Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of HIV and ART with cardiometabolic traits in sub-Saharan Africa: a systematic review and meta-analysis

Background Sub-Saharan Africa (SSA) has the highest burden of HIV in the world and a rising prevalence of cardiometabolic disease; however, the interrelationship between HIV, antiretroviral therapy (ART) and cardiometabolic traits is not well described in SSA populations. Methods We conducted a systematic review and meta-analysis through MEDLINE and EMBASE (up to January 2012), as well as direct author contact. Eligible studies provided summary or individual-level data on one or more of the following traits in HIV+ and HIV-, or ART+ and ART- subgroups in SSA: body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TGs) and fasting blood glucose (FBG) or glycated hemoglobin (HbA1c). Information was synthesized under a random-effects model and the primary outcomes were the standardized mean differences (SMD) of the specified traits between subgroups of participants. Results Data were obtained from 49 published and 3 unpublished studies which reported on 29 755 individuals. HIV infection was associated with higher TGs [SMD, 0.26; 95% confidence interval (CI), 0.08 to 0.44] and lower HDL (SMD, −0.59; 95% CI, −0.86 to −0.31), BMI (SMD, −0.32; 95% CI, −0.45 to −0.18), SBP (SMD, −0.40; 95% CI, −0.55 to −0.25) and DBP (SMD, −0.34; 95% CI, −0.51 to −0.17). Among HIV+ individuals, ART use was associated with higher LDL (SMD, 0.43; 95% CI, 0.14 to 0.72) and HDL (SMD, 0.39; 95% CI, 0.11 to 0.66), and lower HbA1c (SMD, −0.34; 95% CI, −0.62 to −0.06). Fully adjusted estimates from analyses of individual participant data were consistent with meta-analysis of summary estimates for most traits. Conclusions Broadly consistent with results from populations of European descent, these results suggest differences in cardiometabolic traits between HIV-infected and uninfected individuals in SSA, which might be modified by ART use. In a region with the highest burden of HIV, it will be important to clarify these findings to reliably assess the need for monitoring and managing cardiometabolic risk in HIV-infected populations in SSA.
Total tissue factor pathway inhibitor is an independent risk factor for symptomatic paediatric venous thromboembolism and stroke

Summary Tissue factor pathway inhibitor (TFPI) plays an important role in inhibiting tissue factor-induced coagulation by a factor Xadependent pathway of the activated tissue-factor VIIa complex. Decreased values of the latter inhibitor have been recently reported in adult patients with venous thrombosis (VT) or ischaemic stroke (IS). The present case-control study was therefore performed to evaluate whether a decreased TFPI concentration is also involved in paediatric symptomatic thromboembolism (ST). Total TFPI concentrations were measured along with established prothrombotic risk factors six to twelve months after the acute thrombotic onset in 144 Caucasian children aged 0.6 to 18 years (VT: n=80; IS: n=64). The cut-off values defined as age-dependent 10th percentiles were obtained from 244 healthy controls. Median (range) values of TFPI were significantly lower in patients compared with control subjects [50.0(20.0-132.3) ng/ml vs. 59.5(25.4-117.4) ng/ml; p-value < 0.0001]. In addition, 42 of the 144 patients (29.2%) compared with 25 of the 244 controls (10.2%) showed TFPI concentrations below the 10th age-dependent percentiles. Compared to baseline values 78.6% of children with total TFPI Ag < 10th percentiles showed a low response to enoxaparin administration, whereas in children with normal baseline TFPI values 30% show a low TFPI release (p= 0.007). Multivariate analysis adjusted for the presence of established prothrombotic risk factors showed a significantly increased odds ratio (OR) and 95% confidence interval (CI) for patients with ST [OR/CI: 3.8/2.2-6.6; p< 0.0001]. Data shown here give evidence that total TFPI concentrations below the 10th age-dependent percentiles independently increase the risk of ST in Caucasian children 3.8-fold.
Free-space optical link with spatial redundancy for misalignment tolerance

