nils-herrmann/clean_scirepeval huggingface dataset:
V3I-STAL: Visual Vehicle-to-Vehicle Interaction via Simultaneous Tracking and Localization

This paper investigates a visual interaction system for vehicle-to-vehicle (V2V) platform, called V3I. Our system employs common visual cameras that are mounted on connected vehicles to perceive the existence of isolated vehicles in the same roadway, and provides human drivers with imagery situational awareness. This allows effective interactions between vehicles even with a low permeation rate of V2V devices. The underlying research problem for V3I includes two aspects: i) tracking isolated vehicles of interest over time through local cameras; ii) at each time-step fusing the results of local visual perceptions to obtain a global location map that involves both isolated and connected vehicles. In this paper, we introduce a unified probabilistic approach to solve the above two problems, i.e., tracking and localization, in a joint fashion. Our approach will explore both the visual features of individual vehicles in images and the pair-wise spatial relationships between vehicles. We develop a fast Markov Chain Monte Carlo (MCMC) algorithm to search the joint solution space efficiently, which enables real-time application. To evaluate the performance of the proposed approach, we collect and annotate a set of video sequences captured with a group of vehicle-resident cameras. Extensive experiments with comparisons clearly demonstrate that the proposed V3I approach can precisely recover the dynamic location map of the surrounding and thus enable direct visual interactions between vehicles .
Forecasting Emerging Trends from Scientific Literature

Text analysis methods for the automatic identification of emerging technologies by analyzing the scientific publications, are gaining attention because of their socio-economic impact. The approaches so far have been mainly focused on retrospective analysis by mapping scientific topic evolution over time. We propose regression based approaches to predict future keyword distribution. The prediction is based on historical data of the keywords, which in our case, are LREC conference proceedings. Considering the insufficient number of data points available from LREC proceedings, we do not employ standard time series forecasting methods. We form a dataset by extracting the keywords from previous year proceedings and quantify their yearly relevance using tf-idf scores. This dataset additionally contains ranked lists of related keywords and experts for each keyword.
Inositol Treatment and ART Outcomes in Women with PCOS

Polycystic ovary syndrome (PCOS) affects 5-10% of women in reproductive age and is characterized by oligo/amenorrhea, androgen excess, insulin resistance, and typical polycystic ovarian morphology. It is the most common cause of infertility secondary to ovulatory dysfunction. The underlying etiology is still unknown but is believed to be multifactorial. Insulin-sensitizing compounds such as inositol, a B-complex vitamin, and its stereoisomers (myo-inositol and D-chiro-inositol) have been studied as an effective treatment of PCOS. Administration of inositol in PCOS has been shown to improve not only the metabolic and hormonal parameters but also ovarian function and the response to assisted-reproductive technology (ART). Accumulating evidence suggests that it is also capable of improving folliculogenesis and embryo quality and increasing the mature oocyte yield following ovarian stimulation for ART in women with PCOS. In the current review, we collate the evidence and summarize our current knowledge on ovarian stimulation and ART outcomes following inositol treatment in women with PCOS undergoing in vitro fertilization (IVF) and/or intracytoplasmic sperm injection (ICSI).
Tenofovir-related nephrotoxicity in human immunodeficiency virus-infected patients: three cases of renal failure, Fanconi syndrome, and nephrogenic diabetes insipidus.

We report 3 cases of renal toxicity associated with use of the antiviral agent tenofovir. Renal failure, proximal tubular dysfunction, and nephrogenic diabetes insipidus were observed, and, in 2 cases, renal biopsy revealed severe tubular necrosis with characteristic nuclear changes. Patients receiving tenofovir must be monitored closely for early signs of tubulopathy (glycosuria, acidosis, mild increase in the plasma creatinine level, and proteinuria).
The amyloid cascade hypothesis for Alzheimer's disease: an appraisal for the development of therapeutics

The amyloid cascade hypothesis, which posits that the deposition of the amyloid-β peptide in the brain is a central event in Alzheimer's disease pathology, has dominated research for the past twenty years. Several therapeutics that were purported to reduce amyloid-β production or aggregation have failed in Phase III clinical testing, and many others are in various stages of development. Therefore, it is timely to review the science underpinning the amyloid cascade hypothesis, consider what type of clinical trials will constitute a valid test of this hypothesis and explore whether amyloid-β-directed therapeutics will provide the medicines that are urgently needed by society for treating this devastating disease.
A High-throughput Architecture for Lossless Decompression on FPGA Designed Using HLS (Abstract Only)

