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The high cost of centralized photovoltaic power generation projects is an important problem affecting industrial development, which needs to be solved urgently. It is particularly important to explore the influencing factors of cost control and the interaction between them. This paper takes a centralized photovoltaic power generation project as the research object, and determines the index system of influencing factors of cost control from the perspective of the life cycle. Secondly, the logical relationship between influencing factors is judged by the method of combining DEMATEL (decision-making trial and evaluation laboratory) and ISM (interpretive structural modelling). Finally, the multi-order recursive interpretation structure model is obtained, and the action mechanism between various factors is obtained. The results show that national policies and standards are the most profound influencing factors, and their cause degree reaches 2.155; the reason degree of market changes is the second, which is 1.586; bidding and contract management are the factors with the highest centrality, which is 7.120; and transmission and the storage of electricity and equipment repair and maintenance are the most direct factors affecting cost control. Finally, some suggestions are put forward for different types of influencing factors. The research results can better help photovoltaic power generation enterprises solve the problem of cost control. [ABSTRACT FROM AUTHOR]

Organic semiconductor power devices have been attracting increasing attention due to their advantages such as flexibility, low fabrication cost, and sustainability. They have found wide applications in fields such as flexible electronic devices and biomedical devices. However, in the field of power applications, the lack of reliable organic semiconductor power devices is mainly attributed to the limited thermal stability and electrical stability of organic materials. This article provides a detailed review of the development status of organic semiconductor power devices from three aspects: device structure, organic materials, and fabrication methods. It clarifies that the future development goal is to enhance the voltage resistance and thermal stability of organic transistors through higher-performance structure design, higher-mobility materials, and higher-quality fabrication methods. The continuous innovation and development of the structures, materials, and fabrication of these devices will generate more novel devices, offering more possibilities for the application of organic semiconductor power devices. This information is of great reference value and guidance significance for engineers in related fields. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is a common tumor. Our group has previously reported that sorcin (SRI) plays an important role in the progression and prognosis of HCC. This study aims to explore the mechanism of SRI inhibiting the mitochondrial apoptosis. Bioinformatics analysis, co-IP and immunofluorescence were used to analyze the relationship between SRI and STAT3. MMP and Hoechst staining were performed to detect the effect of SRI on cell apoptosis. The expression of apoptosis-related proteins and NF-κB signaling pathway were examined by Western blot and immunohistochemistry when SRI overexpression or underexpression in vivo and in vitro were found. Moreover, inhibitors were used to further explore the molecular mechanism. Overexpression of SRI inhibited cell apoptosis, which was attenuated by SRI knockdown in vitro and in vivo. Moreover, we identified that STAT3 is an SRI-interacting protein. Mechanistically, SRI interacts with STAT3 and then activates the NF-κB signaling pathway in vitro and in vivo. SRI interacting with STAT3 inhibits apoptosis by the NF-κB pathway and further contributes to the proliferation in HCC, which offers a novel clue and a new potential therapeutic target for HCC. [ABSTRACT FROM AUTHOR]

Karst regions are characterized by unique geological formations that pose challenges to soil fertility and plant nutrition. In this study, we investigated the distribution and interactions of selenium (Se) in soils of Zheng'an County, a representative karst region in subtropical China. The results showed that the Se enrichment in the soils of Zheng'an County was high, with total contents ranging from 0.49 to 3.87 mg/kg and an average of 1.22 mg/kg, making the area Se-rich. Despite the abundance of Se, the effective percentage of Se uptake by plants was relatively low due to the generally moderately acidic nature of the soils in the region (pH: 5.98–6.60), which encourages the conversion of the available Se into forms that are not readily accessible. In addition, the high organic matter (OM) content (21.92–127.66 g/kg) promoted Se retention by interacting with Ca2+ in carbonate rocks. In addition, the clay content (50.73% to 76.19%) enhanced Se adsorption and limited Se availability. In conclusion, this study provides a basis for soil management and ecological restoration strategies in karst landscapes, highlights new insights into the dynamics of Se, and calls for further research to elucidate the Se availability mechanism and improve the efficiency of Se uptake by plants. Meanwhile, this study provides the first systematic study of Se transport and transformation, as well as Se-enriched Gastrodia elata in karst regions, and provides a preliminary understanding of the geochemical behavior of Se in karst regions. [ABSTRACT FROM AUTHOR]

To address the problems of existing methods that struggle to effectively extract fault features and unstable model training using unbalanced data, this paper proposes a new fault diagnosis method for rolling bearings based on a Markov Transition Field (MTF) and Mixed Attention Residual Network (MARN). The acquired vibration signals are transformed into two-dimensional MTF feature images as network inputs to avoid the loss of the original signal information, while retaining the temporal correlation; then, the mixed attention mechanism is inserted into the residual structure to enhance the feature extraction capability, and finally, the network is trained and outputs diagnostic results. In order to validate the feasibility of the MARN, other popular deep learning (DL) methods are compared on balanced and unbalanced datasets divided by a CWRU fault bearing dataset, and the proposed method results in superior performance. Ultimately, the proposed method achieves an average recognition accuracy of 99.5% and 99.2% under the two categories of divided datasets, respectively. [ABSTRACT FROM AUTHOR]

Muscles play an indispensable role in human life. Surface electromyography (sEMG), as a non-invasive method, is crucial for monitoring muscle status. It is characterized by its real-time, portable nature and is extensively utilized in sports and rehabilitation sciences. This study proposed a wireless acquisition system based on multi-channel sEMG for objective monitoring of grip force. The system consists of an sEMG acquisition module containing four-channel discrete terminals and a host computer receiver module, using Bluetooth wireless transmission. The system is portable, wearable, low-cost, and easy to operate. Leveraging the system, an experiment for grip force prediction was designed, employing the bald eagle search (BES) algorithm to enhance the Random Forest (RF) algorithm. This approach established a grip force prediction model based on dual-channel sEMG signals. As tested, the performance of acquisition terminal proceeded as follows: the gain was up to 1125 times, and the common mode rejection ratio (CMRR) remained high in the sEMG signal band range (96.94 dB (100 Hz), 84.12 dB (500 Hz)), while the performance of the grip force prediction algorithm had an R2 of 0.9215, an MAE of 1.0637, and an MSE of 1.7479. The proposed system demonstrates excellent performance in real-time signal acquisition and grip force prediction, proving to be an effective muscle status monitoring tool for rehabilitation, training, disease condition surveillance and scientific fitness applications. [ABSTRACT FROM AUTHOR]

Progress in numerical models and improved computational capabilities have significantly advanced our comprehension of how aerosol particles impact thunderstorm clouds. Yet, much of this research has focused on employing bulk microphysics models to explain the impacts of aerosol particles acting as cloud condensation nuclei (CCN) on electrical activities in thunderstorm clouds. The bulk thunderstorm models use mean sizes of particles and terminal-fall velocities. This causes calculation deviation in the electrification simulation, which in turn leads to deviations in the simulation of lightning processes. Developing this further, we established a three-dimensional high-resolution cloud–aerosol bin thunderstorm model with electrification and lightning to provide more accurate microphysics and dynamic fields for studying electrical activities. For evaluating the impacts of aerosol particles, specifically CCN, on the properties of continental thunderclouds, aerosols from both clean and polluted continental environments were selected. Cloud simulations indicate that droplets develop a narrower spectrum in polluted continental conditions, and weakened ice crystal growth increases the number of small ice crystals compared to clean conditions. Smaller droplets and ice crystals result in less effective riming and decreased graupel concentration and mass. Consequently, a significant decrease in large ice particles leads to a weakened process of charge separation under conditions of pollution. As a direct result, there is about a 43% reduction in lightning frequency and a delay of approximately 5 min in the lightning process under polluted conditions. [ABSTRACT FROM AUTHOR]

