We investigated the response of leaf photosynthetic capacity to climate warming and its variation among provenances of Larix gmelinii (Dahurian larch). Seedlings of 11 L. gmelinii provenances were transplanted into two common gardens with different climate conditions (control and warming climate). We measured the leaf photosynthetic capacity and explored its influencing factors. The warming treatment significantly increased the maximum net photosynthetic rate (Pmax-a), photosynthetic nitrogen use efficiency (PNUE), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), triose phosphate utilization rate (TPU), mesophyll conductance (gm), leaf nitrogen content (Narea), and chlorophyll content (Chlm). The Pmax-a was significantly positively associated with Vcmax, Jmax, TPU, gm, and Narea, and the slope of the correlations between Pmax-a and Vcmax, Jmax, and TPU was steeper in the warming treatment. The responses of Pmax-a, PNUE, Vcmax, Jmax, TPU, Narea, and Chlm to warming differed among provenances. The effects of warming on Pmax-a, Vcmax, Jmax, and TPU increased and then decreased as the aridity index of the original site increased. Overall, the warming treatment improved the photosynthetic capacity of L. gmelinii, but the extent of the improvement varied among provenances. These findings provide insights into the mechanisms underlying the responses of L. gmelinii to climate warming.

In-depth insights into the profound impacts of climate change and human activities on water resources are garnered through the dynamic changes in surface water, a crucial aspect of effective water resource management and the preservation of aquatic ecosystems. This paper introduces an innovative approach employing the random forest algorithm for the systematic extraction and monitoring of surface water at large regional or national scales. This method integrates spectral bands, spectral indices, and digital elevation model data, offering a novel perspective on this critical task. A data filling model is proposed to mitigate the impact of missing data due to cloud cover. Leveraging the capabilities of the Google Earth Engine (GEE), detailed information on surface water dynamics during the rainy and dry seasons in the Yangtze River Basin (YRB) from 1991 to 2021 is extracted using Landsat time series imagery. The analysis encompasses spatial-temporal variation characteristics and trends, with a specific focus on the intricate interplay between the areal extent of surface water and hydro-meteorological factors in each sub-basin of the YRB. Importantly, this includes considerations of potential groundwater contributions to surface water. Key findings from our research include: (1) Achieving a remarkable overall accuracy of 0.96 ± 0.03 in obtaining reliable surface water datasets with the support of GEE. (2) Identifying significant trends, such as a noteworthy increase in rainy season surface water bodies (+248.0 km2·yr−1) and a concerning decrease in surface ice/snow cover during both rainy and dry seasons, with change rates of −39.7 km2·yr−1 and −651.3 km2·yr−1, respectively. (3) Uncovering the driving mechanisms behind these changes, revealing positive correlations between the areal extent of rainy season surface water bodies and precipitation, as well as negative correlations between surface ice/snow cover area and average surface skin temperature. It is crucial to note that these driving factors exhibit variation among secondary river systems, underscoring the complexity of surface water dynamics. Furthermore, comparative analyses with existing surface water products are conducted, contributing to a deeper understanding of the advantages and uncertainties inherent in our proposed extraction method. The proposed method for large-scale surface water extraction not only enhances the monitoring of spatio-temporal surface water dynamics in the YRB but also provides valuable insights for the sustainable utilization and protection of water resources, considering the potential role of groundwater in supplementing surface water.

Rail impedance directly affects the transmission performance of track circuit . Considering the condition of earth stratification, for the difficult to calculate the rail impedance due to the semi-infinite integration interval and the oscillation of the integrand by using the Carson formula, The truncation method is proposed to divide the impedance formula is divided into definite integral and tail integral. The integral is approximated by the spline function, and the tail integral is calculated by using the exponential integral and Euler formula. Based on it, the rail impedance calculation formula of track circuit is obtained. The electromagnetic field model of track circuit with earth stratification is simulated by finite element method, and the correctness of the method is verified. Based on the formula, the influence of current frequency, soil depth and conductivity on rail impedance is studied. The relative error between the calculated results of rail impedance and the simulation results of finite element is within 5%. It can be seen that the formula has high accuracy and correctly reflects the law of rail impedance variation with current frequency, soil depth and resistivity. It provides a reliable reference for the theoretical calculation of rail impedance of track circuit.

Flow over a cluster of three equally spaced circular cylinders was studied by numerical simulation on base of the turbulent mode k-kl-ω for two incidence angles β=0° and 60°, at different Reynolds number,in this paper, flow interference pattern characteristics between cylinders, characteristics of force parameters and Strouhal number of each cylinder with different spacing ratios ranging from 1.5 to 4 at Re 8×104, 2×105and 2×106 had been obtained. At incidence angle β=0° and 60°, the wake was nearly symmetric if S/D≥2.0; at β=60°,S/D=1.5 and Re=2×105, the asymmetric periodic flow pattern occurred in the wake region which leaded to the significant effect on the surface mechanical parameters and Strouhal number which was found for the first time; the periodic flow regime of the wake region also occurred at S/D=1.35 and 1.5, without the same phenomenon at S/D=1.7 and 2.0; the phenomenon of periodic flow regime of the wake region was intrinsic and related to Reynolds number and space ratio. in addition, characteristics of force parameters of three cylinders mainly were affected by the interference between cylinders, at 1.5<S/D<4, which leaded to that the drag coefficient of three cylinders reduced with different Reynolds numbers. At incidence angle 60°, in subcritical and critical regime, the Strouhal numbers of the upstream cylinders were more than that of single cylinder, and with the enlargement of spacing ratio, the Strouhal number decreased; for the downstream cylinder , the Strouhal number is far less than that of single cylinder and with the enlargement of spacing ratio, the Strouhal number increases, which were another prominent flow inference influence. The results indicated the effect of flow interference between cylinders subjected to a cross flow over a cluster of three equally spaced cylinders on the flow pattern,surface mechanical parameters and Strouhal number.

In recent years, due to the low energy utilization of the whole life-cycle of buildings and the di-minished indoor and outdoor comfort of buildings and the impact on the surrounding environ-ment caused by the carbon emissions of the building life-cycle, the establishment of a whole life- cycle carbon emission model for buildings to improve their energy utilization at all stages of their life-cycle has received unprecedented attention. In China, the construction industry has become a major carbon emitter, and traditional houses, as a green development building type, are an effec-tive way to achieve carbon neutrality in buildings, but the existing green building evaluation system lacks quantitative indicators of carbon emissions in the building life-cycle. The exclusive evaluation indexes for regional and characteristic buildings, such as traditional houses, are ne-glected; This study explored the formula for calculating the life-cycle carbon emissions model of traditional residential houses under a carbon emission intervention and used real measurements of the physical environment and comparative analysis of the limitations of existing local stand-ards; The results showed that the carbon emission calculation formulas for each stage of the life-cycle of traditional residential houses must be established by combining the selection of local building materials, and the materials for sustainable energy and carbon sinks of green systems. Based on the results of indoor and outdoor heat and humidity environmental tests of residential houses and an analysis of the limitations of existing evaluation indexes due to locality, four im-portant factors affecting locality green buildings in terms of energy utilization, site ecology and landscape, land saving and material saving were extracted; on this basis, the whole life-cycle carbon emission model of traditional residential houses is constructed by combining the existing green building evaluation standards with the carbon emission indexes of the life-cycle of tradi-tional residential houses.

The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions. The study developed a novel method for evaluating the freshness of citrus fruits by integrating near-infrared spectroscopy with the nonlinear data processing capabilities of a BP neural network. This approach utilizes specific wavelength analysis to distinguish between fresh and non-fresh fruits effectively. Advanced preprocessing techniques are employed to remove spectral anomalies, enhancing the network's ability to accurately identify crucial quality indicators like sugar content. Concurrently, an experiment utilising a MATLAB-based BP neural network optimised the number of hidden layer nodes, identifying 61 as optimal. This configuration achieved impressive metrics, including a mean squared error of 0.0025665 and a root mean squared error of 49.8214, over 1000 training iterations with an 80% learning rate. The model demonstrated a high accuracy rate of 97.6275%, confirming its precision and reliability in assessing citrus freshness. This synergy between advanced neural network processing and spectroscopic techniques marks a significant advancement in agricultural quality assessment, setting new standards for speed and efficiency in data processing.

CO2 geological sequestration in coal seams can achieve the dual objectives of CO2 emission reduction and enhanced coalbed methane production, making it a highly promising carbon capture and storage technology. However, the injection of CO2 into coal reservoirs in the form of supercritical fluid (ScCO2) leads to complex physicochemical reactions with the coal seam, altering the properties of the coal reservoir and impacting the effectiveness of CO2 sequestration and methane production enhancement.In this paper, theoretical calculations based on ReaxFF-MD were conducted to study the interaction mechanism between ScCO2 and the macromolecular structure of both low-rank and high-rank coal, to address the limitations of experimental methods. The reaction of ScCO2 with low-rank coal and high-rank coal exhibits significant differences. At swelling stage, the low-rank coal experiences a decrease in aromatic structure and aliphatic structure, high-rank coal shows an increase in aromatic structure and a decrease in aliphatic structure, while swelling phenomenon is more pronounced in high-rank coal. At dissolution stage, low-rank coal is initially decomposed into two secondary molecular fragments, and then recombine to form new molecular structure, the aromatic structure increased and the aliphatic structure decreased. In contrast, high-rank coal occurs stretches-breakage-movement-reconnection, a reduction in aromatic structure and an increase in aliphatic structure.The primary reasons for these variations lie in distinct molecular structure compositions and the properties of ScCO2, leading to different reaction pathways of functional group and aromatic structure. The reaction pathways of functional groups and aromatic structures in coal can be summarized as follows: the breakage of the O-H bond in hydroxyl groups, the breakage of the C-OH bond in carboxyl groups, transformation of aliphatic structures into smaller hydrocarbon compounds or formation of long-chain alkenes, and various pathways involving broken, rearrangement, recombination of aromatic structures. In low-rank coal, there is a higher abundance of oxygen-containing functional groups and aliphatic structures. The breakage of O-H and C-OH chemical bonds results in the formation of free radical ions, while some aliphatic structures detach to produce hydrocarbons. Additionally, some of these aliphatic structures combine with carbonyl groups and free radical ions to generate new aromatic structures. Conversely, in high-rank coal, the lower content of oxygen-containing functional groups and aliphatic structures, along with stronger intramolecular forces, results in fewer chemical bond breakages and makes it less conducive to the formation of new aromatic structures.These results elucidate the specific deformations of different chemical groups, offering a molecular-level understanding of the interaction between CO2 and coal.

Taking a certain type of test centrifuge as the research object, the finite element model of the test centrifuge is established, the vibration characteristics and aerodynamic performance of the test centrifuge are analyzed, and the structural optimization design of the test centrifuge is carried out. In this paper, the load is applied according to the actual working condition of a certain type of test centrifuge. The vibration of the mounting seat of the test centrifuge is analyzed and the structure of the mounting seat is optimized. After optimization, the vibration of the mounting seat is 77.38 % lower than that of the original mounting seat. Then, the aerodynamic analysis of the test centrifuge is carried out. The analysis results show that the test centrifuge moves more smoothly under the whole package shell and the steady flow shell, and the resistance decreases and the shaft load decreases. Finally, the steady flow shell of the test centrifuge is optimized. The analysis shows that the increase of the width of the steady flow shell can reduce the resistance coefficient, which is helpful to the stability of the test centrifuge during operation and reduces the unbalanced response of the system caused by air resistance.

The TGACG motif-binding factor1 (TGA1) transcription factor, a significant protein in the bZIP transcription factor family, exhibits a myriad of functions, contributes to numerous biological events, and holds substantial application potential. In this study, our analysis revealed a diverse range of photoregulatory and hormone regulatory elements within the MtTGA1 promoter region. The expression profile of MtTGA1 indicated its highest expression in the root, with its regulation influenced by SA, ABA, BR, and GA. Under salt stress conditions, transgenic plants demonstrated significantly longer root lengths and heightened activities of antioxidant enzymes such as ascorbic acid catalase (APX), peroxidase (POD), catalase (CAT), and superoxide dismutase (SOD) in their roots and leaves compared to control plants. Simultaneously, the levels of endogenous hormones ABA and BR escalated in transgenic plants, with a marked change in the morphology of their leaf cells. Transcriptome analysis identified a total of 193 differentially expressed genes, implicating a wide array of biological processes. Furthermore, we found that MtTGA1 is able to interact with Medicago truncatula SPX domain containing protein 1 (SPX1). In conclusion, the MtTGA1 transcription factor plays a crucial role in enhancing salt tolerance, which provides new insights for improving plant survival under salt stress conditions.

Recent advances and demands in clinical applications drive a large amount of research to hydroxyapatite (HA) composite coatings fabricated by plasma spray. However, lower degree of HA crystallinity related to high temperature exposure in plasma spray usually leads to rapid weakening and disintegration of HA coatings and often promotes inflammatory responses in the surrounding tissue. In this research, graphene nanosheet (GNS) reinforced HA coatings were fabricated using plasma spray and followed by heat and hydrothermal treatment (hereafter referred to as thermal treatment). The addition of GNSs resulted in competing phenomenon to influence HA crystallinity viz. increased portion of the partially melted/unmelted zones and higher cooling rate during splat formation, leading to slight increase in HA crystallinity (~46.0-51.3%) in the as-sprayed coating. XRD and FTIR results showed that thermal treatment was capable of inducing significant transformation of amorphous HA to the crystalline form and removing other foreign non-HA compounds through regaining OH- ion, and therefore HA coatings displayed ~45.5-47.1% improvements in HA crystallinity regardless of addition or not of the GNS nanofillers. Microstructure observations revealed that thermal treatment enabled microcrack propagation due to stresses caused by crystallisation and phase transformations, and the residual partially melted/unmelted zone of the thermally treated GNS/HA coating was significantly decreased in size. More importantly, the added GNSs contributed greatly to the significant increase in surface nanoroughness of the thermally treated HA coatings owing to the fact that much more structural defects along with the GNSs mainly induced by thermal treatment might act as nucleation sites to accelerate HA nanoparticle precipitation, which would be beneficial for the improved adhesion strength of the osteoblast cells on the coating surface.

