The plastic deformation behavior of 3Y-TZP with weak electric current in oxygen-lean atmosphere was investigated. An electrochemical reduction reaction, induced by the electric current, can significantly promote the plastic deformation of 3Y-TZP at furnace temperature of 1200 °C and a strain rate of 6.67 × 10−4 s−1. Especially, a remarkable variation of the electrical property and grain growth were observed in 3Y-TZP during the deformation. The stress exponent ranging within 2~3 indicated that the deformation was dominated by grain boundary sliding. The applied electric current decreased the apparent activation energy Q of the deformation from 465 kJ mol-1 to 315 kJ mol-1, resulting in a transition of the diffusion mechanism from the lattice diffusion to the grain boundary diffusion. These phenomena were mainly attributed to the enhancement of the cation diffusion caused by the electrochemical reduction reaction, which induced by the electric current in oxygen-lean atmosphere.

Digital images have become an important carrier for people to access information in the information age. However, with the development of the technology, digital images are vulnerable to illegal access and tampering, to the extent that they pose a serious threat to personal privacy, social order and national security. Therefore, image forensic techniques have become an important research topic in the field of multimedia information security. In recent years, deep learning technology has been widely applied in the field of image forensics and the performance achieved has significantly exceeded the conventional forensic algorithms. This survey compares the state-of-the-art image forensic techniques based on deep learning in recent years. The image forensic techniques are divided into passive and active forensics. In passive forensics, forgery detection techniques are reviewed, and the basic framework, evaluation metrics and commonly used datasets for forgery detection are presented. The performance, advantages and disadvantages of existing methods are also compared and analyzed according to different types of detection. In active forensics, robust image watermarking techniques are overviewed, the evaluation metrics and basic framework of robust watermarking techniques are presented. The technical characteristics and performance of existing methods are analyzed based on the different types of attacks on images. Finally, future research directions and conclusions are given to provide useful suggestions for people in image forensics and related research fields.

In recent years, with the rapid development of computer vision technology and the popularization of intelligent hardware, as well as people’s increasing demand for intelligent products for human-computer interaction, visual grounding technology can help machines and humans identify and locate objects, thereby promoting human-computer interaction and intelligent manufacturing. At the same time, human-computer interaction is constantly evolving and improving, becoming increasingly intelligent, humane, and efficient. This paper proposes a new VG model and designs a language verification module that uses language information as the main information to increase the model’s interactivity. Additionally, we propose the combination of visual grounding and human-computer interaction, aiming to explore the research status and development trends of visual grounding and human-computer interaction technology, as well as their application in practical scenarios and optimization directions, to provide references and guidance for relevant researchers and promote the development and application of visual grounding and human-computer interaction technology.

Bridge load testing is crucial in evaluating bridge load-carrying capacity and construction quality. However, conventional techniques have many limitations such as the need for direct contact and low acquisition frequency. This study provides a comprehensive examination of the static and dynamic load tests of a multi-span cable-stayed bridge utilizing a ground-based radar inter-ferometer (GB-radar). The case study was conducted at the Fifth Nanjing Yangtze River Bridge (FNYRB), which is recognized as the world's first lightweight steel-concrete composite cable-stayed bridge, with two spans measuring 600 m. To enhance measurement accuracy, a method was proposed to detect and recover radar phase jumps caused by vehicle motion. Furthermore, precise geometry projection was employed to acquire vertical displacements from GB-radar which were taken along the line-of-sight (LOS) direction. Moreover, during the static load test, a continuous deformation was observed with a maximum pace of 0.31 mm/min, indicating a post-construction settlement caused by soft soil consolidation. This case study highlights the high sampling frequency, high measurement accuracy, and exceptional weatherproof ability of GB-radar, thereby demonstrating its potential to be an alternative to the structural health monitoring (SHM) system.

A controllable synthesis of trisubstituted imidazoles and pyrroles has been developed through rhodium(II)-catalyzed regioselective annulation of N-sulfonyl-1,2,3-trizaoles with β-enaminones. The imidazole ring was formed through 1,1-insertion of N-H bond to α-imino rhodium carbene and subsequential intramolecular 1,4-conjugate addition when α-carbon atom of amino group bearing with methyl, whereas utilizing phenyl substituent constructed pyrrole ring via intramolecular nucleophilic addition. Features such as mild conditions, good functional groups tolerance, gram-scale synthesis, and valuable transformations of the products qualified this unique protocol as an efficient tool for the synthesis of N-heterocycles.

Clarifying the response of plant phenology to drought duration is helpful for accurately interpreting and predicting carbon sinks in ecosystems. Based on the response of different phenological periods of the dominant species Stipa krylovii to monthly, seasonal and semiannual time scale drought in the typical steppe of Inner Mongolia from 1983 to 2018, the results revealed that (1) the start of the growing season (SOS) was characterized by an advance-delay-advance pattern, and the heading stage (HOS), flowering stage (FOS) and end of the growing season (EOS) all showed consistent advanced trends, which provided additional insight into the conclusions of previous studies that found the SOS was advanced in arid and semiarid regions. (2) The response mechanism of the SOS to the timing of drought was not consistent. Among the response mechanism, the SOS was delayed because of January-February drought at different time scales, but advanced because of April drought at different time scales. The HOS/FOS was delayed by June-July drought at different time scales, and the EOS was advanced by August-September drought at different time scales. (3) More importantly, the SOS, HOS, FOS and EOS were affected by predrought and its persistence, and the effects were greater the closer to the phenological periods that drought occurred. (4) At the monthly scale, droughts in January, June and August were the critical drought periods affecting the SOS, HOS/FOS and EOS, while seasonal and semiannual scale droughts in February, June-July and September were the critical periods affecting the SOS, HOS/FOS and EOS. The results of this study enrich our understanding of how drought at different time scales affects different phenological periods, providing a basis for improving plant phenological models.

With the development of society and the economy, the unified planning of architectural style has become a difficult problem in the competition between urban expansion and the protection of tra-ditional buildings in villages and towns. At the same time, it also allows people to re-examine the appearance and quality of life of traditional village buildings. In this paper, the Conditional Gen-erative Adversarial Network (CGAN) is used to construct a method of building facade generation in villages and towns, so as to gradually realize the governance of the style of villages and towns. At the same time, it has also reduced the restoration of the facades of villages and towns and the graphic design of rural tourism products, showing its application value and potential in the field of planning and design. In the research, taking villages and towns in the Wuyishan area of China as an example, the method is used to carry out model training, image generation, and comparison of the derivation results of different assumed building contours and product contours. The research shows that: (1) CGAN can be used to derive and design the facades of conventional civil buildings in villages and towns. (2) In terms of product graphic design, especially the common tourist cultural products fans and water cups, show significant potential. (3) The construction of this method is not only applicable to villages and towns under the World Heritage City, but can be further promoted and used in the future for cities and villages that have a demand for architectural style consistency.

In the development and growth of family businesses, succession is an unsolvable problem, which is also a popular focus of academic research. For a family firm, succession may be a strategic decision but also a long-term and intricate "footrace." It will have a significant impact on the long-term viability of a family firm if it is not handled appropriately. This study mainly explores the influences of family business owners' intergenerational succession intention on their family firms’ innovation strategy in China. In addition, this study further examines the moderating role of the institutional environment in the above relationship. Therefore, the data in this article comes from a survey of 271 family businesses in eight different regions of China. Also, this paper can aid the smooth transition of intergenerational transmission of small and medium-sized family businesses in addition to the untroubled development of technological innovation activities. Specifically, the institutional environment plays a negative moderating role in the relationship between family succession, radical succession, technological innovation, and a positive regulating role in the relationship between single equity succession and technological innovation.

The herd effect is a common phenomenon in social society. The detection of this phenomenon is of great significance in many tasks based on social network analysis such as recommendation. However, the research on social network and natural language processing seldom focuses on this issue. In this paper, we propose an unsupervised data mining method to detect herding in social networks. Taking shopping review as an example, our algorithm can identify other reviews which are affected by some previous reviews and detect a herd effect chain. From the overall perspective, the cross effects of all views form the herd effect graph. This algorithm can be widely used in various social network analysis methods through graph structure, which provides new useful features for many tasks.

(1) Background: Investigating the characteristics of photosynthetic physiological changes of leaves in Mangifera indica L. cv. 'GuIfei' under enhanced UV-B radiation, natural light exposed trees were regarded as control, and 96 kJ·m-2·d-1enhanced UV-B radiation was artificially simulated in the field; (2) Methods: The changes of fruit maturity and fruit quality, leaf net photosynthetic rate (Pn), photosynthetic pigments contents, photochemical reaction, activities of photosynthetic enzymes and their genes expressions were determined; (3) Results: Compared with CK, the percentage of mature fruits of the treatment was significantly increased, and fruit quality was better. The net photosynthetic rate (Pn), the contents of photosynthetic pigment, Hill reaction activity and photochemical quenching coefficient (qP) of the treatment leaves showed a significantly higher trend than CK. The activities of Rubisco and RCA, and the expression of Rubisco genes rbcL and rbcS were significantly increased; (4) Conclusions: 96 kJ·m-2·d-1 enhanced UV-B radiation treatment improved Rubisco activity through increasing the expression of Rubisco genes rbcL and rbcS, thereby enhancing the CO2-fixing capacity and dark reaction capacity of leaves. Based on this, it raised the net photosynthetic rate of leaves, which promoted the early maturity of 'Guifei' mango by the fast accumulating photosynthetic products.

This paper proposes a linear eddy-current feature to determine the radius of a metallic ball in a non-contact manner. An electromagnetic eddy-current sensor with two coils is placed co-axially to the metal ball during measurement. It is well known that the distance between the sensor and test piece (i.e. lift-off) affects eddy-current signals. In this paper, it is found that the peak frequency feature of inductance spectrum is linear to the lift-off spacing between the centre of coil and ball. Besides, the slope of peak frequencies versus lift-offs is linked to the radius of ball. The radius of metallic balls is retrieved from the experimental and embedded analytical result of the slope. Measurements have been carried out on 6 metallic balls with different radii. The radius of the metallic ball can be retrieved with an error of less than 2 %.

As a result of the influence of geographical environment and historical heritage, food preference has significant regional differentiation characteristics. However, the spatial structure of food culture represented by the cuisine culture at the regional level has not yet been explored from the perspective of geography. This study aims to explore such patterns by focusing on the restaurants of the eight most famous cuisines in Mainland China. Initially, the density based geospatial hotspot detector method is proposed to analyze and mapping the spatial quantitative characteristics of the eight major cuisines. A heuristic method for geographical regionalization based on machine learning was used to analyze spatial distribution patterns in accordance with the proportion of these cuisines in each prefecture-level city. Results show that some types of single-category cuisines have a stronger spatial concentration effect in the present, whereas others have a strong diffusion trend. In the comprehensive analysis of multicategory cuisines, the eight major cuisines formed a new structure of geographical regionalization of Chinese cuisine culture. This study is helpful to understand regional structure characteristics of food preference, and the density based hotspot detector proposed in this paper can also be used in the analysis of other type of POI data.

The zero velocity update(ZUPT) algorithm is the core of a foot-mounted pedestrian navigation system. The zero velocity detection method is the premise and guarantee of the effective application of the ZUPT algorithm. To make ZUPT work properly, it is necessary to detect zero velocity intervals correctly. The detection accuracy of the existing zero velocity detection methods is easy to be affected by users and environment. A novel zero velocity detection method based on the plantar pressure is proposed in this paper, which has higher detection accuracy and better environmental adaptability. First, the paper analyzes the motion characteristics of foot during walking. Second, the inherent relationship between the plantar pressure and the gait change during walking is studied based on the pressure sensor. Then, the model of the zero velocity detection method using the plantar pressure is established. Finally, the indoor and outdoor multi-scene experiments show that this method not only has a high detection accuracy, but also has good adaptability to users and walking environment.

The latest emergence of a novel coronavirus (COVID-19) had caused an outbreak of respiratory virus infections in Wuhan, China, and other countries so that the world health organization (WHO) declared the COVID-19 epidemic as a Public Health Emergency of International Concern (PHEIC) on January 31, 2020. At present, it is the fact that we have identified the bats as the host, the route of respiratory droplets, contact, and aerosol can accelerate the transmission from person to person. However, it is not well known about the intermediator and other approaches. Identifying and characterizing the origin and host(s) of COVID-19 can help us to evaluate the potential risk of COVID-19 for transmission among humans or cross-species.

