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Check dams have been widely constructed in the Chinese Loess Plateau and has played an important role in controlling soil loss during last 70 years. However, the large-scale and automatic mapping of the check dams and the resulting silted fields are lacking. In this study, we present a novel methodological framework to extract silted fields and to estimate the location of the check dams at a pixel level in the Wuding River catchment by remote sensing and ensemble learning models. The random under-sampling method and 23 features were used to train and validate three ensemble learning models, namely Random Forest, Extreme Gradient Boosting and EasyEnsemble, based on a large number of samples. The established optimal model was then applied to the whole study area to map check dams and silted fields. Our results indicate that the imbalance ratio of the samples has a significant impact on the performance of the models. Validation of the results on the testing set show that the F1-score of silted fields of three models is higher than 0.75 at the pixel level. Finally, we produced a map of silted fields and check dams at 10 m-spatial resolution by the optimal model with an accuracy of ca. 90% at the object level. The proposed framework can be used for the large-scale and high-precision mapping of check dams and silted fields, which is of great significance for the monitoring and management of the dynamics of check dams and the quantitative evaluation of their eco-environmental benefits.

To gain a profound understanding of the current status and future trends in the comprehensive prevention and control of coal spontaneous combustion, this paper comprehensively reviews stages and research progress in the aspects of “monitoring and early warning, prevention technology, and emergency rescue”. The following future research aspects are proposed: utilizing advanced technologies such as comprehensive multivariate statistical analysis, the Internet of Things (IoT), machine learning, and artificial intelligence to enhance the accuracy of coal spontaneous combustion prediction and forecasting. This involves constructing an intelligent, proactive warning, and situational judgment mechanism to achieve intelligent prediction, forecasting, and proactive warning systems. Through the comprehensive application of interdisciplinary research methods, gaining in-depth insights into the spontaneous combustion mechanism, innovative fire-resistant materials, and the development of new microbial technologies, theses make the technology of spontaneous combustion prevention and control of coal present a trend of in-depth research and multiple innovation. Under the framework of an efficient, collaborative, and intelligent rescue mechanism, the emergency rescue for coal spontaneous combustion is advancing towards a more intelligent and information-oriented direction. The goal is to promote the intelligent advancement of the coal spontaneous combustion prevention and control level.

Abstract GDP-l-galactose phosphorylase (GGP) is a key rate-limiting enzyme in plant ascorbic acid synthesis, which plays an important role in plant growth and development as well as stress response. However, the presence of GGP and its function in potato and pepper are not known. In this study, we first identified two GGP genes in each potato and pepper genomes using a genome-wide search approach. We then analyzed their physicochemical properties, conserved domains, protein structures and phylogenetic relationships. Phylogenetic tree analysis revealed that members of the potato and pepper GGP gene families are related to eggplant (Solanum melongena L.), Arabidopsis (Arabidopsis thaliana L.), tobacco (Nicotiana tabacum L.) and tomato (Solanum lycopersicum L.), with tomato being the most closely related. The promoter sequences mainly contain homeopathic elements such as light-responsive, hormone-responsive and stress-responsive, with light-responsive elements being the most abundant. By analyzing the structure of the genes, it was found that there is no transmembrane structure or signal peptide in the GGP gene family of potatoes and peppers, and that all of its members are hydrophilic proteins. The expression profiles of different tissues show that StGGP1 has the highest expression levels in leaves, StGGP2 has the highest expression levels in stamens, and CaGGPs have the highest expression levels in the early stages of fruit development (Dev1). It was found that StGGPs and CaGGPs genes showed different response to phytohormones and abiotic stresses. Abscisic acid (ABA) treatment induced the most significant change in the expression of StGGPs, while the expression of CaGGPs showed the most pronounced change under methyl jasmonate (MeJA) treatment. StGGPs responded mainly to dark treatment, whereas CaGGPs responded mainly to NaCl stress. These results provide an important basis for a detailed study about the functions of GGP homologous genes in potato and pepper in response to abiotic stresses.

Abstract Background Matrix metalloproteinase-7 (MMP-7) is associated with biliary injury. This study aimed to evaluate the relationships of serum MMP-7 with clinical characteristics in choledochal cysts (CDC) children. Methods Between June 2020 and July 2022, we conducted a prospective study of CDCs who underwent one-stage definitive operation at our center. Serum MMP-7 was measured using an enzyme-linked immunosorbent assay. We evaluated the relationships between serum MMP-7 and age, laboratory tests, imaging examinations, liver fibrosis, MMP-7 expression, and perforation. Results A total of 328 CDCs were enrolled in the study, with a median serum MMP-7 of 7.67 ng/mL. Higher serum MMP-7 was correlated with younger age at diagnosis (p

Abstract During cardiac development, mechanotransduction from the in vivo microenvironment modulates cardiomyocyte growth in terms of the number, area, and arrangement heterogeneity. However, the response of cells to different degrees of mechanical stimuli is unclear. Organ-on-a-chip, as a platform for investigating mechanical stress stimuli in cellular mimicry of the in vivo microenvironment, is limited by the lack of ability to accurately quantify externally induced stimuli. However, previous technology lacks the integration of external stimuli and feedback sensors in microfluidic platforms to obtain and apply precise amounts of external stimuli. Here, we designed a cell stretching platform with an in-situ sensor. The in-situ liquid metal sensors can accurately measure the mechanical stimulation caused by the deformation of the vacuum cavity exerted on cells. The platform was applied to human cardiomyocytes (AC16) under cyclic strain (5%, 10%, 15%, 20 and 25%), and we found that cyclic strain promoted cell growth induced the arrangement of cells on the membrane to gradually unify, and stabilized the cells at 15% amplitude, which was even more effective after 3 days of culture. The platform’s precise control and measurement of mechanical forces can be used to establish more accurate in vitro microenvironmental models for disease modeling and therapeutic research.

Abstract Accurate penetration rate prediction enhances rock-breaking efficiency and reduces disc cutter damage in tunnel boring machine (TBM) construction. However, this process faces significant challenges such as the high uncertainty of ground conditions and the complexity of maintaining optimal TBM operation in long and large tunnels. To address these challenges, we propose TCN-SENet++, a novel hybrid multistep real-time penetration rate prediction model that combines a temporal convolutional network (TCN) and a squeeze-and-excitation (SENet) block for aided tunneling. This study aims to demonstrate the application of TCN-SENet++, as well as other models such as RNN, LSTM, GRU, and TCN, for TBM penetration rate prediction. The model was developed using actual datasets collected from the Yin-Song diversion project. We employ a 30-s time step to predict the future time steps of the penetration rate (1st, 3rd, 5th, 7th, and 9th). The features that influence the penetration rate, such as the cutterhead torque, thrust, and cutterhead power, were considered. A comparative analysis using the mean absolute error and mean squared error revealed that the TCN-SENet++ model outperformed the other models, including RNN, LSTM, GRU, TCN, and TCN-SENet+. In comparison, TCN-SENet++ achieved average MSE reductions of 18%, 6%, 3%, 1%, and 2%, respectively. The TCN-SENet++ model demonstrated fewer errors in the new project, validating its effectiveness and suitability for real-time penetration rate prediction in TBM construction.

