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Objective: Little progress has been made in recent years using first-line chemotherapy, including gemcitabine combined with nab-paclitaxel, FOLFIRINOX, and NALIRIFOX, for advanced pancreatic adenocarcinoma (APC). In addition, the optimal second-line chemotherapy regimen has not been determined. This study aimed to compare the effectiveness of different types of second-line chemotherapy for APC. Methods: Patients with APC who received first-line treatment from January 2008 to January 2021 were considered eligible for this retrospective analysis. The primary and secondary endpoints were overall survival (OS) and progression-free survival (PFS), respectively. Results: Four hundred and thirty-seven and 617 patients were treated with 5-fluorouracil- and gemcitabine-based chemotherapy as first-line treatment, respectively. Demographic and clinical features, except age and liver metastasis, were comparable between the two groups (P < 0.05). The median OS was 8.8 and 7.8 months in patients who received a 5-fluorouracil- and gemcitabine-based combined regimen for first-line therapy, respectively (HR = 1.244, 95% CI = 1.090–1.419; P < 0.001). The median OS was 5.6 and 1.9 months in patients who received second-line chemotherapy and supportive care, respectively (HR = 0.766, 95% CI = 0.677–0.867; P < 0.001). The median PFS was not significantly differently between gemcitabine or 5-fluorouracil monotherapy and combination therapy. Conclusions: A 5-fluorouracil- or gemcitabine-based combined regimen was shown to be as effective as a single 5-fluorouracil or gemcitabine regimen as second-line therapy for patients with APC.

Background Triple-negative breast cancer (TNBC) is a highly aggressive form of breast cancer. Due to its lack of targeted therapy options, TNBC remains a significant clinical challenge. In this study, we investigated the role of nuclear respiratory factor 3 (NRF3) and high-mobility group box 1 (HMGB1) in the progression of TNBC.Methods The study analyzed NRF3’s clinical expression, differentially expressed genes (DEGs), and immune infiltration in TNBC using the TCGA database and bioinformatics tools. Cellular functions of MDA-MB-468 and Hs578t cells were evaluated through MTT, colony formation, transwell, flow cytometry, and western blotting. The regulatory function of NRF3 in TNBC cell lines was assessed using Immunofluorescence, Immunohistochemistry, qRT-PCR, CHIP, luciferase assay, and ELISA. Moreover, a xenograft model was established to investigate the role of NRF3 in TNBC in vivo.Results Low expression of NRF3 in TNBC tumors was associated with unfavorable prognosis and transcripts from tumors with higher NRF3 levels were enriched in oxidative stress and immune-related pathways. The subsequent gain- and loss-functional experiments indicated that NRF3 overexpression significantly suppressed malignant phenotypes, MAPK/ERK signaling pathways, and epithelial-mesenchymal transition (EMT), whereas it promoted reactive oxygen species (ROS) levels in TNBC. Further mechanistic exploration showed that NRF3 inhibited TNBC cell function by regulating oxidative stress-related genes to inhibit the MAPK/ERK signaling pathway by promoting the release of HMGB1 via ROS, thereby promoting M1 macrophage polarization.Conclusion NRF3 promotes M1 macrophage polarization through the ROS/HMGB1 axis, thereby inhibiting the malignant progression of TNBC. It is expected to become a therapeutic biomarker for TNBC.

Oncolytic viruses (OVs), a group of replication-competent viruses that can selectively infect and kill cancer cells while leaving healthy cells intact, are emerging as promising living anticancer agents. Unlike traditional drugs composed of non-replicating compounds or biomolecules, the replicative nature of viruses confer unique pharmacokinetic properties that require further studies. Despite some pharmacokinetics studies of OVs, mechanistic insights into the connection between OV pharmacokinetics and antitumor efficacy remain vague. Here, we characterized the pharmacokinetic profile of oncolytic virus M1 (OVM) in immunocompetent mouse tumor models and identified the JAK‒STAT pathway as a key modulator of OVM pharmacokinetics. By suppressing the JAK‒STAT pathway, early OVM pharmacokinetics are ameliorated, leading to enhanced tumor-specific viral accumulation, increased AUC and Cmax, and improved antitumor efficacy. Rather than compromising antitumor immunity after JAK‒STAT inhibition, the improved pharmacokinetics of OVM promotes T cell recruitment and activation in the tumor microenvironment, providing an optimal opportunity for the therapeutic outcome of immune checkpoint blockade, such as anti-PD-L1. Taken together, this study advances our understanding of the pharmacokinetic-pharmacodynamic relationship in OV therapy.

In unstructured environments, dense grape fruit growth and the presence of occlusion cause difficult recognition problems, which will seriously affect the performance of grape picking robots. To address these problems, this study improves the YOLOX-Tiny model and proposes a new grape detection model, YOLOX-RA, which can quickly and accurately identify densely growing and occluded grape bunches. The proposed YOLOX-RA model uses a 3 × 3 convolutional layer with a step size of 2 to replace the focal layer to reduce the computational burden. The CBS layer in the ResBlock_Body module of the second, third, and fourth layers of the backbone layer is removed, and the CSPLayer module is replaced by the ResBlock-M module to speed up the detection. An auxiliary network (AlNet) with the remaining network blocks was added after the ResBlock-M module to improve the detection accuracy. Two depth-separable convolutions (DSC) are used in the neck module layer to replace the normal convolution to reduce the computational cost. We evaluated the detection performance of SSD, YOLOv4 SSD, YOLOv4-Tiny, YOLO-Grape, YOLOv5-X, YOLOX-Tiny, and YOLOX-RA on a grape test set. The results show that the YOLOX-RA model has the best detection performance, achieving 88.75 % mAP, a recognition speed of 84.88 FPS, and model size of 17.53 MB. It can accurately detect densely grown and shaded grape bunches, which can effectively improve the performance of the grape picking robot.

An 8-week feeding trial was performed on Larimichthys crocea (initial body weight: 19.28 ± 1.85 g) to investigate the impact of replacing fish meal (FM) by chicken liver meal (CLM) on various aspects including growth performance, intestinal health and microflora, antioxidant capacity as well as protein metabolism. Five diets were formulated with different levels of FM replacement by CLM: 0 % (CLM0), 25 % (CLM25), 50 % (CLM50), 75 % (CLM75), and 100 % (CLM100). Results indicated that substituting 50 % of the dietary FM with CLM did not significantly affect growth performance and feed utilization. Analysis of intestinal structure revealed a considerable decrease in villus width (VW) and villus height (VH) in CLM75 and CLM100 groups. The CLM75 and CLM100 diets led to a significant decrease in the activity of amylase (AMS), lipase (LPS), catalase (CAT) as well as total antioxidant capacity (T-AOC) for liver of Larimichthys crocea, while remarkably increasing malondialdehyde (MDA) content. 16S rRNA sequencing revealed that CLM75 and CLM100 diets resulted in increased relative abundances of Proteobacteria phylum and decreased relative abundances of Firmicutes phylum. Moreover, immunoblotting analysis demonstrated that CLM75 and CLM100 diets also caused a significant decrease in the phosphorylation level of 4E-binding protein 1 (4E-BP1) in muscle of Larimichthys crocea. Based on these findings, without negatively altering Larimichthys crocea growth and gut health, CLM can substitute up to 50 % dietary FM.

The working temperature is one of the key factors affecting the efficiency and safety performance of automotive power batteries. Current battery pack design primarily focuses on single layout configurations, overlooking the potential impact of mixed arrangements on thermal management performance. This study presents a module-based optimization methodology for comprehensive concept design of Lithium-ion (Li-ion) battery pack. Firstly, the arrangement modules is optimized and performed using particle swarm optimization algorithms considering various arrangement layout (i.e. rectangular, diamond, and staggered arrangements) by taking the intercell spacing and maximum temperature of the modules as design objectives. Secondly, the battery pack configuration design is performed employing a neural network model reflect diverse battery module configurations within the pack, exploring their impact on thermal management performance. The hybrid battery arrangement effectively improves thermal management, and the module spacing helps to enhance heat dissipation. The staggered arrangement has a greater impact on the heat dissipation performance of the battery pack, but the spacing between different modules varies with the position of the modules. When all configuration schemes are staggered modules, the optimal range of the spacing between modules is between 6 and 7 mm. However, the study observes a non-linear relationship between module spacing and the maximum temperature difference within the battery pack. While increasing module spacing initially decreases temperature differences, it eventually reverses, suggesting that spacing alone may not consistently enhance thermal management. Validation with a lithium-ion battery pack case study demonstrates the method’s effectiveness, providing valuable knowledge for future cell and pack designs that employ different battery cell arrangements and diverse cooling strategies.

