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About ten years ago, Wenhui Li’s research group in China identified the sodium taurocholate co-transporting polypeptide (NTCP), a bile acid transporter predominantly expressed in the liver, as a functional receptor for hepatitis B virus (HBV) and its satellite hepatitis delta virus (HDV) through biochemical and genetic studies. This finding unraveled a longtime mystery in the HBV field and led to the establishment of efficient and easy-to-use HBV infection models, which paved the way for the in-depth study of the HBV entry mechanism and facilitated the development of therapeutics against HBV and HDV. The whole picture of the complex HBV entry process became clear upon the follow-up studies over the years, including the recent resolution found for the NTCP structure. As one of the first authors of the 2012 eLife paper on NTCP identification, here, I (H. Y.) share our experience on the bumpy and exciting journey of receptor hunting, particularly on the photo-cross-linking study and some detailed descriptions of the “fishing” process and summarize the key factors for our successful receptor identification. This review may also provide helpful insights for identifying a protein target by peptide or protein baits through cross-linking and immunoprecipitation.

G-protein-coupled receptors (GPCRs) belong to a cell surface receptor superfamily responding to a wide range of external signals. The binding of extracellular ligands to GPCRs activates a heterotrimeric G protein and triggers the production of numerous secondary messengers, which transduce the extracellular signals into cellular responses. GPCR signaling is crucial and imperative for maintaining normal tissue homeostasis. High-throughput sequencing analyses revealed the occurrence of the genetic aberrations of GPCRs and G proteins in multiple malignancies. The altered GPCRs/G proteins serve as valuable biomarkers for early diagnosis, prognostic prediction, and pharmacological targets. Furthermore, the dysregulation of GPCR signaling contributes to tumor initiation and development. In this review, we have summarized the research progress of GPCRs and highlighted their mechanisms in gastric cancer (GC). The aberrant activation of GPCRs promotes GC cell proliferation and metastasis, remodels the tumor microenvironment, and boosts immune escape. Through deep investigation, novel therapeutic strategies for targeting GPCR activation have been developed, and the final aim is to eliminate GPCR-driven gastric carcinogenesis.

Cerebral ischemia refers to the symptom of insufficient blood supply to the brain. Cells of many different origins participate in the process of repairing damage after cerebral ischemia occurs, in which exosomes secreted by the cells play important roles. For their characteristics, such as small molecular weight, low immunogenicity, and the easy penetration of the blood–brain barrier (BBB), exosomes can mediate cell-to-cell communication under pathophysiological conditions. In cerebral ischemia, exosomes can reduce neuronal damage and improve the brain microenvironment by regulating inflammation, mediating pyroptosis, promoting axonal growth, and stimulating vascular remodeling. Therefore, exosomes have an excellent application prospect for the treatment of cerebral ischemia. This article reviews the roles and mechanisms of exosomes from different sources in cerebral ischemia and provides new ideas for the prevention and treatment of cerebral ischemia.

The magnetic properties of 50 nm Ni80Fe20 deposited on Cu underlayers with different thicknesses by obliquely sputtering were studied. It was found that the in-plane uniaxial magnetic anisotropy (IPUMA) of the Ni80Fe20 film can be induced by the obliquely sputtered Cu underlayer deposited under the NiFe layer. The IPUMA field of NiFe film varies between 20 Oe and 40 Oe when the thickness of Cu underlayer varies from 5 nm to 50 nm. The permeability spectrum results show that the damping factor increases with increasing Cu underlayer thickness. This indicates that changing the thickness of the Cu underlayer of obliquely sputtering is an effective method to adjust the damping factor in the dynamic magnetization process of Ni80Fe20 thin films.

Over the last decade, many bio-inspired crawling robots have been proposed by adopting the principle of two-anchor crawling or anisotropic friction-based vibrational crawling. However, these robots are complicated in structure and vulnerable to contamination, which seriously limits their practical application. Therefore, a novel vibro-impact crawling robot driven by a dielectric elastomer actuator (DEA) is proposed in this paper, which attempts to address the limitations of the existing crawling robots. The novelty of the proposed vibro-impact robot lies in the elimination of anchoring mechanisms or tilted bristles in conventional crawling robots, hence reducing the complexity of manufacturing and improving adaptability. A comprehensive experimental approach was adopted to characterize the performance of the robot. First, the dynamic response of the DEA-impact constraint system was characterized in experiments. Second, the performance of the robot was extensively studied and the fundamental mechanisms of the vibro-impact crawling locomotion were analyzed. In addition, effects of several key parameters on the robot’s velocity were investigated. It is demonstrated that our robot can realize bidirectional motion (both forward and backward) by simple tuning of the key control parameters. The robot demonstrates a maximum forward velocity of 21.4 mm/s (equivalent to 0.71 body-length/s), a backward velocity of 16.9 mm/s, and a load carrying capacity of 9.5 g (equivalent to its own weight). The outcomes of this paper can offer guidelines for high-performance crawling robot designs, and have potential applications in industrial pipeline inspections, capsule endoscopes, and disaster rescues.

Lotus (Nelumbo nucifera Gaertn.) is a traditional Chinese aquatic flower with high ornamental and economic value, but water salinity seriously affects lotus cultivation and distribution. The Dof transcription factors (TFs) play a crucial function in the regulatory network of growth and defense in plants. However, no systematic investigations of the Dof TFs in lotus have been performed. In this study, comprehensive searches of the lotus genome yielded 29 potential NnDofs. We carried out a series of standardized analyses, which include physical properties, multiple sequence alignment, phylogenetic analysis, gene structure, motif composition, cis-acting element prediction, chromosome distribution, and synteny analysis. The results showed that segment duplication probably caused the NnDofs gene family expansion. The potential functions of NnDofs in lotus development and stress conditions are speculated by promoter analysis. Furthermore, a complete expression investigation of NnDofs utilizing an RNA-seq atlas and quantitative real-time polymerase chain reaction (qRT-PCR) was performed. The majority of the NnDofs exhibit tissue-specific expression patterns, and many genes have been identified as being extremely sensitive to salt stressors. Overall, this study is the first to report a genome-wide assessment of the Dof family in lotus, and the findings offer vital insights for prospective functional studies on lotus salinity stress.

The classical continuum mechanics theory cannot sufficiently describe the effect of pebbles on projectile, which leads to a large calculation error. In this paper, an orthogonal curvilinear coordinate system is constructed, which effectively describes and perfects the normal cavity expansion theory. A couple stress theory based on the normal cavity expansion is proposed in which not only the tangential movements but also the rotations of the concrete medium are considered. According to the high-speed impact of pebble concrete, combined with dynamic equations and the FE simulation, the theoretical and simulation results of pebble particles scale on warhead resistance are compared. It is shown that, the larger the scale of pebble particles, the stronger the effect of rotation on the resistant force applied on the warhead.

