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Abstract Renewable energy is essential for power system decarbonization, but extended and unexpected periods of extremely low wind and solar resources (i.e., wind and solar droughts) pose a threat to reliability. The challenge is further exacerbated if shortages of the two occur simultaneously or if they affect neighboring grids simultaneously. Here we present a framework to characterize these events and propose three metrics to comprehensively assess renewable energy quality: resource availability, variability, and extremeness. An examination of long-term data across a vast geographical region shows a strong spatial correlation and temporal coincidence of renewable energy droughts. It also finds a lack of sites that excel in all three quality attributes, which presents a trilemma to investors, system planners, and policymakers. These findings underscore the significance of considering factors beyond mere resource availability and contribute to developing informed strategies for the reliable and sustainable deployment of variable energy resources.

Abstract Amid the escalating global climatic challenges, hydrological risks significantly influence human settlement patterns, underscoring the imperative for an in-depth comprehension of hydrological change’s ramifications on human migration. However, predominant research has been circumscribed to the national level. The study delves into the nonlinear effects of hydrological risks on migration dynamics in 46,776 global subnational units. Meanwhile, leveraging remote sensing, we procured globally consistent metrics of hydrological intrusion exposure, offering a holistic risk assessment encompassing hazard, exposure, and vulnerability dimensions, thus complementing previous work. Here, we show that exposure is the primary migration driver, surpassing socioeconomic factors. Surrounding disparities further intensified exposure’s impact. Vulnerable groups, especially the economically disadvantaged and elderly, tend to remain in high-risk areas, with the former predominantly migrating within proximate vicinities. The nonlinear analysis delineates an S-shaped trajectory for hydrological exposure, transitioning from resistance to migration and culminating in entrapment, revealing dependence on settlement resilience and adaptability.

Abstract Efficient operation of control systems in robotics or autonomous driving targeting real-world navigation scenarios requires perception methods that allow them to understand and adapt to unstructured environments with good accuracy, adaptation, and generality, similar to humans. To address this need, we present a memristor-based differential neuromorphic computing, perceptual signal processing, and online adaptation method providing neuromorphic style adaptation to external sensory stimuli. The adaptation ability and generality of this method are confirmed in two application scenarios: object grasping and autonomous driving. In the former, a robot hand realizes safe and stable grasping through fast ( ~ 1 ms) adaptation based on the tactile object features with a single memristor. In the latter, decision-making information of 10 unstructured environments in autonomous driving is extracted with an accuracy of 94% with a 40×25 memristor array. By mimicking human low-level perception mechanisms, the electronic neuromorphic circuit-based method achieves real-time adaptation and high-level reactions to unstructured environments.

Abstract This work introduces a silent speech interface (SSI), proposing a few-layer graphene (FLG) strain sensing mechanism based on thorough cracks and AI-based self-adaptation capabilities that overcome the limitations of state-of-the-art technologies by simultaneously achieving high accuracy, high computational efficiency, and fast decoding speed while maintaining excellent user comfort. We demonstrate its application in a biocompatible textile-integrated ultrasensitive strain sensor embedded into a smart choker, which conforms to the user’s throat. Thanks to the structure of ordered through cracks in the graphene-coated textile, the proposed strain gauge achieves a gauge factor of 317 with

Lung cancer remains a leading cause of cancer-related deaths globally, with its incidence steadily rising each year, representing a significant threat to human health. Early detection, diagnosis, and timely treatment play a crucial role in improving survival rates and reducing mortality. In recent years, significant and rapid advancements in artificial intelligence (AI) technology have found successful applications in various clinical areas, especially in the diagnosis and treatment of lung cancer. AI not only improves the efficiency and accuracy of physician diagnosis but also aids in patient treatment and management. This comprehensive review presents an overview of fundamental AI-related algorithms and highlights their clinical applications in lung nodule detection, lung cancer pathology classification, gene mutation prediction, treatment strategies, and prognosis. Additionally, the rapidly advancing field of AI-based three-dimensional (3D) reconstruction in lung cancer surgical resection is discussed. Lastly, the limitations of AI and future prospects are addressed.

Abstract Purpose More than 90% of patients with diabetes worldwide are type 2 diabetes (T2D), which is caused by insulin resistance or impaired producing insulin by pancreatic β cells. T2D and its complications, mainly large cardiovascular (LCV) and kidney (Ne) complications, are the major cause of death in diabetes patients. Recently, the dysregulation of peripheral T cell immune homeostasis was found in most T2D patients. However, the characteristics of T-cell receptors (TCR) remain largely unexplored in T2D patients. Patients and methods Here we investigated the TCR repertoire using high-throughput sequencing in peripheral blood collected from T2D patient with (8 LCV and 7 Ne) or without complications. Results Our analysis of TCR repertoires in peripheral blood samples showed that TCR profiles in T2D patients with complications tended to be single and specific compared to controls, according to the characteristics of TCR repertoire in V-J combination number, diversity, principal component analysis (PCA) and differential genes. And we identified some differentially expressed V-J gene segments and amino acid clonotypes, which had the potential to contribute to distinguishing T2D patient with or without complications. As the progression of the disease, we found that the profiling of TCR repertoire was also differential between T2D patients with LVD and Ne complications base on this pilot analysis. Conclusion This study demonstrated the protentional unique property of TCR repertoire in peripheral blood of T2D patient with and without complications, or T2D patients with LVD and Ne complications, which provided the possibility for future improvements in immune-related diagnosis and therapy for T2D complications.

Snow depth is a fundamental parameter in hydrological and climate models, which is crucial for studying climate change, hydrological cycles, and ecosystem changes. Polarimetric synthetic aperture radar interferometry (PolInSAR) is one of the most promising snow depth retrieval methods, which is sensitive to the shape, direction, and vertical distribution of targets. The dense medium random-volume-over-ground (DM-RVoG) model for PolInSAR has been shown to be workable for snow depth retrieval, it still suffers from the inaccuracy of the parameters representing the phase center and decorrelation. In this study, based on the backscattering mechanism of snow, a novel snow depth retrieval method is proposed to improve the DM-RVoG model using polarization decomposition and decorrelation optimization. First, the polarization decomposition is extended to obtain the ground scattering phase. Then, the coherence region boundary estimation method is put forward to obtain pure volume decorrelation. Finally, the proposed method is validated using Ku-band UAV SAR data, and the accuracy is assessed using in situ data. The correlation coefficient, root mean square error, and mean absolute error of the proposed method are 0.88, 4.98, and 4.08 cm, respectively, demonstrating significant improvements compared with the original method.