In precision feeding, non-contact and pressure-free monitoring of sheep feeding behavior is crucial for health monitoring and optimizing production management. The experimental conditions and real-world environments differ when using acoustic sensors to identify sheep feeding behaviors, leading to discrepancies and consequently posing challenges for achieving high-accuracy classification in complex production environments. This study enhances the classification performance by integrating the deep spectrogram features and acoustic characteristics associated with feeding behavior. We conducted the task of collecting sound data in actual production environments, considering noise and complex surroundings. The method included evaluating and filtering the optimal acoustic features, utilizing a customized convolutional neural network (SheepVGG-Lite) to extract Short-Time Fourier Transform (STFT) spectrograms and Constant Q Transform (CQT) spectrograms’ deep features, employing cross-spectrogram feature fusion and assessing classification performance through a support vector machine (SVM). Results indicate that the fusion of cross-spectral features significantly improved classification performance, achieving a classification accuracy of 96.47%. These findings highlight the value of integrating acoustic features with spectrogram deep features for accurately recognizing sheep feeding behavior.

The immune response plays a crucial role in the functionality of oncolytic viruses. In this study, Albendazole, an antihelminthic drug known to modulate the immune checkpoint PD-L1, was combined with the oncolytic virus M1 (OVM1) to treat mice with either prostate cancer (RM-1) or glioma (GL261) tumors. This combination therapy enhanced anti-tumor effects in immunocompetent mice, but not in immunodeficient ones, without increasing OVM1 replication. Instead, it led to an increase in the number of CD8+ T cells within the tumor, downregulated the expression of PD1 on CD8+ T cells, and upregulated activation markers such as Ki67, CD44, and CD69 and the secretion of cytotoxic factors including interferon (IFN)-γ, granzyme B, and tumor necrosis factor (TNF)-α. Consistently, it enhanced the in vitro tumor-killing activity of lymphocytes from tumor-draining lymph nodes or spleens. The synergistic effect of Albendazole on OVM1 was abolished by depleting CD8+ T cells, suggesting a CD8+ T cell-dependent mechanism. In addition, Albendazole and OVM1 therapy increased CTLA4 expression in the spleen, and the addition of CTLA4 antibodies further enhanced the anti-tumor efficacy in vivo. In summary, Albendazole can act synergistically with oncolytic viruses via CD8+ T cell activation, and the Albendazole/OVM1 combination can overcome resistance to CTLA4-based immune checkpoint blockade therapy.

Abstract Although Dynamic Movement Primitives (DMP) is an effective tool for robotic arm trajectory generalisation, the application of DMP in the 3C (Computer, Communication, Consumer Electronics) industry still faces challenges such as low precision and high‐time consumption. To address this problem, we propose a novel Cauchy DMP framework. The main improvements and advantages of Cauchy DMP, compared to the original DMP, are (1) since the Cauchy distribution has a simpler model and wider shape, using the Cauchy distribution instead of the Gaussian distribution in the original DMP reduces the complexity of the algorithm and saves time. (2) Singular Value Decomposition (SVD) can effectively model the error. To reduce the interference of the rounding and human error on the trajectory, SVD can be used to obtain the weight of each basis function. The proposed Cauchy DMP framework combines the above two points and is validated on a real UR5 robotic arm. The results show that Cauchy DMP retains the learnability of the original DMP and has the advantages of short time consumption and low error rate.

Introduction: The aim of this study is to understand nephrology medical staff’s awareness of, basic knowledge of, practical ability of, and the barriers to palliative kidney care to patients on maintenance hemodialysis (HD) in mainland China. Methods: This cross-sectional descriptive study employed convenience sampling of medical staff (physicians and nurses) working in nephrology departments in mainland China. Independent predictors of self-assessment ability for palliative care (PC) were determined using multivariate binary logistic regression. Results: Responses were received from medical staff in 28 provinces and 657 questionnaires were analyzed. Among the participants, 53.1% (349/657) were doctors, and only 4.3% claimed to be confident in providing PC to patients on HD. The average score of self-assessing ability for PC was 2.65 ± 1.15 (range 1–5). Among the 580 participants who experienced patient withdrawal from dialysis, only 16.0% reported that their patients had well-planned withdrawal from dialysis. Male (odds ratio [OR] [95% confidence interval [CI], 0.585 [0.34–0.99], P = 0.048), nurse (OR [95% CI], 1.81 [1.01–3.27], P = 0.047), more experience in dealing with deceased cases (OR [95% CI], 1.28 [1.02–1.61], P = 0.034), less experience of medical disputes before/after withdrawal from dialysis (OR [95% CI], 0.62 [0.40–0.98], P = 0.041), and PC training experiences (OR [95% CI], 2.33 [1.86–2.91], P < 0.001) were independently correlated with significant better self-assessing ability for PC. Conclusion: This study demonstrates that the nephrology medical staff had a positive attitude but lacked relative knowledge and training in PC. Institutionalized education, training models, practice guidelines for kidney PC, and guidelines for well-planned withdrawal from dialysis according to cultural background are urgently needed in mainland China.

Climate change is one of the most pressing challenges facing the world today. The large amount of greenhouse gas emissions produced by human activities, especially the emission of carbon dioxide, is an important driving factor behind climate issues. Under the background of China’s “3060” decarbonization goal”, Chongming District in Shanghai is actively promoting the construction of a world-class ecological island and is committed to creating a carbon–neutral demonstration zone with global influence. However, Chongming District faces challenges as the mechanism of carbon-neutrality transition path remains unclear. The data related to evaluating carbon neutrality status are heterogeneous from multiple sources. It is difficult to effectively implement relevant evaluation and response measures, impeding the progress of its low-carbon transformation. In response to the aforementioned challenges, this paper will propose and discuss the potential methods based on the new generation of information technology, represented by big data and artificial intelligence. These technologies aim to facilitate the integration of diverse factors, including carbon, and explore the nexus among them, thus exploring pathways for low-carbon transformation, and ultimately achieving decarbonization goal in Chongming District. Hopefully, the research conducted in this paper will contribute to the efforts of China and the global community in addressing carbon-related challenges and advancing towards a more sustainable and low-carbon future.

Abstract The buffer layer defects of high‐voltage crosslinked polyethylene (XLPE) cable occur frequently, which makes the detection method become the focus to be studied. Here, the broadband impedance detection technology for the buffer layer defects of high‐voltage XLPE cables with corrugated aluminium sheath is investigated. There are nine cable samples, including new and defective ones. Some of the defective cables are artificial, and the other is retired cables. The influence of wiring mode, the circumferential relative position of electrodes, cable length, artificial white powder, artificial damp, and retired defective cables on the impedance spectrum is studied. It is found that the wiring mode of the insulation shield/aluminium sheath at the end of the cable can effectively detect the buffer layer defects. And the broadband impedance amplitude spectrum of the buffer layer in defective cable, measuring at various circumferential relative positions, is obviously different. When there are white powders, air gaps, or ablation in the buffer layer, the broadband impedance spectrum (BIS) will increase by several times. When the buffer layer is damped, the BIS will reduce. The research here provides theoretical support and technical methods for the buffer layer defects of XLPE cable with corrugated aluminium sheath.