The design scheme and fabrication technology of the detonation control system for the high-speed deep penetration need to be tested for reliability and effectiveness through shooting range tests. However, the shooting range tests of the high-speed deep penetration are so demanding and expensive that it is difficult for the detonation control system to be tested many times. This paper focuses on penetration characteristics of the detonation control system to put forward a laboratory-scaled experiment method with the low impact velocity. Independent parameters of projectile and target affecting the penetration characteristics are effectively analyzed and extracted. A multi-parameter programming method of the scaled experiment for high-speed deep penetration is established. By adjusting the key parameters, the loading conditions of the scaled experiment can be obtained, which can get the comparable deceleration curve with those of the high-speed deep penetration. Finally, the extreme working environment for the detonation control system in the high-speed deep penetration is simulated through the scaled experiment in the laboratory. The scaled experiment method can get the comparable deceleration peak and time history. It is highly economical, and the experimental process is also repeatable, which can provide a reliable reference for the protection design into the projectile.

Formation water scale blocks pipelines and results in oil/gas production decreasing and energy consumption increasing. Many methods have been developed to inhibit scale formation. However, these previous methods are limited by their complications and low efficiency. A new method is proposed in this paper that uses the scale in formation water as a nanomaterial to improve oil recovery via controlling particle size. A series of ligands were synthesized and characterized. Micrometer-CaCO3 was formed and accumulated to form scale of a large size under uncontrolled conditions. The tetradentate ligands (L4) exhibited an excellent capturing yield of Ca2+ (87%). The particle size was very small, but they accumulated to form large particles (approximately 1300 nm) in the presence of Na2CO3. The size of the CaCO3 could be further controlled by poly(aspartic acid) to form sizes of about 700 nm. The flooding test showed that this material effectively improved oil recovery from 55.2% without nano CaCO3 to 61.5% with nano CaCO3. This paves a new pathway for the utilization of Ca2+ in formation water.

Relay channels capture the essence of several important communication scenarios such as sensor network and satellite communication. In this paper, first, we propose an efficient coding scheme for an additive white Gaussian noise (AWGN) relay channel in the presence of AWGN feedback, which generalizes the conventional scheme for the AWGN relay channel with noiseless feedback by introducing a lattice-based strategy to eliminate the impact of the feedback channel noise on the performance of the original scheme. Next, we further extend the proposed scheme to the multi-input single-output (MISO) fading relay channel (FRC) with noisy feedback. The key to this extension is to use a pre-coding strategy to transform the MISO channel into a single-input single-output (SISO) channel and applying a two-dimensional lattice coding strategy to deal with the feedback fading channel noise. Finally, we analyze the security performance of our proposed scheme in several cases, and the results of this paper are further illustrated by numerical examples.

Pork belly, prized for its unique flavor and texture, is often overlooked in breeding programs that prioritize lean meat production. The quality of pork belly is determined by the number and distribution of muscle and fat layers. This study aimed to assess the number of pork belly layers using deep learning techniques. Initially, semantic segmentation was considered, but the intersection over union (IoU) scores for the segmented parts were below 70%, which is insufficient for practical application. Consequently, the focus shifted to image classification methods. Based on the number of fat and muscle layers, a dataset was categorized into three groups: three layers (n = 1811), five layers (n = 1294), and seven layers (n = 879). Drawing upon established model architectures, the initial model was refined for the task of learning and predicting layer traits from B-ultrasound images of pork belly. After a thorough evaluation of various performance metrics, the ResNet18 model emerged as the most effective, achieving a remarkable training set accuracy of 99.99% and a validation set accuracy of 96.22%, with corresponding loss values of 0.1478 and 0.1976. The robustness of the model was confirmed through three interpretable analysis methods, including grad-CAM, ensuring its reliability. Furthermore, the model was successfully deployed in a local setting to process B-ultrasound video frames in real time, consistently identifying the pork belly layer count with a confidence level exceeding 70%. By employing a scoring system with 100 points as the threshold, the number of pork belly layers in vivo was categorized into superior and inferior grades. This innovative system offers immediate decision-making support for breeding determinations and presents a highly efficient and precise method for assessment of pork belly layers.

Although various degradable gel materials have been developed for temporary plugging in oil fields, they often degrade too quickly in high-temperature environments. To address this issue, an unstable crosslinker was synthesized to prepare a high-temperature degradable gel. This gel does not degrade excessively fast at high temperatures. Temperature and crosslinker concentration are the primary factors influencing gel degradation time, followed by monomer and initiator concentrations. Increased temperature and decreased crosslinker concentration both reduce degradation time, which can be adjusted within the range of 90–130 °C by varying the crosslinker concentration. The molecular structure and thermal stability of the degradable gel were analyzed using FTIR, 13C NMR, and TG. Furthermore, the viscoelastic properties, compressive performance, plugging performance, and core damage performance of the gel were evaluated. Within the test range of 0.1–1000 Pa, the storage modulus is higher than the loss modulus. The gel prepared at 130 °C exhibited a compressive stress of 0.25 MPa at 50% strain. The plugging pressure of the gel in sand-filled tubes with varying permeabilities (538.2–2794.1 mD) exceeded 15 MPa while maintaining a core damage rate below 5%. SEM analysis indicated that the degradation mechanism of the gel may involve the collapse of its three-dimensional network structure due to the hydrolysis of amide groups in the crosslinker. The viscosity of the degradation liquid was below 11 mPa·s, enabling it to be brought back to the surface with the formation fluid without the need for further breaking operations.

Transition-metal-based oxygen evolution reaction (OER) catalysts have attracted widespread attention due to their inexpensive prices, unique layered structures, and rich active sites. Currently, designing low-cost, sustainable, and simple synthesis methods is essential for the application of transition-metal-based catalysts. Here, magnetic field (MF)-assisted chemical corrosion, as a novel technology, is adopted to construct superior OER electrocatalysts. The produced Ni(Fe)(OH)2-Fe2O3 electrode exhibits an overpotential of 272 mV at a current density of 100 mA cm−2, presenting a 64 mV reduction compared to the electrode without an MF. The experimental results indicate that an MF can induce the directional growth of Fe2O3 rods and reduce their accumulation. In addition, an external MF is beneficial for the lattice dislocation of the obtained catalysts, which can increase the surface free energy, thus reducing the activation energy and accelerating the electrochemical reaction kinetics. This work effectively combines a magnetic field with chemical corrosion and electrochemical energy, which offers a novel strategy for the large-scale development of environmentally friendly and superior electrocatalysts.

As a novel design of large-mode-area fiber, the single trench fiber (STF) providing high higher-order-mode suppression with a large mode area for the fundamental mode shows potential for high-power and high-brightness applications. However, the output power of STFs has remained relatively low over the past decade. In this paper, we first conducted a design process for STFs and determined the optimal ratio of the fiber structural parameters. Following this ratio, we fabricated an ytterbium-doped STF and demonstrated an all-fiberized fiber amplifier. The system achieved an output power of 2.5 kW with an M2 factor of 1.396. To the best of our knowledge, the power of the STF in this study is approximately three times higher than the previous single-mode power record.