In the field of big data applications, lossless data compression and decompression can play an important role in improving the data center's efficiency in storage and distribution of data. To avoid becoming a performance bottleneck, they must be accelerated to have a capability of high speed data processing. As FPGAs begin to be deployed as compute accelerators in the data centers for its advantages of massive parallel customized processing capability, power efficiency and hardware reconfiguration. It is promising and interesting to use FPGAs for acceleration of data compression and decompression. The conventional development of FPGA accelerators using hardware description language costs much more design efforts than that of CPUs or GPUs. High level synthesis (HLS) can be used to greatly improve the design productivity. In this paper, we present a solution for accelerating lossless data decompression on FPGA by using HLS. With a pipelined data-flow structure, the proposed decompression accelerator can perform static Huffman decoding and LZ77 decompression at a very high throughput rate. According to the experimental results conducted on FPGA with the Calgary Corpus data benchmark, the average data throughput of the proposed decompression core achieves to 4.6 Gbps while running at 200 MHz.
Effects of Continuous Auditory Feedback on Drawing Trajectory-Based Finger Gestures

The well-known “fat finger” issue limits the interaction performance of trajectory-based finger gestures. To alleviate this issue, this work focuses on the possibility of using additional continuous auditory feedback to assist trajectory-based finger gestures. First, the experiment validated that, with the visual feedback only, the bare fingertip led to more errors in drawing of intersectional points, endpoints of closed gestures, and gestural length and shape variability compared to when the finger-attached pen was used. Then, we designed different types of auditory feedback (discrete beep, static, gradual) to provide additional information on the spatial relationship between finger-contact point and the endpoints or intersections of predefined gestures. An experiment that evaluates the effects of individual or combination of designed auditory feedback on trajectory-based finger gestures was conducted. These results show a few differences between them. However, a combination of gradual (amplitude and frequency) continuous sound and beep reached the highest drawing accuracy for trajectory-based finger gestures, which is similar to that of a finger-attached pen. This research offers insights and implications for the future design of continuous auditory feedback on small touchscreens.
Gratitude and Life Satisfaction in the United States and Japan

Being grateful has been associated with many positive outcomes, including greater happiness, positive affect, optimism, and self-esteem. There is limited research, however, on the associations between gratitude and different domains of life satisfaction across cultures. The current study examined the associations between gratitude and three domains of life satisfaction, including satisfaction in relationships, work, and health, and overall life satisfaction, in the United States and Japan. A total of 945 participants were drawn from two samples of middle aged and older adults, the Midlife Development in the United States and the Midlife Development in Japan. There were significant positive bivariate associations between gratitude and all four measures of life satisfaction. In addition, after adjusting for demographics, neuroticism, extraversion, and the other measures of satisfaction, gratitude was uniquely and positively associated with satisfaction with relationships and life overall but not with satisfaction with work or health. Furthermore, results indicated that women and individuals who were more extraverted and lived in the United States were more grateful and individuals with less than a high school degree were less grateful. The findings from this study suggest that gratitude is uniquely associated with specific domains of life satisfaction. Results are discussed with respect to future research and the design and implementation of gratitude interventions, particularly when including individuals from different cultures.
Bromodomain protein 4 discriminates tissue-specific super-enhancers containing disease-specific susceptibility loci in prostate and breast cancer

Epigenetic information can be used to identify clinically relevant genomic variants single nucleotide polymorphisms (SNPs) of functional importance in cancer development. Super-enhancers are cell-specific DNA elements, acting to determine tissue or cell identity and driving tumor progression. Although previous approaches have been tried to explain risk associated with SNPs in regulatory DNA elements, so far epigenetic readers such as bromodomain containing protein 4 (BRD4) and super-enhancers have not been used to annotate SNPs. In prostate cancer (PC), androgen receptor (AR) binding sites to chromatin have been used to inform functional annotations of SNPs. Here we establish criteria for enhancer mapping which are applicable to other diseases and traits to achieve the optimal tissue-specific enrichment of PC risk SNPs. We used stratified Q-Q plots and Fisher test to assess the differential enrichment of SNPs mapping to specific categories of enhancers. We find that BRD4 is the key discriminant of tissue-specific enhancers, showing that it is more powerful than AR binding information to capture PC specific risk loci, and can be used with similar effect in breast cancer (BC) and applied to other diseases such as schizophrenia. This is the first study to evaluate the enrichment of epigenetic readers in genome-wide associations studies for SNPs within enhancers, and provides a powerful tool for enriching and prioritizing PC and BC genetic risk loci. Our study represents a proof of principle applicable to other diseases and traits that can be used to redefine molecular mechanisms of human phenotypic variation.
Deep learning cardiac motion analysis for human survival prediction

