Miracle-dz/UniFAR-FTUs huggingface dataset:
Safety and feasibility of transcranial direct current stimulation (tDCS) combined with sensorimotor retraining in chronic low back pain: a protocol for a pilot randomised controlled trial

Introduction Chronic low back pain (LBP) is a common and costly health problem yet current treatments demonstrate at best, small effects. The concurrent application of treatments with synergistic clinical and mechanistic effects may improve outcomes in chronic LBP. This pilot trial aims to (1) determine the feasibility, safety and perceived patient response to a combined transcranial direct current stimulation (tDCS) and sensorimotor retraining intervention in chronic LBP and (2) provide data to support a sample size calculation for a fully powered trial should trends of effectiveness be present. Methods and analysis A pilot randomised, assessor and participant-blind, sham-controlled trial will be conducted. Eighty participants with chronic LBP will be randomly allocated to receive either (1) active tDCS + sensorimotor retraining or (2) sham tDCS + sensorimotor retraining. tDCS (active or sham) will be applied to the primary motor cortex for 20 min immediately prior to 60 min of supervised sensorimotor retraining twice per week for 10 weeks. Participants in both groups will complete home exercises three times per week. Feasibility, safety, pain, disability and pain system function will be assessed immediately before and after the 10-week intervention. Analysis of feasibility and safety will be performed using descriptive statistics. Statistical analyses will be conducted based on intention-to-treat and per protocol and will be used to determine trends for effectiveness. Ethics and dissemination Ethical approval has been gained from the institutional human research ethics committee (H10184). Written informed consent will be provided by all participants. Results from this pilot study will be submitted for publication in peer-reviewed journals. Trial registration number ACTRN12616000624482
Real-time scalable 6DOF pose estimation for textureless objects

Real-time recognition of the 6DOF pose of textureless objects is a fundamental and challenging problem in robotics. We present a novel approach to perform real-time estimation of the viewpoint, scale, and translation of an object in RGB and RGB-D image captures. In this work, we use a 3D model to render example poses of a textureless object, and find the nearest match to the input image using a GPU implementation. To achieve invariance to illumination and appearance across an object, we transform images to the Laplacian of Gaussian space. To perform real-time matching, we introduce a novel reshaping of the template set and the image, and we restructure the traditional normalized cross-correlation operation to leverage the GPU for fast matrix-matrix multiplication. We provide further speed up of large-scale template matching by contributing a dimensionality reduction approach using principal component analysis, and a candidate elimination method. Our method achieves state-of-the-art performance as shown by qualitative results and quantitative comparisons to pre-existing methods.
A Practical Parallel Algorithm for Diameter Approximation of Massive Weighted Graphs

We present a space and time efficient practical parallel algorithm for approximating the diameter of massive weighted undirected graphs on distributed platforms supporting a MapReduce-like abstraction. The core of the algorithm is a weighted graph decomposition strategy generating disjoint clusters of bounded weighted radius. Theoretically, our algorithm uses linear space and yields a polylogarithmic approximation guarantee, moreover, for important practical classes of graphs, it runs in a number of rounds asymptotically smaller than those required by the natural approximation provided by the state-of-the-art Δ-stepping SSSP algorithm, which is its only practical linear-space competitor in the aforementioned computational scenario. We complement ourtheoretical findings with an extensive experimental analysis on large benchmark graphs, which demonstrates that our algorithm attains substantial improvements on a number of key performance indicators with respect to the aforementioned competitor, while featuring a similar approximation ratio (a small constant less than 1.4, as opposed to the polylogarithmic theoretical bound).
Detection of LSB Matching Steganography using the Envelope of Histogram

As well-known, it is hard to detect LSB matching steganography when cover images are scans of photographs, which usually have high-frequency noise. This paper proposes a novel steganalysis method for this issue by making use of the following two facts: One is the local maxima of an image histogram decrease and the local minima increase after LSB matching steganography. As a result, the area between upper envelope and lower envelope of the histogram of a stego image will be smaller than that of a cover image. The other is LSB matching embedding in the spatial domain of an image corresponds to low-pass filtering of the histogram. So, there are some differences in the high order statistical moments of high frequencies of the histogram. Based on these facts, this paper constructs a novel feature vector to distinguish between stego and cover images. Experimental results show the proposed scheme has better performance than some state-of-the-art steganalyzers in the literature.
A Malware Instruction Set for Behavior-Based Analysis

We introduce a new representation for monitored behavior of malicious software called Malware Instruction Set (MIST). The representation is optimized for effective and efficient analysis of behavior using data mining and machine learning techniques. It can be obtained automatically during analysis of malware with a behavior monitoring tool or by converting existing behavior reports. The representation is not restricted to a particular monitoring tool and thus can also be used as a meta language to unify behavior reports of different sources.
On the Vulnerability of Water Limited Ecosystems to Climate Change