A novel high-voltage powerline inspection system is investigated, which consists of the cooperated ground vehicle and drone. The ground vehicle acts as a mobile platform that can launch and recycle the drone, while the drone can fly over the powerline for inspection within limited endurance. This inspection system enables the drone to inspect powerline networks in a very large area. Both vehicle’ route in the road network and drone’s routes along the powerline network have to be optimized for improving the inspection efficiency, which generates a new two-layer point-arc routing problem. Two constructive heuristics are designed based on “Cluster First, Rank Second” and “Rank First, Split Second”. Then local search strategies are developed to further improve the quality of the solution. To test the performance of the proposed algorithms, practical cases with different-scale are designed based on the road network and powerline network of Ji’an, China. Sensitivity analysis on the parameters related with the drone’s inspection speed and battery capacity is conducted. Computational results indicate that technical improvement on the inspection sensor is more important for the cooperated ground vehicle and drone system.

Milk fat production is important in the New Zealand (NZ) dairy industry. Elsewhere, an amino acid substitution (K232A) in the enzyme diacylglycerol acyl-CoA acyltransferase (DGAT1) has been reported to explain variation in some milk traits, including variation in milk fatty acid (FA) profile. In this study, associations between K232A, and milk traits including milk FA composition, were studied in wholly pasture-fed NZ Holstein-Friesian × Jersey (HF×J) cross-bred dairy cows. With a high frequency of K variant (61.9%), the KK cows produced more milk fat than the AA cows (5.41 ± 0.04 % vs 4.42 ± 0.05 %). The milk volume, fat concentration and protein concentration of AK cows were between the genotypes, AA and KK. More C16:0, CLA and C18:3 cis-9, 12, 15 FA were found in the milk of Kiwi-cross cows feed in outdoor pasture grazing system., and the influence of DGAT1 K232A, on these FAs from mid- and late lactation stages were significant. The AA cows produced (P < 0.001) more CLA and C18:3 cis-9, 12, 15, but less C16:0 (1.137 ± 0.047, 0.855 ± 0.015 and 35.170 ± 0.355) than the KK cows (0.934 ± 0.025, 0.778 ± 0.009 and 38.010 ± 0.250).

Background: Dendrobium officinale is not only an ornamental plant, but also a valuable medicinal herb that is both effective and widely used in traditional Chinese medicine. However, distinguishing D. officinale from other Dendrobium species is usually a difficult task that need much time and complex technologies due to their very similar external morphologies. The aim of this study is to develop a fast, even on-spot approach to identify D. officinale. Methods: We used DNA barcode-based loop-mediated isothermal amplification (LAMP) method with species-specific LAMP primers targeting the internal transcribed spacer (ITS) region of the rDNA of D. officinale. LAMP reaction time and temperature were optimized and the specificity and sensitivity of LAMP species-specific primers were assessed. Results: This technique showed a high specificity and sensitivity to amplify the genomic DNA of D. officinale and allowed for rapid amplification (within 40 min) of the ITS region under a constant and mild temperature range of 65 °C without using thermocyclers. Besides, by using SYBR® Green I dye as the color developing agent, the color change was easily observed with naked eye. Reaction mixture containing DNA of D. officinale changed from orange to green, while the other Dendrobium species and the negative control retained original orange color. The specificity of this LAMP-based method was confirmed by testing 17 samples of D. officinale and 32 adulterant samples from other Dendrobium species. Conclusions: This LAMP-based rapid identification method does not require expensive equipment or specialized techniques and can be used in field surveys for accurate and fast on site identification.

Band-gap alignment engineering has now been extensively studied due to its high potential application. Here we demonstrate a simple route to synthesize two metal oxide layers and align them together according to their bandgaps on surface of crystalline silicon (c-Si) solar cells. The metal oxide layers can not only extend absorption spectrum to generate extra carriers but also serve to separate electron-hole pairs more efficiently. As a consequence, the photovoltaic performance of SnO₂/CdO /Si double-layer solar cell (DLSC) is highly improved compared to CdO/Si and SnO₂/Si single-layer solar cells(SLSCs) and SnO₂/CdO/Si double-layer solar cell (DLSC). By the alignment engineering, the SnO₂/CdO/Si DLSC produces a short circuit photocurrent (J_sc) of 38.20 mA/cm², an open circuit photovoltage (V_oc) of 0.575 V and a fill factor (FF) of 68.7%, corresponding to a light to electric power conversion efficiency (η) of 15.09% under AM1.5 illumination. These results suggest that with the use of metal oxide layers by band-gap alignment engineering, new avenues have been opened for developing high-efficiency and cost-effective c-Si solar cells.

Far-red fluorescent reporter genes can be used for tracking cells non-invasively in vivo using fluorescence imaging. Here, we investigate the effectiveness of the far-red fluorescent protein, E2-Crimson (E2C), for tracking mouse embryonic cells (mESCs) in vivo following subcutaneous administration into mice. Using a knock-in strategy, we introduced E2C into the Rosa26 locus of an E14-Bra-GFP mESC line, and after confirming that the E2C had no obvious effect on the phenotype of the mESCs, we injected them into mice and imaged them over 9 days. The results showed that fluorescence intensity was weak, and cells could only be detected when injected at high densities. Furthermore, intensity peaked on day 4 and then started to decrease, despite the fact that tumour volume continued to increase beyond day 4. Histopathological analysis showed that although E2C fluorescence could barely be detected in vivo at day 9, analysis of frozen sections indicated that all mESCs within the tumours continued to express E2C. We hypothesise that the decrease in fluorescence intensity in vivo was probably due to the fact that the mESC tumours became more vascular with time, thus leading to increased absorbance of E2C fluorescence by haemoglobin. We conclude that the E2C reporter has limited use for tracking cells in vivo, at least when introduced as a single copy into the Rosa26 locus.

This study examines if enterprises’ digital transformation enhances their sustainable development capabilities and reduces carbon emissions, thus enhancing carbon neutrality performance and implementing the "dual-carbon" strategy. It specifically explores the impact of Chinese firms’ digital transformation on carbon neutrality performance in 30 provinces and municipalities in China from 2011 to 2021. Based on the Difference-in-Difference method and spatial econometric modeling, this study finds a U-shaped relationship between enterprise digital transformation and carbon performance, with spatial spillover effects. It also finds that converting environmental charges into taxes can significantly improve carbon performance. In terms of the mechanism of action, digital transformation affects carbon performance by influencing energy use efficiency and adjusting the level of industrial structure advancement and rationalization. In terms of heterogeneity, this U-shaped relationship exists only in the eastern and central regions, and the significance is more substantial in the east; in addition, the impact of enterprise digital transformation on carbon performance is more evident in regions with higher R&D intensity and higher economic development levels. These findings imply that the government should further encourage and guide enterprise digital transformation, monitor the effects of environmental protection policies and select and implement carbon emission reduction strategies according to local conditions to improve carbon performance.

The accurate and timely assessment of lymph node involvement is paramount in the management of patients with malignant tumors, owing to its direct correlation with cancer staging, therapeutic strategy formulation, and prognostication. Dual-energy computed tomography (DECT), as a burgeoning imaging modality, has shown promising results in the diagnosis and prediction of preoperative metastatic lymph nodes in recent years. This article aims to explore the application of DECT in identifying metastatic lymph nodes (LNs) across various cancer types, including but not limited to thyroid carcinoma (focusing on papillary thyroid carcinoma), lung cancer, and colorectal cancer. Through this narrative review, we aim to elucidate the clinical relevance and utility of DECT in the detection and predictive assessment of lymph node metastasis in malignant tumors, thereby contributing to the broader academic discourse in oncologic radiology and diagnostic precision.

As urbanization has accelerated, China has started to build smart cities, which have formed smart city clusters. It is critical to coordinate development within smart city clusters to enhance the efficiency of city cluster construction. From the perspective of demographic economics, this study innovatively constructed an evaluation system for the coordinated development of smart city clusters and utilized the coupled coordination degree model to conduct an in-depth study of smart city clusters in Jiangsu Province. The results show that there are clear differences in the development between the three regions of Jiangsu Province: Southern Jiangsu, Central Jiangsu, and Northern Jiangsu. The development within Jiangsu Province is imbalanced, where the overall development trend is high in the southern region and low in the northern region. The main driving factors include geography, the Matthew effect, game thinking, and industrial structure. Accordingly, the results suggest the following recommendations for the coordinated development of smart city clusters: strengthening cross-regional cooperation, promoting data sharing and interoperability, deepening synergistic industrial development, and expanding innovation capacity.

With the development of the photovoltaic industry, there will be an increasing demand for efficient, high-power density, and low-cost grid interface converters. Compared with two-level inverters, multilevel inverters have the following advantages: (1) lower device voltage ratings; (2) better output filtering spectrum; (3) lower electromagnetic interference (EMI) noise; and (4) higher switching speed capability. However, the complex switching circuit of the multilevel inverter will bring more parasitic inductance, resulting in more serious switching overvoltage (ringing). Consider that commonly used overvoltage absorption schemes are effective only for overvoltage or sup-pression of oscillations. Therefore, a new overvoltage absorption circuit is proposed in this paper, which can not only alleviate the overvoltage and ringing phenomena but also suppress the effect of voltage jumps during low-frequency switching on high-frequency input voltage. This overvoltage absorption circuit is characterized by low overvoltage, fast ringing damping, and minimum ca-pacitance. Experiments and simulations are conducted to verify the effectiveness of this overvoltage absorption circuit using a three-level ANPC inverter as a prototype. The results show that the proposed overvoltage absorption circuit can significantly reduce the overvoltage level, shorten the oscillation time, and reduce the voltage difference between the upper and lower DC bus capacitors.

Rapid urbanization has led to many ecological problems such as landscape fragmentation, decreased landscape connectivity, and decreased biodiversity. Building an ecological security pattern is an important way to ensure ecological security and maintain sustainable urban development. Harbin is an important large-scale city in northeastern China, and the urban central district of Harbin is used as the study area. Ecological sensitivity assessment, MSPA, gravity model, landscape connectivity assessment and MCR model were used to extract ecological source areas, ecological corridors and ecological nodes in the study area to construct and optimize the ecological security pattern. Research shows that: A total of 23 ecological source areas were identified, mainly located along the Songhua River in the central part of the study area and in the mountain forest areas within the A-cheng District in the southeastern part of the study area. 48 ecological corridors were extracted, mainly in Daowai District, A-cheng District and the eastern part of Xiangfang District. There are 8 important ecological corridors and 10 important connecting corridors. 61 ecological nodes of the first level and 65 ecological nodes of the second level were extracted. High, higher, medium, lower and low security areas were classified based on the minimum cumulative resistance surface, with the highest proportion of high ecological security areas accounting for 45.75% of the study area. 65 ecological breakpoints were extracted and restoration measures were proposed. Finally, The structure of the ecological security pattern optimization of "two axes, two belts and four areas" is proposed, and corresponding ecological management measures are put forward. The experimental system of this study can provide new ideas for the construction of ecological security patterns in other regions and provide scientific support for the ecological sustainable development of similar urban areas.

The fatigue delamination damage is one of the most important fatigue failure modes of laminated composite structures. However, the developments of the theoretical framework, mathematical/physical model and numerical simulation of fatigue delamination are still challenging issues, and there is a lack of systematic classification. This article reviews the experimental phenomena of the onset and propagation stage of delamination under fatigue loading, and summarizes the commonly used phenomenological models for laminated composite structures. The research methods, general modeling formulas and development prospects of the phenomenological models are presented in detail. In the light of the analysis of finite element model (FEM) for the laminated composite structures, a number of simulation methods of fatigue delamination crack propagation damage model are carefully classified. Furthermore, within the theoretical framework of strength theory model (SM), fracture mechanics model (FM), damage mechanics model (DM) and hybrid model (HM), the complete procedure, application, capability assessment, advantages and limitations of the models are also discussed in detail. Finally, several valuable suggestions are given for the research interests, and challenging technical problems that need to be overcome on the fatigue delamination prediction of laminated composite structures in the future.

Underwater robotics equipped with visual detection systems have the function of detecting un-derwater artifacts, which is of great significance to deep-sea archaeology. Underwater artifacts are located in complex environments with poor imaging conditions, and the targets have chal-lenging problems such as breakage, stacking, and sediment burial, which causes the marine cul-tural target detection failures. To solve these problems, this paper proposes an underwater cul-tural target detection algorithm based on the deformable deep aggregation network model for underwater robotics exploration. To fully extract the target feature information of underwater targets in complex environments, this paper designs a multi-scale deep aggregation network with deformable convolutional layers. Besides, the BAM attention module is designed for fea-ture optimization, which enhances the potential feature information of the target while weak-ening the background interference information. Finally, the target prediction is achieved through feature fusion at different scales. The proposed algorithm has been extensively validat-ed and analyzed on the collected underwater artifact datasets, and the precision, recall, and mAP of the algorithm have reached 93.1%, 91.4%, and 92.8%, respectively. In addition, the present al-gorithm has been practically deployed on the underwater robotics. In the deep-sea tests, the ar-tifact detection frame rate reaches up to 19 fps, which satisfies the real-time target detection。

A Gem-quality rubies and sapphires are often commercially heat treated at about 800°C or higher temperatures to enhance their colour and clarity, and hence quality. For this study, selected corundum samples containing diaspore- and goethite inclusions were heated step-by-step to a maximum of 1000 °C with the aim to monitor the dehydration and phase transformation of these oxyhydroxides to corundum and hematite during heating. Based on our experiments and in agreement with literature, the dehydration of diaspore in corundum occurs between 525 to 550 °C, whereas goethite transforms to hematite already between 300 and 325 °C. As both, diaspore and goethite are common inclusions in rubies, sapphires, and other corundum varieties, these dehydration reactions and phase transformations can be considered important criteria to separate unheated stones from heated ones, specifically in cases in which other methods (e.g. microscopy, FTIR) are unsuccessful.

