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The mining of Huanglong Coalfield faces a serious threat from roof sandstone water disaster of the extremely thick Luohe Formation. A laboratory study on the microscopic pore characteristics of the sandstone of the Luohe Formation in the Gaojiapu Coal Mine, Binchang Mining Area were carried out using various methods. XRD diffraction, casting thin sections, and scanning electron microscopy were combined to study the pore types of the sandstone particles. Overburden porosimeter was used to illustrate the variation characteristics of porosity and permeability under different confining pressures. High-pressure mercury injection and nuclear magnetic resonance techniques were used to characterize the pore-throat radius of the sandstone core, and X-ray three-dimensional CT scanning was used to quantitatively characterize sandstone pores larger than 9 μm. The results show that, ①the sandstone particles of medium-grained sandstone are larger, and the pore types are mainly residual intergranular pores with a small amount of intergranular dissolved pores, while the particles of fine-grained sandstone are smaller, and the intergranular pores are mostly filled with clay minerals, secondary dissolution intergranular pores, and a smaller degree of pore development.; ②The pore throat radius of large pores in medium-grained sandstone ranges from 0.61 to 4.94 μm, with a cumulative distribution frequency of 48%, while in fine-grained sandstone, the pore-throat radius ranges from 0.188 to 0.683 um, with a cumulative distribution frequency of 47%, indicating that medium-grained sandstone has larger pore-throat radius, which are more conducive to groundwater storage and migration.; ③CT scanning shows that the average surface porosity of medium-grained sandstone is 7.081%, and that of fine grained sandstone is 2.032%. The highly developed macropores (equivalent pore diameter > 180 μm) and micropores contribute to a higher surface porosity. Combined with a larger pore throat radius, the medium-grained sandstone presents a higher permeability. The microscopic pore characteristics of the two types of sandstone are consistent with the on-site evaluation result of the water yield propertyof the corresponding aquifer. The research findings can provide a basic reference for the prevention and control of water disasters from the sandstone roof of the Luohe Formation.

There are many types and numbers of mines in China, covering coal, metallurgy, non-ferrous metals, chemical industry and so on. Most of the mines use dewatering and drainage to control groundwater, and some of the water abundant mines have tens of thousands of m3 to hundreds of thousands of m3 of mine drainage per day, which causes the problems of declining groundwater level, water resources depletion, karst collapse and ground subsidence, surface water pollution, and deterioration of groundwater environment. In order to solve the problem of safe mining and water waste in water abundant mines, research on mine water cut-off curtain technology has been carried out since 1960 s, and after nearly 60 years of development, it has developed from single ground straight drilling and grouting to various water cut-off curtain technologies such as ground directional drilling and grouting, downhole drilling and grouting, combined drilling and grouting up and down the shaft, row of piles, continuous wall and seepage control membrane, etc. In more than 80 mines, semi-closed, closed, drop-bottom and suspended water interception curtains have been successfully applied, with water interception rate mostly above 60% and water level on the outside of the curtain significantly raised, achieving very good application results and protecting mine water resources and mine ecological environment. Four typical water interception curtain cases, such as metal mine karst fissure water fully closed curtain, coal mine bedrock drop bottom type slurry curtain, loose layer and karst stratum directional horizontal hole slurry curtain, loose layer impermeable membrane drop bottom type curtain, were selected for detailed elaboration, and the water interception technology and water resource protection effect of typical water interception curtain cases were analyzed, and the effective water interception rate was above 75%. Based on the development trend of curtain water interception technology, it is proposed that the technologies of continuous jointless water curtain in the lateral direction of loose layer, directional diffusion grouting in the lateral water curtain of bedrock, and lateral water curtain in the thick grass-roots level with low permeability are future directions, so as to practice the concept of “Green Mountains Are Mountains of Gold”, to protect the groundwater resources of mine, and to realize water conservation, ecology conservation, loss reduction and green mining.

The loose layers and shallow weathered bedrock in western China are rich in water, and the inclined shaft crossing the water-rich loose layer is prone to leak at the wellbore construction joints, concrete joints and wall cracks. Leakage will lead to the deterioration of underground working environment, lower working efficiency, increase the burden and cost of underground drainage, and affect the safety of coal mine production. In order to solve the above problems, this paper analyses the characteristics of water seepage in slanting coal mine shafts from the perspective of protecting groundwater resources and safe operation of shafts, and the existing management measures such as drainage, post-wall grouting, rotary pile spraying and curtain grouting. And the principle and structure of soil-cement curtain with equal thickness of water leakage level in inclined shaft, the basis of parameter selection and the method of curtain construction were studied. The effects of formation conditions, comprehensive moisture content, cement content and other factors on the performance of cement curtain were analyzed. The field test application of water leakage control of inclined shaft was carried out in test mining area. The research results shows that the water leakage of inclined shaft in coal mine mostly occurs in the bottom plate, waist wall and the joint of both, and the water inflow was tens of m3/h～ hundreds of m3/h, and some even had water gushing and carrying sand, endangering the safety of the shaft. The equal-thickness soil-cemented curtain forms an equal-thickness wall with uniform thickness, few joints and high water interception rate in the outer stratum of the slanting coal mine shaft through three steps: lateral cutting, retraction cutting and mixing, and slurry mixing to form a wall. It effectively blocks the the hydraulic connection between the inclined shaft, the outside loose layer and the weathered bedrock. The strength of the cement curtain of equal thickness is positively correlated with the cement admixture, and the permeability coefficient is negatively correlated with the cement admixture. The performance of the cement curtain of clay stratum is weaker than that of loess and fine sand stratum. The in-situ core sample of the curtain at the demonstration application site has a compressive strength of 8.62MPa and a permeability coefficient of 2.69×10−8 cm/s. The water influx in the borehole is reduced from 16.8 m3/h to about 1.6 m3/h, which is 90.5% less than before the treatment, and achieved good application results. This method can solve the seepage problem of inlcined shaft in loose layer in western China, ensure the safe operation of the well shaft, and protect the groundwater resources.

Abstract Background Antibiotics are widely used for prophylactic therapy and for improving the growth performance of chicken. The problem of bacterial drug resistance caused by antibiotic abuse has previously attracted extensive attention; however, the influence of early-day use of prophylactic antibiotics on the gut microflora and on the disease resistance ability in chicks has not been explored. Here, we comprehensively evaluate the growth performance, gut microbial dynamics, level of antibiotic resistance genes (ARGs) in the gut microbial community, and resistance to H9N2 avian influenza virus (AIV) in chickens following long-term and short-term early-day prophylactic antibiotic treatment. Results Unexpectedly, long-term prophylactic enrofloxacin treatment slowed the growth rate of chickens, whereas short-term antibiotics treatments were found to increase the growth rate, but these changes were not statistically significant. Strikingly, expansions of Escherichia-Shigella populations were observed in early-life prophylactic antibiotics-treated groups of chickens, which is in contrast to the general perception that antibiotics should control their pathogenicity in chicks. The gut microbiota composition of chickens treated long term with antibiotics or received early-day antibiotics treatment tend to be more dramatically disturbed compared to the gut microbiome of chickens treated with antibiotics for a short term at a later date, especially after H9N2 AIV infection. Conclusions Our data provide evidence that early-day and long-term antibiotic treatments have a more adverse effect on the intestinal microbiome of chickens, compared to short-term late age antibiotic treatment. Furthermore, our metagenomic data reveal that both long-term and short-term antibiotic treatment increase the relative abundance of ARGs. Our findings highlight the adverse effects of prophylactic antibiotic treatment and provide a theoretical basis for the cautious administration of antibiotics in food-producing animal management. Video Abstract

