Search

Abstract Breast cancer has surpassed lung cancer as the most common type of malignancy worldwide. Treatments for breast cancer include surgery, chemotherapy, radiotherapy, targeted therapy, endocrine therapy, immunotherapy, and hyperthermia. Radiotherapy plays an important role in breast cancer treatment. Patients with early breast cancer can have longer survival after combined treatment, but cardiotoxicity caused by radiotherapy may affect long‐term prognosis. This article reviews cardiac damage caused by radiotherapy in breast cancer.

Abstract A precise quantification of energy gap for a molecular semiconductor is crucial. However, there has always been a lack of a suitable method which results in an inaccurate measurement. In this research, a three-terminal vertical structure (Al/AlO X /Au/ molecular semiconductor/Al), named hot electron transistor has been designed to be the most powerful method for energy gap determination. By analysing the IC-hot–VEB curves, the electron injected barrier and hole injected barrier can be extracted. In combination of the both, the energy gap of four objects, including PBDB-T-2Cl, C60, PTCDA, and Alq3, has been determined finally.

Due to the large-scale integration of renewable energy and inevitable disturbing events (including natural disasters and deliberate attacks), the invulnerability of power grids is facing a great challenge, thus the security criterion is demanded to upgrade from N−1 to N−k. However, with the increasing of k and the expanding of network scale, resource consumption of network expansion shows an exponential explosion. Therefore, it is necessary to improve the invulnerability of power grids from a new perspective. In this paper, the definition of nodal N−k security criterion is proposed, which divides buses into different security levels based on realistic demand, and decouples the security analysis from the system level to individual nodes. A two-stage robust optimization model is established, cooperating with the nodal N−k security criterion, the load demand of critical buses could be guaranteed. Moreover, the proposed discrepant upgrade scheme is flexible and has strong generalization performance, where enhanced buses and security levels can be selected independently based on the preferences of decision-makers. The effectiveness and efficiency of the proposal have been demonstrated in 5 cases, i.e., the IEEE 9-bus, 24-bus, 57-bus, 118-bus systems and an actual test system in India.

AimsClostridium perfringens is one of the major anaerobic pathogen causing food poisoning and animal enteritis. With the rise of antibiotic resistance and the restrictions of the use of antibiotic growth promoting agents (AGPs) in farming, Clostridium enteritis and food contamination have become more common. It is time-consuming and labor-intensive to confirm the detection by standard culture methods, and it is necessary to develop on-site rapid detection tools. In this study, a combination of recombinase polymerase amplification (RPA) and lateral flow biosensor (LFB) was used to visually detect C. perfringens in chicken meat and milk.Methods and resultsTwo sets of primers were designed for the plc gene of C. perfringens, and the amplification efficiency and specificity of the primers. Selection of primers produces an amplified fragment on which the probe is designed. The probe was combined with the lateral flow biosensor (LFB). The reaction time and temperature of RPA-LFB assay were optimized, and the sensitivity of the assay was assessed. Several common foodborne pathogens were selected to test the specificity of the established method. Chicken and milk samples were artificially inoculated with different concentrations (1 × 102 CFU/mL to 1 × 106 CFU/mL) of C. perfringens, and the detection efficiency of RPA-LFB method and PCR method was compared. RPA-LFB can be completed in 20 min and the results can be read visually by the LFB test strips. The RPA-LFB has acceptable specificity and the lowest detection limit of 100 pg./μL for nucleic acid samples. It was able to stably detect C. perfringens contamination in chicken and milk at the lowest concentration of 1 × 104 CFU/mL and 1 × 103 CFU/mL, respectively.ConclusionIn conclusion, RPA-LFB is specific and sensitive. It is a rapid, simple and easy-to-visualize method for the detection of C. perfringens in food and is suitable for use in field testing work.

