Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of ankle strengthening exercise program on an unstable supporting surface on proprioception and balance in adults with functional ankle instability

The present study was conducted to investigate the effect of ankle strengthening exercise applied on unstable supporting surfaces on the proprioceptive sense and balance in adults with functional ankle instability. As for the study method, 30 adults with functional ankle instability were randomly assigned to an ankle strengthening exercise group and a stretching group on unstable supporting surfaces, and the interventions were implemented for 40 min. Before and after the interventions, a digital dual inclinometer was used to measure the proprioceptive sense of the ankle, the Balancia program was used to measure static balance ability, and the functional reach test was used to measure dynamic balance ability. In the results, both proprioceptive sense and static dynamic balance ability were significantly different between before and after the intervention in the experimental group (P<0.05). When such results are put together, it can be seen that ankle strengthening exercise applied on unstable supporting surfaces may be presented as an effective treatment method for enhancing the proprioceptive sense and balance ability in adults with functional ankle instability.
Integrative Self-Knowledge and Marital Satisfaction

ABSTRACT Married Iranian couples (N = 210) responded to the Integrative Self-Knowledge Scale along with a measure of marital satisfaction, the International Personality Item Pool (IPIP) Big Five, and an index of interpersonal problems. Integrative self-knowledge correlated positively with marital satisfaction, positively with all but the extraversion Big Five traits, and negatively with three indices of interpersonal problems. Integrative self-knowledge also mediated a number of personality relationships with marital satisfaction. Spouse-ratings of personality confirmed the adaptive implications of integrative self-knowledge for marriage. Linkages with questionnaire response styles supported the description of integrative self-knowledge as a measure of both self-insight and self-development. Results confirmed the potential of integrative self-knowledge for studying self-regulatory processes and suggested that the enhancement of self-knowledge may be a useful goal in efforts to strengthen marriages.
TITLE : MALDI-TOF Mass Spectrometry for Pathogen Identification : A Review of Accuracy and Clinical Effectiveness

Canada. Rapid responses are based on a limited literature search and are not comprehensive, systematic review s. The intent is to provide a list of sources of the best evidence on the topic that CADTH could identify using all reasonable efforts w ithin the time allow ed. Rapid responses should be considered along w ith other types of information and health care considerations. The information included in this response is not intended to replace professional medical advice, nor should it be construed as a recommendation for or against the use of a particular health technology. Readers are also cautioned that a lack of good quality evidence does not necessarily mean a lack of effectiveness particularly in the case of new and emerging health technologies, for w hich little information can be found, but w hich may in future prove to be effective. While CADTH has taken care in the preparation of the report to ensure that its contents are accurate, complete and up to date, CADTH does not make any guarantee to that effect. CADTH is not liable for any loss or damages resulting from use of the information in the report.
Stress-Axis Regulation by Vitamin D3 in Multiple Sclerosis

Introduction Multiple sclerosis (MS) has been associated with both a poor vitamin D status and hyperactivity of the hypothalamus–pituitary–adrenal (HPA) axis. Since nuclear receptor ligands may regulate each other, we explored the association of vitamin D3 supplements with circadian cortisol levels in a double-blind and placebo-controlled supplementation study. Methods Female patients with relapsing-remitting MS received vitamin D3 supplements (4,000 IU/day; n = 22) or placebo (n = 19) during 16 weeks. Salivary cortisol levels, repeatedly measured during the day, and serum 25(OH)D levels were assessed before (T0) and after (T1) this treatment period. Results Median 25(OH)D levels at T1 were 139.9 (interquartile range 123.5–161.2) and 74.5 nmol/L (58.6–88.1) in the vitamin D3 and placebo group, respectively (p < 0.001). Comparisons within and between groups showed no differences in area under the curve (AUC) and slope of the cortisol day curve. Although the AUC of the cortisol awakening response (CAR, sampling each 15 min the first hour after awakening) showed a reduction over time in the vitamin D3 group [39.16 nmol/L (27.41–42.07) at T0 to 33.37 nmol/L (26.75–38.08) at T1] compared to the placebo group [33.90 nmol/L (25.92–44.61) at T0 to 35.00 nmol/L (25.46–49.23) at T1; p = 0.044], there was no significant difference in AUC of CAR at T1 corrected for baseline AUC of CAR (p = 0.066). Conclusion Suppression of HPA-axis activity by vitamin D3 supplements in non-depressed MS patients may be best reflected by CAR as primary outcome measure. Further studies should address this interaction and its potential implications for the disease course of MS. Registration This study was registered on ClinicalTrials.gov (NCT02096133) and EudraCT (2014-000728-97).
A comparative analysis on Finnish and Korean high school English textbooks in the perspective of communicative language teaching

