Miracle-dz/UniFAR-FTUs huggingface dataset:
The meaning of exercise and physical activity in community dwelling people with multiple sclerosis

Abstract Purpose: This study explored the meanings community dwelling people with multiple sclerosis ascribe to exercise and physical activity. Method: Using a qualitative approach, 16 face-to-face, semi-structured interviews were conducted. Data were analysed using Framework Analysis and emerging themes developed. Results: Five themes were identified: “A Type of Movement”, “The Impact of Exercise and Physical Activity”, “It Changes”, “Sense of Loss” and “Coping with Multiple Sclerosis”. The findings demonstrated that people with multiple sclerosis held a multidimensional and complex view about exercise and physical activity. Conclusion: The meanings people with multiple sclerosis ascribe to exercise and physical activity extended beyond movement, reflecting how they lived with a variable neurological condition. Personal and contextual factors were dominant influences. Implications for Rehabilitation Health professionals should consider the impact personal and contextual factors have on influencing decisions around exercise and physical activity in community dwelling people with multiple sclerosis. Understanding the multidimensional and complex views people with multiple sclerosis ascribe to exercise and physical activity might help health professionals in their discussions around exercise and physical activity and create opportunities to increase physical activity levels in people with multiple sclerosis. Health professionals should recognise that people with multiple sclerosis not only engage in exercise and physical activity to manage MS symptoms, but also as a way to connect with others and cope with the variability of the condition.
A 4 Element Phased Array Transmitter with Efficiency Enhancement Using Beamforming for High-Bandwidth WLAN Applications

This paper presents a 4-element phased array transmitter with efficiency enhancement using beamforming for high bandwidths WLAN application. The efficiency enhancement is achieved by over-the-air combining technique and a sequential operation of the different chains. The signal peaks and the remaining data are transmitted through different RF chains, each optimized for a specific power, and recombined over the air to form the desired signal. A 5GHz PA with fast 2nsec on/off switching time was designed in 0.18um CMOS process to demonstrate the efficiency boost technique. For the 4-element array configuration, efficiency enhancement of x2.3 was demonstrated for 80MHz MSC9 802.11ac signals with 9dB peak-to-average-ratio and EVM of −32dB.
On deception and deception detection: Content analysis of computer-mediated stated beliefs

Deception in computer-mediated communication is defined as a message knowingly and intentionally transmitted by a sender to foster a false belief or conclusion by the perceiver. Stated beliefs about deception and deceptive messages or incidents are content analyzed in a sample of 324 computer-mediated communications. Relevant stated beliefs are obtained through systematic sampling and querying of the blogosphere based on 80 English words commonly used to describe deceptive incidents. Deception is conceptualized broader than lying and includes a variety of deceptive strategies: falsification, concealment (omitting material facts) and equivocation (dodging or skirting issues). The stated beliefs are argued to be valuable toward the creation of a unified multi-faceted ontology of deception, stratified along several classificatory facets such as (1) contextual domain (e.g., personal relations, politics, finances & insurance), (2) deception content (e.g., events, time, place, abstract notions), (3) message format (e.g., a complaint: they lied to us, a victim story: I was lied to or tricked, or a direct accusation: you're lying), and (4) deception variety, each tied to particular verbal cues (e.g., misinforming, scheming, misrepresenting, or cheating). The paper positions automated deception detection within the field of library and information science (LIS), as a feasible natural language processing (NLP) task. Key findings and important constructs in deception research from interpersonal communication, psychology, criminology, and language technology studies are synthesized into an overview. Deception research is juxtaposed to several benevolent constructs in LIS research: trust, credibility, certainty, and authority.
Database Structures for Accountable Flow-Net Logging

Computer and network accountability is to make every action in computers and networks accountable. In order to achieve accountability, we need to answer the following questions: what did it happen? When did it happen? Who did it? In order to achieve accountability, the first step is to record what exactly happened. Therefore, an accountable logging is needed and implemented in computers and networks. Our previous work proposed a novel accountable logging methodology called Flow -Net. However, how to storage the huge amount of Flow-net logs into databases is not clear. In this paper, we try to answer this question.
BinMatch: A Semantics-Based Hybrid Approach on Binary Code Clone Analysis