With superior optical properties, high flexibility in engineering its material properties, and strong capability for large-scale on-chip integration, graphene oxide (GO) is an attractive solution for on-chip integration of two-dimensional (2D) materials to implement functional integrated photonic devices capable of new features. Over the past decade, integrated GO photonics, representing an innovative merging of integrated photonic devices and thin GO films, has experienced significant development, leading to a surge in many applications covering almost every field of optical sciences. This paper reviews the recent advances in this emerging field, providing an overview of the optical properties of GO as well as methods for the on-chip integration of GO. The main achievements made in GO hybrid integrated photonic devices for diverse applications are summarized. The open challenges as well as the potential for future improvement are also discussed.

The sexual reproduction of ascomycetes is controlled by the mating-type(MAT) locus. (Pseudo)homothallic reproduction has been hypothesized based on genetic data from Hirsutella sinensis (Genotype #1 of Ophiocordyceps sinensis). In this study, the differential occurrence of the mating-type genes in the MAT1-1 and MAT1-2 idiomorphs, which constitute the genetic control of O. sinensis reproduction, was analyzed in 237 strains and 5 genomes of H. sinensis. The mating-type genes were differentially transcribed in H. sinensis Strain L0106, and the MAT1-2-1 transcript in H. sinensis Strain 1229 was alternatively spliced, with an unspliced intron I containing stop codons; these findings constitute O. sinensis reproduction controls at the transcriptional and coupled transcriptional-translational levels. The occurrence of the mating-type genes and a-/α-pheromone receptor genes differed among the 5 H. sinensis genomes. The differential occurrence and transcription of these genes are inconsistent with self-fertilization under (pseudo)homothallism but suggest self-sterility of H. sinensis, which therefore needs a mating partner to achieve sexual outcrossing under heterothallism or hybridization. Consistent occurrence and transcription of the mating-type genes of both the MAT1-1 and MAT1-2 idiomorphs have been reported in natural and cultivated Cordyceps sinensis, but these findings are insufficient to determine the reproduction mode(s) because of the co-occurrence of >90 fungal species and multiple genomically independent genotypes of O. sinensis. The mutant MAT1-1-1 and α-pheromone receptor transcripts in natural C. sinensis result in the N-terminus or middle-truncated proteins, with changes in hydrophobicity and secondary structures of the proteins, suggesting heterogeneous fungal source(s) of the proteins and hybridization reproduction.

Objective: To evaluate the effect of propofol combined with psychological intervention on pain and emotional evaluation in painless colonoscopic colonic polypectomy patients undergoing endoscopic mucosal resection (EMR).Methods: A total of 80 patients who underwent painless colonoscopic colonic polypectomy with EMR treatment between June 2020 and June 2022 were selected in order of admission and divided into two groups. The control group received conventional analgesia, while the observation group received propofol combined with psychological intervention. Pain visual analog scale (VAS) and emotional scale were used to evaluate pain and emotions in both groups of patients. Adverse reactions and clinical efficacy were also compared between the two groups.Results: The two groups of patients were generally comparable with no significant differences (P > 0.05). The VAS score in the observation group was significantly lower than that in the control group (P < 0.05), and the emotional scale score was also improved compared to the control group (P < 0.05). The number of patients with adverse reactions in the observation group was less than that in the control group. The clinical effective rate in the observation group was significantly higher than that in the control group (P < 0.05).Conclusion: Propofol combined with psychological intervention can effectively alleviate pain and improve emotional status in painless colonoscopic colonic polypectomy patients undergoing EMR treatment, thereby increasing the comfort and success rate of the surgery. The number of patients with adverse reactions in the observation group was less than that in the control group, and the clinical effective rate in the observation group was significantly higher than that in the control group (P < 0.05).

Background The spread of COVID-19 continues, the mutation of SARS-COV-2 is still difficult to control, and the need for antiviral drugs to treat COVID-19 remains urgent. The use of arbidol in the treatment of COVID-19 is limited and controversial. Methods To clarify the efficacy of arbidol on COVID-19, we collected 25 cases and 178 related studies. We analyzed the treatment information of arbidol based on the obtained cases, expanded the scope of the study, and collected current studies on the treatment of COVID-19 in various databases for in-depth analysis. Results History analysis showed that arbidol was effective (76% cure rate) compared with other drugs. However, compared with other antiviral drugs or standard therapy, the arbidol group had no significant advantage in reducing the time to negative virus transformation, length of hospital stays, or improvement in CT (MD=0.22, 95%CI -0.29-0.73; MD = 0.61, 95% CI 1.46 to 2.67; RR=1.15, 95%CI 0.88-1.50); Analysis of adverse events showed no significant difference between the arbidol group and the other groups (RR=0.82, 95%CI 0.25-2.71). Conclusion Our study showed that arbidol had no significant effect on COVID-19, but showed a slight advantage in CT improvement and adverse events. Our study objectively evaluated the efficacy of arbidol in the treatment of COVID-19 and provided some guidance for arbidol in the treatment of COVID-19.

Intergenerational integration has given rise to a novel aging paradigm known as all-age communities, which is garnering international attention. In China, the aging population and the implementation of the three-child policy have resulted in increased demand for retirement and childcare services among residents in older neighborhoods. Consequently, there is a pressing need to retrofit these older neighborhoods to accommodate all-age living arrangements given the high demand they generate. Therefore, this study undertakes research interviews with residents and constructs an exploratory theoretical model rooted in established theory. To assess the significance of our model, we employ Smart PLS 3.0 based on 297 empirical data points. Our findings indicate that anxiety has a significant negative effect on payment behavior; objective perception, willingness to pay, and government assistance exert significant positive effects on payment behavior. By comprehensively analyzing the mechanisms underlying residents’ payment behavior, this study provides valuable insights to the government for promoting the aging process within communities and formulating effective transformation policies.

The power converter is the significant device in a wind power system. Wind turbine will be shut down and off grid immediately with the occurrence of the IGBT module open-circuit fault of power converter, which will seriously impact the stability of grid and even threaten personal safety. However, in the existing diagnosis strategies of power converter, there are few single and double IGBT modules open-circuit fault diagnosis methods producing negative results including erroneous judgment, omissive judgment and low accuracy. In this paper, a novel method to diagnose the single and double IGBT modules open-circuit faults of the permanent magnet synchronous generator (PMSG) wind turbine grid-side converter (GSC) is proposed. Above all, collecting the three-phase current varying with wind speed of 22 failure states including a normal state of PMSG wind turbine GSC as the original signal data. Afterward, the original signal data are decomposed by using variational mode decomposition (VMD) to obtain the mode coefficient series, which are analyzed by the proposed method base on fault trend feature for extracting the trend feature vectors. Finally, the trend feature vectors are used as the input of deep belief network (DBN) for decision-making and obtaining the classification results. The simulation and experimental results show that the proposed method can diagnose the single and double IGBT modules open-circuit faults of GSC, and the accuracy is higher than the benchmark models.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

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.

Automobile proving ground is important for the research of vehicles which is used for the vehicle dynamics, durability testing, braking testing, etc. However, the roads in automobile proving ground will inevitably be damaged with the extension of the service life. In most previous researches, equipment similar to laser cross-section was used to detect pavement quality, the principle of which was to reflect pavement quality by detecting road surface roughness. This method ignores the elastic deformation of the roads itself when the vehicle is traveling on it and hardly compensate for the amendment. Therefore, this article presents a new method based on force sensor to reduce the impact of elastic deformation such as wheel tyre deformation, pavement deformation, and wheel rim deformation. In which, force sensors mounted on the wheels collect the three-dimensional dynamic load of the wheel.The presented method has been tested with two sets of cobblestone road load data, and the results show that The　incentives imposed by the test vehicle on the target road are 88.3%, 91.0%, and 92.05% of the incentives imposed by the test vehicle on the standard road in three dimensions, respectively. It is clear that the proposed method has strong potential effectiveness to be applied for lose detection of the special road application.

Juvenile idiopathic arthritis (JIA) is a disease with unknown causes within all forms of arthritis in children under 16 years of age. The diagnosis is made when another joint pathology is excluded. Difficulties in early and differential diagnosis lead to the rapid disability of patients and an unfavourable life prognosis. Therefore, timely diagnosis is necessary to prevent irreversible damage to the joints and preserve their function. Due to the widespread use of new technologies, modern multimodal imaging has gained recognition, which includes X-ray, ultrasound, and MRI. The combination of methods plays a key role in confirming the diagnosis, monitoring disease activity, prognosis during the course, and outcome in children with JIA. Each method has its own advantages and disadvantages. The introduction of the method of passive microwave radiometry (MWR), in combination with other imaging methods, makes it possible to expand the possibilities of screening the disease in the preclinical and early clinical phases.

Achieving the dual development of rural revitalization and urbanization is an important strategic goal of China’s current modernization. Rural population and settlements are the main components of the countryside in traditional agricultural areas, and play an important role in the development of the countryside itself in terms of urban and rural land use and in the formation of urban and rural development patterns. This study analyzes the spatial and temporal changes in rural populations and settlements at the township level, as well as the degree and type of coupled development. A framework for urban–rural development relationships based on different types of coupled development is proposed, and a model of urban–rural forces is constructed to derive the spatial pattern of urban–rural development at the township level that may be formed in the future. Our study shows that the rural population and settlements in the study area are characterized by significant spatial and temporal dynamics, indicating that traditional rural areas are in a process of rapid development and change. The results of the township-level coupling measurements present four types of development in terms of the spatial pattern of urban–rural development: A-type is most likely to produce new cities or satellite towns in the Jixi–Harbin–Qiqihar area in the future; B-type is the fastest dying area in the future, located in the Harbin and Qitaihe clusters, with a tendency to merge into Harbin; C-type is the area to be focused on in the future to attract population and strictly control the growth of the rural settlement area to avoid it turning into B-type; D-type may develop regional township centers in the future in the combined area of Jiamusi City, Suihua City and Mudanjiang City. The results of the study provide experience in realizing rural revitalization according to local conditions. The new spatial pattern of urban–rural development provides an important reference for formulating land use policies, optimizing urban–rural land allocation and realizing integrated urban–rural development strategies.

The pore-throat radius of shale oil reservoir is extremely small, and it is difficult to accurately obtain the absolute permeability and oil-water two-phase relative permeability of actual oil reservoir through conventional core experiments. However, these parameters are very important for reservoir numerical simulation. In this paper, a method for characterizing flow parameters based on pore network model that considers differential pressure flow and diffusion flow is proposed. Firstly, a digital core was reconstructed using focused ion beam scanning electron microscopy (FIB-SEM) from the Gulong shale reservoir in the Songliao Basin, China, and a pore network model was extracted. Secondly, quasi-static single-phase flow and two-phase flow equations considering diffusion were established in the pore network model. Finally, pore throat parameters, absolute permeability, and oil-water two-phase permeability curves were calculated, respectively. The results show that the pore throat distribution of Gulong shale reservoir is mainly concentrated in the nanometer scale, the mean pore radius is 87 nm, the mean throat radius is 41 nm, and the mean coordination number is 3.97; The calculated permeability considering diffusion is 0.000124mD, which is approximately twice the permeability calculated without considering diffusion; The irreducible water saturation of the Gulong shale reservoir is approximately 0.26, and the residual oil saturation is approximately 0.73. The method proposed in this paper can provide an important approach for characterizing the flow parameters of similar shale oil reservoirs.

Immersion in salt-lake solution was adopted to periodically test the concrete chloride-ion diffusion coefficient. The regression analysis was also completed. Also investigated was the time-dependent law of concrete chloride-ion diffusion coefficient with time. The influence of chloride-ion concentration in solution, water-to-cement ratio, and corrosion time on the largeness and accumulation rate of the concrete chloride-ion diffusion coefficient was also analyzed. Test results show that the concrete chloride-ion diffusion coefficient gradually decreased with increasing time and increased with increasing chloride-ion concentration in a salt lake . Taking into account the influence of factors such as water–binder ratio, chloride-ion concentration, and time-varying characteristics, a multi-factor calculation model for the concrete chloride-ion diffusion coefficient was established. Combining the prediction results and the measured data reported in this paper, the effectiveness and applicability of the established concrete chloride-ion diffusion coefficient calculation model were compared and verified, and the durability design and service life of a concrete structure under cool chlorine were compared. The results of analysis provide important boundary conditions.

