with BPNN. This exhaustive optimization procedure derives the best-fit values of design parameters and identifies the globally optimal lightweight design approach. Subsequently, a comprehensive structural optimization is actualized by modifying the topological distribution of the structure.A simulation experiment of the conceptual car body beam skeleton is conducted as a conclusive step, and the anti-collision capacity of the car body beam skeleton is assessed by measuring deformation intrusion. The findings reveal that in the vehicle topology optimization, a comparative analysis of pre and post-optimization results indicates an improved topological density across diverse sections. The topological density of the vehicle's frontal structure escalates from 0.75 to 0.8. Following optimization, the stiffness assessment records a marginal increase (within the range of 0.02–0.05), implying that the lightweight design does not compromise the general rigidity of the structure.The optimized body structure manifests superior crashworthiness in the crash test: the deformation intrusion diminishes by 27% in front-end collisions. In side impacts, the deformation and intrusion at critical points are reduced by 13.15% to 10% respectively. The comprehensive method proposed herein proves to be an efficient strategy to actualize the lightweight design of vehicles.

This paper reports a new global Mittag-Leffler synchronization criterion with regard to fractional-order hyper-chaotic financial systems by designing the suitable impulsive control and the state feedback controller. The significance of this impulsive synchronization lies in the fact that the backward economic system can synchronize asymptotically with the advanced economic system under the effective impulse macroeconomic management means. Matlab LMI-toolbox is utilized to deduce the feasible solution in numerical example, which shows the effectiveness of the proposed methods. It is worth mentioning that the LMI-based criterion usually requires the activation function of the system to be Lipschitz, but the activation function in this paper is fixed and truly nonlinear, which cannot be assumed to be Lipschitz continuous. This is another mathematical difficulty overcome in this paper.

Electro-mechanical braking(EMB) which represents development direction of autonomous and intelligent braking plays very useful role on enhancing the braking response performance and intelligence level for mine underground electric trackless rubber-tired vehicle (ETRV). However,there is no Electro-Mechanical Brake system applied practically in coal mine UTRV until now.The accurate control of braking clamping force can determine the length and precision of braking distance of mine ETRV.In addition,because of poor working conditions in underground coal mine tunnel ,braking clamping force sensor may be easy to occur failure,which may cause vital accident.Therefore,A cascaded three-closed-loop EMB system with a positive clamping force sensor or force estimator built for ETRV is established to achieve autonomous elimination and reset of braking clearance and reliable braking force tracking ability via utilizing the electro motor rotor angle displacement and hysteresis effect of mechanical components in this EMB.The results of simulation and experiment indicate that clamping force response is faster than traditional hydraulic disk braking system and proposed force estimator presents good fault-tolerant ability when sensor is fault.This EMB can replace the current hydraulic brake system to enhance automation level of braking control for ETRVs and braking force response performance, reduce oil pollution and cost of maintenance, which is also key technology support for really precise motion control of mine autonomous driving vehicles.

Hydrogen sulfide (H₂S) is a novel gasotransmitter, sucrose (SUC) is both cellular energy and signaling molecule. However, their signaling interaction in maize thermotolerance is poorly known. In this study, using maize seedlings as materials, metabolic and functional interaction of H₂S and SUC in maize thermotolerance was investigated. Data show that under heat stress survival rate and tissue viability were increased by exogenous SUC, while malondialdehyde content and electrolyte leakage were decreased by SUC, indicating SUC could upraise maize thermotolerance. Also, SUC-upraised thermotolerance was enhanced by H₂S, while weakened by inhibitor (propargylglycine) and scavenger (hypotaurine) of H₂S and SUC-transport inhibitor (N-ethylmaleimide). To figure out underlying mechanism of H₂S-SUC interaction-upraised thermotolerance, redox parameters in mesocotyls of maize seedlings were measured before and after heat stress. The data display that activity and gene expression of H₂S-metabolizing enzymes were up-regulated by SUC, whereas H₂S had no significant effect on activity and gene expression of SUC-metabolizing enzymes. Besides, activity and gene expression of catalase, glutathione reductase, ascorbate peroxidase, peroxidase, dehydroascorbate reductase, monodehydroascorbate reductase, and superoxide dismutase were reinforced by H₂S, SUC, and their combination under non-heat and heat conditions in varying degrees. Similarly, content of ascorbic acid, flavone, carotenoid, and polyphenol was increased by H₂S, SUC, and their combination, whereas production of superoxide radical and hydrogen peroxide level were impaired by these treatments to different extent. These results imply that the metabolic and functional interaction of H₂S and sucrose exists in the formation of maize thermotolerance through redox homeodynamics.

Imidacloprid, a neonicotinoid, has proven as efficacious against hemipterans including the brown planthopper, Nilaparvata lugens (Stål). Frequent use, however, has resulted in high levels of resistance to imidacloprid among brown planthopper populations. Endosymbionts of insects are important for host insect growth and development and seem to play a role in resistance to imidacloprid. In this study, polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE) was used to analyze the bacterial and yeast-like-symbiont communities of imidacloprid-resistant and imidacloprid-susceptible brown planthopper populations. The Shannon-Weaver diversity index and the evenness index indicated that there were no differences in the composition of the symbiotic communities of resistant and susceptible with a similarity coefficient of 0.53 for bacterial symbionts and 0.56 for yeast-like symbionts for the two planthopper populations. Sequence comparison analysis showed that the numbers of bacterial species in the imidacloprid-resistant versus the imidacloprid-susceptible populations were not significantly different. The bacterial species in the susceptible population were members of the Enterobacteriaceae and Moraxellaceae, while these in the resistant population were members of the Enterobacteriaceae, Oxalobacteriaceae, Rhodobacteriaceae, and Sphingomonadaceae. The imidacloprid-susceptible population had more yeast-like symbiont species than the resistant population.

We attempted to apply the optoelectronic sensor entitled 'OPT101' in intensive care unit clinics, based on its optoelectronic response characteristics in near-infrared wavelength range and near-infrared spectroscopy principle. The successful novel applications in our lab include early-diagnosis and therapeutic effect tracking of thrombus, noninvasive monitoring of patients' shock severity, and fatigue evaluation. This study also expects further improvements of the detector in noninvasive clinical applications.

Metabolites present in the hemolymph of honey bees play a crucial role in modulating the metamorphic process within the species. However, the precise alterations in metabolite composition, along with the associated variances and regulatory pathways implicated during the larvae-to-pupae metamorphosis of honey bees, remain incompletely elucidated. In this investigation, we gathered hemolymph samples from honey bee larvae at three distinct physiological stages-feeding, prepupal, and pupae and subjected them to metabolite analysis utilizing the liquid chromatography-mass spectrometry (LC-MS) technique. Employing principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), we identified significant differential metabolites and conducted a metabolic pathway analysis on those differentially up-regulated during the prepupal and pupae stages. Notably, metabolites up-regulated in the hemolymph of prepupal stage larvae primarily governed glucose metabolism and fat digestion and absorption, while those in pupae stage larvae were involved in regulating chitin and lipopolysaccharide precursor formation, as well as the biosynthesis of phenylalanine, tyrosine, and tryptophan. These findings bear significant implications for advancing our comprehension of the metamorphic processes in honey bees.

Deformation monitoring is beneficial to ensure the service safety of long tunnel. An three-direction (vertical, transverse and axial) deformation estimation method using long-gauge fiber Bragg grating (FBG) sensing technology is proposed and applied to a long tunnel by integrating mechanical analysis and field monitoring during the service state. The key issues of the proposed method for identifying the three-direction deformation are discussed, such as establishing the separation model of coupling strain on cross section, deriving the theory of deformation identification in three directions, and determining the sensor layout of the long tunnel. A major advantage of the proposed method is that the three-direction deformation of the tunnel can be monitored in real time using distributed long-gauge strain sensors. The numerical analysis and field test results verify the feasibility of the proposed method.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

Climate and its fluctuations have wide-ranging impacts on the tourism industry. High temperatures, as a typical meteorological and climatic factor, influence tourists' travel intentions and spatial behavior. This study conducted a descriptive analysis and market trend analysis of Chinese tourism during periods of high temperatures, revealing several key findings. Firstly, tourists seeking respite from summer heat exhibit a preference for short-distance trips and resource-rich destinations. Secondly, heat-escape tourism products undergo changes over time, gradually shifting towards mountainous areas and waterfront locations. Furthermore, taking Shanghai Disneyland as a case study demonstrates that the holiday system holds greater significance than temperature constraints. Despite experiencing a significant decline in the quality of their tourist experience in high-temperature environments, long-distance travelers are not deterred from choosing pre-booked tourism products by sudden bouts of hot weather.

Chickens have extensive phenotypic variation. The Wuhua yellow chicken (WHYC) is an important traditional yellow-feathered chicken in China, characterized by white tail feathers, white flight feathers, and strong disease resistance. However, the genomic basis of traits associated with WHYC is still poorly understood. In this study, whole genome resequencing was performed with an average coverage of 20.77-fold to investigate heritable variation and identify selection signals in WHYC. Reads were mapped onto the chicken reference genome (Galgal5) with a coverage of 85.95%. After quality control, 11,953,471 SNPs and 1,069,574 InDels were obtained. In addition, 41,408 structural variants and 33,278 copy number variants were found. A comparative genomic analysis of WHYC and other yellow-feathered chicken showed that selected regions were enriched in genes involved in transport and catabolism, immune system, infectious diseases, signal transduction, and signaling molecules and interaction. Several genes associated with disease resistance were identified, including IFNA, IFNB, CD86, IL18, IL11RA, VEGFC, and ATG10. Furthermore, PMEL and TYRP1 may contribute to the coloring of white feathers in WHYC. These findings improve our understanding of the genetic characteristics of WHYC and may contribute to future breed improvement.

A low-cost bio-mass-derived carbon substrate has been employed to synthesize MoS₂@carbon composites through a hydrothermal method. Carbon fibers derived from natural cotton provide a three-dimensional and open framework for the uniform growth of MoS₂ nanosheets, thus constructing hierarchically coaxial architecture. The unique structure could synergistically benefit fast Li-ion and electron transport from the conductive carbon scaffold and porous MoS₂ nanostructures. As a result, the MoS₂@carbon composites, when served as anodes for Li-ion batteries, exhibit a high reversible specific capacity of 820 mAh g^-1, high-rate capability (457 mAh g^-1 at 2 A g^-1), and excellent cycling stability. The superior electrochemical performance makes the MoS₂@carbon composites to be low-cost and promising anode materials for Li-ion batteries.

This article couples human metabolic factors and heating environmental factors, and uses a 57 node human thermal physiological model to study the heating effect of radiators. It provides a way to objectively calculate and directly quantify the effect of heating equipment on human thermal physiological parameters. As the inlet speed increases, the surface temperature of the human body first increases and then decreases. At a speed of 3m/s, it basically reaches a high value. Continuing to increase the wind speed, as the indoor convection intensity further increases, the surface temperature of the human body will decrease, leading to a decrease in thermal comfort. Compared with floor radiation heating under similar indoor temperature conditions, forced convection radiator heating has similar skin temperatures in various parts of the human body after the indoor design temperature exceeds 20 ℃, and the overall thermal comfort of the two technical solutions is equivalent. Research has shown that the turbulence wind speed of convective radiators should not be too small, with a wind speed range of 2.5m/s to 3m/s. The heating effect of using horizontal air outlet from the lower part of the radiator is better than that of vertical air outlet from the upper part. Convection type radiator heating is more suitable for buildings with rooms that are not too high due to the large indoor temperature gradient.

When ground-penetrating radar is used to detect targets within concrete, the location of the targets, the identification of different shapes, properties and less obvious echoes all greatly increase the interpretation time of the staff and can easily cause misjudgment of the echo images. In this paper, the ground-penetrating radar echo images (B-scan) after processing are mean filtered to eliminate the direct waves that interfere greatly with the echoes. The RFB-s structure is added to the YOLOv3-SPP network structure, while the Anchor value is optimized and the EIOU loss function is introduced. For four types of data with different shapes and properties at random target locations, three models, YOLOv3, YOLOv3-SPP and the improved YOLOv3-SPP, are used for classification and identification, and the proposed algorithm models are comprehensively evaluated using model evaluation metrics. The experimental results show that the algorithm models proposed in this paper have good recognition effect in ground-penetrating radar echo image target detection.