Photovoltaic power generation and energy storage technology are current hotspots in the clean energy industry. As a core piece of equipment, an inverter is subjected to higher demands for its voltage regulation range and output performance. A differential boost inverter features a boosting function not found in traditional inverters, effectively widening the input voltage range, with characteristics of a single-stage structure and simple modulation. However, the differential boost inverter faces the issue of high common-mode voltage. Considering that the magnitude of the common-mode voltage changes with different modulation methods, a novel modulation strategy with a flexible common-mode voltage is proposed, which can effectively suppress the common-mode voltage under the same gain without affecting the output power quality. This article first introduces the topology, working principle, and traditional modulation methods of the differential boost inverter. Then, the new modulation strategy is defined, and the gain equation is derived. The new modulation method’s applicable scenarios are discussed and compared to other modulation methods based on the gain curve, concluding that the new method has advantages in terms of common-mode voltage amplitude and power quality under low boost gain. Finally, the effectiveness of the proposed method is verified through simulation and experiments.

Abstract The crystal plasticity finite element method (CPFEM) is widely used to explore the microscopic mechanical behavior of materials and understand the deformation mechanism at the grain-level. However, few CPFEM simulation studies have been carried out to analyze the nanoindentation deformation mechanism of polycrystalline materials at the microscale level. In this study, a three-dimensional CPFEM-based nanoindentation simulation is performed on an Inconel 718 polycrystalline material to examine the influence of different crystallographic parameters on nanoindentation behavior. A representative volume element model is developed to calibrate the crystal plastic constitutive parameters by comparing the stress-strain data with the experimental results. The indentation force-displacement curves, stress distributions, and pile-up patterns are obtained by CPFEM simulation. The results show that the crystallographic orientation and grain boundary have little influence on the force-displacement curves of the nanoindentation, but significantly influence the local stress distributions and shape of the pile-up patterns. As the difference in crystallographic orientation between grains increases, changes in the pile-up patterns and stress distributions caused by this effect become more significant. In addition, the simulation results reveal that the existence of grain boundaries affects the continuity of the stress distribution. The obstruction on the continuity of stress distribution increases as the grain boundary angle increases. This research demonstrates that the proposed CPFEM model can well describe the microscopic compressive deformation behaviors of Inconel 718 under nanoindentation.

Design solution space (DSS) exploration is a pivotal process for comprehending design challenges and identifying diverse solution alternatives based on varying requirements. Computer-aided design (CAD) approaches, such as parametric design, knowledge-based design, and generative design, have proven successful in DSS exploration. However, a comparative study evaluating their performance is lacking in the technical literature. This paper addresses this gap by conducting a comparative analysis of these approaches regarding their performance in exploring DSS. The research begins by providing an overview of parametric design, knowledge-based design, and generative design, establishing the foundation for the study. Six evaluation criteria are identified based on the DSS exploration process. A qualitative analysis is then conducted, considering these criteria, to objectively assess the performance of each modeling approach. The results highlight the strengths and weaknesses of each approach, revealing that DSS exploration success is directly tied to the quantity of implemented knowledge. The results also emphasize the complementarity of those approaches, as their strengths and weaknesses are based on different problem-solving logics, demonstrating the synergy that can be achieved through strategic combinations of them. Additionally, the paper discusses open issues related to DSS exploration, contributing valuable insights for future developments in this field.

Ferroelectric ceramics have the potential to be widely applied in the modern industry and military power systems due to their ultrafast charging/discharging speed and high energy density. Considering the structural design and electrical properties of ferroelectric capacitor, it is still a challenge to find out the optimal energy storage of ferroelectric ceramics during the phase-transition process of amorphous/nanocrystalline and polycrystalline. In this work, a finite element model suitable for the multiphase ceramic system is constructed based on the phase field breakdown theory. The nonlinear coupling relationship of multiple physical fields between multiphase ceramics was taken into account in this model. The basic structures of multiphase ceramics are generated by using the Voronoi diagram construction method. The specified structure of multiphase ceramics in the phase-transition process of amorphous/nanocrystalline and polycrystalline was further obtained through the grain boundary diffusion equation. The simulation results show that the multiphase ceramics have an optimal energy storage in the process of amorphous polycrystalline transformation, and the energy storage density reaches the maximum when the crystallinity is 13.96% and the volume fraction of grain is 2.08%. It provides a research plan and idea for revealing the correlation between microstructure and breakdown characteristics of multiphase ceramics. This simulation model realizes the nonlinear coupling of the multiphase ceramic mesoscopic structure and the phase field breakdown. It provides a reference scheme for the structural design and performance optimization of ferroelectric ceramics.

Abstract Exploring the microhabitat determinants of organisms distribution and functional traits differences can help us better understand the importance of intraspecific variations in ecological niches. Investigations on animals functional niche primarily focused on differences among species and tended to neglect the potential variability within species, despite the fact that the ecological and evolutionary importance of intraspecific variations was widely recognized. In this study, we examined the influence of microhabitat features on the intraspecific variability of the distribution and functional traits of a highest elevational distributed lizard species Phrynocephalus erythrurus. To do so, field work was conducted between July and August, 2020 and August and September, 2021 in Namtso watershed in central Xizang, China. Specifically, 11 transects were sampled for P. erythrurus individuals, which were measured for a set of 10 morphological traits. Moreover, 11 microhabitat variables that potentially affect the distribution of lizards were also measured for each transect. Our results indicated that juveniles, males, and females exhibited different functional traits, allowing them to occupy distinct functional space. The distribution of juveniles, males, and females was determined by different microhabitat variables such as illuminance and air temperature. More importantly, these variables also determined the intraspecific functional traits variability in this lizard species. All of these results supported previous claims that intraspecific traits variation should be incorporated into functional ecological studies, and diverse microhabitat features should be conserved to maintain high intraspecific diversity. Future studies can focus on the food analysis to explore the linkage between functional traits and resources utilization within animal populations.

Water use efficiency (WUE) is commonly expressed as the ratio of gross primary productivity (GPP) to evapotranspiration (ET) and reflects the integrated impacts of water, energy, and carbon cycles on ecosystem processes. Understanding the spatiotemporal variations of WUE in the Qinling–Daba Mountains and its influencing factors will contribute to identifying the characteristics of the carbon and water cycles in Qinling–Daba Mountains within the context of climate change. This study analyzed spatiotemporal variations of WUE, GPP to transpiration ratio (GPP/T), transpiration to ET ratio (T/ET), soil moisture (SM), leaf area index (LAI), and vapor pressure deficit (VPD) in the Qinling–Daba Mountains and explored the dominant factors influencing changes in WUE. The study produced several interesting results: (1) The Distance between Indices of Simulation and Observation for the PML-GPP, PML-ET, SMCI, and MOD15A2H datasets are 0.89, 0.87, 1.22, and 1.02, respectively. Hence, they most accurately represent the conditions of GPP, ET, SM, and LAI in the Qinling-Daba Mountains, respectively. (2) GPP/T and WUE show similar spatiotemporal trends, unlike T/ET, which differs significantly. (3) At the regional scale, the contribution rate of the increase in GPP/T and the decrease in T/ET to the increase and decrease in WUE are 74.5 % and 106.83 %, respectively. At both regional and pixel scales, the increase in GPP/T and the decrease in T/ET respectively dominate the increase and decrease in WUE. (4) The increase in LAI, decrease in VPD, and increase in SM indirectly dominate the increase in WUE by controlling the increase in GPP/T at altitudes below 1000 m, between 1000 and 2700 m, and above 2700 m, respectively. The decrease in LAI indirectly dominates the decrease in WUE by controlling the decrease in T/ET at different altitude ranges. The interactions between meteorological and vegetation factors constrain WUE variations in the Qinling-Daba Mountains.

