This paper presents a hybrid probability distribution known as the FCD, which is based on the hazard functions of the Fréchet and Chen distributions. A notable characteristic of the FCD is its ability to model monotonic (increasing and decreasing) and non-monotonic (bathtub-shaped) behaviors, commonly linked to electrical and electronic device failure times in reliability analysis. The paper explores the statistical properties relevant to the reliability analysis of these devices. It proposes a Maximum Likelihood Estimator (MLE) and Bayesian Analysis equations for estimating the parameters of the FCD. Three case studies of electronic device lifetimes with varying behaviors were analyzed to validate the proposed methodology. The FCD was compared to other distributions with similar characteristics, and the results from each case study demonstrated that the proposed distribution yields competitive outcomes, closely reflecting the behavior of the devices analyzed, making it a valuable option for reliability engineering practitioners in warranty and maintenance time evaluations

Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut yield and quality, and accurate prediction models are urgently needed for timely disease management. In this study, we proposed a novel peanut leaf spot prediction method based on an improved long short-term memory (LSTM) model and multi-year meteorological data combined with disease survey records. Our method employed a combination of convolutional neural network (CNN) and LSTM to capture spatial-temporal patterns from the data and improve the model ability to recognize dynamic features of the disease. In addition, we introduced an attention mechanism module to enhance model performance by focusing on key features. Through several hyper-parameter optimization adjustments, we identified a peanut leaf spot disease condition index prediction model with a learning rate of 0.001, a number of cycles (Epochs) of 800, and an optimizer of Adma. The results showed that the integrated model demonstrated excellent prediction ability, obtaining an RMSE of 0.063 and an R2 of 0.951, which reduced the RMSE by 0.253 and 0.204, and raised the R2 by 0.155 and 0.122, respectively, compared to the single CNN and LSTM. Predicting the incidence and severity of peanut leaf spot disease based on the meteorological conditions and neural networks is feasible and valuable to help growers made accurate management decisions and reduced disease impacts through optimal fungicide application timing.

Grapes are a globally popular fruit, with grape cultivation worldwide being second only to citrus. This article focuses on the low efficiency and accuracy of traditional manual grading of red grape external appearance and proposes a small-sample red grape external appearance grading model based on transfer learning with convolutional neural networks (CNNs). Initially, the CNN transfer learning method was used to transfer the pre-trained AlexNet, VGG16, GoogleNet, InceptionV3, and ResNet50 network models on the ImageNet image dataset to the red grape image grading task. By comparing the classification performance of the CNN models of these five different network depths with fine-tuning, ResNet50 with a learning rate of 0.001 and a loop number of 10 was determined to be the best feature extractor for red grape images. Moreover, given the small number of red grape image samples in this study, different convolutional layer features output by the ResNet50 feature extractor were analyzed layer by layer to determine the effect of deep features extracted by each convolutional layer on SVM classification performance. This analysis helped to obtain a ResNet50+SVM red grape external appearance grading model based on the optimal ResNet50 feature extraction strategy. Experimental data showed that the classification model constructed using the feature parameters extracted from the 10th node of the ResNet50 network achieved an accuracy rate of 95.08% for red grape grading. These research results provide a reference for the online grading of red grape clusters based on external appearance quality and have certain guiding significance for the quality and efficiency of grape industry circulation and production.

Background: this study aimed to describe the distribution of the genotype and allele frequencies of GJB2 variants in the Chinese population of the Dongfeng Tongji cohort and to analyze the features of the hearing phenotype. Methods: we used data from 9910 participants in the Dongfeng Tongji cohort in 2013 and selected nine GJB2 variants. Pure-tone audiometry was employed to measure hearing. Differences in genotype and allele frequencies were analyzed by chi-squared test or Fisher's exact test. Results: of the 9910 participants, 5742 had hearing loss. The genotype frequency of the GJB2 variant p.V37I was statistically significantly distributed between the normal and impaired hearing groups, but not for the variant c.235delC. A higher frequency of the p.V37I homozygous genotype was found in the hearing loss group (0.5%) than in the normal hearing group (0.1%). Patients with p.V37I and c.235delC homozygous mutations exhibited varying degrees of hearing loss, mainly presenting sloping and flat audiogram shapes. Conclusions: a significant difference was found in the genotype frequency of the GJB2 variant p.V37I between the case and control groups, but not for the variant c.235delC. Different degrees of hearing loss and various audiogram shapes were observed in patients with p.V37I and c.235delC homozygous mutations.

Glycoside Hydrolase 3 (GH3) is a phytohormone-responsive family of genes that has been found in many plant species. It is implicated in the biological activity of indolacetic (IAA) and jasmonic acids (JA), and also affects plant growth and developmental processes and some stresses. In this study, GH3 genes were identified in 48 plants, which belong to algae, moss, fern, gymnosperm and angiosperm. No GH3 representative gene has been found in algae, and our research identified 4 genes in mosses, 19 in ferns, 7 in gymnosperms, and numerous in Angiosperms. The results showed that GH3 genes mainly occur in seed plants. Phylogenetic analysis of all GH3 genes showed three separate clades. Group I was related to JA adenylation, group II was related to IAA adenylation, and group III was separated from group II but the function was not clear. The structure of GH3 protein indicated highly conserved sequence in the plant kingdom. The analysis of JA-adenylation related to gene expression of GH3 in potato (Solanum tuberosum) showed that StGH3.12 highly responded to Methyl Jasmonate (MeJA) treatment. Expression levels of StGH3.1, StGH3.11, and StGH3.12 were high in flower and StGH3.11 expression was also high in stolon. Our research revealed the evolution of the GH3 family, which is useful for studying the precise function about JA-adenylation GH3 genes in S. tuberosum under development and biotic stresses.

The cellulose/GO networks as the scaffold of free-standing aerogel electrodes are developed by using lithium bromide aqueous solution as the solvent to ensure the complete dissolution of cotton linter pulp and well dispersion/reduction of GO nanosheets. PANI nanoclusters are then coated onto cellulose/GO networks via in-situ polymerization of aniline monomers. By optimized weight ratio of GO and PANI, the ternary cellulose/GO3.5/PANI aerogel film exhibits well-defined three-dimensional porous structures and high conductivity of 1.15 S/cm that contributes to its high areal specific capacitance of 1218 mF/cm2 at the current density of 1.0 mA/cm2. Utilizing this cellulose/GO3.5/PANI aerogel film as electrodes in a symmetric configuration supercapacitor can result in an outstanding energy density as high as 258.2 μWh/cm2 at a power density of 1201.4 μW/cm2. Moreover, the device can maintain nearly constant capacitance under different bending deformations, suggesting its promising applications in flexible electronics.

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

We give a simple proof of the Chen inequality for the Chen invariant $\underbrace{\delta (2,...,2)}_{k\mbox{ terms}}$ of submanifolds in Riemannian space forms.

Based on panel data of 31 provincial-level administrative units (excluding Hong Kong, Macao and Taiwan) in China from 2015 to 2019, using fixed effect model and mediation effect model, this paper makes an empirical analysis on the interaction among digital economy, industrial structure upgrade and high-quality economic development. The results show that, from the overall effect, the digital economy can significantly promote the high-quality development of the economy, and there are regular regional differences, and the relationship between the promotion intensity and the development level of the digital economy is proportional. From the mediation effect, in the relationship between digital economy and high-quality economic development, the upgrade of industrial structure has played a significant part of the mediation effect, the proportion of mediation effect is 25.17% . In addition, the mediation effect of industrial structure upgrade has obvious regional difference, the western area is the strongest, the eastern area is the second, the central area is the weakest. Based on the above research,the concrete policy suggestions are given to promote the development of digital economy and upgrade the level of industrial structure to promote the high-quality development of economy.

The Chen circuit system, a three-dimensional autonomous system with intriguing dynamics, has gained considerable attention due to its potential applications in diverse scientific fields. In this article, a Chen circuit-like system is defined and a comprehensive dynamics has been studied. The system exhibits chaotic dynamics, limit cycles, and bifurcations, making it a captivating subject of study. By employing numerical simulations and analytical techniques, we explore the system's stability and identify critical parameter values leading to qualitative changes. Notably, we delve Hopf bifurcations, which give rise to stability changes and the emergence of limit cycles. Furthermore, we analyze the fractal dimension of the system's attractor, providing insights into its complexity and self-similarity. Through a systematic examination of the Chen circuit-like system, we deepen our understanding of its intricate dynamics and offer valuable insights into the underlying mechanisms. The findings contribute to the field of dynamical systems and hold potential implications in areas such as chaos-based secure communications, signal processing, and nonlinear control. This work serves as a valuable reference for researchers and practitioners interested in the dynamics and bifurcation analysis of nonlinear systems.

Biomimetic delivery systems (BDSs), inspired by the intricate designs of biological systems, have emerged as a groundbreaking paradigm in nanomedicine, offering unparalleled advantages in therapeutic delivery. These systems, encompassing platforms such as liposomes, protein-based nanoparticles, extracellular vesicles, and polysaccharides, are lauded for their targeted delivery, minimized side effects, and enhanced therapeutic outcomes. However, the translation of BDSs from research settings to clinical applications is fraught with challenges, including reproducibility concerns, physiological stability, and rigorous efficacy and safety evaluations. Furthermore, the innovative nature of BDSs demands a reevaluation and evolution of existing regulatory and ethical frameworks. This review provides an overview of BDSs, delve into the multifaceted translational challenges and present emerging solutions, underscored by real-world case studies. Emphasizing the potential of BDSs to redefine healthcare, we advocate for sustained interdisciplinary collaboration and research. As our understanding of biological systems deepens, the future of BDSs in clinical translation appears promising, with a focus on personalized medicine and refined patient-specific delivery systems.

The world is facing an unprecedented socio-economic crisis caused by the novel coronavirus infection (COVID-19). It is also spreading through the import and export food supply chains. The Chinese authorities have discovered the COVID-19 virus in various imported frozen meat packages. Traceability plays a vital role in food quality and food safety. The Internet of Things (IoT) provides solutions to keep an eye on environmental conditions, product quality, and product traceability. These solutions are traditionally based on the centralized architecture, which does not guarantee tamper-proof data sharing. The blockchain is an emerging technology that provides tamper-proof data sharing in real-time. This article presents Hyperledger Fabric-based blockchain use case and a quick reference guide to develop the blockchain network for tracking and tracing the supply chain to minimize the risk of COVID-19 in the frozen meat supply chain.

Factory safety inspections are crucial for ensuring safe production. However, manual inspections present issues such as low efficiency and high workload. Inspection robots provide an efficient and reliable solution for completing patrol tasks. The development of robot localization and path planning technologies provides guarantees for factory inspection robots to autonomously complete inspection tasks in complex environments. This paper studies mapping and localization, as well as path planning methods for robots in order to meet the application requirements of factory inspections. Two SLAM application systems based on multiple-line laser radar and vision are designed for different scenarios in consideration of the limitations of cameras and laser sensors in terms of their own characteristics and applicability in different environments. To address the issue of low efficiency in inspection tasks, a hybrid path planning algorithm that integrates the A-star algorithm and time elasticity band algorithm is proposed. This algorithm effectively solves the problem of path planning in complex environments that is prone to falling into local optimal solutions, thereby improving the inspection efficiency of robots. Experimental tests show that the designed SLAM and path planning methods can meet the needs of robot inspection in complex scenes and have good reliability and stability. The code used in this article is open source and can be accessed at https://github.com/Mxiii99/RSPP_CS.git.