The landscape image is the bridge of communication between people and forests, and the cut point of the supply-side reform of forest tourism products. The research collected 140 copies in total of forest landscape image drawings from non-art-major graduate students by randomly sampling during April and May, 2018, and constructed the landscape image conceptual model of forest by utilizing the landscape image sketching technique. The results showed that (1) In regard to linguistic knowledge, the natural landscape elements for instance, herbaceous plants, terrains, creatures, water and sky, and the broad-leaf forest objectively reflected not only the real forest landscape and the local native vegetation, but the variation of forest species with little attention. (2) On the perspective of spatial view, the sideways view indicated that graduate students preferred to watch forests at a moderate distance externally and few looked at forests internally. (3) In the view of self-orientation, the objective landscape indicated that graduate students preferred to demonstrate forest landscapes, they did not realize to interact with the environment. (4) On the aspect of social meaning, the scenic view and forest structure stated that graduate students preferred rural forest landscapes, not significantly for other special interests for forest. In conclusions, (1) the forest is thought to be a feature of people's life world and of rural scenes around homes, not an objective perception of the forest. (2) The forest is regarded as an important habitat for animals and a limited resource for people's life, production and recreation needs, into which people will go only to meet such needs. (3) The natural values of forests, like the ecology and aesthetics, etc. get more attention, while the social values of forests, like the life, production and culture receives rather low attention.

As the traditional sand fixation measures have many limitations, new sand fixing technologies and methods are urgently needed to be developed. This study demonstrated a new sand fixation method using palm mat geotextile to fix the sand dunes and plant grass. We experimented the physical property of the palm mat geotextile in the laboratory, and observed the vegetation growth in the Hobq Desert. The results showed that (1) The palm mat geotextile is more lighter and tougher than the common straw mat geotextile, the average weight, thickness and tensile strength of palm mat geotextile were 2023 g/m², 20.14 mm, and 842–860 N/m, after a year of field observation, the tensile strength decreased by only 2%. (2) The palm mat geotextile had excellent water retention capacity and scouring resistance, the maximum water content reached 227%, and the substrate lost 2.9% after the simulation of heavy rainfall for 3 hours with rainfall intensity of 30 mm/h in laboratory. (3) The palm mat geotextile significantly decreased the soil temperature and increase the humidity in summer, the observed results shown that the palm mat geotextile had the greatest influence on 5cm depth of the soil temperature and 10cm depth of soil humidity. (4) The field experiment results showed that the vegetation coverage and the biomass of the palm mat geotextile with 2 m × 2 m were 35% and 11.21 g (3.9 times and 4.1 times than that of control group, 1.7 times and 1.8 times than that of high-banded salix psammophila sand-barriers group which is widely used in the Hobq Desert).

The lower reaches of the Changhua River are located in the northwest of Hainan Island, and the shallow groundwater in this area is the main water source for residents living at both sides of the river. In order to sustain the exploitation and use of water resources in this area, it is essential to clarify the chemical characteristics and the formation mechanism of the groundwater. We collected 100 sets of shallow groundwater samples from the lower reaches of the Changhua River, and analyzed the chemical characteristics of the groundwater in shallow aquifers as well as its controlling factors by means of the methods including descriptive statistical analysis, Piper diagram, Gibbs diagram, and ion ratio. The results show that the overall characteristics of groundwater in the study area are near-neutral to weakly alkaline nature, indicating a generally oxidized environment. The groundwater involves in 56 chemical types, and the most predominant types are Ca•Na-HCO3 and Ca-HCO3, respectively. NO- 3 has become a macro component exceeding SO2- 4in most of the sampling groundwater, suggesting a significant impact of human activities in this area. At the same time, the chemical characteristics of groundwater in the study area are mainly affected by the water-rock interaction, while the water-rock interaction is mostly affected by the dissolution of silicate rocks and less by the dissolution of carbonate rocks and evaporite rocks. According to the ion ratio results, Na+ and K+ in the study area are mainly from the leaching of silicate rocks, Ca2+ and Mg2+ are mainly from the dissolution of carbonate rocks, in addition to a certain degree of cationic exchange. NO- 3 is mainly related to human activities, and the human activities are more affected by agricultural activities and domestic sewage than by industrial and mining activities. This study can provide a reference for the development and protection of shallow groundwater in the lower reaches of the Changhua River.

To ensure consumers can purchase high-quality rice, accurate identification of rice varieties is particularly important. Methods: This article conducts research based on machine learning algorithms from the perspectives of image, spectrum, and spectrogram fusion. Six types of hyperspectral image data of rice were preprocessed using convolutional smoothing (SG) and multiple scatter correction (MSC). Texture information of the images was extracted using gray-level co-occurrence matrix. Spectra, texture, and spectrogram data were fused into a new matrix. Spectral, texture, and spectrogram fusion data were used as inputs for the model, and support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) classification models were constructed and compared. Results: From the classification results, the spectrogram fusion classification performance was better than classification models using only spectra or texture. Conclusion: The research results showed that the accuracy of SVM and LR classification models exceeded 90%, and the LR model performed the best, effectively classifying rice varieties.

Research on the development of new lightweight Al-Li alloys using selective laser melting pro-cess has great potential for industrial applications. This paper reports on the development of novel aluminum-lithium alloys using selective laser melting technology. Al-Cu-Li-Mg-Ag-Sc-Zr pre-alloyed powders with lithium contents of 1 wt.%, 2 wt.% and 3 wt.%, respectively, were prepared by inert gas atomization. After SLM process optimization, the microstructure and me-chanical properties of the as-formed specimens were investigated. The densification of the three newly developed alloys are 99.51 %, 98.96 % and 92.01 %, respectively. They all have good form-ability, with the lithium loss rate about 15 %. The as-formed alloy with 1% Li content presents good comprehensive properties with a yield strength of 412.6 ± 16.0 MPa, an ultimate tensile strength of 461.1 ± 11.7 MPa, and an elongation of 13.6 ± 1.1%. The three alloys exhibit a layered molten pool stacking morphology and have a typical heterostructure. The columnar crystals and equiaxed fine grains are alternately arranged, and most of the precipitated phases are enriched at the grain boundaries. The change of Li content mainly affects the precipitation of Cu-containing phase. When the Li content is 1 wt.%, there are θ phase, T1 phase and TB phase. When Li increased to 2 wt.%, T1 and T2 phases precipitated together. When Li reaches 3 wt.%, δ' phase precipitates with T2 phase. This study provides useful guidance for the future SLM form-ing of new crack-free and high-strength Al-Li alloys.

In recent years, distributed generation technology has developed rapidly. Renewable energy, represented by wind energy and solar energy, has been widely studied and utilized. In order to give full play to the advantages of Distributed Generation (DG) and meet the challenges after power grid access, Active Distribution Network (ADN) is considered as the future development direction of traditional distribution network because of its ability of active management. Nowadays, multi-scenario analysis is widely used in the research of optimal allocation of distributed power supply in active distribution network. Aiming at the problems that may arise when using multi-scenario analysis to plan DG with uncertainties in large-scale scenarios, a scenario reduction method based on improved clustering algorithm is proposed. The validity of the scene reduction method is tested, and the feasibility of the method is verified. At present, there are few studies on the optimal allocation of DG in ADN under fault state. In this paper, comprehensive safety indicators are introduced. Considering the timing characteristics of DG and the influence of active management mode, a bi-level programming model is established, which aims at minimizing the investment of annual life cycle and the removal of active power. The bi-level model is a complex mixed integer non-linear programming model. A hybrid algorithm combining cuckoo search algorithm and primal dual interior point method is used to solve the model. Finally, through the simulation of the IEEE-33 node system, the superiority of the scenario reduction method and the comprehensive security index used in this paper to optimize the configuration of DG in ADN is verified.

To decrease privacy risks, consumers may choose to misrepresent when they are asked to offer personal information. This paper examines the impact of consumer misrepresentation on a monopolistic firm and consumers with an economic model. The results show that consumer misrepresentation may benefit the firm but hurt consumers. In addition, consumers misrepresentation may encourage the firm to provide higher personalized service level in certain scenarios, such as, when the unit cost of personalized service is low. Thirdly, when consumers misrepresent, and the firm only covers part of the market, a greater unit value of consumer’s privacy information will reduce the firm’s profit, but a greater unit cost of personalized service increases the firm’s profit.

Due to the special terrain of Urumqi (in the valley area), which often triggers strong foehn weather, and causes huge losses to local people's lives and social economy. This study uses in-situ surface meteorological variables (including the hourly temperature, pressure, humidity, wind, etc.) from the Urumqi Meteorological Station (downstream station, DS) and the Dabancheng Meteorological Station (upstream station, US) in the Middle Tianshan Valley and NCEP/NCAR reanalysis data from 2008 to 2022. A dataset of the foehn weather process at DS in the past 15 years is established and the variation patterns of each meteorological variable during the process of foehn is analyzed. Based on the physical mechanism of the occurrence of foehn, a three-element identification standard for foehn in Urumqi is established by comparing and analyzing the variation of wind direction (WD), wind speed (WS), and the difference of potential temperature (Δθ) between DS and US during the period of foehn and non-foehn from 2013 to 2022, namely: 94°≤ 2-minute average WD ≤168°, 2-minute average WS ≥2.0 m/s, and Δθ between DS and US ≥ 0.29 K. According to the test and evaluation, the three-element identification standard has an accuracy of 82.96%, and a hit rate of 89.50% for the occurrence of foehn in Urumqi from 2008 to 2012. Moreover, the hit rate of foehn identification is 100% for strong wind or above (i.e., 2-minute average WS ≥10.8 m/s) WS. In addition, combined with two predictors of sea-level pressure difference (ΔP) and Δθ between DS and US, forecasting foehn can be more accurately predicted than a single forecasting factor. When ΔP ≤ -12 hPa and Δθ≥5 K, the probability of the occurrence of foehn is more than 90%. This study provides certain reference and application value for the weather forecasting operation of foehn.

Lithium rich layered oxides (LRLO) are a wide class of innovative active materials for positive electrodes in lithium-ion (LIB) and lithium-metal secondary batteries (LMB). LRLOs are over-stoichiometric layered oxides rich in lithium and manganese, with general formula Li1+xTM1-xO2, where TM is a blend of transition metals comprising Mn (main constituent), Ni, Co, Fe and others. Due to the very variable composition and the extended defectivity their structural identity is still debated among researchers being likely an unresolved hybrid between a monoclinic (mC24) and a hexagonal lattice (hR12). Once casted in composite positive electrode films and assembled in LIBs or LMBs, LRLOs can delivery reversible specific capacities above 220-240 mAhg-1, thus beyond any other available intercalation cathode material for LIBs, with mean working potential above 3.3-3.4 V vs Li for hundreds of cycles in liquid aprotic commercial electrodes. In this review we critically outline the recent advancements in the fundamental understanding of the physico-chemical properties of LRLO as well as the most exciting innovations in their battery performance. We focus in particular on the elusive structural identity of these phases, on the complexity of the reaction mechanism in batteries as well as on practical strategies to minimize or remove cobalt from the lattice while preserving the outstanding performance upon cycling.

Tandem mass tag (TMT)-based proteomics facilitate multiplexing in mass spectrometry (MS)-based quantification and identification of proteins and their post-translational modifications. The use of TMT isobaric tags can enable multiplexing of up to 18 samples using commercially available kits. A single TMT experiment can quantify proteome, serine, threonine phosphorylation, and tyrosine phosphorylation. Of note, tyrosine phosphorylation is of low abundance, and identification/quantification can be improved using two complementary strategies. First, by employing SH2 superbinder which increases the number of identified sites. The SH2 Superbinder is more cost-effective than the commonly used phosphotyrosine antibodies. Second, by employing phosphotyrosine booster strategy, a pervanadate-treated channel to boost the signal of low-abundant phosphotyrosine. Noteworthy, pervanadate boost increases the likelihood of low abundant peptide to be selected for MS2, and facilitating the detection of > 6000 proteins, 10,000 unique pS/T and 1000 unique pY sites.

