Search

Abstract An SHS-CFSHS X-joint is fabricated by welding two square hollow section (SHS) braces to a concrete-filled square hollow section (CFSHS) chord. In this paper, the stress concentration factors (SCFs) of SHS-CFSHS X-joints are investigated through experimental tests and finite element analysis (FEA), with the hot spot stress method serving as the analytical approach. Eight specimens are designed and manufactured, with FE models built in software ANSYS. These FE models are validated against the test results. The specimens are tested under brace axial tension to determine the SCFs of the X-joints. It shows that the concrete filled in the chord effectively reduces the SCFs of the X-joints. To further explore various load conditions and the influence of the parameters, FEA is carried out and a total of 64 FE models are built. Based on the FEA results, multiple regression analysis is used to obtain the SCF formulae of SHS-CFSHS X-joints under axial tension load and in-plane bending load in the brace, respectively. Comparison and analysis of the SCF results obtained from experimental tests, the proposed formulae, and FE simulations reveal that the formulae presented in this study are both conservative and suitable for predicting SCFs.

Abstract Glioma, particularly glioblastomas (GBM), is incurable brain tumor. The most targeted receptor tyrosine kinase (RTKs) drugs did not bring benefit to GBM patients. The mechanism of glioma growth continues to be explored to find more effective treatment. Here, we reported that Ser/Thr protein kinase YANK2 (yet another kinase 2) is upregulated in glioma tissues and promotes the growth and proliferation of glioma in vitro and in vivo. Further, we confirmed that oncogene Fyn directly activated YANK2 through phosphorylation its Y110, and Fyn-mediated YANK2 phosphorylation at Y110 site promotes glioma growth by increasing its stability. Finally, YANK2 was proved to be a novel upstream kinase of p70S6K and promotes glioma growth by directly phosphorylating p70S6K at T389. Taken together, we found a new mTOR-independent p70S6K activation pathway, Fyn-YANK2-p70S6K, which promotes glioma growth, and YANK2 is a potential oncogene and serves as a novel therapeutic target for glioma.

Abstract Environmental changes and ground subsidence along railway lines are serious concerns during high-speed railway operations. It is worth noting that AutoRegressive Integrated Moving Average (ARMA), Long Short-Term Memory (LSTM), and other prediction methods may present limitations when applied to predict InSAR time series results. To address this issue, this study proposes a prediction method that decomposes the nonlinear settlement time series of feature points obtained through InSAR technology using Ensemble Empirical Mode Decomposition (EEMD). Subsequently, multiple Intrinsic Mode Functions (IMFs) are generated, and each IMF is individually predicted using the Prophet forecasting model. Finally, we employ an equal-weight superimposition method to combine the results, resulting in the prediction of the InSAR settlement time series. The predicted values of each component are subsequently weighted equally and combined to derive the final prediction outcome. This paper selects InSAR monitoring data along a high-speed railway in inland China and uses the proposed method and ARMA and Prophet models to carry out comparative experiments. The experimental results show that compared with the ARMA and Prophet models, the method in this paper improves the root mean square error by 58.01% and 32.3%, and increases the mean absolute error by 62.69% and 33.78%, respectively. The predicted settlement values generated by our method exhibit better agreement with the actual InSAR monitoring values.

Abstract Greenhouse gas (GHG) emissions from rivers and lakes have been shown to significantly contribute to global carbon and nitrogen cycling. In spatiotemporal-variable and human-impacted rivers in the grassland region, simultaneous carbon dioxide, methane and nitrous oxide emissions and their relationships under the different land use types are poorly documented. This research estimated greenhouse gas (CO2, CH4, N2O) emissions in the Xilin River of Inner Mongolia of China using direct measurements from 18 field campaigns under seven land use type (such as swamp, sand land, grassland, pond, reservoir, lake, waste water) conducted in 2018. The results showed that CO2 emissions were higher in June and August, mainly affected by pH and DO. Emissions of CH4 and N2O were higher in October, which were influenced by TN and TP. According to global warming potential, CO2 emissions accounted for 63.35% of the three GHG emissions, and CH4 and N2O emissions accounted for 35.98% and 0.66% in the Xilin river, respectively. Under the influence of different degrees of human-impact, the amount of CO2 emissions in the sand land type was very high, however, CH4 emissions and N2O emissions were very high in the artificial pond and the wastewater, respectively. For natural river, the greenhouse gas emissions from the reservoir and sand land were both low. The Xilin river was observed to be a source of carbon dioxide and methane, and the lake was a sink for nitrous oxide.

Colorectal cancer (CRC) development involves a series of molecular events that drive the progression from normal colorectal epithelium to adenoma and eventually to invasive carcinoma. While the involvement of extrachromosomal circular DNAs (ecDNAs) in cancer genome remodeling has been established, their specific roles in CRC formation remain unclear. Using Circle-Sequencing and whole transcriptomic sequencing, we comprehensively profile circular DNAs and transcriptomes in healthy individuals, colorectal adenoma, and CRC patients. Our delineate analyses characterize the key circular DNAs involved in oncogene expression through the normal-adenoma-carcinoma continuum and highlight that immune response-related pathways and cell cycle pathways, are the dominat events in CRC progression. Notably, chr8 ecDNA 64950741-114379093 exhibits robust up-regulation during CRC progression. Further validation in a new cohort of 50 CRC patients confirms the higher expression of chr8 ecDNA 64950741-114379093 and its strong correlation with poor prognosis. Thus, these findings provide unprecedented insights into the landscape of circular DNAs in CRC and highlights the potential of chr8 ecDNA 64950741-114379093 as a promising biomarker and therapeutic target for CRC management., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

This study aimed to explore the impact of Brassica rapa L. polysaccharides (BRP) on the growth, immune response, antioxidant capacity, and cecal microbiota in yellow-feathered quails. A total of 250 one-day-old yellow-feathered quails, evenly divided by sex, were randomly assigned to five groups, with each group comprising ten replicates of five quails each. The control group (CON) received a basic diet, while the antibiotic control group (CTC) was fed a basic diet supplemented with chlortetracycline (0.05 g/kg). BRP was administered at concentrations of 0.25 g/kg (Low dose BRP, LBRP), 0.5 g/kg (Medium dose BRP, MBRP), and 1 g/kg (High dose BRP, HBRP). The duration of the experiment was 42 days. The results indicated that, compared to the CON group, the final body weight of quails in the MBRP group significantly increased (P < 0.05), and there was a significant difference in body weight between the LBRP group and the CTC group (P < 0.05). At 21 days of age, the average weights of the thymus and bursa of Fabricius in the MBRP group were significantly greater than those in the CON group (P < 0.05), with no significant difference observed when compared to the CTC group (P > 0.05); at 42 days of age, the average weight of the thymus in the MBRP group was significantly greater than that in the CON group (P < 0.05), with no significant difference observed compared to the CTC group (P > 0.05). At 21 days of age, the levels of IgA and IgG in the MBRP group were significantly elevated compared to the CON group (P < 0.05), with no significant difference noted compared to the CTC group (P > 0.05). Additionally, the MBRP group showed significant increases in CAT, T-SOD, and GSH-Px levels (P < 0.05) compared to the CON group; the levels of IL-1β and TNF-α were significantly reduced (P < 0.05), and the level of IL-10 was significantly elevated (P < 0.05) compared to the CON group. Furthermore, 16 S rRNA sequencing revealed that BRP supplementation increased the populations of beneficial cecal bacteria such as Lactococcus, Weissella, Parabacteroides, and norank&#95;f&#95;Ruminococcaceae, and decreased the population of the harmful bacterium Campylobacter, indicating that BRP modulates the microbial community structure in the cecum of yellow-feathered quails. In summary, BRP enhanced the growth performance, serum immunoglobulin levels, antioxidant functions, and improved the intestinal microbiota in yellow-feathered quails., Competing Interests: Declarations Ethical approval The study was approved by the Animal Experimentation Ethics Committee of the School of Animal Science and Technology, Shihezi University. The code of ethical inspection was A2021-14. All Quail were kept experimentally and euthanized per the committee’s guidelines. During the test, all efforts were made to minimize the suffering of the animals. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Brain tumor diagnosis is an important task in prognosing and treatment planning of the patients with brain cancer. in the meantime, using the Magnetic Resonance Imaging (MRI) as a commonly used non-invasive imaging technique provide the experts a helpful view for detecting the brain tumors. While deep learning methods have shown significant success in analyzing medical images, they often require careful design of architecture and tuning of hyperparameters to achieve optimal results. This study presents a new approach for diagnosing brain tumors in MRI scans using deep learning, focusing on Residual/Shuffle Networks. The designed network structures offer efficient results when compared to traditional deep learning models. To enhance the proposed network for brain tumor classification, a modified metaheuristic algorithm named Augmented Falcon Finch Optimization (AFFO) is introduced. AFFO utilizes bio-inspired principles to effectively search for the best hyperparameter configurations, thereby enhancing the reliability and accuracy of the deep learning model. The performance of the proposed method is evaluated on a standard brain tumor MRI dataset and compared with existing techniques, including ResNet, AlexNet, VGG-16, Inception V3, and U-Net to illustrate the effectiveness of combining Residual/Shuffle Networks with AFFO for brain tumor diagnosis., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

