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Abstract To study the effect of different sizes and speeds of coal gangue falling on hydraulic supports for top‐coal caving discharge hydraulic support on the bearing characteristics of the hydraulic support, the ADAMS hydraulic support rigid‐flexible coupling analysis model was established. HyperMesh is used to flexibly process the hydraulic support, and the column and jack are equivalently replaced by spring damping system. By applying step loads of different sizes and speeds to simulate the impact force generated when the coal gangue falls on different positions of the cover beam, the dynamic response characteristics of the column, balance jack and other articulation points are obtained. Analyses show that: when the impact load is closer to the roof beam, the articulation point of the roof beam‐cover beam and the balancing jack are easy to be damaged. When the same impact load is applied to the cover beam, the faster the load is applied, the hydraulic support column and balancing jack may not be able to absorb and disperse the pressure effectively in time, resulting in the articulation points being subjected to a larger impact force, which is easy to cause damage or destruction. When different sizes and speeds of impact loads are applied to the cover beam, the latter has a greater impact on the dynamic response of the front and rear connecting rod articulation points and the cover beam‐roof beam articulation point than the former, and the hydraulic bracket will be more prone to vibration, deformation, and stress concentration, thus affecting the stability and safety of the bracket. The article is of guiding significance for designing and optimizing the structure and parameters of the hydraulic support, and improving the support performance and stability of the hydraulic support in the comprehensive release working face.

MicroRNAs (miRNAs) have been demonstrated to control chicken skeletal muscle growth, however, the potential function of the miR-181-5p family in chicken myogenesis remains largely unknown. Here, our study identified the two chicken (Gallus gallus; Gga) miR-181-5p family members widely expressed in various tissues, specifically miR-181a-5p and miR-181b-5p. Besides, the breast muscles of fast-growing broilers expressed higher levels of miR-181a-5p and miR-181b-5p than those of slow-growing layers. Functionally, miR-181a-5p and miR-181b-5p both promote the expression level of myogenic factors including myogenin (MyoG), myogenic differentiation 1 (MyoD1), and myosin heavy chain (MyHC), meanwhile accelerating the myotube formation of skeletal muscle satellite cells (SMSCs). Mechanistically, miR-181a-5p and miR-181b-5p directly bind to the 3´ untranslated region (UTR) of the transforming growth factor beta receptor 1 (TGFBR1) mRNA, further reducing the expression of TGFBR1. TGFBR1 is a key Transforming growth factor beta (TGF-β) signaling transduction receptor and had a negative function in muscle cell differentiation. Furthermore, knockdown of TGFBR1 facilitated the expression of chicken myogenic factors, boosted myotube formation, and decreased the SMAD family member 2/3 (SMAD2/3) phosphorylation in chicken SMSCs. SMAD2/3 are downstream of TGF-β signaling, and miR-181a-5p and miR-181b-5p could reduce the expression of TGFBR1 to further diminish the SMAD2/3 phosphorylation. Our findings revealed that the miR-181-5p family targets TGFBR1 to break the TGF-β signaling transduction, which resulted in promoting chicken skeletal muscle development.

The electrode is a core component that affects the overall performance of the hydrogen/iron redox flow battery. To address the drawbacks associated with the limited electrochemical activity and fewer active sites of the carbon-based electrode, this study employs a straightforward and effective flame method to synthesize carbon nanotubes (CNTs) on carbon paper and NiO/CNT composite on graphite felt. The CNT on the modified carbon-based electrode contains many hydrophilic and oxygen-containing functional groups, greatly improving the hydrophilicity of the electrode, thereby increasing the electrochemical surface area. The modified carbon-based electrode exhibits better electrochemical activity due to the CNT or NiO/CNT providing more active sites. At 50 mA cm−2, the energy efficiency of pristine carbon paper and graphite felt is 60.8% and 52.4%, respectively, while the energy efficiency of the modified carbon paper and graphite felt reached 75.3% and 80.5%, respectively. The modified carbon-based electrode achieves a 100% coulombic efficiency, with no significant degradation in energy efficiency after running for 300 cycles, demonstrating excellent stability. This study not only investigates the performance of graphite felt electrodes in hydrogen/iron batteries but also proposes a flame method for preparing CNT-modified carbon-based electrodes for high-performance hydrogen/iron batteries.

