Miracle-dz/UniFAR-FTUs huggingface dataset:
Occupational disorders and return to work: a randomized controlled study.

OBJECTIVE Goal setting and motivational factors are strongly associated with maintaining a job and return to work after sick leave, but research into the effects of interventions targeting these factors is limited. We conducted a randomized controlled study to examine the vocational effect of intervention focusing on motivation, goal setting and planning for return to work. DESIGN AND METHODS Of 243 patients at risk of long-term sick leave or job dropout, 184 (76%) provided complete baseline information for the study. After randomization to an intervention group (n=92) and a reference group (n=92), occupational physicians examined the participants in accordance with standard guidelines. The intervention group received additional support from a social worker in order to enhance goal setting, motivation and planning for return to work. After 1 year 163 participants (89%) provided data on general health and employment status. The risk of not being gainfully employed was analysed by logistic regression analysis with adjustment for several covariates. RESULTS The intervention did not increase the likelihood of gainful employment after 1 year or reduce the average number of days of sick leave. CONCLUSION A low-cost counselling program addressing motivation, goal setting and planning for return to work did not improve vocational outcomes or reduce sick leave among patients with work-related disorders.
Improving the System-on-a-Chip Performance for Mobile Systems by Using Efficient Bus Interface

Minimizing the communication delay is one of the most important design considerations in System-on-a-Chip (SoC) design for mobile systems. In this paper, we present a bus interface design technique, called Efficient Bus Interface (EBI), to reduce the communication delay between the Intellectual Property (IP) core and the memory connected through AMBA3 AXI bus for mobile systems. Several mobile systems require huge multimedia data in the memory to be transferred to the IP core through bus. The EBI is designed to reduce the memory access time by using double buffering, open row access, and bank interleaving. According to our simulations, the proposed EBI improves the performance of the target system by up to 49%.
A novel scalable video streaming system on P2P networks

Peer-to-peer (P2P) media streaming systems have recently become a major type of application traffic. In these applications, an important issue has been the block scheduling problem, which determines how each peer exchanges the data blocks from others. Scalable streaming in P2P networks has recently been proposed to address the heterogeneity of the network environment. In this paper, we first define a priority function for each block according to the block's significance for video content. The block scheduling problem is then transformed to an optimization problem that maximizes the priority sum of the delivered video blocks. The simulation results show that the proposed algorithm offers excellent performance for P2P streaming service.
Privacy preserving clustering over distributed data

Data mining based on privacy preserving is the combination of information security technology and knowledge discovery technology. A simple and effective privacy-preserving distributed mining method of clustering (PPD-SMD) and (PPD-JD) is proposed to solve the issue about privacy preserving of cluster based on Binary and Nominal Attributes distance. This method brings the secure protocol and crypto-algorithm in the data models of the horizontal distributed. Using semi-trusted third party (STTP), PPD-SMD and PPD-JD do not transfer real data to other sites in clustering procedure. In the end, analysis in security, efficient and complexity are carried on.
The Pragmatic Model and Reciprocal Efficacy.

This model of developmental education for college students uses reading tests, think-alouds, and conferences to promote an exchange of learning between instructor and student. ^■iThe Reading and Writing Center, a component of the Office of Instructional Resources at the University of Florida, serves university students seeking to improve their literacy skills. The reading lab, part of a program staffed by instructors who also teach developmental courses, is available to any student requesting help with reading comprehension, particularly in relation to the variety of standardized tests that students face: the Graduate Record Exam (GRE), Graduate Management Admission Test (GMAT), Medical College Admission Test (MCAT), Law School Admission Test (LSAT), Test of English as a Foreign Language (TOEFL), and especially the College Level Academic Skills Test (CLAST). Until recently, all students at the university had to pass this minimum competency examination by the time they completed roughly 2 years' worth of credits. Students who did not pass the reading subsection of this examination after taking it twice have been required to spend at least 3 class hours per week working in the center on literal and critical read-
A Web of Musical Information

We describe our recent achievements in interlinking several music-related data sources on the Semantic Web. In particular, we describe interlinked datasets dealing with Creative Commons content, editorial, encyclopedic, geographic and statistical data, along with queries they can answer and tools using their data. We describe our web services, providing an on-demand access to content-based features linked with such data sources and information pertaining to their creation (including processing steps, applied algorithms, inputs, parameters or associated developers). We also provide a tool allowing such music analysis services to be set up and scripted in a simple way.
Disturbance-free rapid solution exchange for magnetic tweezers single-molecule studies