Abstract Background Body weight and its changes have been associated with cancer outcomes. However, the associations of short‐term peridiagnosis weight dynamics in standardized, clinically operational time frames with cancer survival remain largely unknown. This study aimed to screen for and evaluate the optimal indicator of short‐term peridiagnosis weight dynamics to predict overall survival (OS) in patients with cancer. Methods This multicentre cohort study prospectively collected data from 7460 patients pathologically diagnosed with cancer between 2013 and 2019. Body weight data were recorded 1 month before, at the time of and 1 month following diagnosis. By permuting different types (point value in kg, point height‐adjusted value in kg/m2, absolute change in kg or relative change in percentage) and time frames (prediagnosis, postdiagnosis or peridiagnosis), we generated 12 different weight‐related indicators and compared their prognostic performance using Harrell's C‐index, integrated discrimination improvement, continuous net reclassification improvement and time‐dependent C‐index. We analysed associations of peridiagnosis relative weight change (RWC) with OS using restricted cubic spine (RCS), Kaplan–Meier analysis and multivariable‐adjusted Cox regression models. Results The study enrolled 5012 males and 2448 females, with a median age of 59 years. During a median follow‐up of 37 months, 1026 deaths occurred. Peridiagnosis (1 month before diagnosis to 1 month following diagnosis) RWC showed higher prognostic performance (Harrell's C‐index = 0.601, 95% confidence interval [CI] = [0.583, 0.619]) than other types of indicators including body mass index (BMI), absolute weight change, absolute BMI change, prediagnosis RWC and postdiagnosis RWC in the study population (all P 10%, hazard ratio [HR] = 0.530, 95% CI = [0.413, 0.680]) and moderate (gain 5–10%, HR = 0.588, 95% CI = [0.422, 0.819]) weight gain groups were both associated with improved OS. In contrast, the moderate (loss 5–10%, HR = 1.219, 95% CI = [1.029, 1.443]) and significant (loss >10%, HR = 1.280, 95% CI = [1.095, 1.497]) weight loss groups were both associated with poorer OS. Conclusions The prognostic performance of peridiagnosis RWC is superior to other weight‐related indicators in patients with cancer. The findings underscore the importance of expanding the surveillance of body weight from at diagnosis to both past and future, and conducting it within clinically operational time frames, in order to identify and intervene with patients who are at risk of weight change‐related premature deaths.

Abstract Developing physical methods to modulate biomolecular clusters and condensates on cell membranes is of great importance for understanding physiological and pathological processes as well as for stimulating novel therapeutic strategies. Here, we propose an effective means to control receptor condensation on the cell membrane via specific adhesion to a supported lipid bilayer (SLB) with nanoscale topography. The specific adhesion is mediated by receptors in the cell membrane that bind their ligands anchored in the SLB. Using Monte Carlo simulations and mean-field theory, we demonstrate that the nanoscale topography of the SLB can enhance condensation of the receptors associated with lipid nanodomains. Our results indicate that SLBs with nanoscale topography proves an effective physical stimulus for tuning condensation of membrane adhesion proteins and lipids in cell membranes, and can serve as a feasible option to control and direct cellular activities, e.g., stem cell differentiation for biomedical and therapeutic applications.

Abstract Squamous promoter binding protein-like (SPL) genes encode plant-specific transcription factors (TFs) that play essential roles in modulating plant growth, development, and stress response. Pea (Pisum sativum L.) is a coarse grain crop of great importance in food production, biodiversity conservation and molecular genetic research, providing genetic information and nutritional resources for improving agricultural production and promoting human health. However, only limited researches on the structure and functions of SPL genes exist in pea (PsSPLs). In this study, we identified 22 PsSPLs and conducted a genome-wide analysis of their physical characteristics, chromosome distribution, gene structure, phylogenetic evolution and gene expression patterns. As a result, the PsSPLs were unevenly distributed on the seven chromosomes of pea and harbored the SBP domain, which is composed of approximately 76 amino acid residues. The phylogenetic analysis revealed that the PsSPLs clustered into eight subfamilies and showed high homology with SPL genes in soybean. Further analysis showed the presence of segmental duplications in the PsSPLs. The expression patterns of 22 PsSPLs at different tissues, developmental stages and under various stimulus conditions were evaluated by qRT-PCR method. It was found that the expression patterns of PsSPLs from the same subfamily were similar in different tissues, the transcripts of most PsSPLs reached the maximum peak value at 14 days after anthesis in the pod. Abiotic stresses can cause significantly up-regulated PsSPL19 expression with spatiotemporal specificity, in addition, four plant hormones can cause the up-regulated expression of most PsSPLs including PsSPL19 in a time-dependent manner. Therefore, PsSPL19 could be a key candidate gene for signal transduction during pea growth and development, pod formation, abiotic stress and plant hormone response. Our findings should provide insights for the elucidating of development regulation mechanism and breeding for resistance to abiotic stress pea.

Abstract Background Antibiotic-associated diarrhea (AAD) refers to symptoms of diarrhea that cannot be explained by other causes after the use of antibiotics. AAD is thought to be caused by a disruption of intestinal ecology due to antibiotics. Fecal Microbiota Transplantation (FMT) is a treatment method that involves transferring microbial communities from the feces of healthy individuals into the patient’s gut. Method We selected 23 AAD patients who received FMT treatment in our department. Before FMT, we documented patients’ bowel movement frequency, abdominal symptoms, routine blood tests, and inflammatory markers, and collected fecal samples for 16S rRNA sequencing to observe changes in the intestinal microbiota. Patients’ treatment outcomes were followed up 1 month and 3 months after FMT. Results Out of the 23 AAD patients, 19 showed a clinical response to FMT with alleviation of abdominal symptoms. Among them, 82.61% (19/23) experienced relief from diarrhea, 65% (13/20) from abdominal pain, 77.78% (14/18) from abdominal distension, and 57.14% (4/7) from bloody stools within 1 month after FMT. Inflammatory markers IL-8 and CRP significantly decreased after FMT, but there were no noticeable changes in WBC, IL-6, and TNF-α before and after transplantation. After FMT, the abundance of Bacteroides and Faecalibacterium increased in patients’ fecal samples, while the abundance of Escherichia-Shigella and Veillonella decreased. Conclusion FMT has a certain therapeutic effect on AAD, and can alleviate abdominal symptoms and change the intestinal microbiota of patients.

Abstract The decline in the total fertility rate (TFR) is a key driver of population change and has important implications for population health and social development. However, China’s TFR has been a considerable controversy due to a lack of high-quality data. Therefore, this study used the 2020 national population census of China (NPCC) data and reverse survival method to reassess temporal trends in the TFRs and to reexamine rural–urban differences and regional variations in TFRs from 2000 to 2020 in China. Overall, there were significant gaps between the estimated and reported TFRs before 2020, and the estimated TFRs based on the 2020 NPCC data remained higher than the reported TFRs from government statistics. Although TFRs rebounded shortly in the years after the two-child policy, they have shown a wavelike decline since 2010. Additionally, the estimated TFRs fluctuated below 1.5 children per woman in urban areas compared to above 1.8 in rural areas, but the rural–urban differences continued to decrease. Regarding geographic regional variations, the estimated TFRs in all regions displayed a declining trend during 2010–2020, especially in rural areas. Large decreases of over 25% in TFRs occurred in the north, east, central, and northwest regions. In addition to changing the birth policy, the government and society should adopt comprehensive strategies, including reducing the costs of marriage, childbearing, and child education, as well as promoting work-family balance, to encourage and increase fertility levels.

