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Summary: Low-temperature solid oxide fuel cells (LT-SOFCs) are a promising next-generation fuel cell due to their low cost and rapid start-up, posing a significant challenge to electrode materials with high electrocatalytic activity. Herein, we reported the bimetallic nanoparticles encapsulated in carbon nanotubes (NiFe@CNTs) prepared by carefully controlling catalytic pyrolysis of waste plastics. Results showed that plenty of multi-walled CNTs with outer diameters (14.38 ± 3.84 nm) were observed due to the smallest crystalline size of Ni-Fe alloy nanoparticles. SOFCs with such NiFe@CNTs blended in anode exhibited remarkable performances, reaching a maximum power density of 885 mW cm−2 at 500°C. This could be attributed to the well-dispersed alloy nanoparticles and high graphitization degree of NiFe@CNTs to improve HOR activity. Our strategy could upcycle waste plastics to produce nanocomposites and demonstrate a high-performance LT-SOFCs system, addressing the challenges of sustainable waste management and guaranteeing global energy safety simultaneously.

In order to solve the problems of the low transaction success rate and network imbalance of the payment channel network, an efficient routing strategy of blockchain-based payment channel network was proposed.This strategy established a dedicated payment channel for the high-priority services according to the service type and service priority, and divided the conventional business into multiple transaction unit.Furthermore, a channel balanced routing algorithm was designed to route each transaction unit, which could reduce the number of transactions on the blockchain and maintain long-term stable operation of the off-chain payment channel, as well as improve the transaction success rate.In addition, in order to avoid the temporary shortage of funds and unavailability of channels due to a certain link occupied by multiple transactions simultaneously, a transaction queuing mechanism in the payment channel network was designed.This mechanism established the forwarding rules for transactions by calculating the escrow amount between the node that transactions arrived and the next hop node, where the channel balanced routing algorithm was used to calculate the new forwarding path for the nodes that could not carry out capital injection within the queuing threshold.The simulation results show that the proposed strategy could improve the transaction success rate and realize the equilibrium of the payment channel network.

A coupling mechanism between flicker noise and hot carrier degradation (HCD) is revealed in this work. Predicting the flicker noise properties of fresh and aged devices is becoming essential for circuit designs, requiring an understanding of the fundamental noise behaviors. While certain models for fresh devices have been proposed, those for aged devices have not been reported yet because of the lack of a clear mechanism. The flicker noise of aged FinFETs is characterized based on the measure-stress-measure (MSM) method and analyzed from the device physics. It is found that both the mean and deviations of the noise power spectral density increase compared with the fresh counterparts. A coupling mechanism is proposed to explain the trap time constants, leading to the trap characterizations in their energy profiles. The amplitude and number of contributing traps are also changing and are dependent on the mode of HCD and determined by the position of the induced traps. A microscopic picture is developed from the perspective of trap coupling, reproducing well the measured noise of advanced nanoscale FinFETs. The finding is important for accurate flicker noise calculations and aging-aware circuit designs.

As an essential piece of infrastructure supporting cyberspace security technology verification, network weapons and equipment testing, attack defense confrontation drills, and network risk assessment, Cyber Range is exceptionally vulnerable to distributed denial of service (DDoS) attacks from three malicious parties. Moreover, some attackers try to fool the classification/prediction mechanism by crafting the input data to create adversarial attacks, which is hard to defend for ML-based Network Intrusion Detection Systems (NIDSs). This paper proposes an adversarial DBN-LSTM method for detecting and defending against DDoS attacks in SDN environments, which applies generative adversarial networks (GAN) as well as deep belief networks and long short-term memory (DBN-LSTM) to make the system less sensitive to adversarial attacks and faster feature extraction. We conducted the experiments using the public dataset CICDDoS 2019. The experimental results demonstrated that our method efficiently detected up-to-date common types of DDoS attacks compared to other approaches.

In this paper, a vertically stacked nanosheet gate-all-around field-effect transistor (GAA-NSFET) as a label-free biosensor has been proposed and investigated. The influences of different biomolecules on the biosensor’s electrical properties are analyzed, and the proposed biosensor exhibits good sensitivity for both neutral and charged biomolecules. Furthermore, a deep sensitivity analysis is performed to evaluate the sensing ability of biosensors with different channel structures. The sensitivity variation of biosensors is analyzed in terms of subthreshold swing ( $SS $ ), threshold voltage ( $V_{\text {th}}$ ), and current switching ratio ( $I_{\text {on}} / I_{\text {off}}$ ). The results show that GAA-NSFET-based biosensor obtains the best sensitivity compared with other biosensors (including nanowire FET-based biosensor and vertically stacked nanowire FET-based biosensor) due to its larger channel width and multi-channels. Also, the influences of filling position on sensitivity are analyzed in various cases for the proposed biosensor. Its sensitivity depends on the filling amounts of biomolecules instead of the filling position. Finally, a status map is presented, which plots the sensitivity of some important works in biosensing application along with the sensitivity of the proposed biosensor, and GAA-NSFET-based biosensor is more sensitive compared with those works in terms of $I_{\text {on}}/I_{\text {off}}$ sensitivity.

