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Oxygen evolution reaction (OER) is a very complex process with slow reaction kinetics and high overpotential, which is the main limitation for the commercial application of water splitting. Thus, it is of necessary to design high-performance OER catalysts. NiFe based layered double hydroxides (NiFe-LDHs) have recently gained a lot of attention due to their high reaction activity and simple manufacturing process. In this study, a novel electrocatalyst based on NiFe-LDH was constructed by introducing Ti3C2, which was utilized to modulate the structural and electronic properties of the electrocatalysts. Structural examinations reveal that the Ti3C2 of 2D structure successfully dope the NiFe-LDHs nanosheets, forming NiFe-LDH/Ti3C2 heterojunctions. Firstly, the heterojunction substantially reduces the charge transfer resistance, promoting the electron migration between the LDH nanosheets. Secondly, theoretical calculations demonstrate that the energy barrier between the rate-determining step from *OH to *O is lowered, favoring the formation of the reaction intermediates and thus the occurrence of OER. As a result, the composite electrocatalyst exhibits a low overpotential of 334 mV at a current density of 10 mA/cm2 and a small Tafel slope of 55 mV/dec, which are superior to those of the NiFe-LDH by 11.2 % and 38.5 %, respectively. This study provides inspiration for promoting the performances of NiFe based electrocatalysts by utilizing 2D materials.

Abstract Background Blood transfusion and previous stroke history are two independent risk factors of venous thromboembolism (VTE) in stroke patients. Whether the potential interaction of transfusion history and previous stroke history is associated with a greater risk of VTE remains unclear. This study aims to explore whether the combination of transfusion history and previous stroke history increases the risk of VTE among Chinese stroke patients. Methods A total of 1525 participants from the prospective Stroke Cohort of Henan Province were enrolled in our study. Multivariate logistic regression models were used to explore the associations among transfusion history, previous stroke history and VTE. The interaction was evaluated on both multiplicative and additive scales. The odds ratio (95% CI), relative excess risk of interaction (RERI), attributable proportion (AP), and synergy index (S) of interaction terms were used to examine multiplicative and additive interactions. Finally, we divided our population into two subgroups by National Institutes of Health Stroke Scale (NIHSS) score and re-evaluated the interaction effect in both scales. Results A total of 281 (18.4%) participants of 1525 complicated with VTE. Transfusion and previous stroke history were associated with an increased risk of VTE in our cohort. In the multiplicative scale, the combination of transfusion and previous stroke history was statistically significant on VTE in both unadjusted and adjusted models (P 5 points (P

Abstract Childhood obesity remains one of the most important issues in global health, which is implicated in many chronic diseases. Converging evidence suggests that a higher body mass index during childhood (CBMI) is significantly associated with increased coronary artery disease (CAD) susceptibility in adulthood, which may partly arise from the shared genetic determination. Despite genome-wide association studies (GWASs) have successfully identified some loci associated with CBMI and CAD individually, the genetic overlap and common biological mechanism between them remains largely unexplored. Here, relying on the results from the two large-scale GWASs (n = 35,668 for CBMI and n = 547,261 for CAD), linkage disequilibrium score regression (LDSC) was used to estimate the genetic correlation of CBMI and CAD in the first step. Then, we applied different pleiotropy-informed methods including conditional false discovery rate ( $$\mathrm{cFDR}$$ cFDR ) and genetic analysis incorporating pleiotropy and annotation (GPA) to detect potentially common loci for childhood obesity and CAD. By integrating the genetic information from the existing GWASs summary statistics, we found a significant positive genetic correlation ( $${r}_{g}$$ r g = 0.127, p = 2E−4) and strong pleiotropic enrichment between CBMI and CAD (LRT = 79.352, p = 5.2E−19). Importantly, 28 loci were simultaneously discovered to be associated with CBMI, and 13 of them were identified as potentially pleiotropic loci by $$\mathrm{cFDR}$$ cFDR and GPA. Those corresponding pleiotropic genes were enriched in trait-associated gene ontology (GO) terms “amino sugar catabolic process”, “regulation of fat cell differentiation” and “synaptic transmission”. Overall, the findings of the pleiotropic loci will help to further elucidate the common molecular mechanisms underlying the association of childhood obesity and CAD, and provide a theoretical direction for early disease prevention and potential therapeutic targets.

