mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Impact of climate change on outdoor design conditions and implications to peak loads

This study exams the impact of climate change on outdoor design conditions and peak loads of five Chinese cities over the five major climate zones for the winter and summer conditions.The design dry-bulb temperature (DDBT) and the coincident wet-bulb temperature (CWBT) for two 30-year periods;1971-2000 and 1984-2013 were analysed.It was found that the DDBT of the period 1984-2013 was higher than that of the period 1971-2000,whereas the CWBT and the corresponding outdoor enthalpy of the period 1984-2013 was lower than that of 1971-2000 at the various cumulative frequencies.This trend implies that the increment in conductive heat gain through the building envelope due to the rising temperature can be lower than the reduction in fresh air load due to the lower outdoor air enthalpy.In this case,the peak cooling loads may reduce in all five cities under study,and this is different from the widely held view that global warming will lead to more stringent outdoor design conditions,higher peak cooling loads and larger heating,ventilation and air conditioning (HVAC) plants than the current or historical status.The implications to the "free-cooling" of HVAC systems with enthalpy control are discussed as well.
Digital ID framework for human-centric monitoring and control of smart buildings

Smart offices can help employers attract and retain talented people and can positively impact well-being and productivity. Thanks to emerging technologies and increased computational power, smart buildings with a specific focus on personal experience are gaining attraction. Real-time monitoring and estimation of the human states are key to achieving individual satisfaction. Although some studies have incorporated real-time data into the buildings to predict occupants' indoor experience (e.g., thermal comfort and work engagement), a detailed framework to integrate personal prediction models with building systems has not been well studied. Therefore, this paper proposes a framework to predict and track the real-time states of each individual and assist with decision-making (e.g., room assignment and indoor environment control). The core idea of the framework is to distinguish individuals by a new concept of Digital ID (DID), which is then integrated with recognition, prediction, recommendation, visualization, and feedback systems. The establishment of the DID database is discussed and a systematic prediction methodology to determine occupants' indoor comfort is developed. Based on the prediction results, the Comfort Score Index (CSI) is proposed to give recommendations regarding the best-fit rooms for each individual. In addition, a visualization platform is developed for real-time monitoring of the indoor environment. To demonstrate the framework, a case study is presented. The thermal sensation is considered the reference for the room allocation, and two groups of people are used to demonstrate the framework in different scenarios. For one group of people, it is assumed that they are existing occupants with personal DID databases. People in another group are considered the new occupants without any personal database, and the public database is used to give initial guesses about their thermal sensations. The results show that the recommended rooms can provide better thermal environments for the occupants compared to the randomly assigned rooms. Furthermore, the recommendations regarding the indoor setpoints (temperature and lighting level) are illustrated using a work engagement prediction model. However, although specific indoor metrics are used in the case study to demonstrate the framework, it is scalable and can be integrated with any other algorithms and techniques, which can serve as a fundamental framework for future smart buildings.
A simulation-based evaluation of the absolute and comparative approaches in a code compliance process from the energy use perspective: Cold-climate case study

Like many countries, Canada's building code includes a performance compliance path that compares the energy use of a proposed design to that of a reference house. Today, provinces across Canada are contemplating an alternative absolute energy use intensity approach. However, the effect of adopting the absolute approach on house design is not well understood. This study first developed a proof-of-concept methodology for a technical simulation-based comparison of the two approaches. Then, it performed a comparative analysis between the design outcomes of the two approaches using the developed methodology. To this end, statistically representative archetypes were configured to comply with the prescriptive requirements of the building code. Key characteristics of each archetype were then varied through parametric study, and the resulting energy performance under the absolute and comparative approaches were analyzed. The results of this study indicated that the two approaches had different effects on the design and energy use of houses in heating-dominated climate zones. Houses performing better under the absolute approach consumed less energy and exhibited more compact architectural form. These houses were also less sensitive to improvements in airtightness and envelope than houses performing better under the comparative approach. The results suggest that adopting the absolute approach based on the energy use intensity metric in building codes would encourage design and construction of houses with higher energy efficiency.
Heat and mass transfer model optimization and annual energy efficiency analysis for energy recovery indirect evaporative cooling