Free-space optical interconnects can provide high bandwidth with no physical contact, but suffer from poor tolerances to misalignment. In order to obtain high misalignment tolerances, we propose the use of an active alignment scheme in conjunction with an optimized optical design. The active alignment scheme uses a redundant set of optical links and the active selection of the best link. The optical design maximizes the alignment tolerances between the two boards to /spl plusmn/1 mm of lateral and /spl plusmn/1/spl deg/ of angular misalignment for a target data rate of 1.25 Gb/s.
Design Defects Detection and Correction by Example

Detecting and fixing defects make programs easier to understand by developers. We propose an automated approach for the detection and correction of various types of design defects in source code. Our approach allows to automatically find detection rules, thus relieving the designer from doing so manually. Rules are defined as combinations of metrics/thresholds that better conform to known instances of design defects (defect examples). The correction solutions, a combination of refactoring operations, should minimize, as much as possible, the number of defects detected using the detection rules. In our setting, we use genetic programming for rule extraction. For the correction step, we use genetic algorithm. We evaluate our approach by finding and fixing potential defects in four open-source systems. For all these systems, we found, in average, more than 80% of known defects, a better result when compared to a state-of-the-art approach, where the detection rules are manually or semi-automatically specified. The proposed corrections fix, in average, more than 78%of detected defects.
Volume Rendering for Computational Fluid Dynamics: Initial Results

1.0 Abstract This work describes a direct volume rendering technique adapted for visualization of results from Computational Fluid Dynamics (CFD) flow solvers. The problem is difficult for at least three reasons: (1) the shapes of the grids, (2) v ector as well as scalar data f ields, and (3) the types of features of interest. In addition, the data set sizes are often between ten and one hundred megabytes, which is large even by volume rendering standards. The method, a ray casting implementation, is chosen for its rob ustness and adaptability. The software described here differs from other volume renderers in the handling of vector field data and in the techniques for reducing the time required for intersecting rays with grid cell faces. Vector fields are rendered using mappings from the vector field space to three dimensional color spaces plus opacity. Several mappings are considered and the relati ve merits analyzed. Two techniques for improving the speed of the ordinarily slo w ray casting are described. Future developments and improvements are also discussed.
Design of a gain scheduling photovoltaic energy conversion system

In this paper, a gain scheduling perturbation and observation (P&O) algorithm is proposed to realize the dynamic and rapid maximum power point tracking (MPPT) for a grid-connected photovoltaic energy conversion system (PECS). The hardware implementation of the PECS consists of a 1.5kW (at 500V) monocrystalline silicon photovoltaic (PV) array and a voltage-sourced inverter (VSI) whereby an IGBT-based intelligent power module is applied. In order to reach MPPT, the reference dc-link voltage of the VSI is generated by a command generator based on conventional P&O algorithm. To further improve the performance of the PECS under various daylight irradiations, the control gains for command generator are scheduled according to the gradient of electrical characteristic of the PV array exposed to a daylight irradiation. In contrast to the use of the MPPT algorithm in electrical power conversion, the reactive power compensation is also feasible to improve the power factor for the grid utility under low irradiation and thus increases the facility utilization significantly. The experimental results show that the proposed PECS with gain scheduling P&O algorithm is capable of tracking maximum power point and compensating the reactive power for the grid utility.
Methods and techniques for discovering taxonomies of behavioral process models

Modeling behavioral aspects of business processes is a hard and costly task, which usually requires heavy intervention of business experts. This explains the increasing attention given to process mining techniques, which automatically extract behavioral process models from log data. In the case of complex processes, however, the models identified by classical process mining techniques are hardly useful to analyze business operations at a suitable abstraction level. In fact, the need of process abstraction emerged in several application scenarios, and abstraction methods are already supported in some business‐management platforms, which allow users to manually define abstract views for the process at hand. Therefore, it comes with no surprise that process mining research recently considered the issue of mining processes at different abstraction levels, mainly in the form of a taxonomy of process models, as to overcome the drawbacks of traditional approaches. This paper presents a general framework for the discovery of such a taxonomy, and offers a survey of different kinds of basic techniques that can be exploited to this purpose: (1) workflow modeling and discovery techniques, (2) clustering techniques enabling the discovery of different behavioral process classes, and (3) activity abstraction techniques for associating a generalized process model with each higher level taxonomy node. © 2013 Wiley Periodicals, Inc.
Early olfactory experience induces structural changes in the primary olfactory center of an insect brain