Abstract Background Numerous studies have suggested that lifestyle-related factors are associated with mortality, however limited evidence is available for the Chinese elder population. Methods The data of this study was obtained from the Chinese Longitudinal Health Survey (CLHLS) during 2008 − 2018, lifestyle-related factors including body mass index (BMI), smoking, drinking, consumption of vegetables and fruits, physical activity and sleep duration were included as dependent variables in the analysis. A lifestyle risk score was created using six unhealthy behaviors: smoking, drinking, unhealthy weight, physical inactivity, not eat vegetables or fruits and short or prolonged sleep. The Kaplan–Meier curves were used to illustrate the cumulative effect of lifestyle factors on mortality and cox regression models were conducted to estimate the combined effects of lifestyle-related factors on total mortality. Results The results illustrated that low BMI, smoking, no fruit eating, and no physical inactivity were risk factors for total mortality. KM curves showed significant cumulative effect of unhealthy lifestyle factors on mortality. Compared with participants without any unhealthy factors, the hazard ratio (HR) for participants with six unhealthy factors was 1.335 (1.015,1.757) for all-cause mortality. Conclusions This study demonstrated poor adherence to a healthy lifestyle may increase all-cause mortality and specific combinations of lifestyle related factors have different effects on mortality among Chinese elderly population.

Most current short-term load forecasting models have difficulty in simultaneously taking into account the time-series nature of load data, the non-linear characteristics, and the ineffectiveness of extracting potential high-dimensional features from historical series. To solve this problem, we propose a hybrid neural algorithm model (DPCL). In the DPCL, we use convolutional neural networks to obtain the high-dimensional spatial features of the phase space reconstruction of the load time series. Then, we combine the obtained high-dimensional spatial features with the external influence features extracted in the Pearson correlation analysis. Long and short-term memory networks retrieve Spatio-temporal features through the connection layer and obtain prediction results. In addition, there are problems of network gradient degradation and overfitting during the training process, We use an improved differential evolutionary algorithm to optimize the topology and time step of the hybrid neural network. We use the public dataset of a European utility and the loaded dataset of a Chinese mathematical competition as practical arithmetic examples. Experiments have higher prediction accuracy and faster prediction speed compared with other traditional algorithms.

Due to the rapid development of information technology and network technology, there is a lot of data, but the phenomenon of lack of knowledge is becoming more and more serious. Data mining technology has developed vigorously in this environment, and it has shown more and more vitality. Based on Spark programming model, this paper designs the parallel extension of fuzzy c-means. In order to enhance the performance of fuzzy c-means parallel expansion, the improvement strategy of k-means during the initialization phase is borrowed, and k-means// is extended to fuzzy c-means to obtain better clustering performance. Combined with Spark's programming model, this paper can obtain extended parallel fuzzy c-means algorithm. Several experiments on the data set of the algorithm proposed in this paper have shown good scalability and parallelism, effectively expanding fuzzy c-means clustering to distributed applications, greatly increasing the scale of the data processed by the algorithm. This improves the robustness of the algorithm and the adaptability of the algorithm to the shape and structure of the data, so that the parallel and scalable clustering algorithm can more effectively perform cluster analysis on big data. Three algorithms were simulated on MATLAB platform. We use simple data sets and complex two-dimensional data sets, and compare with the traditional fuzzy c-means algorithm and fuzzy c-means algorithm based on fuzzy entropy. Experiments show that the scalable parallel fuzzy c-means algorithm not only greatly improves the anti-noise performance, but also improves the convergence speed, and it can automatically determine the optimal number of clusters.