The rapid emergence of invasive infections caused by azole-resistant Candida tropicalis has become a public health concern, and there is an urgent need for alternative treatment strategies. Studies have demonstrated the antibacterial effects of nisin, a well-known peptide naturally produced by Lactococcus lactis subsp. lactis. However, there is scant information about the antifungal effect of nisin against C. tropicalis. The present study aims to investigate the in vitro antifungal activity of nisin against clinical isolates of azole-resistant C. tropicalis strains, as well as its inhibitory effect on biofilm formation. A total of 35 C. tropicalis strains isolated from patients with invasive fungal infections were divided into the azole-resistant group and the azole-sensitive group, containing 21 and 14 strains, respectively. The relative expression levels of the ERG11 and UPC2 genes in the azole-resistant group were higher than those in the azole-sensitive group (p

African swine fever virus (ASFV) is one of the most complex viruses. ASFV is a serious threat to the global swine industry because no commercial vaccines against this virus are currently available except in Vietnam. Moreover, ASFV is highly stable in the environment and can survive in water, feed, and aerosols for a long time. ASFV is transmitted through the digestive and respiratory tract. Mucosal immunity is the first line of defense against ASFV. Saccharomyces cerevisiae (SC), which has been certified by the U.S. Food and Drug Administration and has a generally recognized as safe status in the food industry, was used for oral immunization in this study. ASFV antigens were effectively expressed in recombinant SC strains with high DNA copy numbers and stable growth though surface display technology and chromosome engineering (δ-integration). The recombinant SC strains containing eight ASFV antigens—KP177R, E183L, E199L, CP204L, E248R, EP402R, B602L, and B646L— induced strong humoral and mucosal immune responses in mice. There was no antigenic competition, and these antigens induced Th1 and Th2 cellular immune responses. Therefore, the oral immunization strategy using recombinant SC strains containing multiple ASFV antigens demonstrate potential for future testing in swine, including challenge studies to evaluate its efficacy as a vaccine against ASFV.

The running gear mechanism is a critical component of high-speed trains, essential for maintaining safety and stability. Malfunctions in the running gear can have severe consequences, making it imperative to assess its condition accurately. Such assessments provide insights into the current operational status, facilitating timely maintenance and ensuring the reliable and safe operation of high-speed trains. Traditional evidential reasoning models for assessing the health of running gear typically require the integration of multiple characteristic indicators, which are often challenging to obtain and may lack comprehensiveness. To address these challenges, this paper introduces a novel assessment model that combines evidential reasoning with multidimensional fault conclusions. This model synthesizes results from various fault diagnoses to establish a comprehensive health indicator system for the running gear. The diagnostic outcomes serve as inputs to the model, which then assesses the overall health status of the running gear system. To address potential inaccuracies in initial model parameters, the covariance matrix adaptation evolution strategy (CMA-ES) algorithm is utilized for parameter optimization. Comparative experiments with alternative methods demonstrate that the proposed model offers superior accuracy and reliability in assessing the health status of high-speed train running gear.

With the rapid advancement of computer vision, machine learning, and consumer electronics, eye tracking has emerged as a topic of increasing interest in recent years. It plays a key role across diverse domains including human–computer interaction, virtual reality, and clinical and healthcare applications. Near-eye tracking (NET) has recently been developed to possess encouraging features such as wearability, affordability, and interactivity. These features have drawn considerable attention in the health domain, as NET provides accessible solutions for long-term and continuous health monitoring and a comfortable and interactive user interface. Herein, this work offers an inaugural concise review of NET for health, encompassing approximately 70 related articles published over the past two decades and supplemented by an in-depth examination of 30 literatures from the preceding five years. This paper provides a concise analysis of health-related NET technologies from aspects of technical specifications, data processing workflows, and the practical advantages and limitations. In addition, the specific applications of NET are introduced and compared, revealing that NET is fairly influencing our lives and providing significant convenience in daily routines. Lastly, we summarize the current outcomes of NET and highlight the limitations.

Abstract It remains a great challenge to engineer materials with strong and stable interactions for the simultaneously mechanical-robust and room temperature phosphorescence-efficient materials. In this work, we demonstrate a covalent cross-linking strategy to engineer mechanical-robust room temperature phosphorescence materials through the B–O click reaction between chromophores, polyvinyl alcohol matrix and inorganic layered double hydroxide nanosheets. Through the covalent cross-linkage between the organic polyvinyl alcohol and inorganic layered double hydroxide, a polymeric composite with ultralong lifetime up to 1.45 s is acquired based on the inhibited non-radiative transition of chromophores. Simultaneously, decent mechanical strength of 97.9 MPa can be realized for the composite materials due to the dissipated loading stress through the covalent-bond-accommodated interfacial interaction. These cross-linked composites also exhibit flexibility, processability, scalability and phosphorescence responses towards the mechanical deformation. It is anticipated that the proposed covalent click reaction could provide a platform for the design and modulation of composites with multi-functionality and long-term durability.

Abstract Implementing and integrating spiking neurons for neuromorphic hardware realization conforming to spiking neural networks holds great promise in enabling efficient learning and decision‐making. The spiking neurons, however, may lack the spiking dynamics to encode the dynamical information in complex real‐world problems. Herein, using filamentary memristors from solution‐processed hexagonal boron nitride, this study assembles leaky integrate‐and‐fire spiking neurons and, particularly, harnesses the common switching stochasticity feature in the memristors to allow key neural dynamics, including Poisson‐like spiking and adaptation. The neurons, with the dynamics fitted via hardware‐algorithm codesign, suggest a potential in realizing spike‐based neuromorphic hardware capable of handling complex problems. Simulation of an autoencoder for anomaly detection of time‐series real analog and digital data from physical systems is demonstrated, underscoring its promising prospect in applications, especially, at the edges with limited computation resources, for instance, auto‐pilot, manufacturing, wearables, and Internet of things.

ABSTRACT: Objectives: Linezolid-resistant Staphylococcus capitis (LRSC) has become a new challenge for clinical anti-infective therapy. The present study aimed to investigate the trends of LRSC prevalence in a tertiary hospital of China 2017–2020. The resistance mechanisms, virulence genes, biofilm formation, and mass spectrometric characteristics of LRSC isolates were also analysed. Methods: This study retrospectively analysed the antibiotic resistance trends of coagulase negative staphylococci (CoNS) isolated from clinical samples collected between 2017–2020. Antimicrobial resistance profiles were tested by micro-broth dilution and the E-test method. Antimicrobial resistance genes and virulence genes were detected by polymerase chain reaction, and dru-typing sequences were obtained by Sanger sequencing. Crystal violet staining in 96-well plates was used to detect biofilm formation ability. Mass spectrometric characterization of LRSC was analysed by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) coupled with ClinProTools. Results: The linezolid resistance rate in 3575 CoNS clinical strains was 1.6%, wherein the great majority of was LRSC (91.1%, n = 51/56), with a resistant rate of 15.5% (n = 51/328) in all S. capitis isolates. In this study, 48 out of the 51 LRSC strains and 54 of 277 linezolid-susceptible S. capitis (LSSC) strains were enrolled. G2576T, C2104T, T2130A, C2163T, and T2319C mutations in the 23S rRNA V region and acquisition of cfr were the main linezolid resistant mechanisms in LRSC. The biofilm-forming ability of LRSC was more potent than LSSC, with a higher detection rate of bap (P < 0.05). Eleven mass spectrometric peaks of interest were identified by using MALDI-TOF MS and ClinProTools, which were differently distributed between LRSC and LSSC strains, with the area under the receiver operating characteristic curve of more than 0.8, especially for 5465.37 m/z. Conclusions: Linezolid resistance was mediated by mutations in the 23S rRNA V region and presence of the cfr gene in LRSC strains. LRSC strains have stronger biofilm-forming ability than LSSC strains, which maybe associated with the adhesion-related gene of bap. Further, linezolid-resistant and linezolid-susceptible S. capitis could be rapidly identified with mass spectrometric characterization. To the best of our knowledge, this study is the first to document the biofilm formation ability of LRSC and the potential usefulness of MALDI-TOF MS for the discrimination of LRSC and LSSC.

