The CdS nanoparticles were constructed on one-dimensional (1D) CeO2 nanorods by two-step hydrothermal method. The X-ray diffraction (XRD), transmission election microscopy (TEM), Raman spectra, X-ray photoelectron spectra (XPS) and VU-vis diffuse reflection spectroscopy (DRS) techniques were used to characterize these CdS/CeO2 nanocomposites. It is concluded that when the molar ratio of CdS and CeO2 was 1:1, the nanocomposites exhibited the best photo-catalytic desulfurization activity, reaching 92 % in 3 hours. Meanwhile, transient photocurrent (PT) measurement, photoluminescence (PL) spectra and electrochemical impedance spectroscopy（EIS）measurement indicated that the modification of CeO2 nanorods by CdS nanoparticles could sig-nificantly inhibit the recombination of photogenerated electrons and holes. In addition, the pos-sible mechanism of photocatalytic oxidation desulfurization of the nanocomposites was proposed. This study may provide an effective CeO2-based photocatalysts for photocatalytic desulfurization applications.

Drip irrigation systems are becoming more and more mature and are present extensively applied to increase crop yield and water use efficiency in Xinjiang, northwest China. To investigate the effects of irrigation quota on maize growth, the grain yield, and the irrigation water use efficiency (IWUE), a field experiment with four irrigation quotas (T1 4200m3·hm-2, T2 4800m3·hm-2, T3 5400m3·hm-2 and T4 6000m3·hm-2.) were conducted from 2013 to 2021 in Xinjiang China. The re-sults showed significant changes in maize growth, yield, and irrigation water use efficiency in response to different irrigation quotas. The plant height, leaf area index, SPAD, biomass, yield and harvest index of maize at different irrigation quotas all showed a “single peak curve”, and its change was closely related to the irrigation level. The growth index, dry matter accumulation, yield and irrigation water use efficiency with T3 were the highest. The dry matter transfer effi-ciency, contribution of dry matter translocation to grain and the harvest index with T3 showed significant increase of 13.86%, 26.06%, 29.93% and 7.62% compared to T1, respectively. In com-parison to T1, T2 and T4, the yield of T3 increased by 32.17%, 13.54% and 11.27% respectively, and the irrigation water use efficiency (IWUE) increased by 2.80%, 0.93% and 23.63% respectively. The significant correlations established between the maize yield and irrigation quotas could be sim-ulated by kuznets-style relation. The maize yield was negative correlated with irrigation quotas, When the irrigation quota (x) was 5376.73m3·hm-2, the maize yield (y) was 15841.00m3·hm-2. These results demonstrate that the optimized irrigation quota (5400m3·hm-2 treatment) can effectively improve the growth, yield and irrigation water use efficiency of drip irrigation maize in North-west China. In the meanwhile, it can provide theoretical reference and data support for the op-timal irrigation amount of drip irrigation maize in Northwest Xinjiang.

Codon use bias is an important characteristic in the process of genetic information transmission of species. With the publication of the genome of C. panzhihuaensis, it is of great significance to investigate the codon use bias for understanding the genetic evolution of this species and for molecular breeding. In this study, Perl language and CodonW 1.4.2 software was used to systematically analyze the coding gene sequences of the C. panzhihuaensis genome, obtain the characteristics of codon use, and identify the sources of variation affecting codon use. The results showed that GC3s content, GCall content, and ENC value were 46.75%, 47.67%, and 52.8 respectively. As the first seed plant, the GC3 content of Cycas is similar to that of most gymnosperms and most dicotyledons, but considerably different from that of monocotyledons.RSCU value was greater than 1, among which 21 codons ended in U or A. Enc-plot analysis, PR2-plot neutral plot analysis, and correlation coefficient analysis of Axis1 with GC3s and CAI revealed that the codon bias was mainly affected by natural selection, but also by mutation pressure and other factors. Thirty-one optimal codons of Cycas genes were screened. This research can provide a reference for the phylogeny and genome codon evolution of Cycas.

Chemical weed control using herbicide glyphosate to manage emerged weeds is an important production practice in Florida citrus. Despite the extensive use of glyphosate in citrus orchards, very limited information is available on its environmental fate and behavior in Florida soils that are predominantly sandy in nature. Hence, the study's objective was to understand the adsorption-desorption, dissipation dynamics, and vertical movement or leaching of glyphosate in sandy soils in citrus orchards. Laboratory, field, and greenhouse experiments were conducted at Southwest Florida Research and Education Center in Immokalee, Florida. The adsorption-desorption behavior of glyphosate in the soils from three major citrus production areas in Florida was studied utilizing a batch equilibrium method. The dissipation of glyphosate was tracked in the field following its application at the rate of 4.20 kg ae ha-1. Soil leaching columns in greenhouse conditions were used to study the vertical movement of glyphosate. The results suggest that glyphosate has a relatively lower range of adsorption or binding (Kads = 14.28 to 30.88) in the tested soil types. The field dissipation half-life (DT50) of glyphosate from surface soil was found to be 26 days. Glyphosate moved vertically or leached into the soil profile, up to 40 cm in the soil column, when analyzed 40 days after herbicide application. The primary degradation product of glyphosate, i.e., aminomethyl phosphonic acid (AMPA), was also detected up to the depth of 30 cm below the soil surface, indicating the presence of microbial metabolism of glyphosate in the soil.

Surface passivation, which has been intensively studied recently, is essential for the perovskite solar cells (PSCs), due to the intrinsic defects in perovskite crystal. A series of chemical or physical methods have been published for passivating the defects of perovskite, which effectively suppressed the charge recombination and enhanced the photovoltaic performance. In this study, the n-type semiconductor of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) is dissolved in chlorobenzene (CB) for the surface passivation during the spin-coating process for depositing the two-dimensional (2D) perovskite film. This approach simplifies the fabrication process of 2D PSCs and benefits the film quality. As a result, the defects of perovskite film are effectively passivated by this method. A better perovskite/PCBM heterojunction is generated, exhibiting an increased film coverage and improved film morphology of PCBM. It is found that this technology results in an improved electron transporting performance as well as suppressed charge recombination for electron transport layer. As a result, PSCs based on the one-step formed perovskite/PCBM heterojunctions exhibit the optimized power conversion efficiency of 15.69% which is about 37% higher than that of regular perovskite devices. The device environmental stability is also enhanced due to the quality-improved electron transport layer.

The high-power Asymmetric half-bridge Converter (AHBC) LED constant current driver controlled by digital current mode is a fourth-order system. Static operating point, parasitic resistance, load characteristics, sampling effect, modulation mode and loop delay will have great influence on its dynamic performance. In this paper, the small-signal pulse transfer function of the driver is established by the discrete-time modeling method for the two operating points corresponding to the three modulation modes of the trailing edge, leading edge and double edge. And, the effects of parasitic parameters, delay effect, sampling effect and load effect are fully considered in modeling. For a large number of complex exponential matrix operations, the first order Taylor formula is used for approximate calculation after the coefficient matrix is obtained by substituting the data. Then, Matlab software is used to compare and analyze the discrete-time model and the discrete-average model. The results show that the proposed discrete-time model can more accurately characterize the resonant peak and high-frequency dynamic characteristics, and is very suitable for the design of high frequency digital controller.

The explosive emergence of wireless technologies and standards, covering licensed and unlicensed spectrum bands has triggered the appearance of a huge amount of wireless technologies, with many of them coexisting in the same band. Unfortunately, the wireless spectrum is a scarce resource, and the available frequency bands will not scale with the foreseen demand for new capacity. Certain parts of the spectrum, in particular the license-free ISM bands, are overcrowded, while other parts, mostly licensed bands, may be significantly underutilized. As such, there is a need to introduce more advanced techniques to access and share the wireless medium, either to improve the coordination within a given band, or to explore the possibilities of intelligently using unused spectrum in underutilized (licensed) bands. Therefore, in this paper, we present a SDR based framework that can be employed to devise disruptive techniques to optimize the sub-optimal use of radio spectrum that exists today. Additionally, we describe two use cases for the proposed framework.

In terrain analysis and hydrological modeling, surface depressions (or sinks) in a digital elevation model (DEM) are commonly treated as artifacts and thus filled and removed to create a depressionless DEM. Various algorithms have been developed to identify and fill depressions in DEMs during the past decades. However, few studies have attempted to delineate and quantify the nested hierarchy of actual depressions, which can provide crucial information for characterizing surface hydrologic connectivity and simulating the fill-merge-spill hydrological process. In this paper, we present an innovative and efficient algorithm for delineating and quantifying nested depressions in DEMs using the level-set method based on graph theory. The proposed level-set method emulates water level decreasing from the spill point along the depression boundary to the lowest point at the bottom of a depression. By tracing the dynamic topological changes (i.e., depression splitting/merging) within a compound depression, the level-set method can construct topological graphs and derive geometric properties of the nested depressions. The experimental results of two fine-resolution LiDAR-derived DEMs show that the raster-based level-set algorithm is much more efficient (~150 times faster) than the vector-based contour tree method. The proposed level-set algorithm has great potential for being applied to large-scale ecohydrological analysis and watershed modeling.

The ANFC/ABPE-10 composite film was prepared by ABPE-10 impregnating into ANFC films under negative pressure. And the composite film had meted high performance FOLED substrate requirement even when ANFC dosage was high for approximately 70%, which was consistent with for low cost efficiency, recyclability, and environmentally friendly. The enhanced properties of ANFC films were mainly because of the nature of ABPE-10 itself and the IPN structure formed between ABPE-10 and ANFC film. The transparency of composite films with different ANFC dosage was significantly increased from 67% to 88% by UV-Vis analysis. The composite film inherited the properties of AFNC, obtaining low CTE characteristics and ductile compact structure. The contact angles of ANFC films increased by 102% from 49.2° to 102.9°after dipping ABPE-10. Additionally, the composite films had outstanding mechanical properties such as tensile strength 173.72 MPa, Young’s modulus 4.06 GPa, and elongation at break 5.81%.

This study investigates the transformative impact of ChatGPT, a cutting-edge AI language model developed by OpenAI, on the financial sector. We explore ChatGPT's applications in financial analysis, focusing on its ability to perform tasks traditionally handled by human analysts. By creating a set of multi-step and advanced reasoning financial tasks, and establishing several task-specific evaluation metrics, our experimental results demonstrate that ChatGPT-4o can effectively perform both basic and some complex financial analysis tasks comparable to those executed by humans. However, our empirical evaluation reveals limitations in its performance on complex tasks that require comprehensive understanding and critical thinking. The study highlights the necessity for meticulous task formulation and robust evaluation to achieve consistent functionality. While ChatGPT enhances efficiency in financial analysis, its integration with human expertise remains crucial for effective decision-making. This study contributes to the understanding of AI's role in finance and provides insights into its potential and constraints, guiding future integration of AI technologies in financial practices.

Based on the electron-deficient property of picric acid (PA), two neutral Ir(III) complexes 1 and 2 modified with the electron-rich carbazolyl groups were synthesized and characterized. Both 1 and 2 exhibit aggregation-induced phosphorescence emission (AIPE) properties in THF/H2O. Among them, 2 is extremely sensitive for detecting PA with a limit of detection of 0.15 μM in THF/H2O. Furthermore, the selectivity for PA is significantly higher compared to other analytes, enabling efficient detection of PA in four common water samples. The density functional theory calculations and the spectroscopic results confirm that the sensing mechanism is photo-induced electron transfer.

The production of municipal solid waste incineration bottom ash (MSWIBA) is very massive and has the potential to replace cement despite the problems of complex composition, uneven particle size distribution, and low reactivity. This paper adopts sodium silicate activation of MSWIBA-slag to improve the reactivity to prepare composite cementitious materials. It explores the hydration performance study of the composite cementitious materials by isothermal calorimetric analysis, Fourier Transform Infrared (FTIR) spectroscopy, XRD physical diffraction analysis, and SEM/EDS tests. SEM/EDS tests will be used to explore the hydration properties of the composite gelling. The results showed that with the increase of MSWIBA doping, the porosity between the materials increased, the degree of Hydration decreased, and the compressive strength decreased with the rise of MSWIBA. When sodium silicate increased from 25% to 35%, too much alkaline material occurred over the alkaline effect, which inhibited the Hydration of the particles, and the degree of hydration reaction decreased, and the compressive strength decreased accordingly; the exothermic process of Hydration can be mainly divided into five stages, quartz and calcite did not participate in the hydration reaction completely, and sexual aluminum participated in the hydration reaction. The vibrational peaks of Si-O-Ti (T = Si and Al) were present in the material. The vibrational peaks of XRD, FTIR, and SEM-EDS all indicate the presence of silica-aluminate network structures in the hydration products, mainly N-A-S-H and C-A-S-H gels.

This is a brief critique of the functions—particularly olfactory functions—specified for the “Chemosensory Protein” (CSPs) molecule family. On the basis of these proteins’ presence in the sensory antennal lymph of locusts, odor chemosensory ligand binding functions have been hypothesized. According to this hypothesis, the entire protein molecule superfamily is referred to as “CSPs”. However, new information and developments in the field of CSP molecular research, such as the expression of CSP genes in the gut, brain, fat body, epidermis, and pheromone gland, as well as gene expression profiling from most early developmental stages—that is, CSP expression well in advance of the appearance of chemical sense nerve cells—strongly suggest that the protein molecule has other roles that are unrelated to chemosensing. Moreover, CSPs are found in bacterial microbial prokaryote organisms in addition to insects. Thus, we examine the molecule’s name, definition, RNA editing, protein structure, lipid binding properties, DNA interaction, and evolutionary characteristics in brief before referring to this protein family as “Chemosensory Proteins”. This article tries to compel and discuss the most recent information as a way to rename this protein family. Because of its highly conserved molecular distinctive feature (four adjacent cysteines), we propose renaming “CSPs” as “4CSPs” (4 Cysteines Soluble Proteins).

