mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Stochastic seismic slope stability assessment using polynomial chaos expansions combined with relevance vector machine

This paper presents probabilistic assessment of seismically-induced slope displacements considering uncertainties of seismic ground motions and soil properties. A stochastic ground motion model representing both the temporal and spectral non-stationarity of earthquake shakings and a three-dimensional rotational failure mechanism are integrated to assess Newmark-type slope displacements. A new probabilistic approach that incorporates machine learning in metamodeling technique is proposed, by combining relevance vector machine with polynomial chaos expansions (RVM-PCE). Compared with other PCE methods, the proposed RVM-PCE is shown to be more effective in estimating failure probabilities. The sensitivity and relative influence of each random input parameter to the slope displacements are discussed. Finally, the fragility curves for slope displacements are established for sitespecific soil conditions and earthquake hazard levels. The results indicate that the slope displacement is more sensitive to the intensities and strong shaking durations of seismic ground motions than the frequency contents, and a critical Arias intensity that leads to the maximum annual failure probabilities can be identified by the proposed approach.
A chlorinated copolymer donor demonstrates a 18.13% power conversion efficiency

The rapid development of low-bandgap (LBG) nonfullerene acceptors and wide-bandgap (WBG) copolymer donors in recent years has boosted the power conversion efficiency (PCE) of organic solar cells (OSCs) to the 18% level. The commercialization of OSCs is highly expected. However, critical issues like the cost and the stability also determine whether OSCs can enter the market or not. Active materials, i.e. donors and acceptors, are the key materials determining the performance and cost of OSCs. Nowadays, the state-of-the-art donors and acceptors like D18, PM6, Y6, IT-4F and COi 8DFIC generally contain fluorine atoms, presenting high synthesis cost. Replacing fluorine with chlorine to make chlorinated donors or acceptors is an effective strategy to lower the cost while maintain the high efficiency for organic solar cells. In the past few years, remarkable progress has been made in Cl-containing donors. In 2014, Wang et al. reported a chlorinated phenazine copolymer PCTClP with a low bandgap and a deep HOMO level.
Electrolyte-gated transistors for neuromorphic applications

Von Neumann computers are currently failing to follow Moore's law and are limited by the von Neumann bottleneck. To enhance computing performance, neuromorphic computing systems that can simulate the function of the human brain are being developed. Artificial synapses are essential electronic devices for neuromorphic architectures, which have the ability to perform signal processing and storage between neighboring artificial neurons. In recent years, electrolyte-gated transistors (EGTs) have been seen as promising devices in imitating synaptic dynamic plasticity and neuromorphic applications. Among the various electronic devices, EGT-based artificial synapses offer the benefits of good stability, ultra-high linearity and repeated cyclic symmetry, and can be constructed from a variety of materials. They also spatially separate “read” and “write” operations. In this article, we provide a review of the recent progress and major trends in the field of electrolyte-gated transistors for neuromorphic applications. We introduce the operation mechanisms of electric-double-layer and the structure of EGT-based artificial synapses. Then, we review different types of channels and electrolyte materials for EGT-based artificial synapses. Finally, we review the potential applications in biological functions.
Ion migration in perovskite solar cells

The past few years have witnessed a remarkable progress of perovskite solar cells (PSCs), which can be attributed to the high light absorption coefficient, tunable bandgap, long carrier diffusion length, solution processability at low temperature and relatively low cost of perovskite materials. Up to now, the highest certified power conversion efficiency (PCE) of PSCs has reached 25.5% (https://www.nrel.gov/pv/cell-efficiency. html), shedding light on the commercialization of PSCs. Nevertheless, the stability issues of PCSs severely limit the field deployment of solar cell modules. Notably, ion migration in organic-inorganic halide perovskite (OIHP) originating from the ionic nature of perovskite materials has been suggested to be responsible for many instability problems and cannot be eliminated through encapsulation. With crucial significance being attached to the long-term durability of PSCs during operation, it is of profound implication to clarify the fundamental mechanism and potential influence of ion migration on device performance.
Fine-scale genetic structure of Tujia and central Han Chinese revealing massive genetic admixture under language borrowing