With the increase in the number of buildings along the subway, the impact of building construction on the adjacent subway tunnels has gradually come to the forefront and become an important problem to be solved in the engineering field. In particular, the excavation and unloading process of deep foundation pits will trigger an additional deformation of the subway structure, which may pose a serious threat to the safety and stability of subway tunnels. This article is based on a foundation pit project in the sub-center of Beijing, focusing on the form of a connected double foundation pit. Using the HSS constitutive model for soil materials, this study simulates the deformation response of adjacent existing subway tunnels under three excavation sequences: sequential excavation, simultaneous excavation, and the comprehensive excavation of the connected double foundation pits. The study shows that, from the point of view of the total displacement of the whole construction process, the impact of a synchronized excavation of double pits on the existing tunnel line is relatively large in the process, and the impact of sequential excavation is relatively small in the construction cycle. The result of the similarity of the excavation sequence is the similarity of the impact trend. The volume of excavated earth determines the value of displacement change for each excavation scenario in each working condition and is also responsible for the convergence of changes. The trend of total tunnel displacement is more consistent with that of vertical displacement, which is dominated by vertical displacement, with horizontal displacement having a relatively small influence. The maximum value of the total tunnel displacement occurs at the side of the tunnel near the excavation area, and the direction is inclined to the excavation area. The application of supporting structures, especially the center plate and the bottom plate, can suppress the vertical deformation of the tunnel bulge.

The inaccuracy of inhomogeneous sound speed fields in photoacoustic imaging (PAI) can lead to the blurring and distortion of photoacoustic images. To solve this problem, conventional methods build speed models by using some a priori information or additional measuring equipment, which limits the application of PAI greatly. A data-driven speed field inversion method is proposed in this paper. It combines clustering with updates to the speed field. To reduce the complexity of the sound speed field model, the model is divided according to the similarity of the same tissue. The sound speed of the same tissue is regarded as a whole, which reduces the number of sound speed parameter solutions. Based on the simplified sound speed field model, the proposed method can adaptively adjust the step length of the sound speeds of various tissues by weight allocation. In this way, the updated amplitude of sound speeds of various tissues can be balanced and the accuracy of the sound speed field can be improved. A digital breast model is applied to verify the effectiveness of the proposed method. The results demonstrate that the method can build an appropriate speed field without additional information or equipment and improve the imaging performance of PAI.

In lactic acid bacteria, the global transcriptional regulator CcpA regulates carbon metabolism by repressing and activating the central carbon metabolism pathway, thus decreasing or increasing the yield of certain metabolites to maximize carbon flow. However, there are no reports on the deregulation of the inhibitory effects of CcpA on the metabolism of secondary metabolites. In this study, we identified a single-base mutant strain of Lactococcus lactis N8-2 that is capable of metabolizing 2,3-butanediol. It has been established that CcpA dissociates from the catabolite responsive element (cre) site due to a mutation, leading to the activation of derepression and expression of the 2,3-butanediol dehydrogenase gene cluster (butB and butA). Transcriptome analysis and quantitative polymerase chain reaction (Q-PCR) results showed significant upregulation of transcription of butB and butA compared to the unmutated strain. Furthermore, micro-scale thermophoresis experiments confirmed that CcpA did not bind to the mutated cre. Furthermore, in a bacterial two-plasmid fluorescent hybridization system, it was similarly confirmed that the dissociation of CcpA from cre eliminated the repressive effect of CcpA on downstream genes. Finally, we investigated the differing catalytic capacities of the 2,3-butanediol dehydrogenase gene cluster in L. lactis N8-1 and L. lactis N8-2 for 2,3-butanediol. This led to increased expression of butB and butA, which were deregulated by CcpA repression. This is the first report on the elimination of the deterrent effect of CcpA in lactic acid bacteria, which changes the direction of enzymatic catalysis and alters the direction of carbon metabolism. This provides new perspectives and strategies for metabolizing 2,3-butanediol using bacteria in synthetic biology.

Tumor vaccines have been considered a promising therapeutic approach for treating cancer in recent years. With the development of sequencing technologies, tumor vaccines based on neoantigens or genomes specifically expressed in tumor cells, mainly in the form of peptides, nucleic acids, and dendritic cells, are beginning to receive widespread attention. Therefore, in this review, we have introduced different forms of neoantigen vaccines and discussed the development of these vaccines in treating cancer. Furthermore, neoantigen vaccines are influenced by factors such as antigen stability, weak immunogenicity, and biosafety in addition to sequencing technology. Hence, the biological nanomaterials, polymeric nanomaterials, inorganic nanomaterials, etc., used as vaccine carriers are principally summarized here, which may contribute to the design of neoantigen vaccines for improved stability and better efficacy.

The process of forming metal components through selective laser melting (SLM) results in inherent spherical effects, powder adhesion, and step effects, which collectively lead to surface roughness in stainless steel, limiting its potential for high-end applications. This study utilizes a laser-electrochemical hybrid process to polish SLM-formed 316L stainless steel (SS) and examines the influence of process parameters such as laser power and scanning speed on surface roughness and micro-morphology. A comparative analysis of the surface roughness, microstructure, and wear resistance of SLM-formed 316L SS polished using laser, electrochemical, and laser-electrochemical hybrid processes is presented. The findings demonstrate that, compared to laser and electrochemical polishing alone, the laser-electrochemical hybrid polishing exhibits the most significant improvement in surface roughness and the highest material wear resistance. Additionally, the hybrid process results in a surface free of cracks and only a small number of tiny corrosion holes, making it more suitable for polishing the surface of 316L SS parts manufactured via SLM.

The fertility rate and litter size of female pigs are critically affected by the expression of estrus. The objective of this study was to elucidate the regulatory mechanisms of estrus expression by analyzing the differential expression of genes and long intergenic non-coding RNAs (lincRNA), as well as the utilization of alternative polyadenylation (APA) sites, in the vulva and vagina during the estrus and diestrus stages of Large White and indigenous Chinese Mi gilts. Our study revealed that the number of differentially expressed genes (DEG) in the vulva was less than that in the vagina, and the DEGs in the vulva were enriched in pathways such as “neural” pathways and steroid hormone responses, including the “Calcium signaling pathway” and “Oxytocin signaling pathway”. The DEGs in the vagina were enriched in the “Metabolic pathways” and “VEGF signaling pathway”. Furthermore, 27 and 21 differentially expressed lincRNAs (DEL), whose target genes were enriched in the “Endocrine resistance” pathway, were identified in the vulva and vagina, respectively. Additionally, we observed that 63 and 618 transcripts of the 3′-untranslated region (3′-UTR) were lengthened during estrus in the vulva and vagina, respectively. Interestingly, the genes undergoing APA events in the vulva exhibited species-specific enrichment in neural or steroid-related pathways, whereas those in the vagina were enriched in apoptosis or autophagy-related pathways. Further bioinformatic analysis of these lengthened 3′-UTRs revealed the presence of multiple miRNAs binding sites and cytoplasmic polyadenylation element (CPE) regulatory aspects. In particular, we identified more than 10 CPEs in the validated lengthened 3′-UTRs of the NFIX, PCNX4, CEP162 and ABHD2 genes using RT-qPCR. These findings demonstrated the involvement of APA and lincRNAs in the regulation of estrus expression in female pigs, providing new insights into the molecular mechanisms underlying estrus expression in pigs.