Soil improvement methods can result in changes in the microbial community in blueberry soil. However, there have been few reports on the impacts of different soil improvement methods on the microbial function, particularly on endophytic microbe. In this study, we analyzed the response of microbial community composition, microbial function and nitrogen (N) cycle to different improvement methods using high throughput sequencing. We aimed to investigate the best soil improvement method from a microbial perspective. The results showed that the highest microbial diversity was observed in the T4 treatment (peat combined with mushroom bran), followed by the T2 treatment (peat combined with acidified rice husk) both in the rhizosphere and roots. The dominant phyla were Proteobacteria and Actinobacteria, which were most abundance in the T4 and T1 (peat combined with sulfur) treatments in the rhizosphere soil, respectively, but showed the opposite trend in the root endophytic bacterial community. Interestingly, Acidobacterium and Paludibaculum, belonging to the Acidobacteria phylum, were found to have the highest influence according to the correlation network analysis. And these bacteria were most abundant in the T2 treatment in the rhizosphere soil. The rhizosphere soil microbial communities were clustered into two categories: one for T1 and T2 treatments, and another for T3 (mushroom bran) and T4 treatments. Compared to the other treatments, the T1 treatment had the most significant impact on microbial functional pathways in the blueberry roots. T2 treatment promoted the growth of N fixation functional bacteria both in the rhizosphere soil and roots. At the module level, the T2 treatment increased the relative abundance of N fixation and decreased the relative abundance of assimilating nitrate reduction reaction (ANRA), dissimilating nitrate reduction reaction (DNRA), denitrification and completed nitrification in the blueberry rhizosphere soil. Additionally, the T2 treatment increased the abundance of root endophytic microbes involved in N fixation. Overall, our findings suggest that the addition of peat combined with acidified rice husk is the optimal soil improvement method for blueberry cultivation.

The overpopulation of feral pigeons in Hong Kong has significantly disrupted the urban ecosystem, highlighting the urgent need for effective strategies to control their population. In general, control measures should be implemented and re-evaluated periodically following accurate estimations of feral pigeon population in the concerned regions, which, however, is very difficult in urban envi-ronments due to the concealment and mobility of pigeons within complex building structures. With the advances in deep learning, computer vision can be a promising tool for pigeon monitoring and population estimation but has not been well investigated so far. Therefore, we propose an improved deep learning model based on Mask-RCNN (Swin-Mask R-CNN) for feral pigeon detection using computer vision techniques. Specifically, our model consists of a Swin transformer network (STN) as the backbone, a feature pyramid network (FPN) as the neck, and three decoupled detection heads. The STN is utilized to extract deep feature information of feral pigeons through local and cross-window attention mechanisms. The FPN is employed to fuse multi-scale features and enhance the multi-scale learning ability. Heads in the three branches are responsible for classification, pre-dicting best bounding boxes, and segmentation of feral pigeons, respectively. During the prediction phase, a Slicing Aided Hyper Inference (SAHI) tool is employed to zoom in on the feature infor-mation of small feral pigeon targets, and the segmentation head is frozen to expedite inference of large images. Experiments were conducted on feral pigeon dataset to evaluate model performance. The results reveal that our model is well-suited for detecting small targets in high-resolution images and achieves excellent recognition performance for feral pigeons with a mAP (mean average pre-cision) and an AP50 (average precision at 50% intersection over union) of 0.74 and 0.93, respectively. For small target feral pigeons, AP50 in small scale (AP50s) improved by 10% as compared to the Mask R-CNN (AP50s of 0.75), demonstrating its potential for dynamic pigeon detection and population estimation in the future.

This research investigates the environmental characteristics of the saline lake in the Jiangling depression, southwestern Jianghan Basin from Paleocene to Eocene using bulk-rock geochemistry. The ratios of FeO/MnO, Al2O3/MgO and C-value indicate a semi-humid to semi-arid climate in the early-middle Paleocene. There was a rapid shift to a humid climate during the late Paleocene to early Eocene, following a short-time intense dryness. The Eocene climate was arid, but experienced intermittent humidity. The variation trend of CIA, CIW and PIA is similar to that of FeO/MnO, Al2O3/MgO and C-value, so the chemical weathering was influenced by climate changes. The redox conditions of lake in the Jiangling depression during Paleocene to Eocene were reconstructed using the ratios of U/Th, Ni/Co, and V/Cr. In the humidity and alternations of aridity and humidity, the lake water received external water input, resulting in weak stratification, so the sediments were in oxidation condition. In the aridity, lakes become a still water environments, leading to sediments formed in reduced condition. The salinity of the lake in Jiangling depression from Paleocene to Eocene was determined through the analysis of sedimentary sequences and the change of Sr/Ba ratio. In the early-middle Paleocene, the salinity of lake varied greatly. From the late Paleocene to the early Eocene, the salinity of lake decreased. In the Eocene, the salinity of the lake increased, and the halite precipitated, and finally the salinity of the lake decreased due to humid climate.

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

The latest experimental measurements of cosmic rays (CRs) have discovered a series of anomalies, including the hardening of the nuclear spectra at R ∼200 GV followed by softening at R ∼10 TV and complicated energy dependence of anisotropy from GeV to PeV. Recent works have demonstrated nearby sources are crucial for these anomalies of spectra and anisotropy. In this work, we analyze the contributions of five nearby sources within 1 kpc around solar system to the spectra and anisotropy, finally find out which source is the best candidate source. In the calculation process, we also introduce the anisotropic diffusion of CRs induced by the local interstellar magnetic field (LIMF) nearby the solar system based on spatial-dependent propagation (SDP) model. As a result, we find Geminga SNR source can simultaneously account for CR spectra and anisotropy, whereas the other sources can not . Measurements of CR anisotropy and spectra by experiments such as LHAASO and HAWC are expected to test this scenario in the near future.

Bacillus subtilis NCD-2 showed a promising biocontrol effect against plant soil-borne diseases, and was developed as a commercial microbial fungicide against cotton verticillium wilt in China. Spores were main ingredient of the fungicide and played the crucial role in biological control of plant diseases. Therefore, the key to reducing the cost of fungicide was to find ways to increase the number of spores of strain NCD-2 during fermentation. In this study, 755 substances were evaluated by Phenotype Microarray technology, and 5 kinds of carbon sources and 1 kind of nitrogen source were found to promote the metabolism of strain NCD-2. Among carbon sources L-arabinose showed strongest ability to promote the bacteria growth and sporulation of strain NCD-2. When L-arabinose was used as a single carbon source, it could increase the bacteria concentration and the sporulation efficiency of strain NCD-2 by 2.04 times and 1.99 times, respectively, compared with D-glucose. Moreover, L-arabinose could significantly decrease the autolysis of strain NCD-2 revealed by microscopy observation. The mechanism for promoting the sporulation by L-arabinose was analysed by RNA-seq sequencing. Results showed that total of 790, 923 and 1270 genes were up-regulated and 639, 850 and 1001 genes were down-regulated under L-arabinose supplies when cultured at 8 h, 12 h and 16 h, respectively. Fourteen differentially expressed genes associated with arabinose transportation and sporulation were selected for qRT-PCR analysis, and the result showed basically consistent expression trend with transcriptome. Notably, genes associated with arabinose metabolism, sporulation, spore resistance to heat and spore coat formation were significantly up-regulated, and genes associated with sporulation-delaying protein were significantly down-regulated under L-arabinose supplies. msmX gene which was involved in arabinose transport in Bacillus genus was deleted, and the mutant decreased the growth and sporulation by 53.71% and 86.46%, respectively, when compared to strain NCD-2 wild type. Complementary of the mutant by importing intact msmX gene could restore the growth and sporulation of the mutant strain. In conclusion, arabinose played an important role in regulating the growth and sporulation of strain NCD-2.

The recognition of coal-rock interface is very crucial for the research in the intelligent production of coal mine. This study investigates the application of terahertz time-domain spectroscopy in the recognition of coal-rock interface, including the identification of coal-rock and coal-rock mixtures, as well as the accurate characterization of coal seam thickness. Terahertz detection was used to obtain the optical parameter information of the pressed pellets prepared by mixing two different kinds of coal and two kinds of rock. Based on the experiment results, the database was established for the identification of coal-rock interfaces in coal mining machines. The terahertz detection was performed on 10 different kinds of sheet anthracite with different thickness, and the terahertz spectra of coal seams with different thickness were simulated and calculated by using simulation software, which can accurately obtain the thickness of coal seams and provide effective mining thickness parameters for coal seam mining. Through the experiment and simulation, the terahertz time-domain spectroscopy technology has a promising application prospect in the identification of coal-rock interface.

Under the influence of various factors, the bronze ware unearthed by archaeology has various diseases of different degrees, and the mineralization problem is more prominent. The physical properties of mineralized bronzes have been destroyed, and the whole is loose and fragile, which is in urgent need of reinforcement and protection. Common reinforcement and protection materials mainly consider surface sealing, matrix bonding reinforcement and penetration reinforcement. Considering the low matrix strength and complex disease types of fragile bronzeware, it is difficult to achieve targeted protection with commonly used reinforcement and protection materials. In view of the problems such as poor permeability and easy discoloration of commonly used protection materials, this paper uses self-developed reinforcement and protection material AMC to compare its reinforcement and protection performance with B72, which has a high comprehensive evaluation on the performance of commonly used reinforcement and protection materials. The matrix strength was increased, and the appearance intervention degree was less than B72.

Fiber coupling efficiency is one of the key technical indicators of atmospheric laser communication, which directly affects the communication system BER. According to the optical fiber coupling efficiency model, the optical fiber coupling model under atmospheric slant link is established, and the relationship between wavelength, zenith angle, receiving aperture, altitude and coupling efficiency is studied through numerical simulation. Based on the principle of adaptive optics turbulence correction, the relationship between fiber coupling efficiency and adaptive optics order is established. A fast method for estimating the coupling efficiency based on Strehl ratio is proposed. According to the principle of laser communication system, the semi-physical simulation experimental system of atmospheric slant-range channel coupling efficiency is constructed, and the coupling efficiency test and analysis are completed.

In recent years, frequent occurrences of low temperature disasters due to global climate change have significantly impacted the normal growth of crops. Research has indicated that inorganic selenium (which is more toxic) can not only enhance the effects of low temperature stress but also increase selenium content on plants; however, there is a scarcity of studies investigating the impacts of organic selenium and nano-selenium on crops. In order to investigate whether organic selenium and nano-selenium can enhance low-temperature tolerance and increase selenium content in pak choi (Brassica chinensis var. pekinensis. cv. ‘Suzhouqing’), different concentrations (0, 5, 10, 20 mg L-1) of exogenous selenium were applied in this experiment to assess their effects on plant growth, nutritional quality and antioxidant properties. RNA-Seq technology was used to sequence the transcriptome of the leaves. Based on the transcriptome data, a Weighted Gene Co-expression Network Analysis (WGCNA) was employed to construct a network that associates with physiological traits related to stress resistance. Two highly correlated gene co-expression modules were identified, and within them, nine hub genes associated with endocytosis, antioxidant stress, absorption, transport, and metabolism of selenium were discovered. The results indicated that the beneficial effects on yield and total selenium content under low temperature were attributed to (1) protection of photosynthetic pigments for enhancing photosynthetic capacity by the up-regulation of LHca2, LHcb1, LHca1, LHcb4 in KEGG pathway: photosynthesis-antenna proteins; (2) activation of antioxidant system for efficient ROS homeostasis such as SOD, POD and CAT by the genes such as Superoxide dismutase, Monodehydroascorbate and (3) selenium absorption by endocytosis, seleninum transportation by ABC transporter gene family and selenium metabolism related genes such as Cysteine synthase, Glutaredoxin. These findings provide a foundation for further investigation into the molecular mechanisms underlying the effects of organic selenium and nano-selenium on cyanochloride production at low temperatures.

In this paper, a sensitivity sensor of dual-core photonic crystal fiber (DC-PCF) filled with magnetic liquid is introduced and investigated by the finite element method (FEM). To regulate the energy coupling involving the two cores, the magnetic fluid is filled into the pore between the two cores. To adjust the coupling between the supermodes in the DC-PCF, the refractive index of the magnetic fluid-filled air hole may change due to the external magnetic field. This specifically created a magnetic fluid-filled DC-PCF, the magnetic fluid-filled hole is not used as the core for energy transmission, thus avoiding transmission loss. The dip wavelength and the magnetic field displayed an excellent linear connection between 80 and 260 Oe, depending on the numerical data. The detection sensitivity of the magnetic field reached 515.75 pm/Oe at a short fiber length of 482 m. The designed magnetic fluid-filled DC-PCF has high sensitivity and small volume and has great application prospects in medical and industrial field magnetic field detection.

Fusarium species are one of the filamentous fungal taxa with the most pronounced impact on agri-cultural production and human health. The mycotoxins produced by pathogenic Fusarium not on-ly attack various plants including crops, causing various plant diseases that lead to reduced yields and even death, but also penetrate into the food chain of humans and animals to cause food poi-soning and consequent health hazards. Although sporadic studies have revealed some of the bio-synthetic pathways of Fusarium toxins, they are insufficient to satisfy the need for a comprehen-sive understanding of Fusarium toxin production. In this study, we focused on 35 serious patho-genic Fusarium species with available genomes and systematically analyzed the ubiquity of the dis-tribution of identified Fusarium and non-Fusarium derived fungal toxin biosynthesis gene clusters (BGCs) in these species through the mining of core genes and comparative analysis of correspond-ing BGCs. Additionally, novel sesterterpene synthases and PKS_NRPS clusters were discovered and analysed. This work is the first to systematically analyze the distribution of related mycotoxin biosynthesis in pathogenic Fusarium species. These findings enhance the knowledge of mycotoxin production and provide a theoretical grounding for the prevention of fungal toxin production us-ing biotechnological approaches.