Society is facing growing environmental problems that require new research efforts to understand the way ecosystems operate and survive, and their mutual relationships with the hydrologic cycle. In this respect, ecohydrology suggests a renewed interdisciplinary approach that aims to provide a better comprehension of the effects of climatic changes on terrestrial ecosystems. With this aim, a coupled hydrological/ecological model is adopted to describe simultaneously vegetation pattern evolution and hydrological water budget at the basin scale using as test site the Upper Rio Salado basin (Sevilleta, NM, USA). The hydrological analyses have been carried out using a recently formulated framework for the water balance at the daily level linked with a spatial model for the description of the spatial organization of vegetation. This enables quantitatively assessing the effects on soil water availability on future climatic scenarios. Results highlighted that the relationship between climatic forcing (water availability) and vegetation patterns is strongly non-linear. This implies, under some specific conditions which depend on the ecosystem characteristics, small changes in climatic conditions may produce significant transformation of the vegetation patterns.
P3-Mobile: Parallel Computing for Mobile Edge-Clouds

We address the problem of whether networks of mobile devices such as smartphones or tablets can be used to perform opportunistic, best-effort, parallel computations. We designed and implemented P3-Mobile, a parallel programming system for edge-clouds of Android devices to test the feasibility of this idea. P3-Mobile comes with a programming model that supports parallel computations over peer-to-peer overlays mapped onto mobile networks. The system performs automatic load-balancing by using the overlay to discover work. We present preliminary performance results for a parallel benchmark, using up to 16 devices, and discuss their implications towards future work.
Finding long chains in kidney exchange using the traveling salesman problem

Significance There are currently more than 100,000 patients on the waiting list in the United States for a kidney transplant from a deceased donor. To address this shortage, kidney exchange programs allow patients with living incompatible donors to exchange donors through cycles and chains initiated by altruistic nondirected donors. To determine which exchanges will take place, kidney exchange programs use algorithms for maximizing the number of transplants under constraints about the size of feasible exchanges. This problem is NP-hard, and algorithms previously used were unable to optimize when chains could be long. We developed two algorithms that use integer programming to solve this problem, one of which is inspired by the traveling salesman, that together can find optimal solutions in practice. As of May 2014 there were more than 100,000 patients on the waiting list for a kidney transplant from a deceased donor. Although the preferred treatment is a kidney transplant, every year there are fewer donors than new patients, so the wait for a transplant continues to grow. To address this shortage, kidney paired donation (KPD) programs allow patients with living but biologically incompatible donors to exchange donors through cycles or chains initiated by altruistic (nondirected) donors, thereby increasing the supply of kidneys in the system. In many KPD programs a centralized algorithm determines which exchanges will take place to maximize the total number of transplants performed. This optimization problem has proven challenging both in theory, because it is NP-hard, and in practice, because the algorithms previously used were unable to optimally search over all long chains. We give two new algorithms that use integer programming to optimally solve this problem, one of which is inspired by the techniques used to solve the traveling salesman problem. These algorithms provide the tools needed to find optimal solutions in practice.
Large-eddy simulations of the turbulent Hartmann flow close to the transitional regime

A series of large-eddy simulations (LES) of turbulent and transitional channel flows of a conductive fluid under the effect of a uniform magnetic field applied in the wall-normal direction, usually referred to as Hartmann flows, are performed using the dynamic Smagorinsky model. The flow is characterized by the hydrodynamic Reynolds number Re and the Hartmann number Ha that is related to the strength of the external magnetic field. Previous measurements and works on stability analysis have shown that a critical modified Reynolds number, based on the Hartmann layer thickness R=Re∕Ha, exists at approximately R=380. Here, the LES are used to investigate the laminarization of flow when decreasing R. Also, similarities of the turbulent flows are explored for different values of Re and Ha but the same values of R or of the interaction parameter N=Ha2∕Re. The LES confirm that R is the relevant parameter that describes the transition and a critical Reynolds number for relaminarization is observed at R≈500. Howeve.
MED1101: A new dialdehydic compound regulating P2×7 receptor cell surface expression in U937 cells

P2×7R is a member of the ionotropic family of purinergic receptors activated by millimolar concentrations of extracellular ATP such as induced by inflammatory stimuli. The receptor is widely expressed in cells of haematopoietic origin such as monocytes, macrophages and microglia. There is growing interest in anta‐gonist compounds of the P2×7R since it has been demonstrated to be a viable therapeutic target for inflammatory diseases. Here, we tested the possible P2×7 antagonist effect of MED1101, a newly synthesised dialdehydic compound on U937 monocyte cells.
Visualization of tensor fields using superquadric glyphs