Abstract Oncolytic viruses (OVs) represent a type of encouraging multi-mechanistic drug for the treatment of cancer. However, attenuation of virulence, which is generally required for the development of OVs based on pathogenic viral backbones, is frequently accompanied by a compromised killing effect on tumor cells. By exploiting the property of viruses to evolve and adapt in cancer cells, we perform directed natural evolution on refractory colorectal cancer cell HCT-116 and generate a next-generation oncolytic virus M1 (NGOVM) with an increase in the oncolytic effect of up to 9690-fold. The NGOVM has a broader antitumor spectrum and a more robust oncolytic effect in a range of solid tumors. Mechanistically, two critical mutations are identified in the E2 and nsP3 genes, which accelerate the entry of M1 virus by increasing its binding to the Mxra8 receptor and antagonize antiviral responses by inhibiting the activation of PKR and STAT1 in tumor cells, respectively. Importantly, the NGOVM is well tolerated in both rodents and nonhuman primates. This study implies that directed natural evolution is a generalizable approach for developing next-generation OVs with an expanded scope of application and high safety.

Traditional visual detection methods that employ image data are often unstable due to environmental influences like lighting conditions. However, microfiber spectrometers are capable of capturing the specific wavelength characteristics of tail coal suspensions, effectively circumventing the instability caused by lighting variations. Utilizing spectral analysis techniques for detecting ash content in tail coal appears promising as a more stable method of indirect ash detection. In this context, this paper proposes a rapid detection method for the coal ash content in tailings suspensions based on absorption spectra and deep feature extraction. Initially, a preprocessing method, the inverse time weight function (ITWF), is presented, focusing on the intrinsic connection between the sedimentation phenomena of samples. This enables the model to learn and retain spectral time memory features, thereby enhancing its analytical capabilities. To better capture the spectral characteristics of tail coal suspensions, we designed the DSFN (DeepSpectraFusionNet) model. This model has an MSCR (multi-scale convolutional residual) module, addressing the conventional models’ oversight of the strong correlation between adjacent wavelengths in the spectrum. This facilitates the extraction of relative positional information. Additionally, to uncover potential temporal relationships in sedimentation, we propose a CLSM-CS (convolutional long-short memory with candidate states) module, designed to strengthen the capturing of local information and sequential memory. Ultimately, the method employs a fused convolutional deep classifier to integrate and reconstruct both temporal memory and positional features. This results in a model that effectively correlates the ash content of suspensions with their absorption spectral characteristics. Experimental results confirmed that the proposed model achieved an accuracy of 80.65%, an F1-score of 80.45%, a precision of 83.43%, and a recall of 80.65%. These results outperformed recent coal recognition models and classical temporal models, meeting the high standards required for industrial on-site ash detection tasks.

Underwater vision technology is crucial for marine exploration, aquaculture, and environmental monitoring. However, the challenging underwater conditions, including light attenuation, color distortion, reduced contrast, and blurring, pose difficulties. Current deep learning models and traditional image enhancement techniques are limited in addressing these challenges, making it challenging to acquire high-quality underwater image signals. To overcome these limitations, this study proposes an approach called adaptive multi-scale multi-color space underwater image enhancement with GAN-physics fusion (AMSMC-UGAN). AMSMC-UGAN leverages multiple color spaces (RGB, HSV, and Lab) for feature extraction, compensating for RGB’s limitations in underwater environments and enhancing the use of image information. By integrating a membership degree function to guide deep learning based on physical models, the model’s performance is improved across different underwater scenes. In addition, the introduction of a multi-scale feature extraction module deepens the granularity of image information, learns the degradation distribution of different image information of the same image content more comprehensively, and provides useful guidance for more comprehensive data for image enhancement. AMSMC-UGAN achieved maximum scores of 26.04 dB, 0.87, and 3.2004 for PSNR, SSIM, and UIQM metrics, respectively, on real and synthetic underwater image datasets. Additionally, it obtained gains of at least 6.5%, 6%, and 1% for these metrics. Empirical evaluations on real and artificially distorted underwater image datasets demonstrate that AMSMC-GAN outperforms existing techniques, showcasing superior performance with enhanced quantitative metrics and strong generalization capabilities.

Aircraft targets, as high-value subjects, are a focal point in Synthetic Aperture Radar (SAR) image interpretation. To tackle challenges like limited SAR aircraft datasets and shortcomings in existing detection algorithms (complexity, poor performance, weak generalization), we present the Feature Enhancement and Multi-Scales Fusion Network (FEMSFNet) for SAR aircraft detection. FEMSFNet employs diverse image augmentation and integrates optimized Squeeze-and-Excitation Networks (SE) with residual network (ResNet) in a SdE-Resblock structure for a lightweight yet accurate model. It introduces ssppf-CSP module, an improved pyramid pooling model, to prevent receptive field deviation in deep network training. Tailored for SAR aircraft detection, FEMSFNet optimizes loss functions, emphasizing both speed and accuracy. Evaluation on the SAR Aircraft Detection Dataset (SADD) demonstrates significant improvements compared to the contrasted algorithms: precision rate (92%), recall rate (96%), and F1 score (94%), with a maximum increase of 12.2% in precision, 12.9% in recall, and 13.3% in F1 score.

ObjectivesVirus infection closely associated with autoimmune disease. The study aimed to explore the autoantibody profiles and the correlation of autoantibodies with the disease severity and the prognosis of the coronavirus disease 2019 (COVID-19) patients.MethodsThree hundred thirty-seven hospitalized COVID-19 patients from 6th to 23rd January 2023 were enrolled. Logistic and Cox regression analyses were used to analyze the risk factors for the patient’s disease severity and outcome. The association between Anti-extractable nuclear antigen antibody (ENA) positivity and the prognosis of COVID-19 patients was analyzed using Kaplan–Meier survival curves.Results137 of COVID-19 patients were detected positive for antinuclear antibody (ANA), 61 had positive results for ENA, and 38 were positive for ANA and ENA. ANA positivity rate was higher in non-severe illness group (p = 0.032). COVID-19 patients who died during hospitalization had a high rate of ENA positivity than convalescent patients (p = 0.002). Multivariate logistic regression showed that ANA positivity was a protective factor for the disease severity of COVID-19. Multivariate Cox regression analysis revealed that ENA positivity, white blood cells count (WBC), aspartate aminotransferase (AST), Creatinine (CREA), and CRP were independent risk factors for the outcome of COVID-19 patients, and that COVID-19 patients with ENA positivity had a lower cumulative survival rate (p = 0.002).ConclusionA spectrum of autoantibodies were expressed in COVID-19 patients, among which ANA and ENA positivity was associated with the severity and prognosis of COVID-19. Therefore, autoantibodies may help to assess the disease severity and prognosis of COVID-19 patients.

Abstract Differentiation therapy using small molecules is a promising strategy for improving the prognosis of glioblastoma (GBM). Histone acetylation plays an important role in cell fate determination. Nevertheless, whether histone acetylation in specific sites determines GBM cells fate remains to be explored. Through screening from a 349 small molecule-library, we identified that histone deacetylase inhibitor (HDACi) MS-275 synergized with 8-CPT-cAMP was able to transdifferentiate U87MG GBM cells into neuron-like cells, which were characterized by cell cycle arrest, rich neuron biomarkers, and typical neuron electrophysiology. Intriguingly, acetylation tags of histone 3 at lysine 9 (H3K9ac) were decreased in the promoter of multiple oncogenes and cell cycle genes, while ones of H3K9ac and histone 3 at lysine 14 (H3K14ac) were increased in the promoter of neuron-specific genes. We then compiled a list of genes controlled by H3K9ac and H3K14ac, and proved that it is a good predictive power for pathologic grading and survival prediction. Moreover, cAMP agonist combined with HDACi also induced glioma stem cells (GSCs) to differentiate into neuron-like cells through the regulation of H3K9ac/K14ac, indicating that combined induction has the potential for recurrence-preventive application. Furthermore, the combination of cAMP activator plus HDACi significantly repressed the tumor growth in a subcutaneous GSC-derived tumor model, and temozolomide cooperated with the differentiation-inducing combination to prolong the survival in an orthotopic GSC-derived tumor model. These findings highlight epigenetic reprogramming through H3K9ac and H3K14ac as a novel approach for driving neuron-fate-induction of GBM cells.