Single-molecule manipulation technologies have been extensively applied to studies of the structures and interactions of DNA and proteins. An important aspect of such studies is to obtain the dynamics of interactions; however the initial binding is often difficult to obtain due to large mechanical perturbation during solution introduction. Here, we report a simple disturbance-free rapid solution exchange method for magnetic tweezers single-molecule manipulation experiments, which is achieved by tethering the molecules inside microwells (typical dimensions–diameter (D): 40–50 μm, height (H): 100 μm; H:D∼2:1). Our simulations and experiments show that the flow speed can be reduced by several orders of magnitude near the bottom of the microwells from that in the flow chamber, effectively eliminating the flow disturbance to molecules tethered in the microwells. We demonstrate a wide scope of applications of this method by measuring the force dependent DNA structural transitions in response to solution condition change, and polymerization dynamics of RecA on ssDNA/SSB-coated ssDNA/dsDNA of various tether lengths under constant forces, as well as the dynamics of vinculin binding to α-catenin at a constant force (< 5 pN) applied to the α-catenin protein.
Secreted Frizzled-Related Protein 4 Inhibits Glioma Stem-Like Cells by Reversing Epithelial to Mesenchymal Transition, Inducing Apoptosis and Decreasing Cancer Stem Cell Properties

The Wnt pathway is integrally involved in regulating self-renewal, proliferation, and maintenance of cancer stem cells (CSCs). We explored the effect of the Wnt antagonist, secreted frizzled-related protein 4 (sFRP4), in modulating epithelial to mesenchymal transition (EMT) in CSCs from human glioblastoma cells lines, U87 and U373. sFRP4 chemo-sensitized CSC-enriched cells to the most commonly used anti-glioblastoma drug, temozolomide (TMZ), by the reversal of EMT. Cell movement, colony formation, and invasion in vitro were suppressed by sFRP4+TMZ treatment, which correlated with the switch of expression of markers from mesenchymal (Twist, Snail, N-cadherin) to epithelial (E-cadherin). sFRP4 treatment elicited activation of the Wnt-Ca2 + pathway, which antagonizes the Wnt/ß-catenin pathway. Significantly, the chemo-sensitization effect of sFRP4 was correlated with the reduction in the expression of drug resistance markers ABCG2, ABCC2, and ABCC4. The efficacy of sFRP4+TMZ treatment was demonstrated in vivo using nude mice, which showed minimum tumor engraftment using CSCs pretreated with sFRP4+TMZ. These studies indicate that sFRP4 treatment would help to improve response to commonly used chemotherapeutics in gliomas by modulating EMT via the Wnt/ß-catenin pathway. These findings could be exploited for designing better targeted strategies to improve chemo-response and eventually eliminate glioblastoma CSCs.
The Sustainability of Organic Grain Production on the Canadian Prairies—A Review

Demand for organically produced food products is increasing rapidly in North America, driven by a perception that organic agriculture results in fewer negative environmental impacts and yields greater benefits for human health than conventional systems. Despite the increasing interest in organic grain production on the Canadian Prairies, a number of challenges remain to be addressed to ensure its long-term sustainability. In this review, we summarize Western Canadian research into organic crop production and evaluate its agronomic, environmental, and economic sustainability.
Web Services: Distributed Applications Without Limits

Web services technology is all about distributed computing. There is no fundamentally new basic concept behind this and related technologies. What is really new is the reach of Web services and its ubiquitous support by literally all major vendors. Most likely, heterogeneity will at the end no longer be an obstruction for distributed applications. This will have impact on application architectures, middleware, as well as the way in which people will think about computing and businesses use computing resources. We sketch these impacts as well as some exemplary research work to be done to actually build the outline environment.
Adding a Semantic Layer to Flickr Images Search Service

The growing amount of images on the Web, the diffusion of social media sharing web sites demand effective tools for searching targeted images. In general, the performance of Web image search depends on the quality of images annotation, but often the keywords (or tags) associated to an image are given without relevance information, strictly connected to a subjective feeling of the taggers and far from the objective description of the image. In this paper, we propose a simple approach for social media sharing web sites such as Flickr, Zooomr, etc. to support users to retrieve images semantically correlated to a given tagged image. In this paper, we present an application scenario for Flickr: in general Flickr returns all the images that meets the input tags, without no semantic analysis and evaluation of the effectiveness of the search results. Our approach adds a semantic layer on the Flickr output: processes the tags associated to the retuned images to discover the appropriate semantics of them, by arranging the results in a more user friendly view.
KRYLOV SUBSPACE ITERATION