The spatially varying tensor fields that arise in magnetic resonance imaging are difficult to visualize due to the multivariate nature of the data. To improve the understanding of myocardial structure and function a family of objects called glyphs, derived from superquadric parametric functions, are used to create informative and intuitive visualizations of the tensor fields. The superquadric glyphs are used to visualize both diffusion and strain tensors obtained in canine myocardium. The eigensystem of each tensor defines the glyph shape and orientation. Superquadric functions provide a continuum of shapes across four distinct eigensystems (λi, sorted eigenvalues), λ1 = λ2 = λ3 (spherical), λ1 < λ2 = λ3 (oblate), λ1 > λ2 = λ3 (prolate), and λ1 > λ2 > λ3 (cuboid). The superquadric glyphs are especially useful for identifying regions of anisotropic structure and function. Diffusion tensor renderings exhibit fiber angle trends and orthotropy (three distinct eigenvalues). Visualization of strain tensors with superquadric glyphs compactly exhibits radial thickening gradients, circumferential and longitudinal shortening, and torsion combined. The orthotropic nature of many biologic tissues and their DTMRI and strain data require visualization strategies that clearly exhibit the anisotropy of the data if it is to be interpreted properly. Superquadric glyphs improve the ability to distinguish fiber orientation and tissue orthotropy compared to ellipsoids. Magn Reson Med 53:169–176, 2005. Published 2004 Wiley‐Liss, Inc.
Clinical Application of Standardized Cognitive Assessment Using fMRI. I. Matrix Reasoning

Functional MRI is increasingly recognized for its potential as a powerful new tool in clinical neuropsychology. This is likely due to the fact that, with some degree of innovation, it is possible to convert practically any familiar cognitive test into one that can be performed in the MRI scanning environment. However, like any assessment approach, meaningful interpretation of fMRI data for the purpose of patient evaluation crucially requires normative data derived from a sample of unimpaired persons, against which individual patients may be compared. Currently, no such normative data are available for any fMRI-based cognitive testing protocol. In this paper, we report the first of a series of fMRI-compatible cognitive assessment protocols, a matrix reasoning test (f-MRT), for which normative samples of functional activation have been collected from unimpaired control subjects and structured in a manner that makes individual patient evaluation possible in terms of familiar z-score distributions. Practical application of the f-MRT is demonstrated via a contrastive case-study of two individuals with cognitive impairment in which fMRI data identifies subtleties in patient deficits otherwise missed by conventional measures of performance.
Systematic Coupling of Requirements Specifications

Object-oriented requirements specifications comprise the description of behavioral and structural aspects of the system to be built. Use cases for e.g. sketch the system's behavior while the class model expresses its structural properties. The different objectives and modeling techniques of use cases and the class model induce consistency and comprehension problems which are intensified by the different abstraction levels of both techniques. To bridge the gap between use cases and the class model, we refine the UML use case concept by decomposing a use case into well-defined use case steps and complementing it with "control flow" information. Use case steps are specified by preand post-conditions. These assertions take elements of the class model into account which are involved in the steps. For validation purposes, our approach also covers those steps of business processes which are not supported by the system. Granularity and semantics of the resulting model framework SCORES allow for validating the refined use cases and the class model as well as verifying both models against each other. The SCORES tool set provides modeling, validation, and verification facilities including, for example, animated walk-throughs of the refined use cases and bookkeeping of detected errors and anomalies. TABLE OF CONTENTS
An Approach to Content Extraction from Scientific Articles using Case-Based Reasoning

In this paper, we present an eﬃcient approach for content extraction of scientiﬁc papers from web pages. The approach uses an artiﬁcial intelligence method, Case-Based Reasoning(CBR), that relies on the idea that similar problems have similar solutions and hence reuses past experiences to solve new problems or tasks. The key task of content extraction is the classiﬁcation of HTML tag sequences where the sequences representing navigation links, advertisements and, other non-informative content are not of interest when the goal is to extract scientiﬁc contributions. Our method learns from each experience with the tag sequence classiﬁcation episode and stores these in the case base. When a new tag sequence needs to be classiﬁed, the system checks its case base to see whether a similar tag was experienced before in order to reuse it for content extraction. If the tag sequence is completely new, then it uses the proposed algorithm that relies on two assumptions related to the distribution of various tag sequences occurring in the page, and the similarity of the tag sequences with respect to their structure in terms of levels of the tags. Experimental results show that the proposed approach eﬃciently extracts content information from scientiﬁc articles.
Presence Signalling in Unified Communication Systems - A Framework for Customisation in Context

