Miracle-dz/UniFAR-FTUs huggingface dataset:
Interval Dominance-Based Feature Selection for Interval-Valued Ordered Data

Dominance-based rough approximation discovers inconsistencies from ordered criteria and satisfies the requirement of the dominance principle between single-valued domains of condition attributes and decision classes. When the ordered decision system (ODS) is no longer single-valued, how to utilize the dominance principle to deal with multivalued ordered data is a promising research direction, and it is the most challenging step to design a feature selection algorithm in interval-valued ODS (IV-ODS). In this article, we first present novel thresholds of interval dominance degree (IDD) and interval overlap degree (IOD) between interval values to make the dominance principle applicable to an IV-ODS, and then, the interval-valued dominance relation in the IV-ODS is constructed by utilizing the above two developed parameters. Based on the proposed interval-valued dominance relation, the interval-valued dominance-based rough set approach (IV-DRSA) and their corresponding properties are investigated. Moreover, the interval dominance-based feature selection rules based on IV-DRSA are provided, and the relevant algorithms for deriving the interval-valued dominance relation and the feature selection methods are established in IV-ODS. To illustrate the effectiveness of the parameters variation on feature selection rules, experimental evaluation is performed using 12 datasets coming from the University of California-Irvine (UCI) repository.
Social support, social strain and declines in verbal memory: sex-specific associations based on 16-year follow-up of the English Longitudinal Study of Ageing cohort

Abstract Objectives Previous investigations of cognitive aging have mainly focused on structural aspects of social relations (e.g. network size and composition), thereby neglecting the role of qualitative aspects of social relations. The current longitudinal study examined sex-specific differences in verbal memory decline by measures of perceived relationship quality (social support/strain) by relationship type. Method In the English Longitudinal Study of Ageing (ELSA), 10,109 participants aged 50–89 years were assessed at wave 1 (baseline: 2002–03) and followed to wave 9 (2017–18). Verbal memory was assessed by immediate and delayed word-recall tasks. Social support/strain was measured by relationship type (spouse; children; family; friends). Random effects within-between (REWB) modelling was used to separate between- and within-person effects. We estimated associations between social support/strain and (1) baseline levels of memory (main effects), and (2) rate of decline in memory (interaction with time-since-baseline). Results Longitudinal associations were most prominent for men, specific to relationship type, and showed between- rather than within-person effects. Among men, higher spousal strain was associated with faster memory decline (βbetween-effect×time = −0.043; 95% CI [−0.084, −0.002]; p = .039), whilst greater support from children was associated with slower decline (βbetween-effect×time = 0.020; 95% CI [0.002, 0.039]; p = .033). Men with higher strain from friends showed lower baseline memory (βbetween-effect = −0.382; 95% CI [−0.627, −0.137]; p=.002) and faster decline (βbetween-effect×time = −0.047; 95% CI [−0.095, 0.000]; p = .051). Conclusion Between-person differences in social support/strain were modestly associated with memory decline, especially among men.
Suvorexant ameliorated sleep disturbance, opioid withdrawal, and craving during a buprenorphine taper

