mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
To Include Dyslipidemia Management into National Basic Public Health Service: from Project Practice to Policy

As cardiovascular diseases have been increasingly endangering the health and quality of life of Chinese residents, all relevant parties have been actively looking for policies and measures to effectively control the risk factors of the diseases. Hypertension and diabetes have been included in the National Basic Public Health Service Project since 2009; however, as one of the most crucial risk factors for cardio-cerebrovascular diseases, dyslipidemia has not yet been covered by the project due to various reasons. The prevalence of dyslipidemia in China increased rapidly from 18.6% in 2002 to 40.4% in 2012(1), whereas the management of dyslipidemia has been lagging behind and become the "short board" in the prevention and control of cardiocerebrovascular diseases.
Self-Reported Food Allergy Prevalence Among Elementary School Children-Nanchang City, Jiangxi Province, China, 2021

What is already known about this topic? The prevalence of food allergy(FA) among the general population has been increasing in recent decades, and seriously affects the physical and mental health and the quality of life of many people-especially children. What is added by this report? The survey estimated self-reported FA prevalence using a standardized FA questionnaire among school children in Nanchang City, Jiangxi Province, China in 2021. What are the implications for public health practice? Based on the local, epidemiological characteristics of food allergy, public policies on the prevention and management of FA should be developed and preventive practices should be promoted to decrease the overall prevalence of FA.
Field Evaluation of a Duplex RT-RAA Assay for Rapid Detection of SARS-CoV-2—Hebei Province, China, January 2021

Introduction: Recently, a local cluster epidemic has occurred in Shijiazhuang City, Hebei Province. Failure to promptly identify patients with fever in rural areas was the major reason for this epidemic. Methods: We presented the field evaluation of a new real-time reverse transcription recombinase-aided amplification (RT-RAA) kit incorporating an endogenous internal control in a single-tube format, completed at the Hebei CDC from January 17, 2021 to January 27, 2021. Results: We evaluated the diagnostic performance of RT-RAA assay using automatic extracted RNA of 808 clinical samples. Compared with reverse transcriptase real-time quantitative PCR (qRT-PCR), RT-RAA kit achieved 92.41% sensitivity, 98.78% specificity and a 96.29% coincidence rate, demonstrating an excellent agreement between the RTRAA assay and qRT-PCR assay. Furthermore, 58 samples were extracted using a manual extraction method within 5 minutes, but only samples with high nucleic acid concentration (cycle threshold value not higher than 32) could be stably detected. Discussion: The RT-RAA is more suitable to meet the needs of rapid, sensitive, and accurate detection in community-level medical institutions.
A multiscale polymerization framework towards network structure and fracture of double-network hydrogels

Double-network(DN) hydrogels, consisting of two contrasting and interpenetrating polymer networks, are considered as perhaps the toughest soft-wet materials. Current knowledge of DN gels from synthesis methods to toughening mechanisms almost exclusively comes from chemically-linked DN hydrogels by experiments. Molecular modeling and simulations of inhomogeneous DN structure in hydrogels have proved to be extremely challenging. Herein, we developed a new multiscale simulation platform to computationally investigate the early fracture of physically-chemically linked agar/polyacrylamide(agar/PAM) DN hydrogels at a long timescale. A "random walk reactive polymerization"(RWRP) was developed to mimic a radical polymerization process, which enables to construct a physically-chemically linked agar/PAM DN hydrogel from monomers, while conventional and steered MD simulations were conducted to examine the structural-dependent energy dissipation and fracture behaviors at the relax and deformation states. Collective simulation results revealed that energy dissipation of agar/PAM hydrogels was attributed to a combination of the pulling out of agar chains from the DNs, the disruption of massive hydrogen bonds between and within DN structures, and the strong association of water molecules with both networks, thus explaining a different mechanical enhancement of agar/PAM hydrogels. This computational work provided atomic details of network structure, dynamics, solvation, and interactions of a hybrid DN hydrogel, and a different structural-dependent energy dissipation mode and fracture behavior of a hybrid DN hydrogel, which help to design tough hydrogels with new network structures and efficient energy dissipation modes. Additionally, the RWRP algorithm can be generally applied to construct the radical polymerization-produced hydrogels, elastomers, and polymers.
TriCTI:an actionable cyber threat intelligence discovery system via trigger-enhanced neural network