Climate warming is a critical environmental issue affecting rice production. However, its effects on cooked rice texture and rice thermal properties remain unstudied in China. To address this gap, we conducted a two-year multi-site field warming experiment using free-air temperature increase facilities across three major Chinese rice cropping systems. Interestingly, warming had a minimal impact on the hardness of cooked rice, while it significantly increased stickiness by an average of 16.3% under warming conditions. Moreover, compared to control treatments, rice flour exhibited a significant increase in gelatinization enthalpy, onset, peak, and conclusion temperatures under warming conditions, with average increments of 8.7%, 1.00 °C, 1.05 °C, and 1.17 °C, respectively. In addition, warming significantly declined the amylose content, remarkedly elevated the protein content and relative crystallinity, and altered the weight distribution of the debranched starch. Correlation analysis revealed significant relationships between cooked rice stickiness, rice flour thermal properties, amylose content, protein content, and partial starch structures. Therefore, warming-induced alterations in rice composition and starch structure collectively enhanced cooked rice stickiness and rice thermal stability. [ABSTRACT FROM AUTHOR]

Featured Application: This study belongs to the field of intelligent non-destructive testing and proposes a CNN-based method for accurate quantification of defect characterized by ultrasonic diffraction method. The innovation in this study lies in several key aspects: (1) Development of a CNN architecture that automatically classifies A-scan signals in the scan path; (2) Connectivity region solving algorithm to accurately calculate the defect-region size according to the classification results; (3) An intelligent noise reduction framework that enables accurate identification of defective areas in complex noise situations. The purpose of this paper is to automate the interpretation of data during ultrasonic diffraction using a non-destructive testing (NDT) technique to accurately size defects for assisting in decision-making. A convolutional neural network (CNN) architecture was developed to automatically measure the length of the defect. Using the architecture, the population of A-scan signals in the scanning path was classified. The defect region was extracted and its size in the scanning direction was obtained by the connected region solution algorithm based on the classification results. The arrival time of diffraction waves was accurately identified by the intelligent denoising framework proposed, combined with Hilbert transform, and then the height of defects was calculated by corresponding geometric relations. The estimation results demonstrate that the measurement method can be considered as a useful technique for crack sizing in industrial structures, even in the case of complex noise. [ABSTRACT FROM AUTHOR]

The water entry of a torpedo is a complex nonlinear problem, involving transient impact, free surface deformation, droplet splashing, and fluid–structure coupling, which poses severe challenges to traditional mesh methods. The meshless smoothed particle hydrodynamics (SPH) method shows unique advantages in capturing the complex features of the water entry of the torpedo at different entry angles. However, it still suffers from some inherent shortcomings, such as low surface discretization accuracy, poor discretization flexibility, and low calculation efficiency. In this study, an improved adaptive SPH algorithm is proposed to investigate the water entry of the torpedo accurately and efficiently. This method integrates meshless point generation and adaptive techniques simultaneously. The numerical results demonstrate that when the torpedo vertically enters the water at different velocities, the induced impact loads acting on the head of the torpedo fluctuate significantly with two peak values in the initial stage and thereafter stabilize in a later stage. The impact load acting on the torpedo, the entry depth of the torpedo, the splash height of the droplets, and the size of the cavity generated around the torpedo increase with the increment in the entry velocity. When the torpedo enters the water at different entry angles under the same initial entry velocity, both the vertical and the horizontal movements of the torpedo are observed, which results in more complex variations in parameters along the x- and y-axes. The findings and the corresponding numerical method in this study can provide a certain basis for the future designs of the entry trajectory and the structural bearing capacity of torpedoes. [ABSTRACT FROM AUTHOR]

Accurate detection of the preload force of tower crane bolts is of great significance for the stable and safe operation of the equipment. The method of contact ultrasonic detection of bolt preload has always been the focus of attention, which can realize rapid in situ detection without damaging the parts. In order to improve the accuracy and convenience of ultrasonic measurement of bolt preload and meet the urgent needs of the actual industrial site for high-precision measurement of bolt preload, we propose to prepare ZnO piezoelectric coatings as functional layers for ultrasonic transducers using magnetron sputtering and deposit them directly on bolts. The growth behavior of the ZnO coatings is investigated by varying the sputtering power, sputtering gas pressure and target substrate distance, and the morphology, structure, and properties are characterized and analyzed. The ZnO piezoelectric coatings with high c-axis optimal growth orientation and excitation of ultrasonic longitudinal waves were finally obtained and verified to be effective and stable when applied to the bolts. [ABSTRACT FROM AUTHOR]

The application of bionic structures for the design of energy-absorbing structures has been proposed recently. The rapid advancement of additive manufacturing technology provides technical support for the fabrication of non-traditional structures and further improves the energy-absorbing properties of bionic structures. This work proposes a novel bionic hybrid structure that consists of honeycomb-inspired thin-walled tubes filled with weevil-inspired diamond TPMS (triple periodic minimal surface) structures. The energy-absorbing properties and the deformation behaviors of these topologies under axial crushing loads were investigated using combined numerical simulations and experimental tests. First, the effect of filling quantity and filling distribution on energy absorption of the hybrid structures was investigated. Results show that honeycomb tubes and diamond TPMS structures produce a synergistic effect during compression, and the hybrid structures exhibit excellent stability and energy absorption capacity. The bionic hybrid structure improves specific energy absorption (SEA) by 299% compared to honeycomb tubes. Peak crush force (PCF) and SEA are more influenced by filling quantity than by filling distribution. The effects of diamond TPMS structure volume fraction and honeycomb tube wall thickness on the energetic absorptive capacity of the hybrid structure were furthermore investigated numerically. Finally, a multi-objective optimization method was used to optimize the design of the bionic hybrid structure and balance the relationship between crashworthiness and cost to obtain a bionic hybrid energy-absorbing structure with superior performance. This study provides valuable guidelines for designing and fabricating lightweight and efficient energy-absorbing structures with significant potential for engineering applications. [ABSTRACT FROM AUTHOR]

In recent years, various kinds of civil explosive detonation accidents have occurred frequently around the world, resulting in substantial human casualties and significant property losses. It is generally believed that thermal stimulation plays a critical role in triggering the detonation of explosives; consequently, the study of the thermal hazards of explosives is of great significance to many aspects of safety emergency management practices in the production, transportation, storage, and use of explosives. It is known that the thermal stability of the ammonium perchlorate-aluminium system and the ammonium nitrate-aluminium system has been extensively investigated previously in the literature. However, there is a paucity of research on the thermal hazard characteristics of non-ideal explosives under varying oxygen balance conditions within the academic sphere. Therefore, this research focused on the study of the thermal hazards of non-ideal explosives based on thermokinetic analysis. The thermal hazards of non-ideal explosive mixtures of ammonium perchlorate and aluminium and of ammonium nitrate and aluminium were studied by thermal analysis kinetics. The thermokinetic parameters were meticulously studied through differential scanning calorimetry (DSC) analysis. The results showed that the peak reaction temperature and activation energy of the ammonium perchlorate-aluminium system were significantly higher than those of the ammonium nitrate-aluminium system. Under the condition of zero oxygen balance, the peak reaction temperature of the ammonium nitrate-aluminium system was 259 °C (heating rate 5 °C/min), and the activation energy was 84.7 kJ/mol. Under the same conditions, the peak reaction temperature and activation energy of the ammonium perchlorate-aluminium system were 292 °C (heating rate 5 °C/min) and 94.9 kJ/mol, respectively. These results indicate that the ammonium perchlorate-aluminium system has higher safety under the same thermal stimulation conditions. Furthermore, research on both non-ideal explosive systems reveals that the activation energy is at its peak under negative oxygen balance conditions, recorded at 104.2 kJ/mol (ammonium perchlorate-aluminium) and 86.2 kJ/mol (ammonium nitrate-aluminium), which indicates a higher degree of safety. Therefore, the investigation into the thermal hazards of non-ideal explosive systems under different oxygen balance conditions is of utmost importance for the enhancement and improvement of safety emergency management practices. [ABSTRACT FROM AUTHOR]

A chitosan-based Cu2+ fluorescent probe was designed and synthesized independently using the C-2-amino group of chitosan with 1, 8-naphthalimide derivatives. A series of experiments were conducted to characterize the optical properties of the grafted probe. The fluorescence quenching effect was investigated based on the interactions between the probe and common metals. It was found that the proposed probe displayed selective interaction with Cu2+ over other metal ions and anions, reaching equilibrium within 5 min. [ABSTRACT FROM AUTHOR]

