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In the present work, the corrosion behaviour of 2A97 Al-Cu-Li alloy with different thermomechanical treatments is investigated using electron microscopy and electrochemical measurements. The various thermomechanical treatments allowed the assessment of the individual and synergistic influence of local plastic deformation and precipitation on the corrosion susceptibility and mechanism of the alloy. It is found that in NaCl solution, corrosion of the alloys in T3 and T4 tempers occurs in the form of intergranular corrosion, which is closely associated with stored energy distribution. By contrast, the alloys in T6 and T8 tempers exhibit mainly intragranular corrosion due to high volume fractions of precipitates formed by artificial ageing.

BackgroundIn recent years, the development of telemedicine and eHealth services has led to the rapid worldwide growth of Internet hospitals, which played a significant role during the coronavirus disease 2019 (COVID-19) pandemic. However, little is known about the characteristics and safety of Internet hospital outpatient pharmacy services (IHOPSs), which represent a new model of pharmaceutical services.ObjectiveThis study aimed to reveal the comprehensive characteristics and safety of whole-course-based IHOPSs in a general tertiary hospital in western China.MethodsWe established a whole-course–based IHOPS model. A total of 373,936 online prescriptions placed from February 1, 2020 to January 31, 2023 were analyzed. These included information on patients, prescriptions, and deliveries; error rates for prescription reviews and medication dispensations; economic value; and degree of patient satisfaction. Over the course of the study, a total of 373,936 prescriptions representing 351,884 patients and 945,172 medications were delivered to 22 provinces, 5 autonomous regions, and 4 municipalities in China.ResultsIHOPSs saved patients more than 320,376 days (7,689,036 h) and RMB (Renminbi) ¥94.05 million in costs. The error rates of prescription review and dispensing were 0.0011% and 0.0008%, respectively. The infectious disease department (n = 63,903; 17.09%) ranked first in the number of prescriptions written for all three consecutive years. Of the 373,936 delivered prescriptions, 90.15% (337,104/373,936) were sent to Sichuan.ConclusionThe IHOPS was found to be efficient, convenient, and safe because it handled the challenge of precisely and safely delivering medications to patients on time during and to the end of the COVID-19 pandemic. It provided patients with safe and convenient pharmaceutical services unlimited by geography or time zones. Widespread use of this service could help alleviate pressure on offline pharmacists, giving them the time and resources to provide other professional services. Our model can therefore serve as a useful reference for policymakers to support the development of Internet pharmaceutical services. Further efforts are needed to regulate and standardize the management of this novel service.

Abstract Predicting the dynamic mechanical characteristics of rocks during freeze–thaw cycles (FTC) is crucial for comprehending the damage process of FTC and averting disasters in rock engineering in cold climates. Nevertheless, the conventional mathematical regression approach has constraints in accurately forecasting the dynamic compressive strength (DCS) of rocks under these circumstances. Hence, this study presents an optimized approach by merging the Coati Optimization Algorithm (COA) with Random Forest (RF) to offer a reliable solution for nondestructive prediction of DCS of rocks in cold locations. Initially, a database of the DCS of rocks after a series of FTC was constructed, and these data were obtained by performing the Split Hopkinson Pressure Bar Test on rocks after FTC. The main influencing factors of the test can be summarized into 10, and PCA was employed to decrease the number of dimensions in the dataset, and the microtests were used to explain the mechanism of the main influencing factors. Additionally, the Backpropagation Neural Network and RF are used to construct the prediction model of DCS of rock, and six optimization techniques were employed for optimizing the hyperparameters of the model. Ultimately, the 12 hybrid prediction models underwent a thorough and unbiased evaluation utilizing a range of evaluation indicators. The outcomes of the research concluded that the COA-RF model is most recommended for application in engineering practice, and it achieved the highest score of 10 in the combined score of the training and testing phases, with the lowest RMSE (4.570,8.769), the lowest MAE (3.155,5.653), the lowest MAPE (0.028,0.050), the highest R 2 (0.983,0.94).

Abstract The Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway serves as a paradigm for signal transduction from the extracellular environment to the nucleus. It plays a pivotal role in physiological functions, such as hematopoiesis, immune balance, tissue homeostasis, and surveillance against tumors. Dysregulation of this pathway may lead to various disease conditions such as immune deficiencies, autoimmune diseases, hematologic disorders, and cancer. Due to its critical role in maintaining human health and involvement in disease, extensive studies have been conducted on this pathway, ranging from basic research to medical applications. Advances in the structural biology of this pathway have enabled us to gain insights into how the signaling cascade operates at the molecular level, laying the groundwork for therapeutic development targeting this pathway. Various strategies have been developed to restore its normal function, with promising therapeutic potential. Enhanced comprehension of these molecular mechanisms, combined with advances in protein engineering methodologies, has allowed us to engineer cytokines with tailored properties for targeted therapeutic applications, thereby enhancing their efficiency and safety. In this review, we outline the structural basis that governs key nodes in this pathway, offering a comprehensive overview of the signal transduction process. Furthermore, we explore recent advances in cytokine engineering for therapeutic development in this pathway.

Given the characteristics of the flexible job-shop scheduling problem and the practical production of a given enterprise, a flexible job-shop scheduling model was proposed to minimize the maximum completion time. A novel algorithm was proposed to solve the model by integrating the dung beetle optimization algorithm and the simulated annealing algorithm. Algorithmic improvements include the design of a single-layer process encoding scheme with machine selection during decoding to ensure a higher level of the initial population. During population update, the dung beetle optimization algorithm was applied for optimization, followed by simulated annealing operations to enhance the convergence speed and solution quality of the algorithm. Through simulation experiments and comparisons with other algorithms, the effectiveness and superiority of the proposed algorithm were validated. In addition, the feasibility of the algorithm was tested through a real-world factory production case. In conclusion, the improvements made in this paper to the algorithms and scheduling models offer valuable insights into the educational aspects of job-shop scheduling. For instance, the single-layer encoding proposed herein simplifies the coding process, making it more accessible for beginners. Additionally, the accompanying decoding strategy yields relatively higher-quality initial solutions, facilitating subsequent optimization processes by accelerating convergence without compromising solution quality. Students were able to gain a better understanding of real workshop conditions through this project, going beyond the sole goal of minimizing completion time. They began to consider more complex situations in the machining process, such as machine breakdowns, changes in machining schedules, and the load on bottleneck machines and total machine load. This allowed students to have a holistic view of a complex production workshop. In terms of education, the project improved students' ability to consider practical aspects when solving problems and provided them with a way to solve problems.