Rice is the grain feeds more than half of the world population. It is an important staple food provides twenty percent of the calories consumed worldwide. Food safety affects the health of consumers. Establishing an effective traceability system is one of the primary measures to protect rice quality and food safety. Blockchain-based traceability system has the characteristics of data tamper-proofing, decentralization, and co-governance. This paper proposed a rice traceability scheme based on blockchain technology that selects the critical nodes in the rice industry chain to construct a blockchain network to achieve transparent data sharing. It is meaningful for both enterprises and consumers. It can let enterprises get the real quality information of rice and related raw materials. Consumers can get the true information of rice and rice products to buy safe and healthy food. The scheme is proved feasible by simulating the traceability of the rice supply chain.

Mineral identification is an important part of geological analysis. Traditional identification methods rely on either the experiences of the appraisers or the various measuring instruments and the methods are either easily influenced by the experiences or need too much work. To solve the above problems, there have been studies using image recognition and intelligent algorithms to identify minerals. But the current studies can not identify many minerals, and the accuracy is low. To increase the number of identified mineral categories and the accuracy, we proposed the method that uses both the mineral images and the Mohs hardness in the deep neural networks to identify the minerals. The experimental results showed that the method can reach 94.0% Top-1 accuracy and 99.9% Top-5 accuracy for 28 common minerals. The model that combines image and Mohs hardness together can identify more minerals and increase the accuracy using less training data.

A novel physiologically based algorithm (PBA) for fast CFD computation of Flow Fractional Reserve (FFR) in Coronary Artery Trees (CATs) is proposed and developed, which, unlike traditional methods, is based on the extension of the Murray’s law for blood vessels at the outlets and extra inlet conditions prescribed alternatively and iteratively. The PBA is then implemented in both SimVascular and Ansys CFD for testing and validation. For validation purpose, 3D models of CATs are built by using their CT images and computational meshes generated for mesh convergence study. Results obtained are then compared with Invasive Coronary Angiographic (ICA) data for validation and evaluation of its accuracy and computational efficiency. It is found that discrepancies between experimental and calculated values of pressure and flow rate at the inlet were less than 0.1% at the end of the 10^th round of iteration or less. Further validation shows that the difference between estimated and experimental FFR agree with each other with a maximum difference of 1.62% after convergence is achieved. The PBA is found to be a robust patient-specific and physiologically sound method that can be a good alternative to the existing Lumped Parameter Model (LPM) which is based on empirical scaling correlations using limited population-averaged data and requires nonlinear iterative computation for convergence.

Image encryption is increasingly becoming an important area of research in information security and network communications, as digital images are widely used in various applications and are vulnerable to various types of attacks. In this research work, a color image cryptosystem that is based on a 3-layer permutation-substitution network (PSN) is proposed. For every layer, an encryption key and an S-box are generated and utilized. Those are based on a four-dimensional (4D) dynamical Chen system of a fractional-order, the Mersenne Twister, OpenSLL, Rule 30 Cellular Automata and Intel’s MKL. The sequential application of Shannon’s ideas of diffusion and confusion for 3 times guarantees a total distortion of any input plain image, resulting in a totally encrypted one. Apart from the excellent and comparable performance to counterpart algorithms from the literature, showcasing resistance to visual, statistical, entropy, differential, known plaintext and brute-force attacks, the proposed image cryptosystem provides an exceptionally superior performance in 2 aspects: a vast key space of 2^1658 and an average encryption rate of 3.34 Mbps. Furthermore, the proposed image cryptosystem is shown to successfully pass all the tests of the NIST SP 800 suite.

With the breakthroughs and innovative developments in nanotechnology, research on the application of nanomedicine in cancer therapy has so far seen tremendous expansion and success. Intelligent stimulus-responsive nanocarriers are an emerging field of research and have great interest in cancer therapy owing to the fascinating properties such as excellent targeting function, high drug loading capacity, and targeted on-demand release properties. Responsive nanomaterials can be designed and constructed according to the dosing context and therapeutic needs, at the same time, activated by internal bio-stimuli (pH, redox, and enzymes) and/or external stimuli (ultrasound, light, temperature, and magnetic), respectively. What’s more, smart nanocarriers are also utilized for the precise and controllable release of antitumor drugs from cancer tissues and cells to achieve efficient diagnosis and treatment of tumors. Deeply investigated, responsive nanocarriers have attracted considerable attention due to their ability to release precisely at tumor-specific sites. Herein, we review the recent advances of novel stimuli-responsive nanocarriers in the field of cancer therapy. Finally, the challenges and application prospects of smart nanocarriers are further elaborately discussed.

A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA is based on the extension of Murray's law and additional inlet conditions prescribed iteratively, and is implemented in OpenFOAM for testing and validation. 3D models of CATs are created using CT scans and computational meshes, and the results are compared to in-vasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between calculated and experimental FFR is within 2.33-5.26% in steady-state and transient simulations, respectively, when convergence is reached. The PBA is a reliable and physiologically sound technique compared to the current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for conver-gence. The accuracy of the PBA method is further confirmed using the FDA nozzle, which demonstrates good alignment with CFD-validated values.

Due to various industrial developments and artificial inputs, there are emerging environmental contaminats(ECs) of serious concern in a wide range of environmental media. With recent advancements in scientific knowledge and industrial technology, the definition of emerging environmental contaminats has expanded. Among them, emerging contaminants are typically present in trace amounts and pose serious ecological risks and potential hazards to human health, animals and plants, with cumulative effects on organisms. However, Traditional treatment techniques have proven ineffective in eliminating and preventing subsequent environmental problems from new pollutants such as microplastics, antibiotics and fluorocarbons. Consequently, extensive research has been conducted to address these issues. Effective removal methods prioritize not only removal efficiency, but also environmental friendliness and regenerative capacity. The purpose of this paper is to summarize the sources, forms of presence, environmental and human health hazards, and removal technologies of ECs, and to provide various examples of different sources.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

While Twitter has been touted to provide up-to-date information about hazard events, the reliability of tweets is still a concern. Our previous publication extracted relevant tweets containing information about the 2013 Colorado flood event and its impacts. Using the relevant tweets, this research further examined the reliability (accuracy and trueness) of the tweets by examining the text and image content and comparing them to other publicly available data sources. Both manual identification of text information and automated (Google Cloud Vision API) extraction of images were implemented to balance accurate information verification and efficient processing time. The results showed that both the text and images contained useful information about damaged/flooded roads/street networks. This information will help emergency response coordination efforts and informed allocation of resources when enough tweets contain geocoordinates or locations/venue names. This research will help identify reliable crowdsourced risk information to enable near-real time emergency response through better use of crowdsourced risk communication platforms.

A reduced-dimension (RD) method based on the proper orthogonal decomposition (POD) technology and the linearized Crank-Nicolson mixed finite element (CNMFE) scheme for solving the 2D nonlinear Extended Fisher-Kolmogorov (EFK) equation is proposed. The method reduces CPU runtime and error accumulation by reducing the dimension of the unknown CNMFE solution coefficient vectors. For this purpose, The CNMFE scheme of the EFK equation is established and the uniqueness, stability and convergence of the CNMFE solutions are discussed. Subsequently, the matrix-based RDCNMFE scheme is derived by applying the POD method. Furthermore, the uniqueness, stability and error estimates of the linearized RDCNMFE solution are proved. Finally, numerical experiments are carried out to validate the theoretical findings. In addition, we contrast the RDCNMFE method with the CNMFE method, highlighting the advantages of the dimensionality reduction method.

Since the water-borne iodine excessive goiter was firstly found and reported in 19 in Hebei Province, it was confirmed successively. The national water-borne investigation carried out in 2005 demarcated the water-borne iodine excess areas and water-borne iodine excess endemial areas. The high iodine water well was found In 129 counties of 11 provinces, about 30.98 million people of threatened population lived in water-borne iodine excess areas and water borne iodine excess endemial areas. In these areas, the measures of prevention and control was effectively implemented. In 2016, the new standard of iodine excess area was issued, the iodine excess areas redrawed, and in these areas, non-iodized salt should be supplied and the drinking water should be gradually improved of water, and to control the damage of water-borne iodine excess at an early date

Use of antibiotics and other chemicals to combat disease outbreaks have been a bottleneck for the sustainable growth of shrimp industry. Among various replacement proposed, organic acid (OA) and their salts (OS) are commonly used by farmers and feed millers. However, in free forms, their requirement is very high (2-3 kg/MT) as they tend to disassociate before reaching the hindgut. The dosage can be reduced by microencapsulation of the ingredients. In this study, a 63-day trial was conducted to assess the effects of OA and OS (COMP) microencapsulated (ENCAP) with fat (HF), fat + alginate (HA), wax esters – (WE), and HA and WE (HAWE) on performance, digestive enzyme, immune, and resistance to Vibrio parahaemolyticus. A positive control (PC, 200 g/kg fishmeal - FM) and a negative control (NC, 130 g/kg FM) diet were formulated. Eight other diets were formulated supplementing NC diet with microencapsulated OA (OAHF, OAHA, OAWE, OAHAWE) and OS (OSHF, OSHA, OSWE, OSHAWE). Among the ENCAPs, significant difference was observed in serum malondialdehyde (P = 0.026) where HF showed the lowest level (6.4 ±0.3 mmol/L). Significant interactions between COMP and ENCAP were observed in lipid deposition (P = 0.047), serum alkaline phosphatase and acid phosphatase (P < 0.0001), and hepatopancreatic and serum phenol oxidase (P < 0.0001). Despite no differences, 96-h mortality during pathogenic Vibrio parahaemolyticus challenge in all treatment diets (45% - 56%) was lower compared to the NC diets (63%). In conclusion, use of HF microencapsulated OA diets could provide improved performance and disease resistance that could contribute to the reduction of antibiotic use by the shrimp industry.

Rhododendron is well-known for the colorful corolla. Molecular marker systems have the potentials to elucidate genetic diversity as well as to assess the genetic fidelity in rhododendrons. In the present study, the reverse transcription domains of long terminal repeat retrotransposons were cloned from rhododendrons and used to develop inter-retrotransposon amplified polymorphism (IRAP) marker system. Subsequently, 198 polymorphic loci were generated from the IRAP and inter-simple sequence repeat (ISSR) markers, of which 119 were derived from the IRAP markers. It was justified that in rhododendrons, IRAP markers were superior to the ISSRs in some polymorphic parameters such as the average number of polymorphic loci (14.88 versus 13.17). In comparison with the single one, the combination of IRAPs and ISSRs systems was more discriminative for detecting 46 rhododendron accessions. Further, IRAP markers demonstrated more efficiency in genetic fidelity detection of in vitro R. bailiens, an endangered species just recorded in Guizhzhou Province, China. The available evidences revealed the distinct properties of IRAP and ISSR markers in the rhododendron-associated applications, and highlighted the availability of highly informative ISSR and IRAP markers in the genetic diversity evaluation and the genetic fidelity assessment of rhododendrons, which may facilitate the preservation and genetic breeding in rhododendron plants.