Anoikis, a form of apoptosis resulting from the loss of cell–extracellular matrix interaction, is a significant barrier to cancer cell metastasis. However, the epigenetic regulation of this process remains to be explored. Here, we demonstrate that the histone deacetylase sirtuin 6 (SIRT6) plays a pivotal role in conferring anoikis resistance to colorectal cancer (CRC) cells. The protein level of SIRT6 is negatively correlated with anoikis in CRC cells. The overexpression of SIRT6 decreases while the knockdown of SIRT6 increases detachment-induced anoikis. Mechanistically, SIRT6 inhibits the transcription of N-myc downstream-regulated gene 1 (NDRG1), a negative regulator of the AKT signaling pathway. We observed the up-regulation of SIRT6 in advanced-stage CRC samples. Together, our findings unveil a novel epigenetic program regulating the anoikis of CRC cells. [ABSTRACT FROM AUTHOR]

The application of potassium fertilizer application and straw return are effective agronomic measures for increasing crop productivity; however, information on how straw return—when substituting potassium fertilizer—affects crop yield, efficiency, and quality in dryland remains limited. In this study, an experiment on a dryland summer maize and winter wheat rotation system was initiated in 2007. This study included four treatments: CK (no fertilizer and no straw return), NP (nitrogen and phosphorus fertilizer application without straw return), NPK (nitrogen, phosphorus, and potassium fertilizer application without straw return), and NPS (NP treatment with straw return, substituting potassium fertilizer as used in the NPK treatment). These treatments were employed to assess grain yield and fertilizer agronomic efficiency in 2015–2020. Additionally, we evaluated the content of nitrogen (N), phosphorus (P), and potassium (K), as well as the protein content and protein yield in maize and wheat grains and the protein components in wheat grains in 2019–2020. The results showed that compared to the CK treatment, NP, NPK, and NPS treatments not only significantly increased the yield, protein yield, and fertilizer agronomic efficiency in both maize and wheat but also increased the content of protein and protein components in wheat grains. Compared to the NP treatment, the NPK treatment significantly increased the contents of N, K, globulin, and gluten in wheat grains by 5.11%, 21.59%, 10.06%, and 15.14%. Compared to NPK treatment, NPS treatment significantly increased the average yield of summer maize by 21.33% and 20.91%, respectively, as well as the annual yield by 9.99% and 13.59%, the N fertilizer agronomic efficiency of summer maize by 132.47%, and the annual N and P fertilizer agronomic efficiency by 42.83% and 64.36%, over the five-year period. The NPS treatment also significantly increased the summer maize protein yield and annual protein yield by 10.43% and 23.08%, as well as the content of protein components, the protein content, and P content in wheat grains by 4.93–13.58%, 7.81%, and 28.89%, respectively. In conclusion, NPS treatment can not only enhance crop yield, protein yield, and fertilizer agronomic efficiency in summer maize annually but also has the advantage of promoting wheat quality. NPS is an efficient strategy to improve crop yield, efficiency, and quality in a dryland maize–wheat rotation system. [ABSTRACT FROM AUTHOR]

As a flexible, autonomous and intelligent motion platform, underactuated surface vessels (USVs) are expected to be an ideal means of transport in dangerous and complex marine environments. The success and efficiency of maritime missions performed by USVs depend on their ability to accurately follow paths and remain robust against wind and wave disturbances. To this end, this paper focuses on accurate and robust path following control for USVs under wave disturbances. Model predictive control with a quasi-infinite horizon is proposed which converts the objective function from an infinite horizon to an approximate finite horizon, providing the convergence performance in long prediction horizons and reducing the computation load explicitly. To enhance robustness against disturbances, a fixed-time disturbance observer is applied to estimate the time-varying and bounded disturbances. The estimated value is provided to the controller input to form a robust control framework with disturbance feedforward compensation and predictive control feedback correction, which is substantially different from existing works. The convergence and optimality of the proposed algorithm are presented mathematically. Finally, we demonstrate the advantages of the algorithm in both theory and simulation. [ABSTRACT FROM AUTHOR]

The diel vertical migration of mesopelagic fishes in the southern (S-May station and S-Nov station) and central (C-Jun station and C-Dec station) South China Sea was investigated through a series of continuous field surveys conducted in May, June, November, and December 2017. These surveys employed a combination of mid-water trawl and acoustics techniques. The diel migration process, vertical distribution, acoustic migration proportion, and migration pattern of mesopelagic fishes were analyzed. The results revealed that mesopelagic fishes initiated an upward migration before sunset, with the process concluding within 30–120 min after dark. Subsequently, they commenced a downward migration before dawn, which terminated within 10–50 min after sunrise. The mesopelagic deep-sea layers of mesopelagic fishes at the S-May, S-Nov, C-Jun, and C-Dec stations ranged from 360 to 700 m, 350 to 680 m, 350 to 520 m, and 300 to 700 m, respectively. The acoustic migration proportions of mesopelagic fishes at the corresponding stations were found to be approximately 44.5%, 25.7%, 29.8%, and 58.0%, respectively. There were seasonal and regional differences in the vertical migration and distribution patterns of mesopelagic fishes in the South China Sea. A total of 228 species were identified, including 203 fish species, 23 cephalopod species, and 2 shark species. Among these, a subset of 43 fish and cephalopod species exhibited extensive diel vertical migrating behavior. Specifically, this subset comprised 23 lanternfish species, 8 cephalopod species, and 12 other fish species. Lanternfishes were the predominant diel vertical migratory species, while cephalopods also played a significant role in diel vertical migration. The diel migration behavior was found to be slight for Diaphus lucidus, Melamphaes microps, Argyropelecus affinis, and six other fish species. Non-migratory behavior was observed in Sternoptyx obscura, Argyropelecus sladeni, Sternoptyx diaphana, and 13 other fish species. The diel migration habits of 178 additional species of fish, cephalopods, and sharks could not be definitively determined. [ABSTRACT FROM AUTHOR]

Heavy oil accounts for a considerable proportion of the world's petroleum resources, and its exploitation helps to mitigate reliance on conventional oil resources and diversify energy supply. However, due to the high viscosity and high adhesion characteristics of heavy oil, conventional methods such as thermal recovery, emulsification, and dilution have significant limitations and cannot meet the growing demands for heavy oil production. In this study, 3-propyltrimethoxysilane (MPS) was used to modify and graft amphiphilic surfactants (AS) onto nanosilica to prepare a salt-resistant (total mineralization > 8000 mg/L, Ca2+ + Mg2+ > 1000 mg/L) and temperature-resistant (250 °C) nanosilicon viscosity reducer (NSD). This article compares amphiphilic surfactants (AS) as conventional viscosity-reducing agents with NSD. FTIR and TEM measurements indicated successful bonding of 3-propyltrimethoxysilane to the surface of silica. Experimental results show that at a concentration of 0.2 wt% and a mineralization of 8829 mg/L, the viscosity reduction rates of thick oil (LD-1) before and after aging were 85.29% and 81.36%, respectively, from an initial viscosity of 38,700 mPa·s. Contact angle experiments demonstrated that 0.2 wt% concentration of NSD could change the surface of reservoir rock from oil-wet to water-wet. Interfacial tension experiments showed that the interfacial tension between 0.2 wt% NSD and heavy oil was 0.076 mN/m. Additionally, when the liquid-to-solid ratio was 10:1, the dynamic and static adsorption amounts of 0.2 wt% NSD were 1.328 mg/g-sand and 0.745 mg/g-sand, respectively. Furthermore, one-dimensional displacement experiments verified the oil recovery performance of NSD at different concentrations (0.1 wt%, 0.15 wt%, 0.2 wt%, 0.25 wt%) at 250 °C and compared the oil recovery efficiency of 0.2 wt% NSD with different types of demulsifiers. Experimental results indicate that the recovery rate increased with the increase in NSD concentration, and 0.2 wt% NSD could improve the recovery rate of heavy oil by 22.8% at 250 °C. The study of nano-demulsification oil recovery systems can effectively improve the development efficiency of heavy oil. [ABSTRACT FROM AUTHOR]