Increasing demands for mass storage and new paradigm computing ask for non-volatile memories that can meet reliability requirements. Hf0.5Zr0.5O2-based (HZO) memory has attracted growing attention due to its excellent CMOS compatibility. This letter investigated the time dependent dielectric breakdown (TDDB) of HZO ferroelectric under both forward and reverse stress conditions, which is relevant to the memory’s practical operation. The key similarities and the differences for both breakdown conditions have been identified and the underlying mechanism is explored. It is found that the pre-existing oxygen vacancies near the bottom electrode play the key role and all the observed phenomenon can be explained. Therefore, the precise control of these pre-existing oxygen vacancies can be critical for future TDDB improvement.

The RRAM-based array is one of the most promising core functional primitives to accelerate the inference process of neural networks. However, the stress-induced disturbance can cause a significant accuracy drop during inference process where input vectors with different voltage levels are fed to the device. This kind of disturb can hardly be avoided by optimizing the fabrication process. Here, we investigate this phenomenon based on TaOx-based devices with different electrodes. The results indicate that the stress-induced disturb mainly appears in the intermediate resistance states when the voltage is applied on the device. The simulation result by COMSOL reveals the relationship between read disturb and electric field. Therefore, we propose a nonlinear weight quantification method to mitigate read disturb effect on inference accuracy by reducing the number of devices in intermediate resistance states. The simulation results based on the fully-connected networks for MNIST recognition indicate that stress disturb phenomenon can be well suppressed by nonlinear weight quantification compared with the conventional linear quantification method, which will advance the application of the RRAM-based accelerator.

In this study, a transition metal-based perovskite oxide catalyst with high CH3OH yield was successfully developed. The A-site substitution by Pr3+ in La1-xPrxMn0.6Ni0.4O3-δ can effectively adjust the activity of the perovskite catalysts for the direct conversion of CO2 and H2O into hydrocarbon fuels, especially CH3OH. Based on the designed photo-thermo synergetic photosynthesis strategy, the first hour CH3OH yield of La1-xPrxMn0.6Ni0.4O3-δ reached 3.97 mmol g−1, while only 0.24 μmol g−1 under normal photocatalysis mode. The synergistic photo-thermo catalysis was demonstrated to be a promising strategy for the future artificial photosynthesis development.

Introduction: Lower urinary tract symptoms (LUTS) involve benign prostatic hyperplasia (BPH) and overactive bladder (OAB). Standard-of-care medical treatment includes α1-blockers and antimuscarinics for reduction of prostate and detrusor smooth muscle tone, respectively, and 5α-reductase inhibitors (5-ARI) to prevent prostate growth. Current medications are marked by high discontinuation rates due to unfavourable balance between efficacy and treatment-limiting side effects, ranging from dry mouth for antimuscarinics to cardiovascular dysregulation and a tendency to fall for α1-blockers, which results from hypotension, due to vasorelaxation. Agonist-induced smooth muscle contractions are caused by activation of receptor-coupled G-proteins. However, little is known about receptor- and organ-specific differences in coupling to G-proteins. With YM-254890, a small molecule inhibitor with presumed specificity for Gαq/11 became recently available. Here, we investigated effects of YM-254890 on prostate, bladder and vascular smooth muscle contraction, and on growth-related functions in prostate stromal cells.Methods: Contractions of human prostate and detrusor tissues, porcine renal and coronary arteries were induced in an organ bath. Proliferation (EdU assay), growth (colony formation), apoptosis and cell death (flow cytometry), viability (CCK-8) and actin organization (phalloidin staining) were studied in cultured human prostate stromal cells (WPMY-1).Results: Contractions by α1-adrenergic agonists, U46619, endothelin-1, and neurogenic contractions were nearly completely inhibited by YM-254890 (30 nM) in prostate tissues. Contractions by cholinergic agonists, U46619, endothelin-1, and neurogenic contractions were only partly inhibited in detrusor tissues. Contractions by α1-adrenergic agonists, U46619, endothelin-1, and neurogenic contractions were strongly, but not fully inhibited in renal arteries. Contractions by cholinergic agonists were completely, but by U46619 and endothelin-1 only strongly inhibited, and neurogenic contractions reduced by half in coronary arteries. YM-254890 had no effect on agonist-independent contractions induced by highmolar (80 mM) potassium chloride (KCl). Neurogenic detrusor contractions were fully sensitive to tetrodotoxin. In WPMY-1 cells, YM-254890 caused breakdown of actin polymerization and organization, and obvious, but clearly limited decreases of proliferation rate, colony formation and viability, and slightly increased apoptosis.Conclusion: Intracellular post-receptor signaling pathways are shared by Gαq-coupled contractile receptors in multiple smooth muscle-rich organs, but to different extent. While inhibition of Gαq/11 causes actin breakdown, anti-proliferative effects were detectable but clearly limited. Together this may aid in developing future pharmaceutical targets for LUTS and antihypertensive medication.

