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ABSTRACTReports on antimicrobial resistance (AMR) of Mycobacterium leprae, relationship with bacteriological index (BI), and transmission in China are limited. We investigated the emergence of AMR mutations, the relationship between BI and AMR in complete, moderate and lack of BI decline cases, and molecular epidemiological features of AMR cases by enrolling 290 leprosy cases from four endemic provinces. Seven (2.41%), one (0.34%), five (1.72%), one (0.34%), and one (0.34%) strains had single mutations in folP1, rpoC, gyrA, gyrB, and 23S rRNA, respectively. Double mutations in folP1 and gyrA, rpoB and gyrA, and gyrA and 23S rRNA were observed in one (0.34%) strain each. Mutated strains occurred in three out of 81 (95% CI−0.005-0.079, p = 0.083) cases with complete BI decline, in seven out of 103 (95% CI 0.018-0.117, p = 0.008) cases with moderate BI decline, and in four out of 34 (95% CI 0.003-0.231, p = 0.044) cases with lack of BI decline. Most of these mutated strains were geographically separated and diverged genotypically. AMR mutations may not be the main cause of the lack of BI decline. The low transmission of AMR strains at the county level indicates an ongoing transmission at close contact levels.

Due to the ubiquitous utilization of GPS devices, traffic cameras, and sensing devices, data are collected more readily in a smart city. If all the cabs of this city are used as data carriers, data generated by sensing devices will be collected to data centers efficiently and economically. Therefore, vehicular networks joint sensing devices provide more perspectives for a variety of vehicle-based applications. In this paper, three data centers deployment optimization schemes are proposed to optimize data centers' deployment, which can considerably enhance the performance of data collection and code dissemination tasks. Each proposed scheme uses different criteria to optimize the deployment of data centers: 1) locations of sensing devices; 2) locations that have high traffic flow; and 3) locations that have high valid flow, and these schemes are called Scheme 1, Scheme 2, and Scheme 3, respectively. In addition, another scheme that produces the deployment of data centers randomly is called Scheme 4, and it is used as a contrast in experiments. After performing extensive experiments and simulations based on two real-world datasets of cabs' GPS coordinates, the experiment results demonstrate that Scheme 3 noticeably outperformed remaining schemes under various circumstances. The results of February 3 were taken (Dataset 1) for instance. In comparison with Scheme 4, Scheme 3 enhances the total number of collected data packets by 57.71% when the number of the data center is ten, the speed of code dissemination and the coverage of cabs are ameliorated by 23.92% and 12.93%, respectively. Compared with Scheme 1, the total number of Scheme 3's collected packets is 65.00% higher than that of Scheme 1 when there are ten data centers deployed. The figures for Scheme 3's code dissemination and the coverage of sensing devices exceed that of Scheme 1 by 18.98% and 10.21%, respectively.

The recent developments in the areas of the Internet of Things (IoTs) have provided a rapid growth in the epoch of the novel information-centric collections (IC-IoTs). In the IC-IoTs, expanding the ranges of information collections and reducing the costs are important issues for the information required platform. In the previous scenarios, the information is collected in a random manner, which leads to lower coverages and higher costs. Thus, a “optimizing the coverage via the unmanned aerial vehicles (UAVs) with lower costs for information-centric Internet of Things” (OCLC-IoTs) approach is established, which targets to improve the coverage ratio and to reduce the costs of the information-required platform via the cooperation of the information collectors and the UAVs. First, to improve the coverage ratio, an intensive strategy is proposed to inspire the information collectors to bid for the tasks published by the platform and an improved rolling horizon strategy (IRHS) strategy is designed to plan the flying routes of the UAVs to reach more coverage ranges. Then, to reduce the costs factor, the IRHS strategy is designed to shorten the flying routes of the UAVs under the prerequisite of guaranteeing coverage ratio to achieve fewers costs. Finally, a comprehensive theoretical analysis and experiments are provided, which indicates the advancements of the OCLC-IoTs scheme. Compared with the previous studies, the OCLC-IoTs scheme can improve the coverage ratio of information by 21.42% approximately and can reduce the cost ratio by 13.335% to 34.32%.

Due to the huge number of objects/things connected to the Internet of Things (IoT) which are embedded with electronics, software, and sensors, the IoT creates many exciting applications such as smart grids, smart homes, and smart cities. In the IoT, the sensing and control of objects/things can be abstracted as a task, in which many sensing devices sense and collect data. However, the substantial case studies show that by simply connecting them without further collaboration among the objects/things will lead to the bad performance of the system. With the number of sensing devices connected to the IoT increases, the collaboration for completing the task is becoming more and more urgent. In this paper, a Collaborative Multi-Tasks Data Collection Scheme (CMDCS) is proposed to solve the problem by constructing a collaborative platform for task publisher and data reporter. The main contribution of CMDCS includes the following two aspects: (1) a Task Unit Bid-based task selection strategy is proposed to select the task which can bring higher profits to the system, in which the Task Unit Bid is the ratio of task bid to the amount of data which are needed to collect sensing tasks; and (2) a greedy contributed density-based data collector set selection method is proposed to reduce the cost of data collection so as to maximize system profit, in which the contribution density is used to measure the contribution of a single data collector to a specific sensing task. A large number of experiments have been carried out to verify the effectiveness of our proposed strategy. The experiments show that compared to the traditional data collection strategy Random Task selection with Coverage First Reporter selection, in which the Task Unit Bid and Contribution Density are not used, the profit of the system is improved by 92.08%.

