Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement of Neck Circumference and Its Correlation with Body Composition in a Sample of Students in São Paulo, Brazil

Purpose: The purpose of this study was to verify the correlation between neck circumference (NC) and body mass index (BMI) in children, and to determine NC percentiles for Brazilian children. Methods: The subjects of this cross-sectional study were students between the ages of 6 and 19 years from five schools in São Paulo, Brazil. Clinical and anthropometric data were collected from the students from April 2011 to June 2012. NC was measured at the level of the cricoid cartilage. We calculated Pearson correlation coefficients between NC and other indices of obesity with Sigma Stat 3.5. NC percentiles were produced using the LMS (lambda, mu, and sigma) method (STATA 12.0). Results: Among 2,794 students, 49.9% were male. NC was significantly correlated with age, BMI, waist circumference (WC), and body fat percentage (%BF). The NC of boys was greater than that of girls. The NC curves of smoothed 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles were constructed by age and sex. Conclusions: NC can be used in the assessment of obesity in childhood. There was a positive correlation between NC and BMI, WC and %BF. This study was the first to provide NC percentiles for children in Brazil.
Monitoring physical function in patients with knee osteoarthritis using data from wearable activity monitors

Currently used clinical assessments for physical function do not objectively quantify daily activities in routine living. Wearable activity monitors enable objective measurement of routine daily activities, but do not map to clinically measured physical performance measures. We represent physical function as a daily activity profile derived from minute-level activity data obtained via a wearable activity monitor. We construct daily activity profiles representing average time spent in a set of activity classes over consecutive days using the Osteoarthritis Initiative (OAI) data. Using the daily activity profile as input, we trained statistical models that classify subjects into quartiles of objective measurements of physical function as measured via the 400m walk test, the 20m walk test and 5 times sit stand test. We evaluated model performance on held out data from the same calendar year as that used to train the models as well as on activity data two years into the future. The daily activity profile predicts physical performance as measured via clinical assessments. Using held out data, the AUC obtained in classifying performance values in the 1st quartile was 0.79, 0.78 and 0.72, for the 400m walk, the 20m walk and 5 times sit stand tests. For classifying performance values in the 4th quartile, the AUC obtained was 0.77, 0.66 and 0.73 respectively. Evaluated on data from two years into the future, for the 20m pace test and the 5 times sit stand tests, the highest AUC obtained was 0.77 and 0.68 for the 1st quartile and 0.75 and 0.70 for the 4th quartile respectively. We can construct activity profiles representing actual physical function as demonstrated by the relationship between the activity profiles and the clinically measured physical performance measures. Measurement of physical performance via the activity profile as described can enable remote functional monitoring of patients.
Changes in Protein Expression and Lysine Acetylation Induced by Decreased Glutathione Levels in Astrocytes*

Astrocytes and neurons form a highly specialized functional unit, and the loss or gain of astrocytic functions can influence the initiation and progression of different neurodegenerative diseases. Neurons depend on the antioxidant protection provided by neighboring astrocytes. Glutathione (γ-l-glutamyl-l-cysteinyl-glycine) is a major component of the antioxidant system that defends cells against the toxic effects of reactive oxygen/nitrogen species. A decline in glutathione levels has been observed in aging and neurodegenerative diseases, and it aggravates the pathology in an amyotrophic lateral sclerosis-mouse model. Using a SILAC-based quantitative proteomic approach, we analyzed changes in global protein expression and lysine acetylation in primary astrocyte cultures obtained from wild-type mice or those deficient in the glutamate-cysteine ligase modifier subunit (GCLM). GCLM knockout astrocytes display an ∼80% reduction in total glutathione levels. We identified potential molecular targets and novel sites of acetylation that are affected by the chronic decrease in glutathione levels and observed a response mediated by Nrf2 activation. In addition, sequence analysis of peptides displaying increased acetylation in GCLM knockout astrocytes revealed an enrichment of cysteine residues in the vicinity of the acetylation site, which suggests potential crosstalk between lysine–acetylation and cysteine modification. Regulation of several metabolic and antioxidant pathways was observed at the level of protein expression and lysine acetylation, revealing a coordinated response involving transcriptional and posttranslational regulation.
Using Your Fingers to Think: Enabling Subjective Routing with a Rubber Band Metaphor

There is a class of complex problems where solutions must satisfy multiple subjective criteria, while meeting specific quantifiable constraints. Route planning for leisurely travel is an example of a problem in this class. Constraints including total available time, transit times, and one's budget and subjective interests determine whether a potential solution is acceptable to a prospective traveler. In this paper we present a route planning (routing) interface that metaphorically leverages various elastic properties of a rubber band to allow for playful interaction with the relevant constraints. Each of these properties — attenuation, tension, and color — were integrated into an experimental system and then investigated in a series of task-based evaluations. Our research shows this playful interaction enables potential travelers to explore the solution space in order to find a route that meets, not only the easily quantifiable constraints, but also their own subjective preferences.
BGP protocol anti-routing shake performance analysis and simulation