With the population ages, many patients are unable to receive comprehensive care, leading to an increase in hazardous incidents, particularly falls occurring after getting out of bed. To address this issue, this paper proposes a method for recognizing bed-exit intentions using an array air spring mattress. The method integrates convolutional neural networks with feature point matching techniques to identify both global and local features of the array air spring. For global features, a one-dimensional focal loss convolutional neural network (1D-FLCNN) model is employed to classify eight internal pressure time series and determine bed-exit status based on global features. For local features, the distribution matrix and feature point matrix of the internal pressure features are extracted to represent the spatial distribution of bed-exit postures. Euclidean distance is utilized to measure the similarity between these matrices and match bed-exit postures. Finally, the recognition results from both feature types are combined using a logical OR operation to produce the final result. Experimental validation confirms that the proposed method greatly improves the anti-interference capability and effectively avoids the problem of non-recognition due to body position and external environment., (© 2024. The Author(s).)

Radiotherapy has been demonstrated to be one of the most significant treatments for cervical cancer, during which accurate and efficient delineation of target volumes is critical. To alleviate the data demand of deep learning and promote the establishment and promotion of auto-segmentation models in small and medium-sized oncology departments and single centres, we proposed an auto-segmentation algorithm to determine the cervical cancer target volume in small samples based on multi-decoder and semi-supervised learning (MDSSL), and we evaluated the accuracy via an independent test cohort. In this study, we retrospectively collected computed tomography (CT) datasets from 71 pelvic cervical cancer patients, and a 3:4 ratio was used for the training and testing sets. The clinical target volumes (CTVs) of the primary tumour area (CTV1) and pelvic lymph drainage area (CTV2) were delineated. For definitive radiotherapy (dRT), the primary gross target volume (GTVp) was simultaneously delineated. According to the data characteristics for small samples, the MDSSL network structure based on 3D U-Net was established to train the model by combining clinical anatomical information, which was compared with other segmentation methods, including supervised learning (SL) and transfer learning (TL). The dice similarity coefficient (DSC), 95% Hausdorff distance (HD95) and average surface distance (ASD) were used to evaluate the segmentation performance. The ability of the segmentation algorithm to improve the efficiency of online adaptive radiation therapy (ART) was assessed via geometric indicators and a subjective evaluation of radiation oncologists (ROs) in prospective clinical applications. Compared with the SL model and TL model, the proposed MDSSL model displayed the best DSC, HD95 and ASD overall, especially for the GTVp of dRT. We calculated the above geometric indicators in the range of the ground truth (head-foot direction). In the test set, the DSC, HD95 and ASD of the MDSSL model were 0.80/5.85 mm/0.95 mm for CTV1 of post-operative radiotherapy (pRT), 0.84/ 4.88 mm/0.73 mm for CTV2 of pRT, 0.84/6.58 mm/0.89 mm for GTVp of dRT, 0.85/5.36 mm/1.35 mm for CTV1 of dRT, and 0.84/4.09 mm/0.73 mm for CTV2 of dRT, respectively. In a prospective clinical study of online ART, the target volume modification time (MTime) was 3-5 min for dRT and 2-4 min for pRT, and the main duration of CTV1 modification was approximately 2 min. The introduction of the MDSSL method successfully improved the accuracy of auto-segmentation for the cervical cancer target volume in small samples, showed good consistency with RO delineation and satisfied clinical requirements. In this prospective online ART study, the application of the segmentation model was demonstrated to be useful for reducing the target volume delineation time and improving the efficiency of the online ART workflow, which can contribute to the development and promotion of cervical cancer online ART., (© 2024. The Author(s).)

Failure Modes, Effects, and Criticality Analysis (FMECA) is a commonly used method for analyzing system reliability. It is frequently applied in identifying weak points in the reliability of CNC machine tools. However, traditional FMECA has issues such as vague descriptions of risk factors, equal treatment of risk factors, and unclear directions for improving weak points. In response to the issue of vague descriptions of risk factors, this paper further expands severity (S) into machine hazard (M) and personal hazard (P), and subdivides detectability (D) into functional structural complexity (D 1 ) and detection cost (D 2 ). In addressing the issue of treating risk factors equally, this paper integrates Distance Analysis Method (DAM) and Grey Relational Analysis (GRA) to propose Distance-Grey Relational Analysis (D-GRA). Subsequently, based on the D-GRA method, the weights of each risk factor were determined by comprehensively considering expert system scores and actual economic loss indicators. In response to the issue of unclear improvement directions for weak points, this paper introduces the BCC model. It treats common failure modes of CNC machine tools as decision-making units within the BCC model, refines risk factors as input indicators, and evaluates the efficiency values of each decision-making unit based on various actual losses as output indicators. Through efficiency value analysis, it proposes improvement directions for weak points. Then, based on the weights of risk factors and the efficiency values of failure modes, a modified calculation method for the new Risk Priority Number (RPN) is proposed to amend the traditional RPN, This paper takes the electric spindle system of a certain machining center as an example, applies the proposed method to rank common failure modes with the new RPN, and compares it with other RPN calculation methods to verify the rationality of the proposed approach. Finally, it presents improvement directions for reliability enhancement., (© 2024. The Author(s).)

This study proposes and experimentally validates a multifunctional, ultra-wideband polarization conversion metasurface. The design integrates polarization conversion and electromagnetic scattering functions into a single structure, enabling applications in polarization conversion, beam control, and effective reduction of the radar cross-section (RCS). The metasurface achieves linear-to-circular polarization conversion with an axial ratio (AR) of less than 3 dB across dual-band ranges of 14.6-26.8 GHz and 31-33.5 GHz. Additionally, by adjusting metallic resonant rings within the unit structure, cross-polarization conversion with a polarization conversion ratio (PCR) greater than 0.9 is realized in the 13.6-29.8 GHz frequency range, maintaining excellent stability even at oblique incidence angles up to 50°. Leveraging the phase cancellation principle, various coding arrays are designed to precisely control the scattered beams, reducing the RCS by more than 10 dB. The comparison of simulation and experimental results further validates the wide application potential of this polarization converter in fields such as wireless communication, antenna engineering, and radar stealth., (© 2024. The Author(s).)