Abstract The colloidal borescope, using colloidal particle motion, is used to monitor the flow velocities and directions of groundwater. It integrates advanced techniques such as microscopy, high-speed photography, and big data computing and enjoys high sensitivity at the micron level. However, In the same well, the groundwater flow velocity monitored by colloidal hole mirror is varies greatly from that obtained by conventional hydrogeological monitoring, such as pumping test. In order to solve this problem, the stability catcher and stratified packer are designed to control the interference of the vertical flow in drilling, and to monitor the flow velocity and direction of groundwater velocity at the target aquifer and target fracture. Five wells with different aquifers and different groundwater types were selected for monitoring in south-central China. The instantaneous velocity and direction are converted into east–west component and north–south component, the average velocity and direction is calculated according to the time of 10 min, and the particle trajectory diagram is established. Based on these results, it proposed a concept of cumulative flow velocity. Using curve-fitting equations, the limits of cumulative flow velocities as the monitoring time tends to infinity were then calculated as the actual flow velocities of the groundwater. The permeability coefficient of aquifer is calculated by using the fissure ratio of aquifer, hydraulic slope and flow velocity, and compared with the permeability coefficient obtained by pumping test. The results are as follows: (1) The variation coefficient of the instantaneous flow velocity measured at the same depth in the same well at different times is greater than that of the time average flow velocity and greater than that of the cumulative flow velocity. The variation coefficient of the actual velocity is the smallest, indicating that the risk of using the actual flow velocity is lower. (2) The variation coefficient of the flow rate monitored at different depths in the same well is mainly controlled by the properties of the aquifer. The more uniform water storage space in the aquifer, the smaller the variation coefficient. (3) The comparison between the permeability coefficient obtained by monitoring and the permeability coefficient obtained by pumping test shows that the flow of structural fissure water controlled by planar fissure is more surface flow, and the results are consistent. When the groundwater flow is controlled by pores and solution gaps, the flow channel is complicated, which is easy to produce turbulent flow, and the result consistency is poor. (4) According to different research accuracy requirements, different monitoring and calculation methods can be selected for different aquifers and groundwater types. Researches show that, the permeability coefficient calculated for the actual flow velocity in well DR01 is the same as that calculated for the pumping test. The aquifer characteristics reflected by the coefficient of variation of the actual flow velocity in the same aquifer are more realistic. The pumping test method obtains the comprehensive parameters of a certain aquifer, and this method can be used to monitor a certain fissure. In this paper, the new technology developed for monitoring, and the new algorithm established for data processing, can accurately obtain the flow velocity and direction of groundwater, using capsule hole mirror monitoring method. The key parameters of hydrogeology can be obtained by using one well, which can reduce the time and cost input and improve the work efficiency.

IntroductionCurrently, although there have been a few reports on the endocrine-disrupting effects of neonicotinoids, the effect on Chironomidae during long-term exposure remains unknown.MethodsEcdysis and sex ratio, along with ecdysone-relevant gene expressions of representative neonicotinoid dinotefuran on Chironomus kiinensis were investigated at different environmental concentrations by long-term exposure.ResultsA low dose of dinotefuran delayed pupation and emergence via inhibiting ecdysis. Sex ratios of adults shifted toward male-dominated populations with the concentration of dinotefuran increasing. The corresponding transcriptions of ecdysis genes ecr, usp, E74, and hsp70 were significantly downregulated in the midge. For estrogen effects, the vtg gene expression was upregulated, but there was no significant change for the err gene.DiscussionThese results would improve our understanding of the endocrine-disrupting mechanisms of neonicotinoid insecticides to Chironomidae and provide data support for assessing their potential environmental risks.

BackgroundMany patients with constipation also suffer from varying degrees of malnutrition, and the relationship between the two conditions is a vicious cycle. Surgery is the final step in the treatment of constipation, with a success rate of up to 95%. This study aims to investigate the effects of surgical treatment on the nutritional status of patients with chronic constipation and malnutrition.MethodsA total of 60 patients with chronic constipation and various degrees of malnutrition who underwent surgery in our department from January 2020 to March 2023 were included in this study. Biochemical tests including BMI, albumin, total protein, hemoglobin, cholesterol and lymphocyte count were conducted, as well as measurements of inflammatory markers such as Interleukin-6 (IL-6), Interleukin-8 (IL-8), and C-reactive protein (CRP). Additionally, multiple nutritional risk screening scales (NRS2002, MUST, NRI, and MNA) and the prognostic nutritional index (PNI) were used to assess the nutritional status of patients before surgery, as well as at 1 month, 3 months, and 6 months post-surgery. Finally, we analyzed the factors influencing postoperative recovery outcomes in patients.ResultsCompared to pre-operation, the BMI of patients significantly increased at 1 month, 3 months, and 6 months after the operation, with statistically significant differences (p

We developed a partial least squares regression (PLSR) model based on competitive adaptive reweighted sampling (CARS) to predict the processing factors of 54 pesticides during soybean oil processing. Characteristic variables were selected to improve the performance of the model. Four calculators were used to compute the molecular descriptors used in the model, and the model based on values computed with ChemoPy produced the best results: Rc ​= ​0.94, RMSEc ​= ​0.67, Rp ​= ​0.91, and RMSEp ​= ​0.54 for hot-pressed oil and Rc ​= ​0.93, RMSEc ​= ​0.73, Rp ​= ​0.93, and RMSEp ​= ​0.59 for cold-pressed oil. A rapid and quantitative model of processing factors was established to predict the behaviour and distribution of pesticide residues during food processing. The model was further validated using data from field-grown soybeans; it demonstrated a high correlation coefficient between predicted and measured residue concentrations (Rp ​> ​0.93, RMSEp ​

Resilient counties has the capability to navigate adverse environmental changes, adaptively reallocate resources during challenges, and bolster county competitiveness. This study introduces an original framework for nurturing resilient counties based on geographical natures, emphasizing the role of geographic space evolution, termed county space resilience (CSR). This study focuses on 95 counties in Jiangsu, a prominent province in the rapidly urbanizing region of eastern China, as a case study. Employing a multi-dimensional feature model and LISA spatiotemporal transition analysis, this study analyzes the static-dynamic characteristics of CSR and proposes a regional guidance scheme. This study draws three key conclusions. Firstly, it reveals that the average CSR value decreased from 0.327 in 2000 to 0.320 in 2005, then increased to 0.380 in 2021, and the geographic trend of transitioning from more economically developed zones to less developed ones. Secondly, the general structural characteristics of CSR were classified into four groups: upgrade transformation, focus optimization, potential enhancement, and safety adjustment. Furthermore, the spatial–temporal coalescence of the Moran’s I scatterplot equals 0.684, signifying stability in the spatial correlation of CSR. Additionally, the dynamic evolution characteristics of CSR were categorized into positive and negative types, with the Yangtze River Green Development Belt acting as the boundary. Lastly, this study constructs a management scheme comprising zoning control and classification strategy tailored for different counties, offering strategic recommendations customized for each. This scheme can serve as a decision-making foundation for policymakers in county development endeavors, fostering the cultivation of resilient counties.