Increased orexin/hypocretin signaling is implicated in opioid withdrawal, sleep disturbances, and drug-seeking behaviors. This study examined whether a dual-orexin receptor antagonist would improve sleep and withdrawal outcomes when compared with placebo during a buprenorphine/naloxone taper. Thirty-eight participants with opioid use disorder were recruited to a clinical research unit and maintained on 8/2 to 16/4 mg of buprenorphine/naloxone treatment for 3 days before being randomized to 20 mg of suvorexant (n = 14), 40 mg of suvorexant (n = 12), or placebo (n = 12); 26 individuals completed the study. After randomization, participants underwent a 4-day buprenorphine/naloxone taper and 4-day post-taper observation period. Total sleep time (TST) was collected nightly with a wireless electroencephalography device and wrist-worn actigraphy; opioid withdrawal symptoms were assessed via the Subjective Opiate Withdrawal Scale (SOWS); and abuse potential was assessed on a 0- to 100-point visual analog scale of “High” every morning. A priori outcomes included two-group (collapsing suvorexant doses versus placebo) and three-group comparisons of area-under-the-curve (AUC) scores for TST, SOWS, and High. In two-group comparisons, participants receiving suvorexant displayed increased TST during the buprenorphine/naloxone taper and decreased SOWS during the post-taper period. In three-group comparisons, participants receiving 20 mg of suvorexant versus placebo displayed increased AUC for TST during the buprenorphine/naloxone taper, but there was no difference in SOWS among groups. There was no evidence of abuse potential in two- or three-group analyses. The results suggest that suvorexant might be a promising treatment for sleep and opioid withdrawal in individuals undergoing a buprenorphine/naloxone taper. Description Suvorexant reduced sleep disturbance during opioid withdrawal and may improve opioid use disorder treatment outcomes. Reducing withdrawal symptoms In patients with opioid use disorder (OUD), opioid withdrawal is associated with long-term sleep disturbances that can affect drug-seeking behavior and the overall treatment outcome. Previous studies have shown that orexin/hypocretin signaling is implicated in sleep continuity and its inhibition can reduce withdrawal symptoms in rodents. Here, Huhn et al. evaluated the effects of the orexin receptor antagonist suvorexant in 38 participants with OUD while undergoing buprenorphine treatment as part of opioid withdrawal therapy. Suvorexant improved sleep compared to placebo with no evidence of abuse potential, suggesting that targeting the orexin signaling might reduce the negative effects of opioid withdrawal on sleep quality.
NOD/RIPK2 signalling pathway contributes to osteoarthritis susceptibility

Objectives How inflammatory signalling contributes to osteoarthritis (OA) susceptibility is undetermined. An allele encoding a hyperactive form of the Receptor Interacting Protein Kinase 2 (RIPK2) proinflammatory signalling intermediate has been associated with familial OA. To test whether altered nucleotide-binding oligomerisation domain (NOD)/RIPK2 pathway activity causes heightened OA susceptibility, we investigated whether variants affecting additional pathway components are associated with familial OA. To determine whether the Ripk2104Asp disease allele is sufficient to account for the familial phenotype, we determined the effect of the allele on mice. Methods Genomic analysis of 150 independent families with dominant inheritance of OA affecting diverse joints was used to identify coding variants that segregated strictly with occurrence of OA. Genome editing was used to introduce the OA-associated RIPK2 (p.Asn104Asp) allele into the genome of inbred mice. The consequences of the Ripk2104Asp disease allele on physiology and OA susceptibility in mice were measured by histology, immunohistochemistry, serum cytokine levels and gene expression. Results We identified six novel variants affecting components of the NOD/RIPK2 inflammatory signalling pathway that are associated with familial OA affecting the hand, shoulder or foot. The Ripk2104Asp allele acts dominantly to alter basal physiology and response to trauma in the mouse knee. Whereas the knees of uninjured Ripk2Asp104 mice appear normal histologically, the joints exhibit a set of marked gene expression changes reminiscent of overt OA. Although the Ripk2104Asp mice lack evidence of chronically elevated systemic inflammation, they do exhibit significantly increased susceptibility to post-traumatic OA (PTOA). Conclusions Two types of data support the hypothesis that altered NOD/RIPK2 signalling confers susceptibility to OA.
Effects of Chronic Inhalation of Electronic Cigarette Vapor Containing Nicotine on Neurobehaviors and Pre/Postsynaptic Neuron Markers