Geological observation and thermal simulation experiments have revealed that the peak period of hydrocarbon generation of gypsum-bearing mudstone is often advanced in sedimentary basins, but the correlation between the amount of advance and the content of gypsum is still not clear. In this study, the source rock powder samples with different gypsum content in the Lower Ganchaigou Formation from well S49-1 in the western Qaidam Basin were selected and extracted to remove soluble organic matter (SOM). Part of the extracted residue was pickled to remove carbonate. Rock pyrolysis analysis was performed on the original samples and the solid residue after two-step pretreatment. Compared to the Tmax of original samples, the Tmax was higher in the SOM-free residue but lower in the SOM-free and carbonate-free residue, showing that SOM and sulfate minerals (gypsum and anhydrite) in gypsum-bearing mudstone can promote the thermal evolution of organic matter. Although the latter has a more significant effect, it is not proportional to its sulfate content, indicating that the contact area of sulfate minerals and organic matter is more important to Tmax. The hypothesis was verified by the Tmax values of different proportions of kerogen and magnesium sulfate powder mixtures. Therefore, the occurrence state of sulfate minerals will directly affect the contact relationship between organic matter and sulfate, which in turn will affect the process of hydrocarbon generation in thermal evolution.

Abstract Over the past three decades, China's government has implemented many projects under its ecological compensation policy, including paying compensation fees for habitat creation to redress natural habitat losses caused by development. However, a critical evaluation of both the policy design and its ecological outcomes, has not previously been carried out. We assemble diverse data sources to provide the first evaluation of China's eco‐compensation policy and practice, identifying several challenges. In policy, the pricing of forest restoration fees is insufficient in several provinces, and there is no requirement for use of biodiversity metrics or for ecological equivalence of compensation and losses. In practice, only 23% of a sample of 31 developments applied quantitative biodiversity metrics, and fewer than 1% of China's local governments have disclosed information regarding compensation implementation. Thus, to improve the validity of its compensation policy and practice to better secure biodiversity, China may need to embrace higher compensation standards, having first prevented ecological losses where possible. Equally important, China may also need to improve compensation governance for data tracking and conservation effectiveness monitoring.

The inferior temperature stability of piezoelectric response is the main drawback of KNN-based ceramics. Here, the Ba-doped 0.97(K0.48Na0.52)(Nb0.96Sb0.04)O3-0.03Bax(Bi0.5Ag0.5)1-xZrO3 (abbreviated as KNNS-BxBAZ) textured ceramics were prepared by the template grain growth (TGG) method. Excellent comprehensive properties (d33=(406 ± 15) pC/N, TC = 274 °C, strain is 0.17%) were achieved in KNNS-BxBAZ textured ceramics with x = 0.2. Meanwhile, its piezoelectric and strain properties also show superior temperature stability (d33 maintained within ±20% change in a wide temperature range from 25 °C to 200 °C and strain variation was less than 5% in the temperature range from room temperature to 165 °C). The high O-T phase transition temperature (TO-T is 110 °C) induced by incorporating Ba ions accounts for the enhanced temperature stability of piezoelectric properties. In addition, the crystal texture always maintains the contribution of piezoelectric anisotropy to the piezoelectric properties during elevated temperature, which significantly improved the temperature stability of piezoelectric properties. This work provides an effective strategy for simultaneously achieving high piezoelectric response and excellent temperature stability in KNN-based ceramics.

Abstract A comprehensive characterisation of the pore structure in shale oil reservoirs is essential for forecasting oil production and exploration risks. This study forecasted these risks in the oil-rich Songliao Basin using combination of high-resolution field emission scanning electron microscopy and quantitative X-ray diffraction to analyze the pore genesis and evolution mode within the first member of the Cretaceous Qingshankou Formation (K2qn1). The results showed the dominance of inorganic pores over organic pores, wherein diagenetic processes, such as compaction, pressure solution, and cementation, were responsible for the destruction of pore structure in the formation. Notably, the pores formed by dissolution and shrinkage cracks resulting from clay mineral transformation improved the oil storage space. Furthermore, according to the geochemical data and clay composition, the K2qn1 shale is in the middle diagenetic stage A, which can be further subdivided into A1 and A2 stages from top to bottom. The porosity slowly decreased in both sub-stages A1 and A2, wherein the decrease was stable in the latter. The diagenetic observations in this study are significant for the exploration of unconventional shale oil in petroliferous basins worldwide.

Abstract Applying sensors in biomedical institutions and home‐based stroke rehabilitation is now a global research focus. In this review paper, the relationship between stroke diseases’ physiology mechanism and diverse sensors’ functionalities is detailed explained. The review starts by interpreting how stroke influences motion abilities and then introduces broadly adopted physical training methods. After, the working principles of sensors and their use to objectively provide patients’ body information for stroke rehabilitation status are discussed. The content of the paper aims to not only review the state‐of‐the‐art works of developing sensors for assisting in evaluating stroke patients’ status but also bridging the gap between medical staff and engineers.

Diabetic kidney disease (DKD) is the most important microvascular complication of diabetes and the leading cause of end-stage renal disease (ESRD) worldwide. The Janus kinase/signal transducer and activator of the transcription (JAK/STAT) signaling pathway, which is out of balance in the context of DKD, acts through a range of metabolism-related cytokines and hormones. JAK/STAT is the primary signaling node in the progression of DKD. The latest research on JAK/STAT signaling helps determine the role of this pathway in the factors associated with DKD progression. These factors include the renin–angiotensin system (RAS), fibrosis, immunity, inflammation, aging, autophagy, and EMT. This review epitomizes the progress in understanding the complicated explanation of the etiologies of DKD and the role of the JAK/STAT pathway in the progression of DKD and discusses whether it can be a potential target for treating DKD. It further summarizes the JAK/STAT inhibitors, natural products, and other drugs that are promising for treating DKD and discusses how these inhibitors can alleviate DKD to explore possible potential drugs that will contribute to formulating effective treatment strategies for DKD in the near future.

