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.

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

In this paper, we establish the generalized Qi-type inequality involving conformable fractional integrals. The results presented here would provide extensions of those given in earlier works.

Silicon anodes have been considered one of the most promising anode candidates for the next generation of high-energy density lithium-ion batteries due to the high theoretical specific capacity (4200 mAh g-1) of Si. However, high lithiation capacity endows silicon anodes with severe volume expansion effects during the charge/discharge cycling. The repeated volume expansions not only lead to the pulverization of silicon particles and the separation of electrode materials from the current collector, but also brings rupture/formation of solid electrolyte interface (SEI) and also continuous electrolyte consumption, which seriously hinders the commercial application of silicon anodes. Structural design and optimization is the key to improving the electrochemical performances of silicon anodes, which has attracted wide attention and research in recent years. This paper mainly summarizes and compares the latest research progress for the structural design and optimization of silicon anodes.

Infrared dim and small target detection is a key technology of various detection tasks. However, due to the lack of shape, texture, and other information, it is a challenging task to detect dim and small targets. Recently, since many traditional algorithms ingore global information of infrared images, they generate some false alarms in complicated environments. To address this problem, in this paper, a coarse-to-fine deep learning-based method is proposed to detect dim and small targets. Firstly, a coarse-to-fine detection framework integrating deep learning and background prediction is applied for detecting targets. The framework contains of coarse detection module and fine detection module. In coarse detection stage, Region Proposal Network (RPN) is employed to generate masks in target candidate regions. Then, for further optimize the result, inpainting is utilized to predict the background by the global semnantic of images. In this paper, inpainting algorithm with a mask aware dynamic filtering module is incorporated into the fine detection stage to estimate background in candidate target areas. Finally, compared with existing algorithms, the experimental results indicate that the proposed framework have effective detection capability and robustness for complex surroundings.

Developing new energy is critical to China's green and low-carbon development. And the New Energy Demonstration City Policy (NEDCP) is a vital innovation policy that inspires the development of new energy. Is the NEDCP facilitating green and low-carbon development, if so, how? Employing unbalanced panel data from 2003 to 2017, the impact of NEDCP on green and low-carbon development was studied by using the "difference in difference" (DID) model. We find that this policy can take significantly role. After various robustness tests, our results are still valid. According to the heterogeneity analysis, non-resource and non-old industrial base cities have a greater positive impact from this policy. The mechanism analysis denotes that the positive policy effect works through upgrading the industrial structure and stimulating urban innovation. The substantial empirical evidence presented in this article supports the continued promotion and implementation of new energy demonstration cities.

Sensory descriptive analysis was used to evaluate the aged Feng-flavored baijiu. The results indicated that there are notable differences in the samples of different ages. The samples with shorter storage times and fresh distilled Baijiu present bran flavor, and fresh green flavor. with the increase of storage time, the fragrance of honey, sweetness, flowers, and aging gradually increases. The samples of Feng-flavored baijiu were dected by Headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC–TOFMS) , in total, 496 sustances were identified in all samples, mainly containing 14 types of substances, such as esters, aldehydes etc., of which 42 substances were found in Feng-flavored baijiu for the first time. Chemometrics was used to analyze the key differential compounds. 143 differential compounds closely related to aging were preliminarily screened, and principal component analysis revealed that these samples were separated by year. 65 differential compounds were selected out by partial least squares discriminant analysis(PLS-DA). Furthermore, 43 key differential compounds were selected from the aged Feng-flavored baijiu combined with variable importance in projection and Pearson correlation coefficients. Partial least squares regression (PLSR) was used to research the correlation of sensory properties and key differential compounds, and the results indicated that most compounds were closely related to the aged Baijiu . This study afford theoretical basis and reference for flavor research of Feng-flavored baijiu.

This paper introduces a chip-level oven-controlled system for improving the temperature stability of MEMS resonators. Wherein the resonator and the micro-hotplate are manufactured by MEMS technology, then wire-bounded in a package shell at the chip level. The proposed resonator is transduced by the AlN film, and its temperature is monitored by temperature-sensing resistors on both sides. The designed micro-hotplate is placed at the bottom of the resonator chip as a heater and insulated by airgel. The PID pulse width modulation (PWM) circuit controls the heater according to the temperature detection result to provide a constant temperature for the resonator. The proposed oven-controlled MEMS resonator (OCMR) exhibits a frequency drift of 3.5ppm in the range of -50°C to 125°C, and the method also can be applied to other MEMS devices that require temperature control.

In this article, a novel hybrid welding process called plasma-TIG coupled arc welding was proposed to improve the efficiency and quality of welding by utilizing the full advantage of plasma and TIG welding processes. The two arcs of plasma and TIG were pulled into each other into one coupled arc under the effect of Lorentz force and plasma flow force during welding experiments. The arc behavior of coupled arc was studied by means of it’s arc profile, arc pressure and arc force conditions. The coupled arc pressure distribution measurements were performed. The effects of welding conditions on coupled arc pressure were evaluated and the maximum coupled arc pressure was improved compared with single-plasma arc and single-TIG arc. It was found that the maximum arc pressure was mainly determined by plasma arc current and plasma gas flow. According to the results, the proposed coupled arc welding process have both advantages of plasma arc and TIG method, and it has a broad application prospect.

In order to further clarify the growth-promoting effect of non-core Metarhizium spp. M. marquandii on plants, M. marquandii SGSF043, which was obtained from the pre-screening in the laboratory, was selected as a test strain, and the effects of the fungus fermentation broth during the stabilization period of the growth of this strain on the growth and growth of maize seeds were investigated by using fermentation broth as a submerged seed. germination, seedling growth, and inter-root soil enzyme activity of seedlings. The results are as follows: In the seed germination test, M. marquandii SGSF043 fermentation liquid had a certain inhibitory effect on the germination of maize seeds, and the 10-times dilution of the fermentation liquid significantly promoted the seed germination, and the effect was the best; After the germination test, the growth of maize germ was promoted by the treatment groups of 10 times and 1,000 times diluent; In the field plot experiment, the 100-fold dilution had the best growth promotion effect, which could promote the growth of cabbage seedlings and increase the seedling biomass. The results show that M. marquandii SGSF043 has the potential to promote the growth of maize and improve the soil environment, which provides a theoretical basis for the research and application of M. marquandii in farmland.

This study aims to investigate the causal relationship between Levo-carnitine (LC) and its derivatives and schizophrenia (SZ) using a Two-sample Mendelian randomization (MR) method. Forward MR analysis was conducted using LC and its derivatives as exposure and SZ as the outcome. Candidate data were obtained from the openGWAS server. Instrumental variables (IVs) were identified as single nucleotide polymorphisms (SNPs) closely associated with exposure, and were harmonized with the outcome data after removing confounders and outliers. Hence, MR analysis was performed using inverse variance weighting (IVW) as the primary approach, and sensitivity analysis was conducted to assess the reliability and robustness of the MR results. Finally, a reverse MR analysis was carried out using the same analytical procedures as the forward one. The MR results indicate a significant negative causal relationship between isovalery-LC and SZ (P < 0.05), but in no other groups (P>0.05). Additionally, the reverse MR analysis did not identify any causal relationship between SZ and LC related exposures (P>0.05). Sensitivity analyses, including pleiotropy and heterogeneity analysis, did not reveal any potential bias on the MR results (P>0.05). The results implied that elevated levels of isovalery-LC may potentially mitigate the risk of developing SZ, thereby highlighting the prospective therapeutic and preventive implications of isovalery-LC in the clinical management of SZ.Keywords: schizophrenia; levo-carnitine; carnitine; mendelian randomization

Landslide is one of the most common geological disasters in China, which is characterized by suddenness and uncertainty, and it is difficult to realize accurate identification, early warning and forecasting of landslide disaster by conventional means. With the development of high-resolution remote sensing satellites and InSAR surface deformation monitoring technology, the traditional means of landslide monitoring data sources are limited, and there is a lack of effective methods to excavate the characteristics of the spatial distribution of landslide hazards and their triggering factors and other issues. In this paper, the area extending 10 km outside the VII isobar of the Gengma earthquake is taken as the study area, and 13 evaluation factors are screened out by integrating the factors of InSAR surface deformation, topography and geological environment, and the Bayesian Optimized Convolutional Neural Network (BO-CNN) is used for the evaluation of landslide susceptibility, and the BO-RF and PSO-SVM models are selected for the comparative analysis. The model accuracy evaluation was carried out by three indexes: ROC curve, AUC value and FR value, in which the ROC curves of PSO-SVM, BO-RF and BO-CNN were all close to the upper-left corner of the corner, and the AUC values were 0.9388, 0.9529, and 0.9535, respectively, and the FR value of landslide in the high susceptibility area of BO-CNN was as high as 14.9, and was higher than that of PSO-SVM and BO-RF, respectively. SVM and BO-RF model is 4.55 and 3.69 higher, the experimental results show that the BO-CNN model used in this paper has a better effect in landslide susceptibility evaluation, and the research results of the local government's disaster prevention and mitigation measures are of great significance.