A large body of research has examined people’s attitudes toward mandatory vaccination to cope with the COVID-19 pandemic. However, studies have yet to explore how Chinese people view the COVID-19 vaccine mandates, let alone placing such views in the country’s highly politicized context. On the other hand, facing the high pressure of loosening its zero-COVID policies amidst the worldwide practices of co-existing with the COVID-19 virus, the country has to improve its vaccination coverage quickly. In this situation, it is more than necessary to systematically investigate the Chinese public’s attitude to mandatory vaccination against the virus and the underlying determinants. The current study utilizes data from a national survey adopting quota sampling to analyze the Chinese public’s medical and non-medical considerations when judging compulsory COVID-19 vaccination. The study reveals that thanks to China’s successful lockdown policies, personal risk, and benefit perceptions did not dominate their views regarding vaccination mandates. Instead, conspiracy beliefs regarding the pandemic outbreaks, conspiratorial thinking, and nationalism more strongly predicted their willingness to accept mandatory vaccination. Given the potentially massive impacts of the COVID-19 infection, if China opens its door and loosens its strict quarantine restrictions, the Chinese public needs to be educated with more medically valuable and relevant information to improve their vaccination protection against COVID-19.

A series of Ti₄₀Zr₂₅Cu₉Ni₈Be₁₈)_100-xTM_x (x = 0, 1, 2, 3, 4 at.%, TM = Nb, Y) Bulk amorphous alloys were designed and prepared using the copper mold casting method. The microstructures, glass forming ability and mechanical properties of the alloys were investigated by means of X-ray diffractometry (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), differential scanning colorimetry (DSC), depth-sensitive nanoindentation and uniaxial compressive test. The Bulk amorphous alloys with different ductility were investigated by measuring their plastic deformation energy (PDE) of the first pop-in events during loading. The relationships between the PDE value, shear band formation and ductility in Bulk amorphous alloys have been investigated. The results show that the PDE value decreases by the Nb addition and promotes the generation of multiple shear bands easily, which increase the fracture strength and plasticity significantly. Substituting Nb with Y has exactly the reverse effect. A useful rule for preparing of Bulk amorphous alloys with high plasticity is herein proposed, whereby the chemical composition of the Bulk amorphous alloys can be tailored to possess a lower PDE value.

The Kerr nonlinear optical performance of silicon nanowire waveguides integrated with 2D layered graphene oxide (GO) films is theoretically studied and optimized based on experimentally measured linear and nonlinear optical parameters of the GO films. The strong mode overlap between the silicon nanowires and highly nonlinear GO films yields a significantly enhanced Kerr nonlinearity for the hybrid waveguides. A detailed analysis for the influence of waveguide geometry and GO film thickness on the propagation loss, nonlinear parameter, and nonlinear figure of merit (FOM) is performed. The results show that the effective nonlinear parameter and nonlinear FOM can be increased by up to ≈52 and ≈79 times relative to bare silicon nanowires, respectively. Self-phase modulation (SPM)-induced spectral broadening of optical pulses is used as a benchmark to evaluate the nonlinear performance, examining the trade-off between enhancing Kerr nonlinearity and minimizing loss. By optimizing the device parameters to balance this, a high spectral broadening factor of 27.6 can be achieved ‒ more than 6 times that achieved in previous experiments. Finally, the influence of pulse chirp, material anisotropy, and the interplay between saturable absorption and SPM is also discussed. These results provide useful guidance for optimizing the Kerr nonlinear optical performance of silicon waveguides integrated with 2D layered GO films.

This paper aims to build up a preference function to evaluate the public benefits of the type of agricultural farming, biodiversity, water provisions, land use type, ecotourism modes, and a monetary attribute (environmental trust fund and willingness to contribute) associated with an ecosystem service and land use program in a forest park. This study used the choice experiments to build a random utility model, analyze the average preference for the above land use attributes based on the conditional logit and used a latent class model to test the resident’s heterogeneous preferences for land use planning in the forest park. We also estimated the welfare derived from various land use programs. The empirical result had shown that: (1) increasing organic farming area, maintaining the status quo of species biodiversity, increasing the surface water provision, increasing the area of custom flora, increasing the wetland area, and setting up an integrated framework for ecotourism increase the public’s preference for the land use program; (2) we found that farmer and non-farmer haven’t the same land use preferences; (3) the ecotourism development program incorporating biodiversity, organic farming, ethnobotany, and wetland area with integrated ecotourism are more preferred than other land use program scenarios.

The adsorption of supramolecular composites for Cs(I) in high level liquid waste (HLLW) are different due to different carriers. We chose 25,27-bis(ethyl)-calix[4]arene-26,28-crown-6 (EC[4]C6) as adsorbent, SiO2-P, XAD-7 and UiO-66 as carriers. The synthesis and characterization of supramolecular EC[4]C6 loaded with three different carriers were presented. SEM, N2 adsorption/desorption isotherms, TG-DSC spectra, FT-IR spectra results shown that EC[4]C6 was successfully introduced into the pores of carriers via physical intermolecular interactions. EC[4]C6/SiO2-P, EC[4]C6/XAD-7 and EC[4]C6/UiO-66 shown high efficiency, high selectivity towards Cs(I) over 18 typical fission or corrosion products in HNO3 solution. The adsorption properties of the three materials were investigated after electron irradiation. These results demonstrate that EC[4]C6/SiO2-P possess greater potential for highly efficient removal of Cs(I) from HLLW.

We studies the initial value problem for the fractional Navier-Stokes-Coriolis equations, which obtained by replacing the Laplacian operator in the Navier-Stokes-Coriolis equation by the more general operator $(-\Delta)^\alpha$ with $\alpha>0$. We introduce function spaces of the Besove type characterized by the time evolution semigroup associated with the general linear Stokes-Coriolis operator. Next, we establish the unique existence of global in time mild solutions for small initial data belonging to our function spaces characterized by semigroups in both the scaling subcritical and critical settings.

Streptococcus suis is a zoonotic pathogen causing serious infections in both swine and humans. Although metals are essential for life, excess amounts of metals they are toxic to bacteria. when accumulated in excess amounts. Except for zinc, Transcriptome-level data of the mechanisms for resistance to metal-induced toxicity in S. suis are available for no metals other than zinc. have not been investigated from the transcriptome level in S. suis. Herein, we explored the transcriptome-level changes of in S. suis in response to ferrous iron and cobalt toxicity by RNA sequencing. Many A lot of genes were differentially expressed in the presence of excess ferrous iron and cobalt. Most of the genes in response to cobalt toxicity showed the same expression trends as those were expressed in the same trend in response to ferrous iron toxicity. qRT-PCR analysis of the selected genes confirmed the accuracy of RNA sequencing results. Bioinformatics analysis of the differentially expressed genes indicated that ferrous iron and cobalt have similar impacts effects on the cellular processes of S. suis. Treatment with ferrous Ferrous iron treatment resulted in down-regulation of several oxidative stress tolerance-related genes involved in oxidative stress tolerance and up-regulation of the genes in an amino acid ABC transporter operon. Expression of the several genes in the arginine deiminase system was down-regulated in the presence of after ferrous iron and cobalt treatment. Collectively, our results suggested that S. suis alters the expression of a lot of multiple genes to respond to ferrous iron and cobalt toxicity.

Estimation of breeding values through Best Linear Unbiased Prediction (BLUP) using pedigree-based kinship and Marker-Assisted Selection (MAS) are the two fundamental breeding methods used before and after the introduction of genetic markers, respectively. The emergence of high-density genome-wide markers has led to the development of two parallel series of approaches inspired by BLUP and MAS, which are collectively referred to as Genomic Selection (GS). The first series of GS methods alters pedigree-based BLUP by replacing pedigree-based kinship with marker-based kinship in a variety of ways, including weighting markers by their effects in genome-wide association study (GWAS), joining both pedigree and marker-based kinship together in a single-step BLUP, and substituting individuals with groups in a compressed BLUP. The second series of GS methods estimates the effects for all genetic markers simultaneously. For the second series methods, the marker effects are summed together regardless of their individual significance. Instead of fitting individuals as random effects like in the BLUP series, the second series fits markers as random effects. Differing assumptions regarding the underlying distribution of these marker effects have resulted in the development of many Bayesian-based GS methods. This review highlights critical concept developments for both of these series and explores ongoing GS developments in machine learning, multiple trait selection, and adaptation for hybrid breeding. Furthermore, considering the increasing use and variety of GS methods in plant breeding programs, this review addresses important concerns for future GS development and application, such as the use of GWAS-assisted GS, the long-term effectiveness of GS methods, and the valid assessment of prediction accuracy.

The fluid seepage in local-saturated zone of subgrade promotes the migration of fine particles in the filler, resulting in the change of pore structure and morphology of the filler and the deformation of solid skeleton, which affects the fluid seepage characteristics. Repeatedly, the muddy interlayer, mud pumping and other diseases are finally formed. Based on the theory of two-phase seepage, the theory of porous media seepage, and the principle of effective stress in porous media, a two-phase fluid-solid coupling mathematical model in local-saturated zone of subgrade considering the effect of fine particles migration is established. The mathematical model is numerically calculated with the software COMSOL Multiphysics○R, the two-phase seepage characteristics and the deformation characteristics of the solid skeleton in local-saturated zone of the subgrade are studied. The research results show that due to the continuous erosion and migration of fine particles in local-saturated zone of the subgrade, the volume fraction of fine particles first increases then decreases and finally becomes stable with the increase of time. And the volume fraction of fine particles for the upper part of the subgrade is larger than that for the lower part of the subgrade. The porosity, the velocity of fluid, the velocity of fine particles, and the permeability show a trend of increasing first and then stabilizing with time; the pore water pressure has no significant changes with time. The vertical displacement increase first and then decrease slightly with the increase of time, and finally tend to be stable. For a filler with a larger initial volume fraction of fine particles, the maximum value of the volume fraction of fine particles caused by fluid seepage is larger, and the time required to reach the maximum value is shorter. It can be concluded that in actual engineering, the volume fraction of fine particles in the subgrade filler should be minimized on the premise that the filler gradation meets the requirements of the specification.

High dimensional statistical analysis for the yield of large-scale circuits is quite difficult due to expensive simulations, especially for the memory circuits with high sigma requirement (e.g., SRAM). In this paper, we developed an efficient sparse additive model to substitute simulations. To fit high sigma region accurately, the modeling center is moved to near failure boundary searched by scaling the shape of sampling function. To solve the model efficiently, the process variables are grouped by standard cells so that the model can be solved by our developed blockwise greedy algorithm. The experiments on the 28nm memory circuits validate that our method achieves high accuracy and efficiency compared with other state-of-art works.

The genetic diversity of coronavirus (CoV) is high, and its infection in animals has not yet been fully revealed. By RT-PCR detection of partial RNA dependent RNA polymerase (RdRp) gene of CoV, we screened a total of 502 small mammals belonging to 18 species in 12 genera and 4 orders collected in Dali and Nujiang Prefecture of Western Yunnan Province, China. The prevalence of β-CoV in Chevrieri's field mouse (Apodemus chevrieri) and Lancangjiang field mouse (A. ilex) were 3.54% (4/113) and 6.67% (6/90), respectively; the prevalence of α-CoV in White-footed Indochinese rat (Rattus nitidus) and long-tailed red-toothed shrew (Episoriculus leucops) was 75% (3/4) and 5.88% (1/17), respectively. The co-infection rates of β-CoV and α-CoV in Kachin red-backed vole (Eothenomys cachinus), Norway rat (R. norvegicus) were 2.22% (2/90), 3.85% (1/26) respectively. The identity of the partial RdRp genes obtained of 13 strains of β-CoV was 83.42%-99.23% at nucleotide level, and it is worth noting that the two strains from Kachin red-backed vole showed highly homology to BOV-36/IND/2015 from Indian bovine and DcCoV-HKU23 from one-humped camel (Camelus dromedarius) in Morocco, the nucleotide similarity between 97.86%-98.33%. Similarly, the identity of the 7 strains of α-CoV among the partial RdRp sequences was 94.00%-99.18% at nucleotide levels. The viral load in different tissues was measured by quantitative RT-PCR (qRT-PCR). The average CoV viral load in small mammalian intestinal tissue was 1.25×106copies/g, differently, the mean CoV viral load in liver, heart, lung, spleen and kidney tissue was from 1.29×103 to 4.02×103copies/g, which revealed that CoV has extensive tropism of intestinal tissue in small mammals (P &lt; 0.0001). This result revealed the genetic diversity, epidemiology, and infective tropism of α-CoV and β-CoV in small mammals from Dali and Nujiang, which deepens the comprehending of the retention and infection of coronavirus in natural hosts.

The development of cost-effective methods for estimating hydraulic conductivity profiles has been an ongoing effort in the field of engineering practice, which can be used to increase availability to clarify the hydrogeological complexity of fractured rock aquifers for the aid of solving groundwater-related problems. A methodology is presented, which combines electrical well logs, fluid conductivity logs, double packer hydraulic tests, Archie’s law, and the Kozeny-Carman-Bear equation to investigate relations between formation factor and hydraulic conductivity. This method was applied to develop hydraulic conductivity profiles based on the data collected from 88 boreholes in Taiwan's mountainous areas. The investigation results include: (1) Well logging signals were suggested to be categorized by rock types to establish effective relationships with hydraulic conductivity. (2) Removing the mud-bearing section data with two proposed data clustering techniques could effectively enhance the correlation between the formation factor and hydraulic conductivity. (3) The predictive models for estimating hydraulic conductivity have been developed for sandstone, schist, and slate. (4) The prevalence of clay content in most of Taiwan's mountainous rock formations has been found, which implies that careful consideration of clay-related issues in complex geologic formations is essential while applying Archie's law theory.