A series of homogeneous granite specimens were prepared to investigate the Mode I fracture toughness (K_IC) using the cracked chevron-notched Brazilian disk (CCNBD) method and semicircular three-point bending (NSCB) method recommended by the International Society for Rock Mechanics (ISRM). A combination of acoustic emission (AE) and digital image correlation (DIC) was utilized to monitor the crack propagation and analyze the fracture modes at various test stages. The results indicated that the average value of Mode I fracture toughness (K_IC^-) of the CCNBD specimen was approximately 10% higher than that of the NSCB specimen. The coefficient of variation in the NSCB test was small, which could provide more stable result of Mode I fracture roughness. Compared to the CCNBD test, the failure mode of NSCB specimens was mainly tensile damage with instantaneous damage during the experimental process. Furthermore, the failure process of the NSCB test was mainly controlled by tensile fractures, which exhibited instantaneous failure. The CCNBD test was first controlled by tensile fractures and then by shear fractures when the peak was reached, exhibiting progressive failure. The failure mode and the process may be the main factors controlling the difference between the results of the NSCB and CCNBD tests. This work helps select appropriate methods to measure the Mode I rock fracture toughness.

The Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway functions as a central hub for transmitting signals from more than 50 cytokines, playing a pivotal role in maintaining hematopoiesis, immune balance, and tissue homeostasis. Dysregulation of this pathway has been implicated in various diseases, including immunodeficiency, autoimmune conditions, hematological disorders, and certain cancers. Proteins within this pathway have emerged as effective therapeutic targets for managing these conditions, with various approaches developed to modulate key nodes in the signaling process, spanning from receptor engagement to transcription factor activation. Following the success of JAK inhibitors such as tofacitinib for RA treatment and ruxolitinib for managing primary myelofibrosis, the pharmaceutical industry has obtained approvals for over 10 small molecule drugs targeting the JAK-STAT pathway and many more are at various stages of clinical trials. In this review, we consolidate key strategies employed in drug discovery efforts targeting this pathway, with the aim of contributing to the collective understanding of small molecule interventions in the context of JAK-STAT signaling. We aspire that our endeavors will contribute to advancing the development of innovative and efficacious treatments for a range of diseases linked to this pathway dysregulation.

With the advancement of terahertz band applications, extensive research has been conducted on terahertz devices. Terahertz band biosensors find widespread use in biomedical microdetection; however, predicting terahertz spectrum and designing structures pose complex and time-consuming challenges. This article proposes an efficient deep learning method for optimizing the design of terahertz metasurface biosensors. The method employs three neural networks, utilizing spectral response as an intermediary to effectively map customized performance indicators onto geometric structural parameters. Test results demonstrate that the proposed design scheme can generate suitable structural parameters based on the required frequency and bandwidth of the analyte. These output parameters were subsequently simulated and validated using electromagnetic simulation software, yielding results consistent with predictions. This method of using neural networks instead of electromagnetic simulation can be applied to the study of spectrum prediction and inverse design of terahertz devices, providing more possibilities for the future application of terahertz devices.

Consider a branching random walk with a mechanism of elimination. We assume that the underlying Galton-Watson process is supercritical, thus the branching random walk has a positive survival probability. A mechanism of elimination, which is called a barrier, is introduced to erase the particles who lie above $ ri+\varepsilon i^{\alpha} $ and all their descendants, where $ i $ presents the generation of the particles, $ \alpha > 1/3, \varepsilon\in{{\mathbb{R}}} $ and $ r $ is the asymptotic speed of the left-most position of the branching random walk. First we show that the particle system still has a positive survival probability after we introduce the barrier with $ \varepsilon > 0. $ Moreover, we show that the decay of the probability is faster than $ e^{-\beta'\varepsilon^{\beta}} $ as $ \varepsilon\downarrow 0 $, where $ \beta', \beta $ are two positive constants depending on the branching random walk and $ \alpha $. The result in the present paper extends a conclusion in Gantert et al. (2011) in some extent. Our proof also works for some time-inhomogeneous cases.

Plasma electrolytic oxidation (PEO) is normally carried out under conditions with electrolyte cooling. However, the effect of the temperature of the electrolytes on the PEO behavior and properties of the resulting coatings is seldom investigated. In this study, PEO of pure Al was carried out in a dilute aluminate electrolyte with the electrolyte temperature being controlled under low (~10–30 °C), medium (~40–50 °C) and high (~70–80 °C) temperature ranges, respectively. The morphology, microstructure, composition and phase component of the coatings fabricated under the different temperature ranges were analyzed by scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD). The corrosion resistances of the coatings were evaluated by electrochemical methods. The hardness of the coatings and substrate following the PEO treatment in the different electrolyte temperature ranges were also tested. It was found that a higher electrolyte temperature resulted in a higher growth rate and rougher coatings. Moreover, the α-Al2O3 content was reduced as the electrolyte temperature increased. The highest corrosion resistance was registered for the coating obtained under the lowest temperature range, whereas the corrosion resistance of the coating obtained under the highest temperature range was the worst. The higher growth rate under high electrolyte temperatures was associated with the increased kinetics of the PEO reactions. However, the temperature of the electrolyte should be controlled under a suitable range to ensure reasonable coating properties.