The survey findings reveal that rivers worldwide carry an annual sediment load of 15 billion tons into the sea, and the Yellow River basin alone contributes 1.6 billion tons of sand. Therefore, understanding the science of wind and sand in the Yellow River is crucial to ensuring the safe development of similar basins across China and the world. This study examines the midstream wind and sand area of the Xiliugou tributary, a part of the upper Yellow River. The researchers used a stepped sand collector combined with an anemometer to measure the sand transport flux at 0-50 cm height on various underlying surfaces of the basin. Then, they estimated the amount of wind and sand entering the Yellow River using a function model based on the measured factors. Furthermore, the team analyzed the particle size composition of wind-eroded sand to better understand the principles of wind and sand erosion and accumulation in the basin. The results of the study show that the sand transport flux per unit area varies significantly across different underlying surfaces. Moreover, the contribution of moving sandy land, semi-fixed sand, and fixed sand to wind and sand deposition in the Yellow River basin was 77.08%, 15.30%, and 7.62%, respectively. The vertical change of sand transport rate on the basin's surface demonstrates that the total sand transport rate is an exponential function of wind speed. Based on this relationship, the researchers estimated that the total annual average wind and sand entering the Yellow River basin via the Xiliugou tributary is approximately 8.09×105t. Due to the basin's unique geography and sand source, the particle size composition of wind-eroded sand differs between the east and west sides of the river channel. On the west side, desert sand, mainly fine sand, and very fine sand constitutes the sand source. Conversely, on the east side, sand collected in the riverbed by secondary wind erosion is the primary sand source. Furthermore, human activities have disturbed the grain composition, mainly comprising powder and clay particles. This phenomenon, known as "wind-blown mud and water-washed sand," is evident in this geographical unit. In conclusion, the Yellow River basin still faces significant ecological security hazards. Understanding the coupling relationship between desert-basin-sand and wind is the foundation for effectively controlling wind and sand flow into the Yellow River basin.

Liquid-liquid phase separation (LLPS) of proteins has been found ubiquitously in eukaryotic cells, critical in the controlling of many biological processes through forming a temporary condensed phase with different bimolecular components. TDP-43 is recruited to stress granules in cells and is the main component of TDP-43 granules and proteinaceous amyloid inclusions in patients with amyotrophic lateral sclerosis (ALS). TDP-43 low complexity domain (LCD) is able to demix in solution forming the protein condensed droplets. The molecular interactions regulating its LLPS were investigated at the protein fusion equilibrium stage, where the droplets stopped growing. We found the molecules in the droplet were still liquid-like but with enhanced intermolecular helix-helix interaction in the LCD. The protein would start to aggregate after about 200 minutes of lag time and aggregate slower than at the condition when the protein does not phase separate or the molecules have a reduced intermolecular helical interaction. A structural transition intermediate towards protein aggregation was also discovered involving a decrease of the intermolecular helix-helix interaction and a reduction in the helicity. Therefore, LLPS and the intermolecular helical interaction could help maintain the stability of TDP-43 LCD.

In nature and engineering applications, flexible fiber beds covering biological surfaces can play a role in reducing resistance. These fibers deform under the action of fluids, and this deformation affects the fluid flow state, forming a complex fluid-solid interaction phenomenon. To quantitatively analyze such issues, the physical model is simplified to the deformation problem of an soft hair bed caused by Stokes flow, and the deformation problem of a single fiber caused by Stokes flow is further studied. The deformation problem of an elastic single fiber in a channel caused by Stokes flow can be described by a nonlinear integral equation. We have obtained a new series solution, which has been compared with the previous perturbation method to verify the accuracy and effectiveness of the series solution. Meanwhile, we have further provided an extended form of flexible fiber deformation through experimental fitting. This fluid-solid interaction problem involves multiple fields and is very important in many natural and engineering systems. The research in this paper can not only help us better understand complex phenomena in nature but also delve into the interaction mechanism between fluids and solids, providing a theoretical basis for future scientific research and engineering applications.

The nanocomposites with reversible cross-linking covalent bonds were prepared by reacting furfurylamine (FA)-modified diglycidyl ether of bisphenol A (DGEBA) and furfuryl-functionalized aniline trimer-modified graphene (TFAT-G) with bismaleimide (BMI) via Diels-Alder (DA) reaction. The successful synthesis of the TFAT modifier is confirmed by NMR hydrogen spectroscopy and IR spectroscopy tests. The structure and properties of TFAT-G epoxy nanocomposites are characterized by SEM, DSC, tensile and resistivity CES. The results show that TFAT-G was uniformly dispersed in the resin, and 1wt% TFAT-G composites increase to 233% for tensile strength, 63% for elongation at break, 66.1% for modulus and 7.8℃ for Tg. Overall, the graphene/self-healing resin nanocomposites have both good self-healing function and electrical conductivity by adding 1% modified graphene and still maintain the original 83% strength and 89% electrical conductivity after one cycle of heating repair.

The Chinese honeybee (Apis cerana cerana) sacbrood virus (CSBV) causes death of larvae and colony collapse, and could damage the beekeeping industry in China. We sequenced complete genomes of CSBV strains derived from the Maerkang area, Wenjiang area, and Wanyuan area of Sichuan province of China. The genome length of CSBV strains from Sichuan was 8863bp, and it contained one complete Open Reading Frame of a gene with 8544 bp that encoded a protein with 2848 amino acids. The (G+C) % and (A+T) % composition ranged from 40.6 to 40.7 and 59.3 to 59.4, respectively. A phylogenetic tree was constructed using the three CSBV strains and previously reported SBV and CSBV sequences from other regions. We found that viral strains clustered based on their region of origin and host species. The genetic sequences of the CSBV strain from Maerkang were 98.7% and 99.6% similar to CSBV strains from Wanyuan and Wenjiang, respectively. In addition, CSBV from Maerkang had 88.4%-95.2% sequence similarity to previously published genomes of CSBV or SBV from other areas. The VP1 gene sequenced in our study had a 43 bp deletion compared to VP1 sequences of CSBV from other regions in Asia. We detected 10 antigenic determinants on the VP1 protein of CSBV form Aba. Our study provides new insight into the diversity of CSBV strains in China and may help with identifying methods to prevent infection of honeybee colonies.

Heavy metals are toxic, persistent and non-degradable. After sedimentation and adsorption, they accumulate in water sediments. The aim of this study was to understand the heavy metal pollution of Qinjiang River sediments on the ecological environment and apportioning sources. The mean total concentrations of Mn, Zn, Cr, Cu, and Pb are 3.14, 2.33, 1.39, 5.79, and 1.33 times higher than the background values, respectively, except for the Co, Ni, and Cd, which are lower than the background values; Fe, Co, Ni, Cd, Cr, Cu, and Pb are all primarily in the residual state, while Mn and Zn are primarily in the acid-soluble and oxidizable states, respectively. Igeo, RI, SQGs and RAC together indicate that the pollution status and ecological risk of heavy metals in Qinjiang River sediments are generally moderate; among them, Fe, Co, Ni, Cd, Cr, and Pb are not harmful to the ecological environment of the Qinjiang River. Cu is not readily released because of its higher residual composition, depicting that Cu is less harmful to the ecological environment. Mn and Zn, as the primary pollution factors of the Qinjiang River, are harmful to the ecological environment. This heavy metal pollution in surface sediments of the Qinjiang River primarily comes from manganese and zinc ore mining. Manganese carbonate and its weathered secondary manganese oxide are frequently associated with a significant amount of residual copper and Cd, as a higher pH is suitable for the deposition and enrichment of these heavy metals. Lead-zinc ore and its weathering products form organic compounds with residual Fe, Co, Cr, and Ni, and their content is related to salinity. The risk assessment results of heavy metals in sediments provide an important theoretical basis for the prevention and control of heavy metal pollution in Qinjiang River.

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

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

The concept of ‘big data’ has been widely discussed, and its value has been illuminated throughout a variety of domains. To quickly mine potential values and alleviate the ever-increasing volume of information, machine learning is playing an increasingly important role and faces more challenges than ever. Because few studies exist regarding how to modify machine learning techniques to accommodate big data environments, we provide a comprehensive overview of the history of the evolution of big data, the foundations of machine learning, and the bottlenecks and trends of machine learning in the big data era. More specifically, based on learning principals, we discuss regularization to enhance generalization. The challenges of quality in big data are reduced to the curse of dimensionality, class imbalances, concept drift and label noise, and the underlying reasons and mainstream methodologies to address these challenges are introduced. Learning model development has been driven by domain specifics, dataset complexities, and the presence or absence of human involvement. In this paper, we propose a robust learning paradigm by aggregating the aforementioned factors. Over the next few decades, we believe that these perspectives will lead to novel ideas and encourage more studies aimed at incorporating knowledge and establishing data-driven learning systems that involve both data quality considerations and human interactions.