It is generally believed that Carbapenem-resistant Enterobacterales (CRE) colonization is primarily responsible for systemic infection in humans. However, there is no consensus on whether decolonization should be recommended in clinical practice. In China, the specific situation of CRE colonization and consequent systemic infection in hospitalized patients necessitates further exploration. We conducted a cohort study and analyzed various clinical characteristics of inpatients with intestinal CRE colonization. A risk prediction model for consequent CRE infection was established and externally validated. Our prediction model is freely available online at https://creinfection.shinyapps.io/dynnomapp/ . 839 intestinal CRE colonization samples from inpatients were included. 317 cases of intestinal CRE colonization were enrolled, 25.9% of whom developed systemic infections. The consequent CRE infection rates of Klebsiella pneumoniae and Escherichia coli were 27.0% and 32.3%. The departments at high risk for subsequent CRE infection were respiratory medicine, hematology, and intensive care unit. Secondary infection after intestinal CRE colonization in inpatients can significantly prolong the length of hospital stay (26 days vs. 33 days, P < 0.001), increase the total medical cost (144735.34￥ vs. 281852.34￥, P < 0.001), and has poor (85.11% vs. 52.44%, P < 0.001) efficacy and high mortality (5.96% vs. 18.29%, P = 0.001). Our study makes a significant contribution to comprehensively specify CRE infection, because these results can facilitate early identification of high-risk hospitalized patients, timely implementation to decolonize treatment interventions, ultimately achieve the goal of CRE nosocomial infection prevention and control., (© 2024. The Author(s).)

In this study, the effects on silage performance and microbial community of sorghum straw treated with the addition of enzymes (cellulase (CE), xylanase (XE)) and extrusion puffing technology, combined with SEM, XRD, and FTIR techniques, were thoroughly investigated. The results showed that the enzyme preparations, especially xylanase, significantly improved the nutritional value and fermentation efficiency of straw and enhanced the silage effect. Extruding significantly changes the surface structure of the straw, increasing the surface area and porosity, and promoting the attachment of microorganisms. This study not only optimized the sorghum straw silage performance but also provided technical support for the efficient use of straw resources, which is of great significance for the sustainable development of animal husbandry and the resource utilization of agricultural waste., (© 2024. The Author(s).)

Long non-coding RNAs (lncRNAs), such as SNHG6, have been identified as crucial regulators in the progression of various cancers, including esophageal squamous cell carcinoma (ESCC). Although the role of SNHG6 in ESCC is not completely understood, our findings demonstrated that SNHG6 expression is upregulated in ESCC tissues compared to adjacent normal tissues. Furthermore, elevated levels of SNHG6 are significantly correlated with higher TNM stage and poorer clinical prognosis in ESCC patients. Functionally, both in vivo and in vitro experiments have shown that knocking down SNHG6 inhibits proliferation, invasion, and metastasis. Luciferase reporter assays and Ago2-RIP assay confirm that SNHG6 functions as a competing endogenous RNA (ceRNA) by sponging miR-26b-5p to modulate ITGB1 expression in ESCC. Given that ITGB1 is instrumental in EMT and metastasis, we assessed the expression of EMT-related proteins. The findings suggest that miR-26b-5p and reduced ITGB1 expression can reverse the EMT induced by lncRNA SHNG6, as demonstrated through rescue analysis. Overall, this study aims to elucidate the molecular mechanisms through which SNHG6 promotes EMT and metastasis in ESCC, providing a novel theoretical foundation for understanding ESCC progression and identifying new targets for improving outcomes in metastatic ESCC., (© 2024. The Author(s).)

This study aimed to identify predictive factors for the prognosis of acute-on-chronic liver disease (AoCLD) due to both hepatitis B virus (HBV) and alcohol and to develop prognostic models to improve treatment management. AoCLD patients with HBV and alcohol as etiological factors were selected from two multicenter prospective cohorts (NCT02457637,NCT03641872) and included in separate training and validation cohorts (n = 180 and n = 148). In the training cohort, the CATCH-LIFE A nomogram (based on age, bilirubin, international normalized ratio, serum sodium, and hepatic encephalopathy score) and CATCH-LIFE B nomogram (based on age, bilirubin, international normalized ratio, serum albumin, white blood cell, platelet count, and hepatic encephalopathy score) had discriminatory ability for predicting 28-day (c-indexes of 0.910 and 0.899) and 90-day mortality (c-indexes of 0.878 and 0.887, respectively). The area under the curve values for 28-day and 90-day mortality prediction by the CATCH-LIFE A nomogram were 0.922 (95% CI : 0.874, 0.971) and 0.905 (0.856, 0.956), respectively, while those for the CATCH-LIFE B nomogram were 0.916(0.861,0.972) and 0.915 (0.866,0.964), respectively. Similar performance results were observed in the validation cohort. Optimal cut-off scores for each nomogram could be used for patient stratification in high- and low-risk groups, and the high-risk groups showed shorter survival times than the low-risk groups in both the training and validation cohorts. Two nomograms constructed from the first short-term follow-up data from patients with AoCLD due to combined HBV infection and alcohol exposure showed good predictive performance for 28-day and 90-day mortality and might be used to guide clinical management., (© 2024. The Author(s).)

Studies have shown that the cachexia index (CXI) is a useful predictor of cachexia in patients with colorectal cancer. However, the application of the CXI is limited stemming from the intricacy and additional cost of radiographic examinations. This study aimed to develop an easy-to-use and practical CXI based on fat-free mass index (FFMI-CXI) to evaluate the prognostic value of FFMI-CXI in CRC. A total of 656 patients with CRC were enrolled in the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) study. The FFMI-CXI was calculated as [FFMI (kg)/height (m) 2 × serum albumin (g/L)]/neutrophil-lymphocyte ratio. The cutoff value for FFMI-CXI was determined through the analysis of ROC curves and Youden's index for both male and female cohorts. Kaplan-Meier survival curves with log-rank tests were conducted to compare time-event relationships between different groups. Cox proportional hazards regression models incorporating both univariate and multivariate variables were employed to explore the independent prognostic factors associated with OS. Logistic regression analysis was performed to assess the association of the FFMI-CXI with secondary outcomes. The major outcome was 5-year overall survival (OS). Based on the cutoff values, 331 patients had low FFMI-CXI, and 325 patients had high FFMI-CXI. Patients in the low FFMI-CXI subgroup were significantly older and had advanced TNM stage, malnutrition, high systemic inflammation, long hospitalizations, high hospitalization costs, adverse short-term outcomes, and all-cause mortality. Multivariate Cox regression analyses revealed that FFMI-CXI (HR 0.47, 95% CI 0.33-0.66; p < 0.001) and TNM stage (HR 3.38, 95% CI 2.63-4.35; p < 0.001) were independently associated with OS in CRC patients. K-M survival curves revealed that the CRC patients with a high FFMI-CXI had significantly more favorable OS than those with low FFMI-CXI (62.84% vs. 84.31%; log-rank p < 0.001). Furthermore, the FFMI-CXI was valuable for predicting 90-day outcomes, malnutrition, cancer cachexia, length of hospitalization, and hospitalization expenses. This study revealed that the FFMI-CXI can be used as a prognostic indicator in patients with CRC. Patients with low FFMI-CXI should receive more attention., (© 2024. The Author(s).)

Atherosclerosis is a leading cause of cardiovascular diseases, characterized by endothelial dysfunction and lipid accumulation. Long non-coding RNAs (lncRNAs) are emerging as key regulators of endothelial cell behavior. This study aimed to investigate the role of lncRNA NORAD in endothelial cell proliferation and as a potential therapeutic target for atherosclerosis. A total of 75 CAD patients and 76 controls were recruited, and plasma NORAD levels were measured using qRT-PCR. HUVECs were transfected with si-NORAD to evaluate its effects on cell cycle, proliferation, migration, and apoptosis. Plasma NORAD levels were significantly elevated in CAD patients. The NORAD-miRNA-mRNA ceRNA regulatory network was constructed based on GEO database, and G1/S-specific cyclin-D1 (CCND1) was identified as one of the hub factors. NORAD deficiency suppressed cell migration and induced G1 cell cycle arrest in HUVECs by downregulating CCND1 in vitro. NORAD upregulated CCND1 in HUVECs via sponging miR-106a that inhibited cell migration. The dual-luciferase assay confirmed the direct targeting of miR-106a by NORAD, and overexpression of miR-106a inhibited HUVEC proliferation and migration. Si-NORAD transfection resulted in induced early apoptosis, increased intracellular ROS levels, decreased GSH levels, and reduced mitochondrial membrane potential. Additionally, si-NORAD decreased the expression of GPX4, FTH1, KEAP1, NCOA4, and Nrf2, while increasing Xct levels, confirming the involvement of ferroptosis. Our findings reveal that NORAD plays a critical role in endothelial cell proliferation, migration, and apoptosis, and its silencing induces ferroptosis. The regulatory network involving NORAD, miR-106a, and their target genes provides a potential therapeutic avenue for atherosclerosis., (© 2024. The Author(s).)