A novel catechol (CA) biosensor was developed by the immobilization of tyrosinase (Tyr) onto in situ electrochemical reduction graphene (EGR) on choline functionalized gold nanoparticals (AuNPs–Ch) film. The results of UV–visible spectra indicated that Tyr retained its original structure in the film. And electrochemical investigation of the biosensor showed a pair of well–defined, quasi–reversible redox peaks with E_pa= –0.0744V and E_pc= –0.114 V (vs. SCE) in 0.1 M, pH 7.0 sodium phosphate buffered saline at the scan rate of 100 mV/s. The transfer rate constant k_s was 0.66 s^–1. The Tyr–EGR/AuNPs–Ch showed a good electrochemical catalytic response for the reduction of CA, with the linear range from 0.2 to 270 μM and a detection limit of 0.1 μM (S/N= 3). The apparent Michaelis–Menten constant was estimated to be 109 μM.

This paper reports on the changing dynamics of a small town’s social-ecological system (SES) concerning oil and gas industry boom-bust economic cycles and both the vulnerability and resilience of the town over the past 30 years. With the goal to understand how resource-based single industry impact social-ecological systems, we developed indicators of human and environmental well-being and assessed them. Seven indicators include labor force distribution, education, oil price, household income, water quality, air quality, and land cover land use. Over this period, Drayton Valley, Canada quadrupled in size, with more than 20% of the population working in the oil and gas sector. Median income rose to 42% above the national average despite the population lagging national benchmarks for educational attainment. There have also been dramatic fluctuations in levels of fluoride, phosphorus, and other chemicals in water quality samples, implying a correlation with fossil fuel extractive activities over this period. Land cover land use change analysis shows a decreased area of water bodies, wetland, and forests, and increased built capital and agricultural land. While economic boom cycles have led to cash inflows, an exclusive focus on the benefits of the oil and gas industry may leave those dependent on the industry vulnerable to social and environmental risk factors during bust cycles that are beyond their control in the everchanging global oil economy. This phenomenon which has been referred to as the “resource curse” suggests the need to anticipate cyclical (or more sustained) periods of low levels of oil and gas production. These results suggest that single boom-bust economies impact every aspect of social-ecological systems. Therefore, a sustainable development plan that comprehensively considers not only economic growth, but also diversification, environment protection, and strategic land use planning is indispensable to ensure the long-term development of communities that depend upon extractive industries.

This study explores the public library service evaluation domain through user-generated content on Google Maps, highlighting digital feedback's significant yet underexplored potential in understanding public library patronage across Taiwan's six major cities. Utilizing a mixed-methods research design, this study integrates Google Maps review content analysis with Social Network Analysis to delineate public perceptions and identify areas for service enhancement in public libraries. It innovatively leverages personal experiences extracted from over 60,000 Google Maps reviews to evaluate public library services in cities such as Taipei, New Taipei, Taoyuan, Taichung, Tainan, and Kaohsiung. The research taps into the National Library of Taiwan's National Library Statistics System to provide a robust analysis of library performance and user satisfaction, offering a novel perspective by emphasizing user-centric feedback from Google Maps as a primary data source. This approach provides quantitative data on library usage and geographic distribution and enriches our understanding of the qualitative experiences of library users. In analyzing the keywords from Google Maps reviews of public libraries, we categorize and interpret these under the three core LibQUAL+ dimensions—Affect of Service, Information Control, and Library as Place. The findings expose variances in perceived service quality among the cities, with Kaohsiung and Taichung receiving the highest accolades for service satisfaction. Simultaneously, the study identifies potential areas for improvement, particularly in cities with lower satisfaction ratings like Taipei. This personalized feedback illustrates the intimate relationship between public libraries and their communities, offering invaluable insights for policymakers and library management to enhance service delivery and user experience.

The main objective of this work is to study the effects of carbon nanotubes (CNT) on the strength and electrical properties of cement mortar. Molecular dynamic simulations (MDS) were carried out for the mechanical and electrical properties of the cementitious composite and the associated mechanisms. To model the atomic structure of the Calcium-Silicate-Hydrates (C-S-H) gel, tobermorite 11Å was chosen. Single-walled carbon nanotubes (SWCNTs) embedded in tobermorite structure were tested numerically. In particular, the effect of the concentration of CNT in cement paste was studied. An innovative experiment of electrical characterization of a cementitious composite of carbon nanotubes has been developed.

Direct electric curing (EC) is a new green curing method for cement-based materials that improves the early mechanical properties via the uniform high temperature produced by Joule heating. To understand the effects of EC and steam curing (SC) on the mechanical properties and microstructure of cement-based materials, the mortar was cured at different temperature-controlled curing regimes (40°C, 60°C and 80°C). Meanwhile, mechanical properties, hydrate phase and pore structure of specimens were investigated. The energy consumption of two curing methods was compared and analyzed. The results show that the EC specimens have better and more stable growth of mechanical strength. The pore structure of EC specimen is also better than that of SC specimen at different maintenance ages. However, the hydration degree and products of samples cured by EC are similar to that SC samples. The energy consumption of EC is lower than SC. This study provides an important technical support for the EC in the production of energy-saving and high early-strength concrete precast components.

Highly efficient, broadband and distinctively structured electromagnetic wave (EMW) absorption materials exhibit huge exceptions with multi-functions in both military and civilian fields. Searching the relationship between structural and EMW performance is beneficial to develop outstanding microwave absorption materials, and has become an attractive research topic. In this study, we briefly reviewed the different EMW absorption mechanisms and key influence factors, then, present the latest developments in low-dimensional (LD) EMW absorption materials. We provide a comprehensive discussion of remarkable examples and summarize the main information related to the structure-function relationship of dimensional design and structural engineering in order to facilitate the rapid evolution of this fascinating field.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

In this work, thermo-responsive block copolymer brushes modified graphene oxide (GO) nanohybrid was fabricated successfully via the host-guest interaction between β-cyclodextrin functionalized GO and azobenzene-terminated PNIPAM-b-P(St-co-MQ). The block copolymer was synthesized using reversible addition fragmentation chain transfer (RAFT) polymerization based on the monomers of N-isopropylacrylamide (NIPAM), 5-(2-methacryloyl-ethyloxymethyl) -8-quinolinol (MQ), styrene (St) and an azobenzene functional RAFT agent. The 8-hydroxyquinoline units containing in the block polymer can coordinate with CdSe/ZnS quantum dots(QDs) to form a CdSe/ZnS QDs-block copolymer brushes modified graphene oxide fluorescence nanohybrid (QDs/polymer/GO fluorescence nanohybrid) and the resulting fluorescence nanohybrid had a robust temperature responsive property which result from the change in the PNIPAM conformation in the block copolymer on the surface of GO.

In this research article we solve the problem of synchronization and anti-synchronization of chaotic systems described by discrete and time-delayed variable fractional order differential equations. To guarantee the synchronization and anti-synchronization of these systems, we use the well-known PID control theory and the Lyapunov-Krasovskii stability theory for discrete systems of variable fractional order.We illustrate the results obtained through simulation with examples, in which it can be seen that our results are satisfactory, thus achieving synchronization and anti-synchronization of chaotic systems of variable fractional order with discrete time delay.

We provide representations for the generalized Drazin inverse of an anti-triangular matrix of the form $\left( \begin{array}{cc} a&b\\ 1&0 \end{array} \right)$ in a Banach algebra $\mathcal{A}$, under the condition that $ab=ba$. Specifically, we present the representation of Drazin inverse for these types of anti-triangular matrices in Banach algebras.

We investigate the existence and representation of the generalized core-EP inverse of some triangular matrices over a Banach algebra. Further, the general representations of the generalized core-EP inverse of a triangular matrix over a $C^*$-algebra are presented. As applications, the generalized core-EP inverses of some block operator matrices over Hilbert spaces are given.

In this paper, we introduce the notion of the generalized $w$-group inverse in a Banach algebra with proper involution. This is a natural generalization of generalized (weak) group inverse in Banach *-algebras. Many elementary properties of such new weighted generalized inverse are presented. We further establish the equivalent relations between generalized weighted group inverse and weighted generalized Drazin inverse. Related properties of generalized (weak) group inverse are extended to the wider cases.

Incident rates of neurodegenerative diseases have steadily increased globally, but there is no therapeutic access available. We newly prescribed medicinal herbal remedy including five different herbal plants called, Chen-Ma-Dan-Sam-Ga-Mi-Bang (CMST), purposed to prove for pharmacological properties and corresponded actions on hippocampus neuronal cell injury by hypoxia-induced mice model. Mice were adapted to normoxia or hypoxia with or without CMST for 5 days. We gathered pharmacological effects of CMST on cell injury by enhancement of dihydroethidium and 4-hydroxynonenal signals which were correlated with abnormal redox status in the protein or gene expression levels (abnormal elevations of nitric oxide, reactive oxygen species, lipid peroxidation and deteriorations of total glutathione, total antioxidant capacity, and activities of superoxide dismutase and catalase) due to hypoxia. CMST also notably exerted to attenuates molecules for neuronal cell injury markers such as p-tau, cleaved caspase-3 due to DNA oxidations (53bp1and phosphor-histone H2AX), inflammatory cytokines, and hemeoxigenase-1. We further figured out the underlying actions of CMST by in vitro experiment through inactivation of microglial cell which can mediate neuronal cell injury. Collectively, CMST prevented from hippocampal neuronal cells via inactivation of microglial cell with normalization of redox status on hypoxia-induced hippocampus neuronal cell injury.

A large amount of steel slag (SS) and CO2 are generated in the steelmaking process. The indirect CO2 capture using SS is a promising way for co-treatment of the wastes. Ammonium salt solution is widely used to extract Ca2+ from the SS since it is recyclable. Several works have focus on improving the carbonation rate by adjusting various parameters (e.g., temperature and pH). However, there is little detail information about the associating behaviors and interaction strength between the various ions in the ammonia solution during the carbonation process. In this work, the Ca2+–CO32-–NH4+–Cl-–H2O system was established by using Material studio software. The effects of temperature and concentration of CO32- on CaCO3 growth were explored at the atomic scale by calculating the binding energy, mean square displacement, and diffusion coefficient between particles. Furthermore, the microstructure, bonding characteristics, and occurrence behavior of each particle were studied though molecular dynamics simulation methods. The results showed that with the increase of temperature (20–80 ℃), the binding ability and diffusion coefficients of Ca2+ and CO32- increase in the system, which is beneficial to the formation of CaCO3 clusters. With the increase of the concentration of CO32- (15–25 vol.%), the binding ability and diffusion coefficient of Ca2+ and CO32- in the system are enhanced, which is beneficial to the formation of CaCO3 clusters.