IntroductionCreating an ecological space network is essential for safeguarding the core structure of ecological space.MethodsMorphological spatial pattern analysis was used to locate ecological sources in the Kuye River Basin. Using the least cumulative resistance model and gravity model, the resistance surface, ecological corridor, and ecological space management network are determined.Results and discussionThe study revealed that in 2022, the predominant land use types in the Kuye River Basin were wood land and grassland, cultivated land, and construction land. MSPA model software identifies a substantial portion of the landscape pattern as consisting of core and marginal areas, which encompass 30324.05 hm2 and 15088.24 hm2. High ecological resistance surface factors dominate the socioeconomically vibrant zone and northern regions. Resistance values ranging from 0.02 to 0.87, and high and law resistance zones alternate. The minimal cumulative resistance approach found 171 ecological corridors. And gravity model using the interaction matrix of 19 primary ecological sources discovered 8 first-level ecological corridors with the highest interaction force. There are 137 core and 23 subsidiary ecological corridors with significant affects. Overlying the road factors and ecological corridors of national highways, provincial roads, railways, and high-speed roads creates a total of 38 ecological breakpoints, each characterized by specific barrier effects and legal ecological stability.

Abstract Artificial micro/nanomotors using active particles hold vast potential in applications such as drug delivery and microfabrication. However, upgrading them to micro/nanorobots capable of performing precise tasks with sophisticated functions remains challenging. Bubble microthruster (BMT) is introduced, a variation of the bubble‐driven microrobot, which focuses the energy from a collapsing microbubble to create an inertial impact on nearby target microparticles. Utilizing ultra‐high‐speed imaging, the microparticle mass and density is determined with sub‐nanogram resolution based on the relaxation time characterizing the microparticle's transient response. Master curves of the BMT method are shown to be dependent on the viscosity of the solution. The BMT, controlled by a gamepad with magnetic‐field guidance, precisely manipulates target microparticles, including bioparticles. Validation involves measuring the polystyrene microparticle mass and hollow glass microsphere density, and assessing the mouse embryo mass densities. The BMT technique presents a promising chip‐free, real‐time, highly maneuverable strategy that integrates bubble microrobot‐based manipulation with precise bioparticle mass and density detection, which can facilitate microscale bioparticle characterizations such as embryo growth monitoring.

In this study, the pathogenic genes of depression were calculated and analyzed by bioinformatics method, and then the key genes of Shaoyao Gancao Decoction in the treatment of depression were deduced and predicted through the correlation study with the target of Shaoyao Gancao Decoction. Through the production of LPS depression model mice, drug treatment, behavioral test and hippocampal tissue sample detection, it was found that Shaoyao Gancao Decoction can regulate the levels of IL-10, TNF- α, BDNF, SMAD3, FGFR1 and FGFR2 to improve depression, which can provide a theoretical basis for exploring the efficacy of Shaoyao Gancao Decoction in the treatment of depression.

Objective In July 2022(Beijing time), the glacier survey group and mountaineering group of the China University of Geosciences (Wuhan) performed the "Second University Students' Scientific Expedition to the Yangtze River" in the Geladandong Snow Mountain area. Methods To analyse the spatial and temporal characteristics of glaciers in this region, scientific research data were combined with optical remote sensing image interpretation, InSAR deformation information extraction, LiDAR altimetry measurements, and high-precision geodetic survey data to conduct multisource remote sensing image fusion processing research. Aerial triangulation encryption, frequency domain image matching, the waveband ratio method, and visual interpretation were used to extract DOM, DSM, glacier area and number distribution information from high-resolution satellite GF1, GF6, GF7, ZY3, and Landsat 7 remote sensing images of Geladandong Snow Mountain and typical glaciers.Sentinel-1A and ICESat-2 images were used, supported by the cross-correlation offset tracking method in the SAR image space domain, to extract glacier surface velocity and elevation changes, respectively. The 3D spatial coordinates and elevation outliers of all the control points were calculated for the BDS CORS station in Qinghai Province using the Gamit/Globk double difference ionospheric combination model, real-time extended (RTX), and real-time kinematic (RTK) techniques. Results The results revealed 512 glaciers in the Geladandong Snow Mountain area, with an average annual growth rate of 3.12%, an area of 1 111.96 km2, and an average annual retreat rate of 0.63%.The average daily maximum velocity of the Jianggen (gu) Diru glacier is 0.25 cm/d, and the average annual maximum velocity is 91.25 cm/a. The maximum retreat value, accumulation value and annual change rate of Jianggen (gu) Diru glacier on the south side and north side are -74.63 m, 38.44 m, -5.29 m/a to 3.09 m/a, -39.17 m, 35.74 m, -3.02 m/a to 2.85 m/a, respectively. The precision of the regional quasigeoid refinement model and the errors at all control sites both attained mm levels. Conclusion The aforementioned findings can provide data support for subsequent research on glaciers in this region.

Abstract This is the first report on the screening, expression, and recognition mechanism analysis of single-chain fragment variable (scFv) against phenylethanolamine A (PEAA), a newly emerged β-adrenergic agonist illegally used as a feed additive for growth promotion. The PEAA-specific scFv scFv, called scFv-32, was screened from hybridoma cell lines by phage display and was found to be optimally expressed in the E. coli system. The ic-ELISA results revealed an IC50 value of 10.34 μg/L for scFv-32 and no cross-reactivity with other β-adrenergic agonists. Homology modeling and molecular docking revealed the key binding sites VAL178, TYP228, and ASP229. One hydrogen bond, two pi-sigma bonds, and one pi-pi bond maintain the formation of the antibody‒drug complex. Alanine scanning mutagenesis of the three predicted key binding sites showed that the mutants completely lost their recognition activity, which confirmed the accuracy of the theoretical analysis. These results are valuable for the preparation of scFvs and the analysis of the molecular recognition mechanism of antigen-antibodies. Graphical abstract

Abstract Alternative polyadenylation can occur in introns, termed intronic polyadenylation (IPA), has been implicated in diverse biological processes and diseases, as it can produce noncoding transcripts or transcripts with truncated coding regions. However, a reliable method is required to accurately characterize IPA. Here, we propose a computational method called InPACT, which allows for the precise characterization of IPA from conventional RNA-seq data. InPACT successfully identifies numerous previously unannotated IPA transcripts in human cells, many of which are translated, as evidenced by ribosome profiling data. We have demonstrated that InPACT outperforms other methods in terms of IPA identification and quantification. Moreover, InPACT applied to monocyte activation reveals temporally coordinated IPA events. Further application on single-cell RNA-seq data of human fetal bone marrow reveals the expression of several IPA isoforms in a context-specific manner. Therefore, InPACT represents a powerful tool for the accurate characterization of IPA from RNA-seq data.

Rock thermal physical properties play a crucial role in understanding deep thermal conditions, modeling the thermal structure of the lithosphere, and discovering the evolutionary history of sedimentary basins. Recent advancements in geothermal exploration, particularly the identification of high-temperature geothermal resources in Datong Basin, Shanxi, China, have opened new possibilities. This study aims to characterize the thermal properties of rocks and explore factors influencing thermal conductivity in basins hosting high-temperature geothermal resources. A total of 70 groups of rock samples were collected from outcrops in and around Datong Basin, Shanxi Province. Thermal property tests were carried out to analyze the rock properties, and the influencing factors of thermal conductivity were studied through experiments at different temperature and water-filled states. The results indicate that the thermal conductivity of rocks in Datong, Shanxi Province, typically ranges from 0.690 W/(m·K) to 6.460 W/(m·K), the thermal diffusion coefficient ranges from 0.441 mm2/s to 2.023 mm2/s, and the specific heat capacity of the rocks ranges from 0.569 KJ/(kg·°C) to 1.117 KJ/(kg·°C). Experimental results reveal the impact of temperature and water saturation on the thermal conductivity of the rock. The thermal conductivity decreases with increasing temperature and rises with high water saturation. A temperature correction formula for the thermal conductivity of different lithologies in the area is proposed through linear fitting. The findings from this study provide essential parameters for the assessment and prediction, development, and utilization of geothermal resources in the region and other basins with typical high-temperature geothermal resource.