Air pollution is related to the development of people's livelihood. As one of the main pollutants in the air, formaldehyde affects people's physical and mental health. In order to remove formaldehyde and better protect the health of residents, it is very necessary to develop efficient adsorption materials. In this study, a cellulose composite aerogel Microcrystalline Cellulose/ N-(2- aminoethyl) -3- aminopropyl methyl dimethoxysilane (MCC/APMDS) modified by APMDS was explored. The pore volume and specific surface area of the modified aerogel decreased, the average pore diameter increased, and the adsorption capacity of formaldehyde was stronger. The adsorption experiment shows that the sample prepared under the conditions of APMDS dosage of 6 wt%, reaction time of 4 h and reaction temperature of 90℃ has the largest average pore size (14.56 nm) and the largest formaldehyde adsorption capacity (9.52 mg/g). The excellent adsorption of the composite aerogel is due to high porosity and rich active amino groups on the surface. This study provides valuable information for the preparation of adsorption materials with high formaldehyde adsorption capacity for air purification.

Cyberspace map, as one of the important tools to describe cyberspace, gives an image to the unpredictable and illusory cyberspace, and has become a research hotspot in the fields of cartography, cyberspace security. Clarifying the concept of cyberspace map and constructing the conceptual model of cyberspace map can promote people's unified cognition of cyberspace. Based on the view of cartography, this paper compares and analyzes some related concepts of cyberspace map, discusses the characteristics of cyberspace map，and gives its concept. After that, it analyzes people's cognition of cyberspace composition. On this basis, it caters to this cognition mode and proposes the conceptual model of cyberspace map. Then, the connotation of the model is elaborated from three aspects: element-space association dimension, element mapping dimension and the map representation dimension. Finally, the specific composition and symbolization of various elements are analyzed. The model provides the top-level framework and theoretical guidance for the research of cyberspace map. This paper aims to adapt to the development trend of Cartography in ternary space, clarify the basic concept of cyberspace map, promote the development of cyberspace mapping theory, and lay the foundation for subsequent research.

Feline infectious peritonitis (FIP), caused by the feline coronavirus (FCoV), is a devastating dis-ease in cats. Based on its antigenicity, FCoV can be divided into two serotypes: FCoV-I and FCoV-II. Furthermore, according to its pathogenicity, FCoV can be divided into feline enteric coronavirus (FECV) and feline infectious peritonitis virus (FIPV). There are numerous factors that affect the pathogenesis of FIP, among which host immunity and viral genetics can play an es-sential role in the development of FIP. Owing to the lack of specific symptoms, existing individual diagnostic methods can only support the suspicion of FIP, and multiple diagnostic methods and test data need to be combined to make a diagnosis. Although there are still no effective FIPV vaccines or commercial drugs available in the market, various studies have shown that some compounds can be used for treatment. Therefore, FIP is no longer incurable in cats

In-situ observation on the austenite grain growth and martensite transformation in a developed NM500 wear-resistant steel were conducted on a Confocal Laser Scanning High-temperature Microscope (CSLM). Results indicated that the martensite nucleation did not synchronously proceed during quenching process. The selective prenucleation dominated in martensite nucleation, which dividing untransformed austenite into several regions, and resulting in the larger size of fresh martensite. Martensite can not only nucleate at parent austenite grain boundaries, but also nucleate in the preformed martensite laths and twins. Smaller constraint in the martensite growth was achieved in a larger parent austenite grain size, leading to the longer fresh martensite and secondary martensite. Besides, the transformation kinetics of martensite was accelerated in a higher quenching temperature. Moreover, the martensitic laths presented in parallel laths (0~2°) based on the pre-formed lath or distributed in triangle, parallelogram or hexagon with an angle of 60° or 120°. Interestingly, martensitic lath also traversed the unstable new parent austenitic grain boundaries. In addition, the size of austenite grains increased with the quenching temperature, and austenite grains coarsened in a short time at a higher quenching temperature of 1160 ℃. Furthermore, a large amount fine dispersed particles redissolved and ripped at 1160 ℃, resulting in the many large and visible carbonitrides.

A sensitive electrochemical sensor based on AuPtPd trimetallic nanoparticles functionalized multi-walled carbon nanotubes coupled with chitosan modified glassy carbon electrode (GCE/CS/MWCNTs-AuPtPd) for the rapid detection of bisphenol A (BPA) was proposed. AuPtPd trimetallic nanoparticles were first assembled on MWCNTs to obtain MWCNTs-AuPtPd nanocomposite. Then the MWCNTs-AuPtPd was further dispersed on the surface of chitosan modified electrode surface to fabricate the GCE/CS/MWCNTs-AuPtPd sensor. Due to the superior catalytic properties of MWCNTs-AuPtPd and the good film formation of chitosan, the constructed sensor displayed good performances for BPA detection. The structural morphology of CS/MWCNTs-AuPtPd was characterized by many methods, such as SEM, UV-vis and TEM. Under the optimal conditions, the designed sensor showed a linear range from 0.05 to 100 µM for BPA detecting with a low detection limit of 1.4 nM. The designed sensor was further used to realize the determination of BPA in real samples and the recoveries ranged from 94.4% to 103.6%. The results demonstrated that the electrochemical sensor designed by CS/MWCNTs-AuPtPd nanocomposites was reliable and could be a useful tool for the monitoring of food safety.

In order to reduce the influence of ground vibration generated by tractor during driving and operation on driving stability and driver ride comfort, this paper proposes a control method of tractor active seat suspension based on model predictive control. By establishing a 3-degree of freedom tractor active seat suspension model and a ground excitation input model, a new model predictive controller for the active seat suspension system is designed. The vertical acceleration of the seat center of mass, the seat suspension stroke and the tire dynamic displacement are optimized by limiting the dynamic deflection of the seat suspension and the active force output of the actuator. The control model of MPC tractor active seat suspension system is built and its performance is simulated and verified. The results show that compared with the passive seat suspension and the PID seat suspension, the tractor active seat suspension based on model predictive control (MPC) has better damping characteristics and improves ride comfort.

With the improvement of software copyright protection awareness, code obfuscation technology plays a crucial role in protecting key code segments. As the obfuscation technology becomes more and more complex and diverse, it has spawned a large number of malware variants, which make it easy to evade the detection of anti-virus software. Malicious code detection mainly depends on binary code similarity analysis. However, the existing software analysis technologies are difficult to deal with the growing complex obfuscation technologies. To solve this problem, this paper proposes a new obfuscation-resilient program analysis method, which is based on the data flow transformation relationship of the intermediate representation and the graph network model. In our approach, we first construct the data transformation graph based on LLVM IR. Then, we design a novel intermediate language representation model based on graph networks, named DFSGraph, to learn the data flow semantics from DTG. DFSGraph can detect the similarity of obfuscated code by extracting the semantic information of program data flow without deobfuscation. Extensive experiments prove that our approach is more accurate than existing deobfuscation tools when searching for similar functions from obfuscated code.

This paper focuses on the effect of malondialdehyde-induced oxidative modification (MiOM) on the gel properties of duck myofibrillar proteins (DMPs). DMPs were first prepared and treated with oxidative modification at different concentrations of malondialdehyde (0, 0.5, 2.5, 5.0 and 10.0 mmol/L). The physicochemical changes (carbonyl and free thiol group content) and gel properties (gel whiteness, gel strength, water holding capacity, rheological properties and mi-cro-structural properties) were then investigated. The results showed that the content of protein carbonyl groups increased with increasing MDA oxidation (P<0.05), while the content of free thiol groups decreased significantly (P<0.05). Meanwhile, there was a significant trend of decrease in gel whiteness; the hardness and water-holding capacity of protein gels increased significantly under the oxidation of low concentration of MDA (0-5 mmol/L), while the hardness of gels decreased under the oxidation of high concentration (10 mM). The storage modulus and loss modulus of oxidized DMPs also increased with increasing concentration; moreover, microstructural analysis confirmed that the gels oxidized at low concentrations were more compact and homogeneous in terms of pore size compared to the high concentration or blank group. In conclusion, moderate oxidation of malondialdehyde was beneficial to improve the gel properties of duck; however, excessive oxidation was detrimental to the formation of dense structured gels.

Cadmium (Cd) is a toxic non–essential element to plants, and its accumulation in crops has significant adverse effects on human health. The cross–talk between copper (Cu) and Cd has been reported, but the molecular mechanisms remain unknown. Here, the function of wheat Cu transporter 3D (TaCOPT3D) in Cd tolerance was investigated. The TaCOPT3D transcripts significantly accumulated in wheat roots under Cd exposure. To test whether TaCOPT3D was involved in response to Cd stress, overexpressing lines with altered expression of TaCOPT3D transporters were compared to wild–type (WT) plants. The results showed that, under 20 μM Cd treatment, TaCOPT3D–overexpression lines exhibited more biomass and lower Cd accumulation in roots, shoots, and grains compared to WT plants. In addition, the TaCOPT3D–overexpression lines demonstrated less reactive oxygen species (ROS) and a greater amount of active antioxidant enzymes under Cd conditions than WT plants. Moreover, TaCOPT3D–overexpression lines highly reduced Cd accumulation under exposure to 20 μM Cu. The regulation pathway of TaCOPT3D in response to Cd stress was investigated, and transcription factor (TF) TaWRKY22, which targeted the TaCOPT3D promoter, was identified. Therefore, TaCOPT3D can serve as a candidate gene for decreasing Cd accumulation in wheat through genetic engineering.

Drought is one of the most serious abiotic stressors in the environment, restricting agricultural production by reducing plant growth, development, and productivity. To investigate such a complex and multifaceted stressor and its effects on the plants, a systems biology-based approach is necessitated, entailing the generation of co-expression networks, identification of highly-priority transcription factors (TFs) dynamic mathematical modeling, and computational simulations. Here, we studied a high-resolution drought transcriptome of Arabidopsis. We revealed distinct temporal transcriptional signatures and demonstrated the involvement of specific biological pathways. Generation of a large-scale co-expression network followed by network centrality analyses identified 117 TFs that possess critical properties of hubs, bottlenecks, and high clustering coefficients nodes. Dynamic transcriptional regulatory modeling on integrated TF-target and transcriptome datasets uncovered major transcriptional events during the course of drought stress. Mathematical transcriptional simulations allowed us to ascertain the activation status of major TFs as well as the transcriptional intensity and amplitude of their target genes. Finally, we validated our predictions by providing experimental evidence of gene expression under drought stress for a set of four TFs and their major target genes using qRT-PCR. Taken together, we provided a systems-level perspective on the dynamic transcriptional regulation during drought stress in Arabidopsis and uncovered numerous novel TFs that can potentially be used in future genetic crop engineering programs.

Background: A growing number of clinical practice guidelines (CPGs) with regards to non-pharmacological interventions for breast cancer survivors are available. However, given the limitations in guideline development methodologies and inconsistency of recommendations, it remains uncertain how best to design and implement such non-pharmacological strategies to tailor interventions for breast cancer survivors with varied health conditions, healthcare needs, and preferences. Aim: To critically appraise and summarise available non-pharmacological interventions for symptom management and health promotion that can be self-managed by breast cancer survivors based on the recommendations of the CPGs. Methods: Clinical practice guidelines which were published between January 2016 and September 2021 and described non-pharmacological interventions for breast cancer survivors were systematically searched in six electronic databases, nine relevant guideline databases, and five cancer care society websites. The quality of the included CPGs was assessed by four evaluators using the Appraisal of Guidelines for REsearch and Evaluation, second edition tool. Content analysis was conducted to synthesise the characteristics of the non-pharmacological interventions that were recommended by the included CPGs, such as the intervention’s form, duration and frequency, level of evidence, grade of recommendation, and source of evidence. Results: Fourteen CPGs were identified and analysed. Of the 14 CPGs appraised, only five were rated as high quality. The domain with the highest standardised percentage was “scope and purpose” (84.61%), while the “applicability” domain had the lowest standardised percentage (51.04%). Five guidelines were assessed as “recommended”, seven were rated as “recommended with modifications”, and the remaining two were considered “not recommended”. Regarding the content analysis, physical activity/exercise, meditation, hypnosis, yoga, music therapy, stress management, relaxation, massage, and acupressure were the common self-managed non-pharmacological interventions recommended by the 14 CPGs. Physical activity/exercise was the only self-managed non-pharmacological intervention that was mostly recommended for psychological and physical symptom management by the included CPGs. However, there were significant disparities in terms of level of evidence and grade of recommendation in the included CPGs. Conclusion: The recommendations for the self-managed non-pharmacological interventions were varied and limited among the 14 CPGs, and some were based on medium- and low-quality evidence. More rigorous methods are required to develop high-quality CPGs in order to guide clinicians in offering high-quality and tailored breast cancer survivorship care.

In the permanent magnet synchronous motor (PMSM) drive system, the unwilling and ear-piercing vibro-acoustics caused by high-frequency sideband harmonics becomes unacceptable in the electric vehicle application. In this paper, a modified space vector pulse-width modulation (SVPWM) technique implemented with hybrid carrier frequency modulation (HCFM) is provided to reduce the sideband current harmonic components and vibro-acoustic responses. The principle and implementation of the proposed HCFM technique are firstly presented, in which the fixed carrier frequency is improved with the sawtooth and random signal-based coupling modulation based on the rotor position. For verification, the experiment tests are carried out on a prototype 12/10 PMSM and microcontroller unit. The effectiveness of the HCFM technique can hence be confirmed, in which the sideband vibro-acoustics reduction shows more effectively than that in conventional random PWM. The proposed approach may provide a new route in noise-cancelling and electromagnetic compatibility for the electric drive powertrain.