Indirect evaporative cooling (IEC) is a kind of high efficiency,energy-saving and environmental protection cooling technology,which has been widely used in data centers and other fields in recent years.In this paper,the optimized two-dimensional non-condensation state model of indirect evaporative cooling was proposed.Meanwhile the computer program was updated to solve the developed mathematical model under variable fresh air conditions.The optimized model was verified by the experimental data,and the maximum deviation was only 4.6%.Based on the modified model and the annual hourly meteorological parameters in Tianjin,China,it was analyzed the optimal heat transfer area of IEC used as fresh air pre-cooling unit under various air volumes to provide references for system design and equipment selection.Finally,taking an IEC-primary return air conditioning system of a gymnasium as an example,the hourly energy-saving effect of whole year was simulated by the developed IEC model.The simulation results showed that IEC could control the fresh air temperature below 27 °C and the moisture content below 18 g/kg throughout the year,and undertook 102.6% of the total fresh air cooling load.The findings are useful in future system optimization and design of IEC equipment.
Effect of early atopic sensitization in children aged 0-2 years on the development of asthma symptoms at 9-11 years of age

Background Personal genetic predisposition and early life environmental factors are important for the development of childhood asthma. We aimed to search whether egg, milk and mite sensitizations at 0-2 years old are risk factors for asthma symptoms at 9-11 years old. Methods A total of 210 wheezer children who had specific immunoglobulin (Ig) E in 2010-2012 were included in the study (followed by pediatric allergy). Patients were divided into non-atopic (group 1, n = 157) and atopic patients [groups 2-7, n = 53 (5 patients were in both group 4 and group 5)] based on sensitizations. Using the International Study of Asthma and Allergy in Childhood questionnaire, current wheeze (CW, 2nd question), exercise wheezing (EW, 7th question), and dry cough (DC, 8th question) were surveyed. Also, parental allergies, eczema at 0-2 years, current eosinophil percentage and total IgE were recorded. Results Eczema was observed as an important risk factor [CW: odds ratio (OR) = 2.83, 95% confidence interval (CI) = 1.54-5.23, P ≤ 0.001; EW: OR = 2.71, 95% CI = 1.33-5.54, P = 0.006; DC: OR = 3.03, 95% CI = 1.47-6.25, P = 0.003], whereas having no atopic sensitization at 0-2-year-old (group 1) was found as a significant protective factor for asthma at 9-11 years old (CW: OR = 0.32, 95% CI = 0.15-0.70, P = 0.004; EW: OR = 0.21, 95% CI 0.10-0.44, P ≤ 0.001; DC: OR = 0.25, 95% CI = 0.10-0.59, P = 0.002). Conclusion Early personal eczema is a significant risk factor for the development of asthma symptoms at 9-11 years old, whereas not having an allergic sensitization at 0-2 years old (group 1) is an important protective factor.
Artemisinin derivative SM934 in the treatment of autoimmune and inflammatory diseases:therapeutic effects and molecular mechanisms

Artemisinin and its derivatives are the well-known anti-malarial drugs derived from a traditional Chinese medicine.In addition to antimalarial,artemisinin and its derivatives possess distinguished anti-cancer,anti-oxidant,anti-inflammatory and anti-viral activities,but the poor solubility and low bioavailability hinder their clinical application.In the last decades a series of new water-soluble and oil-soluble derivatives were synthesized.Among them,we have found a water-soluble derivative β-aminoarteether maleate (SM934) that exhibits outstanding suppression on lymphocytes proliferation in immunosuppressive capacity and cytotoxicity screening assays with 35-fold higher potency than dihydroartemisinin.SM934 displays significant therapeutic effects on various autoimmune and inflammatory diseases,including systemic lupus erythematosus,antiphospholipid syndrome nephropathy,membranous nephropathy,rheumatoid arthritis,multiple sclerosis,inflammatory bowel disease,and dry eye disease.Here,we summarize the immunomodulatory effects,anti-inflammatory,anti-oxidative and anti-fibrosis activities of SM934 in disease-relevant animal models and present the probable pharmacological mechanisms involved in its therapeutic efficacy.This review also delineates a typical example of natural product-based drug discovery,which might further vitalize natural product exploration and development in pharmacotherapy.
Eight-year trajectories of malalignment progression in symptomatic knee osteoarthritis