BGP protocol routing update has a large amount of calculation, when the network occurs routing shock in the BGP protocol, the computational complexity would increase rapidly. In order to study the anti shock performance of BGP protocol, has take the low rate denial of service attack as the source of the shock, and studied the selection of the critical paths in the BGP routing topology deeply. Focus on the typical BGP shock attack algorithm as the reference sample, studied the improved method of attack, and analyzed the performance of the BGP protocol by the experimental simulation.
CME 372 : Applied Fourier Analysis and Winter 2016 Elements of Modern Signal Processing Lecture 10 — February 4 , 2016 Prof

Last Time: In modeling the problem of X-ray tomography, we introduced the Radon transform, which outputs a collection of line integrals of an input function. The procedure of backprojection was a first attempt at recovering a signal from its Radon transform; however, we saw that it did not return exact reconstruction, but rather a smoothed version of the original signal. Through the projection-slice theorem, we established a relation between the Radon and the Fourier transforms. This relation allowed us to derive a closed-form expression for the actual inverse Radon transform, which we call the filtered backprojection formula.
Automatic mapping of OpenCV based systems on new heterogeneous SoCs

In this paper, a new approach to facilitate the development of heterogeneous embedded vision systems, by means of a software-friendly design flow is proposed. Our work is based on a framework called AMAZynq, especially focused on leverage the resources of Xilinx Zynq devices. Starting from an OpenCV code, the user defines explicitly the HW/SW partition and the AMAZynq produces the corresponding hardware and software infrastructures. The result is a SoC that not only matches the original functionality, but also accelerates it by means of an automatically generated and verified HLS core.
Volumetric quantitation by MRI in primary progressive multiple sclerosis: volumes of plaques and atrophy correlated with neurological disability

In primary progressive multiple sclerosis (PPMS) abnormalities in brain magnetic resonance imaging (MRI) differ from abnormalities in other subtypes of multiple sclerosis (MS). It was investigated whether the extent of brain and spinal cord MRI abnormalities is reflected in the neurological disability in PPMS. Focal and diffuse changes and atrophy in central nervous system (CNS) in patients with PPMS (n = 28) and healthy controls (n = 20) were assessed by semi‐automatic MRI segmentation and volumetric analysis. The measurements were related to neurological disability as expressed by the expanded disability status scale (EDSS), the regional functional scoring system (RFSS), the arm index and the ambulation index. Plaques in T1‐ and/or T2‐weighted images were seen in all brains, while spinal plaques were detected in 23 of 28 patients (82%). The total volumes of brain and spinal cord were significantly smaller in patients than in controls (P = 0.001 and 0.000, respectively). The volumes of T1 or T2 lesions in the brain correlated to the ambulation index (r = 0.51, P = 0.005 and r = 0.53, P = 0.004, respectively). No correlations were detected between MRI measurements and total EDSS score, but relative brain atrophy correlated inversely with the total RFSS scores, poor arm index and higher cerebral disturbances (r = −0.53, P = 0.004; r = −0.53, P = 0.004; and r = −0.52, P = 0.005, respectively). Although the number of spinal T2 lesions correlated with sensory disturbances (r = 0.60, P = 0.001), no correlations were found between EDSS subscores and spinal cord atrophy. These findings show that marked atrophy of brain and spinal cord detected by volumetric quantitation correlates with neurological disability. This observation indicates the importance of neurodegenerative events in PPMS.
Low-rank matrix completion and cellular automaton modelling for interpolation

In this paper, we propose a low-rank matrix completion and cellular automaton model to effectively exploit the nonlocal inter-pixel correlation for image interpolation and enhancement applications. Different from tasks such as image denoising, in image interpolation and colour demosaicking, the many visually unpleasant artefacts (for example, ringing effects and zipper artefacts) are generally fine scale structures and lead to small singular values of the data matrix, and therefore, we propose to use L0-norm, instead of the relaxed L1-norm, to regularise the singular values so that the fine scale artefacts can be effectively removed without affecting the large-scale image edges. The entire framework can be applied for extended matrix arrangement. We also incorporate a cellular automaton model with inter-pixel correlations and extend it for image interpolation. Experimental results show that the proposed method produces reasonably good results as compared with state-of-the-arts in terms of both peak signal-to-noise ratio measure and subjective visual quality.
An Alternative Approach to Measuring Horizontal and Vertical Equity in School Funding.