A switchable and tunable terahertz (THz) metamaterial based on photosensitive silicon and Vanadium dioxide (VO2) was proposed. By using finite-difference time-domain (FDTD) method, the transmission and reflective properties of the metamaterial were investigated theoretically. The results imply that, the metamaterial can realize a dual electromagnetically induced transparency (EIT) or two narrow-band absorption depending on the temperature of the VO2. Additionally, the magnitude of the EIT and two narrow-band absorption can be tuned by varying the conductivity of photosensitive silicon (PSi) via pumping light. Correspondingly, the slow light effect accompanying the EIT can also be adjusted.

Lasiodiplodia theobromae, as one of the causing agents associated with Chinese hickory trunk cankers, has caused huge economic losses to the Chinese hickory industry due to its extremely strong pathogenicity. Though the biological characteristics of this pathogen and the occurrence pattern of this disease have been reported, few studies have focused on investigating the mechanisms responsible for L. theobromae survival strategies and pathogenicity. The high-quality genome data and the efficient transformation system are the basis for researching above mechanism events. In this study we sequenced and assembled L. theobromae strain LTTK16-3, and established the first protoplasmic preparation method and polyethylene glycol (PEG) -mediated genetic transformation system for L. theobromae. These genetic information and transformation methods established the foundation for the future mechanisms study of L. theobromae and set up the possibility of targeted molecular improvements for Chinese hickory canker control.

In the moist environment of soil-water-air, there is a problem of low accuracy in monitoring Volatile Organic Compounds (VOCs) using a Photoionization Detector (PID). This paper analyzes the reasons for the low accuracy of the traditional Support Vector Machine (SVM) regression method. To address the issue, the PID signal is subjected to feature extraction and Principal Component Analysis (PCA) to reduce the data dimensionality. Moreover, the optimal SVM parameters are selected using a Genetic Algorithm (GA), and a combined approach of SVM regression with PCA and GA is utilized for PID signal regression analysis. And the effectiveness of the method is validated through extensive experiments and simulations. Furthermore, the influence of the sample quantity on the regression accuracy is analyzed, enabling accurate monitoring of VOCs concentration in a moist environment.

We experimentally demonstrate enhanced spectral broadening of femtosecond optical pulses after propagation through silicon-on-insulator (SOI) nanowire waveguides integrated with two-dimensional (2D) graphene oxide (GO) films. Owing to the strong mode overlap between the SOI nanowires and the GO films with a high Kerr nonlinearity, the self-phase modulation (SPM) process in the hybrid waveguides is significantly enhanced, resulting in greatly improved spectral broadening of the femtosecond optical pulses. A solution-based, transfer-free coating method is used to integrate GO films onto the SOI nanowires with precise control of the film thickness. Detailed SPM measurements using femtosecond optical pulses are carried out, achieving a broadening factor of up to ~4.3 for a device with 0.4-mm-long, 2 layers of GO. By fitting the experimental results with theory, we obtain an improvement in the waveguide nonlinear parameter by a factor of ~3.5 and the effective nonlinear figure of merit (FOM) by a factor of ~3.8, relative to the uncoated waveguide. Finally, we discuss the influence of GO film length on the spectral broadening and compare the nonlinear optical performance of different integrated waveguides coated with GO films. These results confirm the improved nonlinear optical performance for silicon devices integrated with 2D GO films.

We theoretically investigate and optimize four-wave mixing (FWM) in silicon nitride (SiN) waveguides integrated with two-dimensional (2D) layered graphene oxide (GO) films. Based on extensive previous measurements of the material parameters of the GO films, we perform detailed analysis for the influence of device parameters including waveguide geometry, GO film thickness, length, and coating position on the FWM conversion efficiency (CE) and conversion bandwidth (CB). The influence of dispersion and photo-thermal changes in the GO films is also discussed. Owing to the strong mode overlap between the SiN waveguides and the highly nonlinear GO films, FWM in the hybrid waveguides can be significantly enhanced. We obtain good agreement with previous experimental results and show that by optimizing the device parameters to balance the trade-off between Kerr nonlinearity and loss, the FWM CE can be improved by as much as ~20.7 dB and the FWM CB can be increased by ~4.4 folds, relative to the uncoated waveguides. These results highlight the significantly enhanced FWM performance that can be achieved in SiN waveguides by integrating 2D layered GO films.

Layered two-dimensional (2D) GO films are integrated with silicon-on-insulator (SOI) nanowire waveguides to experimentally demonstrate an enhanced Kerr nonlinearity, observed through self-phase modulation (SPM). The GO films are integrated with SOI nanowires using a large-area, transfer-free, layer-by-layer coating method that yields precise control of the film thickness. The film placement and coating length are controlled by opening windows in the silica cladding of the SOI nanowires. Owing to the strong mode overlap between the SOI nanowires and the highly nonlinear GO films, the Kerr nonlinearity of the hybrid waveguides is significantly enhanced. Detailed SPM measurements using picosecond optical pulses show significant spectral broadening enhancement for SOI nanowires coated with 2.2-mm-long films of 1−3 layers of GO, and 0.4-mm-long films with 5−20 layers of GO. By fitting the experimental results with theory, the dependence of GO’s n₂ on layer number and pulse energy is obtained, showing interesting physical insights and trends of the layered GO films from 2D monolayers to quasi bulk-like behavior. Finally, we show that by coating SOI nanowires with GO films the effective nonlinear parameter of SOI nanowires is increased 16 fold, with the effective nonlinear figure of merit (FOM) increasing by about 20 times to FOM > 5. These results reveal the strong potential of using layered GO films to improve the Kerr nonlinear optical performance of silicon photonic devices.

To improve the accuracy of short-term multi-energy load prediction models for integrated energy systems, the historical development law of the multi-energy loads must be considered. Moreover, understanding the complex coupling correlation of the different loads in the multi-energy systems and accounting for other load-influencing factors, such as weather, may further improve the forecasting performance of such models. In this study, a two-stage fuzzy optimization method is proposed for the feature selection and identification of the multi-energy loads. To enrich the information content of the prediction input feature, we introduced a copula correlation feature analysis in the proposed framework, which extracts the complex dynamic coupling correlation of multi-energy loads and applies Akaike information criterion (AIC) to evaluate the adaptability of the different copula models presented. Furthermore, we combined a NARX neural network with Bayesian optimization and an extreme learning machine model optimized using a genetic algorithm to effectively improve the feature fusion performances of the proposed multi-energy load prediction model. The effectiveness of the proposed short-term prediction model was confirmed by the experimental results obtained using the multi-energy load time-series data of an actual integrated energy system.

Under the double pressure of climate change and human activities, the restrictions of conservation policies and the increasing area of overlap between wildlife conservation areas and community living areas have led to increase conflicts and contradictions between nature reserves and neighboring communities. Effective management of such conflicts is particularly important in order to achieve reconciliation of conservation and development. In this study, we take the Mikumi-Selous region in Tanzania, Africa as an example, and through questionnaire surveys and semi-structured interviews, we sort out the current situation of conflicts between nature reserves and communities in the region, as well as summarize the means of conflict governance. In addition, we focus on identifying the various factors affecting community residents' protection willingness and protection action, and further verify the relationships among residents' family characteristics, protection costs and revenue, protection cognition, willingness and action through empirical analysis methods. The results show that residents' protection cognition has a significant positive effect on their willingness to protect and their actions, meanwhile willingness to protect also positively affects residents' protection action. In addition, it was found that the protection cost inhibits residents' willingness and action. Our study focuses on the willingness to participate and action of core stakeholders towards conflict governance from the perspective of community governance, emphasizing the key role of community participation in achieving coordinated development of biodiversity conservation and community. It provides a new perspective for mitigating conservation and development issues.

Ti17 alloy is mainly used to manufacture aero-engine discs due to its excellent properties such as high strength, toughness and hardenability. It is often subjected to creep-fatigue cyclic loading in service environments. Shakedown theory describes the state in which the accumulated plastic strain of the material stabilizes after several cycles of cyclic loading, without affecting its initial function and leading to failure. This theory includes three behaviors: elastic shakedown, plastic shakedown, and ratcheting. In this paper, the creep-fatigue tests (CF) were conducted on Ti17 alloy at 300℃ to study its shakedown behavior under creep-fatigue cyclic loading. Based on the plasticity-creep superposition model, a theory model that accurately describes the shakedown behavior of Ti17 alloy was constructed, and ABAQUS finite element software was used to validate the accuracy of the model. TEM analysis was performed to observe the micro-mechanisms of shakedown in Ti17 alloy. The results reveal that the Ti17 alloy specimens exhibit plastic shakedown behavior after three cycles of creep-fatigue loading. The established finite element model can effectively predict the plastic shakedown process of Ti17 alloy, with a relative error between the experimental and simulation results within 4%. TEM results reveal that anelastic recovery controlled by dislocation bending and back stress hardening caused by inhomogeneous deformation are the main mechanisms for the plastic shakedown behavior of Ti17 alloy.

A two-way coupled model between polydisperse particle phases with compressible gases and a density-based coupling implicit solution method combining the third-order MUSCL with QUICK spatial discretization scheme and the second-order temporal discretization scheme are constructed based on the discrete-phase model (DPM) and the stochastic wander model (DRWM) in the Eu-lerian-Lagrangian framework in conjunction with a unitary particulate source (PSIC) approach and the SST k-ω turbulence model. The accuracy of the numerical prediction method is verified using previous supersonic nozzle gas-solid two-phase flow experiments. Numerical simulation of two-phase jet of dry powder extinguishing agent gas with pilot-type supersonic nozzle was carried out to analyze the influence of geometrical parameters such as length ratio rL and area ratio rA of main nozzle on the two-phase flow field as well as on the jet performance indexes such as particle mean velocity vp,a, velocity inhomogeneity Φvp, particle dispersion Ψp, particle mean acceleration ap,a and so on. By analyzing the parameters, we indicate the requirements for the combination of jet performance metrics for different flame types such as penetrating, spreading, and dispersing.

Adipose tissue is a crucial organ in energy metabolism and thermoregulation. Adipose tissue phenotype is controlled by various signaling mechanisms under pathophysiological conditions. Type II transmembrane serine proteases (TTSPs) are a group of trypsin-like enzymes anchoring on the cell surface. These proteases act in diverse tissues to regulate physiological processes, such as food digestion, salt-water balance, iron metabolism, epithelial integrity, and auditory nerve development. More recently, several members of the TTSP family, namely, hepsin, matriptase-2, and corin, have been shown to play a role in regulating lipid metabolism, adipose tissue phenotype, and thermogenesis, via direct growth factor activation or indirect hormonal mechanisms. In mice, hepsin deficiency increases adipose browning and protects from high-fat diet-induced hyperglycemia, hyperlipidemia, and obesity. Similarly, matriptase-2 deficiency increases fat lipolysis and reduces obesity and hepatic steatosis in high-fat diet-fed mice. In contrast, corin deficiency increases white adipose weights and cell sizes, suppresses adipocyte browning and thermogenic responses, and causes cold intolerance in mice. These findings highlight an important role of TTSPs in modifying cellular phenotype and function in adipose tissue. In this review, we provide a brief description about TTSPs and discuss recent findings regarding the role of hepsin, matriptase-2, and corin in regulating adipose tissue phenotype, energy metabolism, and thermogenic responses.

Abstract: For the problem of small target of printed circuit board surface defects and low detection accuracy, the printed circuit board surface defect detection network DCR-YOLO is designed to meet the premise of real-time detection speed and effectively improve the detection accuracy. Firstly, the backbone feature extraction network DCR-backbone, consisting of two CR residual blocks and one common residual block, is used for small target defect extraction on printed circuit boards. Secondly, the SDDT-FPN feature fusion module is responsible for the fusion of high level features to low level features, while enhancing feature fusion for the feature fusion layer where the small target prediction head YOLO Head-P3 is located to further enhance the low level feature representation. the PCR module enhances the feature fusion mechanism between the backbone feature extraction network and the SDDT-FPN feature fusion module at different scales of feature layers. the C5ECA module is responsible for adaptive adjustment of feature weights and adaptive attention to the requirements of small target defect information, further enhancing the adaptive feature extraction capability of the feature fusion module. Finally, three YOLO-Heads are responsible for predicting small target defects for different scales. Experiments show that the DCR-YOLO network model detection Map reaches 98.58%, the model size is 7.73MB, which meets the lightweight requirement, and the detection speed reaches 103.15fps, which meets the application requirements for real-time detection of small target defects.

Nowadays, the world's refractory gold ore production accounts for about 30% of the world's total gold, such gold concentrate leaching rate is low, seriously limiting the efficient use of gold resources. The alkaline preoxidation process can improve the leaching rate of this kind of gold deposit, and has a good development and application prospect. So, it is of great significance to study the oxidation and dissolution behavior of pyrite in alka-line environment. In this paper, the oxidation process of gold-bearing pyrite in alkaline electrolyte was studied by electrochemical techniques, and the oxidation products of pyrite electrode in alkaline solution were characterized by XPS，SEM and other analytical methods. The results show that the optimum pH for pyrite electrochemical oxidation dissolution is about 12, and oxidation potential of pyrite should be above 0.8 V. In that proces of alkaline oxidation dissolution of pyrite, part of S element enters the electrolyte in the form of Sx2-, S2O32-, SO32-and SO42-, and a small amount of S element is adsorbed on the surface of the electrode in the form of S0 and becomes a part of the passive layer. Fe element is adsorbed on the surface of electrode in the form of Fe(OH)2, Fe2O3 and Fe2(SO4)3, which becomes the main component of passivation layer. This study provides a theoretical basis and reference data for the chemical preoxidation treatment of sulfide ores.