Controlled drainage (CD) is an important agricultural measure for maintaining soil moisture and nutrients, controlling groundwater level, and increasing crop yield. In arid regions, CD can be used to improve the water supply in agriculture and reduce environmental pollution. In this study, we investigated the effect of CD, including a drainage depth of 40 cm (CWT1) and 70 cm (CWT2) during the plant growth period, free drainage (FD), and open ditch drainage (OD) on the migration of water, nutrients, and salts in the soil; the dynamics of groundwater level; the loss of soil nitrogen; and the growth of oilseed sunflower plants. Compared with FD, CD increased the water and nutrient content in the soil, reduced nitrogen loss, and enhanced the ability of the soil to continuously supply nitrogen to the oilseed sunflower plants, which benefited plant growth at later growth stages and reduced environmental pollution. During the period between irrigation at the budding stage and harvest stage, the average soil water content in the 0–20 cm soil layer in CWT1 increased by 3.67%, 4.78%, and 0.55%, respectively, compared with that in CWT2, FD, and OD. The soil mineral content in CWT1 was 25.17%, 35.05%, and 17.78% higher than that in CWT2, FD, and OD, respectively, indicating that higher soil salinity occurred at the later stage of plant growth in CWT1, which actually had little effect on the plants due to their enhanced salt tolerance and increased need for water and nutrients at that stage. In addition, CD delayed the decline in groundwater level, which allowed the plants to use groundwater at later growth stages, and as a result the yield and water use efficiency were improved. CWT1 significantly increased oilseed sunflower yield by 4.52–11.14% and increased water use efficiency by 1.16–10.8%. Moreover, CWT1 also increased the survival rate of the oilseed sunflower plants by 2.62–2.92%, and the plants demonstrated good growth. Therefore, under CD conditions, plants used soil water and nitrogen more efficiently and, as a result, their productivity was increased, and the water quality was improved.

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

In order to provide high capacity and universal access of telecommunication networks, this paper reviews and prospects the advanced multiplexing technology, physical layer digital signal processing technology, infrastructure sharing technology, security protection technology, intelligent control management and other key technologies for beyond 100G next generation passive optical network (NG-PON).

: Background: The polysaccharides are one of the main active ingredients of Polygonum sibiricum (PSP), which is a traditional food and medicine homologues in China. The antidepressant-like effects of PSP and its underlying mechanisms remain to be studied in depth, especially the regulation of microglial polarization. Methods: The chemical composition and structural characteristics of PSP was determined firstly. The CUMS procedure was carried out to the zebrafish for 5 weeks and PSP were immersed administration for 9 days (1 h/d). The body weight of zebrafish was monitored and the behavioral tests, including the novel tank test and light and dark tank test, were performed to evaluate the antidepressant-like effects of PSP. Then the function of HPI axis, the levels of peripheral inflammation, neuronal and blood-brain barrier damage in mesencephalon and telencephalon and the mRNA expression of M1/M2 phenotype genes in brain were examined. Results: PSP samples had the typical structure characteristics of polysaccharide, consisting of glucose, mannose and galactose with the average Mw 20.48 kDa, which owned a porous and agglomerated morphology. Compared with untreated zebrafish, the depression-like behaviors of CUMS-induced zebrafish were significantly attenuated. PSP significantly decreased the levels of cortisol and the pro-inflammatory cytokines and increased the levels of the anti-inflammatory cytokines in the body of CUMS-induced depressive zebrafish. Furthermore, neuronal and blood-brain barrier damage in mesencephalon and telencephalon and the mRNA expression of M1/M2 phenotype genes in brain were remarkably reversed by PSP. Conclusion: These findings indicated that the antidepressant-like effects of PSP were related to alter the HPI axis hyperactivation, suppress peripheral inflammation, inhibit neuroinflammation induced by microglia hyperactivation, and modulate microglial M1/M2 polarization. The current study provides foundation to the future exploitation of PSP in the functional foods of emotional regulation.

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

An optimal scheduling strategy for cooling, heating and power (CCHP) joint-power-supply system is proposed to improve energy utilization and minimize costs in this paper. Firstly, the mathematical model of CCHP system is established. Particle swarm optimization (PSO) is used to optimize the regularization coefficient C and the kernel parameter λ which can affect the prediction accuracy of KELM(PSO-KELM). Then PV generation and load prediction model are established by PSO-KELM. In order to jump out of local optimal solution, Cauchy variation is introduced in SFLA local update, and adaptive mutation operation is carried out on SFLA individuals. The predictions of PV generation and load power by PSO-KELM are imported into the objective function, and the microgrid dispatching model is solved by the improved SFLA algorithm. Compared with the traditional GA-KELM and KELM, PSO-KELM has faster convergence and prediction accuracy. Compared with the power supply division, the operation cost of the power grid is reduced by the proposed optimization dispatching strategy of CCHP micro-grid.

A method of direction-of-arrival (DoA) estimation for FMCW radars is presented. In addition to MUSIC and ESPRIT, which are well-known high-resolution DoA estimation algorithms, deep learning has recently emerged as a very promising alternative. It is proposed in this paper to use a 3D convolutional neural network (CNN) for DoA estimation. The 3D-CNN extracts from the radar data cube spectrum features of the region of interest (RoI) centered on the potential positions of the targets, thereby capturing the spectrum phase shift information, which corresponds to DoA, along the antenna axis. Finally, the results of simulations and field experiments are provided to demonstrate the superior performance, as well as the limitations, of the proposed 3D-CNN.

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

Controlling Nutritional Status (CONUT) Score is useful for the nutritional screening. We aimed to explore whether the CONUT score may predict a 3-month functional outcome in hemorrhagic stroke (AHS). Totally, 349 patients with incident AHS were consecutively recruited, and their malnutrition risks were determined using a high CONUT score of ≥ 2. Poor functional outcomes were defined as the modified Rankin Scale (mRS) score of ≥ 3 at 3 months. A total of 328 patients (mean age, 60.4 ± 12.83 years; 66.8% male) were included, 172 (52.40%) patients at malnutrition risk and 104 (31.7%) patients with a poor prognosis. High-CONUT patients had lower total lymphocyte counts and total cholesterol levels than low-CONUT patients (p < 0.001 and p = 0.012). At 3-month post discharge, patients with malnutrition risk had higher hospitalization costs (p = 0.021), lower Barthel Index (p = 0.001), and more infectious complications (p = 0.002) than those without, and there was a greater risk for poor functional outcomes in the high-CONUT compared with the low-CONUT patients at admission (adjusted odds ratio: 2.32, 95% confidence interval: 1.28-4.17). High-CONUT scores predict a 3-month poor prognosis in AHS, which may help identify the AHS patients who need additional nutritional managements.

Type 2 diabetes mellitus (T2DM), a multifactorial and complicated metabolic disorder, is a growing public health problems. Numerous studies indicated that bioactive compounds from herbal medicine have beneficial effects on T2DM prevention and treatment, owing to their numerous biological properties. Curcumin, the major curcuminoid of turmeric, is one of the most studied bioactive components of herbal supplements, which has a variety of biological activities. Clinical trials and preclinical research have recently produced compelling data to demonstrate the crucial functions of curcumin against T2DM via several routes. Accordingly, this review systematically summarizes the antidiabetic activity of curcumin, along with various mechanisms. Results showed that effectiveness of curcumin on T2DM is due to it being anti-inflammatory, anti-oxidant, anti-hyperglycemic, anti-apoptotic, anti-hyperlipidemia and other activities. In light of these results, curcumin may be a promising prevention/treatment choice for T2DM.

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

The teaching and learning environment have changed significantly over the last decade with the integration of an increasing amount of information and communication technologies, especially in distance education due to global pandemics, total lockdowns, isolation, and quarantine periods. The number of numerous virtual and non-virtual tools involved in educational processes is growing day by day. In terms of technological innovations used in learning environments, many researchers and educators are trying their best to bring more creative ideas into the technology- based learning environments. Although higher educational institutions have greatly benefited from the growing number of hardware and software resources in the educational process, they have also faced some setbacks that have harmed the learning processes. These technologies have in turn complicated some of the processes in the learning atmosphere. Therefore, we take Spanish teaching course as an example to present the challenging smarter teaching and learning systems that higher educational institutions face today.

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

Aging is the important risk factor for tumorigenesis. Metabolic reprogramming is hallmark of both aging and tumor initiation. However, how the crosstalk between aging and metabolic reprogramming affects the tumor microenvironment (TME) to promote tumorigenesis was poorly explored. We utilized a computational approach proposed by our previous work, termed as MMP3C (Modeling Metabolic Plasticity by Pathway Pairwise Comparison), to depict age-related metabolic plasticity using pan-cancer bulk RNA-seq data. Through MMP3C analysis across 17 age-related cancer types, a high metabolic organized heterogeneity was found across those cancer types. Subsequent analysis revealed a higher degree of glycolysis and impaired oxidative phosphorylation in older patients. Similar phenomenon was also observed at the single cell resolution. Many energy generation pathways, i.e., TCA cycle, oxidative phosphorylation were weakened in activated T cells and macrophages, while it increased in exhausted T cells, immunosuppressive macrophages, and Tregs in older patients. It was suggested that aging-induced metabolic switches alter the utilization of glucose, thereby influencing immune function and resulting in the remodeling of the tumor microenvironment. This study provides new insights into the associations between tumor metabolism and TME mediated by aging, linking with novel strategies for cancer therapy.