Bending pipe is a common component of long distance pipeline. Accurately understanding the flow law of hydrate particles in elbow pipe is of great significance for optimizing pipeline design, improving production efficiency of gas transmission pipeline and ensuring pipeline safety. Taking the flow of hydrate particles in a Bending pipe as the object of study, the spiral flow attenuation and hydrate particle deposition under different bending pipe angles, different rate of bending pipe to diameter, different Reynolds number and different torsion were studied by numerical simulation method. The results show that the larger the swirl number, the higher the spiral flow intensity. When the fluid enters the bending pipe, the Angle of the bending pipe is larger, the torsional rate is smaller, and the Reynolds number is larger, the swirl number is larger, the intensity of the swirl flow is stronger, and the swirl number is larger at the same position. However, the larger the bending pipe to diameter ratio, the greater the change of the total swirl number and the weaker the strength at outflow, but the slower the change of swirl number, indicating that the spiral flow attenuation is slower. The larger the bending pipe Angle, the larger the bending pipe diameter rate, the smaller the torsion rate and the larger the Reynolds number, the smaller the deposition rate of the particles after flowing through the pipe. The results show that the spiral flow strength can be maintained in a proper way to reduce the deposition and ensure the safety of the conveying process.

Slime Mould Algorithm (SMA) is a new swarm intelligence algorithm inspired by the oscillatory behavior of slime molds during foraging. Numerous researchers have widely applied SMA and its variants in various domains and proved its value by the experiments in literatures. In this paper a comprehensive survey on SMA is introduced, which is based on 130 articles visa Google-scholar between 2022 and July, 2023. Firstly, the theory of SMA is described. Secondly the improved SMA variants are provided and categorized according to the approach that they are applied with. Finally, it also discusses the main applications domains of SMA such as engineering optimization, energy optimization, machine learning, network, scheduling optimization, image segmentation and etc. This review presents some research suggestion for researcher who is interested in this algorithm.

This paper propose a kernel geometric mean metric learning (KGMML) algorithm. The basic idea is to obtain the closed-form solution of the geometric mean metric learning (GMML) algorithm in the high-dimensional feature space determined by the kernel function. Then, the solution is generalized as a form of kernel matrix by using the integral representation of the weighted geometric mean and the Woodbury matrix in this new feature space. Experimental results on 15 datasets show that the proposed algorithm can effectively improve the accuracy of the GMML algorithm and other metric algorithms.

In order to investigate the relationship between government policy, the service and design of rural crowdsourcing spaces, the self-efficacy of returning youth, and the innovation performance of businesses, this study focuses on gathering data by distributing questionnaires to returning youth in rural crowdsourcing spaces and developing a structural model. The results demonstrate how important government policies are in encouraging youth entrepreneurship in their local communities. It has the potential to enhance both the development of rural crowdsourcing spaces and the self-efficacy of young entrepreneurs, thereby enhancing the innovative capabilities of local entrepreneurial businesses. Therefore, in order to encourage economic development in rural areas, the government should improve pertinent support measures.

Keywords: FTY720, self-assembled nanoparticles, intracerebral hemorrhage, neuroprotection

The present study employed a modifed QuEChERS method to systematically analyze the presence of fifteen Quinolones and seven Tetracyclines antibiotic residues in local animal food. Additionally, a multi-level-four-factor Box-Behnken design (BBD) within the framework of Response surface methodology (RSM) was utilized to evaluate the various factors affecting the detection efficiency of the sample pretreament procedure. The optimization was performed by Design Expert®, the factors including volume of the acetonitrle, the addition of formic acid, the duration of extract and the addition of EDTA were combined to experiment design until reach an optimal solution. Finally, the sample test was conducted by ultra-high performance liquid chromatography-quadrupole-linear ion trap mass spectrometry in both multiple reaction monitoring (MRM) and enhanced product ion (EPI) scan modes on a QTRAP® 5500 instrument. The overall average recoveries from actual samples fortified with 22 antibiotics at three levels ranged from 74.7 to 122.6% based on the use of matrix-fortified calibration with the variation ranging from 2.1 to 18.2% (n=6). The limits of detection and quantification were 0.3 μg kg-1 and 1.0 μg kg-1, respectively.

Dye wastewater containing bisphenol A (BPA) and dyes as pollutants have not been adequately studied. Our previous study revealed that thermoplastic polyurethane (TPU) nanofiber membranes (NFMs) modified by the addition of polyethyleneimine (PEI) and polydopamine (PDA) satisfactorily adsorb dyes. Herein, we first optimized the synthesis conditions for such membranes, noting a PEI:PDA monomer ratio of 2:2 and a deposition time of 48 h to be optimal. Experiments using these membranes revealed that binary systems containing BPA and the dyes (Congo red (CR), Eosin yellow (EY), or sunset yellow (SY)) exhibit three adsorption behaviors. CR and BPA compete with each other for adsorption sites, decreasing the maximum adsorption capacity (Qmax) for CR 208.3 mg/g (in a monomeric system) to 182.4 mg/g, whereas for BPA, it decreased from 26.7 to 22.8 mg/g. The adsorption rates for CR and BPA decreased from 0.002 min−1 and 0.331 min−1 in the monomeric systems to 8.37 × 10−4 min−1 and 0.072 min−1, respectively, in the binary CR–BPA system, exhibiting antagonistic effects. When EY and BPA coexist, Qmax for EY increased from 60.0 (monomeric) to 71.9 mg/g, whereas that for BPA increased from 35.6 to 43.2 mg/g, showing a synergistic effect due to the possible bridging effect. The adsorption sites for SY and BPA are independent of each other. Thus, PDA/PEI TPU NFMs exhibit the potential for removal of dye–BPA composites, whereas binary systems containing BPA with different dyes are adsorbed differently.

With the increasing utilization of intelligent mobile devices for online inspection of electrical equipment in smart grids, the limited computing power and storage capacity of these devices pose challenges for deploying large algorithm models and it’s hard to obtain a substantial number of images of electrical equipment in public. In this paper, we propose a novel distillation method that compresses the knowledge of teacher networks into a compact few-shot classification network, employing a global and local knowledge distillation strategy. Central to our method is exploiting the global and local relationship between the features exacted by the backbone of the teacher network and student network. We compare our method with recent state-of-the-art (SOTA) methods on three public datasets and achieve superior performance. Additionally, we contribute a new dataset, namely EEI-100, which is specifically designed for classification of electrical equipment. We validate our method on this dataset and demonstrate its exceptional prediction accuracy of 94.12% when utilizing only 5-shot images.

The current methods for lightning risk warnings that are based on atmospheric electric field (AEF) data have a tendency to rely on single features, which results in low robustness and efficiency. Additionally, there is a lack of research on cancelling warning signals, contributing to the high false alarm rate (FAR) of these methods. To overcome these limitations, this study proposes a lightning risk warning method that incorporates enhanced empirical Wavelet transform-Adaptive Savitzky Gorey filter (EEWT-ASG) and one-dimensional morphology, using time-frequency domain features obtained through the Wavelet transform (WT). The proposed method achieved a probability of detection (POD) of 77.11%, miss alarm rate (MAR) of 22.89%, FAR of 40.19%, and critical success index (CSI) of 0.51, as evaluated on 83 lightning processes. This method can issue a warning signal up to 22 minutes in advance for lightning processes.

The operation status of manufacturing equipment is directly related to the reliability of the operation of manufacturing equipment and the continuity of operation of the production system. Based on the analysis of the operation status of manufacturing equipment and its characteristics, it is proposed that the concept of assessing the operation status of manufacturing equipment can be realized by applying real-time acquisition of accurate inspection data of important parts of weak motion units and comparing them with their motion status evaluation criteria. Through the study of the application characteristics of fractional-order calculus theory, a differential data fusion model based on the fractional-order differential operator is established. The advantages of Internet of Things (IoT）technology and fractional order differential fusion algorithm are integrated to obtain real-time high-precision data of the operating parameters of manufacturing equipment, and the research objective of operating condition assessment of manufacturing equipment is realized. The feasibility and effectiveness of the method are verified by the application of the method in machining center operation status assessment.

The eutrophication caused by excessive total nitrogen(TN) and total phosphorus(TP) emissions has been widely concerned by the whole society. Studies have revealed the relationship between land use and TN and TP, but the relationship between land use compound topographic position and TP and TN was seldom studied. Therefore, Spearman correlation and redundancy analyses were used to reveal the relationship between land use compound topographic position and TN and TP based on the monthly data of 28 water quality sampling sites and the land use data of 2013 and 2016 in the lakes of Guizhou Plateau. The results show that the nutritional state of the HBA watershed is medium. The trophic level index (TLI) value and TN concentration were high during flood, while TP concentration was high in dry period. The TN concentration in the tributaries was higher than that in the reservoir area. Construction and valley were the sources of the pollution, whereas forest land and gentle slope were the sink. According to the”source-sink”effect, the optimal zoning of land use was completed, and the urban land pollution govern area should be strengthened firstly. This paper can provide decision support for water environment management and sustainable development decision-making.

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

Carboxypeptidase A4 (CPA4) has shown the potential possibility as a biomarker in the early diagnosis for certain cancers. However, no previous research has linked CPA4 to therapeutic or prognostic significance in bladder cancer. Using data from The Cancer Genome Atlas (TCGA) database, we set out to determine the full extent of the link between CPA4 and BLCA. We further analyzed the interacting proteins of CPA4 and infiltrated immune cells via TIMER2，STRING and GEPIA2 databases. The expression of CPA4 in tumor and normal tissues was compared using the TCGA+GETx database. The connection between CPA44 expression and clinicopathologic characteristics and overall survival (OS) was investigated using multivariate methods and Kaplan-Meier survival curves. The potential functions and pathways were investigated via gene set enrichment analysis. Furthermore, we analyze the associations between CPA4 expression and infiltrated immune cells with their respective gene marker sets using the ssGSEA, TIMER2, and GEPIA2 databases. Compared to matching normal tissues, human CPA4 was found to be substantially expressed. We confirmed that overexpression of CPA4 is linked with shorter OS, DSF, PFI, and increased diagnostic potential using Kaplan-Meier and ROC analysis. The expression of CPA4 is related to T-bet, IL12RB2, CTLA4, and LAG3, among which T-bet and IL12RB2 are Th1 marker genes, while CTLA4 and LAG3 are related to T cell exhaustion, which may be used to guide the application of checkpoint blockade and the adoption of T cell transfer therapy.

Diffuse large B cell lymphoma (DLBCL), the most frequent type of non-Hodgkin lymphoma in adulthood, remains challenging clinical issues. Despite enhanced remission rates can be achieved, there are one-third of patients who will not respond to current treatment or will relapse with resistant disease, necessitating ongoing efforts on effective treatment strategies and agents. The vacuole H+-ATPase inhibitor bafilomycin A1 is broadly used to block late stage of autophagy flux at high concentration. In this study, we show that, to our surprise, bafilomycin A1 effectively inhibited and killed DLBCL cells at nanomolar concentrations (5nM). Bafilomycin A1 targeted cell cycle regulators cyclin D1 and cyclin E2 to induce cell cycle arrest in G0/G1 phase. Meanwhile, it induced caspase-dependent apoptosis with concomitant cleaved caspase-3 and Parp. Furthermore, we found that bafilomycin A1 inhibited autophagy flux at both early and late stages of the autophagy flux through activating ERK and mammalian target of rapamycin signaling, as well as by inhibiting the degradation of autolysosomes. We speculated that bafilomycin A1 as autophagy inhibitor might enhance the effect of DLBCL chemotherapeutic drug rituximab. Accordingly, our results provided evidence that the combination of bafilomycin A1 with rituximab enhanced the inhibition of DLBCL cells notably. Taken together, our data suggest that bafilomycin A1 may be a promising candidate drug in the therapy of diffuse large B cell lymphoma.

