Miracle-dz/UniFAR-FTUs huggingface dataset:
Exercise referral for drug users aged 40 and over: results of a pilot study in the UK

Objectives To test whether older drug users (aged 40 and over) could be recruited to an exercise referral (ER) scheme, to evaluate the feasibility and acceptability and measure the impact of participation on health. Design Observational pilot. Setting Liverpool, UK. Participants (1) 12 men and 5 women recruited to ER. (2) 7 specialist gym instructors. Outcome measures Logistic feasibility and acceptability of ER and associated research, rate of recruitment, level of participation over 8 weeks and changes in health. Results 22 gym inductions were arranged (recruitment time: 5 weeks), 17 inductions were completed and 14 participants began exercising. Attendance at the gym fluctuated with people missing weeks then re-engaging; in week 8, seven participants were in contact with the project and five of these attended the gym. Illness and caring responsibilities affected participation. Participants and gym instructors found the intervention and associated research processes acceptable. In general, participants enjoyed exercising and felt fitter, but would have welcomed more support and the offer of a wider range of activities. Non-significant reductions in blood pressure and heart rate and improvements in metabolic equivalents (METs; a measure of fitness) and general well-being were observed for eight participants who completed baseline and follow-up assessments. The number of weeks of gym attendance was significantly associated with a positive change in METs. Conclusions It is feasible to recruit older drug users into a gym-based ER scheme, but multiple health and social challenges affect their ability to participate regularly. The observed changes in health measures, particularly the association between improvements in METs and attendance, suggest further investigation of ER for older drug users is worthwhile. Measures to improve the intervention and its evaluation include: better screening, refined inclusion/exclusion criteria, broader monitoring of physical activity levels, closer tailored support, more flexible exercise options and the use of incentives.
Probabilistic inference for solving (PO) MDPs

The development of probabilistic inference techniques has made considerable progress in recent years, in particular with respect to exploiting the structure (e.g., factored, hierarchical or relational) of discrete and continuous problem domains. We show that these techniques can be used also for solving Markov Decision Processes (MDPs) or partial observable MDPs (POMDPs) when formulated in terms of a structured dynamic Bayesian network (DBN). The approach is based on an equivalence between maximization of the expected future return in the time-unlimited MDP and likelihood maximization in a related mixture of finite-time MDPs. This allows us to use expectation maximization (EM) for computing optimal policies, using arbitrary inference techniques in the E-step. Unlike previous approaches we can show that this actually optimizes the discounted expected future return for arbitrary reward functions and without assuming an ad hoc finite total time. We first develop the approach for standard MDPs and demonstrate it using exact inference on a discrete maze and Gaussian belief state propagation in non-linear stochastic optimal control problems. Then we present an extension for solving POMDPs. We consider an agent model that includes an internal memory variable used for gating reactive behaviors. Using exact inference on the respective DBN, the EM-algorithm solves complex maze problems by learning appropriate internal memory representations.
Using Inverse Probability-Weighted Estimators in Comparative Effectiveness Analyses With Observational Databases

Inverse probability-weighted estimation is a powerful tool for use with observational data. In this article, we describe how this propensity score-based method can be used to compare the effectiveness of 2 or more treatments. First, we discuss the inherent problems in using observational data to assess comparative effectiveness. Next, we provide a conceptual explanation of inverse probability-weighted estimation and point readers to sources that address the method in more formal, technical terms. Finally, we offer detailed guidance about how to implement the estimators in comparative effectiveness analyses.
FlexDrive: A Framework to Explore NVMe Storage Solutions