Artificial nociceptors, mimicking human-like stimuli perception, are of significance for intelligent robotics to work in hazardous and dynamic scenarios. One of the most essential characteristics of the human nociceptor is its self-adjustable attribute, which indicates that the threshold of determination of a potentially hazardous stimulus relies on environmental knowledge. This critical attribute has been currently omitted, but it is highly desired for artificial nociceptors. Inspired by these shortcomings, this article presents, for the first time, a self-directed channel memristor-based self-reconfigurable nociceptor, capable of perceiving hazardous pressure stimuli under different temperatures and demonstrates key features of tactile nociceptors, including ‘threshold,’ ‘no-adaptation,’ and ‘sensitization.’ The maximum amplification of hazardous external stimuli is 1000%, and its response characteristics dynamically adapt to current temperature conditions by automatically altering the generated modulation schemes for the memristor. The maximum difference ratio of the response of memristors at different temperatures is 500%, and this adaptability closely mimics the functions of biological tactile nociceptors, resulting in accurate danger perception in various conditions. Beyond temperature adaptation, this memristor-based nociceptor has the potential to integrate different sensory modalities by applying various sensors, thereby achieving human-like perception capabilities in real-world environments.

Abstract Bone loss induced by microgravity exposure seriously endangers the astronauts’ health, but its countermeasures still have certain limitations. The study aims to find potential protective drugs for the prevention of the microgravity-induced bone loss. Here, we utilized the network pharmacology approach to discover a natural compound calycosin by constructing the compound-target interaction network and analyzing the topological characteristics of the network. Furthermore, the hind limb unloading (HLU) rats’ model was conducted to investigate the potential effects of calycosin in the prevention of bone loss induced by microgravity. The results indicated that calycosin treatment group significantly increased the bone mineral density (BMD), ameliorated the microstructure of femoral trabecular bone, the thickness of cortical bone and the biomechanical properties of the bone in rats, compared that in the HLU group. The analysis of bone turnover markers in serum showed that both the bone formation markers and bone resorption markers decreased after calycosin treatment. Moreover, we found that bone remodeling-related cytokines in serum including IFN-γ, IL-6, IL-8, IL-12, IL-4, IL-10 and TNF-α were partly recovered after calycosin treatment compared with HLU group. In conclusion, calycosin partly recovered hind limb unloading-induced bone loss through the regulation of bone remodeling. These results provided the evidence that calycosin might play an important role in maintaining bone mass in HLU rats, indicating its promising application in the treatment of bone loss induced by microgravity.

Snow profiles can provide reliable and detailed snow parameters for global change research, but it is still challenging to reconstruct large-scale spatiotemporally continuous snow profiles. Synthetic aperture radar (SAR) tomography (TomoSAR) has been proven to be a promising method for reconstructing the 3D structure of targets and has been used to reconstruct snow profiles from ground-based SAR. However, the experimental condition of ground-based SAR is ideal and the algorithms developed for ground-based SAR have some problems when applied to airborne and spaceborne sensors, such as large computational load and big angular diversity. In this paper, we first collected the Ku-band tomographic SAR dataset in the snow season of Altay, China using the Unmanned Aerial Vehicle (UAV) platform. Then, we reconstructed the snow profile from the dataset using three spectral estimation-based focusing algorithms. According to the non-stationary characteristic of the UAV platform and the dense medium property of snow, phase calibration and medium correction were performed, respectively. Finally, we assessed the reconstruction accuracy of the snow profile and snow depth using the ground synchronous measurement data. The reconstruction accuracy of the three focusing algorithms from high to low is the MUSIC algorithm, the Capon algorithm, and the Beamforming algorithm. Among them, the average error of the MUSIC algorithm to reconstruct the snow profile is 1.13 cm, and the RMSE and MAE of the snow depth retrieval are 3.71 cm and 3.26 cm, respectively. Although TomoSAR is still widely unexplored for snow using air-based sensors, the results show that it has the ability to reconstruct snow profiles accurately, and the proposed method can provide reliable support for reconstructing the large-scale spatiotemporal continuous snow profiles from subsequent spaceborne SAR.

To better understand the diversity and phylogeny of Nemouridae, we sequenced and annotated the complete mitochondrial genome (mitogenome) of Nemoura longicercia Okamoto, 1922. The entire mitochondrial genome of N. longicercia was 15,728 bp. It contained 37 representative genes (22 transfer RNA genes (tRNAs), 13 protein-coding genes (PCGs), and two ribosomal RNA genes (rRNAs)) and a control region. In this genome, 23 genes were found on the heavy strand (H-strand) and 14 genes were on the light strand (L-strand). All PCGs began with the initiation codon ATN. Eleven PCGs stopped with the termination codon TAA or TAG, while COII and ND5 genes stopped with incomplete codon T. Bayesian’s inference (BI) and maximum-likelihood (ML) methods generated the identical tree topology across the PCGR dataset (13 PCGs plus two rRNAs). The monophyly of each subfamily was well-supported. This analysis supported the clade N. longicercia plus N. papilla as sister taxon to the clade N. meniscata plus N. nankinensis.

ABSTRACT: Objectives: Identification and classification of microorganisms is one of the most important but difficult and challenging issues in microbiology. Whole genome sequencing (WGS), which can give a thorough understanding for the genome of bacteria strain, has been universally used for studying bacterial classification, evolution, and drug-related resistant genes. We in this study aimed to identify a Gram-positive, microaerophilic, catalase-negative cocci strain named AV208, which has shown resistance to vancomycin, by whole genome's average nucleotide identity (ANI) and high-throughput sequencing technology. Methods: The AV208 strain was identified by following commercially available identification systems, including API 20 Strep system and Vitek 2 Compact Gram-positive identification system for biochemical phenotypic test. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) and 16S rRNA gene sequencing were used for confirmation identification. The whole genome of AV208 was sequenced by using high throughput sequencing technology and ANI between AV208, and its phylogenetic neighbours were analysed by the Orthologous Average Nucleotide Identity Tool (OAT) software. Polymerase chain reaction (PCR) and DNA sequencing were used to investigate the potential molecular mechanism for vancomycin resistance. Results: The AV208 strain was isolated from an ascites sample from a patient with chronic kidney disease who showed extensive resistance to the drugs detected, such as vancomycin with MIC >256 μg/mL. With combination of biochemical phenotypic test, MALDI-TOF-MS and 16S rRNA gene sequencing, the AV208 strain was tentatively identified as an Aercoccus viridans. By using complete genome sequence, we found a 96.24% ANI between strain AV208 and Aerococcus urinaeequi CCUG 28094T, which was higher than that with A. viridans CCUG4311T (94.9%). The consistency of 16S rRNA sequence of strain AV208 was 100% with A. urinaeequi CCUG 28094T and 99.9% with A. viridans CCUG4311T, with only one base difference between them. PCR and sequencing for van genes revealed that AV208 was positive for the vanA gene. A Tn1546 transposon-like structure with vanA gene was found in the genome, which was predicted locating in plasmid, causing vancomycin resistance phenotypes. Conclusion: Average nucleotide identity analysis based on whole genome sequence is an accurate and effective method for identification of bacteria, especially for strains that are not discernible by existing methods such as Aerococcus.