Establishing global high-rate secure communications is a potential application of continuous-variable quantum key distribution (CVQKD) but also challenging for long-distance transmissions in metropolitan areas. The discrete modulation(DM) can make up for the shortage of transmission distance that has a unique advantage against all side-channel attacks, however its further performance improvement requires source preparation in the presence of noise and loss. Here, we consider the effects of photon catalysis (PC) on the DM-involved source preparation for lengthening the maximal transmission distance of the CVQKD system. We address a zero-photon catalysis (ZPC)-based source preparation for enhancing the DM-CVQKD system. The statistical fluctuation due to the finite length of data is taken into account for the practical security analysis. Numerical simulations show that the ZPC-based DM-CVQKD system can not only achieve the extended maximal transmission distance, but also contributes to the reasonable increase of the secret key rate. This approach enables the DM-CVQKD to tolerate lower reconciliation efficiency, which may promote the practical implementation solutions compatible with classical optical communications using state-of-the-art technology.

This purpose was to compare the ability of body shape index (ABSI) and body roundness index (BRI) with waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and body adiposity index (BAI) to predict metabolic risk. The cross-sectional study was conducted in 17,360 Chinese subjects (were aged 18-95 years old) who escaped cardiovascular disease (CVD) or diabetes. Biochemical and anthropometric variables were measured by trained staff. Receiver operating characteristic curve (ROC) and optimal cutoff values of obesity indices were recruited to compare the predictive ability for metabolic risk factors. The mean age of subjects was 53.7(13.1) years, 41.6 % were males. Within young group (<60 years), the areas under the curve (AUC) demonstrated that WC, BMI, WHR, WHtR and BRI were able to similarly predict high metabolic risk in males (0.74 vs. 0.74 vs. 0.73 vs. 0.73 vs. 0.73) and in females (0.73 vs. 0.73 vs. 0.71 vs. 0.73 vs. 0.73), while the approximate predictive ability were only acquired in males (0.73 vs. 0.73 vs. 0.70 vs. 0.73 vs. 0.73) within elder group (≥60 years). The optimal cut-off values of BRI for high metabolic risk were calculated in males (<60 y: 3.49 vs. ≥60 y: 3.46) and females (<60 y: 3.47 vs. ≥60 y: 3.60). Meanwhile, BRI displayed a strong prediction to elevated BP and elevated TG in males (AUC = 0.64; AUC = 0.70) and to elevated BP, elevated TG and elevated SUA in females (AUC = 0.67; AUC = 0.69; AUC =0.70). BRI was able to similarly predict high metabolic risk compared to WC, BMI, WHR, WHtR and BAI, while ABSI was not. Moreover, BRI revealed specific predictive ability for elevated BP, elevated TG and elevated SUA.

Accurate and efficient traffic incident detection methods can effectively alleviate traffic congestion caused by traffic incidents, prevent secondary accidents and improve the safety of urban road traffic.Aiming at the problems that the traditional machine learning event detection method cannot fully extract the parameter characteristics of traffic flow and is not suitable formulti-dimensional and non-linear massive data, we propose a new traffic event detection method(CNN-XGBoost).This method combines the respective advantages of Convolution Neural Network(CNN) and Extreme Gradation Boosting (XGBoost). Firstly, we preprocessed the original freeway traffic incident detection data set by constructing initial variable set, data normalization, data balance processing and dimension reorganization. Secondly,we use CNN network to automatically extract the deep features of event detection data, and use XGBoost as a classifier to classify the extracted features for expressway traffic event detection.Finally, we use the data set of Hangzhou expressway microwave detector in China to carry out simulation experiments on CNN-XGBoost. The experimental results show that compared with XGBoost, CNN, Support Vector Machine (SVM) and Gradient Boosting Decision Tree (GBDT) and other methods, CNN-XGBoost method can effectively improve the accuracy of expressway traffic event detection and has better generalization ability.

The Doubly-Fed Induction Generator (DFIG) has significant features in comparison with Fixed Speed Wind Turbine (FSWT), which has popularized its application in power system. Due to partial rated back-to-back converters in the DFIG, Fault Ride-Through (FRT) capability improvement is one of the great subjects regarding new grid code requirements. To enhance the FRT capability of the DFIG, many studies have been carried out. Fault current limiting devices as one of the techniques are utilized to limit the current level and protect switches of the back-to-back converter from over-current damage. In this paper, a review is done based on fault current limiting characteristic of the proposed fault current limiting devices Therefore, Fault Current Limiters (FCLs) and Series Dynamic Braking Resistors (SDBRs) are mainly taken into account. Operation of all configurations including their advantages and disadvantages is explained. Impedance type and the fault current limiting devices’ location are two important factors, which significantly affect the DFIG behaviour in the fault condition. These two factors are basically studied by the simulation and their effects on the key parameters of the DFIG are investigated. Finally, future works in respect to the FCL application in the FRT improvement of the DFIG have also been discussed.

This paper develops a novel dynamic correction method for the reliability assessment of large oil-immersed power transformers. First, with the transformer oil-paper insulation system (TOPIS) as the target of evaluation and the winding hot spot temperature (HST) as the core point, an HST-based static ageing failure model is built according to the Weibull distribution and Arrhenius reaction law, in order to describe the transformer ageing process and calculate the winding HST for obtaining the failure rate and life expectancy of TOPIS. A grey target theory based dynamic correction model is then developed, combined with the data of Dissolved Gas Analysis (DGA) in power transformer oil, in order to dynamically modify the life expectancy calculated by the built static model, such that the corresponding relationship between the state grade and life expectancy correction coefficient of TOPIS can be built. Furthermore, the life expectancy loss recovery factor is introduced to correct the life expectancy of TOPIS again. Lastly, a practical case study of an operating transformer has been undertaken, in which the failure rate curve after introducing dynamic corrections can be obtained for the reliability assessment of this transformer. The curve shows a better ability of tracking the actual reliability level of transformer, thus verifying the validity of the proposed method and providing a new way for transformer reliability assessment. This contribution presents a novel model for the reliability assessment of TOPIS, in which the DGA data, as a source of information for the dynamic correction, is processed based on the grey target theory, thus the internal faults of power transformer can be diagnosed accurately as well as its life expectancy updated in time, ensuring that the dynamic assessment values can commendably track and reflect the actual operation state of the power transformers.

The nitrogen-doped amorphous oxide semiconductor (AOS) thin film transistors (TFTs) with double-stacked channel layers (DSCL) were prepared and characterized. The DSCL structure composed of nitrogen-doped amorphous InGaZnO and InZnO films (a-IGZO:N/a-IZO:N or a-IZO:N/a-IGZO:N) made the corresponding TFT devices exhibit quite large field-effect mobility due to the existence of double conduction channels. Especially, the a-IZO:N/a-IGZO:N TFTs showed even better electrical performance (μ_FE = 15.0 cm²·V^-1·s^-1, SS = 0.5 V/dec, V_TH = 1.5 V, I_ON/I_OFF = 1.1×10⁸) and stability (V_TH shift of 1.5, -0.5, and -2.5 V for positive bias-stress, negative bias-stress and thermal stress tests, respectively) than the a-IGZO:N/a-IZO:N TFTs. Based on the X-ray photoemission spectroscopy measurements and energy band analysis, it was assumed that the optimized interface trap states, the less ambient gas adsorption, and the better suppression of oxygen vacancies in the a-IZO:N/a-IGZO:N hetero-structures might be responsible for the better behaviors of the corresponding TFTs.

With the aging of China's population, the problem of pension security has become more and more prominent, and whether delayed retirement can effectively alleviate the pension fund gap and ensure the sustainability of the pension fund has become the focus of social concern. This study predicts the income and expenditure of urban workers' basic pension insurance fund from 2021 to 2050 by constructing an actuarial model of pension insurance fund income and expenditure, and simulates the effect of delayed retirement policy. The prediction results show that under the existing system, the basic pension insurance fund for urban workers will have a shortfall for the first time in 2027, and the shortfall will expand year by year. Compared with the non-implementation of delayed retirement policy, the simulation of the implementation of delayed retirementt program delayed the emergence of the fund gap until 2029, and the forecast period of the pension fund gap significantly narrowed, indicating that delayed retirement policy has a certain positive impact on alleviating the pressure of pension payments, but delayed retirementt can not completely eliminate the pension fund gap. In view of this, this paper suggests that a progressive and flexible delayed retirement policy should be introduced as soon as possible to better adapt to the needs of different groups. At the same time, differentiated policies should be formulated for different groups of people and a pension incentive mechanism for delayed retirement should be set up to improve public acceptance of delayed retirement policy. In addition, delayed retirement policy should be combined with other measures, such as lowering the corporate contribution rate and enhancing the value-added capacity of the pension fund, so as to ensure the sustainability of the pension fund.

Effects of plastic deformation on the indentation feature of hot-rolled commercial pure titanium alloy were detected using microindentation. It was found that the most deformed sample experienced the largest indentation resistance and had the maximum dislocation density and the indentation size influenced the CP-Ti indentation feature. The Vicker hardness and energy dissipated demonstrated the significant influence of the dislocation motion and size effects on the indentation in the indentation deformation. The linear relation of the energy ratio which is related to the microstructures and the indentation depth ratio was obtained for hcp materials Titanium alloys.

Carbon fiber reinforced polymer (CFRP) bending structure is widely used in the aviation field. The occurrence and propagation of delamination damage will reduce the safety of in-service bending structures. As a detection tool with high damage sensitivity, Lamb wave can effectively identify delamination damage. In this study, the signal difference coefficient (SDC) was introduced to quantify delamination damage and evaluate the sensitivity of A0 and S0 mode lamb waves to delamination damage. The simulation results show that compared with the S0 mode Lamb wave, the A0 mode Lamb wave exhibits higher delamination damage sensitivity. The delamination damage can be quantified based on the strong correlation between the SDC and the delamination damage size. The control effect of the linear array PZT phase time-delay method on Lamb wave mode was investigated by simulation. The phase time-delay method realizes the generation of a single-mode Lamb wave, which can separately excite the A0 mode and S0 mode Lamb wave to identify delamination damage of different sizes. The A0 mode Lamb wave was excited by the developed one-dimensional linear comb transducer (LCT), which was used to conduct the detection experiment on the CFRP bending plate with delamination damage sizes of Φ6.0 mm, Φ10.0 mm, and Φ15.0 mm. The experimental results verify the correctness of the simulation. According to the Hermite interpolation results of the finite-element simulation data, the relationship between the delamination damage size and the SDC was fitted by the Gaussian function, which can accurately quantify the delamination damage. The absolute error of the delamination damage quantification with fitting expression is not larger than 0.8 mm, and the percentage error is not more than 8%.

To improve the adaptability of aerial reflective opto-mechanical structures to low-temperature environments, an optimized thermal control design is proposed. Firstly, the relationship be-tween conventional heating methods and axial/radial temperature differences of mirrors with different shapes is analyzed. Based on heat transfer analyses, it is pointed out that optimized thermal control design is necessary to ensure the temperature uniformity of the fused silica mirror and take into account the temperature level when working in low temperature environ-ments. A thermal control scheme based on temperature negative feedback variable power zone heating is proposed for the characteristics of aerial electro-optics systems. Using the thermal control scheme at low temperatures ensures that the average temperature of the mirror fluctu-ates slowly and slightly around 20℃. At the same time, the temperature differences within a mirror and between the primary mirror and the secondary mirror can be controlled within 5℃. Thereby, satisfactory image quality is obtained.

Sodium-potassium (NaK) liquid alloy is a promising candidate for use as anode material in sodium batteries because of its fluidity, which effectively suppresses the growth of sodium or potassium dendrites. However, the poor wettability of the NaK liquid alloy on conventional metal substrates is unfavorable for cell fabrication due to its strong surface tension. In this paper, low-density and low-cost fluorinated aluminum foam is used as a substrate support material for NaK liquid alloy. By combining low surface tension NaK@C with fluorinated aluminum foam, we obtain a uniformly distributed and structurally stable electrode material. The composite electrode has a cycling stability of more than 3000 hours in a symmetrical cell. Furthermore, when coupled with a sulfurized polyacrylonitrile cathode in carbonate electrolyte, it maintains excellent stability even after 800 cycles, with 72% of capacity retention.

Biliary tract cancer, encompassing intrahepatic and extrahepatic cholangiocarcinoma, as well as gallbladder carcinoma, stands as a prevalent malignancy characterized by escalating incidence rates and unfavorable prognoses. The onset of cholangiocarcinoma involves a multitude of risk factors and could potentially be influenced by microbial exposure. The human microbiome, encompassing the entirety of human microbial genetic information, assumes a pivotal role in regulating key aspects such as host digestion, absorption, immune responses, and metabolism. The widespread application of next-generation sequencing technology has notably propelled investigations into the intricate relationship between the microbiome and diseases. An accumulating body of evidence strongly suggests a profound interconnection between biliary tract cancer and the human microbiome. This article critically appraises the existing evidence pertaining to the microbiome milieu within patients afflicted by biliary tract cancer. Furthermore, it delves into potential mechanisms through which dysregulation of the human microbiome could contribute to the advancement of biliary tract cancer. Additionally, the article expounds on its role in the context of chemotherapy and immunotherapy for biliary tract cancer.