NVMe is emerging as the standard protocol for communicating with high performance storage devices over the PCIe interface, independent of the underlying storage technology. Being a relatively new standard, there is a distinct lack of tools that can help in evaluating contemporary and future storage solutions built on NVMe. In this paper, we provide the design and analysis of FlexDrive, a software defined, comprehensive, fully customizable emulation framework that builds on the NVMe protocol. FlexDrive provides a number of knobs that allow system architects and capacity planning engineers to quickly evaluate performance implications of a wide variety of storage solutions, including a number of "what-if" scenarios. We validate FlexDrive against commercially available NVMe SSDs and demonstrate near-perfect correlation. Furthermore, using multiple case studies we show that FlexDrive is able to emulate the performance of a number of existing SSDs as well as extrapolate to future storage devices.
Psychosocial determinants of recovery in depression

There is a growing body of literature on residual symptoms after apparently successful treatment The strong prognostic value of subthreshold symptomatology upon remission and the relationship between residual and prodromal symptomatology (the rollback phenomenon) have been outlined. Most residual symptoms also occur in the prodromal phase of depression and may progress to become prodromes of relapse. These findings entail important implications. It is necessary to closely monitor the patient throughout the different phases of illness and to assess the quality and extent of residual symptoms. A more stringent definition of recovery, which is not limited to symptomatic assessment, but includes psychological well-being, seems to be necessary. Wen therapeutic strategies for improving the level of remission, such as treatment of residual symptoms that progress to become prodromes of relapse and/or increasing psychological well-being, appear to yield more lasting benefits. The sequential model may provide room for innovative treatment approaches, including the use of drugs for specifically addressing residual symptoms. As occurs in other medical disorders (such as diabetes and hypertension), the active role of the patient in achieving recovery (self-therapy homework) should be pursued.
Geometric Gait Design for a Starfish-Inspired Robot With Curvature-Controlled Soft Actuators

This paper presents a geometric gait design and optimization framework for an idealized model of a planar starfish-inspired robot with curvature-controlled soft actuator arms. We describe the range of motion for each arm under the assumption of constant curvature along the length. Two modes of attachment of the ends of the arms to the ground are considered: fixed in position and orientation, and fixed in position but free to rotate. For each mode, we derive mathematical expressions for the local connection relating controlled shape changes to the displacement of the robot’s center. For the rotating case, we additionally model the individual arms as ideal elastica beams and design gaits based on expected buckling behavior for a special case of symmetric (mirrored) curvature inputs via numerical simulations.
Quality of life, disability, and body mass index are related in obese patients

The aim of this study is to analyze the relationship between health-related quality of life (QoL), disability, and degree of obesity. Adult obese patients (BMI>30) were consecutively enrolled in this cross-sectional observational study. The WHO Disability Assessment Schedule (WHO-DAS II) and the short version of the impact of weight on QoL (IWQoL-Lite) were administered. Spearman's rank correlation analysis was performed. A P value of less than 0.01 was used to set the statistical significance. A total of 117 patients (mean age: 47.4 years, mean BMI: 43.7) were enrolled. Correlations between WHO-DAS II and IWQoL-Lite were between 0.21 and 0.78. BMI between 0.19 and 0.26 correlated with WHO-DAS II and BMI between 0.23 and 0.49 correlated with IWQoL-Lite. In conclusion, low/moderate correlations between BMI index, disability, and health-related QoL measures, and a low association between the two outcome measures are reported, supporting the idea that they underline different and not transposable dimensions.
A comparative study on extractive speech summarization of broadcast news and parliamentary meeting speech

We carry out a comprehensive study of acous-tic/prosodic, linguistic and structural features for speech summarization, contrasting two genres of speech, namely Mandarin Broadcast News and Cantonese Parliamentary Speech. We find that structural features are superior to acoustic and lexical features when summarizing broadcast news because of the fact that in the same Mandarin broadcast program, the distribution and flow of summary utterances are relatively consistent. We use different machine learning algorithms to construct the binary-class summarizers to select the best features for extractive summarization, and obtain state-of-the-art performances: ROUGE-L F-measure of 0.682 for Mandarin Broadcast News, and 0.737 for Cantonese Parliamentary Meeting Speech. In the case of Parliamentary Meeting Speech summarization, we show that our summarizer performed surprisingly well ROUGE-L F-measure of 0.729 by using ASR transcription despite the character error rate of 27%. We also discover that the different choices of algorithms almost do not affect the consistency of our findings.
Transcriptional variations in biomarkers of Mytilus galloprovincialis sampled from Central Adriatic coastal waters (Marche region, Italy)