Abstract Optical cavities, resonant with vibrational or electronic transitions of material within the cavity, enable control of light-matter interaction. Previous studies have reported cavity-induced modifications of chemical reactivity, fluorescence, phase behavior, and charge transport. Here, we explore the effect of resonant cavity-phonon coupling on the transient photoconductivity in a hybrid organic-inorganic perovskite. To this end, we measure the ultrafast photoconductivity response of perovskite in a tunable Fabry–Pérot terahertz cavity, designed to be transparent for optical excitation. The terahertz-cavity field-phonon interaction causes apparent Rabi splitting between the perovskite phonon mode and the cavity mode. We explore whether the cavity-phonon interaction affects the material’s electron-phonon interaction by determining the charge-carrier mobility through photoconductivity. Despite the apparent hybridization of cavity and phonon modes, we show that the perovskite properties in both ground (phonon response) and excited (photoconductive response) states remain unaffected by the tunable light-matter interaction. Yet the response of the integral perovskite-terahertz optical cavity system depends critically on the interaction strength of the cavity with the phonon: the transient terahertz response to optical excitation can be increased up to threefold by tuning the cavity-perovskite interaction strength. These results enable tunable switches and frequency-controlled induced transparency devices.

Abstract The vehicle detection algorithm based on visual perception has been applied in all types of automatic driving scenes. However, there are still flaws in the current detection algorithm model, especially for small objects. The detection effect of vehicle objects with small pixels in the image is often missed and wrongly detected. This research proposes an improved feature fusion module based on double‐channel residual pyramid (DRP) structure for autonomous detection algorithm which named binary residual feature pyramid network (BiResFPN) to solve the above problems. Firstly, a DRP structure, which can effectively supplement the shallow information of the network, is proposed. The residual structure is added to the output feature map for further supplement. Then, an average sampling method of positive and negative samples based on intersection‐over‐union (IOU) value is proposed on the basis of this structure, aimed at the unbalanced sampling of positive and negative samples in the training stage of faster regions with CNN features (RCNN). It leads to the reduction of the interference of a large number of simple negative samples, which makes the learned model better. The experimental results based on the KITTI and BDD100K dataset datasets show that the capability of the feature fusion module based on DRP structure is strong for small object detection. Compared with Faster‐RCNN (FPN), the detection algorithm of small object detection accuracy APsmall was increased by 2.6%, APmedium and APlarge was increased by 1.1% and 0.3%.

The Jinchanghe Pb-Zn polymetallic deposit is a representative distal skarn deposit in the Baoshan block. Due to limited research on the sources of ore-forming metals and trace elemental geochemistry of sulfides, the sources and mineralization environments of the Jinchanghe skarn Pb-Zn polymetallic deposit are still controversial. In this study, copper and sulfur isotopes and trace elements of sulfides from the Jinchanghe Pb-Zn polymetallic deposit were analyzed to reveal the sources of ore-forming materials and the ore-forming environments. The trace elemental analysis results show abundant Co, Ni, Mn and Se elements, and less As, Tl and Sb elements dominantly enter pyrite by isomorphic substitution, except for some Zn and Cu that occur as sulfide inclusions in Py1. Abundant Fe and Mn elements could substitute Zn to enter the sphalerite crystal lattice by the isomorphic substitution mechanism of (Fe2+ + Mn2+) ↔ 2Zn2+, and less Ag and Sb elements could enter the sphalerite by the isomorphic substitution mechanism of (Ag+ + Sb3+) ↔ 2Zn2+. The Cu-S isotopic and trace elemental compositions jointly suggest that the Jinchanghe distal skarn Pb-Zn polymetallic deposit formed from magmatic hydrothermal fluids with a sedimentary host-rock contribution, under mesothermal conditions (260 °C on sphalerite).

Salicornia europaea L. is a well-known model plant for studying the mechanism of salt tolerance. A substantial decline in the S. europaea population has been observed in the semi-arid steppe of the Mongolian Plateau. The relationship between environmental factors and its population dynamics in the grassland ecosystem remains inadequately investigated. Rhizosphere microbial communities, representing the most direct and influential biological factors affecting plant populations, have received limited research attention in the context of halophytes. Four density treatments of S. europaea (bare land—SEB, low density—SEL, medium density—SEM, and high density—SEH) in a single-factor randomized-block design with five replications were established to evaluate the relationship between rhizosphere soil bacterial communities and environmental factors. The results showed that as the density of S. europaea increased, the soil pH decreased, while available phosphorus increased. Rhizosphere soil bacterial communities associated with S. europaea populations in the saline-alkali wetland were dominated by Proteobacteria, Bacteroidota, Actinobacteria, Gemmatimonadota, and Halobacterota. Notably, the genera Antarcticibacterium, Wenzhouxiangella, BD2-11_terrestrial_groupBD2-11, Halomonas, and Natronorubrum were found to be particularly abundant. The Simpson index of the rhizosphere soil bacterial community in the S. europaea treatments was significantly higher than that in bare land. Soil pH and nitrate nitrogen were the primary environmental drivers of the rhizosphere bacterial community. Overall, the rhizosphere soil’s bacterial diversity in saline wetlands under a high-salt environment was not affected by the decrease in the S. europaea population. S. europaea plays an important role in shaping soil bacterial community structure through its influence on the surrounding soil environment. The cultivation of S. europaea is a phytoremediation strategy to improve soil salinization.

In a hyperspectral image, there is a close correlation between spectra and a certain degree of correlation in the pixel space. However, most existing low-rank representation (LRR) methods struggle to utilize these two characteristics simultaneously to detect anomalies. To address this challenge, a novel low-rank representation with dual graph regularization and an adaptive dictionary (DGRAD-LRR) is proposed for hyperspectral anomaly detection. To be specific, dual graph regularization, which combines spectral and spatial regularization, provides a new paradigm for LRR, and it can effectively preserve the local geometrical structure in the spectral and spatial information. To obtain a robust background dictionary, a novel adaptive dictionary strategy is utilized for the LRR model. In addition, extensive comparative experiments and an ablation study were conducted to demonstrate the superiority and practicality of the proposed DGRAD-LRR method.

The myocyte enhancer factor 2 (MEF2) gene family play fundamental roles in the genetic programs that control cell differentiation, morphogenesis, proliferation, and survival in a wide range of cell types. More recently, these genes have also been implicated as drivers of carcinogenesis, by acting as oncogenes or tumor suppressors depending on the biological context. Nonetheless, the molecular programs they regulate and their roles in tumor development and progression remain incompletely understood. The present study evaluated whether the MEF2D transcription factor functions as a tumor suppressor in breast cancer. The knockout of the MEF2D gene in mouse mammary epithelial cells resulted in phenotypic changes characteristic of neoplastic transformation. These changes included enhanced cell proliferation, a loss of contact inhibition, and anchorage-independent growth in soft agar, as well as the capacity for tumor development in mice. Mechanistically, the knockout of MEF2D induced the epithelial-to-mesenchymal transition (EMT) and activated several oncogenic signaling pathways, including AKT, ERK, and Hippo-YAP. Correspondingly, a reduced expression of MEF2D was observed in human triple-negative breast cancer cell lines, and a low MEF2D expression in tissue samples was found to be correlated with a worse overall survival and relapse-free survival in breast cancer patients. MEF2D may, thus, be a putative tumor suppressor, acting through selective gene regulatory programs that have clinical and therapeutic significance.