In complex systems constrained by multiple factors, it is of great significance to accurately identify the key influencing factors for mastering the evolution and development law of the system and obtaining scientific decision-making suggestions or schemes. At present, the method based on experimental simulation is limited by the difficulty of system model construction; the method based on decision trial and Evaluation laboratory (DEMATEL) involves a wide range of subjects and is greatly influenced by subjective factors. In view of this, we propose a novel model based on heuristic causal inference. The model uses the FCI algorithm with prior knowledge to learn the global causal network among multiple factors of the complex system. The causal effect among variables in the causal network is calculated by using heuristic causal inference method. Specifically, the causal path contribution degree of cause variable to target variable is calculated to replace the causal effect of each cause variable to target variable. The key influencing factors in the system are screened out according to the contribution degree of causal pathways. Based on the dataset generated in the production process of a semiconductor manufacturing system, we carried out simulation experiments, identified several factors that have a key impact on product quality, and proved the feasibility and effectiveness of the proposed model.

The popularity and development of social media has made it more and more convenient to spread rumors, and it has become especially important to detect rumor information from massive amounts of information. Most of the traditional rumor detection methods use content characteristics or propagation structure to mine rumor characteristics, ignoring the fusion characteristics of content and structure and their interaction characteristics. Therefore, a novel rumor detection method based on heterogeneous convolutional networks is proposed. Firstly, this paper constructs a heterogeneous map of joint rumor content and propagation structure to explore the interaction between content and propagation structure during rumor propagation and obtain rumor representation. On that basis, this paper uses the deep residual graph convolutional neural network to construct the content and structure interaction information of the current network propagation model. Finally, this paper uses the two datasets of Twitter15 and Twitter16 to verify the proposed method. Experimental results show that the proposed method has higher detection accuracy than the traditional rumor detection method.

Converting biowaste into biochar and subsequently putting it into the soil are considered to be an effective approach to sequestrate carbon (C). However, biochar will inevitably undergo the aging process in soil, which influences its stability, and ultimately threatens its carbon sequestration ability. This study selected CaCl2 as exogenous additive of sewage sludge and bone dreg to quantify both surface C and bulk C stability in Ca-rich biochars under three aging processes (dry-wet aging, freeze-thaw aging, and natural aging in farmland soil), and revealed the influence mechanisms of exogenous Ca on biochar stability. Results showed that after dry-wet aging (25 rounds), freeze-thaw aging (25 rounds), and natural aging in different farmland soils (5 months), oxidized surface C in Ca-rich biochar decreased by 10~23%, 28~41%, and 0~74%, respectively, compared to that in pristine biochar, while oxidized bulk C decreased by 6~10%, 0~1%, and 0~35%, respectively. Under three aging processes, the surface C and bulk C stability in Ca-rich biochar were superior to that in corresponding pristine biochar, which was attributed to the “protective effect” of Ca-containing crystals on biochar surface, including CaO, Ca5(PO4)3Cl, Ca5(PO4)3(OH), Ca8H2(PO4)6·H2O and Ca10(PO4)6(OH)2. These Ca-containing crystals could block the connection between biochar-C and the external oxidizing environment, intervening the oxidation of C-C/C=C in biochar, but also prevented aging from damaging C structure of biochar, reducing the generation of fragmented structure. By comprehensively assessing surface C and bulk C stability under three aging processes, final C sequestration in Ca-rich biochar increased to 27~80%, compared to that in pristine biochar (23~74%). Therefore, Ca-rich biochar is more dominant than pristine biochar, considering C sequestration potential during long-term aging in soil.

As one of the most critical parameters to evaluate the quality and performance of mobile phones, real-time temperature monitoring of the mobile phone integrated chips is vitally important in the electronics industry. Although several different strategies for chip surface temperature measurement have been proposed in recent years, distributed temperature monitoring with the high spatial resolution is still a hot issue to be solved urgently. In this work, a fluorescent film material with photothermal properties containing thermosensitive upconversion nanoparticles (UCNPs) and polydimethylsiloxane (PDMS) is fabricated for chip surface temperature monitor-ing. The presented fluorescent films have thicknesses ranging from 23 to 90 μm and are both flexible and elastic. Using the fluorescence intensity ratio (FIR) technique, the temperature sens-ing properties of these fluorescent films are investigated. The maximum sensitivity of the fluo-rescent film was measured to be 1.43% K-1 at 299 K. By testing the temperature at different posi-tions of the optical film, a distributed temperature monitoring with a high spatial resolution down to 10 μm on the chip surface is successfully achieved. It is worth mentioning that the film maintains stable performance even under pull stretch up to 100%. The correctness of the method is verified by taking infrared images of the chip surface with an infrared camera. These results demonstrate that the as-prepared optical film is a promising anti-deformation material for high spatial resolution temperature monitoring on-chip surfaces.

The surface defects of shield subway tunnel can significantly affect the serviceability of the tunnel structure and may compromise the operation safety. To effectively detect the multiple surface defects, this research employs a tunnel inspection trolley (TIT) based on the mobile laser scanning technique. By conducting the inspection of the shield tunnel on a metro line section, various surface defects are identified by the TIT, including water leakage defect, dislocation, spalling, cross-section deformation, etc. To explore the root causes of the surface defects, the association rules between different defects are calculated via an improved Apriori algorithm. Results show that: i) there are significant differences in different association rules of various surface defects of the shield tunnel; ii) the average confidence of the association rule “dislocation &amp; spalling → water leakage” is as high as 57.78%, indicating that most of the water leakage defects are caused by dislocation and spalling of the shield tunnel in the sections being inspected; iii) the weakest rule appears at “water leakage → spalling”, with the average confidence of 13%. The association analysis can be used in predicting the critical defects influencing the structural reliability and operation safety, such as water leakage, and optimizing the construction and maintenance work for the shield subway tunnel.

In recent years, the FDA has approved numerous antitumor drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of development. With the continuous advancements in gene sequencing and high-throughput screening, research and development strategies for personalized clinical drugs have developed rapidly. This review elaborated the recent personalized treatment strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, and computation aided drug design. These technologies rely on the molecular classification of diseases, the global signaling network within organisms, and new models for all targets, which significantly support the development of personalized medicine. Meanwhile, we summarized chemical drugs such as lorlatinib, osimertinib, and other natural products that deliver personalized therapeutic effects based on genetic mutations. This review also highlights potential challenges in interpreting genetic mutations and combining drugs, while providing new ideas for the development of personalized medicine and pharmacogenomics in cancer study.

Currently, the number of lightning casualties and casualty rates have significantly reduced in developed countries, but there has been no significant reduction in developing countries. On the one hand, this is due to the high frequency of lightning; on the other hand, the vulnerability of people in developing countries is also an influencing factor. Through case analysis and summary, this paper expounds on lightning injury’s mechanism and clinical manifestations. It points out that lightning injury is mainly related to heart problems and the impact on the nervous system, rather than burns, which usually cause fewer consequences. Medical treatment needs to pay attention to the order and principles of treatment. Implementing CPR and auxiliary AED is the most effective way to save lives. Attention should be paid to the practical and effective treatment and nursing of lightning stroke sequelae. Finally, combined with the situation of lightning casualties in china, the existing problems are put forward during the process of early treatment, post-hospital treatment, and nursing observation, which provides an objective basis for the cognition of the scientific nature of the lightning injury.

The exponential growth of digital media content has introduced new challenges in managing and classifying internet traffic. Digital media traffic is composed of various applications such as video, audio, social media, and search, and its data structure is complex, incorporating a vast array of features. The classification of traffic data is a crucial aspect of internet traffic management and network security, and it forms the basis for several scenarios, including content distribution, advertising recommendations, and data analysis. Traditional classification methods rely mainly on deep packet inspection and port-based techniques, which have become increasingly ineffective due to the rapid evolution of network traffic. To address this issue, this study proposes a machine learning-based traffic classification method aimed at enhancing the accuracy and efficiency of digital media traffic classification to meet the current needs of traffic management and network security. The paper also analyzes and evaluates the classification effect and prediction capability of various algorithms under different training set sizes to validate the feasibility and effectiveness of the proposed method. The result demonstrates that the neural network algorithm has superior classification and prediction capabilities compared to the decision tree and support vector machine algorithms. Furthermore, our proposed method achieves the highest accuracy of 96.88% with a large training sample of 40,000 data streams, proving its superiority in handling high-dimensional data and complex datasets. The research results are significant for the development of digital media traffic classification and prediction methods and are expected to be applied in practical scenarios.

The processes of soliton generation and interference focus on the complex nonlinear soliton dynamics resembling matter particles. In order to further understand the dynamic process of solitons from a multidimensional perspective, here we report the vectorial solitons nature under two-sets pulse splitting in a single cavity induced by dual-core fiber assisted ultrafast fiber lasers. Owing to the weakly coupled cores in symmetrical dual core fiber (SDCF), two pulse groups interaction are formed in a cavity. By using the dispersive Fourier transformation technique (DFT), it was found that the four-component polarized rotation vector solitons (PRVS) generate. Moreover, gradually increasing the power can obtain the locked soliton bound state in two core space, and the corresponding evolution is similar to that of non-degenerate bright solitons in Bose Einstein condensates (BEC). In addition, by properly controlling the soliton phase offset in SDCF, the soliton rain state of multi pulse evolution can be obtained. The related experimental results would be fruitful to the communities interested in soliton dynamics and frequency comb lasers.

Perennial cropping play vital roles in regulating soil carbon sequestration and thus mitigating climate change. However, how perennial cropping affects soil microbial community remains elusive. Using a field investigation, this study was conducted to examine the effects of mugwort cropping along a chronosequence (that is, wheat-maize rotation, 3-year, 6-year, and 20-year mugwort cropping) on soil microbial community in temperate regions of Northern China. The results showed that the highest total, actinomycetes, and fungi PLFAs were found in the 3-year mugwort cropping soils. All PLFAs of microbial groups were lowest in the 20-year mugwort cropping soils. All of the three cropping years of mugwort increased network complexity of soil microbial community. Changes in total nitrogen and phosphorus content as well as the ratio of ammonium nitrogen to nitrate nitrogen could be primarily explain the variations in soil microbial community along the mugwort cropping chronosequence. Our observations highlight the contrasting impacts of soil microbial community to short-term and long-term mugwort cropping compared to conventional rotations and would have critical implications for sustainable agricultural management under perennial cropping in temperate regions.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article's main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Soil organic carbon (SOC) mineralization is closely related to carbon source or sink of terrestrial ecosystem. Understanding soil organic carbon (SOC) mineralization under plum plantation is essential for improving our understanding of SOC responses to land-use change in karst rocky desertification ecosystem. In this study, 2-y, 5-y and 20-y plum plantations and adjacent woodland were sampled and a 90-day incubation experiment was conducted to investigate the effect of plum plantation with different years on SOC mineralization in subtropical China. Results showed that: (1) there was no significant difference in SOC content between different planting years, but there were significant differences in accumulative SOC mineralization (C_t) and potential SOC mineralization (C₀); (2) the dynamics of the SOC mineralization was a good fit to a first-order kinetic model. Both C₀ and C_t in calcareous soil of this study was several to ten folds lower than that in other soils, indicating that SOC in karst region has higher stability. (3) Correlation analysis revealed that both C_t and C₀ was significantly correlated with soil calcium (Ca) and C/N, indicating the important role of Ca and C/N in SOC mineralization in karst rocky desertification area.

In order to study the crystallinity of different density polyethylenes, the experimental study on the transformation of the conductance mechanism under high electric field was carried out. The X-ray Diffraction(XRD), Different Scanning Calorimeter(DSC), Direct Current(DC) breakdown of Low-density polyethylene(LDPE), Linear low density polyethylene(LLDPE), Medium density polyethylene(MDPE) and High-density polyethylene(HDPE) and the electric field of 5-200kV/mm were tested. Conductivity characteristics experiments, in addition, using the mathematical formula of a variety of conductance mechanisms, the electric field-current density curves of the four kinds of polyethylene were fitted to analyze the conductance transition of the above four kinds of polyethylene in non-ohmic regions under different high field strengths. mechanism. The experimental results show that as the density of polyethylene increases, the crystallinity increases continuously, and the continuous increase of crystallinity causes the electric conduction flow under the same field strength to decrease significantly. The field strength corresponding to the two turning points in the conductance characteristic curve increases simultaneously. Large, the breakdown field strength increases; through analysis, it is found that in the high field, as the electric field increases, the conductance mechanism develops from the ohmic conductance of the low field strength region to the bulk effect of the high field strength region (Poole-Frenkel). Then the electrode effect to the high field strength (Schottky), and the threshold field strength of this conductance mechanism transition increases with the increase of crystallinity.