Abstract The Sansha Yongle Blue Hole (SYBH) is the world’s deepest marine blue hole with unique physicochemical characteristics. However, our knowledge of the biodiversity and community structure in SYBH sediments remains limited, as past studies have mostly focused on microbial communities in the water column. Here, we collected sediment samples from the aerobic zone (3.1 to 38.6 m) and the deep anaerobic zone (150 m, 300 m) of the SYBH and extracted DNA to characterize the archaeal, bacterial, and eukaryotic communities inhabiting these sediments. Our results showed that the archaeal and bacterial communities were dominated by Thaumarchaeota and Proteobacteria, respectively. The dominant taxa of eukaryotes in different sites varied greatly, mainly including Phaeophyceae, Annelida, Diatomea and Arthropoda. All three examined domains showed clear vertical distributions and significant differences in community composition between the aerobic and anaerobic zones. Sulfide played a prominent role in structuring the three domains, followed by salinity, nitrous oxide, pH, temperature and dissolved oxygen, all of which were positively correlated with the turnover component, the main contributor to beta diversity. Neutral community model revealed that stochastic processes contributed to more than half of the community variations across the three domains. Co-occurrence network showed an equal number of positive and negative interactions in the archaeal network, while positive interactions accounted for ~ 80% in the bacterial and eukaryotic networks. Our findings reveal the ecological features of prokaryotes and eukaryotes in SYBH sediments and shed new light on community dynamics and survival strategies in the special environment of marine blue holes.

The rapid development of mobile communication devices has brought challenges to wireless networks, where data packets are able to organize and maintain local area networks more freely without the constraints of wired devices. Scholars have developed diverse network protocols on how to ensure data transmission while maintaining its self-organizational nature. However, it is difficult for traditional network protocols to meet the needs of increasingly complex networks. In order to solve the problem that the better node set may not be selected when selecting the node set responsible for forwarding in the traditional OLSR protocol, a multi-objective optimized OLSR algorithm is proposed in this paper, which incorporating a new MPR mechanism and an improved NSGA-II algorithm. In the process of route discovery, the intermediate nodes responsible for forwarding packets are determined by the new MPR mechanism, and then the main parameters in the OLSR protocol are provided by the multi-objective optimization algorithm. Matlab was used to build a self-organizing network in this study. In addition, the conventional OLSR protocol, NSGA-II algorithm and multi-objective simulated annealing algorithm are selected to compare with the proposed algorithm. Simulation results show that the proposed algorithm can effectively reduce packet loss and end-to-end delay while obtaining better results in HV and Spacing, two multi-objective optimization result evaluation metrics.

In order to alleviate the impact of radio frequency interference (RFI) on the accuracy of ocean salinity satellite remote sensing, scholars have proposed various detection and labeling algorithms for RFI based on remote sensing data from the SMOS satellite. However, the signals that generate RFI are diverse, and the factors that influence remote sensing observation data are complex. Existing algorithms often target specific hypothetical conditions, lacking general applicability, which frequently leads to an important gap between the nominal performance of the literature and practical applications, posing great challenges to data labeling work. To address this problem, this study conducted a comprehensive and systematic analysis of RFI simulation based on scene modeling, algorithm modeling, and RFI energy modeling. Three typical RFI detection algorithms were selected, and the simulation scene was divided into 3 typical scenes: ocean, land, and sea–land scenes, and RFI was analyzed in terms of weak, moderate, strong, and extremely strong based on energy. Through simulation analysis and evaluation of RFI detection algorithms, lookup tables for algorithm selection, detection rate, and false-positive rate have been established for different intensities of independent RFI sources and multiple nearby RFI sources in the above scenario. These lookup tables have universal guiding significance and provide reliability assurance in complex situations.

This work elucidates a methodological approach employed in the process of planning the expansion of distribution network (DN) lines, wherein the amalgamation of system reconfiguration capabilities with operational equilibrium and reliability is paramount. The expansion proposals for the DN and the radial operation schemes post-expansion are encompassed. We formulate a bi-objective DN planning optimization model that concurrently addresses resource optimization configuration and operational optimization. Subsequently, the NSGA-II algorithm is employed to solve the optimization model, providing a coordinated presentation of multiple alternative solutions. However, this problem diverges from conventional bi-objective optimization problems due to its nature as a bi-objective optimization problem with embedded sub-optimization problem, consequently imposing a substantial computational burden. To address this issue, heuristic algorithms are designed to optimize system operational configuration, which is regarded as a sub-optimization problem. The proposed metric, model, and algorithms are validated on two case studies using the IEEE 33-bus and 70-bus test systems. Notably, the proposed method achieves solution efficiency by over 200 times compared to existing methods.