Arctic sea ice prediction holds significant importance for facilitating Arctic route planning, optimizing fisheries management, and advancing the field of sea ice dynamics research. While various deep learning models have been developed for sea ice prediction, they predominantly operate at the seasonal or sub-seasonal scale, often focusing on localized areas, and few cater to full-region daily scale prediction. This study introduces the use of spatiotemporal sequence data prediction models, namely, the convolutional LSTM (ConvLSTM) and predictive recurrent neural network (PredRNN), for the prediction of sea ice concentration (SIC). Our analysis reveals that, when solely utilizing SIC historical data as the input, the ConvLSTM model outperforms the PredRNN model in SIC prediction. To enhance the model's capacity to capture spatiotemporal relationships between multiple variables, we expanded the range of input data types to form the ConvLSTM-multi and PredRNN-multi models. Experimental findings demonstrate that the ConvLSTM-multi model excels in assimilating the influence of reanalysis data on sea ice within the sea ice edge region, thus exhibiting superior performance in predicting daily Arctic SIC over the subsequent 10 days. Furthermore, sensitivity tests on various model parameters highlight the substantial impact of sea surface temperature and prediction date on the accuracy of daily sea ice prediction. Additionally, meteorological and oceanographic parameters primarily affect the prediction accuracy of the thin ice region at the edge of the sea ice.

The solar heat pump system based on photovoltaic photothermal (PV/T) modules is a new technology that integrates photovoltaics and heat reutilization. It can improve the efficiency of photovoltaic conversion and recovery the remaining heat generated during the photoelectric conversion process, thereby improving the comprehensive efficiency of the whole system. Simulink software is a visual simulation tool, which has the advantages of strong applicability, clear simulation structure and calculation process. The design of its graphical programming greatly simplifies the user modeling process and allows for direct viewing of results, therefore improving the simulation efficiency. At present, there is little research on simulation of solar heat pump systems with PV/T modules based on Simulink software. In this paper, the mathematical models of each component contained in the PV/T solar heat pump system were established based on the system working principle, energy conservation equations and some empirical formulas, and then the operation of the system was simulated by the Simulink software. Due to the operation characteristic of PV/T modules is the key influencing factor for the whole system performance, the model and simulation process for PV/T modules were introduced in detail. The results showed that the surface temperature of PV/T modules under different operating conditions was significantly lower than that of ordinary photovoltaic panels, and the temperature change amplitude was lower. As results, the power generation and photovoltaic conversion efficiency were significantly improved.

Cotton is a potential and excellent candidate to balance both agricultural production and reme-diation of mercury-contained soil, as its main production fiber hardly involve into food chains. However, there is known rarely about the tolerance and response to Hg environments in cotton. In this study, The biochemical and physiological damages, in response to mercury (Hg), were investigated in upland cotton seedlings. The results on cottonseeds germination, indicated the germination rate were suppressed by high Hg levels, as the decrease of percentage was more than 10% at 1000 µM Hg. Shoots and roots’ growth were significantly inhibited above 10 µM Hg. The inhibitor rates (IR) in fresh weight were close between shoots and roots, whereas that in dry weight the root growth was more obviously influenced by Hg. In comparison of organs, the growth inhibition ranked as root > leaf > stem. The declining of translocation factor (TF) op-posed the Hg level even as low to 0.05 at 50 µM Hg. The assimilation of cotton plants was af-fected negatively by Hg toxicity, as evidenced from the performances on photosynthesis pig-ments (chlorophyll a and b) and gas exchange (Intercellular CO2 concentration (Ci), CO2 assimila-tion rate (Pn) and stomatal conductance (Gs)). Sick phenotypes on leaf surface included small white zone, shrinking and necrosis. Membrane lipid peroxidation and leakage were Hg dose-dependent as indicated by malondialdehyde (MDA) content and relative conductivity (RC) values in leaves and roots. More than 10 µM Hg damaged antioxidant enzyme system in both leaves and roots (P<0.05). Concludingly, 10 µM Hg post negative consequences to upland cotton plants in growth, physiology and biochemistry, whereas high phytotoxicity and damage ap-peared at more than 50 µM Hg concentration.

In this work, a tailored extreme learning machine (ELM) algorithm to enhance the overall robustness of gas analyzer based on the tunable diode laser absorption spectroscopy (TDLAS) method is presented. The ELM model is tailored through activation function selection, input weight and bias searching, and cross validation method to address the analyzer robustness issues for industrial process analysis field application. The two particular issues are the inaccurate gas concentration measurement caused by the process gas background components variation, and the inaccurate spectra shift calculation caused by spectral interference. By using our algorithm, the concentration error is reduced by one order of magnitude over a much larger stream pressure and component range compared with that obtained by classical least square (CLS) fitting methods based on reference curves. Additionally, it is shown that with our algorithm, the wavelength shift accuracy is improved to less than 1 count over 1000 counts spectra length. In order to test the viability of our algorithm, a trace ethylene (C₂H₄) TDLAS analyzer with coexisting methane was implemented, and its experimental measurements support analyzing robustness enhancement effect.

Cucumber (Cucumis sativus L.) is a vital economic vegetable crop, and TRM (TONNEAU1 Recruiting Motif) gene plays a key role in cucumber organ growth. However, the pan-genomic characteristics of the TRM gene family and their expression patterns under different stresses have not been reported in cucumber. In this study, we identified 29 CsTRMs from the pan-genomes of 13 cucumber accessions, with CsTRM29 existing only in PI183967. Most CsTRM proteins exhibited differences in sequence length, except five CsTRMs having consistent protein sequence lengths among the 13 accessions. All CsTRM proteins showed amino acid variations. Analysis of CsTRM gene expression patterns revealed that six CsTRM genes strongly changed in short-fruited lines compared with long-fruited lines. And four CsTRM genes strongly responded to salt and heat stress, while CsTRM14 showed responses to salt stress, powdery mildew, gray mold and downy mildew. Some CsTRM genes were induced or suppressed at different treatment timepoint, suggesting that cucumber TRM genes may play different roles in responses to different stresses, with expression patterns varying with stress changes. Remarkably, the expression of CsTRM21 showed considerable change between long and short fruit and in responses to abiotic stresses (salt stress, heat stress) as well as biotic stresses (powdery mildew, gray mold), suggesting a dual role of CsTRM21 in both fruit shape determination and stress resistance. Collectively, this study provided a base for further functional identification of CsTRM genes in cucumber plant growth and stress resistance.

Thirty-six healthy 21-day-old weaned ternary piglets (Duroc × Landrace × Yorkshire) were randomly divided into 2 treatments with 18 replicates per treatment and 1 pig per replicate. The control group was fed with basal diet and the test group was fed with diets supplemented with 1 kg/t tea residue. The test period was 28 days. The results are as follows: The addition of tea residue in the diet has no significant effect on the growth performance of weaned piglets (P > 0.05), but it could significantly reduce the diarrhea rate of piglets from 1 to 7 days and 1 to 28 days (P < 0.05). Compared with the control group, the dietary supplementation of tea residue had no significant effect on nutrient apparent digestibility, plasma biochemical indexes and plasma immune indexes (P > 0.05), but increased the content of glutathione in plasma (P < 0.05). Tea residue had no significant effect on the morphology of jejunum and ileum of piglets (P > 0.05), but it could significantly reduce the content of chloride ion in feces (P < 0.05). Compared with the basal diet group, there was no significant difference in the relative expression of TMEM16A and CFTR mRNA in the colon of weaned piglets (P > 0.05). The whole-cell patch clamp recording showed that the TMEM16A and CFTR ion channels could be activated by ionomycin and forskolin, respectively. However, when the HT-29 cells transfected with TMEM16A and CFTR channels were treated with tea residue extract, it could significantly inhibit the chloride current of the TMEM16A and CFTR ion channels (P < 0.05).

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment–based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

Analyzing horse behavior is crucial for assessing training quality, particularly in accurately identifying actions like standing, walking, and running. Research has been conducted both domestically and internationally in this regard; however, challenges persist, including reliance on single sensors, poor real-time performance, and low identification accuracy. In view of these challenges, this study investigated real-time identification of horse behavior based on wearable devices. The system, centered around a microcontroller and utilizing a 4G network as a carrier, employs multi-axis IMU sensors as input sources to perceive horse posture. The study proposed a behavior classification method based on analysis of acceleration thresholds. The method consists primarily of two sequential stages: first, the resultant acceleration interval counting method, which employs a nonlinear segmentation approach for initial behavior classification; and second, the statistical analysis of variance parameters between segments, which when coupled with multi-level threshold processing, achieves a refined classification. Experimental results indicated that the interval counting method alone achieved an accuracy of 87.55%, while for the variance analysis method alone the accuracy was 90.87%. The proposed method, comprising the two stages, reached a classification accuracy of 91.57%, underpinning its usefulness in supporting future equine research.

Signal-to-noise ratio (SNR) is an important index to evaluate radiation performance and image quality of optical imaging systems under low illumination background. Under the nighttime lighting condition, the illumination of remote sensing objects is low and varies greatly, usually ranging from several lux to tens of thousands of lux. Nighttime light remote sensing imaging requires high sensitivity and large dynamic range of detectors. Luojia 1-01 is the first professional nighttime light remote sensing satellite in the world. In this paper, we took the nighttime light remote sensing camera carried on the satellite as research object, proposed an in-orbit SNR test method based on time series images to overcome the problem of low spatial resolution. We first analyzed the process of luminous flux transmission between objects and satellite and established a radiative transfer model. By combining the parameters of large relative aperture optical system and high sensitivity CMOS device, we established SNR model and specially analyzed the effect of exposure time and quantization bits on SNR. Finally we used the proposed in-orbit test method to calculate SNR of lighting images acquired by satellite. And the measured result is in good agreement with the model predicted data. Under the condition of 10lx illumination, the SNR of typical objects can reach 27.02dB, which is much better than the requirement of 20dB for engineering application.

The gut microbiota plays an important role in the physiological activities of the host and affects the formation of important economic traits in agricultural animals. We investigated the effects of cecal microbiota on chicken weights using the Guizhou yellow chicken as a model. We collected experimental cohorts from chickens with high (HC, n=16) and low body weights (LC, n=16) and integrated microbial 16S rRNA gene sequencing and non-targeted serum metabolome data to explore the effect and its metabolic mechanism of cecal microbiota on market weight. The genera Lachnoclostridium, Alistipes, Negativibacillus, Sellimonas and Ruminococcus torques group were enriched in the HC group while Phascolarctobacterium was enriched in the LC group (P<0.05). Metabolomic analysis determined that pantothenic acid, luvangetin (2H-1-benzopyran-6-acrylic acid) and menadione (vitamin K) were significantly higher in HC serum while beclomethasone dipropionate (a glucocorticoid) and chlorophene (2-benzyl-4-chlorophenol) were present at higher levels in the LC group. The microbes enriched in HC that were significantly positively correlated with metabolites including pantothenic acid and menadione and negatively correlated with beclomethasone dipropionate and chlorophene. These results indicated that specific cecal bacteria in Guizhou yellow chickens alter the host metabolism and growth performance. This study provides a reference for revealing the mechanism of cecal microbe actions that affect chicken body weight.

We report on the role of synergistic polarization of Ba0.9Sr0.1TiO3 (BST) nanoparticles in sulfur cathodes to enhance the redox kinetics of polysulfides for high-capacity Li-S batteries. Ferroelectric nanoparticles are known to significantly improve the electrochemical performance of Li-S batteries due to their inherent self-polarization and high adsorption capacity towards polysulfides. X-ray diffraction spectra confirmed the tetragonal symmetry (c/a=1.0073), while Raman spectroscopic analysis validated the presence of tetragonal orientation Raman modes in BST-modified composites. Scanning electron microscope (SEM) images showed a homogeneous distribution of BST in the sulfur cathode system, with grain sizes ranging from 1 to 1.5 μm. Notably, the BST-coupled S50BST30CB10PVDF10 composite cathode achieved a capacity of approximately 820 mAh/g at 100 mA/g, maintaining stability over 100 cycles, demonstrating improved electrochemical performance. Two distinct plateaus between 2.3 V to 2.0 V and 2.0 V to 1.5 V further underscore the superior performance of BST ferroelectric nanoparticles in enhancing the redox kinetics of Li-S batteries. By leveraging the favourable affinity of polar substances towards polysulfides, we aimed to create a more stable reactive environment within the cathodic site, effectively trapping polysulfide intermediates through the synergistic polarization of BST nanoparticles. The synergistic polarization induced by the asymmetric crystal structure of ferroelectrics is anticipated to generate internal electric fields, enhancing chemisorption with heteropolar reactive. The observed high cyclic stability further validates the efficacy of these composite cathodes in mitigating the polysulfide shuttle effect, offering promising prospects for advancing Li-S battery technology.