Abstract The intellectual properties (IP) protection of deep neural networks (DNN) models has raised many concerns in recent years. To date, most of the existing works use DNN watermarking to protect the IP of DNN models. However, the DNN watermarking methods can only passively verify the copyright of the model after the DNN model has been pirated, which cannot prevent piracy in the first place. In this paper, an active DNN IP protection technique against DNN piracy, called ActiveGuard, is proposed. ActiveGuard can provide active authorisation control, users' identities management, and ownership verification for DNN models. Specifically, for the first time, ActiveGuard exploits well‐crafted rare and specific adversarial examples with specific classes and confidences as users' fingerprints to distinguish authorised users from unauthorised ones. Authorised users can input their fingerprints to the DNN model for identity authentication and then obtain normal usage, while unauthorised users will obtain a very poor model performance. In addition, ActiveGuard enables the model owner to embed a watermark into the weights of the DNN model for ownership verification. Compared to the few existing active DNN IP protection works, ActiveGuard can support both users' identities identification and active authorisation control. Besides, ActiveGuard introduces lower overhead than these existing active protection works. Experimental results show that, for authorised users, the test accuracy of LeNet‐5 and Wide Residual Network (WRN) models are 99.15% and 91.46%, respectively, while for unauthorised users, the test accuracy of LeNet‐5 and WRN models are only 8.92% and 10%, respectively. Besides, each authorised user can pass the fingerprint authentication with a high success rate (up to 100%). For ownership verification, the embedded watermark can be successfully extracted, while the normal performance of DNN models will not be affected. Furthermore, it is demonstrated that ActiveGuard is robust against model fine‐tuning attack, pruning attack, and three types of fingerprint forgery attacks.

Abstract Proton exchange membrane fuel cells (PEMFCs) have garnered significant attention due to their high efficiency and low emissions. However, PEMFC always suffers mass transfer and water management in performance improvement. Herein, an integrated gas diffusion layer (GDL) with wavy channel and micro‐tunneled rib is designed and prepared to achieve faster and gentler mass transfer and excellent water management capability by laser engraving. Outstandingly, the new integrated GDL can use the back pressure of air as low as 0 and 50 kPa to respectively achieve 80% and 90% of fuel cell performance realized under pure oxygen. Such high performance is mainly due to the turbulent flow caused by wavy channel and express removing pathway of liquid water provided by micro‐tunneled rib. Moreover, the new integrated GDL also shows wide humidity tolerance from 40% to 100% and a very high specific volume power density of 16,300 W L−1 due to the thin thickness of new integrated GDL. This new integrated GDL is expected to be widely used in PEMFC and other energy conversion devices.

Mapping crop distribution using satellite technology is an effective approach for gaining information about food production over broad, regional scales. However, crop classification in high altitude regions from satellite platforms remains challenging, due to the spatial heterogeneity caused by the complex planting patterns. Moreover, the frequent cloud cover makes it difficult to collect time-series imagery for these regions. Thus, this study used a mosaic of single images of Gaofen-6 data to map the crop distribution in high altitude regions of Xining City and Haidong City prefectures of Qinghai Province, China. To improve the accuracy of the crop classification, random forest-recursive feature elimination (RF-RFE) was used to determine an optimal feature subset from existing spectral, texture and topographic features. Then, a two-layer stacking generalization ensemble model, incorporating Random Forest, XGBoost and AdaBoost, was trained. The results reveal that the stacking algorithm outperformed the other single classifiers, with overall accuracy higher than 85% (87.89% for the optimal feature subset and 85.38% for the original spectral band subset). In addition, the user’s and producer’s accuracies for wheat, rape and maize field all exceeded 90%. Elevation was the variable with the highest importance score, illustrating its importance in crop classification of high altitude regions. Overall, the framework, combining RF-RFE and a stacking algorithm, can improve the accuracy of the crop classification in high altitude regions.