Artificially modified adsorbing materials mainly aim to remedy the disadvantages of natural materials as much as possible. Using clay materials such as rectorite, sodium bentonite and metakaolinite (solid waste material) as base materials, hydrothermally modified and unmodified materials were compared. CM-HT and CM (adsorbing materials) were prepared and used to adsorb and purify wastewater containing malachite green (MG) dye, and the two materials were characterized through methods such as BET, FT-IR, SEM and XRD. Results: (1) The optimal conditions for hydrothermal modification of CM-HT were a temperature of 150 °C, a time of 2 h, and a liquid/solid ratio 1:20. (2) Hydrothermal modification greatly increased the adsorptive effect. The measured maximum adsorption capacity of CM-HT for MG reached 290.45 mg/g (56.92% higher than that of CM). The theoretical maximum capacity was 625.15 mg/g (186.15% higher than that of CM). (3) Because Al-OH and Si-O-Al groups were reserved in unmodified clay mineral adsorbing materials with good adsorbing activity, after hydrothermal modification, the crystal structure of the clay became loosened along the direction of the c axis, and the interlayer space increased to partially exchange interlayer metal cations connected to the bottom oxygen, giving CM-HT higher electronegativity and creating more crystal defects and chemically active adsorbing sites for high-performance adsorption. (4) Chemical adsorption was the primary way by which CM-HT adsorbed cationic dye, while physical adsorption caused by developed pore canal was secondary. The adsorption reaction occurred spontaneously.

Millimeter wave (mmWave) unmanned aerial vehicle (UAV)-aided networks have enormous application potential due to their large bandwidth and ultra-high speed, being regarded as an effective technology for improving the reliability of military and civilian fields. However, due to their complex electromagnetic spectrum environment and the sensitivity of mmWaves to blocking effects, its performance analysis faces certain difficulties. This article investigates the coverage and network capacity of mmWave UAV-aided networks under significant blocking effects and complex electromagnetic environments; for this purpose, we equipped each UAV with mmWave antennas featuring adjustable beamwidth and direction. A Matérn hard-core point process (MHCPP) with repulsion constraints was also employed to reflect the minimum distance constraints to isolate the mutual interference between UAVs. Then, using a stochastic geometric analysis, we derived the coverage and capacity characteristics and further obtained a closed-form expression for the network coverage probability. Finally, the simulation results showed that the network throughput could reach 86% when the density of UAVs was half of that of ground base stations (GBSs) in the city center, validating the efficiency and accuracy of our theoretical derivations.

Selective hydrogenation over earth-abundant metal catalysts is challenging but particularly valuable for practical applications in heterogeneous catalysis. Herein, we demonstrate that the catalytic selectivity of the commercial Raney nickel catalyst can be greatly tuned by modulation of the nickel surface by silica. Using quinoline hydrogenation as a model, we show that the silica-modified Raney nickel catalysts exhibit good activity, excellent selectivity, and long stability, whereas the undesired overhydrogenation reactions are effectively hindered. In contrast, the pristine Raney nickel catalyst shows inferior selectivity for the targeted product. Mechanistic studies confirm a positive role of silica to facilitate the desorption of 1,2,3,4-tetrahydroquinoline from the catalyst surface, thus enhancing the product selectivity.

Abstract Connected and Autonomous Vehicles (CAVs) can receive various information from surrounding vehicles through Vehicle‐to‐Everything (V2X) communication technologies and adjust their car‐following behaviour accordingly. Although several studies have evaluated the impact of CAVs on traffic flow stability in a small segment of networks, most approaches are focused on their specific applications considering the trajectory information, and there is a lack of studies analyzing the impact of CAVs on a large‐scale network. This paper proposes a novel viscous continuum traffic model considering the anticipation of space headway, the throttle angle, and brake torque information during cooperative car‐following. The methods employed to develop the new car‐following model and its counterpart continuum traffic model have been described. The linear and non‐linear stability analyses of the newly developed model have been conducted to obtain the critical stability factors in small perturbations. Numerical simulations have been carried out to investigate the effect of the anticipation, the throttle angle, and brake torque information on traffic stability, fuel consumption, and exhaust emissions. The numerical results reveal that the anticipation of space headway and the transmission of the throttle angle and brake torque information during cooperative car‐following manoeuvres can improve the traffic flow stability and reduce fuel consumption and emissions.

Abstract Hydroformylation is one of the largest industrially homogeneous processes that strongly relies on catalysts with phosphine ligands such as the Wilkinson’s catalyst (triphenylphosphine coordinated Rh). Heterogeneous catalysts for olefin hydroformylation are highly desired but suffer from poor activity compared with homogeneous catalysts. Herein, we demonstrate that rhodium nanoparticles supported on siliceous MFI zeolite with abundant silanol nests are very active for hydroformylation, giving a turnover frequency as high as ~50,000 h−1 that even outperforms the classical Wilkinson’s catalyst. Mechanism study reveals that the siliceous zeolite with silanol nests could efficiently enrich olefin molecules to adjacent rhodium nanoparticles, enhancing the hydroformylation reaction.

Abstract Wildlife is reservoir of emerging viruses. Here we identified 27 families of mammalian viruses from 1981 wild animals and 194 zoo animals collected from south China between 2015 and 2022, isolated and characterized the pathogenicity of eight viruses. Bats harbor high diversity of coronaviruses, picornaviruses and astroviruses, and a potentially novel genus of Bornaviridae. In addition to the reported SARSr-CoV-2 and HKU4-CoV-like viruses, picornavirus and respiroviruses also likely circulate between bats and pangolins. Pikas harbor a new clade of Embecovirus and a new genus of arenaviruses. Further, the potential cross-species transmission of RNA viruses (paramyxovirus and astrovirus) and DNA viruses (pseudorabies virus, porcine circovirus 2, porcine circovirus 3 and parvovirus) between wildlife and domestic animals was identified, complicating wildlife protection and the prevention and control of these diseases in domestic animals. This study provides a nuanced view of the frequency of host-jumping events, as well as assessments of zoonotic risk.

Communication interference identification is critical in electronic countermeasures. However, existed methods based on deep learning, such as convolutional neural networks (CNNs) and transformer, seldom take both local characteristics and global feature information of the signal into account. Motivated by the local convolution property of CNNs and the attention mechanism of transformer, we designed a novel network that combines both architectures, which make better use of both local and global characteristics of the signals. Additionally, recognizing the challenge of distinguishing contextual semantics within the one-dimensional signal data used in this study, we advocate the use of CNNs in place of word embedding, aligning more closely with the intrinsic features of the signal data. Furthermore, to capture the time-frequency characteristics of the signals, we integrate the proposed network with a cross-attention mechanism, facilitating the fusion of temporal and spectral domain feature information through multiple cross-attention computational layers. This innovation obviates the need for specialized time-frequency analysis. Experimental results demonstrate that our approach significantly improves recognition accuracy compared to existing methods, highlighting its efficacy in addressing the challenge of communication interference identification in electronic warfare.