To quantitatively estimate the risk of power system operation under extreme rainfall, a multi-scenario stochastic risk assessment method is proposed. First, a scenario generation scheme considering waterlogged faults of power facilities is constructed based on the storm water management model (SWMM) and the extreme learning machine method. These scenarios will be merged to several typical scenario sets for further processing. The outage of power facilities will induce power flow transfer which may consequently lead to transmission lines’ thermal limit violation. Semi-invariant and Gram-Charlier level expansion methods are adopted to analytically depict the probability density function and cumulative probability function of each line’s power flow. The optimal solution is performed by a particle swarm algorithm to obtain proper load curtailment at each bus, and consequently the violation probability of line thermal violations can be controlled within an allowable range. The volume of load curtailment as well as their importance are considered to quantitatively access the risk of power supply security under extreme precipitation scenarios. The effectiveness of the proposed method is verified in case studies based on the IEEE 24-bus system.

This work compared the performance of three methods for constructing a regional ensemble prediction system (EPS) for wind speed forecasts: dynamical downscaling, breeding of growth modes (BGM), and blending method. The Weather Research and Forecasting (WRF) model was used to downscale the European Centre for Medium-range Weather Forecast (ECMWF) EPS. In addition, as the BGM method needs observation data for generating scaling factors, an alternative method for generating scaling factors was proposed to eliminate dependence on observation data. One-month tests between October 1st and October 30th, 2020, were implemented to evaluate the performance of three methods in the Gansu province of China. The results demonstrate that the blending method outperforms the other two methods. Furthermore, the difference in performance is evident mainly in early forecast lead time and becomes negligible as forecast time increases.

Brucella abortus is a facultative intracellular Gram-negative bacterium that causes chronic persistent infections in humans and livestock. In this study, conventional bio-typing, multiple-locus variable-number tandem repeat analysis (MLVA), and whole-genome sequencing-single-nucleotide polymorphism (WGS-SNP) were used to investigate the molecular epidemiology characteristics of Brucella abortus strains in China and their relationships to world lineages. A total of 100 strains were collected from 1953 to 2013, suggesting that B. abortus circulated in China in the past five decades. Moreover, most strains were mainly distributed in the northwest area. During this period, seven biovars were found, indicating that B. abortus displayed a high diversity of biovars and that the main epidemic areas are in the northern provinces. Strains have high genetic diversity, and bruce07 is the most helpful locus for genotyping of this population. Moreover, 17 MLVA-11 genotypes were found; 13 of them are of known genotypes and four are unassigned genotypes, indicating that B. abortus in this study had several geographic origins. Still, strains from unassigned genotypes may originate from China. Many shared MLVA-16 genotypes were observed in strains from the same provinces in Northern China, which confirmed a brucellosis outbreak within northern regions. WGS-SNP analysis showed that eight Chinese strains formed a ladder-like phylogram (C. Ⅶ) with strains from nine countries, including Uganda, Iraq, Russia, Georgia, Spain, Italy, Egypt, Mongolia, and China; strains were introduced to these countries from a single source. Notably, Chinese strains were closely related to strains from Russia and Mongolia; frequent animal (cattle) trade and exchanges may promote this process. We will provide new and insightful information for strength surveillance and control of B. abortus brucellosis in China.

Resonance inductive coupling is widely used for wireless power transfer (WPT) in medical applications. In this paper, we analyze the LCL-compensated WPT structure and propose a novel constant voltage transmission system based on gain estimation, without any extra feedback from the receiver. The system is capable for implant neural stimulation where the load impedance and the coupling coefficient are both variable. Compared to existing methods for constant voltage transmission, our approach offers advantages in compact size and the compatibility with the industrial, scientific and medical (ISM) band. We validate the load-independent resonant characteristic and the feasibility of constant voltage transmission using an experimental prototype working at 6.78MHz. Finally, we discuss the structure of the implant stimulator and methods of applying the proposed WPT system.

Monin-Obukhov similarity theory (MOST) overestimates wind shear in some atmospheric stable conditions, i.e. Richardson number $R_f<0.25$. The overestimated wind shear that leads to an under-predicted friction wind speed and a lower ambient turbulence intensity for a given hub-height reference wind speed and a given roughness length, could influence wake modeling of a wind turbine. This work investigates the side effects of the breakdown of MOST on wake modeling under stable conditions and makes some modifications to the flow similarity functions to eliminate these side effects. Based on a field measurement in a wind farm, we firstly show that MOST predicts a larger wind shear for the atmospheric stability parameter $\zeta>0.1$ and proposes new flow similarity functions without constraining $R_f$ to limit the overestimated wind shear by MOST. Next, different turbulence models based on MOST and a modified one based on the new similarity functions are investigated through numerical simulations. These turbulence models are combined with the actuator disk model (AD) and Reynolds-averaged Navier–Stokes equations (RANS) to model wind turbine wakes under stable conditions. As compared to measurements, numerical results show that turbulence models based on MOST result in larger wake deficits and slower wake recovery rate with a square root of the mean-squared-error (RSME) of wake deficit in the range of 0.07-0.18. This overestimated wake effect is improved by applying the new similarity functions and the RSME of wake deficit is averagely reduced by 0.05. Finally, we check the role of the under-predicted turbulence intensity playing in the larger wake deficit predicted by models based MOST. Additional numerical simulations using the modified turbulence model are carried out, in which the roughness length is reduced to impose a hub-height ambient turbulence intensity equivalent to the MOST case. Simulation results show that reducing turbulence intensity enhances wake effects, however, it cannot reproduce the large wake deficit predicted by models based on MOST, which suggests that the overestimated wake effect by MOST could be also related to the overestimated wind shear.

p-Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking based virtual screening were performed to identify novel potential HPPD inhibitors. The complex based pharmacophore model (CBP) with 0.721 of ROC used for screening compound showed remarkable ability to retrieve known active ligands from decoy molecule. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5(DS 2.5) to discern interactions with key residues at the active site of HPPD. 4 Compounds with top rank in HipHop model and well-known binding model were finally chosen as identification of lead compounds with potentially inhibitory effects on active site of target. The results provided powerful insight to the development of novel HPPD inhibitors herbicides using computational techniques.

The energy E takes the place of the gravitational mass m_G to produce gravity [1]. We wonder whether the inertial mass m_i in the inertial force is also replaced by E. The experiments to measure the inertial force and weight of a carrier are presented. Now we can test the principle of equivalence and study foundations of physics in condensed matter.

Background: Currently, many detection methods have high sensitivity to the diagnosis of lung cancer. However, some postoperative patients with pulmonary nodule were eventually diagnosed as benign nodules. The ideal evaluation of an individual with a pulmonary nodule would expedite therapy for a malignant nodule and minimize testing for those with a benign nodule.Methods: This case-control study is designed to explore the relationship between ACE1 rs4646994 polymorphism and the risk of lung cancer in patients with pulmonary nodules, 400 individuals with lung cancer and benign pulmonary nodules were included. A DNA extraction kit was used to extract plasm DNA from peripheral blood. The relationship between ACE1 rs4646994 and the risk of lung cancer in patients with pulmonary nodules was determined by chi-square test, logistic regression analysis and cross analysis. Results: The results showed that the DD genotype of ACE1 rs4646994 may increase the risk of lung cancer in patients with pulmonary nodules, and this correlation was more significant in the female subgroup. In the age stratification analysis, it was found that the risk of lung cancer was significantly increased in the DD genotype of ACE1 rs4646994 in the older subgroup (&gt; 45 years). In addition, the possibility of EGFR mutation in lung adenocarcinoma patients with ACE1 rs4646994 DD genotype was lower than that of II or ID genotype carriers. Conclusions: Our study indicated that ACE1 rs4646994 polymorphism increases the risk of lung cancer in patients with pulmonary nodules from China.

Co-free Li-rich oxide is a promising cathode for low cost high energy density Li-ion battery but presents poor cyclic stability. To address this issue, CeO2 is coated on Co-free Li-rich oxide through a low-temperature aged process, resulting in a novel CeO2-coated Li-rich oxide compo-site. Due to the low-temperature aged process, a uniform CeO2 coating layer of 6 nm in thickness is successfully coated on Co-free Li-rich oxide. With this uniform coating, the resulting CeO2-coated Li-rich oxide composite presents improved cyclic stability as well as rate capability as the cathode of Li-ion battery. The capacity retention of the resulting CeO2-coated Li-rich oxide is enhanced from 67% to 85% after 100 cycles and its capacity retention of 5C/0.05C is enhanced from 10% to 23%, compared with the uncoated sample. Such significant improvements enable this low-temperature aged process to be helpful for the practical application of Li-rich oxide materials, not limited to Co-free Li-rich oxide.

Malaxidinae is one of the confusing groups with classification in Orchidaceae. Previous phylogenetic analysis reveals that the relationships among the taxa in Malaxidinae have not yet been reliably established using a few plastome regions or nuclear ribosomal internal transcribed spacer (nrITS). In the present study, the complete plastomes of Oberonia integerrima and Crepidium purpureum were assembled using high-throughput sequencing. Combined with publicly available complete plastome data, this resulted in a data set of 19 plastomes, including 17 species of Malaxidinae. The plastome feature and phylogenetic relationship were compared and analyzed. The results showed that: (1) The plastomes of Malaxidinae species possessed the quadripartite structure of typical angiosperms, with sizes ranging from 142,996 bp to 158,787 bp and encoding from 125 to 133 genes. The ndh genes were lost or pseudogenized with varying degrees in six species. An unusal inversion was detected in the Large Single-Copy region (LSC) of Oberonioides microtatantha. (2) A total of 8 regions, including ycf1, matK, rps16, rpl32, ccsA-ndhD, clpP-psbB, trn-FGAA-ndhJ, and trnSGCU-trnGUCC, were identified as mutational hotspots. (3) Based on complete plastomes, 68 protein-coding genes and 51 intergenic regions, respectively, the phylogenetic analyses resolved genera-level relationships in this subtribe with strong support. The Liparis was supported as polyphyletic.

Endoscopic retrograde cholangiopancreatography (ERCP) is a routinely used therapeutic procedure for the biliary and pancreatic diseases. Population aging may increase the typical indications of ERCP and come with more complexity and difficulties, especially in cannulation. This study aimed to evaluate the incidence, causes, and management of difficult biliary cannulation during ERCP in super-aged patients and the role of difficult cannulation as a risk factor for adverse events. A total of 614 patients, underwent ERCP, were prospectively studied as a cohort and divided into two groups based on their age. There were 146 patients aged 80 years or older in group A and 468 patients aged less than 80 years in group B. The primary outcome measures were the difficulty grade of papilla cannulation, clinical outcomes, and ERCP-related complications in the two groups. The adverse events were analyzed using logistic regression for patient age, co-morbidities, indications, and cannulation difficulty grade variables. There was no difference in the incidence of difficult cannulation between the two groups (32.9% vs. 34.4%, p=0.765) though, as expected, super-aged Group A had a higher prevalence of periampullary diverticulum (29.5% vs. 16.7%, p=0.001). The technical cannulation success rate was (96.6% vs. 96.8%, p= 0.54). All used cannulation techniques in the elderly group were efficient and safe. Logistic regression showed that age ≥80 was not associated with increased adverse events; however, difficult cannulation (adjusted odds ratio [AOR]=3.478; 95% confidence interval [CI]=1.877, 6.442; p<0.001) and CCI ≥2 (AOR=1.824; 95% CI=0.993, 3.349; p=0.045) were more likely to have adverse events. Age ≤65 (AOR=3.460; 95% CI=1.511, 7.922; p=0.003), female gender (AOR=2.362; 95% CI=1.089, 5.124; p=0.030), difficult cannulation (AOR=4.527; 95% CI=2.078, 9.860; p<0.001), and patients with cholangitis (AOR=3.261; 95% CI=1.204, 8.832; p=0.020) were strongly associated with increasing Post-ERCP Pancreatitis (PEP). Advanced age has not proved to be a risk factor of difficult cannulation, and secondary cannulation techniques can be safely and efficaciously utilized for this group. CCI ≥2 and difficult cannulation are associated with increased overall adverse events rate while age ≥80 factor is not.