Full waveform (FW) LiDAR holds great potential for retrieving vegetation structure parameters at a high level of detail, but this prospect is constrained by practical factors such as lack of available handy processing tools and technical intricacy of waveform processing. This study introduces a new product, named the Hyper Point Cloud (HPC) derived from FW LiDAR data, and explore its potential applications such as tree crown delineation using the HPC-based intensity and percentile height (PH) surfaces, which show a promising solution to the constraints of using FW LiDAR data. Results of the HPC present a new direction to handle FW LiDAR data and offer prospects for studying the mid-story and understory of vegetation with high point density (~ 182 points/m2). The intensity-derived digital surface model (DSM) generated from the HPC shows that the ground region has larger maximum intensity (MAXI) and mean intensity (MI) than the vegetation region while having smaller total intensity (TI) and number of intensities (NI) at the given grid cell. Our analysis of intensity distribution contours at individual tree level exhibit similar patterns, indicating that the MAXI and MI are decreasing from the tree crown center to tree boundary while a rising trend is observed for TI and NI. These intensity variable contours provide a theoretical justification for using HPC-based intensity surfaces to segment tree crowns and exploit their potential for extracting tree attributes. The HPC-based intensity surfaces and the HPC-based PH Canopy Height Models (CHM) demonstrate promising tree segmentation results comparable to the LiDAR derived CHM for estimating tree attributes such as tree locations, crown widths and tree heights. We envision that products such as the HPC and the HPC-based intensity and height surfaces introduced in this study can open new perspectives to use FW LiDAR data and alleviate the technical barrier of exploring FW LiDAR data for detailed vegetation structure characterization.

Primary urethral malignancies are rare in clinical practice and elderly female are prone to suffer. The cause of PUC is unknown and may be related to long-term chronic inflammation, infection, sexual intercourse, pregnancy and irritation of the urethra. Incipient symptom of PUC is not distinctness and can easily lead to misdiagnosis. The final diagnosis relied on transvaginal ultrasound-guided mass biopsy and urethral biopsy. Early tumor treatment is mainly based on surgical resection. For advanced tumors, it is recommended to adopt a comprehensive treatment plan combining surgery, radiotherapy and chemotherapy We report this case with the aim of bringing attention to that primary urethral cancer progresses rapidly and has a poor prognosis, it is urged to call for a need of diagnostic and treatment specification.

The use of salt rock for underground radioactive waste disposal facilities requires a comprehensive analysis of creep-damage process in salt rock. A computer-controlled creep setup is employed to carry out a creep test of salt rock lasted as long as 359 days under a constant uniaxial stress. The AE space-time evolution and energy releasing characteristics during creep test are studied in the meantime. A new creep-damage model is proposed on the basis of fractional derivative by combining the AE statistical regularity. It indicates that the AE data in non-decay creep process of salt rock can be divided into three stages. Furthermore, the parameters of new creep-damage model are determined by Quasi-Newton method. The fitting analysis suggests that the creep-damage model based on fractional derivative in this paper provides a precise description of full creep regions in salt rock.

The interaction between different regions normally is reflected by the form of the stream. For example, the interaction of the flow of people and flow of information between different regions can reflect the structure of cities’ network, and also can reflect how the cities function and connect to each other. Since big data has become increasingly popular, it is much easier to acquire flow data for various types of individuals. Currently, it is a hot research topic to apply the regional interaction model, which is based on the summary level of individual flow data mining. So far, previous research on spatial interaction methods focused on point-to-point and area-to-area interaction patterns. However, there are a few scholars who study the hotspot interaction pattern between two regional groups with some predefined neighborhood relationship by starting with two regions. In this paper, a method for identifying a similar hotspot interaction pattern between two regional groups has been proposed, and the Geo-Information-Tupu methods are applied to visualize the interaction patterns. For an example of an empirical analysis, we discuss China’s air traffic flow data, so this method can be used to find and analyze any hotspot interaction patterns between regional groups with adjoining relationships across China. Our research results indicate that this method is efficient in identifying hotspot interaction flow patterns between regional groups. Moreover, it can be applied to any analysis of flow space that is used to excavate regional group hotspot interaction patterns.

The efficiency and performance of Proton Exchange Membrane Fuel Cells (PEMFCs) are primarily influenced by ORR electrocatalysts. In recent years, atomically dispersed met-al-nitrogen-carbon (M-N-C) catalysts have gained significant attention due to their high active center density, high atomic utilization, and high activity. These catalysts are now considered the preferred alternative to traditional noble metal electrocatalysts. The unique properties of M-N-C catalysts are anticipated to enhance the energy conversion efficiency and lower the manufac-turing cost of the entire system, thereby facilitating the commercialization and widespread ap-plication of fuel cell technology. This article initially delves into the origin of performance and degradation mechanisms of Fe-N-C catalysts from both experimental and theoretical perspectives. Building on this foundation, the focus shifts to strategies aimed at enhancing the activity and durability of atomically dispersed Fe-N-C catalysts. These strategies encompass the use of bi-metallic atoms, atomic clusters, heteroatoms (B, S, and P), and morphology regulation to optimize catalytic active sites. The article concludes by detailing the current challenges and future pro-spects of atomically dispersed Fe-N-C catalysts.

Microplastics pollution in sugarcane areas of China is severe, and reducing their ecological risks is critical. This study aims to explore the effects and mechanisms of microplastics combined with or without biochar on sugarcane growth, soil biochemical properties in red soil by a potted experiment. The results showed that compared with control (CK), microplastic alone treatments reduced the dry biomass of sugarcane, soil pH and the nitrogen (N) and phosphorus (P) contents, obviously decreased the observed_OTUs, Chao1 and Shannon indices of soil total bacteria (16S rRNA gene-based bacteria) while increasing them in phoD-harbouring bacteria. Interestingly, microplastics combined with biochar could alleviate the negative effects of microplastic accumulation on sugarcane growth and soil quality. There were significant differences in the bacterial community compositions among different treatments. Compared with CK, all other treatments significantly decreased the relative abundance of Gemmatimonadota while only microplastic combined with biochar treatments significantly increased the abundance of Subgroup_10 for the 16S rRNA gene, and only microplastic alone treatments significantly increased the relative abundance of Streptomyces for the phoD gene. Moreover, the treatments with microplastics combined with biochar increased the relative abundance of Subgroup_10 and Bradyrhizobium while decreased the IMCC26256 and Streptomyces compared with that in the treatment with microplastics alone. Correlation analysis showed that Subgroup_10 and Bradyrhizobium were significantly positively correlated with sugarcane biomass and several soil properties, while IMCC26256 and Streptomyces were just the opposite. Additionally, different treatments also changed the abundance of potential microbial functional genes. Compared to CK, other treatments increased the abundance of aerobic_ammonia_oxidation, denitrification while decreased the abundance of nitrate_respiration, nitrogen_respiration; meanwhile, these four functional genes involved in N cycling processes were obviously higher in treatments with microplastics combined with biochar than in treatments with microplastic alone. In conclusion, microplastics combined with biochar could alleviate the negative effects of microplastic accumulation on sugarcane growth by improve soil nutrients and microbial community structure and function.

The physical properties of coal reservoirs are the main restrictions to exploration and development of CBM. The study of the physical characteristics of coal reservoirs and their controlling factors is of great significance to the safe and efficient development and utilization of CBM resources in the mining area. The Pingdingshan No. 10 coal mine was chosen for this study because of its better gas production effect at the test wells. The reservoir properties of the main coal seams of the No. 10 coal mine were tested and analyzed to comprehensively evaluate the reservoir properties. The results indicate that (1) The gas content and methane purity of the No. 4 coal seam are significantly higher than the No. 2 seam, and therefore they have better development potential than the No. 2 seam; (2) The average adsorption time of the No. 2 coal seam is less than that of the No. 4 seam, making it easier to reach the peak production capacity of CBM wells in the short term, but is not conducive to long-term stable production of CBM. The Langmuir volume of the No. 2 coal seam samples was significantly greater than for the No. 4 coal seam; however, the No. 4 coal seam contains about three times the amount of gas in the No. 2 seam; (3) All three coal seams have high porosity, which is favorable for large amounts of CBM adsorption and storage. Micropores predominate, transitional pores are less frequent, and a few mesopores occur; macropores are the least common. Samples from the No. 4 seam contained the highest proportion of micropores; (4) Organic pores were common in the all coal samples, with pore diameters not more than 30 µm, mainly concentrated between 50.5 and 1000 nm. Microfractures with aperture less than 70 nm were relatively frequent, mainly in the 50–65 nm range. A large number of the nanoscale microfractures were curved or jagged; (5) Fractures in the No. 2 and No. 4 coal seam samples with widths of 50 nm to 20 µm were more developed, and many were filled with kaolinite, quartz and other minerals; (6) The samples contained mostly layered silicate minerals (kaolinite), with hard granular minerals (quartz) next, and a very small quantity of iron-type minerals such as siderite and pyrite in dendritic form. The results of this study can provide a reference basis for the large-scale development and utilization of subsequent CBM wells.

Autophagy is an evolutionarily conserved mechanism for degrading and recycling different cellular components in both normal development and stress conditions. Our recent research demonstrated that autophagy-mediated compartmental cytoplasmic deletion is essential for pollen germination. However, how autophagy regulates pollen germination to ensure its fertility remains largely unknown. Here, we applied multi-omic analyses to investigate the downstream pathways of autophagy in the process of pollen germination. Although ATG2 and ATG5 play similar roles in regulating pollen germination, high-throughput transcriptomic analysis reveals that silencing ATG5 has greater impact on the transcriptome than silencing ATG2. Cross-comparisons of transcriptome and proteome analysis reveal that gene expression at mRNA level and protein level are differentially affected by autophagy. Furthermore, high-throughput metabolomics analysis demonstrates that pathways related amino acid metabolism and aminoacyl-tRNA biosynthesis can be affected by both ATG2 and ATG5 silencing. Collectively, our multi-omic analyses reveal a central role of autophagy in cellular metabolism, which is critical for the initiation of pollen germination and the guarantee of pollen fertility.

With the development of the volume of information exchange and perception increases, the demands for intelligent, miniaturized and integrated optical devices for information acquisition are also increasing. As the core component of optical networks for transmitting information, how to further optimize its structural characteristics to generate richer optical characteristics and apply them to information exchange and optical field control has become a key research hotspot. The introduction of chiral twist characteristics has led to new phenomena and applications in optical field transmission and transformation for traditional optical fibers or microstructured optical fibers (MOF). Therefore, this review mainly starts from the principle of chiral optical fibers, introduces their preparation and latest application scenarios, and finally looks forward to their potential future development prospects.

The implementation of grey and green infrastructure is an effective mean to address urban flooding and nonpoint source pollution, but due to the complexity of the process and the diver-sity of benefits, there is a lack of measurement for their comprehensive benefits. Adopting a typ-ical university in Beijing as an example, this paper simulated the multidimensional benefits of the water quantity, water quality, and ecology of grey and green facility renovation by coupling the storm water management model (SWMM) and InfoWorks Integrated Catchment Manage-ment (ICM). Monetization methods and economical means were employed to characterize the comprehensive benefits. The results showed that grey and green infrastructure retrofitting re-duces the number of severe overflow nodes in the study area by 54.35%, the total overflow vol-ume by 22.17%, and the nonpoint source pollution level by approximately 80% under the heavy rain scenario and 60% under the rainstorm scenario. The annual benefits of grey and green infra-structure renovation reached ¥765,600/year, of this amount, ¥83,100/year is from hydrological regulation, ¥454,100/year is from nonpoint source pollution reduction, and ¥228,300/year is from ecological improvement. The benefits of green facilities were higher than those of grey facilities, and the combined benefits were negatively correlated with the rainfall level, with a total bene-fit–cost ratio of 1.19. The results provide methodological and data support for grey and green in-frastructure retrofitting within the context of sponge cities.

Antimicrobial peptides (AMPs) are a promising alternative to antibiotics to combat drug resistance in pathogenic bacteria. However, the development of AMPs with high potency and specificity remains a challenge, and new tools to evaluate antimicrobial activity are needed to accelerate the discovery process. As a step toward direct prediction of the experimental minimum inhibitory concentration (MIC) of AMPs, we proposed MBC-Attention, a combination of a multi-branch CNN architecture and attention mechanism. Using a curated dataset of 3929 AMP against Escherichia coli, the optimal MBC-Attention model achieved an average Pearson correlation coefficient of 0.775 and an RMSE of 0.533 (log μM) in three independent tests of 393 sequences each. This results in a 5–12% improvement in PCC and 7–13% improvement in RMSE compared with RF and SVM models. Ablation studies confirmed that both attention mechanisms contributed to performance improvement.