Although comprehensive land consolidation may stimulate industrial revitalization, the interactions and pathways between land consolidation and industrial revitalization are unclear. Using villages in China as case studies, the historical development process and pathways of comprehensive land consolidation, and rural industrial revitalization, are summarized and clarified. Development processes and pathways for villages in Puhe, Maosi, Dianzi, and Baicaopo in Gansu Province were compared. The comparison suggested the following nested generic strategy for revitalization, comprising: (1). A core strategy for guiding industrial development that consolidates the spatial layout; (2). Strengthening ecological restoration as a key part of the optimization strategy with (1); and (3). Including and enhancing cultural industrialization as a desirable supplement. Our study and worked examples can be applied to other villages or regions worldwide to explore the development path of village industry revitalization under the guidance of our proposed comprehensive land consolidation framework.

Currently, precious metal group materials are known as the efficient and widely used oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) catalysts. The exorbitant prices and scarcity of the precious metals have stimulated scale exploration of alternative non-precious metal catalysts with low-cost and high performance. Layered double hydroxides (LDHs) are a promising precursor to prepare cost-effective and high-performance catalysts because they possess abundant micropores and nitrogen self-doping after pyrolysis, which can accelerate the electron transfer and serve as active sites for efficient OER. Herein, we developed a new highly active NiFeMn-layered double hydroxide (NFM LDH) based electrocatalyst for OER. Through building NFM hydroxide/oxyhydroxide heterojunction and incorporation of conductive graphene, the prepared NFM LDH-based electrocatalyst delivers a low overpotential of 338 mV at current density of 10 mA cm−2 with a small Tafel slope of 67 mV dec−1, which are superior to those of commercial RuO2 catalyst for OER. The LDH/OOH heterojunction involves strong interfacial coupling, which modulates the local electronic environment and boosts the kinetics of charge transfer. In addition, the high valence Fe3+ and Mn3+ species formed after NaOH treatment provide more active sites and promote the Ni2+ to higher oxidation states during the O2 evolution. Moreover, graphene contributes a lot to the reduction of charge transfer resistance. The combining effects have greatly enhanced the catalytic ability for OER, demonstrating that the synthesized NFM LDH/OOH heterojunction with graphene linkage can be practically applied as a high-performance electrocatalyst for oxygen production via water splitting.

Research has demonstrated that the formation of composites of titanium dioxide (TiO2) with silver phosphate (Ag3PO4) through the construction of heterojunctions can expand its light absorption range and suppress the recombination of photogenerated electron–hole pairs, thereby improving the photocatalytic performance. However, this method offers only limited performance improvements, and the composite photocatalysts are costly due to the expensive Ag3PO4. In this study, Ti3C2 MXene, which has good hydrophilicity and excellent electrical conductivity, is first used to form Schottky junction composites with bronze TiO2 (TiO2(B)) via electrostatic self-assembly. Then, Ag3PO4 quantum dots were further formed on the surface of the TiO2(B)/Ti3C2 MXene by in situ self-growth, and Ag3PO4 formed heterojunctions and Schottky junctions with TiO2(B) and Ti3C2 MXene, respectively. Finally, a ternary composite photocatalyst TiO2(B)/Ti3C2 MXene/Ag3PO4 was jointly constructed by these functional junctions. Under the synergistic effect of these functional junctions, the mobility and fast separation performance of photogenerated electron–hole pairs of the composite photocatalyst were significantly improved, the recombination of photogenerated electron–hole pairs was effectively suppressed, and the light absorption performance was enhanced. As a result, the composite photocatalyst exhibited excellent photocatalytic performances.

Due to the ever-increasing industrial activity, humans and the environment suffer from deteriorating air quality, making the long-term monitoring of air particle indicators essential. The advances in unmanned aerial vehicles (UAVs) offer the potential to utilize UAVs for various forms of monitoring, of which air quality data acquisition is one. Nevertheless, most current UAV-based air monitoring suffers from a low payload, short endurance, and limited range, as they are primarily dependent on rotary aerial vehicles. In contrast, a fixed-wing UAV may be a better alternative. Additionally, one of the most critical modules for 3D profiling of a UAV system is path planning, as it directly impacts the final results of the spatial coverage and temporal efficiency. Therefore, this work focused on developing 3D coverage path planning based upon current commercial ground control software, where the method mainly depends on the Boustrophedon and Dubins paths. Furthermore, a user interface was also designed for easy accessibility, which provides a generalized tool module that links up the proposed algorithm, the ground control software, and the flight controller. Simulations were conducted to assess the proposed methods. The result showed that the proposed methods outperformed the existing coverage paths generated by ground control software, as it showed a better coverage rate with a sampling density of 50 m.