Archaeological, genetic, and linguistic evidence has supported the idea that northern China is the original center of modern Sino-Tibetan-speaking populations. However, the demographic history of subsequent southward migration and genetic admixture of Han Chinese with surrounding indigenous populations remain uncharacterized, and the language shifts and assimilations accompanied by movement of people, or just an adaptation of cultural ideas among populations in central China is still unclear, especially for Tibeto-Burmanspeaking Tujia and central Han Chinese populations. To resolve this, we genotyped over 60K genome-wide markers in 505 unrelated individuals from 63 indigenous populations. Our results showed both studied Han and Tujia were at the intermediate position in the modern East Asian North-South genetic cline and there was a correlation between the genetic composition and the latitude. We observed the strong genetic assimilation between Tujia people and central Han Chinese, which suggested massive population movements and genetic admixture under language borrowing. Tujia and central Han Chinese could be modeled as a two-way admixture deriving primary ancestry from a northern ancestral population closely related to the ancient DevilsCave and present-day Tibetans and a southern ancestral population closely related to the present-day Tai-Kadai and Austronesian-speaking groups. The ancestral northern population we suspect to be related to the Neolithic millet farming groups in the Yellow River Basin or central China. We showed that the newly genotyped populations in Hubei Province had a higher proportion of DevilsCave or modern Tungusic/Mongolic-related northern ancestries, while the Hunan populations harbored a higher proportion of Austronesian/Tai-Kadai-related southern ancestries.
Gray Matter-Based Age Prediction Characterizes Different Regional Patterns

The brain experiences ongoing changes across different ages to support brain development and functional reorganization.During the span of adulthood,although the brain has matured from a neurobiological perspective,it is still continuously shaped by external factors such as habits,the family setting,socioeconomic status,and the work environment [1].In contrast to chronological age(CA),brain(or biological)age(BA)is conceptualized as an important index for characterizing the aging process and neuropsychological state,as well as individual cognitive performance.Growing evidence indicates that BA can be assessed by neuroimaging techniques,including MRI [2].Due to their short collection time,stable image features,and(usual)availability during clinical diagnosis,T1-weighted MRIs are considered the first choice for estimating BA,with structural features including local/global volumes of gray matter(GM)and white matter(WM),geometrical characteristics of the cerebral cortex,and distinctions between GM and WM at the boundary [3].
Advantages of employing multilevel monitoring wells for design of tunnels subjected to multi-aquifer alluvial

For tunnels being excavated through multiple aquifer formations, having precise knowledge of the aquifers' hydraulic head becomes essential for determining groundwater inflow into the tunnel and analyzing its stability, specifically using multilevel monitoring systems. In the multi-aquifer alluvial section of the Glas tunnel (Iran), since the hydraulic head calculations were based on the data obtained from single-piezometer boreholes, the excavation risk was assessed to be at high level and the tunnel seemed to be unstable, thus an incorrect conclusion was derived from the misleading data. To take cost mitigation measures into account, it was necessary to calculate the hydraulic head at tunnel level accurately. By installing nested and clustered wells the mean hydraulic head was measured to be 70 m, significantly different from the 90 m previously determined by boreholes. Considering the updated value, the groundwater inflow and bulkhead load, formerly calculated as 0.65 m~3/s and 9.5 bars, were determined to be 0.49 m~3/s and 7.5 bars, respectively.
Topographically derived subpixel-based change detection for monitoring changes over rugged terrain Himalayas using AWiFS data

