Miracle-dz/UniFAR-FTUs huggingface dataset:
Searching for active ingredients in rehabilitation: applying the taxonomy of behaviour change techniques to a conversation therapy for aphasia

Abstract Purpose A taxonomy of behaviour change techniques has been developed to help specify the active ingredients of behaviour change interventions. Its potential for rehabilitation research is significant, however, reliable use among allied health professionals has not yet been explored. This article describes the content of a conversation therapy for post-stroke aphasia using the taxonomy and investigates inter-rater reliability among Speech and Language Therapists. Methods and materials Two Speech and Language Therapists undertook the same half day, self-led training programme in the behaviour change technique taxonomy and independently coded all materials in the “Better Conversations with Aphasia” programme. Inter-rater reliability was evaluated using the kappa coefficient and percentage agreement. Reliably agreed techniques were categorised according to the speaker and type of behaviour they targeted. Results Sixteen behaviour change techniques were reliably agreed to be present. Inter-rater reliability was moderate (K = 0.465), and in line with satisfactory percentage agreement (79.8%). More techniques were used to target the adoption of new behaviours (15) than the termination of old ones (3). People with aphasia received fewer behaviour change techniques (10) than their communication partners (16). Conclusions Describing the content of conversation therapy with the taxonomy of behaviour change techniques offers clinically useful insights with potential to enhance both research and practice. The intervention is shown to target different types of behaviour in different ways, and offer different speaker groups different content. Non-psychologist users of the taxonomy may encounter challenges working with unfamiliar concepts and terminology, which may impact on reliable use. IMPLICATIONS FOR REHABILITATION In order to change communicative behaviours within conversation, feedback should focus not only on performance but also on the immediate social and emotional consequences of a behaviour. This study adds to the evidence that unhelpful conversational behaviours can be reduced by providing speakers with information about any unwanted consequences, and then agreeing on a supportive behaviour to use instead. People with aphasia should be offered the same range of behaviour change techniques as their communication partners.
Tetrahedron Probes for Ultrasensitive in Situ Detection of Telomerase and Surface Glycoprotein Activity in Living Cells.

In the present study, a tetrahedron probe with encoded internal reference nanoparticles (NPs) was self-assembled by a complementary nucleic acid aptamer for simultaneous ratiometric detection of telomerase (TE) and epithelial cell-adhesion molecule (EpCAM) in living cells. In the presence of target, the dissociation of gold (Au) NPs, which were modified with corresponding tags, resulted in decreased surface-enhanced Raman scattering (SERS) signals. In addition, the ratio of Raman intensity at 1346 cm-1/1096 cm-1 (TE) and 1614 cm-1/1096 cm-1 (EpCAM) compared with the internal reference were demonstrated to quantify the level of TE and EpCAM, respectively, and can eliminate certain background noise. A good linear relationship was observed between them, and the linear range of TE and EpCAM in Hela cells was 0.7×10-12 IU to 37.5×10-12 IU and 1.24 pg/mL to 75.48 pg/mL with a limit of detection (LOD) of 7.6×10-16 IU and 0.53 pg/mL, respectively, which were consistent with the results of Raman confocal imaging. Meanwhile, the versatility and specificity of the developed probes were confirmed in cell lines. These results provide a reliable and ultrasensitive strategy for the in situ detection of biomarkers and a new method for SERS-based tetrahedrons in the early diagnosis of cancer.
Older Cannabis Users Are Not All Alike: Lifespan Cannabis Use Patterns

Although several studies have examined individual-level correlates of cannabis use in later life, there is scant evidence identifying heterogeneity among older users. Using data from Colorado, this study examines variability in lifespan patterns of cannabis use among individuals aged 60 years and older. Sample respondents reported cannabis use in the past year and frequency of use in four periods of adulthood. Analyses used a multi-way contingency table to identify mutually exclusive subgroups of cannabis users based on lifetime reports of use and linear probability models to identify predictors of group identity. Three subgroups of older cannabis users were identified: new users, stop-out or intermittent users, and consistent users. The three groups varied on current use frequency and method of ingestion, as well as social and health characteristics. Screening for past history of cannabis use may help health care providers identify older adults who need health information and monitoring related to cannabis use.
Poor maternal nutrition during gestation in sheep alters prenatal muscle growth and development in offspring.

