Diagnosing congenital heart disease (CHD) remains challenging because of its complex morphology. Representing the intricate structures of CHD on conventional two-dimensional flat screens is difficult owing to wide variations in the pathologies. Technological advancements, such as three-dimensional printed heart models (3DPHM) and virtual reality (VR), could potentially address the limitations of viewing complex structures using conventional methods. This study aimed to investigate the usefulness and clinical value of four visualization modalities across three different cases of CHD, including ventricular septal defect, double outlet right ventricle, and tetralogy of fallot. Seventeen cardiac specialists were invited to participate in this study, which was aimed at assessing the usefulness and clinical value of four visualization modalities, namely, DICOM images, 3DPHM, VR, and 3D PDF. Of these modalities, 76.4% of the specialists ranked VR as the best for understanding the spatial associations among cardiac structures and for presurgical planning. Meanwhile, 94.1% ranked 3DPHM as the best modality for communicating with patients and their families. Of the various visualization modalities, VR was the best tool for assessing anatomical locations and vessels, comprehending the spatial relationships among cardiac structures, and for presurgical planning. The 3DPHM models were the best tool for medical education as well as communication. In summary, both 3DPHM and VR have their own advantages and outperform the other two modalities, i.e., DICOM images and 3D PDF, in terms of visualizing and managing CHD.

To address the issue of traditional static evaluation models being unable to comprehensively analyse the performance of ultra-supercritical coal-fired units under varying loads, we propose a dynamic comprehensive evaluation model based on the improved Criteria Importance Through Inter-criteria Correlation (CRITIC) method and Entropy Weight Method (EWM). The comprehensive performance evaluation index system of ultra-supercritical coal fired units is constructed by examining the boiler performance, turbine performance, plant power performance, environmental performance, and flexible performance of coal powered units. The CRITIC and EWM methods are used to calculate the weights of the indicators, which are then combined with the static evaluation results. Using a dynamic comprehensive evaluation model, we analysed ultra-supercritical coal-fired units, taking into account time weight. This allowed us to obtain the comprehensive dynamic real-time evaluation value of the units under different loads. The research indicates that the dynamic comprehensive evaluation model, which uses an improved CRITIC and EWM, has significant advantages in improving evaluation accuracy, weight-balanced distribution, and generality. Provides more accurate, reasonable, and reliable evaluation results for practical decision making.

Environmental responsibility and economic benefits have promoted the development of closed-loop supply chain (CLSC), and shortages and channels are considered to be two important issues in CLSC. This paper explores ordering and channel decisions in CLSC with new and differentiated remanufactured products, and considers the price and sales effort-dependent demands, as well as the proportion of emergency orders determined by emergency order costs and backorder losses, and establishes an integrated and decentralized CLSC game models. We introduce a stochastic sales effort, which affects two types of products. Numerical results show that sales effort and the order quantity of new and remanufactured products exhibit concave and convex functions, respectively. Wherein, the upper limit of sales effort has a greater impact on supply chain decisions. High sales efforts can serve as a means of coordinating dispersed supply chains. Moreover, in different cases, decisions of integrated channel are better than those of decentralized channel. Finally, whether the supply chain adopts an emergency order strategy depends on the relative cost of emergency orders and out of stock costs. According to the research in this article, some management insights are also provided.

As part of the Earth Climate Observatory space mission concept for the direct observation from space of the Earth Energy Imbalance, we propose an advanced camera suite for the high resolution observation of the Total Outgoing Radiation of the Earth. For the observation of the Reflected Solar Radiation, we propose the use of two multispectral cameras covering the range from 400 to 950 nm, with a nadir resolution of 1.7 km, combined with a high resolution RGB camera, with a nadir resolution of 0.57 km. For the observation of the Outgoing Longwave Radiation, we propose the use of 6 microbolometer cameras, with each a spectral bandwidth of 1 μm in the range from 8 to 14 μm, and with a nadir resolution of 2.2 km.

Objective: To explore the application effect of Atropine injection combined with nursing intervention on the interventional treatment of PATENTS with ST-segment elevation myocardial infarction. Methods: A total of 60 patients with ST-segment elevation myocardial infarction treated in our hospital from January 2022 to January 2023 were selected as the research objects. According to different nursing methods, they were divided into conventional group (n = 30) and systematic group (n = 30), both groups were treated with percutaneous coronary intervention (PCI). The conventional group received routine nursing before and after operation. On the basis of routine nursing, systematic nursing cooperation was given in the system group. The time of opening infarct vessels, the incidence of total adverse reactions during interventional treatment, mortality, success rate of treatment, improvement of cardiac function and length of hospital stay were compared between the two groups. Results: The time of opening infarct vessel in system group was significantly better than that in routine group (P < 0.05). The total adverse reaction rate in system group was significantly lower than that in routine group (P < 0.05); The mortality of routine group was significantly higher than that of system group (P < 0.05). The success rate of system group was significantly higher than that of routine group (P < 0.05); The number of patients with improved cardiac function and length of hospital stay in system group were significantly better than those in routine group (P < 0.05). Conclusion: Good intraoperative cooperation and nursing is an important guarantee for patients with ST-segment elevation myocardial infarction, which can effectively reduce the occurrence of adverse reactions during interventional treatment, improve the success rate of treatment, and reduce the death of patients during interventional treatment.

In recent years, since the propagation channel characteristics have been effectively used for applications such as motion sensing, position detection, etc. A great deal of attention is attracted to channel sounding methods easy to utilize using low-cost devices. This paper presents a device-free indoor location estimation method using spatio-temporal features of radio propagation channels using the 2.4-GHz band 3-by-3 MIMO channel sounder developed using commodity wireless LANs. The measurement results demonstrated a reasonable performance of the proposed method with small number of antennas.

The outbreak of COVID-19 has brought unprecedented risks and challenges to everyone in the world. Myasthenia gravis is an autoimmune disease of the nervous system. Infection can worsen it and cause severe symptoms such as myasthenia crisis and respiratory failure. At present, the pandemic of COVID-19 may promote the aggravation of patients with MG. This article focuses on the respiratory management of MG patients during the epidemic of COVID-19.

Radiotherapy is the primary treatment modality for non-metastatic nasopharyngeal carcinoma (NPC) across all TNM-stages. Locoregional control rates have been impressive even from the 2D-radiotherapy (RT) era, except when the ability to deliver optimal dose coverage to the tumor is compromised. However, short- and long-term complications following head and neck RT are potentially debilitating, and thus, there had been much research investigating technological advances in RT delivery over the past decades, with the primary goal of limiting normal tissue damage. On this note, with a plateau in gains of therapeutic ratio by modern RT techniques, future advances have to be focused on individualization of RT, both in terms of dose prescription and delineation of target volumes. In this review, we analyzed the guidelines and evidence related to contouring methods, and dose prescription for early and locoregionally-advanced (LA-) NPC. Next, with the preference for induction chemotherapy (IC) in patients with LA-NPC, we assessed the evidence concerning radiotherapy adaptations guided by IC response, as well as functional imaging and contour changes during treatment. Finally, we discussed on RT individualization that is guided by EBV DNA assessment, and its importance in the era of combinatorial immune checkpoint blockade therapy with RT.

Shear deflection effects are traditionally neglected in most structural system identification methods. Unfortunately, this assumption might lead to significant errors in some structures, like deep beams. Although some inverse analysis methods based on the stiffness matrix method including shear deformation effects have been presented in the literature, none of these methods is able to deal with actual rotations in their formulations. Recently, the observability techniques, one of the first methods for the inverse analysis of structures included the shear effects into the system of equations. In this approach, the effects of shear rotation are neglected. When actual rotations on site are used to estimate the mechanical properties in the inverse analysis, it can result in serious errors in the observed properties. This characteristic might be especially problematic in structures such as deep beams where only rotations can be measured. To solve this problem and increase the observability techniques' applicability, this paper proposes a new approach to include shear rotations into the inverse analysis by observability techniques. This modification is based on the introduction of a new iterative process. To illustrate the applicability and potential of the proposed method, the inverse analysis of several examples of growing complexity is presented.

Sleep postures monitoring systems in the hospital aim at transforming sensing signals into quantitative data to characterize the sleep behaviors of the patient. However, a home-care sleep posture monitoring system needs to be user friendly. In this paper, we present iSleePost - a user-friendly home-care intelligent sleep posture monitoring system. We address the labor-intensive labeling issue of traditional machine learning approaches in the training phase. Our proposed mobile health (mHealth) system leverages the communications and computation capabilities of mobile phones for provisioning a continuous sleep posture monitoring service. Our experiments show that iSleePost can achieve 90 percent accuracy in recognizing sleep postures. More importantly, iSleePost demonstrates that an easily-wear wrist sensor can accurately quantify sleep postures.

As e-commerce services and Internet technology have rapidly developed in recent years, many services and applications integrating these technologies can now be completed online. These commercial activities include online auctions, online ticketing and online payments. The client shops from the store online, andthe store delivers the goods to the client. The goods can be divided into digital products without entities, as well as actual entities. If it is a physical product, the store will deliver the package to the client through itslogistics. However, there have been many cases of switched goods purchased by clients in recent years. Earlier, some scholars proposed a security mechanism with a subliminal channel for E-cash and digital content. Only the sender and the receiver would know that the secret information was hidden in the signature. So the privacy of this subliminal message couldbe ensured. We apply this concept to the logistics environment to design secure logistics architecture with subliminal messages. The client can check the subliminal message of the received package, and know whether the package has been switched by malicious people. In addition, the proposed scheme also applies sensor technology;the client can check the GPS location, the temperature and humidity at any time during the delivery process. So intelligent logisticswouldthereby be achieved. This paper proposes an intelligent and secure package sensoring logistics system based on a subliminal channel. The proposed architecture uses the related mechanisms tosolve the problems of a logistics system, including how to achieve mutual authentication, data integrity, anti-switch package, package location and status tracing, resisting replay attacks, forward and backward secrecy, and non-repudiation issues.

This study aims to determine the protective effects of red seaweed Eucheuma cottonii (EC) ethanol extract on acute colitis disease in mice. Male BALB/c mice used for acute colitis disease model by induced 2.5% (w/v) of dextran sulfate sodium (DSS) for 7 days for all groups, except control group. The DSS-induced mice then treated by three different doses of EC extracts (0.35, 0.70, 1.75 g/kg body weight), curcumin (as a positive control, 0.10 g/kg), and a group was orally only by water. In 8^th day, the mice sacrificed and collected the blood, then measured the body weight, colon weight, and colon length. Disease activity index (DAI), pro-inflammatory such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6, as well as IL-10 as anti-inflammatory were measured. The results showed that after treatment for 7 days, EC extract protected the weight loss and decreased the colon weight per length ratio. In addition, EC extract also decreased the pro-inflammatory cytokines expression in serum and increased the IL-10. Moreover, EC extract protected the colonic tissue damage. According to this results, the EC ethanol extract might be can used for the treatment of colitis disease.

Landing is one of the most dangerous tasks in all the operations on the aircraft carrier, and the landing safety is very important to the pilot and the flight deck operation. The problem of landing path selection is studied in this paper as there several candidates corresponding to different situations. A fuzzy path selection strategy is proposed to solve the problem considering the fuzziness of environmental information and human judgment, and the goal is to provide the pilot with more reasonable decision. The strategy is based on Fuzzy Multi-attribute Group Decision Making (FMAGDM), which has been widely used in industry. Firstly, the background of the path selection problem is given. Then the essential elements of the problem are abstracted to build the conceptual model. A group decision-making method is applied to denote the preference of each decision maker for each alternative route, and the optimal landing path under the current environment is determined taking into account the knowledge and the weight of both decision makers. Experimental studies under different setups, i.e., different environments, are carried out. The results demonstrate that the proposed path selection strategy is validated in different environments, and the optimal landing paths corresponding to different environments can be determined.

The surface velocity of the Amery Ice Shelf (AIS) is vital to assessing its stability and mass balance. Previous studies have shown that the AIS basin has a stable multi-year average surface velocity. However, spatiotemporal variations in the surface velocity of the AIS and the underlying physical mechanism remain poorly understood. This study combined offset tracking and DInSAR methods to extract the monthly average surface velocity of the AIS and obtained the inter-annual surface velocity from the ITS_LIVE product. An uneven spatial distribution in inter-annual variation of the surface velocity was observed between 2000–2022, although the magnitude of variation was small at less than 20.5 m/yr. The increase and decrease in surface velocity on the eastern and western-central sides of the AIS, respectively, could be attributed to the change in the thickness of the AIS. There was clear seasonal variation in monthly average surface velocity at the eastern side of the AIS between 2017–2021, which could be attributed to variations in the area and thickness of fast-ice and also to variations in ocean temperature. This study suggested that changes in fast-ice and ocean temperature are the main factors driving spatiotemporal variation in the surface velocity of the AIS.