The rusting of metals brings huge losses to the industry every year, and post-treatment of rusted metals to restore their properties to the initial state is a hot topic of current research. In particular, 20 steel, which is widely used in various structural components such as ships, is prone to oxidation in atmospheric environment. Therefore, in this study, a nanosecond pulsed laser was used to remove the rust layer on the surface of 20 steel. The effects of different energy densities and spot overlap rates on the roughness, surface morphology, chemical composition, microhardness and corrosion resistance of the rust layer were analyzed. The results showed that the best cleaning effect was achieved at an energy density of 4.26 J/cm2 and a spot overlap rate of 75%. Under these conditions, the rust layer was completely removed without damage to the substrate, and it even improved the corrosion resistance of 20 steel. At energy densities of 1.42 J/cm2 and 2.84 J/cm2, the rust layer was not completely removed, while at 5.68 J/cm2, the rust layer was removed but the substrate was damaged. In addition, the mechanism of rust removal and substrate damage is discussed.

The MYB transcription factor gene family is among the most extensive superfamilies of transcription factors in plants and is involved in various essential functions, such as plant growth, defense, and pigment formation. Salvia nemorosa is a perennial herb belonging to the Lamiaceae family, and S. nemorosa has various colors and high ornamental value. However, there is little known about its genome-wide MYB gene family and response to flower color formation. In this study, 142 SnMYB genes (MYB genes of S. nemorosa) were totally identified, and phylogenetic relationships, conserved motifs, gene structures, and expression profiles during flower development stages were analyzed. A phylogenetic analysis indicated that MYB proteins in S. nemorosa could be categorized into 24 subgroups, as supported by the conserved motif compositions and gene structures. Furthermore, according to their similarity with AtMYB genes associated with the control of anthocyanin production, ten SnMYB genes related to anthocyanin biosynthesis were speculated and chosen for further qRT-PCR analyses. The results indicated that five SnMYB genes (SnMYB75, SnMYB90, SnMYB6, SnMYB82, and SnMYB12) were expressed significantly differently in flower development stages. In conclusion, our study establishes the groundwork for understanding the anthocyanin biosynthesis of the SnMYB gene family and has the potential to enhance the breeding of S. nemorosa.

Photoacoustic tomography (PAT) is an emerging imaging technique with great potential for a wide range of biomedical imaging applications. The transducers impulse response (TIR) is a key factor affecting the performance of photoacoustic imaging (PAI). It is customary in PAI to assume that TIR is known or obtain it from experiments. In this paper, we investigate the possibility of obtaining TIR in another way. A new method is proposed to extract TIR from observed optoacoustic signal (OPAS) data, without prior knowledge, as a known condition. It is based on the relation between the OPAS data and the photoacoustic pressure signal (PAPS) at transducer positions. The relation can be expressed as a homogeneous linear equation. The TIR is solved by solving the homogeneous equation. The numerical test verifies the effectiveness of the presented method. This article also discusses the effect of calculation parameters on the extracting precision of TIR.

The five northwestern provinces face numerous challenges in sustainable development, particularly water scarcity, economic imbalances, and ecological degradation. This study aims to deeply assess the region’s water resource conditions, the current status of economic development, and the health of the ecosystem while exploring the relationships and coupling mechanisms among them. Using the obstacle model, the research analyzes the primary barriers affecting these three significant factors in the region. The study further reveals a continually improving trend of coordinated development within the water–economic–ecological system in the five northwestern provinces of China, indicating that water usage per ten thousand GDP is the primary obstacle. This research enriches our understanding of the development in China’s five northwestern provinces and provides a theoretical foundation for achieving sustainable development.

In pig production, pigs often show more aggressive behavior after mixing, which adversely affects animal welfare and growth performance. The Jumonji and structural domain-rich AT interaction domain 2 (JARID2) gene plays an important role in neurodevelopment in mice and various psychiatric disorders in humans. The JARID2 gene may impact the aggressive behavior of pigs. By observing the behavior of 500 weaned pigs during the first 72 h after mixing, the ear tissue samples of the 12 most aggressive and 12 least aggressive pigs were selected for DNA resequencing based on the intensity of their aggressive behavior. Large group correlation analysis indicated that the rs3262221458 site located in the 3′-UTR region of the porcine JARID2 gene has a strong relationship with the aggressive behavior of weaned pigs. Pigs with the mutant TT genotype of rs3262221458 have more aggressive behavior than those pigs with the GG and GT genotypes. The dual luciferase assay indicated that the luciferase activity of the plasmids containing the G allele of rs326221458 was significantly less than that of plasmids containing the T allele of rs326221458 and control groups. The binding ability of miR-9828-3p to sequences containing the T allele was less than that of sequences containing the G allele. The overexpression of miR-9828-3p in porcine neuroglial cells (PNGCs) and PK15 cells significantly decreased the mRNA and protein levels of the JARID2 gene. In addition, miR-9828-3p inhibited the proliferation of PNGCs. After inhibiting miR-9828-3p, the mRNA and protein expression levels of JARID2 increased, and the proliferation of PNGCs showed an opposite trend to the cells that forced the expression of miR-9828-3p. In addition, interference with the JARID2 gene by siRNA can effectively inhibit the proliferation of PNGCs. In summary, we found that the rs326221458 locus regulates the expression of the JARID2 gene by affecting the binding of miR-9828-3p and the JARID2 gene, thereby affecting the aggressive behavior of weaned pigs after mixing.

Waterlogging is a common abiotic stress in global maize production. Maize flowering stage (from tasseling to silking) is more fragile to environmental stresses, and this stage frequently overlapped the plum rain season in the middle and lower reaches of Yangtze river in China and affect the yield and quality of spring-sown maize severely. In the present study, the soil moisture content under control and waterlogging conditions at the flowering stage was controlled by a negative-pressure water supply and controlling pot device in a pot trial in 2014–2015. The grain yield, starch content, and starch structural and functional properties under two soil moisture levels were compared using Suyunuo5 (SYN5) and Yunuo7 (YN7) as materials, which are the control hybrids of National waxy maize hybrid regional trials in Southern China. The results observed that the grain yield was reduced by 29.1% for SYN5 with waterlogging due to the decreased grain weight and numbers, which was significantly higher than that of YN7 (14.7%), indicated that YN7 was more tolerant to waterlogging. The grain starch content in YN7 was decreased by 9.4% when plants suffered waterlogging at the flowering stage, whereas the content in SYN5 was only decreased in 2014 and unaffected in 2015. The size of starch granules and proportion of small-molecule amylopectin with waterlogging at the flowering stage increased in SYN5 and decreased in YN7 in both years. The type of starch crystalline structure was not changed by waterlogging, whereas the relative crystallinity was reduced in SYN5 and increased in YN7. The pasting viscosities were decreased, and the pasting temperature was unaffected by waterlogging in general. The gelatinization enthalpy was unaffected by waterlogging in both hybrids in both years, whereas the retrogradation enthalpy and percentage in both hybrids were reduced by waterlogging in 2014 and unaffected in 2015. Between the two hybrids, YN7 has high pasting viscosities and low retrogradation percentage than SYN5, indicated its advantages on produce starch for more viscous and less retrograde food. In conclusion, waterlogging at the flowering stage reduced the grain yield, restricted starch accumulation, and deteriorated the pasting viscosity of waxy maize. Results provide information for utilization of waxy maize grain in food production.