This study intends to build a theoretical mechanism of agricultural socialization services for the eco-efficiency of agricultural land use from two paths, namely the agricultural division of labor and technological progress, and empirically calibrate the Tobit model based on the data of the China Family Tracking Survey (CFPS) for 4453 farming households in 23 provinces (autonomous regions and municipalities) across China. The results of the study show the following: (1) Agricultural socialization services can significantly improve the eco-efficiency of agricultural land use. (2) Hired labor services are more likely to promote eco-efficiency in agricultural land use than farm machinery leasing, especially in major food-producing areas; however, in non-major food-producing areas, the effectiveness of farm machinery leasing services is limited or affected by regional policy differences. (3) In the analysis of the mechanism of agricultural socialization services on the eco-efficiency of agricultural land use, the division of labor in agriculture plays an intermediary role, and the intermediary effect accounts for about 11.4%; however, there is a masking effect of technological progress. This means that China should further develop the role of agricultural socialized services in promoting the ecological efficiency of agricultural land use by developing agricultural socialized service organizations, accelerating the integration of farmers into the modern agricultural division of labor, and promoting the application of green agricultural machinery, among other measures. [ABSTRACT FROM AUTHOR]

Flame spread over discrete fuels is a typical phenomenon in fire scenes. Experimental and theoretical research on flame spread over discrete thermally thin fuels separated by air gaps with different inclination angles was conducted in the present study. Experiments with six inclination angles ranging from 0° to 85° and various fuel coverage rates from 0.421 to 1 were designed. The flame spread behavior, the characteristic flame size, and the flame spread rate were analyzed. The results show that the flow pattern, stability, and flame size exhibit different characteristics with different inclination angles and gap sizes. As the inclination angle increases, particularly with smaller gaps, turbulent and oscillating flames are observed, while larger gap sizes promote flame stability. The mechanism of flame propagation across the gap depends on the interplay between the flame jump effect and heat transfer, which evolves with gap size. Average flame height, average flame width, and flame spread rate initially increase and then decline with the increase in fuel coverage, peaking at fuel coverage rates between 0.93 and 0.571 for different inclination angles. A theoretical model is proposed to predict the flame spread rate and the variation in the flame spread rate with inclination angle and fuel coverage. Furthermore, the map determined by inclination angle and fuel coverage is partitioned into distinct regions, comprising the accelerated flame spread region, the flame spread weakening region, and the failed flame spread region. These findings provide valuable insights into flame spread dynamics over discrete thermally thin fuels under diverse conditions. [ABSTRACT FROM AUTHOR]

Simple Summary: In poultry production, fasting can remodel ovarian function and thereby delay the aging process of chickens. However, this approach may induce various stresses on the intestinal health of chickens. So, intestinal injury, the microbiome, and the metabolome were analyzed individually and integrated to elucidate the impact of the intestinal flora on intestinal injury during fasting-induced molting (FIM). The findings revealed that fasting led to intestinal villus atrophy, inflammation in the intestines, and disruption of gut microbiota and metabolites. During the fasting period, intestinal injury is associated with an increased abundance of Escherichia_Shigella and related metabolites Citrulline and Sterobilin, as well as a decreased abundance of Ruminococcaceae_UCG-013 and Lactobacillus and related metabolites Lanthionine and reduced Glutathione. This provides an experimental basis for improving the gut microbiota and reducing intestinal inflammation during the FIM process. Fasting-induced molting (FIM) is a common method used to improve the laying performance of aged laying hens. Nevertheless, this approach may impose various stresses on chickens, such as disruptions in intestinal flora and inflammation issues within the intestines. However, the impact of an imbalance in intestinal flora on intestinal health during the FIM process remains elusive. Therefore, intestinal injury, the microbiome, and the metabolome were analyzed individually and integrated to elucidate the impact of the intestinal flora on intestinal health during the FIM process. The findings indicated that fasting resulted in a notable reduction in villus height and villus/crypt ratio, coupled with elevated levels of intestinal inflammation and permeability. During the fasting period, microbiota compositions changed. The abundance of Escherichia_Shigella increased, while the abundance of Ruminococcaceae_UCG-013 and Lactobacillus decreased. Escherichia_Shigella was positively correlated with Citrinin and Sterobilin, which lead to intestinal inflammation. Ruminococcaceae_UCG-013 and Lactobacillus exhibited positive correlations with Lanthionine and reduced Glutathione, thereby reducing intestinal inflammation. This study screened the intestinal probiotics, Ruminococcaceae UCG-013 and Lactobacillus, that influence gut health during the fasting period, providing an experimental basis for improving gut microbiota and reducing intestinal inflammation during the FIM process. [ABSTRACT FROM AUTHOR]

Dahurian larch (Larix gmelinii) is the dominant tree species in boreal forests, and its photosynthetic response to climate warming is important in modeling and predicting carbon cycling for boreal forest ecosystems. In 1983, seedlings of L. gmelinii from 11 provenances were transplanted into two common gardens with different climate conditions (control and warming climate). Forty years after the transplant, we investigated the response of leaf photosynthetic capacity to climate warming and its variation among provenances. The warming treatment significantly increased the maximum net photosynthetic rate (Pmax-a), photosynthetic nitrogen use efficiency (PNUE), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), triose phosphate utilization rate (TPU), mesophyll conductance (gm), leaf nitrogen content (Narea), and chlorophyll content (Chlm). Pmax-a was significantly positively associated with Vcmax, Jmax, TPU, gm, and Narea, and the slope of the linear regression between Pmax-a and Vcmax, Jmax, and TPU was greater in the warming treatment. The responses of Pmax-a, PNUE, Vcmax, Jmax, TPU, Narea, and Chlm to warming differed among provenances. As the aridity index of the original site increased, the magnitude of the warming treatment's effect on Pmax-a, Vcmax, Jmax, and TPU represented a varying form of a bell-shaped curve. Overall, the warming treatment improved the photosynthetic capacity of L. gmelinii, but the extent of the improvement varied among provenances. These findings provide insights into the mechanisms underlying the responses of L. gmelinii to climate warming. [ABSTRACT FROM AUTHOR]

Antibacterial hydrogel wound dressings hold great potential in eliminating bacteria and accelerating the healing process. However, it remains a challenge to fabricate hydrogel wound dressings that simultaneously exhibit excellent mechanical and photothermal antibacterial properties. Here we report the development of polydopamine-functionalized graphene oxide (rGO@PDA)/calcium alginate (CA)/Polypyrrole (PPy) cotton fabric-reinforced hydrogels (abbreviated as rGO@PDA/CA/PPy FHs) for tackling bacterial infections. The mechanical properties of hydrogels were greatly enhanced by cotton fabric reinforcement and an interpenetrating structure, while excellent broad-spectrum photothermal antibacterial properties based on the photothermal effect were obtained by incorporating PPy and rGO@PDA. Results indicated that rGO@PDA/CA/PPy FHs exhibited superior tensile strength in both the warp (289 ± 62.1 N) and weft directions (142 ± 23.0 N), similarly to cotton fabric. By incorporating PPy and rGO@PDA, the swelling ratio was significantly decreased from 673.5% to 236.6%, while photothermal conversion performance was significantly enhanced with a temperature elevated to 45.0 °C. Due to the synergistic photothermal properties of rGO@PDA and PPy, rGO@PDA/CA/PPy FHs exhibited excellent bacteria-eliminating efficiency for S. aureus (0.57%) and E. coli (3.58%) after exposure to NIR for 20 min. We believe that the design of fabric-reinforced hydrogels could serve as a guideline for developing hydrogel wound dressings with improved mechanical properties and broad-spectrum photothermal antibacterial properties for infected-wound treatment. [ABSTRACT FROM AUTHOR]