Abstract Background Functional diversity is important to maintain ecosystem functioning. Species with different ecomorphological traits may display distinct functional roles in ecosystems. Accordingly, functionally extreme species are more important as they can exhibit specific strategies. However, little is known about the distribution patterns of functionally extreme species at a local scale and whether the prior extinction of extreme species can cause significant effects on functional diversity. In addition, no empirical studies have been conducted on the microhabitat determinants of extreme species to maintain the functional diversity. Results This study collected 1470 tadpoles belonging to 6 families and 20 anuran species. These species were subsequently divided into 65 functional entities based on their developmental stages to incorporate intraspecific traits variability. As a result, we detected seven extreme functional entities, accounting for 10.7% of the total number of entities. Moreover, the prior extinction of extreme entities can lead to a significant decrease in functional diversity compared with the random extinction of entities. Microhabitat variables such as conductivity, water depth, and current velocity determined the distribution of extreme entities. Conclusion Although the functionally extreme entities only represented a small proportion of the total number of tadpoles, they played irreplaceable roles in maintaining functional diversity. Their extinction may induce high functional vulnerability in tadpole communities. Therefore, anuran species with extreme tadpole traits need to be projected for amphibian conservation.

IntroductionIn recent years, extensive research has been conducted on the synchronous behavior of neural networks. It is found that the synchronization ability of neurons is related to the performance of signal reception and transmission between neurons, which in turn affects the function of the organism. However, most of the existing synchronization methods are faced with two difficulties, one is the structural parameter dependency, which limits the promotion and application of synchronous methods in practical problems. The other is the limited adaptability, that is, even when faced with the same control tasks, for most of the existing control methods, the control parameters still need to be retrained. To this end, the present study investigates the synchronization problem of the fractional-order HindmarshRose (FOHR) neuronal models in unknown dynamic environment.MethodsInspired by the human experience of knowledge acquiring, memorizing, and application, a learning-based sliding mode control algorithm is proposed by using the deterministic learning (DL) mechanism. Firstly, the unknown dynamics of the FOHR system under unknown dynamic environment is locally accurately identified and stored in the form of constant weight neural networks through deterministic learning without dependency of the system parameters. Then, based on the identified and stored system dynamics, the model-based and relearning-based sliding mode controller are designed for similar as well as new synchronization tasks, respectively.ResultsThe synchronization process can be started quickly by recalling the empirical dynamics of neurons. Therefore, fast synchronization effect is achieved by reducing the online computing time. In addition, because of the convergence of the identification and synchronization process, the control experience can be constantly replenished and stored for reutilization, so as to improve the synchronization speed and accuracy continuously.DiscussionThe thought of this article will also bring inspiration to the related research in other fields.

Lightweight and adaptive adjustment are key research directions for deep neural networks (DNNs). In coal industry mining, frequent changes in raw coal sources and production batches can cause uneven distribution of appearance features, leading to concept drift problems. The network architecture and parameters should be adjusted frequently to avoid a decline in model accuracy. This poses a significant challenge for those without specialist expertise. Although the Neural Architecture Search (NAS) has a strong ability to automatically generate networks, enabling the automatic design of highly accurate networks, it often comes with complex internal topological connections. These redundant architectures do not always effectively improve network performance, especially in resource-constrained environments, where their computational efficiency is significantly reduced. In this paper, we propose a method called Topology Complexity Neural Architecture Search (TCNAS). TCNAS proposes a new method for evaluating the topological complexity of neural networks and uses both topological complexity and accuracy to guide the search, effectively obtaining lightweight and efficient networks. TCNAS employs an adaptive shrinking search space optimization method, which gradually eliminates poorly performing cells to reduce the search space, thereby improving search efficiency and solving the problem of space explosion. In the classification experiments of coal and gangue, the optimal network designed by TCNAS has an accuracy of 83.3%. And its structure is much simpler, which is about 1/53 of the parameters of the network dedicated to coal and gangue recognition. Experiments have shown that TCNAS is able to generate networks that are both efficient and simple for resource-constrained industrial applications.

Abstract Inkjet-printed electronics have become a popular research topic in recent years. For common drop-on-demand (DOD) inkjet printing technology, uneven edges are a universal problem. Many factors, such as the properties of the ink and printing parameters, influence this problem, and numerical methods are better than experimental methods for studying these influences. In this paper, a model based on the Volume of Fluid (VOF) method and user-defined files (UDFs) in Ansys F is established to simulate the formation process of deposited ink droplets. The model and UDFs include the friction effect, and the morphology of a single droplet, two fused droplets, and multiple droplets is simulated to study the influence of different factors; some results can serve as guidelines for improving pattern quality. Finally, the effect of selective treatment is also studied to understand its advantages for inkjet printing.

Abstract Accumulating evidence supports the existence of glioma stem cells (GSCs) and their critical role in the resistance to conventional treatments for glioblastoma multiforme (GBM). Differentiation therapy represents a promising alternative strategy against GBM by forcing GSCs to exit the cell cycle and reach terminal differentiation. In this study, we demonstrated that cAMP triggered neuronal differentiation and compromised the self-renewal capacity in GSCs. In addition, cAMP induced negative feedback to antagonize the differentiation process by activating β-catenin pathway. Suppression of β-catenin signaling synergized with cAMP activators to eliminate GSCs in vitro and extended the survival of animals in vivo. The cAMP/PKA pathway stabilized β-catenin through direct phosphorylation of the molecule and inhibition of GSK-3β. The activated β-catenin translocated into the nucleus and promoted the transcription of APELA and CARD16, which were found to be responsible for the repression of cAMP-induced differentiation in GSCs. Overall, our findings identified a negative feedback mechanism for cAMP-induced differentiation in GSCs and provided potential targets for the reinforcement of differentiation therapy for GBM.

Abstract Over the last decade, oncolytic virus (OV) therapy has shown its promising potential in tumor treatment. The fact that not every patient can benefit from it highlights the importance for defining biomarkers that help predict patients’ responses. As particular self-amplifying biotherapeutics, the anti-tumor effects of OVs are highly dependent on the host factors for viral infection and replication. By using weighted gene co-expression network analysis (WGCNA), we found matrix remodeling associated 8 (MXRA8) is positively correlated with the oncolysis induced by oncolytic virus M1 (OVM). Consistently, MXRA8 promotes the oncolytic efficacy of OVM in vitro and in vivo. Moreover, the interaction of MXRA8 and OVM studied by single-particle cryo-electron microscopy (cryo-EM) showed that MXRA8 directly binds to this virus. Therefore, MXRA8 acts as the entry receptor of OVM. Pan-cancer analysis showed that MXRA8 is abundant in most solid tumors and is highly expressed in tumor tissues compared with adjacent normal ones. Further study in cancer cell lines and patient-derived tumor tissues revealed that the tumor selectivity of OVM is predominantly determined by a combinational effect of the cell membrane receptor MXRA8 and the intracellular factor, zinc-finger antiviral protein (ZAP). Taken together, our study may provide a novel dual-biomarker for precision medicine in OVM therapy.

For decades, researches have concentrated on the mechanical properties, biodegradation, and biocompatibility of implants used in the therapy of large size bone defect. In vivo studies demonstrate that bioabsorbable bone substitute materials can reduce the risk of common symptoms such as inflammation and osteonecrosis caused by bio-inert materials after long-term implantation. Several organic, inorganic, and composite materials have been approved for clinical application, based on their unique characteristics and advantages. Although some artificial bioabsorbable bone substitute materials have been used for years, there are still some disadvantages existing, such as low mechanical strength, high brittleness, and low degradation rate. Therefore, novel bioabsorbable composite materials biomaterials have been developed for bone defect repair. In this review, we provide an overview of the development of artificial bioabsorbable bone substitute materials and highlight the advantages and disadvantages. Furthermore, recent advances in bioabsorbable bone substitute materials used in bone defect repair are outlined. Finally, we discuss current challenges and further developments in the clinical application of bioabsorbable bone substitute materials.