Many parameters and complex boundaries are involved in the spatial arrangement of an under-ground powerhouse for a hydropower station, which requires reference to many relevant cases and specifications. However, in practical applications, retrieving relevant cases or specifications is difficult, and there is a lack of knowledge of cascading logic among design parameters. For this question, a targeted knowledge graph based on knowledge graph management technology is established to support subsequent applications. This paper proposes a new concept of con-structing a knowledge graph for building information modeling (BIM) underground power-houses of hydropower stations. Firstly, the ontology skeleton of hydropower station spatial ar-rangement design, which represents the knowledge organization structure of the knowledge graph, is reconstructed by carefully analyzing the requirements for intelligent modeling of un-derground powerhouses. A large amount of unstructured data is identified based on optical character recognition (OCR) technology and is divided into words to extract correlation knowledge based on THULAC. In the next step, the knowledge triad of the spatial arrangement of the underground powerhouse is extracted based on ChatGPT and stored in a Neo4j knowledge base to build a knowledge graph. Finally, the knowledge graph is serviced to realize the query of knowledge and parameter recommendation to assist the digital intelligent design of spatial arrangement of an underground powerhouse of pumped storage hydropower stations.

Natural killer cells are associated with the pathogenesis of ulcerative colitis (UC), but their precise contributions remain unclear. The present study sought to investigate the diagnostic value of activated NK-associated genes (ANAGs) in UC. Bulk RNA-seq and scRNA-seq datasets were obtained from the Gene Expression Omnibus (GEO) and Single Cell Portal (SCP) databases. In the bulk RNA-seq, 92 differentially expressed genes (DEGs) were screened out by the “Batch correction” and “Robust rank aggregation” (RRA) methods. The immune infiltration landscape was estimated by single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT, which revealed a higher abundance of activated NK cells in noninflamed UC tissues. 54 DEGs correlated with activated NK cells were identified as ANAGs. Protein-protein interaction (PPI) analysis and least absolute shrinkage and selection operator (LASSO) regression were utilized to screen out 4 key ANAGs (SELP, TIMP1, MMP7, and ABCG2) and establish an activated NK-associated gene score (ANAG score). The ANAG score demonstrated excellent diagnostic value and was validated in three external datasets. The expression of the 4 key ANAGs was validated in UC patients and healthy controls (HC) samples. Through scRNA-seq data analysis, higher expression levels of SELP, TIMP1, MMP7, and ABCG2 were observed in post-capillary venules, inflammatory fibroblasts, enterocytes, and immature enterocytes. The cell scores based on the ANAGs showed enrichment in endothelial cells and fibroblasts. In conclusion, we established and validated an ANAG score with the ability to precisely diagnose UC. The 4 key ANAGs have the potential to serve as therapeutic targets in UC.

Identifying fake news on the media has been an important issue. This is especially true considering the wide spread of rumors on the popular social networks such as Twitter. Various kinds of techniques have been proposed for automatic rumor detection. In this work, we study the application of graph neural networks for rumor classification at a lower level, instead of applying existing neural network architectures to detect rumors. The responses to true rumors and false rumors display distinct characteristics. This suggests that it is essential to capture such interactions in an effective manner for a deep learning network to achieve better rumor detection performance. To this end we present a simplified aggregation graph neural network architecture. Experiments on publicly available Twitter datasets demonstrate that the proposed network has performance on a par with or even better than that of state-of-the-art graph convolutional networks, while significantly reducing the computational complexity.

Mangrove forests play a vital role in maintaining the ecological balance of coastal regions. Ac-curately assessing changes in their ecosystem service value (ESV) requires more than precise mangrove distribution data, an appropriate set of evaluation methods is also needed. In this study, we obtain the spatial distribution and structural changes of mangrove forests based on Sentinel-2 imagery and build a mangrove forest ESV evaluation system by combining spatial pattern and the millennium ecosystem services. The results showed that: (1) the area of mangroves in Guangxi increased from 6245.15 ha in 2016 to 6750.01 ha to 2020, with a net increase of 504.81 ha which mainly concentrated in Lianzhou Bay, Tieshan Harbour and Dandou Bay; (2) the ESV of mangrove forests was 379.85 million U.S. dollars (USD) in 2016 and 413.13 million USD in 2020; (3) the value of fishery, soil conservation, wave absorption, and pollution purification comprise the largest proportion of the ESV of mangrove forests. From 2016 to 2020, mangroves in Guangxi had demonstrated a positive development trend and was undergoing a process of recovery. Results and conclusions of this study provide valuable insights and information to facilitate a more profound comprehension of the relationship between the mangrove forest and its ecological significance.

Quantitative analysis of human gait is critical for early discovery, progressive tracking, and rehabilitation of neurological and musculoskeletal disorders, such as Parkinson’s Disease, stroke, and Cerebral Palsy. Gait analysis typically involves estimating gait characteristics, such as spatio-temporal gait parameters and gait health indicators (e.g., step time, length, symmetry, and balance). Traditional methods of gait analysis involve the use of cameras, wearables, and force plates, but are limited in operational requirements when applied in daily life - such as direct line-of-sight, carrying devices, and dense deployment. This paper introduces a novel approach for gait analysis by passively sensing footstep-induced floor vibrations during walking using vibration sensors mounted on the floor surface. Our approach is non-intrusive, scalable, and perceived as more privacy-friendly, making it suitable for continuous gait health monitoring in daily life. We developed a floor vibration-based gait analysis framework to estimate various gait parameters that are used as standard metrics in medical practices, including temporal parameters (step, stride, stance, swing, double-support, single-support time) and spatial parameters (step length, width, angle, stride length), and extracts gait health indicators (cadence/walking speed, left-right symmetry, gait balance, initial contact types). The main challenge is that floor vibrations are distinct across different floor types. To address this challenge, our approach develops floor-adaptive algorithms to extract floor-specific features and is designed to be generalizable to various settings, including homes, hospitals, and eldercare facilities. We evaluate our approach through real-world walking experiments with 20 adults with 12,231 labeled gait cycles across concrete and wooden floors. Our results show 90.5% (RMSE 0.08s), 71.3% (RMSE 0.38m), and 92.3% (RMSPE 7.7%) accuracy in estimating temporal, spatial parameters, and gait health indicators, respectively.

Recent prolonged dry periods and lack of irrigation water have severely affected the productivity of coffee farms’ in the Central Highlands of Vietnam. This paper analyzes the efficiency of irrigation water use for Robusta coffee (Coffea canephora) in Lam Dong province, Highlands, Vietnam. A Cobb-Douglas production function was used to determine coffee productivity’s response to the application of irrigation water and other production factors using data collected from 194 farmers while the Technical Efficiency (TE) and Irrigation Water Use Efficiency (IWUE) were analyzed using a Data Envelopment Analysis (DEA) model. The correlation of different factors to IWUE was determined using the Tobit model. The production function analysis using Cobb-Douglas shows that the volume of irrigation water, amount of working capital, labor and farm size significantly influence coffee productivity. It also shows that indigenous farmers are more efficient in utilizing irrigation water than the (mostly Kinh) migrant farmers. The Tobit result, on the other hand. indicates that farmers’ experience, education level, distance of farm to water source, security of access to water source, extension contact and credit access significantly affect IWUE. The study findings further suggest that mitigating water shortages in coffee farms require sub-regional and national policy support such as better access to credit and extension services, training, land management and household-level effort to improve farming practices, through the application of appropriate technologies and traditional knowledge.

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

Objective: This study aimed to demonstrate the availability of portable devices for nasal FeNO measurement, which could replace exhaled NO measurement based on the continuous aspiration of multiple flow measurement systems. Methods: A descriptive cross-sectional study. The healthy subjects without rhinosinusis disorders (control group) and those with diagnosed allergic rhinitis (AR group) were enrolled in the study. They underwent nasal and bronchial FeNO measurements by both fixed flow NObreath® connected to nasal mask and multiple flows HypAir FeNO®. Results: A total of 153 people were recruited including 63 healthy subjects and 90 subjects with AR. There were no statistically significant differences in anthropometric characteristics between the two groups (P > 0.05). There were a significant increase in FeNO values in the AR group compared to the control group; concentrations of nasal and bronchial FeNO mearsured by NObreath® were 76.0 ± 50.7 ppb (vs 36.0 ± 28.1 ppb, P < 0.01) and 32.3 ± 15.4 ppb (vs 9.2 ± 5.6 ppb, P < 0.001), and those mearsured by NObreath® Hypair FeNO® were 1796.9 ± 523.3 ppb (vs 400.2 ± 123.1 ppb, P < 0.001) and 37.3 ± 23.0 ppb (vs 17.4 ± 18.3 ppb, P < 0.01). A weak correlation between the values measured by NObreath® and Hypair FeNO® devices was observed (r = 0.023 and r = 0.089, respectively; p < 0.05). Conclusions: The handheld NObreath® device is effective in measuring FeNO concentrations in both normal subjects and AR patients. The advantages in price and size, creating a compact, low-cost device that is convenient for use and research.

Soil organic matter is an important component that reflects soil fertility and promotes plant growth. The soil of typical Chinese tea plantations was used as the research object in this work, and by combining soil hyperspectral data and image texture characteristics, a quantitative prediction model of soil organic matter based on machine vision and hyperspectral imaging technology was built. Three methods, standard normalized variate (SNV), multisource scattering correction (MSC) and smoothing, were first used to preprocess the spectra. After that, random frog (RF), variable combination population analysis (VCPA) and variable combination population analysis and iterative retained information variable algorithm (VCPA-IRIV) algorithms were used to extract the characteristic bands. Finally, the quantitative prediction model of nonlinear support vector regression (SVR) and linear partial least squares regression (PLSR) for soil organic matter was established by combining nine color features and five texture features of hyperspectral images. The outcomes demonstrate that, in comparison to single spectral data, fusion data may greatly increase the performance of the prediction model, with MSC+VCPA-IRIV+SVR (R2C=0.995, R2P=0.986, RPD=8.155) being the optimal approach combination. This work offers excellent justification for more investigation into nondestructive methods for determining the amount of organic matter in soil.

Accurate forecast of tail water level (TWL) is of great importance for the safe and economic operation and management of hydropower stations. The predictive performance is significantly influenced by the backwater effect of downstream hydropower stations and tributaries, but the explicit quantification method of the backwater effect is lacked. In this study, a deep learning model based forecasting framework for TWL predictions is established and applied to forecast TWL of Xiangjiaba (XJB) hydropower stations, which is influenced by the backwater effect of downstream tributaries including Hengjiang River (HJR) and Minjiang River (MJR). Firstly, the lag time of the backwater effect of HJR and MJR is analyzed based on the permutation importance. The results demonstrate that the lag time of backwater effect on the TWL of XJB is 5-7 hours for the HJR and 1-2 hours for the MJR. Then, the runoff thresholds of the HJR and MJR for impacting the TWL of the XJB station are obtained by scenario comparison, and the results show that the thresholds of HJR and MJR are 700 m3/s and 7000 m3/s respectively. Finally, the deep learning methods based TWL forecasting model is established based on the lag time and threshold analysis. The model is used to forecast the TWL in future 48 hours. The results show that the forecasting model has a good predictive performance with 98.22% of absolute errors less than 20 cm. The mean absolute error over the validation dataset is 5.27 cm and the maximum absolute error is 63.35 cm.

Fifteen new diterpenoids, namely xishaklyanes A-O (1-15), along with three known related ones (16-18), were isolated from the soft coral Klyxum molle collected from Xisha Islands, South China Sea. The stereochemistry of the new compounds were elucidated by a combination of detailed spectroscopic analyses, chemical syntheses, quantum chemical calculations and comparison with the reported data. The absolute configuration of compound 18 was established by the modified Mosher's method for the first time. In bioassay, some of these compounds exhibited considerable antibacterial activities on fish pathogenic bacteria, and compound 4 showed the most effective activity with MIC of 0.225 g/mL against Lactococcus garvieae.

In the process of construction and operation of the pumping station, a large number of axial flow pumps pose a threat to the survival of fish in the natural environment. Through experiments, the survival conditions of many kinds of fish in extreme positive and negative pressure environment are explored, and -40 kPa is established as the low pressure damage threshold, which is used as a reference to analyze the probability of fish damage caused by pumps. The immersion boundary-lattice Boltzmann numerical method (LES-IB-LBM) based on large eddy simulation is used to optimize the parameters of the prototype runner of axial flow pump. A new type of runner with leading edge thickness of 11.4mm and blade cutting angle of 18 ° is optimized. This kind of runner has both hydraulic performance and fish-passing ability. The runner of the fish-friendly axial flow pump effectively guides the fish into the low risk area and reduces the risk of friction, shear and impact damage to the fish. the total impact mortality ratio of the runner of the axial flow pump before and after optimization is close to 7:1. The pressure damage analysis shows that the lowest negative pressure of the fish is -59.2 kPa, which is higher than -64.5 kPa of the prototype pump, and the highest positive pressure of the body surface is 11.8 kPa, which is lower than the 43.8 kPa of the prototype pump. Shear damage analysis shows that the fish will not be damaged by shear in the prototype pump and fish-friendly pump.

Conclusions: Molecular classification could provide reliable supplementary information for evaluating prognostic and contribute to treatment option decision-making in EEC patients. Fertility-sparing treatment is not recommended for EEC patients with CNH and MSI-H. Furthermore, fertility-sparing treatment can be attempted in EEC patients with CHL, but regular follow-up should be carried out to early detection of EC relapse and prevention of disease progression.

