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The urban heat island (UHI) effect refers to how cities tend to be warmer than their non-urban surroundings, which increases the risk for heat-related illnesses and amplifies energy demands. Therefore, developing UHI mitigation strategies is crucial. Bengaluru, India has been rapidly urbanizing, but has yet to receive attention regarding potential UHI mitigation strategies. This work uses the Weather Research and Forecasting model with the single-layer urban canopy model to determine how UHI intensity changes in Bengaluru with perturbations of − 10%, + 10%, + 20%, and + 30% in vegetation amount since recent work has shown that vegetation amount is the leading control of urban heat in Bengaluru. These perturbations illustrate how much the UHI could be amplified by near-depletion of vegetation or mitigated via realistic increases in vegetation. The simulations were investigated diurnally and during the dry and wet seasons. Results show that increases in vegetation were associated with a decrease in urban land surface temperature, an increase in the latent heat flux, and decreases in the sensible heat flux, and vice versa for a decrease in vegetation. Significant changes in UHI intensity usually occurred only when vegetation was increased by 20% or more. However, for the dry season nighttime, which exhibited the highest UHI intensity in the control run (1.70oC), the 10% increase in vegetation produced a significant decrease of − 0.19oC in UHI intensity, likely due to a shallow planetary boundary layer height. These results could have implications for mitigating urban heat, and reducing energy demands and public health risk in Bengaluru. [ABSTRACT FROM AUTHOR]

The exploitation of high-performance third-order nonlinear optical (NLO) materials that have a favorable optical limit (OL) threshold is essential due to a rise in the application of ultra-intense lasers. In this study, a Cu-based MOF (denoted as Cu-bpy) was synthesized, and its third-order NLO and OL properties were investigated using the Z-scan technique with the nanosecond laser pulse excitation set at 532 nm. The Cu-bpy exhibits a typical rate of reverse saturable absorption (RSA) with a third-order nonlinear absorption coefficient of 100 cm GW−1 and a favorable OL threshold of 0.75 J cm−2 (at a concentration of 1.6 mg mL−1), which is lower than that of most NLO materials that have been reported on so far. In addition, a DFT calculation was performed and was in agreement with our experimental results. Furthermore, the mechanism of the third-order NLO properties was illustrated as one-photon absorption (1PA). These results investigate the relationship between the structure and the nonlinear optical properties of Cu-bpy, and provide an experimental and theoretical basis for its use in optical limiting applications. [ABSTRACT FROM AUTHOR]

The joint inversion of Rayleigh and Love waves plays a crucial role in mitigating the non‐uniqueness of surface wave inversion results and enhancing the stability of these inversions. Existing approaches to the joint inversion of Rayleigh and Love wave dispersion curves, which rely on conventional objective functions, often struggle with complex stratigraphic configurations and yield results of limited accuracy. This study introduces two novel nonlinear joint inversion techniques for Rayleigh and Love waves: Pearson correlation coefficient and thickness mean sharing. The Pearson correlation coefficient approach employs the Pearson correlation coefficient and alternating iterative objective functions to synchronize the shear wave velocity structures derived from Rayleigh and Love waves, thereby enhancing the accuracy of the joint inversion. Conversely, the thickness mean sharing method computes an average of the thickness values obtained in each iteration of the inversion, utilizing the traditional joint inversion objective function. Tests on three distinct stratigraphic structures—characterized by increasing velocity, high‐speed hard interlayers and low‐speed soft interlayers—as well as on measured data, demonstrate that the proposed methods significantly improve the stability and accuracy of nonlinear joint inversion. [ABSTRACT FROM AUTHOR]

The coupling electromechanical enriched finite element technique (CE-EFEM) is introduced to examine the statics characteristic of piezoelectric structures to properly solve the coupled multiphysical mechanics characteristic of these structures and lessen the complexity of meshing. A number of standard numerical examples are thought to demonstrate the exceptional efficacy of CE-EFEM, which is suggested as a solution for electromechanical coupling issues in piezoelectric structures. It is evident that the current CE-EFEM offers a bright future in piezoelectric device design, development, and performance analysis. [ABSTRACT FROM AUTHOR]

To improve the application depth and breadth of intelligent unit devices made from piezoelectric structures, their kinetic properties shall be urgently studied. Herein, based on the basic equations and boundary conditions of piezoelectric materials, an interpolation coverage function of node displacement was introduced into the displacement shape function and potential shape function of coupling electromechanical finite element method (FEM), forming an electromechanical coupling enriched FEM generalized shape function. Together with the variation principle, an electromechanical coupling enriched FEM was put forward, and its motion equations were deduced. Next, the free vibration and transient response of the piezoelectric structure were analyzed, and the accuracy and validity of the new method were validated with numerical cases. Results show this method has high application prospects for analyzing the dynamic properties of piezoelectric material structures. [ABSTRACT FROM AUTHOR]

Real-time online monitoring of track deformation during railway construction is crucial for ensuring the safe operation of trains. However, existing monitoring technologies struggle to effectively monitor both static and dynamic events, often resulting in high false alarm rates. This paper presents a monitoring technology for track deformation during railway construction based on dynamic Brillouin optical time-domain reflectometry (Dy-BOTDR), which effectively meets requirements in the monitoring of both static and dynamic events of track deformation. Dy-BOTDR can provide a two-dimensional spatial–temporal distribution map of track strain changes to characterize various events for better monitoring accuracy and lower false alarm rates. [ABSTRACT FROM AUTHOR]

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Autophagy is an important catabolic process to maintain cellular homeostasis and antagonize cellular stresses. The initiation and activation are two of the most important aspects of the autophagic process. This review focuses on mechanisms underlying autophagy initiation and activation and signaling pathways regulating the activation of autophagy found in recent years. These findings include autophagy initiation by liquid–liquid phase separation (LLPS), autophagy initiation in the endoplasmic reticulum (ER) and Golgi apparatus, and the signaling pathways mediated by the ULK1 complex, the mTOR complex, the AMPK complex, and the PI3KC3 complex. Through the review, we attempt to present current research progress in autophagy regulation and forward our understanding of the regulatory mechanisms and signaling pathways of autophagy initiation and activation. [ABSTRACT FROM AUTHOR]