A tunable near-infrared surface plasmon resonance (SPR) biosensor based on gate-controlled graphene plasmons is investigated theoretically. The novel characteristics of chemical potential sensing make the proposed sensor promising in the application of ultra-sensitive and highly specific biosensing technology. The sensitivity of chemical potential sensing in wavelength interrogation mode can be calculated to be 1.5, 1.89, 2.29, 3.21, 3.73 and 4.68 nm/meV respectively at the central wavelength of 1100, 1200, 1310, 1550, 1700 and 1900 nm. The much smaller full width half maximum (FWHMs) comparing with that of 2D nanomaterial-enhanced metal SPR sensors indicates higher figure of merit. The sensitivity of chemical potential sensing in gate voltage interrogation mode also can be calculated to be 156.9822, 143.6147, 131.0779, 111.0351, 101.3415 and 90.6038 mV/meV respectively at the incident wavelength of 1100, 1200, 1310, 1550, 1700 and 1900 nm. It can be estimated theoretically that the limit of detection (LOD) in DNA sensing of the proposed sensor can reach femtomolar level and even attomolar level, comparable to and even lower than that of 2D nanomaterial-enhanced metal SPR sensors with AuNPs as a sensitivity enhancement strategy. The feasibility of preparation and operation of this new concept SPR biosensor is also analyzed and discussed.

The four-way reversing valve is a key component determining whether a heat pump air conditioning system can work. Studying the four-way reversing valve is of great significance for improving the performance of the heat pump air conditioning system. In this paper, the control equation of the sliding block movement process is constructed to simulate the reversing process of the four-way reversing valve in fluid mechanics, and a detailed study is carried out from the sliding block speed, sliding block acceleration, sliding block force, refrigerant leakage, and other aspects. Research has shown that optimizing the structure of the slider can greatly improve the working performance of the four-way reversing valve. Increasing the height of the slider not only improves the pressure relief ability of the four-way reversing valve and prevents the slider from being damaged by high-pressure gas impact, but also reduces the leakage of refrigerant during the directional process; When reducing the length of the slider, although it will improve the pressure relief capacity of the four-way reversing valve, it also increases the amount of refrigerant leakage. The research results provide a theoretical basis and improvement direction for designers to improve the performance of four-way reversing valves.

Little is known about the association between equol and bioavailable testosterone (BT) in adults. We examined the associations of urinary equol concentrations with serum total, bioavailable and free testosterone (FT), dehydroepiandrosterone sulfide (DHEAS), free androgen index (FAI) and sex hormone-binding globulin (SHBG) concentrations. This cross-sectional study included 1904 women aged 59.7 years. Urinary equol and serum sex hormone concentrations were measured. Overall, urinary equol tended to be inversely associated with bioactive forms of androgenic indices (BT, FT or FAI) but not with total testosterone (TT) or DHEAS. Urinary equol was also positively associated with SHBG. In multi-covariate-adjusted analyses stratified by menopausal status, graded and inverse associations between urinary equol and bioactive forms of androgenic indices (BT, FT and FAI) were observed in postmenopausal women (all p-trends <0.05), but not in premenopausal women. A significant positive association between urinary equol and SHBG was observed only in postmenopausal women. No significant associations were observed between urinary equol and TT or DHEAS in either group. A path analysis indicated that these associations of equol with androgens in postmenopausal women might be mediated by SHBG. Our findings indicated urinary equol exhibited graded and inverse associations with BT or FT but not TT in women.

The emergence of drug resistant pathogenic bacteria is increasingly challenging conventional antibiotics. Plant derived flavonoids are considered as potential alternatives to antibiotics due to their antimicrobial properties. However, the mechanisms by which flavonoids modulate pathogenic microorganisms’ growth are not fully understood. In our previous studies we found that Rutin, a kind of flavonoids showed inhibition against Klebsiella pneumoniae strains. In order to better understand its inhibitory mechanism on strain growth, we used both Rutin and Luteolin as treatments to incubate K. pneumoniae ATCC700603 strain. After incubation for 4 hours, the homogenous and differential effects of two different flavonoids on the growth of K. pneumoniae were evaluated. The integrated metabolomic and transcriptomic analysis was performed. The expression levels of 5,483 genes and the contents of 882 metabolites were measured. The differentially expressed genes (DEGs) and metabolites (DEMs) were screened and analyzed. The correlation between DEGs and DEMs were also studied. Our results showed that Rutin could inhibit the strain growth by changing metabolic pathways and ABC transporters pathways. Our study also revealed FU841_RS17580 and FU841_RS19145 as functional genes that played vital roles in the strain growth.

This paper is concerned with developing an efficient numerical algorithm for fast implementation of the sparse grid method for computing the $d$-dimensional integral of a given function. The new algorithm, called the MDI-SG ({\em multilevel dimension iteration sparse grid}) method, implements the sparse grid method based on a dimension iteration/reduction procedure, it does not need to store the integration points, nor does it compute the function values independently at each integration point, instead, it reuses the computation for function evaluations as much as possible by performing the function evaluations at all integration points in a cluster and iteratively along coordinate directions. It is shown numerically that the computational complexity (in terms of CPU time) of the proposed MDI-SG method is of polynomial order $O(Nd^3 )$ or better, compared to the exponential order $O(N(\log N)^{d-1})$ for the standard sparse grid method, where $N$ denotes the maximum number of integration points in each coordinate direction. As a result, the proposed MDI-SG method effectively circumvents the curse of dimensionality suffered by the standard sparse grid method for high-dimensional numerical integration.

This paper outlines our effort on optimizing Pulsed Magneto-Oscillation (PMO) design in order to improve the efficiency of ingot manufacturing under PMO. Our calculation and experiment provided optimized PMO coil design and special configuration. Our optimized PMO design offered us a device that enabled the operator to examine and operate the melt without losing the efficiency. In one of the designs, the equipment even refined the grain sizes. Our work also showed an optimized distance range between the coil and the melt surface that maximized the refinement effects.

Atmospheric stability affects wind turbine wakes significantly. High-fidelity approaches such as large eddy simulations (LES) with the actuator line (AL) model which predicts detailed wake structures, fail to be applied in wind farm engineering applications due to its expensive cost. In order to make wind farm simulations computationally affordable, this paper proposes a new actuator disk model (AD) based on the blade element method (BEM) and combined with Reynolds-averaged Navier–Stokes equations (RANS) to model turbine wakes under different atmospheric stability conditions. In the proposed model, the upstream reference velocity is firstly estimated from the disk averaged velocity based on the one-dimensional momentum theory, and then is used to evaluate the rotor speed to calculate blade element forces. Flow similarity functions based on field measurement are applied to limit wind shear under strongly stable conditions, and turbulence source terms are added to take the buoyant-driven effects into consideration. Results from the new AD model are compared with field measurements and results from the AD model based on the thrust coefficient, the BEM-AD model with classical similarity functions and a high-fidelity LES approach. The results show that the proposed method is better in simulating wakes under various atmospheric stability conditions than the other AD models and has a similar performance to the high-fidelity LES approach however in much lower computational cost.

Dendrobium Sw have multiple photosynthetic pathways but due to the lack of identification, the influence of CAM pathway on the plastid genomic evolution of Dendrobium and the origin of CAM pathway are still poorly understood. In this study, based on the results of δ13C, net photosynthetic rates (Pn) and titratable acid value, we identified Dendrobium species into three photosynthetic pathways. Then the chloroplast whole genome characteristics of 10 Dendrobium species were analyzed with next-generation sequencing technology. The quadripartite-structure plastomes ranged from 151,673 bp to 160,375 bp and included 127 to 132 genes. Five noncoding mutational hotspots (rbcL-accD, atpB-rbcL, rbcL, trnLUAA, accD, Pi &gt; 0.10) were identified. A total of 41–60 SSRs were recognized, the average trinucleotide content was only about 4%, which is probably due to a more conserved SSR. Among multiple photosynthetic pathways, the apparent differences in IR junctions of SSC/IRB junctions (JSBs) were measured within chloroplast genomes, and the chloroplast genome size of constitutive CAM plants is shorter because of their ndh gene loss or pseudogenization, and this phenomenon accounts for a decreasing proportion of constitutive CAM, facultative CAM, and obligate C3 plants, so that the loss of the ndh gene may be speculated to be closely related to the CAM pathway. Phylogenetic analyses showed that there are multiple independent CAM origins in selected Dendrobium species, and the ancestral Dendrobium plastome possessed full ORFs for all ndh genes. The study aims to clarify the chloroplast genomic features of different photosynthetic pathways, enrich the genomic data of CAM plants, and provide genetic information from different perspectives for further systematic study of Dendrobium.

For an enterprise, the most critical aspect of development is resource management, which has a significant impact on all aspects of the enterprise. Therefore, enterprises must pay attention to resource management allocation, which can better promote the sustainable development of the enterprise and obtain optimal benefits. In the production and development of modern enterprises, the acquisition of benefits also involves the allocation of resources in enterprise management. This paper proposed a benefit optimization scheduling algorithm based on a macroeconomic prediction model under auction mechanism and a grid resource scheduling algorithm driven by a benefit function to allocate resources reasonably. This article used macroeconomic forecasting models to fully understand the resource needs of various departments and the resources held by enterprises, and rationally allocate various resources in various departments. This can improve the work efficiency of various departments, thereby reducing the cost of the enterprise, and achieving optimal benefits for the enterprise. The experimental results in this paper showed that the cost of resource management allocation for the benefit optimization scheduling algorithm and the grid resource scheduling algorithm based on the benefit function driven under the auction mechanism was 105.6 yuan and 46.8 yuan respectively when the task volume was 125 under the multi user environment. The time allocated for resource management was 36.6s and 18.9s respectively. It can be seen that the efficiency function driven grid resource scheduling algorithm had a lower cost and time for resource management allocation, so the efficiency function driven grid resource scheduling algorithm can achieve enterprise efficiency optimization.

Abstract: Toxicity of emerging organic pollutants to photosystems of aquatic plants are still not well clarified. This study aimed to develop a novel ecotoxicological experimental protocol based on nanoscale electrochemical mapping of photosynthetic oxygen evolution of aquatic plants by SECM (scanning electrochemical microscopy). The protocol was also checked by confocal laser scanning microscopy (CLSM), the traditional Clark oxygen electrode method and chlorophyll fluorescence technique. The typical persistent organic pollutant 2,4-dichlorophenol (2,4-DCP) in water environment and the common aquatic Microsorium pteropus (M. pteropus) were chosen as the model organic pollutant and tested plant, respectively. It was found that the SECM method could well discriminated the responses of stoma micromorphology and spatial pattens of photosynthetic oxygen evolution on single stoma. The shape of stoma blurred with increasing 2,4-DCP concentration, which was in good agreement with the CLSM images. The dose-response curves and IC50 values obtained from the SECM data were verified by the data measured by the traditional Clark oxygen electrode method and chlorophyll fluorescence test. The IC50 value of single stoma oxygen emission of 24 h exposed plant leave, which was derived from the SECM current data (32535 μg L-1), was close to those calculated from the maximum photosynthetic efficiency (Fv/Fm) measured by chlorophyll fluorescence test (33963 μg L-1), and the Clark oxygen electrode method photosynthetic oxygen evolution rate (32375 μg L-1). The 72 h and 96 h 2,4-DCP exposure data further confirmed the reliability of the nanoscale stoma oxygen emission mapping methodology for ecotoxicological assessment. In this protocol, the procedures for how to collect effective electrochemical data and how to extract useful information from the single stoma oxygen emission pattern were well established. This study showed that SECM is a feasible and reliable ecotoxicological tool for evaluation of toxicity of organic pollutants to higher plants with unique nanoscale visualization advantage over the conventional methods.

