mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Bioplastic classifications and innovations in antibacterial, antifungal, and antioxidant applications

Conventional plastics exacerbate climate change by generating substantial amounts of greenhouse gases and solid wastes throughout their lifecycle. To address the environmental and economic challenges associated with petroleum-based plastics, bioplastics have emerged as a viable alternative. Bioplastics are a type of plastic that are either biobased, biodegradable, or both. Due to their biodegradability and renewability, bioplastics are established as earth-friendly materials that can replace nonrenewable plastics. However, early bioplastic development has been hindered by higher production costs and inferior mechanical and barrier properties compared to conventional plastics. Nevertheless, studies have shown that the addition of additives and fillers can enhance bioplastic properties. Recent advancements in bioplastics have incorporated special additives like antibacterial, antifungal, and antioxidant agents, offering added values and unique properties for specific applications in various sectors. For instance, integrating antibacterial additives into bioplastics enables the creation of active food packaging, extending the shelf-life of food by inhibiting spoilage-causing bacteria and microorganisms. Moreover, bioplastics with antioxidant additives can be applied in wound dressings, accelerating wound healing by preventing oxidative damage to cells and tissues. These innovative bioplastic developments offer promising opportunities for developing sustainable and practical solutions in various fields. Within this review are two main focuses: an outline of the bioplastic classifications to understand how they fit in as the coveted conventional plastics substitute and an overview of the recent bioplastic innovations in the antibacterial, antifungal, and antioxidant applications. We cover the use of different polymers and additives, presenting the findings and potential applications within the last decade. Although current research primarily focuses on food packaging and biomedicine, the exploration of bioplastics with specialized properties is still in its early stages, offering a wide range of undiscovered opportunities.
Fractional-order Sliding Mode Control of Hybrid Drive Wind Turbine for Improving Low-voltage Ride-through Capacity

A hybrid drive wind turbine equipped with a speed regulating differential mechanism can generate electricity at the grid frequency by an electrically excited synchronous generator without requiring fully or partially rated converters. This mechanism has extensively been studied in recent years. To enhance the transient operation performance and low-voltage ride-through capacity of the proposed hybrid drive wind turbine, we aim to synthesize an advanced control scheme for the flexible regulation of synchronous generator excitation based on fractional-order sliding mode theory. Moreover, an extended state observer is constructed to cooperate with the designed controller and jointly compensate for parametric uncertainties and external disturbances. A dedicated simulation model of a 1.5 MW hybrid drive wind turbine is established and verified through an experimental platform. The results show satisfactory model performance with the maximum and average speed errors of 1.67% and 1.05%, respectively. Moreover, comparative case studies are carried out considering parametric uncertainties and different wind conditions and grid faults, by which the superiority of the proposed controller for improving system on-grid operation performance is verified.
Multi-stage Coordinated Robust Optimization for Soft Open Point Allocation in Active Distribution Networks with PV

To optimize the placement of soft open points (SOPs) in active distribution networks (ADNs), many aspects should be considered, including the adjustment of transmission power, integration of distributed generations (DGs), coordination with conventional control methods, and maintenance of economic costs. To address this multi-objective planning problem, this study proposes a multi-stage coordinated robust optimization model for the SOP allocation in ADNs with photovoltaic (PV). First, two robust technical indices based on a robustness index are proposed to evaluate the operation conditions and robust optimality of the solutions. Second, the proposed coordinated allocation model aims to optimize the total cost, robust voltage offset index, robust utilization index, and voltage collapse proximity index. Third, the optimization methods of the multi-and single-objective models are coordinated to solve the proposed multi-stage problem. Finally, the proposed model is implemented on an IEEE 33-node distribution system to verify its effectiveness. Numerical results show that the proposed index can better reveal voltage offset conditions as well as the SOP utilization, and the proposed model outperforms conventional ones in terms of robustness of placement plans and total cost.
Distributed Real-time Optimal Power Flow Strategy for DC Microgrid Under Stochastic Communication Networks

This paper addresses a distributed real-time optimal power flow (RTOPF) strategy for DC microgrids. In this paper, we focus on the scenarios where local information sharing is conducted in stochastic communication networks subject to random failures. Most existing real-time optimal power flow (OPF) algorithms for the DC microgrid require all controllers to work in concert with a fixed network topology to maintain a zero gap between estimated global constraint violations. Thus, the high reliability of communication is required to ensure their convergence. To address this issue, the proposed RTOPF strategy tolerates stochastic communication failures and can seek the optimum with a constant step size considering the operation limitations of the microgrid. These aspects make the strategy suitable for real-time optimization, particularly when the communication is not reliable. In addition, this strategy does not require information from non-dispatchable devices, thereby reducing the number of sensors and controllers in the system. The convergence of the proposed strategy and the optimal equilibrium points are theoretically proven. Finally, simulations of a 30-bus DC microgrid are performed to validate the effectiveness of the proposed designs.
Optimal Scheduling of Residential Heating, Ventilation and Air Conditioning Based on Deep Reinforcement Learning