Although the notions of vertical and horizontal equity are straightforward, constructing valid measures of each has proven difficult in states that make revenue adjustments for multiple factors. In this article we introduce an alternative approach for assessing horizontal and vertical equity that addresses this problem. This approach is based on the multivariate relationships between a school district's per-pupil revenues and the various factors used to determine per-pupil funding in the district's state. The vertical equity metrics are based on how close the linear relationships between per-pupil funding and vertical equity factors are to their intended values. We examine horizontal equity by looking at the unexplained variations in per-pupil funding levels from the same model. This leads to improved measurement of "equal treatment of equals" without assuming that all school districts have comparable funding needs. We use data for 292 public school districts in Indiana to illustrate how the new measures can be implemented and whether changes in the state's foundation program in 2005 resulted in gains in horizontal and vertical equity.
Apache Spark GEP : Graph Extractor and Packing In Memory Distributed Execution Engine NScaleSpark : User API Subgraph Computation Output results HDFS

In this paper, we describe NSCALESPARK, a framework for executing large-scale distributed graph analysis tasks on the Apache Spark platform. NSCALESPARK is motivated by the increasing interest in executing rich and complex analysis tasks over large graph datasets. There is much recent work on vertex-centric graph programming frameworks for executing such analysis tasks – these systems espouse a “think-like-a-vertex” (TLV) paradigm, with some example systems being Pregel, Apache Giraph, GPS, Grace, and GraphX (built on top of Apache Spark). However, the TLV paradigm is not suitable for many complex graph analysis tasks that typically require processing of information aggregated over neighborhoods or subgraphs in the underlying graph. Instead, NSCALESPARK is based on a “think-like-a-subgraph” paradigm (also recently called “think-like-an-embedding” [24]). Here, the users specify computations to be executed against a large number of multi-hop neighborhoods or subgraphs of the data graph. NSCALESPARK builds upon our prior work on the NSCALE system [19], which was built on top of the Hadoop MapReduce system. We describe how we reimplemented NSCALE on the Apache Spark platform, the key challenges therein, and the design decisions we made. NSCALESPARK uses a series of RDD transformations to extract and hold the relevant subgraphs in distributed memory with minimal footprint using a cost-based optimizer. Our in-memory graph data structure enables efficient graph computations over large-scale graphs. Our experimental results over several real world data sets and applications show orders-of-magnitude improvement in performance and total cost over GraphX and other vertex-centric approaches.
Unified GPU-Parallelizable Robot Forward Dynamics Computation Using Band Sparsity

This letter proposes a unified GPU-parallelizable approach for robot forward dynamics (FD) computation based on the key fact that parallelism of prevailing FD algorithms benefits from the essential band sparsity of the joint space inertia (JSI) matrix or its inverse. The existing FD algorithms are categorized into three classes: direct JSI algorithms, propagation algorithms, and constraint force algorithms. Their associated systems of linear equations are transformed into a set of block bidiagonal (the first and second classes) and tridiagonal (the third class) linear systems, which can be conveniently and efficiently parallelized over the existing CPU–GPU programming platforms using various state-of-the-art parallel algorithms, such as parallel all-prefix sum (scan) and odd–even elimination. This high-level perspective allows unified and efficient implementation of all three classes of algorithms and also other potentially efficient algorithms, with the bonus that different algorithms can be swiftly compared to recommend problem-specific solutions.
A Fluid-Based Model of a Transport Protocol in Content-Centric Networking

In this paper, we propose a modeling approach for a Content-Centric Networking (CCN) network by considering the dynamics of its transport layer protocol. Transport layer protocols for CCN have mainly been investigated through simulation experiments because CCN itself is a complicated network architecture compared with IP, and the complex interaction between CCN caching and the behavior of a transport layer protocol must be considered. Several analytical studies of transport layer protocols in CCN have been reported; however, these modeling approaches cannot model the dynamical behavior of a transport layer protocol or a large-scale CCN network. In this paper, by extending an existing large-scale CCN modeling approach, we build a fluid-based model for a CCN network with an AIMD-based window flow control mechanism. Moreover, we verify the validity of our approximate analysis by comparing the analytical results with simulation results.
Analgesic Effects of Low-dose Intravenous Orphenadrine in the State of Capsaicin Hyperalgesia