Abstract Background The purpose of this study was to explore the reason for guanine nucleotide binding‐protein gamma subunit‐4 (GNG4) overexpression and the relationship between GNG4 overexpression and the poor prognosis of lung adenocarcinoma (LUAD) patients. Methods The genes and phenotypes related to GNG4 expression in patients with lung adenocarcinoma were analyzed by bioinformatics. The phenotype indicated by bioinformatic analysis was confirmed by experiments. Results GNG4 expression is elevated in lung adenocarcinoma, and overexpressed GNG4 is related to the poor prognosis of patients with lung adenocarcinoma. The hypoxic microenvironment of lung adenocarcinoma can promote GNG4 expression and GNG4 promotes the migration and proliferation of lung adenocarcinoma cells. Conclusions GNG4 expression in lung adenocarcinoma was significantly higher than in paired adjacent tissues. GNG4 overexpression is associated with a variety of malignant phenotypes of lung adenocarcinoma. Increased GNG4 expression is related to the hypoxic microenvironment in lung adenocarcinoma.

Understanding the spatial patterns and the maintenance of biodiversity is a central target in ecology and biogeography, which provide important insights into community assembly processes. Mountain ecosystems provide informative systems for examining how biodiversity is distributed and identifying the mechanisms underlying those patterns. However, most of the existed studies only focused on plants, birds, and microbes, while little attention has been paid on amphibians, especially tadpoles. In the present study, we explored the elevational patterns of multiple facets of tadpole diversity and the community assembly mechanisms in temperate montane streams of Mount Emei, China. The taxonomic, functional, and phylogenetic diversity of tadpole assemblages in montane streams were quantified. Their elevational patterns were investigated using first and second-order polynomial regression analyses. The microhabitat determinants of these patterns were assessed by ordinary least squares models and hierarchical partitioning analyses. The phylogenetic tree of tadpoles and the Eucliden distance of traits between tadpoles were constructed. They were subsequently used to calculate the standardized effect size of mean pairwise phylogenetic and functional distances, and to speculate the tadpole assembly rules. Our results indicated that the Faith’s PD and the standardized effect size of Faith’s PD had hump-shaped responses to elevation, while the relationships between elevation and observed taxonomic diversity, observed functional diversity, and the standardized effect size of functional diversity were not significant. Interestingly, these patterns were determined by microhabitat variables, such as water conductivity, river width, water depth, and substrate type. Mean pairwise phylogenetic distance also showed hump-shaped correlations with the elevational gradient. Tadpole functional and phylogenetic structures were more clustered in low and high elevational streams, suggesting that environmental filtering was the main driver. At mid-elevations, functional and phylogenetic structures were overdispersal, indicating that limiting similarity plays a dominant role in shaping the tadpole assemblages.

Although fish steak meal (FSM) is a potentially available protein source, its efficiency as a fish meal (FM) substitute remains unclear to date. To this end, this study was carried out to determine the effects of dietary FM replaced by FSM on growth performance, antioxidant capacity, intestinal health and microflora, inflammatory response, and protein metabolism of large yellow croaker. Five isolipidic and isonitrogenous diets were formulated by substituting FM with FSM at levels of 0% (FSM0, control diet), 25% (FSM25), 50% (FSM50), 75% (FSM75), and 100% (FSM100), and were fed to juvenile large yellow croaker for 8 weeks. Compared with the control diet, the replacement of 25% dietary FM with FSM did not markedly alter the weight gain (WG) and specific growth rate (SGR). When the FM substitution level was over 25%, WG and SGR markedly reduced. The intestinal structure observation found that the FSM75 and FSM100 diets markedly decreased villus height, villus width, and muscle thickness of the anterior intestine. The FSM75 and FSM100 diets significantly decreased enzyme activities of amylase (AMS), lipase (LPS), trypsin, catalase (CAT), and total superoxide dismutase (T-SOD) and the total antioxidant capacity (T-AOC), and increased the malondialdehyde (MDA) content in the liver of large yellow croaker. The mRNA expression levels of intestinal barrier and inflammatory response-related genes suggested that the FSM50, FSM75, and FSM100 diets significantly decreased the mRNA abundances of intestinal barrier-related genes and anti-inflammatory response-related genes, and increased the mRNA abundances of proinflammatory gene il-6 in the anterior intestine. The compositions of intestinal microflora displayed that the FSM50, FSM75, and FSM100 diets decreased relative abundances of Firmicutes phylum and increased relative abundances of Proteobacteria phylum. In addition, the results of protein expression levels showed that the phosphorylation level of mammalian target of rapamycin (mTOR) and 4E-binding protein 1 (4E-BP1) in FSM75 and FSM100 groups were markedly reduced. In conclusion, FSM can replace up to 25% dietary FM without compromising the growth performance, intestinal health, and protein metabolism of the large yellow croaker.

The interval section of the Liuyang River flood control levee project of the Changsha Metro Line 6 is used as the engineering background of this study. A three-dimensional finite element numerical model of a tunnel shield containing complex interfaces is established by using the multifield coupling software COMSOL. The paper studied the deformation of flood control levees under shield tunnel excavation working conditions. The results show that when the left line shield machine is excavated below the Liuyang River flood control levee, the deformation of the flood control levee and the surrounding rock of the tunnel is biased towards the built right line tunnel. And it has an impact on the bridge pile near the tunnel. When the shield of the left line crosses the flood control levee, it can easily cause a large deformation and displacement of the levee above the area between the two shields. To ensure the controlled deformation of the levee, the construction should ensure the spacing between the two tunnel palm faces as far as possible and should be far away from other structures on the levee. When the shield crosses the levee, the deformation that occurs at the base of the levee is significantly higher than the deformations that occur at other locations of the levee. Displacement monitoring and secondary reinforcement at the base of the flood control levee appear to be necessary. The numerical simulation results validate the feasibility of using the multifield coupling software COMSOL to study the construction modeling of shield tunnels through rivers and its advantages. This method provides a practical framework for similar tunnel performance engineering or displacement monitoring in future projects.

The present study investigated the growth performance, feed utilization, intestinal morphology, and microbiota communities of juvenile large yellow croaker (Larimichthys crocea) fed diets containing different proportions of soy protein concentrate (SPC) (0, 15%, 30%, and 45%, namely FM, SPC15, SPC30, and SPC45) as a substitute for fish meal (FM) for 8 weeks. The weight gain (WG) and specific growth rate (SGR) in fish fed SPC45 were significantly lower than those fed FM and SPC15 but not differ with these fed SPC30. The feed efficiency (FE) and protein efficiency ratio (PER) decreased sharply when the dietary SPC inclusion level was higher than 15%. The activity of alanine aminotransferase (ALT) and expression of alt and aspartate aminotransferase (ast) were significantly higher in fish fed SPC45 than those fed FM. The activity and mRNA expression of acid phosphatase were opposite. The villi height (VH) in distal intestine (DI) showed a significant quadratic response to increasing dietary SPC inclusion levels and was highest in SPC15. The VH in proximal intestine, middle intestine decreased significantly with increasing dietary SPC levels. The 16S rRNA sequences in intestine revealed that fish fed SPC15 had higher bacterial diversity and abundance of Phylum Firmicutes such as order Lactobacillales and order Rhizobiaceae than those fed other diets. Genus vibrio, family Vibrionaceae and order Vibrionales within phylum Proteobacteria were enriched in fish fed FM and SPC30 diets. Tyzzerella and Shewanella that belongs to phylum Firmicutes and Proteobacteria, respectively, were enriched in fish fed SPC45 diet. Our results indicated that SPC replacing more than 30% FM could lead to lower quality diet, retard growth performance, ill health, disordered intestine structure, and microbiota communities. Tyzzerella could be the bacteria indicator of intestinal in large yellow croaker fed low quality diet due to high SPC content. Based on the quadratic regression analysis of WG, the best growth performance could be observed when the replacement of FM with SPC was 9.75%.