The non-destructive harvesting of fresh tomatoes with agricultural robots requires the robotic arm to approach the fruit with the correct posture to ensure successful harvesting. However, this process faces significant challenges due to the small size of fruit pedicels, cluttered environments, and varied poses of the tomatoes and pedicels. Accurately identifying, localizing, and estimating the 6D spatial pose of the cutting points is critical for efficient and non-destructive harvesting. To address these challenges, we propose a keypoint-based pose estimation model, TomatoPoseNet, tailored to meet the agronomic requirements of tomato harvesting. The model integrates an efficient fusion block (EFBlock) based on the CSPLayer, referred to as the CSEFLayer, as the backbone network, designed to fuse multiscale features while maintaining efficient computational resource usage. Next, a parallel deep fusion network (PDFN) is utilized as the neck network to integrate features from multiple parallel branches. Furthermore, simple coordinate classification (SimCC) is employed as the head network for keypoint detection, and a StripPooling block is introduced to enhance the model's ability to capture features of different scales and shapes by applying strip pooling in horizontal and vertical directions. Finally, a geometric model is constructed based on the information about the predicted 3D keypoints to estimate the 6D pose of the cutting points. The results show the following: (1) The average precision for keypoint detection (PCK@0.05) reached 82.51%, surpassing those of ViTPose, HRNet, Lite-HRNet, Hourglass, and RTMPose by 3.78%, 9.46%, 11%, 9.14%, and 10.07%, respectively. (2) The mean absolute errors (MAEs) of the yaw and pitch angles for 6D pose estimation of the cutting points were 2.98° and 3.54°, respectively, with maximum errors within 6.5°, meeting the requirements for harvesting. The experimental results demonstrate that the proposed method can accurately locate the 6D pose of cutting points in an unstructured tomato harvesting environment, enabling non-destructive harvesting. [ABSTRACT FROM AUTHOR]

Solving mathematical story problems has proven to be a challenge for primary school students with and without developmental disabilities. The present study replicates a behavior analytic study (Neef et al.) by teaching three autistic Chinese students in inclusive education classes to solve addition/subtraction story problems by acquiring an overt precurrent behavior chain. The intervention was effective for all participants by employing a multiple baseline design across behaviors. Additionally, the study extends Neef et al. by conducting maintenance, generalization, and social validity assessments, and expands the teaching format to distance learning (telehealth). The results and limitations are discussed based on Skinner's conceptualization of problem‐solving and its clinical application in teaching complex mathematical skills to students with developmental disabilities. [ABSTRACT FROM AUTHOR]

The purpose of this study was to replicate previous research that examined the effects of tact and listener instruction on the emergence of bidirectional intraverbals, and to extend this research line to include teaching a foreign language to students with autism spectrum disorders (ASD) via telehealth. The study participants were four Chinese native primary school‐aged students. An adaptive alternative treatment design was used to compare the effects of tact and listener instruction on bidirectional intraverbals, and pre‐probe and post‐probe data demonstrated that both forms of instruction led to bidirectional intraverbal relations, with tact instruction being relatively more effective. Maintenance and social validity were assessed for all participants, and booster instructions were provided as needed. The results were discussed in the context of inclusive education and improving foreign language instruction for students with special needs. [ABSTRACT FROM AUTHOR]

The mechanic-electro coupling overlapping finite element method (OFEM) is proposed to improve the accuracy in solving the mechanical characteristics of piezoelectric structures. Based on the basic equations and boundary conditions of piezoelectric materials, overlapping triangle elements are used to discretize the solution domain of piezoelectric structures, and the displacement function and potential function of the mechanic-electro coupling OFEM are constructed through local interpolation. The control equation of the mechanic-electro coupling OFEM is derived using the variation principle. The accuracy and validity of this method are verified by comparing with the reference solution and analytical solution in patch test and piezoelectric patch bending test. The static characteristics of the cantilever-typed piezoelectric sensor model, the rectangular plate with one-sided piezoelectric patch configuration, and the hole-containing piezoelectric energy harvester model are analyzed. The mechanic-electro coupling OFEM has high engineering value and broad application prospects in analyzing the structural mechanical properties of intelligent piezoelectric components. [ABSTRACT FROM AUTHOR]

Featured Application: our proposed method can perform numerical simulations in the full wavenumber range and can be applied to forward simulations in anisotropic media while maintaining high accuracy. The staggered grid finite difference method has emerged as one of the most commonly used approaches in finite difference methodologies due to its high computational accuracy and stability. Inevitably, discretizing over time and space domains in finite difference methods leads to numerical artifacts. This paper introduces a novel approach that combines the widely used Taylor series expansion with the least squares method to effectively suppress numerical dispersion. We have derived the coefficients for the staggered grid finite difference method by integrating Taylor series expansions with the least squares method. To validate the effectiveness of our approach, we conducted analyses on accuracy, dispersion, and stability, alongside simple and complex numerical examples. The results indicate that our method not only inherits the capabilities of the original Taylor series and least squares methods in suppressing numerical dispersion across small and medium wavenumber ranges but also surpasses the original methods. Moreover, it demonstrates robust dispersion suppression capabilities at high wavenumber ranges. [ABSTRACT FROM AUTHOR]

In this paper, a novel 3300 V/40 A 4H-SiC junction barrier Schottky diode (JBS) with a multi-step separated trench (MST) structure is proposed and thoroughly investigated using TCAD simulations. The results show that the introduction of MST expands the Schottky contact area, resulting in a decrease in the forward voltage drop. Furthermore, the combination of the deep P+ shielded region and the central P+ region effectively reduces the leakage current, leading to a 43.7% increase in the blocking voltage compared to conventional 4H-SiC JBS. The effects of the step depth (ds) and the width of the central P+ region (wm) on the device performance are analyzed in depth. In addition, a multi-step trenched linearly graded field-limiting rings (MTLG-FLR) termination ensures a more uniform electric field distribution, and the terminal protection efficiency reaches up to 90%, which further enhances the reliability of the terminal structure. [ABSTRACT FROM AUTHOR]