Abstract Objective: this work evaluates the expression of several biomarker genes (i.e. CAT, HSPs, MT10, p53, GSTpi, ER1/2) in Mytilus galloprovincialis native specimens to identify pollution related transcriptional changes. Methods: gene expression levels were analysed in the gills of mussels from five sites along a coastal area of the central Adriatic Sea, using qPCR. Results: we observed higher expression levels of biomarker genes in mussels from the local harbour or river mouths than in mussels from the reference site and offshore platform. Conclusions: the variations in gene expression observed indicated high sensitivity to pollutants, and showed differences among the sampling sites.
Image-based clothes transfer

Virtual dressing rooms for the fashion industry and digital entertainment applications aim at creating an image or a video of a user in which he or she wears different garments than in the real world. Such images can be displayed, for example, in a magic mirror shopping application or in games and movies. Current solutions involve the error-prone task of body pose tracking. We suggest an approach that allows users who are captured by a set of cameras to be virtually dressed with previously recorded garments in 3D. By using image-based algorithms, we can bypass critical components of other systems, especially tracking based on skeleton models. We rather transfer the appearance of a garment from one user to another by image processing and image-based rendering. Using images of real garments allows for photo-realistic rendering quality with high performance.
Tohoku at SemEval-2016 Task 6: Feature-based Model versus Convolutional Neural Network for Stance Detection

In this paper, we compare feature-based and Neural Network-based approaches on the supervised stance classiﬁcation task for tweets in SemEval-2016 Task 6 Subtask A (Moham-mad et al., 2016). In the feature-based approach, we use external resources such as lexicons and crawled texts. The Neural Network based approach employs Convolutional Neural Network (CNN). Our results show that the feature-based model outperformed the CNN model on the test data although the CNN model was better than the feature-based model in the cross validation on the training data.
Teaching Medical Students an Integrative Approach to Chronic Musculoskeletal Pain

Painful conditions of the musculoskeletal system are some of the most important, and frustrating, chronic problems encountered in a clinical practice. One in two adults reported a chronic musculoskeletal condition, according to a recent national survey [1], twice the rate of reported cardiovascular or respiratory conditions. Yet despite the prevalence of chronic musculoskeletal pain, physicians often feel less confident in their treatment planning for pain patients than they do for others in their practice. Conventional medical approaches to chronic musculoskeletal pain, such as non steroidal anti inflammatory medications and muscle relaxants may be in effective for some patients. In addition, these patients consume more than their share of scarce healthcare resources. Patients with clinically diagnosed fibromyalgia were found to incorrect twice as many direct healthcare costs as matched controls [2].
Stem cell tracking using iron oxide nanoparticles

Superparamagnetic iron oxide nanoparticles (SPIONs) are an exciting advancement in the field of nanotechnology. They expand the possibilities of noninvasive analysis and have many useful properties, making them potential candidates for numerous novel applications. Notably, they have been shown that they can be tracked by magnetic resonance imaging (MRI) and are capable of conjugation with various cell types, including stem cells. In-depth research has been undertaken to establish these benefits, so that a deeper level of understanding of stem cell migratory pathways and differentiation, tumor migration, and improved drug delivery can be achieved. Stem cells have the ability to treat and cure many debilitating diseases with limited side effects, but a main problem that arises is in the noninvasive tracking and analysis of these stem cells. Recently, researchers have acknowledged the use of SPIONs for this purpose and have set out to establish suitable protocols for coating and attachment, so as to bring MRI tracking of SPION-labeled stem cells into common practice. This review paper explains the manner in which SPIONs are produced, conjugated, and tracked using MRI, as well as a discussion on their limitations. A concise summary of recently researched magnetic particle coatings is provided, and the effects of SPIONs on stem cells are evaluated, while animal and human studies investigating the role of SPIONs in stem cell tracking will be explored.
Genepleio Software for Effective Estimation of Gene Pleiotropy from Protein Sequences

