Miracle-dz/UniFAR-FTUs huggingface dataset:
User perspective on receiving adaptive equipment after stroke: A mixed-methods study

Background. Adaptive equipment (AE) is frequently provided during stroke rehabilitation by occupational therapists. Purpose. This study aimed to identify the AE that people typically use after a stroke and the outcomes achieved as a result, and to explore people’s experiences obtaining and using AE, to inform both practice and policy in this field. Method. A mixed-methods study, involving a postal questionnaire and interviews, used descriptive statistics and grounded theory to analyze the quantitative and qualitative data, respectively. Findings. Questionnaire data (n = 258) revealed mobility AE was issued most frequently, with increased safety as the primary reported outcome. Interview data (n = 15) indicated relationships with health professionals and the hospital environment shaped early AE selection and use. Once home, making sense of AE and community participation were more influential. Implications. Therapeutic relationships and reflection time are critical to maximize AE use after stroke. Policy and related funding for AE need to prioritize community participation.
Face Spoof Detection by Motion Analysis on the Whole Video Frames

Since the popularity of social media has increased, the spoofing attack is one of the many issues that occur in the face authentication system. Video replay attack is the most vulnerable type of spoofing attack, because distinguishing the face spoofing video from its original is very difficult. Most of the existing studies to detect face spoofing attack focused only on the face area and on static images. These approaches have weaknesses since in the real situation, the background texture and other body parts such as hair and shoulders have also been captured by the camera. In this paper, a face spoofing detection method using motion analysis in the whole video frame was discussed. To optimize the segmentation process between the object and the background area, the model-based segmentation was implemented so that all parts of the object‘s/user's body can be correctly separated from the background. The data used are 1200 videos from IDIAP Replay-Attack database and 500 videos from synthesized database for additional experimental data. The results of the experiment were that Half Total Error Rate (HTER) were 4% for IDIAP Replay-Attack data and 1% for synthesized data.
Attitudes toward euthanasia among hospice nurses: Political ideology or religious commitment?

Abstract Attitudes toward euthanasia have been linked with political ideology among hospice nurses; however, a larger body of research has linked attitudes toward euthanasia with religiosity. The purpose of this study was to explore relationships between political ideology, religious commitment, and attitudes toward active and passive euthanasia among hospice nurses. Hospice nurses (N = 90) volunteered to take an online survey. Religious commitment fully mediated the relationship between social political ideology and disapproval of active euthanasia. The results suggest that, among hospice nurses, religious commitment accounts for links between social political ideology and disapproval of active euthanasia.
Knee Angle Measurement Device Using Fiber Bragg Grating Sensor

Human joint kinematics has established its capacity as a vital tool for joint pathology and gait analysis. Range of motion (ROM) of a knee joint performed by flexion and extension is an essential tool to assess the efficacy of surgical interventions or therapeutic assessment. This paper proposes a novel wearable device for dynamic measurement of knee joint angle using fiber Bragg grating (FBG) sensor. The proposed knee angle measurement device (KAMD) can transduce the angular movement between the shin and the thigh into strain variations on a cantilever, which is acquired by the FBG sensor over it. The KAMD is also facilitated with tuneable sensitivity with three modes of high sensitivity mode, medium sensitivity mode, and low sensitivity mode, which can be opted based on application specific resolution and range of measurement. The ROM data obtained from the KAMD are validated against ROM obtained from commercially available Polhemus Sensors. Furthermore, the synchronization of the knee joint movement of both legs during walking along with stance and swing phase is illustrated, which shows the ability of KAMD to perform gait analysis. Employment of KAMDs on both legs eliminating the time synchronization complexity makes the proposed FBG-based KAMD an efficient means to evaluate the knee angle from both legs simultaneously.
DFT Calculations of Structure and Optical Properties in Wide Band-Gap Semiconductor Clusters for Dye-Sensitized Solar Cells

We report results of a computational study of TiO2 clusters to understand their structure and optical properties as well as the binding and charge transfer from organic dyes to such clusters. We perform density functional theory calculations of several coumarin-based and oligomethine cyanine-based dyes as well as complex systems consisting of the dye bound to a TiO2 cluster. We provide the electronic structure of the dyes alone and adsorbed to the cluster, and discuss the matching with the solar spectrum. We display the energy level diagrams and the electron density of the key molecular orbitals and analyze the electron transfer from the dye to the oxide.
Measuring Daily Disposable Contact Lenses against Nonwearer Benchmarks.