Abstract: This study aimed to illustrate the impact of injury-related deaths on life expectancy in China in 2016 and to identify the high-risk population. Standard life tables were used to calculate life expectancy and cause-eliminated life expectancy by utilizing mortality data from the national mortality surveillance system. In 2016, the life expectancy of Chinese residents was 78.91 years. After eliminating injury-related mortality, the life expectancy of the residents increased by 1.13 years, which was higher in male and rural residents compared with female and urban residents. The life expectancy on the Eastern and Central regions increased slowly compared with the Western region. The greatest influencing factor on life expectancy was road traffic injuries, followed by falls. Falls had a greater impact on life expectancy for children under 5 years old and those aged over 65 years. This study indicates that deaths caused by injury had a noteworthy impact on life expectancy in China. More attention should be paid to road traffic injuries, and effective preventive measures should be taken to reduce deaths related to injury to increase the life expectancy of residents, especially in children under 5 years and adults over 65 years. By reducing the deaths caused by injury, the life expectancy level is likely to further improve.

The Xihu Sag in the East China Sea Shelf Basin contains abundant oil and gas reserves and is a focus for hydrocarbon exploration and development. Source rocks are mainly coals and coal-measures mudstones in the Paleogene Pinghu and Huagang formations. Samples from the Pinghu Formation in the Xihu Sag were collected for petrology, total organic carbon, and Rock-Eval analysis for the purpose of investigating macerals component and their contributions to hydrocarbon generation potential. The coaly source rocks from the Pinghu Formation are dominated by vitrinite (average 86.18%) but have an obviously elevated content of liptinite (average 12.59%) and a much lower amount of inertinite (average 1.23%). Liptinite of the samples is mainly composed of resinite, with a small amount of cutinite, sporinite and alginate in descending order. TOC values are 37.55%–65.58% (average 49.16%). Effective HI values are 167–281 mg HC/g TOC (average 223.5 mg HC/g TOC), suggesting the organic matter is type II kerogen. Relatively high HI values and macerals components suggest that the coaly source rocks can generate both oil and gas. Although the liptinite in the coaly source rocks has a content lower than vitrinite values, it makes a significant contribution to both total hydrocarbon and liquid hydrocarbon generation. The contributions of vitrinite, liptinite and inertinite to the total hydrocarbon generation approximately are 63.21%, 36.46% and 0.33%, respectively. The contributions of vitrinite and liptinite to the liquid hydrocarbon generation are approximately 40.95% and 59.05%, respectively. These results demonstrate that the coaly source rocks are dominated by vitrinite macerals with a relatively higher content of liptinite macerals, especially resinite, and these source rocks are more prone to both total hydrocarbon and liquid hydrocarbon generation. Paleogene coaly source rocks from other parts of the world should be considered for their oil-prone nature.

Brain health quality pre-monitoring has become an urgent need, and this is a system of complex engineering. From the perspective of intelligent decision-making based on big data, the intelligent air index prediction is introduced, the popular classification algorithm is introduced, the hidden information of historical data is mined, and the brain health quality prediction is realized. The brain health quality monitoring system based on the Internet of Things is constructed, and the classification algorithm is used to realize real-time acquisition, intelligent processing of data. In order to improve the data processing speed and enhance the real-time performance of brain health quality prediction, this paper introduces cloud computing technology to accelerate data processing. In order to enable users to understand the air index, anytime and anywhere, it is also designed based on the problem of large historical data of air index and real-time data collection. The Android platform develops an air index forecast client.