Abstract Background Numerous previous studies have reported an association between type 2 diabetes mellitus (T2DM) and lung cancer risk, but the underlying mechanism of the interaction remains unclear. This study aimed to investigate the shared genetic features and immune infiltration processes between lung cancer and T2DM. Methods Epidemiological data from the National Health and Nutrition Examination Survey (NHANES) 2000–2018 was used to explore the relationship between lung cancer and diabetes systematically. In addition, we also used bioinformatics methods to analyze the transcriptome data from the Gene Expression Omnibus (GEO) to explore the potential functional mechanisms from the perspective of genes and immune infiltration. Results Logistic regression analysis showed that prediabetes (OR = 3.289,95%CI 1.231, 8.788, p = 0.01760, model 3)and type 2 diabetes (OR = 3.032 95%CI,1.015, 9.054, p = 0.04689) were significantly associated with an increased risk of lung cancer after adjusting for multiple covariates. Data from NHANES showed an inverted U-shaped relationship between fasting blood glucose and glycosylated haemoglobin and the risk of lung cancer (P for non-linear

Abstract MALTA2 is the latest full-scale prototype of the MALTA family of Depleted Monolithic Active Pixel Sensors (DMAPS) produced in Tower Semiconductor 180 nm CMOS sensor imaging technology. In order to comply with the requirements of high energy physics (HEP) experiments, various process modifications and front-end changes have been implemented to achieve low power consumption, reduce random telegraph signal (RTS) noise, and optimise the charge collection geometry. Compared to its predecessors, MALTA2 targets the use of a high-resistivity, thick Czochralski (Cz) substrates in order to demonstrate radiation hardness in terms of detection efficiency and timing resolution up to 3 $$\times $$ × 10 $$^{15}$$ 15 1 MeV $$\mathrm {n_{eq}/{cm}^2}$$ n eq / cm 2 with backside metallisation to achieve good propagation of the bias voltage. This manuscript shows the results that were obtained with non-irradiated and irradiated MALTA2 samples on Cz substrates from the CERN SPS test beam campaign from 2021 to 2023 using the MALTA telescope.

Abstract Wet-tissue adhesives have long been attractive materials for realizing complicated biomedical functions. However, the hydration film on wet tissues can generate a boundary, forming hydrogen bonds with the adhesives that weaken adhesive strength. Introducing black phosphorus (BP) is believed to enhance the water absorption capacity of tape-type adhesives and effectively eliminate hydration layers between the tissue and adhesive. This study reports a composite patch integrated with BP nanosheets (CPB) for wet-tissue adhesion. The patch’s improved water absorption and mechanical properties ensure its immediate and robust adhesion to wet tissues. Various bioapplications of CPB are demonstrated, such as rapid hemostasis (within ~1-2 seconds), monitoring of physical-activity and prevention of tumour-recurrence, all validated via in vivo studies. Given the good practicability, histocompatibility and biodegradability of CPB, the proposed patches hold significant promise for a wide range of biomedical applications.

Predicting cutterhead torque is essential for optimizing TBM construction strategies and minimizing jamming risks. This study presents a novel hybrid model (IEWOA-TSVD-ITELM), developed using data from 7635 tunneling cycles from the Yinsong Project, to enhance cutterhead torque prediction accuracy. The EWOA enhances its global search capability by introducing new position updating and adaptive adjustment strategies (IEWOA). In addition, by leveraging the Softsign function for the nonlinear transformation of the expected output matrix of the TELM, a third hidden layer is added to enhance the feature extraction capabilities (ITELM), whereas truncated singular value decomposition (TSVD) is employed to reduce the noise in the output matrix of the third hidden layer of the ITELM (TSVD-ITELM). Furthermore, the IEWOA optimized the number of neurons and randomly generated weights and biases in the TSVD-ITELM. This study comprehensively evaluates and compares six optimization algorithms using 25 standard test functions. Additionally, the IEWOA-TSVD-ITELM is compared with eight classical machine learning models. This study examines the impact of different timing lengths of the rising phase and rock mass grades on model performance. The results demonstrate the outstanding performance of the IEWOA as an optimization algorithm. The IEWOA-TSVD-ITELM model achieves an R2 value of 0.644 on the test set, with an MAE of 326.623 and an RMSE of 435.821, outperforming the other algorithms. Increasing the timing length from 30 to 60 s reduces the MAE and RMSE by 11.82% and 9.56%, respectively, but the gains diminish when the timing length increases from 60 to 90 s.

Large Language Models (LLMs) excel in interactive chat scenarios due to their advanced conversational abilities. However, their training process invariably exposes them to a diverse range of harmful or toxic content, posing significant challenges in ensuring that LLM responses align with human ethical values. Consequently, the detection and quantification of adverse content remains a paramount issue in contemporary research. In this paper, we introduce the SAFE dataset, a novel resource designed to advance safety assessment research in LLMs. Our dataset extends beyond the binary categorization of content into “safe” and “unsafe”. Drawing upon human interpretations of safety, we further delineate unsafe content into six granular categories: Sensitivity, Harmfulness, Falsehood, Information Corruption, Unnaturalness, and Deviation from Instructions. This refined classification aims to enhance LLMs’ ability to discern unsafe data more accurately. In total, we have created a dataset comprising 52,340 instruction-response pairs, each annotated with safety meta-tags. Additionally, we have compiled expert comparative assessments for these indicators. We developed a multi-expert rating model trained on the SAFE dataset, designed to evaluate the responses of LLMs across various dimensions. This approach highlights the potential of our dataset in the realm of safety assessment for LLMs. The model’s capability to provide multi-faceted evaluations reflects an advanced understanding of the nuanced requirements in LLM response assessment. We believe this dataset represents a valuable resource for the community, contributing to the safe development and deployment of LLMs. Our findings and resources are poised to fuel future research endeavors in this domain.

Accurate delineation of paddy fields holds importance in ensuring food security, efficient water resource management, and precise evaluation of greenhouse gas emissions. Here we propose an innovative approach, the asynchronous flooding and object-based (AF-OB) model, aimed at optimizing phenology-based paddy field mapping. The AF-OB model capitalizes on the asynchronous flooding phenomenon observed between paddy fields and nonpaddy fields, along with the seasonal variations in the normalized difference vegetation index. The simple noniterative clustering algorithm is integrated to mitigate the common issue of the “pretzel effect” encountered in paddy field mapping. Evaluation through independent samples yields compelling results, with the paddy field map generated by the AF-OB method achieving an overall accuracy of 94.28%. The paddy fields extracted using the AF-OB method exhibit alignment with statistical data, surpassing comparable algorithms relying on alternative land use products in terms of visual quality. Furthermore, the AF-OB model exhibits stability across time, space, and sensors, thus enhancing its applicability and robustness. The outputs of the AF-OB method offer reference data for informed agricultural production planning and the effective management of water resources.