Spider silk has excellent strength and elasticity in natural, researchers have been working for decades try to achieve natural spider silk outstanding mechanical properties using recombinant spider silk protein (spidroin) through artificial spinning. In this work, we chose wet spinning method to explore the relationship between concentration of coagulation bath and fiber performance. It was found that the concentration of methanol has important effect on fiber continuity, diameter and mechanical properties. Lower concentration favors spinning continuous thinner, fibers with high strain. Secondary stretching benefits spinning silk fibers with stable mechanical properties, and thermal stability. Through applying different methanol concentration and additional stretching, we obtained silk fibers with Young’s modulus of 3.052± 2.626 GPa, stress of 25.3944 ± 17.48 MPa, and strain of 140 ± 95.4%.

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

The visual perception of leisure spaces between residences in cold regions is important for public health. To compensate for the existing researches` lack of ignoring the cold snow season`s influence, this study selected two types of outdoor leisure space environments in non-snow and snow seasons as research objects. An eye tracker combined with a Semantic Difference (SD) questionnaire was used to verify the feasibility of the application of virtual reality technology, screen out leisure gaze characteristics, and reveal the environmental factors related to leisure visual perception. In snow season, spatial aspect ratio (SAR), building elevation saturation (BS), and grass proportion in the field of view (GP) showed strong correlation to the leisure visual perception scores (W). In non-snow season, apart from the above three factors, roof height difference (RHD), tall tree height (TTH) and color contrast (HC) also influenced W obviously. The effects of factors on W were revealed in immersive virtual en-vironment (IVE) orthogonal experiments and genetic algorithm (GA) and k-nearest neighbor algorithm (KNN) were combined to optimized the environmental factors. The optimized threshold ranges in the non-snow season environment were SAR: 1.82‒2.15, RHD: 10.81 m‒20.09 m, BS: 48.53‒61.01, TTH: 14.18 m‒18.29 m, GP: 0.12‒0.15, and HC: 18.64‒26.83. In the snow season environment, the optimized threshold ranges were SAR: 2.22‒2.54, BS: 68.47‒82.34, and GP: 0.1‒0.14.

Polarimetric features extracted from polarimetric synthetic aperture radar (PolSAR) images contain abundant scattering information of objects. Utilizing this information for PolSAR image classification can improve accuracy and enhance object monitoring. Although significant progress has been achieved in related research, there are still issues such as insufficient utilization of polarimetric information and features. In this paper, a deep learning classification method based on polarimetric channel power features for PolSAR is proposed. The distinctive characteristic of this method is that the polarimetric features inputted into the deep learning network are the power values of polarimetric channels, where these channels are treated equivalently and contain complete polarimetric information. In terms of experimental comparative study, besides polarimetric power combinations, three different data input schemes were employed as data for the input end of the convolutional neural network (CNN), taking into account existing research. The neural networks utilizes the extracted polarimetric features to classify images, and the classification accuracy analysis is employed to compare the strengths and weaknesses of different input schemes. It is worth mentioning that the polarized characteristics of the data input scheme mentioned in this article have been derived through rigorous mathematical deduction, and each polarimetric feature has clear physical meaning. By testing different data input schemes on the Gaofen-3 (GF-3) PolSAR image, the experimental results show that the method proposed in this article outperforms existing methods and can improve the accuracy of classification to a certain extent, validating the effectiveness of this method in large-scale area classification.

In this paper, the problem of observer-based adaptive sliding mode control is discussed for nonlinear systems with sensor and actuator faults. The time-varying actuator degradation factor and external disturbance are considered in the system simultaneously. In this study, the original system is described as a new normal system by combining the state vector, sensor faults and external disturbance into a new state vector. For the augmented system, a new sliding mode observer is designed, where a discontinuous term is introduced such that the effects of sensor and actuator faults and external disturbance will be eliminated. In addition, based on a tricky design of the observer, the time-varying actuator degradation factor term is developed in the error system. On the basis of the state estimation, an integral-type adaptive fuzzy sliding mode controller is constructed to ensure the stability of the closed-loop system. Finally, the effectiveness of the proposed control methods can be illustrated with a numerical example.

CNN-based methods have dominated the field of aerial scene classification for the past few years. While achieving remarkable success, CNN-based methods suffer from excessive parameters and notoriously rely on large amounts of training data. In this work, we introduce few-shot learning to the aerial scene classification problem. Few-shot learning aims to learn a model on base-set that can quickly adapt to unseen categories in novel-set, using only a few labeled samples. To this end, we proposed a meta-learning method for few-shot classification of aerial scene images. First, we train a feature extractor on all base categories to learn a representation of inputs. Then in the meta-training stage, the classifier is optimized in the metric space by cosine distance with a learnable scale parameter. At last, in the meta-testing stage, the query sample in the unseen category is predicted by the adapted classifier given a few support samples. We conduct extensive experiments on two challenging datasets: NWPU-RESISC45 and RSD46-WHU. The experimental results show that our method yields state-of-the-art performance. Furthermore, several ablation experiments are conducted to investigate the effects of dataset scale, the impact of different metrics and the number of support shots; the experiment results confirm that our model is specifically effective in few-shot settings.

Soil washing is a rapid and efficient method for heavy metals removal. In this study, in order to prove the feasibility of leaching remediation technology for remediation of lead-contaminated soil around a smelter, intermittent oscillating washing tests and extensive continuous tests were conducted to remediate Pb contaminated soils. Plant growth tests with wheat (Bainong Aikang 58) were also conducted to investigate the effects of leaching on plant growth and the Pb content of stems and leaves. The results revealed that in soils, Pb mainly exists in the forms of PbCO3, Pb5(PO4)3Cl2, PbSO4, and in small amounts of PbS. The intermittent oscillating washing tests showed that a lower liquidsolid(L/S) ratio and a higher leaching temperature and time were related to increased Pb removal efficiency. The Pb removal efficiency rates in the oscillating washing tests and the extensive continuous tests were 72.50% and 69.94%, respectively. In addition, the chemical and physical characteristics of the soil were basically unchanged after the leaching regimes. The results of the plant growth tests showed that the leaching regimes did not have a negative effect on the survival rate and growth of the wheat, and the heavy metal contents of the stem and leaf were effectively reduced. This study provides a reference for the large-scale remediation of contaminated soils.

Alzheimer’s disease and related dementias (ADRD) remain a public health challenge in developing counties. We developed a needs-based essential care service package (ECSP) for care planning of persons living with dementia (PLWD) using a cross-sectional survey among PLWD in institutions in six cities in China (n= 1,299). Face-to-face interviews were conducted with caregivers of PLWD by trained staff between 2018 and 2019. Care service needs and utilization by the level of cognitive impairment were summarized. The average age of PLWD was 80.7 years. 76% of participants had severe cognitive impairment. The needs-based ECSP with 30 service items would be sufficient in supporting care services of PLWD in China, of which seven items are core care. The selection plan for ECSP at different levels is designed as “General Care Services + Selective Care Services”, in which service items for low-, mid-and high-level care for PLWD are 7+3, 7+6, and 7+10, respectively. The findings provide the first large-scale data on service needs and utilization of PLWD in mainland China. The ECSP for PLWD advanced in the paper was a practicable and effective quantitative management means. It is deserved to application in a large scale.

This study employs the reflection symmetry decomposition (RSD) method to extract polarization scattering features from ground object images, aiming to determine the optimal data input scheme for deep learning networks in polarimetric synthetic aperture radar classification. Eight distinct polarizing feature combinations are designed, and the classification accuracy of various approaches is evaluated using the classic convolutional neural networks(CNNs) AlexNet and VGG16. The findings reveal that the commonly employed 6-parameter input scheme, favored by many researchers, lacks the comprehensive utilization of polarization information and warrants attention. Intriguingly, leveraging the complete 9-parameter input scheme based on the polarization coherence matrix results in improved classification accuracy. Furthermore, the input scheme incorporating all 21 parameters from the RSD and polarization coherence matrix notably enhances overall accuracy and the Kappa coefficient compared to the other 7 schemes. This comprehensive approach maximizes the utilization of polarization scattering information from ground objects, emerging as the most effective CNN input data scheme in this study. Additionally, the classification performance using the second and third component total power values (P2 and P3) from the RSD surpasses the approach utilizing surface scattering power value (PS) and secondary scattering power value (PD) from the same decomposition.

This paper introduces a method for tunnel point cloud and BIM model integration and cross-section monitoring, providing information to analyse tunnel cross-sections and surrounding rock deformation, and support for tunnel maintenance and reconstruction. Three types of data are processed for the integration: laser scanning point cloud, BIM tunnel model and terrain model from oblique photogrammetry. An adaptive BIM modelling scheme is proposed for tunnels with alien structures. Precise spatial registration of the data sets is conducted by applying singular value decomposition (SVD) algorithm to calculate transformation parameters from the point cloud model to the BIM model. Since the tunnel central line has high-order derivability, a cross-section calculation method based on tangent vector is proposed to obtain the cross-sectional profile of tunnels at any mileage. The proposed method has been verified by applying it to a tunnel reconstruction project. The experiment results show that the tunnel point cloud and the BIM model were highly coincident after the integration. The developed program can effectively get the cross-section of the tunnel at any mileage, and correctly express the spatial relationship between the BIM tunnel, the point cloud of tunnel and the external mountainous terrain.

DDX3 is an ATP-dependent RNA helicase involved in multiple cellular activities, including RNA metabolism and innate immunity. DDX3 is known to assist the replication of some viruses while restricting some others through direct interaction with the viral proteins. However, the role of DDX3 in the replication of the hepatitis E virus (HEV) is unknown. In this study, DDX3 is shown to interact with the HEV capsid protein and provide an indispensable role in HEV replication. The DDX3 C-terminal domain was demonstrated to interact with the capsid protein, which was previously demonstrated to inhibit the production of type I interferons. Knockdown of DDX3 compromised the capsid protein-mediated blockage of interferon induction. Notably, DDX3 silencing led to a significant reduction in HEV replication. Also, the ATPase activity of DDX3 is required for the HEV replication as an ATPase-null mutant DDX3 failed to rescue the viral replication in the DDX3-silenced cells. These results demonstrate a pro-viral role of DDX3 in HEV replication, providing further insights into the virus-cell interactions.

Ensuring bus priority is to improve traffic sustainability at the signalized intersection. To achieve this, the Bus Priority Lane (BPL) is adopted to provide exclusive right-of-way for buses. However, the BPL is underutilization if the frequency of buses is low. To address this issue, many studies focus on improving the BPL’s utilization efficiency by intermittently allowing general vehicles to access it. However, these studies still have some shortcomings: i) bus priority cannot be guaranteed if general vehicles run on the BPL; ii) the traffic system lacks resilience, especially when the traffic demand is unbalanced. This paper proposes a dynamic right-of-way allocation on the BPL considering traffic system resilience. On the one hand, it ensures absolute bus priority by controlling Connected Automated Vehicles (CAVs) to not interfere with buses. On the other hand, it can improve traffic system resilience by allocating right-of-way for CAVs with heavy turning-movement demand. To validate the effectiveness, the proposed control strategy is evaluated against the non-control baseline. Sensitivity analysis is conducted under seven unbalanced traffic demand levels, four congestion levels, and five CAV Penetration Rates. The results show that the proposed control strategy can ensure absolute bus priority and improve traffic efficiency and traffic system resilience.

In this study, we resequenced the mitogenomes of P. megacephalus from different regions using a “primer bridging” approach with Sanger sequencing technologies. The mitogenome of this species was found to contain two copies of the ND5 genes and three copies of the control regions. Furthermore, multiple tandem repeats were identified in the control regions. Notably, we observed that there was no correlation between the distribution of species and their genetic distance. However, our research revealed the discovery of the “missing” ATP8 gene in P. megacephalus as well as three other previously published Polypedates, as a result of manual data curation. Using the mitogenome, gene expression analysis was performed via RT-qPCR of liver samples and determined that COIII, ND2, ND4, and ND6 were reduced to 0.64±0.24, 0.55±0.34, 0.44±0.21 and 0.65±0.17 under the low-temperature stress (8℃), respectively, as compared with controls (P<0.05). Remarkably, the transcript of long non-coding RNA (LncRNA) between positions 8029 and 8612 decreased significantly with exposure to low-temperature stress (8℃). Antisense ND6 gene expression showed a downward trend but this was not significant. These results reveal that modulations of protein-coding mitogenomes genes and lncRNAs of P. megacephalus play a crucial part in the molecular response to cold stress.

This paper draws upon the theory of turbulence in physics to explore the similarities and differences between volatility in financial markets and turbulent phenomena at a statistical physics level. By analogizing the dynamics of financial markets with fluid turbulence, we have developed an innovative analytical framework aimed at deepening the understanding of the complexity inherent in financial markets. Our research methodology includes a comparative analysis of simulated time series data for the Standard & Poor's 500 Index and fully developed turbulent velocity time series. We focus on the similarities in key statistical physical properties, including probability distributions, correlation structures, and power spectral densities. Furthermore, we have established a model of capital flow in financial markets and proposed corresponding solutions. Through computational simulations and data analysis, we find that while financial market volatility shares some statistical characteristics with turbulent phenomena, significant differences exist in the shapes of probability distributions and the temporal scales of correlations. This suggests that although financial markets exhibit patterns akin to turbulence, the behavior of this complex, multi-variable driven system does not completely correspond to natural turbulence, highlighting the limitations of directly applying turbulence theory to financial market analysis. Our study offers a new perspective for the theories of financial markets and the field of econophysics, providing fresh insights into the complexity of financial markets and contributing to the prevention and management of financial risk.