In recent years, jamming strategies for Synthetic Aperture Radar (SAR) pertaining to target detection and identification, such as the creation of false targets, electromagnetic (EM) deception, and signal spoofing, have been increasingly emphasized. Distinct from traditional SAR jamming approaches, the introduction of an innovative artificial material cloak in SAR target jamming presents augmented capabilities. These methods demonstrate a proficient redirection of incident EM waves in specific or arbitrary directions, effectively masking the vital information linked to critical targets. This study introduces a broadband SAR target jamming system employing an information metasurface that incorporates intelligent information processing algorithms in conjunction with a space-time-coding digital metasurface, endowing it with the capacity to adeptly modulate incident EM waves. This integration facilitates a versatile approach to jamming, enabling the deployment of multi-mode protective measures against critical targets. The conducted simulation and experiment results validate the system’s ability to adjustably produce EM deception and generate multiple false targets independently of the SAR system. The outcomes of this research significantly advance the practicality of SAR protection strategies, pushing the boundaries toward more dynamic, broadband, and controllable scenarios, thereby substantially improving the concealment of critical targets in highly sensitive conflict areas.

Abstract In Internet of Things scenarios, the problem of restricted energy and limited computation capability of user node usually exists. To address the problem, a multiple‐input‐multiple‐output full‐duplex multi‐hop relay simultaneous wireless information and power transfer (SWIPT) mobile‐edge computing (MEC) system is proposed in this paper, where energy harvesting model is non‐linear. With the aid of MEC and SWIPT, user node equipped with power splitting receiver can locally execute computation tasks or offload partial or all of it to access point associated with an MEC server by using its battery energy, and harvest energy to replenish its battery while downloading the computation results. In addition, the system introduces full‐duplex multi‐hop relay and non‐linear energy model to improve network coverage and model practical energy harvesting circuit. Aiming at minimising the system energy consumption, an energy efficient optimisation problem is formulated while satisfying the latency and energy constraints. Since the original problem is non‐linear and non‐convex, it is converted into two subproblems and successive convex approximation‐based algorithm and geometric programming‐based algorithm based alternating optimisation technique are adopted to solve them. Numerical results verify the superiority of the proposed optimisation scheme compared with other benchmark schemes.

The gap plasmon resonance can generate a local enhanced electric field and make the electromagnetic field energy mostly confined in the microfluidic, thereby increasing the interaction between the detection sample and terahertz wave. In this paper, a five-layer microfluidic terahertz biosensor based on gap plasmon resonance is presented. The simulation results show that the designed biosensor can realize a resonant absorption peak with near-perfect absorption at the frequency of 0.655 THz and high refractive index sensitivity of 191.3 GHz/RIU. In addition, the biosensor possesses the characteristics of polarization insensitivity and 50° incidence angle insensitivity due to the symmetry of the metal metasurface, which make the biosensor can be widely used in the biological label-free detection, medical trace element detection.

In the present work, a novel one-step plasma electrolytic oxidation (PEO) method is developed for the formation of PEO/Mg-Al layered double hydroxide (LDH) composite coating on AZ31 Mg alloy. Through the control of electrolyte concentration, a Mg-Al LDH layer was formed on the surface of the resultant PEO coating. The corrosion properties of the composite coating were evaluated by electrochemical analysis, hydrogen evolution measurement and salt spraying testing, which exhibited improved corrosion resistance due to the presence of the Mg-Al LDH layer. This work provides a new strategy to take advantage of alloying elements in Mg alloys in PEO treatment to enhance corrosion resistance.

Abstract Creating gradients of nanostructure on the surface has found broad applications such as enhanced optical spectroscopy, optical storage of information, and broadband solar energy harvesting. Here, a facile strategy is presented for fabricating gradient nanoparticle arrays with tunable size. It takes a ZnO:Ga microwire as the starting material, and the Ga3+ doping gradient along the microwire is induced by the high voltage applied. Such a doping gradient facilitates the formation of a temperature gradient in a Joule heating process. And this temperature gradient produced by this technique can be as high as 800 °C/mm, which could be later used for gradient annealing of thin metal films. After annealing, the thin metal films turn to gradient nanoparticle arrays. The obtained gradient nanoparticle arrays are confirmed effective in multi-wavelength surface enhanced Raman scattering enhancement.

Background: Amniotic fluid embolism (AFE) is an urgent, catastrophic obstetric complication, but not all medical settings are equipped to manage AFE. The purpose of this study is to summarize the experience of referral of women with AFE in order to save the lives of women and improve the prognosis. Methods: We retrospectively collected the demographic characteristics, delivery process, symptoms and test indicators at the onset of AFE, as well as the treatment status and outcomes after referral of women with AFE who were treated at our hospital from January 2015 to November 2022. We descriptively summarized and analyzed these data. Results: A total of 13 women with AFE transferred to our hospital were included in the study. After referral, 3 women (23.08%) eventually died. One of the deceased women presented with hypothermia (34.5 °C) at the time of referral, and all 3 fatalities had lactic acidosis (pH

Energy storage technology can effectively solve the problems caused by large-scale grid connection of renewable energy with volatility and uncertainty. Due to the high cost of the energy storage system, the research on capacity allocation of energy storage system has important theoretical and application value. In this paper, an optimization method for determining the capacity of energy storage system for smoothing the power output of renewable energy is proposed. First, based on the actual data of Ulanqab, the output characteristics of wind power and photovoltaic power generation are studied, and the K-means algorithm is used to select typical days. Then, the energy storage configuration model is built according to the objective function and constraints. Finally, genetic algorithm is used to solve the optimization model, obtain the corresponding parameters, and complete the configuration of energy storage capacity. Based on the results of renewable energy spectrum analysis, the minimum capacity of the energy storage system that meets the constraint of target power output volatility after compensation by the energy storage system can be optimized. The simulation results show that at 1 and 10 min, the flattened volatility is about 2% and 5%, while the actual penetration volatility is about 20% and 30%. The volatility of the optimized model is greatly reduced, which proves the effectiveness of the proposed strategy.