Residential heating, ventilation and air conditioning (HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that adapt to realtime electricity price signals formulated by demand response program and ambient temperature can significantly reduce electricity costs while ensuring occupants' comfort. However, since the pricing process and weather conditions are affected by many factors, conventional model-based method is difficult to meet the scheduling requirements in complex environments. To solve this problem, we propose an adaptive optimal scheduling strategy for residential HVAC based on deep reinforcement learning (DRL) method. The scheduling problem can be regarded as a Markov decision process (MDP). The proposed method can adaptively learn the state transition probability to make economical decision under the tolerance violations. Specifically, the residential thermal parameters obtained by the least-squares parameter estimation (LSPE) can provide a basis for the state transition probability of MDP. Daily simulations are verified under the electricity prices and temperature data sets, and numerous experimental results demonstrate the effectiveness of the proposed method.
A critical review of carbonate reservoir wettability modification during low salinity waterflooding

The nature of carbonate reservoirs promotes the adsorption of oil onto the rock surface hence making oil recovery a challenge even with the interventions of varied chemical EOR methods.Recently,low salinity water flooding has become of great interest since it is cost-effective and environmentally friendly.Although low salinity waterflooding has been highly investigated in sandstone reservoirs,it is not the same for carbonate reservoirs due to its complexities.Nonetheless,it has been proposed as a favourable technique to mobilise the trapped oil in carbonate reservoirs.Wettability alteration is regarded as the most accepted mechanism for low salinity flooding but has not been well understood making field scale applications doubtful.In this paper,we present a detailed review of the wettability alteration mechanisms in carbonate reservoirs during low salinity waterflooding.Parameters influencing wettability alteration in carbonates and the interactions that occur at the rock/brine/oil interface are also presented.The different methods utilised for wettability measurements during low salinity waterflooding are also reviewed including their drawbacks and advantages and recommendations.This will provide an improved understanding of the low salinity flooding application in carbonate reservoirs.
Study on the supercritical phase behavior of Yaha condensate gas reservoir in Tarim Basin

Yaha condensate gas reservoir is condensate gas reservoir developed by gas injection in the Tarim Basin.The practice of gas injection in condensate gas reservoir shows that the key to improve gas injection effect is to control gas channeling.Dynamic monitoring shows that there is no instantaneous miscibility between dry gas and condensate gas during gas injection.Based on the principle of entropy increase and mass transfer kinetics,the phase behavior of condensate gas and dry gas in reservoir is analyzed theoretically.The new technique to improve condensate recovery is adopted for condensate gas field.By using the density difference and seepage characteristics of dry gas and condensate gas,the injected dry gas cap is formed at the top of the gas reservoir,and the three-dimensional displacement is realized by the expansion of dry gas cap.Gas injection gravity assisted flooding technology is to realize vertical displacement of injected gas through the expansion of dry gas cap by using gravity differentiation caused by gas density difference.This technology can keep the front edge of gas injection advance evenly and solve the problem of gas channeling in the process of cyclic gas injection.
Differences in pseudogene evolution contributed to the contrasting flavors of turnip and Chiifu, two Brassica rapa subspecies

Pseudogenes are important resources for investigation of genome evolution and genomic diversity because they are nonfunctional but have regulatory effects that influence plant adaptation and diversification. However, few systematic comparative analyses of pseudogenes in closely related species have been conducted. Here, we present a turnip(Brassica rapa ssp. rapa)genome sequence and characterize pseudogenes among diploid Brassica species/subspecies. The results revealed that the number of pseudogenes was greatest in Brassica oleracea(CC genome), followed by B. rapa(AA genome)and then Brassica nigra(BB genome), implying that pseudogene differences emerged after species differentiation. In Brassica AA genomes, pseudogenes were distributed asymmetrically on chromosomes because of numerous chromosomal insertions/rearrangements, which contributed to the diversity among subspecies. Pseudogene differences among subspecies were reflected in the flavor-related glucosinolate(GSL)pathway. Specifically, turnip had the highest content of pungent substances, probably because of expansion of the methylthioalkylmalate synthase-encoding gene family in turnips; these genes were converted into pseudogenes in B. rapa ssp. pekinensis(Chiifu). RNA interference-based silencing of the gene encoding 2-oxoglutarate-dependent dioxygenase 2, which is also associated with flavor and anticancer substances in the GSL pathway, resulted in increased abundance of anticancer compounds and decreased pungency of turnip and Chiifu. These findings revealed that pseudogene differences between turnip and Chiifu influenced the evolution of flavor-associated GSL metabolism-related genes, ultimately resulting in the different flavors of turnip and Chiifu.
Identification, biogenesis, function, and mechanism of action of circular RNAs in plants