The spatiotemporal patterns and shifts of net ecosystem productivity (NEP) play a pivotal role in ecological conservation and addressing climate change. For example, by quantifying the NEP information within ecosystems, we can achieve the protection and restoration of natural ecological balance. Monitoring the changes in NEP enables a more profound understanding and prediction of ecosystem alterations caused by global warming, thereby providing a scientific basis for formulating policies aimed at mitigating and adapting to climate change. The accurate prediction of NEP sheds light on the ecosystem’s response to climatic variations and aids in formulating targeted carbon sequestration policies. While traditional ecological process models provide a comprehensive approach to predicting NEP, they often require extensive experimental and empirical data, increasing research costs. In contrast, machine-learning models offer a cost-effective alternative for NEP prediction; however, the delicate balance in algorithm selection and hyperparameter tuning is frequently overlooked. In our quest for the optimal prediction model, we examined a combination of four mainstream machine-learning algorithms with four hyperparameter-optimization techniques. Our analysis identified that the backpropagation neural network combined with Bayesian optimization yielded the best performance, with an R2 of 0.68 and an MSE of 1.43. Additionally, deep-learning models showcased promising potential in NEP prediction. Selecting appropriate algorithms and executing precise hyperparameter-optimization strategies are crucial for enhancing the accuracy of NEP predictions. This approach not only improves model performance but also provides us with new tools for a deeper understanding of and response to ecosystem changes induced by climate change.

The Yellow River Basin holds significance as a vital ecological shield and economic hub within China. Adapting land utilization practices and optimizing landscape patterns are of paramount significance in preserving the ecological equilibrium of the Yellow River Basin while fostering high-quality economic development. In this study, we selected the Yellow River Basin in Henan Province as our research area. We use a land use transition matrix and FRAGSTATS 4.2 software to analyze changes in land use and landscape patterns within the study area from 1990 to 2020. Furthermore, Geographical Detector is employed to explore the impact of different natural and social economic factors that have influenced the progress of the landscape surface pattern in the study area. Finally, to identify the zonal aggregation effects of primary components in connection with landscaping feature indices at the city dimension, we use bivariate local spatial autocorrelation. The results are as follows: (1) In terms of land use change characteristics, the area of cultivated land, grassland, shrubs, and bare land shows a decreasing tendency, the area of construction land and forest land shows an increasing tendency, and the water area fluctuates and changes. Most of the cultivated land is shifted to construction land, followed by forest land, construction land, and cultivated land mainly transferred from grassland. (2) At the level of type in terms of shifting landscape patterns, cultivated land, forest land, water, and construction land have a more complex landscape shape, reduced fragmentation, and better natural connectivity. At the overall level, the overall landscape pattern indices are relatively stable, with more patch types and a more balanced distribution. (3) The findings regarding influencing factors reveal that the primary industry output value, population, secondary industry output value, and temperature are the principal driving forces behind the progress of the landscape surface pattern. The main drivers have changed over time in different regions. As indicated by the findings from bivariate local spatial autocorrelation analysis, at the city scale, the leading cause of landscape fragmentation in Luoyang is the primary industry output value, while in Xinxiang, landscape fragmentation is primarily driven by the secondary industry output value and temperature. In this study, we introduce the bivariate local spatial autocorrelation method to analyze the clustering effects of key influencing factors and landscape patterns at the city scale. This is crucial for the harmonized growth of land use planning and the urban economy in the Yellow River Basin.

The zinc-tin-oxide (ZTO) thin-film transistor (TFT) is one of the most promising candidates for advanced display applications, though its popularity is limited by its performances. In this work, a heterojunction channel strategy was adopted to regulate the electron transport behaviors and the TFT performances by manipulating the concentration and the distribution of oxygen vacancies, and a reasonable physical model was proposed based on experimental and simulation results. It is difficult to mediate the contradiction between mobility and threshold voltage for the single channel. Via a heterojunction channel strategy, desirable TFT performances, with mobility of 12.5 cm2/Vs, threshold voltage of 1.2 V and Ion/Ioff of 3 × 109, are achieved when the oxygen-vacancy-enriched layer gets close to the gate insulator (GI). The enhanced performances can be mainly attributed to the formation of two-dimensional electron gas (2DEG), the insensitive potential barrier and the reasonable distribution of oxygen vacancy. On the contrary, when the oxygen-vacancy-enriched layer stays away from GI, all the main performances degenerate due to the vulnerable potential well. The findings may facilitate the development and application of heterojunction channels for improving the performances of electronic devices.

Several studies have confirmed that the pathophysiological progression of Alzheimer’s disease (AD) is closely related to changes in the intestinal microbiota; thus, modifying the intestinal microbiota has emerged as a new way to treat AD. Effective interventions for gut microbiota include the application of probiotics and other measures such as fecal microbiota transplantation (FMT). However, the application of probiotics ignores that the intestine is a complete microecosystem with competition among microorganisms. FMT also has issues when applied to patient treatment. In a previous study, we found that eight species of bacteria that are isolated with high frequency in the normal intestinal microbiota (i.e., intestinal dominant microbiota) have biological activities consistent with the effects of FMT. In this article, we confirmed that the treatment of intestinal dominant microbiota significantly restored intestinal microbiota abundance and composition to normal levels in APP/PS1 mice; downregulated brain tissue pro-inflammatory cytokines (IL-1β and IL-6) and amyloid precursor protein (APP) and β-site APP cleavage enzyme 1 (BACE1) expression levels; and reduced the area of Aβ plaque deposition in the brain hippocampus. Our study provides a new therapeutic concept for the treatment of AD, adjusting the intestinal microecological balance through dominant intestinal microbiota may be an alternative to FMT.

The interaction between low-molecular-weight organic acids (LMWOAs) and minerals in nature has been widely studied; however, limited research has been conducted on the dissolution mechanism of sillimanite in the presence of different organic acids. In this study, the interaction between the sillimanite sample and LMWOAs (citric acid, oxalic acid, and citric/oxalic mixture) at the same pH was investigated. The dissolution rate of Si and Al was high during the initial reaction time, then slowed down in the presence of LMWOAs. The dissolution data for Si and Al from sillimanite in the LMWOAs fit well with the first-order equation (Ct = a(1 − exp(−kt))) (R2 > 0.991). The dissolution process of sillimanite in the organic acids was controlled by the surface chemical reaction step. The dissolution concentration of Si in aqueous citric acid was higher than that in oxalic acid. In contrast, the dissolution concentration of Al in oxalic acid was more than that in citric acid. The maximum concentrations of Si and Al in the presence of composite organic acids were 1754 μmol/L and 3904 μmol/L. The sillimanite before and after treatment with LMWOAs were studied using X-ray diffraction (XRD) and scan electron microscopy (SEM). These results are explained by the characterization of the sillimanite. Under the single acid solution, the (210) crystal plane with a high areal density of Al in sillimanite was easily dissolved by the oxalic acid, while the (120) in sillimanite with a high areal density of Si was more easily dissolved by citric acid. In the composite organic acids, the Si-O bond and Al-O bond in sillimanite were attacked alternately, leading to the formation of some deeper corrosion pits on the surface of sillimanite. The results are of interest in the dissolution mechanisms of sillimanite in the low-molecular-weight organic acids and the environmentally friendly activation of sillimanite.