The antennal lobe (AL) is the first olfactory center of the insect brain and is constituted of different functional units, the glomeruli. In the AL, odors are coded as spatiotemporal patterns of glomerular activity. In honeybees, olfactory learning during early adulthood modifies neural activity in the AL on a long‐term scale and also enhances later memory retention. By means of behavioral experiments, we first verified that olfactory learning between the fifth and eighth day of adulthood induces better retention performances at a late adult stage than the same experience acquired before or after this period. We checked that the specificity of memory for the odorants used was improved. We then studied whether such early olfactory learning also induces long‐term structural changes in the AL consistent with the formation of long‐term olfactory memories. We also measured the volume of 15 identified glomeruli in the ALs of 17‐day‐old honeybees that either experienced an odor associated with sucrose solution between the fifth and eighth day of adulthood or were left untreated. We found that early olfactory experience induces glomerulus‐selective increases in volume that were specific to the learned odor. By comparing our volumetric measures with calcium‐imaging recordings from a previous study, performed in 17‐day‐old bees subjected to the same treatment and experimental conditions, we found that glomeruli that showed structural changes after early learning were those that exhibited a significant increase in neural activity. Our results make evident a correlation between structural and functional changes in the AL following early olfactory learning.
Robust Acoustic Speech Feature Prediction From Noisy Mel-Frequency Cepstral Coefficients

This paper examines the effect of applying noise compensation to acoustic speech feature prediction from noisy mel-frequency cepstral coefficient (MFCC) vectors within a distributed speech recognition architecture. An acoustic speech feature (comprising fundamental frequency, formant frequencies, speech/nonspeech classification, and voicing classification) is predicted from an MFCC vector in a maximum a posteriori (MAP) framework using phoneme-specific or global models of speech. The effect of noise is considered and three different noise compensation methods, that have been successful in robust speech recognition, are integrated within the MAP framework. Experiments show that noise compensation can be applied successfully to prediction with best performance given by a model adaptation method that performs only slightly worse than matched training and testing. Further experiments consider application of the predicted acoustic features to speech reconstruction. A series of human listening tests show that the predicted features are sufficient for speech reconstruction and that noise compensation improves speech quality in noisy conditions.
Melanoma Transition Is Frequently Accompanied by a Loss of Cytoglobin Expression in Melanocytes: A Novel Expression Site of Cytoglobin

The tissue distribution and function of hemoglobin or myoglobin are well known; however, a newly found cytoglobin (CYGB), which also belongs to the globin family, remains to be characterized. To assess its expression in human malignancies, we sought to screen a number of cell lines originated from many tissues using northern blotting and real time PCR techniques. Unexpectedly, we found that several, but not all, melanoma cell lines expressed CYGB mRNA and protein at much higher levels than cells of other origins. Melanocytes, the primary origin of melanoma, also expressed CYGB at a high level. To verify these observations, immunostaining and immunoblotting using anti-CYGB antibody were also performed. Bisulfite-modified genomic sequencing revealed that several melanoma cell lines that abrogated CYGB expression were found to be epigenetically regulated by hypermethylation in the promoter region of CYGB gene. The RNA interference-mediated knockdown of the CYGB transcript in CYGB expression-positive melanoma cell lines resulted in increased proliferation in vitro and in vivo. Flow cytometric analysis using 2′-, 7′-dichlorofluorescein diacetate (DCFH-DA), an indicator of reactive oxygen species (ROS), revealed that the cellular ROS level may be involved in the proliferative effect of CYGB. Thus, CYGB appears to play a tumor suppressive role as a ROS regulator, and its epigenetic silencing, as observed in CYGB expression-negative melanoma cell lines, might function as an alternative pathway in the melanocyte-to-melanoma transition.
Particle size and metal composition of gouging and lancing fumes