(1) Background: Bacterial reinfection and root fracture are the main culprits related to root canal treatment failure. This study aimed to assess the utility of quercetin solution as an adjunctive endodontic irrigant that strengthen root canal dentin with commitment anti-biofilm activity and bio-safety. (2) Methods: Based on a noninvasive dentin infection model, dentin tubules infected with Enterococcus faecalis (E. faecalis) were irrigated with sterile water (control group), and 0, 1, 2, 4 wt% quercetin-containing ethanol solutions. The live and dead bacteria proportions within E. fae-calis biofilms were analyzed using confocal laser scanning microscopy (CLSM). Elastic modulus and hydroxyproline release and X-ray photoelectron spectroscopy (XPS) characterization was tested on irrigant-treated demineralized dentin to evaluate irrigants’ biostability. The cytotoxicity of irrigants was tested by CCK-8 assay. (3) Results: Quercetin increased the proportion of dead bacteria volumes within E. faecalis, and improved the flexural strength of dentin collagen com-pared to control group. The XPS characterization revealed an increase in C-O peak area under both C1s and O1s narrow-scan spectra. The CCK-8 assay confirmed no cytotoxicity of quercetin solutions. (4) Conclusions: Quercetin exhibited anti-biofilm activity, collagen-stabilizing effect as well as cytocompatibility, supporting quercetin as a potential candidate for endodontic irrigant.

Waterbomb structures are origami-inspired deformable structural components used in new types of robots. They have a unique radially deployable ability that enables robots to better adapt to their environment. In this paper, we propose a series of new waterbomb structures with square, rectangle, and parallelogram base units. Through quasi-static axial and radial compression experiments and numerical simulations, we prove that the parallelogram waterbomb structure has a twist displacement mode along the axial direction. Compared with the square waterbomb structure, the proposed optimal design of the parallelogram waterbomb structure reduces the critical axial buckling load-to-weight ratio by 55.4% and increases the radial stiffness-to-weight ratio by 67.6%. The significant increase in the radial stiffness-to-weight ratio of the waterbomb structure and decrease in the critical axial buckling load-to-weight ratio make the proposed origami pattern attractive for practical robotics applications.

Trueperella pyogenes is a common opportunistic pathogen which is one of the main causes of postpartum endometritis in dairy cows. As a substitute for antibiotics, the probiotic Lactobacillus rhamnosus GR-1 has been used in a wide range of clinical treatments. Our experiments were designed to establish a model of anti-damage which LGR-1 was used to protect bovine endometrial epithelial cells (BEECs) from inflammatory damage and cell destruction caused by T. pyogenes. Increased expression of NLRP3 inflammasomes and cytokines was observed following T. pyogenes challenge, but this increase was relieved by LGR-1 pretreatment. Immunofluorescence and Western blot analyses revealed that T. pyogenes infection also results in the damage of tight junction proteins in BEECs. The expression levels of Claudin-1, Occludin, and ZO-1 were decreased in cells only infected with T. pyogenes but not in cells pretreated with LGR-1. Moreover, the detection of the anti-apoptotic protein Bcl-2 and apoptotic proteins BAX, cytochrome c, as well as the activating effector caspase-3 revealed that T. pyogenes induced apoptosis of BEECs, which was also confirmed by DAPI staining to observe the morphological changes of the nuclei of cell apoptosis and by TUNEL staining to locate the cells undergoing apoptosis. Our data indicate that LGR-1 ameliorates the T. pyogenes–induced barrier dysfunction of BEECs and pre-application of LGR-1 could be an effective strategy for controlling T. pyogenes infection.

Hot deformation at elevated temperature is essential to densify the particle reinforced Aluminum matrix composites (AMCs) and improve their performance. However, hot deformation behavior of the AMCs is sensitive to the variation of hot processing parameters. In this paper, optimal processing parameters of the dual-scale SiCp/A356 composites was determined to explore the control strategy of the microstructure. Hot compression tests were conducted at the temperature ranging from 460 to 520℃ under strain rates from 0.01 to 5 s−1. Constitutive equation and processing maps were presented to determine the hot processing parameters. Microstructure evolution of the dual-scale SiCp/A356 composites was analyzed. The strain rate of 0.62 ~ 5s-1 and deformation temperature of 495 ~ 518℃ is suitable for the hot processing. The number of DRX grains in the “safe” domains is larger and the dislocation density is lower compared to those of instability domains. DRX particles mainly occurred around SiC particles. The presence of SiC particles can promote effectively the DRX nucleation, which result in that the dynamic softening mechanism of the dual-scale SiCp/A356 composites is dominated DRX.

Recently, various relations and criteria have been presented to establish a proper relationship between control systems and control Global Positioning System (GPS)-intelligent buoy system. Given the importance of controlling the position of buoys and the construction of intelligent systems, in this paper, dynamic system modeling is applied to position marine buoys through the improved neural network with a backstepping technique. This study aims at developing a novel controller based on adaptive fuzzy neural network to optimally track the dynamically positioned vehicle on water with unavailable velocities and unidentified control parameters. In order to model the network with the proposed technique, uncertainties and the unwanted disturbances are studied in the neural network. The presented study aims at developing a neural controlling which applies the vectorial back-stepping technique to the surface ships, which have been dynamically positioned with undetermined disturbances and ambivalences. Moreover, the objective function is to minimize the output error for the neural network (NN) based on closed-loop system. The most important feature of the proposed model for the positioning buoys is its independence from comparative knowledge or information on the dynamics and the unwanted disturbances of ships. The numerical and obtained consequences demonstrate that the controller system can adjust the routes and the position of the buoys to the desired objective with relatively few position errors.

A variety of myricetin derivatives bearing ferulic acid amide scaffolds were designed and synthesized. The structures of all title compounds were determined by 1 H NMR, 13 C NMR, 19 F NMR and HRMS. Preliminary bioassays suggested that some of the target compounds exhibited remarkable antiviral activities. In particular, compound 4l possessed significant protection activity against tobacco mosaic virus (TMV), with an half maximal effective concentration (EC50) value of 196.11 μg/mL, which was better than commercial agent ningnamycin (447.92 μg/mL). Meanwhile, microscale thermophoresis (MST) indicated that compound 4l have strong binding capability to tobacco mosaic virus coat protein (TMV-CP) with dissociation constant (Kd) values of 0.34 μmol/L, which was better than ningnamycin (0.52 μmol/L). These results suggest that novel myricetin derivatives bearing ferulic acid amide scaffolds may be considered as an activator for antiviral agents.

The cross-linkable PCL-PEG analogues block-graft copolymer was designed and synthesized, which with the copolymer of the MEO₂MA and OEGMA as graft chains to improve the mPEG-b-PCL-b-mPEG copolymer the aqueous solution properties. And successfully prepared two hydrogels via a copper-catalyzed 1, 3-dipolar azide-alkyne cycloaddition reaction of alkyne-terminated poly[glycidyl methacrylate-co-2-(2-methoxyethoxy) ethyl methacrylate-co-oligo (ethylene glycol) methacrylate] [P(GMA-co-MEO₂MA-co-OEGMA)] with azide end-functionalized PCL-PEG analogues block-graft copolymer, and tetrakis (2-propynyloxymethyl) -methane (TPOM) and with azide end-functionalized PCL-PEG analogues block-graft copolymer. The copolymer's chemical structure was characterized by proton nuclear magnetic resonance spectroscopy and fourier transform infrared spectroscopy. The molecular weights of the copolymers were decided with gel permeation chromatography. The water solubility and temperature sensitivity of the copolymers were studied by taking digital photos and transmittance change measured by UV spectrophotometer at different temperatures. Fluorescence probes, surface tension, dynamic light scattering and transmission electron microscopy were used to analyze the micelles that copolymers self-assembly in aqueous solution. The sol-gel behavior of copolymer solutions at high concentrations was explored by vial inversion experiments. Finally, the network structure of the gels was observed by scanning electron microscopy. These conclusions indicate that these hydrogels are expected to be used as a new material in the field of biomedicine.

Information-theoretically provable unique true random numbers, which cannot be correlated or controlled by an attacker, can be generated based on quantum measurement of vacuum state and universal-hashing randomness extraction. Quantum entropy in the measurements decides the quality and security of the random number generator (RNG). At the same time, it directly determines the extraction ratio of true randomness from the raw data, in other words, it obviously affects quantum random bits generating rate. In this work, we commit to enhancing quantum entropy content in the vacuum noise based quantum RNG. We have taken into account main factors in this proposal to establish the theoretical model of quantum entropy content, including the effects of classical noise, the optimum dynamical analog-digital convertor (ADC) range, the local gain and the electronic gain of the homodyne system. We demonstrate that by amplifying the vacuum quantum noise, abundant quantum entropy is extractable in the step of post-processing even classical noise excursion, which may be deliberately induced by an eavesdropper, is large. Based on the discussion and the fact that the bandwidth of quantum vacuum noise is infinite, we propose large dynamical range and moderate TIA gain to pursue higher local oscillator (LO) amplification of vacuum quadrature and broader detection bandwidth in homodyne system. High true randomness extraction ratio together with high sampling rate is attainable. Experimentally, an extraction ratio of true randomness of 85.3% is achieved by finite enhancement of the laser power of the LO when classical noise excursions of the raw data is obvious.

Baduanjin exercise is a traditional Chinese health-Qigong routine, created by an ancient physician for health promotion. Its mild-to-moderate exercise intensity is suitable for individuals with medical conditions. Recently, a large number of trials were conducted to investigate the effects of Baduanjin exercise in patients with chronic obstructive pulmonary disease (COPD). It needs to be determined whether Baduanjin exercise prescription is beneficial for the management of COPD patients. Thus, we conducted a systematic review to objectively evaluate the existing literature on this topic. We searched six databases (PubMed, Web of Science, Cochrane Library, Scopus, CNKI, and Wanfang) from its inception till early May, 2018. The adapted PEDro scale was used for study quality assessment of all randomized controlled trials (RCT). The pooled effect size (Hedge’s g) of exercise capability (6-Minute Walking Test, 6-MWT), lung function parameters (forced expiratory volume in first second, FEV1; forced volume vital capacity, FVC; FEV1/FVC ratio), and quality of life were calculated based on the random-effects model. Twenty RCTs (n = 1975 COPD patients) were included in this review, with sum scores of the adapted PEDro scale between 5 and 9. Study results of meta-analysis indicate that Baduanjin is effective in improving exercise capability (Hedge’s g = 0.69, CI 0.44 to 0.94, p < 0.001, I2 = 66%), FEV1 (Hedge’s g = 0.47, CI 0.22 to 0.73, p < 0.001, I2 = 68.01%), FEV1% (Hedge’s g = 0.38, CI 0.21 to 0.56, p < 0.001, I2 = 54.74%), FVC (Hedge’s g = 0.39, CI 0.22 to 0.56, p < 0.001, I2 = 14.57%), FEV1/FVC (Hedge’s g = 0.5, CI 0.33 to 0.68, p < 0.001, I2 = 53.49%), and the quality of life of COPD patients (Hedge’ s g = - 0.45, CI -0.77 to - 0.12, p < 0.05, I2 = 77.02%), as compared to control groups. Baduanjin exercise as an adjunctive treatment may potentially improve exercise capability and pulmonary function of COPD patients as well as quality of life. Baduanjin exercise could be tentatively prescribed for COPD in combination with the conventional rehabilitation program to quicken the process of recovery. To confirm the positive effects of Baduanjin exercise for COPD patients, future researchers need to consider our suggestions mentioned in this article.

Cost-efficient catalyst for hydrogen evolution reaction (HER) and methanol oxidization reaction (MOR) is of great importance for industrial application. The alloying of platinum with cheap transition metal offers a great opportunity to reduce cost and enhance the electro-catalytic performance. Herein, we report a simple and green route to synthesize porous Pt-Cu catalysts, where Pt-Cu solid particles were first produced by using cuprous chloride (CuCl) nanoparticles as the template, followed by a dealloying treatment to obtain final porous product. The porous alloy nanoparticles show higher catalytic activity and superior stability for HER and methanol oxidation reaction, which is beneficial from the porous structure and synergetic effect between Pt and Cu.

Quantitative structure-activity relationship (QSAR) model is adopted to study the relationship between the chemical and physical properties of various substances and the structure. Through QSAR studies, the internal relationship between the invisible structure and the activity can be obtained. In this paper, a novel chaos-enhanced accelerate particle swarm algorithm (CAPSO) is proposed, which is used to molecular descriptors screening and optimization of the weights of back propagation artificial neural network (BP ANN). Then, the QSAR model based on CAPSO and BP ANN is put forward, hereinafter referred to as CAPSO BP ANN model. The prediction experiment showed that the CAPSO algorithm is a reliable method for screening molecular descriptors and the five molecular descriptors obtained by CAPSO algorithm could well characterize the molecular structure of each compound in pKa prediction. The experimental results also showed the CAPSO BP ANN model has a good performance in predicting the pKa values of various compounds, the absolute mean relative error, root mean square error, and square correlation coefficient are respectively 0.5364, 0.0632, and 0.9438, indicating the higher prediction accuracy and correlation. The proposed hybrid intelligent model can be applied in all kinds of engineering design, prediction of physical and chemical properties and intelligent calculation.

In recent years, remote sensing technology has been widely used to predict forest stand parameters. In order to compare the effects of different features of remote sensing images and topographic information on the prediction of forest stand parameters, multivariate stepwise regression analysis method was used to build estimation models for important forest stand parameters by using textural and spectral features as well as topographic information of SPOT-5 satellite images in northeastern Heilongjiang Province in China as independent variables. The study results show that the optimal window to predict forest stand parameters using textural features of SPOT-5 satellite image is 9×9; the ability of textural features was better than that of spectral features in terms of predicting forest stand parameters; with the inclusion of topographic information, the accuracy of prediction of all models was improved, of which elevation has the most significant effect. The highest accuracy was achieved when predicting the stand volume (SV) (R²_adj=0.820), followed by basal area (BA) (R²_adj =0.778), accuracy of both above models exceeded 75%. The results show that models combined use of textural, spectral features and topographic information of SPOT-5 images have a good application prospect in predicting forest stand parameters.