Browning is one of the main phenomena limiting the production of fresh-cut sweetpotatoes. This study investigated the anti-browning effect of citrus peel extracts and the key components and modes of action associated with browning in fresh-cut sweetpotatoes. Five different concentrations of citrus peel extract (1, 1.5, 2, 2.5 and 3 g/L) were selected to ensure storage quality; and the physical and chemical properties of fresh-cut sweetpotato slices were analysed. A concentration of 2 g/L of citrus peel extract significantly inhibited the browning of fresh-cut sweetpotatoes. The results showed that the browning index and textural characteristics of fresh-cut sweetpotatoes improved significantly after treatment with citrus peel extract; all the citrus peel extract solutions inhibited browning to some extent compared to the control. In addition; LC-IMS-QTOFMS analysis revealed a total of 1366 components in citrus peel extract; the evaluation of citrus peel extract monomeric components that prevent browning in fresh-cut sweetpotato indicated that the components with better anti-browning effects were citrulloside, hesperidin, sage secondary glycosides, isorhamnetin and quercetin. The molecular docking results suggest that citrullosides play a key role in the browning of fresh-cut sweetpotatoes. In this study, the optimum amount of citrus peel extract concentration was found to be 2 g/L.

The development of new fungicides is vital for safeguarding crops and ensuring sustainable agriculture. Building on our previous finding that 4-(3,4-dichloroisothiazole)-7-hydroxy coumarins can be used as fungicidal leads, 44 novel coumarin ester derivatives were designed and synthesized to evaluate whether esterification could enhance their fungicidal activity. In vitro fungicidal bioassays indicated that compound 2ai displayed good activity against Alternaria solani, Botrytis cinereal, Cercospora arachidicola, Physalospora piricola and Sclerotinia sclerotiorum, with an EC50 value ranging from 2.90 to 5.56 μg/mL, comparable to the lead compound 1a, with its EC50 value ranging from 1.92 to 9.37 μg/mL. In vivo bioassays demonstrated that compounds 1a, 2ar and 2bg showed comparable, excellent efficacy against Pseudoperonospora cubensis at a dose of 25 µg/mL. Our research shows that the esterification of 4-(3,4-dichloroisothiazole) 7-hydroxycoumarins results in a fungicidal activity equivalent to that of its lead compounds. Furthermore, our density functional theory (DFT) calculations and 3D-QSAR modeling provide a rational explanation of the structure–activity relationship and offer valuable insights to guide further molecular design.

ObjectiveThis retrospective study aims to explore the effect of silver nanoparticles with thermoplastic polyurethane (TPU/NS) on the rehabilitation of diabetic patients with open fracture of lower extremities.MethodsDiabetic patients (n = 98) with open fracture of lower extremities treated in our hospital were analyzed retrospectively from June 2015 to December 2021. TPU/NS nanocomposites were prepared for postoperative treatment of diabetic patients with open fracture of lower extremities. First, the cultured Staphylococcus aureus and Escherichia coli were used to test the antibacterial effect of TPU/NS dressing in vitro. After using TPU/NS dressing (observation group) and traditional dressing (control group), the inflammatory reaction, clinical treatment, functional rehabilitation, and adverse reactions in patients were compared.ResultsTPU/NS dressing effectively inhibited the growth of bacteria with a minimum inhibitory concentration of 2 μg/mL. The usage of TPU/NS dressing reduced the inflammatory reaction by reducing positive rate of bacteria after the dressing on the seventh day postoperatively. Besides, the times of dressing, stopping time of wound exudation, wound healing time, length of hospital stay, and VAS score in the observation group were lower than those in the control group; the incidence of adverse reactions after treatment was lower in the observation group as compared with the control group (17.07% vs. 35.09%). Meanwhile, the functional rehabilitation and life quality of patients in the observation group were better TPU/NS dressing treatment.ConclusionTPU/NS dressing has the function of promoting the postoperative recovery of patients by inhibiting the bacterial infection of the wound, thus improving the limb function and life quality. As a result, there was a tremendous potential to apply the constructed TPU/NS membrane to diabetic patients with open fractures, especially those with soft tissue injury.

Abstract Background Coronavirus disease 2019 (COVID-19) has become a global pandemic. Studies showed COVID-19 affected not only the lung but also other organs. In this study, we aimed to explore the cardiac damage in patients with COVID-19. Methods We collected data of 100 patients diagnosed as severe type of COVID-19 from February 8 to April 10, 2020, including demographics, illness history, physical examination, laboratory test, and treatment. In-hospital mortality were observed. Cardiac damage was defined as plasma hypersensitive troponin I (hsTnI) over 34.2 pg/ml and/or N-terminal-pro brain natriuretic peptide (NTproBNP) above 450 pg/ml at the age