CircularRNAs(circRNAs)are a class of single-stranded, closedRNAmolecules with unique functions that are ubiquitously expressed in all eukaryotes. The biogenesis of circRNAs is regulated by specific cis-acting elements and trans-acting factors in humans and animals. circRNAs mainly exert their biological functions by acting as microRNA sponges, forming R-loops, interacting with RNA-binding proteins, or being translated into polypeptides or proteins in human and animal cells. Genome-wide identification of circRNAs has been performedin multiple plant species, and the results suggest that circRNAs are abundant and ubiquitously expressed in plants. There is emerging compelling evidence to suggest that circRNAs play essential roles during plant growthanddevelopment as well as inthe responses to bioticandabiotic stress.However,compared with recent advances in human and animal systems, the roles of most circRNAs in plants are unclear at present. Here we review the identification, biogenesis, function, and mechanism of action of plant circRNAs, which will provide a fundamental understanding of the characteristics and complexity of circRNAs in plants.
Ribosome profiling reveals the translational landscape and allele-specific translational efficiency in rice

Translational regulation is a critical step in the process of gene expression and governs the synthesis of proteins from mRNAs.Many studies have revealed translational regulation in plants in response to various environmental stimuli.However,there have been no studies documenting the comprehensive landscape of translational regulation and allele-specific translational efficiency in multiple plant tissues,especially those of rice,a main staple crop that feeds nearly half of the world's population.Here we used RNA sequencing and ribosome profiling data to analyze the transcriptome and translatome of an elite hybrid rice,Shanyou 63 (SY63),and its parental varieties Zhenshan 97 and Minghui 63.The results revealed that gene expression patterns varied more among tissues than among varieties at the transcriptional and translational levels.We identified 3392 upstream open reading frames (uORFs),and the uORF-containing genes were enriched in transcription factors.Only 668 of 13 492 long non-coding RNAs could be translated into peptides.Finally,we discovered numerous genes with allele-specific translational efficiency in SY63 and demonstrated that some cis-regulatory elements may contribute to allelic divergence in translational efficiency.Overall,these findings may improve our understanding of translational regulation in rice and provide information for molecular breeding research.
通过预植入氟原子形成"嵌入型"SEI构筑高性能钠金属电池

钠金属的不均匀沉积/剥离和不可控的界面反应是影响钠金属电池(SMBs)循环寿命和容量的主要因素.与锂金属相比,由于钠金属的活泼性更强,与电解质接触后更容易给出电子,导致钠金属表面更难形成致密而坚固的固体电解质相间(SEI).此外,钠金属的机械模量更低,更容易导致苔藓钠的持续溶解,继而进一步消耗电解质造成死钠形成.这些独特的性质决定钠的沉积行为倾向于表面生长模式,钠在成核点处的各向异性和不均匀积累生长,会导致大量的沉积颗粒黏附在隔膜上并造成电池的快速失效.一个理想的SEI不仅要有特定的结构和组成,更重要的是要实现与金属电极的紧密结合,以促进快速和致密的钠电镀/剥离过程.然而,到目前为止,没有报道过一个可以在金属钠中生根和固定的SEI,实现与电极的紧密连接,解决SMBs循环稳定性差的问题.我们基于功能分子双三氟乙酰胺(ECDA)和氟代碳酸乙烯酯(FEC)的相互作用,设计了一种可以通过原位预植入F原子而形成扎根于金属的"嵌入型"SEI(R-SEI).通过多项实验表征与分子动力学模拟表明,该R-SEI具有立体多层结构和浓度梯度组分等特点,加速Na~+的传输,促进了纳米球形沉积颗粒的形成.最终在高压全电池上表现出优异的电池性能.该成果发表在Energy & Environmental Science.
三明治结构金属有机框架复合材料的微环境调控优化光催化制氢