Binary code clone analysis is an important technique which has a wide range of applications in software engineering (e.g., plagiarism detection, bug detection). The main challenge of the topic lies in the semantics-equivalent code transformation (e.g., optimization, obfuscation) which would alter representations of binary code tremendously. Another challenge is the trade-off between detection accuracy and coverage. Unfortunately, existing techniques still rely on semantics-less code features which are susceptible to the code transformation. Besides, they adopt merely either a static or a dynamic approach to detect binary code clones, which cannot achieve high accuracy and coverage simultaneously. In this paper, we propose a semantics-based hybrid approach to detect binary clone functions. We execute a template binary function with its test cases, and emulate the execution of every target function for clone comparison with the runtime information migrated from that template function. The semantic signatures are extracted during the execution of the template function and emulation of the target function. Lastly, a similarity score is calculated from their signatures to measure their likeness. We implement the approach in a prototype system designated as BinMatch which analyzes IA-32 binary code on the Linux platform. We evaluate BinMatch with eight real-world projects compiled with different compilation configurations and commonly-used obfuscation methods, totally performing over 100 million pairs of function comparison. The experimental results show that BinMatch is robust to the semantics-equivalent code transformation. Besides, it not only covers all target functions for clone analysis, but also improves the detection accuracy comparing to the state-of-the-art solutions.
Multiplexed CRISPR/Cas9 Targeting of Genes Implicated in Retinal Regeneration and Degeneration

Thousands of genes have been implicated in retinal regeneration, but only a few have been shown to impact the regenerative capacity of Müller glia—an adult retinal stem cell with untapped therapeutic potential. Similarly, among nearly 300 genetic loci associated with human retinal disease, the majority remain untested in animal models. To address the large-scale nature of these problems, we are applying CRISPR/Cas9-based genome modification strategies in zebrafish to target over 300 genes implicated in retinal regeneration or degeneration. Our intent is to enable large-scale reverse genetic screens by applying a multiplexed gene disruption strategy that markedly increases the efficiency of the screening process. To facilitate large-scale phenotyping, we incorporate an automated reporter quantification-based assay to identify cellular degeneration and regeneration-deficient phenotypes in transgenic fish. Multiplexed gene targeting strategies can address mismatches in scale between “big data” bioinformatics and wet lab experimental capacities, a critical shortfall limiting comprehensive functional analyses of factors implicated in ever-expanding multiomics datasets. This report details the progress we have made to date with a multiplexed CRISPR/Cas9-based gene targeting strategy and discusses how the methodologies applied can further our understanding of the genes that predispose to retinal degenerative disease and which control the regenerative capacity of retinal Müller glia cells.
Efficient approach for the automatic detection of haemorrhages in colour retinal images

Advances in the eye care telemedicine system aid the diabetic patients in remote areas to stop the unwanted visit to ophthalmologist, reduces overall cost, time and money. Diabetic retinopathy, which is the primary cause of sight loss, has the most common symptoms like microaneurysms, haemorrhages, cotton-wool spots, exudates and drusen. In this work, an efficient approach for the automatic detection of haemorrhages in colour retinal images is proposed and validated. The colour retinal images captured from the diabetic patients are enhanced by an effective pre-processor. A bag of features based on intensity, colour and texture are extracted. Finally, the features are classified with the help of partial least square classifier. The classifier performance is validated on two publicly available databanks. The developed method obtains an area under receiver operating characteristic curve of 0.98 with an average execution time of 6 s. This application outperforms the existing approaches with high robustness and efficiency.
A novel analytical approach to assess dyskinesia in patients with Parkinson disease

A novel analytical methodology is presented aimed at the objective evaluation of dyskinetic movements which occur in Parkinson’s disease. The methodology is based on the comparison between the harmonic contents of voluntary and non-voluntary movements, highlighting their correlation in terms of frequency and phase mismatches. Interestingly, we demonstrated that there is a time delay between these two kinds of movements. The dyskinesia was measured by means of lowcost and easy-to-use wearable electronics based on inertial sensor units.
Embedding of Communication and Measurement Equipment in Drones

This paper describes some features of communications and measurement equipment installation in drones. The following problems are discussed: power supply causing problems to the communication and measurement equipment and the impact of communication tools on the technical parameters of drone flight. The paper considers the possibility of supporting the main power supply of a drone by means of solar panels.
Data-driven framework for real-time thermospheric density estimation

In this paper, we demonstrate a new data-driven framework for real-time neutral density estimation via model-data fusion in quasi-physical ionosphere-thermosphere models. The framework has two main components: (i) the development of a quasi-physical dynamic reduced order model (ROM) that uses a linear approximation of the underlying dynamics and effect of the drivers, and (ii) dynamic calibration of the ROM through estimation of the ROM coefficients that represent the model parameters. We have previously demonstrated the development of a quasi-physical ROM using simulation output from a physical model and assimilation of non-operational density estimates derived from accelerometer measurements along a single orbit. In this paper, we demonstrate the potential of the framework for use with operational measurements. We use simulated GPS-derived orbit ephemerides with 5 minute resolution as measurements. The framework is a first of its kind, simple yet robust and accurate method with high potential for providing real-time operational updates to the state of the upper atmosphere using quasi-physical models with inherent forecasting/predictive capabilities.
Hole-Induced Threshold Voltage Shift Under Reverse-Bias Stress in E-Mode GaN MIS-FET