Feldspar is a high-abundance mineral in the earth’s crust, and its natural weathering and dissolution processes are an important phenomenon on the earth’s surface. This study focused on the dissolution behavior of silicon (Si) and aluminum (Al) in feldspar minerals (microcline and albite) when exposed to low-molecular-weight organic acids (LMWOAs). Various analytical techniques, including atomic absorption spectrophotometer, X-ray diffraction, scanning electron microscope, and Fourier-transform infrared spectroscopy, were employed to investigate these processes. The results revealed that the concentration of Si and Al released from alkali feldspar increased after treatment with LMWOAs, exhibiting non-stoichiometric dissolution. The Si/Al release ratio from feldspar deviated from the expected value of three. Among the LMWOAs tested, oxalic acid was found to be more effective in dissolving aluminum, while citric acid showed greater efficacy in dissolving silicon. Notably, the composite acid demonstrated the highest capacity for feldspar dissolution, with values of 538 μM (Si) and 287 µM (Al) after treatment for 720 h, respectively. The dissolution data for Si and Al in the organic acid solution was fittingly described by a first-order equation, with high correlation coefficients (R2 ≥ 0.992). The characterization of feldspar powders indicated that the (040) crystal plane of feldspar was particularly susceptible to attack by organic acids. In the presence of these acids, the chemical bonds Si (Al)-O, Si-Si(Al), and O-Si(Al)-O shifted to higher wavenumbers. Additionally, the surface corrosion morphology of feldspar exhibited distinct nanostructures, which became more pronounced with increasing exposure time. It was also observed that the reactivity of feldspar increased over time. These findings provide valuable insights into the natural dissolution process of feldspar and offer a new perspective for the study of this phenomenon.

Copy number variation (CNV) represents a significant reservoir of genetic diversity within the genome and exhibits a strong association with economically valuable traits in livestock. The manifestation of aggressive behavior in pigs has detrimental effects on production efficiency, immune competency, and meat quality. Nevertheless, the impact of CNV on the aggressive behavior of pigs remains elusive. In this investigation, we employed an integrated analysis of genome and transcriptome data to investigate the interplay between CNV, gene expression changes, and indicators of aggressive behavior in weaned pigs. Specifically, a subset of pigs comprising the most aggressive pigs (MAP, n = 12) and the least aggressive pigs (LAP, n = 11) was purposefully selected from a herd of 500 weaned pigs following a mixing procedure based on their composite aggressive score (CAS). Subsequently, we thoroughly analyzed copy number variation regions (CNVRs) across the entire genome using next-generation sequencing techniques, ultimately revealing the presence of 6869 CNVRs. Using genome-wide association study (GWAS) analysis and evaluating variance-stabilizing transformation (VST) values, we successfully identified distinct CNVRs that distinguished the MAP and LAP counterparts. Among the prioritized CNVRs, CNVR-4962 (designated as the top-ranked p-value and VST value, No. 1) was located within the Solute Carrier Organic Anion Transporter Family Member 3A1 (SLCO3A1) gene. The results of our analyses indicated a significantly higher (p < 0.05) copy number of SLCO3A1 in the MAP compared to the LAP. Furthermore, this increased copy number exhibited a positive correlation with the CAS of the pigs (p < 0.05). Furthermore, we integrated genomic data with transcriptomic data from the temporal lobe to facilitate the examination of expression quantitative trait loci (eQTL). Importantly, these observations were consistent with the mRNA expression pattern of SLCO3A1 in the temporal lobe of both MAP and LAP (p < 0.05). Consequently, our findings strongly suggest that CNVs affecting SLCO3A1 may influence gene expression through a dosage effect. These results highlight the potential of SLCO3A1 as a candidate gene associated with aggressive traits in pig breeding programs.

The protein phosphatase 2C (PP2C) constitutes a large gene family that plays crucial roles in regulating stress responses and plant development. A recent study has shown the involvement of an AtPP2C family member in long-distance nitrogen signaling in Arabidopsis. However, it remains unclear whether maize adopts a similar mechanism. In this study, we conducted a genome-wide survey and expression analysis of the PP2C family in maize. We identified 103 ZmPP2C genes distributed across 10 chromosomes, which were further classified into 11 subgroups based on an evolutionary tree. Notably, cis-acting element analysis revealed the presence of abundant hormone and stress-related, as well as nitrogen-related, cis-elements in the promoter regions of ZmPP2Cs. Expression analysis demonstrated the distinct expression patterns of nine genes under two nitrogen treatments. Notably, the expression of ZmPP2C54 and ZmPP2C85 in the roots was found to be regulated by long-distance signals from the shoots. These findings provide valuable insights into understanding the roles of ZmPP2Cs in long-distance nitrogen signaling in maize.

Intelligentization of materials and structures is an important trend. Herein, the stimuli-responsive 4D aerogel is used as a smart substrate for rapid reduction in tetracycline (TC) pollution, in which this smart stimuli-responsive substrate is designated as P4D. Its fourth dimension originates from stimuli-responsive characteristics with time evolution. Meanwhile, the covalent organic frameworks (COFs) composite is constructed by BiPO4 and triazine-based sp2 carbon-conjugated g-C18N3-COF (COF-1), which is another key aspect of COF-1/BiPO4@P4D for rapid photocatalytic degradation regarding TC pollution. This emerging smart structure of COFs@P4D can fix programmable temporary state and recover permanent state under thermal or water stimulus without any complicated equipment. Its performance can be tailored by structure, composition, and function. Compared with traditional powder-form photocatalysts, this stimuli-responsive structure provides attractive advantages, such as high permeable framework, self-adaptivity, flexibly customized functional groups, and fast reduction in TC pollution. The predictable development of COFs@P4D could draw much attention for various promising applications in pollution treatment and sensors.

For this study, a new point cloud alignment method is proposed for extracting corner points and aligning them at the geometric level. It can align point clouds that have low overlap and is more robust to outliers and noise. First, planes are extracted from the raw point cloud, and the corner points are defined as the intersection of three planes. Next, graphs are constructed for subsequent point cloud registration by treating corners as vertices and sharing planes as edges. The graph-matching algorithm is then applied to determine correspondence. Finally, point clouds are registered by aligning the corresponding corner points. The proposed method was investigated by utilizing pertinent metrics on datasets with differing overlap. The results demonstrate that the proposed method can align point clouds that have low overlap, yielding an RMSE of about 0.05 cm for datasets with 90% overlap and about 0.2 cm when there is only about 10% overlap. In this situation, the other methods failed to align point clouds. In terms of time consumption, the proposed method can process a point cloud comprising 104 points in 4 s when there is high overlap. When there is low overlap, it can also process a point cloud comprising 106 points in 10 s. The contributions of this study are the definition and extraction of corner points at the geometric level, followed by the use of these corner points to register point clouds. This approach can be directly used for low-precision applications and, in addition, for coarse registration in high-precision applications.