Tocilizumab against interleukin-6 receptor (IL-6R) has been demonstrated to inhibit the progression of diverse cancers in vitro and in vivo. Nonetheless, evidence regarding the anti-tumor effects of Tocilizumab on human colorectal carcinoma (CRC) corresponding to IL-6R expression levels re-mains scarce. To investigate the influence of IL-6R expression, SW480 and HT-29 cells inoculated subcutaneously into NU/NU mice were used as our human CRC xenograft models with anti-IL-6R antibody (Tocilizumab) therapy. IL-6R expression levels, the histology of CRC growth/ invasiveness and tumor growth-related signaling pathway were estimated by H&E and immunohistochemical staining. SW480 tumor cells with higher IL-6R expression levels exerted better responsiveness in Tocilizumab therapy than the treated HT-29 group. Likewise, therapeutic effects of Tocilizumab on the proliferative ability with mitotic index and Ki-67 expressions, the invasiveness with MMP-9 proteinase expressions, ERK 1/2 and STAT3 signaling transduction in SW480 treatment group were superior to HT-29 treatment group. In light of our results, IL-6R is the key indicator for the efficacy of Tocilizumab treatment in CRC xenografts. From the perspective of precision medicine, tumor response to anti-IL-6R antibody therapy could be predicted on the basis of IL-6R expression levels. In this manner, Tocilizumab may serve as a targeted and promising anti-CRC therapy.

Deformation monitoring is beneficial to ensure the service safety of long tunnel. An three-direction (vertical, transverse and axial) deformation estimation method using long-gauge fiber Bragg grating (FBG) sensing technology is proposed and applied to a long tunnel by integrating mechanical analysis and field monitoring during the service state. The key issues of the proposed method for identifying the three-direction deformation are discussed, such as establishing the separation model of coupling strain on cross section, deriving the theory of deformation identification in three directions, and determining the sensor layout of the long tunnel. A major advantage of the proposed method is that the three-direction deformation of the tunnel can be monitored in real time using distributed long-gauge strain sensors. The numerical analysis and field test results verify the feasibility of the proposed method.

The Homotopy Analysis Method (HAM) is a useful method to derive analytical approximate solutions of black holes in modified gravity theories. In this paper, we study the Einstein-Weyl gravity coupled with Maxwell field, and obtain analytical approximation solutions for charged black holes by using the HAM. It is found that the analytical approximate solutions are sufficiently accurate in the entire spacetime outside the black hole's event horizon, and also consistent with numerical ones for charged black holes in the Einstein-Maxwell-Weyl gravity.

Background and Aims: Of all primary liver tumors, primary hepatic angiosarcoma (PHA) is a rare and aggressive malignant vascular tumor. The standard therapeutic care for hepatic angiosarcoma remains unclear. This study compared the survival outcomes of aggressive treatment (resection and liver transplant) and nonaggressive treatment (chemotherapy, transarterial chemoembolization [TACE], and conservative treatments) for patients with PHA and analyzed the prognostic factors influencing survival. Materials and Methods: Data of patients diagnosed as having PHA at our facility were retrospectively reviewed. The primary outcome was survival time. The secondary outcome was calculated baseline characteristics. Results: We included a total of 19 patients, who were divided into 2 treatment groups: aggressive (8 patients had undergone resection or transplants) and nonaggressive (11 patients had undergone TACE, chemotherapy, or conservative treatment). The mean survival time was 233.1 ± 189.7 days in the aggressive treatment group and 146.5 ± 115.8 days in the nonaggressive treatment group. A Kaplan-Meier plot revealed no significant difference in survival time between the 2 treatment groups (P = .3256). Conclusions: The survival time of patients receiving aggressive treatment was longer than that of those receiving nonaggressive treatment. The long term survival time in some selective cases of aggressive treatment will be achieved. Thought a difference was not significant between the groups. Because the number of patients was limited, more cases are required to confirm these findings.

In this study, a composite flame retardant was created by combining fish scale (FS), fishery waste, and ammonium polyphosphate (APP), a commercially available flame retardant. The composite flame retardant was added to epoxy resin (EP) to form an EP/APP/FS composite that prevents burns and is environmentally friendly. The use of FS conforms to the concept of circular economy and lowers costs by reducing the consumption of APP. Thermogravimetric analysis (TGA), integral procedural decomposition temperature (IPDT), pyrolysis kinetics, limiting oxygen index (LOI), the Underwriters Laboratories 94 (UL94) flammability test, scanning election microscopy, Raman spectroscopy, and energy-dispersive X-ray spectroscopy were used to determine the thermal properties, flame retardant properties, flame retardant mechanism, char morphology, and composition of the composites. The TGA results indicated that the addition of 40% flame retardant raised the char residue from 16.45 wt% (pure EP) to 36.07 wt%, IPDT from 685.6 °C (pure EP) to 1143.1°C, LOI from 21% (pure EP) to 30%, and UL94 classification from fail (pure EP) to V-0. These results suggest an increase in char residue, which indicates better protection of the polymer matrix material. The improvements in IPDT, LOI, and UL94 classification, which indicate greater thermal stability, lower flammability (from flammable to fireproof), and higher flammability rating (from fail to V-0), respectively, suggest that the composite material has favorable thermal properties and is less inflammable.

The anti-inflammatory effect of ginsenoside Rh2 (GRh2) is one of the most important ginsenosides. The purpose of this study is to identify the anti-inflammatory and antioxidant effects of GRh2 after LPS challenge lung injury animal model. GRh2 reduced LPS-induced NO, TNF-α, IL-1, IL-4, IL-6 and IL-10 productions in lung tissues. GRh2 treatment decreased the histological alterations in the lung tissues and BALF protein content and total cells number also diminished in LPS-induced lung injury mice. Moreover, GRh2 blocked iNOS, COX-2, the phosphorylation of IκB-α, ERK, JNK, p38, Raf-1 and MEK protein expression which is corresponded to the growth of HO-1, Nrf-2, catalase, SOD and GPx expressions in LPS-induce lung injury. An experimental study has suggested that GRh2 has provided with anti-inflammatory effects in vivo, and its potential therapeutic efficacy in major anterior segment lung diseases.

The present study examined and compared the effects of high- and low-molecular weight (MW) chitosan, a nutraceutical, on intestinal and liver lipid metabolism in rats fed with high-fat diet. Both high- and low-MW chitosan decreased liver weight, elongated small intestine, improved the dysregulation of blood lipids and liver fat accumulation, and increased fecal lipid excretion in high-fat diet-fed rats. Supplementation of both high- and low-MW chitosan significantly inhibited the decreased phosphorylated AMP-activated protein kinase (AMPK)α and peroxisome proliferator-activated receptor (PPAR)α protein expressions and the increased lipogenesis/cholesterogenesis-associated protein expressions (sterol regulatory element binding protein (SREBP)1c, SREBP2, and PPARγ) and the decreased apolipoprotein (Apo)E and microsomal triglyceride transfer protein (MTTP) protein expressions in the livers of high-fat diet-fed rats. Both high and low-MW chitosan supplementation could also suppress the increased MTTP protein expression and the decreased angiopoietin-like protein (Angptl)4 protein expression in the intestines of high-fat diet-fed rats. Comparison between high and low-MW chitosan, high-MW chitosan has a higher efficiency than low-MW chitosan on the inhibition of intestinal lipid absorption and the increase of hepatic fatty acid oxidation, which can improve liver lipid biosynthesis and accumulation.

This paper proposes a single-stage asymmetrical half-bridge fly-back (AHBF) converter with resonant mode using dual-mode control. The presented converter has an integrated boost converter and asymmetrical half-bridge fly-back converter and operates in resonant mode. The boost-cell always operates in discontinuous conduction mode (DCM) to achieve high power factor. The presented converter operates simultaneously using a variable-frequency-controller (VFC) and pulse-width-modulation (PWM) controller. Unlike the conventional single-stage design, the intermediate bus voltage of this controller can be regulated depending on the main power switch duty ratio. The asymmetrical half-bridge fly-back converter utilizes a variable switching frequency controller to achieve the output voltage regulation. The asymmetrical half-bridge fly-back converter can achieve zero-voltage-switching (ZVS) operation and significantly reduce the switching losses. Detailed analysis and design of this single-stage asymmetrical half-bridge fly-back converter with resonant mode is described. A wide AC input voltage ranging from 90 to 264 Vrms and output 19 V/ 120 W prototype converter was built to verify the theoretical analysis and performance of the presented converter.

Poly(2,6-dimethyl phenyl oxide) (PPO) is known for its low dissipation factor. To achieve insulating materials with low dissipation factor for high-frequency communication application, a monomer-type benzoxazine (P-APPO) and a main-chain-type benzoxazine (BPA-APPO) were prepared from an amine end-capped oligo (2,6-dimethyl phenylene oxide) (APPO). The APPO was prepared from a nucleophilic substitution of a phenol-end capped oligo (2,6-dimethyl phenylene oxide) (a commercial product, SA 90) with fluoronitrobenzene, and followed by catalytic hydrogenation. After self-curing or curing with a dicyclopentadiene-phenol epoxy (HP 7200), thermosets with high-T_g and low-dissipation factor can be achieved. Furthermore, the resulting epoxy thermosets show better thermal and dielectric properties than those of epoxy thermoset cured from its precursor SA90, demonstrating it is a successful modification in simultaneously enhancing the thermal and dielectric properties.

Objective: To evaluate the effect of propofol combined with psychological intervention on pain and emotional evaluation in painless colonoscopic colonic polypectomy patients undergoing endoscopic mucosal resection (EMR).Methods: A total of 80 patients who underwent painless colonoscopic colonic polypectomy with EMR treatment between June 2020 and June 2022 were selected in order of admission and divided into two groups. The control group received conventional analgesia, while the observation group received propofol combined with psychological intervention. Pain visual analog scale (VAS) and emotional scale were used to evaluate pain and emotions in both groups of patients. Adverse reactions and clinical efficacy were also compared between the two groups.Results: The two groups of patients were generally comparable with no significant differences (P > 0.05). The VAS score in the observation group was significantly lower than that in the control group (P < 0.05), and the emotional scale score was also improved compared to the control group (P < 0.05). The number of patients with adverse reactions in the observation group was less than that in the control group. The clinical effective rate in the observation group was significantly higher than that in the control group (P < 0.05).Conclusion: Propofol combined with psychological intervention can effectively alleviate pain and improve emotional status in painless colonoscopic colonic polypectomy patients undergoing EMR treatment, thereby increasing the comfort and success rate of the surgery. The number of patients with adverse reactions in the observation group was less than that in the control group, and the clinical effective rate in the observation group was significantly higher than that in the control group (P < 0.05).

In swarm-robotics foraging, the purpose of task allocation is to adjust the number of active foraging robots dynamically based on the task demands and changing environment. It is a difficult challenge to generate self-organized foraging behavior in which each robot can adapt to environmental changes. To complete the foraging task efficiently, this paper presents a novel self-organized task allocation strategy known as the dynamic response threshold model (DRTM). To adjust the behavior of the active foraging robots, the proposed DRTM newly introduces the traffic flow density, which can be used to evaluate the robot density. First, the traffic flow density and the amount of obstacle avoidance are used to adjust the threshold which determines the tendency of a robot to respond to a stimulus in the environment. Then, each individual robot uses the threshold and external stimulus to calculate the foraging probability that determines whether or not to go foraging. Simulation and physical experiments are carried out to evaluate the performance of the proposed method. The experimental results show that the DRTM is superior to and more efficient than the adaptive response threshold model (ARTM) in swarm foraging.

Reconstruction of acoustic relaxation absorption curve is a powerful approach to ultrasonic gas sensing, but requires known of a series ultrasonic absorption at various frequencies around effective relaxation frequency. Ultrasonic transducer is a most widely deployed sensor for ultrasonic wave propagation measurement and works only at a fixed frequency or specific environment like water, so a large number of ultrasonic transducers operating at various frequencies are required to recover an acoustic absorption curve with a relative large bandwidth, which cannot suit for large-scale practical applications. This paper proposes a wideband ultrasonic sensor using a distributed Bragg reflector (DBR) fiber laser for gas concentration detection through acoustic relaxation absorption curve reconstruction. With a relative wide and flat frequency response, the DBR fiber laser sensor measures and restores a full acoustic relaxation absorption spectrum of CO2 using a decompression gas chamber between 0.1 and 1 atm to accommodate the main molecular relaxation processes, and interrogates with a non-equilibrium Mach-Zehnder (M-Z) interferometer to gain a sound pressure sensitivity of -45.4 dB. The measurement error of the acoustic relaxation absorption spectrum is less than 1.32%.