Background and AimsThe extent of surgical treatment for most patients with thyroid cancer (TC) remains controversial and varies widely. As an emerging technology, genetic testing facilitates tumor typing and disease progression monitoring and is expected to influence the choice of surgical approach for patients with TC. Recent genome-wide association studies (GWASs) have identified that rs2439302 (8p12) variants near NRG1 are associated with TC risk; however, the results remain inconclusive. Therefore, we aimed to perform a meta-analysis to clarify the association between rs2439302 variants and the risk of TC.MethodsWe search eligible studies using Pubmed, Scopus, Embase, Web of Science, and Cochrane library by July 2021. We analyzed the pooled OR and the corresponding 95% confidence interval (95% CI) of the included studies and then conducted subgroup analysis according to the ethnicity. We also performed a sensitivity analysis to validate the findings.ResultsThis meta-analysis finally included 7 studies involving 6,090 cases and 14,461 controls. Results showed that the G allele of the rs2439302 polymorphism was a significant risk factor of TC in Allele (G/C), Dominant (GG+GC/CC), Recessive (GG/GC+CC), Homozygote (GG/CC), Heterozygote (GC/CC) models, with pooled ORs of 1.38 (95%CI, 1.31–1.45), 1.51 (95%CI, 1.41–1.62), 1.52 (95%CI, 1.40–1.66), 1.90 (95%CI, 1.71–2.10), and 1.40 (95%CI, 1.30–1.51), respectively. The subgroup analysis showed that rs2439302 polymorphism was associated with higher TC risk in different ethnicities with OR > 1. The sensitivity analysis exhibited that the results were stable by omitting any included studies.ConclusionsThe study revealed that rs2439302 variants were associated with higher TC risk and may have a major influence on the choice of operative approach for patients with TC.

Reusing traction electric machine windings in electric vehicles as an integrated filtering inductor is a promising solution to reduce the size of the vehicle to grid (V2G) charging/discharging system. Obviously, the integrated inductors need to meet the requirements of traction and charging/discharging, which brings challenge for the design of traction machines. As one of the most popular traction electric machine types, the high-speed induction machine usually has large electrical time constant and consequently unacceptably long transient time in the design stage when finite element analysis is adopted. In this article, a method is proposed to quickly and accurately calculate the steady state performance of the induction machine by time-stepping transient magnetic finite element analysis. First, the stator current magnitude is ramped up from zero to full magnitude gradually to control the DC component in rotor flux and torque. Second, a multistep equivalent resistance method is adopted to decrease rotor time constant and suppress slot-tooth harmonic transient response. The proposed method can predict the FEA computation load before running the calculation, and it does not rely on the machine parameter and feedback signal. Its performance is tested by an example induction machine. The result shows that the proposed method can reduce the finite element calculation time of a high-speed operating point by 99%.

As an important indicator of atmospheric aridity, the vapor pressure deficit (VPD) is being paid increasing attention in global change researches during recent decades. However, available proxy data with the capability to represent VPD is still scarce in the globe. Herein we demonstrated a “hidden” frequency-dependent indication of tree-ring cellulose oxygen isotope (δ18OTRC) to atmospheric aridity in the western Kunlun Mountains, Central Asia. In applying correlation and partial correlation analysis, frequency-dependent climatic drivers triggering the δ18OTRC values were detected. For the raw data with inter-decadal variability, δ18OTRC variations mainly indicated May–August precipitation (Local: r = –0.59, p