Nicotine-exposed animal models exhibit neurobehavioral changes linked to impaired synaptic plasticity. Previous studies highlighted alterations in neurotransmitter levels following nicotine exposure. Vesicular glutamate transporter (VGLUT1) and vesicular gamma-aminobutyric acid (GABA) transporter (VGAT) are essential for the transport and release of glutamate and GABA, respectively, from presynaptic neurons into synapses. In our work, an e-cigarette device was used to deliver vapor containing nicotine to C57BL/6J mice for four weeks. Novel object recognition, locomotion, and Y-maze tests were performed to investigate the behavioral parameters. Protein studies were conducted to study the hippocampal expression of VGLUT1, VGAT, and postsynaptic density protein 95 (PSD95) as well as brain cytokine markers. Long-term memory and locomotion tests revealed that e-cigarette aerosols containing nicotine modulated recognition memory and motor behaviors. We found that vapor exposure increased VGLUT1 expression and decreased VGAT expression in the hippocampus. No alterations were found in PSD95 expression. We observed that vapor-containing nicotine exposure altered certain brain cytokines such as IFNβ-1 and MCP-5. Our work provides evidence of an association between neurobehavioral changes and altered hippocampal VGLUT1 and VGAT expression in mice exposed to e-cigarette vapors containing nicotine. Such exposure was also associated with altered neurobehaviors, which might affect neurodegenerative diseases.
Changes in the development of opioid tolerance on re-exposure among people who use heroin: A qualitative study

Background and aims This qualitative study aimed to explore how the development of tolerance to both the psychoactive and respiratory depressant effects of heroin on re-exposure are experienced by people who use heroin. Methods Semi-structured one-to-one interviews were conducted with 20 adults who currently or previously used heroin (for at least 6 months), with any type of administration (injected, smoked) and experience of abstinence (at least 2 weeks) and relapse. Topic guides explored the participants understanding of tolerance, their experience of developing tolerance to heroin and of tolerance following relapse. Interviews were audio‐recorded and transcribed. Thematic analysis was used to generate salient themes. Results The analysis produced three broad themes: lay understanding of tolerance; tolerating tolerance; and rapid tolerance development following relapse. Tolerance was defined as the body adapting to regular drug use, so that the drug no longer produced the same level of effect. Tolerance was experienced as interacting and co-developing with physical dependence and the symptoms of withdrawal. Indeed, several participants did not differentiate between tolerance and dependence. Most participants did not notice tolerance to respiratory depression. Tolerance levels fluctuated—increasing over periods of regular use and reducing when abstinent. Using more drug was the most common response to increasing tolerance to the desired effects. On re-use following abstinence, tolerance was experienced as developing more quickly in the most recent relapse compared to the first. Tolerance was also perceived to return more quickly with each abstinence-relapse cycle. Conclusions Qualitative accounts of tolerance report that tolerance returns more quickly with each relapse episode. By elucidating the mechanism(s) involved and potentially discovering how they could be switched on prior to relapse occurring we might be able to develop a beneficial harm reduction treatment for people in abstinence that would protect against overdose occurring on subsequent relapse.
Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review

Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain disease and monitor treatment as non-invasive imaging technology. MRI produces three-dimensional images that help neurologists to identify anomalies from brain images precisely. However, this is a time-consuming and labor-intensive process. The improvement in machine learning and efficient computation provides a computer-aid solution to analyze MRI images and identify the abnormality quickly and accurately. Image segmentation has become a hot and research-oriented area in the medical image analysis community. The computer-aid system for brain abnormalities identification provides the possibility for quickly classifying the disease for early treatment. This article presents a review of the research papers (from 1998 to 2020) on brain tumors segmentation from MRI images. We examined the core segmentation algorithms of each research paper in detail. This article provides readers with a complete overview of the topic and new dimensions of how numerous machine learning and image segmentation approaches are applied to identify brain tumors. By comparing the state-of-the-art and new cutting-edge methods, the deep learning methods are more effective for the segmentation of the tumor from MRI images of the brain.
Phylogenomic and functional characterization of an evolutionary conserved cytochrome P450-based insecticide detoxification mechanism in bees