Multi-sensor data fusion of E-tongue and E-nose can provide a more comprehensive and more accurate analysis results. However, it also brings some redundant information, it is a hot issue to reduce the feature dimension for pattern recognition. In this paper, the taste-olfactory data fusion based on E-tongue and E-nose combined with Support Vector Machine (SVM) was used to classify five different beers. First, the taste and olfactory feature information were obtained based on E-tongue and E-nose. Second, the original feature data of single system were fused, then Principal Component Analysis (PCA) was applied to extract principal components, Genetic Algorithm-Partial Least Squares (GA-PLS) was used to select the characteristic variables, 20 subsets were generated with those variables based on the best Variable Importance of Projection (VIP) score. Finally, the classification models based on SVM were established, also c and g of SVM were calculated by Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), the classification results of all subsets were obtained. The results showed that the classification accuracy using data fusion was much higher over single E-tongue and single E-nose, and the variable selection method by VIP had the best classification performance in #12 subset coupled with GA-SVM.

Wireline Formation Testing is an important technique in the oil field of exploration and development. Not only it can make real fluid samples of the formation directly obtained to know exactly oil existed in formation or not; but it can also show flowing pressure change to see the production capacity of the formation. So it is important measurement for formation evaluation during the drilling process and supports for activities of the exploration and development in the oil field. A numerical simulation model in this article is researched and established based on the Finite Volume Method with considering the influence of sensitive parameters such as reservoir heterogeneity, probe suction area, and mud-filtrate invasion depth during the drilling. The model is capable to design and evaluate for formation fluid sampling operations with calculating hydrocarbon content and flowing pressure. Furthermore, through case application, the performance and effect in the process of Wireline Formation Testing was demonstrated. The results indicate that this technology can be served as an effective auxiliary tool for fluid sampling operations with the function of optimizing fluid sampling measures. It can improve the accuracy of predicting indicators such as hydrocarbon content and breakthrough time during the sampling process. This study provides important backups and technical guidance for professionals in geological exploration and oilfield development.

Land cover segmentation, a fundamental task within the domain of remote sensing, boasts a broad spectrum of application potential. In this article, we focus on the land cover segmentation tasks and complete the following research work: Firstly, to address the issues of uneven distribution of foreground and background and significant differences in target scales in remote sensing images, we propose a decoder called MDCFD based on multi-dilation rate convolution fusion. The decoder utilizes dilated convolution to expand the receptive field, enhancing the model's ability to capture global features and thus improving the model's ability to distinguish between foreground and background. Meanwhile, we design a multi-dilation rate convolution fusion module (MDCFM), which fuses the outputs of different dilation rate convolution layers. Secondly, aiming at the problems of diverse scenes, significant differences between categories, and many background interferences in remote sensing images, we propose a hybrid attention module called LKSHAM based on large kernel convolution. This module combines spatial attention and channel attention mechanisms and combines the two attention modules in series. By introducing large kernel convolution, the model's ability to extract contextual information is improved. At the same time, we adopt a strategy of decomposing large kernel convolution into multiple depthwise convolutions to reduce computational complexity. The improved network models designed by this paper can achieve an improvement of over 1.1% in the mIoU metric on segmentation tasks on the Potsdam and Vaihingen datasets.

The rebound behaviors of rubber balls based on ethylene-propylene-diene monomer (EPDM) / chlorinated butyl rubber (CIIR) blends were investigated systematically. A novel method was proposed to characterize the damping capacity of the EPDM/CIIR blends. The damping capacity can be represented by the rebound height of rubber balls, and lower rebound height corresponds to better damping capacity. A mathematical model expressed by an equation obtained through theoretical derivation has been proposed to predict the rebound height of the rubber balls. The energy dissipation rate (EDR) defined by the ratio of the height loss to the rebound time was proposed to further characterize the damping capacity. The EDR value shows the highest for the pure CIIR and lowest for the pure EPDM, showing a decrease trend with the increase of EPDM content in the rubber blends. By comparison one can obtain that the damping capacity of the EPDM/CIIR blends decreases with the decrease of external excitation, the conclusion of which plays a key role in the formulation design of viscoelastic damping rubber materials.

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

Climate change is a global issue that draws widespread attention from the international society. As an important component of the climate system, the water cycle is directly affected by climate change. Thus, it is very important to study the influences of climate change on the basin water cycle with respect to maintenance of healthy rivers, sustainable use of water resources, and sustainable socioeconomic development in the basin. In this study, by assessing the suitability of multiple General Circulation Models (GCMs) recommended by the Intergovernmental Panel on Climate Change, Statistical Downscaling Model (SDSM) and Automated Statistical Downscaling model (ASD) were used to generate future climate change scenarios. These were then used to drive distributed hydrologic models (Variable Infiltration Capacity, Soil and Water Assessment Tool) for hydrological simulation of the Yangtze River and Yellow River basins, thereby quantifying the effects of climate change on the basin water cycle. The results showed that suitability assessment adopted in this study could effectively reduce the uncertainty of GCMs, and that statistical downscaling was able to greatly improve precipitation and temperature outputs in global climate mode. Compared to a baseline period (1961–1990), projected future periods (2046–2065 and 2081–2100) had a slightly decreasing tendency of runoff in the lower reaches of the Yangtze River basin. In particular, a significant increase in runoff was observed during flood seasons in the southeast part. However, runoff of the upper Yellow River basin decreased continuously. The results provide a reference for studying climate change in major river basins of China.

A free-fall baited camera lander was launched for the first time on the Cosmonaut Sea shelf of East Antarctica at the depth of 694 m during the 38th Chinese National Antarctic Research Expedition (CHINARE) in 2022. We identified 31 unique taxa (23 of invertebrates and 8 of fishes) belonging to 8 phyla from 2403 pictures and 40 videos. The Antarctic jonasfish (Notolepis coatsi) was the most frequently observed fish taxa. Ten species of vulnerable marine ecosystem (VME) taxa were observed, accounting for 32% of all species. The maximum number (MaxN) of Natatolana meridionalis individuals per image frame was ten, and they were attracted to the bait. The macrobenthic community type was sessile suspension feeders with associated fauna (SSFA), which was shaped by the muddy substrata with scattered rocks. Rocks served as the best habitats for sessile fauna. The study reveals the megafauna community and their habitat by image survey in the Cosmonaut Sea for the first time. It helped us obtain Antarctic biodiversity baselines and monitoring data for future’s ecosystem health assessment and better protection.

Abstract: Chronic Obstructive Pulmonary Disease (COPD) is a continually advancing respiratory disorder, characterized by enduring airflow limitation along with long-lasting inflammation in the airways. An expanding pool of evidence is emphasizing how mitochondrial dysfunction directly impacts the development and progression of COPD. This comprehensive review delves deeper into the intricate cellular and molecular biology of mitochondria within the framework of COPD, spotlighting significant alterations in structure and function that accompany mitochondrial dysfunction. In this narrative, we delve into the observed changes in mitochondrial shape, behavior, and respiratory chain complex alterations seen in individuals afflicted with COPD. The discussion includes implications on cellular signaling pathways and how this affects the natural process of programmed cellular death (apoptosis) and cellular aging, particularly in reference to COPD. Additionally, we consolidate ongoing therapeutic strategies, honing in on the management of COPD through a focus on mitochondrial dysfunction. Prominent among these strategies is the potential role of antioxidants and mitochondrial biogenesis inducers, which are emerging as promising fields of intervention. Furthermore, we embark on an overview of the possible use of mitochondrial biomarkers as innovative tools in diagnosing COPD, evaluating disease progression, and monitoring the efficacy of COPD treatments. As we unravel the rather complex interplay between mitochondrial biology and COPD, this review highlights the critical importance of formulating treatments that target mitochondrial dysfunction. The ultimate goal of these strategic interventions is to slow down the rate of COPD progression and significantly improve patient outcomes. Lastly, though our understanding of the nexus between COPD and mitochondrial dysfunction has significantly enhanced, ample scope remains for further investigation. Improved insights into the mechanisms of mitochondrial dysfunction, discovered biomarkers, and targeted therapies could encompass a revolutionary step towards comprehensive disease management. The future of COPD treatment seems to lean towards a combination of strategies, prioritizing not only the management of symptoms but also focused on preserving and restoring lung function, improving physical capacity, and enhancing quality of life for COPD patients.

Good Boussinesq equations will be considered in this work. First we apply three combined compact schemes to approximate spatial derivatives of good Boussinesq equations. Then three fully discrete schemes are developed based on symplectic scheme in time direction, which are sympletic-structure preserving.Meanwhile, the convergence and conservation of the fully discrete schemes are analyzed. Finally, we present numerical experiments to confirm our theoretical analysis. Both our analysis and numerical test indicate that the fully discrete schemes are efficient in solving the spatial derivative mixed equation.

Recently, attention mechanisms have developed into an important tool for performance improvement of deep neural networks. In computer vision, attention mechanisms are generally divided into two main branches: spatial and channel attention. Both attention categories have their own advantages. The fusion of both attentions achieves higher performance, on the cost of the computational load. This paper introduces an innovative and lighter n-shifted sigmoid channel and spatial attention (CSA) module to reduce the computational cost and to improve the 3D scene relevant features selection. To validate the proposed attention module, 3D scene object detection in the deep Hough voting point sets is considered as the testing application. The proposed attention module with its piecewise n-shifted sigmoid activation function improves the network’s learning and generalization capacity which effectively predict bounding box parameters directly from 3D scenes and detect objects more accurately. This advantage is achieved by selectively attending to more relevant features of the input data. When used in the deep Hough voting point sets, the proposed attention module outperforms state-of-the-art 3D detection methods on the sizable SUNRGBD dataset. Experiments conducted showed an increase of 12.02 mean accuracy precision (mAP) when compared to the celebrated VoteNet (without attention). It also got 9.92 mAP higher compared to the MLVCNet, and 10.32 mAP higher than the Point Transformer. The proposed model not only decreases the sigmoid vanishing gradient problem but also brings out valuable features by fusing channel-wise and spatial information while improving accuracy results in 3D object detection.

Survival of Medulloblastoma (MB) depends on various factors, including the gene expression profiles of MB tumor tissues. In this study, we identified 967 MB survival related genes (SRBs) using the gene expression dataset of Cavalli et al. (2017) and the Cox proportional hazards regression model. Notably, the SRGs were over-represented on chromosomes 6 and 17, known for the abnormalities monosomy 6 and isochromosome 17 in MB. The most significant SRG was HMGA1 (high mobility group AT-hook 1), which is a known oncogene and a histone H1 competitor. High expression of HMGA1 was associated with worse survival, primarily in the Group 3γ subtype. The high expression of HMGA1 was unrelated to any known somatic copy number alteration. Most SRGs on chromosome 17p were associated with low expression in Group 4β, the MB subtype with 93% deletion of 17p and 98% copy gain of 17q. Pathway analysis showed that both chromosomes 6 and 17 included SRGs related to telomere maintenance and provide a rationale for testing telomerase inhibitors in Group 3 MBs. We conclude that HMGA1, along with other SRGs on chromosome 6 and 17 warrant further investigation as potential therapeutic targets in selected subgroups or subtypes of MB.

Taiwan’s auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid sampling bias, keep randomness and variability, and target the risker samples. We first apply a Naive Bayes classifier to classify data into some classes. Next, a user-based, item-based, or hybrid approach is employed to draw audit evidence. The representativeness index is the primary metric for measuring the representativeness of audit evidence. The user-based approach denotes the selection of samples between two percentiles in a class as audit evidence. It may be equivalent to a combination of monetary and variable sampling methods. The item-based approach represents the choice of risky samples as audit evidence. It may be identical to a combination of non-statistical and monetary sampling methods. Auditors can hybridize those user-based and item-based approaches to balance representativeness and riskiness in selecting audit evidence. Three experiments show that sampling using machine learning integration has the benefits of drawing unbiased samples, handling complex patterns, correlations, and unstructured data, and improving efficiency in sampling big data. However, the limitations are the classification accuracy output by machine learning algorithms and the range of prior probabilities.

Urban tree classification is pivotal in urban planning and management, facilitating informed decision-making processes. In this study, we introduce a novel data presentation method termed Pseudo Tree Crown, designed to enhance the accuracy and efficiency of urban tree classification. Leveraging the latest advancements in artificial intelligence (AI), we employ a state-of-the-art classification scheme, PyTorch, to maximize the accuracy of tree classification. Our results demonstrate a robust classification accuracy of over 95% from high spatial resolution imagery from Unmanned Aerial Vehicle (UAV), underscoring our proposed approach’s effectiveness. Moreover, the adaptability of our method renders it applicable to various study areas, highlighting its versatility and potential for widespread implementation in urban planning and management initiatives.

Yellow nanorod Mg-MOF-74 was obtained by solvothermal synthesis method. XRD、N2 adsorption-desorption isotherms、SEM and TGA results suggest that the particle size of Mg-MOF-74 reaches 400 nm after the introduction of sodium acetate in the precursor of Mg-MOF-74. Besides, the morphology of Mg-MOF-74 was changed from cauliflower to rod particles. At the same time, the BET specific surface area and pore volume of Mg-MOF-74 were also increased a lot. Then the CO2 dynamic adsorption capacity of Mg-MOF-74 was measured by self-made fix bed under 30 ℃、0.1 bar CO2 partial pressure. The results show that the CO2 adsorption capacity of Mg-MOF-74-N2 reaches 3.67 mmol/g and its CO2 adsorption capacity remains unchanged after 10 times CO2 adsorption-desorption cycles.