Hermansky–Pudlak syndrome (HPS)-associated pulmonary fibrosis (HPS-PF) is a progressive lung disease that is a major cause of morbidity and mortality in HPS patients. Previous studies have demonstrated that the HPS proteins play an essential role in the biogenesis and function of lysosome-related organelles (LROs) in alveolar epithelial type II (AT2) cells and found that HPS-PF is associated with dysfunction of AT2 cells and abnormal immune reactions. Despite recent advances in research on HPS and the pathology of HPS-PF, the pathological mechanisms underlying HPS-PF remain poorly understood, and no effective treatment has been established. Therefore, it is necessary to refresh the progress in the pathogenesis of HPS-PF to increase our understanding of the pathogenic mechanism of HPS-PF and develop targeted therapeutic strategies. This review summarizes the recent progress in the pathogenesis of HPS-PF provides information about the current treatment strategies for HPS-PF, and hopefully increases our understanding of the pathogenesis of HPS-PF and offers thoughts for new therapeutic interventions. [ABSTRACT FROM AUTHOR]

The multichannel synthetic aperture radar (SAR) possesses the capability to acquire high-resolution, wide-swath SAR imagery, which has great potential for application. However, similar to traditional single-channel SAR systems, it suffers from imaging quality degradation due to motion errors. Many motion compensation algorithms have been used to improve the quality of single-channel SAR images, while fewer studies have been conducted on multichannel SAR motion compensation methods. The sub-image motion compensation method utilizes the single channel motion errors to perform multichannel motion errors compensation, considering that multiple channels have the same phase errors. To improve the quality of multichannel SAR imaging when multiple channel motion errors are inconsistent, this paper proposes a motion compensation method with multichannel phase correction for HRWS SAR. First, the method derives the phase errors estimation model via maximum sharpness to simultaneously estimate multichannel phase. Then, it compensates for the motion errors of all channels during backprojection imaging. The inconsistent motion errors of multiple channels can be compensated by estimating the phase errors of all channels, improving the image quality. The channel phase errors can be corrected while compensating for the motion errors. Moreover, the experimental results of point targets and complex scenes validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Magneto-electro-elastic (MEE) composites have promising application prospects due to the rapid response to the excitation of external electric or magnetic fields. Finite element simulation of the multi-physics coupling problems in MEE-based structures is significant. The enriched finite element method (EFEM) is derived from the standard finite element method (FEM), with finite element shape functions improved by interpolation covers. Considering the complex mechanical-electro-magnetic multi-physics coupling mechanism of MEE-based structures, the mechanical-electro-magnetic coupling enriched finite element method (MEM-EFEM) was proposed. The method is well worked for investigating the mechanical-electro-magnetic multi-physics coupling issues to calculate the generalized displacement (displacement components, electric and magnetic potential) with 3-node triangular elements. In a set of numerical experiments involving the static analysis of MEE-based structures, MEM-EFEM outperforms the regular FEM. When it comes to the same solution accuracy level, the number of elements used by MEM-EFEM is lower than that of the standard FEM, suggesting that MEM-EFEM has better convergence and accuracy on this subject. Besides, the MEM-EFEM solution accuracy can be enhanced by mesh refinement. Overall, the MEM-EFEM has the potential to be used in engineering practice to solve the static responses of MEE-based structures on mechanical-electro-magnetic multi-physics coupling issues. [ABSTRACT FROM AUTHOR]

Extreme rainfall can severely affect all vegetation types, significantly impacting crop yield and quality. This study aimed to assess the response and recovery of vegetation phenology to an extreme rainfall event (with total weekly rainfall exceeding 500 mm in several cities) in Henan Province, China, in 2021. The analysis utilized multi-sourced data, including remote sensing reflectance, meteorological, and crop yield data. First, the Normalized Difference Vegetation Index (NDVI) time series was calculated from reflectance data on the Google Earth Engine (GEE) platform. Next, the 'phenofit' R language package was used to extract the phenology parameters—the start of the growing season (SOS) and the end of the growing season (EOS). Finally, the Statistical Package for the Social Sciences (SPSS, v.26.0.0.0) software was used for Duncan's analysis, and Matrix Laboratory (MATLAB, v.R2022b) software was used to analyze the effects of rainfall on land surface phenology (LSP) and crop yield. The results showed the following. (1) The extreme rainfall event's impact on phenology manifested directly as a delay in EOS in the year of the event. In 2021, the EOS of the second growing season was delayed by 4.97 days for cropland, 15.54 days for forest, 13.06 days for grassland, and 12.49 days for shrubland. (2) Resistance was weak in 2021, but recovery reached in most areas by 2022 and slowed in 2023. (3) In each year, SOS was predominantly negatively correlated with total rainfall in July (64% of cropland area in the first growing season, 53% of grassland area, and 71% of shrubland area). In contrast, the EOS was predominantly positively correlated with rainfall (51% and 54% area of cropland in the first and second growing season, respectively, and 76% of shrubland area); however, crop yields were mainly negatively correlated with rainfall (71% for corn, 60% for beans) and decreased during the year of the event, with negative correlation coefficients between rainfall and yield (−0.02 for corn, −0.25 for beans). This work highlights the sensitivity of crops to extreme rainfall and underscores the need for further research on their long-term recovery. [ABSTRACT FROM AUTHOR]

Acidic microenvironments is a cancer progression driver, unclear core mechanism hinders the discovery of new diagnostic or therapeutic targets. ASIC3 is an extracellular proton sensor and acid-sensitive, but its role in acidic tumor microenvironment of colorectal cancer is not reported. Functional analysis data show that colorectal cancer cells respond to specific concentration of lactate to accelerate invasion and metastasis, and ASIC3 is the main actor in this process. Mechanism reveal de novo lipid synthesis is a regulatory process of ASIC3, down-regulated ASIC3 increases and interacts with ACC1 and SCD1, which are key enzymes in de novo lipid synthesis pathway, this interaction results in increased unsaturated fatty acids, which in turn induce EMT to promote metastasis, and overexpression of ASIC3 reduces acidic TME-enhanced colorectal cancer metastasis. Clinical samples of colorectal cancer also exhibit decreased ASIC3 expression, and low ASIC3 expression is associated with metastasis and stage of colorectal cancer. This study is the first to identify the role of the ASIC3-ACC1/SCD1 axis in acid-enhanced colorectal cancer metastasis. The expression pattern of ASIC3 in colorectal cancer differs significantly from that in other types of cancers, ASIC3 may serve as a novel and reliable marker for acidic microenvironmental in colorectal cancer, and potentially a therapeutic target. [ABSTRACT FROM AUTHOR]