Nodal invulnerability has broad application prospects because of its emphasis on the differences between buses. Due to their long-term exposure, transmission lines are inevitably susceptible to damage caused by physical attacks or extreme weather. Therefore, restoring nodal invulnerability through a remedial approach or the introduction of mobile generators (MGs) is pivotal for resisting subsequent damage after a system is attacked. However, the research devoted to this field is limited. In order to fill the gap, this study conducts research on the configuration of MGs considering power generation balance to recover nodal invulnerability. First, a defender–attacker–defender (DAD) model is established, corresponding to the bi-objective robust optimization problem. The upper-level model is formulated to obtain the optimal compromise configuration scheme, the uncertainties of the attacked lines are elucidated in the middle level, and the nodal N−k security criterion utilized for measuring nodal invulnerability cooperates in the lower level. Then, a modified column-and-constraint generation (C&CG) algorithm is developed to incorporate fuzzy mathematics into the solution framework. In addition, the nodal invulnerability settings are optimized under limited resources. Numerical experiments are executed on the IEEE 24-bus system to verify the effectiveness and rationality of the proposed method.

Abstract Methylation of RNA plays an important role in cancer. Classical forms of such modifications include N6-methyladenine (m6A), 5-methylcytosine (m5C), and N1-methyladenine (m1A). Methylation-regulated long non-coding (lnc) RNAs are involved in various biological processes, such as tumor proliferation, apoptosis, immune escape, invasion, and metastasis. Therefore, we performed an analysis of transcriptomic and clinical data of pancreatic cancer samples in The Cancer Genome Atlas (TCGA). Using the co-expression method, we summarized 44 m6A/m5C/m1A-related genes and obtained 218 methylation-associated lncRNAs. Next, with COX regression, we screened 39 lncRNAs that are strongly associated with prognosis and found that their expression differed significantly between normal tissues and pancreatic cancer samples (P

Introduction To identify proteins and corresponding genes that share sequential and structural similarity with programmed cell death protein-1 (PD-1) in patients with type 1 diabetes mellitus (T1DM) via bioinformatics analysis.Research design and methods All proteins with immunoglobulin V-set domain were screened in the human protein sequence database, and the corresponding genes were obtained in the gene sequence database. GSE154609 was downloaded from the GEO database, which contained peripheral blood CD14+ monocyte samples from patients with T1DM and healthy controls. The difference result and the similar genes were intersected. Analysis of gene ontology and Kyoto encyclopedia of genes and genomes pathways was used to predict potential functions using the R package ‘cluster profiler’. The expression differences of intersected genes were analyzed in The Cancer Genome Atlas pancreatic cancer dataset and GTEx database using t-test. The correlation between the overall survival and disease-free progression of patients with pancreatic cancer was analyzed using Kaplan-Meier survival analysis.Results 2068 proteins with immunoglobulin V-set domain similar to PD-1 and 307 corresponding genes were found. 1705 upregulated differentially expressed genes (DEGs) and 1335 downregulated DEGs in patients with T1DM compared with healthy controls were identified. A total of 21 genes were overlapped with the 307 PD-1 similarity genes, including 7 upregulated and 14 downregulated. Of these, mRNA levels of 13 genes were significantly increased in patients with pancreatic cancer. High expression of MYOM3 and HHLA2 was significantly correlated with shorter overall survival of patients with pancreatic cancer, while high expression of FGFRL1, CD274, and SPEG was significantly correlated with shorter disease-free survival of patients with pancreatic cancer.Conclusions Genes encoding immunoglobulin V-set domain similar to PD-1 may contribute to the occurrence of T1DM. Of these genes, MYOM3 and SPEG may serve as potential biomarkers for the prognosis of pancreatic cancer.