Background and aimsDyslipidemia is known to contribute to arterial stiffness, while the inverse association remains unknown. This study aimed to explore the association of baseline arterial stiffness and its changes, as determined by brachial-ankle pulse wave velocity (baPWV), with dyslipidemia onset in the general population.MethodsThis study enrolled participants from Beijing Health Management Cohort using measurements of the first visit from 2012 to 2013 as baseline, and followed until the dyslipidemia onset or the end of 2019. Unadjusted and adjusted Cox proportional regression models were used to evaluate the associations of baseline baPWV and baPWV transition (persistent low, onset, remitted and persistent high) with incident dyslipidemia.ResultsOf 4362 individuals (mean age: 55.5 years), 1490 (34.2%) developed dyslipidemia during a median follow-up of 5.9 years. After adjusting for potential confounders, participants with elevated arterial stiffness at baseline had an increased risk of dyslipidemia (HR, 1.194; 95% CI, 1.050-1.358). Compared with persistent low baPWV, new-onset and persistent high baPWV were associated with a 51.2% and 37.1% excess risk of dyslipidemia.ConclusionThe findings indicated that arterial stiffness is an early risk factor of dyslipidemia, suggesting a bidirectional association between arterial stiffness and lipid metabolism.

Introduction: Phasor measurement is crucial for the monitoring and management of power grids. Traditional hardware-based phasor measurement units (PMUs) are effective but often complex and expensive. This paper introduces a software-based phasor measurement method that utilizes soft synchronization with temporal pulse signals from GPS and mobile communication stations, offering a simpler and cost-effective alternative.Methods: The proposed method synchronizes the local oscillator with Pulse Per Second (PPS) signals from GPS and primary synchronization signals from mobile communication bases. Raw data affected by the local oscillator’s instability are transformed into calibrated data using B-Spline interpolation to emulate an ideal sampling rate. The calibrated data are then subjected to a Recursive Discrete Fourier Transform (RDFT) algorithm for synchronized phasor measurement.Results: The method’s performance was assessed in compliance with the C37.118.1 standard. Key performance indicators, such as frequency, phase, and Total Vector Error (TVE), were evaluated. The proposed software-based approach demonstrated high accuracy in synchronized phasor measurements.Discussion: The results confirm that the proposed method can serve as a highly accurate and simpler alternative to conventional hardware-based solutions. Its application promises to advance synchronized phasor measurement practices in power grid monitoring, enhancing reliability and reducing complexity and costs.

Objective: The objective of this study was to investigate the use of contrast-enhanced magnetic resonance imaging (CE-MRI) combined with radiomics and deep learning technology for the identification of spinal metastases and primary malignant spinal bone tumor. Methods: The region growing algorithm was utilized to segment the lesions, and two parameters were defined based on the region of interest (ROI). Deep learning algorithms were employed: improved U-Net, which utilized CE-MRI parameter maps as input, and used 10 layers of CE images as input. Inception-ResNet model was used to extract relevant features for disease identification and construct a diagnosis classifier. Results: The diagnostic accuracy of radiomics was 0.74, while the average diagnostic accuracy of improved U-Net was 0.98, respectively. the PA of our model is as high as 98.001%. The findings indicate that CE-MRI based radiomics and deep learning have the potential to assist in the differential diagnosis of spinal metastases and primary malignant spinal bone tumor. Conclusion: CE-MRI combined with radiomics and deep learning technology can potentially assist in the differential diagnosis of spinal metastases and primary malignant spinal bone tumor, providing a promising approach for clinical diagnosis.

Abstract To support artificial intelligence (AI)‐involved tasks offloaded from the mobile devices (MDs), it is necessary to equip the Unmanned Aerial Vehicle (UAV) with custom‐made co‐processor (CP) for handling AI workloads in multi‐UAV‐empowered Edge Intelligence. Existing CPU‐oriented task scheduling algorithm cannot apply to the CPU+CP heterogeneous architecture. In this backdrop, this paper first formulates the joint service function placement, collaborative task scheduling, UAV deployment, and MD position determination problem as a Mixed Integer Non‐Linear Programming problem. Then, an alternating optimization‐based algorithm is put forward to derive a sub‐optimal solution of the problem utilizing Differential Evolution and Greedy‐based Hungarian algorithms. A series of experiments are conducted to evaluate the performance of the proposal. Results show that authors' proposal can achieve an overall revenue that is roughly 50% higher than those of existing methods.

The tribological properties of the self-lubricating polymer were improved by strengthening the properties of the transfer film. The graphene oxide (GO) reinforced polytetrafluoroethylene (PTFE)/poly-p-phenylene terephthamide (PPTA) composites (GPPs) were prepared by dual-size synthesis. The tribological properties of GPPs were studied on a ball-on-disk tribometer. GPPs have low friction coefficient (minimum = 0.061) and hydrophobicity (maximum = 137.1385°). The structure–property relationships and the practical effect of transfer film enhancement induced by GO were revealed. We attempt to provide guidance for the GO reinforced self - lubricating polymers design. Finally, in light of the excellent properties of GPPs, this study provides guidance for the GO reinforced self - lubricating polymers design.

At present, in arbitrary-oriented object detection, the angular periodicity problem of rotated bounding box described by angle causes an object to have different numerical representations, which leads to uncertainty of rotated bounding box regression. To eliminate the angular periodicity problem, in this article, we propose a novel and simple ellipse parameters representation method for arbitrary-oriented object, which hides the angle of the object in the focal vector of ellipse to avoid direct angle prediction. Moreover, the proposed representation method can enable the arbitrary-oriented object to have only one numerical representation, which is beneficial to alleviate the uncertainty of bounding box regression. In order to adapt the proposed ellipse parameters representation method, we adopt 2-D Gaussian distribution label assign for coarse samples selection, then the Kullback–Leibler divergence loss and SimOTA are used to refine the coarse samples to obtain the best positive samples. We extend the YOLOX with medium parameters as an oriented ship detector according to the proposed ellipse parameters representation method, and conduct the experiments on HRSC2016, RSDD-SAR, and RHRSID to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed representation method achieves impressive results compared with state-of-the-art arbitrary-oriented object detection methods.

This paper aims to establish a driving style recognition method that is highly accurate, fast and generalizable, considering the lack of data types in driving style classification task and the low recognition accuracy of widely used unsupervised clustering algorithms and single convolutional neural network methods. First, we propose a method to collect the information on driver’s operation time sequence in view of the imperfect driving data, and then extract the driver’s style features through convolutional neural network. Then, for the collected temporal data, the Long Short Term Memory networks (LSTM) module is added to encode and transform the driving features, to achieve the driving style classification. The results show that the accuracy of driving style recognition reaches over 93%, while the speed is improved significantly.

The low rank and sparse representation (LRSR) technique has attracted increasing attention for hyperspectral anomaly detection (HAD). Although a large quantity of research based on LRSR for HAD is proposed, the detection performance is still limited, due to the unsatisfactory dictionary construction and insufficient consideration of global and local characteristics. To tackle the above-mentioned concern, a novel HAD method, termed dual collaborative constraints regularized low-rank and sparse representation via robust dictionaries construction, is proposed in this article. Concretely, a robust dictionary construction strategy, which thoroughly excavates the potential of the density estimation model and local outlier factor, is proposed to yield pure and representative dictionary atoms. To fully exploit the global and local characteristics of hyperspectral images, dual collaborative constraints corresponding to the background and anomaly components are imposed on the LRSR model. Notably, two weighted matrices are further exerted on the representation coefficients to improve the effect of collaborative constraints, considering the fact that the surrounding pixels similar to the testing pixel should be given a large weight, otherwise the weight is expected to be small. In this way, the background and anomaly components can be well modeled. Additionally, a nonlinear transformation operation, which combines the output of the density estimation model and local outlier factor with the detection result derived from the LRSR model, is developed to suppress the background. The experiments conducted on one simulated dataset and three real datasets demonstrate the superiority of the proposed method compared with the four typical methods and four state-of-the-art methods.