Backfilling is a promising measure for controlling surface subsidence in mined-out areas and disposing solid wastes from the mineral processing, there are increasing demands of enhanced toughness and anti-cracking properties of backfill materials to prolong the service life under the complex loads. In this study, polypropylene (PP) fibers were employed to improve performance of backfills, four-point bending and uniaxial compression tests were conducted to investigate the failure process and damage evolution of fiber-reinforced aeolian-sand backfill materials (FABs) using Digital Image Correlation (DIC) and Acoustic Emission (AE) techniques. The results show that the compressive strength tends to decrease with the increasing fiber volume fractions, while the four-point bending strength shows a tendency to increase initially and then decrease, and the optimum volume fraction of PP fiber is 0.6%. At the optimal fiber volume fraction, PP fibers with lengths of 3 mm and 9 mm resulted in a 65.25% and 81.62% increase in the four-point bending strength of FABs, respectively. As indicated by DIC measurements, PP fibers with a length of 9 mm were more effective in controlling the horizontal and vertical displacements of FABs under four-point bending loads than that of 3 mm, and the cracks developed more slowly at the same deflection. In addition, PP fibers with a length of 9 mm have stronger crack extension delay characteristics due to longer effective anchorage distance, as evidenced by more frequent acoustic emission ringing counts and higher cumulative ringing counts. The results of the study may provide a theoretical basis for the application of FABs materials in backfilling., (© 2024. The Author(s).)

Aspect-based sentiment analysis (ABSA) is a challenging task due to the presence of multiple aspect words with different sentiment polarities in a sentence. Recently, pre-trained language models like BERT have been widely used as context encoders in ABSA. Graph neural networks have also been employed to extract syntactic and semantic information from sentence parsing trees, resulting in superior results. However, dependency trees may establish irrelevant dependencies for sentences with irregular syntax and complex structures. Additionally, previous methods have not fully utilized recent developments in pre-trained language models. Therefore, we propose a Dual Syntax aware Graph attention networks with Prompt (DSGP) model to address these issues. Our model utilizes prompt templates to maximize the potential of pre-trained models and masked vector outputs of templates as supplementary aspect feature representations. We also leverage both dependency trees and constituent trees with graph attention networks to extract different types of syntactic information. The dependency tree captures syntactic correlation between words, while the constituent tree provides a high-level formation of the sentence. Finally, the output from the prompt and parsing trees is fused and fed into a standard classifier. Experimental results on four public datasets demonstrate the competitive performance of our model., (© 2024. The Author(s).)

Some studies have reported that the gut microbiota can influence adrenal-related hormone levels. However, the causal effects of the gut microbiota on adrenal function remain unknown. Therefore, we employed a two-sample Mendelian randomization (MR) study to systematically investigate the impact of gut microbiota on the function of different regions of the adrenal gland. The summary statistics for gut microbiota and adrenal-related hormones used in the two-sample MR analysis were derived from publicly available genome-wide association studies (GWAS). In the MR analysis, inverse variance weighting (IVW) was used as the primary method, with MR-Egger, weighted median, and cML-MA serving as supplementary methods for causal inference. Sensitivity analyses such as the MR-Egger intercept test, Cochran's Q test, and leave-one-out analysis were used to assess pleiotropy and heterogeneity. We identified 27 causal relationships between 23 gut microbiota and adrenal function using the IVW method. Among these, Sellimonas enhanced the function of the adrenal cortex reticularis zone (beta = 0.008, 95% CI: 0.002-0.013, P = 0.0057). The cML-MA method supported our estimate (beta = 0.009, 95% CI: 0.004-0.013, P = 2 × 10 - 4 ). Parasutterella, Sutterella, and Anaerofilum affect the functioning of different regions of the adrenal gland. Notably, pleiotropy was not observed. Our findings revealed that the gut microbiota is causally associated with adrenal function. This enhances our understanding of the gut-microbiota-brain axis and provides assistance in the early diagnosis and treatment of adrenal-related diseases in clinical practice., (© 2024. The Author(s).)

Patients with advanced idiopathic pulmonary fibrosis (IPF), a complex and incurable lung disease with an elusive pathology, are nearly exclusive candidates for lung transplantation. Improved identification of patient subtypes can enhance early diagnosis and intervention, ultimately leading to better prognostic outcomes for patients. The goal of this study is to identify new immune patterns and biomarkers in patients. Immune subtypes in IPF patients were identified using single-sample gene set enrichment analysis, and immune subtype-related genes were explored using the weighted correlation network analysis algorithm. A machine learning integration framework was used to establish the optimal prognostic model, known as the immune-related risk score (IRS). Single-cell sequencing was conducted to investigate the major role of macrophage-derived PLA2G7 in the immune microenvironment. We assessed the stability of celecoxib in targeting PLA2G7 through molecular docking and surface plasmon resonance. IPF patients present two distinct immune subtypes, one characterized by immune activation and inflammation, and the other by immune suppression. IRS can predict the immune status and prognosis of IPF patients. Furthermore, multi-cohort analysis and single-cell sequencing analysis demonstrated the diagnostic and prognostic value of PLA2G7 derived from macrophages and its role in shaping the inflammatory immune microenvironment in IPF patients. Celecoxib could effectively and stably bind with PLA2G7. PLA2G7, as identified through IRS, demonstrates marked stability in diagnosing and predicting the prognosis of IPF patients as well as predicting their immune status. It can serve as a novel biomarker for IPF patients., (© 2024. The Author(s).)

Synergistically improving the strength and toughness of metallic materials is a central focus in the field of physical metallurgy. Yet, there is a noticeable lack of research in strengthening and toughening large-size metal components, whereas those components are extensively used in the modern industry. In this work, a deformation-assisted tempering (DAT) process was proposed to create a novel microstructure in 1.4 tons low-alloyed plain steel. After DAT treatment, the steel contains low dislocation density but high density of low-angle subgrain boundaries and dispersed spherical nano carbides. Such microstructure enables a much better combination of tensile strength and fracture toughness compared to the small-size quench and temper steels. The significant improvement in low-temperature impact toughness is due to the occurrence of delamination and subsequent large plastic deformation at the notch tip. The DAT process can provides a new strategy for the development of large-size fail-safe steel with excellent strength and fracture resistance., (© 2024. The Author(s).)

Microplastics pollution in agricultural soil is increasingly recognized, but the specific situation varies with geography, climate conditions, and farming practices. The karst landscape, a typical geomorphology in China, demands a deeper understanding of microplastics pollution in such areas. This research zeroes in on Guizhou, a province known for its karst formations, by collecting soil samples from the mulched cultivation layer in ten counties and cities. The study employed metallographic microscopy, scanning electron microscopy (SEM-EDS), and Fourier-transform infrared spectroscopy (FT-IR) to analyze the presence and distribution of microplastics. Results show that polyethylene is the predominant component of microplastics in the mulched agricultural soils of Guizhou, primarily existing as irregular fragments in black, transparent, and translucent forms, with diameters of 40 ~ 120 μm and rough surfaces marked by significant erosion. The concentration of microplastics varies from 143.28 to 3,283.46 items/kg, averaging 1,150.60 ± 647.86 items/kg. The majority of particles accounting for 64.79% are sized between 10 ~ 100 μm. A highly significant positive correlation (p < 0.001) is found between mulching duration and microplastics concentration, indicating that prolonged mulching increases microplastics accumulation in farmlands. Additionally, crop type, irrigation method, and soil type also influence microplastics concentration. This study highlights the escalating issue of microplastics pollution in China's karst regions, underscoring the need for attention., (© 2024. The Author(s).)