A system, e.g., a wavelength division multiplexed optical network, having a tunable add/drop filter is provided. The filter of the invention contains a substrate having a waveguide capable of guiding both optical waves and acoustic waves. An interdigital transducer induces one or more acoustic waves of desired wavelengths in the waveguide, along the same direction as the optical waves, such that one or more desired optical wavelength channels are reversed in direction, i.e., reflected back in the direction from which the light entered the waveguide. The filter of the invention thus provides reversal of direction of selected optical wavelengths in a manner similar to that of a fiber grating, but, unlike a fiber grating, the filter of the invention is also capable of being tuned in real-time to reflect light of selected wavelength bands, by adjusting the frequency of the voltage applied to the interdigital transducer.
Golden hamster embryonic genome activation occurs at the two‐cell stage: Correlation with major developmental changes

The earliest time of onset of embryonic genome activation in golden hamsters was investigated. The inhibition of transcription by α‐amanitin (11 μg/ml) in cultured embryos resulted in a total arrest of development of early 2‐cell embryos (26 hr post‐egg activation); under similar conditions, immediate cleavage divisions of 1‐, late 2‐, 4‐, and 8‐cell embryos were not affected. Electrophoretic analysis of [35S]methionine‐labeled embryonic proteins showed that α‐amanitin treatment apparently inhibited transcription‐dependent protein synthesis in early 2‐cell and, to some extent, in late 2‐cell when compared to 4‐cell embryos. Analysis of total RNA synthesis, using [α32P]‐UTP or [32P]‐orthophosphate, showed that there was a high proportion of radioactivity associated with the macromolecular fraction (RNA) at the early and late 2‐cell stages and at the 4‐cell stage compared to that at the 1‐cell stage. These results indicate that the de novo synthesis of RNA, encoded by the embryonic genome, occurs at the 2‐cell stage and that the second and subsequent cleavage divisions of hamster preimplantation embryos are dependent on new transcriptional activity. This initial activity of the embryonic genome in hamsters is coincident with several characteristic features of in vitro development such as a block to development, synthesis of major proteins, change in energy substrate preference, phosphate‐inhibition of development and a requirement for amino acids.
An artificial molecular switch that mimics the visual pigment and completes its photocycle in picoseconds

Single molecules that act as light-energy transducers (e.g., converting the energy of a photon into atomic-level mechanical motion) are examples of minimal molecular devices. Here, we focus on a molecular switch designed by merging a conformationally locked diarylidene skeleton with a retinal-like Schiff base and capable of mimicking, in solution, different aspects of the transduction of the visual pigment Rhodopsin. Complementary ab initio multiconfigurational quantum chemistry-based computations and time-resolved spectroscopy are used to follow the light-induced isomerization of the switch in methanol. The results show that, similar to rhodopsin, the isomerization occurs on a 0.3-ps time scale and is followed by <10-ps cooling and solvation. The entire (2-photon-powered) switch cycle was traced by following the evolution of its infrared spectrum. These measurements indicate that a full cycle can be completed within 20 ps.
[Regulatory mechanism of osteoblast differentiation and bone formation].

(20-22). This review describes recent advances regarding the mechanism of osteoblast differentiation and its regulation by the systemic factors and local factors including Regulatory mechamism of osteo blast differentiation and bne formation. Osteoblast differentiation is regulated by various hormones and local factors such as estrogen, parathyroid hormone , bone morphogenetic proteins ( BMPs ) and hedgehogs . Estrogen-deficiency increases systemic factors that stimulate osteoblast differentiation, resulting in a high turnover bone remodeling with accelerated bone formation. Parathyroid hormone has diverse effects on osteoblast differentiation depending on the exposure time in vitro mediated through different signal transduction systems. Among local factors, BMPs are the most potent inducers and stimulators of osteoblast differentiation: BMPs not only stimulate osteoprogenitors to differentiate into mature osteoblasts but also induce non-osteogenic cells to differentiate into osteoblast lineage cells. Sonic and Indian hedgehogs also play important roles in regulation of osteoblast differentiation by interacting with BMPs. Cbfa1, a transcription factor belonging to the runt-domain gene family, is essential for osteoblast differentiation and bone formation because Cbfa1 -deficient mice completely lack bone formation due to maturational arrest of osteoblasts. BMPs are important local factors that up-regulate Cbfa1 expression. The phenotype of heterozygous Cbfa1 mutation is similar to that of cleidocranial dysplasia. The intimate interaction between the local factors including hedgehogs and BMPs as well as the transcription factor Cbfa1 play crucial roles in the process of osteoblast differentiation and bone formation. Further progress in bone research will provide information important not only in the field of cell biology but also for clinical research of various bone diseases.