Poor maternal nutrition during gestation can have immediate and life-long negative effects on offspring growth and health. In livestock, this leads to reduced product quality and increased costs of production. Based on previous evidence that both restricted- and over-feeding during gestation decrease offspring muscle growth and alter metabolism postnatally, we hypothesized that poor maternal nutrition during gestation would reduce the growth and development of offspring muscle prenatally, reduce the number of myogenic progenitor cells, and result in changes in the global expression of genes involved in prenatal muscle development and function. Ewes were fed a control (100% NRC)-, restricted (60% NRC)-, or over-fed (140% NRC) diet beginning on day 30 of gestation until day 45, 90, and 135 of gestation or until parturition. At each time point fetuses and offspring (referred to as CON, RES, and OVER) were euthanized and longissimus dorsi (LM), semitendinosus (STN), and triceps brachii (TB) were collected at each time point for histological and RNA-Seq analysis. In fetuses and offspring, we did not observe an effect of diet on cross sectional area (CSA), but CSA increased over time (P < 0.05). At day 90, RES and OVER had reduced secondary:primary muscle fiber ratios in LM (P < 0.05), but not in STN and TB. However, in STN and TB percent PAX7 positive cells were decreased compared with CON (P < 0.05). Maternal diet altered LM mRNA expression of 20 genes (7 genes down-regulated in OVER and 2 down-regulated in RES compared with CON; 5 down-regulated in OVER compared with RES; FDR-adj. P < 0.05). A diet by time interaction was not observed for any genes in the RNA-Seq analysis; however, 2,205 genes were differentially expressed over time between day 90 and day 135 and birth (FDR-adj. P < 0.05). Specifically, consistent with increased protein accretion, changes in muscle function and increased metabolic activity during myogenesis, changes in genes involved in cell cycle, metabolic processes, and protein synthesis were observed during fetal myogenesis. In conclusion, poor maternal nutrition during gestation contributes to altered offspring muscle growth during early fetal development which persists throughout the fetal stage. Based on muscle-type specific effects of maternal diet, it is important to evaluate more than one type of muscle to fully elucidate the effects of maternal die ton offspring muscle development.
Dual-peptide-functionalized nanofibrous scaffolds recruit host endothelial progenitor cells for vasculogenesis to repair calvarial defects.

Vasculogenesis (de novo formation of vessels) induced by endothelial progenitor cells (EPCs) is requisite for vascularized bone regeneration. However, there exist few available options for promoting vasculogenesis within artificial bone grafts except for exogenous EPCs transplantation, which suffers from the source of EPCs, safety, cost, and time concerns in clinical applications. This study aimed at endogenous EPCs recruitment for vascularized bone regeneration by using a bioinspired EPC-induced graft. The EPC-induced graft was created by immobilizing two bioactive peptides, WKYMVm and YIGSR, on the surface of poly(ε-caprolactone) (PCL)/poliglecaprone (PGC) nanofibrous scaffolds via a polyglycolic acid (PGA)-binding peptide sequence. Remarkable immobilization efficacy of WKYMVm and YIGSR peptides and their sustained release (over 14 days) from scaffolds were observed. In vivo and in vitro studies showed robust recruitment of EPCs, which subsequently contributed to early vasculogenesis and ultimate bone regeneration. The dual-peptide-functionalized nanofibrous scaffolds proposed in this study provide a promising therapeutic strategy for vasculogenesis in bone defect repair.
Clinical phenotypes and classification algorithm for complex regional pain syndrome

Objective We pursued the hypothesis that complex regional pain syndrome (CRPS) signs observed by neurologic examination display a structure allowing for alignment of patients to particular phenotype clusters. Methods Clinical examination data were obtained from 3 independent samples of 444, 391, and 202 patients with CRPS. The structure among CRPS signs was analyzed in sample 1 and validated with sample 2 using hierarchical clustering. For patients with CRPS in sample 3, an individual phenotype score was submitted to k-means clustering. Pain characteristics, quantitative sensory testing, and psychological data were tested in this sample as descriptors for phenotypes. Results A 2-cluster structure emerged in sample 1 and was replicated in sample 2. Cluster 1 comprised minor injury eliciting CRPS, motor signs, allodynia, and glove/stocking-like sensory deficits, resembling a CRPS phenotype most likely reflecting a CNS pathophysiology (the central phenotype). Cluster 2, which consisted of edema, skin color changes, skin temperature changes, sweating, and trophic changes, probably represents peripheral inflammation, the peripheral phenotype. In sample 3, individual phenotype scores were calculated as the sum of the mean values of signs from each cluster, where signs from cluster 1 were coded with 1 and from cluster 2 with −1. A k-means algorithm separated groups with 78, 36, and 88 members resembling the peripheral, central, and mixed phenotypes, respectively. The central phenotype was characterized by cold hyperalgesia at the affected limb. Conclusions Statistically determined CRPS phenotypes may reflect major pathophysiologic mechanisms of peripheral inflammation and central reorganization.
Exploring the experiences and perspectives of substitute decision-makers involved in decisions about deceased organ donation: a qualitative study protocol