Shale of the Middle–Upper Permian Dalong Formation and Gufeng Formation in the Lower Yangtze region is characterized by large thickness, high total organic carbon (TOC), wide distribution and moderate organic thermal evolution degree, so it may be the next important field of shale gas exploration. In order to point out the target and direction of shale gas exploration and development in this region, this paper selects the Dalong Formation and Gufeng Formation shale in the Xuanjing area of Lower Yangtze as the research object to quantitatively describe the development characteristics of shale pores of different scales by means of scanning electron microscopy (SEM), high pressure mercury injection, CO2 and N2adsorption. Then, the fractal dimension of sample pores is calculated by using the FHH (Frenkel–Halsey–Hill) model. Finally, combined with TOC and mineral compositions, the relationship between pore structure and fractal dimension is discussed. And the following research results are obtained. First, dominant lithofacies of Dalong Formation are argillaceous-rich siliceous shale and argillaceous-rich/siliceous mixed shale, which has smaller specific surface area and pore volume, larger average pore diameter. The pore development is mainly controlled by clay mineral content. Dominant lithofacies of Gufeng Formation is siliceous shale, which has a larger specific surface area and pore volume, and smaller average pore diameter. The pore development is controlled by organic matter and brittle mineral content. Second, the influencing factors of fractal dimension can be attributed to the controlling factors of micropore development. The fractal dimension D1of Dalong Formation ranges from 2.4515 to 2.5513 (average 2.5227), and D2ranges from 2.5817 to 2.6578 (averagely 2.6246). The fractal dimension D1of Gufeng Formation ranges from 2.5817 to 2.6578 (averagely 2.6246), and D2ranges from 2.7227 to 2.871 (averagely 2.813). Gufeng Formation shale presents the characteristics of more complex pore structure. Third, the fractal dimension D1is more sensitive to specific surface area, pore development and mineral composition, while D2is more effective in characterizing the average pore diameter. In conclusion, Dalong Formation shale with high D1and D2and Gufeng Formation shale with low D1and high D2can be taken as the favorable exploration targets of Permian marine shale gas in the Lower Yangtze region, and the regional overpressure zones (belts) with weaker structural deformation in hydrocarbon rich sags will be the favorable shale gas exploration targets in this area.

Muntjac deer underwent rapid species radiation and dramatic chromosome fusions within a short period of time. Here the authors reveal that repeat sequences likely mediated illegitimate recombination to result in chromosome fusions and that 3D chromatin architecture around fusion sites have no significant change, while significant interactions across fusion sites were gradually established after speciation.

China is one of the world’s most seriously affected regions by water and soil erosion. Soil erosion is a major cause and an important component of land degradation, which has a negative impact on ecological protection and sustainable socioeconomic development. Rainfall erosivity (RE) is one of the key parameters to assess the degree of soil erosion. Quantifying the content of RE and the formation mechanism is important to accurately measure the degree of soil erosion and provide a theoretical basis for soil erosion management. Here, this study analyzed the spatial and temporal characteristics of RE and their driving mechanisms in the Qinba Mountains from 1970 to 2017 using a daily rainfall model. Furthermore, geographical detector methods were used to quantitatively identify the dominant factors affecting RE and the dominant factors affecting RE on different topographic reliefs. The results showed that the RE between 1970 and 2017 averaged 4,197.85 MJ mm hm−2 h−1 a−1, with a mutation coefficient of 0.16. The spatial distribution of RE is high in the southeast and low in the northwest, and the mean annual RE declines with the increase in latitude in longitude and increases with the reduction in longitude in latitude. In addition, precipitation and temperature are the main factors affecting the spatial distribution of RE. Among these, precipitation can explain about 97% of the RE and temperature can explain about 65% of the RE. These findings should be essential for managing soil and water loss in the North–South Transition Zone, China.

Accurate grasping state detection is critical to the dexterous operation of robots. Robots must use multiple modalities to perceive external information, similar to humans. The direct fusion method of visual and tactile sensing may not provide effective visual–tactile features for the grasping state detection network of the target. To address this issue, we present a novel visual–tactile fusion model (i.e., RFCT) and provide an incremental dimensional tensor product method for detecting grasping states of weak-stiffness targets. We investigate whether convolutional block attention mechanisms (CBAM) can enhance feature representations by selectively attending to salient visual and tactile cues while suppressing less important information and eliminating redundant information for the initial fusion. We conducted 2250 grasping experiments using 15 weak-stiffness targets. We used 12 targets for training and three for testing. When evaluated on untrained targets, our RFCT model achieved a precision of 82.89%, a recall rate of 82.07%, and an F1 score of 81.65%. We compared RFCT model performance with various combinations of Resnet50 + LSTM and C3D models commonly used in grasping state detection. The experimental results show that our RFCT model significantly outperforms these models. Our proposed method provides accurate grasping state detection and has the potential to provide robust support for robot grasping operations in real-world applications.

Rapid urbanization has led to a significant expansion of urban space, causing ecological problems such as fragmentation, declining landscape connectivity, and decreasing biodiversity. There is an urgent need to mitigate the conflict between urban expansion and ecological environmental protection by constructing ecological networks to help promote sustainable regional development. This study selected the Funiu Mountain area as the study area. Morphological spatial pattern analysis, the minimal cumulative resistance model, and network index evaluation were used to construct an ecological network in the study area and conduct a comparative analysis with local nature reserves. The results showed: (1) nine ecological source sites were identified, concentrated in the central and northern regions, which had a high spatial overlap with local nature reserves; (2) 34 ecological corridors were extracted, which could effectively connect all ecological source sites as well as most nature reserves; (3) 32 ecological nodes were identified, of which 20 strategic points were scattered along ecological corridors, and 12 artificial environment points were scattered in low-lying areas around nature reserves; (4) the ecological network showed a structure of central concentration and peripheral dispersion. The structural evaluation of the network indicated that it had strong integrity.

Understanding the spatio-temporal changes of vegetation and its climatic control factors can provide an important theoretical basis for the protection and restoration of eco-environments. In this study, we analyzed the normalized difference vegetation index (NDVI) in the Chinese Loess Plateau (CLP) from 2002 to 2018 via trend analysis, stability analysis, and Mann-Kendall mutation test to investigate the change of vegetation. In addition, we also used the skewness analysis and correlation analysis to explore the contribution of climate change and human activities on regional vegetation changes. The results indicated that the overall increasing trend of NDVI from 2002 to 2018 was significant. The areas showing increased NDVI were mainly distributed in the southeastern CLP and the irrigation districts of the Yellow River to the north and west of the CLP, while the areas showing decreased NDVI were concentrated in the desert of the western Ordos Plateau, Longzhong Loess Plateau, and the built-up and adjacent areas. Precipitation was the dominant factor contributing to vegetation growth in the CLP, while vegetation was less dependent on precipitation in the irrigation districts. The increasement of NDVI has led to a prolonged response time of vegetation to water stress and a lag effect of less than two months in the CLP. The effect of temperature on NDVI was not significant; significant negative correlations between NDVI and temperature were found only in the desert, the Guanzhong Plain, the southern Liupan Mountains, and the southeastern Taihang Mountains, owing to high temperatures, urban heat islands, and large cloud cover in mountainous areas. Affected by the “Grain for Green Program” (GGP), NDVI in the CLP increased from 2002 to 2018; however, the increasing trends of NDVI for different vegetation cover types were significantly different owing to the difference in background status. The increasing contribution rate of NDVI in the CLP mainly came from crops and steppes. Urban not only led to the destruction of vegetation but also had radiation effect causing negative impact of NDVI around the cities. This resulted in the aggravation of the negative bias of NDVI with time in the CLP. The results provide a long-term perspective for regional vegetation protection and utilization in the CLP.