Abstract The general silhouette‐based gait recognition methods usually rely on binary human silhouette, which is easily affected by external factors, making it unsuitable for situations while wearing heavy clothes or carrying objects, etc. In this study, a new skeleton‐based gait recognition model is proposed. The model first extracts the spatial and temporal features of gait using the space and time relationship between body joints, and second, it eliminates redundant features by decomposing the feature map, to achieve a better recognition accuracy in the presence of external factors. Through abundant experiments on two common datasets, CASIA‐B and OUMVLP‐Pose, the proposed model has been proved to have higher recognition accuracy and remarkable robustness.

Abstract The memristor is a resistive switch where its resistive state is programable based on the applied voltage or current. Memristive devices are thus capable of storing and computing information simultaneously, breaking the Von Neumann bottleneck. Since the first nanomemristor made by Hewlett‐Packard in 2008, advances so far have enabled nanostructured, low‐power, high‐durability devices that exhibit superior performance over conventional CMOS devices. Herein, the development of memristors based on different physical mechanisms is reviewed. In particular, device stability, integration density, power consumption, switching speed, retention, and endurance of memristors, that are crucial for neuromorphic computing, are discussed in detail. An overview of various neural networks with a focus on building a memristor‐based spike neural network neuromorphic computing system is then provided. Finally, the existing issues and challenges in implementing such neuromorphic computing systems are analyzed, and an outlook for brain‐like computing is proposed.

Abstract Humanoid robots, intelligent machines resembling the human body in shape and functions, cannot only replace humans to complete services and dangerous tasks but also deepen the own understanding of the human body in the mimicking process. Nowadays, attaching a large number of sensors to obtain more sensory information and efficient computation is the development trend for humanoid robots. Nevertheless, due to the constraints of von Neumann‐based structures, humanoid robots are facing multiple challenges, including tremendous energy consumption, latency bottlenecks, and the lack of bionic properties. Memristors, featured with high similarity to the biological elements, play an important role in mimicking the biological nervous system. The memristor‐based nervous system allows humanoid robots to obtain high energy efficiency and bionic sensing properties, which are similar properties to the biological nervous system. Herein, this article first reviews the biological nervous system and memristor‐based nervous system thoroughly, including the structures and also the functions. The applications of memristor‐based nervous systems are introduced, the difficulties that need to be overcome are put forward, and future development prospects are also discussed. This review can hopefully provide an evolutionary perspective on humanoid robots and memristor‐based nervous systems.

Abstract Purpose STAT3 and p-STAT3 are often overexpressed in various human tumours and participate in cancer development and progression. However, whether STAT3/p-STAT3 expression is associated with clinicopathologic characteristics and has prognostic significance for people suffering from ovarian cancer remains controversial. We conducted a systematic review and meta-analyses to clarify the associations between STAT3/p-STAT3 expression and clinicopathologic characteristics and prognostic factors of ovarian cancer. Methods A systematic electronic search in the PubMed, Embase, CNKI, and Wanfang databases was conducted to identify relevant articles published before 3 April 2021. All statistical analyses were performed using Stata 15.1. Results We included 16 eligible studies incorporating 1747 ovarian cancer patients. The expression of STAT3/p-STAT3 was upregulated in ovarian cancer samples versus normal ovarian tissue, benign tumours and borderline tumours (OR = 10.14, p

Recently, there has been increasing concern about the health hazards of heavy metal-polluted farmlands. Recent findings suggest that intercropping could be effective remediation strategy for agricultural soils without affecting crop biomass yield. However, there are concerns on the heavy metal accumulation in plant organs in phytoremediation, emphasizing the need to develop an effective intercropping remediation model. In this study, we evaluated the effects of intercropping rape and wheat with different accumulation characteristics of cadmium (Cd), and crop growth and physiological characteristics. Intercropping significantly reduced the Cd content of rape shoot and root, with the rape–low Cd-accumulating wheat intercropping system yielding the best results. However, intercropping had no significant effect on Cd accumulation in wheat. Additionally, intercropping affected the root system configuration and structure, photosynthetic indicators, chlorophyll content, crop enzyme content, and rhizosphere enzyme activity of both species, but did not significantly affect the biomass of wheat and rape. Overall, our findings showed that intercropping rape with a low Cd-accumulating wheat variety could be an effective model for safe production of wheat and rape in weak alkaline soils without compromising biomass yield. The study demonstrates that similar innovative, effective, and judicious intercropping strategy can enrich the theory of contaminated soil remediation.

Considering the advantages of high Curie temperature and environment-friendly nature of KNN piezoelectric ceramics, the limitation of weak piezoelectric response and their temperature sensitivity to applications is worth exploring. Herein, the textured (1-[Formula: see text])(K[Formula: see text]Na[Formula: see text])(Nb[Formula: see text]Sb[Formula: see text])O3-[Formula: see text](Bi[Formula: see text]Na[Formula: see text])HfO3([Formula: see text] = 0.01−0.045) lead-free ceramics were synthesized by templated grain-growth method. The high piezoelectric performance (d[Formula: see text] of 474 pC/N and strain of 0.21%) and excellent temperature stability (unipolar strain maintained within 4.3% change between 30[Formula: see text]C and 165[Formula: see text]C) were simultaneously achieved in the textured KNNS-0.03BNH ceramics. The high piezoelectric performance can be attributed to the summation of the crystallographic anisotropy and phase structure contributions in textured ceramics. The superior temperature stability of piezoelectric properties can be interpreted by the contribution of crystal anisotropy to piezoelectric properties reduces the effect of phase transition on piezoelectric properties deterioration. This study provides an effective strategy for simultaneously achieving high piezoelectric properties and superior temperature stability in KNN-based textured ceramics.

Electromyography (EMG) is an integral part of many biomedical and healthcare applications. It has been used as a metric for tracking rehabilitation progress and identifying diseases that affect muscle activation patterns. Although it is widely used in many disciplines, conventional EMG recording and interpretation techniques lack in providing precise signal detection and robust classification accuracy. In recent years, thanks to advances in both material science and artificial intelligence, EMG detection techniques are improving at a rapid pace. Materials that allow for enhanced biocompatibility have improved the quality of data recorded by electrodes. The use of machine learning algorithms has paved new ways to understand complex EMG signals, triggering diverse, novel, and improved application scenarios within the healthcare framework. To help readers establish a clear picture of the two most important components in EMG technology, i.e., electrodes and algorithms, while catching up with the latest research outcomes, this review article is composed. The article starts by introducing conventional EMG electrode materials and architectures, then explains how state‐of‐the‐art works have improved electrode utilization. Subsequently, EMG signal conditioning and interpretation algorithms are investigated. Finally, current challenges in the research domain and authors’ perspectives are discussed.