IntroductionExploring the influencing factors and functioning mechanisms of thriving at work is of practical significance both for teachers and kindergartens. Based on the socially embedded model of thriving at work, this study aimed to examine the association between negative workplace gossip and thriving at work. The mediating role of psychological contract breach and the moderating role of bianzhi were also examined.MethodsA total of 1105 Chinese kindergarten teachers were chosen to complete a questionnaire on negative workplace gossip, psychological contract breach, and thriving at work.ResultsThe results demonstrated that negative workplace gossip was positively associated with psychological contract breach and negatively associated with thriving at work. In addition, psychological contract breach was negatively associated with thriving at work. According to the mediation model test, psychological contract breach was a mediating factor between negative workplace gossip and thriving at work. The impact of psychological contract breach on thriving at work could be further moderated by bianzhi.ConclusionThis study complements knowledge systems about the influential factors and functional mechanisms of thriving at work. In practical terms, this study offers a fresh and innovative perspective for kindergartens seeking to enhance teachers’ thriving at work.

Zanthoxylum esquirolii Léveillé is mainly distributed in southwest China, and its wild germplasm resources are scarce and in urgent need of conservation. In this study, we report the first complete chloroplast genome sequence of Z. esquirolii using next-generation sequencing. The circular genome is 158,390 bp in length, containing two inverted repeat (IR) regions of 27,622 bp separated by a large single copy (LSC) region of 85,580 bp and a small single copy (SSC) region of 17,566 bp. The chloroplast genome contains a total of 132 genes, including 87 protein-coding genes, 37 tRNA genes, and eight rRNA genes. The overall GC content of the chloroplast genome was 38.46%, with corresponding values in the LSC, SSC, and IR regions of 36.84%, 33.55%, and 42.51%, respectively. The phylogenetic tree revealed that Z. esquirolii Levl. formed a clade with Z. piperitum DC., Z. bungeanum Maxim., Z. simulans Hance and Z. sp. NH-2018, and had a strongly supported sister relationship with Z. bungeanum.

It is important to develop a catalyst that has high catalytic activity and can improve the degradation efficiency of refractory organic pollutants in the catalytic ozonation process. In this study, Fe-Mn-Cu-Ce/Al2O3 was synthesised via impregnation calcination for catalytic ozonation of bio-treated coking wastewater. The physical and chemical characteristics of the catalysts were analysed using X-ray diffraction (XRD), X-ray fluorescence spectrometry (XRF), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and Brunauer–Emmett–Teller nitrogen adsorption–desorption methods. The effects of catalyst dosage, pH, and reflux ratio on the degradation efficiency of wastewater were examined in laboratory-scale experiments. The chemical oxygen demand (COD) removal rate of bio-treated coking wastewater was estimated to be 52.76 % under optimal conditions. The experiments on the catalytic mechanism demonstrated that the surface hydroxyl formed by the Lewis acid sites on the surface of the catalyst can react with ozone as the active site forming the active oxygen (·OH, ·O2–, and 1O2), thereby efficiently degrading the organic pollutants in coking wastewater. Furthermore, a pilot-scale experiment on the catalytic ozonation of bio-treated coking wastewater was carried out using an Fe-Mn-Cu-Ce/Al2O3 catalyst, while the effects of the initial pollutant concentration, ozone concentration, and gas flow on the COD removal rate were studied on a pilot scale. It was found that the COD removal rate of the wastewater was ∼ 60 % under optimal parameters. After the treatment, the wastewater steadily reached the coking wastewater discharge standard (COD

IntroductionIn China, the high turnover rates of teachers have become one of the biggest obstacles to the development of rural preschool education. Objective: Based on the social information processing theory and the strength model of selfcontrol, this study examined the relationship between negative workplace gossip and turnover intention and the role of ego depletion and bianzhi in this relationship.MethodsThe questionnaire method was applied, and 411 rural preschool teachers in Hubei Province, China, participated in the survey.ResultsThe correlation results showed that negative workplace gossip was positively correlated with ego depletion, and ego depletion was positively correlated with turnover intention. After controlling for age, negative workplace gossip positively predicted turnover intention. The mediation analysis indicated that ego depletion played a mediating role in the relationship between negative workplace gossip and turnover intention. Moreover, the mediation effect was moderated by bianzhi. Negative workplace gossip had a stronger effect on the ego depletion of teachers without bianzhi than on that of teachers with bianzhi.ConclusionThe current research is the first to clarify that ego depletion mediates the relationship between negative workplace gossip and turnover intention, and the mediation effect is moderated via bianzhi. These findings expand our understanding of the influential factors and formation mechanisms of turnover intention. In practice, this study provides a novel perspective for policymakers and administrators to reduce the turnover intention among rural preschool teachers in China.