Significance Bee pollinator pesticide risk assessment is a regulatory requirement for pesticide registration and is largely based on experimental data collected for surrogate species such as the western honeybee. Recently, CYP9Q3, a honeybee cytochrome P450 enzyme, has been shown to efficiently detoxify certain insecticides such as the butenolide flupyradifurone and the neonicotinoid thiacloprid. Here we analyzed genomic data for 75 bee species and demonstrated by the recombinant expression of 26 CYP9Q3 putative functional orthologs that this detoxification principle is an evolutionary conserved mechanism across bee families. Our toxicogenomics approach has the potential to inform pesticide risk assessment for nonmanaged bee species that are not accessible for acute toxicity testing.
Chromosome 1q21 aberrations identify ultra high‐risk myeloma with prognostic and clinical implications

Numerical abnormalities of chromosome 1q (+1q21) are common in patients with newly diagnosed multiple myeloma (MM) but their prognostic impact remains a matter of debate. In addition, the impact of the number of copies of 1q21 is not known. We analyzed 912 consecutive patients with symptomatic MM to evaluate the prognostic implications of +1q21 and of their copy number variations, as assessed by FISH. At the time of initial diagnosis, 249 (27.3%) patients had +1q21, of which 150 (16.4%) had 3 copies and 99 (10.9%) had 4 or more copies. Presence of +1q21 was associated with advanced ISS stage (p = .003), concurrent presence of other cytogenetics aberrations and advanced R‐ISS stage (p < .001). Patients with +1q21 had inferior PFS (median 34 vs. 20 months, p < .001) and OS (median 75 vs. 44 months, p < .001) but the copy number of 1q21 had no additional prognostic impact. In multivariate analysis, adjusting for R‐ISS, age, treatment and HDM, +1q21 remained an independent prognostic factor both for PFS (p < .001) and OS (p = .008). The detrimental prognostic effect of +1q21 was more profound in R‐ISS‐3 patients, identifying a subgroup with OS of just 16 months (vs. 46 for R‐ISS‐3 without +1q21, p < .001). We further validated our findings in an independent cohort of 272 patients. In conclusion, the presence of +1q21 is associated with more advanced disease, inferior PFS, and OS but especially patients with R‐ISS‐3 disease and +1q21 have a very poor outcome comprising an ultra‐high‐risk group.
A Systematic Review of Clinical Practice Guidelines for Cataract: Evidence to Support the Development of the WHO Package of Eye Care Interventions

The World Health Organization (WHO) is developing a Package of Eye Care Interventions (PECI) to facilitate the integration of eye care into Universal Health Coverage. This paper presents the results of a systematic review of clinical practice guidelines for cataract in adults, to help inform PECI development. We searched academic and guideline databases, and websites of professional associations, for guidelines published between January 2010 and April 2020. Guidelines were excluded if there was commercial funding or unmanaged conflicts of interest. Quality appraisal was conducted using the Appraisal of Guidelines for Research and Evaluation (AGREE) II tool. We identified 3778 reports, 35 related to cataract guidelines, four of which met the inclusion criteria (United Kingdom: 2, United States: 1, Iran: 1). The recommendations across the four guidelines covered pre-operative (43%), intra-operative (37%), and post-operative interventions (20%). Most ‘strong’ recommendations were supported by good quality evidence. Differences in recommendations across guidelines may be attributable to time of publication or regional differences in surgical practice. Few guidelines met the quality criteria, and only three countries were represented. The results of this step of the PECI development process will inform subsequent phases for development of the WHO’s package of evidence-based eye care interventions for cataract.
Form-finding optimization methods for free-form reticulated shells: Reverse realization and numerical simulation

Free-form reticulated shells should not only satisfy the requirement of a specific geometric configuration but also have rational mechanical properties. This article introduced two form-finding methods of free-form configuration. The first method was a reverse realization method that is based on hanging fabric with a given boundary condition; the second method was a numerical simulation method that is based on the equilibrium characteristics of a natural tension membrane combined with a geometrical characteristics analysis and a mechanical properties optimization. The article then discusses the conducted beneficial comparison. The analytical results demonstrate that both these form-finding methods are feasible for obtaining rational free-form shells, and the numerical simulation method is more convenient for obtaining the surface family.
Interparental Conflict and Young Adult Romantic Relationships: A Systematic Review