Porcine pasteurellosis is an infectious disease caused by Pasteurella multocida (P. multocida), which seriously endangers the healthy development of pig breeding industry. Early detection of disease transmission in animals is a crucial early warning for humans. Therefore, predicting risk areas for disease is essential for public health authorities to adopt preventive measures and control strategies against diseases. In this study, we developed a predictive model based on multi-criteria decision analysis (MCDA) and assessed risk areas for porcine pasteurellosis in the Chinese mainland. By using principal component analysis, the weights of seven spatial risk factors were determined. Fuzzy membership function was used to standardize all risk factors, and weight linear combination was used to create a risk map. The sensitivity of the risk map was analyzed by calculating the mean of absolute change rates of risk factors, as well as calculating an uncertainty map. The results showed that risk areas for porcine pasteurellosis were predicted to be locate in the south-central of the Chinese mainland, including Sichuan, Chongqing, Guangdong, and Guangxi. The maximum standard deviation of the uncertain map was less than 0.01and the ROC results showed that the prediction model has moderate predictive performance with the area under the curve (AUC) value of 0.80 (95% CI 0.75-0.84). Based on the above process, MCDA was combined with WebGIS technology to construct a system for predicting risk areas of porcine pasteurellosis. Risk factor data was directly linked to the developed model, providing decision support for disease prevention and control through monthly updates., (© 2024. The Author(s).)

Pyrolysis of animal manure at high temperature is necessary to effectively immobilize heavy metals, while the available phosphorus (P) level in biochar is relatively low, rendering it unsuitable for use as fertilizer. In this study, the pretreatment of swine manure with different potassium (K) sources (KOH, K 2 CO 3 , CH 3 COOK and C 6 H 5 K 3 O 7 ) was conducted to produce a biochar with enhanced P availability and heavy metals immobility. The addition of all K compounds lowered the peak temperature of decomposition of cellulose in swine manure. The percentage of ammonium citrate and formic acid extractable P in biochar increased with K addition compared to undoped biochar, with CH 3 COOK and C 6 H 5 K 3 O 7 showing greater effectiveness than KOH and K 2 CO 3 , however, water- extractable P did not exhibit significant changes. Additionally, the available and dissolved Si increased due to the doping of K, with KOH and K 2 CO 3 having a stronger effect than CH 3 COOK and C 6 H 5 K 3 O 7 . X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FTIR) analysis revealed that K addition led to the formation of soluble CaKPO 4 and silicate. In addition, the incorporation of K promoted the transformation of labile copper (Cu) and znic (Zn) into the stable fraction while simultaneously reducing their environmental risk. Our study suggest that the co-pyrolysis of swine manure and organic K represents an effective and valuable method for producing biochar with optimized P availability and heavy metals immobility., (© 2024. The Author(s).)

The stress hyperglycemia ratio (SHR) is established as a reliable marker for assessing the severity of stress-induced hyperglycemia. While its effectiveness in managing patients with Acute Ischemic Stroke (AIS) remains to be fully understood. We aim to explore the relationship between SHR and clinical prognosis in AIS patients and to assess how diabetes status influences this relationship. In this study, we analyzed data from the Medical Information Mart for Intensive Care (MIMIC-IV) database, selecting patients with AIS who required ICU admission. These patients were categorized into tertiles based on their SHR levels. We applied Cox hazard regression models and used restricted cubic spline (RCS) curves to investigate relationships between outcomes and SHR. The study enrolled a total of 2029 patients. Cox regression demonstrated that a strong correlation was found between increasing SHR levels and higher all-cause mortality. Patients in the higher two tertiles of SHR experienced significantly elevated 30-day and 90-day mortality rates compared to those in the lowest tertile. This pattern remained consistent regardless of diabetes status. Further, RCS analysis confirmed a progressively increasing risk of all-cause mortality with higher SHR levels. The findings indicate that SHR is association with increased 30-day and 90-day mortality among AIS patients, underscoring its potential value in risk stratification. Although the presence of diabetes may weaken this association, significant correlations persist in diabetic patients., (© 2024. The Author(s).)

This study improves the Logistic chaotic system and combines it with the hyperchaotic Chen system to create a dual chaotic system. The algorithm encrypts images in three stages. In the first stage, a plaintext-related key generation scheme is designed to generate the parameters and initial values of the dual chaotic system. In the second stage, the chaotic sequences generated by the dual chaotic system are used for dynamic DNA encoding and computation. In the third stage, the chaotic sequences generated by the improved Logistic chaotic system are used to perform row-column permutations, completing the scrambling. The security analysis of the encrypted images shows that the algorithm described in this paper is robust and secure, capable of resisting most known attacks. The algorithm is fast in encryption, provides high-quality image reconstruction, and is suitable for scenarios with high comprehensive performance and image quality requirements., (© 2024. The Author(s).)

Contrast-enhanced magnetic resonance neurography (CE-MRN) holds promise for diagnosing brachial plexopathy by enhancing nerve visualization and revealing additional imaging features in various lesions. This study aims to validate CE-MRN's efficacy in improving brachial plexus (BP) imaging across different patient cohorts. Seventy-one subjects, including 19 volunteers and 52 patients with BP compression/entrapment, injury, and neoplasms, underwent both CE-MRN and plain MRN. Two radiologists assessed nerve visibility, with inter-reader agreement evaluated. Quantitative parameters such as signal intensity (SI), contrast-to-noise ratio (CNR), and contrast ratio (CR) of the C7 nerve were measured. Both qualitative scoring and quantitative metrics were compared between CE-MRN and plain MRN within each patient group. Patient classification followed the Neuropathy Score Reporting and Data System (NS-RADS), summarizing additional imaging features for each brachial plexopathy type. Inter-reader agreement for qualitative assessment was strong. CE-MRN significantly enhanced BP visualization and nerve-tissue contrast across all cohorts, particularly in volunteers and patients with injuries. It also uncovered additional imaging features such as hypointense signals in ganglia, compressed nerve sites, and neoplastic enhancements. CE-MRN effectively mitigated muscle edema and vascular contamination, enabling precise classification of BP injuries. Overall, CE-MRN consistently enhances BP visualization and provides valuable imaging features for accurate diagnosis., (© 2024. The Author(s).)

Antiphospholipid syndrome (APS) is an autoimmune disorder characterized by vascular thrombosis and obstetric morbidity, with accurate laboratory examination of antiphospholipid antibodies (aPLs) being crucial for diagnosis. This study focused on anti-β2 glycoprotein I (aβ2GPI) antibodies and aimed to establish the first population-based cutoff values for aβ2GPI IgA/IgM/IgG antibodies in non-pregnant women of reproductive age in Southwest China. The study cohort comprised 181 healthy women of reproductive age for study. Blood samples were collected on an early morning fast. Anti-β2GPI antibodies including IgA, IgM and IgG were measured in serum using the HOB ® BioCLIA kit. According to the Clinical and Laboratory Standards Institute (CLSI) guidelines, the study used non-parametric percentile methods to calculate the 95th, 97.5th, and 99th percentiles cutoff values for aβ2GPI IgA/IgM/IgG antibodies, along with corresponding 90% confidence intervals (CI), while excluding outliers. A total of 168 independent samples were collected for verification, including 85 samples from healthy subjects and 83 samples from APS patients, in order to evaluate the analytical performance of the obtained cutoff values. The 99th percentile cutoff values were 3.36 RU/mL for aβ2GPI IgA, 27.54 RU/mL for aβ2GPI IgM and 1.81 RU/mL for aβ2GPI IgG, which indicated that the levels of aβ2GPI IgM antibodies were generally higher compared to those of IgA and IgG antibodies. Our established reference range was confirmed to be successful in validating the detected values of aβ2GPI antibodies in all healthy controls. With the 99th percentile cutoff value, the sensitivity was 14.46% for aβ2GPI IgA, 22.89% for aβ2GPI IgG, and 9.64% for aβ2GPI IgM in APS patients. This study established population-based cutoff values that are applicable to the local population for the accurate laboratory examination of aβ2GPI antibodies in non-pregnant women of reproductive age. The study also recommends paying more attention to IgM positivity in women of reproductive age., (© 2024. The Author(s).)