Photocatalytic degradation, as an emerging method to control environmental pollution, is considered one of the most promising environmental purification technologies. As Tibet is a region with some of the strongest solar radiation in China and even in the world, it is extremely rich in solar energy resources, which is ideal for applying photocatalytic technology to its ecological environment protection and governance. In this study, Na2Ti3O7 nanobelts were prepared via a hydrothermal method and converted to TiO2∙xH2O ion exchange, which was followed by high-temperature calcination to prepare TiO2(B) nanobelts (“B” in TiO2(B) means “Bronze phase”). A simple in situ method was used to generate Ag3PO4 particles on the surface of the TiO2 nanobelts to construct a Ag3PO4/TiO2(B) heterojunction composite photocatalyst. By generating Ag3PO4 nanoparticles on the surface of the TiO2(B) nanobelts to construct heterojunctions, the light absorption range of the photocatalyst was successfully extended from UV (ultraviolet) to the visible region. Furthermore, the recombination of photogenerated electron–hole pairs in the catalyst was inhibited by the construction of the heterojunctions, thus greatly enhancing its light quantum efficiency. Therefore, the prepared Ag3PO4/TiO2(B) heterojunction composite photocatalyst greatly outperformed the TiO2(B) nanobelt in terms of photocatalytic degradation.

Hydrogen is regarded to be one of the most promising renewable and clean energy sources. Finding a highly efficient and cost-effective catalyst to generate hydrogen via water splitting has become a research hotspot. Two-dimensional materials with exotic structural and electronic properties have been considered as economical alternatives. In this work, 2D SnSe films with high quality of crystallinity were grown on a mica substrate via molecular beam epitaxy. The electronic property of the prepared SnSe thin films can be easily and accurately tuned in situ by three orders of magnitude through the controllable compensation of Sn atoms. The prepared film normally exhibited p-type conduction due to the deficiency of Sn in the film during its growth. First-principle calculations explained that Sn vacancies can introduce additional reactive sites for the hydrogen evolution reaction (HER) and enhance the HER performance by accelerating electron migration and promoting continuous hydrogen generation, which was mirrored by the reduced Gibbs free energy by a factor of 2.3 as compared with the pure SnSe film. The results pave the way for synthesized 2D SnSe thin films in the applications of hydrogen production.

Bi2Se3 possesses a two-dimensional layered rhombohedral crystal structure, where the quintuple layers (QLs) are covalently bonded within the layers but weakly held together by van der Waals forces between the adjacent QLs. It is also pointed out that Bi2Se3 is a topological insulator, making it a promising candidate for a wide range of electronic and optoelectronic applications. In this study, we investigate the growth of high-quality Bi2Se3 thin films on mica by the molecular beam epitaxy technique. The films exhibited a layered structure and highly c-axis-preferred growth orientation with an XRD rocking curve full-width at half-maximum (FWHM) of 0.088°, clearly demonstrating excellent crystallinity for the Bi2Se3 deposited on the mica substrate. The growth mechanism was studied by using an interface model associated with the coincidence site lattice unit (CSLU) developed for van der Waals epitaxies. This high (001) texture favors electron transport in the material. Hall measurements revealed a mobility of 726 cm2/(Vs) at room temperature and up to 1469 cm2/(Vs) at 12 K. The results illustrate excellent electron mobility arising from the superior crystallinity of the films with significant implications for applications in conducting electrodes in optoelectronic devices on flexible substrates.

The network planning is a key factor that directly affects the performance of the wireless networks. Distributed antenna system (DAS) is an effective strategy for the network planning. This paper investigates the antenna deployment in a DAS for the high-speed railway communication networks and formulates an optimization problem which is NP-hard for achieving the optimal deployment of the antennas in the DAS. To solve this problem, a scheme based on an improved cuckoo search based on dimension cells (ICSDC) algorithm is proposed. ICSDC introduces the dimension cell mechanism to avoid the internal dimension interferences in order to improve the performance of the algorithm. Simulation results show that the proposed ICSDC-based scheme obtains a lower network cost compared with the uniform network planning method. Moreover, ICSDC algorithm has better performance in terms of the convergence rate and accuracy compared with the conventional cuckoo search algorithm, the particle swarm optimization, and the firefly algorithm.