Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Distributed Big Data Clustering-based on Adaptive Density Partitioning using Apache Spark

Unsupervised machine learning and knowledge discovery from large-scale datasets have recently attracted a lot of research interest. The present paper proposes a distributed big data clustering approach-based on adaptive density estimation. The proposed method is developed-based on Apache Spark framework and tested on some of the prevalent datasets. In the first step of this algorithm, the input data is divided into partitions using a Bayesian type of Locality Sensitive Hashing (LSH). Partitioning makes the processing fully parallel and much simpler by avoiding unneeded calculations. Each of the proposed algorithm steps is completely independent of the others and no serial bottleneck exists all over the clustering procedure. Locality preservation also filters out the outliers and enhances the robustness of the proposed approach. Density is defined on the basis of Ordered Weighted Averaging (OWA) distance which makes clusters more homogenous. According to the density of each node, the local density peaks will be detected adaptively. By merging the local peaks, final cluster centers will be obtained and other data points will be a member of the cluster with the nearest center. The proposed method has been implemented and compared with similar recently published researches. Cluster validity indexes achieved from the proposed method shows its superiorities in precision and noise robustness in comparison with recent researches. Comparison with similar approaches also shows superiorities of the proposed method in scalability, high performance, and low computation cost. The proposed method is a general clustering approach and it has been used in gene expression clustering as a sample of its application.
System justification: Experimental evidence, its contextual nature, and implications for social change

We review conceptual and empirical contributions to system justification theory over the last fifteen years, emphasizing the importance of an experimental approach and consideration of context. First, we review the indirect evidence of the system justification motive via complimentary stereotyping. Second, we describe injunctification as direct evidence of a tendency to view the extant status quo (the way things are) as the way things should be. Third, we elaborate on system justification's contextual nature and the circumstances, such as threat, dependence, inescapability, and system confidence, which are likely to elicit defensive bolstering of the status quo and motivated ignorance of critical social issues. Fourth, we describe how system justification theory can increase our understanding of both resistance to and acceptance of social change, as a change moves from proposed, to imminent, to established. Finally, we discuss how threatened systems shore up their authority by co-opting legitimacy from other sources, such as governments that draw on religious concepts, and the role of institutional-level factors in perpetuating the status quo.
The dopamine transporter VNTR polymorphism moderates the relationship between acute response to alcohol and future alcohol use disorder symptoms

Alcohol use disorder (AUD) is a genetically influenced disease with peak onset in young adulthood. Identification of factors that predict whether AUD symptoms will diminish or persist after young adulthood is a critical public health need. King and colleagues previously reported that acute response to alcohol predicted future AUD symptom trajectory. Genes associated with brain dopamine signaling, which underlies alcohol's rewarding effects, might influence this finding. This study analyzed whether variation at a variable number tandem repeat polymorphism in DAT1/SLC6A3, the gene encoding the dopamine transporter, moderated the predictive relationships between acute response to alcohol and future AUD symptoms among participants enrolled in the Chicago Social Drinking Project (first two cohorts). Heavy‐drinking young adults (N = 197) completed an alcohol challenge, in which acute response (liking, wanting, stimulation, and sedation) was measured. Alcohol use disorder symptoms were assessed over the following 6 years. DAT1 genotype significantly moderated the interactions between follow‐up time and alcohol liking (P = 0.006) and wanting (P = 0.006) in predicting future AUD symptoms. These predictive effects were strongest among participants who carried the DAT1 9‐repeat allele, previously associated with enhanced striatal dopamine tone relative to the 10‐repeat allele. Exploratory analyses indicated that DAT1 effects on the relationship between alcohol liking and AUD symptoms appeared stronger for females (n = 79) than males (n = 118) (P = 0.0496). These data suggest that heavy‐drinking DAT1 9‐repeat allele carriers who display high alcohol‐induced reward in young adulthood may be predisposed to persistent AUD symptoms and support combining genotypic and phenotypic information to predict future AUD risk.
FootNotes