Accurate mechanical analysis is essential for reliable utilization of piezoelectric composite materials (PCMs). Isogeometric analysis (IGA) of PCMs (termed PCMIGA) based on the asymptotic homogenization method (AHM) is presented in this study and employed to investigate the static mechanical characteristics of PCMs. PCMIGA provides accurate curve representation and shorter preprocessing time, and thus demonstrates both precision and efficiency. First, AHM is utilized to calculate the effective parameters of PCMs at different volume fractions. Next, these effective parameters are combined with the basic equations and boundary conditions of PCMs to derive equations of PCMIGA based on AHM. Finally, the results from several numerical examples are compared with the reference solution to validate the convergence and precision. PCMIGA is proven to be a reliable and accurate method for analyzing the mechanical properties of PCMs. [ABSTRACT FROM AUTHOR]

The traditional transmission line detection has the problems of low efficiency. To improve the performance, this paper proposes an improved you only look once version 5 (YOLOv5) transmission line foreign object detection algorithm. First, efficient channel attention (ECA) module is introduced in the backbone network for focusing the target features and improving the feature extraction capability of the network. Secondly, bilinear interpolation upsampling is introduced in the neck network to improve the model detection accuracy. Finally, by integrating the efficient intersection over union (EIoU) loss function and Soft non-maximum suppression (Soft NMS) algorithm, the convergence speed of the model is accelerated while the detection effect of the model is enhanced. Relative to the original algorithm, the improved algorithm reduces the number of parameters by 16.4%, increases the mean average precision (mAP)@0.5 by 3.9%, mAP@0.5: 0.95 by 6.3%, and increases the detection speed to 55.3 frames per second (FPS). The improved algorithm is able to improve the performance of the foreign object detection in transmission lines effectively. [ABSTRACT FROM AUTHOR]

The Ningbo Birth Cohort of Population Undergoing Assisted Reproductive Technology (NBart) is a study conducted in Ningbo, China, that examines the effects of assisted reproductive technology (ART) on pregnancy complications and children's health. The study recruited 11,954 couples undergoing ART treatment, resulting in 5,328 live births and 587 children followed for up to 6 years. Data was collected through questionnaires, physical examinations, medical records, and laboratory testing. The cohort data is available for researchers interested in the NBart data. The study aims to explore the relationship between ART interventions and pregnancy complications, assess factors affecting the growth and health of ART-conceived offspring, and examine the immune response of pregnant women who underwent ART. The study found that certain protocols and methods in ART treatment achieved comparable pregnancy rates, and correlations were found between sperm DNA fragmentation and various outcomes in ART treatment. The study also compared the incidence rates of pregnancy complications and perinatal outcomes between women who conceived via ART and those who conceived naturally. The NBart cohort has strengths such as a homogenous population and comprehensive health monitoring systems, but also weaknesses such as potential biases in cohort selection and limited long-term follow-up of ART offspring. Researchers interested in the NBart cohort can contact Lindan Ji for potential collaborations and access to the data. The study was approved by the Ningbo University Medical Science Research Ethics Committee. [Extracted from the article]

Acidic microenvironments is a cancer progression driver, unclear core mechanism hinders the discovery of new diagnostic or therapeutic targets. ASIC3 is an extracellular proton sensor and acid-sensitive, but its role in acidic tumor microenvironment of colorectal cancer is not reported. Functional analysis data show that colorectal cancer cells respond to specific concentration of lactate to accelerate invasion and metastasis, and ASIC3 is the main actor in this process. Mechanism reveal de novo lipid synthesis is a regulatory process of ASIC3, down-regulated ASIC3 increases and interacts with ACC1 and SCD1, which are key enzymes in de novo lipid synthesis pathway, this interaction results in increased unsaturated fatty acids, which in turn induce EMT to promote metastasis, and overexpression of ASIC3 reduces acidic TME-enhanced colorectal cancer metastasis. Clinical samples of colorectal cancer also exhibit decreased ASIC3 expression, and low ASIC3 expression is associated with metastasis and stage of colorectal cancer. This study is the first to identify the role of the ASIC3-ACC1/SCD1 axis in acid-enhanced colorectal cancer metastasis. The expression pattern of ASIC3 in colorectal cancer differs significantly from that in other types of cancers, ASIC3 may serve as a novel and reliable marker for acidic microenvironmental in colorectal cancer, and potentially a therapeutic target. [ABSTRACT FROM AUTHOR]

Surgical resection of glioblastoma multiforme (GBM) often results in tumor recurrence and mild neurologic deficits. Here, a 3D asynchronous drug delivery system is innovatively developed to address the dual challenges of GBM recurrence and postoperative neurological deficit. Based on transcriptome analysis of tumor cells and tumor microenvironment (TME) cells between primary and recurrent mouse GBM tissues, a novel dual‐targeting approach is developed to combine mTOR pathway inhibition with microglia/macrophage repolarization. Then, in situ injectable methacrylated gelatin (GelMA) is constructed to perfectly fit into the tumor resection cavity and achieve direct delivery of dual‐targeted drugs, exhibiting outstanding postoperative GBM inhibitory effects in vivo. At the same time, neurotrophic factor‐saturated 3D‐printed GelMA patches are used to construct a 3D asynchronous drug delivery system, allowing gradual penetration of the neurotrophic factors into the underlying hydrogel to promote axonal sprouting after GBM suppression. Notably, this 3D asynchronous drug delivery system promotes neurological recovery without weakening the efficacy of inhibiting tumor recurrence. Therefore, this study not only proposes a new dual‐targeted GBM treatment strategy but also pioneers the construction of a 3D asynchronous drug delivery system for the comprehensive treatment of GBM. This study is expected to improve the poor prognosis of patients with GBM. [ABSTRACT FROM AUTHOR]