ABSTRACTInverting grassland above-ground biomass (AGB) presents a significant challenge due to difficulties in characterizing leaf physiological states and obtaining accurate ground-truth data. This study introduces an innovative hybrid model for AGB inversion based on the AGB = leaf mass per area (LMA) * leaf area index (LAI) paradigmn in the Ewenki Banner region of Inner Mongolia. The model integrates the PROSAIL radiative transfer model, machine learning regression, LEnKF data assimilation theory, multisource remote sensing, and meteorological data, following a four-step approach. Firstly, we establish LAI and LMA inversion models by combining the PROSAIL model with machine learning techniques. Secondly, data assimilation fuses the PROSAIL-derived LAI with MODIS-LAI. In the third phase, a Random Forest predictive model is developed for LMA estimation. Lastly, the accuracy of the hybrid model is assessed using empirical data. Precision evaluation with ground-truth samples demonstrates that the assimilated LAI and RF-predicted LMA yield the lowest prediction error for grassland AGB (RMSE = 0.0033 g/cm2; MAE = 0.0028 g/cm2). This model framework addresses the challenge of limited prior knowledge in the PROSAIL-AGB prediction model, thereby enhancing the prediction accuracy while maintaining its key advantages: providing continuous observations at high spatiotemporal resolutions without relying on measured sample data.

ABSTRACT: This study was performed to investigate the effects of potassium diformate (KDF) on growth performance, apparent digestibility of nutrients, serum biochemical indices, and intestinal microflora of Cherry Valley ducks. In total, 144 female healthy 1-day-old Cherry Valley ducks were divided into 3 groups with 6 replicates per group and 8 ducks per replicate according to the principle of similar body weight. The control group was fed a basic diet. In the 2 experimental groups, 0.8% and 1.2% KDF was added to the basic diet, respectively. The trial period was 6 wk and the pretrial period was 3 wk. The final weight and ADG were significantly higher in the 0.8% KDF group than in the control group (P < 0.05). The feed-to-gain ratio was significantly lower in both KDF groups than in the control group (P < 0.05). The apparent digestibility of CP was significantly higher in both KDF groups than in the control group (P < 0.05). The apparent digestibility of calcium was also significantly higher in the 0.8% KDF group (P < 0.05). The serum levels of alkaline phosphatase, cholesterol, and total protein were significantly lower in the 0.8% KDF group than in the control group (P < 0.05), the IgM content was significantly higher (P < 0.05), the low-density lipoprotein cholesterol, triglyceride, and urea levels were significantly lower (P < 0.01), and the glucose level was significantly higher (P < 0.01). The serum total protein level was significantly higher in the 1.2% KDF group than in the control group (P < 0.05). The relative abundance of Firmicutes and Patescibacteria in the gut of ducks was significantly higher in the 0.8% KDF group than in the control group (P < 0.05), the relative abundance of unclassified Erysipelotrichaceae and Lactobacillus was significantly higher (P < 0.01), and the relative abundance of Fusobacteriota was significantly lower (P < 0.05). However, the relative abundance of Firmicutes in the gut of ducks was significantly higher in the 1.2% KDF group than in the control group (P < 0.05). The relative abundance of unclassified Erysipelotrichaceae and Clostridium sensu stricto 1 was significantly higher (P < 0.01), as was the relative abundance of Fusobacteriota and Proteobacteria (P < 0.05). These findings indicate that the addition of 0.8% KDF to the diet can improve the growth performance of Cherry Valley ducks, promote the absorption of nutrients, change the structure of the microflora in the cecum, and increase the relative abundance of dominant bacteria. It was also shown that there was a significant difference between the 0.8% and 1.2% KDF levels which suggest that the safety margin for overdosing is quite low.

Plasma membranes not only serve as physical barriers to separate the cell or organelle from extracellular or intracellular environments, but also play important roles in many cellular processes, e.g., cell adhesion, cell migration, endocytosis as well as membrane budding, whose correct executions rely on locally highly curved membrane shaping. Mechanically, these membranes are soft fluid interfaces exhibiting extremely dynamic remodeling processes in response to mechanobiological stimulus from their surrounding complex intra/extra-membranous circumstances containing thermal fluctuations, protein binding, protein-protein interaction on the membrane surface forming protein superstructures and active cytoskeletal networks. Correlating these dynamic membrane shaping involving characteristic membrane mechanical properties with cellular functions is essential to improving fundamental understandings in cell physiology and cell biomechanics. The challenge here is to explicitly describe the dynamics of membrane remodeling under the complex biological situations. Interestingly, the developed mesoscopic Monte Carlo (MC) method has the capacity to concurrently capture the elasticity and fluidity of fluid membranes well on large time and length scales, as well as to successfully reproduce fluctuating membrane morphology as observed in experiments. In this review, we focus on this mesoscopic MC method used to depict the thermodynamics of fluctuating fluid membranes and further explore how diverse biophysical factors drive large membrane curvature generation. We also discuss the current efforts of the roles of membrane morphology on the regulation of biological processes on the basis of this mesoscopic MC method, provide the insights into the known biomechanical mechanisms of effect of membrane shape on cellular functions, and point out the potential opportunities where this mesoscopic dynamic MC method can be modified to investigate more intricate biological processes, such as membrane fusion and adhesion.

Mounting evidence suggests that intraplaque angiogenesis is associated with the progression of atherosclerotic plaques and the development of intraplaque hemorrhage. The specificity of intraplaque immune cell infiltration may be associated with abnormalities in the structure and function of the nascent capillaries. Here, we analyzed expression levels of angiogenesis-associated genes in early and advanced carotid atheromatous plaque tissues as well as in stable and intraplaque hemorrhage plaques. Expression profiles of advanced arterial plaques based on angiogenesis-associated genes were classified into subtypes by performing a consensus clustering analysis. The correlation between the immune microenvironment of plaques and expression of angiogenesis-associated genes was also explored using the single sample gene set enrichment analysis method and the CIBERSORT algorithm. We identified hub angiogenesis-associated genes showing similar expression patterns throughout plaque adverse progression, and constructed a prediction model using the random forest algorithm. Receiver operating curves were constructed to evaluate efficacy in identification of intraplaque hemorrhage in a plaque. Our results suggest that heterogeneity of angiogenesis-related genes may promote the malignant development of plaques and cause plaque rupture. In conclusion, we propose a model based on expression of angiogenesis-related genes to predict the risk of plaque rupture.

To comprehensively investigate the molecular transmission patterns of HIV-1 genotypes among men who have sex with men (MSM) in Chongqing, we employed 392 pol sequences of MSM to construct a phylogenetic tree and gene transmission network. Among the viral subtypes, CRF07_BC accounted for 73.2% (287/392) and CRF01_AE accounted for 20.7% (81/392), emerging as the predominant subtypes in this investigation. Additionally, we observed the presence of CRF55_01B, subtype B, CRF08_BC and other circulating recombinant forms. The HIV-1 molecular network was constructed with a gene distance threshold of 1.5%, resulting in an entry rate of 61.4% (241/392). Within the network, we identified a total of 23 molecular clusters, with the largest cluster being the CRF07_BC molecular cluster comprising 148 node values. Transmitted drug-resistance (TDR) mutations were found in 4.34% of the cases, with 1.79% associated with protease inhibitors (PIs), 0.51% with nucleoside reverse transcriptase inhibitors (NRTIs), and 2.55% with non-nucleoside reverse transcriptase inhibitors (NNRTIs). Statistical analysis indicated a higher enrollment rate in the HIV-1 molecular network among infected individuals with the CRF07_BC subtype, those identifying with same-sex sexual roles as “vers,” and individuals with higher education levels. This suggests the need for strengthened investigation and intervention in this population to prevent the formation of larger transmission clusters. Furthermore, continuous monitoring of the HIV-1 molecular dynamics network is necessary to promptly and accurately track changes in molecular epidemic characteristics.