Pancreatic cancer is one of the most common malignant tumors in the digestive system with a poor prognosis. Accordingly, better understanding of the molecular mechanisms and innovative therapies are warranted to improve the prognosis of this patient population. In addition to playing a crucial role in coagulation, platelets reportedly contribute to the growth, invasion and metastasis of various tumors, including pancreatic cancer. This narrative review brings together currently available evidence on the impact of platelets on pancreatic cancer, including the platelet-related molecular mechanisms of cancer promotion, pancreatic cancer fibrosis, immune evasion, drug resistance mechanisms, thrombosis, targeted platelet therapy, combined radiotherapy and chemotherapy treatment, platelet combined with nanotechnology treatment and potential applications of pancreatic cancer organoids. A refined understanding of the role of platelets in pancreatic cancer provides the foothold for identifying new therapeutic targets.

Abstract Background Central line-associated bloodstream infections (CLABSI) are largely preventable when evidence-based guidelines are followed. However, it is not clear how well these guidelines are followed in intensive care units (ICUs) in China. This study aimed to evaluate Chinese ICU nurses’ knowledge and practice of evidence-based guidelines for prevention of CLABSIs issued by the Centers for Disease Control and Prevention, US and the Department of Health UK. Method Nurses completed online questionnaires regarding their knowledge and practice of evidence-based guidelines for the prevention of CLABSIs from June to July 2019. The questionnaire consisted of 11 questions, and a score of 1 was given for a correct answer (total score = 0–11). Results A total of 835 ICU nurses from at least 104 hospitals completed the questionnaires, and 777 were from hospitals in Guangdong Province. The mean score of 11 questions related to evidence-based guidelines for preventing CLABSIs was 4.02. Individual total scores were significantly associated with sex, length of time as an ICU nurse, educational level, professional title, establishment, hospital grade, and incidence of CLABSIs at the participant’s ICU. Importantly, only 43% of nurses reported always using maximum barrier precautions, 14% of nurses reported never using 2% chlorhexidine gluconate for antisepsis at the insertion site, only 40% reported prompt removal of the catheter when it was no longer necessary, and 33% reported frequently and routinely changing catheters even if there was no suspicion of a CLABSI. Conclusion Chinese ICU nurses in Guangdong Province lack of knowledge and practice of evidence-based guidelines for the prevention of CLABSIs. National health administrations should adopt policies to train ICU nurses to prevent CLABSIs.

Designing energy efficient and scalable artificial networks for neuromorphic computing remains a challenge. Here, the authors demonstrate online learning in a monolithically integrated 4 × 4 fully memristive neural network consisting of volatile NbOx memristor neurons and nonvolatile TaOx memristor synapses.

Blockchain is a kind of distributed ledger technology that upgrades to a complete storage system by adding logic control functions such as intelligent contracts.With the changes of its classification,service mode and application requirements,the core technology forms of Blockchain show diversified development.In order to understand the Blockchain ecosystem thoroughly,a hierarchical technology architecture of Blockchain was proposed.Furthermore,each layer of blockchain was analyzed from the perspectives of basic principle,related technologies and research progress in-depth.Moreover,the technology selections and characteristics of typical Blockchain projects were summarized systematically.Finally,some application directions of blockchain frontiers,technology challenges and research prospects including Smart Cities and Industrial Internet were given.

Introduction MicroRNAs (miRs) are small noncoding RNAs which are regulators of gene expression and also regulate the genes in heart tissues. The aim of the study was to evaluate the effect of miRs on the expression level of myosin heavy chain (MHC), which is responsible for regulation of cardiac functions in neonatal rat ventricular myocytes and mice. Material and methods The miRs were suppressed in neonatal rat ventricular myocytes using small interfering RNAs (siRNAs) against Dicer followed by evaluation of MHC levels. For in vivo study the C57 black/6 Jacksonian mice were subjected to the transverse aortic constriction (TAC) procedure. Results The Dicer siRNA suppressed the endogenous miRs and the α-MHC gene but failed to down-regulate the β-MHC. Among the 17 selected miRs, miR-29a was found to up-regulate the α-MHC gene significantly but not β-MHC. The expression of α-MHC was suppressed by silencing the expression of miR-29a. Bioinformatics study done by TargetScan suggested thyroid hormone receptor-β1 (TR-β1) as a potential target of miR-29a. Additionally, miR-29a was found to regulate the expression of α-MHC via TR-β1 signaling. Conclusions The findings of the present study indicated that miR-29a modulates expression of α-the MHC gene by targeting TR-β1 in cardiac cells. The study may provide a new direction for treating cardiac failure and cardiac hypertrophy.