The exceptional performance of graphene has driven the advancement of its preparation technique and application. Laser-induced graphene (LIG), as a novel graphene preparation technique, has been applied in various fields. Graphene periodic structures created by LIG technique exhibit superhydrophobic characteristics and can be used for deicing and anti-icing applications, which are significantly influenced by the laser parameters. The laser surface treatment process was simulated by a finite element software analysis (COMSOL Multiphysics) to optimize the scanning parameter range, and the linear array surface structure were subsequently fabricated by the LIG technique. The generation of graphene was confirmed by Raman spectroscopy, and energy-dispersive X-ray spectroscopy. The periodic linear array structure were observed by Scanning electron microscopy (SEM) and confocal laser imaging (CLSM). In addition, CLSM testings, contact angle measurements, and delayed icing experiments were systematically performed to investigate the effect of scanning speed on surface hydrophobicity. The results show that the high quality and uniform graphene can be achieved using the laser scanning speed of 125 mm/s. The periodic linear array structures can obviously increase the contact angle and suppress delayed icing. Furthermore, these structures have the enhanced ability of the electric heating deicing, which can reach 100°C and 240°C within 15 s and within 60 s under the DC voltage power supply ranging from 3 to 7 V, respectively. These results indicate that the LIG technique can be developed to provide an efficient, economical, and convenient approach for preparing graphene and the hydrophobic surface array structure based on LIG has considerable potential for deicing and anti-icing applications.

Bulbophyllum is one of the largest genera and presents some of the most intricate taxonomic problems in the family Orchidaceae, including species of ornamental and medical importance. The lack of knowledge regarding the characterization of Bulbophyllum chloroplast (cp) genomes has imposed current limitations on our study. Here, we reported the complete cp genomes of seven Bulbophyllum species, including B. ambrosia, B. crassipes, B. farreri, B. hamatum, B. shanicum, B. triste and B. violaceolabellum, and compared with related taxa to provide a better understanding of their genomic information on taxonomy and phylogeny. A total of 28 Bulbophyllum cp genomes exhibit typical quadripartite structures with lengths ranging from 145,092 bp to 165,812 bp and GC content of 36.60% to 38.04%. Each genome contained 125–132 genes, encompassing 74–86 protein-coding genes, 38 tRNA genes, and eight rRNA genes. The genome arrangements, gene contents and length were similar with differences observed in ndh gene composition. A total of 18–49 long repeats and 38–80 simple sequence repeats (SSRs) were detected and the single-nucleotide (A/T) was dominant in Bulbophyllum cp genomes, with an obvious A/T preference. An analysis of relative synonymous codon usage (RSCU) revealed Leucine (Leu) was the most frequently used codon, while cysteine (Cys) was the least used. Six highly variable regions including ndhF-trnLUAG, trnTUGU-trnLUAA, trnFGAA-ndhJ, rps15-trnNGUU, rbcL-accD and psbI-trnSGCU were identified based on the ranking of the Pi values, had the potential to serve as DNA markers for species identification and phylogeny of the genus Bulbophyllum. Phylogenetic analysis based on the complete cp genome sequences and 68 protein-coding genes strongly supported 28 Bulbophyllum species can be divided into four branches and sects. Brachyantha, Cirrhopetalum, Leopardinae defined by morphology were non-monophyly. Our results enriched the genetic resources of Bulbophyllum species, providing valuable information to illustrate the complicated taxonomy, phylogeny and evolution process of the genus.

The proliferation and differentiation of mammalian skeletal muscle satellite cells (MuSCs) are highly complicated. Apart from the regulatory signaling cascade driven by the protein-coding genes, non-coding RNAs like microRNAs (miRNA) and circular RNAs (circRNAs) play essential roles in this biological process. However, circRNA functions in MuSCs proliferation and differentiation remain largely to be elucidated. Here, we screened for an exonic circTCF4 based on our previous RNA-Seq data, specifically expressed during the development of the longest dorsal muscle in goats. Subsequently, the circular structure and whole sequence of circTCF4 were verified using Sanger sequencing. Besides, circTCF4 was spatiotemporally expressed in multiple tissues from goats but strikingly enriched in muscles. Furthermore, circTCF4 suppressed MuSCs proliferation and differentiation, independent of AGO2 binding. Finally, we conducted Poly(A) RNA-Seq using cells treated with small interfering RNA targeting circTCF4 and found that circTCF4 would affect multiple signaling pathways, including insulin signaling pathway and AMPK signaling pathway related to muscle differentiation. Our results provide additional solid evidence for circRNA regulating skeletal muscle formation.

Flavonoids are major secondary metabolites in plants, which play important roles in maintaining the cellular redox balance in cells. Chalcone synthase (CHS) is the key enzyme in the flavonoids biosynthesis pathway, and has been proved to monitor the changes to drought stress tolerance. In this work, we overexpressed a CHS gene in tobacco (Nicotiana tabacum). The transgenic tobacco plants were more tolerant than the control plants to drought stress. The transcription levels of the key genes involved in the flavonoids pathway and the contents of seven flavonoids were also significantly raised in the transgenic tobacco plants. In addition, overexpression of the CHS gene lead to a lower concentration of the oxidative stress product malondialdehyde. Overall, the NtCHS gene studied in this work was considered as a candidate gene for genetic engineering to enhance drought tolerance of plants and improve response to oxidative stress.

The gravitational charge should be the energy instead of mass. This modification will lead to some different results and the experiments to test are also presented. Especially, we propose a scheme to achieve the negative energy and gravitational repulsive force in the lab.

Exploring the effect of the sample size on the estimation accuracy of airborne LiDAR forest attributes in a large-scale area can help in optimizing the technical application scheme of operational ALS-based large-scale forest stand inventories. In our study, sample datasets composed of different sample plots were constructed by repeated sampling from 1003 sample plots in a subtropical study area covering 2376 × 103 km2. Sixteen multiplicative power models were built in each forest type consisting of four forest attributes. Through these models, the variations of standard deviation (SD) and coefficient of variation (CV) of R2 and rRMSE of forest attribute estimation models for different quantity levels of sample plots were also analyzed. The results showed that, first, when the sample size increased from 30 to the top limit, the SD of the forest attributes and LiDAR variables showed a decreasing trend. Second, as the sample size increased, the rRMSE of the 16 forest attribute estimation models gradually decreased, while the R2 gradually increased. Third, when the sample size was small, both the SD of R2 and rRMSE of the models were large, and the SD of R2 and rRMSE gradually decreased as the sample size increased. In 50 models conducted for each attribute at the same sample size, for the mean standard deviations of forest attributes, the ten best performing models were lower than those of the total 50 models, and the worst ten models were the opposite. When the sample size increased, the accuracy of each forest attribute estimation model for each forest type gradually improved. The variation of forest attributes and the LiDAR variable of the construction model are critical factors that affect the model’s accuracy. To efficiently apply airborne LiDAR in order to survey large-scale subtropical forest resources, the sample size of the Chinese fir forest, pine forest, eucalyptus forest, and broad-leaved forest should be 110, 80, 85, and 70, respectively.

The cooking method is extremely important for the production of low-salt, wet-marinated, fermented golden pomfret because it strongly influences its flavor components and organoleptic quality. There are also significant differences in flavor preferences in different populations. The present study analyzed differences in the aroma characteristics of wet-marinated fermented golden pomfret after boiling, steaming, microwaving, air frying and baking using a combination of an electronic nose, GC-IMS and SPME-GC-MS. Electronic nose PCA showed that the flavors of the boiled (A), steam (B) and microwave (C) treatment groups were similar, and the flavors of baking (D) and air frying (E) were similar. A total of 72 flavor compounds were detected in the GC-IMS analysis, and comparative analysis of the cooked wet-marinated and fermented golden pomfret yielded a greater abundance of flavor compounds. SPME-GC-MS analysis detected 108 flavor compounds, and the results were similar to the baking and air frying. Twelve key flavor substances, including hexanal, isovaleraldehyde, and (E)-2-dodecenal, were identified by orthogonal partial least squares discriminant analysis (OPLS-DA) and VIP analysis. These results show that cooking method is a key factor in the flavor distribution of wet-marinated fermented golden pomfret, and consumers can choose the appropriate cooking method accordingly.

Tungsten carbide (WC) was well known as a wear-resistant material. Iron-based pow-der was suitable for remanufacturing of cast iron engine parts. To improve the wear resistance of the remanufactured iron-based cast iron engine parts, WC-Co was intro-duced into iron-based powders to prepare composite coatings for cast iron engine components. In this work, FeAlC-x(WC-Co) composite coatings were prepared by plasma transfer arc on compacted graphite cast iron. The influences of WC-Co con-tents in the Fe-AlC-x(WC-Co) composite coatings on the microstructure and properties of the composite coatings were investigated. The composite coatings contained γ-Fe, α-Fe, WC and Fe3W3C mainly. The microhardness of FeAlC-x(WC-Co) composite coatings had the highest hardness of 814 HV0.2, the-lowest coefficient of 0.5 and the lest wear mass loss of 1.3mg when the weight content of WC-Co in the composite coating was 20wt%. As compared with the FeAlC coating, FeAlC-x(WC-Co) composite coating achieved the effect of reducing friction and wear resistance simultaneously, which resulted from the self-lubricating effect of graphite and high wear-resistance of carbides in the claddings.

Hyperspectral small target detection (HSTD) is a promising pixel-level detection task. However, due to the low contrast and imbalance number between the target and background spatially and high dimensions spectrally, it is a challenging one. To address these issues, this work proposes a representation learning-based graph and generative network for hyperspectral small target detection. The model builds a fusion network through frequency representation for HSTD, where the novel architecture incorporates irregular topological data and the spatial-spectral feature to improve its representation ability. Firstly, a graph convolutional network (GCN) module better models the non-local topological relationship between samples to represent the hyperspectral scene’s underlying data structure. The mini-batch-training pattern of the GCN decreases the high computational cost of building an adjacency matrix for high-dimensional data sets. In parallel, the generative model enhances the differentiation reconstruction and the deep feature representation ability with respect to the target spectral signature. Finally, a fusion module compensates for the extracted different types of HS features and integrates their complementary merits for hyperspectral data interpretation while increasing detection and background suppression capabilities. Experiments on different hyperspectral data sets demonstrate the advantages of the proposed architecture.

In this study, the effects of various beryllium (Be) addition (Be-free, 0.1, 0.25, 0.50 wt.%) on the microstructure, mechanical properties, and corrosion corrosion of the Al-Mg-Li alloys were systematically investigated. The best performance was obtained in alloy with 0.1 wt.% Be addition. Trace Be addition promotes the grain refinement of the as-cast alloy ingot and contributes positive effects to the recrystallization, bringing improvement of tensile property. Meanwhile, the best anti-corrosion behavior is also presented at 0.1 wt.% Be addition, due to its potential to reduce the width of precipitates free zone (PFZ). As the Be content increase to an excessive level, the comprehensive performance decreases. Therefore, it is strongly recommended that adding trace Be element into Al-Mg-Li alloys has a positive effect on the comprehensive service performance.

Accurate lithium battery diagnosis and prognosis is critical to increase penetration of electric vehicles and grid-tied storage systems. They are both complex due to the intricate, nonlinear, and path-dependent nature of battery degradation. Data-driven models are anticipated to play a significant role in the behavioral prediction of dynamical systems such as batteries. However, they are often limited by the amount of training data available. In this work, we generated the first big data comprehensive synthetic datasets to train diagnosis and prognosis algorithms. The proof-of-concept datasets are over three orders of magnitude larger than what is currently available in the literature. With benchmark datasets, results from different studies could be easily equated, and the performance of different algorithms can be compared, enhanced, and analyzed extensively. This will expend critical capabilities of current AI algorithms, tools, and techniques to predict scientific data.

Li₂MnO₃ is critical component in the well-studied Li-excess cathode materials xLi₂MnO₃•(1- x)LiMO₂ for achieving high lithium storage capacity. In this article, the diffusion of Li ions in Li₂MnO₃ is studied using molecular dynamics (MD) simulation with well-behaved empirical force fields obtained by fitting against the crystal structure from experiment and phonons calculated using Density Function Theory (DFT). We have found two possible tetrahedral hopping channels, 0-TM and 1-TM(Mn⁴⁺) channel, which are differentiated by the face sharing octahedral cations. Simulation results show that the 0-TM channel is active for Li hopping, while 1-TM(Mn4+) channel is inactive. During the delithiation process, the Li ions in the TM layered are firstly removed, then those in the Li layer. However, the Li ions will be trapped in the tetrahedral 0-TM channels as long as the four face sharing octahedral sites are cleared. Up to x=1.0 for Li₂-xMnO₃, almost all the Li ions are located at the tetrahedral sites, forming a regular array along a axis. The de-intercalation of tetrahedral Li ions requires a high voltage (>5.2 V vs. Li/Li+), limiting the practical capacities measured in lab. The diffusion of Mn ions into the Li layers is observed in a deeper delithiated structure (x=1.2 for Li₂-xMnO₃), indicating an initial phase transformation to a spinel-like structure. However, the Mn ions are mainly trapped in the tetrahedral sites in the Li layer, instead of the octahedral sites fin spinel-like structure. A few of Mn ions diffusing into the octahedral sites in Li layers have no face sharing tetrahedral Li ions, revealing a further Li de-intercalation is imperative for the complete phase transformation. Our model is not stable for x≥1.4 in Li₂-xMnO₃. Other charge compensation mechanism should be considered in this high delithiation stage, eg. oxygen release.