SIGNIFICANCE Since becoming a popular form of refractive error correction, contact lenses have aspired to replicate the nonwearer experience. This study assessed how well currently available daily disposable soft lenses have achieved that goal, using a graphical representation to show individual lens behavior relative to benchmarks. PURPOSE The purpose of this study was to assess comfort, vision, and adverse events during daily disposable contact lens wear, relative to emmetropes and spectacle wearers. METHOD Three-month clinical studies, where participants either wore one of five daily disposable contact lenses (n = 201), were full-time spectacle wearers with no history of contact lens wear (n = 34), or emmetropic non-contact lens wearers (n = 40). Vision quality and comfort were assessed at the beginning and end of the day (1 to 10). Corneal infiltrative events were recorded. Between-group comparisons were made using a linear mixed model and literature estimates of clinical significance. RESULTS Initial comfort among emmetropes (mean ± 95% confidence interval, 8.0 ± 0.5) was not significantly different from any of the lens types (range, 7.2 ± 0.4 to 8.0 ± 0.4, all P > .06) or spectacle wearers (7.3 ± 0.5, P = .45). Comfort deteriorated during the day in all groups (P < .05). End-of-day comfort for emmetropes (7.3 ± 0.6) was significantly better, only than lenses B (5.7 ± 0.6, P < .001) and D (6.2 ± 0.5, P = .01). Vision quality for emmetropes (8.6 ± 0.5) was better than spectacle wearers (7.8 ± 0.5, P = .04) and lenses A (7.6 ± 0.4, P = .003) and B (7.5 ± 0.4, P < .001). Corneal infiltrative events occurred in 0% of emmetropes and 2.9% of spectacle wearers and ranged from 2.4 to 7.5% in lens wearers. CONCLUSIONS Under the conditions of this study, comfort and vision with some contemporary daily disposable contact lenses were indistinguishable from nonwearing emmetropes. Although the contact lens-wearing groups had rates of corneal infiltrative events that were not statistically different from the nonwearers, the study had insufficient power to permit robust conclusions in this respect.
Emotion Regulation and the Experience of Future Negative Mood: The Importance of Assessing Social Support

Emotion regulation refers to the use of various strategies, such as cognitive reappraisal and expressive suppression, to help manage our negative experiences, emotions, and thoughts. Although such emotion regulation often occurs within broader social dynamics and interactions, little is known about how social contexts interact with specific regulation strategies to shape the experience of negative emotions. Using data from 544 young adult university students, we provide initial evidence that habitual use of cognitive reappraisal is associated with lower future experience of depression and anxiety primarily through higher perceived social support (PSS). In contrast, expressive suppression is associated with higher future depression and anxiety primarily through lower PSS. These patterns are consistent with the importance of interpersonal influences on emotion regulation and suggest that assessment of social support can help elucidate the mechanisms of successfully regulating negative mood.
The correlation between body mass index and prostatic-related parameters in men 40 years or older in Zhengzhou