As a new distributed machine learning (ML) approach, federated learning (FL) shows the great potential to preserve data privacy by enabling distributed data owners to collaboratively build a global model without sharing their raw data. However, the heterogeneity in terms of data distribution and hardware configurations make it hard to select participants from the thousands of nodes. In this paper, we propose a multi-objective node selection approach to improve time-to-accuracy performance while resisting malicious nodes. We firstly design a deep reinforcement learning assisted FL framework. Then the problem of multi-objective node selection under this framework is formulated as a Markov decision process (MDP), which aims to reduce the training time and improve model accuracy simultaneously. Finally, a deep Q-netwok (DQN) based algorithm is proposed to efficiently solve the optimal set of participants for each iteration. Simulation results show that the proposed method not only significantly improves the accuracy and training speed of FL, but has stronger robustness to resist malicious nodes.

Currently, an interactive environmental planning analysis system platform based on " Three Lines One Permit " (TLOP) is being developed to support environmental planning, construction project approval, and the application of TLOP outcome data in Guangzhou. The main objective is to provide governments, businesses and the public with environmental planning analysis tools to determine the site of construction projects. The platform is using the system architecture of the browser and server. Its core functions are interactive environmental planning analysis tool for construction project and the results display tool supporting map viewing. It provides users with a large number of detailed geospatial data and TLOP results data access and environmental planning analysis functions. This article describes the system architecture and implementation of the system platform and has a case study illustrating the system functionality. At present, the platform has been deployed and trial-operated. The content of the analysis framework is constantly expanding. This promotes the matching of environmental planning and analysis with local conditions. This will implement the application of TLOP and improve the efficiency of project construction and the level of ecological environment planning and management.

Ultrasound based haptic feedback is a potential technology for human-computer interaction (HCI) with the advantages of low cost, low power consumption and controlled force. In this paper, the phase optimization for multipoint haptic feedback based on ultrasound array is investigated and the corresponding experimental verification is provided. A mathematical model of acoustic pressure is established for the ultrasound array and then a phase optimization model for an ultrasound transducer is constructed. We propose a pseudo-inverse (PINV) algorithm to accurately determine the phase contribution of each transducer in the ultrasound array. By controlling the phase difference of the ultrasound array, the multipoint focusing forces are formed leading to various shapes such as geometries and letters that can be visualized. Because the unconstrained PINV solution results in unequal amplitudes for each transducer, a weighted amplitude iterative optimization is deployed to further optimize the phase solution, by which the uniform amplitude distributions of each transducer are obtained. For the purpose of experimental verifications, a platform of ultrasound haptic feedback consisting of a Field Programmable Gate Array (FPGA), an electrical circuit and an ultrasound transducer array is prototyped. The haptic performances of single point, multiple points and dynamic trajectory were verified by controlling the ultrasound force exerted on the liquid surface. The experimental results demonstrate that the proposed phase optimization model and theoretical results are effective and feasible, and the acoustic pressure distribution is consistent with the simulation results.

This paper presents an optimized feature-centered reflection symmetry axis detection and localization framework for object perception. The proposed framework is formed to obtain an improved reflection symmetry axis based on the salient symmetry feature. It starts with a refined Multi-scale Saliency Symmetry Model (MSSM), which is realized by applying isotropic symmetry operator on salient points in scale-space rather than all pixels. In each scale, salient points are initially extracted as local extremal from an image, and they are further refined by a multi-scale implementation for generating salient symmetry feature maps. A Symmetric Transformation Matrix is then computed using the optimal feature matching pairs, which can be explicitly used as an abstract representation of the constraint regions of symmetry objects in an image to optimize the performance of the potential symmetry axis detection. The framework has been investigated experimentally both on the classical dataset from a symmetry detection challenge and the latest dataset. It has shown that the framework can get a better or comparative result and also can be further adapted into terminated human--computer equipment for reflection symmetry object perception and tracking.

SARS-CoV-2, the causal agent of the globally spreading COVID-19, is capable of infecting variable animals besides human being. We evaluated the potential susceptibility of important livestock, pets and aquatic mammals by performing a multi-species sequence analysis of ACE2 based on the reported affected and unaffected animals. We identified a triple amino acid pattern of ACE2, at position 30, 31 and 34, that might be associated with SARS-CoV-2 infection and H34 might be an indicator of the susceptibility to COVID-19.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

Identifying group movement patterns of crowds and understanding group behaviors is valuable for urban planners, especially when the groups are special such as tourist groups. In this paper, we present a framework to discover tourist groups and investigate the tourist behaviors using mobile phone call detail records (CDRs). Unlike GPS data, CDRs are relatively poor in spatial resolution with low sampling rates, which makes it a big challenge to identify group members from thousands of tourists. Moreover, since touristic trips are not on a regular basis, no historical data of the specific group can be used to reduce the uncertainty of trajectories. To address such challenges, we propose a method called group movement pattern mining based on similarity (GMPMS) to discover tourist groups. To avoid large amounts of trajectory similarity measurements, snapshots of the trajectories are firstly generated to extract candidate groups containing co-occurring tourists. Then, considering that different groups may follow the same itineraries, additional traveling behavioral features are defined to identify the group members. Finally, with Hainan province as an example, we provide a number of interesting insights of travel behaviors of group tours as well as individual tours, which will be helpful for tourism planning and management.

Health care in Canada is managed by provinces/territories. We investigated regional differences in survival among Canadians diagnosed with central nervous system (CNS) tumours. We identified 50,670 patients diagnosed with a first-ever primary CNS tumour between 2008 and 2017 with follow-up until December 31, 2017. We selected the four highest incidence histologies and used proportional hazards regression to estimate hazard ratios (HRs) for five regions (British Columbia, Prairie provinces, Ontario, Atlantic provinces and the Territories), adjusting for sex, tumour behaviour and patient age. Ontario had the best survival profile for all histologies investigated. The Atlantic provinces had the highest HR for glioblastoma (HR=1.26, 95% CI:1.18-1.35) and malignant glioma not otherwise specified (NOS) (Overall: HR=1.87, 95% CI:1.43-2.43; Pediatric population: HR=2.86, 95% CI:1.28-6.39). For meningioma, the Territories had the highest HR (HR=2.44, 95% CI:1.09-5.45) followed by the Prairie provinces (HR=1.52, 95% CI:1.38-1.67). For malignant unclassified tumours, the highest HRs were in British Columbia (HR=1.45, 95% CI:1.22-1.71) and the Atlantic provinces (HR=1.40, 95% CI:1.13-1.74). There are regional differences in the survival of CNS patients at the population level for all four specific histological types of CNS tumours investigated. Factors contributing to these observed regional survival differences are unknown and warrant further investigation.

The presence of phase diffusion can lead to the loss of the advantages of quantum measurements. Squeezing is considered to be an effective method to reduce the detrimental effect of phase diffusion on the measurement. The Mach-Zehnder (MZ) interferometer has been exploited as a generic tool for precise phase measurement. Describing the reduction in quantum advantage caused by phase diffusion in an MZ interferometer that can be mitigated by squeezing is not easy to handle analytically, because the input state will change from a pure state to a mixed state after experiencing the diffusion noise in the MZ interferometer. We introduce a truncated MZ interferometer that can achieve the same potential phase sensitivity as the conventional MZ interferometer. This scheme can theoretically explain how phase diffusion reduces phase estimation and why squeezing counteracts in the presence of phase diffusion. Using the Gaussian property of the input state and the characteristic of Gaussian operation in the squeezing, the two orthogonal field quantities of the quantum state are squeezed and anti-squeezed to different degrees, and the analytic results are obtained. The truncated MZ interferometer is simpler to build and operate than the conventional MZ interferometer, and also mitigates the phase diffusion noise by the squeezing operation, thus making it useful for applications in precision metrology.

Accurate prediction of the degree of airport delays under the influence of convective weather is crucial for collaborative traffic management implementation and improving the efficiency of airport operations. However, existing studies usually only consider numerical-type quantitative features of weather-affected traffic in their models, and lack the introduction of spatial information to comprehensively portray the traffic operation scenarios under the influence of weather. In order to overcome this problem, this paper firstly designs a new image representation of weather-affected air traffic, and constructs a multi-channel traffic and weather scene image (MTWSI) by populating the airspace two-dimensional grid with traffic and meteorological information to represent the overall traffic operation situation in the terminal area under the influence of convective weather; then, a deep convolutional neural network-based airport delay prediction model ( ADLCNN), which takes MTWSI images as input and uses a specific CNN model to extract the deep features that affect traffic operation in it to input into the subsequent classification algorithm to predict the flight delay level; finally, a series of comparative experiments are carried out on the operational data of Guangzhou Baiyun Airport, and the experimental validation shows that, compared with the traditional machine learning methods, the proposed CNN-based airport delay prediction The experimental validation shows that the proposed CNN-based airport delay prediction model has satisfactory prediction performance compared with the traditional machine learning methods, which also proves that the proposed MTWSI method can more comprehensively respond to the real traffic conditions.

Point defect-based single-photon emitters (SPEs) in GaN have aroused a great deal of interest due to their room-temperature operation, narrow line width and high emission rate. The room-temperature SPEs at the telecommunication bands have also been realized recently by localized defects in GaN in experiments, which are highly desired for the practical applications of SPEs in quantum communication with fiber compatibility. However, the origin and underlying mechanism of the SPEs remain unclear to date. Herein, our first-principle calculations predict and identify an intrinsic point defect NGa in GaN that owns a zero-phonon line (ZPL) at telecommunication windows. By tuning the triaxial compressive strain of the crystal structure, the ZPL of NGa can be modulated from 0.849 eV to 0.984 eV, covering the fiber telecommunication windows from the O band to the E band. Besides the ZPL, the formation energy, band structure, transition process and lifetime of the SPEs under different strains are investigated systematically. Our work gives insight into the emission mechanism of the defect SPEs in GaN and also provides effective guidance for achieving wavelength-tunable SPEs working in fiber telecommunication windows.

In this study, the degradable superhydrophobic Mg/P/Z/F/H (magnesi-um/poly(-caprolactone)/zinc oxide/1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFDTES)/ heating process) composite materials were prepared through one-step method for enhancing the corrosion resistance of AZ91D magnesium alloys. Electrochemical measurements showed that Mg/P/Z/F/H materials significantly improved the corrosion resistance of magnesium alloys in 3.5 wt.% NaCl. The self-cleaning, adhesion and stability tests suggested that Mg/P/Z/F/H composite materials had well self-cleaning properties, good adhesion strength and stability in wet atmosphere.

Active films based on carboxymethyl chitosan incorporated corn peptide were developed. Physicochemical properties of the films, including thickness, opacity, moisture content, color, mechanical properties, water vapor permeability, and oil resistance, were measured. Biological activities of the films, including the antioxidant and antibacterial activities, were characterized in terms of 2, 2-diphenyl-1-picrylhydrazyl free radical scavenging activity, reducing power, the total antioxidant activity, and the filter disc inhibition zone method. The results indicated that the incorporation of corn peptide caused interactions between carboxymethyl chitosan and corn peptide in Maillard reaction and gave rise to the films light yellow appearance. Compared with the Control, the degree of glycosylation, browning intensity, thickness, opacity, tensile strength, antioxidant activity, and antibacterial activity of films were increased, but the elongation, vapor permeability, and oil resistance of films were decreased. The films based on corn peptide and carboxymethyl chitosan can potentially be applied to food packaging.

Abstract: Guanxi, a Chinese term that defines social networks of power and benefits, can be divided into inter-personal and inter-organizational relationships, and guanxi significantly influences construction innovation in China. Many studies have examined the relationship between guanxi and construction innovation at the project or organizational level. However, few of these studies explained how guanxi could affect an individual’s innovative behaviour from a double-level perspective. This paper builds on social capital theory and social exchange theory to examine guanxi’s role in motivating innovative behaviour in a China-specific construction context. It investigates the main effects of inter-personal relationships on innovative behaviour, the mediating effects of knowledge sharing, and the cross-level moderating effects of inter-organizational relationships. These elements were tested using a survey that received 178 responses from 35 different organizations. The results were analysed using Hierarchical Linear Modelling (HLM) and revealed that inter-personal relationships have positive influences on innovative behaviour, thus highlighting the partial mediating effects of knowledge sharing. In addition, the analyses showed that inter-organizational relationships augment inter-personal relationships and knowledge sharing on innovative behaviour by cross-level interaction. The research findings enhance an understanding of guanxi and innovative behaviour in China-specific construction project settings, as well as verifying the significance of guanxi in stimulating innovative behaviour.