Antibiotics, as emerging persistent pollutants, pose significant threats to human health. The effective and low-cost removal of ciprofloxacin (CIP) from wastewater has become an important research focus. In this study, fly ash (FA) was used as the raw material, and modified fly ash (MFA) was prepared by varying microwave power, alkali concentration, and immersion time to investigate its adsorption characteristics for CIP. Results showed that the optimal preparation conditions for MFA with the most effective adsorption of CIP, using the Box-Behnken response surface methodology, were a microwave power of 480 W, an alkali concentration of 1.5 mol/L, and a modification time of 3 h. Scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction analyses revealed that after modification, the glassy structure of FA is destroyed, the specific surface area is increased, and obvious hydroxyl O-H absorption peaks appear. Both FA and MFA exhibited adsorption processes for CIP that conformed to pseudo-second-order kinetics and the Langmuir equation. Maximum adsorption of CIP (9.61 and 12.67 mg/g) was achieved at pH = 6. With increasing temperature, the adsorption capacity of both FA and MFA for CIP decreased, indicating an exothermic process. The adsorption capacity of CIP decreased with increasing ion concentration, with the impact order of ions being Al 3+  > Ca 2+  > Na + . The results show that pore filling, electrostatic interaction, ion exchange and complexation are the main ways of CIP adsorption by FA. Microwave alkali modified fly ash is an economical and efficient adsorbent for CIP removal in water, realizing the purpose of "treating waste with waste". This study provides a scientific basis for controlling CIP treatment in wastewater., (© 2024. The Author(s).)

This study explored subjective responses towards various environmental quality parameters. It would be helpful to approach an overall comfort improvement relating to physics. In order to investigate the combined effects of sound, light and heat on the overall comfort of pedestrians, which could be evaluated by overall comfort vote, two residential areas in Yubei District, Chongqing (a Cfa city in China) were selected for field measurements and questionnaires. Three were three key findings were concluded based on subjective responses to environmental parameters via multiple linear regression. First, the average outdoor neutral temperature, mean neutral sound level and neutral illumination intensity were determined to be 26.6 °C (determined by physiologically equivalent temperature), 56.5 dBA (determined by A-weighted equivalent continuous sound level) and 21.4 klx (determined by LUX), respectively. Second, considering the effects of both physiology and psychology, thermal perceptions varied for acoustic and light environments. Residents partially had lower neutral temperatures at the noisy condition. Third, environmental quality factors had a significant effect on overall comfort. Positive correlation between physiologically equivalent temperature and overall comfort vote was found (sig < 0.000); while the effects of sound pressure and light intensity were not always significant. Hence, thermal stress played a significant role in people's overall comfort. This study has explored the effects of three environment quality parameters on human perceptions. It provided better understanding against dwellers' feelings under complex circumstances. Future urban design and planning works should consider the cooling factors regarding contextual acoustical and visual environments., (© 2024. The Author(s).)

In the mechanical cutting industry, trial production is used for predicting and evaluating the quality of product processes before batch production, and it can be expressed through the qualification rate. However, it cannot objectively and comprehensively evaluate the quality of product processes. This study optimizes the analysis of outliers and stability in mathematical statistics to better apply it in the mechanical cutting industry; then, it combines them with process capability analysis. Simultaneously, considering the non-normal distribution of process parameters, a batch production-prediction model is proposed. The reliability of batch production-prediction model is verified by the diameter, roundness and roughness of structural common samples. Meanwhile, for other mechanical parts in the mechanical cutting industry, the model proposed in this paper can be used to quickly and accurately predict and evaluate batch production., (© 2024. The Author(s).)

Hailstorms, characterized by their intensity, are often accompanied by strong winds and heavy rain, posing significant destructive potential. Data indicate that the economic losses caused by hail to buildings, particularly solar panels, have been increasing annually. However, research on the hail resistance of photovoltaic panels has predominantly focused on the isolated effects of hail impacts and wind loads, neglecting the coupling effects between wind and hail. In this study, a device was designed to couple both wind and hail. The effects of turbulence, hail size, and velocity on hail impact behavior were systematically studied and quantified. A predictive formula for the peak load of hail impact on structures was established. The results indicate that the impact of turbulence on hail is significant. When turbulence intensity varies with hail velocity, hail impact force increases as turbulence decreases and hail velocity increases. When both turbulence and hail diameter vary, the impact force of smaller hailstones shows less variation with increasing turbulence. According to variance analysis, hail velocity is the most significant factor affecting hail impact, followed by hail diameter and finally turbulence. The regression equation is given by F = - 0.624 I u + 5116.25 D + 7.85 V hail - 259.709 , where F represents the peak impact force in Newtons (N), I u denotes the turbulence intensity, D is the hail diameter in meters (m), and V hail is the hail velocity in meters per second (m/s)., (© 2024. The Author(s).)

TNFAIP8 family molecules have been recognized for their involvement in the progression of tumors across a range of cancer types. Emerging experimental data suggests a role for certain TNFAIP8 family molecules in the development of glioma. Nonetheless, the comprehensive understanding of the genomic alterations, prognostic significance, and immunological profiles of TNFAIP8 family molecules in glioma remains incomplete. In the study, using the comprehensive bioinformatics tools, we explored the unique functions of 4 TNFAIP8 members including TNFAIP8, TNFAIP8L1, TNFAIP8L2 and TNFAIP8L3 in glioma. The expressions of TNFAIP8, TNFAIP8L1, TNFAIP8L2, and TNFAIP8L3 were notably upregulated in glioma tissues compared to normal tissues. Furthermore, survival analysis indicated that elevated expression levels of TNFAIP8, TNFAIP8L1 and TNFAIP8L2 were correlated with unfavorable outcomes in terms of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) among glioma patients. Genetic modifications, such as mutations and copy number alterations, within the TNFAIP8 family exhibited a significant association with extended OS, DSS and PFS in individuals diagnosed with glioma. The findings suggest a noteworthy correlation between TNFAIP8 family members and the age and 1p/19q codeletion status of glioma patients. We also found that there were significant relationships between TNFAIP8 family expression and tumor immunity in glioma. Furthermore, functional annotation of TNFAIP8 family members and their co-expressed genes in gliomas was carried out using GO and KEGG pathway analysis. The GO analysis revealed that the primary biological processes influenced by the TNFAIP8 family co-expressed genes included cell chemotaxis, temperature homeostasis, and endocytic vesicle formation. Additionally, the KEGG analysis demonstrated that TNFAIP8 family co-expressed genes are involved in regulating various pathways such as inflammatory mediator regulation of TRP channels, pathways in cancer, prolactin signaling pathway, and Fc gamma R-mediated phagocytosis. Overall, the findings suggest that TNFAIP8 family members may play a significant role in the development of glioma and have the potential to serve as prognostic indicators and therapeutic targets for individuals with glioma., (© 2024. The Author(s).)