Functionally graded materials (FGMs) used in electrical insulation have spatially inhomogeneous dielectric properties (i.e., permittivity or conductivity), which can be applied to relieve localized electric field (E-field) intensification and improve insulation performance. However, previous research shows some limitations in inadequate considerations on the material feasibility, and insufficient universality on material grading type and voltage form. In this study, a material study of silicone rubber (SiR) nanocomposites containing carbon nanotubes (CNTs) is conducted to determine the practical variation range of dielectric properties (both permittivity and conductivity) in joint insulation materials. Then, the optimal design of both multilayer and pointwise FGM joint insulation is investigated under both AC and DC voltage, in which the lower and upper limits of permittivity and conductivity were derived from the experimental results. Experimental results on SiR/CNT nanocomposites indicate that low-amount doping of the CNTs (0-0.5% wt%) can effectively increase the permittivity and conductivity of joint insulation materials. The successive simulation study indicates that compared to uniform joints, cable joints employing optimally designed FGM insulation show a considerable increase in the E-field utilization factor (from 0.08-0.17 to 0.23-0.56), indicating elevated E-field uniformity. Finally, the optimal range of CNT doping ratios is determined to be 0-0.3 wt% from both experimental and simulation results. This study systematically verifies the applicability of FGMs in enhancing the performance of power cable accessories, which can show some guidance to the design and fabrication of advanced power cable systems.

The reintroduction of captive-bred individuals is a primary approach to rebuild the wild populations of the Chinese giant salamander (Andrias davidianus), the largest extant amphibian species. However, the complexity of the wild habitat (e.g., diverse microorganisms and potential pathogens) potentially threatens the survival of reintroduced individuals. In this study, fresh (i.e., containing environmental microbiota) or sterilized river sediments (120°C sterilized treatment) were added to the artificial habitats to treat the larvae of the Chinese giant salamander (control group—Cnt: 20 individuals, treatment group 1 with fresh river sediments—T1: 20 individuals, and treatment group 2 with sterilized river sediments—T2: 20 individuals). The main objective of this study was to test whether this procedure could provoke their wild adaptability from the perspective of commensal microbiotas (skin, oral cavity, stomach, and gut) and larvae transcriptomes (skin, spleen, liver, and brain). Our results indicated that the presence of habitat sediments (whether fresh or sterilized) reshaped the oral bacterial community composition. Specifically, Firmicutes decreased dramatically from ~70% to ~20–25% (mainly contributed by Lactobacillaceae), while Proteobacteria increased from ~6% to ~31–36% (mainly contributed by Gammaproteobacteria). Consequently, the proportion of antifungal operational taxonomic units (OTUs) increased, and the function of oral microbiota likely shifted from growth-promoting to pathogen defense. Interestingly, the skin microbiota, rather than the colonization of habitat microbiota, was the major source of the pre-treated oral microbiota. From the host perspective, the transcriptomes of all four organs were changed for treated individuals. Specifically, the proteolysis and apoptosis in the skin were promoted, and the transcription of immune genes was activated in the skin, spleen, and liver. Importantly, more robust immune activation was detected in individuals treated with sterilized sediments. These results suggested that the pathogen defense of captive-bred individuals was improved after being treated, which may benefit their survival in the wild. Taken together, our results suggested that the pre-exposure of captive-bred Chinese giant salamander individuals to habitat sediments could be considered and added into the reintroduction processes to help them better adapt to wild conditions.

Abstract Background Viruses are obligate parasites that depend on host cells to provide the energy and molecular precursors necessary for successful infection. The main component of virus-induced metabolic reprogramming is the activation of glycolysis, which provides biomolecular resources for viral replication. However, little is known about the crosstalk between oncolytic viruses and host glycolytic processes. Methods A MTT assay was used to detect M1 virus-induced cell killing. Flow cytometry was used to monitor infection of M1 virus expressing the GFP reporter gene. qPCR and western blotting were used to detect gene expression. RNA sequencing was performed to evaluate gene expression under different drug treatments. Scanning electron microscopy was performed to visualize the endoplasmic reticulum (ER). Caspase activity was detected. Last, a mouse xenograft model was established to evaluate the antitumor effect in vivo. Most data were analyzed with a two-tailed Student’s t test or one-way ANOVA with Dunnett’s test for pairwise comparisons. Tumor volumes were analyzed by repeated measures of ANOVA. The Wilcoxon signed-rank test was used to compare nonnormally distributed data. Results Here, we showed that the glucose analog 2-deoxy-d-glucose (2-DG) inhibited infection by M1 virus, which we identified as a novel type of oncolytic virus, and decreased its oncolytic effect, indicating the dependence of M1 replication on glycolysis. In contrast, lonidamine, a reported hexokinase 2 (HK2) inhibitor, enhanced the infection and oncolytic effect of M1 virus independent of HK2. Further transcriptomic analysis revealed that downregulation of the antiviral immune response contributes to the lonidamine-mediated potentiation of the infection and oncolytic effect of M1 virus, and that MYC is the key factor in the pool of antiviral immune response factors inhibited by lonidamine. Moreover, lonidamine potentiated the irreversible ER stress-mediated apoptosis induced by M1 virus. Enhancement of M1′s oncolytic effect by lonidamine was also identified in vivo. Conclusions This research demonstrated the dependence of M1 virus on glycolysis and identified a candidate synergist for M1 virotherapy.

The high degree of thermal evolution is a main factor restricting the development of the Lower Paleozoic shale gas in the Yangtze region. The latest field study shows that there is a region with relatively lower thermal evolution in the Jiangshan-Tonglu area in western Zhejiang province. Centering on the lower thermal evolution area, this paper analyzes the geological and geochemical characteristics of the Lower Cambrian Hetang Formation, based on the regional geological survey of the western Zhejiang province and the latest borehole data analysis. The study area is located in a good sedimentary facies belt (basin-shelf facies), with a large deposition thickness, and a high organic matter abundance. While the thermal evolution degree is relatively low, with high brittle mineral content and moderate clay mineral content. And micro-pores and micro-fractures are well developed. The study area has a good material basis for accumulation. The Changshan-Kaihua area has been identified as the most favorable area for shale gas exploration on the basis of considering a thick shale deposit with high organic matter abundance, relatively low thermal evolution, stable tectonic background and deeply buried area, while avoiding the areas with relatively strong igneous activity.

Human cytomegalovirus (HCMV) infection can induce apoptosis of vascular endothelial cells, which may be the most important element of development and progression of reported atherosclerosis caused by HCMV. As there are no specific drugs to clear HCMV infection, exploration of relevant drugs and mechanisms that can intervene in HCMV-induced atherosclerosis is urgently needed. The present study confirmed that vitamin D3 protected vascular endothelial cells from HCMV-induced apoptosis by inhibiting endoplasmic reticulum (ER) and mitochondrial apoptosis pathway. Mechanistically, HCMV infection could induce aberrantly elevated m6A modification, especially the increases of methyltransferases-“writers” (METTL3) and m6A binding proteins-“readers” (YTHDF3). METTL3 methylates mitochondrial calcium uniporter (MCU), the main contributor to HCMV-induced apoptosis of vascular endothelial cells, at three m6A residues in the 3′-UTR, which promotes the association of the YTHDF3 with methylated MCU mRNA and subsequently increases the translation and expression of MCU. Further analysis shows that ALKBH5 is the demethylases-“eraser” of MCU mRNA, which can negatively regulate the m6A modification process of MCU. Conversely, vitamin D3 downregulated the METTL3 by inhibiting the activation of AMPK, thereby inhibiting the m6A modification of MCU and cell apoptosis. Our findings extend the understanding of m6A driven machinery in virus-induced vascular endothelium damage and highlight the significance of vitamin D3 in the intervention of HCMV-induced atherosclerosis.

In this study, the precise tracking problem for electrostatic micromirror systems with disturbances and input saturation is investigated. Inspired by the composite nonlinear feedback (CNF)’s improvement of the transient performance and the sliding mode control’s enhancement of the robustness, a novel integral sliding mode with reaching law (ISMRL)-based composite nonlinear feedback (CNF) controller is proposed. Then, the stability of the closed-loop system is proved based on Lyapunov theorem. Finally, numerical simulations are investigated to evaluate the effectiveness of the proposed scheme. It is shown that the closed-loop system with the proposed scheme has precise positioning and improved transient performance in presence of time-varying disturbances.