Soybean in relay intercropping is initially exposed to a shade environment, followed by exposure to full sunlight after the harvesting of primary crops, e.g., maize. Therefore, soybean’s ability to acclimate to this changing light environment determines its growth and yield formation. However, the changes in soybean photosynthesis under such light alternations in relay intercropping are poorly understood. This study compared the photosynthetic acclimation of two soybean varieties with contrasting shade tolerance, i.e., Gongxuan1 (shade-tolerant) and C103 (shade-intolerant). The two soybean genotypes were grown in a greenhouse under full sunlight (HL) and 40% full sunlight (LL) conditions. Subsequently, after the fifth compound leaf expanded, half of the LL plants were transferred to a high-sunlight environment (LL-HL). Morphological traits were measured at 0 and 10 days, while chlorophyll content, gas exchange characteristics and chlorophyll fluorescence were assayed at 0, 2, 4, 7 and 10 days after transfer to an HL environment (LL-HL). Shade-intolerant C103 showed photoinhibition 10 days after transfer, and the net photosynthetic rate (Pn) did not completely recover to that under a high light level. On the day of transfer, the shade-intolerant variety, C103, exhibited a decrease in net photosynthetic rate (Pn), stomatal conductance (Gs) and transpiration rate (E) in the low-light (LL) and low-light-to-high-light (LL-HL) treatments. Additionally, intercellular CO2 concentration (Ci) increased in low light, suggesting that non-stomatal factors were the primary limitations to photosynthesis in C103 following the transfer. In contrast, the shade-tolerant variety, Gongxuan1, displayed a greater increase in Pn 7 days after transfer, with no difference observed between the HL and LL-HL treatments. Ten days after transfer, the shade-tolerant Gongxuan1 exhibited 24.1%, 10.9% and 20.9% higher biomass, leaf area and stem diameter than the intolerant C103. These findings suggest that Gongxuan1 possesses a higher capacity to adapt to variations in light conditions, making it a potential candidate for variety selection in intercropping systems.

Large-scale production of green and pollution-free materials is crucial for deploying sustainable clean energy. Currently, the fabrication of traditional energy materials involves complex technological conditions and high costs, which significantly limits their broad application in the industry. Microorganisms involved in energy production have the advantages of inexpensive production and safe process and can minimize the problem of chemical reagents in environmental pollution. This paper reviews the mechanisms of electron transport, redox, metabolism, structure, and composition of electroactive microorganisms in synthesizing energy materials. It then discusses and summarizes the applications of microbial energy materials in electrocatalytic systems, sensors, and power generation devices. Lastly, the research progress and existing challenges for electroactive microorganisms in the energy and environment sectors described herein provide a theoretical basis for exploring the future application of electroactive microorganisms in energy materials.

Change detection (CD), as a special remote-sensing (RS) segmentation task, faces challenges, including alignment errors and illumination variation, dense small targets, and large background intraclass variance in very high-resolution (VHR) remote-sensing images. Recent methods have avoided the misjudgment caused by illumination variation and alignment errors by increasing the ability of global modeling, but the latter two problems have still not been fully addressed. In this paper, we propose a new CD model called SFCD, which increases the feature extraction capability for small targets by introducing a shifted-window (Swin) transformer. We designed a foreground-aware fusion module to use attention gates to trim low-level feature responses, enabling increased attention to the changed region compared to the background when recovering the changed region, thus reducing background interference. We evaluated our model on two CD datasets, LEVIR-CD and CDD, and obtained F1 scores of 91.78 and 97.87, respectively. The experimental results and visual interpretation show that our model outperforms several previous CD models. In addition, we adjusted the parameters and structure of the standard model to develop a lightweight version that achieves an accuracy beyond most models with only 1.55 M parameters, further validating the effectiveness of our design.

As a natural sweetener, stevioside is extracted from Stevia rebaudiana Bertoni and possesses potent antioxidant activity. However, little information is known about its protective role in maintaining the intestinal epithelial cells health under oxidative stress. The aim of this study was to investigate the protective effects and underlying mechanisms of stevioside on alleviating inflammation, apoptosis, and improving antioxidant capacity in intestinal porcine epithelial cells (IPEC-J2) under oxidative stress by diquat. The results demonstrated that the pretreatment with stevioside (250 μM) for 6 h increased cell viability and proliferation and prevented apoptosis induced by diquat at 1000 μM for 6 h in IPEC-J2 cells, compared with the diquat alone-treated cells. Importantly, stevioside pretreatment significantly reduced ROS and MDA production as well as upregulated T-SOD, CAT, and GSH-Px activity. Moreover, it also decreased cell permeability and improved intestinal barrier functions by significantly upregulating the tight junction protein abundances of claudin-1, occludin, and ZO-1. At the same time, stevioside significantly down-regulated the secretion and gene expression of IL-6, IL-8, and TNF-α and decreased the phosphorylation levels of NF-κB, IκB, and ERK1/2 compared with the diquat alone group. Taken together, this study demonstrated that stevioside alleviated diquat-stimulated cytotoxicity, inflammation, and apoptosis in IPEC-J2 cells, protecting cellular barrier integrity and mitigating oxidative stress by interfering with the NF-κB and MAPK signaling pathways.

Recently, laser polishing, as an effective post-treatment technology for metal parts fabricated by laser powder bed fusion (LPBF), has received much attention. In this paper, LPBF-ed 316L stainless steel samples were polished by three different types of lasers. The effect of laser pulse width on surface morphology and corrosion resistance was investigated. The experimental results show that, compared to the nanosecond (NS) and femtosecond (FS) lasers, the surface material’s sufficient remelting realized by the continuous wave (CW) laser results in a significant improvement in roughness. The surface hardness is increased and the corrosion resistance is the best. The microcracks on the NS laser-polished surface lead to a decrease in the microhardness and corrosion resistance. The FS laser does not significantly improve surface roughness. The ultrafast laser-induced micro-nanostructures increase the contact area of the electrochemical reaction, resulting in a decrease in corrosion resistance.

Currently, aqueous zinc-ion batteries, with large reserves of zinc metal and maturity of production, are a promising alternative to sustainable energy storage. Nevertheless, aqueous solution has poor frost resistance and is prone to side reactions. In addition, zinc dendrites also limit the performance of zinc-ion batteries. Biomass, with complex molecular structure and abundant functional groups, makes it have great application prospects. In this review, the research progress of biomass and its derived materials used in zinc-ion batteries are reviewed. The different regulation strategies and characteristics of biomass used in zinc-ion battery electrodes, electrolyte separators and binders are demonstrated. The regulation mechanism is analyzed. At the end, the development prospect and challenges of biomass in energy materials application are proposed.