Summary The present investigation aimed to elucidate the analgesic efficacy of 30 mg of intravenous orphenadrine citrate (CAS 4682-36-4) in a human pain model. Eighteen healthy female and male subjects were enrolled and received single infusions of 30 mg orphenadrine citrate and matching placebo in two periods -which were separated by a 1 week washout period. The study was designed as a randomised, double-blind, placebo-controlled, two-period, cross-over trial. The intended neurogenic inflammation and hyperalgesia were induced by topical, occlusive application of 1 % capsaicin solution (INCI: Capsicum frutescens, containing capsaicinoides from Capsicum annuum annuum, CAS 84603-55-4) for 30 min on defined skin areas of the back. The pain response to CO2 laser pulses applied to the capsaicin pre-treated skin was measured by event related Vertex-EEG recordings. This technique allowed studying the influence of orphenadrine citrate on the (central) P2-component and the (peripheral) N1-component of the pain response (LSEP). Both, orphenadrine citrate and placebo were given as intravenous infusions over 60 min. Orphenadrine citrate exerted a significant reduction in central and peripheral components of the pain response when compared to placebo. The effect on the central component was highly significant and more pronounced than the peripheral effect of the drug. The analgesic effect developed fast, was already present during infusion, was ongoing, and exceeded the observational period of 4 h after start of infusion. In summary, orphenadrine citrate was able to exert an analgesic/anti-hyperalgesic effect in a low-dose paradigm (30 mg dose) which was predominantly due to central/spinal mechanisms in this capsaicin model with laser somatosensory evoked potentials.
Series-shunt power active filter for high penetration of embedded production one dynamic approach

The increase of the embedded production brings problems of energy quality which must be solved. Several literatures show that these problems can be reduced with the installation of Unified Power Quality Conditioners (UPQC). In this paper in alternative to the Theory of Instantaneous Power (p-q) and to the Direct Quadrature Zero transformation (dq0), one novel approach to the UPQC is proposed. That is inspired on the Methods of Qualitative Theory in Nonlinear Dynamics along with the classic control methods. Its architecture allows a strongly reducing of the harmonics in both currents and voltages in balanced or unbalanced systems with linear or nonlinear loads. Moreover, in that situations the transients are strongly mitigated too. The large increase in the power quality achieved with these devices allows a high level of embedded electrical energy production.
An Eye Tracking Study on the Perception and Comprehension of Unimodal and Bimodal Linguistic Inputs by Deaf Adolescents

An eye tracking experiment explored the gaze behavior of deaf individuals when perceiving language in spoken and sign language only, and in sign-supported speech (SSS). Participants were deaf (n = 25) and hearing (n = 25) Spanish adolescents. Deaf students were prelingually profoundly deaf individuals with cochlear implants (CIs) used by age 5 or earlier, or prelingually profoundly deaf native signers with deaf parents. The effectiveness of SSS has rarely been tested within the same group of children for discourse-level comprehension. Here, video-recorded texts, including spatial descriptions, were alternately transmitted in spoken language, sign language and SSS. The capacity of these communicative systems to equalize comprehension in deaf participants with that of spoken language in hearing participants was tested. Within-group analyses of deaf participants tested if the bimodal linguistic input of SSS favored discourse comprehension compared to unimodal languages. Deaf participants with CIs achieved equal comprehension to hearing controls in all communicative systems while deaf native signers with no CIs achieved equal comprehension to hearing participants if tested in their native sign language. Comprehension of SSS was not increased compared to spoken language, even when spatial information was communicated. Eye movements of deaf and hearing participants were tracked and data of dwell times spent looking at the face or body area of the sign model were analyzed. Within-group analyses focused on differences between native and non-native signers. Dwell times of hearing participants were equally distributed across upper and lower areas of the face while deaf participants mainly looked at the mouth area; this could enable information to be obtained from mouthings in sign language and from lip-reading in SSS and spoken language. Few fixations were directed toward the signs, although these were more frequent when spatial language was transmitted. Both native and non-native signers looked mainly at the face when perceiving sign language, although non-native signers looked significantly more at the body than native signers. This distribution of gaze fixations suggested that deaf individuals – particularly native signers – mainly perceived signs through peripheral vision.
Sequence of PSE-2 beta-lactamase

The nucleotide sequence of PSE-2 beta-lactamase, an enzyme that readily hydrolyzes both carbenicillin and oxacillin, has been determined. The deduced sequence of 266 amino acids contained 93 residues identical to those of OXA-2 beta-lactamase and the Ser-Thr-Phe-Lys tetrad also found in the active site of TEM-1 beta-lactamase.
Robust Regression for Clustered Data with Application to Binary Responses

Summary. Generalized estimating equations (GEE) can be highly influenced by the presence of unusual data points. A generalization of the GEE procedure, which yields parameter estimates and fitted values that are resistant to influential data, is introduced. Resistant generalized estimating equations (REGEE) include weights in the estimating equations to downweight influential observations or clusters. Influential observations are downweighted according to their leverage or residual in an example of correlated binary regression applied to 137 urinary incontinent elderly patients from 38 medical practices.
Abnormalities of brain response during encoding into verbal working memory among euthymic patients with bipolar disorder

Individuals with bipolar disorder (BD) have trait‐like deficits in attention and working memory (WM). A fundamental dissociation for most verbal WM theories involves the separation of sensory‐perceptual encoding, reliant upon attention, from the maintenance of this information in WM proper. The present study examined if patients with BD demonstrate differential neural changes in encoding and maintenance WM processes that underlie cognitive impairment.