In this study, we improved the photovoltaic (PV) properties and storage stabilities of inverted perovskite solar cells (PVSCs) based on methylammonium lead iodide (MAPbI3) by employing bathocuproine (BCP)/poly(methyl methacrylate) (PMMA) and BCP/polyvinylpyrrolidone (PVP) as hole-blocking and electron-transporting interfacial layers. The architecture of the PVSCs was indium tin oxide/poly(3,4-ethylenedioxythiophene):polystyrenesulfonate/MAPbI3/[6,6]-phenyl-C61-butyric acid methyl ester/BCP:PMMA or BCP:PVP/Ag. The presence of PMMA and PVP affected the morphological stability of the BCP and MAPbI3 layers. The storage-stability of the BCP/PMMA-based PVSCs was enhanced significantly relative to that of the corresponding unmodified BCP-based PVSC. Moreover, the PV performance of the BCP/PVP-based PVSCs was enhanced when compared with that of the unmodified BCP-based PVSC. Thus, incorporating hydrophobic polymers into BCP-based hole-blocking/electron-transporting interfacial layers can improve the PV performance and storage stability of PVSCs.

Japanese encephalitis is a zoonotic disease caused by Japanese encephalitis virus (JEV). It is mainly epidemic in Asia with an estimated 69,000 cases occurring per year. However, no approved agents are available for the treatment of JEV infection, and existing vaccines cannot resist various types of JEV strains. Drug repurposing is a new concept for finding new indication of existing drugs, and recently, it has been used to discover new antiviral agents. Identifying host proteins involved in the progress of JEV infection and using these proteins as targets are the center of drug repurposing for JEV infection. In this study, based on the gene expression data of JEV infection and the phenome-wide association study (PheWAS) data, we identified 286 genes participating in the progress of JEV infection using the systems biology methods. The enrichment analysis of these genes suggested that the genes identified by our methods were predominantly related to viral infection pathways and immune response-related pathways. We found that bortezomib which can target these genes may have potential effect on the treatment of JEV infection. Subsequently, we evaluated the antiviral activity of bortezomib using the JEV-infected mice model. The results showed that bortezomib can lower JEV-induced lethality in mice, alleviate suffering in JEV-infected mice and reduce the damage in brains caused by JEV infection. This work provides a new method for the development of antiviral agents.

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

We introduce a full binary directed tree structure to represent the set of natural numbers, further categorizing them into three distinct subsets: pure odd numbers, pure even numbers, and mixed numbers. We adopt a binary string representation for natural numbers and elaborate on the composite methodology encompassing odd- and even-number functions. Our analysis focuses on examining the iteration sequence (or composition) of the Collatz function and its reduced variant, which serves as an analog to the inverse function, to scrutinize the validity of the Collatz conjecture. To substantiate this conjecture, we incorporate binary strings into an algebraic formula that captures the essence of the Collatz sequence. By this means, we transform discrete powers of 2 into continuous counterparts, ultimately culminating in the smallest natural number, 1. Consequently, the sequence generated through infinite iterations of the Collatz function emerges as an eventually periodic sequence, thereby validating an enduring 87-year-old conjecture.

We use binary string to represent a natural number and show the composite procedure of odd-number and even-number functions, thus we propose full binary directed tree to represent the set of natural numbers and give another partition the natural number set to three sets: pure odd, pure even and mixed number. For the Collatz conjecture we make use of the parity of a natural number to analyse the sequence of iteration (or composite) of Collatz function and reduced Collatz function analog to the inverse function. We give tabular and binary strings to the algebra expression to state the sequence of Collatz, this is the key topic to proof the conjecture: the discrete powers of 2 can be changed to ultimately continuous powers of 2, finally get to pure even number and to the smallest number 1. The sequence created by the infinite iterations of the Collatz function becomes the ultimately periodic sequence if any natural number is the beginning value, proving the conjecture that has been held for 87 years.

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.

The identification of spatiotemporal heterogeneity, its key determinants, and the interaction effects between the driving factors of urban resilience (UR) within and between subregions is fundamental for understanding its underlying mechanisms. A resilience evaluation model was applied to analyze the temporal and spatial differences in UR in Hunan Province, China. The standard deviation ellipse was used to explore the spatial and dynamic evolution and direction of UR. A hot spot analysis identified clusters of cold and hot spots. The contribution of spatiotemporal differences in UR within and between subregions was assessed using the Theil index. A geodetector analysis determined the factors influencing UR and their interactions. There was an increasing trend in UR from 0.2692 in 2014 to 0.3422 in 2022. The number of cities with high resilience gradually increased from 2014 to 2022, while there was a decreasing gradient in UR from northeast to southwest across the province. High-resilience cities had positive spillover effects on the surrounding area. Hot spots were predominantly located in the northeast, while cold spots were concentrated in the southwest. The barycenter of UR shifted from northeast to southwest by 2018, before moving southeast by 2022. The Theil index values declined over time both within and between subregions. Per capita GDP, average wages of on-the-job employees, per capita social consumption, and doctor density enhanced UR. Two-factor interactions had a greater influence on the spatiotemporal heterogeneity of UR than single factors. Two-factor and nonlinear enhancements were identified as the primary mode of influence.

Polygonum sibiricum is a traditional Chinese food and medicine homologues with multiple active ingredients and extensive bioactive effects. Polygonum sibiricum polysaccharides (PSP) are one of the main active ingredients with the antidepressant activity, meanwhile the specific mechanisms of its action are still unclear. Recently, it is recognized by researchers that microglia play a double-edged role in neuroinflammation and the transformation of M1/M2 microglial phenotypes appears to be a potential therapeutic strategy in depression. Therefore, the present study evaluated the effects of PSP on microglial M1/M2 polarization and the molecular mechanisms were studied based on the lipopolysaccharide (LPS)-induced BV2 cell activation model. The results show that PSP significantly inhibited NO and LDH release and reduced ROS levels in LPS-induced BV2 cells. PSP could significantly reduce the protein expression level of Iba-1, decreased the mRNA levels of TNF-, IL-1 and IL-6, increased the mRNA level of IL-10. PSP also significantly reduced the protein expression level of CD16/32 and increased it of CD206, reduced the mRNA level and fluorescence intensity of iNOS and increased them of Arg-1. However, PSP pretreatment reversed the alterations of BDNF/TrkB/CREB and Notch/Hes1 pathways in LPS-induced BV2 cells. These results suggested that PSP exerted the anti-inflammatory effects by inhibiting M1 phenotype polarization and promoting microglia polarization toward M2 phenotype, and its regulation of microglia M1/M2 polarization may be associated with modulating the BDNF/TrkB/CREB and Notch/Hes1 pathways.

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

This study aimed to develop extended–release tablets containing 25 mg IMM−H014, an original drug formulated by a direct powder pressing method based on pharmaceutical–grade hydrophilic matrix polymers, such as hydroxypropyl methylcellulose, to establish an in vitro−in vivo corre-lation (IVIVC) to predict bioavailability. The tablets’ mechanical properties and in vitro and in vivo performance were studied. The formulation was optimized using a single factor experiment and the reproducibility was confirmed. The in vitro dissolution profiles of the tablet were de-termined in five dissolution media, in which the drug released from the hydrophilic tablets fol-lowed Ritger–Peppas model kinetics in 0.01 N HCl medium for the first 2 h, and in phosphate buffer saline medium (pH 7.5) for further 24 h. Accelerated stability studies (40°C, 75% relative humidity) proved that the optimal formulation was stable for 6 months. The in vivo pharmaco-kinetics study in beagle dogs showed that compared to the IMM−H014 immediate release prep-aration, the maximum plasma concentration of the extended release (ER) preparation was sig-nificantly decreased, while the maximum time to peak and mean residence time were significantly prolonged. The relative bioavailability was 97.9% based on an area under curve, indicating that the optimal formulation has an obvious ER profile. And a good IVIVC was established, which could be used to predict in vivo pharmacokinetics from the formulation composition.

Pleione is a genus of Orchidaceae and is one of the major sources of Pseudobulbus Cremastrae seu Pleiones (PCsP). It contains many constituents, such as phenanthrene, bibenzyl, glycoside, flavonoid and so on, which have plenty of bioactivities, including anti-tumor, anti-oxidation, anti-inflammatory, lowering glycemic levels and other pharma cological activities. In order to further utilize the edible and medicinal functions of Pleione, and clarify its medicinal active ingredients, this review systematically summarizes the constituents and pharmacological effects of Pleione, which will provide a theoretical foundation for the clinical application and new drug development．

The shear stress generated by wall turbulence is the main cause of wall friction resistance in turbulent flow through pipes. This paper investigates the impact of inserting rest periods (regions of constant Reynolds number) within the pulsating operating cycle of velocity on the fully turbulent flow at large time-averaged Reynolds numbers, using the Large Eddy Simulation (LES) method. The study aims to explore the effect of increasing rest periods within pulsations on drag resistance. The dimensionless shear stress and drag reduction rates during different time periods of rest were analyzed. Numerical simulation results indicate that the pulsating velocity operation mode does not necessarily lead to drag reduction; it may even result in increased resistance. Inserting rest periods within the pulsation cycle can achieve drag reduction effects, with the maximum drag reduction rate reaching 21.8\%. Comparisons with experimental data and Direct Numerical Simulation (DNS) from the literature validate the feasibility of using the LES method for pipe pulsating operation modes.