Namgung, Wook. 2016. A Comparative Analysis on Finnish and Korean High School Textbooks in the Perspective of Communicative Language Teaching. Master's Thesis in Education. University of Jyväskylä. Department of Education. 111 pages. English textbooks are a key resource for English courses in both Finnish and Korean high schools. The present study aims to compare the similarities and differences of Finnish and Korean high school English textbooks and analyze them from the perspective of Communicative Language Teaching (CLT) on which English textbooks of both countries are theoretically based. Two English textbooks have been selected from each country for this research. One textbook is targeted for 10th grade and the other for 11th grade. The textbooks have been analyzed according to six dimensions: textbook structure, vocabulary, language forms, topics and cultural backgrounds, communicative functions, and activities for language skills. The study conducts a quantitative content analysis for the comparison of English textbooks of both countries and a qualitative theory-driven content analysis through the lens of CLT. The findings show a variety of similarities and differences between Finnish and Korean textbooks in the six dimensions. The results provide some implications for communicative textbooks from the perspective of CLT. The impact of the national testing system on English textbook design was discussed on the basis of the findings. This study suggests the reconsideration of the current vocabulary control for English textbooks in the Korean national curriculum and the substitution for the translation works noticeably visible in Finnish textbooks for CLT. The findings can provide English teachers with pedagogical benefits and the textbooks publishers with insights for textbook design. These findings also give some academic ideas on how diversely CLT can be realized in English textbooks.
Tuning the Molecular Weight Distribution from Atom Transfer Radical Polymerization Using Actor Critic Methods

We devise a novel technique to control the shape of polymer molecular weight distributions (MWDs) in atom transfer radical polymerization (ATRP). This technique makes use of recent advances in both simulation-based, model-free reinforcement learning (RL) and the numerical simulation of ATRP. A simulation of ATRP is built that allows an RL controller to add chemical reagents throughout the course of the reaction. The RL controller incorporates fully-connected and convolutional neural network architectures and bases its decision upon the current status of the ATRP reaction. The initial, untrained, controller leads to ending MWDs with large variability, allowing the RL algorithm to explore a large search space. When trained using an actor-critic algorithm, the RL controller is able to discover and optimize control policies that lead to a variety of target MWDs. The target MWDs include Gaussians of various width, and more diverse shapes such as bimodal distributions. The learned control policies are robust and transfer to similar but not identical ATRP reaction settings, even under the presence of simulated noise. We believe this work is a proof-of-concept for employing modern artificial intelligence techniques in the synthesis of new functional polymer materials.
Incorporating Subword Information into Matrix Factorization Word Embeddings

The positive effect of adding subword information to word embeddings has been demonstrated for predictive models. In this paper we investigate whether similar benefits can also be derived from incorporating subwords into counting models. We evaluate the impact of different types of subwords (n-grams and unsupervised morphemes), with results confirming the importance of subword information in learning representations of rare and out-of-vocabulary words.
Interprofessional population health advocacy: Developing and implementing a panel management curriculum in five Veterans Administration primary care practices