With the development of engineering technology, engineering has higher requirements for the accuracy and the scale of simulation calculation. The computational efficiency of traditional se-rial program can not meet the requirements of engineering。Therefore, reducing the calcula-tion time of temperature control simulation program has important engineering significance for real-time simulation of temperature field and stress field, and then adopting more reasona-ble temperature control and crack prevention measures. GPU parallel computing is introduced into the temperature control simulation program of massive concrete to solve this problem and the optimization is carried out. Considering factors such as GPU clock rate, number of cores, parallel overhead and Parallel Region, The improved GPU parallel algorithm analysis indicator formula is proposed. It makes up for the shortcomings of traditional formula that focus only on time. According to this formula, when there are enough threads, the parallel effect is limited by the size of the parallel domain, and when the parallel domain is large enough, the efficiency is limited by the parallel overhead and the clock rate. This paper studies the optimal Kernel execu-tion configuration. Shared Memory is utilized to improve memory access efficiency by 155%. After solving the problem of bank conflicts, an accelerate rate of 437.5x was realized in the sub-routine of the matrix transpose of the solver. The asynchronous parallel of data access and logi-cal operation is realized on GPU by using CUDA Stream , which can overlap part of the data access time. On the basis of GPU parallelism, asynchronous parallelism can double the compu-ting efficiency. Compared with the serial program, the accelerate rate of inner product matrix multiplication of the GPU asynchronous parallel program is 61.42x. This study further proposed a theoretical formula of data access overlap rate to guide the selection of the number of CUDA streams to achieve the optimal computing conditions. The GPU parallel program compiled and optimized by CUDA Fortran platform can effectively improve the computational efficiency of the simulation program for concrete temperature control, and better serve for engineering computing.

Li-rich manganese-based cathode materials (LRMs) are considered one of the most promising cathode materials for the next generation lithium-ion batteries (LIBs) because of their high energy density. However, there are problems such as capacity decay, poor rate performance, and continuous voltage drop, which seriously limit their large-scale commercial applications. In this work, Li1.2Mn0.54Co0.13Ni0.13O2 coated with Li2MoO4 with unique spinel structure was prepared by wet chemistry method and the subsequent calcination process. The Li2MoO4 coating layer with spinel structure can provide a 3D Li+ transport channel, which is beneficial for improving rate performance, while protecting LRMs from electrolyte corrosion, suppressing interface side reactions, and improving cycling stability. The capacity retention rate of LRMs coated with 3wt% Li2MoO4 increased from 69.25% to 81.85% after 100 cycles at 1C, and the voltage attenuation decreased from 7.06 to 4.98 mV per cycle. The lower Rct also exhibits improved magnification performance. The results indicate that the Li2MoO4 coating effectively improves the cyclic stability and electrochemical performance of LRMs.

A numerical method using combined detached-eddy simulation (DES) and cavitation model considering the rotation effect is used for unsteady cavitation flow field of the centrifugal pump. Closed type pump test system was established to obtain the pump performance and pressure pulsation characteristics under different flow rates and cavitation condition, which provide boundary conditions and verification of calculations. Based on the calculation results of the unsteady flow field of the centrifugal pump cavitation, the entropy generation analysis of the flow field and the pressure fluctuation characteristics were carried out. Then the relationship between cavitation and the deterioration of the centrifugal pump performance and the generation of the unstable operation excitation force was tried to reveal. The internal energy loss is mainly concentrated in the impeller, volute, and pump cavity area, which accounts for more than 85% of the total entropy generation. The characteristic frequency of about 0.333 Strouhal Number appears at the volute tongue due to the cavitation flow spread downstream.

Hubei, Hunan and Henan Provinces are located in Central China, a region with extensive transport networks and trade. Bursaphelenchus xylophilus, the causative agent of pine wilt disease, is spreads mainly through human activities. In order to further understand the genetic structure of PWN in Central China, we studied the genetic information of PWN populations in this region and compared the genetic relationship with strains from Guangdong and Jiangsu provinces. We found that the HB (Hubei) 15, HEN (Henan) 20, HN (Hunan) 07, HN08 and HN10 had significantly more SNPs and homozygotes than other strains from Central China, and their most frequent mutant genotypes also differed from other strains. The clustering results indicated that HB15, HEN 20, HN07, HN08 and HN10 were genetically distinct from other strains and closely related to Guangdong strains. We also observed significant genetic variation among strains in Henan province, suggesting that some of them might have different transmission sources than those from Hubei and Hunan provinces. The results provide a basis for tracing the origin and spread of PWD in China.

To address the problems of poor recognition, low detection accuracy, a large number of model parameters and computation, complex network structure, and unfavorable portability to embedded devices in traditional tennis ball detection algorithms, this study proposes a lightweight tennis ball detection algorithm YOLOv5s-Z based on Robomater EP. The main work is as follows: Firstly, constructing lightweight G-Backbone and G-Neck network layers to reduce the number of parameters and computation of the network structure. Secondly, the convolutional coordinate attention is incorporated in G-Backbnone to embed the location information into the channel attention, which makes the network obtain the location information in a larger area through multiple convolutions and enhances the expression ability of the mobile network learning features. In addition, the Concat module in the original feature fusion is modified into a weighted bi-directional feature pyramid W-BiFPN with settable learning weights to improve the feature fusion capability and achieve efficient weighted feature fusion and bi-directional cross-scale connectivity. The EIOU loss is introduced to split the influence factor of aspect ratio and calculate the length and width of the target frame and anchor frame respectively, combined with Focal-EIOU Loss to solve the problem of imbalance between difficult and easy samples. The activation function Meta-ACON is introduced to achieve an adaptive selection of whether to activate the neurons and improve the detection accuracy. Finally, the experimental results show that compared with the original algorithm, the YOLOv5s-Z algorithm reduces the number of parameters and computation by 42$\%$ and 44$\%$, the model size by 39$\%$, and 2$\%$ improvement in average accuracy mean value, which verifies the effectiveness of the improved algorithm and the light weight of the model to meet the deployment requirements of embedded devices, and adapts Robomaster EP for accurate detection and real-time recognition of tennis balls.

Classical laws of friction suggest that friction force is proportional to the normal load and independent of the nominal contact area. As a great improvement in this subject, it is now widely accepted that friction force is proportional to the real area in contact, and much work has been conducted based on this hypothesis. In present study, this hypothesis will be carefully revisited by measuring the friction force and real contact area in-site and real-time at both normal loading and unloading stages. Our experiments reveal that the linear relation always holds between friction force and normal load. However, for the relation between friction force and real contact area, the linearity holds only at the loading stage while fails at the unloading stage. This study may improve our understanding of the origin of friction.

With the rapid development of China's economy, construction industrialization has become the main development trend of China's construction industry, and the convenient, efficient, environmental protection has become the new fashion, therefore the application of prefabricated building is more and more common. Stair serves as the weak link in prefab type building, the connecting node has an important influence on its failure. In this paper, pseudo-static tests are carried out on the joints in different forms of ladder holes to study the mechanical properties of flexible hinge points filled with flexible materials, and the hysteresis curve, skeleton curve and bearing capacity of each specimen are analyzed. The test results show that the flexible hinge can give full play to its flexible characteristics to ease the stress of ladder beam, pin bolt reinforcement and ladder hole, and the bearing capacity of flexible hinge points is moderate, which can not only mitigate the inclined bracing effect under the action of small and medium earthquakes, but also ensure the stair does not fall off under the action of large earthquakes. Through the experiment comparison, the ladder hole adopts node form 2, which can give full play to the advantage of flexible material.

Herein, bamboo-laminated lumber for furniture was coated with waterborne acrylic paint. The effects of different painting techniques and quantities on the drying rate, smoothness, hardness, adhesion and wear resistance of the paint film were investigated. Then, the thermal properties of the paint were analysed using thermogravimetry and differential scanning calorimeter to examine the film-forming mechanism. The results showed that painting technique had no effect on the drying time, flatness, hardness and adhesion of the paint film, but it influenced the wear resistance. Herein, the films’ flatness showed little variation with different painting methods (one-layer primer one-layer topcoat, one-layer primer two-layer topcoat, two-layer primer one-layer topcoat and two-layer primer two-layer topcoat). The drying time for primer surfaces/solids was 8min/8.5 min, while it was 6.5/7 min for topcoats. The paint films exhibited grade B hardness and grade 0 adhesion and the better wear resistance when using one-layer primer one-layer topcoat at 51.24 mg·100 r−1. The amount of paint applied significantly affected the drying time and flatness of the paint film. As the quantity increased, the drying time of the paint’s surfaces and solids also increased, whereas the film’s flatness initially increased before decreasing. The film’s optimal adhesion, hardness and wear resistance values were grade 0, grade B and 51.24 mg·100 r−1, respectively, when 80 g/m2 of paint was applied. Thermal analysis of the primer and topcoat showed that water decomposition occurred at 100℃ and thermal decomposition of organic components occurred at 350℃. The primer and topcoat exhibited the same weight loss, but primer’s thermal loss rate was higher than that of topcoat. Consequently, the topcoat displayed better thermal stability than the primer.

The cutter structure and layout scheme of PDC (Polycrystalline Diamond Compact) bits are important factors in improving efficiency. To further improve the drilling efficiency of PDC bits, axe, triangular prism, and cylindrical PDC cutters were used as research objects. Based on the measured granite data, a finite element model of non-homogeneous granite was established and verified by uniaxial compression simulation. The rock-breaking process of different cutter combination schemes was compared using the finite element method, and the parameters in the best scheme were optimized using the Box-Behnken response surface method. The results show that the constructed model of non-homogeneous granite is consistent with the stress-strain relationship of real granite and is reliable. The axe PDC cutter is more aggressive than the other two cutters and is more suitable for the front row of the bit blade tooth arrangement, while the triangular prism cutter is the second most aggressive and is suitable for the rear row of tooth arrangement, and the best combination scheme is the front row of axe cutter and the rear row of triangular prism cutter arranged alternately with the axe cutter. The optimal transverse and longitudinal distances of the optimized triangular prism cutter from the front axe cutter are 10mm and 7mm, and the optimal transverse and longitudinal distances of the rear axe cutter from the front cutter are 10.06mm and 7mm. The drilling speed is more stable during drilling and the PDC bit with mixed tooth arrangement has 16.8% and 16.6% higher rate of penetration(ROP) compared with the bit with single axe cutter and triangular prism cutter, and the drilling speed is more stable during working, which can effectively improve the rock breaking efficiency of the PDC bit. The field application proves that the bit with mixed cutter arrangement is easier to break the complex formations, with more stable ROP and better efficiency. The study can provide theoretical support for the cutter layout of the PDC bit.

Wireless Sensor Networks (WSNs) has the characteristics of large-scale deployment, flexible networking, and wide application. It is an important part of the wireless communication networks. However, due to limited energy supply, the development of WSN is greatly restricted. Wireless Rechargeable Sensor Networks (WRSNs) transform the distributed energy around the environment into usable electricity through energy collection technology. In this work, a joint optimization strategy is proposed to improve the energy management efficiency for WRSNs. The joint optimization strategy is divided into two phases. In the first phase, we design an Annulus Virtual Force based Particle Swarm Optimization (AVFPSO) algorithm for area coverage planing. It adopts the multi-parameter joint optimization method to improve the efficiency of the algorithm. In the second phase, a Queuing Game-based Energy Supply (QGES) algorithm is designed for energy scheduling. It converts energy supply and consumption into network service. By solving the game equilibrium of the model, the optimal energy distribution strategy can be obtained. The simulation results show that our scheme improves the efficiency of coverage and energy, and extends the lifetime of WSN.

Nitride and carbide are the second phases which play an important role in the performance of bearing steel, and their precipitation behavior is complicated. In this study, TiN-MC_x precipitations in GCr15 bearing steels were obtained by non-aqueous electrolysis, and their precipitation mechanisms were studied. TiN is the effective heterogeneous nucleation site for Fe₇C₃ and Fe₃C, therefore, MC_x can precipitate on the surface of TiN easily, its chemistry component consists of M₃C and M₇C₃ (M = Fe, Cr, Mn) and Cr₃C₂. TiN-MC_x with high TiN volume fraction, TiN forms in early stage of solidification, and MC_x precipitates on TiN surface after TiN engulfed by the solidification advancing front. TiN-MC_x with low TiN volume fraction, TiN and MC_x form in late stage of solidification, TiN can not grow sufficiently and is covered by a large number of precipitated MC_x particles.