With the advancement of power systems, the integration of a substantial portion of renewable energy often leads to frequent voltage surges and increased fluctuations in distribution networks (DNs), significantly affecting the safety of DNs. Active distribution networks (ADNs) can address voltage issues arising from a high proportion of renewable energy by regulating distributed controllable resources. However, the conventional mathematical optimization-based approach to voltage reactive power control has certain limitations. It heavily depends on precise DN parameters, and its online implementation requires iterative solutions, resulting in prolonged computation time. In this study, we propose a Volt-VAR control (VVC) framework in ADNs based on multi-agent reinforcement learning (MARL). To simplify the control of photovoltaic (PV) inverters, the ADNs are initially divided into several distributed autonomous sub-networks based on the electrical distance of reactive voltage sensitivity. Subsequently, the Multi-Agent Soft Actor-Critic (MASAC) algorithm is employed to address the partitioned cooperative voltage control problem. During online deployment, the agents execute distributed cooperative control based on local observations. Comparative tests involving various methods are conducted on IEEE 33-bus and IEEE 141-bus medium-voltage DNs. The results demonstrate the effectiveness and versatility of this method in managing voltage fluctuations and mitigating reactive power loss. [ABSTRACT FROM AUTHOR]

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA) technology has shown considerable promise in enhancing real-time applications across various domains. This paper presents an innovative edge computing system design specifically tailored for pavement defect detection within the Advanced Driver-Assistance Systems (ADASs) domain. The system seamlessly integrates the AMD Xilinx AI platform into a customized circuit configuration, capitalizing on its capabilities. Utilizing cameras as input sensors to capture road scenes, the system employs a Deep Learning Processing Unit (DPU) to execute the YOLOv3 model, enabling the identification of three distinct types of pavement defects with high accuracy and efficiency. Following defect detection, the system efficiently transmits detailed information about the type and location of detected defects via the Controller Area Network (CAN) interface. This integration of FPGA-based edge computing not only enhances the speed and accuracy of defect detection, but also facilitates real-time communication between the vehicle's onboard controller and external systems. Moreover, the successful integration of the proposed system transforms ADAS into a sophisticated edge computing device, empowering the vehicle's onboard controller to make informed decisions in real time. These decisions are aimed at enhancing the overall driving experience by improving safety and performance metrics. The synergy between edge computing and FPGA technology not only advances ADAS capabilities, but also paves the way for future innovations in automotive safety and assistance systems. [ABSTRACT FROM AUTHOR]

Simple Summary: A decrease in eggshell quality in the late laying period leads to eggshell breakage, seriously affecting production efficiency. Guinea fowl with relatively high eggshell strength have the same layers of eggshell structure and various identical proteins as laying hens. However, their eggshell structures have not been systematically compared. Therefore, this study systematically compared the eggshell ultrastructure, bubble pore index, and composition of laying hens and Guinea fowl. The differences in the eggshell ultrastructure, bubble pores, and composition revealed, to some extent, the structure and composition necessary to increase the eggshell quality of laying hens. This study provides a reference for improving eggshell quality. The decrease in eggshell quality seriously affects production efficiency. Guinea fowl (GF) eggs possess strong eggshells because of their unique crystal structure, and few systematic studies have compared laying hen and GF eggs. Sixty eggs were collected from both 40-week-old Dwarf Layer-White (DWL-White) laying hens and GF, and the eggshell quality, ultrastructure, bubble pores, and composition were measured. The results showed that the DWL-White eggs had a higher egg weight and a lower eggshell strength, strength per unit weight, thickness, and ratio than the GF eggs (p < 0.01). There were differences in the mammillary layer thickness ratio, the effective layer thickness ratio, the quantity of bubble pores (QBPs), the ratio of the sum of the area of bubble pores to the area of the eggshell in each image (ARBE), and the average area of bubble pores (AABPs) between the DWL-White and GF eggs (p < 0.01). The composition analysis demonstrated that there were differences in the organic matter, inorganic matter, calcium, and phosphorus between the DWL-White and GF eggs (p < 0.01). There were positive associations between the mammillary knob number in the image and the QBPs and ARBE and a negative correlation with the AABPs in the DWL-White eggs (p < 0.01). This study observed distinctions that offer new insights into enhancing eggshell quality. [ABSTRACT FROM AUTHOR]

A modified 3D re-entrant honeycomb is designed and fabricated utilizing Laser Cladding Deposition (LCD) technology, the mechanical properties of which are systematically investigated by experimental and finite element (FE) methods. Firstly, the influences of honeycomb angle on localized deformation and the response of force are studied by an experiment. Experimental results reveal that the honeycomb angles have a significant effect on deformation and force. Secondly, a series of numerical studies are conducted to analyze stress characteristics and energy absorption under different angles (α) and velocities (v). It is evident that two variables play an important role in stress and energy. Thirdly, response surface methodology (RSM) and the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) are implemented with high precision to solve multi-objective optimization. Finally, the final compromise solution is determined based on the fitness function, with an angle of 49.23° and an impact velocity of 16.40 m/s. Through simulation verification, the errors of energy absorption (EA) and peak crush stress (PCS) are 9.26% and 0.4%, respectively. The findings of this study offer valuable design guidance for selecting the optimal design parameters under the same mass conditions to effectively enhance the performance of the honeycomb. [ABSTRACT FROM AUTHOR]

Experimental research and numerical simulations of the structural response to shock waves with pulse durations of hundreds of milliseconds, or even seconds, are extremely challenging. This paper takes typical single-layer and sandwich cylindrical shells as the research objects. The response rules of cylindrical shells under long-duration blast loadings were studied. The results show that when the pulse duration is greater than or equal to 4~5 times the first-order period of the structure, the maximum response of the structure tends to be consistent, that is, the maximum response of the cylindrical shells with different vibration shapes shows a saturation effect as the pulse duration increases. This study established the relationship between the saturation loading time and the inherent characteristics of the structure. It was found that the saturation effect was applicable under the following conditions, including different load waveforms, elastic–plastic deformation of the structure, and the loading object being a sandwich shell. This will help transform the long-duration explosion wave problem into a finite pulse-duration shock wave problem that can be realized by both experiments and numerical simulations. [ABSTRACT FROM AUTHOR]

Quantitative precipitation estimation (QPE) by radar observation data is a crucial aspect of meteorological forecasting operations. Accurate QPE plays a significant role in mitigating the impact of severe convective weather. Traditional QPE methods mainly employ an exponential Z–R relationship to map the radar reflectivity to precipitation intensity on a point-to-point basis. However, this isolated point-to-point transformation lacks an effective representation of convective systems. Deep learning-based methods can learn the evolution patterns of convective systems from rich historical data. However, current models often rely on 2 km-height CAPPI images, which struggle to capture the complex vertical motions within convective systems. To address this, we propose a novel QPE model: combining the classic extrapolation model ConvLSTM with Unet for an encoder-decoder module assembly. Meanwhile, we utilize three-dimensional radar echo images as inputs and introduce the convolutional block attention module (CBAM) to guide the model to focus on individual cells most likely to trigger intense precipitation, which is symmetrically built on both channel and spatial attention modules. We also employ asymmetry in training using weighted mean squared error to make the model concentrate more on heavy precipitation events which are prone to severe disasters. We conduct experiments using radar data from North China and Eastern China. For precipitation above 1 mm, the proposed model achieves 0.6769 and 0.7910 for CSI and HSS, respectively. The results indicate that compared to other methods, our model significantly enhances precipitation prediction accuracy, with a more pronounced improvement in forecasting accuracy for heavy precipitation events. [ABSTRACT FROM AUTHOR]