Abstract Purpose To understand the relationship between body mass index (BMI), age, prostate volume (PV), prostate-specific antigen (PSA), International Prostate Symptom Score (IPSS) and quality of life (QoL) in Zhengzhou. Materials and methods In the cross-sectional study, men living in Zhengzhou were invited to participate in this study. Men who were 40 years or older were subjected to the IPSS and related examination. A total of 1360 participants were included. Body mass index < 18.5 kg/m2 was determined as underweight, 18.5–24.99 kg/m2 normal, 25–29.99 kg/m2 overweight, and ≥30 kg/m2 obese. Results The mean BMI was 24.92 ± 3.37 kg/m2. The mean PSA was 1.06 ± 0.85 ng/mL. The mean PV was 20.10 ± 9.96 mL. The mean age was 62.72 ± 11.03 years. The mean IPSS was 5.87 ± 3.48 scores. The mean QoL was 2.33 ± 1.28 scores. PSA showed a significant tendency to decrease with increasing BMI (r = −0.061, p = 0.018, p trend = 0.037). The same with age (r = –0.109, p < .001; p trend = .045). But the result suggested that both IPSS and QoL were positively correlated with BMI (r = 0.120, p < .001, p trend < .001; r = 0.083, p = .001, p trend = .021, respectively). PV increased with increasing BMI (r = 0.110, p < .001, p trend = 0.045 ). Conclusions Age, PSA decreased with increasing BMI. But larger PV, IPSS, and QoL were associated with higher BMI.
Effectiveness of Trauma-Focused Psychological Therapies for Treating Post-traumatic Stress Disorder Symptoms in Women Following Childbirth: A Systematic Review and Meta-Analysis

Background: Approximately 3% of women in community samples develop posttraumatic stress disorder (PTSD) after childbirth. Higher prevalence rates are reported for high risk samples. Postpartum PTSD can adversely affect women's wellbeing, mother-infant relationships and child development. This study aims to examine the effectiveness of trauma-focused psychological interventions (TFPT), for postnatal women. Methods: We conducted a systematic review and meta-analysis including all clinical trials which reported post-traumatic stress symptoms for both the intervention and control groups or at least two time-points, pre- and post-intervention. We searched four databases: CENTRAL, MEDLINE, PsycINFO, and OpenGrey. Screening of search results, data extraction, and risk of bias assessment were undertaken independently by two reviewers. Results: Eleven studies, reported in 12 papers, involving 2,677 postnatal women were included. All were RCTs, bar one case series. Interventions varied in modality, duration and intensity, and included exposure therapy, trauma-focused cognitive behavioral therapy, eye movement desensitization and reprocessing and other psychological approaches. Participants had experienced uncomplicated births, emergency cesarean sections and/or preterm births. Results suggest that TFPT are effective for reducing PTSD symptoms in the short term (up to 3 months postpartum [4 RCTs, n = 301, SMD = −0.50, 95% CI = −0.73 to −0.27]), and medium term (i.e., 3–6 months postpartum [2 RCTs, n = 174, SMD = −1.87, 95% CI = −2.60 to −1.13]). However, there is no robust evidence to suggest whether TFPT can also improve women's recovery from clinically significant PTSD symptoms. Conclusion: Further larger studies, distinguishing between low and high risk groups, and with adequate follow-up, are needed to establish which TFPT are most effective and acceptable for treating postnatal PTSD.
Assessing and improving the quality of security methodologies for distributed systems

Security methodologies represent systematic approaches for introducing security attributes into a system throughout the development lifecycle. While isolated attempts have been made to demonstrate the value of particular security methodologies, the “quality” of security methodologies, as such, has never been given due consideration; indeed, it has never been studied as a self‐standing topic. The literature therefore entirely lacks supportive artifacts that can provide a basis for assessing, and hence for improving, a security methodology's quality. In this paper, we fill the aforementioned gap by proposing a comprehensive quality framework and accompanying process, within the context of an existing approach to engineering security methodologies, which can be used for both (bottom‐up) quality assessment and (top‐down) quality improvement. The main framework elements can be extended and customized to allow an essentially arbitrary range of methodology features to be considered, thus forming a basis for flexible, fine‐grained quality control. We demonstrate the bottom‐up application of the latter framework and process on three real‐life security methodologies for distributed systems, taken as case studies. Based on the assessment results, we subsequently show in detail (for one) and briefly discuss (for the remaining set) how the case study methodologies can be re‐engineered to improve their quality.
Musculoskeletal manifestations of alkaptonuria: A case report and literature review

