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Yushan Liu,1,2 Gezhi Zheng,1,3 Jing Li,1,3 Nan Yang,1– 4 Juan Li,1,2 Zhengwen Liu,1– 4 Qunying Han,1– 4 Yingren Zhao,1– 4 Fenjing Du,1,3 Yingli He,1,* Taotao Yan1,* 1Department of Infectious Diseases, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China; 2Institution of Hepatology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China; 3Clinical Research Center for Infectious Diseases, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China; 4Shaanxi Clinical Research Center for Infectious Diseases, Xi’an, Shaanxi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yingli He; Taotao Yan, Department of Infectious Diseases, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277 Yanta Road(w), Xi’an, Shaanxi, People’s Republic of China, Tel +86 189-9123-2863 ; +86 186-9148-5175, Email heyingli2000@xjtu.edu.cn; yantaotao_sweet@163.comAbstract: Anthrax is caused by Bacillus anthracis. Humans are mainly infected through contact with the fur and meat of livestock. The cutaneous form is the most common form. The skin lesions of typical cutaneous anthrax are characterized by shallow ulcers with black crusts, surrounded by small blisters and nonpitting edema of nearby tissues. Metagenomic next-generation sequencing (mNGS) is a new pathogenic detection method which is rapid and unbiased. We reported the first case of cutaneous anthrax diagnosed by mNGS. Ultimately, the man received prompt antibiotic therapy and had a good prognosis. In conclusion, mNGS is proved to be a good method for etiological diagnosis, especially for rare infectious diseases.Keywords: cutaneous anthrax, metagenomic next-generation sequencing, mNGS, case report, etiology diagnosis

The slump, cube compressive strength and splitting tensile strength tests of 9 groups of hybrid fiber reinforced shale ceramisite concrete (HFSC) and 1 group of C30 reference concrete were conducted by orthogonal experimental method. The effects of shale ceramisite volume replacement, basalt fiber volume fraction and polypropylene fiber volume fraction on the mechanical properties of HFSC were investigated. The results show that the splitting tensile strength and tension-compression ratio of concrete can be significantly improved by adding fiber, which plays a positive hybrid effect. The maximum increase in the tensile strength of concrete by basalt fiber and polypropylene fiber is 57.33% and 58.19% respectively, while the influence of compressive strength was small. Shale ceramisite significantly reduces the compressive and tensile strength of concrete. When the replacement increases from 0% to 15%, the compressive strength of HFSC decreases by 19.98%, while the tensile strength has underwent an iterative process of increasing and decreasing due to the fiber reinforcement effect. All three factors reduced the slump of concrete mixture. The shale ceramisite and basalt fiber have significant influence, and polypropylene fiber has a greater impact. The influence mechanism of three factors on mechanical properties of HFSC was revealed.The prediction models of cube compressive strength and splitting tensile strength of HFSC were obtained, and the accuracy of model is high.

Global crises and regulatory developments require increased supply chain transparency and resilience. Companies do not only need to react to a dynamic environment but have to act proactively and implement measures to prevent production delays and reduce risks in the supply chains. However, information about supply chains, especially at the deeper levels, is often intransparent and incomplete, making it difficult to obtain precise predictions about prospective risks. By connecting different data sources, we model the supply network as a knowledge graph and achieve transparency up to tier-3 suppliers. To predict missing information in the graph, we apply state-of-the-art knowledge graph completion methods and attain a mean reciprocal rank of 0.4377 with the best model. Further, we apply graph analysis algorithms to identify critical entities in the supply network, supporting supply chain managers in automated risk identification., Comment: Accepted at the D2R2 workshop (ESWC 2023)

At present, most of the pitch control methods are based on PI controller, the pitch control system has poor disturbance resistance, and the research of variable parameter feedforward based on Light detection and ranging (LIDAR) and the Linear Active Disturbance Rejection controller (LADRC) composite control is rarely studied to reduce the blade root load, so this paper conceives a hybrid intelligent and adaptive pitch control approach to reduce a wind turbine generator speed fluctuation and its blade root load. Specifically, we combine the Radial Basis Neural Network and Finite Impulse Response filter (RBFNNFIR) based on LIDAR wind measurement. We then use a variable bandwidth of LADRC controller. Overall the approach enables and facilitates self-adaption and self-adjustment. We use Matlab s-function to call the multi-freedom mathematical wind turbine model based on FAST code, the composite intelligent control algorithm is established in Simulink. Initial results from the statistical analysis of the experiments under different turbulent wind conditions shows that the hybrid intelligent pitch control approach can reduce the generator speed fluctuation by about 40.8%, and the blade root max value of load moment by about 13.1%, compared with the baseline values of the traditional variable gain PI control algorithm.