The majority of information in the physical environment is conveyed visually, meaning that people with vision impairments often lack access to the shared cultural, historical, and practical features that define a city. How can someone who is blind find out about the sleek skyscrapers that dot a modern city's skyline, historic cannons that have been remade into traffic pillars, or ancient trees that uproot a neighborhood's sidewalks? We present FootNotes, a system that embeds rich textual descriptions of objects and locations in OpenStreetMap, a popular geowiki. Both sighted and blind users can annotate the physical environment with functional, visual, historical, and social descriptions. We report on the experience of ten participants with vision impairments who used a spatialized audio application to interact with these annotations while exploring a city. By sharing rich annotations of physical objects and areas, FootNotes helps people thoroughly explore a new location or serendipitously discover previously unknown features of familiar environments.
A Model-Driven Approach to Evolve Recommender Systems

Recommender systems have become an important issue on Web applications, but its research is usually focused on algorithms and data optimization. However, as the recommendation techniques improve and these systems become more commonly used in software applications, there is the need of easily adapt and evolve them. To address this need, we propose a model-driven approach to evolve recommender systems and present an architecture solution from our research, using an events management system as the domain for an use-case scenario. Future work might demonstrate the architecture feasibility.
Analysis of Urban Regions Popularity Using Foursquare

With the raising of social networks and social sensing, several methods and applications focused on urban and economic analysis emerged to assist urban planning and business solutions. Thus, the inhabitants of a city share social data according to their context, acting as sensors. In this way, location-based social networks have become important because they associate social data with precise locations, which allows promising studies. In this work, we present a method of popularity analysis in urban regions through Foursquare, using the concept of functional regions. For this, we used 204,737 check-ins for 2 years from the same locality for a case study. In this way, we consider not only the main functions of each region, but also the secondary functions. We also present a machine learning model in which a neural network is used to define strategic regions for venues considering not only the subcategories of Foursquare, but also the macrocategories.
linc‐SCRG1 accelerates liver fibrosis by decreasing RNA‐binding protein tristetraprolin

The biologic roles of long noncoding RNAs (lncRNAs) in liver fibrosis remained unknown. Through microarray analysis, linc‐SCRG1 (a lncRNA with transcript length 3118 bp) was found up‐regulated 13.62‐fold in human cirrhotic tissues. Quantitative PCR verified that linc‐SCRG1 increased along with liver fibrosis progression in human tissues and in activated LX2 cells induced by TGF‐β1. Knockdown of linc‐SCRG1 significantly reversed the effects of TGF‐β1 on LX2, including inhibiting activation, promoting apoptosis, reducing proliferation, lessening invasion, and down‐regulating genes [fibrosis‐related mRNA: α‐smooth muscle actin (α‐SMA), type I collagen, and B‐cell lymρhoma‐2; invasion‐related mRNA: matrix metalloρeρtidase‐2 (MMP‐2), MMP‐9, and MMP‐13; inflammation‐related mRNA: TNF‐α, IL‐6, and IL‐10]. linc‐SCRG1 had binding sites with tristetraprolin (TTP), a kind of RNA‐binding protein, and specifically combined to TTP proteins. Overexpression of linc‐SCRG1 would cause TTP mRNA unstably and proteins decreasing. TTP mRNA was proved having negative relevance with linc‐SCRG1 and was gradually reduced during human liver fibrosis progression. Overexpressing TTP resulted in knockdown of lincSCRG1 and degraded downstream target genes (MMP‐2 and TNF‐α) in activated LX2. Overexpressing TTP had the same effects as small interfering RNA‐lincSCRG1 (si‐lincSCRG1), whereas knockdown of TTP had reversal effects on si‐lincSCRG1 in activated LX2. In summary, linc‐SCRG1 reduced TTP and restricted its degradation of target genes TNF‐α and MMP‐2. Therefore, linc‐SCRG1 had a repressing TTP‐elicited inactivation effect on hepatic stellate cell (HSC) phenotypes. Inhibition of linc‐SCRG1 may be a novel therapeutic approach to inactivate HSCs and extenuate human liver fibrosis. —Wu, J.‐C. , Luo, S. ‐Z. , Liu, T. , Lu, L. ‐G. , Xu, M. ‐Y. linc‐SCRG1 accelerates liver fibrosis by decreasing RNA‐binding protein tristetraprolin. FASEB J. 33, 2105–2115 (2019). www.fasebj. org
GritNet 2: Real-Time Student Performance Prediction with Domain Adaptation