Abstract This study presents a high efficiency Ho:YAG laser based on a narrow linewidth tunable 1.91 μm laser. A tunable Tm:YLF laser is the pump source and the wavelength continuous tunability ranges from 1906.04 to 1908.83 nm, corresponding to a linewidth of less than 0.41 nm. The tunable Tm:YLF laser is achieved by changing the operating temperature of the VBG. The output power of the Ho:YAG laser is between 21.04 and 23.53 W and the slope efficiency is between 64.08 and 68.26% at the pump power of 39.8 W. The output power and slope efficiency corresponding to the pump wavelength of 1907.36 nm are 23.53 W and 68.26%, respectively. This study illustrates that fine-tuning the pump wavelength is an effective way to improve the slope efficiency and output power of the Ho:YAG laser at room temperature.

Sparse representation (SR)-based approaches and collaborative representation (CR)-based methods are proved to be effective to detect the anomalies in a hyperspectral image (HSI). Nevertheless, the existing methods for achieving hyperspectral anomaly detection (HAD) generally only consider one of them, failing to comprehensively exploit them to further promote the detection performance. To address the issue, a novel HAD method, which integrates both SR and CR, is proposed in this article. To be specific, an SR model, whose overcomplete dictionary is generated by means of the density-based clustering algorithm and superpixel segmentation method, is first constructed for each pixel in an HSI. Then, for each pixel in an HSI, the used atoms in SR model are sifted to form the background dictionary corresponding to the CR model. To fully exploit both SR and CR information, we further combine the residual features obtained from both SR and CR model by the nonlinear transformation function to generate the response map. Finally, to preserve contour information of the objects, a postprocessing operation with guided filter is imposed into the response map to acquire the detection result. Experiments conducted on simulated and real datasets demonstrate that the proposed SRCR outperforms the state-of-the-art methods.

Human–machine interface technology is fundamentally constrained by the dexterity of motion decoding. Simultaneous and proportional control can greatly improve the flexibility and dexterity of smart prostheses. In this research, a new model using ensemble learning to solve the angle decoding problem is proposed. Ultimately, seven models for angle decoding from surface electromyography (sEMG) signals are designed. The kinematics of five angles of the metacarpophalangeal (MCP) joints are estimated using the sEMG recorded during functional tasks. The estimation performance was evaluated through the Pearson correlation coefficient (CC). In this research, the comprehensive model, which combines CatBoost and LightGBM, is the best model for this task, whose average CC value and RMSE are 0.897 and 7.09. The mean of the CC and the mean of the RMSE for all the test scenarios of the subjects’ dataset outperform the results of the Gaussian process model, with significant differences. Moreover, the research proposed a whole pipeline that uses ensemble learning to build a high-performance angle decoding system for the hand motion recognition task. Researchers or engineers in this field can quickly find the most suitable ensemble learning model for angle decoding through this process, with fewer parameters and fewer training data requirements than traditional deep learning models. In conclusion, the proposed ensemble learning approach has the potential for simultaneous and proportional control (SPC) of future hand prostheses.

Bovine leukemia virus (BLV) is a retrovirus that causes enzootic bovine leucosis (EBL), which is the most significant neoplastic disease in cattle. Although EBL has been successfully eradicated in most European countries, infections continue to rise in Argentina, Brazil, Canada, Japan, and the United States. BLV imposes a substantial economic burden on the cattle industry, particularly in dairy farming, as it leads to a decline in animal production performance and increases the risk of disease. Moreover, trade restrictions on diseased animals and products between countries and regions further exacerbate the problem. Recent studies have also identified fragments of BLV nucleic acid in human breast cancer tissues, raising concerns for public health. Due to the absence of an effective vaccine, controlling the disease is challenging. Therefore, it is crucial to accurately detect and diagnose BLV at an early stage to control its spread and minimize economic losses. This review provides a comprehensive examination of BLV, encompassing its genomic structure, epidemiology, modes of transmission, clinical symptoms, detection methods, hazards, and control strategies. The aim is to provide strategic information for future BLV research.

Abstract 2D lead halide perovskites (LHPs) show strong excitonic and spin‐orbit coupling effects, generating a facile spin injection. Besides, they possess a polaron character due to the soft crystal lattice, which can prolong the spin lifetime, making them favorable materials for spintronic applications. Here, the spin dynamics of 2D PEA2PbI4(MAPbI3)n−l thin films with different layers by temperature‐ and pump fluence–dependent circularly polarization‐resolved transient absorption (TA) measurements is studied. These results indicate that the spin depolarization mechanism is gradually converted from the Maialle–Silva–Sham (MSS) mechanism to the polaronic states protection mechanism with the layer number increasing from = 1 to 3, which is determined by the interplay between the strength of Coulomb exchange interaction and the strength of polaronic effect. While for ≥ 4, the Elliot–Yafet (EY) impurities mechanism is proposed, in which the formed polaronic states with free charge carriers no longer play the protective role.

This study investigated the distribution features of uranium-238 (238U), radium-226 (226Ra), thorium-232 (232Th), and potassium-40 (40K) and evaluated the associated environmental radiological hazards of the topsoil and river sediments in the Jinding lead-zinc (Pb-Zn) mine catchment from Southwest China. The activity concentrations of 238U, 226Ra, 232Th, and 40K ranged from 24.0 ± 2.29–60.3 ± 5.26 Bq.kg-1, from 32.5 ± 3.95–69.8 ± 3.39 Bq.kg-1, from 15.3 ± 2.24–58.3 ± 4.92 Bq.kg-1, and from 203 ± 10.2–1140 ± 27.4 Bq.kg-1, respectively. The highest activity concentrations for all these radionuclides were primarily found in the mining areas and decreased with increasing distance from the mining sites. The radiological hazard indices, including radium equivalent activity, absorbed gamma dose rate in the air, outdoor annual effective dose equivalent, annual gonadal dose equivalent, and excess lifetime cancer, revealed that the highest values were observed in the mining area and downstream, specifically in the vicinity of the ore body. These elevated values exceeded the global mean value but remained below the threshold value, suggesting that routine protection measures for Pb-Zn miners during production activities are sufficient. The correlation analysis and cluster analysis revealed strong associations between radionuclides such as 238U, 226Ra, and 232Th, indicating a common source of these radionuclides. The activity ratios of 226Ra/238U, 226Ra/232Th, and 238U/40K varied with distance, suggesting the influence of geological processes and lithological composition on their transport and accumulation. In the mining catchment areas, the variations in these activity ratios increased indicated the impact of limestone material dilution on the levels of 232Th, 40K, and 238U in the upstream region. Moreover, the presence of sulfide minerals in the mining soils contributed to the enrichment of 226Ra and the removal of 238U caused those activity ratios decreased in the mining areas. Therefore, in the Jinding PbZn deposit, the patterns of mining activities and surface runoff processes in the catchment area favored the accumulation of 232Th and 226Ra over 40K and 238U. This study provides the first case study on the geochemical distributions of natural radionuclides in a typical Mississippi Valley-type PbZn mining area and offers fundamental information on radionuclide migration and baseline radiometric data for PbZn deposits worldwide.