The Antarctic region plays a key role in regulating the Earth’s climate and contains a unique record of environmental change. Foraminifera, a group of shell-bearing protists, are widely used as paleoenvironmental proxies. However, core-based reconstructions of Antarctic paleoenvironments are often hindered by the lack of foraminiferal fossil record. Foraminiferal ancient DNA provides new avenues for understanding environmental change, but the correlation between molecular ecological features of foraminifera and environmental conditions remains poorly understood. Here, we obtained surface sediment samples from the Southern Ocean at water depths ranging from 50 to 4399 m and measured eight environmental variables. We generated a DNA metabarcoding dataset of foraminifera and presented the first assessment of relationships between foraminiferal molecular diversity and environmental variables in the Antarctic region. The results showed that the alpha diversity of whole community and abundant subcommunity was positively correlated with water depth and negatively correlated with temperature, chlorophyll a and pheophytin a, while the alpha diversity of rare subcommunity had no linear correlation with the above environmental variables. Both rare and abundant foraminiferal subcommunities exhibited distance-decay relationships, but only the beta diversity of rare subcommunity showed a significant positive correlation with water depth. This study reveals contrasting biogeographical patterns of abundant and rare foraminifera and their different correlations with Antarctic environmental variables, holding promise to provide more proxies for reconstructing past environments using foraminiferal ancient DNA and more information for predicting the impact of future environmental changes on polar biodiversity.

Path planning is an important area of mobile robot research, and the ant colony optimization algorithm is essential for analyzing path planning. However, the current ant colony optimization algorithm applied to the path planning of mobile robots still has some limitations, including early blind search, slow convergence speed, and more turns. To overcome these problems, an improved ant colony optimization algorithm is proposed in this paper. In the improved algorithm, we introduce the idea of triangle inequality and a pseudo-random state transfer strategy to enhance the guidance of target points and improve the search efficiency and quality of the algorithm. In addition, we propose a pheromone update strategy based on the partition method with upper and lower limits on the pheromone concentration. This can not only improve the global search capability and convergence speed of the algorithm but also avoid the premature and stagnation phenomenon of the algorithm during the search. To prevent the ants from getting into a deadlock state, we introduce a backtracking mechanism to enable the ants to explore the solution space better. Finally, to verify the effectiveness of the proposed algorithm, the algorithm is compared with 11 existing methods for solving the robot path planning problem, including several ACO variants and two commonly used algorithms (A* algorithm and Dijkstra algorithm), and the experimental results show that the improved ACO algorithm can plan paths with faster convergence, shorter path lengths, and higher smoothness. Specifically, the algorithm produces the shortest path length with a standard deviation of zero while ensuring the most rapid convergence and the highest smoothness in the case of the shortest path in four different grid environments. These experimental results demonstrate the effectiveness of the proposed algorithm in path planning.

Abstract Increasing evidence demonstrates that long noncoding RNAs (lncRNAs) play critical roles in human breast cancer (BC) tumorigenesis. However, the mechanisms by which lncRNA and N6-methyladenosine (m6A) regulate BC tumorigenesis are still unclear. In the present research, LINC00958 was markedly overexpressed in BC tissue and cells, and LINC00958 upregulation promoted the tumor progression of BC cells. Mechanistically, m6A methyltransferase-like 3 (METTL3) gave rise to the upregulation of LINC00958 by promoting its RNA transcript stability. Moreover, LINC00958 acted as a competitive endogenous RNA for miR-378a-3p to promote YY1. Overall, these data provide novel insight into how m6A-mediated LINC00958 regulates BC tumorigenesis.