Background: Although various therapies have been developed to treat malalignment in osteoarthritic knees, the pattern of malalignment progression is still unclear. This study aimed to identify homogeneous subgroups with distinct trajectories of malalignment progression in subjects with symptomatic knee osteoarthritis (KOA) and to determine corresponding risk factors. Methods: Eight-year follow-up (from 2004 to 2012) data on 1252 participants with symptomatic KOA from the Osteoarthritis Initiative were included. Varus/valgus angle progression was characterized by group-based trajectory models. Time-varying covariates were introduced into the model to investigate how they affected trajectories. Multinomial logistic regression for trajectory group membership was applied to ascertain risk factors. Results: Five subgroups were identified. Participants in the varus worsening trajectory (n = 166) or valgus worsening trajectory (n = 118) proceeded to worsen malalignment over time. The neutral trajectory (n = 378),varus stable trajectory (n = 328),and valgus stable trajectory (n = 262) maintained close to the initial varus/valgus angle over 8 years. Higher baseline Kellgren and Lawrence grade (odds ratio [OR] = 4.35,P< 0.001 for varus; OR = 3.85, P < 0.001 for valgus) and “severe” baseline malalignment (OR = 13.57,P < 0.001 for varus; OR = 23.04, P < 0.001 for valgus) were risk factors for worsening trajectories. The cutoff point of the baseline varus/valgus angle to discriminate between stable or worsening trajectory was—4.50 for varus and 3.6° for valgus. Conclusions: This study identified the malalignment progression pattern—minor malalignment (—4.5° to +3.6°) tends to remain stable, while major baseline malalignment is likely to progress. This provides a reference for therapy to prevent malalignment from deteriorating and emphasizes the necessity of determining the trigger factors for malalignment onset.
Bronchiectasis and COVID-19 infection: a two-way street

Bronchiectasis (BE) has been linked to past viral infections such as influenza, measles, or adenovirus. Two years ago, a new pandemic viral infection severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke out and it still persists today, and a significant proportion of surviving patients have radiological and clinical sequelae, including BE. Our aim was to thoroughly review the information available in the literature on the bidirectional relationship between SARS-CoV-2 infection and the development of BE, as well as the impact of this infection on patients already suffering from BE. Available information indicates that only a small percentage of patients in the acute phase of coronavirus disease 2019 (COVID-19) pneumonia develop BE, although the latter is recognized as one of the radiological sequelae of COVID-19 pneumonia, especially when it is caused by traction. The severity of the initial pneumonia is the main risk factor for the development of future BE, but during the COVID-19 pandemic, exacerbations in BE patients were reduced by approximately 50%. Finally, the impact of BE on the prognosis of patients with COVID-19 pneumonia is not yet known.
Uncovering novel human gut virome using ultra-deep metagenomic sequencing

Human gastrointestinal tract harbors trillions of commensal microbes including bacteria, viruses, and fungi to form an ecological community, commonly known as the gut microbiome. Being the second most dominant taxonomic kingdom in the gut (5.8% of total microbiome DNA),enteric viruses are increasingly acknowledged for their roles in shaping the overall composition of the gut microbiome and maintaining human health. Recent advancements in metagenomic sequencing have brought breakthrough in deciphering the features and functions of the gut virome. Notably, there are several factors restricting the application of this technology in virome study. For instance, the amount of isolated viral DNA from human samples is usually insufficient for metagenomic sequencing. To solve this issue, amplification techniques such as polymerase chain reaction and multiple displacement amplification are widely used to increase the amount of extracted viral DNA prior to sequencing, which in turn could introduce amplification bias, chimeric reads, and random mutations. Meanwhile, given that most studies analyzed metagenomic reads at low depth (from 0.0003 GB to 7.7 GB), there is currently lack of high quality assembled viral genomes, as well as failure in identifying viruses with low abundance in samples. In addition, Illumina sequencing that generates short reads, has been frequently used. However, short sequencing reads were reported to be inadequate for accurate assembly of viral genomes as they contain hypervariable sequences and repeating regions.
Rapid accessibility evaluation for ballistic lunar capture via manifolds:A Gaussian process regression application