Abstract Metal gouging and lancing liberate particles of an unknown size and composition. Fumes are formed when vaporized materials condense in air, creating fine and ultrafine particles which can agglomerate. Particle sizes may be <1 µm in diameter. Inhalation of this mixture of metal fumes can lead to adverse health effects. This study characterized fumes by particle size fractions and metal composition. As particles may be in the submicron range, the nano-size fraction was included. Randomized, side-by-side area samples of fumes liberated during gouging and lancing were collected. Samplers included the conductive plastic Institute of Occupational Medicine (IOM) samplers (inhalable fraction), GK2.69 stainless steel thoracic cyclones (thoracic fraction), aluminum respirable cyclones (respirable fraction), Nanoparticle Respiratory Deposition (NRD) samplers (nano-size fraction), and open-face filter cassettes (particle size distribution—PSD). Samplers were mounted at a height of between 1.3 m and 1.7 m, in the worst-case scenario area (down-wind). Forty-six samples were collected during gouging and 26 during lancing. Mass concentrations per fraction ranges (excluding nano-size) were found to be 1.27–17.27 mg/m3 (inhalable), 1.83–13.96 mg/m3 (thoracic) and 0.88–15.82 mg/m3 (respirable) for gouging; and 2.34–5.60 mg/m3 (inhalable), 2.82–4.01 mg/m3 (thoracic), and 1.89–3.24 mg/m3 (respirable) for lancing. PSD analysis confirmed the presence of nano-size particles with a mean size of 171.76 (±56.27) nm during gouging and 32.33 (±7.17) nm during lancing. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis of samples indicated the presence of chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), molybdenum (Mo), nickel (Ni), and tin (Sn) in the respective particle size fractions (including nano-size) of both processes. Negative health effects associated with metal inhalation are well known, while nanoparticles’ unique properties enable them to cause further detrimental health effects. The nano-size fraction should be included in personal exposure assessments and control measures.
Selective attention automatic focus for cognitive crowd monitoring

In most recent Intelligent Video Surveillance systems, mechanisms used to support human decisions are integrated in cognitive artificial processes. Large scale video surveillance networks must be able to analyse a huge amount of information. In this context, a cognitive perception mechanism integrate in an intelligent system could help an operator for focusing his attention on relevant aspects of the environment ignoring other parts. This paper presents a bio-inspired algorithm called Selective Attention Automatic Focus (S2AF), as a part of more complex Cognitive Dynamic Surveillance System (CDSS) for crowd monitoring. The main objective of the proposed method is to extract relevant information needed for crowd monitoring directly from the environmental observations. Experimental results are provided by means of a 3D crowd simulator; they show how by the proposed attention focus method is able to detect densely populated areas.
Applying Internet of Things for personalized healthcare in smart homes

The paper advocates for applying Internet of Things (IoT) for personalized healthcare in smart homes. An IoT architecture is presented which enables such healthcare services. Continuous monitoring of physical parameters and processing of the medical data form the basis of smarter, connected and personalized healthcare. The core functionalities of the IoT architecture are exposed using RESTful web services to the consumers. The main contributions of the paper are: (i) providing a unified approach for discovery, management and interaction with physical devices, (ii) utilizing Machine-to-Machine Measurement (M3) framework to generate high level abstraction from wearable sensors, (iii) combining cross-domain sensor data using M3 and (iv) controlling home automation devices based on health sensor information. Prototype implementations and performance evaluations of the architecture components are discussed.
synASM: A High-Level Synthesis Framework With Support for Parallel and Timed Constructs

This paper presents a high-level synthesis framework called synASM that synthesizes abstract state machines (ASMs) to VHDL for field-programmable gate arrays (FPGAs). In particular, this paper focuses on the specification, scheduling, and synthesis of parallel and timed constructs. ASMs possess well-defined formal semantics for sequential and parallel computation, and their composition. We extend ASMs to support the specification of timing requirements, which we call timed constructs. We also describe the composition of timed constructs with sequential and parallel computation. A key contribution of this paper is the extension of the force-directed scheduling algorithm to support both parallel and timed constructs. We implement the synthesis back-end in synASM that targets FPGAs. Our experiments show improvements of up to 52% in lookup table usage and 34% in total area for certain examples.
Testing and calibration of smart pebble for river bed sediment transport monitoring