Wireless sensor networks play an important role in Internet of Things systems and services but are prone and vulnerable to poor communication channel quality and network attacks. In this paper we are motivated to propose resilient routing algorithms for wireless sensor networks. The main idea is to exploit the link reliability along with other traditional routing metrics for routing algorithm design. We proposed firstly a novel deep-learning based link prediction model, which jointly exploits Weisfeiler-Lehman kernel and Dual Convolutional Neural Network (WL-DCNN) for lightweight subgraph extraction and labelling. It is leveraged to enhance self-learning ability of mining topological features with strong generality. Experimental results demonstrate that WL-DCNN outperforms all the studied 9 baseline schemes over 6 open complex networks datasets. The performance of AUC (Area Under the receiver operating characteristic Curve) is improved by 16% on average. Furthermore, we apply the WL-DCNN model in the design of resilient routing for wireless sensor networks, which can adaptively capture topological features to determine the reliability of target links, especially under the situations of routing table suffering from attack with varying degrees of damage to local link community. It is observed that, compared with other classical routing baselines, the proposed routing algorithm with link reliability prediction module can effectively improve the resilience of sensor networks while reserving high-energy-efficiency.

The detection of pathogens in food and clinical samples remains a challenge. Here, Shen et al. present a detection system, involving a combination of nucleic acid-based allosteric probes and CRISPR-Cas13a components, that can detect very low numbers of a bacterial pathogen in milk and serum samples without isolation.

Autosomal recessive cerebellar ataxia type 1 (ARCA-1), also known as autosomal recessive spinocerebellar ataxia type 8 (SCAR8), is caused by spectrin repeat containing nuclear envelope protein 1 (SYNE1) gene mutation. Nesprin-1, encoded by SYNE1, is widely expressed in various tissues, especially in the striated muscle and cerebellum. The destruction of Nesprin-1 is related to neuronal and neuromuscular lesions. It has been reported that SYNE1 gene variation is associated with Emery-Dreifuss muscular dystrophy type 4, arthrogryposis multiplex congenita, SCAR8, and dilated cardiomyopathy. The clinical manifestations of SCAR8 are mainly characterized by relatively pure cerebellar ataxia and may be accompanied by upper and/or lower motor neuron dysfunction. Some affected people may also display cerebellar cognitive affective syndrome. It is conventionally held that the age at the onset of SCAR8 is between 6 and 42 years (the median age is 17 years). Here, we report a pedigree with SCAR8 where the onset age in the proband is 48 years. This case report extends the genetic profile and clinical features of SCAR8. A new pathogenic site (c.7578del; p.S2526Sfs*8) located in SYNE1, which is the genetic cause of the patient, was identified via whole exome sequencing (WES).

As semiconductor technology enters the more than Moore era, there exists an apparent contradiction between the rapidly growing demands for data processing and the visible inefficiency rooted in traditional computing architecture. Neuromorphic systems hold great prospects in enabling a new generation of computing paradigm that can address this issue, which demands device components with rich dynamics and nonlinearity. Herein, the nonlinearity in memristive devices and their application in building neuromorphic dynamic systems are reviewed. The internal mechanisms that endow memristive devices with nonlinearity and rich dynamics are reviewed and subsequently the nonlinear spiking neurons that are implemented utilizing the physical processes in memristors are shown. Typical examples on neuromorphic dynamic systems based on nonlinear memristors are summarized, including memristive reservoir, memristive oscillatory neural network, and memristive chaotic computing. Finally, an outlook in the development of neuromorphic dynamic systems is given.

The vibration induced by blasting excavation of the subway tunnel in complex urban environments may cause harmful effects on adjacent buildings. Investigating the dynamic response of adjacent buildings is a key issue to predict and control blasting hazards. In this paper, the blasting excavation of the subway tunnel right below a building was selected as a case study, and the blast vibrations in the field were monitored. The Hilbert–Huang Transform (HHT) model was used to extract and analyze the time-frequency characteristic parameters of blasting dynamic response signals. By substituting intrinsic mode functions (IMF) component frequency and instantaneous energy for main frequency and blasting total input energy, respectively, the characteristics of time-instantaneous frequency-instantaneous energy of buildings under blasting seismic load were analyzed, and the concept of effective duration of vibration was proposed.