This study aims to investigate the psychological cognitive mechanisms of rural residents amidst the renewal of suburban historical and cultural villages by examining the interplay between nostalgia, collective memory, subjective well-being and place identity in rural tourism destinations. Using Naobao Village as a case study—a suburban historical and cultural village in Hohhot, Inner Mongolia, this research employs a comprehensive approach integrating experimental methods and questionnaire surveys. The findings demonstrate that analyzing the interaction among the four emotions can elucidate the psychological cognitive mechanism of residents. Moreover, it uncovers that tourism effects significantly influence residents' perception of their living environment with positive effects on collective memory, subjective well-being and place identity. In the theoretical model for generating psychological cognition among residents in suburban historical and cultural villages, subjective well-being and collective memory play crucial mediating roles. This study provides a theoretical foundation and practical guidance for spatial reconstruction and cultural evolution of tourist landscapes in suburban rural tourist destinations.

Analyzing urban-rural spatial structures and changes are of great significance for under-standing the urban-rural relationship evolution. While previous studies mostly focused on the urban internal spatial structure evolution, less from the regional scale to explore the urban and rural evolution. Here, taking Dezhou city, a rapidly urbanization city in China as a case study, we employed the local contour tree method and nighttime light data to map urban and active rural regions’ range during 2012-2020, and further explored the respective development processes of them. This study found that different from rural regions, internal structures of urban regions are more complex, and there are often multiple hot spots inside them. The urban-rural regions’ area had increased significantly by 39.3% during 2012-2020 (p&lt;0.05). The urban and rural region rankings of the identified counties are basically consistent with the urban and rural population rankings. Particularly, different from perspectives of earlier land use (i.e., built-up land or impervious surface), this study identified urban and active rural regions in view of the scope of active human activities. This study therefore found populations were greatly responsible for affecting changes of urban and active rural region structures. These findings could be helpful for understanding urban-rural dynamics.

Ice accumulation poses considerable challenges in transportation, notably in the domain of general aviation. The present study combines the strengths and limitations of conventional aircraft de-icing techniques with the emerging trend toward all-electric aircraft. The study aims to utilize laser-induced graphene (LIG) technology to create a multifunctional surface, seamlessly integrating hydrophobic properties with efficient electrical heating to mitigate surface icing effectively. We investigated the utilization of a 10.6 μm CO2 laser for direct writing on polyimide (PI), a widely-used insulating encapsulation material. From the thermomechanical perspective, our initial analysis using COMSOL Multiphysics software revealed that when the laser power P exceeds 5 W, the PI substrate experience ablative damage. The experimental results show that when P ≤ 5W, an increase in power has a positive impact on the quality, surface porosity, roughness reduction, line-spacing reduction, and water contact-angle enhancement of the graphene. Conversely, when P &gt; 5 W, higher power negatively affects both the substrate and the graphene structure by inducing excessive ablation. However, it influences the graphene line height positively and is consistent with overall experimental-simulation congruence. Furthermore, the incorporation of high-quality graphene resulted in a surface that exhibited higher contact angles (CA &gt; 120°), lower energy consumption, and higher heating efficiency compared to the use of traditional electrically heated materials for anti-icing applications. The potential applications of this one-step fabrication method extend across various industries, particularly aviation, marine engineering, and other ice-prone domains. Moreover, the method has extensive prospects for addressing pivotal challenges associated with ice formation and serves an innovative and efficient anti-icing technology.

Type 2 diabetes mellitus(T2DM) is an increasingly prevalent and serious health problem. Its onset is typically associated with metabolic disorders and disturbances in the gut microbiota. Previous studies have reported the anti-T2DM effects of Pueraria thomsonii Radix as a functional food. However, the mechanism of action is still unknown. In this study, the effects of Pueraria thomsonii Radix water extract(PTR) on db/db mice were evaluated by pharmacology, metabolomics, and 16S rRNA gene sequencing. The results showed that PTR could improve the body weight of mice, reduce fasting blood glucose(FBG), urinary glucose(UGLU), homeostasis model assessment insulin resistance(HOMA-IR), urinary albumin/creatinine ratio(UACR), and reduce pancreatic tissue damage. Metabolomics showed that the Model group produced 109 differential metabolites, of which 74 could be regulated by PTR. 16S rRNA sequencing was done in fecal samples and results showed that PTR could reduce the Firmicutes/Bacteroidetes ratio(F/B) associated with obesity and regulate 3 beneficial bacteria and 1 harmful bacteria. In conclusion, the results showed that PTR could ameliorate T2DM symptoms, metabolic disorder, and gut microbiota imbalance of db/db mice, and it was superior to metformin in some aspects. We suggested for the first time that γ-aminobutyric(GABA) may be involved in the regulation of the microbiota-gut-brain axis(MGB) and thus affect the metabolic disorders associated with T2DM. This study will provide a scientific basis for the development of functional food with PTR.

Omicron variants have higher infectivity, more immune escape but lower risk of severe clinical outcomes than the ancestral variants. However, people are still wondering whether SARS-CoV-2 may become lethal again or whether some highly-pathogenic strain may emerge in the future. Omicron is more selective proliferation in the upper respiratory tract (URT). The temperature of human URT is 33–34°C, and the virus strains other than Omicron cannot replicate effectively at this temperature. While Omicron adapted to the low temperature environment, so its distribution mainly depends on the expression levels of ACE2 in cells. Similar distribution switch from lungs to URT has been observed for the 1918 H1N1 influenza virus, who vanished after 1921 and has been turned to be the seasonal human influenza A viruses. However, some relatively high-pathogenic SARS-CoV-2 strains and influenza-virus strains may still emerge in the future. Dynamic changes in the viral virulence should be monitored constantly.

The structural stability of γ-boron is investigated using Raman spectra under high pressures up to 126 GPa at ambient temperature. The pressure dependence of all the Raman-active modes of the γ-boron is reported. We also observe amusing changes within the B3g and B1g Raman-active vibrational modes, which results in the phenomenon of merging first and then separating of the Raman peaks. In addition to the Raman measurements, the changes in crystal structure and force constants are calculated to reasonably explain the discrepancy between the two Raman modes in response to pressure. The results of the continuous shifts for all Raman modes with increasing pressure indicate that γ-boron remains stable below this pressure value, with no changes in either symmetry or structure.

This study investigates optimal decisions in a green supply chain consisting of a manufacturer and a leading retailer considering the green marketing and fairness preferences of member firms. Four Stackelberg game decision models are constructed in which the manufacturer and the re-tailer engage in green marketing separately when the manufacturer has no and has fairness preferences. The impacts of fairness preferences and green marketing on the optimal decision in the green supply chain are comparatively analyzed. The study finds that member firms perform green marketing regardless of the presence or absence of fairness preferences and that such be-havior increases the wholesale price, retail price, and market demand of low-carbon products as well as the profits of member firms and the supply chain. A more interesting finding is that the profit growth of member firms and the supply chain due to the manufacturer’s green marketing is more pronounced than that due to the retailer’s green marketing. When the retailer and the manufacturer engage in conduct green marketing, the manufacturer's fairness preferences have different effects on the wholesale price, retail price, market demand, level of green marketing efforts, member enterprises and profits of supply chain. Therefore, firms should consider the impact of green marketing and fairness preferences to make pricing and performance decisions, so as to achieve efficient operation of the whole supply chain and avoid double marginal effects. Finally, the above conclusions are verified through numerical simulation, providing a reference for the decision-making of member firms in the green supply chain.

Thin twin-roll cast strips from a model Al-Cu-Mg-Li-Zr alloy with a small addition of Sc were prepared. A combination of a fast solidification rate and a favorable effect of Sc microalloying impacts the size and distribution of primary phase particles and the dimension of eutectic cells. Small interdendritic spacing in the range of 10-15 um enables substitution of the initial long-term homogenization annealing by a two-step annealing at 300 and 450 °C and a short solution treatment at 530 °C before quenching and the final age-hardening procedure. A dense dispersion of small Al3(Sc,Zr) precipitates intensively inhibiting recrystallization forms during this treatment. Further refining and fragmentation of the structure were performed using constrained groove pressing before the solution treatment. Small pre-straining of quenched specimens and subsequent age-hardening simulating T8 temper were used to promote the formation of a homogeneous distribution of strengthening particles and to suppress preferential heterogeneous precipitation on subgrain and grain boundaries. Microstructural features and microhardness evolution during annealing were critically examined and confronted with microstructural characteristics observed on reference mold cast alloy or alloys without Sc alloying. The proposed treatment represents a model near net shape procedure for manufacturing thicker sheets for the aerospace industry.

Molecular dynamics (MD) simulations present a sophisticated nano-scale computational approach that can play a critical role in material design for next generation batteries. One critical piece of information needed for MD simulations is the non-bonded potential parameters, which can be obtained through quantum mechanics (QM) calculations or experimental methods. However, experimental data is not available for exploratory and novel materials to derive the potential parameters. Also, the QM approach needs significant computational power and is too time consuming for large systems. On the other hand, current Artificial Intelligence techniques are faster, but they cannot be generalized across molecules and properties. As a result, there is a significant barrier to discovering and exploring new materials. Overcoming this barrier, in this work, we propose a Machine Learning (ML) based technique that can learn inter-atomic potential parameters for various particle-particle interactions employing QM calculations. This ML model can be used as an alternative for QM calculations for predicting non-bonded interactions in a computationally efficient manner. Using these parameters as input to MD simulations, we can predict a diverse range of properties, enabling researchers to design new and novel materials suitable for various applications in the absence of experimental data. We employ our ML-based technique to learn the Buckingham potential, a non-bonded interatomic potential. Subsequently, we utilize these predicted values to compute the densities of four distinct molecules, achieving an accuracy exceeding 93%. This serves as a strong demonstration of the efficacy of our proposed approach.

Regional Climatic Comfort Index (CCI) deteriorated significantly due to the climate change and anthropogenic interference. Knowledge regarding the long-term temporal dynamics of CCI in typical regions should be strengthened. In this study, we analyze the temporal and spatial evolution of CCI from 1969 to 2018 in Guangdong Province, based on meteorological indicators, including heat, humidity, wind and cloth loading etc.. Additionally, the population exposure to climate unconformity was examined since 1990 with the help of population data. Our study found that: (1) the warming and humidifying of the summer climate served as the main driving force for the continuous deterioration of CCI, with the comfortable days decreased by 1.06d/10a and the extremely muggy days increased by 2.83d/10a; (2) spatially, the lowest climate comfortability concentrated in southwestern Guangdong with more than 50 uncomfortable days each year, while the climate comfortability in northeastern Guangdong tends to deteriorated whit higher rate, which can reach as high as 6d/10a; (3) in summer, the population exposure to uncomfortable climate highly centralized in the Pearl River Delta, Shantou, Jieyang, and the surrounding areas, and both area and population exposure showed increasing trends. Particularly, Shenzhen held the highest growth rate of population exposure with an increase rate of 2.94 million/10a; (4) although the discomfort distribution and deterioration rate vary across the province, the spatial heterogeneity of comfortability is diminishing in Guangdong Province. This study will provide scientific reference for regional urban planning, thermal environment improvement, local resident health risk analysis, and key strategy implementation, etc.