New targeted chemotherapy agents greatly improved five-year survival in NSCLC patients, but which were susceptible to drug resistance. NVP-AUY922, terminated in phase II clinical trials, exhibited promising anti-NSCLC (non-small-cell lung cancer) activity targeting to Hsp90N (heat shock protein), which demonstrated advantages in overcoming drug resistance as a broad-spectrum anti-cancer target. It was expected to develop novel anti-NSCLC drugs to overcome drug resistance by the structural optimization of NVP-AUY922. However, the absence of high-resolution complex crystal structure of Hsp90N-NVP-AUY922 blocked the way. Herein, 1.59 Å-resolution complex crystal structure of Hsp90N-NVP-AUY922 (PDB ID 6LTI) was successfully determined by X-ray diffraction. Meanwhile, there was a strong binding capability between NVP-AUY922 and its target Hsp90N verified by TSA (ΔTm, −15.56 ± 1.78°C) and ITC (Kd, 5.10 ± 2.10 nM). Results by the complex crystal structure, TSA and ITC verified that NVP-AUY922 well accommodated in the ATP-binding pocket of Hsp90N to disable the molecular chaperone activity of Hsp90. Therefore, NVP-AUY922 exhibited approving inhibitory activity on NSCLC cell line H1299 (IC50, 2.85 ± 0.06 μM) by inhibiting cell proliferation, inducing cell cycle arrest and promoting cell apoptosis. At the basis of the complex crystal structure and molecular interaction analysis, thirty-two new NVP-AUY922 derivatives were further designed, and among which twenty-eight new ones display enhanced binding force with Hsp90N by molecular docking evaluation. The results would promote anti-NSCLC new drug development to overcome drug resistance based on the lead compound NVP-AUY922.

This paper presents a small and efficient model for predicting NOx emissions from coal-fired boilers. The raw data collected are processed by the min–max scale method and converted into a multivariate time series. The overall model’s architecture is mainly based on building blocks consisting of separable convolutional neural networks and efficient channel attention (ECA) modules. The experimental results show that the model can learn good representations from sufficient data covering different operation conditions. These results also suggest that ECA modules can improve the model’s performance. The comparative study shows our model’s strong performance compared to other NOx prediction models. Then, we demonstrate the effectiveness of the model proposed in this paper in terms of predicting NOx emissions.

As the classic branching process, the Galton-Watson process has obtained intensive attentions in the past decades. However, this model has two idealized assumptions–discrete states and time-homogeneity. In the present paper, we consider a branching process with continuous states, and for any given n∈N, the branching law of every particle in generation n is determined by the population size of generation n. We consider the case that the process is extinct with Probability 1 since in this case the process will be substantially different from the size-dependent branching process with discrete states. We give the extinction rate in the sense of L2 and almost surely by the form of harmonic moments, that is to say, we show how fast {Zn−1} grows under a group of sufficient conditions. From the result of the present paper, we observe that the extinction rate will be determined by an asymptotic behavior of the mean of the branching law. The results obtained in this paper have the more superiority than the counterpart from the existing literature.

Since December 2019, COVID-19 has aroused global attention. Studies show the link between obesity and severe outcome of influenza and COVID-19. Thus, we aimed to compare the impacts of obesity on the severity and mortality of influenza and COVID-19 by performing a meta-analysis. A systematic search was performed in MEDLINE, EMASE, ClinicalTrials.gov, and Web of Science from January 2009 to July 2020. The protocol was registered onto PROSPERO (CRD42020201461). After selection, 46 studies were included in this meta-analysis. The pooled odds ratios (ORs) with 95% confidence intervals (CIs) were analyzed. We found obesity was a risk factor for the severity and mortality of influenza (ORsevere outcome = 1.56, CI: 1.28-1.90; ORmortality = 1.99, CI: 1.15-3.46). For COVID-19, obesity was a significant risk factor only for severe outcome (OR = 2.07, CI: 1.53-2.81) but not for mortality (OR = 1.57, CI: 0.85-2.90). Compared with obesity, morbid obesity was linked with a higher risk for the severity and mortality of both influenza (OR = 1.40, CI: 1.10-1.79) and COVID-19 (OR = 3.76, CI: 2.67-5.28). Thus, obesity should be recommended as a risk factor for the prognosis assessment of COVID-19. Special monitoring and earlier treatment should be implemented in patients with obesity and COVID-19.

Three yeast strains, namely Cryptococcus albidus (Ca63), Cryptococcus albidus (Ca64), and Candida parapsilosis (Yett1006), and their combinations, including single yeast agent, two combined yeast strains, single yeast agent + NaHCO3, single yeast agent + chitosan, single yeast agent + ascorbic acid, and single yeast agent + konjac powder, were evaluated for their activity against Botrytis cinerea, the most economically important fungal pathogens causing postharvest disease of snap beans. In in vitro tests, no inhibition zone was observed in dual cultures of three yeast strains and B. cinerea. The mycelial growth inhibition rates of B. cinerea for Ca63, Ca64, and Yett1006 were 97%, 95%, and 97%, respectively. In in vivo tests, the optimal combination of the lowest disease index of snap beans with B. cinerea was Ca63 + Ca64, with a preventing effect of 75%. The decay rate and rust spots index of Ca64 + ascorbic acid combination were 25% and 20%, respectively, which were the lowest. The activities of defense-related enzymes increased, while malondialdehyde (MDA) content was suppressed in snap beans after different treatments. Our results highlight the potential of the three yeast strains and their combinations as new nonpolluting agents for the integrated control of B. cinerea on snap beans.

20(S)-Ginsenoside Rg3 (20(S)-Rg3) has been shown to induce apoptosis by interfering with several signaling pathways. Furthermore, it has been reported to have anticancer and antidiabetic effects. In order to detect the protective effect of 20(S)-Rg3 on diabetic kidney disease (DKD), diabetic rat models which were established by administering high-sugar, high-fat diet combined with intraperitoneal injection of streptozotocin (STZ), and age-matched wild-type (WT) rat were given 20(S)-Rg3 for 12 weeks, with three groups: control group (normal adult rats with saline), diabetic group (diabetic rats with saline), and 20(S)-Rg3 treatment group (diabetic rats with 20(S)-Rg3 (10 mg/kg body weight/day)). The biochemical indicators and the changes in glomerular basement membrane and mesangial matrix were detected. TUNEL staining was used to detect glomerular and renal tubular cell apoptosis. Immunohistochemical staining was used to detect the expression of fibrosis factors and inflammation factors in rat kidney tissues. Through periodic acid-Schiff staining, we observed that the change in renal histology was improved and renal tubular epithelial cell apoptosis decreased significantly by treatment with 20(S)-Rg3. Plus, the urine protein decreased in the rats with the 20(S)-Rg3 treatment. Fasting blood glucose, creatinine, total cholesterol, and triglyceride levels in the 20(S)-Rg3 treatment group were all lower than those in the diabetic group. Mechanistically, 20(S)-Rg3 dramatically downregulated the expression of TGF-β1, NF-κB65, and TNF-α in the kidney. These resulted in a significant prevention of renal damage from the inflammation. The results of the current study suggest that 20(S)-Rg3 could potentially be used as a novel treatment against DKD.