Introduction In Canada, deceased organ donation provides over 80% of transplanted organs. At the time of death, families, friends or others assume responsibility as substitute decision-makers (SDMs) to consent to organ donation. Despite their central role in this process, little is known about what barriers, enablers and beliefs influence decision-making among SDMs. This study aims to explore the experiences and perspectives of SDMs involved in making decisions around the withdrawal of life-sustaining therapies, end-of-life care and deceased organ donation. Methods and analysis SDMs of 60 patients admitted to intensive care units will be enrolled for this study. Ten hospitals across five provinces in Canada in a prospective multicentre qualitative cohort study. We will conduct semistructured telephone interviews in English or French with SDMs between 6 and 8 weeks after the patient’s death. Our sampling frame will stratify SDMs into three groups: SDMs who were not approached for organ donation; SDMs who were approached and consented to donate and SDMs who were approached but did not consent to donate. We will use two complementary theoretical frameworks—the Common-Sense Self-Regulation Model and the Theoretical Domains Framework— to inform our interview guide. Interview data will be analysed using deductive directed content analysis and inductive thematic analysis. Ethics and dissemination This study has been approved by the Centre Hospitalier de l’Université de Montréal Research Ethics Board. The findings from this study will help identify key factors affecting substitute decision-making in deceased organ donation, reasons for non-consent and barriers to achieve congruency between SDM and patient wishes. Ultimately, these data will contribute to the development and evaluation of tools and training for healthcare providers to support SDMs in making decisions about organ donation. Trial registration number NCT03850847.
Impact of seed priming with different UV rays on morphological and physio-biochemical attributes of pea (Pisum sativum L.)

In order to investigate the effect of priming and UV stress on pea (Pisum sativum L. cv. Dorian), a pot experiment was conducted as factorial based on completely randomized design with 22 treatments (11 type of seed priming and 2 UV stress conditions) and four replications at Razi University during 2014. The results showed that the impact of seed pretreatment was significant on all traits studied. Also, effect of UV stress was significant on relative water content (RWC), maximum quantum yield of PSII, total chlorophyll (Chl total) content and hydrogen peroxide concentration (H2O2). Interaction between seed priming and UV stress was also significant (p≤ 0.01) for RWC, Chl total content and H2O2 concentration. Generally, the results indicated that UV stress has harmful effect on the pea plants. On the other hand, hydro-priming (HP) had a better effect on the morphological characteristics (stem length and fresh weight) and RWC, especially, under non-UV stress condition. But, HP for 12 h + UV-AB for 2 h and also HP for 11 h + UV-AB for 3 h showed the lowest Chl total content, maximum quantum yield of PSII, stem length and fresh weight of plant and also had the highest concentration of H2O2. Therefore, these two pre-treatments have a negative impact on the pea plant and their use is not recommended for the pre-treatment of seeds in pea.
From DANTE to Dictionary: The New English-Irish Dictionary

Most major bilingual dictionary projects tend to largely involve adapting an existing bilingual dictionary, by adopting or amending the existing source language material as required and then supplying the necessary target language material. This paper describes the innovative approach followed in the production of the New English-Irish Dictionary (NEID) project. The online version of NEID was launched in 2013 (www. focloir.ie) and the project is to be completed when a printed version is produced in 2016. The English language content of NEID is based on the Database of ANalysed Texts of English (the DANTE database), a ground-breaking corpus-based lexical database developed specifically for the project. Attention is drawn to how the DANTE entry frameworks evolved through the various translation and editing processes to the final entries now available in the online. The paper also discusses the development of the Irish-language material and details some of the challenges, practical and editorial, encountered in the course of the production of the dictionary, and the working solutions that were developed.
S2VG: SOFT STOCHASTIC VALUE GRADIENT

Model-based reinforcement learning (MBRL) has shown its advantages in sampleefficiency over model-free reinforcement learning (MFRL). Despite the impressive results it achieves, it still faces a trade-off between the ease of data generation and model bias. In this paper, we propose a simple and elegant model-based reinforcement learning algorithm called soft stochastic value gradient method (S2VG). S2VG combines the merits of the maximum-entropy reinforcement learning and MBRL, and exploits both real and imaginary data. In particular, we embed the model in the policy training and learn Q and V functions from the real (or imaginary) data set. Such embedding enables us to compute an analytic policy gradient through the back-propagation rather than the likelihood-ratio estimation, which can reduce the variance of the gradient estimation. We name our algorithm Soft Stochastic Value Gradient method to indicate its connection with the well-known stochastic value gradient method in (Heess et al., 2015).
CRAFTING DATA-FREE UNIVERSAL ADVERSARIES

We introduce a method to create Universal Adversarial Perturbations (UAP) for a given CNN in a data-free manner. Data-free approaches suite scenarios where the original training data is unavailable for crafting adversaries. We show that the adversary generation with full training data can be approximated to a formulation without data. This is realized through a sequential optimization of the adversarial perturbation with the proposed dilate loss. Dilate loss basically maximizes the Euclidean norm of the output before nonlinearity at any layer. By doing so, the perturbation constrains the ReLU activation function at every layer to act roughly linear for data points and thus eliminate the dependency on data for crafting UAPs. Extensive experiments demonstrate that our method not only has theoretical support, but achieves higher fooling rate than the existing data-free work. Furthermore, we evidence improvement in limited data cases as well.
QGAN: QUANTIZE GENERATIVE ADVERSARIAL NET-