As an immune adjuvant, proinflammatory allogeneic dendritic cells (AlloDCs) have demonstrated promising immune-priming effects in several preclinical and clinical studies. The effector cells, including NK cells and T cells are widely acknowledged as pivotal factors in the effectiveness of cancer immunotherapy due to their ability to selectively identify and eradicate malignant cells. 4-1BB, as a costimulatory receptor, plays a significant role in the stimulation of effector cell activation. This study evaluated the anti-tumor effects when combining intratumoral administration of the immune-adjuvant AlloDCs with systemic α4-1BB treatment directly acting on effector cells. In both the CT-26 murine colon carcinoma model and B16 murine melanoma model, AlloDCs demonstrated a significant enhancement in the therapeutic efficacy of α4-1BB antibody. This enhancement was observed through the delayed growth of tumors and prolonged survival. Analysis of the tumor microenvironment (TME) in the combined-treatment group revealed an immune-inflamed TME characterized by increased infiltration of activated endogenous DCs and IFNγ+ CD8+ T cells, showing reduced signs of exhaustion. Furthermore, there was an augmented presence of tissue-resident memory (TRM) CD8+ T cells (CD103+CD49a+CD69+). The combination treatment also led to increased infiltration of CD39+CD103+ tumor-specific CD8+ T cells and neoantigen-specific T cells into the tumor. Additionally, the combined treatment resulted in a less immunosuppressive TME, indicated by decreased infiltration of myeloid-derived suppressor cells and Tregs. These findings suggest that the combination of intratumoral AlloDCs administration with systemic agonistic α4-1BB treatment can generate a synergistic anti-tumor response, thereby warranting further investigation through clinical studies.

To improve the performance and efficiency of ordinary galloping energy harvesters (GEHs), this paper proposes a GEH with a striped bluff body. The fluid-structure coupling simulation of the bluff body and the oscillator of the energy harvester was carried out using COMSOL Multiphysics. The cloud diagram in the flow field, tip displacement at the tip of the beam, lifting and dragging force, and trace and frequency response of the harvester are analyzed. Simulation results show that the GEH with a striped bluff body has the characteristics of rising frequency and falling peak compared with the ordinary GEH, which can be locked at a fixed peak to form a stable periodic response. Experimental results show that the striped bluff body energy harvester displays better energy harvest performance. The output root mean square voltage can be increased by 119.2% at 2 m/s wind speed, which means that the galloping harvester with a striped bluff body has more stable dynamic characteristics and shows better energy harvest performance.

Background Long-term asexual reproduction can easily lead to the degradation of plant germplasm, serious diseases and insect pests, reduction of production and even catastrophic crop failure. “Mountain Breeding and Dam Cultivation” is the main cultivation mode of Ligusticum chuanxiong Hort., which successfully avoided the germplasm degradation caused by long-term asexual reproduction. The recombination of endophytic fungi of L. chuanxiong caused by off-site transplantation was considered to be an important reason for its germplasm rejuvenation. However, whether bacteria have the same regularity is not yet known. Methods In this study, we carried out the experiment of cultivating propagation materials of L. chuanxiong in different regions and transplanting them to the same region. High-throughput sequencing was performed to analyze the bacterial communities in L. chuanxiong and its soil. Results The results showed that after transplanting, the plant height, tiller number, fresh weight, etc. of L. chuanxiong in mountainous areas were significantly higher than those in dam areas. At the same time, significant changes had taken place in the endophytic bacteria in reproductive material stem nodes (Lingzi, abbreviated as LZ). The diversity and abundance of bacteria in dam area LZ (YL) are significantly higher than those in mountainous area LZ (ML). The relative abundance of bacteria such as Xanthobacteraceae, Micromonosporaceae, Beijerinkiaceae, Rhodanobacteria, in ML is significantly higher than YL, mainly classified in Proteobateria and Actinobacteriota. In addition, the abundance advantage of Actinobacteriota still exists in MY (underground mature rhizomes obtained by ML). Meanwhile, the bacterial community was different in different area of transplanting. The diversity of bacterial communities in dam soil (YLS) is significantly higher than that in mountain soil (MLS). MLS had more Acidobacteriota than YLS. Comparative analysis showed that 74.38% of bacteria in ML are found in MLS, and 87.91% of bacteria in YL are found in YLS. Conclusions We can conclude that the community structure of endophytic bacteria recombined after the transplantation of L. chuanxiong, which was related to the bacterial community in soils. Moreover, after transplanting in mountainous areas, LZ accumulated more potentially beneficial Actinobacteriota, which may be an important reason for promoting the rejuvenation of germplasm in L. chuanxiong. However, this hypothesis requires more specific experiments to verify. This study provided a new idea that off-site transplanting may be a new strategy to restore vegetative plant germplasm resources.

BackgroundVertebral artery stenosis and occlusion (VASO) is a high-risk factor for posterior circulation stroke. Post-stent restenosis and drug tolerance have facilitated the exploration of microsurgical vascular reconstruction. This study aims to evaluate the safety and efficacy of microsurgical reconstruction of the proximal VA.MethodsTwenty-nine patients (25 men, aged 63.2 years) who had symptoms of posterior circulation ischemia underwent microsurgical revascularization for proximal VASO were retrospectively included in this study. Procedural complications and clinical and angiographic outcomes were reviewed.ResultsTwelve, three, and five patients underwent VA endarterectomy, artery transposition, or both, respectively; seven patients underwent vertebral endarterectomy plus stent implantation; and two patients failed surgery because of the difficult exposure of the VA and the occurrence of vascular dissection. The perioperative period-related complications included seven cases of Horner’s syndrome, five cases of hoarseness, and one case of chylothorax. No cases of perioperative stroke or death were reported. The mean follow-up period was 28.4 (8–62 months). Most patients improved clinically; however, the vertebrobasilar ischemia symptoms did not decrease significantly in two patients during the follow-up. Moreover, follow-up imaging was performed in all the patients, and no signs of anastomotic stenosis were reported.ConclusionMicrosurgical reconstruction is an alternative option that can effectively treat refractory proximal VASO disease and in-stent stenosis, with a high rate of postoperative vascular recirculation. Prospective cohort studies with larger sample sizes must be conducted to validate the above conclusions.

With the ability to produce components with complex and precise structures, additive manufacturing or 3D printing techniques are now widely applied in both industry and consumer markets. The emergence of tissue engineering has facilitated the application of 3D printing in the field of biomedical implants. 3D printed implants with proper structural design can not only eliminate the stress shielding effect but also improve in vivo biocompatibility and functionality. By combining medical images derived from technologies such as X-ray scanning, CT, MRI, or ultrasonic scanning, 3D printing can be used to create patient-specific implants with almost the same anatomical structures as the injured tissues. Numerous clinical trials have already been conducted with customized implants. However, the limited availability of raw materials for printing and a lack of guidance from related regulations or laws may impede the development of 3D printing in medical implants. This review provides information on the current state of 3D printing techniques in orthopedic implant applications. The current challenges and future perspectives are also included.