The advancement of performance in the domain of flexible wearable strain sensors has become increasingly significant due to extensive research on laser-induced graphene (LIG). An innovative doping modification technique is required owing to the limited progress achieved by adjusting laser parameters to enhance LIG’s performance. By pre-treating with AgNO3, we successfully manufactured LIG with a uniform dispersion of silver nanoparticles across its surface. The experimental results for the flexible strain sensor exhibit exceptional characteristics, including low resistance (183.4 Ω), high sensitivity (426.8), a response time of approximately 150 ms, and a relaxation time of about 200 ms. Moreover, this sensor demonstrates excellent stability under various tensile strains and remarkable repeatability during cyclic tests lasting up to 8,000 s. Additionally, this technique yields favorable results in finger bending and hand back stretching experiments, holding significant reference value for preserving the inherent characteristics of LIG preparation in a single-step and in situ manner.

Questions：SAP in mountainous cities of China serve as crucial carriers for species and wild food, constituting potential green infrastructure. These patches should be recognized as locally specific resources. This study investigates the transformation characteristics of the landscape patterns of SAP, along with their elements, across urban-rural gradients, providing foundational support for the planning of conservation and utilization strategies. Location: Yongchuan area of Chongqing in southwest China. Methods: The study investigated urban-rural gradient-based transformation of SAP. A four-direction transect space was selected and divided into uniform sample squares. Fragstats 4.3 calculated the landscape index of SAP, and Spearman correlation coefficients in SPSS were used to evaluate the influence of landform and artificial factors on agroforestry patch transformation. Results: 1) Patch area (PA), Plaque density (PD), and CLUMPY of SAP systematically transform, showing increased SAP areas and higher connectivity with greater distance from the city, resulting in reduced patch fragmentation. However, Edge density (ED) and Largest plaque index (LPI) exhibit irregular transformation patterns. 2) With increased distance from the city, woodland patch area and connectivity increase, leading to decreased fragmentation, dispersal, and lower fractal dimensions. Conversely, Cultivated land follows the opposite trend. garden land patch area, fractal dimension, fragmentation, and dispersal all increase, while connectivity decreases. 3) Landscape pattern transformations of SPA are significantly influenced by artificial factors. Woodland patches are influenced similarly by landform and artificial factors. In contrast, cultivated land and garden land patches are more significantly impacted by artificial factors. Conclusions: SAP exhibit differentiated conservation and utilization measures across urban-rural gradients. Small patches located far from urban centers may benefit from systematic conservation measures to prevent further fragmentation and erosion in peri-urban areas.

Target recognition and fine-grained ship classification in remote sensing face the challenges of high inter-class similarity and sample scarcity. A transfer fusion-based ship image harmonization algorithm is proposed to overcome these challenges. This algorithm designs a feature transfer fusion strategy based on the combination of region aware instantiation and attention mechanism. Implement adversarial learning through image harmony generator and discriminator module to generate realistic remote sensing ship harmony images. Furthermore, the do-main encoder and domain discriminator modules are responsible for extracting feature representations of foreground and background, and further aligning ship foreground with remote sensing ocean background features through feature discrimination. Compared with other advanced image conversion techniques, our algorithm delivers more realistic visuals, improving classification accuracy for six ship types by 3% and twelve types by 2.94%, outperforming Sim2RealNet. Finally, a mixed dataset containing data augmentation and harmonizing samples and real data was proposed for the fine-grained classification task of remote sensing ships. Evaluation experiments were conducted on 8 typical fine-grained classification algorithms, and the accuracy of fine-grained classification for all categories of ships was analyzed. The experimental results show that the mixed dataset proposed in this paper effectively alleviates the long tail problem in real datasets, and the proposed remote sensing ship data augmentation framework performs better than state-of-the-art data augmentation methods in fine-grained ship classification tasks.

Desert ecosystem occupies an important position in the composition of global biodiversity. The Tarim Basin locates in south Xinjiang of China and has the world 's second largest mobile desert, the Taklamakan Desert. As an endemic species in this region, Phrynocephalus forsythii has been demonstrated with potential high extinction risk to climate change. In order to understand the overall genetic status and provide accordant conservation strategies of the species, we investi-gated the genetic diversity and population structure of P. forsythii from 15 sites in the Tarim Basin using 21 highly polymorphic microsatellite markers. We found significant genetic structure across the study region. We also revealed generally low levels of gene flow between the 25 sites, sug-gesting individual dispersal and migration may be restricted within populations. In addition, geographical distance and ambient temperature might be important factors in explaining the observed genetic structure. Our results will provide scientific basis for the future protection of P. forsythii in this area, as well as an important reference for the conservation and management of biodiversity in desert ecosystems.

In recent years, the analysis of macro- and micro-expression has drawn the attention of researchers since they provide visual cues of an individual's emotions for a broad range of potential applications such as lie detection and criminal detection. In this paper, we address the challenge of spotting facial macro- and micro-expression from videos and present compelling results by using a deep learning approach to analyze the optical flow features. Different from other deep learning approaches that are mainly based on Convolutional Neural Networks (CNNs), we propose a Transformer-based deep learning approach that predicts a score indicating the probability of a frame being within an expression interval. In contrast to other Transformer-based models that achieve high performance by being pre-trained on large datasets, our deep learning model, called SL-Swin, which incorporates Shifted Patch Tokenization and Locality Self-Attention into the backbone network Swin Transformer, effectively spots macro- and micro-expressions by being trained from scratch on small-size expression datasets. Our evaluation outcomes surpass the MEGC 2022 spotting baseline result, obtaining an overall F1-score of 0.1366. Additionally, our approach also performs well in the MEGC 2021 spotting task with an overall F1-score of 0.1824 and 0.1357 on CAS(ME)^2 and SAMM Long Videos, respectively. The code is publicly available on GitHub (https://github.com/eddiehe99/pytorch-expression-spotting).

Whether there is any inclination between structures and functions of antimicrobial peptides (AMPs) is a mystery yet to be unraveled. AMPs have various structures associated with many different antimicrobial functions, including antibacterial, anticancer, antifungal, antiparasitic and antiviral activities. However, none has yet reported any antimicrobial functional tendency within a specific category of protein/peptide structures nor any structural tendency of a specific antimicrobial function with respect to AMPs. Here we examine the relationships between structures categorized by three structural classification methods (CATH, SCOP and TM) and seven antimicrobial functions with respect to AMPs using an enrichment analysis. The results show that antifungal activities of AMPs were tightly related to two-layer sandwich structure of CATH, knottin fold of SCOP, and the first structural cluster of TM. The associations with knottin and TM cluster 1 even sustained through the AMPs with a low sequence identity. Besides, another significant mutual enrichment was observed between the third cluster of TM and anti-gram-positive-bacterial/anti-gram-negative-bacterial activities. The findings of the structure-function inclination further our understanding of AMPs and could help us design or discover new therapeutic potential AMPs.

Background: With the trend of intelligent display, the interface design of in-vehicle HUD is an expanding research field; Methods: To solve the subjectivity and uncertainty in the optimization of HUD interface design schemes, this paper proposed a hybrid scheme evaluation and optimization method based on entropy weight and VIKOR. The entropy weight method was used to reduce the subjectivity the decision-maker's weighting and obtain the objective weight of each indicator; The VIKOR method was used to obtain the best ranking of alternative schemes, and then the optimal interface design scheme was selected; Results: The evaluation of in-vehicle HUD interface design schemes were taken as an example for verification and calculation. The results showed that this method considers the subjectivity and uncertainty of the decision-making process in the optimization of design scheme, which can effectively improve the objectivity and accuracy of the evaluation results, and provide a reference for designers to optimize interface design schemes.

Heptanuclear {GdIII7} (complex 1) and tetradecanuclear {GdIII14} (complex 2) have been synthesized using a Rhodamine 6G ligand HL (Rhodamine 6G salicylaldehyde hydrazone) and characterized. Complex 1 has a rare disc-shaped structure, where the central Gd ion was connected to the peripheral six GdIII ions via CH3O-/μ3-OH- bridges. Complex 2 has an unexpected three-layer double sandwich structure with a rare μ6-O2- ion in the center of the cluster. Magnetic studies revealed that complex 1 exhibits a magnetic entropy change of 17.4 J kg−1 K−1 at 3 K and 5 T. On the other hand, complex 2 shows a higher magnetic entropy change of 22.3 J kg−1 K−1 at 2 K and 5 T.

This study investigated the effect of replacing part of the dietary soybean meal with either polymer-coated urea or gelatinized starch urea on the performance, nutrient digestibility, blood biochemical indexes, ruminal fermentation and rumen microflora of Angus heifers. The urea release profiles of two kinds of slow-release urea were evaluated in vitro and indicated a superior nitrogen retention with the polymer-coated urea. 210 purebred Angus cattle (BW = 314.26 kg) were divided into three groups: no urea group (CON), polymer-coated urea group (PCU), gelatinized starch urea group (GSU), 20g/kg polymer-coated urea or 25g/kg gelatinized starch urea was used to replace part of soybean meal in the concentrate feed respectively according to the principle of iso-metabolic energy and iso-nitrogenous. During the whole experiment, the ADG of PCU group was higher than both the GSU group and the CON group. The feed-weight ratio of the PCU group was significantly lower than both the GSU group and the CON group during the 90-day feeding period. The ADF apparent digestibility in the PCU group was significantly higher than that of the CON group, and extremely significantly higher than that of the GSU group. On the 86th day, the ALB content in the PCU group was significantly higher than that in the CON group. The contents of acetic acid and butyric acid, total volatile fatty acid and propionic acid were significantly higher in the PCU group than in the CON group. Bacterial diversity analysis found that the abundance of Firmicutes was higher in the PCU group than that in the GSU group and the CON group at the phylum level, and inverse result was observed in Bacteroidetes. The abundance of Paraprevotella was higher in the PCU group, whereas higher abundance of Prevotella was found in the GSU group at the genus level. These results indicate that both polymer-coated urea and gelatinized starch urea can replace part of soybean meal in the diet, and the amount of substitution in this trial had no diverse effect on the performance of Angus heifers, and the effect and economic benefits brought by polymer-coated urea were better than gelatinized starch urea.

In recent times, there has been significant enthusiasm for the development of all solid state batteries. This interest stems from a dual focus on safety—addressing concerns related to toxic and flammable organic liquid electrolytes—and the pursuit of high energy density. \cite{SCHNELL2018160,Zheng2018}. While liquid electrolyte batteries constitute for now the vast majority of commercial cells, solid electrolyte batteries show great promise. In parallel with experimental research, computational models \cite{GrazioliEtAlCM2016} clarify the several fundamental physics \cite{LiMonroeARCBM2020} that take place throughout battery operations. We review some classical models, emphasizing the conceptual advancements documented in the most recent works.

The possibility of using graphane monolayer crystals as the electrode material is becoming popular. Graphane is stable at room temperature and has large surface area, but its chemical inertness hinders its direct interactions with Li ions. In this study, we performed density functional theory calculations to study the energetic stability, structural and electronic properties of Li on graphane with various CH divacancy configurations (v12, v13 and v14 ). The results show that adsorption of Li atom reduces the formation energy of the CH divacancy configurations. The Li-v12 is most stable with the highest binding energy of 3.25 eV/Li and relaxes to in-plane with other C atoms. Altering the Li charge state to have Li−1-v12 or Li+1 -v12 affects the energetic stability and electronic characters of Li-v12 . The Li−1-v12 (Li +1-v 12 ) enhances (reduces) the binding force between Li and v 12 configuration, and furthermore it improves (deteriorates) the conductivity of the structure. Further investigation of graphane with vacancies is encouraged due to these intriguing observations, as it holds promise for potential utilization as an electrode material.

Li-rich manganese-based cathode materials (LRMs) are considered one of the most promising cathode materials for the next generation lithium-ion batteries (LIBs) because of their high energy density. However, there are problems such as capacity decay, poor rate performance, and continuous voltage drop, which seriously limit their large-scale commercial applications. In this work, Li1.2Mn0.54Co0.13Ni0.13O2 coated with Li2MoO4 with unique spinel structure was prepared by wet chemistry method and the subsequent calcination process. The Li2MoO4 coating layer with spinel structure can provide a 3D Li+ transport channel, which is beneficial for improving rate performance, while protecting LRMs from electrolyte corrosion, suppressing interface side reactions, and improving cycling stability. The capacity retention rate of LRMs coated with 3wt% Li2MoO4 increased from 69.25% to 81.85% after 100 cycles at 1C, and the voltage attenuation decreased from 7.06 to 4.98 mV per cycle. The lower Rct also exhibits improved magnification performance. The results indicate that the Li2MoO4 coating effectively improves the cyclic stability and electrochemical performance of LRMs.