During downward mining of a bifurcated coal seam, the roof of the lower coal seam is relatively broken and difficult to control due to the mining influence of the upper coal seam. Roof accidents occur frequently during mining of the lower coal seam, reducing mining efficiency. How to ensure safe and efficient mining of the lower coal seam is a significant issue. In this paper, overlying strata migration and fracture characteristics of the lower coal seam, the structure and stability of the regenerated roof, and porosity and permeability characteristics of the overlying strata under the mining influence of the upper coal seam are studied by using similar simulation tests. Results show that the overburden structure of the lower coal seam is altered due to the mining influence of the upper coal seam, and the regenerated roof of the lower coal seam is divided into three structural types from top to bottom, namely: intact rock mass+block fracture rock mass+loose rock mass (type I structure); intact rock mass+block fracture rock mass+loose rock mass+cataclastic rock mass (type II structure); and intact rock mass+block fracture rock mass+loose rock mass+cataclastic rock mass+slab-rent rock mass (type III structure). The stability of each type of rock mass structure is evaluated, and the stability of three types of rock mass structures is III > II > I. The overburden porosity and slurry permeability coefficient are relatively large at the cutting hole and stopping line. The porosity of the caving zone within 70 m of the cut hole and stopping line is greater than 5%, and the permeability coefficient is greater than 0.1 m/s. Based on differences in the surrounding rock porosity and permeability characteristics, the grouting difficulty of overburden is divided into three types of areas: extremely easy grouting areas, easy grouting areas, and difficult grouting areas. The results of this paper can provide reference for the stability evaluation of the regenerated roof and the selection of grouting treatment parameters for the broken roof under similar conditions.

Deep neural networks (DNNs) are one of the key fields of machine learning. It requires considerable computational resources for cognitive tasks. As a novel technology to perform computing inside/near memory units, in-memory computing (IMC) significantly improves computing efficiency by reducing the need for repetitive data transfer between the processing and memory units. However, prior IMC designs mainly focus on the acceleration for DNN inference. DNN training with the IMC hardware has rarely been proposed. The challenges lie in the requirement of DNN training for high precision (e.g. floating point (FP)) and various operations of tensors (e.g. inner and outer products). These challenges call for the IMC design with new features. This paper proposes a novel Hadamard product-based IMC design for FP DNN training. Our design consists of multiple compartments, which are the basic units for the matrix element-wise processing. We also develop BFloat16 post-processing circuits and fused adder trees, laying the foundation for IMC FP processing. Based on the proposed circuit scheme, we reformulate the back-propagation training algorithm for the convenience and efficiency of the IMC execution. The proposed design is implemented with commercial 28 nm technology process design kits and benchmarked with widely used neural networks. We model the influence of the circuit structural design parameters and provide an analysis framework for design space exploration. Our simulation validates that MobileNet training with the proposed IMC scheme saves $91.2\%$ in energy and $13.9\%$ in time versus the same task with NVIDIA GTX 3060 GPU. The proposed IMC design has a data density of 769.2 Kb mm ^−2 with the FP processing circuits included, showing a 3.5 × improvement than the prior FP IMC designs.

Accounting for 41.7% of China’s total land area, grasslands are linked to the livelihoods of over 20 million people. Although grassland fires cause severe damage in China every year, their spatiotemporal patterns and climate drivers are not well understood. In this study, we used grassland fire record forms provided by the National Forestry and Grassland Administration and grassland fire location data from the Wildfire Atlas of China to examine the spatiotemporal patterns and and seasonality of fires in China for the period from 2008 to 2020. We found that most grassland fires occurred in Inner Mongolia in northern China, specifically in the Hulun Buir and Xilingol grasslands. We found distinct differences in fire seasonality in northern China, which has a major fire season in April, versus southwestern China, where the major fire season occurs in February, March and April. April grassland fires in northern China are the result of strong winds, typically from the west, and spring drought. A secondary fire season in northern China occurs in October and is also driven by strong winds. The fire season in southwestern China seems to be less shaped by climatic factors such as wind speed, precipitation, and drought. This study provides support for decision-making by fire prevention and fire management authorities in China.