Increasingly fast development and update cycle of online course contents, and diverse demographics of students in each online classroom, make student performance prediction in real-time (before the course finishes) an interesting topic for both industrial research and practical needs. In that, we tackle the problem of real-time student performance prediction with on-going courses in domain adaptation framework, which is a system trained on students' labeled outcome from one previous coursework but is meant to be deployed on another. In particular, we first review recently-developed GritNet architecture which is the current state of the art for student performance prediction problem, and introduce a new unsupervised domain adaptation method to transfer a GritNet trained on a past course to a new course without any (students' outcome) label. Our results for real Udacity students' graduation predictions show that the GritNet not only generalizes well from one course to another across different Nanodegree programs, but enhances real-time predictions explicitly in the first few weeks when accurate predictions are most challenging.
The Multifunctional Fungal Ergosterol

The roles of ergosterol in the regulation of membrane fluidity and structure, as well its role as a target for the activity of antifungals, have been known for decades. Two recent studies, however, demonstrated that ergosterol is an immunologically active lipid that induces pyroptosis and that virtually all steps of its biosynthetic process are potential drug targets. ABSTRACT The roles of ergosterol in the regulation of membrane fluidity and structure, as well its role as a target for the activity of antifungals, have been known for decades. Two recent studies, however, demonstrated that ergosterol is an immunologically active lipid that induces pyroptosis and that virtually all steps of its biosynthetic process are potential drug targets. In combination, those two reports strongly indicate that the biological relevance of ergosterol is broader than the current literature suggests.
Defective DNA repair in hereditary ovarian cancers: Implications for therapy

Purpose. The role of mutated DNA repair pathways in hereditary ovarian cancer (OC) and the clinical basis for the use of poly(ADP‐ribose) polymerase (PARP) enzyme inhibitors and an immune checkpoint inhibitor as novel targeted therapies in the treatment of certain OC subtypes are reviewed. Summary. OC is the most lethal of all gynecologic malignancies and encompasses a highly diverse collection of cancers. Hereditary OCs are a unique subtype of OC encompassing up to 24% of all OCs, including cancers driven by germline mutations of the BRCA1 or BRCA2 genes, mutations associated with Fanconi anemia (FA), BRCAness germline mutations, and Lynch syndrome. With an increasing wealth of genomic data available in cancer research, a common thread of defective DNA repair pathways as a primary driver of hereditary OCs has emerged. OCs driven by BRCA1/2, FA‐associated, and BRCAness germline mutations have a demonstrated sensitivity to PARP inhibitors due to underlying deficiencies in DNA homologous recombination; however, clinical responses are often partial and highly dependent on platinum sensitivity. Additionally, the immune checkpoint inhibitor pembrolizumab is indicated for certain metastatic solid tumors characterized by microsatellite instability, a distinguishing feature highly associated with DNA mismatch repair deficiency in Lynch syndrome–associated cancers, including some OCs. Conclusion. In hereditary OC syndromes, mutations in DNA repair pathways form the clinical basis for the use of PARP inhibitors and an immune checkpoint inhibitor as novel targeted therapies.
Investigational drugs targeting prostaglandin receptors for the treatment of glaucoma