This study presents application of demand response strategy in a standalone wind-solar-battery hybrid energy system (HES). Inputs for the designed HES are wind speed, solar radiation, temperature and load demand which is variable with time. In this study, hourly values of meteorological data and hourly load demand are considered in one year. An improved gravitational search algorithm (IGSA) is used to optimize the configuration of the standalone wind-solar-battery hybrid power system. The optimal objectives of the system are cost of the system in life cycle, the loss of power supply probability（LPSP）and the energy excess percentage（EXC）.The effect of demand response on economic benefit and energy storage allocation of the standalone wind-solar-battery system is studied. The obtained optimal configuration of the proposed HES can provide minimal energy cost with excellent performance and reduced waste and unmet load.

This paper first discusses a fractional-order Liu system of order as low as 2.7 and shows its chaotic characteristics by carrying out numerical simulations such as Lyapunov exponents, bifurcation diagrams and phase portraits. Then, by using the topological horseshoe theory and computer-assisted proof, the existence of chaos in the system is verified theoretically. Finally, the fractional-order system is implemented on a Field Programmable Gate Array (FPGA) and the results obtained show that the fractional-order Liu system is indeed chaotic.

The 2019 novel SARS-like coronavirus (SARS-CoV-2) entry depends on the host membrane serine protease TMPRSS2, which can be blocked by some clinically-proven drugs. Here we analyzed spatial relevance between glycosylation sequons and antibody epitopes and found that, different from SARS-CoV S, most high-surface-accessible epitopes of SARS-CoV-2 S are blocked by the glycosylation, and the optimal epitope with the highest surface accessibility is covered by the S1 cap. TMPRSS2 inhibitor treatments may prevent unmasking of this epitope and therefore prolong virus clearance and may induce antibody-dependent enhancement. Interestingly, a heparin-binding sequence immediately upstream of the S1/S2 cleavage site has been found in SARS-CoV-2 S but not in SARS-CoV S. Binding of SARS-CoV-2 with heparins may lead to exposure of S686, which then facilitates the S1/S2 cleavage, induces exposure of the optimal epitope, and therefore increases the antibody titres. A combination of heparin and vaccine (or convalescent serum) treatments thus is recommended.

Avian infectious bronchitis virus (IBV) is the causative agent of infectious bronchitis, which causes considerable economic losses to the poultry industry worldwide. It is imperative to develop safe and efficient candidate vaccines to control IBV infection. In the current study, recombinant baculoviruses co-expressing S1 and N proteins, mono-expressing S1 or N proteins alone of IBV were constructed and prepared into subunit vaccines rHBM-S1-N, rHBM-S1 and rHBM-N. The levels of immune protection of these subunit vaccines were evaluated by inoculating specific pathogen-free (SPF) chickens at 14 days of age, boosting with the same dose 14 days later, and following challenge with a virulent GX-YL5 strain of IBV 14 days post-booster (dpb). The commercial vaccine strain H120 was used as a control. The IBV-specific antibody levels as well as the percentages of CD4+ and CD8+ T lymphocytes were detected within 28 days post-vaccination (dpv). The morbidity, mortality, and re-isolation of virus from the tracheas and kidneys of challenged birds were evaluated at 5 days post-challenge (dpc). The results showed that the IBV-specific antibody levels and the percentages of CD4+ and CD8+ T lymphocyte in rHBM-S1-N group were higher than those of rHBM-S1 and rHBM-N groups, especially the cellular immunity response. At 5 dpc, the mortality, morbidity and virus re-isolation rate of rHBM-S1-N were slightly higher than those of H120 group, but were lower than those of rHBM-S1 group and rHBM-N group. The present study demonstrated that the protection of recombinant baculovirus co-expressing S1 and N proteins was better than that of recombinant baculoviruses mono-expressing S1 or N protein alone. Thus, the recombinant baculovirus co-expressing S1 and N proteins could serve as a potential IBV vaccine and this demonstrates that the bivalent subunit vaccine including the S1 and N proteins might be a strategy for the development of an IBV subunit vaccine.

The layout of deep chamber for coal-gangue separation (DCCS) based on the horizon of the weak stratum can affect the stability of its surrounding rocks. First, the work summarized the main structural characteristics of DCCS. Similar simulation tests were performed to analyze the deformation and failure law of surrounding rocks of DCCS under different horizons of the weak stratum. Then, 60 numerical simulation schemes were designed by considering the lateral pressure coefficient and the thickness and horizon of the weak stratum. A comprehensive evaluation method was proposed for the stability of surrounding rocks. The optimal layout methods of the DCCS were determined based on the thickness and horizon of the weak stratum in different ground stress fields. If the thickness of the weak stratum was large and lateral pressure coefficient λ &lt; 0.6 or λ &gt; 1, the stability of surrounding rocks was optimal to arrange the side of DCCS along the weak stratum. When 0.6 ≤ λ ≤ 1, the optimal approach for controlling surrounding rocks was to position the floor of DCCS along the weak stratum. If the thickness of the weak stratum was small and λ&lt;0.6 or λ&gt;1, the stability of surrounding rocks was optimal to arrange the side of DCCS near roof along the weak stratum. When 0.6 ≤ λ ≤ 1, the optimal approach for controlling surrounding rocks was to arrange the side of DCCS near the floor along the weak stratum. The results can provide an important theoretical reference for the spatial layout and support design of DCCS.

In this paper, through high-temperature tensile tests of 55NiCrMoV7 steel, the high-temperature fracture behavior, microstructure evolution and carbide distribution characteristics of both thermal-mechanical coupling zone (fracture zone) and thermal stress zone (clamping zone) at different temperatures were studied. Intrinsic relationship between high temperature fracture and carbides types, distribution and size were revealed and evolution mechanism of microstructure near cracks in 55NiCrMoV7 hot-working die steel during high temperature deformation was clarified. Samples were stretched at different temperatures from 25 °C to 700 °C, and microscopic examinations were carried out by using SEM and TEM. The results showed that: With the increase of temperature, tensile strength and yield strength decreased, elongation and reduction of area increased, and fracture mode changed from brittle fracture to ductile fracture by transition temperature at about 400℃. During high temperature deformation, the grain dislocation density decreased, the tempered martensite decomposed, recovered, recrystallized, and then grain grew. M7C3 and M23C6 carbides precipitated and grew along the grain boundary, and a small amount of fine granular MC carbides were dispersed in the grain. The work done by the external force on the deformation zone would cause the temperature of it to be higher than tensile temperature, which provides thermodynamic conditions for the re-dissolution of small carbides near the fracture zone and the grain growth of large carbides, resulting in the decrease of small carbides and increase of large carbides in thermal-mechanical coupling zone.

The bilateral trade relationship between PRC and ASEAN is close. As early as 2012, China has been the largest trading partner of ASEAN, and ASEAN has also taken the place of the United States as PRC’s second largest trading partner in 2019.This paper uses the theory of ecological population evolution, selects the total import and export volume of PRC and the ten ASEAN countries from 2000 to 2019 as the data sample, studies the bilateral trade relations between PRC and the ten ASEAN countries, analyzes the competition and symbiotic relationship of bilateral trade between PRC and the ten ASEAN countries and the possibility of trade friction according to the results, and proposes corresponding improvement strategies. According to the results of the population evolution competition model, China has a competitive relationship with Indonesia, Malaysia, the Philippines, Singapore and Thailand, which is most likely to cause trade friction. China has a biased relationship with Brunei, Cambodia, Laos, Myanmar and Vietnam, which is more likely to cause trade friction. On this basis, in order to further strengthen the trade relations between PRC and the ten ASEAN countries, this paper puts forward policy suggestions on improving infrastructure, strengthening independent innovation, seeking cooperation fields and actively investing abroad.

In this paper, we discuss optical properties of the topologically charged rotating black hole. We study the horizon, the photon region, the shadow of the black hole and other observables. The results show that in addition to the black hole spin parameter $a$, the other two parameters, five-dimensional mass parameter $\beta$ and electric charge $q$, are also found to affect the horzion, the photon region and the black hole shadow. In a certain range, with the increase of the three parameters, the horizon distance, shape of the photon region and the black hole shadow will all shrink. Moreover, with the increase of these three parameters, the distortion parameter $\delta_{s}$ gradually increases, while the peak of the black hole energy emission rate decreases.

Super-Resolution Microscopy enables non-invasive, molecule-specific imaging of the internal structure and dynamics of cells with sub-diffraction limit spatial resolution. One of its major limitations is the requirement for high-intensity illumination, generating considerable cellular phototoxicity. This factor considerably limits the capacity for live-cell observations, particularly for extended periods of time. Here, we overview new developments in hardware, software and probe chemistry aiming to reduce phototoxicity. Additionally, we discuss how the choice of biological model and sample environment impacts the capacity for live-cell observations.

Initial attempts to develop monoclonal antibodies as therapeutics to resolve influenza infections focused mainly on searching for antibodies with the potential to neutralise the virus in vitro with classical haemagglutination inhibition and micro-neutralisation assays. This led to the identification of many antibodies that bind to the head domain of haemagglutinin (HA) which generally have potent neutralisation capabilities that block viral entry or viral membrane fusion. However, this class of antibodies has a narrow breadth of protection in that they are usually strain specific. This led to the emphasis on stalk targeting antibodies which are able to bind a broad range of viral targets that span across different influenza subtypes. Recently, a third class of antibodies targeting the vestigial esterase (VE) domain have been characterised. In this review, we describe the key features of neutralising VE targeting antibodies and compare them with head and stalk class antibodies.

Two novel inorganic–organic hybrid supramolecular assemblies, namely, (4-HNA)(18-crown-6)(HSO₄) (1) and (4-HNA)₂(18-crown-6)₂(PF₆)₂(CH₃OH) (2) (4-HNA = 4-nitroanilinium), were synthesized and characterized by infrared spectroscopy, single X-ray diffraction, differential scanning calorimetry (DSC), and temperature-dependent dielectric measurements. The two compounds underwent reversible phase transitions at about 255 K and 265 K, respectively. These phase transitions were revealed and confirmed by the thermal anomalies in DSC measurements and abrupt dielectric anomalies during heating. The phase transition may have originated from the [(4-HNA)(18-crown-6)]⁺ supramolecular cation. The inorganic anions tuned the crystal packings and thus influenced the phase-transition points and types. The variable-temperature X-ray diffraction data for crystal 1 revealed the occurrence of a phase transition in the high-temperature phase with the space group of P2₁/c and in the low-temperature phase with the space group of P2₁/n. Crystal 2 exhibited the same space group P2₁/c at different temperatures. The results indicated that crystals 1 and 2 both underwent an iso-structural phase transition.

Ensuring the accuracy of wind power prediction is paramount for the reliable and stable operation of power systems. This study introduces a novel approach aimed at enhancing the precision of wind power prediction through the development of a multiscale hybrid model. This model integrates advanced methodologies including Improved Intrinsic Mode Function with Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), Permutation Entropy(PE), Least Squares Support Vector Regression (LSSVR), Regularized Extreme Learning Machine(RELM), Multi-head Attention (MHA), and Bidirectional Gated Recurrent Unit (BiGRU). Firstly, the ICEEMDAN technique is employed to decompose the non-stationary raw wind power data into multiple relatively stable sub-modes, while concurrently utilizing PE to assess the complexity of each sub-mode. Secondly, the dataset is reconstituted into three distinct components: high-frequency, mid-frequency, and low-frequency, to alleviate data complexity. Following this, the LSSVR, RELM, and MHA-BiGRU models are individually applied to predict the high, mid,and low-frequency components, respectively. Thirdly, the parameters of the low-frequency prediction model are optimized utilizing the Dung Betele Optimizer(DBO) algorithm. Ultimately, the predicted results of each component are aggregated to derive the final prediction. Empirical findings illustrate the exceptional predictive performance of the multiscale hybrid model incorporating LSSVR, RELM,and MHA-BiGRU. In comparison to other benchmark models, the proposed model exhibits a reduction in Root Mean Square Error(RMSE) values of over 10%, conclusively affirming its superior predictive accuracy.