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors. This dense motion model formed the input to a supervised denoising autoencoder (4Dsurvival), which is a hybrid network consisting of an autoencoder that learns a task-specific latent code representation trained on observed outcome data, yielding a latent representation optimised for survival prediction. To handle right-censored survival outcomes, our network used a Cox partial likelihood loss function. In a study of 302 patients the predictive accuracy (quantified by Harrell's C-index) was significantly higher (p = .0012) for our model C=0.75 (95% CI: 0.70 - 0.79) than the human benchmark of C=0.59 (95% CI: 0.53 - 0.65). This work demonstrates how a complex computer vision task using high-dimensional medical image data can efficiently predict human survival.
Multiprocess 3D printing for increasing component functionality

Layer-by-layer deposition of materials to manufacture parts—better known as three-dimensional (3D) printing or additive manufacturing—has been flourishing as a fabrication process in the past several years and now can create complex geometries for use as models, assembly fixtures, and production molds. Increasing interest has focused on the use of this technology for direct manufacturing of production parts; however, it remains generally limited to single-material fabrication, which can limit the end-use functionality of the fabricated structures. The next generation of 3D printing will entail not only the integration of dissimilar materials but the embedding of active components in order to deliver functionality that was not possible previously. Examples could include arbitrarily shaped electronics with integrated microfluidic thermal management and intelligent prostheses custom-fit to the anatomy of a specific patient. We review the state of the art in multiprocess (or hybrid) 3D printing, in which complementary processes, both novel and traditional, are combined to advance the future of manufacturing.
The intergenerational effects of Indian Residential Schools: Implications for the concept of historical trauma

The current paper reviews research that has explored the intergenerational effects of the Indian Residential School (IRS) system in Canada, in which Aboriginal children were forced to live at schools where various forms of neglect and abuse were common. Intergenerational IRS trauma continues to undermine the well-being of today's Aboriginal population, and having a familial history of IRS attendance has also been linked with more frequent contemporary stressor experiences and relatively greater effects of stressors on well-being. It is also suggested that familial IRS attendance across several generations within a family appears to have cumulative effects. Together, these findings provide empirical support for the concept of historical trauma, which takes the perspective that the consequences of numerous and sustained attacks against a group may accumulate over generations and interact with proximal stressors to undermine collective well-being. As much as historical trauma might be linked to pathology, it is not possible to go back in time to assess how previous traumas endured by Aboriginal peoples might be related to subsequent responses to IRS trauma. Nonetheless, the currently available research demonstrating the intergenerational effects of IRSs provides support for the enduring negative consequences of these experiences and the role of historical trauma in contributing to present day disparities in well-being.
Wireless Access in Ultra-Reliable Low-Latency Communication (URLLC)

The future connectivity landscape and, notably, the 5G wireless systems will feature Ultra-Reliable Low Latency Communication (URLLC). The coupling of high reliability and low latency requirements in URLLC use cases makes the wireless access design very challenging, in terms of both the protocol design and of the associated transmission techniques. This paper aims to provide a broad perspective on the fundamental tradeoffs in URLLC as well as the principles used in building access protocols. Two specific technologies are considered in the context of URLLC: massive MIMO and multi-connectivity, also termed interface diversity. The paper also touches upon the important question of the proper statistical methodology for designing and assessing extremely high reliability levels.
Rhodiola rosea for physical and mental fatigue: a systematic review

Rhodiola rosea (R. rosea) is grown at high altitudes and northern latitudes. Due to its purported adaptogenic properties, it has been studied for its performance-enhancing capabilities in healthy populations and its therapeutic properties in a number of clinical populations. To systematically review evidence of efficacy and safety of R. rosea for physical and mental fatigue.



Six electronic databases were searched to identify randomized controlled trials (RCTs) and controlled clinical trials (CCTs), evaluating efficacy and safety of R. rosea for physical and mental fatigue. Two reviewers independently screened the identified literature, extracted data and assessed risk of bias for included studies.



Of 206 articles identified in the search, 11 met inclusion criteria for this review. Ten were described as RCTs and one as a CCT. Two of six trials examining physical fatigue in healthy populations report R. rosea to be effective as did three of five RCTs evaluating R. rosea for mental fatigue. All of the included studies exhibit either a high risk of bias or have reporting flaws that hinder assessment of their true validity (unclear risk of bias).