Larix gmelinii is an important ecological construction tree species in northern China, and its carbon storage and distribution characteristics are of great significance for evaluating the carbon balance and climate effect of forest ecosystems. However, at present, there is a lack of systematic research on the carbon storage of L. gmelinii forests and its change with forest age. In this paper, the biomass and carbon density of L. gmelinii forests at different ages and the distribution of carbon storage in vegetation and soil were analyzed by means of sample plot investigation and model simulation in the northern forest area of Daxing’anling, Inner Mongolia. The influence of forest age on the carbon storage and carbon pool distribution characteristics of L. gmelinii forests and the mechanism of influencing factors were also discussed. Results show that: (1) As forest age increased, the total amount of carbon pools initially increased and then decreased, and the distribution structure of carbon pools showed a trend of transferring from soil to trees. The proportion of soil carbon pools gradually decreased (72.72–51.87%), while the proportion of tree carbon pools gradually increased (23.98–39.33%). The proportion of shrub and grass carbon pools was also relatively stable (0.51–0.53%). (2) Soil carbon pool was affected by the input and output of soil organic matter, soil depth, soil carbon content, and soil bulk density, shrub–grass carbon pool was affected by undergrowth light conditions and soil moisture, litter carbon pool was affected by litter input and output, and the carbon pool of trees was affected by the growth rate and carbon balance of trees. This study provides scientific basis and management suggestions for the carbon storage capacity of L. gmelinii forests and the mitigation of climate change.

Abstract Sedentary, inadequate sleep and exercise can affect human health. Artificial intelligence (AI) and Internet of Things (IoT) create the Artificial Intelligence of Things (AIoT), providing the possibility to solve these problems. This paper presents a novel approach to monitor various human behaviors for AIoT‐based health management using triboelectric nanogenerator (TENG) sensors. The insole with solely one TENG sensor, creating a most simplified system that utilizes machine learning (ML) for personalized motion monitoring, encompassing identity recognition and gait classification. A cushion with 12 TENG sensors achieves real‐time identity and sitting posture recognition with accuracy rates of 98.86% and 98.40%, respectively, effectively correcting sedentary behavior. Similarly, a smart pillow, equipped with 15 sensory channels, detects head movements during sleep, identifying 8 sleep patterns with 96.25% accuracy. Ultimately, constructing an AIoT‐based health management system to analyze these data, displaying health status through human‐machine interfaces, offers the potential to help individuals maintain good health.

Background: There is a lack of comprehensive profile assessment on complete blood count (CBC)-derived systemic-inflammatory indices, and their correlations with clinical outcome in patients with anterior circulation acute ischemic stroke (AIS) who achieved successful recanalization by endovascular thrombectomy (EVT). Methods: Patients with anterior circulation AIS caused by large vessel occlusion (AIS-LVO) were retrospectively screened from December 2018 to December 2022. Systemic-inflammatory indices including ratios of neutrophil-to-lymphocyte (NLR), monocyte-to-lymphocyte (MLR), platelet-to-lymphocyte (PLR), and platelet-to-neutrophil (PNR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate inflammation systemic index (AISI) on admission and the first day post-EVT were calculated. Their correlations with symptomatic intracranial hemorrhage (sICH) and unfavorable 90-day functional outcome (modified Rankin Scale score of 3–6) were analyzed. Results: A total of 482 patients [65 (IQR, 56–72) years; 33 % female] were enrolled, of which 231 (47.9 %) had unfavorable 90-day outcome and 50 (10.4 %) developed sICH. Day 1 neutrophil and monocyte counts, NLR, MLR, PLR, SII, SIRI, and AISI were increased, while lymphocyte and PNR were decreased compared to their admission levels. In multivariate analyses, neutrophil count, NLR, SII, and AISI on day 1 were independently associated with 90-day functional outcome. Moreover, day 1 neutrophil count, NLR, MLR, PLR, PNR, SII, and SIRI were independently linked to the occurrence of sICH. No admission variables were identified as independent risk factors for patient outcomes. Conclusion: CBC-derived systemic-inflammatory indices measured on the first day after successful EVT are predictive of 90-day functional outcome and the sICH occurrence in patients with anterior circulation AIS-LVO.

PurposeDuring the second stage surgery for anorectal malformations (ARM), patients whose distal intestine of the colostomy is particularly short underwent laparoscopic-assisted distal colon excision and proximal colon pull-through anorectoplasty (PCPARP). This study aimed to discuss the outcomes of PCPARP after colostomy in patients with ARM.MethodsThis is a single-center propensity score-matched (PSM) study which was retrospectively initiated patients with intermediate- or high-type ARM who underwent laparoscopic surgery from June 2007 to December 2018. These patients were divided into PCPARP group and conventional laparoscopic-assisted anorectoplasty (LAARP) group according to specific surgical methods. The general data, surgical data, postoperative complications, and functional results were evaluated.ResultsIn total, 216 patients were included in this study: 190 (88.0%) undergoing LAARP approach and 26 (12.0%) undergoing PCPARP approach. After PSM, two well-balanced groups of 26 patients were analyzed and showed the postoperative complications (P = 0.126) and bowel function (P = 0.809) were similiar between the two groups.ConclusionsThe curative effect of PCPARP after colostomy is similar to that of classic LAARP surgery, which can be used for ARM patients with a very short and abnormal distal intestine of the stoma.

The tracheal Y-shaped stent is mainly used for the treatment of critical patients with airway stenosis or esophagotracheal fistula near carina. A novel method for precise implantation of Y-shaped tracheal stents was developed using double-lumen endotracheal intubation and flexible bronchoscopy. This approach aims to address the limitations associated with X-ray or rigid bronchoscopy guidance, such as operational difficulties and the risk of inaccurate stent placement leading to implantation failure or suffocation. With this new technique, 13 tracheal Y-shaped stents were successfully implanted. This method shows promise in reducing the complexity of stent implantation and facilitating timely treatment for patients in need. Additionally, it has the potential to update current operating standards and guidelines for this procedure.

A water-saving cooling tower was proposed in the power plant to save water resources. In this paper, the multiphase flow model and the species transport model in FLUENT software are used to simulate the condensation process of wet air, and the performance of the water-saving device is studied. Comparing the experimental results with the simulation results, the relative error of the cooling tower outlet temperature is 0.15%, and the relative error of the cooling tower outlet humidity is 4.65%. We use the mixture model in the multiphase flow model and the species transport model to consider the wet air as a mixture of air and water vapor and ignore the effect of the liquid film on heat transfer. This modeling approach enables the study of humidity variations in wet air condensation and is suited for studying cooling tower water-saving devices. The study results show that an optimum channel length gives the device the best water-saving performance, with a relative channel length of 0.6. In addition, decreasing the cold air inlet temperature by 12 K reduces the cooling tower outlet humidity by 1 g/kg, while increasing the cold air inlet velocity by 6 m/s leads to a reduction in the cooling tower outlet humidity by 1 g/kg.