People have always hoped to be able to fill an entire plane with ``single unit cells'' without periodicity. This wish was realized after the mathematician discovered a 13-sided ``single unit cell'' named `einstein'. These non-periodic tessellations generally exhibit anisotropic properties, making them superior in terms of mechanical performance compared to periodic structures. From the perspective of information entropy, the reason behind the improved mechanical properties of these structures is the higher entropy associated with non-periodic configurations. To quantify the disorder of non-periodic structures, we propose an entropy expression for the `einstein' metamaterial. To demonstrate the mechanical properties of these high-entropy structures, we fabricate specimens using 3D printing and conducte mechanical experiments. For comparative analysis, we also use ABAQUS to perform finite element analysis of the problem. The research results reveal that the mechanical properties of high-entropy structures created by the non-periodic stacking of cells are significantly improved compared to those of low-entropy structures created by periodic stacking. The conclusions drawn from the study of individual issues are generalizable and may be of assistance in future material and structural design.

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.

Black soldier fly larvae (BSFL) can use food by-products or residues as a growth substrate, and their use is considered a strategic solution to improve the sustainability and efficiency of animal production. BSFL need to be reared under controlled environmental conditions, as temperature can affect the welfare of the larvae and the efficiency of their bioconversion. The goal of this experiment was to test different diets: control, vegetable, carnivorous, omnivorous and to assess their effect on larval growth performance, chemical composition, and substrate temperature. BSFL (6-days-old) were randomly selected and allocated to one of the four diets for the entire experiment (8 days). The temperature in each container was measured twice daily using a thermal imaging camera. The vegetable diet led to significantly lower growth performance (p

The genus Lirianthe in the family Magnoliaceae includes approximately 25 species, each with exceptional landscaping and horticultural or medical worth. Many of these plants are considered rare and protected due to their endangered status. The limited knowledge of species within this genus and the absence of research on its chloroplast genome have greatly impeded studies on the relationship between its evolution and systematics. In this study, the chloroplast genomes of 8 species from the genus Lirianthe were sequenced and analyzed, their phylogenetic relationships with other genera of the family Magnoliaceae are also elucidated. The results showed that the chloroplast genome sizes of the 8 Lirianthe species ranged from 159,548 to 159,833 bp. The genomes consisted of a large single copy region, a small single copy region, and a pair of inverted repeat sequences. The GC content was very similar across species. Gene annotation revealed that the chloroplast genomes contained 85 protein-coding genes, 37 tRNA genes, and 8 rRNA genes, totaling 130 genes. Codon usage analysis indicated that codon usage was highly conserved among the 8 Lirianthe species. Repeat sequence analysis identified 42-49 microsatellite sequences, 16-18 tandem repeats, and 50 dispersed repeats, with microsatellite sequences being predominantly single nucleotide repeats. DNA polymorphism analysis revealed 10 highly variable regions located in the large single copy and small single copy regions, among which rpl32-trnL, petA-psbJ and trnH-psbA are recommended candidate DNA barcodes for the genus Lirianthe species. The inverted repeat boundary regions show little variation between species and are generally conserved. Phylogenetic tree analysis confirmed the monophyly of the genus Lirianthe and its closest relationship with the genera, Talauma and Dugandiodendron. Morphological studies found noticeable differences between Lirianthe species in aspects including leaf indumentum, stipule scars, floral orientation, tepal number, tepal texture, and fruit dehiscence. In summary, this study elucidated the chloroplast genome evolution within Lirianthe and laid a foundation for further systematic and taxonomic research of this genus.

Background: Coronavirus Disease 2019 (COVID-19) has been demonstrated to be the cause of pneumonia. Nevertheless, it has not been reported as the cause of acute myocarditis or fulminant myocarditis. Case presentation: A 63-year-old male was admitted with pneumonia and cardiac symptoms. He was genetically confirmed as having COVID-19 according to sputum testing on the day of admission. He also had elevated troponin I (Trop I) level (up to 11.37 g/L) and diffuse myocardial dyskinesia along with a decreased left ventricular ejection fraction (LVEF) on echocardiography. The highest level of interleukin-6 was 272.40 pg/ml. Bedside chest radiographs showed typical ground-glass changes indicative of viral pneumonia. Laboratory test results for viruses that cause myocarditis were all negative. The patient conformed to the diagnostic criteria of the Chinese expert consensus statement for fulminant myocarditis. After receiving antiviral therapy and mechanical life support, Trop I was reduced to 0.10 g/L, and interleukin-6 was reduced to 7.63 pg/ml. Moreover, the LVEF of the patient gradually recovered to 68%. The patient died of aggravation of secondary infection on the 33^rd day of hospitalization. Conclusion: COVID-19 patients may develop severe cardiac complications such as myocarditis and heart failure. This is the first report of COVID-19 complicated with fulminant myocarditis. The mechanism of cardiac pathology caused by COVID-19 needs further study.

With the advances in industry and commerce, passengers have become more accepting of environmental sustainability issues; thus, more people now choose to travel by bus. Government administration constitutes an important part of bus transportation services as the government gives the right-of-way to transportation companies allowing them to provide services. When these services are of poor quality, passengers may lodge complaints. The increase in consumer awareness and developments in wireless communication technologies have made it possible for passengers to easily and immediately submit complaints about transportation companies to government institutions, which has brought drastic changes to the supply-demand chain comprised of the public sector, transportation companies, and passengers. This study proposed the use of big data analysis technology including systematized case assignment and data visualization to improve management processes in the public sector and optimize customer complaint services. Taichung City, Taiwan was selected as the research area. There, the customer complaint management process in public sector was improved, effectively solving such issues as station-skipping, allowing the public sector to fully grasp the service level of transportation companies, improving the sustainability of bus operations, and supporting the sustainable development of the public sector-transportation company-passenger supply chain.

In electromagnetic ultrasonic testing, it is difficult to recognize small-size bottom cracks by time of flight (ToF), and the lift-off fluctuation of the probe affects the accuracy and consistency of the inspection results. In order to overcome the difficulty, a novel EMAT (electromagnetic acoustic transducer)-PEC (pulse eddy current) composite sensor is designed. We use amplitude of bottom echo recorded by EMAT to identify the tiny bottom crack as well as the amplitude of PEC signals picked up by the integrated symmetric coils to measure the average lift-off of the probe in real time. Firstly, the effects of lift-off and bottom cracks on amplitude of bottom echo are distinguished combining the theoretical analysis and finite element method (FEM). And then an amplitude correction method based on the fusion of EMAT and PEC signals is proposed to reduce the impact of lift-off on the defect signal. The experimental results demonstrate that the designed composite sensor can effectively detect the bottom crack as small as 0.1mm* 0.3mm. The signal fusion method can accurately correct the amplitude of defect signal and the relative error is less than ±8%.

This study chose the indoor soil column test as the main method and the field test as the validation test to investigate the effects of various straw mulching techniques (surface, deep and straw mulching + deep burial) on evaporation and salt dynamics in saline soils. The results showed that straw mulching treatment could effectively reduce soil water evaporation, promote desalination in the stage of leaching infiltration and alleviate salt return in the stage of water evaporation, and the effect of straw mulching + deep burial treatment was better than that of single-layer straw mulching treatment. The indoor soil column test showed that S2D1 treatment (a 2:1 ratio of soil surface cover to the amount of straw buried 40cm below the soil surface) had the best effect on the suppression of soil moisture evaporation, and the cumulative evaporation of soil moisture was reduced by 65.85% compared with that of the CK, and the rate of salinity return in the evaporation stage was effectively reduced by 92.04% compared with that of the CK. In addition, there is a significant positive correlation between cumulative evaporation of soil moisture and cumulative soil salinity, which implies that cumulative soil salinity increases with cu-mulative evaporation of soil moisture. The results of the field experiment were consistent with the soil column test, and the S2D1 treatment was able to maintain high soil moisture content in all soil layers in all periods of the experiment and kept soil salinity in the 0-40 cm soil layer at a low level. However, in the 40-80 cm soil layer, the soil salinity suppression effect of DB treatment (straw buried at 40 cm below soil surface) was the best. So in summary, the S2D1 treatment had the best salinity and evapo-transpiration suppression effect in saline soils. This study is of great significance for the resource uti-lization of straw waste, improvement of water utilization and efficiency, and soil salinization manage-ment.

Black ginseng is a type of processed ginseng that is traditionally used as herbal medicine in East Asian countries. It is prepared from fresh, white, or red ginseng by undergoing a process of steaming and drying nine times. However, the chemical differentiation of black ginseng with different processing levels is not well understood. The aim of this study is to propose a new method for discriminating and quantifying black ginseng. Six ginsenosides from black ginseng were accurately quantified, and based on this, the black ginseng samples were divided into uncompleted and completed black ginseng. Ultra-high-performance liquid chromatography-quadrupole-time of flight/mass spectrometry (UPLC-Q-TOF/MS) combined with a multivariate statistical analysis strategy was then employed to differentiate the two groups. A total of 141 ions were selected as analytical markers of black ginseng, with 45 of these markers being annotated by matching precise m/z and MS/MS data from prior studies.