Some chronic diseases, including Parkinson’s disease (PD), diabetic foot, flat foot, stroke, elderly falling, and knee osteoarthritis (KOA), are related to orthopedic organs, nerves, and muscles. The interaction of these three parts will generate a comprehensive result: gait. Furthermore, the lesions in these regions can produce abnormal gait features. Therefore, monitoring the gait features can assist medical professionals in the diagnosis and analysis of these diseases. Nowadays, various insole systems based on different sensing techniques have been developed to monitor gait and aid in medical research. Hence, a detailed review of insole systems and their applications in disease management can greatly benefit researchers working in the field of medical engineering. This essay is composed of the following sections: the essay firstly provides an overview of the sensing mechanisms and parameters of typical insole systems based on different sensing techniques. Then this essay respectively discusses the three stages of gait parameters pre-processing, respectively: pressure reconstruction, feature extraction, and data normalization. Then, the relationship between gait features and pathogenic mechanisms is discussed, along with the introduction of insole systems that aid in medical research; Finally, the current challenges and future trends in the development of insole systems are discussed.

Body size is one of the most important traits of an organism. Among reptiles, both lizards and snakes show body size differences that span a similar six orders of magnitude variation. However, the molecular mechanisms underlying body size variation in squamates remain obscure. Here, we performed comparative genomic analyses of 101 body-size-related genes from 28 reptilian genomes. Phylogenetic analysis by maximum likelihood (PAML) revealed that snakes showed higher evolutionary rates in body-size-related genes, and had an almost two-fold increase in the number of positively selected genes (∼20.3%) compared with lizards (∼8.9%). The high similarities in dN/dS values were obtained between the branches of large-bodied lizards and large-bodied snakes by Spearman correlation analysis. Combining the results from site model, branch-site model and clade model analyses, we found some key genes regulating the evolution of body size in squamates, such as COL10A1, GHR, NPC1, GALNS, CDKN2C, FBN1, and LCORL. Phylogenetic generalized least squares (PGLS) indicated that AKT1, BMP1, IGF1, SOX5, SOX7 in lizards and BMP5, BMP7, GPC6, SH2B3, SOX17 in snakes were significantly correlated with body length and body mass. Furthermore, ecological factors had varying degrees of impact on body size and the evolutionary rate of body-size-related genes in squamates. Intriguingly, climate had little effect on body size of lizards and snakes, but the contribution of climate-related factors to the variation in evolutionary rate of body-size-related genes were relatively higher. Our study lays a foundation for a comprehensive understanding of genetic mechanisms of body size evolution in squamates during the process of adapting to terrestrial life.

The gut microbiome is vital to the physiological and biochemical functions of the host, and changes in the composition of these microbial communities may affect growth and adaptability to the environment. Pomacea canaliculata is an invasive freshwater snail which has become a serious agricultural pest. Temperature adaptation is considered an important reason for the widespread distribution of this species. To date, the contribution of the gut microbes to host fitness of P. canaliculata during long-term temperature stress is not well understood. In this study, the morphological changes and intestinal microbiome of P. canaliculata under long-term stress at low temperature (15°C) and high temperature (35°C) were investigated with laboratory experiments. Compared with control group (25°C), the alpha diversity increased and pathogenic bacteria enriched changed under high and low temperature stress. The effect of high temperature stress on the intestinal microbiome of P. canaliculata was more significant than that of low temperature stress. A sustained high temperature environment led to an increase in the abundance of pathogenic bacteria, such as Aeromonas and Enterobacter, and a decrease in the abundance of immune-related bacteria such as Bacteroidetes, Firmicutes, and Lactococcus. These intestine microbiome changes can increase the risk of diseases like intestinal inflammation, and lead to more deaths at high temperature environments. In addition, with the extension of stress time from 14 to 28 days, the beneficial bacteria such as Bacteroidetes, Firmicutes, and Lactococcus were significantly enriched, while potential pathogenic bacteria such as Pseudomonas, Acinetobacter, Shivalella, and Flavobacterium decreased, suggesting that intestinal microbiota may play an important role in host response to heat stress. These results are consistent with previously reported results that the survival rate of both male and female P. canaliculata no longer significantly reduced after 21 days of high temperature stress, suggesting that the surviving P. canaliculata had gradually adapted to high temperature environments under long-term high temperature stress.

The development of precise virtual entities of human bodies has been pursued for many years, but to date, there have been few positive reports. In recent years, the success of digital twin (DT) technology in industrial applications has led to greater interest in establishing human‐body DT models. In particular, many recent advances in materials science, electrical engineering, and computer engineering have exhibited the intrinsic power of DT models in the detection and processing of complex body signals, indicating that the goals of establishing human‐body DTs are getting “within reach.” Herein, current DT technologies in industry are discussed and advanced electronics and artificial intelligent algorithms are reviewed, which are must‐have building blocks for human DTs. Finally, perspectives on the use of human‐body DTs in improving the quality of life and introduction of never‐have immersive virtual reality experiences are discussed.

Objective To assess and compare the performance of fluorine‐18‐labeled fluorodeoxyglucose positron emission tomography (18F‐FDG‐PET/ CT) and gallium‐68‐labeled tetraazacyclododecanetetraacetic acid‐DPhe1‐Tyr3‐octreotate (68Ga‐ DOTATATE) PET/CT in the targeted imaging of culprit tumors causing osteomalacia. Methods This was a clinical retrospective analysis. We analyzed 13 patients (five men, eight women; mean age, 49 years; range, 19–55 years) with suspicion of tumor‐induced osteomalacia (TIO) between March 2017 and October 2019. All patients underwent two functional imaging methods to locate the culprittumors. Studies were performed on a PET/CT scanner. The injection doses of 18F‐ FDG and 68Ga‐DOTATATE were 0.5mCi/kg and approximately 5.0mCi, respectively. In the two scans, the whole body was captured from head to toe 45 to 60 min after intravenous tracer injection. 68Ga‐DOTATATE PET/CT and 18F‐FDG PET/CT imaging results locate culprit tumors according to the following criteria: (i) abnormal foci uptake concentration was observed locally, and the uptake level was higher than the background level of the right lobe of the liver; (ii) combined CT showed or did not have obvious abnormal density changes; and (iii) non‐specific ingestion lesions due to fracture, arthritis, necrosis of femoral head are excluded. Compared with the results of pathological examination and clinical follow‐up, the sensitivity, specificity and accuracy of 68Ga‐DOTATATE PET/CT imaging and 18F‐FDG PET/CT imaging for TIO were analyzed. Results All patients had symptoms of osteomalacia and hypophosphatemia. The lag time (symptoms to PET diagnosis) ranged from 2 to 12 years. There were eight cases of TIO patients and five cases of non‐TIO patients confirmed by surgery, pathology and follow‐up. Among the eight TIO patients, there were six cases (75.0%) of PMTs, one case (12.5%) of giant cell tumor, one case (12.5%) of hemangiopericutoma. Most (n = 6, 75.0%) of the confirmed tumors in our patient population were in the lower extremities, followed by craniofacial regions (n = 1, 12.5%), and torso (n = 1, 12.5%), respectively. Among the five non‐TIO patients, there were two cases of Fanconi syndrome, one case of rickets, and two cases of sporadic osteomalacia hypophosphorus. The culprit tumors could be located either in the bone (n = 5, 62.5%) or the soft tissue (n = 3, 37.5%). 18F‐FDG PET/CT was able to localize the tumor in six (6/13, 46.1%) patients. 68Ga‐DOTATATE PET/CT detected tumor in 8 (83.3%) of 13 patients. The sensitivity of 68Ga‐DOTATATE PET/CT imaging and 18F‐FDG PET/CT imaging in the evaluation of TIO in our patient population were 100% (8/8) vs 75% (6/8). The specificity of the two different methods was 80% (4/5). The overall accuracy was 92.3% (12/13) vs 76.9% (10/13). Conclusions 68Ga‐DOTATATE PET/CT is very effective in assessing hypophosphatemia patients with TIO typical symptoms compared with 18F‐FDG. Therefore, in clinically suspected cases of hypophosphatemic osteomalacia, 68Ga‐DOTATATE PET/CT should be preferred as an imaging modality investigation to avoid delay in the treatment of this disease.