ABSTRACT Introduction: Prostaglandin F2α analogs were the first prostaglandin agonists introduced for glaucoma treatment. Thanks to their efficacy and favorable tolerability they set a high bar in competition, with a resultant paucity in new hypotensive drug development for many years. However, the scientific community has shown recently a new interest in exploring new options for glaucoma treatment, generating a remarkable incentive in the marketplace for new drugs. Areas covered: This article reviews agents targeting prostaglandin receptors that are currently being investigated for glaucoma treatment. We searched published literature for agonists targeting all subtypes of prostaglandin receptors found in ocular tissues. EP and FP receptor agonists are currently in the spotlight of clinical research, while less attention is paid in DP receptor agonists. Expert opinion: Prostaglandin analogs, targeting different and combinations of receptor subtypes and compounds that exhibit additivity to commonly prescribed medications seem to be highly promising options. New treatments need to be safe, more effective, superior to existing therapies, tolerable and cost-effective. New generation compounds with multiple mechanisms of action or multiagent formulations are vigorously being investigated and generated in laboratories around the world.
Wavelet Transform Based ECG Denoising Using Adaptive Thresholding

Electrocardiogram (ECG) is a widely employed tool for the analysis of cardiac disorders and clean ECG is often desired for proper treatment of cardiac ailments. In the real scenario, ECG signals are usually corrupted with various noises during acquisition and transmission. As an important branch of wavelet transform, multiresolution has achieved good results in the noise reduction processing in many fields, such as ECG signal, voice signal, image signal and so on. However, multiresolution has strong dependence on the selection of wavelet threshold and wavelet function. In this paper, an adaptive wavelet threshold calculation and selection method is proposed. Based on the heuristic threshold optimization method, the adjustment factor of wavelet decomposition layer number and level influence is incorporated into the method. By dynamically adjusting the threshold calculation function for wavelet coefficients of each layer, more reasonable signal decomposition and noise reduction could be realized. The experimental results show that the proposed algorithm could achieve better performance in reducing the noise of ECG and could meet the needs of clinical application.
Comprehensive transcriptome profiling in elderly cancer patients reveals aging‐altered immune cells and immune checkpoints

Aging is the single most significant risk factor for cancer development. However, the potential impact of aging on cancer microenvironment remains poorly understood. Here, we performed a pan‐cancer transcriptome analysis to identify aging‐specific molecular patterns across 18 cancer types. Strikingly, aging‐specific molecular features define human cancers into two types, including the strong and weak aging‐effect groups. Significant aging associated molecular signature was observed in 16 cancer types (strong aging‐effect group) such as breast invasive carcinoma and acute myeloid leukemia. In such 16 cancer types, old patients showed obvious poor survival compared to young patients, but this observation was not found in the weak aging‐effect cancers. Aging‐associated cancer‐relevant molecules significantly enriched in 23 pathways including EMT and KRAS signaling. More interestingly, in cancer microenvironment, aging significantly restrains adaptive immunity, but strikingly, increases the number of infiltrated innate immune cells. Further analysis shows that the expression of immune checkpoints including PD‐1, PD‐L1, PD‐L2 and CTLA‐4 are mostly correlated with age. In general, cancer cells in elderly patients show a more aggressive phenotype and their surrounding microenvironment is under a more immune suppression status compared to young patients. Our study provides a systematic understanding of aging‐associated molecular features in pan‐cancer and indicates a clinical requirement to develop aging‐specific therapeutic strategies in a majority of cancer types. Furthermore, aging‐altered immune cells and immune checkpoints should be considered in cancer immunotherapy.
Applicability of Selective Data Collection to Cancer Clinical Studies for Supplemental Marketing Approvals: Frequency of Adverse Reactions Observed During Supplemental Approval Compared With First Approval

Background In 2012, the US Food and Drug Administration (FDA) issued the draft guidance “Determining the Extent of Safety Data Collection Needed in Late Stage Premarket and Postapproval Clinical Investigations. ” The selective data collection approach proposed in this guidance leads to reductions in costs and work time and may improve the quality of the database for clinical trials. The current study evaluated the applicability of selective data collection for oncology drugs. Methods The labeling information of oncology drugs obtained supplemental approvals from the FDA between 2005 and 2014 were used. The frequency of adverse reactions observed in clinical trials between the first approval and supplemental approvals of a specific drug were compared. Paired studies were categorized into the following 4 groups: A, same tumor type and same usage; B, same tumor type and different usage; C, different tumor type and same usage; D, different tumor type and different usage. Results A total of 46 study pairs for additional drug indications were investigated. In group A, 6 of the 7 pairs showed a high correlation coefficient ( r = 0.988, 0.953, 0.947, 0.935, 0.853, and 0.846). Conclusions Selective data collection should be adopted in cases in which the additional indication of a drug is for the same tumor type and usage as the first or previous indication.
Steer-By-WiFi: Lateral Vehicle Control for Take-Overs with Nomadic Devices