The smart pebble (smart particle), SP, has been developed for the past two years to monitor sediment transport in riverbeds. The implementation is based on use of small size and low cost acceleration and angular motion sensors. In this stage, the project is focused on calibrating and testing the final version of the SP as well as its packaging in a 4-cm diameter spherical package. The calibration was done in two stages; individual sensor calibration and complete system calibration. The complete SP unit was tested under linear motions generated by a shake table, and 2D rotational motions using two manually controlled servomotors. Offline digital signal conditioning was done in MATLAB. The preliminary results show that the system has relatively large amplitude error due to low sampling frequency. Experiments conducted by sampling a 1-Hz sinusoidal signal at different rates show that to keep the amplitude error of the system under 5% the sampling rate has to be at least 10 times the maximum bandwidth of the signals acquired from sensors.
Persuasive Technology for Human Development: Review and Case Study

Technology is an extremely potent tool that can be leveraged for human development and social good. Owing to the great importance of environment and human psychology in driving human behavior, and the ubiquity of technology in modern life, there is a need to leverage the insights and capabilities of both fields together for nudging people towards a behavior that is optimal in some sense (personal or social). In this regard, the field of persuasive technology, which proposes to infuse technology with appropriate design and incentives using insights from psychology, behavioral economics, and human-computer interaction holds a lot of promise. Whilst persuasive technology is already being developed and is at play in many commercial applications, it can have the great social impact in the field of Information and Communication Technology for Development (ICTD) which uses Information and Communication Technology (ICT) for human developmental ends such as education and health. In this paper we will explore what persuasive technology is and how it can be used for the ends of human development. To develop the ideas in a concrete setting, we present a case study outlining how persuasive technology can be used for human development in Pakistan, a developing South Asian country, that suffers from many of the problems that plague typical developing country.
DYNAMICAL GENERATION OF THE GAUGED SU(2) LINEAR SIGMA MODEL

The fermion and meson sectors of the quark-level SU(2) linear sigma model are dynamically generated from a meson–quark Lagrangian, with the quark (q) and meson (σ, π) fields all treated as elementary, having neither bare masses nor expectation values. In the chiral limit, the masses are predicted to be mq = fπg, mπ = 0, mσ = 2mq, and we also find that the quark–meson coupling is $g =2\pi /\sqrt{N_c}$, the three-meson coupling is $g' =m_\sigma^2 /2f_\pi =2gm_q$ and the four-meson coupling is λ = 2g2 = g′/fπ, where fπ ≃ 90 MeV is the pion decay constant and Nc = 3 is the color number. By gauging this model one can generate the couplings to the vector mesons ρ and A1, including the quark–vector coupling constant gρ = 2π, gρππ, gA1ρπ and the masses mρ ~ 700 MeV, $m_{A_1}\simeq \sqrt{3} m_\rho$; of course the vector and axial currents remain conserved throughout.
Discrete regression methods on the cone of positive-definite matrices

We consider the problem of fitting a discrete curve to time-labeled data points on the set ‘n of all n-by-n symmetric positive-definite matrices. The quality of a curve is measured by a weighted sum of a term that penalizes its lack of fit to the data and a regularization term that penalizes speed and acceleration. The corresponding objective function depends on the choice of a Riemannian metric on ’n. We consider the Euclidean metric, the Log-Euclidean metric and the affine-invariant metric. For each, we derive a numerical algorithm to minimize the objective function. We compare these in terms of reliability and speed, and we assess the visual appearance of the solutions on examples for n = 2. Notably, we find that the Log-Euclidean and the affine-invariant metrics tend to yield similar—and sometimes identical—results, while the former allows for much faster and more reliable algorithms than the latter.