Under reverse-bias stress (i.e., OFF-state stress with <inline-formula> <tex-math notation="LaTeX">${V} _{\text {GS}} < {V}_{\text {TH}}$ </tex-math></inline-formula>) with high drain voltage, ultraviolet (UV) illumination and larger negative gate bias are found to accelerate the positive shift in threshold voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{\text {TH}}$ </tex-math></inline-formula>) of enhancement-mode GaN MIS-FETs with fully recessed gate. These results suggest a hole-induced degradation mechanism. In the absence of UV illumination, holes could be generated by impact ionization in the high electric-field region, which is initiated by electrons injected from the source through the buffer layer. With a larger negative gate bias, more holes will flow to the gate side and pass through the silicon nitride (SiN<sub><italic>x</italic></sub>) gate dielectric, as SiN<sub><italic>x</italic></sub> does not present any energy barrier to holes. The enhanced hole transport through the dielectric under large negative gate bias could accelerate new defects generation and therefore result in the larger positive threshold voltage shifts.
Optimization of Center-of-Pressure-Based Indices for Assessing Balance Ability

Balance ability assessment is crucial for screening mobility decline group and introducing early interventions. However, it is a big challenge to identify the population with moderate balance problems. Force platform test provides a tool for acquiring and analyzing the Center-of-Pressure (COP) signal of the human body. In this paper, the envelope curve area (ECA), and trajectory mean velocity (TMV) of COP signal were extracted as the magnitude and responsiveness parameters of COP. The tests on 136 subjects indicate that ECA and TMV offer comprehensive and efficient indices for assessing balance ability and suggest that the most reliable results are achieved under eyes opened condition.
Bayesian negative binomial mixture regression models for the analysis of sequence count and methylation data

In this article, we develop a Bayesian hierarchical mixture regression model for studying the association between a multivariate response, measured as counts on a set of features, and a set of covariates. We have available RNA‐Seq and DNA methylation data measured on breast cancer patients at different stages of the disease. We account for the heterogeneity and over‐dispersion of count data (here, RNA‐Seq data) by considering a mixture of negative binomial distributions and incorporate the covariates (here, methylation data) into the model via a linear modeling construction on the mean components. Our modeling construction includes several innovative characteristics. First, it employs selection techniques that allow the identification of a small subset of features that best discriminate the samples while simultaneously selecting a set of covariates associated to each feature. Second, it incorporates known dependencies into the feature selection process via the use of Markov random field (MRF) priors. On simulated data, we show how incorporating existing information via the prior model can improve the accuracy of feature selection. In the analysis of RNA‐Seq and DNA methylation data on breast cancer, we incorporate knowledge on relationships among genes via a gene‐gene network, which we extract from the KEGG database. Our data analysis identifies genes which are discriminatory of cancer stages and simultaneously selects significant associations between those genes and DNA methylation sites. A biological interpretation of our findings reveals several biomarkers that can help understanding the effect of DNA methylation on gene expression transcription across cancer stages.
Family Physicians Attaching New Patients From Centralized Waiting Lists: A Cross-Sectional Study

Purpose: In response to more than 15% of Canadians not having a family physician, 7 provinces have implemented centralized waiting lists for unattached patients. The aim of this study is to analyze the association between family physicians’ characteristics and their participation in centralized waiting lists. Methods: Cross-sectional observational study using administrative data in 5 local health networks in Quebec, between 2013 and 2015. All physicians who had attached at least 1 patient were included (n = 580). Multivariate linear regressions for the number of patients and proportion of vulnerable patients attached per physician were performed. Results: Physicians with more than 20 years of experience represented more than half of those who had participated in the centralized waiting lists and physicians in traditional primary care models represented more than 40%. Physicians’ number of years of practice, primary care model, local health network, and the number of physicians participating in the centralized waiting lists per clinic influenced physicians’ participation. Physicians with 0 to 4 years of experience and those practicing in network clinics were found to attach more patients. Practicing in a Centre Locaux de Services Communautaires (local community service center) was associated with attaching 19% more vulnerable patients compared with practicing in a Family Medicine Unit (teaching unit). Conclusion: Centralized waiting lists seem to be used by early career physicians to build up their patient panels. However, because of the large number of them participating in the centralized waiting lists, physicians with more experience and those practicing in traditional models of primary care might be of interest for future measures to decrease the number of patients waiting for attachment in centralized waiting lists.
Context-Awareness in Non-Contact, Multi-Modality, Bed-Based Monitoring of Vital Signs