An accurate prediction of the future service state of long-span bridges is crucial for the structural reliability evaluation, maintenance planning, and further life-cycle cost analysis. By extending the average conditional exceedance rate (ACER) statistical model and applying input–output data collected through a structural health monitoring (SHM) system, this paper proposes a novel methodology for predicting the future service state of long-span bridges. The advantages lie in the consideration of the main excitation load as the structural input and the strain response of the bridge as the output. Therefore, a mapping relationship between the extreme excitation load and extreme strain could be established, and the future service state of long-span bridges could be predicted. The proposed method comprises three steps: (1) extraction of the ambient temperature-induced strain and vehicle-induced strain from the measured strain series through the SHM system using the baseline estimation and denoising with sparsity (BEADS) method, (2) establishing statistical models of the extreme values of different excitations (input) and structural strains (output) using a cascade of conditioning approximations and the ACER to obtain the tail trend of the data and extrapolating it, and (3) establishing a functional relationship between the input and output extreme values based on the same conditions of the regression period at the target prediction level, after which the future service state of long-span bridges can be predicted. The proposed method is applied to a case study of the Jinchao Bridge in Guangdong Province, China, and the results are expected to provide a scientific reference for the design of new bridges and in the maintenance of existing ones in service. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) ranks among the most prevalent malignancies worldwide, characterized by its complex etiology and slow research progress. Diabetes, as an independent risk factor for CRC, has been widely certified. Consequently, this study centers on elucidating the intricacies of CRC cells initiation and progression within a high‐glucose environment. Methods: A battery of assays was employed to assess the proliferation and metastasis of CRC cells cultured under varying glucose concentrations. Optimal glucose levels conducive to cells' proliferation and migration were identified. Western blot analyses were conducted to evaluate alterations in apoptosis, autophagy, and EMT‐related proteins in CRC cells under high‐glucose conditions. The expression of PI3K/AKT/mTOR pathway‐associated proteins was assessed using western blot. The effect of high glucose on xenograft growth was investigated in vivo by MC38 cells, and changes in inflammatory factors (IL‐4, IL‐13, TNF‐α, IL‐5, and IL‐12) were measured via serum ELISA. Results: Our experiments demonstrated that elevated glucose concentrations promoted both the proliferation and migration of CRC cells; the most favorable glucose dose is 20 mM. Western blot analyses revealed a decrease in apoptotic proteins, such as Bim, Bax, and caspase‐3 with increasing glucose levels. Concurrently, the expression of EMT‐related proteins, including N‐cadherin, vimentin, ZEB1, and MMP9, increased. High‐glucose cultured cells exhibited elevated levels of PI3K/AKT/mTOR pathway proteins. In the xenograft model, tumor cells stimulated by high glucose exhibited accelerated growth, larger tumor volumes, and heightened KI67 expression of immunohistochemistry. ELISA experiments revealed higher expression of IL‐4 and IL‐13 and lower expression of TNF‐α and IL‐5 in the serum of high‐glucose‐stimulated mice. Conclusion: The most favorable dose and time for tumor cells proliferation and migration is 20 mM, 48 h. High glucose fosters CRC cell proliferation and migration while suppressing autophagy through the activation of the PI3K/AKT/mTOR pathway. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI), recognized as the world's most serious public health problem, currently lacks effective treatment options. The development of the patch has great clinical significance whether it is used as a skull implant material or TBI repair. In response to this critical health challenge, a novel 3D‐printed bi‐layer cranial‐brain patch (SMB6) with dual functionality, addressing both TBI repair and skull regeneration, is developed. In the first layer, the incorporation of high concentrations of mesoporous bioactive glass nanoparticles establishes a microenvironment for bone regeneration. Meanwhile, the second layer, comprised of methacrylated silk fibroin hydrogel, provides essential mechanical support for nanocell membrane vesicles loaded with macrophage colony‐stimulating factor and interleukin‐6. This innovative design aims to interrupt the cascade of secondary brain injury. In experimental models of TBI, SMB6 demonstrates remarkable efficacy in inhibiting brain edema, exerting therapeutic effects on blood vessels, nerves, and inflammation. Additionally, promising outcomes are observed in promoting bone regeneration in skull defect models. This work not only introduces a potential therapeutic patch for TBI‐related diseases but also provides novel insights for the clinical translation of cranial patches. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy and efficiency of piezoelectric structure design, the static mechanic-electric coupling of two-dimensional piezoelectric material problems are investigated by a cell-based smoothed isogeometric analysis (CS-IGA) in this work. The CS-IGA was developed on the basis of the isogeometric analysis by using strain smoothing technology. Based on the generalized Galerkin weak form and the constitutive equation of piezoelectric structures, the equilibrium equation of piezoelectric material in the problem of mechanic-electric coupling is obtained. For further improving the calculation precision of the algorithm, average strain is defined in the element domains. It completely avoids the gradient calculation of rational NURBS basis function in the stiffness matrix formula and further improves the computational efficiency. Besides, numerical example results can verify the precision, correctness and reliability of the proposed method in comparison with the finite element method in the analysis of piezoelectric material problems. Overall, this work can provide a help for analyzing the problems of piezoelectric structures. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) is the most recognized and leading mode of atmospheric variability observed over the Atlantic sector of the Northern Hemisphere, and its impacts on weather and climate over the North Atlantic and Eurasia via large-scale teleconnections have been extensively studied. Here we use a multidata synthesis approach to analyze surface and tropospheric variables from multiple long-term observational and reanalysis datasets to identify the NAO's footprint on interannual temperature variability over the vast but least-studied Sahara Desert during December–January–February–March for the satellite era (1979–2022) and century-long periods. Our results present evidence for a solid teleconnection pattern in surface and tropospheric temperatures associated with the NAO over the Sahara and document some major spatial–temporal and vertical characteristics of this pattern. It is found that the Saharan temperature anomalies are negatively correlated with the NAO index and this correlation is very strong, consistent, and statistically significant between different periods and across different datasets. The teleconnection is closely linked to large-scale circulation anomalies throughout the troposphere over the North Atlantic–Sahara sector, where the anomalous horizontal wind components and geopotential height exhibit opposite changes in sign with altitude from the lower to upper troposphere. During the negative NAO− (positive NAO+) phase, above-normal (below-normal) temperatures over the Sahara could be mainly explained by three major processes: (1) advection of climatological warm and moist (cold and dry) air over the North Atlantic (northern higher latitudes) by the anomalous southwesterly (northeasterly) flow in the lower troposphere; (2) advection of anomalous North Atlantic warm (cold) air by the climatological strong westerlies in the middle and upper troposphere; and (3) strengthened (weakened) vertical mixing in the atmospheric boundary layer. These results suggest that the NAO plays an important role in modulating the interannual temperature variability over the Sahara, and that this NAO footprint is mostly realized through horizontal temperature advection and vertical heat transfer by turbulent mixing. [ABSTRACT FROM AUTHOR]