With the real-time changes of wind speed and operating conditions, it is a challenge to fully tap the active power regulation ability and improve the control performance of automatic generation control (AGC) in a wind farm (WF). The essence of tapping the active power regulation ability is to realise the coordination and complementarity of each wind turbine's (WT's) dynamic adjustment performance (DAP). To address this, a novel data mining method is developed to derive the internal relations between WTs’ output power and pitch angle, impeller speed and pitch angle during the power adjustment process, and a unified mechanism model is established to describe DAP of WTs. Based on the discovered relationship between WTs’ DAP and its operating states, an active power distribution algorithm and a dynamic interval control method are proposed. Then, an active power dynamic interval control strategy that has been implemented using Java script in MyEclipse for WFs is further developed. The control strategy has been tested and applied in a 50 MW WF in northwest China. The preliminary results showed that the control strategy has improved the rapidity and accuracy of AGC in the WF.

BACKGROUNDMultisystem inflammatory syndrome in children (MIS-C) is a rare but potentially severe illness that follows exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Kawasaki disease (KD) shares several clinical features with MIS-C, which prompted the use of intravenous immunoglobulin (IVIG), a mainstay therapy for KD. Both diseases share a robust activation of the innate immune system, including the IL-1 signaling pathway, and IL-1 blockade has been used for the treatment of both MIS-C and KD. The mechanism of action of IVIG in these 2 diseases and the cellular source of IL-1β have not been defined.METHODSThe effects of IVIG on peripheral blood leukocyte populations from patients with MIS-C and KD were examined using flow cytometry and mass cytometry (CyTOF) and live-cell imaging.RESULTSCirculating neutrophils were highly activated in patients with KD and MIS-C and were a major source of IL-1β. Following IVIG treatment, activated IL-1β+ neutrophils were reduced in the circulation. In vitro, IVIG was a potent activator of neutrophil cell death via PI3K and NADPH oxidase, but independently of caspase activation.CONCLUSIONSActivated neutrophils expressing IL-1β can be targeted by IVIG, supporting its use in both KD and MIS-C to ameliorate inflammation.FUNDINGPatient Centered Outcomes Research Institute; NIH; American Asthma Foundation; American Heart Association; Novo Nordisk Foundation; NIGMS; American Academy of Allergy, Asthma and Immunology Foundation.

Biomedical knowledge graphs permit an integrative computational approach to reasoning about biological systems. The nature of biological data leads to a graph structure that differs from those typically encountered in benchmarking datasets. To understand the implications this may have on the performance of reasoning algorithms, we conduct an empirical study based on the real-world task of drug repurposing. We formulate this task as a link prediction problem where both compounds and diseases correspond to entities in a knowledge graph. To overcome apparent weaknesses of existing algorithms, we propose a new method, PoLo, that combines policy-guided walks based on reinforcement learning with logical rules. These rules are integrated into the algorithm by using a novel reward function. We apply our method to Hetionet, which integrates biomedical information from 29 prominent bioinformatics databases. Our experiments show that our approach outperforms several state-of-the-art methods for link prediction while providing interpretability., Accepted at ESWC 2021 (18th Extended Semantic Web Conference). arXiv admin note: text overlap with arXiv:2007.05292

A 3D layered Ni(HCO3)2/rGO nano-architecture was fabricated by coordination self-assembly for high performance storage of Li-ions with fast electrode kinetics and a super-long life., Rechargeable lithium-ion batteries (LIBs) have been the dominating technology for electric vehicles (EV) and grid storage in the current era, but they are still extensively demanded to further improve energy density, power density, and cycle life. Herein, a novel 3D layered nanoarchitecture network of Ni(HCO3)2/rGO composites with highly uniform Ni(HCO3)2 nanocubes (average diameter of 100 ± 20 nm) wrapped in rGO films is facilely fabricated by a one-step hydrothermal self-assembly process based on the electrostatic interaction and coordination principle. Benefiting from the synergistic effects, the Ni(HCO3)2/rGO electrode delivers an ultrahigh capacity (2450 mA h g–1 at 0.1 A g–1), ultrafast rate capability and ultralong cycling stability (1535 mA h g–1 for the 1000th cycle at 5 A g–1, 803 mA h g–1 for the 2000th cycle at 10 A g–1). The detailed electrochemical reaction mechanism investigated by in situ XRD further indicates that the 3D architecture of Ni(HCO3)2/rGO not only provides a good conductivity network and has a confinement effect on the rGO films, but also benefits from the reversible transfer from LiHCO3 to LixC2 (x = 0–2), further oxidation of nickel, and the formation of a stable/durable solid electrolyte interface (SEI) film (LiF and LiOH), which are responsible for the excellent storage performance of the Li-ions. This work could shed light on the design of high-capacity and low-cost anode materials for high energy storage in LIBs to meet the critical demands of EV and mobile information technology devices.