The cybersecurity report provides unstructured actionable cyber threat intelligence (CTI) with detailed threat attack procedures and indicators of compromise (IOCs),e.g.,malware hash or URL (uniform resource locator) of command and control server.The actionable CTI,integrated into intrusion detection systems,can not only prioritize the most urgent threats based on the campaign stages of attack vectors (i.e.,IOCs) but also take appropriate mitigation measures based on contextual information of the alerts.However,the dramatic growth in the number of cybersecurity reports makes it nearly impossible for security professionals to find an efficient way to use these massive amounts of threat intelligence.In this paper,we propose a trigger-enhanced actionable CTI discovery system (TriCTI) to portray a relationship between IOCs and campaign stages and generate actionable CTI from cybersecurity reports through natural language processing (NLP) technology.Specifically,we introduce the "campaign trigger"for an effective explanation of the campaign stages to improve the performance of the classification model.The campaign trigger phrases are the keywords in the sentence that imply the campaign stage.The trained final trigger vectors have similar space representations with the keywords in the unseen sentence and will help correct classification by increasing the weight of the keywords.We also meticulously devise a data augmentation specifically for cybersecurity training sets to cope with the challenge of the scarcity of annotation data sets.Compared with state-of-the-art text classification models,such as BERT,the trigger-enhanced classification model has better performance with accuracy (86.99%) and F1 score (87.02%).We run TriCTI on more than 29k cybersecurity reports,from which we automatically and efficiently collect 113,543 actionable CTI.In particular,we verify the actionability of discovered CTI by using large-scale field data from VirusTotal (VT).The results demonstrate that the threat intelligence provided by VTlacks a part of the threat context for IOCs,such as the Actions on Objectives campaign stage.As a comparison,our proposed method can completely identify the actionable CTI in all campaign stages.Accordingly,cyber threats can be identified and resisted at any campaign stage with the discovered actionable CTI.
Investigation of three different cooling treatments on dynamic mechanical properties and fragmentation characteristics of granite subjected to thermal cycling

Underground thermal engineering such as geothermal exploitation usually involves the response of impact loads due to the drilling operation and blasting load. This study investigated the dynamic mechanical properties and fragmentation characteristics of granite subjected to thermal cycling under natural cooling, water cooling, and liquid nitrogen cooling. Firstly, split Hopkinson pressure bar tests were performed on granite under three different cooling methods to study the dynamic mechanical parameters with thermal cycles. Subsequently, the damage factors were calculated to evaluate the damage on granite and the relationship between damage and stress. Finally, the granite fragments after impact were sieved, and the fractal dimension and average fragment size were introduced to analyze the fragmentation characteristics. The results demonstrate that the degradation of dynamic mechanical properties mainly occurs in the first four thermal cycles; with the increase of damage factor, the stress decreases linearly under the three cooling methods, and the damage caused by liquid nitrogen cooling to granite is the most significant, followed by water cooling. Fragments of granite change from axial splitting failure to a more complex composite failure mode. In addition, with the decrease of the average fragment size, the fractal dimension of the granite gradually increases, resulting in the higher fragmentation degree and the better uniformity of fragmentation.
Numerical study on rock failure around a tunnel destressed by a conceptualized notched technique

A destressing method for reducing the strainburst risk in burst-prone grounds is suggested.In this method,the rock is destressed by cutting notches at the excavation boundary.First,the concept of the proposed method is described both analytically and numerically.Then,the method is applied to a tunneling problem.Several numerical models are built to study the destressing process and the failure mechanism around a circular tunnel.Results show that when the notch is added to the model,the rock at the tunnel wall is destressed,and the stress concentration zones shift to a farther distance away from the wall.Also,the analysis of the failure zone around the tunnel and the velocity of the failed elements show that the failure in the notched tunnel is less violent compared to that in the tunnel without the notch.Finally,a parametric study is conducted to investigate the influences of the notch dimensions on the stress distribution,deformation,and failures around the tunnel.
Response of operating metro tunnels to compensation grouting of an underlying large-diameter shield tunnel:A case study in Hangzhou