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

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

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

This study introduces a novel predictive model for atomization droplet size, developed through comprehensive data collected under elevated temperature and pressure conditions using a twin swirl airblast nozzle. The model, grounded in flow instability theory, has been meticulously parameterized using the Particle Swarm Optimization (PSO) algorithm. Through rigorous analysis, including analysis of variance (ANOVA), the model has demonstrated robust reliability and precision, with a maximum relative error of 19.3% and an average relative error of 6.8%. Compared to the classical atomization model by Rizkalla and Lefebvre, this model leverages theoretical insights and incorporates a range of interacting variables, enhancing its applicability and accuracy. Spearman correlation analysis reveals that air pressure and the air pressure drop ratio significantly negatively impact droplet size, whereas the fuel-air ratio (FAR) shows a positive correlation. Experimental validation at ambient conditions shows that the model is applicable with a reliability threshold of ≥0.13 and highlight the predominance of the pressure swirl mechanism over aerodynamic atomization at higher fuel flow rates (q > 1.25 kg/h). This research effectively bridges theoretical and practical perspectives, offering critical insights for the optimization of airblast nozzle design.

PVC items are environmentally friendly as, unlike polyolefins, they are mainly based on chlorine, one of the most abundant elements on earth. However, in the eco-design context, articles' durability plays the crucial role, contributing to the enhancement of their sustainability. In this framework the research on additives capable of increasing the weatherability of outdoor articles is essential. The theory section of the paper reviews the mechanisms of weathering leading to PVC degradation that undermine the durability of items such as window frames or roller shutters. The weathering of PVC items is a complex phenomenon involving photo-chemical and secondary chemical reactions, that yields the formation of conjugated polyene sequences underskin in absence of oxygen and carbonyls in the surface. Here the chain scission of the polymer backbone occurs, bringing the disintegration of the surface of the item and causing the typical discoloration called chalking, especially evident in dark-colored articles. In the experimental section of the paper the effect of different acid scavengers on the item weathering has been studied with natural outdoor and two accelerated exposures, xenon-arc and Q-UV testing devices. Results confirm that some acid scavengers are efficient in preventing chalking, but some are ineffective or even detrimental. Thus, the PVC formulations of durable articles upon weathering still depend on a complex choice of the appropriate ingredients, and several outdoor and indoor accelerated weathering tests are needed to predict the articles' lifetime.

(1) Background: in the context of sustainable development goals (SDGs), this work explores the repair direction of future cultivated land protection policies based on the Smith policy implementation model from the historical evolution to ensure that the cultivated land protection policy does not deviate during the implementation process. (2) Methods: this paper uses literature research and inductive deduction methods to sort out the evolution process of Chinese cultivated land protection policy, summarize the successful experience of transferring the focus of cultivated land protection in chronological order, and conclude the repair direction of Chinese cultivated land protection. (3) Results: although the Chinese cultivated land protection policy in the historical evolution has through three significant phases, there are still certain issues in the development trend of Chinese cultivated land protection policy based on regional division of labor for grain transportation and sales. (4) Conclusion: directly utilizing feedback from farmers as stakeholders will contribute to the maturity and improvement of cultivated land protection policies in the specific implementation of cultivated land protection policies.

Limoncella of Mattinata, a rare and ancient Mediterranean citrus fruit, was investigated by sequence analysis of the ribosomal internal transcribed spacer regions, which assigns it as a variety of Citrus medica L. Morphological, chemical, and biomolecular approaches were used to characterize flavedo and albedo, parts usually rich of bioactive compounds. The morphological findings showed albedo and flavedo cellular structures as “reservoirs” of nutritional components. Both albedo and flavedo hydroalcoholic extracts were rich in polyphenols, but they were different in compounds and quantity. The flavedo is rich in p-coumaric acid and rutin, whereas the albedo contains high levels of hesperidin and quercitrin. Antioxidant, anti-inflammatory, and genoprotective effects for albedo and flavedo were found. The results confirmed the health properties of flavedo and highlighted that albedo is also a rich source of antioxidants. Moreover, this study valorizes Limoncella of Mattinata's nutritional properties, cueing its crops' repopulation.

In 2020 the world experienced the threat of the COVID-19 epidemic, as seniors and chronic disease patients typically try to reduce their exercise and social activities to avoid increasing the risk of infection, which could lead to increased loneliness and even many diseases. This research combining golf croquet games with AIoT companion robots constructs a home-based intelligent exercise system thus uses the Technology Acceptance Model (TAM), deduces users’ intention to use this system based on perceived usefulness and perceived ease of use, and adds the needs of love and belonging, esteem, cognitive, aesthetic, and self-actualization in Maslow’s needs theory to conduct system needs analysis. The analysis results show that participants have a high level of acceptance of this system, believing that it is easy to learn and operate, can increase interaction with others, also found that this system can improve self-confirmation, satisfying the third for knowledge, feeling happy, and self-actualization needs are easier to fulfill. In the future, we shall collect and record the seniors in the process of use, so as to find out their health problems as soon as possible, expand their daily life through this exercise, and achieve the goal of happy living and health care.

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

The threat of fine particulate matter concentration (PM2.5) is increasing globally, Tackling this issue requires an accurate understanding of its trends and drivers. The article investigates the PM2.5 characteristics of 285 prefecture-level cities in China from 2000-2018 based on multiscale geographically weighted regression(MGWR), and the results show that（1）previous studies based on classical MGWR models may be somewhat unstable, while MGWR can reflect the scale of influence of different variables on the dependent variable, and its regression results are more reliable.（2）PM2.5 is very sensitive to carbon emission(CE) factors, and there is a high degree of spatial heterogeneity, and the influence scale of location is the smallest among all variables, close to the municipal scale.（3）In 2000, the constant term all, IS, OFT, CE, and LT positively affect PM2.5, while GDP (jurisdiction) and UR negatively affect PM2.5; in 2010, the constant term all, GDP (jurisdiction), IS, OFT and LT positively affect PM2.5, while UR and CE negatively affect PM2.5; in 2018 the constant term all, IS, OFT and CE factors positively affect PM2.5, and GDP (jurisdiction), UR and LT negatively affect PM2.5.

Zinc cobalt oxide-zinc hydroxide (ZnCo2O4-Zn(OH)2) microspheres were successfully fabricated on carbon cloth via a sample hydrothermal method. The surface morphology of these microspheres and their efficacy in degrading methyl violet were further modulated by varying the thermal annealing temperatures. The manipulation of thermal annealing temperatures was pivotal in adjusting the porosity of ZnCo2O4-Zn(OH)2 microspheres to amplify their photocatalytic performance. Various analytical techniques were utilized to evaluate the physical and chemical properties of the ZnCo2O4-Zn(OH)2 microspheres, including field-emission scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, field-emission transmission electron microscopy, X-ray photoelectron spectroscopy, and UV-vis spectroscopy. Compared to untreated ZnCo2O4-Zn(OH)2 microspheres, those subjected to thermal annealing exhibited increased specific surface area and light absorption capacity, rendering them highly effective photocatalysts under UVC light exposure. Subsequent studies have confirmed the superior performance of ZnCo2O4-Zn(OH)2 microspheres as a reusable photocatalyst for degrading methyl violet and tetracycline. Additionally, trapping experiments during the photodegradation process involving ZnCo2O4-Zn(OH)2 microspheres have identified hydroxyl radicals (·OH) and superoxide radicals (·O2–) as the primary reactive species.

Abstract Background: Small Cajal body-specific RNAs (scaRNAs) are a specific subset of small nucleolar RNAs (snoRNAs) that have recently been emerged as pivotal contributors in diverse physiological and pathological processes. However, their defined roles in carcinogenesis remain largely elusive. This study aims to explore the potential function and mechanism of SCARNA12 in bladder cancer (BLCA) and to provide a theoretical basis for further investigations into the biological functionalities of scaRNAs. Materials and Methods: TCGA, GEO and GTEx data sets were used to analyze the expression of SCARNA12 and its clinicopathological significance in BLCA. Quantitative real-time PCR (qPCR) and in situ hybridization were applied to validate the expression of SCARNA12 in both BLCA cell lines and tissues. RNA sequencing (RNA-seq) combined with bioinformatics analyses were conducted to reveal the changes of gene expression patterns and functional pathways in BLCA patients with different expression of SCARNA12 and T24 cell lines upon SCARNA12 knockdown. Single-cell mass cytometry (CyTOF) was then used to evaluate the tumor-related cell cluster affected by SCARNA12. Moreover, SCARNA12 was stably knocked down in T24 and UMUC3 cell lines by lentivirus-mediated CRISPR/Cas9 approach. The biological effects of SCARNA12 on the proliferation, clonogenic, migration, invasion, cell apoptosis, cell cycle and tumor growth were assessed by in vitro MTT, colony formation, wound healing, transwell, flow cytometry assays and in vivo nude mice xenograft models, respectively. Finally, chromatin isolation by RNA purification (ChIRP) experiment were further conducted to delineate the potential mechanisms of SCARNA12 in BLCA. Results: The expression of SCARNA12 was significantly up-regulated in both BLCA tissues and cell lines. RNA-seq data elucidated that SCARAN12 may play a potential role in cell adhesion and extracellular matrix (ECM) related signaling pathways. CyTOF results further showed that an ECM-related cell cluster with vimentin+, CD13+, CD44+, CD47+ was enriched in BLCA patients with high SCARNA12 expression. Additionally, SCARNA12 knockdown significantly inhibited the proliferation, colony formation, migration, and invasion abilities in T24 and UMUC3 cell lines. SCARNA12 knockdown prompted cell arrest in the G0/G1 and G2/M phase, and promoted the apoptosis in T24 and UMUC3 cell lines. Furthermore, SCARNA12 knockdown could suppress the in vivo tumor growth in nude mice. ChIRP experiment further suggested that SCARNA12 may combine transcription factors H2AFZ to modulate transcription program and then affect BLCA progression. Conclusion: Our study is the first to propose aberrant alteration of SCARNA12 and elucidate its potential oncogenic roles in BLCA via the modulation of ECM signaling. The interaction of SCARNA12 with the transcriptional factor H2AFZ emerges as a key contributor to the carcinogenesis and progression of BLCA. These findings suggest SCARNA12 may serve as a diagnostic biomarker and potential therapeutic target for the treatment of BLCA.