Viral infection can regulate the cell cycle, thereby promoting viral replication. Hijacking and altering the cell cycle are important for the virus to establish and maintain a latent infection. Previously, Spodoptera exigua multiple nucleopolyhedrovirus (SeMNPV)-latently infected P8-Se301-C1 cells, which grew more slowly than Se301 cells and interfered with homologous SeMNNPV superinfection, were established. However, the effects of latent and superinfection with baculoviruses on cell cycle progression remain unknown. In this study, the cell cycle profiles of P8-Se301-C1 cells and SeMNPV or Autographa californica multiple nucleopolyhedrovirus (AcMNPV)-infected P8-Se301-C1 cells were characterized by flow cytometry. The results showed that replication-related genes MCM4, PCNA, and BAF were down-regulated (p < 0.05) in P8-Se301-C1 cells, and the S phase of P8-Se301-C1 cells was longer than that of Se301 cells. P8-Se301-C1 cells infected with SeMNPV did not arrest in the G2/M phase or affect the expression of Cyclin B and cyclin-dependent kinase 1 (CDK1). Furthermore, when P8-Se301-C1 cells were infected with SeMNPV after synchronized treatment with hydroxyurea and nocodazole, light microscopy and qRT-PCR analysis showed that, compared with unsynchronized cells and S and G2/M phase cells, SeMNPV-infected P8-Se301-C1 cells in G1 phase induced G2/M phase arrest, and the amount of virus adsorption and intracellular viral DNA replication were significantly increased (p < 0.05). In addition, budded virus (BV) production and occlusion body (OB)-containing cells were both increased at 120 h post-infection (p < 0.05). The expression of Cyclin B and CDK1 was significantly down-regulated at 48 h post-infection (p < 0.05). Finally, the arrest of SeMNPV-infected G1 phase cells in the G2/M phase increased BV production (p < 0.05) and the number of OB-containing cells. In conclusion, G1 phase infection and G2/M arrest are favorable to SeMNPV proliferation in P8-Se301-C1 cells, thereby alleviating the homologous superinfection exclusion. The results contribute to a better understanding of the relationship between baculoviruses and insect cell cycle progression and regulation. [ABSTRACT FROM AUTHOR]

An adaptive particle refinement (APR) algorithm has been developed for the smoothed particle hydrodynamics (SPH) method to augment the resolution of the region of interest to achieve high accuracy and simultaneously reduce the cost of computational resources. It is widely applied in the field of fluid-controlling problems involving large interface deformations, such as the two-phase flow and fluid–structure interaction because this algorithm can capture the interface with high accuracy. Nonetheless, existing APR algorithms widely encounter computational dispersion issues at the interface of regions of different particle resolutions. Moreover, traditional shifting algorithms applied in the APR processes also have difficulties in dealing with particles with different smooth lengths. In this work, an algorithm for fast particle generation was first developed based on the accelerated ray method, which accelerates the discretization of the flow field into particles. Then, a dynamic refinement/coarsening algorithm based on the APR algorithm is proposed to solve the computational dispersion problem that occurs at the refinement/coarsening interfaces. In addition, the shifting algorithm was improved in this work to ensure the particles are always well distributed during numerical calculations and, thus, can efficiently facilitate the adaptive particle refinement/coarsening processes. Comparative analysis indicates that the robust algorithms developed for the SPH method in this work can lead to more precise and reasonable flow fields compared with the conventional SPH adaptive methods. [ABSTRACT FROM AUTHOR]

Cerebral cavernous malformations (CCMs) are a neurological disorder characterized by enlarged intracranial capillaries in the brain, increasing the susceptibility to hemorrhagic strokes, a major cause of death and disability worldwide. The limited treatment options for CCMs underscore the importance of prognostic biomarkers to predict the likelihood of hemorrhagic events, aiding in treatment decisions and identifying potential pharmacological targets. This study aimed to identify blood biomarkers capable of diagnosing and predicting the risk of hemorrhage in CCM1 patients, establishing an initial set of circulating biomarker signatures. By analyzing proteomic profiles from both human and mouse CCM models and conducting pathway enrichment analyses, we compared groups to identify potential blood biomarkers with statistical significance. Specific candidate biomarkers primarily associated with metabolism and blood clotting pathways were identified. These biomarkers show promise as prognostic indicators for CCM1 deficiency and the risk of hemorrhagic stroke, strongly correlating with the likelihood of hemorrhagic cerebral cavernous malformations (CCMs). This lays the groundwork for further investigation into blood biomarkers to assess the risk of hemorrhagic CCMs. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03–0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02–0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8–94.5%) versus 0.0% (95% CI, 0.0–60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4–97.5%) versus 0.0% (95% CI, 0.0–36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer. [ABSTRACT FROM AUTHOR]

As the role of human capital in enhancing corporate value becomes increasingly prominent in the new economic era, employee satisfaction has garnered widespread attention in organizational behavior theory and business practices. However, constrained by the traditional governance model of "shareholder primacy", which tends to view employees instrumentally, adverse effects on employee satisfaction and organizational identification persist. Currently, corporate ESG behaviors are flourishing in China, bringing profound and extensive transformations to economic and social sustainability. Yet, the research on whether and how corporate ESG behaviors improve employee satisfaction remains unclear. This study, based on data from the "China's 100 Best Employers Award" and employing regression analysis on panel data from listed companies on the Shanghai and Shenzhen stock exchanges, reveals that corporate ESG behaviors have the potential to enhance employee satisfaction. Transparency in corporate environmental information and internal control mechanisms emerge as the primary means through which corporate ESG behaviors elevate employee satisfaction. Furthermore, heightened environmental awareness among executives and higher educational qualifications among employees strengthen the relationship between corporate ESG behaviors and employee satisfaction. [ABSTRACT FROM AUTHOR]

With the rapid development of smart manufacturing, data-driven deep learning (DL) methods are widely used for bearing fault diagnosis. Aiming at the problem of model training crashes when data are imbalanced and the difficulty of traditional signal analysis methods in effectively extracting fault features, this paper proposes an intelligent fault diagnosis method of rolling bearings based on Gramian Angular Difference Field (GADF) and Improved Dual Attention Residual Network (IDARN). The original vibration signals are encoded as 2D-GADF feature images for network input; the residual structures will incorporate dual attention mechanism to enhance the integration ability of the features, while the group normalization (GN) method is introduced to overcome the bias caused by data discrepancies; and then the model is trained to complete the classification of faults. In order to verify the superiority of the proposed method, the data obtained from Case Western Reserve University (CWRU) bearing data and bearing fault experimental equipment were compared with other popular DL methods, and the proposed model performed optimally. The method eventually achieved an average identification accuracy of 99.2% and 97.9% on two different types of datasets, respectively. [ABSTRACT FROM AUTHOR]

This study presents a detailed investigation into the use of β-cyclodextrin (β-CD) encapsulated iron oxide nanoparticle (β-CD@Fe3O4) composites, modified with different ligands, to activate peroxymonosulfate (PMS) for the degradation of pharmaceutical contaminants, namely, diclofenac, carbamazepine, and erythromycin. The focus is on understanding the ligand effect, particularly using citric acid (CIT), polyethyleneimine (PEI), and cetyl trimethyl ammonium bromide (CTAB), on the degradation performance of these composites. Employing density functional theory (DFT) calculations, this work examines the electronic structure and charge distributions of β-CD@Fe3O4 composites, providing insights into their interaction with various pollutants. The study reveals that the β-CD@PEI@Fe3O4 composite demonstrates superior degradation efficiency due to optimal electrostatic interactions, regardless of the pollutant's hydrophobicity. On the other hand, β-CD@CIT@Fe3O4 shows moderate efficiency, and β-CD@CTAB@Fe3O4 exhibits selective efficiency, particularly for hydrophobic compounds. These findings underscore the significant role of surface chemistry in modulating the activation of PMS and the degradation of contaminants, opening avenues for designing tailored β-CD composites for environmental remediation. [ABSTRACT FROM AUTHOR]