Alkaptonuria (AKU) is a rare autosomal recessive disorder that results from the deficient activity of homogentisate 1,2-dioxygenase and leads to increased levels of homogentisic acid (HGA) and its oxidized product benzoquinone acetic acid (BQA). Both HGA and BQA form polymerized deposits that lead to a bluish-black discoloration of the cartilage as well as degeneration, inflammation, and calcification of the tendons, ligaments, intervertebral discs, and large joints and increased bone resorption. A brittle and fragmented cartilage forms and leads to aberrant loading of the subchondral bone. These fragments then adhere to the synovial membrane and cause fibrosis or chondromatosis, leading to ochronotic arthropathy. Ochronotic tendinopathy most commonly affects the patellar or Achilles tendon and can lead to enthesopathy or spontaneous tendon ruptures. Ochronotic pigments deposited in the bone impair the bone mineralization process and lead to osteopenia or osteoporosis. Here, we report a case of a patient with several musculoskeletal manifestations of AKU and reviewed the literature to summarize the pathophysiology, clinical characteristics, and radiologic findings of the rheumatic features of AKU. Though medical treatment options are limited, early identification of AKU can facilitate prompt surgical intervention.
Generalized Bayesian D criterion for single‐stratum and multistratum designs

The Bayesian D criterion modifies the D‐optimality approach to reduce dependence of the selected design on an assumed model. This criterion has been applied to select various single‐stratum designs for completely randomized experiments when the number of effects is greater than the sample size. In many industrial experiments, complete randomization is sometimes expensive or infeasible, and hence, designs used for the experiments often have multistratum structures. However, the original Bayesian D criterion was developed under the framework of single‐stratum structures and cannot be applied to select multistratum designs. In this paper, we study how to extend the Bayesian approach for more complicated experiments and develop the generalized Bayesian D criterion, which generalizes the original Bayesian D criterion and can be applied to select single‐stratum and multistratum designs for various experiments when the number of effects is greater than the rank of the model matrix.
Universal Testbed for Algorithm Researches and Setting of Relay Protection and Automation in Power Systems with Distributed Generation and Renewable Energy Sources

Currently, distributed generation (DG) and renewable energy sources (RES) objects are widespread in many countries of the world. Wind farms or wind power plants (WPP) and solar power plants (SPP) are the most actively developing types of energy sources on the RES basis. As a result, the wind power global capacity was about 487 GW by the end of 2016, solar global capacity − 303 GW. It shows an increase in wind and solar energy by 12,7% and 32,9%, respectively, compared to the previous year [1]. DG integration on the basis of wind turbines and photovoltaic panels into the electric power systems (EPS) changes the generating capacities structure, as well as causes EPS regime and emergency control problems, which in turn forces the use of completely different organization principles for control systems, in particular, for relay protection and automation (RP A). Thus, it is possible to note the main essential integration problems of DG and RES objects into EPS:
Characterization and Electrical Modeling Including Trapping Effects of AIN/GaN HEMT 4×50μm on Silicon Substrate

This paper reports the full characterization and modeling of novel AlN/GaN HEMTs on silicon using a short gate length. This device has been optimized for high frequency analog circuits applications. The presented model includes DC and small-signal modeling steps taking into account the trapping effects. It contains a trap model inside the current source which allows to accurately predict gate-lag transient response and low frequency dispersion of the output admittance. The model is validated by comparing the 4 GHz load-pull measurement results with the simulation ones.
Protection Against Invasive Infections in Children Caused by Encapsulated Bacteria

The encapsulated bacteria Streptococcus pneumoniae, Neisseria meningitis, Haemophilus influenzae, and Streptococcus agalactiae (Group B Streptococcus) have been responsible for the majority of severe infections in children for decades, specifically bacteremia and meningitis. Isolates which cause invasive disease are usually surrounded by a polysaccharide capsule, which is a major virulence factor and the key antigen in protective protein-polysaccharide conjugate vaccines. Protection against these bacteria is largely mediated via polysaccharide-specific antibody and complement, although the contribution of these and other components, and the precise mechanisms, vary between species and include opsonophagocytosis and complement-dependent bacteriolysis. Further studies are required to more precisely elucidate mechanisms of protection against non-type b H. influenzae and Group B Streptococcus.
Caveats for information bottleneck in deterministic scenarios