Artificial neural networks (ANNs), like convolutional neural networks (CNNs), have achieved the state-of-the-art results for many machine learning tasks. However, inference with large-scale full-precision CNNs must cause substantial energy consumption and memory occupation, which seriously hinders their deployment on mobile and embedded systems. Highly inspired from biological brain, spiking neural networks (SNNs) are emerging as new solutions because of natural superiority in brain-like learning and great energy efficiency with event-driven communication and computation. Nevertheless, training a deep SNN remains a main challenge and there is usually a big accuracy gap between ANNs and SNNs. In this paper, we introduce a hardware-friendly conversion algorithm called “scatter-and-gather” to convert quantized ANNs to lossless SNNs, where neurons are connected with ternary {−1,0,1} synaptic weights. Each spiking neuron is stateless and more like original McCulloch and Pitts model, because it fires at most one spike and need be reset at each time step. Furthermore, we develop an incremental mapping framework to demonstrate efficient network deployments on a reconfigurable neuromorphic chip. Experimental results show our spiking LeNet on MNIST and VGG-Net on CIFAR-10 datasetobtain 99.37% and 91.91% classification accuracy, respectively. Besides, the presented mapping algorithm manages network deployment on our neuromorphic chip with maximum resource efficiency and excellent flexibility. Our four-spike LeNet and VGG-Net on chip can achieve respective real-time inference speed of 0.38 ms/image, 3.24 ms/image, and an average power consumption of 0.28 mJ/image and 2.3 mJ/image at 0.9 V, 252 MHz, which is nearly two orders of magnitude more efficient than traditional GPUs.

Aim: Since the 2019 coronavirus disease (COVID-19) outbreak, medical staff have faced greater psychological stress and are prone to psychological problems such as anxiety and depression, as confirmed by several studies. This study further clarifies the psychological status of Chinese medical staff during the stable phase of the pandemic through a cross-sectional investigation in a large population sample in northern China.Methods: Subjects: Clinical frontline medical staff from seven hospitals in Liaoning Province were recruited from November 2020 to February 2021.Research Tools: The research tools used were the Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), Simplified Coping Style Questionnaire (SCSQ), and General Status Questionnaire.Statistical Analysis: SPSS 22.0, ANOVA variance analysis, and multiple logistics regression were used for statistical analysis. P-values of

With the development of the internet of things (IoT),5G and industrial technology,industrial IoT has become a new research field.Due to the specific requirements of delay,security and stability in industrial production,the traditional DNS has limitations to meet the needs of industrial IoT because of its single identity object,rigid resolution results,and weak security.In this context,how to provide efficient,flexible and secure resolution services for universal objects has become a hot area worldwide.Firstly,we discussed the design principles and key supporting technologies of the identity resolution system in industrial IoT.Then summarized and compared the existing identity resolution systems in detail.Next,the new identity resolution schemes in academic research were introduced.Finally,the core problems and the future research trend in this field were discussed.

Abstract Background Although significant improvement in efficacy measured by a sustained virological response, the high acquisition costs of direct-acting antivirals limit the access for patients and influence the costs of healthcare resource utilisation in hepatitis C. It is important to have the latest estimates of prevalence, especially in high-risk groups, for cost of illness, cost-effectiveness and budget impact studies. Methods Original studies on the estimates of the prevalence among general and high-risk groups in the European Union/European Economic Area (EU/EEA) were retrieved from Medline and Embase for the period from 2015 to 2018. All included studies were evaluated for risk of selection bias and summarised together in a narrative form. Results from previous reviews and updated searches were compared per country among different populations, respectively. Results Among the 3871 studies identified, 46 studies were included: 20 studies were used for the estimate of the general population; 3 for men who have sex with men (MSM); 6 for prisoners; and 17 for people who inject drugs (PWID). Compared with the results reported in previous systematic reviews, the updated estimates were lower than previously in most available countries. Anti-HCV general population prevalence estimates ranged from 0.54 to 1.50% by country. The highest prevalence of anti-HCV was found among PWID (range of 7.90–82.00%), followed by prisoners (7.00–41.00%), HIV-positive MSM (1.80–7.10%), HIV-negative MSM (0.20–1.80%), pregnant women (0.10–1.32%) and first-time blood donors (0.03–0.09%). Conclusions Our study highlights the heterogeneity in anti-HCV prevalence across different population groups in EU/EEA. The prevalence also varies widely between European countries. There are many countries that are not represented in our results, highlighting the need for the development of robust epidemiological studies.

Gastric lesions presenting as polyps becomes common these days. Many different underlying causes have been suspected with the origin of gastric polyps. Generally, a gastric polyp is considered as benign in the first impression unless proven otherwise. Though, they show a vast variety of malignant potentials. This literature is intended to describe and evaluate the variations, presentations, features, and potentials of gastric polypoid lesions.

Network virtualization allows multiple isolated virtual networks (VNs) to share the same substrate network (SN). VN embedding (VNE) algorithms can efficiently allocate the limited SN resources to VNs and assign a unique identifier to each VN. However, the fixed bit width of VN identifier in the packet header limits the number of VNs, and extending the bit width leads to the increase of the network traffic. In this paper, we consider the label-combination method to generate VN identifiers by combining the link-grained labels with location information. This method requires the efficient allocation of labels, but the existing VN embedding works only consider the CPU and bandwidth resources. To address this issue, we propose a novel embedding model that considers the label, CPU and bandwidth resource constraints. Furthermore, two window-based heuristic algorithms called VNE-LIA and VNE-iLIA using the greedy algorithm and the proximity principle are presented to solve the VNE problem. The simulation experiments show that our proposed algorithms increase the number of VN identifiers and the revenue to cost ratio under the different resource conditions of SN.