IntroductionGlioblastoma (GBM), the most lethal primary brain malignancy, is divided into histological (hist-GBM) and molecular (mol-GBM) subtypes according to the 2021 World Health Organization classification of central nervous system tumors. This study aimed to characterize the clinical, radiological, molecular, and survival features of GBM under the current classification scheme and explore survival determinants.MethodsWe re-examined the genetic alterations of IDH-wildtype diffuse gliomas at our institute from 2011 to 2022, and enrolled GBMs for analysis after re-classification. Univariable and multivariable analyses were used to identify survival determinants.ResultsAmong 209 IDH-wildtype gliomas, 191 were GBMs, including 146 hist-GBMs (76%) and 45 mol-GBMs (24%). Patients with mol-GBMs were younger, less likely to develop preoperative motor dysfunction, and more likely to develop epilepsy than hist-GBMs. Mol-GBMs exhibited lower radiographic incidences of contrast enhancement and intratumoral necrosis. Common molecular features included copy-number changes in chromosomes 1, 7, 9, 10, and 19, as well as alterations in EGFR, TERT, CDKN2A/B, and PTEN, with distinct patterns observed between the two subtypes. The median overall survival (mOS) of GMB was 12.6 months. Mol-GBMs had a higher mOS than hist-GBMs, although not statistically significant (15.6 vs. 11.4 months, p=0.17). Older age, male sex, tumor involvement of deep brain structure or functional area, and genetic alterations in CDK4, CDK6, CIC, FGFR3, KMT5B, and MYB were predictors for a worse prognosis, while MGMT promoter methylation, maximal tumor resection, and treatment based on the Stupp protocol were predictive for better survival.ConclusionThe definition of GBM and its clinical, radiological, molecular, and prognostic characteristics have been altered under the current classification.

Controller design for airplane flight control is challenged to achieve an optimum result, particularly for safety purposes. The experiment evaluated the linear quadratic regulator (LQR) method to research the optimal gain of proportional-integral-derivative (PID) to hover accurately the bicopter model by minimizing error. The 3 degree of freedom (DOF) helicopter facility is a suitable bicopter experimental simulator to test its complex multiple input multiple output (MIMO) flight control model to respond to the challenge of multipurpose drone control strategies. The art of LQR setting is how to search for appropriate cost matrices scaling to optimize results. This study aims to accurately optimize take-off position control of the bicopter model by investigating LQR cost matrices variation in actual experiments. From the experimental results of weighted matrix variation on the bicopter simulator, the proposed LQR method has been successfully applied to achieve asymptotic stability of roll angle, although it yielded a significant overshoot. Moreover, the overshoot errors had good linearity to weighting variation. Despite that, the implementation of cost matrices is limited in the real bicopter experiment, and there are appropriate values for achieving an optimal accuracy. Moreover, the unstable step response of the controlled angle occurred because of excessive weighting.

Abstract Trajectory prediction of surrounding vehicles is a crucial capability of intelligent driving vehicles. In a scene, a vehicle and its surrounding vehicles constitute an integral system, and the vehicle's future motion trajectory is affected by the actions of surrounding vehicles. The influencing mode and degree are hidden in the relevant historical information of the vehicle and its neighbour vehicle. The existing trajectory prediction methods either do not consider the confidence of the predicted trajectory, or the accuracy requirement is ignored when considering the confidence of the predicted trajectory. In order to address this problem, a mixed Conditional AutoEncoder Generative Adversarial Network (CAE‐GAN) model based on the multi‐loss function is proposed. The proposed model uses the encoder–decoder structure with a convolutional social pool to extract general features. The generative adversarial networks (GANs) are used to extract the confidence features of the generated trajectories, which enables the proposed model to generate trajectories that are close to the real trajectories. In addition, a classifier structure based on an LSTM network is added to output the probability that the predicted trajectory belongs to a particular lateral maneuver so that the generated trajectory lateral maneuver of the model is consistent with the real trajectory lateral maneuver. The proposed model is evaluated using the publicly available NGSIM US‐101 and I‐80 datasets, and results show that the accuracy of the proposed model is higher than that of the existing methods. The proposed model achieves an average accuracy improvement of 16.34% in comparison to the most advanced existing models.

Abstract The combination of reinforcement learning and platooning control has been widely studied, which has been considered to be altruistic on the basis of safety. However, the platooning control method based on reinforcement learning is not mature. This paper proposes a platoon sharing deep deterministic policy gradient algorithm (PSDDPG) for a multi‐vehicle network which overcomes the problem of low efficiency of continuous action space exploration. On the basis of the noise of deep deterministic policy gradient (DDPG) algorithm, additional platoon noise is added to enhance the diversity of training samples during exploration and avoid using a single‐vehicle data, which could weaken model robustness. The method of using the time sequence information as an input and replay buffer backup is proposed to prevent the problems of insufficient exploration and low sampling efficiency from deteriorating the training effect. The robustness of the proposed algorithm is verified by tests using the Carla simulator. Also, the platoon merging, overtaking, cruising following and obstacle avoidance control of a vehicle platoon is realized under typical traffic flow conditions. The experimental results show that the PSDDPG algorithm can provide an efficient control strategy and thus has the potential to reduce energy consumption and improve road efficiency.

Abstract Electro‐optic electric field sensors based on LiNbO3 are widely used for the measurement of electric fields or transient voltages. However, the working bias of the sensor is influenced by the temperature due to the thermo‐optic effect of LiNbO3. An athermal electro‐optic electric field sensor was demonstrated by coating a thin layer of TiO2 film which has a negative thermo‐optic coefficient, on the common‐path interferometer based sensor to compensate LiNbO3's positive thermo‐optic coefficient. Both calculation and experimental studies were conducted. The experimental results reasonably agree well with the calculated values, and the results show the sensor coated with a 640 nm thick TiO2 film has a much smaller temperature dependence of 0.011°/°C compared to the initial value of 0.1°/°C.

Abstract Autonomous vehicles need to have the ability to predict the future behaviour of surrounding vehicles, which helps with proper trajectory planning and tracking. Many behaviour prediction methods have limited application because they have a very limited prediction horizon. This paper proposes a deep learning‐based hybrid model for behaviour prediction over long‐time periods, including manoeuvre recognition and a behaviour prediction module. In manoeuvre recognition module, the CNN extracts the social characteristics of the target vehicle and LSTM outputs the manoeuvre probability vector to form a contextual feature vector with the social features. In the behaviour prediction module, LSTM and Attention are based on the contextual feature vector to capture multi‐time step information in the behaviour time window to complete the prediction of the target vehicle behaviour. Real‐car collection and open‐source vehicle trajectory datasets were used for training and testing. The results show that the proposed algorithm could predict vehicle behaviour with an accuracy of 89.73% and an average prediction time of 2.032 s, which has a high engineering application value.