Long term, non-contact monitoring allows for continuous and consistent health measurements. The use of multi-modality systems to monitor vital signals of a given subject, should result in less error and require less processing time. Context-awareness has the potential to facilitate the use of several modalities in one system. This paper examines the viability of context-awareness in a multi-modality system to facilitate system synergy. This is achieved by extracting pulse measurements from both modalities and examining the extracted signals as one set of algorithms is forced to fail. Thermal and visible light video data was collected from one subject as they sat quietly. The visible light video was augmented to present with diminishing light over time. The thermal and augmented visible light video data was then subjected to pre-processing, data segmentation and Adaptive Eulerian Video Magnification before extracting pulse measurements. The data processing methods were successful in identifying and enhancing signals representative of pulse. The visible-light algorithms failed to extract pulse measurements when the light became too dim, while the thermal algorithms continued to extract pulse measurements. These results suggest that context-awareness may improve error and processing time by detecting system failures, and accounting for them. In examining signal accuracy, the thermal and visible light pulse signals generally correlated well with the gold standard, Respiratory Inductance Plethysmography (RIP) data, with some differences in phase. These results suggest that the algorithm can be optimized using techniques such as region tracking. Future work involves system optimization and multi-modality signal fusion.
A Novel Mutation in Brain Tumor Causes Both Neural Over-Proliferation and Neurodegeneration in Adult Drosophila

A screen for neuroprotective genes in Drosophila melanogaster led to the identification of a mutation that causes extreme, progressive loss of adult brain neuropil in conjunction with massive brain overgrowth. We mapped the mutation to the brain tumor (brat) locus, which encodes a tripartite motif-NCL-1, HT2A, and LIN-41 (TRIM-NHL) RNA-binding protein with established roles limiting stem cell proliferation in developing brain and ovary. However, a neuroprotective role for brat in the adult Drosophila brain has not been described previously. The new allele, bratcheesehead (bratchs), carries a mutation in the coiled-coil domain of the TRIM motif, and is temperature-sensitive. We demonstrate that mRNA and protein levels of neural stem cell genes are increased in heads of adult bratchs mutants and that the over-proliferation phenotype initiates prior to adult eclosion. We also report that disruption of an uncharacterized gene coding for a presumptive prolyl-4-hydroxylase strongly enhances the over-proliferation and neurodegeneration phenotypes. Together, our results reveal an unexpected role for brat that could be relevant to human cancer and neurodegenerative diseases.
Timescales of influenza A/H3N2 antibody dynamics

Human immunity influences the evolution and impact of novel influenza strains. Because individuals are infected with multiple influenza strains during their lifetime and each virus can generate a cross-reactive antibody response, it is challenging to quantify the processes that shape observed immune responses, or to reliably detect recent infection from serological samples. Using a Bayesian model of antibody dynamics at multiple timescales, we explain complex cross-reactive antibody landscapes by inferring participants’ histories of infection with serological data from cross-sectional and longitudinal studies of influenza A/H3N2 in southern China and Vietnam. We show an individual’s influenza antibody profile can be explained by a short-lived, broadly cross-reactive response that decays within a year to leave a smaller long-term response acting against a narrower range of strains. We also demonstrate that accounting for dynamic immune responses can provide a more accurate alternative to traditional definitions seroconversion for the estimation of infection attack rates. Our work provides a general model for explaining mechanisms of influenza immunity acting at multiple timescales based on contemporary serological data, and suggests a two-armed immune response to influenza infection consistent with competitive dynamics between B cell populations. This approach to analysing multiple timescales for antigenic responses could also be applied to other multi-strain pathogens such as dengue and related flaviviruses.
Morphology Control Effects of Ternary Blended ICBA Toward Low-Temperature-Processed Thick-Film Organic Solar Cells

We obtain an improvement of the power conversion efficiency of organic solar cell (OSC) from 8.06% to 9.81% by blending indene-C<sub>60</sub> bis-adduct (ICBA) in the poly[(5,6-difluoro-2,1,3-benzothiadiazol-4,7-diyl)-alt-(3,3′′′-di(2-octyl-dodecyl) -2,2′;5′,2′′;5′′,2′′′-quaterthiophen-5, 5′′′-diyl)]: [6,6]-phe-nyl C<sub>71</sub>-butyric acid methyl ester (PffBT4T-2OD: PCBM) active layer. We find the incorporation of ICBA could lead to the PffBT4T-2OD: PCBM solution with less temperature-dependent preaggregation, thus promoting the crystalline and preferable morphology of the active layer. Additionally, we demonstrate the addition of ICBA can increase the charge carrier lifetime, ensuring efficient charge carrier transport and collection with suppressed bimolecular recombination and thus enhanced FF. This paper illustrates a valuable strategy toward low-temperature-processed thick-film OSCs with high performances.