In this study,a supervised machine learning approach called Gaussian process regression (GPR) was applied to approximate optimal bi-impulse rendezvous maneuvers in the cis-lunar space.We demonstrate the use of the GPR approximation of the optimal bi-impulse transfer to patch points associated with various invariant manifolds in the cis-lunar space.The proposed method advances preliminary mission design operations by avoiding the computational costs associated with repeated solutions of the optimal bi-impulsive Lambert transfer because the learned map is computationally efficient.This approach promises to be useful for aiding in preliminary mission design.The use of invariant manifolds as part of the transfer trajectory design offers unique features for reducing propellant consumption while facilitating the solution of trajectory optimization problems.Long ballistic capture coasts are also very attractive for mission guidance,navigation,and control robustness.A multi-input single-output GPR model is presented to represent the fuel costs (in terms of the ΔV magnitude) associated with the class of orbital transfers of interest efficiently.The developed model is also proven to provide efficient approximations.The multi-resolution use of local GPRs over smaller sub-domains and their use for constructing a global GPR model are also demonstrated.One of the unique features of GPRs is that they provide an estimate of the quality of approximations in the form of covariance,which is proven to provide statistical consistency with the optimal trajectories generated through the approximation process.The numerical results demonstrate our basis for optimism for the utility of the proposed method.
不同高血压人群起始降压治疗阈值的研究进展

高血压是心血管病最常见的独立危险因素,是全球心血管病死亡和残疾的罪魁祸首。据2015年一项全球高血压调查显示,全世界每年将近1 000万人死于高血压并发症,与高血压相关的残疾调整生命年损失高达2亿。有效防治高血压是减轻世界人口心血管病负担、延长寿命的关键。高血压防控的目标是降低高血压的心脑肾与血管并发症发生和死亡的总危险。大量研究证实早期干预是最经济有效的防控策略。然而,目前关于起始降压的时机仍然存在争议,不同高血压人群起始降压治疗的阈值可能也存在差异,本文就近年来各指南推荐的不同人群起始降压治疗阈值进行综述。
硬膜外分娩镇痛相关产时发热研究进展

产时发热是产妇在分娩期间出现体温过高的异常表现。目前产时发热的具体机制仍不明确,可能原因包括感染性炎症及非感染性炎症等。其中硬膜外镇痛是诱导产时发热的可能因素之一,硬膜外相关产时发热可能与麻醉药物、硬膜外穿刺技术及体温中枢调节等相关。产时发热会引发母婴不良的结局,如器械助产及剖宫产率增高、新生儿出生后Apgar评分降低等。因此,加强对产时发热的认知与研究,针对性地对产妇进行诊治,可改善母婴结局。
细菌在肿瘤治疗中的应用--从基础到临床

目前,肿瘤治疗方法日趋多样,其中细菌治疗渐成近年来的研究热点。细菌治疗肿瘤主要基于其独特的作用机制能触发宿主抗肿瘤免疫作用,以及部分细菌能靶向性定植于肿瘤内部的特点,在实体肿瘤的基础研究和临床研究中均取得令人鼓舞的疗效。综述就工程化细菌在肿瘤免疫治疗中的具体策略以及一些临床试验研究进行整理,讨论细菌疗法目前所面临的挑战及应对策略等,以期为进一步的研究奠定基础,推进细菌在肿瘤治疗中的临床应用。
White Fluorescent Organic Light-Emitting Diodes with 100% Power Conversion

Energy-efficient lighting sources are desired to provide another solution of carbon emission reduction. White organic light-emitting diodes are promising, because of theoretical internal quantum efficiencies for 100% electric-to-light conversion. However, pure organic fluorescent materials still face a challenge in harvesting triplet excitons for radiation. Herein, we report a white fluorescent organic light-emitting diode having an external quantum efficiency of 30.7% and a power efficiency of 120.2 lm W~(-1). In the single emissive layers, we use blue thermally activated delayed fluorescent emitters to sensitize a yellow fluorescent emitter. Transient photoluminescence and electroluminescence analyses suggest that a blue thermally activated delayed fluorescent molecule with ~100% reverse intersystem crossing efficiency and negligible triplet nonradiative rate constant completely converts triplet to singlet, suppressing triplet quenching by a yellow fluorescent emitter and ensuring 100% power conversion.
Enhanced replication of SARS-CoV-2 Omicron BA.2 in human forebrain and midbrain organoids