In the last two decades, researchers have been progressively investigating the impact of interparental conflict (IPC) on young adults romantic relationships. This systematic review aimed to synthesize literature on IPC and romantic relationship outcomes among young adults and highlight mechanisms found in this link. Following the PRISMA protocol, 3232 studies were identified using Boolean searches on ProQuest, PubMed, EBSCOhost, Jstor, Cochrane, and Google Scholar, and 17 met the eligibility criteria. To be included, in addition to having IPC and romantic relationship outcomes as variables, studies had to be quantitative in design, have a mean sample age of 18–25, include only participants in romantic relationships at the time of the study, and be published in English with full text available. The review found that IPC is associated with negative conflict management, both perpetration and victimization of aggression, worse communication, negative conflict behaviors, and poor relationship quality. Other outcomes like relationship satisfaction, commitment, as well as mediator variables in the link between IPC and young adult romantic relationship outcomes, such as attitudes towards marriage and conflict attributions, yielded varied results. Several shortcomings in the methodology of the reviewed articles, such as the research sample and measures, were discovered. To deal with the impact of IPC on offspring’s romantic relationships, preventive interventions should be designed and evaluated, and more research with different variables and study designs, with more men, other ethnicities, and more representative sample frames are needed to detect crucial mediators and obtain reliable and generalizable results.
Novel COVID-19 Diagnosis Delivery App Using Computed Tomography Images Analyzed with Saliency-Preprocessing and Deep Learning

This app project was aimed to remotely deliver diagnoses and disease-progression information to COVID-19 patients to help minimize risk during this and future pandemics. Data collected from chest computed tomography (CT) scans of COVID-19-infected patients were shared through the app. In this article, we focused on image preprocessing techniques to identify and highlight areas with ground glass opacity (GGO) and pulmonary infiltrates (PIs) in CT image sequences of COVID-19 cases. Convolutional neural networks (CNNs) were used to classify the disease progression of pneumonia. Each GGO and PI pattern was highlighted with saliency map fusion, and the resulting map was used to train and test a CNN classification scheme with three classes. In addition to patients, this information was shared between the respiratory triage/radiologist and the COVID-19 multidisciplinary teams with the application so that the severity of the disease could be understood through CT and medical diagnosis. The three-class, disease-level COVID-19 classification results exhibited a macro-precision of more than 94.89% in a two-fold cross-validation. Both the segmentation and classification results were comparable to those made by a medical specialist.
Hybrid Dynamical System Methods for Legged Robot Locomotion with Variable Ground Contact

This thesis investigates the variable contact situations of rigid robot feet in legged robot locomotion. One major goal is to include the rotation around foot edges in locomotion cycles. For walking robots they are referred to as the toe roll phase and the heel roll phase. The alternation between underactuated motion phases and completely actuated motion phases is believed to contribute in a decisive manner in enabling dynamic locomotion. Dynamic locomotion comprises e.g. walking, running, hopping, standing up, and many more motion patterns characterized by variable contact with the environment. A control-theoretic approach to legged robot locomotion is presented that uses an event-based hybrid (discrete-continuous) model with underlying rigid-body assumption. Events occur whenever the ground contact situation changes; this is either when a contact resolves or when a contact is established. The continuous time dynamics that is generally different for all contact situations is allowed to switch at these contact changes. Then discontinuous collision behavior is taken into account. To obtain periodic locomotion cycles, a trajectory planning algorithm is proposed where the boundary value problem is solved that relates the initial and final configuration of the robot. The resulting periodic robot locomotion is investigated for orbital stability using Poincare map analysis of the hybrid trajectories. Finally, a hybrid control strategy is presented for balance control which makes use of the invariance control method. Throughout this thesis, the methods are demonstrated for three example robots: a compass gait robot, a monoped robot, and a gymnast robot.