Efficient solar-thermal energy conversion and storage is significant to overcome current energy shortage problems. Monitoring solar-thermal energy storage process by an evident and convenient display is conducive to improving energy utilization. Herein, fluorescent thermochromic wood-based composite phase change materials (WPCMs) were constructed for visual solar-thermal energy conversion and storage. It was fabricated by encapsulating polyethylene glycol (PEG) and aggregation-induced emission carbon dots (AIE-CDs) showing blue dispersed emission and red aggregation-induced emission into delignified wood (DW). The DW well-preserved the distinctive anisotropic porous structure and prevented the leakage problem of PEG. The WPCMs possessed great solar-thermal conversion capacity benefitting from strong and broad solar light absorption behaviors of AIE-CDs. Additionally, WPCMs showed real-time and visual fluorescent thermochromic property, it exhibited red AIE, and the fluorescence (FL) decreased and shifted into the blue emission band under solar radiation. The solar-thermal energy conversion and storage led to solid–liquid transformation of WPCMs, which promoted AIE-CDs’ dispersion, thereby changing the FL. It also exhibited a high latent heat of fusion (160.8 J·g−1), favorable stability over 150 heating–cooling cycles, thermal stability below 210 °C and good shape stability. The WPCMs can be extended to applications in energy-saving buildings and optical lighting materials with visual thermal regulation capability.

Formaldehyde (FA) is a widespread indoor air pollutant, and its efficient detection is a major industrial challenge. The development of a building material with real-time and visual self-detection of FA gas is highly desirable for meeting both construction and human health demands. Herein, a luminescent transparent wood (LTW) as the building material was developed for dual-channel, real-time, and visual detection of FA gas. It was fabricated by encapsulating multicolor lignin-derived carbon dots (CDs) and poly(vinyl alcohol) (PVA) into a delignified wood framework. It exhibited 85% optical transmittance, tunable room-temperature phosphorescence (RTP), and ratiometric fluorescence (FL) emission. The tunable luminescence was attributed to different CD graphitization and surface functionalization. The color-responsive ratiometric FL and delayed RTP detections of FA were displayed over the range of 20-1500 μM (

The graph structure of biomedical data differs from those in typical knowledge graph benchmark tasks. A particular property of biomedical data is the presence of long-range dependencies, which can be captured by patterns described as logical rules. We propose a novel method that combines these rules with a neural multi-hop reasoning approach that uses reinforcement learning. We conduct an empirical study based on the real-world task of drug repurposing by formulating this task as a link prediction problem. We apply our method to the biomedical knowledge graph Hetionet and show that our approach outperforms several baseline methods., Accepted at the ICML 2020 Workshop Graph Representation Learning and Beyond (GRL+)

Due to the lack of effective strategies on the treatment of castration resistant prostate cancer (CRPC), we established a multifunctional nanoplatform (GNS@IR820/DTX-CD133) for the synergistic photothermal therapy (PTT)/photodynamic therapy (PDT)/chemotherapy (CT) under the monitoring of multimodal near-infrared (NIR) fluorescence/photoacoustic (PA) imaging. Benefiting from the guided effect of CD133 antibody, GNS@IR820/DTX-CD133 can targetedly deliver the loaded drug to the tumor tissues, which can further contribute to the combined therapeutic effect. Our experimental results prove that the bio-distribution of GNS@IR820/DTX-CD133 can be monitored with NIR fluorescence and PA imaging. In addition, the application of GNS@IR820/DTX-CD133 for in vitro and in vivo therapy achieves the excellent antitumor effects of the synergistic PTT/PDT/CT strategies under the NIR-light irradiation. Therefore, as a multifunctional nanoplatform integrating the PTT/PDT/CT strategies with tumor multimodal imaging or drug tracing, GNS@IR820/DTX-CD133 has the great potential for clinical applications in the antitumor therapy of CRPC.

Diagnosing diseases such as leukemia or anemia requires reliable counts of blood cells. Hematologists usually label and count microscopy images of blood cells manually. In many cases, however, cells in different maturity states are difficult to distinguish, and in combination with image noise and subjectivity, humans are prone to make labeling mistakes. This results in labels that are often not reproducible, which can directly affect the diagnoses. We introduce TIMELY, a probabilistic model that combines pseudotime inference methods with inhomogeneous hidden Markov trees, which addresses this challenge of label inconsistency. We show first on simulation data that TIMELY is able to identify and correct wrong labels with higher precision and recall than baseline methods for labeling correction. We then apply our method to two real-world datasets of blood cell data and show that TIMELY successfully finds inconsistent labels, thereby improving the quality of human-generated labels., Comment: Accepted at ECAI 2020 (24th European Conference on Artificial Intelligence)