Due to the shield tunneling underneath,long-term settlements may develop in the existing metro tunnels.The compensation grouting is applied worldwide to stabilize the settlement of ground and existing structures.Few field studies concerning large-diameter shield passing tunnel from below have analyzed the interaction between the compensation grouting and the existing tunnel.This paper presents a case study on the response of the operating metro tunnels to the compensation grouting of an underlying large-diameter tunnel in muddy clay stratum.The tunnel deformations before,during,and after the compensation grouting were monitored and analyzed.The long-term tunnel settlements were mitigated and stabilized by the timely compensation grouting.Smaller settlement rates were observed during the grouting treatment,and the settlement was gradually stabilized three months after the grouting.The grouting holes at the tunnel invert were used initially for better grouting efficiency.The horizontal displacement and convergence developed during the grouting construction and remained stable after the grouting process.Moreover,some limitations of the grouting treatment were discussed.The tunnel settlement in the section close to the center-line of the south-line tunnel cannot be prevented effectively.The differential displacement cannot be reduced by this grouting program.
Deposition chamber technology as building blocks for a standardized brain-on-chip framework

The in vitro modeling of human brain connectomes is key to exploring the structure-function relationship of the central nervous system. Elucidating this intricate relationship will allow better studying of the pathological mechanisms of neurodegeneration and hence result in improved drug screenings for complex neurological disorders, such as Alzheimer's and Parkinson diseases. However, currently used in vitro modeling technologies lack the potential to mimic physiologically relevant neural structures. Herein, we present an innovative microfluidic design that overcomes one of the current limitations of in vitro brain models: their inability to recapitulate the heterogeneity of brain regions in terms of cellular density and number. This device allows the controlled and uniform deposition of any cellular population within unique plating chambers of variable size and shape. Through the fine tuning of the hydrodynamic resistance and cell deposition rate, the number of neurons seeded in each plating chamber can be tailored from a thousand up to a million. By applying our design to so-called neurofluidic devices, we offer novel neuro-engineered microfluidic platforms that can be strategically used as organ-on-a-chip platforms for neuroscience research. These advances provide essential enhancements to in vitro platforms in the quest to provide structural architectures that support models for investigating human neurodegenerative diseases.
Reconfiguration of PV Arrays (T-C-T,B-L, H-C) Considering Wiring Resistance

Partial shadings on the photovoltaic (PV) array causes reduction in maximum power generation. Reconfiguration of PV arrays plays an important role in increasing the maximum power generation from PV array configurations under partial shadings. In general, partial shadings on the PV arrays are concentrated on a group of modules. Therefore, the distribution of shading over the array increases the maximum power generation. This paper uses a modified Sudoku pattern to increase the maximum power generation from the PV array configurations. The PV array configurations are analyzed by considering column wiring resistance and cross ties resistance. The modified Sudoku pattern is applied to Total-Cross-Tied (T-C-T), Bridge-Link (B-L) and Honey-Comb (H-C) configurations and their performances are analyzed under various shading patterns, such as short narrow, short wide, long narrow, long wide, middle and diagonal. The specifications,such as Global Maximum Power (GMP), Mismatch losses, Fill Factor, Efficiency are considered to see the efficacy of various PV array configurations and their reconfigurations. From the results, it can be concluded that reconfigured T-C-T PV array generates the highest GMP compared to other configurations under considered shading patterns.
Economic Profit Enhancement of a Demand Response Aggregator Through Investment of Large-scale Energy Storage Systems