The snow temperature above the ice sheet is one of the basic characteristic parameters of the ice sheet, which plays an important role in the study of the global climate. Because infrared and microwaves with different frequencies have different penetration depths in snow, it is possible to retrieve the snow temperature profiles by combining microwave and infrared brightness temperatures. This paper proposes a conjoint inversion algorithm to retrieve snow temperature profiles by combining multi-frequency microwave brightness temperature (BT) with infrared BT, in which different weight functions of microwave BT at different frequencies are adopted, and the atmosphere influence has also been corrected. The snow temperature profile data are retrieved based on AMSR2 microwave BT data and MODIS infrared BT data in 2017 and 2018, which are evaluated by comparing with the measured snow temperature at Dome-C station. The results confirm that the inverted snow temperature profiles are consistent with the field observation data from the Dome-C station. Multi-frequency microwave brightness temperature can be used to invert the snow temperature profiles; however, the inverted snow surface temperature is more accurate by combining the infrared BT with the microwave BT in the conjoint inversion algorithm.

In order to improve the spatial resolution of a one-dimensional aperture synthesis (1-D AS) radiometer without increasing the size of the antenna array, the method of visibility extension (VE) is proposed in this article. In the VE method, prior information about the visibility distribution of various scenes is learnt by a residual convolutional neural network (ResCNN). Specifically, the relationship between the distribution of low-frequency visibility and that of high-frequency visibility is learnt. Then, the ResCNN is used to estimate the high-frequency visibility samples from the low-frequency visibility samples obtained by the AS system. Furthermore, the low- and high-frequency visibility samples are combined to reconstruct the brightness temperature image of the scene, to enhance the spatial resolution of AS. The simulation and experiment both demonstrate that the VE method can enhance the spatial resolution of 1-D AS.

The Cascade Correlation learning algorithm is a special supervised learning algorithm for artificial neural network architecture. The optimization algorithm in the traditional neural network has the disadvantages of a single optimization goal, slow convergence speed, and can easily fall into local area, which cannot fully meet the key elements in the cascade correlation learning algorithm. In comparison, the group intelligence optimization algorithm can take into account these key elements in the optimization process at the same time, and obtain better optimization results. In this paper, we propose the single-objective optimization algorithm jDE-B and the multi-objective optimization algorithm MOEA-T, and improve the network expansion mode in the learning process of Cascade Correlation neural networks. We investigate the effect of applying the group intelligent optimization algorithm in the Cascade Correlation learning algorithm. Experimental results show that our improved algorithm is able to enhance the ability of the Cascade Correlation neural network to fit problems, reduce the number of hidden units and the depth of the network, and optimize the network structure.

ObjectivesVaginal microbiota is not only an important source of bacterial colonization for neonates, but also plays a crucial role in maternal and neonatal health. This study aimed to investigate the vaginal microbial community structure right after delivery and its impact on the neonatal oral microbiome.MethodsIn this study, 27 women were recruited from Bao'an Maternal and Child Health Hospital. Bacterial compositions of vaginal samples before and right after delivery and neonatal oral samples right after birth were investigated using 16S rRNA sequencing of V3–V4 hyperregions.ResultsVaginal microbiome before delivery was dominated by the genus Lactobacillus. After delivery, the vaginal microbial community was altered, with significantly decreased proportion of Lactobacillus, increased alpha-diversity, and a more diverse ecological network. A large number subjects dominated by Lactobacillus species before delivery shifted to CST (community state type) IV after delivery. In addition, similar changes were observed in the neonatal oral microbiome, and its community profile was closer to vaginal samples after delivery than before delivery with principal coordinates analysis and microbial source tracking analysis.ConclusionThe vaginal microbiome was altered right after delivery and impacted the colonization of the neonatal oral microbiome in China. Further, it is vital to understand the longitudinal influence on maternal and neonatal health of vaginal microbiome community changes after delivery.