Neoadjuvant therapy (NAT) is an important treatment for patients with resectable locally advanced esophageal squamous cell carcinoma (ESCC), but neoadjuvant resistance affects the overall treatment outcome. Therefore, it is particularly important to accurately screen the population for NAT and explore the mechanism of resistance. Usually, different chemotherapy regimens cause different drug resistance mechanisms. Prior to combining immunotherapy with chemotherapy, extensive research has been conducted on previous drug resistance mechanisms. Currently, the mainstream NAT for ESCC involves chemotherapy combined with immunotherapy. We have witnessed the remarkable effect of this combination therapy; however, there are still a considerable number of patients whose tumor tissues show no change or even progress after NAT, and their drug resistance mechanisms remain unclear. Hence, we aim to identify relevant evidence that can distinguish and predict the effectiveness of NAT from a clinical perspective in order to provide a clinical basis for future screening of suitable populations for NAT and discovery of drug resistance mechanisms. This study is based in China's high incidence area of esophageal cancer, where enrolled patients all receive the current mainstream NAT regimen resulting in more reliable outcomes., (© 2024. The Author(s).)

Virus‒host protein‒lncRNA interaction (VHPLI) predictions are critical for decoding the molecular mechanisms of viral pathogens and host immune processes. Although VHPLI interactions have been predicted in both plants and animals, they have not been extensively studied in viruses. For the first time, we propose a new deep learning-based approach that consists mainly of a convolutional neural network and bidirectional long and short-term memory network modules in combination with transfer learning named CBIL‒VHPLI to predict viral-host protein‒lncRNA interactions. The models were first trained on large and diverse datasets (including plants, animals, etc.). Protein sequence features were extracted using a k-mer method combined with the one-hot encoding and composition-transition-distribution (CTD) methods, and lncRNA sequence features were extracted using a k-mer method combined with the one-hot encoding and Z curve methods. The results obtained on three independent external validation datasets showed that the pre-trained CBIL‒VHPLI model performed the best with an accuracy of approximately 0.9. Pretraining was followed by conducting transfer learning on a viral protein-human lncRNA dataset, and the fine-tuning results showed that the accuracy of CBIL‒VHPLI was 0.946, which was significantly greater than that of the previous models. The final case study results showed that CBIL‒VHPLI achieved a prediction reproducibility rate of 91.6% for the RIP-Seq experimental screening results. This model was then used to predict the interactions between human lncRNA PIK3CD-AS2 and the nonstructural protein 1 (NS1) of the H5N1 virus, and RNA pull-down experiments were used to prove the prediction readiness of the model in terms of prediction. The source code of CBIL‒VHPLI and the datasets used in this work are available at https://github.com/Liu-Lab-Lnu/CBIL-VHPLI for academic usage., (© 2024. The Author(s).)

Soils around bedrock outcrops, even if they are protected by vegetation to some extent after ecological restoration, are prone to being washed away by rock surface flow (RSF) derived from these outcrops in rocky desertification land. However, the extent of the scouring scale and sorting effect of RSF on the soils around outcrops remains unknown. To solve this problem, a series of soils around bedrock outcrops exposed in sloping farmland (SF, without RSF), abandoned land (AL, 1 year of RSF) and shrub-grassland (SG, 5 years of RSF) were examined by the laser diffraction method in a natural ecological restoration area of rocky desertification, where the duration of the RSF is also the time for ecological restoration. It was found that the RSF had a limited effect on the particle size distribution of the soils, only having a significant scouring effect on the soils at the rock-soil interface within a horizontal distance of 2 cm from the outcrops and an insignificant effect on the soils far away from the outcrops in terms of horizontal distance (10 cm and 20 cm). The particle size distributions of the soil around the outcrops were related to erosion caused by the RSF, but mainly benefited from ecological restoration. Compared with SF, the fine particle content in the soils around the outcrops significantly decreased in AL, but significantly increased in SG. Within a short period (1 year) after natural recovery, the RSF had a reduced effect on the fine particles of the soil around the outcrops; however, this did not occur after a long period (5 years). The results of this study further explain the influence of the RSF on soil erosion and leakage loss in karst areas., (© 2024. The Author(s).)

Water permeability of reinforced concrete is essential for transportation of ingress ions inside concrete structures. The coupling effect of permeability and loading presents a challenge for the experimental simulation of water-permeate reinforced concrete subjected to tension. This renders the development of the model based on dimensionless analysis, using a series of experimental tests from an innovative experimental system that allows simultaneous measurement of permeability and crack width. The experiments focused on both ordinary concrete and high strength concrete under tension. The relationship between permeability and variables such as deformation, diameter of rebars, tensile load, and crack width under tension was formulated through multiple regression analysis using the testing data. The load to deformation characteristics determines the permeability of the concrete under tension. The proposed model accounts for the influence of continuous loading on permeability, as demonstrated by the robust analysis and proposed yield effective point. The robust analysis demonstrates that the diameter of the rebar, load, and crack width exert minimal influence on the permeability of concrete at lower significance levels. However, permeability variations become pronounced from 0.5 threshold, with significant changes observed between 0.5 and 0.9 thresholds. The findings indicate a differential impact of the variables on the permeability of concrete under tension. The yield-effective points delineate the relationship between the rebar diameter, load, and crack-width on the permeability of concrete with a threshold of 0.5, 0.5, and 0.58, respectively. At a threshold of 0.78, higher permeability will occur in the concrete, attributed to the prevalence of deformation. This deformation highlights the parameters with the most significant influence on the permeability of concrete under tension. The robust analysis and yield effective point derivative are useful parameters to measure concrete permeability and evaluate the behavior of the permeability model under tension., (© 2024. The Author(s).)

Head and neck squamous carcinoma (HNSC) is a prevalent malignant disease, with the majority of patients being diagnosed at an advanced stage. Endoplasmic reticulum stress (ERS) is considered to be a process that promotes tumorigenesis and impacts the tumor microenvironment (TME) in various cancers. The study aims to investigate the predictive value of ERS in HNSC and explore the correlation between ERS-related genes and TME. A series of bioinformatics analyses were carried out based on mRNA and scRNA-seq data from the TCGA and GEO databases. We conducted RT-qPCR and western blot to validate the signature, and performed cell functional experiments to investigate the in vitro biological functions of the gene. We identified 63 ERS-related genes that were associated with outcome and stage in HNSC. A three-gene signature (ATF6, TRIB3, and UBXN6) was developed, which presents predictive value in the prognosis and immunotherapy response of HNSC patients. The high-risk group exhibited a worse prognosis but may benefit from immunotherapy. Furthermore, there was a significant correlation between the signature and immune infiltration. In the high-risk group, fibroblasts were more active in intercellular communication, and more T cells were observed at the end of the sequential phase. The genes in the ERS-related signature were overexpressed in HNSC cells, and the knockdown of TRIB3 significantly inhibited cell proliferation and migration. This study established a novel ERS-related signature that has potential implications for HNSC therapy and the understanding of TME., (© 2024. The Author(s).)

With the advancement of science and technology, coal-washing plants are transitioning to intelligent, information-based, and professional sorting systems. This shift accelerates the construction a modern economic system characterized by green and low-carbon development, thereby promoting the high-quality advancement of the coal industry. Traditional manual gangue picking and multi-axis robotic arm gangue selection currently suffer from low recognition accuracy, slow sorting efficiency, and high worker labor intensity. This paper proposes a deep learning-based, non-contact gangue recognition and pneumatic intelligent sorting system. The system constructs a dynamic database containing key feature information such as the target gangue's contour, quality, and center of mass. The system elucidates the relationships between ejection speed, mass, volume, angle of incidence, and the impact energy matching mechanism. Demonstration experiments using the system prototype for coal gangue sorting reveal that, compared to existing robotic arm sorting methods in coal washing plants, this system achieves a gangue identification accuracy exceeding 97%, a sorting rate above 91%, and a separation time of less than 3 s from identification to separation, thereby effectively enhancing raw coal purity., (© 2024. The Author(s).)