Trimeresurus albolabris, also known as the white-lipped pit viper or white-lipped tree viper, is a highly venomous snake distributed across Southeast Asia and the cause of many snakebite cases. In this study, we report the first whole genome assembly of T. albolabris obtained with next-generation sequencing from a specimen collected in Mengzi, Yunnan, China. After genome sequencing and assembly, the genome of this male T. albolabris individual was 1.51 Gb in length and included 38.42% repeat-element content. Using this genome, 21,695 genes were identified, and 99.17% of genes could be annotated using gene functional databases. Our genome assembly and annotation process was validated using a phylogenetic tree, which included six species and focused on single-copy genes of nuclear genomes. This research will contribute to future studies on Trimeresurus biology and the genetic basis of snake venom.

Globally, weeds interfere with agricultural production activities and have a very serious impact on agriculture and animal husbandry. Identifying a safe and reliable weed control strategy might increase yield, production net income, and improve crop quality. A field experiment was carried out to explore the effects of weeds interference frequency on the yield and quality of Glycyrrhiza uralensis Fisch in an arid and semi-arid area of northwest China. The experiment consisted of seven treatments and were (1) no weeding, marked as WF0; (2)-(7) artificial weeding by hoe once every 1, 2, 4, 6, 8, 10 weeks after emergence, marked as WF1, WF2, WF4, WF6, WF8 and WF10, respectively. We found that the higher weeding frequency had a higher the plant height, photosynthesis, yield and quality. The highest yield was obtained in the WF1 treatment, while the cost of weeding was the highest among all treatments. The concentration of liquiritin and glycyrrhizic acid were increased by 53.24% and 36.57%, with the highest nitrogen metabolism enzymatic activities and quality in WF4 treatment. WF4 treatment exhibited the largest increases in the net income among all treatments in both growing seasons, with respective increases up to 71.39 % and 78.81%. These findings suggested that weeding once every 4 weeks would be an effective and sustainable measure to control weeds in an arid and semi-arid area.

Cell junction that is usually associated with dynamic cytoskeletons is essential for a wide range of cellular activities such as cell migration, cell communication, barrier function and signal transduction. Real-time observation of cell junction facilitates understanding of the mechanisms by which cell junction regulate relevant cellular activities. In this study, we examined the binding capacity of a modified tridecapeptide from Cx43 to cell junction protein ZO-1 and sought to create a fluorescent peptide that could be used to label cell junction. To introduce the fluorescent peptide into the cells, a cell-penetrating peptide was linked to the modified tridecapeptide and synthesized. The binding of the modified tridecapeptide was tested using pull down and immunoprecipitation assay. The ability of the peptide to label cell junction was assessed by adding it to fixed or cultured Caco-2 cells. Testing assay revealed that the Cx43-derived peptide can bind to ZO-1. Besides, the peptide was able to label cell junction of fixed cell, although no obvious cell junction labeling was observed clearly in living cells, probably due to the inadequate affinity. These results indicate that a peptide-based strategy for labeling cell junction may be feasible, and efforts to improve its affinity are warranted in the future.

The transition region is a very thin but most peculiar layer in the solar atmosphere, located between the solar chromosphere and the corona. It is a key region for understanding the coronal heating, the solar eruptions triggering, and the origin of solar winds. Here, the gradients of all physical parameters are very high, including plasma density, ionization degree, temperature, and magnetic fields, etc. Therefore, the transition region should be highly dynamic, such as fast energy releasing and transporting, plasma heating, and even particle accelerating. They include two physical aspects: thermal and non-thermal processes. The thermal processes can be observed from the ultraviolet (UV) and extreme ultraviolet (EUV) emission by multi-wavelength images. The non-thermal processes, however, should be related to radio emissions especially at millimeter wavelengths, and the frequency range should span from several GHz to beyond 300 GHz, and the emission mechanism should be highly related to the magnetic fields and variations. The ultra-wide broadband spectral observations at millimeter wavelengths with high spectral resolutions may provide rich dynamic information about the transition region, such as non-thermal energy release and transmission, the flows of plasma and energetic particles, the magnetic fields and their variations, the generation and transportation of various waves, and the formation and evolution of the source regions of solar eruptions. Here, we discussed the spectral characteristics of millimeter-wave emission from the transition region and proposed a new conception of ultra-wide broadband millimeter-wave spectrometers to observe them.

Addressing the contemporary challenges of mitigating and adapting to climate change, conserving biodiversity, and ensuring human well-being constitutes a central focus for humanity. These challenges, though often treated in isolation, are intricately interconnected, sharing common drivers. Current and future research emphasizes the pursuit of an integrated approach that minimizes trade-offs and fosters synergies among the Sustainable Development Goals (SDGs). The nexus between ecosystem service value (ESV) and the social cost of carbon (SCC) is pivotal in informing national and governmental decisions regarding human well-being and climate change mitigation and adaptation, respectively. This study employs the Zhoushan Archipelago as a case study, exploring ESV and SCC dynamics from 2010 to 2020. An in-depth analysis of spatial development characteristics and the temporal and spatial correlation between ESV and SCC is conducted. The findings reveal an increase in Zhoushan Archipelago's land area from 2010 to 2015, stabilizing thereafter, with construction land exhibiting the most notable proportional growth. Carbon emissions were observed during the study period, with forests identified as the primary carbon sink, followed by mudflat and waterbody, while construction land contributed significantly to carbon emissions. Notably, the SCC in Zhoushan Archipelago increased by 2452%, contrasting with a modest 1.5% decrease in ESV during the study period. Global spatial correlation analysis demonstrated a significant positive correlation between ESV and SCC in Zhoushan Archipelago throughout the study period, validated by passing the P-value test. However, local spatial correlation analysis revealed a specific nature of the global spatial correlation between ESV and SCC in the island area. This nuanced understanding enhances our comprehension of the intricacies surrounding ESV and SCC dynamics, contributing valuable insights to the broader discourse on sustainable regional development, economic decarbonization, and human well-being improvement.

Diatomite (DME) consists of natural ordered porous structures that are excellent candidates as microcontainers. However, to the best of our knowledge, the application of DME loaded with corrosion inhibitors in anti-corrosion coatings has not hitherto been reported. In this study, DME has been used as a source of microcontainers to load benzotriazole (BTA) inhibitor by an immersion method. In order to prevent unwanted early release of the small molecule BTA inhibitor from the DME microcontainers, inspired by the adhesion characteristics of catechol and amine in mussel adhesion protein, polydopamine (PDA) was coated on their surfaces to generate BTA@DME/PDA microcapsules. Because of the depolymerization characteristics of PDA at low pH, the synthesize microcapsules showed a controllable release function. The SEM morphology, chemical structure, and loading capacity of the synthesized BTA@DME/PDA microcapsules were characterized. The corrosion resistances of epoxy coatings with different contents of BTA@DME/PDA microcapsules were compared by saline immersion and electrochemical impedance tests. A scratched coating with 5wt.% BTA@DME/PDA microcapsules showed the best anti-corrosion effect.

Abstract: To explore the interrelationship between groundwater microbial communities and hydrochemical characteristics in Mancheng district, Baoding city, samples from karst groundwater and porous groundwater were collected respectively. The hydrochemical analysis and 16s RNA gene V4-V5 region sequencing method were used to detail the water environmental characteristics and microbial community distribution pattern in the study area. The hydrochemical results reveal significant differences in major ion contents and other hydrochemical indices between karst water and porous water. Microbial community analysis demonstrates that Proteobacteria, Actinobacteria, and Firmicutes are the dominant taxa in both types of water bodies, but their proportions vary significantly in different water bodies. The difference in microbial communities between karst water and porous water reflects the influence of environmental factors such as ion concentration and pH on microbial distribution. Redundancy analysis (RDA) indicates significant associations between microbial community composition and environmental factors in both types of groundwater environments. Studying the distribution pattern of microbial communities and the connection with environmental factors in two types of groundwater provides important basis for interpreting the functional roles of microbes in groundwater ecosystems.

The material undergoes high temperature and high strain rate deformation process during cutting process, may induce the dynamic recrystallization behavior and result the evolution of dynamic mechanical properties of the material to be machined. In this paper, the modified Johnson-Cook(J-C) model for Nickel based powder metallurgy superalloy considering dynamic recrystallization behavior in high strain rate and temperature is proposed. The dynamic mechanical properties of the material under different strain rates and temperature conditions are obtained by quasi-static compression test and split Hopkinson pressure bar (SHPB) test. The coefficients of the modified J-C model are obtained by linear regression method. The modified model is verified by comparison with experimental and model prediction results. The results show that the modified J-C model proposed in this paper can accurately describe the mechanical properties of nickel-based powder metallurgy superalloys at high temperature and high strain rate. Which provides help for studying the cutting mechanism and finite element simulation of nickel-based powder metallurgy superalloy.

Face swapping is an intriguing and intricate task in the field of computer vision. Currently, most mainstream face swapping methods employ face recognition models to extract identity features and inject them into the generation process. Nonetheless, such methods often struggle to effectively transfer identity information, result in generated results failing to achieve a high identity similarity with the source face. Furthermore, if we can accurately disentangle identity information, we can achieve controllable face swapping, thereby providing more choices to users. In pursuit of this goal, we propose a new face swapping framework (ControlFace) based on the disentanglement of identity information. We disentangle the structure and texture of the source face, encoding and characterizing them in the form of feature embeddings separately. According to the semantic level of each feature representation, we inject them into the corresponding feature mapper and fuse them adequately in the latent space of StyleGAN. Owing to such disentanglement of structure and texture, we are able to controllablely transfer parts of the identity features. Extensive experiments and comparisons with state-of-the-art face swapping methods demonstrate the superiority of our face swapping framework in terms of transferring identity information, producing high-quality face images and controllable face swapping.

Since China’s economic reform launched in the late 1970s, rural industrial parks (RIPs) have played a crucial role in the rise of the manufacturing industry in the Pearl River Delta (PRD), transforming the former agricultural land into a location of world-famous factories. However, as China has put forward higher requirements for economic development and stricter control measures for environmental pollution, RIPs with low-end industries and low efficiency present an urgent need for renovation and upgrade. By analyzing the spatial and socioeconomic cross-sectional dataset of rural industrial parks in Nanhai District of Foshan City, this paper attempts to classify the existing industrial parks into groups and propose corresponding redevelopment strategies. The results of the spatial analysis show that the spatial distribution of rural industrial parks is closely related to their location and transportation conditions. Failure of the market has resulted in large tracts of advantageous land being taken up by inefficient industrial parks. Cluster analysis and overlay analysis are used evaluate the difficulty of redevelopment and divide the industrial parks into three clusters: retained RIPs, medium-term-removed RIPs, and near-term-removed RIPs. It is shown that some of the industrial parks are still in good form while the majority need substantial reconstruction. Taking economic and institutional factors into consideration, the authors put forward that different strategies should be adopted for the future renovation of medium-term-removed and near-term-removed RIPs.

Jacobian-free Newton Krylov (JFNK) is an attractive method to solve nonlinear equations in nuclear engineering systems, and has been successfully applied to steady-state neutron diffusion (k-eigenvalue) problems and multi-physics coupling problems. Preconditioning technique plays an important role in JFNK algorithm, significantly affecting computational efficiency. The key point is how to automatically construct a high-quality preconditioning matrix that can improve the convergence rate, and perform the preconditioning matrix factorization efficiently. An efficient reordering-based ILU(k) preconditioner is proposed to achieve the above objectives. In detail, the finite difference technique combined with the coloring algorithm is utilized to construct an efficient preconditioning matrix with low computational cost automatically. Furthermore, the reordering algorithm is employed for the ILU(k) to reduce the additional non-zero elements and pursue robust computational performance. A two-dimensional LRA neutron steady-state benchmark problem is used to evaluate the performance of the proposed preconditioning technique, and steady-state neutron diffusion problem with thermal-hydraulic feedback is also utilized as a supplement. The results show that coloring algorithms can efficiently and automatically construct the preconditioning matrix. The reordering-based ILU(k) preconditioner shows excellent robustness, avoiding the effect of fill-in levels k choice in incomplete LU factorization.

Background: We screened key genes involved in the dedifferentiation process of thyroid cancer by analyzing differentially expressed genes in anaplastic thyroid carcinoma (ATC) using Gene Expression Omnibus (GEO) database. Methods: We analyzed differentially expressed genes in ATC from GEO database and constructed a co-expression network using Weighted Gene Co-expression Network Analysis (WGCNA) . Cytoscape was used to calculate top ten key genes based on their gene scores. DEPDC1 was selected as interest gene for further validation, including examination of its prognostic relationship with thyroid cancer, correlation analysis with thyroid differentiation markers, immune cell infiltration, and tumor microenvironment. The impact of DEPDC1 on cancer cell migration, invasion, and proliferation was validated through downregulation and overexpression of DEPDC1 gene in thyroid cancer cell lines c643 and BCPAP. Results: We identified top 10 key genes in ATC: AURKA, TPX2, RACGAP1, MELK, DLGAP5, DEPDC1, KIF2C, NCAPG, CCNB1, and PBK. DEPDC1 showed a strong correlation with the prognosis of thyroid cancer. The odds ratio (OR) for overall survival was 3.5 (P=0.016) in individuals with high DEPDC1 expression, and the OR for disease-free survival was 2.6 (P=0.003). Additionally, the analysis revealed a significant negative correlation between the expression of DEPDC1 and thyroid differentiation markers. Gene Ontology enrichment analysis demonstrated that DEPDC1 co-expressed genes were enriched in cellular processes, cell cycle pathways, and dynamic protein groups. Matrix and immune scoring indicated tumor microenvironment and immune scores were associated with DEPDC1 expression. TIMER2.0 online analysis revealed a strong correlation between DEPDC1 expression and immune cell infiltration in papillary thyroid carcinoma. After downregulation of DEPDC1 expression, the invasion, migration, and proliferation abilities of tumor cells were significantly reduced. Conversely, overexpression of DEPDC1 exhibited the opposite effect. Conclusion: DEPDC1, a newly identified dedifferentiation gene in thyroid cancer, inversely correlated with the degree of differentiation. High expression of DEPDC1 promotes cancer progression and leads to poor prognosis in thyroid cancer.