To enhance the safety of power grid operations, this study proposes a high-precision short-term photovoltaic power prediction method that integrates information from surrounding pho-tovoltaic stations and the Conv-LSTM-ATT model. In the deep learning prediction model, not only is numerical weather prediction (NWP) data from the target photovoltaic station used as input features, but also highly correlated features from nearby photovoltaic stations are incor-porated. The research begins by analyzing the correlation between irradiance and power se-quences, along with distance factors, to calculate a composite similarity index between the target and other regional photovoltaic stations. Stations with high similarity indices are then selected as data sources. Subsequently, Bayesian optimization techniques are employed to find the optimal data fusion ratios. Ultimately, using the selected data, power prediction mod-eling is conducted via the Conv-LSTM-ATT deep neural network. Experimental results con-firm the superiority of the proposed model, which demonstrates higher predictive accuracy compared to three other classical models. The data fusion strategy determined by Bayesian optimization significantly enhances prediction accuracy, reducing the root mean square error (RMSE) of the test set by 20.04%, 28.24%, and 30.94% for three weather types, respectively.

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

Rice production in the Anhui province is threatened by fungal diseases. We obtained twenty-five fungal isolates from rice and wild-rice leaves showing leaf spot disease collected along the Yangtze River. A phylogenetic analysis based on internal transcribed spacer (ITS), translation elongation factor 1 alpha (TEF1-α), and beta tubulin (TUB2) sequences revealed that one isolate (SS-2-JB-1B) grouped with Nigrospora shaerica, one (QY) with Nigrospora chinensis, twenty-two with Ngrospora oryzae, and one strain (QY-2) grouped in its own clade, related to but clearly different from N. oryzae. Nineteen tested isolates including sixteen strains from the N. oryzae clade and the three isolates of the other three clades, caused disease on detached rice leaves. The three isolates that did not belong to N. oryzae were also able to cause disease on rice seedlings, suggesting that they were rice pathogens. Isolate QY-2 differed from the other isolates in terms of colony mor-phology, cell-size, and susceptibility to fungicides, indicating that this isolate represents a new species that we named Nigrospora anhuiensis. Our analysis showed that N. sphaerica, N. chinensis, and the new species N. anhuiensis can cause rice leaf spot disease in the field. This research pro-vides new knowledge for understanding rice leaf spot disease.

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

One new cassane diterpene possessing an unusual N bridge between C-19 and C-20 named caesalsappanin R (1), as well as another new diterpene caesalsappanin S (2), were isolated from the seeds of Caesalpinia sappan with methanol extract. Their structures were determined by spectroscopic analysis and examined alongside existing data from prior studies. Their biological activities were profiled by their antiplasmodial activity.

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

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

ChatGPT is an AI language model trained on vast amounts of text data, including scientific papers, providing a comprehensive understanding of catalysis. However, its reliability in catalysis research is unknown. To evaluate reliability, we compared a ChatGPT-generated review article on heterogeneous catalysts for higher alcohols synthesis by CO₂ hydrogenation to published peer-reviewed papers. Although the ChatGPT review article covers most necessary parts, it lacks sufficient discussion of the reaction mechanism. The core sections are too general, being not specific enough to the topic, and contain errors. The lack of citations further increases unreliability. While ChatGPT can provide much content on catalysis, it is insufficient and inaccurate for research on specific topics.

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

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

Frequently Asked Questions (FAQs) systems rely on semantic symmetry similarity measuring between two sentences. To address the challenges of insufficient training data and limited domain-specific understanding in low-resource FAQs, this paper proposes a general framework, PDAMF-FAQ, to solve these issues. Firstly, we propose a paraphrasing-based data augmentation model that integrates syntactic information and edit vectors. Using a rule-based approach, it retrieves template sentences from a corpus and masks relevant words with special characters. Edit vectors between the original and paraphrase sentences are added to a pre-trained model's encoding layer to enhance the model's ability to learn the differences between the original and reference paraphrase sentences. Additionally, this paper presents a mixed-feature semantic matching model based on SimBERT. The model extracts keyword features from the text, replacing these keywords with special characters to construct intent features. These intent features, along with the user question and keyword features, are then concatenated to form the model's input. Experiments were conducted respectively on the paraphrasing-based data augmentation model, mixed-feature semantic matching model and their comprehensive application in a low-resource domain-specific FAQ. The experimental results show that the proposed framework effectively improve the performance of domain-specific FAQ system.

In the paper, the author introduces the notions "multi-order logarithmic numbers" and "multi-order logarithmic polynomials", establishes an explicit formula, an identity, and two recurrence relations by virtue of the Faa di Bruno formula and two identities of the Bell polynomials of the second kind in terms of the Stirling numbers of the first and second kinds, and constructs some determinantal inequalities, product inequalities, logarithmic convexity for multi-order logarithmic numbers and polynomials by virtue of some properties of completely monotonic functions.

Abstract: Chloroplast is a new hotspot in the field of plant transformation system of plant genetic engineering. Initially developed in Chlamydomonas and tobacco, it is now feasible in a broad range of species. They exploit the homologous recombination and segregation pathways acting on chloroplast genomes and are based on direct repeats, transient co-integration or co-transformation and segregation of trait and marker genes. Foreign site-specific recombinases and their target sites provide an alternative and effective method for removing marker genes from plastids.Chloroplast genetic engineering has many advantages over nuclear genetic enginering, especially site-specific introduction of foreign genes ,leading to the absence of gene siliency and positon effect,which providing the available to explore the regulation and mechanism of chloroplast genes`expression in vitro .It also can identify the structure and function of the chloroplast genome , the expression of chloroplast affect the nulear genome. In this paper, the basic methodology of chloroplast transformation, the current techniques and applications, and the future possibilities for Chloroplast genetic engineering was reviewed[1-3].

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

Over the few decades, cancer-associated mortalities and morbidities were continuously increased worldwide despite sophisticated technological advancements. Pharmaceutical interventions associated with drugs exhibit a high degree of side effects and toxicities in addition to very high costs. Subsequently, to reduce or to vanish the side effects and high costs, researchers are now exploring natural bioactive compounds such as quercetin in its nanoformulations along with biologics as cargo delivery vehicles. Quercetin along with mesenchymal stromal lineage-derived extracellular vesicles (EVs) possesses an anti-cancer potential that can be explored to treat hepatocellular carcinoma (HCC). Exerting enhanced effect, nano quercetin synergistically with EVs triggers the anti-cancer mechanisms by regulating and dysregulating several signalling mechanisms including NF-κB, p53, JAK/STAT, MAPK, Wnt/β-catenin and PI3K/AKT, in addition to PBX3/ERK1/2/CDK2, and miRNAs modulation. In addition, findings regarding the potential checkpoints of anti-cancer signalling pathways were investigated that offer opportunities to develop engineered EVs incorporated with nano quercetin for the development of novel therapeutics to treat HCC in future. In this present mechanistic review, we abridged the regulation of such signalling mechanisms synergetic approach of nano quercetin and EVs. The regulatory role of EVs in the manifestation of innumerable miRNAs has also been tailed with special context to HCC.

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

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

This study has investigated the effect of nutrition labeling on consumer guilt, in situations where consumers ingest products that have an unhealthy image. The first investigation has examined the effects of types of nutrition labeling (adding healthy ingredients/reducing unhealthy ingredients). The second investigation has examined the influence of two goal-activation types(utilitarian and hedonic) and nutrition labeling on consumer guilt. The findings reveal that the utilitarian-goal-activation group felt less guilty about consuming a product with a reduced unhealthy ingredient than they did about consuming a product with an added healthy ingredient. In addition, there were interactions between the two variables, since consumer goal activation had more effect on consumer guilt about products with reduced unhealthy ingredients than on products with added healthy ingredients. Based on these results, the academic and practical implications of the present study are discussed. and proposes several directions for future research.