Concrete cracks and local damage can affect the bond performance between concrete and steel bars, thereby reducing the durability of reinforced concrete structures. Compared with general concrete crack repair methods, biomineralization repair not only has effective bonding capabilities but is also particularly environmentally friendly. In view of this, this study aimed to apply biomineralization technology to repair damaged fiber-reinforced lightweight aggregate concrete (LWAC). Two groups of LWAC specimens were prepared. The control group used lightweight aggregates (LWAs) without bacterial spores and nutrient sources, and the experimental group used LWAs containing bacterial spores and nutrient sources. These specimens were first subjected to compression tests and pull-out tests, respectively, and thus were damaged. After the damaged specimen healed itself in different ways for 28 days, secondary compression and pull-out tests were conducted. The self-healing method of the control group involved placing the specimens in an incubator. The experimental group was further divided into experimental group I and experimental group II. The self-healing method of experimental group I was the same as that of the control group. The self-healing method of experimental group II involved soaking the specimen in a mixed solution of urea and calcium acetate for two days, and then taking it out and placing it in an incubator for two days, with a cycle of four days. The test results showed that, compared with the control group specimens, the relative bond strength ratio of the experimental group II specimens increased by 17.9%. Moreover, the EDS and XRD analysis results confirmed that the precipitate formed at the crack was calcium carbonate, which improved the compressive strength and bond strength after self-healing. This indicates that the biomineralization maintenance method used in experimental group II is more effective.

Abstract: High step-up voltage gain nonisolated DC-DC converter have attracted much attention in photovoltaic, fuel cells and other renewable energy system applications. In this paper, by combining input current ripple-free boost cell with coupled-inductor voltage-doubler cell, an input current ripple-free high voltage gain nonisolated converter is proposed. In addition, passive lossless clamp circuit is adopted to recycle the leakage inductor energy and to reduce the voltage spike across the power switch. By utilizing voltage-doubler cell consisting of diode and capacitor, the voltage stress of switch is further reduced and the resonance between the leakage inductor and the stray capacitor of the output diode is eliminated. A low switch-on-resistance low-voltage-rated MOSFET can therefore be employed to reduce the conduction loss and cost. The reverse recovery loss of output diode is reduced, and the efficiency of converter can be improved. Furthermore, the proposed converter can achieve nearly zero input current-ripple and make the design of electromagnetic interference (EMI) filter easy. Steady state analysis and operation mode of the converter is performed. Finally, experimental results are presented to verify the analysis results of the proposed converter.

With the rapid development of electronic and communication technology in military radar, the demand for microwave absorbing materials in low-frequency with thin layer is growing increasingly. In this study, flexible Co3O4/CC (carbon cloth) composites derives from Co-MOFs (metal-organic frameworks)/CC are prepared by hydrothermal and thermal treatment processes. The flexible precursors of Co-MOFs/CC are calcined with different calcination temperatures, which the material structure, dielectric properties and microwave absorption performance are changed. With the increase of calcination temperature, the minimum reflection loss of the corresponding Co3O4/CC composites gradually moves to the lower frequency with thinner thickness. In addition, the Co3O4/CC composites with 25 wt% filler loading ratio exhibit the minimum reflection loss (RL) of -46.59 dB at 6.24 GHz with 4.2 mm thickness. When the thickness is 3.70 mm, the effective absorption bandwidth is 3.04 GHz from 5.84 to 8.88 GHz. This study not only proves that the composite Co3O4/CC is a kind of outstanding microwave absorbing material with better flexibility, but also provides a useful inspiration for the low frequency and broadband microwave absorbing material.

This paper studies ionospheric vertical total electron content (VTEC) variations before the 2014 Mw8.2 Chile earthquake. VTEC derived from 14 GPS (Global Positioning System) stations and GIM (Global Ionospheric Map) were used to analyze ionospheric variations before the earthquake using the sliding interquartile range method, and results showed that significant positive VTEC anomalies occurred on 28 March. To explore possible causes of these anomalies, effects of solar and geomagnetic activities were examined, and VTEC variations during 17 March to 31 March in 2009-2013 were cross-compared. Also, VTEC for a full year before the earthquake was investigated. Results indicated that these anomalies were weakly associated with high solar activities and geomagnetic storms and that these anomalies were not normal seasonal and diurnal variations. An analysis of the spatial distribution of the observed anomalies was also presented, and it demonstrated that anomalies specifically appeared around the epicenter on 28 March. It suggests that observed anomalies may be associated with the subsequent Chile earthquake. Equatorial anomaly variations were analyzed to discuss the possible physical mechanism, and results showed that the equatorial anomaly unusually increased on 28 March, which indicates that anomalous electric fields generated in the earthquake preparation area and the meridional wind are possible causes of the observed ionospheric anomalies.

The rapid, sensitive, and selective detection of pathogenic bacteria is of utmost importance in ensuring food safety and preventing the spread of infectious diseases. Here, we present a novel, reusable, and cost-effective impedimetric sensor based on a dual bacteria-imprinted polymer (DBIP) for the specific detection of Escherichia coli O157:H7 and Staphylococcus aureus. The DBIP sensor stands out with its remarkably short fabrication time of just 20 minutes, achieved through the efficient electro-polymerization of o-phenylenediamine monomer in the presence of dual bacterial templates, followed by in-situ template removal. The key structural feature of the DBIP sensor lies in the cavity-free imprinting sites, indicative of a thin layer of bacterial surface imprinting. This facilitates rapid rebinding of the target bacteria within a mere 15 minutes, while the sensing interface regenerates in just 10 minutes, enhancing the sensor's overall efficiency. A notable advantage of the DBIP sensor is its exceptional selectivity, capable of distinguishing the target bacteria from closely related bacterial strains, including different serotypes. Moreover, the sensor exhibits high sensitivity, showcasing a low detection limit of approximately 9 CFU mL-1. The sensor's reusability further enhances its cost-effectiveness, reducing the need for frequent sensor replacements. The practicality of the DBIP sensor was demonstrated in the analysis of real apple juice samples, yielding good recoveries. The integration of quick fabrication, high selectivity, rapid response, sensitivity, and reusability makes the DBIP sensor a promising solution for monitoring pathogenic bacteria, playing a crucial role in ensuring food safety and safeguarding public health.

In this paper we investigate the differential topological properties of a subclass of singular space--subcarteisan spaces. First, we get further result on partition of unity for differential spaces. Second, we establish the tubular neighborhood theorem for subcartesian spaces with constant structural dimension. Third, we generalize the concept of Morse functions on smooth manifolds to differential spaces. For subcartesian space with constant structural dimension, we provide examples of Morse functions; With the assumption that the subcartesian space can be embedded as a bounded subset of an Euclidean space, we prove that smooth bounded functions on this space can be approximated by Morse functions; We study the infinitesimal stability of Morse functions on subcartesian spaces. Classical results on Morse functions on smooth manifolds can be treated directly as corollaries of our results here.

The greatly diversified flowering plants (angiosperms) are the dominating and defining group in the current earth ecosystem. However, from which group by what way the flowers, especially their gynoecia (key characteristics of angiosperms), are derived have been the questions in botany unanswered over centuries. Such an embarrassing situation can be attributed to the lack of plants with partially enclosed ovules, which are supposed to be a post between gymnosperms and angi-osperms. Here we report a fossil plant that has an apparent coniferous vegetative and reproduc-tive morphologies but has a single seed partially wrapped by the subtending bract. Such a mor-phology suggests that the carpels in angiosperms may be equivalent to bracts enclosing their axil-lary seed(s). Such a non-traditional interpretation of the homology of angiosperm carpels is com-patible with various new progresses made in botany and is in line with Tomlinson’s recent hy-pothesis. Together with other fossil evidence reported recently, it appears that gynoecia in angio-sperms are derived in multiple ways.

The degree of ore rock fragmentation of mine blasting is an important index for evaluating the effect of engineering blasting. In order to study the effect of millisecond delayed blasting on the internal fragmentation of the ore rock, LS-DYNA numerical simulation software was used to obtain the damage characteristics of the ore rock in the blasting area using the RHT model. The Mohr-Coulomb strength damage criterion was applied to analyze the internal stress state of the ore rock, and the effects of 25ms, 50ms and 75ms delay time conditions on ore rock fragmentation were studied. The results show that, within a certain range of delay time, the degree of rock fragmentation increases with the increase of delay time. The stress state in the ore rock due to blasting is strengthened with the increase of delay time in the direction of the blast hole, which shows that the stress concentration is strengthened from the excavation face to the interior of the ore rock. The damage and the degree of fragmentation show a characteristic relationship of 25ms＜50ms＜75ms, which is verified by carrying out blasting experiments on site.

：Non-Euclidean data, such as social networks, and citation relationships between documents, has node information and structural information. Graph Convolutional Network(GCN) can automatically learn node features and association information between nodes. The core ideology of the graph convolutional network is to aggregate node information by using edge information, thereby generating a new node feature. In the process of updating node features, there are two core influencing factors. One is the number of neighboring nodes of the central node, the other is the contribution of the neighboring nodes to the central node. Due to the previous GCN methods not simultaneously considering the numbers and different contributions of neighboring nodes to the central node, we design the Adaptive Attention Mechanism(AAM). To further enhance the representational capability of the model, we utilize Multi-Head Graph Convolution(MHGC). Finally, we adopt cross-entropy(CE) loss function to describe the difference between the predicted results of node categories and the ground truth (GT). Combined with backpropagation, this ultimately achieves accurate node classification. Based on AAM, MHGC and CE, we contrive the novel Graph Adaptive Attention Network (GAAN). Experiments show that the classification accuracy has achieved outstanding performances on Cora, Citeseer and Pubmed datasets.

The existing segmentation-based scene text detection methods mostly need complicated post-processing, and the post-processing operation is separated from the training process, which greatly reduces the detection performance. The previous method, DBNet successfully simplified post-processing and integrated the post-processing into a segmentation network. However, the training process of the model took a long time for 1200 epochs and the sensitivity to texts of various scales was lacking, leading to some text instances being missed. Considering the above two problems, we design the text detection Network with Binarization of Hyperbolic Tangent(HTBNet). First of all, we propose Binarization of Hyperbolic Tangent (HTB), optimized along with which, the segmentation network can expedite the initial convergent speed by reducing the amount of epochs from 1200 to 600. Because features of different channels in the same scale feature map focus on the information of different regions in the image, to better represent the important features of all objects in the image, we devise the Multi-Scale Channel Attention(MSCA). Meanwhile considering that multi-scale objects in the image cannot be simultaneously detected, we propose a novel module named Fused Module with Channel and Spatial(FMCS), which can fuse the multi-scale feature maps from channel and spatial dimension. Finally we adopt cross entropy as the loss function, which measures the difference between predicted values and ground truths. The experimental results show that HTBNet compared with lightweight models has achieved competitive performance and speed on Total-Text(F-measure:86.0%, FPS:30) and MSRA-TD500 (F-measure:87.5%, FPS:30).