1.1 What is an iterative method and why is it useful? • All the numerical methods can be divided into two broad categories. 1. Direct methods: A direct method is one that produces the result in a prescribed, finite number of steps. e.g. All versions of Gaussian elimination for solving Ax = b (1) where A is n × n and non-singular, are direct methods. 2. Iterative methods(Indirect methods): Iterative methods are in contrast to direct methods. An iterative method is an attempt to solve a problem, for example an equation or system of equations, by finding successive approximations to the solution starting from an initial guess. • The answer of the question " why is iterative method useful? " is contained in the following questions.
Scaling-up action learning neuro-controllers with GPUs

Neural networks have been used in many different robot motor-control experiments, however, so far the complexity of these neuro-controllers have remained at the similar level. The focus of this paper is to demonstrate that it is possible to scale-up these neuro-robotic controllers with GPUs leading to richer, more realistic and more complex motor control.
Person Authentification by Finger Vein Images: A Review

— Biometric system has been actively emerging in various industries and continuing to roll to provide higher security features for access control system. The proposed system simultaneously acquires the finger surface and subsurface features from finger-vein and finger print images. This paper reviews the acquired finger vein and finger texture images are first subjected to pre-processing steps, which extract the region-of-interest (ROI). The enhanced and normalized ROI images employed to extract features and generate matching score. For this I will develop and investigate two new score-level combinations i.e. Gabour filter, Repeated line Tracking and Neural network comparatively evaluate them more popular score-level fusion approaches to ascertain their effectiveness in the proposed system. MATLAB software will be using for proposed work .
Can quantum communication speed up distributed computation?

The focus of this paper is on quantum distributed computation, where we investigate whether quantum communication can help in speeding up distributed network algorithms. Our main result is that for certain fundamental network problems such as minimum spanning tree, minimum cut, and shortest paths, quantum communication does not help in substantially speeding up distributed algorithms for these problems compared to the classical setting. In order to obtain this result, we extend the technique of Das Sarma et al. [SICOMP 2012] to obtain a uniform approach to prove non-trivial lower bounds for quantum distributed algorithms for several graph optimization (both exact and approximate versions) as well as verification problems, some of which are new even in the classical setting, e.g. tight randomized lower bounds for Hamiltonian cycle and spanning tree verification, answering an open problem of Das Sarma et al., and a lower bound in terms of the weight aspect ratio, matching the upper bounds of Elkin [STOC 2004]. Our approach introduces the Server model and Quantum Simulation Theorem which together provide a connection between distributed algorithms and communication complexity. The Server model is the standard two-party communication complexity model augmented with additional power; yet, most of the hardness in the two-party model is carried over to this new model. The Quantum Simulation Theorem carries this hardness further to quantum distributed computing. Our techniques, except the proof of the hardness in the Server model, require very little knowledge in quantum computing, and this can help overcoming a usual impediment in proving bounds on quantum distributed algorithms. In particular, if one can prove a lower bound for distributed algorithms for a certain problem using the technique of Das Sarma et al., it is likely that such lower bound can be extended to the quantum setting using tools provided in this paper and without the need of knowledge in quantum computing.
Neuromorphic visual information processing for vulnerable road user detection and driver monitoring

Considering the number of fatalities and serious injuries of road users, the safety enhancement has begun to gain more attention, in particular the innovation and application of Advanced Driver Assistance System Technologies. We have proposed that the neuromorphic visual processing algorithm based on the biological vision system is an effective approach for making detection of human figures from a moving vehicle, with the focus on either the driver or other vulnerable road users, such as the pedestrians or cyclists on the road. The effectiveness of proposed neuromorphic networks of visual processing is evaluated for the vulnerable road user detection technology via the 99% (day time) and 88% (night time) of successful detection rate. The post enhancement with deep networks showed that further applications could be sought from incorporating neuromorphic visual processing into Driver State Monitoring for the purpose of enhancing vulnerable road users' safety. The early implementation demonstrated the advantages of fast and robust neuromorphic vision with either the small embedded system or the portable computer based emulator, and the orientation processing of 30 frames per second with the neuromorphic ASIC and FPGA.
Heterogeneity in fibroblast proliferation and survival in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is the most common form of interstitial lung disease characterized by the persistence of activated myofibroblasts resulting in excessive deposition of extracellular matrix proteins and profound tissue remodeling. Myofibroblasts have been shown to arise from interstitial fibroblasts, epithelial to mesenchymal transition of type II alveolar epithelial cells, and the differentiation of recruited fibrocytes. There are many mechanisms that are utilized by these cells for survival, proliferation, and persistent activation including up-regulation of cytokines [i.e., Interleukin 6 (IL-6) and C-C motif chemokine ligand 21 (CCL21)], cytokine receptors [i.e., Interleukin 6 Receptor 1 (IL-6R1), Glycoprotein 130 (gp130) and C-C Chemokine Receptor type 7 (CCR7)], and innate pattern recognition receptors [(PRRs; i.e., Toll Like Receptor 9 (TLR9)]. In this review, we will discuss the role of the cytokines IL-6 and CCL21, their receptors and the PRR, TLR9, in fibroblast recruitment, activation, survival, and differentiation into myofibroblasts in IPF.
A Hybrid Genetic Programming and Boosting Technique for Learning Kernel Functions from Training Data