Regarding applicative, facile, green chemical research, a bio-inspired approach is being reported for the synthesis of Ag nanoparticles by pectin as a natural reducing and stabilizing agent without using any toxic and harmful reagent. The biosynthesized Pectin/Ag NPs were characterized by advanced physicochemical techniques like ultraviolet–visible (UV–Vis), Fourier Transformed Infrared spectroscopy (FT-IR), Scanning Electron Microscopy (SEM), High-Resolution Transmission Electron Microscopy (HR-TEM), Energy Dispersive X-ray spectroscopy (EDX), and X-ray Diffraction (XRD) study. It has been established that pectin-stabilized silver nanoparticles have a spherical shape with a mean diameter from 15 to 20 nm. After that, the biological performance of those biomolecules functionalized Ag NPs was investigated. In the MTT assay, human colorectal carcinoma (HCT-8 [HRT-18], Ramos.2G6.4C10, HT-29, and HCT 116) and normal cell lines (HUVEC) were used to study the cytotoxicity and anticancer potential of human colorectal over the AgNO3 and Pectin/Ag NPs. The cell viability of Pectin/Ag NPs was very low against human colorectal carcinoma cell lines without any cytotoxicity on the normal (HUVEC) cell line. The best anti-human colorectal carcinoma properties of Pectin/Ag NPs against the above cell lines was in the case of the HCT 116 cell line. The antioxidant properties of the AgNO3 and Pectin/Ag NPs were calculated against DPPH free radicals. The IC50 of Pectin/Ag NPs was 167 µg/mL. According to the above results, the Pectin/Ag NPs may be administrated to treat human colorectal carcinoma in humans.

Abstract Background Penicillin allergy is frequently reported in adults and children. Recent studies suggest that microbiota plays a key role in the development and progression of allergy. In this study, the relationship between vaginal microbiome and pregnant women with penicillin allergy was investigated. Methods Vaginal samples before labor from 12 pregnant women with penicillin allergy and 15 non-allergic pregnant women were collected. Bacterial community structure of all study subjects and the discrepancies between the two groups were analyzed using 16S rRNA sequencing based on Illumina Hiseq 2500 platform. Results The abundant phyla among all participants were Firmicutes, Actinobacteria and Bacteroidetes. The predominant genus was Lactobacillus. Compared to non-allergic pregnant women, Actinobacteria, Coriobacteriaceae, Lachnospiraceae, Paraprevotella and Anoxybacillus significantly decreased, whereas Deltaproteobacteria, Peptostreptococcaceae, Enterococcus and Megamonas were more abundant in penicillin allergic women. Additionally, obvious discrepancies were observed in the co-abundance network at the genus level between the two groups. Conclusions There were differences in the microbial community structure and composition of reproduction tract between penicillin allergic and non-allergic pregnant women. These shifts may be related to maternal and neonatal health.

We prove that the steady states of a class of multidimensional reaction–diffusion systems are asymptotically stable at the intersection of unweighted space and exponentially weighted Sobolev spaces, paying particular attention to a special case, namely, systems of equations that arise in combustion theory. The steady-state solutions considered here are the end states of the planar fronts associated with these systems. The present work can be seen as a complement to the previous results on the stability of multidimensional planar fronts.

RGB and depth modalities contain more abundant and interactive information, and convolutional neural networks (ConvNets) based on multi-modal data have achieved successful progress in action recognition. Due to the limitation of a single stream, it is difficult to improve recognition performance by learning multi-modal interactive features. Inspired by the multi-stream learning mechanism and spatial-temporal information representation methods, we construct dynamic images by using the rank pooling method and design an interactive learning dual-ConvNet (ILD-ConvNet) with a multiplexer module to improve action recognition performance. Built on the rank pooling method, the constructed visual dynamic images can capture the spatial-temporal information from entire RGB videos. We extend this method to depth sequences to obtain more abundant multi-modal spatial-temporal information as the inputs of the ConvNets. In addition, we design a dual ILD-ConvNet with multiplexer modules to jointly learn the interactive features of two-stream from RGB and depth modalities. The proposed recognition framework has been tested on two benchmark multi-modal datasets—NTU RGB + D 120 and PKU-MMD. The proposed ILD-ConvNet with a temporal segmentation mechanism achieves an accuracy of 86.9% and 89.4% for Cross-Subject (C-Sub) and Cross-Setup (C-Set) on NTU RGB + D 120, 92.0% and 93.1% for Cross-Subject (C-Sub) and Cross-View (C-View) on PKU-MMD, which are comparable with the state of the art. The experimental results shown that our proposed ILD-ConvNet with a multiplexer module can extract interactive features from different modalities to enhance action recognition performance.