The associations among ion uptake, root development and biomass under salt stress have not been fully understood. To study this, a pot experiment was conducted with the objective to determine the concentrations of sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), zinc (Zn) and iron (Fe) and explore their associations with the biomass and root development by using eight wheat cultivars grown on control and salt stress treatments. About 6 folds increase Na+/K+ ratio in root, while 10 folds in the shoot were detected in salt stress compared to that for control. Ca, Mg, Zn concentrations in both root and shoot, and Fe concentration in the shoot were significantly changed by salt stress, except Fe concentration in the root. Principal component analysis revealed significant associations of these ions with the aboveground biomass and root traits. On salt stress treatment, the Na+/K+ ratio in shoot showed a significant negative correlation with root weight and aboveground biomass, while aboveground biomass correlated positively with lateral root length and root weight. A strategy towards manipulating the ion homeostasis, particularly Na+/K+, combined with selecting genotypes with better salt tolerance is of promise to alleviate the effects of salt stress.

Although different types of drugs are available for postmenopausal osteoporosis, the limitations of the current therapies including drug resistances and adverse effects require identification of novel anti-osteoporosis agents. Here, we defined that norlichexanthone (NOR), a natural product, is a ligand of estrogen receptor-alpha (ERα) and revealed its therapeutic potential for postmenopausal osteoporosis. We used mammalian-one hybrid assay to screen for ERα modulators from crude extracts of several plant endophytes. As a result, NOR purified from the extract of endophyte ARL-13 was identified as a selective ERα modulator. NOR directly bound to ERα with an affinity in nanomolar range, revealing that it is a natural ligand of ERα. NOR induced osteoblast formation in MC3T3-E1 precursor cells. Conversely, NOR inhibited receptor activator of nuclear factor-kappa B ligand (RANKL)-induced osteoclast formation in both RAW264.7 macrophages and mouse primary monocytes. Mechanistically, NOR inhibited RANKL-induced association of ERα and TRAF6 to prevent ERα-mediated TRAF6 activation via Lys63-linked ubiquitination. Importantly, NOR exhibited potent anti-osteoporosis efficacy in an ovariectomized mouse model. Comparing to estrogen, NOR was of much less capability in stimulating endometrial hyperplasia and promoting mammalian cancer cell proliferation. Taken together, our study identified NOR as a natural and high affinity ligand of ERα with substantial anti-osteoporosis but less estrogenic activity.

Multitemporal interferometric synthetic aperture radar (InSAR) technology is extensively applied in earth observations. As a critical processing step, the estimation of covariance matrix directly affects the accuracy of its final result. Adaptive multilooking is proven to be an efficient estimator employing statistically homogeneous pixels (SHPs). In this context, the SqueeSAR initially introduced the Kolmogorov-Smirnov test to select SHPs. Furthermore, many test methods were developed based on real-valued data. Therefore, only amplitude is used and complex coherence is typically ignored. In this paper, a new SHP selection algorithm is proposed based on covariance matrix patch, named CMP. In particular, the complex patch is estimated using temporal samples rather than spatial samples. The Kullback-Leibler divergence is employed to evaluate the similarity between two complex patches. Then, the SHP set is initially determined by performing thresholding operation, and an iterative methodology is used to obtain a refined SHP set. Further application of CMP to estimate covariance matrix is investigated. The derived products include the filtered amplitude, interferometric phase and coherence. A series of experiments show the effectiveness of the proposed SHP selection method, especially suitable for cases with only interferometric phase differences. Moreover, due to the high computational cost, this method is generally recommended for small-sized stacks. The experimental results of filtered images also suggest its high performance in both noise suppression and detail preservation.

Wolbachia is a maternally inherited bacterium that is widely distributed among arthropods, in which it manipulates the reproduction of its hosts. Phage WO is the only bacteriophage known to infect Wolbachia, and may provide benefit to its host or arthropods. We screened for the presence of phage WO in Wolbachia-infected butterfly species for the first time, to investigate their diversity and evolutionary dynamics. All Wolbachia-infected butterfly species, including members of the families Hesperiidae, Lycaenidae, Nymphalidae, Papilionidae, and Pieridae, were found to harbor phage WO. Interestingly, 84% of 19 butterfly species, which were infected with a single Wolbachia strain harbored high levels of multiple phage types (ranging from 3 to 17 types), another three species harbored one or two phage types. For Wolbachia strains (ST-41, ST-19, ST-125 and ST-374) shared among various butterfly species, their host insects all harbored multiple phage types, while two Wolbachia strains (ST-297 and ST-wPcau) were found to infect one butterfly species, whose insect hosts harbored a single phage type, suggesting that horizontal transfer of Wolbachia between insects increased the likelihood of exposure to phages, resulting in increased phage genetic diversity. Twelve horizontal transmission events of phage WO were found, which shared common phage WO types among different Wolbachia strains associated with butterflies. Most horizontal transfer events involved different Wolbachia supergroups (A and B). Horizontal acquisition of phage WO might also occur between eukaryotes without Wolbachia transfer. Furthermore, 22 putative recombination events were identified in 13 of 16 butterfly species which harbored multiple phage types. These results showed that horizontal transfer of Wolbachia caused it to be exposed to the phage gene pool, and that horizontal transmission of phage WO, as well as intragenic recombination were important dynamics for phage WO genome evolution, which effectively promoted the high level of phage WO diversity associated with butterflies.

Among diverse intelligent assistive systems developed for amyotrophic lateral sclerosis (ALS) patients, headwear eye tracking based ones trigger broad interests due to their merits such as noninvasive, cost effective, and high operation freedom. However, with headwear eye trackers, patients are easy to feel tired during human–machine interactivities (HMIs), and the operation accuracy is not satisfied compared with its counterparts. To address these two issues, herein, a visual feedback technique is developed which allows users to recognize machine's vision by positioning a laser spot to the user watched object, according to the location information interpreted from user's eye movement. Through the visual feedback technique, users not only obtain real‐time feedback, but also can fine‐tune the laser spot to the desired location before performing further operations. Experimental results demonstrate that the presented work can successfully reduce user's fatigue and boost operation accuracy by 25.1% and 27.6%, respectively, therefore, advancing the field of intelligent assistive technologies.