The International Maritime Organization (IMO) is enforcing increasingly stringent regulations on ship carbon emissions, The International Maritime Organization (IMO) has been implementing progressively strict regulations on ship carbon emissions, leading to the adoption of the virtual arrival (VA) method by many vessels to reduce their carbon footprint. However, the effectiveness of the traditional VA method often varies in busy ports with complex traffic organization scenarios. To address this, our study presents a novel, comprehensive model that integrates vessel scheduling with the VA approach. This model is designed to achieve a dual objective: reducing carbon emissions through Virtual Arrival and simultaneously minimizing vessel waiting times. In addition to these goals, it incorporates essential aspects of safety, efficiency, and fairness in port management, utilizing the NSGA-2 algorithm to find optimal solutions. This model has been tested and validated through a case study at Ningbo-Zhoushan port, employing its dataset. The results demonstrate that our innovative model and algorithm significantly outperform traditional scheduling methods, such as First-Come-First-Serve (FCFS) and Virtual-Arrival Last-Serve (VALS), particularly in terms of operational efficiency and reduction in vessel carbon emissions.

In this study, the effects of combined addition of CeLa and GdY on microstructure and mechanical properties of as-cast Al-4Cu-1Mn alloys were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopies (TEM) and tensile testing. The results show that the minor addition of CeLa and GdY leads to the refinement of grain size. The addition of CeLa results in the formation of supersaturated vacancies in the Al matrix, whereas the addition of GdY leads to a decrease in the precipitation temperature of the Al2Cu phase. The combined CeLa and GdY addition can significantly increase ultimate tensile strength (UTS) while losing only a small amount of elongation (EL). Compared with the unmodified alloy, the grain size and SDAS of the alloy (0.2 wt% CeLa + 0.1 wt% GdY) were diminished by 67.2% and 58.7%, respectively, while maximum hardness and UTS rose by 31.2% and 36.9%, correspondingly.

The management of blunt abdominopelvic trauma with combined hemoperitoneum and pelvic fractures is challenging for trauma surgeons. Although angioembolization can achieve hemostasis in most visceral organ injuries and pelvic fractures after blunt abdominal trauma, it cannot effectively control hemorrhage in patients with blunt bowel mesenteric injury (BBMI). This study aimed to determine the risk factors associated with hemodynamically unstable patients with BBMI and to test the hypothesis that pelvic fracture is an independent risk factor for patients with unstable BBMI and concomitant pelvic fracture to guide the therapeutic sequence for difficult-to-manage patients. This retrospective study reviewed the data of hospitalized patients with trauma between 2009 and 2021 and included 158 adult patients with surgically proven BBMI. The patients were divided on the basis of the presence of a shock episode before emergency laparotomy. The shock group included 44.3% of all patients in the study (n = 70). Clinical injury severity and prognosis for patients in the shock group were poorer than those for patients in the non-shock group, and more invasive treatments and transfusions were performed for patients in the shock group than for those in the non-shock group. Pelvic fractures were more frequently associated in the shock group than in the non-shock group (21.4% vs. 5.7%; p = 0.003). In multivariate analysis, the presence of intracerebral hemorrhage (odds ratio [OR] = 10.87, 95% confidence intervals [CIs]: 1.70–69.75) and rib fracture (OR = 5.94, 95% CIs = 1.06–33.45) were identified as independent predictors of shock, whereas the effect of pelvic fracture did not achieve statistical significance (OR = 2.94, 95% CIs = 0.66–13.13) after adjusting for confounding factors. For patients with BBMI, outcomes need to be improved during early diagnosis and treatments should be expeditiously performed on the basis of the rapid identification of unstable hemodynamic status. In unstable patients with concomitant pelvic fractures, we support the current management algorithm that recommends performing laparotomy first.

Biodiversity has long been the main objectives in conservation planning while protecting ecosystem services are rarely concerned with. Protecting ecosystem services are gradually recognized by researchers to be included in conservation planning as its significant benefits to human beings. Currently, the most commonly used protecting strategies only focused on high-value areas so that not all the valuable areas would be protected. Furthermore, there are correlation of trade-off and synergy between ecosystem services, aiming at protecting one ecosystem service may have to sacrifice the conservation effectiveness for others. To ensure all the ecosystem services are adequately protected, spatial explicit relations between all the paired ecosystem services were identified via the calculation of Local Moran’s I, a local scale relationship between ecosystem services were defined and they were classified into 5 kinds of cluster. To alleviate the conflict solutions for multiple ecosystem services goals, we used methodology of Systematic Conservation Planning to identify the priority areas for ecosystem service protection, which act the plan with principles of representativeness, complementarity and persistence. By setting scenarios of optimizing each and all the ecosystem services at the target level from 10% to 90%, we found that positive correlation between each of the 4 ecosystem services occupied large areas in the Yangtze River Basin and all the high-value areas were not congruence in spatial distributions. The optimal conservation spatial pattern showed that the priority areas were quite different when the target level was low. Our results implicated that an integrated conservation planning of achieving objectives of all the ecosystem services is more efficient than superposing multiple planning time after time.

Sterol regulatory element-binding proteins (SREBPs) are transcription factors that regulate genes involved in the biogenesis of cholesterol, fatty acids, and triglycerides. SREBPs are involved in the pathogenesis of non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), fibrosis, and hepatocellular carcinoma (HCC). We review the mechanisms by which SREBPs regulate lipogenesis, the alterations in these processes associated with liver diseases, and therapeutic strategies to target these pathways.

The airborne and satellite-based synthetic aperture radar enables the acquisition of high-resolution SAR oceanographic images in which even the outlines of ships can be identified. The detection of ship targets from SAR images has a wide range of applications, such as the military, where the dynamic grasp of enemy targets can help improve the early warning capability of naval defence, and the civilian detection of illegal fishing vessels can help improve the level of maritime management. Due to the density of ships in SAR images, the extreme imbalance between foreground and background clutter, and the diversity of target sizes, achieving lightweight and highly accurate multi-scale ship target detection remains a great challenge. To this end, this paper proposes an attention mechanism for multiscale receptive fields convolution block (AMMRF). AMMRF not only makes full use of the location information of the feature map to accurately capture the regions in the feature map that are useful for detection results, but also effectively captures the relationship between the feature map channels, so as to better learn the relationship between the ship and the background. Based on this, a new YOLOv7-based ship target detection method, You Only Look Once SAR Ship Identification (YOLO-SARSI), is proposed, which acquires the abstract semantic information extracted from the high-level convolution while retaining the detailed semantic information extracted from the low-level convolution. Compared to the deep learning detection methods proposed by previous authors, our model is more lightweight, only 18.43M. We examined the effectiveness of our method on two SAR image public datasets: the High-Resolution SAR Images Dataset (HRSID) and the Large-Scale SAR Ship Detection Dataset-v1.0 (LS-SSDD-V1.0). The results show that the average accuracy AP50 of the detection method YOLO-SARSI proposed in this paper on the HRSID and LS-SSDD-V1.0 datasets is 4.9% and 5% higher than that of YOLOv7, respectively.

It’s been reported that Mori Folium (MF) and Eucommiae Cortex (EC) exhibit pharmacological effects on the treatment of immunosuppression. However, the mechanism of MF and EC against immunosuppression remains unclear. This study aims to explore the mechanism of action of MF and EC for the treatment of immunosuppression through network pharmacology, molecular docking, molecular dynamics simulations and animal experiments. As a result, 11 critical components, 9 hub targets, and related-signaling pathways of treatment of immunosuppression were obtained based on network pharmacology. The molecular docking suggested that 11 critical components exhibited great binding affinity to 9 hub targets of immunosuppression. The molecular dynamics simulations results showed that (-)-Tabernemontanine-AR, beta-sitosterol-AR and Dehydrodieugenol-HSP90AA1 complexes are stably bound. Additionally, in the animal experiments, the treated group results compared to the control group suggest that MF and EC have a significant effect on the treatment of immunosuppression. Therefore, the MF and EC treatment for immunosuppression may take effects in a multi-component, multi-target, and multi-pathway manner. The results would provide novel insights into the treatment of immunosuppression in humans.

Pool boiling is extensively utilized in various fields, such as electronics cooling, battery cooling, nuclear power plants, and chemical processing. In the process of temperature control through boiling, the generation and transportation of bubbles play a crucial role in calculating the heat transfer capacity of the system. Therefore, it holds immense significance to gain a profound understanding of the mechanisms underlying bubble formation, growth, and detachment. Currently, numerous mechanistic explanations and empirical correlations have been proposed to elucidate various parameters of bubbles during the boiling process. These findings were considered valuable references in selecting appropriate boiling media and designing efficient heating surfaces. To comprehensively present the progress of bubble formation and heat transfer during the boiling process, the forces exerted on the bubbles was highlighted in this article. And a meticulous review on bubble force analysis and correlation formulas pertaining to various relevant parameters (e.g. nucleation sites density, bubble growth rate, detachment diameter, detachment frequency) were conducted. This review article also were expected to provide a novel foundation for further exploration of enhanced boiling heat transfer.

Constructed wetlands (CWs) is a kind of green environmental protection technology, which is widely used in sewage treatment. The traditional CWs is faced with the problem of low treatment effect of high concentration sewage. In recent years, biochar, as a new type of adsorption material, has been used in CWs because of its advantages of large specific surface area, strong adsorption capacity and wide material sources. This paper systematically summarized the characteristics of biochar and the preparation of biochar by studying the changes of microorganisms added to CWs, and compared the effects of different treatment methods coupled with biochar on the treatment performance of CWs, the effects of biochar coupled with CWs on enzyme activity, functional genes, metabolites and microbial communities were investigated. This review summarizes how different preparation methods affect the properties of biochar and how these biochar cause changes in the microorganisms added to CWs.

In order to balance the conflicts among mass flow rate, total pressure ratio, adiabatic efficiency and stall margin in a low-bypass transonic fan, the optimization of the rotor blade is implemented in this study. An advanced 3D optimization design system is adopted, and flow diagnostic methods based on vorticity dynamics are employed to discuss the flow field. Results indicate that by controlling the blade camber line curvature, significant improvements in the aerodynamic performance for the fan stage are achieved, the total pressure ratio is increased by 1.90%, while the adiabatic efficiency and mass flow rate are increased by 4.45% and 5.82%, respectively. Vorticity diagnosis suggest that there exists a close link between performance parameters and vorticity parameters in the axial fan/compressor, both azimuthal vorticity and boundary vortex flux have significant influences on the stage performance. Moreover, the boundary layer separation is accompanied by the spike of entropy and static pressure, while the derivation/gradient of these flow parameters would also suffer drastic changes under the effect of shock wave. The vorticity parameters could provide detailed flow information about the on-wall flow with high accuracy, which provides the researchers with a novel method for the turbomachinery aerodynamic design and analysis.

Conical emission is a typical nonlinear phenomenon that occurs when the femtosecond laser pulses interact with transparent media. In this work, the conical emission induced by two kinds of typical vortex beams (i.e., Laguerre-Gaussian (LG) and Bessel-Gaussian (BG) beams) in water is experimentally studied. By recording the light spots of different wavelengths on the screen, the characteristics of the conical emission induced by femtosecond vortex beams are studied. It is found that the spots of the supercontinuum induced by the two kinds of vortex beams differ greatly from each other: The spots of the supercontinuum induced by the BG beam are a set of concentric rings like a rainbow with a white center, while the whit light spot in the case of the LG beam are a circular white disk, which is different from the commonly observed white light spots. By measuring the maximum divergence angle, it is observed that the divergence angle increases with the decrease of the wavelength, while the TC merely affects the divergence angle, which is explained from the formation mechanism of conical emission in terms of self-phase modulation. We hope this work can be helpful to the understanding of interaction between the intense laser pulses and matters.

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.

Long-term storage may reduce the nutritional quality of brown rice, so the present study was aimed to evaluate the nutritive values and application in pig diets. In Exp.1, 18 Landrace × Yorkshire (L × Y) barrows with initial body weight (IBW) of 25.48 ± 3.21 kg were randomly assigned to three treatments, which included corn diet, one-year stored brown rice (BR1) diet and six-year stored brown rice (BR6) diet, to determine the digestible energy (DE) and metabolisable energy (ME) value of stored brown rice. In Exp. 2, 24 barrows (L × Y; IBW: 22.16 ± 2.42 kg) fixed with ileal T-cannula were randomly allotted to four dietary treatments, including corn diet, two stored brown rice diets and nitrogen-free diet, to evaluate the amino acid (AA) digestibility of stored brown rice. In Exp. 3 and 4, 108 crossbred weaned piglets (L × Y; IBW: 9.16 ± 0.89 kg) and 90 crossbred growing pigs (L × Y; IBW: 48.28 ± 3.51 kg) were allotted to 3 treatment diets, including control diet and two stored brown rice diets, respectively, to investigate the application of stored brown rice in weaned piglet and growing-finishing pig diets. Results showed that: 1) The DE and ME of corn and stored brown rice showed no significant differences (P > 0.05), while the apparent ileal digestibility (AID) of arginine, histidine, aspartic acid, and the standardized ileal digestibility (SID) of arginine and histidine were higher in stored brown rice compared to corn (P < 0.05). 2) Compared with the control diet, the stored brown rice diets showed no significant effects on growth performance, nutrient apparent total tract digestibility (ATTD) and serum biochemical indices (P > 0.05), but decreased digestive enzymes activities in duodenum, jejunum and ileum of piglets (P < 0.05). 3) Compared with the control diet, the stored brown rice diets showed no significant effects on growth performance, carcass traits, meat quality, fatty acids profiles in the longissimus dorsi muscle of growing-finishing pigs (P > 0.05). In conclusion, the brown rice stored for 6 years under good conditions has no obvious changes in available energy and nutrient values. Although it may reduce digestive enzyme activity in small intestine of the piglets, the stored brown rice showed no obvious adverse effect on growth performance and meat quality, and can be effectively used in pig diet.