Objectives. To investigate the risk factors for cognitive impairment in Chinese type 2 diabetes mellitus (T2DM) patients of advanced age and to identify effective biomarkers of mild cognitive impairment (MCI) in these patients. Methods. Chinese T2DM patients (n=120) aged 50–70 years were divided into groups with impaired (mild, moderate, and severe) and normal cognitive function based on Montreal Cognitive Assessment and Mini-Mental State Examination scores. Data regarding demographic characteristics, clinical features of diabetes, biochemical markers, and metabolomics were collected. Results. Age, educational level, duration of diabetes, fasting blood glucose (FBG), HbA1c, total cholesterol (TC), triglyceride (TG), and 24-hour urine protein were significantly associated with cognitive impairment in T2DM patients of advanced age. The severity of fundus retinopathy and the incidence of macrovascular disease also differed significantly among the groups (P

The differential diagnosis of syndrome of inappropriate antidiuretic hormone secretion (SIADH) and cerebral salt-wasting syndrome (CSWS) in patients with neurological disorders has been a perplexing clinical controversy. The purpose of this review is to summarize the characteristics and risk factors of patients with different types of neurological disorders complicated by hyponatremia (HN) and review various methods to distinguish SIADH from CSWS. Common neurological disorders with high rates of HN include subarachnoid hemorrhage (SAH), traumatic brain injuries, stroke, cerebral tumors, central nervous system (CNS) infections, and Guillain-Barré syndrome (GBS), which have their own characteristics. Extracellular volume (ECV) status of patients is a key point to differentiate SIADH and CSWS, and a comprehensive assessment of relevant ECV indicators may be useful in differentiating these two syndromes. Besides, instead of monitoring the urinary sodium excretion, more attention should be paid to the total mass balance, including Na+, K+, Cl−, and extracellular fluid. Furthermore, the dynamic detection of fractional excretions (FE) of urate before and after correction of HN and a short-term infusion of isotonic saline solution may be useful in identifying the etiology of HN. As for brain natriuretic peptide (BNP) or N-terminal prohormone of BNP (NT-proBNP), more prospective studies and strong evidence are needed to determine whether there is a pertinent and clear difference between SIADH and CSWS.

The induced draft (ID) fan is an important piece of auxiliary equipment in coal-fired power plants. Early fault detection of the ID fan can provide predictive maintenance and reduce unscheduled shutdowns, thus improving the reliability of the power generation. In this study, an adaptive model was developed to achieve the early fault detection of ID fans. First, a non-parametric monitoring model was constructed to describe the normal operating characteristics with the multivariate state estimation technique (MSET). A similarity index representing operation status was defined according to the prediction deviations to produce warnings of early faults. To deal with the model accuracy degradation because of variant condition operation of the ID fan, an adaptive strategy was proposed by using the samples with a high data quality index (DQI) to manage the memory matrix and update the MSET model, thereby improving the fault detection results. The proposed method was applied to a 300 MW coal-fired power plant to achieve the early fault detection of an ID fan. In addition, fault detection by using the model without an update was also compared. Results show that the update strategy can greatly improve the MSET model accuracy when predicting normal operations of the ID fan; accordingly, the fault can be detected more than 4 h earlier by using the strategy with the adaptive update when compared to the model without an update.

Background: Since early December 2019, coronavirus disease 2019 (COVID-19) has emerged as a global pandemic and public health crisis. This study aims to explore the relationship between cardiac injury and inflammatory biomarkers in patients with severe COVID-19. Methods: We collected data on 91 patients with a confirmed diagnosis of severe COVID-19 from February 8 to March 31, 2020. Demographic characteristics, clinical data, and in-hospital outcomes were compared. The relationship between cardiac injury and inflammatory biomarkers was analyzed. Logistic regression was used to explore the independent risk factors for cardiac injury. Results: The mean age of all patients was 61 years±14 years. About half of the patients were male. Hypertension and coronary heart disease were more common in the cardiac injury group. The levels of inflammatory biomarkers in patients who experienced cardiac injury were generally higher than the levels of those without cardiac injury, including interleukin-6, interleukin-2 receptor (IL-2R), procalcitonin, and high-sensitivity C-reactive protein. There were positive correlations between the levels of high-sensitivity troponin I and N-terminal prohormone of brain natriuretic peptide and the levels of inflammatory biomarkers. Logistic regression shows that IL-2R (odds ratio 1.001, 95% confidence interval 1.000–1.002, P=0.045) and comorbidities (odds ratio 4.909, 95% confidence interval 1.231–19.579, P=0.024) are independent risk factors for cardiac injury in patients with severe COVID-19. Conclusion: High levels of inflammatory biomarkers are associated with higher risk of cardiac injury in patients with severe COVID-19. IL-2R and comorbidities are predictors of cardiac injury.