Fast and energy efficient transmission is an important and challenging issue for wireless sensor networks (WSNs). Energy efficiency is also an important concern of green communication in WSNs. Optimizing the duty cycle (DC) of nodes and the size of forwarding node-set (SFNS) can effectively reduce the delay and improve energy efficiency. In this paper, we conclude that an optimal DC value can minimize the delay when the number of SFNS is constant. The reason why the delay is larger when the DC is smaller than the optimal value is that when the sender sends data, it needs to wait for the forwarding node to wake up which causes a large delay. When DC is larger than the optimal value, the delay is also larger because SFNS has more than one node in the awake state, which causes conflicts and increases the delay. For energy consumption, the sender with smaller DC has fewer collisions, so the energy consumption is less. Similarly, when DC is constant, SFNS also has an optimal value, which minimizes the delay. Based on the theoretical analysis, an Optimization Duty-Cycle and Size of Forwarding Node Set (ODC-SFNS) scheme is proposed to reduce delay and improve energy efficiency. The main optimization methods adopted are as follows: (a) For dense and high-DC networks, one hop delay and the number of hops needed for the packet to reach sink can be reduced by appropriately limiting the SFNS, thus the end-to-end delay can be effectively reduced. (b) For sparse and low-DC networks, increasing the DC in the far sink region can reduce delay while not reducing the network life, and improve energy efficiency. Compared with the traditional scheme, the ODC-SFNS scheme can reduce the end-to-end delay by 20.52%-79.96%, and it has dramatically increased energy efficiency. Moreover, its scope of application is broader than previous strategies.

In services-oriented computing networks, packets in the process of routing to a data center must wait for a sufficient amount of data before service aggregation to reduce the network transmission load. However, packets must be uploaded to the data center as soon as possible to reduce delay. With the exponential growth in the number of IoT connected devices, the wait time for packets is longer at routers due to massive amounts of data, which causes a large queuing delay. If this queuing time can be utilized for service aggregation in a service-oriented computing network, the network performance will be substantially improved. Therefore, a queuing delay utilization scheme for on-path service aggregation (SAQD) is proposed in this paper. This scheme has the following innovations: 1) SAQD fully utilizes the queuing delay of packets for service aggregation, which can effectively reduce the transmission volume and communication overhead. Based on the proposed service aggregation algorithm, packets are divided into forwarding packets and aggregating packets, and the service aggregation of aggregating packets is completed by utilizing the transmission time of forwarding packets to ensure that the transmission volume and communication overhead are effectively reduced without additional latency. 2) SAQD can effectively alleviate the traffic pressure of the data center and balance the workload of routers. By the service aggregation and intranet cache of routers, some requests for the data center can be handled by routers, which reduces the traffic pressure of the data center, especially in the peak period. Compared with conventional schemes, the experimental results demonstrate that SAQD reduces the workload of the data center by 55.8%-66.26% and provides users with a better quality of experience by reducing the request response delay by 31.33%~51.41%.

The Internet of Things (IoT) is an important part of the new generation of information technology. It utilizes many sensor nodes to collect data and monitor the environment and can be applied in various fields. However, because the energy of sensor nodes is limited and the batteries cannot be replaced, the lifetimes of the sensor nodes are limited by the energy of their batteries. Only a reasonable method for saving energy can reduce the energy loss of the nodes in the communication process. Many studies have found that batteries have the property of battery-friendliness; that is, if they continue working, their energy drops rapidly. However, if they rest after working for a period of time, the batteries' energy can be partially restored. In this paper, an effective relay selection scheme for prolonging the lifetimes of nodes is designed based on the battery-friendly nature of the battery. In the proposed battery-friendly relay selection (BFRS) scheme, the relay node is selected based on the weighted synthesis value of the recovered energy, its distance to the sink and the residual energy. A forwarding node that has recovered more energy and is closer to the sink is more likely to be selected as the relay node because of its larger weight. Hence, the BFRS-based routing scheme can improve the lifetime by recovering more energy. Through extensive experiments, we demonstrate that our BFRS scheme outperforms previously proposed schemes. In a network with 500 nodes, compared with the shortest routing algorithm, the network lifetime is increased by 51.26%, and the amount of transferred data is increased by 42.93%.

This paper pays close attention to the adaptive neural network tracking control. Aiming at a class of uncertain nonlinear systems with completely unknown output disturbance and unknown time delay, a corresponding robust control method is proposed based on the backstepping design technology. Neural network approximation is introduced as a very effective estimation technique for modeling uncertain partitions in the design process of virtual controller. The suitable Lyapunov–Krasovskii function is constructed, and by using the organic combination of Young’s inequality, unknown time delays are compensated. Nussbaum function is used to handle unknown virtual control directions. A practical robust control method is proposed to deal with the controller singularity problems. A priori knowledge is not required for this method. In this method, all signals achieve semi-global uniform ultimate boundedness, and it is demonstrated that the tracking error eventually converges the region around the origin. The simulation results verify this method’s feasibility and effectiveness.