During routine bridge maintenance, edge detection allows the partial condition of the bridge to be viewed. However, many edge detection methods often have unsatisfactory performances when dealing with images with complex backgrounds. Moreover, the processing often involves the manual selection of thresholds, which can result in repeated testing and comparisons. To address these problems in this paper, the wavelet transform modulus maxima method is used to detect the target image, and then the threshold value of the image can be determined automatically according to the OTSU method to remove the pseudo-edges. Thus, the real image edges can be detected. The results show that the information entropy and SSIM of the detection results are the highest when compared with the commonly used Canny and Laplace algorithms, which means that the detection quality is optimal. To more fully illustrate the advantages of the algorithms, images with more complex backgrounds were detected and the processing results of the algorithms in this paper are still optimal. In addition, the automatic selection of thresholds saves the operator’s effort and improves the detection efficiency. Thanks to the combined use of the above two methods, detection quality and efficiency are significantly improved, which has a good application in engineering practice.

The E-learning system has achieved great development after the pandemic. In this work, we proposed three artificial intelligence-based enhancements to our linguistic interactive E-learning system from different aspects. Compared with the original phonetic transcription exam system, our enhancements include an MFCC+CNN-based disordered speech classification module, a Transformer-based Grapheme-to-Phoneme converter, and a Tacotron2-based IPA-to-Speech speech synthesis system. This work not only provides a better experience for the users of this system but also explores the utilization of artificial intelligence technologies in the E-learning field and linguistic field.

The relative position of the orchard robot to the rows of fruit trees is an important parameter for achieving autonomous navigations. The current methods for estimating the position parameters between rows of orchard robots obtain low parameter accuracy, and to address this problem, this paper proposes a machine vision-based method for detecting the relative position of orchard robots and fruit tree rows. Firstly, the fruit tree trunk is identified based on the improved YOLOv4 model; secondly, the camera coordinates of the tree trunk are calculated from the principle of binocular camera triangulation, and the ground projection coordinates of the tree trunk are obtained through coordinate conversion; finally, the midpoints of the projection coordinates of different sides are combined and the navigation path is obtained by linear fitting with the least squares method, and the position parameters of the orchard robot are obtained through calculation. The experimental results show that the average accuracy and average recall of the improved YOLOv4 model for fruit tree trunk detection are 97.05% and 95.42%, respectively, which are 5.92 and 7.91 percentage points higher than those of the original YOLOv4 model. The average errors of heading angle and lateral deviation estimates obtained based on the method in this paper are 0.57° and 0.02 m. The method can accurately calculate heading angle and lateral deviation values at different positions between rows, and can provide a reference for autonomous visual navigation of orchard robots.

The Yellow River Basin (YRB) is a crucial ecological zone and an environmentally vulnerable re-gion in China. Understanding the temporal and spatial trends of terraced-field areas (TRAs) and the factors underlying them in the YRB is essential for improving land use, conserving water re-sources, promoting biodiversity, and preserving cultural heritage. In this study, we employed ma-chine learning on the Google Earth Engine (GEE) platform to obtain spatial distribution images of TRAs from 1990 to 2020 using Landsat 5 (1990－2010) and Landsat 8 (2015－2020) remote sens-ing data. The GeoDa software platform was used for spatial autocorrelation analysis, revealing distinct spatial clustering patterns. Mixed linear and random forest models were constructed to identify the driving force factors behind TRA changes. The research findings reveal that TRAs were primarily concentrated in the upper and middle reaches of the YRB, encompassing provinc-es such as Shaanxi, Shanxi, Qinghai, and Gansu, with areas exceeding 40,000 km2, whereas other provinces had TRAs of less than 30,000 km2 in total. The TRAs exhibited a relatively stable trend, with provinces such as Gansu, Qinghai, and Shaanxi showing an overall upward trajectory. Conversely, Shanxi and Inner Mongolia demonstrated an overall declining trend. When com-pared with other provinces, the variations in TRAs in Ningxia, Shandong, Sichuan, and Henan appeared to be more stable. The linear mixed model (LMM) revealed that farmland, shrubs, and grassland had significant positive effects on the TRA, explaining 41.6% of the variance. The ran-dom forest model also indicated positive effects for these factors, with high R² values of 0.983 and 0.86 for the training and testing sets, respectively, thus outperforming the LMM. The findings of this study can contribute to the restoration of the YRB's ecosystem and support sustainable devel-opment. The insights gained will be valuable for policymaking and decision support in soil and water conservation, agricultural planning, and environmental protection in the region.

Titanium alloys are difficult to machine and have poor tribological properties. This paper investigates the lubricating performance of γ-Al2O3/ZnO hybrid nanofluids for Ti-6Al-4V. The pure and hybrid nanofluid are compared, and the effects of γ-Al2O3/ZnO ratios are studied. The results show that γ-Al2O3/ZnO hybrid nanofluids outperform pure nanofluid in terms of lower friction coefficients and better surface quality. Moreover, the hybrid nanofluid with a mass ratio of Al2O3 to ZnO of 2:1 demonstrates the best lubrication performance with a reduced friction coefficient of up to 22.1% compared to the base solution, resulting in improved surface quality. Al2O3 nanoparticles can adhere to the surface of ZnO nanoparticles and work as a coating, which further enhances the lubrication performance of the water-based nanofluid.

In light of advancing technology, the conventional clock network architecture has become inadequate for addressing the intricacies inherent in modern System-on-Chip (SoC) designs. While clock mesh topology offers resilience against On-Chip Variation (OCV) fluctuations, it still necessitates manual intervention. Therefore, substantial scope exists for methodological enhancements and the refinement of rapid analytical techniques. This paper introduces a novel clock mesh synthesis approach, underpinned by dynamic programming algorithms, that guarantees latency constraints. Our experimental findings demonstrate that our algorithm achieves an additional 26.6% reduction in power consumption compared to the baseline methodology. Furthermore, it substantially reduces runtime by an average of 78.0% when contrasted with traditional simulation methods. These results highlight the potential of our methodology for enhancing the efficiency and power management of clock mesh.

A recent study demonstrated that noninvasive measurements of cortical hemodynamics and metabolism in the resting human prefrontal cortex can facilitate quantitative metrics of unilateral mitochondrial-hemodynamic coupling and bilateral connectivity in infraslow oscillation (ISO) frequencies in young adults (YA). The ISO includes three distinct vasomotions with endogenic (E), neurogenic (N), and myogenic (M) frequency bands. The goal of this study was to prove the hypothesis that there are significant differences between young and older adults (OA) in the unilateral coupling (uCOP) and bilateral connectivity (bCON) in the prefrontal cortex. Accordingly, we performed measurements from 24 OA (67.2 ± 5.9 years of age) using the same 2-channel broadband near-infrared spectroscopy (bbNIRS) setup and resting-state experimental protocol as those in the recent study (Shahdadian et al, Cerebral Cortex Communications, 2022). After quantification of uCOP and bCON in three E/N/M frequencies and statistical analysis, we demonstrated that OA had significantly weaker bilateral hemodynamic connectivity but significantly stronger bilateral metabolic connectivity than YA in the M band. Furthermore, OA exhibited significantly stronger unilateral coupling on both prefrontal sides in all E/N/M bands, particularly with a very large effect size in the M band (&gt; 1.9). These age-related results clearly support our hypothesis and were well interpreted following neurophysiological principles. The key finding of this paper is that the neurophysiological metrics of uCOP and bCON are highly associated with age and may have the potential to become meaningful features for human brain health and be translatable for future clinical applications, such as early detection of Alzheimer’s disease.

Background: Plasma levels of von Willebrand factor (VWF) are significantly elevated in patients with COVID-19. However, the dynamic changes and prognostic value of this biomarker in hospitalized patients with COVID-19 are not determined. Methods: 124 patients infected with SARS-CoV2 were prospectively recruited for the study. Serial blood samples were obtained at the time of admission (D1), 3-4 days following standard of care treatments (D2), and 1-2 days prior to discharge or death (D3). Plasma VWF antigen, ADAMTS13 antigen and activity, as well as the ratio of VWF/ADAMTS13 were determined, followed by statistical analyses. Results:While admission plasma levels of VWF in COVID-19 patients were significantly elevated, no statistical significance was detected among patients of different disease severity. Plasma ADAMTS13 activity, but not its antigen levels, were significantly lower in patients with severe or critical COVID-19 compared with other groups. Interestingly, the ratios of plasma VWF antigen to ADAMTS13 antigen were significantly higher in patients with severe or critical COVID-19 than in those with mild to moderate disease. More importantly, plasma levels of VWF and VWF/ADAMTS13 ratios were persistently elevated in patients with COVID-19 during hospitalization. Kaplan-Meier and Cox proportional hazard regression analysis revealed that an increased plasma VWF or ratio of VWF/ADAMTS13 at D2 and D3 associated with an increased mortality rate. Conclusions: Persistent endotheliopathy, marked by an elevated level of plasma VWF or an increased VWF/ADAMTS13 ratio, is present in all hospitalized patients following SARS-CoV2 infection and strongly associated with mortality.

(1) Background: Endoscopic submucosal dissection (ESD) has been widely accepted as the standard method for treating early-stage cancer or precancerous lesions in the upper gastrointestinal tract, however it may be difficult in patients with liver cirrhosis due to coagulation dysfunction or presence of gastroesophageal varices. We aimed to demonstrate the safety and efficacy of ESD in these population. (2) Methods: We retrospectively collected the clinical data and analyzed. Patients inclusion criteria: 1) patients with liver cirrhosis; 2) patients who underwent ESD; 3) patients diagnosed of early-stage cancer or precancerous lesions in the upper gastrointestinal tract. (3) Results: Eight patients were enrolled from April 2019 to April 2023, of whom 3 were male and 5 female, with age ranging from 43 to 70 years old. Seven lesions were located in the stomach, and the other one lesion in the esophagus. ESD was performed successfully in all patients, and the resected lesion size ranged from 2 to 6 cm. Only one patient encountered postoperative complication, chest pain and fever. No recurrence of noticed during a follow-up of 6 to 36 months. (4) Conclusions: ESD is safe and effective for treating upper gastrointestinal early-stage cancer or precancerous lesions in patients with liver cirrhosis.

Cellobiose phosphorylase (CBP) catalyzes the reversible phosphorolysis of cellobiose into α-glucose 1-phosphate and glucose. When it was used in transforming cellulose to amylose (PNAS, 110: 7182-7187, 2013) as well as in constructing a yeast with the ability to phosphorolytically use cellodextrin to produce ethanol, a CBP with a broadened substrate specificity would be more desirable. Based on the structure differences in the catalytic loops of CBP and cellodextrin phosphorylase from Clostridium thermocellum (named CtCBP and CtCDP, respectively), CtCBP was mutated. A single-site mutant S497G was identified to have a 5.7-fold higher catalytic efficiency with cellotriose as a substrate in phosphorolytic reaction direction compared to wild type, without any loss of catalytic efficiency on its natural substrate cellobiose. When S497G variant was used in the transformation of mixed cellodextrin (cellobiose + cellotriose) to amylose, a significant increase in amylose yield was achieved compared to that of wild type CtCBP. Structure change in the substrate binding pocket of S497G variant accounted for its capacity to accept longer cellodextrins than cellobiose. Taken together, S497G variant of CtCBP was confirmed to acquire a promising feature favorable to those application scenarios involving cellodextrin’s phosphorolysis.

The study investigated the relationships between sarcopenia, frailty, and related factors in hemodialysis patients with chronic kidney disease. A prospective cross-sectional study with convenience sampling was conducted between August 2021 and February 2022 at a hospital-affiliated hemodialysis center. Ninety-six hemodialysis patients participated in the study. Quantitative data were collected with structured interviews. Sarcopenia was determined with a rapid screening tool. Frailty was determined with the Rockwood clinical frailty score. Descriptive analysis, Person Correlations, and Linear regression analysis were used to evaluate the associations between frailty, sarcopenia, and health-related factors in hemodialysis patients. The mean age of the participants was 65.4 11.5 years, with an average of 95.0 77.5 months of hemodialysis. The most common comorbidity was hypertension (72.9%), followed by diabetes mellitus (39.6%) and cardiovascular health problems (35.4%). A significant difference in frailty between sarcopenia patients and a healthy population (X2 =9.51, p &lt;.001) was identified. There was a strong negative correlation (r= −.853, p&lt;.001) between sarcopenia and frailty, while moderate correlations between sarcopenia and frailty in sarcopenia patients (r= −.66, p&lt;.001) and a healthy population (r= −.58, p&lt;.001) were observed. Age, body weight before dialysis, and hand grip strength were found to be potential predictors of sarcopenia and frailty. Left calf circumference was significantly associated with sarcopenia (ß= −.128, p = .049). Age, body weight before dialysis, and hand grip strength are potential predictors of sarcopenia and frailty in hemodialysis patients with chronic kidney disease. Comorbidities, which may be preventable, are common in this population.

Two-dimensional (2D) transition metal dichalcogenides (TMDCs) draw much attention as critical semiconductor materials for 2D, optoelectronic, and spin electronic devices. Although controlled doping of 2D semiconductors can also be used to tune their bandgap and type of carrier and further change their electronic, optical, and catalytic properties, it remains an ongoing challenge. Here, we successfully doped a series of metal elements (including Hf, Zr, Gd, Dy) into the monolayers MoS2 through a single-step chemical vapor transport (CVT), and the atomic embedded structure is confirmed by scanning transmission electron microscope (STEM) with a probe corrector measurement. In addition, the host crystal is well preserved, and no random atomic aggregation is observed. More importantly, adjusting the band structure of MoS2 enhanced fluorescence and carrier effect. This work provides a growth method for doping nonlike elements into 2D MoS2 and potentially many other 2D materials to modify their properties.