Energy poverty, defined as a lack of access to reliable electricity and reliance on traditional biomass resources for cooking, affects over a billion people daily. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS). Increasing demand for energy has led to dramatic increases in carbon emissions. The need for reliable electricity and limiting carbon emissions drives research on Resil-ient Hybrid Energy Systems (RHES) that provide low-carbon energy through combined wind, so-lar, and biomass energy with traditional fossil energy, increasing production efficiency and relia-bility, and reducing generating costs and carbon emissions. Microgrids have been shown as an ef-ficient means of implementing RHES, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing and ap-plying microgrids involve conducting a cradle-to-grave life cycle assessment (LCA) to evaluate these systems' environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES has been developed and used to demonstrate implementation in rural applications. This system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. This paper's primary focus is the challenges of using resilient energy sys-tems in the Middle East.

Surimi-based products occupy an important position in the aquatic product processing industry. To enhance the quality and flavor of surimi-based products, the effects of pre-emulsified safflower seed oil on the texture, water-holding capacity (WHC), microstructure, and flavor of Nemipterus virgatus surimi gel was evaluated. The texture and whiteness of gel were improved, and the WHC increased (P &lt; 0.05) as the content of safflower seed oil increased up to 2 mL per 100 g surimi. Furthermore, the drops of pre-emulsified safflower seed oils with an average diameter of less than 0.10 μm were evenly distributed in gel matrix. Microstructure and infrared spectroscopy analyses indicated that low-content pre-emulsified safflower seed oil acted as filler particles to occupy void spaces, resulting in gel exhibiting a dense network structure. Volatile analysis showed the gel containing pre-emulsified oil enriched volatile compounds, mainly resulting from oxidation and decomposition of oils by the activation of lipoxygenase, which synergistically contributes to unique flavors of gel. Consequently, low-content pre-emulsified safflower seed oil can used to enhance the quality and flavor of N. virgatus surimi-based products. These findings are especially relevant to the current growing interest in low-fat and high-protein diets.

To explore the spatial network structure characteristics and driving effects of carbon emission intensity in China's construction industry, the investigation combined the modified gravity model and social network analysis method to deeply analyze the spatially associated network structure characteristics and driving effects of carbon emission intensity in China's construction industry, based on the measurement of carbon emission data of China's construction industry from 2006 to 2017. The results show that the regional differences of carbon emission of construction industry are significant, and the carbon emission intensity of construction industry show a fluctuation trend. The overall network of carbon emission intensity shows an obvious “core-edge” state, the hierarchical network structure is gradually broken. Economically developed provinces generally play a leading role in the network, and play an intermediary role to guide other provinces to develop together with them. Among the network blocks, most of the blocks play the role of “brokers”. The block with the leading economic development has a strong influence on the other blocks. The increase of network density, the decrease of network hierarchy and network efficiency will reduce the construction carbon emission intensity.

Peri-implantitis occurs at a significant rate, which is the leading cause of implant failure. The main reason for this unwanted complication is bacterial invasion and biofilm formation. To reduce the incidence of peri-implantitis, we constructed a carboxymethyl dextran (CMD) based nanomicelles antibacterial coating on microarc-oxidized titanium (MAO-Ti) surface. After cross-linking, the drug-loaded nanomicelles were spherical with a particle size of 130nm and uniformly dispersed. Zeta potential was negative, and the absolute value was greater than 10 mV, effectively avoiding micelles aggregation. It was observed by dynamic light scattering (DLS) that the stability of nanomicelles was significantly improved after cross-linking. The hemolysis rate of micelles was less than 5%, and the overall survival rate of human umbilical vein endothelial cells was more than 90%. After being coated on MAO-Ti surface, the cumulative drug release rate of drug-loaded nanomicelles reached 86.6% after 360 hours. Fluorescence staining of immobilized bacteria showed more dead bacteria on the coating surface, and the number of live bacteria was significantly reduced. It was concluded that dextran-based nanomicelles, which showed long-term drug release properties and excellent biocompatibility, are potential drug carriers for fabricating antibacterial coating on titanium surfaces.

Panchromatic (PAN) images contain abundant spatial information that is useful for earth observation, but always suffer from low-resolution due to the sensor limitation and large-scale view field. The current super-resolution (SR) methods based on traditional attention mechanism have shown remarkable advantages but remain imperfect to reconstruct the edge details of SR images. To address this problem, an improved super-resolution model which involves the self-attention augmented WGAN is designed to dig out the reference information among multiple features for detail enhancement. We use an encoder-decoder network followed by a fully convolutional network (FCN) as the backbone to extract multi-scale features and reconstruct the HR results. To exploit the relevance between multi-layer feature maps, we first integrate a convolutional block attention module (CBAM) into each skip-connection of the encoder-decoder subnet, generating weighted maps to enhance both channel-wise and spatial-wise feature representation automatically. Besides, considering that the HR results and LR inputs are highly similar in structure, yet cannot be fully reflected in traditional attention mechanism, we therefore design a self augmented attention (SAA) module, where the attention weights are produced dynamically via a similarity function between hidden features, this design allows the network to flexibly adjust the fraction relevance among multi-layer features and keep the long-range inter information, which is helpful to preserve details. In addition, the pixel-wise loss is combined with perceptual and gradient loss to achieve comprehensive supervision. Experiments on benchmark datasets demonstrate that the proposed method outperforms other SR methods in terms of both objective evaluation and visual effect.

Wireless Sensor Networks (WSNs) has the characteristics of large-scale deployment, flexible networking, and wide application. It is an important part of the wireless communication networks. However, due to limited energy supply, the development of WSN is greatly restricted. Wireless Rechargeable Sensor Networks (WRSNs) transform the distributed energy around the environment into usable electricity through energy collection technology. In this work, a joint optimization strategy is proposed to improve the energy management efficiency for WRSNs. The joint optimization strategy is divided into two phases. In the first phase, we design an Annulus Virtual Force based Particle Swarm Optimization (AVFPSO) algorithm for area coverage planing. It adopts the multi-parameter joint optimization method to improve the efficiency of the algorithm. In the second phase, a Queuing Game-based Energy Supply (QGES) algorithm is designed for energy scheduling. It converts energy supply and consumption into network service. By solving the game equilibrium of the model, the optimal energy distribution strategy can be obtained. The simulation results show that our scheme improves the efficiency of coverage and energy, and extends the lifetime of WSN.

Background: The reported associations between time to first antibiotic dose after hospital arrival and short-term mortality have varied in prior studies of CAP. It is unclear the benefit of early antibiotics in all patients given the risks of antibiotic overuse and misdiagnosis; Methods: A PubMed and Google Scholar search was performed to identify articles detailing the epidemiology, prognosis, diagnosis, and preliminary management of CAP; Results: In sepsis, antibiotics should not be delayed, and should be administered as soon as possible after recognition. For moderate or severe CAP patients without sepsis, antibiotics should be administered as soon as the diagnosis of CAP is highly likely. For stable, non–critically ill patients with CAP, the timing of antibiotics is not as clear and available evidence does not recommend strict requirements. Antibiotic timing – both rapid and delayed could be used as indicators of quality care in differing clinical scenarios; Results: The dogma of starting antibiotics quickly, within a rigid timeframe of expectations and guidelines has not improved outcomes in pneumonia patients, and has led to an increase in antibiotic treatment in uninfected patients. Severity of illness is the key factor associated with poor outcomes and should more significantly guide the timing of antibiotic initiation.

The Double Random Phase Encoding (DRPE) image encryption method has garnered significant attention in color image processing and optical encryption, thanks to its parallel encryption of R, G, B. However, DRPE-based color image encryption faces two challenges. Firstly, it disregards the correlation of R, G, and B, compromising the encrypted image's robustness. Secondly, DRPE schemes relying on Discrete Fourier Transform (DFT) and Discrete Fractional Fourier Transform (DFRFT) are vulnerable to linear attacks, such as Known Plaintext Attack (KPA) and Chosen Plaintext Attack (CPA). Quantum walk stands out as a remarkable tool for designing modern cryptographic mechanisms, offering resistance to potential attacks from both classical and quantum computers.Therefore, this study presents an optical color image encryption algorithm that combines two-dimensional quantum walk with 24-bit plane permutation, dubbed OCT. This approach employs pseudo-random numbers generated by Two-Dimensional Quantum Walking (TDQW) for phase modulation in DRPE and scrambles the encrypted image's real and imaginary parts using the Generalized Arnold Transform. The 24-bit plane permutation helps reduce correlation of the R, G, B, while the Generalized Arnold Transform bolsters DRPE's resistance to linear attacks. By incorporating TDQW, the key space is significantly expanded. Experimental results validate the effectiveness and security of proposed method.

To meet the International Maritime Organization’s requirements for carbon dioxide emissions from ships, a cost-effective and practical ship decarbonization tower was autonomously designed based on the marine diesel engine model 6135G128ZCa. The tower is internally filled with structured packing, and a slot-type liquid distributor at the top of the packing evenly distributes the NaOH solution to absorb carbon dioxide from the ship’s exhaust gas. Experimental research was conducted to investigate the influence of factors such as liquid-to-gas ratio and NaOH concentration on the performance of the decarbonization tower. The results confirmed that the use of NaOH solution can effectively absorb CO2 from ship exhaust gas, reducing CO2 emissions by more than 81.59% and meeting the EEDI (Energy Efficiency Design Index) requirements specified by the IMO.

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

Transition delaying is of great importance for the drag and heat flux reduction of hypersonic flight vehicles. The first mode within low frequency and the second mode within high frequency exist simultaneously during the transition of hypersonic boundary layer. This paper proposes a novel bi-frequency synthetic jet to suppress low- and high-frequency disturbances at the same time. Orthogonal table and variance analysis are used to compare the control effects of jet with different frequencies, amplitudes and positions. Linear stability analysis results show that, low frequency synthetic jet can suppress the first mode when it is arranged upstream of synchronization point, while the second mode control effect is relatively weak. The higher the high frequency is, the stronger the suppression effect is on the first mode. For the second mode, the suppression effect is only at f2=89.09kHz. The larger the amplitude, the weaker the promoting effect for the first mode and the second mode, and the more obvious the suppressing effect. For the cases with synthetic jet downstream of synchronization point, all levels of the three parameters promote the unstable mode. In terms of the growth rate with the spanwise wave number, the control effect of the same factor and level under different spanwise wave number is different. In order to obtain the optimal control effect on transition, the three factors and the arrangement position of the synthetic jet should be selected as follows: the position is arranged in the upstream, with f1 = 17.82kHz, f2 = 89.9kHz, a =0.007, so that the maximum growth rate of the first mode is reduced by 9.06% and that of the second mode is reduced by 1.28% compared with the uncontrolled state.

Tourism sustainability is a significant approach to forming a synergistic model of industry and ecology in ecologically vulnerable areas. Scientifically detecting the effect mechanism of tourism development (TDI) on eco-environment resilience (ERI) is important in achieving regional social-ecological system sustainability. Empirical exploration is conducted on the levels of TDI and ERI in the Yangtze River Economic Belt (YREB) to study the spatiotemporal heterogeneity of TDI's effect on ERI. The results indicate a significant growth in TDI in the YREB, with the formation of tourist clusters around Shanghai and Chongqing as the core. Although ERI typically exhibits a declining trend, the rate of decline has notably slowed, forming a "high at the sides and low in the middle" spatial pattern. TDI and ERI are spatially dependent in the YREB, with predominantly high-high (HH) and low-high (LH) clusters in Shanghai, Zhejiang, and Jiangsu. Conversely, upstream regions with strong eco-environmental foundations exhibit low-low (LL) and high-low (HL) clusters. In general, TDI promotes ERI, but there is significant spatiotemporal heterogeneity in the YREB. Positive impact regions are expanding, while negative impact regions are shrinking. These results could provide scientific evidence for differentiated classification and control policies in the YREB.

The problem of health status prediction of insulated-gate bipolar transistors (IGBTs) gains a lot of attention in the field of health management of power electronic equipment. The performance degradation of IGBT gate oxide layer is one of the important failure modes. In view of failure mechanism analysis and easy implementation of monitoring circuit, this paper selects the gate leakage current of IGBT as the precursor parameter of gate oxide degradation, and uses time domain characteristic analysis, gray correlation degree, Mahalanobis distance, Kalman filter and other methods to carry out feature selection and fusion, and finally obtains a health indicator characterizing the degradation of IGBT gate oxide. Based on the Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) network, this paper constructs an IGBT gate oxide degradation prediction model, and performs experimental analysis on the dataset released by NASA-Ames Laboratory, and the average absolute error of performance degradation prediction is as low as 0.0216. Compared with Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Support Vector Regression (SVR) and CNN-LSTM models, CNN-LSTM network has the highest prediction accuracy. These results show the feasibility of gate leakage current as a precursor parameter of IGBT gate oxide layer failure, as well as the accuracy and reliability of the CNN-LSTM prediction model.