Abstract Study design A combined retrospective and prospective analysis on the therapeutic effect of physiotherapeutic scoliosis-specific exercise (PSSE) in mild juvenile idiopathic scoliosis (JIS) patients. Background At present, patients with mild JIS are generally treated by observation without any interventional treatment. This study analyzed the effects of PSSE on mild JIS, which provided a new approach for the treatment of JIS. Method A total of 52 patients with mild JIS (Cobb angle 10–19°), aged 4–9 years, self-selected into an observation group and a PSSE group. Patients performed the corrective posture exercises daily based on the Scientific Exercise Approach to Scoliosis (SEAS) to the best of their ability, and performed the over-corrective training based on Schroth methods for 30 min each day. Before and one year after the treatment, the Cobb angle and the angle of trunk rotation (ATR) were evaluated, and the results were compared between the two groups. Results After one year of treatment, the Cobb angle in the PSSE group decreased from 15.0(11.0–17.0)° to 5.0(2.0–12.0)°(p ≤ 0.001), while the Cobb angle in the observation group increased from 13.5(11.0–17.3)° to 16.0(10.8–20.0)° (p = 0.010). The ATR in the PSSE group decreased from 5.0(2.0–7.0)° to 3.0(2.0–4.0)° (p = 0.009), while the change of ATR in the observation group was not significant. Compared with the observation group, 69.57% of patients in PSSE group had a decreased Cobb angle of more than 5 degrees, which was statistically significant(p ≤ 0.001). Conclusion For mild JIS, PSSE decreased the Cobb angle and ATR.

Abstract Objective To investigate efficacy and safety of endoscopic ultrasonography (EUS) guiding to cut the scar of esophageal stricture after endoscopic injection sclerotherapy (EIS). Methods The data of 10 patients with oesophageal stricture after esophageal varices EIS in our hospital from September 1, 2021 to December 31, 2021 treated by cutting the scar guided by ultrasonic endoscopy were retrospective, and the efficacy was evaluated. Results The dysphagia was obviously relieved in 9 patients during follow-up, and 1 patient suffered dysphagia again after the treatment. There was no complications of perforation, bleeding and infection among the paitents. Conclusion EUS guiding to cut the scar of esophageal stricture after EIS was safe and reliable.

In order to further improve the combination of strength and ductility for 30Si2MnCrMoVE ultra-high strength steel (UHSS), a thermomechanical treatment, named deformation direct quenching and partitioning (DQ&P), was carried out on it. The microstructure evolutions and mechanical properties of 30Si2MnCrMoVE UHSS treated by DQ&P were compared with those treated by conventional off-line quenching and tempering (Q&T) through various microscopic characterization methods and uniaxial tensile tests. Moreover, the effects of austempering temperature on the microstructure evolutions and mechanical properties of the studied steel after DQ&P process were also investigated. The results show that the DQ&P samples, although lower or slightly lower yield strength, possess significantly higher ultimate tensile strength due to higher work-hardening rate caused by high density dislocations and fine dispersed carbides. Moreover, DQ&P310 sample exhibit apparently higher uniform elongation than Q&T sample despite of comparable content of retained austenite due to more prone to transformation induced plasticity (TRIP) effect. The DQ&P process can increase the ultimate tensile strength by 267 MPã423 MPa and the uniform elongation by 78%∼85%, respectively, as compared to Q&T process, which indicates that DQ&P process may be a promising thermomechanical treatment method to improve the comprehensive mechanical properties of the studied steel. The strengths and elongations of DQ&P samples do not vary monotonously with the increase of austempering temperature, which are both closely related to the content of retained austenite.

Malayan pangolin SARS-CoV-2-related coronavirus (SARSr-CoV-2) is closely related to SARS-CoV-2. However, little is known about its pathogenicity in pangolins. Using CT scans we show that SARSr-CoV-2 positive Malayan pangolins are characterized by bilateral ground-glass opacities in lungs in a similar manner to COVID-19 patients. Histological examination and blood gas tests are indicative of dyspnea. SARSr-CoV-2 infected multiple organs in pangolins, with the lungs the major target, and histological expression data revealed that ACE2 and TMPRSS2 were co-expressed with viral RNA. Transcriptome analysis indicated that virus-positive pangolins were likely to have inadequate interferon responses, with relative greater cytokine and chemokine activity in the lung and spleen. Notably, both viral RNA and viral proteins were detected in three pangolin fetuses, providing initial evidence for vertical virus transmission. In sum, our study outlines the biological framework of SARSr-CoV-2 in pangolins, revealing striking similarities to COVID-19 in humans.

BackgroundThe World Health Organization (WHO) CNS5 classification system highlights the significance of molecular biomarkers in providing meaningful prognostic and therapeutic information for gliomas. However, predicting individual patient survival remains challenging due to the lack of integrated quantitative assessment tools. In this study, we aimed to design a WHO CNS5-related risk signature to predict the overall survival (OS) rate of glioma patients using machine learning algorithms.MethodsWe extracted data from patients who underwent an operation for histopathologically confirmed glioma from our hospital database (2011–2022) and split them into a training and hold-out test set in a 7/3 ratio. We used biological markers related to WHO CNS5, clinical data (age, sex, and WHO grade), and prognosis follow-up information to identify prognostic factors and construct a predictive dynamic nomograph to predict the survival rate of glioma patients using 4 kinds machine learning algorithms (RF, SVM, XGB, and GLM).ResultsA total of 198 patients with complete WHO5 molecular data and follow-up information were included in the study. The median OS time of all patients was 29.77 [95% confidence interval (CI): 21.19–38.34] months. Age, FGFR2, IDH1, CDK4, CDK6, KIT, and CDKN2A were considered vital indicators related to the prognosis and OS time of glioma. To better predict the prognosis of glioma patients, we constructed a WHO5-related risk signature and nomogram. The AUC values of the ROC curves of the nomogram for predicting the 1, 3, and 5-year OS were 0.849, 0.835, and 0.821 in training set, and, 0.844, 0.943, and 0.959 in validation set. The calibration plot confirmed the reliability of the nomogram, and the c-index was 0.742 in training set and 0.775 in validation set. Additionally, our nomogram showed a superior net benefit across a broader scale of threshold probabilities in decision curve analysis. Therefore, we selected it as the backend for the online survival prediction tool (Glioma Survival Calculator, https://who5pumch.shinyapps.io/DynNomapp/), which can calculate the survival probability for a specific time of the patients.ConclusionAn online prognosis predictor based on WHO5-related biomarkers was constructed. This therapeutically promising tool may increase the precision of forecast therapy outcomes and assess prognosis.

IntroductionThe fifth edition of the World Health Organization (WHO) classification of central nervous system (CNS) tumors released in 2021 formally defines pediatric-type diffuse gliomas. However, there is still little understanding of pediatric-type diffuse gliomas, and even less attention has been paid to adult patients. Therefore, this study describes the clinical radiological, survival, and molecular features of adult patients with pediatric-type glioma.MethodsAdult patients who underwent surgery from January 2011 to January 2022, classified as pediatric-type glioma, were included in this study. Clinical, radiological, histopathological, molecular pathological, and survival data were collected for analysis.ResultsAmong 596 adult patients, 20 patients with pediatric-type glioma were screened, including 6 with diffuse astrocytoma, MYB- or MYBL1-altered, 2 with diffuse midline glioma, H3 K27-altered, and 12 with diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype. Pediatric high-grade glioma (pHGG) frequently showed tumor enhancement, peritumoral edema, and intratumoral necrosis. Adult patients with pHGG showed a longer life expectancy than adult patients with glioblastoma. Common molecular alterations included chromosome alterations and CDKN2A/B, PIK3CA, and PTEN, while altered KMT5B and MET were found to affect the overall survival.ConclusionOur study demonstrated adult patients with pediatric-type glioma. Notably, our research aims to expand the current understanding of adult patients with pediatric-type diffuse gliomas. Furthermore, personalized therapies consisting of targeted molecular inhibitors for MET and VEGFA may exhibit beneficial effects in the corresponding population.