There is no doubt that seagrass beds constitute one of the most productive ecosystems in shallow coastal waters. Despite this, picoplankton in seagrass ecosystems has received relatively little attention. The purpose of this study was to compare picoplankton growth and mortality rates between seagrass and unvegetated habitats using chamber incubations. We tested two main hypotheses: (i) incubation with seagrass would result in higher bacterial growth rates due to increased DOM release from seagrass photosynthesis, and (ii) Synechococcus spp. would be lower in the presence of seagrass due to competition for inorganic nutrients. Our results showed bacterial growth rates of 2.31 and 2.44 d–1 without and with seagrass, respectively. In seagrass chambers, bacterial growth was higher than that in non-seagrass chambers, suggesting that organic carbon coming from the seagrass community may support bacterial production. Furthermore, we observed a negative Synechococcus spp. growth rate (-0.9 d–1) in the seagrass treatment, likely reflecting nutrient competition with the seagrass. Small-scale chambers proved to be a useful tool for studying the factors controlling spatial and temporal patterns of picoplankton across different habitats. Furthermore, future studies should examine picoplankton growth over a wider range of spatial scales in seagrass beds and adjacent unvegetated sediment.

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

In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship radiated noise. After that, the characteristic parameters, namely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropy, are compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship radiated noise can be extracted efficiently with the method.

Different studies corroborate a role for ceramide synthases and their downstream products, ceramides, in modulation of apoptosis and autophagy in the context of cancer. These mechanisms of regulation, however, appear to be context dependent in terms of ceramides’ fatty acid chain length, subcellular localization, and the presence or absence of their downstream targets. Our current understanding of the role of ceramide synthases and ceramides in regulation of apoptosis and autophagy could be harnessed to pioneer the development of new treatments to activate or inhibit a single type of ceramide synthase, thereby regulating the apoptosis induction or cross talk of apoptosis and autophagy in cancer cells. Moreover, the apoptotic function of ceramide suggests that ceramide analogues can pave the way for the development of novel cancer treatments. Therefore, in the current review paper we discuss the impact of ceramide synthases and ceramides in regulation of apoptosis and autophagy in context of different types of cancers. We also briefly introduce the latest methods to analyze the lipids in biological samples. Finally, we discuss the drug development strategies focusing on the ceramide synthases and ceramides as future therapeutic approaches in cancer therapy.

The formation of rock fractures in nature has a certain relationship with water seepage. In order to analyze the shape of rock fracture, we propose a rock deformation theoretical model in three-dimensional space considering with the condition of seepage water pressure, and establish the mass conservation equation, seepage equation, surrounding rock displacement equation, so as to deduce the rock deformation control equation under seepage pressure action. The numerical analysis of the nonlinear quadratic partial differential equation obtains the fracture deformation distribution in the example, and verifies with the calculated fracture morphology. And we further use this principle to analyze the fracture morphology in nature and prove the rationality of the theory.

This paper explores in depth the mechanism of enterprise digital capability effects in supply chain digital development by reconstructing the supply chain cooperation capabilities (digital diffusion capability and digital collaborative capability). We use the questionnaire data covering 272 Chi-nese manufacturing enterprises and apply a structural equation model to test the hypothesis. The results show that enterprise digital capability does not directly have a significant impact on sup-ply chain digitalization, and the supply chain cooperation capabilities play mediation role be-tween enterprise digital capability and supply chain digitalization. The results are robust due to we thoroughly consider the action boundary of enterprise capabilities, and verify the systematic requirements of supply chain digitalization and the high-order of enterprise digital capability. These provide a theoretical basis for enterprises to promote the digital transformation of supply chain through digital technology.

We study L_2-approximation problems in the weighted Hilbert spaces in the worst case setting. Three interesting weighted Hilbert spaces appear in this paper, whose weights are equipped with two positive parameters $\ga_j$ and $\az_j$ for $j=1,\,2,\dots,\,d$. We consider the worst case error of algorithms that use finitely many arbitrary continuous linear functionals. We discuss the exponential convergence-(t,s)-weak tractability (EC-(t,s)-WT) of these L_2-approximation problems under the absolute or normalized error criterion. In particular, we obtain the sufficient and necessary conditions for EC-(1,1)-WT and EC-(t,1)-WT with t

The monocular structured light measurement system has low cost, simple algorithms, and a wide measurement range, making it widely applicable in multiple fields. However, in practical applications, the system may be affected by various factors including noise, non-linear intensity, changes in the reflectivity of the object being measured, and the calibration method and accuracy of the system, thereby reducing the measurement accuracy. In order to solve these issues, this paper proposes a new monocular structured light measurement method, mainly comprises the following two points: (a) A denoising algorithm for phase images based on DAE is proposed, which calculates the wrapped phase of the phase-shifted fringes after initial denoising by DAE. Then, a new phase-shifted fringe pattern is generated and input into DAE for iterative denoising, achieving high-performance image denoising and high-precision wrapped phase solution. (b) A new absolute phase height calibration algorithm is proposed, which introduces camera internal and external parameters and uses a two-layer feedforward network to directly establish the relationship between phase and the 3D coordinate system. Without the need for high-precision motion platforms, high-precision phase height calibration is attainable. In general, compared to conventional methods, the experimental results indicate the effectiveness of the proposed method for low-quality phase-shifted fringe 3D reconstruction. In addition, the measurement method described in this article also demonstrates effectiveness in high-dynamic scenes.

As an important civil and military infrastructure, airport runway pavement is faced up with threats from cluster munitions, since it is vulnerable to projectile impact with internal explosion. Aiming at the damage assessment of island airport runway pavement under impact, this work dealt with discrete modeling of rigid projectile penetration into concrete pavement and calcareous sand subgrade multi-layer structure. First, Discrete Element Method (DEM) is introduced to model concrete and calcareous sand granular material features like cohesive fracture and strain hardening due to compression, with mesoscale constitutive laws governing the normal and shear interactions between adjacent particles. Second, sequent DEM simulations of uniaxial and triaxial compression were performed to calibrate the DEM parameters for pavement concrete as well as subgrade calcareous sand. Piror to multi-layer structure investigations, penetration into sole concrete or calcareous sand is validated in terms of projectile deceleration and depth of penetration (DOP) with relative error

Abstract In order to solve the problem that it is difficult to obtain the accurate trigger signal moment when using the time difference of UAV flight acoustic signals collected by acoustic sensors arranged in advance to locate the position of UAVs when they cannot be tracked by radar and are difficult to be observed by the human eye, an acoustic source localisation method with improved empirical modal decomposition (REMD) under an adaptive frequency window is proposed. Firstly, the collected UAV flight signals are smoothed and filtered, then the robust empirical modal decomposition (REMD) is used for IMF modal decomposition and spectral analysis of the collected signals, and a panning frequency window with variable bandwidth is introduced for corresponding frequency locking and extracting the IMFs; the GWO optimisation is used and the sliding metrics are set to determine the position of the panning frequency window automatically; finally, the extracted Finally, the extracted IMF components are reconstructed according to the criterion, and the trigger signal moments in the reconstructed IMF components are resolved and recorded, and the algorithm is used to calculate the difference between the reception moments of different sensors; for the traditional sound source localisation algorithms with a small detection range, which are prone to fall into the no-solution or false-solution, i.e., unable to achieve the localisation, a weighted least-squares-based Chan-Taylor algorithm is proposed for the localisation computation, and a weighted least-squares algorithm is proposed for the localisation computation, through the Inputting the sensor delay parameter and solving the linear equation system to get the target position information; finally, this paper verifies the robustness and performance of the design method with simulated and actual signals. The results show that the maximum positioning error is no more than 5% in an area with a side length of 15m in the measurement area. With the improved accuracy of time delay estimation, the positioning simulation results meet the positioning requirements even though the positioning error is further expanded when the measurement area is further expanded.

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

In order to correct attenuated millimeter-wavelength (Ka-band) radar data and address the problem of instability, an attenuation correction methodology (attenuation correction with variation trend constraint; VTC) was developed. Using synchronous observation conditions and multi-band radars, the VTC method adopts the variation trends of reflectivity in X-band radar data captured with wavelet transform as a constraint to adjust reflectivity factors of millimeter-wavelength radar. The correction was evaluated by comparing reflectivities obtained by millimeter-wavelength cloud radar and X-band weather radar. Experiments showed that attenuation was a major contributory factor in the different reflectivities of the two radars when relatively intense echoes exist, and the attenuation correction developed in this study significantly improved data quality for millimeter-wavelength radar. Reflectivity differences between the two radars were reduced and reflectivity correlations were enhanced. Errors caused by attenuation were eliminated, while variation details in the reflectivity factors were retained. The VTC method is superior to the bin-by-bin method in terms of correction amplitude and can be used for attenuation correction of shorter wavelength radar assisted by longer wavelength radar data.

The impact of drought stress on plant growth in arid regions is a critical concern, necessitating the exploration of strategies to enhance plant drought resistance, particularly during the early stages of drought stress. This study focuses on the ectomycorrhizal fungus Cenococcum geophilum, renowned for its extensive genetic diversity and broad host compatibility, making it a crucial ally for host plants facing external stresses. We utilized approximately 5-month-old Pinus massoniana seedlings inoculated with different ecotypic strains of C. geophilum for 7 days of drought stress. The results showed that the inoculation of most strains of C. geophilum enhanced the drought resistance of P. massoniana seedlings under the early stages of drought stress, by influencing the water content, photosynthesis, accumulation of osmotic adjustment substances, and antioxidant enzyme activities in both shoots and roots of seedlings. These responses were further validated through transcriptome analysis. Notably, the level of drought resistance observed in mycorrhizal seedlings was irrespective of the level of drought tolerance of C. geophilum strains. This study contributes essential data for understanding the drought response mechanisms of mycorrhizal P. massoniana seedlings inoculated by distinct C. geophilum ecotypes, and guidance on selecting candidate species of ectomycorrhizal fungi for mycorrhizal afforestation in drought areas.

Bandsaw blades are typical band-shaped cutting tools characterized by low stiffness and micro-level cutting depth, resulting in distinct wear mechanisms compared to rigid cutting tools. In this study, the wear curve and wear mechanisms of bandsaw tooth during the bandsawing of Cr12MoV cold-working steel was investigated. The tool life was divided into two stages: a rapid wear stage (Stage I) and a homogeneous wear stage (Stage II). In Stage I, the wear was dominated by chipping although multiple wear mechanisms were found due to the relatively poor manufacturing accuracy compared to rigid cutting tools, which results in remarkable differences among the cutting depths of individual teeth. In Stage II, abrasive and adhesive wear were the primary wear mechanisms instead of chipping, which was related to the microstructure of Cr12MoV. Furthermore, methods for increasing the bandsaw performance were proposed based on the tooth wear mechanisms.