Fake news detection has become a significant topic based on the fast-spreading and detrimental effects of such news. Many methods based on deep neural networks learn clues from claim content and message propagation structure or temporal information, which have been widely recognized. However, such models (i) ignore the fact that information quality is uneven in propagation, which makes semantic representations unreliable. (ii) Most models do not fully leverage spatial and temporal structure in combination. (iii) Finally, internal decision-making processes and results are non-transparent and unexplained. In this study, we develop a trust-aware evidence reasoning and spatiotemporal feature aggregation model for more interpretable and accurate fake news detection. Specifically, we first design a trust-aware evidence reasoning module to calculate the credibility of posts based on a random walk model to discover high-quality evidence. Next, from the perspective of spatiotemporal structure, we design an evidence-representation module to capture the semantic interactions granularly and enhance the reliable representation of evidence. Finally, a two-layer capsule network is designed to aggregate the implicit bias in evidence while capturing the false portions of source information in a transparent and interpretable manner. Extensive experiments on two benchmark datasets indicate that the proposed model can provide explanations for fake news detection results, as well as can achieve better performance, boosting 3.5% in F1-score on average.

The liquid droplet cooling technique for fast scanning chip calorimetry (FSC) is introduced, increasing the cooling rate for large samples on a given sensor. Reaching higher cooling rates and using a gas as the cooling medium, the common standard for ultra-fast temperature control in cooling, requires reducing the lateral dimensions of the sample and sensor. The maximum cooling rate is limited by the heat capacity of the sample and the heat exchange between the gas and the sample. The enhanced cooling performance of the new liquid droplet cooling technique is demonstrated for both metals and polymers, on examples of solidification of large samples of indium, high-density polyethylene (HDPE), and poly (butylene 2,6-naphthalate) (PBN). It was found that the maximum cooling rate can be increased up to 5 MK/s in room temperature environment, that is, by 2 orders of magnitude, compared to standard gas cooling. Furthermore, modifying the droplet size and using coolants at different temperatures provide options to adjust the cooling rate in the temperature ranges of interest.

The issue of measurement reliability is certainly undervalued in the local agricultural marketplace organization. Besides, there was nothing identified concerning the extent of cereal commodity trade measurement cost. Hence, this paper aimed to estimate the magnitude of cereals trade quantity measurement cost caused by instrument error and unreliability; mainly by targeting the local marketplace in Ethiopia. The survey was conducted in six different districts’ marketplaces (n = 602) of Oromia region by employing administered structured questionnaires and site mass measurement calibration. The gathered data were analyzed using independent samples t-test, one sample t-test, and analysis of variance. According to the findings, the actual value measurement means of the quantity of most local units of the farmers were greater than small traders. The independent t-test result indicated that the average values of the quantity of the majority of units of measurement between farmers and small traders were varied significantly. Estimated measuring instruments’ error and unreliability associated average measurement cost of one-day market transaction over total cereals marketed amount were higher comparatively for a sack, bowl, and glass units. This study demonstrates that homogeneity in measurement, policy, and institutions that aid cereals trade would have an indispensable role to reduce measurement costs and ensure equitable exchange.

This study explores the dependence of drone acoustic detection systems performance on distance, using learning machines with different complexities, from simple linear discriminants, to deep neural networks, such as YAMNet, which exploits transfer learning. Other machine learning systems studied are the multilayer perceptron, support vector machines and random forest. These methods have been evaluated with a meticulously selected database that includes a wide variety of drone and interference sounds, previously processed by array signal processing and affected by ambient noise. Two strategies for training learning machines are considered. In the first one, they are trained with unattenuated signals, trying to preserve the information generated by the sound sources, but they are tested considering the attenuation with distance, achieving effective detection at distances up to 200 metres with some methods, especially linear discriminant. In all cases, the existence of interferences that hinder detection is considered. In the second strategy, the systems are trained and tested with attenuated signals as a function of distance. The effective detection range increases up to 300 metres for most methods and up to 500 metres for the YAMNet based detector. In addition, this second approach raises the possibility of developing specialised detectors for each distance range, thus significantly extending the effective detection range. These results underline the promising potential of acoustic detection of drones at various distances, encouraging further exploration in this research area.

In our article in Genome Biology Ecology six years ago, one complete plastid genome of Belian was assembled for comparative analyses of the plastomes in Lauraceae. However, Ariati et al. (2023) concluded that our sequenced Belian individual could be located in the clade of Myristicaceae instead of that of Lauraceae. Here, we performed re-analyses of additional two Belian plastomes, along with 42 plastomes from plants spanning ten families of the Magnoliids. The plastomes of the three Belian individuals range from 157,535 to 157,577 bp in length. Comparative genomic analysis revealed 170 mutation sites in their plastomes, which include 111 substitutions, 53 indels, and six microinversions. Phylogeny was reconstructed using maximum likelihood and Bayesian approaches for 44 magnoliids species indicated that our three Belian individuals are nested among the species in the family Lauraceae rather than Myristicaceae.

With the global outbreak of COVID-19, the panic buying incidents triggered by the variants of the Omicron strain have severely affected the normal social order. This paper considers the complex interest game and interactive relationship among multiple subjects in the mass panic buying event caused by rumors and constructs a three-party evolution game model of local government, rumor-monger, and public. Based on the theory of evolution game, the evolutionary process of the strategy selection of game subjects is studied, and the strategy selection of the three-game subjects under different scenarios is compared and analyzed. Taking the example of the montmorillonite powder panic buying caused by the XBB virus strain rumor in China, the evolutionary game model constructed in this study is simulated and analyzed. The study shows that: the evolution process of the mass panic buying event is characterized by six stages: the initial stage E1(0,0,0); the outbreak stage E3(0,1,0);the spread stage E7(0,1,1);the climax stage E8(1,1,1);the relief stage E5(1,1,0);and the recovery stage E4(1,0,0); there are four stable points in the evolutionary game of the three game subjects, namely (no intervention, no rumor, no panic buying), (no intervention, rumor, no panic buying), (intervention, no rumor, no panic buying), and (intervention, rumor, no panic buying), and the strategy of government intervention will be adjusted according to the strategy selection of the public and the rumor-monger; under the mechanism of reward and punishment of the higher-level government, increasing the punishment and reward intensity of the higher-level government will promote the local government to intervene in the rumor-mongering event faster, but increasing the reward intensity has a more significant impact on the intervention behavior of the local government than punishment, and increasing punishment intensity has a more significant impact on the non-rumor-mongering behavior of the rumor-monger than reward; the parameters of social risk-bearing cost, risk transmission coefficient, rumor-mongering income and cost, and public drug purchase cost have different degrees of influence on the evolutionary behavior of game subjects. This study provides new ideas for effectively responding to mass panic buying events in the context of public emergencies.

Chemical safety is related to public health, safety and environmental concerns, and the dangerous chemicals safety problem is becoming the one that people commonly pay attention to. Strengthening chemical safety supervision not only involves safe production, but also is an important link to maintain social safety. Most related studies focus on chemical safety under normal regulation, this paper addresses the perspective of ‘special rectification’ and ‘normal regulation’, and establishes an evolutionary game model between chemical enterprises and government supervision departments under different supervision modes. Based on the evolutionary game theory, this paper studies the evolution process of the two game players' strategy choices, and compares and analyzes the evolution, stability and equilibrium between the chemical safety and the behavior strategies of government regulatory departments. The model is effectively analyzed based on numerical simulation, and the results show that: Under the ‘special rectification’ mode, the strategic choice of chemical enterprises engaging in safety without investment depends on the difference between the benefits and costs of safety without investment; In the ‘normal regulation’ mode, the choice of its safety non-investment strategy depends on the difference between the cost of engaging in safety investment and the cost of safety non-investment; Increasing the government's punishment will encourage chemical enterprises to take safety investment behavior under the two supervision modes. Increasing the punishment has a significant impact on the safety investment behavior of chemical enterprises under the ‘normal regulation’ mode, but it has no significant impact on the behavior of chemical enterprises under the ‘special rectification’ mode. At the same time, increasing the punishment will inhibit the strict supervision behavior of the government. The research conclusion provides important decision support for government departments to effectively supervise the safety production of chemical enterprises.

Osteosarcoma (OSA) is the most common primary malignant bone tumor. More than 40% of patients with OSA have poor prognoses. We aimed to discover a biomarker for patient stratification and therapeutic targets for these high-risk patients. Using Single Sample Gene Set Enrichment Analysis (ssGSEA) and univariate Cox analysis, six hallmarks were identified as significant prognostic factors for overall survival (OS). Three were selected to construct a multivariate Cox model. Then, WGCNA, univariate Cox regression, Kaplan-Meier (KM) survival analyses, and multivariate Cox analyses were combined to filter promising candidates and establish a seven-gene signature to predict OS, whose prognostic value was validated internally and externally. Subsequently, Differential Expression Analysis was conducted between high- and low-risk patients, and the Robust Rank Aggregation algorithm was used to determine the robust DEGs. Metascape was used to perform pathway and process enrichment analyses as well as construct protein-protein interaction (PPI) networks. Finally, RPS28 was identified as an independent risk factor by using univariate and multivariate Cox regression, which was preliminarily validated as a promising therapeutic target by using RNA interference. In conclusion, we might contribute to optimizing risk stratification and an excellent therapeutic target for high-risk patients with OSA.

Background Reliable and field-applicable diagnosis of schistosome infections in non-human animals is important for surveillance, control, and verification of interruption of human schistosomiasis transmission. This study aimed to summarize uses of available diagnostic techniques through a systematic review and meta-analysis. Methods and principal findings We systematically searched the literature and reports comparing two or more diagnostic tests in non-human animals for schistosome infection. Out of 4,909 articles and reports screened, 18 met our inclusion criteria, four of which were considered in the meta-analysis. A total of 14 techniques (parasitologic, immunologic, and molecular) and nine types of non-human animals were involved in the studies. Notably, four studies compared parasitologic tests (miracidium hatching test (MHT), Kato-Katz (KK), the Danish Bilharziasis Laboratory technique (DBL), and formalin-ethyl acetate sedimentation-digestion (FED-SD)) with quantitative polymerase chain reaction (qPCR), and sensitivity estimates (using qPCR as the reference) were extracted and included in the meta-analyses, showing significant heterogeneity across studies and animals hosts. The pooled estimate of sensitivity was 0.21 (95% confidence interval (CI): 0.03 – 0.48) with FED-SD showing highest sensitivity (0.89, 95% CI: 0.65 – 1.00). Conclusions and significance Our findings suggest that the parasitologic technique FEA-SD and the molecular technique, qPCR, are the most promising field-applicable techniques for schistosome diagnosis in non-human animal hosts. Future studies are needed for validation and standardization of the techniques for real-world field applications.

The homeostasis of cellular calcium is fundamental for many physiological activities, while calcium levels maintain inhomogeneous within cells. During the onset of asthma, epithelial and inflammatory cells secrete platelet derived growth factor (PDGF), inducing proliferation and migration of airway smooth muscle (ASM) to the epidermal layer, narrowing the airway. The regulation of ASM cells by PDGF is closely related to the conduction of calcium signals. In this work, we generated subcellular-targeted FRET biosensors to investigate calcium regulations at different compartments of ASM cells. PDGF-induced cytoplasmic calcium [Ca2+]C increase was attributed from both extracellular calcium influx and endoplasmic reticulum (ER) calcium [Ca2+]ER release, which was partially regulated by PLC-IP3R pathway. Interestingly, removal of extracellular calcium influx led to inhibited ER calcium release, likely through inhibitory effect on calcium-dependent activation of ER ryanodine receptor. Inhibition of L-type calcium channel on plasma membrane, or SERCA pump on ER resulted in both reduced [Ca2+]C and [Ca2+]ER from PDGF stimulation, while IP3R channel inhibition led to reduced [Ca2+]C only. Inhibited SERCA pump caused immediate [Ca2+]C increase and [Ca2+]ER decrease, indicating an active calcium exchange between cytosol and ER storage in resting cells. PDGF-induced calcium at outer mitochondrial membrane sub-region showed similar regulatory response to cytosolic calcium, not influenced by inhibition of mitochondrial calcium uniporter channel. Therefore, our work identified calcium flow pathways among extracellular medium, cell cytosol, and ER by regulatory calcium channels. Particularly, extracellular calcium flow has an essential function to fully activate ER calcium release.