Though pleiotropy, which refers to the phenomenon of a gene affecting multiple traits, has long played a central role in genetics, development, and evolution, estimation of the number of pleiotropy components remains a hard mission to accomplish. In this paper, we report a newly developed software package, Genepleio, to estimate the effective gene pleiotropy from phylogenetic analysis of protein sequences. Since this estimate can be interpreted as the minimum pleiotropy of a gene, it is used to play a role of reference for many empirical pleiotropy measures. This work would facilitate our understanding of how gene pleiotropy affects the pattern of genotype-phenotype map and the consequence of organismal evolution.
A Stochastic Singular Vector Based MIMO Channel Model for MAC Layer Tracking

A novel stochastic technique is presented to directly model singular vectors and singular values of a multiple input multiple output channel. Thus the component smodeled directly in the eigen domain can be adapted to exhibit realistic physical domain behavior when assembled. The model exploites natural paths of eigenmodes, such that a simple Doppler filter generator process can be used. Furthermore it is possible to directly manipulate the singular vector dynamics in a way that an unrealistic "stress channel" can be modeled in the eigen domain. This is particularly useful for testing the eigenmode channel tracking ability internal to a communication device such as a modem, where impairments in tracking will cause interference between eigenmodes. The model can also facilitate mode tracking testing as it directly produces tracked ungtangled eigenmodes, providing the narrowest possible singular vector Doppler spectra and consequently lowest required update rates of each eigenmode. The singular vector based model targets testing of the eigen domain functionality of MIMO modems/devices, an apparatus focus, without the need for including the decomposition stages.
Asymptotic distribution for the birthday problem with multiple coincidences, via an embedding of the collision process

We study the random variable B(c, n), which counts the number of balls that must be thrown into n equally‐sized bins in order to obtain c collisions. The asymptotic expected value of B(1, n) is the well‐known nπ/2 appearing in the solution to the birthday problem; the limit distribution and asymptotic moments of B(1, n) are also well known. We calculate the distribution and moments of B(c, n) asymptotically as n goes to ∞ and c = O(n). We have two main tools: an embedding of the collision process — realizing the process as a deterministic function of the standard Poisson process — and a central limit result by Rényi. © 2015 Wiley Periodicals, Inc. Random Struct. Alg. , 48, 480–502, 2016
A survey of printable piezoelectric sensors

Availability of solution-processable piezoelectric sensor and electrode materials enable low-cost and high-throughput fabrication of fully printable piezoelectric sensors. Results obtained with piezoelectric polymer (polyvinylidenefluoride, PVDF), cellulose nanoflbril (CNF) and cellulose nanocrystal (CNC) films as sensor materials are presented here. These sensor materials can be processed in solution and used in combination with printed electrodes to obtain full printability of the sensors. A commercial PVDF film and in-house fabricated CNF and CNC film are used as sensor materials. In addition, conducting polymer, graphene and carbon nanotube (CNT) based inks are used as solution-processable electrode materials in the sensors, whereas conventional metallic electrodes are used as reference electrode material. The sensor operation of the fabricated sensors is evaluated through piezoelectric sensitivity measurements. The sensor sensitivity measurements revealed mean sensitivities from 2 pC/N to 42 pC/N in transverse direction, depending on set of the sensor and electrode materials used.
The complexity and accuracy of discrete state models of protein structure.