Zanthoxylum undulatifolium is an excellent economic tree species with important medical value. This study reports the first complete chloroplast genome sequence of Z. undulatifolium. Its whole chloroplast genome is 158,400 bp in length, including a large single-copy (LSC) region of 85,898 bp, a small single-copy (SSC) region of 17,610 bp, and two inverted repeat (IR) regions of 27,446 bp. The chloroplast genome contains a total of 132 genes, comprising 87 protein-coding genes, 37 tRNA genes, and eight rRNA genes. The overall GC content of the chloroplast genome is 38.46%, with the corresponding values in the LSC, SSC, and IR regions are 36.87%, 33.51%, and 42.55%, respectively. Phylogenetic analysis revealed the sister relationship between Z. undulatifolium and Z. bungeanum.

The urban alternate water source (AWS) is of great significance to the sustainable development of the city, the pollution degree, and source of heavy metals (HMs) in AWS, and whether it will adversely affect human health has received widespread attention. In this study, the urban AWS of Xinbian River in Suzhou City, Huaibei Plain, China, was used as the research object to study the seasonal changes of HMs (As, Cr, Cu, Cd, Pb, and Zn), quantitative identification of pollution sources, and human health risks (HHR). Research results show that the contents of those HMs, except As, are less than the drinking standards limit set by the World Health Organization (WHO), and the contents of As, Cr, and Zn are the largest in summer. The multivariate statistical analysis combined with positive matrix factorization (PMF) model analysis revealed that industrial sources accounted for 44.83%, and agricultural sources accounted for 55.17%. HHR assessment based on Monte Carlo simulation shows that the noncarcinogenic risks of adults and children are in the acceptable range (hazardous ingestion (HI)

Background and Purpose. Ferroptosis, a mechanism of cell death that is iron-dependent, participates in various pathologies of cancer (CC). Nevertheless, the specific function that ferroptosis plays in the onset and progression of cervical cancer (CC) is yet uncertain. This research sought to examine the value of ferroptosis-related genes (FRGs) in the progression and prognosis of CC. Methods. Datasets containing RNA sequencing and corresponding clinical data of cervical cancer patients were obtained from searching publicly accessible databases. The “NMF” R package was conducted to calculate the matrix of the screened prognosis gene expression. Ferroptosis-related differential genes in cervical cancer were detected using the “limma” R function and WGCNA. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analysis were conducted to develop a novel prognostic signature. The prediction model was verified by the nomogram integrating clinical characteristics; the GSE44001 dataset was used as an external verification. Then, the immune status and tumor mutation load were explored. Finally, immunohistochemistry as well as quantitative polymerase chain reaction (RT-qPCR) was utilized to ascertain the expression of FRGs. Results. Two molecular subgroups (cluster 1 and cluster 2) with different FRG expression patterns were recognized. A ferroptosis-related model based on 4 genes (VEGFA, CA9, DERL3, and RNF130) was developed through TCGA database to identify the unfavorable prognosis cases. Patients in cluster 1 showed significantly decreased overall survival in contrast with those in cluster 2 (P

A major performance index for analyzing a stochastic transport network is the two-terminal capacity reliability Rd, defined as the probability that d units of goods can be successfully transported via stochastic arc capacities from the source to the destination. This paper presents an efficient d-minimal path method to calculate Rd based on some newly obtained results. The proposed method uses a simple method to check d-minimal path candidates and a more efficient approach to remove duplicate d-minimal paths that are the biggest obstacle in solving d-minimal paths, along with an indication of the advantage over the existing methods. Besides, sensitivity analysis is adopted to explore the most important arc whose reliability change affects the network reliability most significantly, which helps supervisor identify and enhance the critical arcs for improving the network reliability more effectively. Computational and application examples demonstrate the efficiency and utility of the method, respectively.