Coronavirus Disease 2019 (COVID-19) is associated with a variety of neurological complications, including encephalopathy, encephalitis, dementia, and others. The pathogenic mechanism of these neurological manifestations remains incompletely understood but may be due to factors such as coagulation problem, immune-mediated response, or direct viral invasion into the central nervous system (CNS).2 We and others previously reported that ancestral SARS-CoV-2 could infect and replicate in human brain organoids.3,4 More recently, SARS-CoV-2 Omicron BA.1 emerged in late 2021 and demonstrated altered virological features including increased immunoevasion and attenuated pathogenicity comparing to SARS-CoV-2 wildtype (WT) and previous variants. However, the neuroinvasiveness of Omicron sublineages remain unexplored. Here, we investigated the neuroinvasion and neurotoxicity of Omicron BA.1 and BA.2, and compared the findings with those of SARS-CoV-2 WT and Delta in human forebrain and midbrain organoids. Our results demonstrated that BA.2 replicated more efficiently while triggered lower levels of type I interferon response than that of SARS-CoV-2 WT, Delta, and BA.1 in both human forebrain and midbrain organoids. In addition, BA.2 triggered substantially higher levels of apoptosis in the infected human forebrain and midbrain organoids. Together, these findings suggest that BA.2 may be different from SARS-CoV-2 WT and previous variants in its capacity in targeting and causing diseases in the human brain.
Genome-wide identification and characterization of the JAZ gene family and its expression patterns under various abiotic stresses in Sorghum bicolor

The jasmonate ZIM domain (JAZ) protein belongs to the TIFY ((TIF[F/Y]XG) domain protein) family, which is composed of several plant-specific proteins that play important roles in plant growth, development, and defense responses. However, the mechanism of the sorghum JAZ family in response to abiotic stress remains unclear. In the present study, a total of 17 JAZ genes were identified in sorghum using a Hidden Markov Model search. In addition, real-time quantification polymerase chain reaction (RT-qPCR) was used to analyze the gene expression patterns under abiotic stress. Based on phylogenetic tree analysis, the sorghum JAZ proteins were mainly divided into nine subfamilies. A promoter analysis revealed that the SbJAZ family contains diverse types of promoter cis-acting elements, indicating that JAZ proteins function in multiple pathways upon stress stimulation in plants. According to RT-qPCR, SbJAZ gene expression is tissuespecific. Additionally, under cold, hot, polyethylene glycol, jasmonic acid, abscisic acid, and gibberellin treatments, the expression patterns of SbJAZ genes were distinctly different, indicating that the expression of SbJAZ genes may be coordinated with different stresses. Furthermore, the overexpression of SbJAZ1 in Escherichia coli was found to promote the growth of recombinant cells under abiotic stresses, such as PEG 6000, NaCl, and 40°C treatments. Altogether, our findings help us to better understand the potential molecular mechanisms of the SbJAZ family in sorghum in response to abiotic stresses.
Internal Defects Detection Method of the Railway Track Based on Generalization Features Cluster Under Ultrasonic Images

There may be several internal defects in railway track work that have different shapes and distribution rules, and these defects affect the safety of high-speed trains. Establishing reliable detection models and methods for these internal defects remains a challenging task.To address this challenge, in this study, an intelligent detection method based on a generalization feature cluster is proposed for internal defects of railway tracks. First, the defects are classified and counted according to their shape and location features. Then, generalized features of the internal defects are extracted and formulated based on the maximum difference between different types of defects and the maximum tolerance among same defects'types. Finally, the extracted generalized features are expressed by function constraints, and formulated as generalization feature clusters to classify and identify internal defects in the railway track. Furthermore, to improve the detection reliability and speed, a reduced-dimension method of the generalization feature clusters is presented in this paper. Based on this reduced-dimension feature and strongly constrained generalized features, the K-means clustering algorithm is developed for defect clustering, and good clustering results are achieved. Regarding the defects in the rail head region, the clustering accuracy is over 95%, and the Davies-Bouldin index (DBI) index is negligible, which indicates the validation of the proposed generalization features with strong constraints. Experimental results prove that the accuracy of the proposed method based on generalization feature clusters is up to 97.55%, and the average detection time is 0.12 s/frame, which indicates that it performs well in adaptability, high accuracy, and detection speed under complex working environments.The proposed algorithm can effectively detect internal defects in railway tracks using an established generalization feature cluster model.