Gross strap muscle invasion (gSMI) in patients with differentiated thyroid cancer (DTC) was defined as high-risk recurrent group in the 2015 American Thyroid Association guidelines. However, controversy persists because several studies suggested gSMI had little effect on disease outcome. Herein, a systematic review and meta-analysis was conducted to investigate impact of gSMI on outcome of DTC. Methods: A systematic search of electronic databases (PubMed, EMBASE, Cochrane Library, and MEDLINE) for studies published until February 2020 was performed. Case-control studies and randomized controlled trials that studied the impact of gSMI on outcome of DTC were included. Results: Six studies (all retrospective studies) involving 13639 patients met final inclusion criteria. Compared with no extrathyroidal extension (ETE), patients with gSMI were associated with increased risk of recurrence (P=0.0004,OR, 1.46; 95% CI: 1.18 to 1.80) and lymph node metastasis (LNM) (P<0.00001,OR 4.19;95% CI. 2.53 to 6.96). For mortality (P=0.34,OR 1.47;95% CI:0.67 to 3.25), ten-year disease-specific survival (P=0.80, OR 0.91;95% CI:0.44 to 1.88) and distant metastasis (DM) (P=0.21, OR 2.94;95% CI. 0.54 to 15.93), there was no significant difference between gSMI and no ETE group. In contrast with maximal ETE, patients with gSMI were associated with decreased risk of recurrence (P<0.0001,OR, 0.58; 95% CI: 0.44 to 0.76) , mortality (P=0.0003,OR 0.20;95% CI:0.08 to 0.48), LNM (P=0.0003,OR 0.64;95% CI. 0.50 to 0.81) and DM (P=0.0009,OR 0.28;95% CI. 0.13 to 0.59). Conclusions: DTC patients with gSMI had a higher risk of recurrence and LNM than those without ETE. However, in contrast with maximal ETE, a much better prognosis was observed in DTC patients with only gSMI. The findings of our meta-analysis provide supportive evidence for the validity of the T category changes in the 8th edition American Joint Committee on Cancer system. The actual impact of gSMI should be re-evaluated and revised in the recurrent risk stratification system in the future.

The liquid-vapor phase change lattice Boltzmann method is used to investigate the pinning-depinning mechanism of the contact line during droplet evaporation on the stripe-patterned surfaces in 3D space. Considering the curvature of the contact line and the direction of the unbalanced Young’s force, the local force balance theory near the stripe boundary is proposed to explain the steady state of the droplets on the stripe-patterned surfaces. An equation is proposed to evaluate the characteristic contact angle of the stabilized droplets. During the evaporation of the droplet, the stick-slip-jump behavior and the CCR-Mixed-CCA mode can be well captured by the lattice Boltzmann simulation. When the contact line is pinned to the stripe boundary, the contact line in the direction perpendicular to the stripes is slowly moving while the curvature of the contact line is gradually increasing. The gradually increasing curvature of the contact line accelerates the movement of the contact line, and the final contact line is detached from the stripe boundary. The research results provide theoretical support and guidance for the design, improvement and application of patterned surfaces in the field of micro-fluidic and evaporation heat transfer.

Blind deconvolution (BD) is one of the effective methods that help pre-process vibration signals and assist in bearing fault diagnosis. Currently, most BD methods design an optimization criterion and use frequency or time domain information independently to optimize a deconvolution filter. It recovers weak periodic impulses related to incipient faults. However, the random noise interference may cause the optimizer to overfit. The time-domain-based BD methods tend to extract fault-unrelated single peak impulse, and the frequency-domain-based BD methods tend to retain the maximum energy frequency component, which will lose the fault-related harmonics frequency components. To solve the above issue, we propose a hybrid criterion that combines the kurtosis for time domain optimization and the $G-l_1/l_2$ norm for the frequency domain. These two criteria are monotonically increasing and decreasing, so they mutually constrain to avoid overfitting. After that, we design a multi-task one-dimensional convolutional neural network with time and frequency branches to achieve an optimal solution for this hybrid criterion. The multi-task neural network realizes the simultaneous optimization of two domains. Experimental results show that our proposed method outperforms other state-of-the-art methods.

In tobacco plants, symbiont endophytic fungi are widely distributed in all tissues where they play important roles. It is therefore important to determine the species distribution and characteristics of endophytic fungi in tobacco. Here, two parasitic fungi Leptosphaerulina chartarum and Curvularia trifolii were isolated and identified from normal tobacco tissue. We sequenced the mitogenomes of these two species and analysed their features, gene content, and evolutionary histories. The L. chartarum and C. trifolii mitochondrial genomes were 68,926 bp and 59,100 bp long circular molecules with average GC contents of 28.60% and 29.31%, respectively. The L. chartarum mitogenome contained 36 protein coding genes, 26 tRNA genes, and 2 rRNA genes (rrnL and rrnS), which were located on both strands. The C. trifolii mitogenome contained 26 protein coding genes, 29 tRNA genes, and 2 rRNA genes (rrnL and rrnS). The L. chartarum 26 tRNAs ranged from 70 bp to 84 bp in length, whereas the 29 tRNAs in C. trifolii ranged from 71 bp to 85 bp. L. chartarum and C. trifolii mtDNAs had an identical mitochondrial gene order and orientation and were phylogenetically identified as sisters. These data therefore provide an understanding of the gene content and evolutionary history of species within Pleosporales.

Nowadays, the study of preparing silica/rubber composites, which can be used in “green tire”, in energy saving method is fast-growing. In our work, silica modified by using alcohol polyoxyethylene ether (AEO) and 3-Mercaptopropyltriethoxysilane (K-MEPTS) together were investigated. Thermal gravimetric analyzer (TGA) result indicated that both AEO and K-MEPTS could be grafted on the silica surface. Raman spectroscopy confirmed that the AEO could generate a certain steric hindrance for the mercaptopropyl group on K-MEPTS. Silica modified by using AEO and K-MEPTS together can be completely co-coagulated with the rubber in preparing silica/natural rubber (NR) composites by latex compounding method. AEO can form a physical interface between silica and rubber; meanwhile, K-MEPTS can form a chemical interface between silica and rubber. The effects of chemical and physical interface between silica and rubber on dynamic and mechanical performances of silica/NR composites were also given in this research. A proper combination of physical and chemical interface between silica and NR can improve performances of silica/NR composites.

The need for cross-modal retrieval (CMR) among users is growing because of the swift advancements in computer vision and natural language processing. Promoting home operating systems is greatly aided by the openKylin home operating system. It is focused on enhancing the functionality of the operating system with safe and dependable operating technologies. Practical implications abound for integrating computer vision research into home operating systems. A multimodal retrieval approach based on openKylin is presented to improve the usability of text search graphs, audio, and video. The overview of pertinent domestic and international research is the main topic of this article. This technological advancement. It then offers details on the design, implementation procedure, and final implementation outcomes for demonstration. The works of natural operations show that this strategy has excellent accuracy and performance.

As metabolomics is widely used in the study of disease mechanisms, more and more studies have found that metabolites play an important role in the occurrence of diseases. The aim of this study is to investigate the effects and mechanisms of quercetin in high-fat-sucrose diet (HFD)-induced nonalcoholic fatty liver disease (NAFLD) development using nontargeted metabolomics. A rat model of NAFLD was established by feeding with a HFD for 30 and 50 days. Results indicated quercetin exhibited hepatoprotective activity in HFD-induced NAFLD rats in 30 days by regulating fatty acids related metabolites (adrenic acid, etc.), inflammation related metabolites (arachidonic acid, etc.), oxidative stress related metabolites (2-hydroxybutyric acid) and other differential metabolites (citric acid, etc.). However, quercetin couldn’t improve NAFLD in 50 days maybe it couldn’t reverse the inflammation condition induced by long-term high-fat diet. These data indicate that dietary quercetin may be beneficial to NAFLD at early stages. Furthermore, combining metabolomics and experimental approaches opens up avenues of effects and mechanisms of drugs for complex diseases.

China’s Grassland Eco-Subsidy Program has been implemented since 2011 to protect and sustain grassland resources and improve the economic situation of herders. In this case study, we evaluated the policy from the perspective of pastoral differentiations and their willingness to accept (WTA) the eco-subsidy. Using the contingent valuation method (CVM), we interviewed 410 herder households in the grass-livestock balance sub-policy zones across Inner Mongolia, and examined how their horizontal and vertical differentiation affected their WTA and compensation expectations in a sorted Logistic model and a Tobit model, respectively. Our findings suggest that horizontal differentiation of herders (variations of income sources and employments) promoted the WTA for eco-subsidy and inhibited the increase of compensation expectations. A large vertical differentiation extent (income disparity) lowered the WTA but raised expectations for payment levels. Besides, factors such as operating pasture area, precipitation, and supervision intensity had significant impacts. Grazing income remained the primary income source for most herder households, reflecting the characteristics of "the rational economic man." Our results suggest a need for policy improvements to guide herders towards becoming "rational ecological men.” By considering this differentiation, policymakers can better tailor the program to meet the needs and expectations of diverse herder households.

Single cell RNA-seq (scRNA-seq) profiles conceal temporal and spatial tissue developmental information. De novo reconstruction of single cell temporal trajectory has been fairly addressed, but reverse engineering single cell 3D spatial tissue localization is hitherto landmark based, and de novo spatial reconstruction is a compelling computational open problem. Here we show that a new algorithm - named D-CE - for coalescent embedding of single cell transcriptomic networks can address this open problem. We rely merely on the spatial information encoded in the expression patterns of developmental signal transcription factor (DST) genes, and we find that D-CE of cell-cell association DST-transcriptomic networks reliably reconstructs the Geo-seq or single cell samples’ 3D spatial tissue distribution. Comparison to the novoSpaRC and CSOmap (recent and only available de novo 3D spatial reconstruction methods) on 16 datasets and 681 reconstructions, reveals a significantly distinctive superior performance of D-CE.

The regenerated magnesia-calcium brick samples that had added 0, 1.5, 3.0 wt.% aluminium oxide (Al2O3) were prepared by using spent magnesia-calcium bricks, fused magnesia and Al2O3 powder additive as the main raw materials. The phases, microstructures, room temperature and hot flexural strength, resistance to cement clinker corrosion and strength of coating adherence were investigated respectively. It indicated that the addition of Al2O3 increased mainly resulting in the content of tetracalcium aluminoferrite (C4AF) and tricalcium aluminate (C3A) increased in the regenerate samples. The bulk density, the room temperature flexural strength and the strength of coating adherence all increased, while the hot flexural strength and corrosion resistance both deteriorated along with the increase of Al2O3 addition. It was because that on the one hand the low melting point phases of C4AF and C3A improved the sinterability of the regenerated samples during the burning stage, on the other hand they melted or existed in liquid phase during the experimental temperature (1573 K and 1823 K) which degraded hot flexural strength and corrosion resistance, and enhanced the strength of coating adherence as the wettability of the liquid phase. The content of Al2O3 in the regenerated magnesia-calcium brick should not be higher than 1.1 wt.%, considering its room and high-temperature performances for cement rotary kiln.

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

The ketogenic diet and walking exercise training activity are two key public health lifestyle factors. The potential of combined lifestyle factors interventions focused on getting to compliance in forced exercise. A balanced ketogenic diet and regular exercise activity is a key modifiable factor to the prevention and management of chronic diseases. Influence health across the lifespan and reduction of the risk of premature death through several biological mechanisms. Community older group’s lifestyle factors interventions contribute identity in their natural living environment. While the older health benefits of walking exercise training strategies are commonly to study, combined ketogenic diet and walking exercise interventions have induced greater benefits in community older groups.

The basic idea is to expand the completed zeta function $\xi(s)$ in MacLaurin series (infinite polynomial), which can be further expressed as infinite product (Hadamard product) by conjugate complex roots. Finally, the functional equation $\xi(s)=\xi(1-s)$ leads to $(s-\alpha_i)^2 = (1-s-\alpha_i)^2, i \in \mathbb{N}$ with solution $\alpha_i= \frac{1}{2}, i \in \mathbb{N}$, where $\alpha_i$ are the real parts of the zeros of $\xi(s)$, i.e., $s_i =\alpha_i\pm j\beta_i, i\in \mathbb{N}$. Therefore, a proof of the Riemann Hypothesis is achieved.

Aiming at the problems of high labor intensity and high cost of manual picking, high loss rate of mechanical picking seeds, low mechanization level and difficult to guarantee the quality of picking plates in the process of picking plates of edible sunflower. Based on the principle of manual plate taking, a plate taking control system for sunflower harvesting table was designed. Through the research and analysis of the principle of taking the plate of the edible sunflower harvesting table. According to the actual operation requirements, the overall scheme of the sunflower plate control system is determined, and the control strategy of imitating artificial low loss harvesting is designed. To reduce the grain loss in the process of taking the plate and improve the control accuracy of the system on the movement speed and displacement of the key components in the process of taking the plate, a trapezoidal acceleration and deceleration control algorithm is designed as the control algorithm of taking the plate. To verify the working performance of the plate control system, with the absolute error, relative error and total loss rate of the harvest as objectives. The bench and field verification experiments were both carried out. The bench experiment showed that the speed error of the plate parts was not more than 0.028 m/s. In the bench experiments of the device, the maximum positioning error was 1.25 mm, the average relative error is only 0.94 %, and the grain loss rate was not more than 2.26 %. It result showed that the system algorithm was reliable, the positioning accuracy was high, and the taking plate operation can be completed well. The field verification experiment showed that the forward speed of the unit was in the range of 0.4~0.8 m/s, and the total loss rate of harvest was less than 5 %. When the forward speed is 0.6 m/s, the minimum harvest loss rate is 2.32 %, and which indicated the control system meets the requirements of sunflower harvesting operation.