太阳能光催化制氢是有希望解决全球能源危机的可行性手段,提高人工光催化剂的效率是该领域面临的核心问题.由于催化位点与周围微环境之间的协同作用,天然酶表现出超高的催化效率.受此启发,研究人员在热催化剂的催化位点周围制造合适的微环境,有效提高了催化效率.然而,由于在光催化反应中光激发、电荷分离和表面反应等多过程相互纠缠、相互影响,这给利用微环境调控优化光催化性能带来巨大的挑战.应对挑战的有效手段就是构建可以在原子精度上调节光敏剂和催化单元周围微环境的平台.金属有机框架(metal-organic frameworks, MOFs)是一类由金属节点和有机配体构成的多孔晶体材料,在多相催化领域引起广泛关注.尤其是其具有结构精确、孔环境可变和结构、成分灵活可调等特性,可以促进原子尺度上精确的微环境调制,在光催化方面显示出极大的潜力.此外,一些具有新型结构的MOF复合材料,如三明治结构、蛋壳结构已被成功合成并且实现了复杂的催化功能.因此, MOF材料是研究光催化中微环境调节作用的重要模型,其中UiO-66型MOF具有优异的结构可定制型和稳定性,已被广泛应用于光催化领域,是研究微环境调制的理想平台.
Clock基因多态性与不同发情模式绵羊产羔数的关联分析

本研究旨在探究绵羊Clock基因g.70873128G>A、g.70875941C>T和g.70885750G>T位点多态性与绵羊产羔数之间的关系,以期为绵羊高繁殖力分子育种提供新的遗传标记。利用Sequenom MassARRAY®SNP技术对常年发情绵羊品种(小尾寒羊、湖羊和策勒黑羊)和季节性发情绵羊品种(滩羊、苏尼特羊和草原型藏羊)Clock基因3个多态位点多态性进行检测,并与小尾寒羊产羔数进行关联分析。分型结果表明:g.70873128G>A位点存在AA、AG和GG 3种基因型,g.70875941C>T位点存在TT、TC和CC 3种基因型,g.70885750G>T位点存在GG、GT和TT 3种基因型。群体遗传学分析表明:3个位点基因型频率和等位基因频率在2种发情模式绵羊品种间均达到差异极显著水平。g.70873128G>A位点在滩羊和草原型藏羊中表现为中度多态(0.25
2022中国孤立性房颤复合消融治疗专家共识

心房颤动(房颤)是常见、复杂且严重危害人类健康和生命安全的一种疾病,可显著增加患者血栓栓塞、心力衰竭和死亡的风险。房颤在一般人群中的患病率为0.4%~1.0%,成人患病率为2%~4%,目前全世界房颤患者超过5 900万,我国有800~2 000万房颤患者。随着社会老龄化发展,预计未来20~30年患者可能翻倍。
重力异常揭示印度大陆地幔岩石圈在喜马拉雅东部之下陡俯冲

印度大陆地幔岩石圈(ICML)在印-亚碰撞带之下的几何结构和变形对于了解陆-陆汇聚模式至关重要.本文利用重力数据和地震速度模型,估算了藏南地区上地幔剩余重力异常,然后通过三维重力反演构建了上地幔密度模型.结果显示,在喜马拉雅东部之下的上地幔中存在低密度异常,其东西长约300km,南北宽约100km;而在喜马拉雅西部之下则没有明显的密度异常.低密度异常的西界对应于亚东-谷露裂谷(地表经度为89°~90°E),南界可能代表地幔缝合线,位于28°N附近(即雅鲁藏布江缝合带以南约130km处).研究认为,与西部的ICML近水平俯冲不同,东部的ICML可能为陡俯冲,并可能伴随软流圈上涌.这种横向变化的几何结构表明, ICML可能在地幔缝合线与亚东-谷露裂谷在上地幔的交点处发生了重大撕裂. ICML撕裂以及在东部陡俯冲这一地质过程可能与藏南裂谷的发育以及喜马拉雅-冈底斯东部的中新世岩浆活动、成矿作用有关.
Multitask Learning with Multiscale Residual Attention for Brain Tumor Segmentation and Classification

Automatic segmentation and classification of brain tumors are of great importance to clinical treatment. However, they are challenging due to the varied and small morphology of the tumors. In this paper, we propose a multitask multiscale residual attention network (MMRAN) to simultaneously solve the problem of accurately segmenting and classifying brain tumors. The proposed MMRAN is based on U-Net, and a parallel branch is added at the end of the encoder as the classification network. First, we propose a novel multiscale residual attention module (MRAM) that can aggregate contextual features and combine channel attention and spatial attention better and add it to the shared parameter layer of MMRAN. Second, we propose a method of dynamic weight training that can improve model performance while minimizing the need for multiple experiments to determine the optimal weights for each task. Finally, prior knowledge of brain tumors is added to the postprocessing of segmented images to further improve the segmentation accuracy. We evaluated MMRAN on a brain tumor data set containing meningioma, glioma, and pituitary tumors. In terms of segmentation performance, our method achieves Dice, Hausdorff distance (HD), mean intersection over union (MIoU), and mean pixel accuracy (MPA) values of 80.03%, 6.649 mm, 84.38%, and 89.41%, respectively. In terms of classification performance, our method achieves accuracy, recall, precision, and F1-score of 89.87%, 90.44%, 88.56%, and 89.49%, respectively. Compared with other networks, MMRAN performs better in segmentation and classification, which significantly aids medical professionals in brain tumor management. The code and data set are available at https://github.com/linkenfaqiu/MMRAN.
Soliton molecules for combined mKdV-type bilinear equation