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

The diffusion coefficient--a measure of dissipation, and the entropy--a measure of fluctuation are found to be intimately correlated in many physical systems. Unlike the fluctuation dissipation theorem in linear response theory, the correlation is often strongly non-linear. To understand this complex dependence, we consider the classical Brownian diffusion in this work. Under certain rational assumption, i.e. in the bi-component fluid mixture, the mass of the Brownian particle $M$ is far greater than that of the bath molecule $m$, we can adopt the weakly couple limit. Only considering the first-order approximation of the mass ratio $m/M$, we obtain a linear motion equation in the reference frame of the observer as a Brownian particle. Based on this equivalent equation, we get the Hamiltonian at equilibrium. Finally, using canonical ensemble method, we define a new entropy that is similar to the Kolmogorov-Sinai entropy. Further, we present an analytic expression of the relationship between the diffusion coefficient $D$ and the entropy $S$ in the thermal equilibrium, that is to say, $D =\frac{\hbar}{eM} \exp{[S/(k_Bd)]}$, where $d$ is the dimension of the space, $k_B$ the Boltzmann constant, $\hbar $ the reduced Planck constant and $e$ the Euler number. This kind of scaling relation has been well-known and well-tested since the similar one for single component is firstly derived by Rosenfeld with the expansion of volume ratio.

As customer demand for green products increases in the digital economic era, this study analyses the green innovation of the e-tailer and supplier in drop shipping models. Moreover, drop shipping e-tailers and suppliers with a drop shipping option need to make choices regarding whether to provide green or normal products to the market. When a supplier with a drop shipping option produces green products, more fees may be invested on the production of green products than on normal products. The drop shipping e-tailers and suppliers with a drop shipping option can also choose to sell normal products at a low cost, as before. This study designs four models of drop shipping e-teilers and suppliers with a drop shipping option under different choices, analyzes their operational process in drop shipping models, and investigates five theorems. The optimal pricings decisions and green degree of drop shipping e-tailers and suppliers with a drop shipping option were evaluated in this study. The impacts of the green innovation factor, green elasticity coefficient, manufacturing and distribution costs on the drop shipping e-tailers and suppliers with a drop shipping option, and the effect of other environmental parameters on the green degree of green products are also analyzed through computer simulation. The findings of the simulation analysis provide valuable guidance for e-tailers and suppliers with green innovation in drop shipping models and offer important academic and practical implications for e-commerce and the digital economy.

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

Background: Despite advances in the treatment of hepatocellular carcinoma (HCC) over the last few decades, treatment opportunities for patients with HCC remain limited. HCC is the most common form of liver cancer, accounting for approximately 90% of all cases worldwide. Moreover, apart from the current pharmacological interventions, hepatic resection and liver transplantation are the mainstay curative approaches for patients with HCC. Methods: This systematic review included phase I, II, III, and IV clinical trials (CTs) and randomized controlled trials (RCTs) on current treatments for patients with HCC in an Asian population (2013–2023). A total of 427 articles were screened, and 184 non-duplicate publications were identified. After screening titles and abstracts, 96 publications were excluded, and another 28 were excluded after full-text screening. The remaining 60 eligible RCTs/CTs were finally included. Results: Sixty clinical trials fulfilled our inclusion criteria and screened 36 drugs as monotherapy or combination therapy for HCC. Most studies used sorafenib alone or in combination with any of the treatment regimens. Lenvatinib or atezolizumab with bevacizumab was used for HCC after initial sorafenib treatment. Eighteen studies compared the efficacy of sorafenib with that of other drugs, including lenvatinib, cabozantinib, tepotinib, tigatuzumab, linifanib, erlotinib, resminostat, brivanib, tislelizumab, selumetinib, and refametinib. Conclusion: This study provides comprehensive insights into effective treatment interventions for HCC in Asian populations. The overall assessment indicated that sorafenib alone or in combination with atezolizumab and bevacizumab has been the first treatment choice in the past decade to achieve better outcomes in patients with HCC in an Asian population

Objectives: This study aimed to analyze the awareness of local residents regarding healthcare projects and to suggest some ideas for the revision of local ones. Methods: To delve into the opinions of local residents, the author of this study created a questionnaire composed of eight questions on the general characteristics of the respondents, eight questions on satisfaction with health centers, 16 questions on the awareness of healthcare projects, and 22 questions on local healthcare. The survey was conducted for 409 residents who visited public centers in Gimcheon from 15 March to 14 April 2021. Results: Data analysis revealed the following: The proportion of local residents who use health centers was 39.1%, and those users visit health centers, on average, 3.92 times a year. Among healthcare projects, the project known by the highest proportion of people was vaccinations (84.5%), which was also the project that was most used (38.1%). Among healthcare projects needed in the with-COVID-19 age, respondents awarded the highest score to vaccinations (4.15 points on a five-point Likert scale) and the second highest score to infectious disease management (4.12). Conclusions: For healthcare projects, central and local governments should focus on activating vaccinations, solving the problem of medical accessibility through untact remote treatment and establishing national infectious disease-specializing hospitals and local infectious disease management based on such national hospitals.

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

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

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

Coal is an important resource that is closely related to people’s lives and has an irreplaceable role. However, coal mine safety accidents occur from time to time in the process of working underground. To this end, this paper proposes a coal mine environmental safety early warning model to detect abnormalities and ensure worker safety in a timely manner by assessing the underground climate environment. In this paper, the support vector machine (SVM) parameters are optimized using an improved artificial hummingbird algorithm (IAHA), and its safety level is classified by combining various environmental parameters. To address the problems of insufficient global exploration capability and slow convergence of the artificial hummingbird algorithm during iterations, a strategy incorporating Tent chaos mapping and backward learning is used to initialize the population, a Levy flight strategy is introduced to improve the search capability during the guided foraging phase, and then the simplex method is introduced to replace the worst value before the end of each iteration of the algorithm. The IAHA-SVM safety warning model was established using the improved algorithm to classify and predict the safety of the coal mine environment into four classes. Finally, the performance of the IAHA algorithm and the IAHA-SVM model are simulated separately. The simulation results show that the convergence speed and the search accuracy of the IAHA algorithm are improved, and the performance of the IAHA-SVM model has a significant improvement.

Primary Sjögren's syndrome (pSS) is a chronic, systemic autoimmune disease defined as exocrine gland hypofunction resulting in dry eyes and dry mouth. Recent interest in biological therapies for pSS has been garnered, however achieving FDA-approval has been challenging due to the numerous complications in the trials. Current literature lacks insight and a molecular target-based approach to the development of biological therapies. This review focuses on novel research in newly defined drug targets and latest clinical trials for pSS treatment. A literature search was conducted on ClinicalTrials.gov using the search term “Primary Sjögren's syndrome”. Articles published between 2000 and 2021 in English language were included. Our findings revealed the potential targets for pSS treatment in clinical trials and the most recent advances in understand-ing of molecular mechanisms underlying the pathogenesis of pSS. A prominent gap in current trials is overlooking the treatment of extraglandular symptoms such as fatigue, depression and anxiety which pervade most patients with pSS. Based on dryness and these symptom-directed therapies, emerging biological agents targeting inflammatory cytokines, signal pathways and immune reaction have been studied and proved the efficacy and safety. Novel therapies may complement existing non-pharmacological methods of alleviating symptoms of pSS. Better grad-ing systems adding extraglandular symptoms to gauge disease activity and severity should be created. The future of pSS therapies may lie in gene therapy, stem cell and tissue engineering ther-apy.

Avian influenza viruses (AIVs) are highly contagious respiratory viruses of birds, lead-ing to significant morbidity and mortality globally and causing substantial economic losses to the poultry industry. Since their first isolation in 2013, the Asian-origin H5N1 highly pathogenic avian influenza viruses (HPAI) of clade 2.3.4.4b have undergone unprecedented evolution and re-assortment of internal gene segments and have spread to Asia, Europe, Africa, and America, caus-ing outbreaks in all the poultry categories. Novel epidemiological and pathobiological character-istics, distinct from other clades, are specific of clade 2.3.4.4b viruses. Wild waterfowl, the natu-ral reservoir of AIVs, are frequently found infected with clade 2.3.4.4b viruses, which can also cause high morbidity and mortality in these birds. The sustained clade 2.3.4.4b virus circulation in waterfowl has also led to virus infection in other wild bird species, with implications for the conservation of endangered species. Furthermore, clade 2.3.4.4b viruses have been isolated in var-ious wild and domestic mammals worldwide, and critical mutations related to virus adaptation to mammalian species have been identified, raising concerns about virus spillover to humans. The main clinical signs, and anatomopathological findings associated to clade 2.3.4.4b virus infection in birds and non-human mammals are hereby summarized.

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

Three monoruthenium complexes 1(PF6)23(PF6)2 bearing a N(CH3)-bridged ligand have been synthesized and characterized. These complexes have a general formula of [Ru(bpy)2(L)](PF6)2, where L is a 2,5-di(N-methyl-N-(pyrid-2-yl)amino)pyrazine (dapz) derivative with various substituents and bpy is 2,2′-bipyridine. The photophyscial and electrochemical properties of these compounds have been examined. The solid-state structure of complex 3(PF6)2 is studied by single crystal X-ray analysis. These complexes show two well-separated emission bands centered at 451 and 646 nm (max = 195 nm) for 1(PF6)2, 465 and 627 nm (max = 162 nm) for 2(PF6)2, and 455 and 608 nm (max = 153 nm) for 3(PF6)2 in dilute acetonitrile solution, respectively. The emission maxima of the higher-energy emission bands of these complexes are similar, while the lower-energy emission bands are dependent on the electronic nature of substituents. These complexes display two consecutive redox couples owing to the stepwise oxidation of the N(CH3)-bridged ligand and ruthenium component. In addition, density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations are carried out to elucidate these experimental findings.