Tools for robust identification of crop diseases are crucial for timely intervention by farmers to minimize yield losses. Visual diagnosis of crop diseases is time-consuming and laborious, and has become increasingly unsuitable for the needs of modern agricultural production. Recently, deep convolutional neural networks (CNNs) have been used for crop disease diagnosis due to their rapidly improving accuracy in labeling images. However, previous CNN studies have mostly used images of single leaves photographed under controlled conditions, which limits operational field use. In addition, the wide variety of available CNNs and training options raises important questions regarding optimal methods of implementation of CNNs for disease diagnosis. Here, we present an assessment of seven typical CNNs (VGG-16, Inception-v3, ResNet-50, DenseNet-121, EfficentNet-B6, ShuffleNet-v2 and MobileNetV3) based on different training strategies for the identification of wheat main leaf diseases (powdery mildew, leaf rust and stripe rust) using field images. We developed a Field-based Wheat Diseases Images (FWDI) dataset of field-acquired images to supplement the public PlantVillage dataset of individual leaves imaged under controlled conditions. We found that a transfer-learning method employing retuning of all parameters produced the highest accuracy for all CNNs. Based on this training strategy, Inception-v3 achieved the highest identification accuracy of 92.5% on the test dataset. While lightweight CNN models (e.g., ShuffleNet-v2 and MobileNetV3) had shorter processing times (

Background: The relationship between utricle diseases and structural lesions is not very clear in the clinic due to the complexity and delicacy of the utricle structure. Therefore, it is necessary to study the perception mechanism of the utricle. Methods: Imitating the sensory cells in the macula of the utricle, a symmetrical metal core PVDF fiber (SMPF) was designed as a bionic hair sensor to fabricate a bionic macula (BM), a bionic macula with sand (BMS) and a bionic utricle (BU). Then experiments were carried out on them. Results: This indicated the SMPF sensor can sense its bending deformation, which was similar to the sensory cell. The amplitude of the output charges of the SMPF in BMS and BU were significantly improved. The SMPF, whose electrode boundary was perpendicular to the impact direction, exhibited the largest output charges. Conclusion: The presence of otoliths and endolymph can improve the sensing ability of the utricle. The human brain can judge the direction of head linear accelerations based on the location of the sensory cell in the macula that produces the largest nerve signals. This provides a possibility of studying utricle abnormal functions in vitro in the future.

Abstract Background Cervical cancer is the most common cancer among women in Nepal. The prevalence of human papillomavirus (HPV) 16 and or HPV 18 among women with cervical pre-cancer and cancer is higher than the incidence of HPV in the world population. The population-based epidemiological data of HPV in the general population in most parts of the country remains unknown. The objective of this study was to assess the prevalence and type distribution of HPV infection and association of abnormal cytology with high risk HPV infection among women in mid-western rural, Nepal. Methods A population-based cross sectional study was conducted in Jumla, one of the most remote districts in Nepal. A total of 1050 cervical samples were collected from married and non- pregnant women aged 20–65 years during mobile Cervical Cancer Screening Clinics conducted from May 2016 to January 2017. The presence of HPV DNA was firstly confirmed by HPV consensus PCR using PGMY09/PGMY11 designed primers, then HPV positive samples were further genotyped by the membrane hybridization method to detect the 21 high-risk HPV (HR-HPV) and low-risk HPV types. The prevalence of HR-HPV among women with normal and abnormal cytology was calculated. Data were analyzed using SPSS software for Windows. P

Most of modern technological networks that can perform their tasks with various distinctive levels of efficiency are multistate networks, and reliability is a fundamental attribute for their safe operation and optimal improvement. For a multistate network, the two-terminal reliability at demand level d, defined as the probability that the network capacity is greater than or equal to a demand of d units, can be calculated in terms of multistate minimal paths, called d-minimal paths (d-MPs) for short. This paper presents an efficient algorithm to find all d-MPs for the multistate two-terminal reliability problem. To advance the solution efficiency of d-MPs, an improved model is developed by redefining capacity constraints of network components and minimal paths (MPs). Furthermore, an effective technique is proposed to remove duplicate d-MPs that are generated multiple times during solution. A simple example is provided to demonstrate the proposed algorithm step by step. In addition, through computational experiments conducted on benchmark networks, it is found that the proposed algorithm is more efficient.