Starting from the multi-soliton solutions obtained by the Hirota bilinear method, the soliton molecule structures for the combined mKdV-type bilinear equation (D_t +Σ _(n=1)~N α_nD_x~(2n+1))f~*·f=0 are investigated using the velocity resonance mechanism. The two-soliton molecules of the mKdV-35 equation and the three-soliton molecules of the mKdV-357 equation are specifically demonstrated in this paper. With particular selections of the involved arbitrary parameters, especially the wave numbers, it is confirmed that, besides the usual multi-bright soliton molecules, the multi-dark soliton molecules and the mixed multibright- dark soliton molecules can also be obtained. In addition, we discuss the existence of the multi-soliton molecules for the combined mKdV-type bilinear equation with more higher order nonlinear terms and dispersions. The results demonstrate that when N ≥ 4, the combined mKdVtype bilinear equation no longer admits soliton molecules comprising more than four solitons.
ABC-AF-Stroke score predicts thromboembolism in nonanticoagulated patients following successful atrial fibrillation ablation:a report from the Chinese Atrial Fibrillation Registry

Background:The age,biomarkers,and clinical history (ABC)-atrial fibrillation (AF)-Stroke score have been proposed to refine stroke risk stratification,beyond what clinical risk scores such as the CHA_2DS_2-VASc score can offer.This study aimed to identify risk factors associated with thromboembolism and evaluate the performance of the ABC-AF-Stroke score in predicting thromboembolism in non-anticoagulated AF patients following successful ablations.Methods:A total of 2692 patients who underwent successful ablations with discontinued anticoagulation after a 3-month blanking period in the Chinese Atrial Fibrillation Registry (CAFR) between 2013 and 2019 were included.Cox regression analysis was conducted to present the association of risk factors with thromboembolism risk.The ABC-AF-Stroke score was evaluated in terms of discrimination,including concordance index (C-index),net reclassification improvement (NRI) and integrated discrimination improvement (IDI),clinical utilization by decision curve analysis (DCA),and calibration by comparing the predicted risk with the observed annualized event rate.Results:After a median follow-up of 3.5 years,64 patients experienced thromboembolism events.Age,prior history of stroke/transient ischemic attack (TIA),high-sensitivity cardiac troponin T (cTnT-hs),and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were independently associated with thromboembolism risk.The ABC-AF-Stroke score performed statistically significantly better than the CHA_2DS_2-VASc score in terms of C-index (0.67,95% confidence interval [CI]:0.59-0.74 vs.0.60,95% CI:0.52-0.67,P = 0.030) and reclassification capacity.The DCA implied that the ABC-AF-Stroke score could identify more thromboembolism events without increasing the false positive rate compared to the CHA_2DS_2-VASc score.The calibration curve showed that the ABC-AF-Stroke score was well calibrated in this population.Conclusions:In this real-world study enrolling non-anticoagulated AF patients following successful ablations,age,prior history of stroke/TIA,level of NT-proBNP,and cTnT-hs were independently associated with an increased risk of thromboembolism.The ABC-AF-Stroke score was well-calibrated and statistically significantly outperformed the CHA_2DS_2-VASc score in predicting thromboembolism risk.
Thermal Stability and Electrochemical Properties of Separators for Lithium-ion Batteries

The mechanical properties, contact angle, thermomechanical and electrochemical properties of PE, PVDF, and ceramic separators were compared. The experimental results show that the PE separator has the largest porosity, the PVDF separator has the best mechanical properties, wettability, and heat resistance. Three kinds of separators were assembled into lithium-ion batteries for electrochemical tests. Among them, the PE separator has the best rate performance, and the ceramic separator has poor performance in charge-discharge cycles. At the same time, the PE and ceramic separators were tested with different amounts of electrolytes at room temperature and a high temperature, and it is found that the capacity of the PE separator is higher at room temperature, while the performance of the ceramic separator is better at a high temperature. The amount of electrolyte also has a certain influence on its electrochemical performance.