Brand trust holds significant importance in the Mongolian cashmere industry. This study examines the primary predictors of customer brand trust among Mongolian cashmere users. Our research includes a survey with 800 participants and 20 individual interviews conducted among both Mongolian cashmere users and non-users. We utilized an online platform to reach participants, employing convenience sampling. The study investigates the relationship between various factors and brand trust within the context of Mongolian cashmere brands. Through a combination of in-dividual interviews and statistical analysis, we test six hypotheses. The findings indicate that higher brand quality, a strong reputation, greater transparency, effective issue resolution, commitment to environmental and social responsibility, and pre-purchase research on such commitments positively impact brand trust. Key insights gleaned from the interviews emphasize the importance of quality, reputation, transparency, customer service, and environmental responsibility in shaping consumer trust. These results offer valuable implications for cashmere brands aiming to bolster consumer trust and foster loyalty.

End-to-end learned image compression codecs have notably emerged in recent years. These codecs have demonstrated superiority over conventional methods, showcasing remarkable flexibility and adaptability across diverse data domains while supporting new distortion losses. Despite challenges such as computational complexity, learned image compression methods inherently align with learning-based data processing and analytic pipelines due to their well-suited internal representations. The concept of Video Coding for Machines has garnered significant attention from both academic researchers and industry practitioners. This concept reflects the growing need to integrate data compression with computer vision applications. In light of these developments, we present a comprehensive survey and review of lossy image compression methods. Additionally, we provide a concise overview of two prominent international standards, MPEG Video Coding for Machines and JPEG AI. These standards are designed to bridge the gap between data compression and computer vision, catering to practical industry use cases.

Baijiu is popular with its long history and balanced flavor, and flavor type was the most widely used classification mode for Baijiu. However, the evolution relationship of Baijiu flavor types and the differential markers between flavor types are still unclear, which has greatly affected the development of Baijiu industry. In this study, a total of 319 trace components were identified by gas chromatography-olfactometry-mass spectrometry and gas chromatography-mass spectrometry. Among them, 91 trace components with high odor active values or taste active values were recognized as flavor components. Then random forests were conducted to screen differential markers between derived and basic flavor types, and principal component analysis was carried out to evaluate their effectiveness in distinguishing the flavor types of Baijiu. Finally, 19 differential markers were screened and proved to effectively reveal the evolution Baijiu flavor types, and were further verified as key differential markers by addition test and correlation analysis.

Fabrication of durable materials with excellent oil adsorption capacity and separation performance for the treatment of oily wastewater is meaningful based on smart responsiveness. Herein, a solvent-responsive melamine sponge (MS) was developed via silanization followed by the in-situ growth of zeolitic imidazolate framework-8 (ZIF-8). Detailed characterization of the resultant composite MS was conducted using scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The multiscale hierarchical MS substrate exhibited highly hydrophobic property in the pH range of 1-11, along with a satisfactory adsorption capacity in the range of 65.4-134.2 g/g for different oils. The modified surface transformed from superhydrophobicity/superlipophilicity to superhydrophilicity/underwater superoleophobicity upon ethanol wetting, reverting to its original superhydrophobic state upon drying. The separation flux of the MS substrate was above 1.5×104L/m2h for both oil and water removal, along with the separation efficiency more than 98.7%. No obvious changes of the separation performance after 50 successive immiscible oil/water separation indicated the excellent durability and robustness of the anchored ZIF-8 nanoparticles on the surface of modified MS substrate. More importantly, oil-in-water emulsion separation was successfully carried out via the ZIF-8 MS composite with a high separation efficiency over 99.1%. The developed smart sponge with high oil absorption capacity, excellent chemical stability and fire resistance exhibited a wide range of potential practical applications in the convenient treatment of oily wastewater.

Anti-interferon (IFN)-γ autoantibodies are linked to varicella-zoster virus (VZV) infection. Given the elevated risks of herpes zoster (HZ) in rheumatoid arthritis (RA) patients treated with Janus kinase inhibitors (JAKi), we aimed to examine the relationship between anti-IFN-γ autoantibodies with HZ development in JAKi-treated patients. In twenty-four RA patients with new-onset HZ and forty-two without HZ, serum titers of anti-IFN-γ autoantibodies, plasma levels of IFN-γ, monocyte chemoattractant protein-1 (MCP-1), and IFN-γ inducible protein-10 (IP-10) were measured by ELISA. Significantly lower MCP-1 levels were observed in patients with HZ compared to those without (median, 98.21pg/ml, interquartile range (IQR) 77.63-150.30pg/ml versus 142.3pg/ml, IQR 106.7-175.6pg/ml, p&lt;0.05). There was no significant difference in anti-IFN-γ titers, IFN-γ levels, or IP-10 levels between patients with and without HZ. Three of 24 patients with HZ had severe HZ with multi-dermatomal involvement. Anti-IFN-γ titers were significantly higher in patients with severe HZ than in those with non-severe HZ (median 24.8ng/ml, IQR 21.0-38.2ng/ml versus 10.5ng/ml, IQR 9.9-15.0ng/ml, p&lt;0.005). In conclusion, patients with HZ had significantly lower MCP-1 levels than those without HZ, and patients with severe HZ had significantly higher titers of anti-IFN-γ than those with non-severe HZ. Given small sample size, our results need further validation in future studies.

Micro channel tube (MCT) is widely employed in industry due to its excellent efficiency in heat transfer. An MCT is commonly produced through extrusion within a porthole die, where severe plastic deformation is inevitably involved. Moreover, the plastic deformation, which dramatically affects the final property of the MCT, varies significantly from location to location. In order to understand the development of the microstructure and its effect on the final property of the MCT, the viscoplastic self-consistent (VPSC) model, together with the finite element analysis and the flow line model, is employed in the current study. The flow line model is used to reproduce the local velocity gradient within the complex porthole die, while VPSC model is employed to predict the evolution of the microstructure accordingly. In addition, electron backscatter diffraction (EBSD) measurement and mechanical tests are used to characterize the evolution of the microstructure and the property of the MCT. The simulation results agree well with the corresponding experimental ones. The influence of the material’s flow line on the evolution of the orientation and morphology of the grains, and the property of the produced MCT are discussed in detail.

The impact of antecedent soil moisture content on soil erosion is a complicated phenomenon, which is still under argument with contradictions in research results. Hence, the objective of this study is to investigate the impact of antecedent soil moisture content to soil loss on clay soil by conducting two-year field experiments under natural rainfall on runoff plots with length of 10 meters, width of 3 meters, and uniform slope of 9%. Volumetric soil moisture sensors were used to log soil moisture changes, and soil moisture readings were used along with rainfall records to quantify the antecedent soil moisture conditions for each rainfall event. Results of this study show duration of the effective erosion event outranks the antecedent volumetric soil moisture content. Field study also suggests that accumulative rain falling within 48 hours (Pp48) prior to an effective erosion event strongly correlated with soil loss per Rainfall-Runoff Erosivity Index (Soil Loss / EI30), particularly when the duration of an effective erosion event is either between 3 ~ 7 hours or 10~ 30 hours. Hence, Pp48 can be considered as an alternative to replace antecedent soil moisture content in RUSLE 2’s cover and management factor.

Strong-aroma Baijiu is a traditional Chinese spirit distilled from grains that undergo solid-state fermentation. At the end of each fermentation cycle, a significant quantity of Huangshui accumulates at the bottom of the fermentation pit, constituting one of the primary by-products in the brewing process of strong-flavor liquor. In this report, the chemical component analysis of Huangshui obtained from a strong-flavor liquor factory revealed a diverse array of organic acids, alcohols, esters, starch, reducing sugars, amino acids, and other compounds present in Huangshui. Additionally, two specialized solid-state fermentation models were developed to investigate the formation process of Huangshui. Our findings demonstrate a positive correlation between the yield of Huangshui and the initial moisture content of fermented grains. It is concluded that Huangshui is the percolate produced during the solid-state brewing process of strong-flavor liquor, with its water content originating from the initial moisture of fermented grains.

Hyperspectral images (HSI) contain abundant spectral information. Efficient extraction and utilization of this information for image classification remain prominent research topics. Previously, hyperspectral classification techniques primarily relied on statistical attributes and mathematical models of spectral data. Deep learning classification techniques have recently been extensively utilized for hyperspectral data classification, yielding promising outcomes. This study proposes a deep learning approach that uses polarization feature maps for classification. Initially, the polar coordinate transformation method is employed to convert the spectral information of all pixels in the image into spectral feature maps. Subsequently, the proposed Deep Context Feature Fusion Network (DCFF-NET) is utilized to classify these feature maps. The model is validated using three open-source hyperspectral datasets: Indian Pines, Pavia University, and Salinas. The experimental results indicated that DCFF-NET achieves excellent classification performance. Experimental results on three public HSI datasets demonstrate that the proposed method accurately recognizes different objects with an overall accuracy (OA) of 86.68%, 94.73%, and 95.14% based on the pixel method, and 98.15%, 99.86%, and 99.98% based on the pixel-patch method.

With the significant annual increase in the market demand for biopesticides, the industrial production demand for predatory mites, which hold the largest market share among biopesticides, has also been rising.To achieve efficient and low energy consumption control of predatory mite breeding environmental parameters, accurate estimation of breeding environmental parameters is necessary. This paper collects and pre-processing hourly time-series data of temperature and humidity from industrial breeding environments. Time series prediction models such as SVR, LSTM, GRU, and LSTNet are applied to model and predict historical data of the breeding environment. Experiments validate that the LSTNet model is more suitable for such environmental modeling. To further improve prediction accuracy, the training data for the LSTNet model is enhanced using hierarchical clustering of time-series features. After augmentation, the root mean square error (RMSE) of temperature prediction decreased by 27.3%, and the RMSE of humidity prediction decreased by 32.8%, significantly improving the accuracy of multi-step predictions and providing substantial industrial application value.

This study used Dutch potatoes at the end of dormancy as the material to explore the impact of menthol (0.2 and 0.5 g/kg based on potato mass) treatment on sprouting inhibition and potato quality. The findings revealed that a menthol concentration of 0.5 g/kg effectively inhibited potato tuber sprouting and significantly reduced glucoside alkaloids production. After a storage period of 15 days, the sprouting percentage and glucoside alkaloids content of potatoes treated with 0.5 g/kg menthol were observed to be significantly lower at 4.17% and 68.63 mg/kg, respectively, compared to the control group which exhibited values of 100% and 282.01 mg/kg, respectively (P < 0.05). Throughout the storage period, 0.5 g/kg of menthol promoted respiration, reduced malondialdehyde production in potatoes, inhibited polyphenol oxidase activity, and slowed down tissue browning. Additionally, it mitigated the decline in starch and soluble protein content, inhibiting the accumulation of reducing sugars.