The separation of Li+ and [Bmim]+(1-Butyl-3-methylimidazolium) by electrically driven membrane technology was studied. The effects of the types and modification processes of cation exchange membranes, current density, total cation concentration, temperature, and anion types on separation efficiency were investigated. The results indicated that it is feasible to achieve efficient separation of Li+ and [Bmim]+ using the selectivity of cation exchange membranes under electric field. Membrane CMX and the modified membrane A and B which obtained from the CMX showed obvious selective of Li+ from [Bmim]+. When the current density is 5 mA/cm2 and the feed concentrations of Li+ and [Bmim]+ are 0.3 mol/L and 0.2 mol/L, the selective transport coefficient of the modified membrane B can reach 6.2 in the first 120 minutes of the process. Reducing current density and increasing total cation concentration can improve separation efficiency. Lowering the temperature can improve the separation effect, but improvement is not obviously. Changing the anion of the feed from chloride ion to acetate has no effect on the separation.

Lower urinary tract dysfunction (LUTD) was associated with bladder inflammation and tissue hypoxia with oxidative stress. This study investigated the profiles of urine inflammatory and oxidative stress biomarkers in females with LUTD and to develop a urine biomarker-based decision tree model for the prediction. Urine samples were collected from 31 female patients with detrusor overactivity (DO), 45 with dysfunctional voiding (DV), and 114 with interstitial cystitis/ bladder pain syndrome (IC/BPS). The targeted analytes included 15 inflammatory cytokines and 3 oxidative stress biomarkers (8-hydroxy-2-deoxyguanosin, 8-isoprostane, and total antioxidant capacity [TAC]). Different female LUTD groups had distinct urine biomarker profiles, including IL-1β, IL-2, IL-8, IL-10, eotaxin, CXCL10, MIP-1β, RANTES, TNFα, VEGF, NGF, BDNF, 8-isoprostane, and TAC. The urine biomarker-based decision tree, using IL-8, IL-10, CXCL10, TNFα, NGF, and BDNF as nodes, demonstrated an overall accuracy rate of 85.3%. DO, DV, and IC/BPS accuracy rates were 74.2%, 73.3%, and 93.0%, respectively. Internal validation revealed similar overall accuracy rate. Random forest models supported the significance and importance of all selected nodes in this decision tree model. Urine inflammatory and oxidative stress biomarker profiles of different female LUTDs were different. This internally validated urine biomarker-based decision tree model predicted different female LUTDs with high accuracy.

Background and Objectives: Although researchers suggested that non-pharmaceutical intervention (NPI) and vaccination together can provide the best protection from the COVID-19 [1], people’s willingness to adopt personal NPIs seems to decrease through the COVID-19 waves. This study seeks for an explanation for this observation based on the framework of risk perception. Materials and Methods: Two cross-sectional surveys (N = 407 in Survey 1 and N = 505 in Survey 2) were administered before and in the first outbreak of COVID-19 in Taiwan. The survey items were designed to measure people’s recognized severity of COVID-19, worry of COVID-19, intention to adopt personal NPIs, and attitude toward COVID-19 vaccines. We established a structural model according to the framework of risk perception, which was applied to fit the data of the two surveys. Results: The multigroup SEM (Structural Equation Modeling) results showed that worry (i.e., emotional component of risk perception) fully mediates the influence of recognized severity of COVID-19 (cognitive component of risk perception) on the intention to adopt NPIs in each survey. Before the outbreak (i.e., Survey 1), people’s attitude toward COVID-19 vaccines has nothing to do with their worry of COVID-19. However, when people have experienced the real outbreak of COVID-d19 (i.e., Survey 2), their attitude toward COVID-19 vaccines negatively predicts their worry of COVID-19, forming an indirectly negative effect on their intention to adopt personal NPIs, suggesting the occurrence of the Peltzman effect. That is, receiving vaccination makes people feel safer, that the other way around relaxes their alert for COVID-19, thus, declining the intention to adopt personal NPIs.

Artificial intelligence algorithms have gained widespread adoption in the field of air conditioning load prediction. However, their prediction accuracy is substantially influenced by the quality of training samples. Training samples that lack relevance to the predicted moments can introduce interference into the neural network's learning process, potentially leading to a state of local convergence during its iterative process. This, in turn, diminishes the robustness and generalization capabilities of the prediction model. To enhance the prediction accuracy of air conditioning load prediction models based on artificial intelligence algorithms, this study presents an artificial intelligence algorithm prediction model based on the method of sample similarity sample screening. Initially, the comprehensive similarity coefficient between samples is computed using the gray correlation analysis method, enriched with enhancements in information entropy. Subsequently, a subset of closely related samples is extracted from the original dataset and employed as the training dataset for the artificial intelligence prediction model. Finally, the trained artificial intelligence algorithm prediction model is deployed for air conditioning load prediction. The results illustrate that the method of screening training samples based on sample similarity effectively improves the prediction accuracy of BP neural network (BPNN) and extreme learning machine (ELM) prediction models. However, it is important to note that this approach may not be suitable for genetic algorithm BPNN (GABPNN) and support vector regression (SVR) models.

(1) Background: ganoderic acids (GAs) are specific triterpenes of Ganoderma lucidum. The HPLC fingerprint profile of GAs of the fruiting body has been well-known, but the mycelial fingerprinting remains unclear. (2) Methods: the ethanol extract of the mycelium of G. lucidum (YK-01) was further purified by preparative HPLC. The HPLC spectra for four strains of G. lucidum and one strain of G. formosanum (purple lingzhi) were investigated. (3) Results: nineteen lanostane triterpenes, including five new triterpenes, GA-TP (1), ganodermic acid Jc (GmA-Jc) (2), GmA-Jd (3), GA-TQ1 (4), and ganoderal B1 (5), and fourteen known triterpenes 6-19 were isolated from the ethanol extract. A green chemical HPLC analytical method was developed by using ethanol and acetic acid as mobile phase. These triterpenes comprise of a unique HPLC triterpenoid spectral pattern of G. lucidum mycelium. All four G. lucidum strains showed the same HPLC spectral pattern, whereas G. formosanum displayed a different pattern. Quantitation methods for ganoderic acid T (10) and S (12) were also validated. (4) Conclusions: the triterpenoid HPLC analytical method can be used to identify G. lucidum species, and to determine the contents of GA-T and GA-S.

Recently, resistive random access memory (RRAM) has been an outstanding candidate among various emerging nonvolatile memories for high density storage and in-memory computing applications. However, the traditional RRAM, which accommodates two states depending on applied voltage, cannot meet the high density requirement in the era of big data. Many research groups have demonstrated that RRAM possesses the possibility of multi-level cell to overcome the demand of mass storage. Among numerous semiconductor materials, gallium oxide, as the fourth-generation semiconductor material, is highly-profile due to its excellent material proper-ties, and already be widely used in optoelectronics, high-power, resistive switching device and so on, due to its wide bandgap and transparent properties. In this study, we have successfully demonstrated the Al/GO/Ga2O3/ITO RRAM to achieve the possibility of two-bit storage. Compared to the single-layer counterpart, the bilayer structure has excellent electrical properties and stable reliability. The endurance characteristics could be enhanced above 100 switching cycles with an ON/OFF ratio of over 103. Moreover, the filament models are also described in this thesis to clarify the transport mechanisms.

To further explore the bearing capacity and sustainable construction of vacuum drainage pipe (VDP) piles, field tests were carried out to compare and analyze the ultimate single pile bearing capacity, pile side friction and pile end resistance of ordinary piles and vacuum drainage pipe piles. The effect of the VDP pile on energy conservation and emission reduction in practical projects is discussed. The results shows that the VDP pile basically eliminated the soil squeeze and did not cause excessive relative displacement of pile and soil after vacuum consolidation. The VDP pile enhances pile side friction resistance, resulting in a 17.6% increase in ultimate bearing capacity compared to traditional piles. The VDP pile method can reduce carbon emissions by 31.4% compared to traditional methods. This study provides guidance for the production and design of VDP piles in the future and demonstrates their potential for energy conservation and emission reduction benefits compared to traditional methods.

This study aims to implement a SSDBI (single-stage differential boost inverter, SSDBI) applying in a single-stage BESS (battery energy storage system, BESS) topology, which can supply power from lower voltage battery module to AC load. Compared with the common two-stage topology, which has a two-stage converter and higher voltage battery module array, the single-stage topology can reduce the number of cells and components, and improve the power density. In addition, a modified SPWM control was proposed to reduce the control complexity of the SSDBI while improving the THD of the inverter. The modified SPWM control can reduce the duty ratio of the SSDBI and the stress on the components to improve the AC voltage output waveform and reduce the THD value about 2.654%.

This study used the sol–gel method to synthesize a non-halogenated hyperbranched flame retardant containing nitrogen, phosphorus and silicon, HBNPSi, which was then added to a polyurethane (PU) matrix to form an organic–inorganic hybrid material. Using 29Si nuclear magnetic resonance, energy-dispersive X-ray spectroscopy of P- and Si-mapping, scanning electron microscopy, and X-ray photoelectron spectroscopy, this study determined the organic and inorganic dispersity, morphology, and flame retardance mechanism of the hybrid material. The condensation density of the hybrid material PU/HBNPSi was found to be 74.4%. High condensation density indicates a dense network structure of the material. The P- and Si-mapping showed that adding inorganic additives in quantities of either 20% or 40% results in homogeneous dispersion of the inorganic fillers in the polymer matrix without agglomeration, indicating that the organic and inorganic phases had excellent compatibility. In the burning test, adding HBNPSi to PU resulted in the material passing the UL-94 standard at the V2 level, unlike the pristine PU, which did not meet the standard. The results demonstrated that after non-halogenated flame retardant was added to PU, the material’s flammability and dripping were lower, thereby proving that flame retardants containing elements such as nitrogen, phosphorus, and silicon exert an excellent flame retardant synergistic effect.

This study integrated coastal-watershed models and combined a risk assessment method to develop a methodology to investigate the impact resulting from coastal disasters under climate change. The mid-western coast of Taiwan suffering from land subsidence was selected as the demonstrative area for the vulnerability analysis based on prediction of sea level rise (SLR), wave run-up, overtopping, and coastal flooding under the scenarios of 2020 to 2039. Database from tidal gauges and satellite images were used to analyze sea level rise using EEMD (Ensemble Empirical Mode Decomposition). Extreme wave condition and storm surge were estimated by numerical simulation using WWM (Wind Wave Model) and POM (Princeton Ocean Model). Coastal inundation was then simulated via WASH123D watershed model. The risk map of study areas based on the analyses of vulnerability and disaster were established using the AHP (Analytic Hierarchy Process) technique. Predictions of sea level rise, the maximum wave condition and storm surge under the scenarios of 2020 to 2039 are presented. The results indicate that the sea level at the mid-western coast of Taiwan will rise in an average of 5.8 cm, equivalent to a rising velocity of 2.8 mm/year. The analysis indicates that Wuqi, Lukang, Mailiao, and Taixi townships are susceptive, low resistant and low resilient, and reaches the high risk level. The assessment provides that important information for making adaption policy in the mid-western coast of Taiwan.

Accurate segmentation of the Left Ventricle (LV) in Echocardiogram (Echo) images is essential for cardiovascular analysis. Conventional techniques are labor-intensive and exhibit inter-observer variability. Deep learning has emerged as a powerful tool for automated medical image segmentation, offering advantages in speed and potentially superior accuracy. This study explores the efficacy of employing the YOLO (You Only Look Once) segmentation model for automated LV segmentation in Echo images. YOLO, a cutting-edge object detection model, achieves exceptional speed-accuracy balance through its well-designed architecture. It utilizes efficient dilated convolutional layers and bottleneck blocks for feature extraction, while incorporating innovations like path aggregation and spatial attention mechanisms. These attributes make YOLO a compelling candidate for adaptation to LV segmentation in Echo images. We posit that by fine-tuning a pre-trained YOLO based model on a well-annotated Echo image dataset, we can leverage the model's strengths in real-time processing and precise object localization to achieve robust LV segmentation. The proposed approach entails fine-tuning a pre-trained YOLO model on a rigorously labeled Echo image dataset. Model performance has been evaluated using established metrics such as mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 50% (mAP50) with 98.31%and across a range of IoU thresholds from 50% to 95% (mAP50:95) with 75.27%. Successful implementation of YOLO for LV segmentation has the potential to significantly expedite and standardize Echo image analysis. This advancement could translate to improved clinical decision-making and enhanced patient care.