Polarization light has been used as a key navigation cue by many animals under a stable celestial polarization pattern. Inspired by animals' unrivaled navigation skill, a bionic polarization sensor is designed previously to obtain the angle of polarization and degree of polarization. However, the accuracy and stability of the sensor are restricted by multi-source errors. In order to improve the accuracy of the sensor, in this paper, the multi-source errors are analyzed and modeled. A coarse calibration is presented to reduce the effect of inconsistency and interference. In addition, the extended Kalman filter and the unscented Kalman filter are designed to estimate the multi-source error or interference and compensate for the bionic polarization sensor. Finally, simulation and indoor experiments are conducted to validate the effectiveness of the proposed calibration method.

Fast and energy efficient data collection is the most important function of wireless sensor networks (WSNs) which governs the performance of WSNs. Time division multiple access (TDMA) is an effective data collection strategy in which node only schedules the active slot to save energy when transmitting data. However, many previous studies are designed for static traffic pattern such that each node to generate one data packet in a data collection cycle. Moreover, all nodes in the network use the same transmission radius r, so that the network data collection has a larger delay, a lower lifetime, and energy utilization rate. In view of the shortcomings of previous research, this paper proposes a reducing delay and maximizing lifetime (RDML) data collection strategy for WSNs with dynamic traffic patterns. The main innovation point of our work is the data transmission radius is no longer unified as r, while some nodes with energy surplus use a data transmission radius of mr(m > 1). The following network performance can be achieved by adopting the RDML scheme. First, because the nodes in the near sink mr radius area can send data directly to sink, the amount of data carried by hotspots nodes in the original strategy is greatly reduced, and the lifetime is improved. Second, since some nodes can go mr distance to the sink in data transmission, thus accelerating the data routing and reducing the time needed for data collection. Finally, since the remaining energy of nodes is fully utilized to increase the radius of data transmission, the energy utilization rate can be effectively improved. Through the theoretical analysis and experimental results, the RDML scheme can reduce the maximum delay of data collection by 22.32% and improve lifetime as well as the energy utilization rate by 0.86%-84.40%, and 23.33%-88.00%, respectively, compared with previous strategies.

The technology of software-defined devices has great prospect in updating the programs of the sensing devices to enable the devices to adapt to the new environments and applications. However, to effectively spread the code to each node in the software-defined-based wireless sensor networks (WSNs) is still a challenging task. In this paper, a proportion to duty cycle length-based broadcast (PDLB) scheme is proposed to disseminate code in duty cycle-based WSNs in a fast and energy-efficient style. In PDLB scheme, the sink first initiates a code broadcast. Then, the nodes that have received code start counting and calculate the priority of broadcasting based on an improved counter-based priority broadcasting approach proposed in this paper. Next, the nodes with the highest priority select k slots to broadcast according to the length of duty cycle so that the code can be spread from the sink to the network periphery. Finally, the nodes that have not obtained the code wait for a period of timeout to broadcast to actively send code request; after receiving code request, the node that obtained the code initiates a code broadcast to cause the code requester to obtain the code. The PDLB scheme has been validated by comprehensive experiments that show the following regularities. The smaller the count threshold value Ch, the larger the number of slots selected for broadcasting that can guarantee a certain coverage ratio, while the code dissemination speed slows down at the same time. The longer the duty cycle is, the more the broadcast time is required, and the larger the transmission delay is. For each slot added in a working cycle, the number of broadcasts is increased by 1.54%-33.33% and the transmission delay is augmented by 2.27%-70.04%. The higher the node density is, the shorter the code spread speed is. As the network density increases, the transmission delay is reduced by 0.83%-65.87%. When the number of broadcasting slots is half of the total number of slots in a work cycle, the energy consumption reaches the lowest value.

High-voltage direct current (HVDC) transmission is playing an increasingly important role in modern power systems, and the resulted power/voltage stability issue has raised widespread concern. This paper presents an on-line power/voltage stability index (PVSI) for multi-in-feed HVDC (MIDC) systems. Different from the existing indices which are developed mainly for off-line and static analysis, the proposed PVSI can be applied in real time. Effects of system changes on stability assessment such as change of system states and control strategies are considered. Thus, helpful guidance can be provided for on-line HVDC stability and controls. The PVSI is originally deduced for single-infeed HVDC systems in an “AC way” by analyzing the power and voltage stability of both pure AC systems and HVDC systems. Moreover, its on-line application in practical MIDC systems is realized by building an equivalent single-infeed model, and utilizing nowadays measurement and communication infrastructures such as wide-area measurement system (WAMS). The effectiveness of the PVSI is verified through simulations in real-time digital simulator (RTDS).

Objective To evaluate the prevalence of depression and quality of life and their correlation in non-dialysis patients with chronic renal failure and analyze the factors affecting the occurrence of depression in these patients. Methods This study was conducted among 356 non-dialysis patients with chronic renal failure (including both inpatients and outpatients) from 4 general hospitals in Chongqing during the period from May, 2017 to March, 2018. Beck Depression Inventory-Ⅱ (BDI-Ⅱ) was used to assess the patient's depression, and the quality of life the patients was assessed using Quality of Life Instrument for Chronic Disease-Chronic Renal Failure (QLICD-CRF2.0). Results The incidence of depression was 45.22% in the 356 patients with chronic renal failure without dialysis. The patients with depression had significantly lower quality of life scores (including the physiological function, psychological function, social function and total scores), but had significantly higher scores in the specific modules of response symptoms than those without depression (P < 0.05). Binary logistic regression analysis of depression and quality of life showed that occupation (OR=1.753, 95%CI: 1.352-2.273), hospitalization frequency (OR=1.221, 95%CI: 1.007-1.480), specific modules (OR=1.034, 95%CI: 1.011-1.058), psychological function (OR=0.922, 95%CI: 0.902-0.942), education level (OR=0.597, 95%CI: 0.394-0.906), and annual income of the family (OR=0.514, 95%CI: 0.346-0.765) were all independent risk factors for the occurrence of depression in these patients. Conclusion The incidence of depression is high in non-dialysis patients with chronic renal failure. The patients with depression have lower quality of life scores than those without depression. Occupation, hospitalization frequency, specific modules, psychological function, education level and annual income of the family may affect the quality of life among the non-dialysis patients.