Research regarding R. rosea efficacy is contradictory. While some evidence suggests that the herb may be helpful for enhancing physical performance and alleviating mental fatigue, methodological flaws limit accurate assessment of efficacy. A rigorously-designed well reported RCT that minimizes bias is needed to determine true efficacy of R. rosea for fatigue.
Deep Echo State Network (DeepESN): A Brief Survey

The study of deep recurrent neural networks (RNNs) and, in particular, of deep Reservoir Computing (RC) is gaining an increasing research attention in the neural networks community. The recently introduced Deep Echo State Network (DeepESN) model opened the way to an extremely efficient approach for designing deep neural networks for temporal data. At the same time, the study of DeepESNs allowed to shed light on the intrinsic properties of state dynamics developed by hierarchical compositions of recurrent layers, i.e. on the bias of depth in RNNs architectural design. In this paper, we summarize the advancements in the development, analysis and applications of DeepESNs.
Motion Database Motion Examples Full-body Motion Synthesis velocity body state sync agent Avatar Control Input sync avatar User

We present an interactive algorithm to generate plausible movements for human-like agents interacting with other agents or avatars in a virtual environment. Our approach takes into account high-dimensional human motion constraints and bio-mechanical constraints to compute collision-free trajectories for each agent. We present a novel full-body movement constrained-velocity computation algorithm that can easily be combined with many existing motion synthesis techniques. Compared to prior local navigation methods, our formulation reduces artefacts that arise in dense scenarios and close interactions, and results in smoother and plausible locomotive behaviors. We have evaluated the benefits of our new algorithm in single-agent and multi-agent environments. We investigated the perception of a single agent’s movements in dense scenarios and observed that our algorithm has a strong positive effect on the perceived quality of the simulation. Our approach also allows the user to interact with the agents from a first-person perspective in immersive settings. We conducted a study to investigate the perception of such avatar-agent interactions, and found that interactions generated using our approach lead to an increase in the user’s sense of co-presence.
Diabetes and cardiovascular risk factors: the Framingham study.

The impact of cardiovascular disease was compared in non-diabetics and diabetics in the Framingham cohort. In the first 20 years of the study about 6% of the women and 8% of the men were diagnosed as diabetics. The incidence of cardiovascular disease among diabetic men was twice that among non-diabetic men. Among diabetic women the incidence of cardiovascular disease was three times that among non-diabetic women. Judging from a comparison of standardized coefficients for the regression of incidence of cardiovascular disease on specified risk factors, there is no indication that the relationship of risk factors to the subsequent development of cardiovascular disease is different for diabetics and non-diabetics. This study suggests that the role of diabetes as a cardiovascular risk factor does not derive from an altered ability to contend with known risk factors.
Banks ’ Payments-Driven Revenues

lthough banks’ lending activities draw the attention of supervisors, lawmakers, researchers, and the press, a very substantial and growing portion of the industry’s total revenue is received in the form of fee income. The amount of fee, or noninterest, income earned by the banking sector suggests that the significance of payments services has been understated or overlooked. A lack of good information about the payments area may partly explain the failure to gauge the size of this business line correctly. In reports to supervisory agencies, banking organizations provide data relating primarily to their safety and soundness. By the design of the reports, banks transmit information on profitability, capital, and the size and condition of the loan portfolio. Limited information can be extracted from regulatory reports on individual business lines; in fact, these reports imply that banks receive just 7 percent of their net revenue from payments services. A narrow definition of payments, or transactions, services may also contribute to a poor appreciation of this banking function. While checking accounts are universally recognized as a payments service, credit cards, corporate trust accounts, and securities processing should also be treated as parts of a bank’s payments business. The common but limited definition of the payments area reflects the tight focus of banking research on lending and deposit taking. In theoretical studies, economists explain the prominence of commercial banks in the financial sector in terms of these two functions. First, by developing their skills in screening applicants, monitoring borrowers, and obtaining repayment, commercial banks became the dominant lender to relatively small-sized borrowers. Second, because investors demand protection against the risk that they may need liquidity earlier than anticipated, bank deposits are a special and highly useful financial instrument. While insightful, neither rationale explains why A
A Micromachined Terahertz Waveguide 90 $^{\circ}$ Twist

Waveguide twists are often necessary to provide polarization rotation between waveguide-based components. At terahertz frequencies, it is desirable to use a twist design that is compact in order to reduce loss; however, these designs are difficult if not impossible to realize using standard machining. This paper presents a micromachined compact waveguide twist for terahertz frequencies. The Rud-Kirilenko twist geometry is ideally suited to the micromachining processes developed at the University of Virginia. Measurements of a WR-1.5 micromachined twist exhibit a return loss near 20 dB and a median insertion loss of 0.5 dB from 600 to 750 GHz.