It is necessary to develop new energy technologies because of serious environmental problems. As one of the most promising electrochemical energy conversion and storage devices, the Zn–air battery has attracted extensive research in recent years due to the advantages of abundant resources, low price, high energy density, and high reduction potential. However, the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) of Zn–air battery during discharge and charge have complicated multi-electron transfer processes with slow reaction kinetics. It is important to develop efficient and stable oxygen electrocatalysts. At present, single-function catalysts such as Pt/C, RuO2, and IrO2 are regarded as the benchmark catalysts for ORR and OER, respectively. However, the large-scale application of Zn–air battery is limited by the few sources of the precious metal catalysts, as well as their high costs, and poor long-term stability. Therefore, designing bifunctional electrocatalysts with excellent activity and stability using resource-rich non-noble metals is the key to improving ORR/OER reaction kinetics and promoting the commercial application of the Zn–air battery. Metal–organic framework (MOF) is a kind of porous crystal material composed of metal ions/clusters connected by organic ligands, which has the characteristics of adjustable porosity, highly ordered pore structure, low crystal density, and large specific surface area. MOFs and their derivatives show remarkable performance in promoting oxygen reaction, and are a promising candidate material for oxygen electrocatalysts. Herein, this review summarizes the latest progress in advanced MOF-derived materials such as oxygen electrocatalysts in a Zn–air battery. Firstly, the composition and working principle of the Zn–air battery are introduced. Then, the related reaction mechanism of ORR/OER is briefly described. After that, the latest developments in ORR/OER electrocatalysts for Zn–air batteries are introduced in detail from two aspects: (i) non-precious metal catalysts (NPMC) derived from MOF materials, including single transition metals and bimetallic catalysts with Co, Fe, Mn, Cu, etc.; (ii) metal-free catalysts derived from MOF materials, including heteroatom-doped MOF materials and MOF/graphene oxide (GO) composite materials. At the end of the paper, we also put forward the challenges and prospects of designing bifunctional oxygen electrocatalysts with high activity and stability derived from MOF materials for Zn–air battery.

Background: Hypertension is a highly prevalent disorder. A nomogram to estimate the risk of hypertension in Chinese individuals is not available. Methods: 6201 subjects were enrolled in the study and randomly divided into training set and validation set at a ratio of 2:1. The LASSO regression technique was used to select the optimal predictive features, and multivariate logistic regression to construct the nomograms. The performance of the nomograms was assessed and validated by AUC, C-index, calibration curves, DCA, clinical impact curves, NRI, and IDI. Results: The nomogram140/90 was developed with the parameters of family history of hypertension, age, SBP, DBP, BMI, MCHC, MPV, TBIL, and TG. AUCs of nomogram140/90 were 0.750 in the training set and 0.772 in the validation set. C-index of nomogram140/90 were 0.750 in the training set and 0.772 in the validation set. The nomogram130/80 was developed with the parameters of family history of hypertension, age, SBP, DBP, RDWSD, and TBIL. AUCs of nomogram130/80 were 0.705 in the training set and 0.697 in the validation set. C-index of nomogram130/80 were 0.705 in the training set and 0.697 in the validation set. Both nomograms demonstrated favorable clinical consistency. NRI and IDI showed that the nomogram140/90 exhibited superior performance than the nomogram130/80. Therefore, the web-based calculator of nomogram140/90 was built online. Conclusions: We have constructed a nomogram that can be effectively used in the preliminary and in-depth risk prediction of hypertension in a Chinese population based on a 10-year retrospective cohort study. Funding: This study was supported by the Hebei Science and Technology Department Program (no. H2018206110).