The pretreatment serum albumin/globulin ratio (AGR) has been used as a prognostic biomarker for various cancer types. However, the prognostic value of the AGR for prostate cancer, especially for metastatic prostate cancer (mPCa) after maximal androgen blockade (MAB), remains unclear. The aim of this study was to evaluate the prognostic value of the pretreatment serum AGR for mPCa treated with MAB. This retrospective study included 214 mPCa patients receiving MAB from October 2007 to March 2017. The correlation of the AGR with survival was estimated using Kaplan–Meier analysis and Cox proportional hazards models. The cutoff value of the AGR was 1.45 according to the receiver operating characteristic curve. Kaplan–Meier analysis demonstrated that patients with a low AGR (

The performance of ski jumping is underpinned by multi-disciplinary principles, in which the aerodynamics of the ski dominates the flying distance and affects the biomechanics of the athletes’ ankle during the flight period. Conventional research on this topic was supported by wind tunnel experiments. Here, the aerodynamics of a full-scale ski jumping ski was calculated via Computational Fluid Dynamics (CFD) methods and good agreement with experimental data was achieved. The impacts of the angle of attack, yaw angle, and roll angle on the aerodynamic performance are explained. The inclusion of yaw angle can enhance the lift generation, which originates from the formation of a tilted multi-vortex system and the induced low-pressure footprints on the upper surface of the ski. Our results thus establish a database for the aerodynamic forces and moments of the ski and the associations between our findings and the skills in ankle control are discussed.

We demonstrate the generation of a space-variant vector beam with catenary-shaped polarization states based on the polarization interferometry. With a spatial light modulator and a common path interferometric configuration, two orthogonally circularly polarized beams with different phase modulation overlap each other, yielding the vector beams. In addition, the polarization states of this vector beam are scalable to the arbitrary spatial distribution because of its great flexibility and universal applicability. It is expected that this vector beam may have many potential and intriguing applications in the micro/nano material processing, liquid crystal elements fabrication and optical micro-manipulation, and so on.

It is very important to calculate the interference of high voltage direct current (HVDC) grounding current with pipelines accurately and take proper protective measures to ensure energy transmission safety. There is still a lack of systematic research into related prediction methods that consider the nonlinear polarization on the interface between the soil and pipelines. In this paper, a methodology is proposed for calculating the coupling voltage and current on buried pipelines induced by grounding currents that accounts for nonlinear polarization based on the method of moments (MoM) and the finite element method (FEM). The validity of the proposed mathematical model is verified by a scale experiment. The interference distribution characteristics under different parameters are analyzed using the proposed method. The results show that the relationship between the maximum leakage current density and the electrode grounding current satisfy the linear function. The corrosion area becomes more concentrated as the grounding current increases. The corrosion area range increases substantially as the distance increases, whereas the influence degree decreases substantially. Both the maximum leakage current density and corrosion risk area are positively correlated with the soil resistivity.

Calotropis gigantea is often found in mining areas with heavy metal pollution. However, little is known about the physiological and molecular response mechanism of C. gigantea to Cd stress. In the present study, Cd tolerance characteristic of C. gigantea and the potential mechanisms were explored. Seed germination test results showed that C. gigantea had a certain Cd tolerance capacity. Biochemical and transcriptomic analysis indicated that the roots and leaves of C. gigantea had different responses to early Cd stress. A total of 176 and 1618 DEGs were identified in the roots and leaves of C. gigantea treated with Cd compared to the control samples, respectively. Results indicated that oxidative stress was mainly initiated in the roots of C. gigantea, whereas the leaves activated several Cd detoxification processes to cope with Cd, including the upregulation of genes involved in Cd transport (i.e., absorption, efflux, or compartmentalization), cell wall remodeling, antioxidant system, and chelation. This study provides preliminary information to understand how C. gigantea respond to Cd stress, which is useful for evaluating the potential of C. gigantea in the remediation of Cd-contaminated soils.

Engineering hybrid perovskites at the molecular level to solve the stability problem remains a challenge. Here Grätzel et al. design a multifunctional molecular modulator that interacts with the perovskite via modes elucidated by solid state NMR spectroscopy and show high efficiency and operational stability.