Tor is the most widely used anonymity network, currently serving millions of users each day. However, there is no access control in place for all these users, leaving the network vulnerable to botnet abuse and attacks. For example, criminals frequently use exit relays as stepping stones for attacks, causing service providers to serve CAPTCHAs to exit relay IP addresses or blacklisting them altogether, which leads to severe usability issues for legitimate Tor users. To address this problem, we propose TorPolice, the first privacy-preserving access control framework for Tor. TorPolice enables abuse-plagued service providers such as Yelp to enforce access rules to police and throttle malicious requests coming from Tor while still providing service to legitimate Tor users. Further, TorPolice equips Tor with global access control for relays, enhancing Tor's resilience to botnet abuse. We show that TorPolice preserves the privacy of Tor users, implement a prototype of TorPolice, and perform extensive evaluations to validate our design goals., Comment: Conference Version is Published in IEEE ICNP 2017

Destination governance has emerged as a very important issue in local and regional development in Sweden. The article investigates the pattern in which local tourism governance operates based on a single case study of the ski resort of Hemavan and Tärnaby, and evaluates the effectiveness of this governance pattern on local tourism development according to a six-measurement criteria scale. A semi-structured interview approach with open-ended questions was used in this paper. Ten respondents were interviewed in Hemavan and Tärnaby, and they are representatives from both private and public sector. In the concluding section, the results are developed into an evaluation and analysis concerning how the characteristics of the local DMO matter in terms of its governance effectiveness. The results indicate that overall the DMO is an effective form by organizing various actors with mutual resource dependencies. However, the uneven balance of power between Tärnaby and Hemavan, as well as between various network participants, is hard to reconcile, which may strongly influence their governance effectiveness. Managing Heritage Assets as Tourism Products - The case of the World Heritage of the Falun Copper Mine

Experiments were conducted on the leaching of gold from greenstone by chloride solution under the temperature of 200-550°C and the pressure of 60 MPa. During part of the experiments, the oxygen fugacity was controlled. The results show that the leaching rate of gold is related to temperature, composition of the solution, pH and oxygen fugacity. In the experiment with oxidative acidic solution, the leaching rate was up to 50% or more. It is known that the leaching of gold is restricted by the reaction in which the gold is dissolved from the rock to form gold chloride complex. Therefore, the authors hold that the acidic chloride solution derived from granite magma has caused the remobilization-migration of gold from greenstone and its enrichment into ore.

Experiments for oxygen isotope exchange between ferberite and water were carried out and the following equation on oxygen isotope fractionation between ferberite and water against temperature was obtained: 10001nα FeWO4 −H2O = 1.04 × 106T −2 − 2.5 Combining this equation with the equation of Clayton et al. (1972) on oxygen isotope fractionation between quartz and water, an equation on oxygen isotope fractionation between quartz and ferberite was obtained: 10001nαSiO2 − FeWO4 = 2.34 × 106T−2 − 0.4 The Bigeleison-Mayer function method was used to calculate the oxygen isotope fractionation between quartz and ferberite. The theoretical curve obtained agrees with the experimental calibration results quite well in the temperature range of study. The above calibrated equation has been used in 5 world famous tungsten deposits to determine their temperatures of formation. The results show that the temperature range for an idividual deposit determined by this geothermometer agrees with those obtained from fluid inclusion determination and other isotope geothermometers.

The quasi-Z source (qZS) cascaded multilevel inverter (CMI) (qZS-CMI) presents attractive advantages in application to photovoltaic (PV) power system. Each PV panel connects to an H-bridge qZS inverter (qZSI) to form a power generation module. The distributed maximum power point tracking and all modules' dc-link peak voltage balance can be achieved. However, it is the same with the conventional CMI that the second-harmonic (2ω) voltage and current ripples exist in each qZSI module. It is crucial for a qZS-CMI to design the reasonable qZS network parameters to limit the ripples within a desired range. This paper proposes an analytic model to accurately calculate the 2ω voltage and current ripples of each qZSI module. A qZS impedance design method based on the built model is proposed to limit the 2ω ripples of dc-link voltage and inductor current. Simulated and experimental results through using the designed 1.5-kW prototype validate the proposed analytic model and the design method. Furthermore, this paper analyzes all of the operating states for a qZSI module and calculates the power loss. The measured efficiency from the prototype verifies the theoretical calculation, and the qZS-CMI-based grid-tie PV power system is tested in practical. © 1982-2012 IEEE.

This paper introduced the conflict conception and the theory of inventive problem solving-TRIZ. It analyzed 39 standard parameters of describing technical conflict, 40 inventive principles, techno-conflict and solving matrix and substance-field analytic theory. The research offers a problem-solving process to solve the problem of stocks of supply chain inventory, and uses Substance-Field model and the 76 standard solutions, quotes for the production bottlenecks existed in inventory management of W manufacturing enterprises, proposes the feasible solutions, improves the production performance, developed the application domain of the problem solving using TIRZ tool, enriched the method of the enterprise management.