This paper proposes a technique for learning kernel functions that can be used in non-linear SVM classification. The technique uses genetic programming to evolve kernel functions as additive or multiplicative combinations of linear, polynomial and RBF kernels, while a procedure inspired from InfoBoost helps the evolved kernels concentrate on the most difficult objects to classify. The kernels obtained at each boosting round participate in the training of non-linear SVMs which are combined, along with their confidence coefficients, into a final classifier. We compared on several data sets the performance of the kernels obtained in this manner with the performance of classic RBF kernels and of kernels evolved using a pure GP method, and we concluded that the boosted GP kernels are generally better.
POLYPATH: Supporting Multiple Tradeoffs for Interaction Latency

Modern mobile systems use a single input-to-display path to serve all applications. In meeting the visual goals of all applications, the path has a latency inadequate for many important interactions. To accommodate the different latency requirements and visual constraints by different interactions, we present POLYPATH, a system design in which application developers (and users) can choose from multiple path designs for their application at any time. Because a POLYPATH system asks for two or more path designs, we present a novel fast path design, called Presto. Presto reduces latency by judiciously allowing frame drops and tearing. We report an Android 5-based prototype of POLYPATH with two path designs: Android legacy and Presto. Using this prototype, we quantify the effectiveness, overhead, and user experience of POLYPATH, especially Presto, through both objective measurements and subjective user assessment. We show that Presto reduces the latency of legacy touchscreen drawing applications by almost half; and more importantly, this reduction is orthogonal to that of other popular approaches and is achieved without any user-noticeable negative visual effect. When combined with touch prediction, Presto is able to reduce the touch latency below 10 ms, a remarkable achievement without any hardware support.
Class Specificity and the Lexical Encoding of Participant Information

It is commonly assumed across the language sciences that some semantic participant information is lexically encoded and some is not. In this article, we propose that semantic obligatoriness and verb class specificity are criteria which influence whether semantic information is lexically encoded. We present a comprehensive survey of the English verbal lexicon and two continuation studies which confirm that both factors play a role in the lexical encoding of participant information.
Using emotional context from article for contextual music recommendation

This paper proposes a context-aware approach that recommends music to a user based on the user's emotional state predicted from the article the user writes. We analyze the association between user-generated text and music by using a real-world dataset with user, text, music tripartite information collected from the social blogging website LiveJournal. The audio information represents various perceptual dimensions of music listening, including danceability, loudness, mode, and tempo; the emotional text information consists of bag-of-words and three dimensional affective states within an article: valence, arousal and dominance. To combine these factors for music recommendation, a factorization machine-based approach is taken. Our evaluation shows that the emotional context information mined from user-generated articles does improve the quality of recommendation, comparing to either the collaborative filtering approach or the content-based approach.
SYNOPSIS : DUAL EQUIVALENCE GRAPHS , RIBBON TABLEAUX AND

The primary focus of this dissertation is symmetric function theory. The main objectives are to present a new combinatorial construction which may be used to establish the symmetry and Schur positivity of a function expressed in terms of monomials, and to use this method to find a combinatorial description of the Schur expansion for two important classes of symmetric functions, namely LLT and Macdonald polynomials. Symmetric function theory plays an important role in many areas of mathematics including algebraic combinatorics, representation theory, Lie groups and Lie algebras, algebraic geometry and the theory of special functions. Multiplicities of irreducible components, dimensions of algebraic varieties, and various other algebraic constructions that require the computation of certain integers may be translated to the computation of the coefficients in the expansion of certain generalizations of the Schur basis. Often the coefficients can be identified as generating functions of tableau-like structures, providing a useful and often insightful combinatorial formula. Since their introduction in 1988, Macdonald polynomials have been intensely studied and have been found to have applications in such areas as representation theory, algebraic geometry, group theory, statistics, and quantum mechanics. Unfortunately, given the indirect definition of these polynomials as the unique functions satisfying certain conditions, most results require difficult technical machinery. Recent work by Haglund, Haiman and Loehr has connected the study of Macdonald polynomials to that of LLT polynomials. Though both Macdonald polynomials and LLT polynomials have been shown to be Schur positive using geometric methods, finding a combinatorial proof of positivity remains an important open problem in this area.