Caffeoylquinic acids, coumarins and dicaffeoyl derivatives are considered to be three kinds of the most abundant bioactive components in Sarcandra glabra, an anti-inflammatory herb mainly found in Southern Asia. The combined anti-inflammatory effect of three typical constituents C + R + I (chlorogenic acid + rosmarinic acid + isofraxidin) from this plant has been investigated. The result implies that targeting the MAPK-NF-κB pathway would be one of the major mechanisms involved, using LPS stimulated RAW 264.7 cells as in vitro model and LPS-induced acute lung injury in mice as in vivo model. C + R + I can significantly suppress the levels of nitric oxide (NO), pro-inflammatory cytokines, and inhibit iNOS and COX-2 expression in LPS-treated RAW264.7 macrophage cells. Western blot analysis showed that C + R + I suppressed phosphorylation of NF-κB and MAPK, including phosphorylation of p65-NF-κB, IKB, ERK, JNK and P38. Besides, C + R + I suppressed MPO protein expression, but promoted SOD and HO-1 expression, and the related targets for C, R, and I were also predicted by molecular docking. This indicated that C + R + I could alleviate oxidative stress induced by LPS, which were further verified in the in vivo model of mice with acute lung injury through the measurement of corresponding inflammatory mediators and the analysis of immunehistochemistry.

Tumor-associated macrophages (TAMs) affect cancer progression and therapy. Ovarian carcinoma often metastasizes to the peritoneal cavity. Here, we found 2 peritoneal macrophage subsets in mice bearing ID8 ovarian cancer based on T cell immunoglobulin and mucin domain containing 4 (Tim-4) expression. Tim-4+ TAMs were embryonically originated and locally sustained while Tim-4– TAMs were replenished from circulating monocytes. Tim-4+ TAMs, but not Tim-4– TAMs, promoted tumor growth in vivo. Relative to Tim-4– TAMs, Tim-4+ TAMs manifested high oxidative phosphorylation and adapted mitophagy to alleviate oxidative stress. High levels of arginase-1 in Tim-4+ TAMs contributed to potent mitophagy activities via weakened mTORC1 activation due to low arginine resultant from arginase-1–mediated metabolism. Furthermore, genetic deficiency of autophagy element FAK family-interacting protein of 200 kDa resulted in Tim-4+ TAM loss via ROS-mediated apoptosis and elevated T cell immunity and ID8 tumor inhibition in vivo. Moreover, human ovarian cancer–associated macrophages positive for complement receptor of the immunoglobulin superfamily (CRIg) were transcriptionally, metabolically, and functionally similar to murine Tim-4+ TAMs. Thus, targeting CRIg+ (Tim-4+) TAMs may potentially treat patients with ovarian cancer with peritoneal metastasis.

The long-term stability of perovskite solar cells (PSCs) remains an issue impeding their commercialization. Generally, polycrystalline perovskite thin films have many defects on the grain boundaries, which affect the optoelectronic performance and stability of the devices under moisture, heat, illumination, and the presence of an electric field condition. The O-donor Lewis base is often employed to regulate the performance of PSCs such as carbonyl and carboxyl compounds. Herein, we have developed a concept of radical molecular modulation using the O-donor group for high-performance perovskite photovoltaic devices. The judiciously designed radical modulators 2,2,6,6-tetramethyl-1-piperidinyloxy (TEMPO), which located at the perovskite grain boundary through interaction with the perovskite surface sites, effectively passivated the surface defects while templating the formation of large grain crystal and high-quality perovskite thin films. Accordingly, the optimized TEMPO-modulated PSCs achieved a power conversion efficiency of 20.73% with superior stability. This work makes an important contribution for exploring the effect of radical in perovskites to improve the performance of PSCs and other optoelectronic devices.

Motivation: At present, a number of correlation analysis methods between SNPs and ROIs have been devised to explore the pathogenic mechanism of Alzheimer's disease. However, some of the deficiencies inherent in these methods, including lack of statistical efficacy and biological meaning. This study aims at addressing issues: insufficient correlation by previous methods (relative high regression error) and the lack of biological meaning in association analysis.Results: In this paper, a novel three-stage SNPs and ROIs correlation analysis framework is proposed. Firstly, clustering algorithm is applied to remove the potential linkage unbalanced structure of two SNPs. Then, the group sparse model is used to introduce prior information such as gene structure and linkage unbalanced structure to select feature SNPs. After the above steps, each SNP has a weight vector corresponding to each ROI, and the importance of SNPs can be judged according to the weights in the feature vector, and then the feature SNPs can be selected. Finally, for the selected feature SNPS, a support vector machine regression model is used to implement the prediction of the ROIs phenotype values. The experimental results under multiple performance measures show that the proposed method has better accuracy than other methods.

Cancer of unknown primary site (CUPS) is a type of metastatic tumor for which the sites of tumor origin cannot be determined. Precise diagnosis of the tissue origin for metastatic CUPS is crucial for developing treatment schemes to improve patient prognosis. Recently, there have been many studies using various cancer biomarkers to predict the tissue-of-origin (TOO) of CUPS. However, only a very few of them use copy number alteration (CNA) to trance TOO. In this paper, a two-step computational framework called CNA_origin is introduced to predict the tissue-of-origin of a tumor from its gene CNA levels. CNA_origin set up an intellectual deep-learning network mainly composed of an autoencoder and a convolution neural network (CNN). Based on real datasets released from the public database, CNA_origin had an overall accuracy of 83.81% on 10-fold cross-validation and 79% on independent datasets for predicting tumor origin, which improved the accuracy by 7.75 and 9.72% compared with the method published in a previous paper. Our results suggested that the autoencoder model can extract key characteristics of CNA and that the CNN classifier model developed in this study can predict the origin of tumors robustly and effectively. CNA_origin was written in Python and can be downloaded from https://github.com/YingLianghnu/CNA_origin.