We reported the acceleration of skin wound healing in diabetic rats by repeated exposure to low-dose radiation (LDR). Here, we explored whether the wound healing could be further improved when LDR was combined with a topical application of basic fibroblast growth factor (bFGF) or zinc. Wounds were established on the backs of type 1 diabetic rats induced by a single injection of streptozotocin. Rats were treated daily with normal saline (Diabetes), LDR, bFGF, zinc, or combined 3 treatments for 5 consecutive days with a 2-day break between each consecutive 5-day treatment. Changes in wound size, histopathology, and microvessel density were assessed on days 5, 10, and 15, respectively, once treatment is started. All treatment regimens significantly accelerated skin wound healing, tissue remodeling, and new vessel formation compared to diabetes group. However, the combined LDR plus bFGF and zinc provided a better beneficial effect on wound healing than either one of these treatments alone. Further, we found that the effects of LDR and bFGF were similar, whereas zinc alone induced a weaker response. Our results suggest that whole-body LDR plus the topical application of bFGF and zinc can further accelerate wound healing in diabetic rats.

As a potent bronchodilator, the anti-inflammatory effects of tiotropium and its interaction with budesonide against cadmium-induced acute pulmonary inflammation were investigated. Compared to values obtained in rats exposed to cadmium, cytological analysis indicated a significant decrease of total cell and neutrophil counts and protein concentration in bronchoalveolar lavage fluid (BALF) in rats pretreated with tiotropium (70μg/15ml or 350μg/15ml). Zymographic tests showed a decrease of MMP-2 activity in BALF in rats pretreated only with high concentration of tiotropium. Histological examination revealed a significant decrease of the severity and extent of inflammatory lung injuries in rats pretreated with both tested concentrations of tiotropium. Though tiotropium (70μg/15ml) or budesonide (250μg/15ml) could not reduce cadmium-induced bronchial hyper-responsiveness, their combination significantly decreased bronchial contractile response to methacholine. These two drugs separately decreased the neutrophil number and protein concentration in BALF but no significant interaction was observed when both drugs were combined. Although no inhibitory effects on MMP-2 and MMP-9 was observed in rats pretreated with budesonide alone, the combination with the ineffective dose of tiotropium induced a significant reduction on these parameters. The inhibitory effect of tiotropium on lung injuries was not influenced by budesonide which alone induced a limited action on the severity and extent of inflammatory sites. Our findings show that tiotropium exerts anti-inflammatory effects on cadmium-induced acute neutrophilic pulmonary inflammation. The combination of tiotropium with budesonide inhibits cadmium-induced inflammatory injuries with a synergistic interaction on MMP-2 and MMP-9 activity and airway hyper-responsiveness.

Metabolic diseases, especially diabetes mellitus, have become global health issues. The etiology of diabetes mellitus can be attributed to genetic and/or environmental factors. Current evidence suggests the association of gut microbiota with metabolic diseases. However, the effects of glucose-lowering agents on gut microbiota are poorly understood. Several studies revealed that these agents affect the composition and diversity of gut microbiota and consequently improve glucose metabolism and energy balance. Possible underlying mechanisms include affecting gene expression, lowering levels of inflammatory cytokines, and regulating the production of short-chain fatty acids. In addition, gut microbiota may alleviate adverse effects caused by glucose-lowering agents, and this can be especially beneficial in diabetic patients who experience severe gastrointestinal side effects and have to discontinue these agents. In conclusion, gut microbiota may provide a novel viewpoint for the treatment of patients with diabetes mellitus.

Under the dynamic working conditions of a star sensor, motion blur of the star will appear due to its energy dispersion during imaging, leading to the degradation of the star centroid accuracy and attitude accuracy of the star sensor. To address this, a restoration method of a blurred star image for a star sensor under dynamic conditions is presented in this paper. First, a kinematic model of the star centroid and the degradation function of blurred star image under different conditions are analyzed. Then, an improved curvature filtering method based on energy function is proposed to remove the noise and improve the signal-to-noise ratio of the star image. Finally, the Richardson Lucy algorithm is used and the termination condition of the iterative equation is established by using the star centroid coordinates in three consecutive frames of restored images to ensure the restoration effect of the blurred star image and the accuracy of the star centroid coordinates. Under the dynamic condition of 0~4°/s, the proposed algorithm can effectively improve the signal-to-noise ratio of a blurred star image and maintain an error of the star centroid coordinates that is less than 0.1 pixels, which meets the requirement for high centroid accuracy.

Road detection is a crucial research topic in computer vision, especially in the framework of autonomous driving and driver assistance. Moreover, it is an invaluable step for other tasks such as collision warning, vehicle detection, and pedestrian detection. Nevertheless, road detection remains challenging due to the presence of continuously changing backgrounds, varying illumination (shadows and highlights), variability of road appearance (size, shape, and color), and differently shaped objects (lane markings, vehicles, and pedestrians). In this paper, we propose an algorithm fusing appearance and prior cues for road detection. Firstly, input images are preprocessed by simple linear iterative clustering (SLIC), morphological processing, and illuminant invariant transformation to get superpixels and remove lane markings, shadows, and highlights. Then, we design a novel seed superpixels selection method and model appearance cues using the Gaussian mixture model with the selected seed superpixels. Next, we propose to construct a road geometric prior model offline, which can provide statistical descriptions and relevant information to infer the location of the road surface. Finally, a Bayesian framework is used to fuse appearance and prior cues. Experiments are carried out on the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) road benchmark where the proposed algorithm shows compelling performance and achieves state-of-the-art results among the model-based methods.

A novel carboxymethyl cellulose (CMC)-supported graphene oxide aerogel (CGOA) was fabricated from a cost-effective and abundant bituminous coal by a mild hydrothermal process and freeze-drying treatment. Such an aerogel has cross-linked graphene oxide layers supported by CMC, and therefore, displays high mechanical strength while having ultra-low density (8.257 mg·cm−3). The CGOA has a 3D interconnected porous structure, beneficial graphene framework defects and abundant oxygen-containing functional groups, which offer favorable diffusion channels and effective adsorption sites for the transport and adsorption of dye molecules. The adsorption performance of rhodamine B by an optimized CGOA shows a maximum monolayer adsorption capacity of 312.50 mg·g−1, as determined by Langmuir isotherm parameters. This CGOA exhibited a better adsorption efficiency (99.99%) in alkaline solution, and satisfactory stability (90.60%) after three cycles. In addition, adsorption experiments on various dyes have revealed that CGOA have better adsorption capacities for cationic dyes than anionic dyes.