To provide flexibility for the operation of smart electricity networks, a large number of scattered demand response resources are managed by a demand response aggregator (DRA). Increasing the economic viability of this new entity, i.e.,DRA, has attracted a great deal of attention in recent years. Following this direction, this paper proposes stochastic model of multiple large-scale energy storage system (LESS) investments from the perspective of a DRA. A LESS directly connects to smart distribution networks and provides the possibility to save energy costs and thereafter increase the energy efficiency of the DRA. In this paper, a novel mixed-integer model is proposed to determine the optimal capacity and operation of a LESS in coordination with a DR scheme. The model, as a main contribution to literature, comprises novel managerial options, such as the number of allowed DR actions, the number of allowed charging and discharging. Moreover, the model is designed to be capable enough to exclude the hours in which the demand side is not allowed to participate in DR. The proposed model is tested through a numerical example with various case studies. The simulation results show the substantial economic impacts of considering the introduced managerial options in the coordination of a LESS operation with DR.
Hybrid q-Rung Orthopair Fuzzy Sets Based CoCoSo Model for Floating Offshore Wind Farm Site Selection in Norway

Unlocking offshore wind farms' high energy generation potential requires a comprehensive multi-disciplinary analysis that consists of intensive technical, economic, logistical, and environmental investigations. Offshore wind energy projects have high investment volumes that make it essential to conduct extensive site selection to ensure feasible investment decisions that reduce the potential financial risks. Depending on the scenario and circumstances, a ranking of alternative offshore wind energy projects helps to prioritise the investment decisions. Decisionmaking algorithms based on expert knowledge can support the prioritisation and thus alleviate the work load for investment decisions in the future. The case study considered here is to find the best site for a floating offshore wind farm in Norway from four pre-selected alternatives: Utsira Nord, Stadthavet, Froyabanken, and Traena Vest. We propose a hybrid decisionmaking model as a combined compromised solution (CoCoSo) based on the q-rung orthopair fuzzy sets (q-ROFSs) including the weighted q-rung orthopair fuzzy Hamacher average (Wq-ROFHA) and the weighted q-rung orthopair fuzzy Hamacher geometric mean (Wq-ROFHGM) operators. In this model, the q-ROFSs based full consistency method (FUCOM) is introduced as a new methodology to determine the weights of the decision criteria. The results of the proposed model show that the best site among the investigated four alternatives is A1: Utsira Nord. A sensitivity analysis has verified the stability of the proposed decision-making model.
Stochastic Economic Dispatch Considering the Dependence of Multiple Wind Farms Using Multivariate Gaussian Kernel Copula

Wind farms usually cluster in areas with abundant wind resources. Therefore, spatial dependence of wind speeds among nearby wind farms should be taken into account when modeling a power system with large-scale wind power penetration. This paper proposes a novel non-parametric copula method, multivariate Gaussian kernel copula (MGKC), to describe the dependence structure of wind speeds among multiple wind farms. Wind speed scenarios considering the dependence among different wind farms are sampled from the MGKC by the quasi-Monte Carlo (QMC) method, so as to solve the stochastic economic dispatch (SED) problem, for which an improved mean-variance (MV) model is established, which targets at minimizing the expectation and risk of fuel cost simultaneously. In this model, confidence interval is applied in the wind speed to obtain more practical dispatch solutions by excluding extreme scenarios, for which the quantile-copula is proposed to construct the confidence interval constraint. Simulation studies are carried out on a modified IEEE 30-bus power system with wind farms integrated in two areas, and the results prove the superiority of the MGKC in formulating the dependence among different wind farms and the superiority of the improved MV model based on quantile-copula in determining a better dispatch solution.
Exosomal miR-155 from gastric cancer induces cancer-associated cachexia by suppressing adipogenesis and promoting brown adipose differentiation via C/EPBβ