Information bottleneck (IB) is a method for extracting information from one random variable $X$ that is relevant for predicting another random variable $Y$. To do so, IB identifies an intermediate "bottleneck" variable $T$ that has low mutual information $I(X;T)$ and high mutual information $I(Y;T)$. The "IB curve" characterizes the set of bottleneck variables that achieve maximal $I(Y;T)$ for a given $I(X;T)$, and is typically explored by maximizing the "IB Lagrangian", $I(Y;T) - \beta I(X;T)$. In some cases, $Y$ is a deterministic function of $X$, including many classification problems in supervised learning where the output class $Y$ is a deterministic function of the input $X$. We demonstrate three caveats when using IB in any situation where $Y$ is a deterministic function of $X$: (1) the IB curve cannot be recovered by maximizing the IB Lagrangian for different values of $\beta$; (2) there are "uninteresting" trivial solutions at all points of the IB curve; and (3) for multi-layer classifiers that achieve low prediction error, different layers cannot exhibit a strict trade-off between compression and prediction, contrary to a recent proposal. We also show that when $Y$ is a small perturbation away from being a deterministic function of $X$, these three caveats arise in an approximate way. To address problem (1), we propose a functional that, unlike the IB Lagrangian, can recover the IB curve in all cases. We demonstrate the three caveats on the MNIST dataset.
The Impact of Childhood Maltreatment on Age of Onset of Alcohol Use Disorder in Women

It is unclear whether exposure to childhood maltreatment is associated with the age of onset of alcohol use disorder (AUD). A group of socially stable women with AUD seeking treatment (n = 75) were interviewed using the Addiction Severity Index and the Mini International Neuropsychiatric Interview. They also filled out the Childhood Trauma Questionnaire-short form. Emotional abuse, sexual abuse and multiple childhood traumas were found to be associated with earlier onset of AUD. Multivariable linear regression analysis showed that independent predictors for an earlier onset of AUD were exposure to emotional abuse (beta = –7.44, SE = 2.83, adjusted p = 0.010) and mother’s alcohol/substance problems (beta = –7.87, SE = 3.45, adjusted p = 0.026). These variables explained 18.9% of the variance of age of onset of AUD. These findings highlight a need for increased clinical attention to AUD subgroups who have experienced childhood maltreatment, especially emotional abuse, as well as a need for including support in the patient’s own parental role in the treatment.
Identifying Rules for Electroencephalograph (EEG) Emotion Recognition and Classification

In order to identify rules of emotion classification in EEG-based emotion recognition, this paper utilizes rule-based classifier and decision tree algorithm to construct EEG-based emotion classification models for four target emotions, namely happy, sad, angry, and relaxed. Considering different bands of frequency in EEG signals, the band pass IIR filter with Chebyshev type II window was applied to separate the EEG signal into gamma, beta, alpha, and theta bands. Time and frequency domain features extraction methods are presented to seek the relevant features within the EEG signals related to emotional states. For emotion classification, we compared three methods: rules algorithm (RIPPER), decision tree algorithm (J4.8), and SVM. To evaluate our proposed method, a real EEG dataset from DEAP database were used. For the recorded 5-channel EEG signals, the result shows that the RIPPER algorithm yields best performance accuracy of 92.01% in binary classification of sad versus relaxed emotional state. In regards with emotion classification accuracy, rule-based classification model performed better compared to decision tree algorithm. A promising result was obtained from features extracted from beta and gamma bands of EEG signals. From the experiment, the rules classifier model generated 10 rules of emotion classification, while the validation of the rules achieved an average accuracy of 81.64% for relaxed emotion class.