This study focuses on the decisions of picking, inventory, ripening, delivering, and selling mangoes in a harvesting season. Demand, supply, and prices are uncertain, and their probability density functions are fitted based on actual trading data collected from the largest spot market in Taiwan. A stochastic programming model is formulated to minimize the expected cost under the considerations of labor, storage space, shelf life, and transportation restrictions. We implement the sample-average approximation to obtain a high-quality solution of the stochastic program. The analysis compares deterministic and stochastic solutions to assess the uncertain effect on the harvest decisions. Finally, the optimal harvest schedule of each mango type is suggested based on the stochastic program solution.

Fracture is a global public health disease. Bone health and fracture risk have become the focus of public and scientific attention. Observational studies have reported that tea consumption is associated with fracture risk, but the results are inconsistent. The present study was conducted to evaluate whether tea consumption was causally associated with the risk of bone fracture through two-sample Mendelian Randomization (MR) analysis. We included a large genome-wide association study (GWAS) associated with tea consumption of 447,485 individuals and analyzed the effects of genetic instruments on fractures using fracture cases from the UK Biobank dataset (n=361,194). Inverse variance weighted (IVW) indicated no causal effects of tea consumption on fractures of the skull and face, shoulder and upper arm, hand and wrist, femur, calf, and ankle (odds ratio=1.000, P=0.881; OR=1.000, P=0.857; OR=1.002, P=0.339; OR=0.997, P=0.054; OR=0.998, P=0.569, respectively). Consistent results were also found in MR-Egger, weighted median, and weighted mode. Our research provided evidence that tea consumption is unlikely to affect the incidence of fractures.

Background: The phase III KEYNOTE-604 study confirmed the benefit of pembrolizumab combined with chemotherapy in the first-line treatment of extensive-stage small-cell lung cancer(ES-SCLC). Intergrated the clinical benefits of pembrolizumab and its high cost into account, this study aim to assess the cost-effectiveness of adding pembrolizumab to standard first-line etoposide-platinum (EP) for patients with ES-SCLC from the the US payer perspective. Methods: A Markov model was developed to compared the costs and quality-adjusted life-years (QALYs) of pembrolizumab plus EP and placebo plus EP over a 10-year time horizon. Clinical efficacy, treatment utilization and safety data were pooled from the KEYNOTE-604 trial. Utilities were obtained from published resources. Costs were mainly collected from Medicare in 2020. Sensitivity analyses were performed to examined the robustness of our model. Results: Adding pembrolizumab to standard first-line EP, resulted in better effectiveness than the use of EP alone for ES-SCLC by 0.22 QALYs. Pembrolizumab plus EP was dominated economically by placebo plus EP, leading to an incremental cost-effectiveness ratio(ICER) of $334,373/ QALY. Deterministic sensitivity analyses indicated that the uncertainty in model parameters exerts no substantial effect on our results. Probability sensitivity analysis indicated that probabilities for pembrolizumab plus EP being cost-effective within a wide rang of willingness to pay were modest. Conclusion: From the US payer perspective, the first-line treatment for ES-SCLC with pembrolizumab plus EP was not cost-effective compare with placebo plus EP. Although pembrolizumab combination chemotherapy was beneficial to the survival of ES-SCLC, price reduction may be the necessary measure to improve its cost-effectiveness.

MEMThe PdNi film hydrogen sensors with Wheatstone bridge structure were designed and fabricated by the micro-electro-mechanical system (MEMS) technology. The integrated sensors consisted of four PdNi alloy film resistors. The interval two of them were shielded with silicon nitride film and used as reference resistance, while the others were used for hydrogen sensing. The PdNi alloy films and SiN films were deposited by magnetron sputtering. The morphology and microstructure of the PdNi films were characterized with X-ray diffraction (XRD). The output resistance signal was converted to millivolt output voltage signal for easy data acquisition. Hydrogen (H2) sensing properties of PdNi film hydrogen sensor with Wheatstone bridge structure was investigated under different temperatures (30℃, 50℃ and 70℃) and H2 concentrations (from 10 ppm to 0.4%). The hydrogen sensor demonstrated good response at different hydrogen concentrations and high repeatability in cycle testing under 0.4% H2 concentration. Under 10ppm hydrogen, the PdNi film hydrogen sensor had evident and collectable output voltage of 600 μV.

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

Insulin-like Growth Factor 2 mRNA binding Protein 1 (IGF2BP1) is a promising candidate gene for influencing economic traits in livestock and poultry. The second intronic region of IGF2BP1 is closely related to growth traits, although the exact mechanism remains unclear. The preliminary resequencing results of goats in our laboratory demonstrated that the IGF2BP1 gene region was subject to strong selection, then we selected multiple single nucleotide polymorphisms (SNPs) to identify. Seven SNPs were located in the conserved region of the second intron, and their functions and relationship with growth traits require further clarification. This study selected 348 Nanjiang Yellow goats as experimental subjects, and chose Time of Flight Mass Spectrometer (MALDI-TOF) as the main method. Our results showed that six SNPs were significantly correlated with the growth traits of the Nanjiang yellow goat by association analysis. Among them, the rs652062749(A>G) was identified as the primary locus affecting the later stage of growth traits of Nanjiang yellow goat. Moreover, there was a strong linkage among three SNPs, and the rs638185407 (T>A) mutant type was observed to increase the luciferase activity in H293T cells extremely significantly. The TTAACT, TTCCCC, and ATCACT combination genotypes were dominant combination genotypes, which provided theoretical references for further genetic co-breeding. The results of our study demonstrate the potential role of the IGF2BP1 gene as a functional genetic marker in the breeding programs of Nanjiang Yellow goats.

We introduce a new generalized inverse which is a natural generalization of (pseudo) right core inverse in a Banach *-algebra. We characterize this generalized inverse by using right core and quasi-nilpotent decomposition. We then present its polar-like characterization and investigate related algebraic properties. Finally, the right core-EP inverse is characterized by certain new ways.

In order to solve the problem of large eddy current loss and high temperature rise caused by large amount of permanent magnet, a new type of combined magnetic pole permanent magnet motor is proposed in this paper. The sinusoidal distribution subdomain model of non-uniform air gap rotor is established by using Laplace equation, and the analytical expression of eddy current loss of rotor in uniform air-gap and non-uniform air-gap is derived. The effect of rotor eccentricity on eddy current loss is obtained. According to the characteristics of distributed winding of non-uniform air gap combined pole permanent magnet motor, equivalent treatment is performed to obtain the equivalent thermal conductivity, so as to establish equivalent thermal network model of motor, calculate the temperature value of each component of the motor, and verify the correctness of the thermal network model through the method of magnetothermal bidirectional coupling. Finally, an experimental platform is set up to carry out temperature rise experiments on the two prototypes respectively. Experimental results show that the non-uniform air-gap rotor structure can effectively reduce the rotor eddy current loss and motor temperature rise, and also verify the accuracy of the analytical model calculation results.

Classifying network flow subsequences in an Industrial IoT gateway is an effective method for identifying Industrial IoT faults. This paper proposes a subsequence classification algorithm SSGBUL-IKNN based on unsupervised learning encoding to address the problem of low classification accuracy. Firstly, we built a network module based on unsupervised learning to encode the flow sequence of the Industrial IoT gateway. In the encoding module, a subsequence calibration algorithm controls the increasing error during the coding process. Then, the specific fault type is obtained through an improved KNN classification algorithm based on the indication distance source from the integrated coding sequences converted by multi-dimensional network flow sequences. The test result on three Industrial IoT datasets of a sewage treatment plant shows that the accuracy of SSGBUL-IKNN in this paper exceeds 92%, significantly higher than the algorithm DTW and TSF. It reaches the classification requirements of Industrial IoT fault diagnosis.

In this paper, we study the global existence and exponential decay for a dynamic contact problem between a Timoshenko beam with second sound and two rigid obstacles, of which the heat flux is given by Cattaneo's law instead of the usual Fourier's law. The main difficulties arise from the irregular boundary terms, from the low regularity of the weak solution and from the weaker dissipative effects of heat conduction induced by Cattaneo's law. By considering related penalized problems, proving some a priori estimates and passing to the limit, we prove the global existence of the solutions. By considering the approximate framework, constructing some new functionals and applying the perturbed energy method, we obtain the exponential decay result for the approximate solution, and then prove the exponential decay rate to the original problem by utilizing the weak lower semicontinuity arguments.

This research takes Cuiwei Village in Qianshan District of Zhuhai City as an example. Through field research, the village is investigated and analyzed, and the street scale, spatial structure, functional characteristic streets, internal commercial distribution forms, and functions of Cuiwei Historic District are studied. analysis. On this basis, based on the convex space method and the line-of-sight analysis method in the space syntax theory, with the help of Depthmap software, the complex street node, that is, the space of the two nodes A and B, is established through the establishment of a visual field model. It includes the analysis of the integration degree of the horizon, the concentration of the horizon, the connection value of the horizon and the spatial characteristics of the historical area, as well as the traditional buildings that are the most representative of the village, namely the Three Kings Temple and the Webster's Mansion. When R=N and radius R=3, observe the changes in the two parameters of the visual integration and visual depth of the two historical buildings. And with the help of Baidu Time Machine photos in different periods to observe and record the changes in the store and the characteristics of people's behavior, and draw conclusions.

To estimate the progressive collapse resistance capacity of a multi-column frame tube structure with the assembled truss beam composite floor (ATBCF), the pushdown analysis, and the nonlinear dynamic analysis as well, are conducted for such a structure by using the alternate load path (ALP) method. The bearing capacities of the remaining structures at three different work conditions, which are the side middle column failure, the edge middle column failure, and the corner column failure, are individually studied, and the collapse mechanism for the remaining structures is analyzed from the aspects of the internal force redistribution and the failure mode of the second defense line. Simultaneously, the influence of the column failure time on the dynamic response of the remaining structure and the dynamic amplification coefficient are discussed. The results show that the residual bearing capacity of the remaining structure with the bottom corner column failure is higher than that of the one with the side or edge middle column failure, while the latter has a stronger plastic deformation capacity. When the ALP method is adopted to operate the progressive collapse analysis, it is reasonable to take the column failure time as 0.1 times of the first-order vertical vibration period of the remaining structure, and it is suitable to set the dynamic amplification coefficient as of 2.0, which is the ratio of the maximum dynamic displacement to the static displacement of the remaining structure under the transient loading condition.

The paper addresses the challenging issue of trajectory tracking for uncertain quadrotor UAVs, particularly under the constraints of input saturation and external disturbances. It introduces adaptive laws for managing uncertainties in mass and inertia moments without requiring prior knowledge, ensuring effective control even with varying system parameters. To counteract the effects of input saturation, the study incorporates an auxiliary system designed to compensate for these limitations. Additionally, a disturbance observer(DO) is utilized to manage and mitigate the impact of time-varying external disturbances. The proposed control strategy integrates a sliding mode adaptive control approach with an inner-outer loop structure, enhancing robustness and adaptability. Numerical simulations demonstrate the effectiveness of the designed control strategy.