Objective: The aim of this research was to identify whether exosomes were involved in impairing adipogenesis in cancer-associated cachexia(CAC) by detecting the adipodifferentiation capacity and the expressions of adipogenic proteins in gastric cancer(GC)-associated adipocytes. Methods: Western blotting and RT-PCR were used to investigate the expressions of C/EPBβ, C/EPBa, PPARγ, and UCP1 in adipose mesenchymal stem cells(A-MSCs) to evaluate the function of exosomal miR-155. BALB/c nude mice were intravenously injected in vivo with GC exosomes with different levels of miR-155 to determine changes in adipodifferentiation of A-MSCs. Results: Exosomes derived from GC cells suppressed adipogenesis in A-MSCs as characterized by decreased lipid droplets. Similarly, A-MSCs co-cultured with GC exosomes exhibited increased ATP production through brown adipose differentiation characterized by highly dense mitochondria and enhanced UCP1 expression(P < 0.05). Mechanistically, exosomal miR-155 secreted from GC cells suppressed adipogenesis and promoted brown adipose differentiation by targeting C/EPBβ, accompanied by down regulated C/EPBa and PPARγ and upregulated UCP1(P < 0.05). Moreover, overexpression of miR-155 in GC exosomes improved CAC in vivo, which was characterized by fat loss, suppressed expressions of C/EPBβ,C/EPBa, and PPARγ in A-MSCs, and high expression of UCP1(P < 0.05). Decreasing the level of miR-155 in injected GC exosomes abrogated the improved CAC effects. Conclusions: GC exosomal miR-155 suppressed adipogenesis and enhanced brown adipose differentiation in A-MSCs by targeting C/EPBβ of A-MSCs, which played a crucial role in CAC.
Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets

Objective: The aim of this study was to identify hub genes associated with immune cell infiltration in breast cancer through bioinformatic analyses of multiple datasets. Methods: Nonparametric(NOISeq) and robust rank aggregation-ranked parametric(EdgeR) methods were used to assess robust differentially expressed genes across multiple datasets. Protein-protein interaction network, GO, KEGG enrichment, and subnetwork analyses were performed to identify immune-associated hub genes in breast cancer. Immune cell infiltration was evaluated with the CIBERSORT, XCELL, and TIMER methods. The association between the hub gene-based risk signature and survival was determined through Kaplan-Meier survival analysis, multivariate Cox analysis, and a nomogram with external verification. Results: We identified 163 robust differentially expressed genes in breast cancer through applying both nonparametric and parametric methods to multiple GEO(n = 2,212) and TCGA(n = 1,045) datasets. Integrated bioinformatic analyses further identified 10 hub genes: CXCL10, CXCL9,CXCL11, SPP1, POSTN, MMP9, DPT, COLIA1,ADAMDEC1,and RGS1. The 10 hub-gene-based risk signature significantly correlated with the prognosis of patients with breast cancer. Moreover, these hub genes were strongly associated with the extent of infiltration of CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and myeloid dendritic cells into breast tumors. Conclusions: Integrated analyses of multiple databases led to the discovery of 10 robust hub genes that together may serve as a risk factor characteristic of the immune microenvironment in breast cancer.
Agronomical selection on loss-of-function of GIGANTEA simultaneously facilitates soybean salt tolerance and early maturity

Salt stress and flowering time are major factors limiting geographic adaptation and yield productivity in soybean (Glycine max).Although improving crop salt tolerance and latitude adaptation are essential for efficient agricultural production,whether and how these two traits are integrated remains largely unknown.Here,we used a genome-wide association study to identify a major salt-tolerance locus controlled by E2,an ortholog of Arabidopsis thaliana GIGANTEA (GI).Loss of E2 function not only shortened flowering time and maturity,but also enhanced salt-tolerance in soybean.E2 delayed soybean flowering by enhancing the transcription of the core flowering suppressor gene E1,thereby repressing Flowering Locus T (FT) expression.An E2 knockout mutant e2~(CR) displayed reduced accumulation of reactive oxygen species (ROS) during the response to salt stress by releasing peroxidase,which functions in ROS scavenging to avoid cytotoxicity.Evolutionary and population genetic analyses also suggested that loss-of-function e2 alleles have been artificially selected during breeding for soybean adaptation to high-latitude regions with greater salt stress.Our findings provide insights into the coupled selection for adaptation to both latitude and salt stress in soybean;and offer an ideal target for molecular breeding of early-maturing and salttolerant cultivars.