The 1060 aluminium alloy is widely applied to electronic industry, construction area, aerospace field, traffic engineering, decoration and consumption goods market for its good chemical, physical and mechanical properties. In general, excellent processing property is necessary and important for manufacturing of complicated panels. In this paper, a special 2D ultrasonic vibration incremental forming method is designed to improve its plasticity and mechanical properties. Three kind of processing methods including traditional single point incremental forming, longitudinal ultrasonic vibration incremental forming and 2D ultrasonic vibration incremental forming are conducted for flexible manufacture of conical parts of 1060 aluminium alloy sheet. Then micro-hardness tests, residual stress tests and scanning electron microscopy tests are carried out to probe its revolution of micro-structure and mechanical properties and to analysis the effects of different types of ultrasonic vibration on plasticity and fracture characteristic of 1060 aluminium alloy. It is proved that 2D ultrasonic vibration is facilitated to improvement of plasticity and surface qualities of 1060 aluminium alloy than the other two processing methods. So, the novel 2D ultrasonic vibration incremental forming possesses substantial application values on flexible and rapid manufacturing of complicated thin-walled component of aluminium alloy.

Studies report variable effects of sex hormones on serious diseases. Severe disease and mortality rates in COVID-19 show marked gender differences that may be related to sex hormones. Sex hormones regulate the expression of the viral receptors ACE2 and TMPRSS2, which affect the extent of viral infection and consequently cause variable outcomes. In addition, sex hormones have complex regulatory mechanisms that affect the immune response to viruses. These hormones also affect metabolism through obesity, and severe disease can result from complications such as thrombosis. This review presents the latest research on the regulatory functions of hormones in viral receptors, immune responses, complications as well as their role in COVID-19 progression. It also discusses the therapeutical possibilities of these hormones by reviewing the recent findings of clinical and assay studies.

Calligraphy works have high artistic value, but there is a rampant problem of forgery. Indeed, authentication of traditional calligraphy heavily relies on calligraphers' subjective judgment. Therefore, spurred by the recent development of neural networks, this paper proposes a method for authenticating calligraphy works based on an improved EfficientNet network. Specifically, the developed method utilizes the character box algorithm and the centroid algorithm to extract individual calligraphy characters, which are then augmented and used as the training set for the model. The training process employs CBAM and Self-Attention modules to enhance the attention mechanism of the EfficientNet network. The model is tested on authentic works, imitated works, and works from other calligraphers and is compared with other networks. The experimental results demonstrate that the proposed method effectively achieves the authentication of calligraphy works, and the improved CBAM-EfficientNet network and SA-EfficientNet network achieve better authentication performance.

In the process of construction and operation of the pumping station, a large number of axial flow pumps pose a threat to the survival of fish in the natural environment. Through experiments, the survival conditions of many kinds of fish in extreme positive and negative pressure environment are explored, and -40 kPa is established as the low pressure damage threshold, which is used as a reference to analyze the probability of fish damage caused by pumps. The immersion boundary-lattice Boltzmann numerical method (LES-IB-LBM) based on large eddy simulation is used to optimize the parameters of the prototype runner of axial flow pump. A new type of runner with leading edge thickness of 11.4mm and blade cutting angle of 18 ° is optimized. This kind of runner has both hydraulic performance and fish-passing ability. The runner of the fish-friendly axial flow pump effectively guides the fish into the low risk area and reduces the risk of friction, shear and impact damage to the fish. the total impact mortality ratio of the runner of the axial flow pump before and after optimization is close to 7:1. The pressure damage analysis shows that the lowest negative pressure of the fish is -59.2 kPa, which is higher than -64.5 kPa of the prototype pump, and the highest positive pressure of the body surface is 11.8 kPa, which is lower than the 43.8 kPa of the prototype pump. Shear damage analysis shows that the fish will not be damaged by shear in the prototype pump and fish-friendly pump.

TiO2-based building materials have air purification, auto-cleaning and sterilization functions, and these innovative green building materials have great potential for energy-saving and emission reduction applications in the future. However, there are still great challenges in improving photocatalytic efficiency and stability from laboratory to practical applications. In recent years, researchers have done a lot of work to improve the efficiency and stability of TiO2-based building materials. This paper briefly discussed the air purification principle by photocatalytic building, and the preparation techniques of TiO2-based building materials and the strategies to improve the efficiency of TiO2. Moreover, this paper has outlined the key factors that affect the photocatalytic building performance in practical applications, and analyzed the limitations and future development trends. Finally, we proposed some suggestions for further research on photocatalytic buildings and its application in practice, aiming to provide an efficient reference for developing highly efficient and stable photocatalytic building materials. The aim of this paper is to provide effective guidance for the application of TiO2-based photo-catalysts in the field of green buildings, helping to develop more efficient and stable low-carbon buildings for the development of sustainable cities.

In the past decades, the world is actively working towards the global goal of net-zero emission. To decrease emissions, there is a notable trend of electrification in transportation, which is a transition from traditional fuel-based systems to electrical power systems onboard different transportation platforms. For this transition, it is important to study the electrical structure, specifically the onboard microgrid, powered by various energy sources. In this paper, traditional energy management strategies for onboard microgrid systems are discussed, which usually require complicated optimization algorithms and high computation capabilities. Driven by the recent advancements in information technologies, artificial intelligence and digital twin have gained much interest within the transportation sector. These technologies can effectively utilize data to achieve intelligent decision-making, optimize resource utilization, and save energy consumption. This paper presents an overview of the usage of these emerging information technologies in energy management strategies, providing an overall summary and classification of the practical applications. In addition, after examining the potential challenges associated with artificial intelligence and digital twin, this paper also discusses future trends in this field.

CMC/PVA composite nanofiber membrane was prepared by electrostatic spinning method, using carboxymethyl cellulose (CMC) and polyvinyl alcohol (PVA) as raw materials and glutaraldehyde as cross-linking agent. The structure, morphology, thermal stability, and filtration performance of CMC/PVA nanofiber membranes were characterized by advanced instrumental analysis methods such as scanning electron microscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis, ultraviolet analysis and energy spectrum analysis. The results show that the average fiber diameter decreases from 381 nm to 183 nm, when the spinning voltage is 23 KV and the jet speed is 2 µL/min. The obtained fiber has the smallest particle size and the most uniform distribution. Infrared spectroscopy analysis confirms that the adsorption behavior of nanofiber membranes on Cu2+ and Cr6+ is chemical adsorption. The retention rates of CMC/PVA nanofiber membranes for Cu2+ and Cr6+ reached 97% and 98%, respectively.

Smart Internet of Vehicles (IoVs) combined with Artificial Intelligence (AI) will contribute to vehicle decision-making in the Intelligent Transportation System (ITS). Multi-Vehicle Pursuit games (MVP), a multi-vehicle cooperative ability to capture mobile targets, is becoming a hot research topic gradually. Although there are some achievements in the field of MVP in the open space environment, the urban area brings complicated road structures and restricted moving spaces as challenges to the resolution of MVP games. We define an Observation-constrained MVP (OMVP) problem in this paper and propose a Transformer-based Time and Team Reinforcement Learning scheme (T3OMVP) to address the problem. First, a new multi-vehicle pursuit model is constructed based on decentralized partially observed Markov decision processes (Dec-POMDP) to instantiate this problem. Second, by introducing and modifying the transformer-based observation sequence, QMIX is redefined to adapt to the complicated road structure, restricted moving spaces and constrained observations, so as to control vehicles to pursue the target combining the vehicle’s observations. Third, a multi-intersection urban environment is built to verify the proposed scheme. Extensive experimental results demonstrate that the proposed T3OMVP scheme achieves significant improvements relative to state-of-the-art QMIX approaches by 9.66%~106.25%. Code is available at https://github.com/pipihaiziguai/T3OMVP.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

The plate embedded with acoustic black hole (ABH) indentations is potential for structural vibration and noise control. This work focuses on the mid- and low-frequency performance of plates embedded with the array of ABH for energy focalization and vibration &amp; noise suppression. Plates embedded with two-dimensional ABHs are modelled with detailed Finite Element (FE) models, and the power flow method is introduced to analyze the energy propagation characteristics arising from ABH effect. Then the distribution of average vibration power density along ABH radius is studied. Next, the energy dissipation effects of the plate model embedded with ABH array with two types of damping layers are investigated. Finally, the sound pressure levels of the ABH structure are calculated and discussed. This work is helpful to understand the characteristics of plates embedded with ABH array in reducing vibration and noise radiation. Results show the tremendous potential of ABH array for vibration and noise control.

This paper introduces a new rotor design for the easy insertion and removal of the rotor windings. The shape of the rotor is optimized based on surrogate method in order to achieve the lowest power loss under the maximum power output. The performance of the new rotor is examined in 2-D finite element software and validated by experiments. This rotor shows good potentials for reducing the maintenance and repair costs of synchronous machines, making it suitable for manufacturers within the mass production markets such as gen-sets, steam turbines, wind power generators and hybrid electric vehicles.

The key to simulating soil erosion is to calculate the vegetation cover (C) factor. Methods that apply remote sensing to calculate C factor at regional scale cannot directly use the C factor formula. That is because the C factor formula is obtained by experiment, and needs the coverage ratio data of croplands, woodlands and grasslands at standard plot scale. In this paper, we present a C factor conversion method from a standard plot to a km-sized grid based on large sample theory and multi-scale remote sensing. Results show that: 1) Compared with the existing C factor formula, our method is based on the coverage ratio of croplands, woodlands and grasslands on a km-sized grid, takes the C factor formula obtained from the standard plot experiment and applies it to regional scale. This method improves the applicability of the C factor formula, and can satisfy the need to simulate soil erosion in large areas. 2) The vegetation coverage obtained by remote sensing interpretation is significantly consistent (paired samples t-test, t = −0.03, df = 0.12, 2-tail significance p < 0.05) and significantly correlated with the measured vegetation coverage. 3) The C factor of the study area is smaller in the middle, southern and northern regions, and larger in the eastern and western regions. The main reason for that is the distribution of woodlands, the Hunshandake and Horqin sandy lands and the valleys affected by human activities. 4) The method presented in this paper is more meticulous than the C factor method based on the vegetation index, improves the applicability of the C factor formula, and can be used to simulate soil erosion on large scale and provide strong support for regional soil and water conservation planning.

Thermal-expandable microcapsules (TEMs) for water-based coatings were synthesized with co-polymer of Acrylonitrile (AN) - Methyl methacrylate (MMA) - Ethylhexyl acrylate (EHA) - Divinylbenzene (DVB) as shell and toluene-p-sulfonyl hydrazide as core by suspension polymerization method. It was found that the microcapsules with desirable thermal expansion property and good heat stability could be obtained with a shell monomers composition of 70% AN /20% MMA /9% EHA /1% DVB. When 2% styrene-maleic acid copolymer (SMC) as emulsifier and 3% poly (vinyl pyrrolidone) (PVP) as dispersing agent were used, well defined spherical and more uniform microcapsules could be prepared. It was also found that when the shell/core mass ratio was 3:1, an encapsulation efficiency of ca. 94.5% could be achieved. Beyond this ratio, the increase of encapsulation efficiency reached a plateau. The 100 μm thickness film of water-based coating containing 5% microcapsules could be expanded to the thickness of 450 μm after exposed at 150 °C for 2 minutes. TG analysis revealed the mass loss start temperature of coating increased by more than 30 °C when 5% microcapsules were added to water-based coatings, which demonstrated the flame-retardant function of the coatings.

This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved.

Remote sensing imagery is of great significance for policy decisions, especially for disaster assessment and disaster relief. To ensure the privacy and inviolability of personal buildings, the information containing these buildings must be anonymized during the remote sensing mapping process. Traditional processing methods for these targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Deep learning provides a new direction for target hiding. Although the image inpainting method based on deep learning is faster than the manual method, the cost of training calculation is a disadvantage. And the element-wise product operation used in the model increases the risk of vanished or exploded gradients. We propose a Residual Attention Target Hiding (RATH) model for remote sensing target hiding based on deep learning. RATH uses residual attention modules to replace gated convolutions, reducing parameters and mitigating gradient issues. The residual attention module preserves gated convolution performance but provides an adjustable kernel size. RATH retains gated convolutions for dynamic feature selection and balances model depth and width. Furthermore, this paper modifies the contextual attention layer by adjusting the fusion process to enlarge the fusion patch size. Finally, we extend the edge-guided function to preserve the original target information and confound viewers. Ablation studies on an open dataset prove RATH’s efficiency for image inpainting and target hiding. RATH achieves state-of-the-art results with lower complexity. And it has the highest similarity for edge-guided target hiding. RATH enables robust, efficient target hiding for privacy protection in remote sensing imagery while balancing performance and complexity. Experiments show RATH's superiority over existing methods in hiding arbitrary-shaped targets.