Continuous and accurate monitoring of earth surface changes over rugged terrain Himalayas is important to manage natural resources and mitigate natural hazards. Conventional techniques generally focus on per-pixel based processing and overlook the sub-pixel variations occurring especially in case of low or moderate resolution remotely sensed data. However, the existing subpixel-based change detection (SCD) models are less effective to detect the mixed pixel information at its complexity level especially over rugged terrain regions. To overcome such issues, a topographically controlled SCD model has been proposed which is an improved version of widely used per-pixel based change vector analysis (CVA) and hence, named as a subpixel-based change vector analysis (SCVA). This study has been conducted over a part of the Western Himalayas using the advanced wide-field sensor (AWiFS) and Landsat- 8 datasets. To check the effectiveness of the proposed SCVA, the cross-validation of the results has been done with the existing neural network-based SCD (NN-SCD) and per-pixel based models such as fuzzybased CVA (FCVA) and post-classification comparison (PCC). The results have shown that SCVA offered robust performance (85.6%-86.4%) as compared to NN-SCD (81.6%-82.4%), PCC (79.2%-80.4%), and FCVA (81.2%-83.6%). We concluded that SCVA helps in reducing the detection of spurious pixels and improve the efficacy of generating change maps. This study is beneficial for the accurate monitoring of glacier retreat and snow cover variability over rugged terrain regions using moderate resolution remotely sensed datasets.
Necrotising otitis externa: A single centre experience

Introduction: Necrotising otitis externa (NOE) is a rare infection of the ear canal with frequent bone erosion. This study’s objective is to describe the different features of NOE as well as its management in an ear-nose-throat department. We also tried to identify the particularities of the fungal infection. Patients and methods: It is an observational cohort that included all the patients hospitalised for the management of NOE. The study was carried out in the ear-nose-throat Department of Mahdia University Hospital in Tunisia between January 2006 and december 2019. Results: A total of 40 patients were included. The mean age was 65 ± 12.9 years and the sex ratio was 0.9. Ninety percent of the patients included were diabetics. The most common signs found were oedema of the external canal (97.5%) and auricular discharge (92.5%). The main pathogen isolated was Pseudomonas aeruginosa (61.7%). Fungi were isolated in 9 cases (26.47%). Computed tomography was performed for 32 patients (80%). Bone erosion was seen in 26 cases (81.3%). The main complications were cerebral venous thrombosis, retropharyngeal abscess and cerebral empyema. Thirty one patients received only antibiotics, 2 received only antifungal treatment, and 7 received both antibiotics and antifungal treatment. All patients had a favorable outcome. Univariate analysis showed a higher median erythrocyte sedimentation rate was associated with fungal infections. No other differences were noted. Conclusion: Our management protocol seems to be efficient since all patients had initial favorable outcome. A higher median erythrocyte sedimentation rate was associated with fungal infections.
Visualizing Meiotic Chromosome Pairing and Segregation in Interspecific Hybrids of Rice by Genomic in situ Hybridization

Meiotic disturbances in F1 hybrids and their progenies are still major problems in wide hybridization.To investigate the genome affinity reflected in chromosome pairing and segregation,we studied chromosome behaviors during meiosis in two interspecific F1 hybrids [O.minuta × O.australiensis(Om × Oa,BCE genome)and Oa × O.ridleyi(Or,EHJ genome)]by using both traditional staining methods and genomic in situ hybridization(GISH).GISH analysis has been successfully performed on mitotic chromosomes to distinguish different Oryza genomes,but relatively fewer systematic analyses of meiotic chromosomes of interspecific hybrids have been reported.In the hybrids,highly irregular chromosome behaviors through meiosis resulted in producing microspores with unbalanced genome.At diakinesis of these two hybrids,most chromosomes present as univalent,with low frequency as bivalents and occasionally as trivalents.In a pollen mother cell,2 to 8 bivalents and 0 to 4 trivalents were observed in the hybrid Oa × Or,and 1 to 8 bivalents and 0 to 5 trivalents were observed in the hybrid Om × Oa.GISH results indicated that 51.52% bivalents in Oa × Or and 79.65% bivalents in Om × Oa involved allosyndetic association,which indicates that recombination and introgression should be possible if viable backcrosses can be recovered even from triploid hybrids.In this study,we revealed that the meiotic disturbance due to low affinities between parental genomes is the major reason for the sterility of these two triploid interspecific hybrids.The two hybrids showing vigor in reproductive growth are potential genetic resources in future breeding programs.A better understanding of genomic affinities between these distant Oryza species can facilitate planning an effective breeding program by using wide hybridization,and efficient and routine GISH analysis is helpful to monitor alien introgression in the process.
Numerical investigation of the seismic response of a UHV composite bypass switch retrofitted with wire rope isolators