Background: Although step counters are popularly employed for physical rehabilitation in chronic obstructive pulmonary disease (COPD) patients, their effectiveness is inconsistent and even questioned. This meta-analysis aimed to investigate whether step counter use increases physical activity or improves exercise capacity in COPD patients. Methods: Electronic databases were searched for randomized controlled trials that assessed the efficacy of step counter use in increasing physical activity or in improving exercise capacity. Data were aggregated using a random-effects model to get the overall effect sizes [standard mean difference (SMD) with 95% confidence interval (CI)], and subgroup analyses were performed. Results: A total of 15 trials enrolling 1316 patients with moderate to severe COPD were included. Step counter use increased physical activity compared with controls (SMD = 0.57, 95% CI 0.31–0.84), which is equal to a magnitude of 1026 steps/day in daily steps. It also enhanced exercise capacity with an effect size of 0.30 (95% CI 0.16–0.45), approximating to a magnitude of 11.6 m in the 6-min walking distance. Step counter use could augment physical activity (SMD = 0.64, 95% CI 0.19–1.08) and exercise capacity (SMD = 0.32, 95% CI 0.01–0.62) for patients receiving pulmonary rehabilitation. Yet it cannot enhance physical activity or exercise capacity in patients with severe COPD or among studies with intervention durations ⩾6 months (both p > 0.50). Conclusions: Step counter use increases physical activity and improves exercise capacity in COPD patients, at least in the short term, which supports the notion of recommending step counter use in COPD management.

The fabrication and luminescent performance of novel phosphors Na2YMg2V3O12:Dy3+ were investigated by a conventional solid-state reaction method. Under near-UV light, the Na2YMg2V3O12 host self-activated and released a broad emission band (400−700 nm, with a peak at 524 nm) ascribable to charge transfer in the (VO4)3− groups. Meanwhile, the Na2YMg2V3O12:Dy3+ phosphors emitted bright yellow light within both the broad emission band of the (VO4)3- groups and the sharp peaks of the Dy3+ ions at 490, 582, and 663 nm at a quenching concentration of 0.03 mol. The emission of the as-prepared Na2YMg2V3O12:Dy3+ phosphors remained stable at high temperatures. The obtained phosphors, commercial Y2O3:Eu3+ red phosphors, and BaMgAl10O17:Eu2+ blue phosphors were packed into a white light-emitting diode (WLED) device with a near-UV chip. The designed WLED emitted bright white light with good chromaticity coordinates (0.331, 0.361), satisfactory color rendering index (80.2), and proper correlation to a color temperature (7364 K). These results indicate the potential utility of Na2YMg2V3O12:Dy3+ phosphor as a yellow-emitting phosphor in solid-state illumination.

Optimal sensor placement is an important part in the structural health monitoring of bridge structures. However, some defects are present in the existing methods, such as the focus on a single optimal index, the selection of modal order and sensor number based on experience, and the long computation time. A hybrid optimization strategy named MSE-AGA is proposed in this study to address these problems. The approach firstly selects modal order using modal participation factor. Then, the modal strain energy method is adopted to conduct the initial sensor placement. Finally, the adaptive genetic algorithm (AGA) is utilized to determine the optimal number and locations of the sensors, which uses the root mean square of off-diagonal elements in the modal assurance criterion matrix as the fitness function. A case study of sensor placement on a numerically simulated bridge structure is provided to verify the effectiveness of the MSE-AGA strategy, and the AGA method without initial placement is used as a contrast experiment. A comparison of these strategies shows that the optimal results obtained by the MSE-AGA method have a high modal strain energy index, a short computation time, and small off-diagonal elements in the modal assurance criterion matrix.