Abstract Background Impaired pattern separation occurs in the early stage of Alzheimer’s disease (AD), and hippocampal dentate gyrus (DG) neurogenesis participates in pattern separation. Here, we investigated whether spatial memory discrimination impairment can be improved by promoting the hippocampal DG granule cell neogenesis-mediated pattern separation in the early stage of AD by electroacupuncture (EA). Methods Five familial AD mutations (5 × FAD) mice received EA treatment at Baihui and Shenting points for 4 weeks. During EA, mice were intraperitoneally injected with BrdU (50 mg/kg) twice a day. rAAV containing Wnt5a shRNA was injected into the bilateral DG region, and the viral efficiency was evaluated by detecting Wnt5a mRNA levels. Cognitive behavior tests were conducted to assess the impact of EA treatment on cognitive function. The hippocampal DG area Aβ deposition level was detected by immunohistochemistry after the intervention; The number of BrdU+/CaR+ cells and the gene expression level of calretinin (CaR) and prospero homeobox 1(Prox1) in the DG area of the hippocampus was detected to assess neurogenesis by immunofluorescence and western blotting after the intervention; The gene expression levels of FZD2, Wnt5a, DVL2, p-DVL2, CaMKII, and p-CaMKII in the Wnt signaling pathway were detected by Western blotting after the intervention. Results Cognitive behavioral tests showed that 5 × FAD mice had impaired pattern separation (P

Abstract It is difficult to distinguish other pathologies mimicking Ménière’s disease (MD) clinically. This study aims to investigate the differences of imaging findings and features between MD and other menieriform diseases via intravenous gadolinium-enhanced magnetic resonance imaging (MRI). 426 patients with menieriform symptoms, including MD, vestibular migraine (VM), and vestibular schwannoma (VS), underwent 3D-FLAIR and 3D-T2WI MRI 6 h after the intravenous gadolinium injection. MR images were analyzed for inner ear morphology, perilymphatic enhancement (PE), EH and other abnormalities. EH was observed at a higher rate in MD patients (85.71%) than patients with other menieriform diseases (VM group = 14.75%, VS group = 37.50%). The prevalence of unilateral EH as well as both cochlear and vestibular EH showed significant differences between MD and VM groups. The prevalence of cochlear EH (I and II) and vestibular EH (II and III) was different between MD and VM groups. The prevalence of PE was higher in MD than VM group. The degrees of cochlear and vestibular hydrops were higher in the definite than probable MD group (P

An experimental study is conducted on several retro-reflective beamforming schemes for wireless power transmission to multiple wireless power receivers (referred to herein as “targets”). The experimental results demonstrate that, when multiple targets broadcast continuous-wave pilot signals at respective frequencies, a retro-reflective wireless power transmitter is capable of generating multiple wireless power beams aiming at the respective targets as long as the multiple pilot signals are explicitly separated from one another by the wireless power transmitter. However, various practical complications are identified when the pilot signals of multiple targets are not appropriately differentiated from each other by the wireless power transmitter. Specifically, when multiple pilot signals are considered to be carried by the same frequency, the wireless power transmission performance becomes heavily dependent on the interaction among the pilot signals, which is highly undesirable in practice. In conclusion, it is essential for a retro-reflective wireless power transmitter to explicitly discriminate multiple targets’ pilot signals among each other.

Cancer remains a significant global health challenge with limited treatment options beyond systemic therapies, such as chemotherapy, radiotherapy, and molecular targeted therapy. Immunotherapy has emerged as a promising therapeutic modality but the efficacy has plateaued, which therefore provides limited benefits to patients with cancer. Identification of more effective approaches to improve patient outcomes and extend survival are urgently needed. Drug repurposing has emerged as an attractive strategy for drug development and has recently garnered considerable interest. This review comprehensively analyses the efficacy of various repurposed drugs, such as transforming growth factor-beta (TGF-β) inhibitors, metformin, receptor activator of nuclear factor-κB ligand (RANKL) inhibitors, granulocyte macrophage colony-stimulating factor (GM-CSF), thymosin α1 (Tα1), aspirin, and bisphosphonate, in tumorigenesis with a specific focus on their impact on tumor immunology and immunotherapy. Additionally, we present a concise overview of the current preclinical and clinical studies investigating the potential therapeutic synergies achieved by combining these agents with immune checkpoint inhibitors.

Abstract In this paper, a cloud-edge-end collaboration-based control architecture is established for frequency regulation in interconnected power systems (IPS). A model predictive control (MPC)-based load frequency control strategy for the IPS with photovoltaic aggregation and energy storage systems under model uncertainty and communication delay is proposed. This can effectively overcome the issues of model uncertainty, random load perturbation and communication delay. First, a state space model for the IPS is constructed. To coordinate the frequency and contact line power fluctuation of the IPS, a robust controller based on the theory of MPC is then designed. Then, considering the communication delay of frequency response commands during transmission, a predictive compensation mechanism is introduced to eliminate the effect of delay while considering model uncertainty. Finally, simulation results verify the effectiveness and robustness of the proposed control strategy.

Using Antarctic krill (Euphausia superba) as the research object, we optimized the process conditions for Antarctic krill sauce (AkS) by including three factors (salt addition, rock sugar addition, and the oil-to-material ratio) and sensory evaluation as response values. The data from the response surface were fed into the back propagation (BP) neural network training, generating a model mapping the process conditions and sensory scores, which were subsequently combined with the genetic algorithm (GA) for global optimization to determine the optimal process for AkS preparation. The results revealed that the response surface model was well suited to the BP neural network training and prediction sets, with correlation values of 0.98 and 0.95, respectively. The fitting prediction effect was obvious for the sensory scoring results of the product. The parameters obtained from the GA’s global optimization search accord with the analytical results of the response surface. The findings demonstrated that combining a BP neural network with a GA can enhance the AkS preparation technique. Under optimal processing conditions, AkS has a high sensory score and protein and carbohydrate contents, moderate fat content, minimal fat oxidation, and non-detectable pathogens, indicating that the AkS in this study was nutritious and safe to consume.

A long-span double-deck steel truss suspension bridge is easy to produce vortex-induced vibration (VIV) at low air velocity, which affects bridge service life. Additional aerodynamic measures play a role in suppressing VIV by changing the aerodynamic shape, which is a common control method. As the main aerodynamic measure to suppress the VIV response, wind fairing is widely used in engineering practice. In order to obtain the optimal additional position and shape parameters of the fairing, Huangjuetuo Yangtze River Bridge is the research target. Through the combination of a wind tunnel test and numerical simulation, the VIV response of the original and fairing section is studied. Based on data analysis, it is revealed that these additional fairings to the upper chord can significantly reduce the VIV response. When the shape parameters of the fairing are h/D = 1/4 and l/D = 1, the VIV inhibition efficiency is the highest, which can reach 65.51%. By analyzing the flow distribution, it can be seen that VIV is caused mainly by vortex separation in the upper bridge board area. Although this wind fairing does not change the original vortex shedding forms, it changes the first separation point and movement direction of the airflow, making the vortex scale generated by the airflow smaller and the vorticity lower, thus effectively suppressing VIV.