Existing methods for building extraction from remotely sensed images strongly rely on aerial or satellite-based images with very high resolution, which are usually limited by spatiotemporally accessibility and cost. In contrast, relatively low-resolution images have better spatial and temporal availability but cannot directly contribute to fine- and/or high-resolution building extraction. In this paper, based on image super-resolution and segmentation techniques, we propose a two-stage framework (SRBuildingSeg) for achieving super-resolution (SR) building extraction using relatively low-resolution remotely sensed images. SRBuildingSeg can fully utilize inherent information from the given low-resolution images to achieve high-resolution building extraction. In contrast to the existing building extraction methods, we first utilize an internal pairs generation module (IPG) to obtain SR training datasets from the given low-resolution images and an edge-aware super-resolution module (EASR) to improve the perceptional features, following the dual-encoder building segmentation module (DES). Both qualitative and quantitative experimental results demonstrate that our proposed approach is capable of achieving high-resolution (e.g. 0.5 m) building extraction results at 2×, 4× and 8× SR. Our approach outperforms 8 other methods with respect to the extraction result of mean Intersection over Union (mIoU) values by a ratio of 9.38%, 8.20% and 7.89% with SR ratio factors of 2, 4, and 8, respectively. The results indicate that the edges and borders reconstructed in super-resolved images serve a pivotal role in subsequent building extraction and reveal the potential of the proposed approach to achieve super-resolution building extraction. Our code is available at https://github.com/xian1234/SRBuildSeg.

In this paper, a novel integrated high precision vacuum microelectronic accelerometer is put forward based on the theory of field emission, the accelerometer consists of sensitive structure and interface ASIC. The sensitive structure has a mass of a cathode cone tips array, a folded beam, an emitter electrode and a feedback electrode. The sensor is fabricated on a double side polished (1 0 0) N-type silicon wafer, the tips array of cathode are shaped by wet etching with HNA (HNO3, HF and CH3COOH) and metalized by TiW/Au thin film. The structure of sensor is released by ICP process finally. The interface ASIC was designed and fabricated based on the P-JFET high voltage bipolar process. The accelerometer is tested through static field rollover test, and the test results show the integrated vacuum microelectronic accelerometer has good performances, which sensitivity is 3.081V/g and non-linearity is 0.84% in the measuring range of −1g~1g.

Lirianthe delavayi has valuable ornamental and medicinal value, is an important economic tree, and has a long history of cultivation. As important regulatory molecules, miRNAs are involved in important physiological processes, such as the plant stress response, organ morphogenesis, hormone secretion, and signaling. In this study, based on miRNA sequencing analysis of wild and cultivated Lirianthe delavayi, we explored the differences in posttranscriptional regulation during the cultivation of Lirianthe delavayi from the aspect of miRNA molecular regulation. The results revealed the following: 1. A total of 365 miRNAs were sequenced and identified, and their first bases had obvious uracil (U) base preferences. Among them, 242 miRNAs were classified into 32 miRNA families; 2. Analysis of miRNA expression differences revealed that 39 miRNAs had significant expression differences between wild and cultivated populations; 3. Bioinformatics target gene prediction and target gene enrichment analysis of significantly differentially expressed miRNAs revealed that the target genes were significantly enriched in plant‒pathogen interactions, sphingolipid metabolism, defense responses, and ADP binding. 4. The plant‒pathogen interaction pathway involves seven differentially expressed miRNAs and 30 miRNA‒target gene regulatory pairs, which are involved mainly in pathogen signature molecule recognition and binding, signal transduction, and the regulation of disease resistance molecules or gene expression; Ath-MIR169g-p3_2ss7AG19GA, ath-MIR169g-p5_2ss7AG19GA, and ath-miR408-3p_L-3 are expressed only in wild population, and it is hypothesized that the domestication process from wild to cultivation species may be accompanied by the loss of disease resistance-related miRNAs. This study provides a reference for exploring the posttranscriptional-level regulatory mechanisms of adaptive changes in Lirianthe delavayi from wild to cultivated.

Remote sensing technology is crucial for accurate rooftop detection, benefiting urban planning, disaster management, and solar resource estimation. This study employs Efficient Interactive Segmentation (EISEG) to enhance the efficiency of remote sensing image labeling, with a particular focus on rooftop detection. It is necessary to use modern technology because traditional manual labelling methods are labor-intensive and complicated. The study introduces a novel framework on deep learning semantic segmentation models, facilitating an efficient approach to rooftop identification using high-resolution UAV remote sensing datasets. Large dataset of labeled UAV rooftop building images, in which each superpixel region is assigned a binary label indicating rooftop presence. Advanced methods including Asymmetric Neural Network (ANN), Dual At-tention Network (DANet), PP-LiteSeg, and Deeplab3 are implemented for automatic rooftop detection due to their higher performance and advanced architectures. These models are executed on the Baidu deep learning platform PaddlePaddle, generating initial rooftop segmentation maps crucial for estimating photovoltaic resources. The ANN model emerges with the highest accuracy at 96%, followed by DANet at 95.09%, PP-LiteSeg at 94.54%, and Deeplab3 at 81.61%. The outcomes presenting efficient models for automated rooftop identification, and demonstrating the continuous need for improving deep learning techniques in smart and sustainable cities.

Langya Henipavirus (LayV) is a new zoonotic Henipavirus reported in 2022. Patients infected by LayV show common cold symptoms, such as fever, fatigue, and cough. Non-fatal cases associated with this virus have been reported in Henan and Shandong provinces in China. Should human-to-human transmission occur, it has the potential to be a pandemic like SARS-CoV-2. LayV is an enveloped negative-sense RNA virus. Its polymerase (encoded by the L gene) is considered a conserved target shared within Henipavirus viruses, allowing for qPCR detection, in which primers play a pivotal role. For the development of a diagnostic kit, we designed three primer sets targeting the L gene and evaluated their detection of plasmids carrying part of the L gene. Primer sets 1 and 2 were found to be suitable for further sensitivity, specificity, and efficiency testing. Both primer sets were able to amplify PCR products in the presence of human saliva, and both the melt curve analysis and gel electrophoresis showed distinct peaks and bands, supporting the specificity of the qPCR primers. Based on standard curve analysis, both primers detected as low as approximately 1000 copies of the L gene. Given the specificity and robustness to work in the presence of saliva, the primers can be used for pandemic-preparedness in LayV detection.

Cathode materials play a key role in the development and application of lithium-ion batteries, but the unfavorable factors such as structural phase transformation and low conductivity in the cycling process restrict the further improvement of battery performance, so the development and modification of high-performance cathode materials is a current research hotspot. LiNixCoyMn1-x-yO2(x≥0.6), a high-nickel cathode material, has the advantages of high platform potential, high energy density and low cost, and is an ideal material to achieve the goal of 300 Wh kg-1 and above for batteries. However, its poor thermal stability, poor interface stability, safety and life cannot meet the requirements of current power batteries. In this paper, the research status of high-nickel cathode materials is introduced, including bulk doping and surface coating, and the modification method of doping and coating integration is also introduced. Finally, we put forward the prospect of the future development trend of high-nickel cathode materials.

Nano-titanium has excellent corrosion resistance and can be widely used in the field of corrosion resistant coatings. This paper introduces nano-weight titanium modified phenolic resin coatings and their anti-corrosion properties to explore the principle of nano-titanium modification and the mechanism of anti-corrosion to further develop more advanced corrosion resistant coatings. The article uses scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy and UV-Vis spectrophotometer to characterise the morphology and structure of the nano-titanium modified phenolic resin coatings and to determine the corrosion resistance properties of the modified phenolic resin coatings. The results show that the 4% nano-titanium modified phenolic resin coating, nano-titanium powder and phenolic resin will maximize the dispersion and combination, and the structure is good; nano-titanium grafted on phenolic resin, the successful preparation of nano-titanium modified phenolic resin; modified nano-titanium added to improve the coating's ability of UV absorption. The corrosion resistance of the coating is much better than that of the unmodified phenolic resin coating.

The present paper provides a new definition for dual spline curves in a geometric intuitive way based on adaptive curve refinement techniques. The dual spline is an implementation of the interpolatory subdivision scheme for curve modeling, which is comprised of polynomial segments of different degrees. Specially, the dual spline curves are mainly aims to solve the difficult geometry defeaturing problems in the existing computer-aided technology. Dual spline curves maintain various desirable properties of conventional curve modeling methods, such as local adaptive subdivision, high interpolation accuracy and convergence, continuous and discontinuous boundary approximation. By adding fictitious and intrinsic nodes inside or at the vertices of interpolation elements, the dual spline is flexible and convenient for approximating a set of ordered points or discrete segments. Combined with the Lagrange interpolation polynomial and meshless method, the proposed approach is capable of approximating the non-smooth boundary for geometry defeaturing. Experimental results are given to verify the validity, robustness, and accuracy of the proposed method.

Background: Exposure to inorganic arsenic (iAs) remains a global public health problem. The liver is the main target organ of arsenic, leading to arsenic-induced liver fibrosis. Autophagy is involved. Phosphatase and tensin homology deleted on chromosome ten (PTEN) may participate in arsenic-induced liver fibrosis by regulating autophagy, but the exact mechanisms remain unclear. We established a mouse model of arsenic poisoning through the drinking water, and a fibrosis model using the huma stellate cell (HSC) line LX-2, which was exposed to NaAsO₂ for 24h. HE and Masson staining was adopted to observe the degree of liver fibrosis. The cells were transfected using PTEN overexpression plasmid. Western blot and qRT-PCR were used to determine the levels of protein/mRNA expression. The in vivo results were confirmed in HSCs exposed to NaAsO₂, with changes suggesting fibrosis as seen in mice. NaAsO₂ upregulated the expression of the autophagic markers microtubule-associated protein light chain A/B (LC3), recombinant human autophagy effector protein (Beclin-1), hairy and enhancer of split homolog-1 (HES1), but downregulated PTEN. α-smooth muscle actin (α-SMA) expression was significantly upregulated in all NaAsO₂ groups. PTEN overexpression altered NaAsO₂-induced autophagy which LC3, Beclin-1 were downregulated. Notch1, HES1, α-SMA, and collagenⅠexpression were all downregulated in the NaAsO₂ groups. In conclusion, PTEN overexpression might decrease autophagy and inhibit fibrosis progression caused by this toxin. The NOTCH1/HES1 pathway is likely to be involved in this process. Most previous studies did not investigate PTEN and arsenic-induced liver fibrosis specifically. The present study highlights the importance of targeting PTEN for the management of arsenic exposure.

Three-dimensional reconstruction plays an important role in assisting doctors and surgeons in diagnosing bone defects’ healing progress. Common three-dimensional reconstruction methods include surface and volume rendering. As the focus is on the shape of the bone, volume rendering is omitted. Many improvements have been made on surface rendering methods like Marching Cubes and Marching Tetrahedra, but not many on working towards real-time or near real-time surface rendering for large medical images, and studying the effects of different parameter settings for the improvements. Hence, in this study, an attempt towards near real-time surface rendering for large medical images is made. Different parameter values are experimented on to study their effect on reconstruction accuracy, reconstruction and rendering time, and the number of vertices and faces. The proposed improvement involving three-dimensional data smoothing with convolution kernel Gaussian size 0.5 and mesh simplification reduction factor of 0.1, is the best parameter value combination for achieving a good balance between high reconstruction accuracy, low total execution time, and a low number of vertices and faces. It has successfully increased the reconstruction accuracy by 0.0235%, decreased the total execution time by 69.81%, and decreased the number of vertices and faces by 86.57% and 86.61% respectively.

There is currently a lack of pathologic data on the novel coronavirus (SARS-CoV-2) pneumonia, or COVID-19, from autopsy or biopsy. Two patients who recently underwent lung lobectomies for adenocarcinoma were retrospectively found to have had COVID-19 at the time of surgery. These two cases thus provide important first opportunities to study the pathology of COVID-19. Pathologic examinations revealed that, apart from the tumors, the lungs of both patients exhibited edema, proteinaceous exudate, focal reactive hyperplasia of pneumocytes with patchy inflammatory cellular infiltration, and multinucleated giant cells. Hyaline membranes were not prominent. Since both patients did not exhibit symptoms of pneumonia at the time of surgery, these changes likely represent an early phase of the lung pathology of COVID-19 pneumonia.