This paper proposes a novel facial expression recognition network called the Lightweight Facial Network with Spatial Bias (LFNSB). The LFNSB model balances model complexity and recognition accuracy. It has two key components: a lightweight feature extraction network (LFN) and a Spatial Bias (SB) module for aggregating global information. The LFN introduces combined channel operations and depthwise convolution techniques, effectively reducing the number of parameters while enhancing feature representation capability. The Spatial Bias module enables the model to focus on local facial features while also capturing the dependencies between different facial regions. Additionally, a novel loss function called Cosine-Harmony Loss is designed. This function optimizes the relative positions of feature vectors in high-dimensional space, resulting in better feature separation and clustering. Experimental results on the AffectNet and RAF-DB datasets show that the proposed LFNSB model performs excellently in facial expression recognition tasks. It achieves high recognition accuracy while significantly reducing the number of parameters, thus substantially lowering model complexity.

Wireless sensor networks (WSN) are widely used in various fields such as military, industrial and transportation for real-time monitoring, sensing and data collection of different environments or objects. However, the development of WSN is hindered by several limitations, including energy, storage space, computing power and data transmission rate. Among these, the availability of power energy plays a crucial role as it directly determines the lifespan of WSN. To extend the life cycle of WSN, two key approaches are power supply improvement and energy conservation. Therefor, we proposed an energy harvesting system and a low energy consumption mechanism for WSN. Firstly, we delved into the energy harvesting technology of WSN, explored the utilization of solar energy and mechanical vibration energy to ensure a continuous and dependable power supply to the sensor nodes, and analyzed the voltage output characteristics of bistable piezoelectric cantilever. Secondly, we proposed a neighbor discovery mechanism that utilizes a separation beacon, is based on reply to ACK, and can facilitate the identification of neighboring nodes. This mechanism operates at a certain duty cycle ratio, significantly reduces idle listening time and results in substantial energy savings. In comparison to the Disco and U-connect protocols, our proposed mechanism achieves a remarkable reduction of 66.67% and 75% in the worst discovery delay, respectively. Furthermore, we introduced a data fusion mechanism based on integer wavelet transform. This mechanism effectively eliminates data redundancy caused by spatio-temporal correlation, results in a data compression rate of 5.42. Additionally, it significantly reduces energy consumption associated with data transmission by the nodes.

Abstract: Dispersal strategies of a species can affect its invasion success. Investigation into the dispersal strategies of invasive species in relation to different factors helps our understanding of the invasion mechanisms and provides knowledge for population management and invasion evaluation. Tetranychus ludeni Zacher (Acari: Tetranychidae) is an invasive species, which is native to Europe but now cosmopolitan. Here, we examined the effects of age and density on dispersal in mated females. Our results show that older females with more eggs were more likely to disperse and moved longer distances than younger ones with fewer eggs. Older females spread most of their eggs out of the natal habitats and over longer distances, which reduced competition and increased offspring fitness. Females significantly increased dispersal probability and distance with the increase of population density to avoid crowding. The synchronization of dispersal and reproduction, along with the positive density-dependent dispersal strategy, may facilitate habitat colonization and invasion speed of T. ludeni.

The details of antigen-antibody interactions and the identification of epitopes are critical for the development of monoclonal antibody drugs. Ab42 is a native human-derived anti-CFH monoclonal antibody. In this study, the interaction between antigen pCFH and antibody (Ab42) was theoretically demonstrated by molecular docking and MD simulation, combined with free energy calculation and computational alanine scanning (CAS), and key amino acids and epitopes were identified. Experimental alanine scanning (EAS) was then carried out to verify the results of the calculation, and our results indicated that Ab42 antibody forms hydrogen bonds and interacts hydrophobically with pCFH through the Tyr315, Ser100, Gly33, and Tyr53 residues on its CDR, while the main pCFH epitopes are located at the six sites of Pro441, Ile442, Asp443, Asn444, Ile447, and Thr448. In conclusion, this study has explored the mechanism of antigen-antibody interaction from both theoretical and experimental aspects, and our results have important theoretical significance for the design and development of relevant antibody drugs.

Shrews (Soricidae) are common small wild mammals. Some species of shrews, such as Asian house shrews (Suncus murinus), have a significant overlap in their habitats with humans and domestic animals. Currently, over 190 species of viruses in 32 families, including Adenoviridae, Arenaviridae, Arteriviridae, Astroviridae, Anelloviridae, Bornaviridae, Caliciviridae, Chuviridae, Coronaviridae, Filoviridae, Flaviviridae, Hantaviridae, Hepadnaviridae, Hepeviridae, Nairoviridae, Nodaviridae, Orthoherpesviridae, Orthomyxoviridae, Paramyxoviridae, Parvoviridae, Phenuiviridae, Picobirnaviridae, Picornaviridae, Polyomaviridae, Poxviridae, Rhabdoviridae, Sedoreoviridae, Spinareoviridae, and three unclassified families, have been identified in shrews. Diverse shrew viruses, such as Borna disease virus 1, Langya virus, and severe fever with thrombocytopenia syndrome virus, cause diseases in humans and/or domestic animals, posing significant threats to public health and animal health. This review compiled fundamental information about shrews and provided a comprehensive summary of the viruses that have been detected in shrews, with the aim of facilitating a deep understanding of shrews and the diversity, epidemiology, and risks of their viruses.

Weak signal spectral detection is a serious problem in many applications, especially the target possesses certain frequency band and under low signal-to-noise ratio (SNR). A kind of novel technique based on pre-whitening scale-transformation symmetric bistable parallel stochastic resonance (SR) is proposed to solve the problem. Firstly, the pre-whitening can ensure the even distribution of the receiving signal to fit the requirement of SR processing. Secondly, the scale- transformation can help to utilize the weak signal improvement property especially under low frequency band more effectively. Thirdly, the symmetric bistable parallel SR can try to reduce the variance of the clutter and additive noise fluently. Fourthly, by subtracting the steady state re-sponse of the selected symmetric bistable SR system from the parallel SR output, the weak signal spectral detection objective can be realized successfully. Simulation results based on the real sea clutter radar data guarantee the effectiveness and applicability of the proposed symmetric bistable PSR processing approach.

Flexible humidity sensors (FHS) with fast response and durability to high-humidity environment are highly desirable for practical applications. Herein, an FHS based on crosslinked sodium alginate (SA) and MXene was fabricated, which exhibited high sensitivity (impedance varied from 107 to 105 Ω between 10% and 90% RH), good selectivity, prompt response (response/recover time of 4 s/11 s), high sensing linearity (R2 = 0.992) on a semi-logarithmic scale, relatively small hysteresis (~5% RH), good repeatability, and good resistance to high humid environment (negligible change in sensing properties after placed in 98% RH over 24 h). It is proposed that the formation of crosslinking structure of SA and introduction of MXene with good conductivity and high specific surface area contributed to the high performance of the composite FHS. Moreover, the FHS could promptly differentiate respiration status, recognize speech and measure fingertip movement, indicating potentials in breath monitoring and non-contact human-machine interactions. This work provides guidance for developing advanced flexible sensors with wide application scope in wearable electronics.

The esterification of propylene glycol methanol (PM) and acetic acid (AA) is an important reaction for the production of propylene glycol methyl ether acetate (PMA). Herein, we used macroporous ion exchange resin Amberlyst-35 as a catalyst to explore the effects of reaction conditions on the reaction rate and equilibrium yield of PMA. Under the optimized conditions of reaction temperature of 353 K, initial reactant PM/AA molar ratio of 1:3, and catalyst loading of 10 wt%, PMA equilibrium yield reached 78%, which is the highest equilibrium yield so far. The reaction equilibrium constants and activity coefficients were estimated to obtain reaction thermodynamic properties, indicating the exothermicity of the reaction. Furthermore, Pseudo-homogeneous (PH), Eley-Rideal (ER), and Langmuir-Hinshelwood-Hogen-Watson (LHHW) kinetic models were fitted based on experimental reaction kinetic data. The results demonstrate that the LHHW model is the most consistent with experimental data, indicating surface reaction controlled process and exhibiting an apparent activation energy of 62.0 kJ/mol. This work represents a valuable example of calculating the reaction thermodynamic and kinetics, which are particularly essential for promising industrial reactor design.

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

Carnivore protoparvovirus 1 (CPPV-1) is a DNA virus causing gastrointestinal disease and immunosuppression in various terrestrial carnivores. Domestic dogs and cats are considered the primary CPPV-1 reservoirs. The habitat overlaps of wild carnivores and free-roaming dogs increases the threat of CPPV-1 transmission between them. This study explored the CPPV-1 distribution among wild carnivores through PCR screening and compared the DNA sequences of the partial capsid protein (VP2) between wild and domestic carnivores. In total, 181 samples were screened for the CPPV-1 VP2 gene, including 32 masked palm civets (Paguma larvata), 63 Chinese ferret badgers (Melogale moschata), and 86 crab-eating mongooses (Herpestes urva), from 2015 to 2019 in Taiwan. The average prevalence of CPPV-1 was 17.7% (32/181), with the highest prevalence in masked palm civets (37.5%). In addition, a masked palm civet was coinfected with two CPPV-1 strains. Among the 33 partial VP2 gene sequences, 23 were identical to sequences amplified from domestic dogs and cats in Asia and the remaining 10 were identified for the first time. This study demonstrated that CPPV-1 has circulated between domestic and wild carnivores in rural Taiwan. Therefore, further population control and health management of free-roaming domestic carnivores are recommended.

A facile iridium/graphene-catalyzed methodology providing an efficient synthetic route for C-N bond formation is reported. This catalyst can directly promote the formation of C-N bonds, without pre-activation steps, and without solvents, alkalis and other additives. This protocol provides a direct N -alkylation of amines using a variety of primary and secondary alcohols with good selectivity and excellent yields. Charmingly, the use of diols resulted in intermolecular cyclization of amines, and such products are privileged structures in biologically active compounds. Two examples illustrate the advantages of this catalyst in organic synthesis: the tandem catalysis to synthesize hydroxyine, and the intermolecular cyclyzation to synthesize cyclizine. Water is the only by-product, which makes this catalytic process sustainable and environmentally friendly.

Deep learning methods paired with sidescan sonar (SSS) are commonly used in underwater search and rescue operations for drowning victims, wrecks, and airplanes. However, these techniques are primarily designed to detect mine-like objects and are rarely applied to identifying features in dynamic dredge pit environments, due to a lack of datasets. In this study, we present a Sandy Point Dredge Pit (SPDP) dataset, in which high-resolution SSS data were collected from the west flank of Mississippi bird foot delta of the Louisiana inner shelf. This dataset contains a total of 385 SSS images. We introduce an Effective Geomorphology Classification model (EGC). By ablation studies, we analyze the utility of transfer learning on different model architectures and the impact of data augmentations on model performance. This EGC model will make geomorphic features identification in dredge pit environments quick and efficient which requires extensive experience and professional knowledge. The combination of SSS images and EGC model is a cost-effective and valuable toolkit for hazards monitoring in marine dredge pit environment. The SPDP SSS images dataset, especially the feature of pit wall without rotational slump, is also valuable for other machine learning modelers.