Automated vehicles could omit traditional steering controls to provide larger spaces for driver-passengers or prevent unnecessary interventions. However, manual control could still be necessary to provide manual driving fun or respond to Take-Over requests (TORs). This paper investigates, whether brought-in consumer devices (in this case a 10.2 inch tablet) can act as input alternative to classical steering wheels in TOR situations. Results of a driving simulator study (n=14) confirm that responding to Take-Overs with nomadic devices can reduce response times in imminent transitions during engagement in Non-Driving Related Tasks (NDRTs), as a change of the 'device in hands' is omitted. Further on, subjective scales addressing user experience show that the approach is well accepted. We conclude that nomadic device integration is a crucial pre-requisite for the success of automated vehicles, but for steering input several pivotal issues still need to be solved.
Evaluating Water Use Efficiency in China's Western Provinces Based on a Slacks-Based Measure (SBM)-Undesirable Window Model and a Malmquist Productivity Index

This paper evaluated the water use efficiency in 12 Chinese western provinces from 2005 to 2015. Based on data availability and the index selection rationality and the slacks-based measure (SBM)-undesirable Window analysis model and the Malmquist productivity index, the water resource inputs and outputs were measured to analyze water use efficiency. Total investment in fixed assets for the whole society and total water, made up of total agricultural water, total industrial water, and total domestic water, were used as the input indexes, and regional GDP and waste water discharge were the output indexes, with the waste water discharge being regarded as an undesirable output. The data from different years and different provinces in the same period, and data from the same year and the same provinces in different periods were compared in order to derive the water resource efficiency and technical changes over time and space. It was found that the total water resource factor productivity in the 12 provinces grew slowly in the study period, that water resource technical progress positively affected water use efficiency, and that a lack of technical efficiency restricted water use efficiency growth. Several suggestions are given to optimize water use efficiency in the 12 provinces. The research findings and suggestions provide valuable reference for studies in related fields.
Experiencing Electrical Muscle Stimulation

Electrical Muscle Stimulation (EMS) offers rich opportunities for interaction. By varying stimulation parameters (amplitudes, pulse widths and frequencies), EMS can be used to either trigger muscle contractions, and so convey object affordances or guide user movements, or provide rich haptic feedback. However, the way users' experience changes with these parameters, and EMS in general, is poorly understood. Using a phenomenologically inspired interview technique, the explicitation interview, we study fifteen users' experience of EMS across 48 combinations of stimulation parameters. We synthesize the descriptions of EMS and relate stimulation parameters to categories of experience, such as 'temperature', 'motion', and 'sensitivity'. From the interviews, we explore more general topics in body-based interfaces, including the experience of control, metaphors for having your body actuated, and the relation between EMS parameters and perceived depth and location of sensations. These findings provide a vocabulary of EMS experience, and an insight into the relationship between specific parameters and associated sensations. In turn, this can help designers consider the user experience of EMS when developing interfaces.
RecTwitter: A Semantic-Based Recommender System for Twitter Users

Twitter is a microblog which contains large amounts of users who contribute with messages for a wide variety of real-world events. It is possible to identify users who share interests using the messages published in their timeline. However, this task is an exhausting process because the algorithm has to analyze all users' messages. In this project, we propose a semantic recommendation system based on SWRL rules to recommend accounts to be followed or unfollowed. In order to evaluate the recommendations, we conducted an experiment with real users. The results show that 80% of the recommendations were generated to unfollow and 20% to follow some account.