Background: The world faced crises of prevention and control and shortage of medical resources during the COVID-19 (Corona Virus Disease 2019) outbreak. The establishment of temporary integrated isolation wards in hospitals, which is universal and representative in China, is one of the most-effective strategies in solving these problems according to China's experiences.Aim: To conduct a preliminary study on the establishment of a temporary integrated isolation ward during the outbreak of COVID-19 and to evaluate related impact.Methods: SWOT analysis was used to analyze the advantages, disadvantages, opportunities, and risks in the establishment of the temporary integrated isolation ward, and corresponding corrective measures were made according to the analysis results.Findings: The ward has formulated more than 10 related work procedures and prevention and control measures. A total of 93 patients with 18 critically ill patients were admitted for treatment and isolation. They were all evaluated based on established procedures and protocols. Twenty-four supplementary nucleic acid tests were ordered and conducted. One new patient with COVID-19 was confirmed and was successfully transferred to the designated COVID-19 infectious control hospital. There were no missed diagnosis or misdiagnosis, no cross-infection of patients, no cluster outbreak, and no infection of medical workers during the entire process.Conclusion: SWOT analysis is helpful in guiding the establishment of a temporary integrated isolation ward and the formulation of prevention and control measures in Hebei General Hospital during the COVID-19 outbreak. It provides the guidance and reference of significance for the establishment of similar types of wards in the future.

Innovation subsidy is of great significance to promoting enterprise innovation development. However, in recent years, the frequent occurrence of R&D subsidy deception in China has greatly reduced effectiveness of innovation. From the perspective of the strategic choice motivation of the innovation subject (including the enterprises, research institutions, and local governments), this paper constructs a multiplayer stochastic evolutionary game model. The influence of each variable on the subject strategy adoption is analyzed by simulation. There are two important findings in this paper. First, the paper confirms that there is an optimal boundary for the high subsidies received by enterprises and academic institutions, and the “subsidy boundary” is solved through the model. Second, this paper analyzes the effectiveness of the regulation of each variable through simulation and provides management and policy implications.

With the potential prospects of the ϒ(1S) data samples at the running LHC and upcoming SuperKEKB, the ϒ(1S)→Bcρ weak decay is studied with the pQCD approach. It is found that (1) the lion's share of branching ratio comes from the longitudinal polarization helicity amplitudes; (2) branching ratio for the ϒ(1S)→Bcρ decay can reach up to O(10−9), which might be hopefully measurable.

The branching ratio and direct CP asymmetry of the ϒ(1S)→BcDs weak decay are estimated with the perturbative QCD approach firstly. It is found that (1) the direct CP-violating asymmetry is close to zero, (2) the branching ratio Br(ϒ(1S)→BcDs)≳10−10 might be measurable at the future experiments.

The ϒ(nS)→BcDs, BcDd weak decays are studied with the pQCD approach firstly. It is found that branching ratios Br(ϒ(nS)→BcDs)∼O(10−10) and Br(ϒ(nS)→BcDd)∼O(10−11), which might be measurable in the future experiments.

With the potential prospects of the ϒ(nS) at high-luminosity dedicated heavy-flavor factories, the color-favored ϒ(nS)→Bcπ, BcK weak decays are studied with the pQCD approach. It is found that branching ratios for the ϒ(nS)→Bcπ decay are as large as the order of O(10−11), which might be measured promisingly by the future experiments.

This paper deals with the antenna mutual coupling effect in interferometric aperture synthesis radiometers (IASRs), which degrades the system radiometric performance. First, the conventional mutual impedance (CMI) is adopted to analyze the mutual coupling effect on the performance of IASR and a practical model of the coupled visibilities is developed. Based on the model, an external calibration method is then proposed to compensate for the mutual coupling effect. In this method, the measured visibilities are decoupled through the difference measurement between the original scene and a naturally occurring reference scene. Compared to the previous methods, the proposed method requires no extra additional hardware cost and has easier implementation and, therefore, fits for the large interferometric array radiometers. Experimental results validate the effectiveness of the proposed method.