The intensive computation and memory requirements of generative adversarial neural networks (GANs) hinder its real-world deployment on edge devices such as smartphones. Despite the success in model reduction of convolutional neural networks (CNNs), neural network quantization methods have not yet been studied on GANs, which are mainly faced with the issues of both the effectiveness of quantization algorithms and the instability of training GAN models. In this paper, we start with an extensive study on applying existing successful CNN quantization methods to quantize GAN models to extreme low bits. Our observation reveals that none of them generates samples with reasonable quality because of the underrepresentation of quantized weights in models, and the generator and discriminator networks show different sensitivities upon the quantization precision. Motivated by these observations, we develop a novel quantization method for GANs based on EM algorithms, named as QGAN. We also propose a multi-precision algorithm to help find an appropriate quantization precision of GANs given image qualities requirements. Experiments on CIFAR-10 and CelebA show that QGAN can quantize weights in GANs to even 1-bit or 2-bit representations with results of quality comparable to original models.
Effects of nutritional intake on performance in master athletes during an extreme ultra-trail

The purpose of our study was to monitor a well-trained master athlete who competed in the race, keeping under review his performance outcomes. TransPyrenea (La Grande Traversee des Pyrenees) is an Ultra Trail 13-16-d race, 866 km long, 53200 meters of elevation gain, performed for the first time in 2016, becoming the longest race in the world. At every checkpoint, a member of the team ascertained total macronutrients intake and body composition. A wearable device was used to monitor glycemia during all the race. The athlete completed the race with an average speed of 2.6 km/h, including 26 hours and 30 minutes of sleeping. Multiple regression analysis showed that the increase of the speed (β: 0.5 km/h, 95% CI: 0.07 | 1.02 km/h, p-value: .035 and β: 1.32 km/h, 95% CI: 0.53 | 2.11 km/h, p-value: .004) was related to the increase of one hour of sleep and one kg of weight respectively. This evidence could induce the use of specific nutritional supplements and the analysis of body composition on the management strategies of the race, with eventually the planning of a greater number of hours of sleep to acquire greater speed.
Utilization value of medical Big Data created in operation of medical information system

The purpose of this study is to provide ways to utilize and create valuable medical information utilizing Medical Big Data created by field in hospital information system. The results of this study first creates new medical information of Medical Information system through medical big data analysis and integration of created data of PACS linked with many kinds of testing equipment and medical image equipment along with medical treatment information. Medical information created in this way produces various health information for treatment and prevention of disease and infectious disease. Second, it creates profit statistics information in various ways by analyzing medical big data accumulated through integration of billings and receipt, admission breakdown of patients. Profit statistics information created in this way produces various administration information to be utilized in profit anaysis and operation of medical institution. Likewise, data integration of personal health history, medical information of public institutions, medical information created in hospital information system produces valuable medical health information utilizing medical data.
Enabling Self-Awareness for Knowledge Workers Through Visualization of Instrumentation Data

Computer activity logging tools can provide useful high-level overviews of a user’s computer usage and interaction patterns, but currently available tools usually lack specificity and can deliver only limited insights. Instrumentation tools that can capture and visualize richer activity-related data can especially benefit knowledge workers in exploring their personal context and activity histories while they undertake information analysis tasks. Moreover, providing users access to their personal activity data through engaging and effective visualizations is an incentive for them to participate in data gathering efforts. We are undertaking an effort to instrument computer workstations of knowledge workers to gather digital data to study the process of information analysis. As part of this effort we have developed visualizations to enable our user base to explore their instrumentation data and gain awareness about their personal context. This has allowed them to gain actionable insights can improve their working patterns.
Analysis of risk measures in multiobjective optimization portfolios with cardinality constraint

Portfolio selection has been the subject of extensive studies in order to obtain increased returns, minimizing the investment risk. However, the most appropriate risk measure to be considered is still an open problem. The aim of this work is to study different risk measures in the multiobjective portfolios optimization with cardinality constraint and rebalancing. The in-sample analysis compares the fronts of each algorithm, metric and range of cardinality, and out-of-sample analysis compares the results of each measure of risk with each other and with two benchmarks. The returns of portfolios are compared in terms of assets choice and assignment of weights. Statistical tests are performed to verify if any measure of risk shows some superiority. Results indicate that downside risk measures can reduce the cardinality and the risk of financial drawdown without reducing drawup, once they are able to reduce just the negative historical returns scenarios.