The skin is constantly exposed to a range of environmental stressors, including ultraviolet (UV) radiation, which can cause damage to the skin. Repairing UV-damaged skin has been a major focus of research in recent years. The therapeutic potential of human umbilical cord mesenchymal stem cells (HUCMSCs) exhibits anti-photoaging properties. In this study, we developed a strategy for concentrating an HUCMSC supernatant, and examined the protective effects of CHS on UVB exposure in vitro and in vivo. Our results demonstrate that CHS repairs UVB exposure by promoting cell viability and migration and reducing senescent and apoptosis cells. We further found that the photoprotective effect of CHS is due to autophagy activation. Moreover, CHS reduces wrinkles and senescent cells, increases collagen expression, and improves immune function in UVB exposure-induced skin damage. In summary, our study provides a new approach for repairing cell damage, and suggests that CHS might be a potential candidate for preventing UVB-induced skin photodamage. [ABSTRACT FROM AUTHOR]

In the realm of high-speed precision broadcasting, the existing seeder opener proves inadequate for the speed of the seeding operation. We focus on the duckbill opener and employ the quadratic regression orthogonal rotation combination test design method to optimize the structural parameters of the opener. Throughout the experiment, the primary performance metrics encompassed the opener's working resistance and the side dumping distance. The selected experimental factors comprised the penetration angle, the angle of soil entry gap, the shovel body width, and the shovel length. The optimal arrangement of structural parameters has been determined: a penetration angle, a soil entry gap angle, a shovel body width of 21 mm, and a shovel length of 142 mm. These parameters contribute to increased velocity, reduced operational resistance, and minimal soil disturbance. Under this combination, the relative deviations between the recorded measurements and the theoretical outcomes for working resistance and the side dumping distance stand at 4.24% and 1.06%, respectively; these confirm the credibility of the optimization results. We performed adaptability testing and conducted a comparative analysis under various operational conditions to assess the innovative opener's ability to reduce force, minimize soil disruption, and maintain depth stability. The findings are as follows: At a depth of 5 cm and velocities ranging from 6 km/h to 8 km/h, an average working resistance reduction of 19.73%, a 5.64% decrease in the side dumping distance, and an average depth stability of 89.5% were observed. When operated at a speed of 7 km/h with a depth ranging from 3 cm to 5 cm, an average reduction of 19.66% in operational resistance, a 2.59% decrease in the side dumping distance, and an average depth stability of 91.1% were recorded. These results illustrate the innovative opener's capacity to significantly reduce working resistance and side dumping distance while satisfying the depth stability requisites. [ABSTRACT FROM AUTHOR]

Diabetes mellitus complicated with heart failure has high mortality and morbidity, but no reliable diagnoses and treatments are available. This study aimed to develop and verify a new model nomogram based on clinical parameters to predict diastolic cardiac dysfunction in patients with Type 2 diabetes mellitus (T2DM). 3030 patients with T2DM underwent Doppler echocardiography at the First Affiliated Hospital of Shenzhen University between January 2014 and December 2021. The patients were divided into the training dataset (n = 1701) and the verification dataset (n = 1329). In this study, a predictive diastolic cardiac dysfunction nomogram is developed using multivariable logical regression analysis, which contains the candidates selected in a minor absolute shrinkage and selection operator regression model. Discrimination in the prediction model was assessed using the area under the receiver operating characteristic curve (AUC-ROC). The calibration curve was applied to evaluate the calibration of the alignment nomogram, and the clinical decision curve was used to determine the clinical practicability of the alignment map. The verification dataset was used to evaluate the prediction model's performance. A multivariable model that included age, body mass index (BMI), triglyceride (TG), creatine phosphokinase isoenzyme (CK-MB), serum sodium (Na), and urinary albumin/creatinine ratio (UACR) was presented as the nomogram. We obtained the model for estimating diastolic cardiac dysfunction in patients with T2DM. The AUC-ROC of the training dataset in our model was 0.8307, with 95% CI of 0.8109–0.8505. Similar to the results obtained with the training dataset, the AUC-ROC of the verification dataset in our model was 0.8083, with 95% CI of 0.7843–0.8324, thus demonstrating robust. The function of the predictive model was as follows: Diastolic Dysfunction = −4.41303 + 0.14100*Age(year)+0.10491*BMI (kg/m2) +0.12902*TG (mmol/L) +0.03970*CK-MB (ng/mL) −0.03988*Na(mmol/L) +0.65395 * (UACR > 30 mg/g) + 1.10837 * (UACR > 300 mg/g). The calibration plot diagram of predicted probabilities against observed DCM rates indicated excellent concordance. Decision curve analysis demonstrated that the novel nomogram was clinically useful. Diastolic cardiac dysfunction in patients with T2DM can be predicted by clinical parameters. Our prediction model may represent an effective tool for large-scale epidemiological study of diastolic cardiac dysfunction in T2DM patients and provide a reliable method for early screening of T2DM patients with cardiac complications. This study used clinical parameters to predict diastolic cardiac dysfunction in patients with T2DM. This study established a nomogram for predicting diastolic cardiac dysfunction by multivariate logical regression analysis. Our predictive model can be used as an effective tool for large-scale epidemiological study of diastolic cardiac dysfunction in patients with T2DM and provides a reliable method for early screening of cardiac complications in patients with T2DM. [ABSTRACT FROM AUTHOR]