Broomcorn millet is one of the earliest domesticated plants and has the highest water use efficiency among cereals. Here, the authors report its genome assembly and annotation, which provides a valuable resource for breeders and paves the way for studying plant drought tolerance and C4 photosynthesis.

Introduction: Mirabegron is available for treatment of storage symptoms in overactive bladder, which may be improved by β3-adrenoceptor-induced bladder smooth muscle relaxation. In addition to storage symptoms, lower urinary tract symptoms in men include obstructive symptoms attributed to benign prostatic hyperplasia, caused by increased prostate smooth muscle tone and prostate enlargement. In contrast to the bladder and storage symptoms, effects of mirabegron on prostate smooth muscle contraction and obstructive symptoms are poorly understood. Evidence from non-human smooth muscle suggested antagonism of α1-adrenoceptors as an important off-target effect of mirabegron. As α1-adrenergic contraction is crucial in pathophysiology and medical treatment of obstructive symptoms, we here examined effects of mirabegron on contractions of human prostate tissues and on proliferation of prostate stromal cells.Methods: Contractions were induced in an organ bath. Effects of mirabegron on proliferation, viability, and cAMP levels in cultured stromal cells were examined by EdU assays, CCK-8 assays and enzyme-linked immunosorbent assay.Results: Mirabegron in concentrations of 5 and 10 μM, but not 1 µM inhibited electric field stimulation-induced contractions of human prostate tissues. Mirabegron in concentrations of 5 and 10 µM shifted concentration response curves for noradrenaline-, methoxamine- and phenylephrine-induced contractions to the right, including recovery of contractions at high concentrations of α1-adrenergic agonists, increased EC50 values, but unchanged Emax values. Rightshifts of noradrenaline concentration response curves and inhibition of EFS-induced contractions were resistant to L-748,337, l-NAME, and BPIPP. 1 µM mirabegron was without effect on α1-adrenergic contractions. Endothelin-1- and U46619-induced contractions were not affected or only inhibited to neglectable extent. Effects of mirabegron (0.5–10 µM) on proliferation and viability of stromal cells were neglectable or small, reaching maximum decreases of 8% in proliferation assays and 17% in viability assays. Mirabegron did not induce detectable increases of cAMP levels in cultured stromal cells.Conclusion: Mirabegron inhibits neurogenic and α1-adrenergic human prostate smooth muscle contractions. This inhibition may be based on antagonism of α1-adrenoceptors by mirabegron, and does not include activation of β3-adrenoceptors and requires concentrations ranging 50-100fold higher than plasma concentrations reported from normal dosing. Non-adrenergic contractions and proliferation of prostate stromal cells are not inhibited by mirabegron.

Abstract Picotamide is a thromboxane A2 (TXA2) receptor antagonist and TXA2 synthase inhibitor. In clinical studies, it has been considered as a platelet aggregation inhibitor and improved renal function. In vitro studies suggested inhibition of smooth muscle contraction by picotamide, which is poorly understood. Here, we examined effects of picotamide on contractions of renal interlobar and coronary porcine arteries, induced by different vasoconstrictors. Contractions were induced in an organ bath by agonists or electric field stimulation (EFS). Picotamide inhibited EFS‐induced contractions of interlobar arteries around 50% using concentrations of 100 and 300 µM. In interlobar arteries, concentration response curves for contractions induced by three different α1‐adrenoceptor agonists were shifted to the right by picotamide (2–10‐fold increases in EC50). In coronary arteries, α1‐adrenergic contractions were inhibited without right shift (approx. 50%). Contractions induced by two different cholinergic agonists in coronary arteries were inhibited by picotamide (≥50%) withouth right shift. Inhibition of serotonin‐induced contractions by picotamide showed features of a right shift, whereas contractions induced by the TXA2 analog U46619, angiotensin‐II, and endothelin‐1 were inhibited by picotamide in interlobar and coronary arteries without right shifts and to different degree. Picotamide inhibits a wide spectrum of vasoconstrictor‐induced contractions in porcine interlobar and coronary arteries. Inhibition of vasocontraction may contribute to beneficial effects of picotamide in the cardiovascular system and kidney.