ABSTRACT Health care systems expect primary care clinicians to manage panels of patients and improve population health, yet few have been trained to do so. An interprofessional panel management (PM) curriculum is one possible strategy to address this training gap and supply future primary care practices with clinicians and teams prepared to work together to improve the health of individual patients and populations. This paper describes a Veterans Administration (VA) sponsored multi-site interprofessional PM curriculum development effort. Five VA Centers of Excellence in Primary Care Education collaborated to identify a common set of interprofessionally relevant desired learning outcomes (DLOs) for the PM and to develop assessment instruments for monitoring trainees’ PM learning. Authors cataloged teaching and learning activities across sites. Results from pilot testing were systematically discussed leading to iterative revisions of curricular elements. Authors completed a retrospective self-assessment of curriculum implementation for the academic year 2015–16 using a 5-point scale: contemplation (score = 0), pilot (1), action (2), maintenance (3), and embedded (4). Implementation scores were analyzed using descriptive statistics. DLOs were organized into five categories (individual patients, populations, guidelines/measures, teamwork, and improvement) along with a developmental continuum and mapped to program competencies. Instruction and implementation varied across sites based on resources and priorities. Between 2015 and 2016, 159 trainees (internal medicine residents, nurse practitioner students and residents, pharmacy residents, and psychology post-doctoral fellows) participated in the PM curriculum. Curriculum implementation scores for guidelines/measures and improvement DLOs were similar for all trainees; scores for individual patients, populations, and teamwork DLOs were more advanced for nurse practitioner and physician trainees. In conclusion, collaboratively identified DLOs for PM guided development of assessment instruments and instructional approaches for panel management activities in interprofessional teams. This PM curriculum and associated tools provide resources for educators in other settings.
A Hybrid DV-Hop Algorithm Using RSSI for Localization in Large-Scale Wireless Sensor Networks

With the increasing realization of the Internet-of-Things (IoT) and rapid proliferation of wireless sensor networks (WSN), estimating the location of wireless sensor nodes is emerging as an important issue. Traditional ranging based localization algorithms use triangulation for estimating the physical location of only those wireless nodes that are within one-hop distance from the anchor nodes. Multi-hop localization algorithms, on the other hand, aim at localizing the wireless nodes that can physically be residing at multiple hops away from anchor nodes. These latter algorithms have attracted a growing interest from research community due to the smaller number of required anchor nodes. One such algorithm, known as DV-Hop (Distance Vector Hop), has gained popularity due to its simplicity and lower cost. However, DV-Hop suffers from reduced accuracy due to the fact that it exploits only the network topology (i.e., number of hops to anchors) rather than the distances between pairs of nodes. In this paper, we propose an enhanced DV-Hop localization algorithm that also uses the RSSI values associated with links between one-hop neighbors. Moreover, we exploit already localized nodes by promoting them to become additional anchor nodes. Our simulations have shown that the proposed algorithm significantly outperforms the original DV-Hop localization algorithm and two of its recently published variants, namely RSSI Auxiliary Ranging and the Selective 3-Anchor DV-hop algorithm. More precisely, in some scenarios, the proposed algorithm improves the localization accuracy by almost 95%, 90% and 70% as compared to the basic DV-Hop, Selective 3-Anchor, and RSSI DV-Hop algorithms, respectively.
Demonstrating Doubly-Differential Quadrature Phase Shift Keying in the Optical Domain

We report for the first time the experimental demonstration of doubly differential quadrature phase shift keying (DDQPSK) using optical coherent detection. This method is more robust against high frequency offsets (FO) than conventional single differential quadrature phase shift keying (SDQPSK) with offset compensation. DDQPSK is shown to be able to compensate large FOs (up to the baud rate) and has lower computational requirements than other FO compensation methods. DDQPSK is a simple algorithm to implement in a real-time decoder for optical burst switched network scenarios. Simulation results are also provided, which show good agreement with the experimental results for both SDQPSK and DDQPSK transmissions.
Comparison of antimicrobial activity of selected, commercially available wound dressing materials.