To better understand the diversity and phylogeny of Perlodidae, we sequenced and annotated the complete mitochondrial genome (mitogenome) of Arcynopteryx dichroa. This mitogenome was 16,215 bp long and encoded 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), 2 ribosomal RNA unit genes (rRNAs), and a control region like other plecopteran. The nucleotide composition of A. dichroa mitochondrial genome obviously biases toward A and T. The A + T content of the whole mitochondrial genome, the PCGs, tRNAs, rRNAs, and the control region were: 69.3%, 67.6%, 69.8%, 71.3%, and 78.7%. Phylogenetic relationship based on the concatenated sequences of 13 PCGs and two ribosomal RNAs showed that the family Perlodidae and Chloroperlidae are sister relationship, family Perlidae being the sister group to the clade (Perlodidae + Chloroperlidae). The monophyly of the family Perlodidae is well supported but the subfamily Perlodinae and Isoperlinae are not monophyletic groups.

Abstract Background Vancomycin-resistant Enterococcus spp. (VRE) have spread all over the world. The present study aims to investigate the species distribution, specimen type and susceptibilities of Enterococcal species collected from Nanjing Drum Tower Hospital from 2013 to 2018. Additionally, distribution of VRE and prevalence of van gene among VRE isolates were also analyzed. Methods The susceptibilities of 3913 Enterococcus isolates were retrospectively investigated. Among these strains, 60 VRE strains were further anazlyed in this study. The minimum inhibitory concentrations (MICs) of the VRE strains towards vancomycin, teicoplanin and linezolid were determined by E-test. Polymerase chain reaction (PCR) and DNA sequencing were used to investigate the prevalence of van genes among VRE. Furthermore, the sequence types (STs) of VRE strains were explored by multi-locus sequence typing (MLST). Results Among the 3913 enterococci isolates, Enterococcus faecalis (n = 1870, 47.8%) and Enterococcus faecium (1738, 44.4%) were the main isolates. These Enterococcus strains were mainly isolated from urine (n = 1673, 42.8%), followed by secretions (n = 583, 14.9%) and ascites (n = 554, 14.2%). VRE displayed a decreasing trend year by year. Molecular analysis revealed that 49 out of 60 VRE isolates carried vanA gene, 10 carried vanM, and 1 carried both vanA and vanM genes. Sixteen distinct STs were identified among the 58 VREM, with ST78 (n = 16), ST192 (n = 8) and ST570 (n = 7) being the most dominant ones. Conclusions E. faecalis and E. faecium were the major enterococci strains which are the main pathogens of urinary traction infections; vanA and vanM were the main determinants conferring resistance to vancomycin; ST78, ST192 and ST570 were the leading STs of VREM which displayed a decreasing trend of prevalence year by year.

The MOD10A1 daily snow cover product offers a fine temporal resolution, which is particularly important for time-critical applications. Although the reliability of this product was mostly verified by ground measurements before use, the inadequate representativeness of point-scale observations may lead to errors in the assessment of MOD10A1. In this study, based on the Google Earth Engine, MOD10A1 was thoroughly evaluated by a total of 20 131 binary snow maps generated from 30 m Landsat imagery for the 2000-2016 snow seasons in three typical snow regions across China. The three typical snow regions included Northern Xinjiang, Northeast China, and the Tibetan Plateau. In general, the accuracy of MOD10A1 under clear sky conditions is 86.5% based on ground observations from meteorological stations and 90.3% based on Landsat imagery. Compared with ground measurements, snow cover derived from Landsat images is in better agreement with MOD10A1 due to a better spatial match. The error analyses also indicate that 1) compared with land cover, topography has larger effects on the accuracy of MOD10A1 over the three snow regions with statistically significant negative relationships, particularly in Northern Xinjiang (R = -0.604, P

Touch and vision perception are two important functions humans use to interact with the real world. To mimic human‐like abilities, tactile‐ and visual‐sensing‐based intelligent humanoids have emerged and are going through a fast phase of development. Studies have demonstrated that the combination of tactile and visual information not only enables humanoids to better learn the environment, but also allows them to have pseudocognitive ability. Being a new and rapidly developing field of research, a significant growth in articles reporting different aspects of sensing and related machine learning is being witnessed. To help readers comprehensively understand the fundamentals and insights, and the current state of the art, this review is compiled to explain the working mechanisms of tactile and visual sensing, introduce the application of intelligent humanoids in diverse scenarios, discuss current challenges, and predict future trends.

Objective. A 3-month depot of leuprorelin acetate (LA) was introduced in China in July 2020. However, the clinical experience is limited. The purpose of this study was to compare the efficacy of a LA 11.25 mg 3-month depot with that of a 3.75 mg 1-month depot in suppressing pubertal development for the treatment of central precocious puberty (CPP). Subjects and Methods. A prospective study, including 78 girls with CPP treated with LA, was conducted. 31 patients were treated with a LA 3-month depot, and 47 were treated with a LA 1-month depot. Participants were interviewed at baseline and 6 months. Anthropometric, metabolic, and reproductive data were assessed at each interview. Bone age, serum endocrine hormones, maximum diameter of uterus and volume of ovary of each patient were evaluated. A pharmacoeconomic evaluation was also conducted. Results. Treatment with a 3-month depot was similar to treatment with a 1-month depot in terms of baseline characteristics. After 6 months of treatment, a suppressed level of luteinizing hormone (LH) (LH

To improve the spatial density and quality of measurement points in multitemporal interferometric synthetic aperture radar, distributed scatterers (DSs) should be processed. An essential procedure in DS interferometry is phase estimation, which reconstructs a consistent phase series from all available interferograms. Influenced by the well-known suboptimality of coherence estimation, the performance of the state-of-the-art phase estimation algorithms is severely degraded. Previous research has addressed this problem by introducing the coherence bias correction technique. However, the precision of phase estimation is still insufficient because of the limited correction capabilities. In this paper, a modified phase estimation approach is proposed. Particularly, by incorporating the information on both interferometric coherence and the number of looks, a significant bias correction to each element of the coherence magnitude matrix is achieved. The bias-corrected coherence matrix is combined with advanced statistically homogeneous pixel selection and time series phase optimization algorithms to obtain the optimal phase series. Both the simulated and Sentinel-1 real data sets are used to demonstrate the superiority of this proposed approach over the traditional phase estimation algorithms. Specifically, the coherence bias can be corrected with considerable accuracy by the proposed scheme. The mean bias of coherence magnitude is reduced by more than 29%, and the standard deviation is reduced by more than 18% over the existing bias correction method. The proposed approach achieves higher accuracy than the current methods over the reconstructed phase series, including smoother interferometric phases and fewer outliers.