The prediction of protein structure depends on the quality of the models used. In this paper, we examine the relationship between the complexity and accuracy of representation of various models of protein alpha-carbon backbone structure. First, we develop an efficient algorithm for the near optimal fitting of arbitrary lattice and off-lattice models of polypeptide chains to their true X-ray structures. Using this, we show that the relationship between the complexity of a model, taken as the number of possible conformational states per residue, and the simplest measure of accuracy, the root-mean-square deviation from the X-ray structure, is approximately (Accuracy) varies; is directly proportional to (Complexity)-1/2. This relationship is insensitive to the particularities of individual models, i.e. lattice and off-lattice models of the same complexity tend to have similar average root-mean-square deviations, and this also implies that improvements in model accuracy with increasing complexity are very small. However, other measures of model accuracy, such as the preservation of X-ray residue-residue contacts and the alpha-helix, do distinguish among models. In addition, we show that low complexity models, which take into account the uneven distribution of residue conformations in real proteins, can represent X-ray structures as accurately as more complex models, which do not: a selected 6-state model can represent protein structures almost as accurately (1.7 A root-mean-square) as a 17-state lattice model (1.6 A root-mean-square). Finally, we use a novel optimization procedure to generate eight 4-state models, which fit native proteins to an average of 2.4 A, and preserve 85% of native residue-residue contacts. We discuss the implications of these findings for protein folding and the prediction of protein conformation.
New Insights into the Assembly of Extracellular Microfibrils from the Analysis of the Fibrillin 1 Mutation in the Tight skin Mouse

The Tight skin (Tsk) mutation is a duplication of the mouse fibrillin 1 (Fbn1) gene that results in a larger (418 kD) than normal (350 kD) protein; Tsk/+ mice display increased connective tissue, bone overgrowth, and lung emphysema. Lung emphysema, bone overgrowth, and vascular complications are the distinctive traits of mice with reduced Fbn1 gene expression and of Marfan syndrome (MFS) patients with heterozygous fibrillin 1 mutations. Although Tsk/+ mice produce equal amounts of the 418- and 350-kD proteins, they exhibit a relatively mild phenotype without the vascular complications that are associated with MFS patients and fibrillin 1–deficient mice. We have used genetic crosses, cell culture assays and Tsk-specific antibodies to reconcile this discrepancy and gain new insights into microfibril assembly. Mice compound heterozygous for the Tsk mutation and hypomorphic Fbn1 alleles displayed both Tsk and MFS traits. Analyses of immunoreactive fibrillin 1 microfibrils using Tsk- and species-specific antibodies revealed that the mutant cell cultures elaborate a less abundant and morphologically different meshwork than control cells. Cocultures of Tsk/Tsk fibroblasts and human WISH cells that do not assemble fibrillin 1 microfibrils, demonstrated that Tsk fibrillin 1 copolymerizes with wild-type fibrillin 1. Additionally, copolymerization of Tsk fibrillin 1 with wild-type fibrillin 1 rescues the abnormal morphology of the Tsk/Tsk aggregates. Therefore, the studies suggest that bone and lung abnormalities of Tsk/+ mice are due to copolymerization of mutant and wild-type molecules into functionally deficient microfibrils. However, vascular complications are not present in these animals because the level of functional microfibrils does not drop below the critical threshold. Indirect in vitro evidence suggests that a potential mechanism for the dominant negative effects of incorporating Tsk fibrillin 1 into microfibrils is increased proteolytic susceptibility conferred by the duplicated Tsk region.
PiQASso: Pisa Question Answering System

PiQASso is a Question Answering system based on a combination of modern IR techniques and a series of semantic filters for selecting paragraphs containing a justifiable answer. Semantic filtering is based on several NLP tools, including a dependency-based parser, a POS tagger, a NE tagger and a lexical database. Semantic analysis of questions is performed in order to extract key word used in retrieval queries and to detect the expected answer type. Semantic analysis of retrieved paragraphs includes checking the presence of entities of the expected answer type and extracting logical relations between words. A paragraph is considered to justify an answer if similar relations are present in the question. When no answer passes the filters, the process is repeated applying further levels of query expansions in order to increase recall. We discuss results and limitations of the current implementation.