An efficient prediction of the extreme value of traffic loads is crucial for the structural design, reliability evaluation, maintenance planning, and further life-cycle cost analysis of bridges. In this work, a novel method is proposed for predicting the appropriate extreme traffic load distribution. Specifically, the average conditional exceedance rate (ACER) statistical model is estimated from the historical traffic loads which was collected through a weigh-in-motion system installed in toll stations. The basic idea of the ACER approach lies in the introduction of a cascade of conditioning approximations and the average exceedance rate to capture the dependence effects and obtain the data tail, the trend features of which are fitted with a similar Gumbel distribution function and extrapolated to the concerned level. An illustration case dealing with traffic loads using the ACER strategy is presented, the extreme value and confidence interval (CI) in any return period can be predicted by application of this approach. Furthermore, the peaks-over-threshold (POT) method based on the asymptotic extreme theory is also applied to illustrate the advantages of the ACER method. The ACER method has advantages in analyzing extreme traffic loads, with good robustness and the ability to handle extreme value prediction for different sampling strategies, it also can produce more accurate confidence intervals and predicts consistent extreme values. The study results are expected to help accurately determine traffic loads and ensure safety in bridge engineering. [ABSTRACT FROM AUTHOR]

The thermo-electro-mechanical coupling (TEMC) problem of the piezoelectric structure was analyzed. And the stabilized node-based smoothed radial point interpolation method (SNS-RPIM) was utilized during the computation. And the fundamental formulas were derived under thermo-mechanical load and the model of the problem was analyzed with triangular elements. The existence of thermal stress was taken into consideration. The dynamic behaviors for the TEMC problem were investigated by SNS-RPIM and finite element method (FEM) when different kinds of thermo-mechanical loadings were applied. The superiority of the proposed scheme for the TEMC problems was verified. The empirical constant was set to negative. Besides, the temperature rise can make the model softer and thermal load increase, which leads to a decrease of structural stiffness and natural frequency, thus, the displacement increases. [ABSTRACT FROM AUTHOR]

In response to the problem of bowl seedling detachment caused by the shaking of the transplanting machine in plant factories, this paper proposes a physical entity monitoring method for the digital twin (DT) plant factory transplanting system. The method is used to analyze the vibration signals of the transplanting machine under different operating conditions and explore the optimal working conditions. Firstly, a demand analysis for the physical entity of the DT plant factory transplanting system is conducted, focusing on practical applications. Then, an optimal deployment plan is designed based on the axiomatic design (AD) theory. Subsequently, a comparative analysis of the operating conditions of the plant factory transplanting equipment is carried out using data-driven approaches. Finally, the optimal working condition parameters are determined by comparing the modal vibration power spectral density of the transplanting equipment under different operating conditions. The results show that the maximum amplitude occurs in the Z-axis, with a magnitude of 2.1 m/s2. By comparing the cloud maps, it is evident that the vibration trends in the Z-axis and X-axis above the transplanting robotic arm are more pronounced compared to the Y-axis. This indicates that under the operating condition of transplanting 3000 plants per hour, a high transplanting efficiency can be maintained, and the vibration signals in the XYZ-axis above the transplanting robotic arm are relatively smooth, making them suitable for transplanting operations. This study combines digital twin technology to analyze the vibration signals of the plant factory transplanting machine under different operating conditions and explore the optimal working conditions. Compared to traditional monitoring platforms, this method facilitates the real-time visualization of different operating conditions of the transplanting machine in a virtual mapping, providing a more intuitive reflection of the equipment operation status. [ABSTRACT FROM AUTHOR]

On the background that the operating frequency of electronic devices tends to the radio frequency (RF) segment, a film bulk acoustic resonator (FBAR) filter is widely used in communication and military fields because of its advantages of high upper frequency, ample power capacity, small size, and low cost. However, the complex and harsh working environment puts higher requirements for packaging FBAR filters. Based on the Anand constitutive equation, the stress–strain response of the bonded ceramic package was studied by the finite element method for the FBAR filter-bonded ceramic package, and the thermal fatigue life of the device was predicted. We developed solder models with various spillage morphologies based on the random generation technique to examine the impact of spillage on device temperature reliability. The following are the primary conclusions: (1) Solder undergoes periodic deformation, stress, and strain changes throughout the cycle. (2) The corner of the contact surface between the chip and the solder layer has the largest stress at the end of the cycle, measuring 19.377 MPa. (3) The Engelmaier model predicts that the gadget will have a thermal fatigue life of 1928.67 h. (4) Expanding the layered solder area caused by any solder overflow mode may shorten the device's thermal fatigue life. The thermal fatigue life of a completely spilled solder is higher than that of a partially spilled solder. [ABSTRACT FROM AUTHOR]

External defects of kiwifruit seriously affect its added commercialization. To address the existing problems, kiwifruit external defects detection has a few methods for detecting multi-category defects and weak adaptability to complex images. In this study, we proposed ResNet combined with CBAM for the automatic detection of external defects in kiwifruit. The experiment first built an acquisition device to obtain high-quality images. The optimal fusion scheme of ResNet and CBAM was investigated, the network training parameters were optimized, and Adam was used to accelerate the convergence speed of the model. It was found that the average recognition accuracy of ResNet34 + CBAM for kiwifruit was 99.6%, and all evaluation metrics were greater than 99%. Meanwhile, the experiment selected AlexNet, VGG16, InceptionV3, ResNet34, and ResNet34 + CBAM for comparison. The results showed that the recognition accuracy of ResNet34 + CBAM was 7.9%, 12.7%, 11.8%, and 4.3% higher than that of AlexNet, VGG16, InceptionV3, and ResNet34, respectively. Therefore, it can be concluded that ResNet34 + CBAM has the advantages of high recognition accuracy and good stability for kiwifruit external defect sample detection. It provides a technical guarantee for online detection and sorting of kiwifruit and other fruit defects. [ABSTRACT FROM AUTHOR]

The Rh(III)‐catalyzed ortho alkylation of N‐pyridylcarbazoles with nitroalkenes has been developed, furnishing a wide range of 2‐(2‐nitroalkyl)carbazoles. Both aromatic and aliphatic nitroalkenes participated in this alkylation reaction successfully. This protocol also proceeded well with an indoline based substrate. Derivatization of the representative nitroalkane product was described. [ABSTRACT FROM AUTHOR]