OBJECTIVE The aim of our study was to examine the antimicrobial potential of eight selected, commercially available wound dressings containing different antimicrobial agents: silver, chlorhexidine acetate, povidone-iodine, and manuka honey. METHOD The materials were tested against four reference strains of bacteria: Staphylococcus aureus (PCM 2051), Staphylococcus epidermidis (PCM 2118), Pseudomonas aeruginosa (ATCC 27853), and Escherichia coli (K12), using the disc diffusion-like method and a time-killing assay. RESULTS For both experiments, the highest activity against all four tested strains of bacteria was observed in the case of Mepilex Ag, which contains silver as an antibacterial agent. Incubation for four hours of a 10x10mm2 piece of this material in 10ml cells suspension (concentration: 109-1010CFU/ml) resulted in complete elimination of bacteria of all four strains tested. The same results were obtained for a povidone-iodine containing dressing, Inadine, though its activity was lower in the disc diffusion assay. Silvercel, Aquacel Ag and Melgisorb Ag, which also contain silver, also exhibited a satisfactory level of activity. In the case of Aquacel Ag, 24 hours' incubation resulted in complete elimination of the cells of both Gram-negative bacteria, Escherichia coli and Pseudomonas aeruginosa.The Escherichia coli cells were killed after only four hours' treatment. High effectiveness against Escherichia coli was also demonstrated for Silvercel. However, 24 hours' includation was required for complete elimination of the cells of this bacteria strain. High activity against all tested bacteria, but only in the disc diffusion assay, was observed for Algivon, which contains manuka honey. The Medisorb Silver Pad, containing silver, and Bactigras, which contains chlorhexidine acetate, revealed much lower antimicrobial activity, particularly noticeable in the time-killing assay. In addition, we also tested the anti-staphylococcal activity of a biopolymer material impregnated with lysostaphin. Results revealed that its activity against Staphylococcus aureus was comparable to the most active wound dressings impregnated with silver or inadine. CONCLUSION Some important differences in the antimicrobial potential of investigated materials have been found. The presented results could be of interest to clinicians managing wounds.
A digital PWM controlled KY step-up converter based on frequency domain ΣΔ ADC

This paper introduces a digital PWM control of the KY step-up converter based on frequency domain sigma-delta (ΣΔ) analog-to-digital converter (ADC), in which we deduce the mathematical modeling of the KY step-up converter and the frequency-domain digitization technique based on the first-order non-feedback sigma-delta frequency discriminators (NF-SDFD). Then, the digital control of the KY converter with voltage control oscillator (VCO), NF-SDFD, cascaded integrator comb (CIC) decimator, PID compensator and digital pulse width modulation (DPWM) generator has been successfully built in MATLAB Simulink for verification. This modeling work is useful in the design of a low power digital controlled KY step-up converter with low output voltage ripple and fast transient response.
Nanomaterials processing for flexible electronics

Inorganic nanomaterials such as nanowires (NWs) and nanotubes (NTs) are explored for future flexible electronics applications due to their attributes such as high aspect ratio, enhanced surface-to-volume ratio, prominent mobility and ability to integrate on non-conventional substrates. Device performance of semiconducting NWs are demonstrated to be superior compared to the organic counterparts. Among the synthesis methods, bottom-up vapour-liquid-solid (VLS) growth mechanism playing central role for preparing wide variety of high crystal quality semiconducting NWs. However, the high temperature synthesis process prevents fabrication of NW devices directly over flexible substrates which imply the investigation of efficient transfer techniques such as dry contact printing and electric field assisted assembly. Currently, many efforts are directed to study the integration techniques of NWs from growth substrates to non-conventional receiver substrates and parameters such as transfer-yield, alignment and density. These efforts will help to utlilize NWs as building blocks in future flexible electronic devices and circuits. This work focuses on VLS growth of semiconducting NWs and their transfer-printing over large area substrate to fabricate flexible electronics.
REGGAE: a novel approach for the identification of key transcriptional regulators