In this study, a ground-based washing inerting (GBWI) method was proposed, and the application of GBWI in the field of fire prevention and explosion suppression of unmanned aerial vehicle (UAV) fuel tanks was studied using a volume of fluid (VOF) two-phase flow model at a given typical flight envelope. The variation in oxygen concentration in tank ullage during flight was calculated considering the entrance of ambient air and the escape of dissolved oxygen from the fuel. The results indicate that the oxygen concentration in the ullage increases with increasing initial oxygen concentration in the ullage and the initial fuel load after GBWI. In the climb and cruise stages, the oxygen concentration in the ullage increases slowly, while in the tactical descent stage, the oxygen concentration in the ullage increases rapidly, easily exceeding the limiting oxygen concentration (LOC) of aviation fuel combustion. To expand the application range of GBWI, an optimization scheme of nitrogen filling protection was proposed so that the GBWI could meet the requirements of an inert tank at different fuel loads and initial oxygen concentrations in the ullage. Compared with a traditional on-board inert gas generation system (OBIGGS), the optimized GBWI method could greatly reduce the fuel compensation loss and improve the maneuverability of UAVs at the same time.

Semantic mapping can help robots better understand the environment and is extensively studied in robotics. However, it is a challenge for semantic mapping that calibrates all the obstacles with semantics. We propose integrating two network models to realize the salient semantic segmentation used for mobile robot mapping, which differs from traditional segmentation methods. Firstly, we detected salient objects. The detection result was the grayscale image form, which was recognized and annotated by our trained model. Then, we projected the salient objects’ contour with semantics to the corresponding RGB image, which realized the salient objects’ semantic segmentation. We treated the salient objects instead of all the obstacles as semantic segmentation objects that could reduce the background consideration. The neural network model trained based on the salient object’s shape information was stable for object recognition and easy for model training. We only used the shape feature for training, which could reduce the calculation amount of feature details. Experiments demonstrated that the algorithm could quickly realize the model’s training and provide a semantic landmark in the point cloud map as the relative position reference for robot repositioning when the map needs to be used again and exist in a similar environment.

Parallel hierarchical scheduling of multicore processors in avionics hypervisor is being studied. Parallel hierarchical scheduling utilizes modular reasoning about the temporal behavior of the upper Virtual Machine (VM) by partitioning CPU time. Directed Acyclic Graphs (DAGs) are used for modeling functional dependencies. However, the existing DAG scheduling algorithm wastes resources and is inaccurate. Decreasing the completion time (CT) of DAG and offering a tight and secure boundary makes use of joint-level parallelism and inter-joint dependency, which are two key factors of DAG topology. Firstly, Concurrent Parent and Child Model (CPCM) is researched, which accurately captures the above two factors and can be applied recursively when parsing DAG. Based on CPCM, the paper puts forward a hierarchical scheduling algorithm, which focuses on decreasing the maximum CT of joints. Secondly, the new Response Time Analysis (RTA) algorithm is proposed, which offers a general limit for other execution sequences of Noncritical joints (NC-joints) and a specific limit for a fixed execution sequence. Finally, research results show that the parallel hierarchical scheduling algorithm has higher performance than other algorithms.

This retrospective study aimed to derive the clinical phenotypes of ventilated ICU patients to predict the outcomes on the first day of ventilation. Clinical phenotypes were derived from the eICU Collaborative Research Database (eICU) cohort via cluster analysis and were validated in the Medical Information Mart for Intensive Care (MIMIC-IV) cohort. Four clinical phenotypes were identified and compared in the eICU cohort (n = 15,256). Phenotype A (n = 3112) was associated with respiratory disease, had the lowest 28-day mortality (16%), and had a high extubation success rate (~80%). Phenotype B (n = 3335) was correlated with cardiovascular disease, had the second-highest 28-day mortality (28%), and had the lowest extubation success rate (69%). Phenotype C (n = 3868) was correlated with renal dysfunction, had the highest 28-day mortality (28%), and had the second-lowest extubation success rate (74%). Phenotype D (n = 4941) was associated with neurological and traumatic diseases, had the second-lowest 28-day mortality (22%), and had the highest extubation success rate (>80%). These findings were validated in the validation cohort (n = 10,813). Additionally, these phenotypes responded differently to ventilation strategies in terms of duration of treatment, but had no difference in mortality. The four clinical phenotypes unveiled the heterogeneity of ICU patients and helped to predict the 28-day mortality and the extubation success rate.

A high sintering temperature is required to acquire excellent performance in the production of porcelain but results in high fuel consumption. To prepare the porcelain with outstanding performance at a lower temperature, a self-produced additive containing calcium (CaK) was added into a three-component system of kaolinite–feldspar–quartz. XRD and SEM were used to characterize the samples. The toughening mechanism and Gibbs free energy were investigated. After introducing the CaK, the bending strength of the porcelain fired at 1513 K increased from 56.32 ± 0.65 MPa to 95.31 ± 0.63 MPa, which was 21.83% higher than that of the porcelain without CaK at an optimal firing temperature of 1603 K. The main crystal phase of the sample comprised mullite and quartz in the raw materials at 1453~1603 K. The anorthite was observed at 1453 K and interlocked with needle-shaped mullite at 1513 K in the porcelain after adding CaK, which resulted in the higher bending strength. Quantitative analysis indicated that the amount of anorthite decreased at 1513 K and disappeared at 1543 K; the amount of mullite increased with temperature. The Gibbs free energy of the reaction (CaO•Al2O3•2SiO2 + 2(Al2O3•2SiO2) → 3Al2O3•2SiO2 + CaO + 4SiO2) at high temperature was negative, which suggested that the formation of mullite (3Al2O3•2SiO2) from anorthite (CaO•Al2O3•2SiO2) was possible. These findings implied that the addition of CaK contributed to the appropriate phase composition and microstructure, and the excellent performance of the porcelain at a lower temperature. In addition, the transformation between anorthite and mullite was possible in the special raw material system. The results are of interest in producing anorthite/mullite ceramics at reduced sintering temperatures and the conversion between anorthite and mullite.

River water and sand conditions are important factors affecting river morphology, biogeochemical processes and ecosystems. However, climate change and long-term human activities have changed the water–sediment conditions of rivers. This study combines the ecohydrological indicator range of the variation approach (IHA-RVA) and the genetic planning approach in order to dissect the water–sediment situation and its ecological response relationship in the upper Yangtze River. The synergistic effects of climate change and human activities on sediment–runoff were quantified based on the Budyko hypothesis and the sediment attribution decomposition method. The results showed that the interannual trend in sand transport decreased significantly compared to the runoff at each station in the upper Yangtze River, and that it began to change abruptly in 1985 and 1993, respectively (mean values of 56.8% and 70%, respectively); there were also different degrees of decreases in fish species diversity attributed to the combined effects of reduced rainfall and reservoir construction. The factors driving changes in watershed runoff were dominated by human activities (approximately 60%), while changes in sand transport were mainly driven by the sand production capacity in the watershed, both of which contributed more than 95%. The research process and results contribute to an in-depth understanding of the characteristics and driving mechanisms of river water and sand evolution under changing environments, and provide a scientific basis for watershed water resource management and ecological restoration.