An ultra-high voltage (UHV) composite bypass switch (BPS) faces increasing seismic challenges when UHV projects extend to high seismic intensity areas.The UHV composite BPS still generates excessive stress at the bottom section although hollow composite insulators with high flexural strength are adopted.Since the standard retrofitting strategy by using stiffer supports cannot reduce stress responses,wire rope isolation is introduced.The optimal design of isolation considers both stress and displacement responses since the slenderness and composite material of insulators contribute to significant displacement.The results show that properly designed isolation can significantly reduce stress without excessive displacement responses.A larger radius configuration helps to improve the applicability of small stiffness isolators under high winds.When the isolation still cannot satisfy the requirement,smaller stiffness isolators with a larger radius,or isolators with increased loops and smaller radius,can be introduced to gain better energy dissipation capacity and effectiveness in response mitigation.Accordingly,a three-step design procedure is proposed to increase the damping force but fix the rotational stiffness of isolation.Hence,the application of wire rope isolation can be extended to UHV composite BPS with a low natural frequency,but conductors with enough redundancy should be used.
Humulus lupulus L.Extract Prevents Ovariectomy-Induced Osteoporosis in Mice and Regulates Activities of Osteoblasts and Osteoclasts

Objective:To systematically evaluate the protective effects of Humulus lupulus L.extract (HLE) on osteoporosis mice.Methods:In vivo experiment,a total of 35 12-week-old female ICR mice were equally divided into 5 groups:the sham control group (sham);the ovariectomy with vehicle group (OVX);the OVX with estradiol valerate [EV,0.2 mg/(kg·d)];the OVX with low-or high-dose HLE groups [HLE,1 g/(kg·d) and 3 g/(kg·d)],7 in each group.Treatment began 1 week after the ovariectomized surgery and lasted for 12 weeks.Bone mass and trabecular bone mircoarchitecture were evaluated by micro computed tomography,and bone turnover markers in serum were evaluated using enzyme-linked immunosorbent assay (ELISA) kits.In vitro experiment,osteoblasts and osteoclasts were treated with HLE at doses of 0,4,20 and 100 μg/mL.Biomarkers for bone formation in osteoblasts and bone resorption in osteoclasts were analyzed.Results:Compared with the OVX group,HLE exerted bone protective effects by the increase of estradiol (P<0.05),the improvement of cancellous bone structure,bone mineral density (P<0.01) and the reduction of serum alkaline phosphatase (ALP),tartrate resistant acid phosphatase (TRAP),bone gla-protein,c-terminal telopeptides of type Ⅰ collagen (CTX-Ⅰ) and deoxypyridinoline levels (P<0.01 for all).In vitro experiment,compared with the control group,HLE at 20 μg/mL promoted the cell proliferation (P<0.01),and increased the expression of bone morphogenetic protein-2 and osteopontin levels in osteoblasts (both P<0.05).HLE at 100 μg/mL increased the osteoblastic ALP activities,and HLE at all dose enhanced the extracellular matrix mineralization (both P<0.01).Furthermore,compared with the control group,HLE at 20 μg/mL and 100 μg/mL inhibited osteoclastic TRAP activity (P<0.01),and reduced the expression of matrix metalloproteinase-9 and cathepsin K (both P<0.05).Conclusion:HLE may protect against bone loss,and have potentials in the treatment of osteoporosis.
Introducing an effective coherence function to generate non-uniform ground motion on topographic site using time-domain boundary element method