Silicone rubber composites with good comprehensive properties modified with polyurethane were obtained through mixing and vulcanizing methods. Firstly, the polyurethane prepolymer with double bonds was prepared by polytetrahydrofuran glycol (PTMG, Mn = 1000), isophorone diisocyanate (IPDI), and 2-hydroxyethyl methacrylate (HEMA). The prepolymer was then added to the silicone rubber compounds to prepare silicone rubber composites, combining the excellent properties of polyurethane with the silicone rubber materials. The effects of polyurethane content on the mechanical properties, insulation, hydrophobicity, thermal stability, and flame retardancy of composites were studied in detail. The results showed that the silicone rubber composites not only have good hydrophobicity, thermal stability and flame retardant properties, but the addition of polyurethane significantly improves the tensile strength at room and low temperatures and the volume resistivity of the materials. The tensile strength increased by 32.5%, and the volume resistivity nearly doubled. The excellent electrical insulation, high hydrophobicity and good mechanical properties make the silicone rubber composites appropriate for use in the field of polymeric house arresters. [ABSTRACT FROM AUTHOR]

The two-dimensional porphyrin-based covalent organic framework (denoted by Tph-TDC-COF) was used as the sensitive layerto build an aptamer-based electrochemical sensor for the detection of Escherichia coli (E.coli). Tph-TDC-COF produced with 5,10,15,20-tetrakis(4-aminophenyl)-21H, 23H-porphine (Tph) and [2,2′-bithiophene]-2,5′-dicarbaldehyde (TDC) as building blocks exhibited a highly conjugated structure, outstanding conductivity, large specific surface area, and strong bioaffinity towards aptamers. The adoption of Tph-TDC-COF-modified electrode resulted in improved sensing performance and increased anchoring affinity toward the E.coli-targeted aptamer. Under optimal conditions, the Tph-TDC-COF-based electrochemical aptasensor demonstrated an extremely low detection limit of 0.17 CFU mL−1 for E.coli detection within a linear range of 10 to 1 × 108 CFU mL−1, accompanied by good stability, excellent reproducibility and regeneration ability, and wide practical applications. The current electrochemical aptasensing technique has the potential to be extended to detect different foodborne bacteria using specific aptamer, therefore widening the application of COFs in biosensing and food safety fields. [ABSTRACT FROM AUTHOR]

Object detection in remote sensing images (RSIs) has become crucial in recent years. However, researchers often prioritize detecting small objects, neglecting medium- to large-sized ones. Moreover, detecting objects hidden in shadows is challenging. Additionally, most detectors have extensive parameters, leading to higher hardware costs. To address these issues, this paper proposes a multi-scale and high-precision lightweight object detector named MHLDet. Firstly, we integrated the SimAM attention mechanism into the backbone and constructed a new feature-extraction module called validity-neat feature extract (VNFE). This module captures more feature information while simultaneously reducing the number of parameters. Secondly, we propose an improved spatial pyramid pooling model, named SPPE, to integrate multi-scale feature information better, enhancing the model to detect multi-scale objects. Finally, this paper introduces the convolution aggregation crosslayer (CACL) into the network. This module can reduce the size of the feature map and enhance the ability to fuse context information, thereby obtaining a feature map with more semantic information. We performed evaluation experiments on both the SIMD dataset and the UCAS-AOD dataset. Compared to other methods, our approach achieved the highest detection accuracy. Furthermore, it reduced the number of parameters by 12.7% compared to YOLOv7-Tiny. The experimental results illustrated that our proposed method is more lightweight and exhibits superior detection accuracy compared to other lightweight models. [ABSTRACT FROM AUTHOR]

In this paper, an optimal inspection model for three-dimensional structures under random loading is presented from the view of reliability. Neuber method and finite element analysis as well as experiential stress intensity factor (SIF) were applied in the analysis of fatigue life. Based on the series system theory, the reliability function for the structural fatigue life is given. Treat the crack initiation life (CIL) as service life and the crack propagation life (CPL) as inspection period, the optimal inspection period was obtained under a given reliability. The proposed method is proved to be feasible by a numerical example, which involves a bracket under random loading. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) image object detection has great application value in the military and civilian fields. However, the objects in the captured images from UAVs have problems of large-scale variation, complex backgrounds, and a large proportion of small objects. To resolve these problems, a multi-scale object detector based on coordinate and global information aggregation is proposed, named CGMDet. Firstly, a Coordinate and Global Information Aggregation Module (CGAM) is designed by aggregating local, coordinate, and global information, which can obtain features with richer context information. Secondly, a Feature Fusion Module (FFM) is proposed, which can better fuse features by learning the importance of different scale features and improve the representation ability of multi-scale features by reusing feature maps to help models better detect multi-scale objects. Moreover, more location information of low-level feature maps is integrated to improve the detection results of small targets. Furthermore, we modified the bounding box regression loss of the model to make the model more accurately regress the bounding box and faster convergence. Finally, we tested the CGMDet on VisDrone and UAVDT datasets. The proposed CGMDet improves mAP0.5 by 1.9% on the VisDrone dataset and 3.0% on the UAVDT dataset. [ABSTRACT FROM AUTHOR]

To address challenges such as the complex correlations among multiple parameters during the modeling process of plant factory transplanters, the large differences between simulations and actual models, and the difficulties in data acquisition and processing, this paper proposes the concept of a Plant Factory Transplanter (PFT) digital twin five-dimensional model based on research of plant factory transplanters. The PFT digital twin five-dimensional model builds on traditional 3D modeling and includes physical entities, virtual models, services, twin data, and connecting interactions. This study delves deeply into the connotations and construction methods of the PFT five-dimensional model from the five aspects of PFT physical entity, virtual entity, services, twin data, and connections, and illustrates the implementation steps and effects of each link. Finally, practical examples of the application of the PFT digital twin five-dimensional model are presented in actual scenarios. The five-dimensional modeling approach for plant factory transplanters based on digital twins can monitor the working status of transplanters online and evaluate the effectiveness of transplantation. This method overcomes problems such as poor adaptability and difficulty in updating physical models, thus improving the efficiency of monitoring and optimizing configuration parameters. Moreover, the generated virtual entities are more intuitively reflected in the control interface, significantly reducing the reliance of equipment operators on relevant professional skills. In the future, the proposed digital twin five-dimensional model is expected to be further refined and optimized, with creation tools and application scenarios studied. Application research will also be conducted to meet different application requirements. [ABSTRACT FROM AUTHOR]