Scene classification is one of the fundamental techniques shared by many basic remote sensing tasks with a wide range of applications. As the demands of catering with situations under high variance in the data urgent conditions are rising, a research topic called few-shot scene classification is receiving more interest with a focus on building classification model from few training samples. Currently, methods using the meta-learning principle or graphical models are achieving state-of-art performances. However, there are still significant gaps in between the few-shot methods and the traditionally trained ones, as there are implicit data isolations in standard meta-learning procedure and less-flexibility in the static graph neural network modeling technique, which largely limit the data-to-knowledge transition efficiency. To address these issues, this paper proposed an novel few-shot scene classification algorithm based on a different meta-learning principle called continual meta-learning, which enhances the inter-task correlation by fusing more historical prior knowledge from a sequence of tasks within sections of meta-training or meta-testing periods. Moreover, as to increase the discriminative power between classes, a graph transformer is introduced to produce the structural attention, which can optimize the distribution of sample features in the embedded space and promotes the overall classification capability of the model. The advantages of our proposed algorithm are verified by comparing with nine state-of-art meta-learning based on few-shot scene classification on three popular datasets, where a minimum of a 9% increase in accuracy can be observed. Furthermore, the efficiency of the newly added modular modifications have also be verified by comparing to the continual meta-learning baseline.

Introduction: Alzheimer’s disease (AD) is the most common progressive neurodegenerative disorder in the elderly, which will eventually lead to dementia without an effective precaution and treatment. As a typical complex disease, the mechanism of AD’s occurrence and development still lacks sufficient understanding. Research design and methods: In this study, we aim to directly analyze the relationship between DNA variants and phenotypes based on the whole genome sequencing data. Firstly, to enhance the biological meanings of our study, we annotate the deleterious variants and mapped them to nearest protein coding genes. Then, to eliminate the redundant features and reduce the burden of downstream analysis, a multi-objective evaluation strategy based on entropy theory is applied for ranking all candidate genes. Finally, we use multi-classifier XGBoost for classifying unbalanced data composed with 46 AD samples, 483 mild cognitive impairment (MCI) samples and 279 cognitive normal (CN) samples. Results: The experimental results on real whole genome sequencing data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) show that our method not only has satisfactory classification performance but also finds significance correlation between AD and RIN3, a known susceptibility gene of AD. In addition, pathway enrichment analysis was carried out using the top 20 feature genes, and three pathways were confirmed to be significantly related to the formation of AD. Conclusions: From the experimental results, we demonstrated that the efficacy of our proposed method has practical significance.

Bladder cancer is one of the most malignant tumors closely associated with macrophage immune dysfunction. The Chinese medicine polyporus has shown excellent efficacy in treating bladder cancer, with minimal side effects. However, its material basis and mechanism of action remain unclear. A new water-soluble polysaccharide (HPP) with strong immunomodulatory activity was isolated from the fungus Polyporus umbellatus (Pers.) Fries. HPP had an average molecular weight of 6.88 kDa and was composed mainly of an

Abstract Optical metasurfaces enable novel ways to locally manipulate light's amplitude, phase, and polarization, underpinning a newly viable technology for applications, such as high‐density optical storage, holography, and displays. Here, a high‐security‐level platform enabled by centimeter‐scale plasmonic metasurfaces with full‐color, high‐purity, and enhanced‐information‐capacity properties is proposed. Multiple types of independent information can be embedded into a single metamark using full parameters of light, including amplitude, phase, and polarization. Under incoherent white light, the metamark appears as a polarization‐ and angle‐encoded full‐color image with flexibly controlled hue, saturation, and brightness, while switching to multiwavelength holograms under coherent laser illumination. More importantly, for actual applications, the extremely shallow functional layer makes such centimeter‐scale plasmonic metamarks suitable for cost‐effective mass production processes. Considering these superior performances of the presented multifunctional plasmonic metasurfaces, this work may find wide applications in anticounterfeiting, information security, high‐density optical storage, and so forth.

The Balloon Analogue Risk Task (BART) provides a reliable and ecologically valid model for the assessment of individual risk-taking propensity and is frequently used in neuroimaging and developmental research. Although the test-retest reliability of risk-taking behavior during the BART is well established, the reliability of brain activation patterns in response to risk-taking during the BART remains elusive. In this study, we used functional magnetic resonance imaging (fMRI) and evaluated the test-retest reliability of brain responses in 34 healthy adults during a modified BART by calculating the intraclass correlation coefficients (ICC) and Dice’s similarity coefficients (DSC). Analyses revealed that risk-induced brain activation patterns showed good test-retest reliability (median ICC ​= ​0.62) and moderate to high spatial consistency, while brain activation patterns associated with win or loss outcomes only had poor to fair reliability (median ICC ​= ​0.33 for win and 0.42 for loss). These findings have important implications for future utility of the BART in fMRI to examine brain responses to risk-taking and decision-making.