In this study,a comprehensive parametric analysis was performed on non-uniform excitation of V-shaped topography using the boundary element method in time domain.For this purpose,wave scattering analysis was carried out on a topography subjected to the SV-wave for different predominant frequencies and shape ratios.Based on the numerical results,new coherence and time delay functions are proposed to generate non-uniform ground motion for topographic irregularities.The efficiency and accuracy of the proposed functions for real engineering problems are indicated by comparison with observations reported in previous literature.
Knowing Your Dog Breed: Identifying a Dog Breed with Deep Learning

Dog breed identification is essential for many reasons, particularly for understanding individual breeds′ conditions, health concerns, interaction behavior, and natural instinct. This paper presents a solution for identifying dog breeds using their images of their faces. The proposed method applies a deep learning based approach in order to recognize their breeds. The method begins with a transfer learning by retraining existing pre-trained convolutional neural networks (CNNs) on the public dog breed dataset. Then, the image augmentation with various settings is also applied on the training dataset, in order to improve the classification performance. The proposed method is evaluated using three different CNNs with various augmentation settings and comprehensive experimental comparisons. The proposed model achieves a promising accuracy of 89.92% on the published dataset with 133 dog breeds.
Investigation on One-Dimensional Loss Models for Predicting Performance of Multistage Centrifugal Compressors in Supercritical CO_2 Brayton Cycle

The main compressor in a supercritical carbon dioxide (SCO_2) Brayton cycle works near the critical point where the physical properties of CO_2 are far away from the ideal gas. To investigate the effectiveness of the conventional one-dimensional (1D) loss models for predicting the performance of compressors working in such nontraditional conditions, detailed comparisons of 1D predicted performance, experimental data and threedimensional CFD results are made. A 1D analysis method with enthalpy and total pressure based loss system is developed for multistage SCO_2 centrifugal compressors, and it is firstly validated against the experimental results of a single stage SCO_2 centrifugal compressor from the Sandia National Laboratory. A good agreement of pressure ratios with experiments can be achieved by the 1D method. But the efficiency deviations reveal the potential deficiencies of the parasitic loss models. On the basis of the validation, a two-stage SCO_2 centrifugal compressor is employed to do the evaluation. Three-dimensional CFD simulations are performed. Detailed comparisons are made between the CFD and the 1D results at different stations located in the compressor. The features of the deviations are analyzed in detail, as well as the reasons that might cause these deviations.
Delineation of an Urban Community Life Circle Based on a Machine-Learning Estimation of Spatiotemporal Behavioral Demand

Delineating life circles is an essential prerequisite for urban community life circle planning.Recent studies combined the environmental contexts with residents' global positioning system (GPS) data to delineate the life circles.This method,however,is constrained by GPS data,and it can only be applied in the GPS surveyed communities.To address this limitation,this study developed a generalizable delineation method without the constraint of behavioral data.According to previous research,the community life circle consists of the walking-accessible range and internal structure.The core task to develop the generalizable method was to estimate the spatiotemporal behavioral demand for each plot of land to acquire the internal structure of the life circle,as the range can be delineated primarily based on environmental data.Therefore,behavioral demand estimation models were established through logistic regression and machine learning techniques,including decision trees and ensemble learning.The model with the lowest error rate was chosen as the final estimation model for each type of land.Finally,we used a community without GPS data as an example to demonstrate the effectiveness of the estimation models and delineation method.This article extends the existing literature by introducing spatiotemporal behavioral demand estimation models,which learn the relationships between environmental contexts,population composition and the existing delineated results based on GPS data to delineate the internal structure of the community life circle without employing behavioral data.Furthermore,the proposed method and delineation results also contributes to facilities adjustments and location selections in life circle planning,people-oriented transformation in urban planning,and activity space estimation of the population in evaluating and improving the urban policies.