Motivation: Transcriptional regulators play a major role in most biological processes. Alterations in their activities are associated with a variety of diseases and in particular with tumor development and progression. Hence, it is important to assess the effects of deregulated regulators on pathological processes. Results: Here, we present REGulator‐Gene Association Enrichment (REGGAE), a novel method for the identification of key transcriptional regulators that have a significant effect on the expression of a given set of genes, e.g. genes that are differentially expressed between two sample groups. REGGAE uses a Kolmogorov‐Smirnov‐like test statistic that implicitly combines associations between regulators and their target genes with an enrichment approach to prioritize the influence of transcriptional regulators. We evaluated our method in two different application scenarios, which demonstrate that REGGAE is well suited for uncovering the influence of transcriptional regulators and is a valuable tool for the elucidation of complex regulatory mechanisms. Availability and implementation: REGGAE is freely available at https://regulatortrail.bioinf. uni‐sb.de. Supplementary information: Supplementary data are available at Bioinformatics online.
Artificially Expanded Genetic Information Systems for New Aptamer Technologies

Directed evolution was first applied to diverse libraries of DNA and RNA molecules a quarter century ago in the hope of gaining technology that would allow the creation of receptors, ligands, and catalysts on demand. Despite isolated successes, the outputs of this technology have been somewhat disappointing, perhaps because the four building blocks of standard DNA and RNA have too little functionality to have versatile binding properties, and offer too little information density to fold unambiguously. This review covers the recent literature that seeks to create an improved platform to support laboratory Darwinism, one based on an artificially expanded genetic information system (AEGIS) that adds independently replicating nucleotide “letters” to the evolving “alphabet”.
Age Estimation Using Expectation of Label Distribution Learning

Age estimation performance has been greatly improved by using convolutional neural network. However, existing methods have an inconsistency between the training objectives and evaluation metric, so they may be suboptimal. In addition, these methods always adopt image classification or face recognition models with a large amount of parameters, which bring expensive computation cost and storage overhead. To alleviate these issues, we design a lightweight network architecture and propose a unified framework which can jointly learn age distribution and regress age. The effectiveness of our approach has been demonstrated on apparent and real age estimation tasks. Our method achieves new state-of-the-art results using the single model with 36$\times$ fewer parameters and 2.6$\times$ reduction in inference time. Moreover, our method can achieve comparable results as the state-of-the-art even though model parameters are further reduced to 0.9M~(3.8MB disk storage). We also analyze that Ranking methods are implicitly learning label distributions.
RaPID-2 : Resources and ProcessIng of Linguistic , Para-Linguistic and Extra-Linguistic Data from People with Various Forms of Cognitive / Psychiatric Impairments

In the past decade the preclinical stage of Alzheimer’s Disease (AD) has become a major research focus. Subjective cognitive decline (SCD) is gaining attention as an important risk factor of AD-pathology in early stages of mild-cognitive impairment (MCI), preclinical AD and depression. In this context, neuropsychological assessments aim at detecting sorts of subtle cognitive decline. Automatic classification may help increasing the expressiveness of such assessments by selecting high-risk subjects in research settings. In this paper, we explore the use of neuropsychological data and interview based data designed to detect AD-related SCD in different clinical samples to classify patients through the implementation of machine learning algorithms. The aim is to explore the classificatory expressiveness of features derived from this data. To this end, we experiment with a sample of 23 memory-clinic patients, 21 depressive patients and 21 healthy-older controls. We use several classifiers, including SVMs and neural networks, to classify these patients using the above mentioned data. We reach a successful classification based on neuropsychological data as well as on cognitive complaint categories. Our analysis indicates that a combination of these data should be preferred for classification, as we achieve an F-score above 90% in this case. We show that automatic classification using machine learning is a powerful approach that can be used to improve neuropsychological assessment.