Abstract Phosphoinositide 3‐kinases, delta (PI3Kδ) and gamma (PI3Kγ) are enriched in immune cells and regulate the development and function of innate and adaptive immunity. Dual PI3Kδγ inhibitors are considered high value targets for their potential to treat a variety of immune‐mediated diseases, but their discovery has been challenging. Here we describe the preclinical pharmacology of HM5023507, an orally active dual inhibitor of δγ isoforms in immune signaling. HM5023507 inhibited PI3Kδ and PI3Kγ isoforms with greater than 100‐fold selectivity against PI3Kα and PI3Kβ in recombinant enzymatic assays and in primary human immune cells with an exquisite selectivity against other targets. HM5023507 attenuated the PI3Kδ/γ signaling in human basophils (IC50: 42/340 nmol/L; selectivity ratio ~1:8). HM5023507 attenuated the activation and function of human B and T cells, Th17 differentiation of CD4 T cells in the blood of healthy donors and rheumatoid arthritis patients, and cytokine and IgG production in human T and B cell cocultures, in vitro. Orally dosed HM5023507 attenuated PI3K δ/γ‐mediated immune signaling in the rat in a dose‐related manner. In addition, HM5023507 inhibited semiestablished collagen‐induced arthritic inflammation in the rats (ED50 of 0.25mg/kg, p.o. BID or 0.5 mg/kg, QD, AUC: 1422 ng/mL*h), improved histopathology‐ and micro‐computed tomography (µCT)‐based indices of joint damage, bone destruction, and attenuated the levels of anti‐collagen antibody, with an overall anti‐inflammatory profile matching that of a TNFα neutralizing antibody. The PI3K δγ inhibitory profile of HM5023507 and its selectivity make it a useful tool to further delineate immunobiology of dual PI3K δγ targeting.

The existing motor frame is made of metal materials. In this paper, a carbon fiber reinforced plastic (CFRP) motor frame, which uses material damping to reduce vibration amplitude, which is proposed to design and manufacture low-vibration motors. The damp ratio of the CFRP motor frame is calculated by the damp prediction model based on strain energy, which is verified by the combination of the finite element method and experiment. The vibration characteristics of the CFRP frame motor are studied experimentally and compared with that of the metal frame motor. The results show that the CFRP frame motor has good vibration reduction. The amplitude reduction is up to 5 times higher than that of the metal motor frame, which proves that the damping vibration reduction of the CFRP motor frame has a good application value.

In this paper, we consider an equivalent form of the Nosé–Hoover oscillator, x′=y,y′=−x−yz, and z′=y2−a, where a is a positive real parameter. Under a series of transformations, it is transformed into a 2-dimensional reversible system about action-angle variables. By applying a version of twist theorem established by Liu and Song in 2004 for reversible mappings, we find infinitely many invariant tori whenever a is sufficiently small, which eventually turns out that the solutions starting on the invariant tori are quasiperiodic. The discussion about quasiperiodic solutions of such 3-dimensional system is relatively new.

Abstract More than 100 counties, mainly in southwest China, report incidence rates of leprosy >1/100,000. The current study analysed the epidemiology of leprosy in southwest China to improve our understanding of the transmission pattern and improve control programs. 207 counties were selected in southwest China. Leprosy patients and their household contacts were recruited. The data from the medical interview and the serological antileprosy antibody of the leprosy patients were analysed. A total of 2,353 new cases of leprosy were interviewed. The distribution of leprosy patients was partly associated with local natural and economic conditions, especially several pocket areas. A total of 53 from 6643 household contacts developed leprosy, and the incidence rate of leprosy in the household contacts was 364/100,000 person-years. We found that NDO-BSA attained higher positive rates than MMP-II and LID-1 regardless of clinical types, disability and infection time in leprosy patients. By means of combination of antigens, 88.4% patients of multibacillary leprosy were detected, in contrast to 59.9% in paucibacillary leprosy. Household contacts should be given close attention for the early diagnosis, disruption of disease transmission and precise control. Applications of serology for multi-antigens were recommended for effective coverage and monitoring in leprosy control.

Abstract Background The poly ADP ribose polymerase (PARP) inhibitor olaparib has been approved for treating prostate cancer (PCa) with BRCA mutations, and veliparib, another PARP inhibitor, is being tested in clinical trials. However, veliparib only showed a moderate anticancer effect, and combination therapy is required for PCa patients. Histone deacetylase (HDAC) inhibitors have been tested to improve the anticancer efficacy of PARP inhibitors for PCa cells, but the exact mechanisms are still elusive. Methods Several types of PCa cells and prostate epithelial cell line RWPE-1 were treated with veliparib or SAHA alone or in combination. Cell viability or clonogenicity was tested with violet crystal assay; cell apoptosis was detected with Annexin V-FITC/PI staining and flow cytometry, and the cleaved PARP was tested with western blot; DNA damage was evaluated by staining the cells with γH2AX antibody, and the DNA damage foci were observed with a fluorescent microscopy, and the level of γH2AX was tested with western blot; the protein levels of UHRF1 and BRCA1 were measured with western blot or cell immunofluorescent staining, and the interaction of UHRF1 and BRCA1 proteins was detected with co-immunoprecipitation when cells were treated with drugs. The antitumor effect of combinational therapy was validated in DU145 xenograft models. Results PCa cells showed different sensitivity to veliparib or SAHA. Co-administration of both drugs synergistically decreased cell viability and clonogenicity, and synergistically induced cell apoptosis and DNA damage, while had no detectable toxicity to normal prostate epithelial cells. Mechanistically, veliparib or SAHA alone reduced BRCA1 or UHRF1 protein levels, co-treatment with veliparib and SAHA synergistically reduced BRCA1 protein levels by targeting the UHRF1/BRCA1 protein complex, the depletion of UHRF1 resulted in the degradation of BRCA1 protein, while the elevation of UHRF1 impaired co-treatment-reduced BRCA1 protein levels. Co-administration of both drugs synergistically decreased the growth of xenografts. Conclusions Our studies revealed that the synergistic lethality of HDAC and PARP inhibitors resulted from promoting DNA damage and inhibiting HR DNA damage repair pathways, in particular targeting the UHRF1/BRCA1 protein complex. The synergistic lethality of veliparib and SAHA shows great potential for future PCa clinical trials.