Due to the large computational overhead, underutilization of features, and high bandwidth consumption in traditional SDN environments for DDoS attack detection and mitigation methods, this paper proposes a two-stage detection and mitigation method for DDoS attacks in SDN based on multi-dimensional characteristics. Firstly, an analysis of the traffic statistics from the SDN switch ports is performed, which aids in conducting a coarse-grained detection of DDoS attacks within the network. Subsequently, a Multi-Dimensional Deep Convolutional Classifier (MDDCC) is constructed using wavelet decomposition and convolutional neural networks to extract multi-dimensional characteristics from the traffic data passing through suspicious switches. Based on these extracted multi-dimensional characteristics, a simple classifier can be employed to accurately detect attack samples. Finally, by integrating graph theory with restrictive strategies, the source of attacks in SDN networks can be effectively traced and isolated. The experimental results indicate that the proposed method, which utilizes a minimal amount of statistical information, can quickly and accurately detect attacks within the SDN network. It demonstrates superior accuracy and generalization capabilities compared to traditional detection methods, especially when tested on both simulated and public datasets. Furthermore, by isolating the affected nodes, the method effectively mitigates the impact of the attacks, ensuring the normal transmission of legitimate traffic during network attacks. This approach not only enhances the detection capabilities but also provides a robust mechanism for containing the spread of cyber threats, thereby safeguarding the integrity and performance of the network., (© 2024. The Author(s).)

The problem of coal compression under buildings is common in underground mining of coal mines in China. The selection of traditional mining programme is subjective and lacks scientific rationality. In order to solve this problem, this paper studies the evaluation index system and model applicable to the selection of coal filling mining scheme under buildings. A multi-objective evaluation index system integrating economic, technical and adaptive factors is constructed. And an integrated optimization model is established, which is based on the traditional grey target model, combining the game theory optimal combination of weights with the hierarchical analysis method, entropy weight method, Critic method to determine the weights, and then introducing the TOPSIS model and the Mars distance to establish an improved grey target decision-making model. The validity of the evaluation index system and model is verified by taking the example of coal mining under pressure of buildings in five mining areas of a coal mine, which provides technical support for decision makers. This study helps to scientifically and reasonably carry out the preferred mining scheme of coal filling under building pressure., (© 2024. The Author(s).)

We explored physiological effects of the sodium-glucose co-transporter-2 inhibitor empagliflozin on intact experimentally hypertrophic murine hearts following transverse aortic constriction (TAC). Postoperative drug (2-6 weeks) challenge resulted in reduced late Na + currents, and increased phosphorylated (p-)CaMK-II and Nav1.5 but not total (t)-CaMK-II, and Na + /Ca 2+ exchanger expression, confirming previous cardiomyocyte-level reports. It rescued TAC-induced reductions in echocardiographic ejection fraction and fractional shortening, and diastolic anterior and posterior wall thickening. Dual voltage- and Ca 2+ -optical mapping of Langendorff-perfused hearts demonstrated that empagliflozin rescued TAC-induced increases in action potential durations at 80% recovery (APD 80 ), Ca 2+ transient peak signals and durations at 80% recovery (CaTD 80 ), times to peak Ca 2+ (TTP 100 ) and Ca 2+ decay constants (Decay 30-90 ) during regular 10-Hz stimulation, and Ca 2+ transient alternans with shortening cycle length. Isoproterenol shortened APD 80 in sham-operated and TAC-only hearts, shortening CaTD 80 and Decay 30-90 but sparing TTP 100 and Ca 2+ transient alternans in all groups. All groups showed similar APD 80 , and TAC-only hearts showed greater CaTD 80 , heterogeneities following isoproterenol challenge. Empagliflozin abolished or reduced ventricular tachycardia and premature ventricular contractions and associated re-entrant conduction patterns, in isoproterenol-challenged TAC-operated hearts following successive burst pacing episodes. Empagliflozin thus rescues TAC-induced ventricular hypertrophy and systolic functional, Ca 2+ homeostatic, and pro-arrhythmogenic changes in intact hearts., (© 2024. The Author(s).)

Previous studies have reported associations between newly diagnosed diabetes and poor outcomes after percutaneous coronary intervention (PCI), but there is limited data focusing on elderly patients (age ≥ 65). This study aimed to analyze the prevalence and clinical implications of newly diagnosed diabetes in elderly patients who underwent PCI. From 2004 to 2021, a total of 2456 elderly patients who underwent invasive PCI at Korea University Guro Hospital were prospectively enrolled and followed up for a median of five years. The primary endpoint was five-year major adverse cardiovascular events (MACE). Cox regression was used to evaluate whether newly diagnosed diabetes impacted on long-term clinical outcomes. Newly diagnosed diabetes was presented in approximately 8.1% to 10.9% of elderly patients who underwent PCI. Those who had a new diagnosis of diabetes had a higher risk of MACE than previously known diabetes (25.28% vs. 19.15%, p = 0.039). After adjusting for significant factors, newly diagnosed diabetes remained an independent predictor of MACE (HR [hazard ratio] 1.64, 95% confidence interval [CI] 1.24-2.17, p < 0.001), cardiac death (HR 2.15, 95% CI 1.29-3.59, p = 0.003) and repeat revascularization (HR 1.52, 95% CI 1.09-2.11, p = 0.013), but not for non-fatal myocardial infarction (HR 1.66, 95% CI 0.94-2.12, p = 0.081). Newly diagnosed diabetes was associated with an increased risk of 5-year MACE compared with non-diabetes and previously diagnosed diabetes in elderly patients underwent PCI. More attention should be given to those elderly newly diagnosed diabetes population., (© 2024. The Author(s).)

In traditional von Neumann computing architecture, the efficiency of the system is often hindered by the data transmission bottleneck between the processor and memory. A prevalent approach to mitigate this limitation is the use of non-volatile memory for in-memory computing, with spin-orbit torque (SOT) magnetic random-access memory (MRAM) being a leading area of research. In this study, we numerically demonstrate that a precise combination of damping-like and field-like spin-orbit torques can facilitate precessional magnetization switching. This mechanism enables the binary memristivity of magnetic tunnel junctions (MTJs) through the modulation of the amplitude and width of input current pulses. Building on this foundation, we have developed a scheme for a reconfigurable spintronic logic gate capable of directly implementing Boolean functions such as AND, OR, and XOR. This work is anticipated to leverage the sub-nanosecond dynamics of SOT-MRAM cells, potentially catalyzing further experimental developments in spintronic devices for in-memory computing., (© 2024. The Author(s).)

Network analysis provides an innovative approach to examining symptom-to-symptom interactions in mental health, and adverse external conditions may change the network structures. This study compared the networks of common risk factors and mental health problems (loneliness, depressive symptoms, and anxiety symptoms) in community-dwelling older people before and during COVID-19. Older adults (aged ≥ 60) at risk for depression were recruited through non-governmental organizations. Loneliness, depressive symptoms and anxiety symptoms were measured using the three-item Loneliness Scale (UCLA-3), nine-item Patient Health Questionnaire (PHQ-9), and seven-item Generalized Anxiety Disorder Scale (GAD-7), respectively. Data from 2549 (before) and 3506 (during COVID-19) respondents were included using propensity score matching. Being restless (GAD-7-item5) was most central, indicated by Expected Influence, in both pre and during COVID-19 networks despite low severity (mean score). The network during COVID-19 had higher global strength and edge variability than the pre-pandemic network, suggesting easier symptom spread and potentially more complex symptom presentation. In addition, feeling isolated from others (UCLA-3-item3) had stronger connections with feeling worthless/guilty (PHQ-9-item6) and anticipatory anxiety (GAD-7-item7) during COVID-19 than before. These findings may enhance our knowledge of the symptom structure of common mental health problems and the impacts of the pandemic. Targeting central symptoms may offer novel preventive strategies for older people., (© 2024. The Author(s).)