Reducing space debris is a critical challenge in current space exploration. This study focuses on designing a drag sail for CubeSat models and examining their aerodynamic properties using the direct simulation Monte Carlo (DSMC) method. The analysis encompasses the aerodynamic performance of intricate three-dimensional shapes with varying sail dimensions at orbital altitudes of 125 km, 185 km, 300 km, and 450 km. Additionally, free molecular flow (FMF) theory is applied and compared with the DSMC findings for both a flat-plate model and the CubeSat. The results reveal that FMF accurately predicts the drag coefficient at altitudes of 185 km and above, while significant discrepancies occur at lower altitudes due to increased inter-molecular collisions. This study also suggests that the drag sail substantially enhances the CubeSat's drag force, which effectively reduces its deorbiting time. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases pose a long-term risk to human health. This study focuses on the rich-spectrum mechanical vibrations generated during cardiac activity. By combining Fourier series theory, we propose a multi-frequency vibration model for the heart, decomposing cardiac vibration into frequency bands and establishing a systematic interpretation for detecting multi-frequency cardiac vibrations. Based on this, we develop a small multi-frequency vibration sensor module based on flexible polyvinylidene fluoride (PVDF) films, which is capable of synchronously collecting ultra-low-frequency seismocardiography (ULF-SCG), seismocardiography (SCG), and phonocardiography (PCG) signals with high sensitivity. Comparative experiments validate the sensor's performance and we further develop an algorithm framework for feature extraction based on 1D-CNN models, achieving continuous recognition of multiple vibration features. Testing shows that the recognition coefficient of determination ( R 2 ), mean absolute error (MAE), and root mean square error (RMSE) of the 8 features are 0.95, 2.18 ms, and 4.89 ms, respectively, with an average prediction speed of 60.18 us/point, meeting the re-quirements for online monitoring while ensuring accuracy in extracting multiple feature points. Finally, integrating the vibration model, sensor, and feature extraction algorithm, we propose a dynamic monitoring system for multi-frequency cardiac vibration, which can be applied to portable monitoring devices for daily dynamic cardiac monitoring, providing a new approach for the early diagnosis and prevention of cardiovascular diseases. [ABSTRACT FROM AUTHOR]

A series of novel zinc-salophen (salophen = N, N′-phenylenebis(salicylimine)) complexes (Zn-1–4) with electron donor–acceptor (D–A) structure were synthesized and characterized using a triphenylamine structure as the electron donor. Zn-salophen complexes with the same substituent sites have been reported to exhibit significant CT properties. The design of the D–A structure and the increase in the number of benzene rings to increase the length of bridging groups have led to a reduction in the energy difference between charge separation singlet and triplet states, resulting in the production of reactive oxygen species (ROS) under light irradiation. The ability has been enhanced (in terms of the production of singlet oxygen (1O2), compared with Zn-salophen, Zn-4 is 1.58 times higher). This method has been reported to enhance the intersystem crossing process of compounds, thereby enabling them to reach a triple excited state, but the generation of ROS has not been studied. Although the enhancement is not very significant, it has expanded the medical application prospects of these types of complexes and has provided a new strategy to enhance the production of ROS. [ABSTRACT FROM AUTHOR]

When buildings are exposed to erosion from the natural environment, erosion behaviors such as surface damage and structural instability occur, which greatly affect the aesthetic value and service life of the buildings. The study of erosion behaviors and the establishment of a suitable erosion model are constructive references for the protection and restoration of buildings. In order to establish a suitable erosion model for architectural red sandstone, two types of red sandstone specimens were selected in this paper to carry out dry and wet cycle tests. Combining the theoretical analysis and the actual erosion situation, a unidirectional corrosion model is proposed to describe the erosion of buildings by the natural environment. In this model, it is assumed that only the outer surface of the building is in contact with external erosion factors for a long period of time, so this situation can be considered a unidirectional erosion process. The paper uses XRD, SEM, and ultrasonic methods to record changes in the properties of the red sandstone samples. Finally, the rationality of the unidirectional erosion model was verified numerically. The test results show that the red sandstone specimens subjected to erosion by the natural environment will be accompanied by the development of defects, such as cracks, fissures, and holes, as well as the generation of fresh material. The demarcation point of different erosion stages exists in both the in-service red sandstone specimens and the fresh red sandstone specimens, which is consistent with the results of the unidirectional erosion model. In this paper, a calculation model for the demarcation point of different erosion stages is established, and the model estimation shows that the demarcation point of different erosion stages of the in-service red sandstone sample is 1.1528 cm from the erosion surface, and the demarcation point of different erosion stages of the fresh red sandstone sample is 1.67 cm. [ABSTRACT FROM AUTHOR]

Urban public open spaces are crucial for residents' well-being, yet accessibility issues persist, affecting activities and social interactions. To this end, we take the main urban area of Jiamusi City, the most northeastern city in China, as an example. We start by examining both spatial and perceptual dimensions, using the Gaussian two-step moving search method to measure spatial accessibility, combining online data with multi-source data from questionnaires. Furthermore, we utilize structural equation modeling to explore the impact of accessibility on place attachment within urban public open spaces. The results show that (1) accessibility has a positive effect on place attachment, while place satisfaction plays a mediating role. (2) There were significant differences in spatial accessibility across modes of travel. Car travel had the best spatial accessibility, followed by bicycle, and walking had the lowest spatial accessibility. (3) Perceived accessibility and spatial accessibility differ, but perceived accessibility it is more persuasive in explaining and illustrating place attachment. Reducing travel costs and meeting the user needs will effectively increase place attachment and place identity. (4) Social factors such as age, education, and residency length also affect accessibility, satisfaction, and attachment. By understanding the impact of accessibility on place attachment, this study helps urban planners to better design urban spatial layout and transportation networks. It enhances people's attachment to specific places by improving the convenience of traveling, promotes sustainable urban development, and enriches the discourse on the enhancement of psychological motivation in urban public open spaces. [ABSTRACT FROM AUTHOR]

The identification of influencing factors (IFs) of land surface temperature (LST) is crucial for developing effective strategies to mitigate global warming and conducting other relevant studies. However, most previous studies ignored the potential impact of interactions between IFs, which might lead to biased conclusions. Generalized additivity models (GAMs) can provide more explanatory results compared to traditional machine learning models. Therefore, this study employs GAMs to investigate the impact of IFs and their interactions on LST, aiming to accurately detect significant factors that drive the changes in LST. The results of this case study conducted in Nanjing, China, showed that the GAMs incorporating the interactions between factors could improve the fitness of LST and enhance the explanatory power of the model. The autumn model exhibited the most significant improvement in performance, with an increase of 0.19 in adjusted-R2 and a 17.9% increase in deviance explained. In the seasonal model without interaction, vegetation, impervious surface, water body, precipitation, sunshine hours, and relative humidity showed significant effects on LST. However, when considering the interaction, the previously observed significant influence of the water body in spring and impervious surface in summer on LST became insignificant. In addition, under the interaction of precipitation, relative humidity, and sunshine hours, as well as the cooling effect of NDVI, there was no statistically significant upward trend in the seasonal mean LST during 2000–2020. Our study suggests that taking into account the interactions between IFs can identify the driving factors that affect LST more accurately. [ABSTRACT FROM AUTHOR]

Debris flow can cause damage only when its discharge exceeds the drainage capacity of the prevention engineering. At present, most rainfall thresholds for debris flows mainly focus on the initiation of debris flow and do not adequately consider the magnitude and drainage measures of debris flows. These thresholds are likely to initiate numerous warnings that may not be related to hazardous processes. This study proposes a method for calculating the rainfall threshold that is related to a defined level of debris flow magnitude, over which certain damage may be caused. This method is constructed by using the transient rainfall infiltration analysis slope stability model (TRIGRS) and the fluid dynamics process simulation model (MassFlow). We first use the TRIGRS model to analyze slope stability in the study area and obtain the distribution of unstable slopes under different rainfall conditions. Afterward, the MassFlow model is employed to simulate the movement process of unstable slope units and to predict the depositional processes at the mouth of the catchment. Lastly a rainfall threshold is constructed by statistically analyzing the rainfall conditions that cause debris flows flushing out of the given drainage ditch. This method is useful to predict debris flow events of a hazardous magnitude, especially for areas with limited historical observational data. [ABSTRACT FROM AUTHOR]