In this work, the crystallization behaviors, such as degree of crystallinity and crystalline thickness of poly(ε-caprolactone) (PCL) matrix with the incorporation of graphene oxide (GO) and their evolution with time were examined in order to better understand the influences of residual groups of GO on the semi-crystalline polyester. The results showed that the residual strong oxidizing debris on the GO surface could induce the degradation of amorphous parts in PCL matrix. Moreover, the increasing degree of crystallinity and almost constant crystalline thickness implies that oxidative degradation cannot degrade the crystal structure of PCL matrix.

Cultural relics represent national or even global resources of inestimable value. How to efficiently manage and preserve these cultural relics is a vitally important issue. To achieve this goal, this study proposed, designed, and implemented an RFID and Sensor Web–enabled smart cultural relics management system (SCRMS). In this system, active photovoltaic subtle energy-powered Radio Frequency Identification (RFID) is used for long-range contactless identification and lifecycle management of cultural relics during their storage and circulation. In addition, different types of ambient sensors are integrated with the RFID tags and deployed around cultural relics to monitor their environmental parameters, helping to ensure that they remain in good condition. An Android-based smart mobile application, as middleware, is used in collaboration with RFID readers to collect information and provide convenient management for the circulation of cultural relics. Moreover, multiple sensing techniques are taken advantage of simultaneously for preservation of cultural relics. The proposed system was successfully applied to a museum in the Yongding District, Fujian Province, China, demonstrating its feasibility and advantages for smart and efficient management and preservation of cultural relics.

BACKGROUND: Our previous research and other studies with radiotracers showed evidence of a centripetal drainage pathway, separate from blood or lymphatic vessels, that can be visualized when a small amount of low molecular weight tracer is injected subcutaneously into a given region on skin of humans. In order to further characterize this interesting biological phenomenon, animal experiments are designed to elucidate histological and physiologic characteristics of these visualized pathways. METHODS: Multiple tracers are injected subcutaneously into an acupuncture point of KI3 to visualize centripetal pathways by magnetic resonance imaging or fluorescein photography in 85 healthy rabbits. The pathways are compared with venography and indirect lymphangiography. Fluid flow through the pathways is observed by methods of altering their hydrated state, hydrolyzing by different collagenases, and histology is elucidated by optical, fluorescein and electron microscopy. RESULTS: Histological and magnetic imaging examinations of these visualized pathways show they consist of perivenous loose connective tissues. As evidenced by examinations of tracers' uptake, they appear to function as a draining pathway for free interstitial fluid. Fluorescein sodium from KI3 is found in the pathways of hind limbs and segments of the small intestines, partial pulmonary veins and results in pericardial effusion, suggesting systematical involvement of this perivenous pathway. The hydraulic conductivity of these pathways can be compromised by the collapse of their fiber-rich beds hydrolyzed by either of collagenase type I, III, IV or V. CONCLUSIONS: The identification of pathways comprising perivenous loose connective tissues with a high hydraulic conductivity draining interstitial fluid in hind limbs of a mammal suggests a potential drainage system complementary to vascular circulations. These findings may provide new insights into a systematically distributed collagenous connective tissue with a circulatory function and their potential relevance to the nature of acupuncture meridians.

Background: Colistin is commonly used as a last-resort antibiotic for multidrug resistance (MDR) bacterial infections. The emergence of colistin-resistant (CL-R) Salmonella has become a significant public health concern. However, the prevalence of CL-R Salmonella in Guizhou province remains unknown. Therefore, it is necessary to monitor CL-R Salmonella in Guizhou and systematically elucidate their characteristics-related resistance, virulence, and molecular epidemiology to develop effective public health strategies against resistant pathogens. Methods: The CL-R Salmonella isolates were identified from 933 Salmonella isolates by antimicrobial resistance testing. To further evaluate the molecular epidemiology, the CL-R Salmonella isolates underwent whole-genome sequencing (WGS) analysis followed by bioinformatic analysis. Results: A total of 43 CL-R isolates (4.6%) were identified from 933 Salmonella isolates, of which 39 isolates being MDR (resistance to three or more classes of antimicrobials). WGS analysis revealed 34 antibiotic resistance genes (ARGs), and point mutations in the gyrA gene (D87Y and D87G) were identified in all 43 CL-R isolates. Only one isolate carried the mcr-1.1 gene, a known colistin resistance. All CL-R isolates were found to carry multidrug efflux pumps. Furthermore, the most common resistance gene was aac(6′)-ly (40 out of 43), followed by blaTEM-1 (39 out of 43). The majority of CL-R isolates contained the virulence factor spvB and a notable diversity in other virulence factors with varied functions. Core genome multilocus sequence typing (cgMLST) revealed that 43 CL-R Salmonella isolates were divided into 19 cgSTs, with cgST179151 (10 out of 43) being the most prevalent. Additionally, the CL-R Salmonella isolates exhibited genetic similarities with human Salmonella isolates from Poland, Canada, and Zhejiang province. Among the 42 CL-R isolates lacking markers for CL-R, 12 single-nucleotide variations (SNVs) were observed in 24 isolates using genome-wide association study (GWAS) analysis, which was possibly associated with colistin resistance. Conclusion: This study revealed that the majority of CL-R Salmonella isolates in Guizhou province exhibited MDR, with complex resistance mechanisms, representing a significant public health challenge. The genetic similarities between isolates from Guizhou and other regions suggested the possibility of international transmission or shared reservoirs of resistance. These results highlighted the urgent need for enhanced surveillance and effective public health strategies to address the risks posed by these pathogens in Guizhou. [ABSTRACT FROM AUTHOR]