Flow-injection mass spectrometry (FIMS) coupled with a chemometric method is proposed in this study to profile and distinguish between rhizomes of Smilax glabra (S. glabra) and Smilax china (S. china). The proposed method employed an electrospray-time-of-flight MS. The MS fingerprints were analyzed using principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) with the aid of SIMCA software. Findings showed that the two kinds of samples perfectly fell into their own classes. Further predictive study showed desirable predictability and the tested samples were successfully and reliably identified. The study demonstrated that the proposed method could serve as a powerful tool for distinguishing between S. glabra and S. china.

The capacity of plants to accumulate cadmium (Cd) is significant for phytoremediation of Cd-polluted soils. Turnips cultivated in China include species featuring high Cd accumulation and some of these plants act as Cd hyperaccumulator landraces. These plants can accumulate over 100 mg Cd kg−1 dry weight in leaves without injury. Hence, studies that explore mechanisms underlying Cd detoxification and transport in turnip plants are essential. In the present study, we compared physiological and biochemical changes in turnip leaves treated with two Cd concentrations to controls. We discovered that Cd stress significantly increased the enzymatic activities or compound contents in the antioxidant system, including members of the glutathione-ascorbic acid cycle, whereas oxidation of reactive oxygen species (ROS) remained stable. Cd treatments also increased the contents of phytochelatins as well as a number of amino acids. Based on these results, we conclude that turnips initiate a series of response processes to manage Cd treatment. First, the antioxidant system maintaining ROS homeostasis and osmotic adjustment is excited to maintain stability of cell osmotic potential. Cd is chelated into its stable form to reduce its toxicity. Cd is possibly transported to vacuoles or non-protoplasts for isolation. Amino acid synthesis may directly and indirectly play an important role in these processes. This study partly revealed physiological and biochemical mechanisms underlying turnip response to Cd stress and provides information on artificially increasing or decreasing Cd accumulation in turnips and other plants.

Broadband absorber in the terahertz region (0.1-10 THz) has attracted considerable attentions due to its important applications in detecting, imaging, and electromagnetic stealth. Recently, terahertz absorber with broadband features has been widely investigated, however, the achievement of ultrabroad bandwidth is still challenging due to the limitations of complex structural design and fabrication processes. In this paper, an ultrabroadband terahertz absorber covering the entire terahertz regime (0.1-10 THz) based on the heavily doped silicon has been designed and fabricated, which is composed of double-layer binary gratings filled with the SU-8 photoresist. Antireflection techniques (SU-8 layer) were utilized to further promote the performance of the terahertz absorber at high frequencies through matching the impedance between free space and doped-silicon substrate. The measured absorption exceeding 87% within the frequency range of 0.3-10 THz has verified the proposed approach in designing the ultrabroadband terahertz absorber. Furthermore, the designed absorber remains high performance in the case of wide-angle incidence even up to 60°. Benefiting from the simple structure, the absorber is easy to be fabricated by common optical lithography. We believe that the results of this paper could broaden the application areas of terahertz absorbers.

The emergence of the metasurface has spawned an ultrathin, compact, and planner way to generate the orbital angular momentum (OAM) beam array. Several types of OAM beam array generators based on the metasurface have been reported, however, most of them only performed at the certain wavelength for lack of the wavelength-dependent modulation, which restricted the flexibility and capacity of the generators. Here, we propose a single-layered metasurface to realize the generation of the wavelength-dependent three-dimensional (3-D) volumetric vortex beam array. The metasurface is composed by two different nanoantennas, which shows the distinct properties of wavelength selectivity and wavelength-dependent phase modulation. By employing such properties, 3-D volumetric vortex beams operating at different wavelengths can be multiplexed. Our design may facilitate the development of the optical multiplexing, and the wavelength-dependent control of the OAM light will improve the capacity and the security of the optical information.

Nickel smelting slag contains valuable metals including nickel and copper. Failure to recycle these metals wastes resources, and disposal of nickel slag in stockpiles results in environmental pollution. Nickel slag recycling is important, and metals can be recovered from slag by flotation. However, considering the complex forms in which valuable metals occur in nickel slag, high yields are difficult to achieve by direct flotation. In this study, nickel slag was modified by reduction and sulfurization to render it more amenable to metal recovery through flotation. The mechanism was assessed based on thermodynamics and elements’ phase distributions. Thermodynamic analyses indicated the feasibility of nickel slag modification by reduction–sulfurization smelting. The results of chemical phase analysis show that the forms in which valuable metals occur in nickel slag can be modified by reduction–sulfurization, and the proportion of metals existing in sulfide and free metal states in nickel slag can be increased. Compared with the direct flotation of raw slag, the recovery of nickel and copper from top-blowing slag increased by 23.03% and 14.63%, respectively. The recoveries of nickel and copper from settling slag increased by 49.68% and 43.65%, respectively.