This study was aimed to investigate the effect of xylan depolymerizing enzyme namely endo-xylanase (Xyn) combined with debranching enzymes namely arabinofuranosidase (Afd) and feruloyl esterase (FE) on digestion, growth performance and intestinal volatile fatty acid profile of piglets. The in vitro experiments were firstly conducted to examine the enzymological properties of Xyn, Afd and FE, the synergy among these enzymes, together with the effect of combination of these enzymes on digestion of piglet diet. The in vivo experiment was then implemented by allocating 270 35-d-old postweaning piglets into 3 treatment groups: control group, Xyn group and (Xyn+Afd+FE) group. Each group had 6 replicates (15 piglets/replicate). The results revealed a satisfying thermostability and pH stability of Xyn, Afd and FE. Combination of Xyn, Afd and FE had a superiority (P < 0.05) over Xyn alone and its combination with Afd or FE in promoting degradation of different bran fibers rich in arabinoxylan (Abx). Treatment with combination of Xyn, Afd and FE had advantages over Xyn alone to induce increasing trends (P < 0.10) of in vitro digestibility of dietary nutrients (dry matter, crude protein, crude ash and gross energy) and piglet growth performance (average daily gain, final body weight and feed efficiency), concurrent with a reduction (P < 0.05) of diarrhea rate and increases (P < 0.05) in cecal acetic acid, butyric acid and total volatile fatty acids concentrations as well as pH value of piglets. Collectively, combination of Xyn, Afd and FE was efficient in benefiting degradation of Abx in brans, as well as improving digestion, growth performance and intestinal volatile fatty acid profile of piglets.

Expansins (EXPs) which are the essential components of plant cell wall function as relaxation factors to directly promote turgor-driven expansion of cell wall and control plant growth and development and diverse environmental stress responses. A lot of EXPs genes have been widely identified and characterized in numerous plant species, but not in sweetpotato. In the present study, a total of 59 EXPs genes that unevenly distributed onto 14 of 15 chromosomes were identified from sweetpotato genome, and segmental and tandem duplications were exhibited to act as dominant functions in IbEXPs diversity. Phylogenetic analysis exhibited that IbEXPs members were clustered into four subfamilies according to EXPs in Arabidopsis and rice and the regularity of motif, domain and gene structures was in accordance with the subfamily classification. The collinearity analysis between IbEXPs and related homologous sequences in 9 plants provided the phylogenetic insights of EXPs gene family. Cis-element analysis futhrer revealed the potential roles of IbEXPs in sweetpotato development and stress responses. Evidence from RNA-seq and qRT-PCR analysis of eight selected IbEXPs genes displayed their various tissue specificity in different tissues, and their transcripts were varyingly induced or suppressed under multiple hormone treatments (ABA, SA, JA and ACC) and abiotic stresses (low and high temperature). These results supply worthy foundations to further comprehensively investigate the exact functions of IbEXPs genes, and multiple members may function as promising regulators to control plant development and enhance the stress resistance of transgenic plants.

The nuclear factor-ĸB (NF-ĸB) transcriptional system is a major effector pathway involved in inflammatory responses. Previous studies found that a Gardenia decoction (GD) inhibited the expression of NF-κB in a lipopolysaccharide (LPS)-stimulated mouse intestinal injury model. Herein, we hypothesized that geniposide (GE), a component of Gardenia jasminoides Ellis, also exerts anti-inflammatory effects and inhibits NF-ĸB activity in LPS-induced intestinal epithelial cells (IEC-6). IEC-6 cells were stimulated with LPS, following which the effects of GE on NF-ĸB signaling in the IEC-6 cells were examined by western blotting to detect IĸB phosphorylation/degradation. The expression of NF-κB was determined by immunofluorescence assay (IFA). Enzyme-linked immunosorbent assay (ELISA) was used to detect the inhibitory effect of GE on the release of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-1β (IL-1β) activated by LPS in IEC-6 cells. In addition, the migration ability of IEC-6 cells was observed by the scratch method. These results showed that GE dose-dependently downregulated levels of the proinflammatory cytokines TNF-α, IL-6 and IL-1β that had been upregulated by LPS and suppressed the phosphorylation of IĸB and NF-ĸB induced by LPS. Our findings indicated that GE could reduce LPS-induced NF-ĸB signaling and proinflammatory expression in IEC-6 cells and significantly enhance the migration of IEC-6 cells. Moreover, GE inhibited the expression of NF-κB, nuclear transfer, and transcriptional activity in IEC-6 cells. GE could block the synthesis of inflammatory factors of IEC-6 cells by inhibiting activation of the IĸB/NF-κB signaling pathway induced by LPS.

Synthetic cannabinoids are a series of synthetic substances that mimic the effects of natural cannabinoids and produce a much stronger toxicity than natural cannabinoids, which have become the most abused family of new psychoactive substances. A solid-phase extractive-liquid chromatography-triple quadrupole/linear ion trap mass spectrometry method was developed to determine 11 synthetic cannabinoids in rat urine. The factors affecting recovery were optimized, and Oasis HLB was selected to extract synthetic cannabinoids simultaneously. The results showed that the linear correlation coefficients of the synthetic cannabinoids ranged from 0.993 to 0.999, and the limit of quantitation ranged from 0.01 to 0.1 ng/mL, and the spiked recoveries ranged from 69.90% to 118.39%. This method has the advantages of good purification ability, simple operation, and good reproducibility, and can be used for the high sensitivity analysis of various synthetic cannabinoids in urine.

The frequency synthesizer is a critical component in Cs beam clock technology. In this paper, we present a demonstration of a direct microwave frequency-synthesis chain for a cesium-beam atomic clock, which utilizes frequency multiplication and a dual-phase-locked loop mode. A detailed analysis of the frequency-synthesis chain is conducted, and a mathematical model is established. The phase settling time and system stability are simulated, measured, and verified. The experimental results for the phase settling time align with the simulation outcomes. The phase settling time can be adjusted within the range of 644.5 µs to 1.5 ms, and the absolute phase noise values are -63.7 dBc/Hz, -75.7 dBc/Hz, -107.1 dBc/Hz, and -122.5 dBc/Hz at 1 Hz, 10 Hz, 1 kHz, and 10 kHz offset frequencies, respectively. Additionally, the Ramsey fringes are detected, and the Allan deviations of the 10 MHz output from the cesium-beam atomic clock are measured to be 2.99×10−12 at 1s and 8.02×10−14 at 10,000 s.

The thoracic surgery has increased drastically in recent years, especially in the light of the severe outbreak of 2019 novel coronavirus disease (COVID-19). Routine “passive” chest computed tomography (CT) screening of inpatients detects some pulmonary diseases requiring thoracic surgeries timely. As an essential device for thoracic anesthesia, the double-lumen tube (DLT) is particularly important for anesthesia and surgery. With the continuous upgrading of the DLTs and the widespread use of the fiberoptic bronchoscopy (FOB), the position of DLT in thoracic surgery is gradually becoming more stable and easier to observe or adjust. However, the DLT malposition still occurs during transferring patients from supine to lateral position in thoracic surgery, which leads to lung isolation failure and hypoxemia during one-lung ventilation (OLV). Recently some innovative DLTs or improved intervention methods have shown good results in reducing the incidence of DLT malposition. This review aims to summarize the recent studies of the incidence of left-sided DLT malposition, the reasons and effects of malposition, and summarize current methods for reducing DLT malposition and prospects for possible approaches. Meanwhile, we use bibliometric analysis to summarize the research trends and hot spots of the DLT research.

Predatory mites are a type of biological control agent used in many countries against various vegetable pests, particularly spider mites. Despite the significant presence of predatory mites in the Tibetan plateau, there is limited research on their fitness and prey capacity in the area. Herein, four predatory mite species, including one species Neoseiulus californicus and three species from genus Amblyseius (Amblyseius swirskii, Amblyseius barkeri, and Amblyseius cucumeris) were investigated. Specifically, their fitness and prey capacity on two-spotted mites (Tetranychus urticae) at highland conditions were evaluated. Compared to the other three predatory species, A. swirskii had the highest fecundity (Mean ± SEM=11.60 ± 0.34) and the highest pre-adult survival rate (Mean ± SEM = 83.33 ± 3.33%). Since their juvenile Survival Rate (SR) was extremely low (Mean ± SEM =13.33% ± 5.77%), most A. barkeri nymphs died before emergence. Compared to the other three predatory mites, A. swirskii had the highest predation capacity on T. urticae adult mites at 15 d post-release (Mean ± SEM =14.28 ± 2.24). Collectively, these findings imply notable advantages in employing A. swirskii for controlling two-spotted mites in the Tibetan Plateau. Furthermore, based on the results, A. swirskii was the most effective, and A. barkeri was the least effective in controlling two-spotted mites in the Tibetan Plateau. These findings could inform the development of a feasible biological control method based on suitable predatory mite species to manage T. urticae in the Tibetan Plateau, and would be helpful in delaying the rise or emergence of chemical pesticide resistance in two-spotted mites.

An effective approach to fabricate large-scale of conducting polyaniline (PANI) by an in situ anodic electrochemical polymerization on the nickel foam, which coated by a novel aryl diazonium salt (ADS)-functionalized graphene (ADS-G). In present work, ADS-G was used as a high surface area support material for electrochemical polymerization of PANI. Electrochemical performances of the ADS-G/PANI composites exhibited better suitability as supercapacitor electrode materials than that of the PANI. The ADS-G/PANI composites achieved the specific capacitance of 528 F g-1, which was higher than that of PANI (266 F g-1) due to the excellent electrode-electrolyte interaction and synergistic effect of electrical conductivity between ADS-G and PANI in the composites. These findings suggested that the ADS-G/PANI composites were a suitable composite for the potential supercapacitor applications.

(1) Background:The objective of this study was to explorethe dynamic changes of gut microbiota in Simmental calves before weaning, and compared microbial composition and functionality differences between diarrhea and health calves; (2) Methods: Fourteen neonatal Simmental calves were divided into a health group (n = 8) and diarrhea group (n = 6). The rectal stool samples were collected from each calf on days 1, 3, 5, 7, 9, 12, 15, 18, 22, 26, 30, 35, and 40. The high-throughput sequencing analysis of the 16S rRNA gene V1–V9 region was conducted to explore the changes in gut microbiota over time in both groups and assess the influence of diarrhea on microbiota structure and function; (3) Results: E.coli, B.fragilis, and B.vulgatus were the top three bacterial species of pre-weaning Simmental calves.Meanwhile, the major functions of fecalmicrobiota included the “Metabolic pathways”,“Biosynthesis of secondary metabolites”,“Biosynthesis of antibiotics”, “Microbial metabolism in diverse environments”, and “Biosynthesis of amino acids”. For calves in health group, PCoA revealed that the bacterial profiles generated from days 1, 3, 5, 7, and 9 separated from days 15, 18, 22, 26, 30, 35, and 40. While the microbial profiles of calves on day 12 crossed with both clusters, suggesting that the dynamic changes of microbial structures with the increasing of ages. When compared the difference of the relative abundance of bacteria between calves in health and diarrhea groups, the results showed that the relative abundance of the beneficial L.johnsonii, F.prausnitzii, and Limosilactobacillus in the health group were significantly higher than those in the diarrhea group (p

Remote sensing (RS) technology has significantly contributed to geological exploration and mineral resource assessment. However, its effective application in vegetated areas encounters various challenges. This paper aims to provide a comprehensive overview of the challenges and opportunities associated with RS-based lithological identification in vegetated regions. The article begins by introducing the sources and processing methods of RS data, which serve as the foundation for subsequent analysis. Moreover, it highlights the techniques and methodologies employed for lithological classification in vegetated areas. Notably, hyperspectral RS and Synthetic Aperture Radar (SAR) have emerged as prominent tools in lithological identification. In addition, this paper addresses the limitations inherent in RS technology, including issues related to vegetation cover and terrain effects, which significantly impact accurate lithological mapping. To propel further advancements in the field, the paper proposes promising avenues for future research and development. These include the integration of multi-source data to enhance classification accuracy and the exploration of novel RS technologies and algorithms. In summary, this paper presents valuable insights and recommendations for advancing the study of RS-based lithological identification in vegetated areas.

Penile squamous cell carcinoma (SCC) is a rare disease. Treatment options for advanced penile cancer are often limited and prognosis remains poor. We reported a 52-year-old male recurrent and metastatic penile SCC patient with high PD-L1 expression(90%) and TMB(14.4 muts/Mb). He had undergone penectomy, bilateral inguinal lymph node dissection and excision of the abdominal wall mass during two surgeries. Despite cisplatin-based concurrent chemoradiotherapy and sequential chemotherapy with docetaxel plus cisplatin were then carried out, the carcinoma still had progressed. The patient then obtained progression free survival exceeding 32 months with continuous sintilimab, although new onset of ICI-induced diabetes after 24 cycles of sintilimab and required sustained insulin treatment. He didn’t have positive type 1 diabetes associated autoantibodies, but had susceptible HLA genotype DR3-DQ2 haplotype. This is the first patient with radiation and multichemorefractory penile SCC obtained remarkable anti-tumor effect of partial regression exceeding 32 months during continuous sintilimab.