Simple Summary: The H9N2 subtype of avian influenza virus (AIV) was first identified in turkey flocks in Wisconsin, USA, in 1966. Since then, H9N2 AIVs have been detected in mammals, domestic poultry, and wild birds. In June 2020, a new H9N2/Y280 was discovered in Korea. Existing commercial vaccines might not be fully effective against H9N2/Y280. Since influenza viruses undergo mutations rapidly, fast and accurate vaccine production is critical to address variant strains. Consequently, this study focused on rapid and effective vaccine production techniques against H9N2/Y280. The recombinant rHVT/Y280 was successfully constructed using NHEJ-CRISPR/Cas9 gene-editing technology. rHVT/Y280 vaccination induced strong humoral immunity, providing significant protection against H9N2/Y280 strain A21-MRA-003 following a challenge of 2 × 107 50% egg infectious dose. Therefore, rHVT/Y280 is a potential candidate for a live vaccine against H9N2/Y280. Since the outbreak of the H9N2/Y439 avian influenza virus in 1996, the Korean poultry industry has incurred severe economic losses. A novel possibly zoonotic H9N2 virus from the Y280-like lineage (H9N2/Y280) has been prevalent in Korea since June 2020, posing a threat to the poultry sector. Rapid mutation of influenza viruses urges the development of effective vaccines against newly generated strains. Thus, we engineered a recombinant virus rHVT/Y280 to combat H9N2/Y280. We integrated the hemagglutinin (HA) gene of the H9N2/Y280 strain into the US2 region of the herpesvirus of turkeys (HVT) Fc126 vaccine strain, utilizing CRISPR/Cas9 gene-editing technology. The successful construction of rHVT/Y280 was confirmed by polymerase chain reaction and sequencing, followed by efficacy evaluation. Four-day-old specific pathogen-free chickens received the rHVT/Y280 vaccine and were challenged with the H9N2/Y280 strain A21-MRA-003 at 3 weeks post-vaccination. In 5 days, there were no gross lesions among the vaccinated chickens. The rHVT/Y280 vaccine induced strong humoral immunity and markedly reduced virus shedding, achieving 100% inhibition of virus recovery in the cecal tonsil and significantly lowering tissue viral load. Thus, HVT vector vaccines expressing HA can be used for protecting poultry against H9N2/Y280. The induction of humoral immunity by live vaccines is vital in such cases. In summary, the recombinant virus rHVT/Y280 is a promising vaccine candidate for the protection of chickens against the H9N2/Y280. [ABSTRACT FROM AUTHOR]

Pedestrian trajectory prediction is extremely challenging due to the complex social attributes of pedestrians. Introducing latent vectors to model trajectory multimodality has become the latest mainstream solution idea. However, previous approaches have overlooked the effects of redundancy that arise from the introduction of latent vectors. Additionally, they often fail to consider the inherent interference of pedestrians with no trajectory history during model training. This results in the model's inability to fully utilize the training data. Therefore, we propose a two-stage motion pattern de-perturbation strategy, which is a plug-and-play approach that introduces optimization features to model the redundancy effect caused by latent vectors, which helps to eliminate the redundancy effects in the trajectory prediction phase. We also propose loss masks to reduce the interference of invalid data during training to accurately model pedestrian motion patterns with strong physical interpretability. Our comparative experiments on the publicly available ETH and UCY pedestrian trajectory datasets, as well as the Stanford UAV dataset, show that our optimization strategy achieves better pedestrian trajectory prediction accuracies than a range of state-of-the-art baseline models; in particular, our optimization strategy effectively absorbs the training data to assist the baseline models in achieving optimal modeling accuracy. [ABSTRACT FROM AUTHOR]

Simple Summary: Immune-checkpoint inhibitors have been proven to aid in tumor regression. We performed a meta-analysis and systematic review to investigate the relationship between hospital volume and patient outcomes. We found that centers performing ≥ 33 annual cases had fewer cardiac-related adverse events (AEs). The pooled estimated rates of grade 5 AEs were 2.75% (95%CI: 2.18–3.47), with higher annual cases associated with reduced grade 5 AEs at meta-regression. Ultimately, patients should be referred to high-volume centers when severe immune-related AEs occur. Immune-checkpoint inhibitors (ICIs) were proven effective in inducing tumor regression. However, its toxicity tends to be fatal. We sought to investigate the hospital volume/outcomes relationship. Databases were searched for studies reporting immune-checkpoint inhibitors adverse events (AEs) in patients with solid-organ malignancies. The outcomes were A) the pooled events rate (PER) of grade 5, grade 3–4, cardiac-related, and pulmonary-related AEs, and B) the assessment of the volume/outcomes relationship. One hundred and forty-seven studies met our inclusion criteria. The PER of grade 5, grade 3–4, and any-grade AEs was 2.75% (95%CI: 2.18–3.47), 26.69% (95%CI: 21.60–32.48), and 77.80% (95%CI: 70.91–83.44), respectively. The PER of pulmonary-related AEs was 4.56% (95%CI: 3.76–5.53). A higher number of annual cases per center was significantly associated with reduced grade 5 (p = 0.019), grade 3–4 (p = 0.004), and cardiac-related AEs (p = 0.035) in the meta-regression. In the current era of cancer immunotherapy, knowledge regarding the early diagnosis and management of immunotherapy-related AEs is essential. Our meta-analysis demonstrates the importance of center volume in improving outcomes and reducing the incidence of severe AEs. [ABSTRACT FROM AUTHOR]

Simple Summary: Despite massive strides taken across the board in oncology, there remain gaps in understanding the relationship between cancer cells and the body's immune system, tissues, and signaling pathways. This review explores some of the recent steps made toward filling these gaps and understanding how certain cytokine signals create a tumor microenvironment that facilitates the growth and survival of cancer cells. New treatment approaches targeting these facilitators have been developed as potential disruptors of tumor growth. Lastly, a discussion of current gaps in the research can help navigate new directions to continue life-saving research for lung cancer treatments. The intricate interplay between inflammatory processes and the tumor microenvironment (TME) in lung cancer has garnered increasing attention due to its implications for both oncogenesis and therapeutic strategies. In this review, we explore recent advances in understanding the paracrine regulation and immune system pathways within the inflammatory TME of lung cancer. We delve into the molecular mechanisms underpinning oncogenesis, highlighting the role of immune cell populations, cancer-associated fibroblasts, and endothelial cells, as well as their interactions through immune system pathways regulated in a paracrine pattern. Additionally, we discuss emerging immunotherapeutic strategies with a specific focus on the potential of leveraging the inflammatory TME through these pathways to enhance treatment efficacy in lung cancer. [ABSTRACT FROM AUTHOR]

To investigate the influence of temperature and humidity variations on creep in high-performance concrete beams, beam tests were conducted in both natural and laboratory settings. The findings indicate that the variations in creep primarily stem from temperature changes, whereas humidity changes have little influence on fluctuations in both basic creep and total creep. The influence of humidity on creep is more strongly reflected in the magnitude of creep. Functions describing the influence of temperature and humidity on the creep behavior of high-performance concrete (HPC) subjected to fluctuating conditions are proposed. The findings were employed to examine creep deformation in engineering applications across four places. This study complements the correction method for the creep of members under fluctuating temperature and humidity. This research application can provide a basis for the calculation of the long-term deformation of HPC structures in natural environments. [ABSTRACT FROM AUTHOR]

Traditional positioning verification using cone-beam computed tomography (CBCT) may incur errors due to potential misalignments between the isocenter of CBCT and the treatment beams in radiotherapy. This study introduces an innovative method for verifying patient positioning in radiotherapy. Initially, the transmission images from an electronic portal imaging device (EPID) are acquired from 10 distinct angles. Utilizing the ART-TV algorithm, a sparse reconstruction of local megavoltage computed tomography (MVCT) is performed. Subsequently, this MVCT is aligned with the planning CT via a three-dimensional mutual information registration technique, pinpointing any patient-positioning discrepancies and facilitating corrective adjustments to the treatment setup. Notably, this approach employs the same radiation source as used in treatment to obtain three-dimensional images, thereby circumventing errors stemming from misalignment between the isocenter of CBCT and the accelerator. The registration process requires only 10 EPID images, and the dose absorbed during this process is included in the total dose calculation. The results show that our method's reconstructed MVCT images fulfill the requirements for registration, and the registration algorithm accurately detects positioning errors, thus allowing for adjustments in the patient's treatment position and precise calculation of the absorbed dose. [ABSTRACT FROM AUTHOR]