Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of wearable rectangular textile antenna and investigation of its performance under bent condition at different angles

In recent years, a growing interest in flexible electronic devices has been the origin of the formation of extensive research in providing the best method for the production of these tools. In this context, manufacturing of flexible textile antennas due to opportunities to integrate unique technical attributes with their applications is highly regarded by researchers. Therefore, in this paper, using inkjet printing technology with textiles and subsequently reducing it by metal nanoparticles with various deposition techniques to develop micro-layers of fabric has been suggested. It is anticipated that this method can produce electrically conductive textiles with flexibility and signal transmission in different wavelengths. According to the method in this article, after primary preparation of polyester fabric, it will print active materials with different designs at suitable operating conditions and then it will enter into the nickel electroless bath. The antenna having a conductive nickel fabric as ground plane was tested at different angles than receivers. That indicating zero degree angle relative to a line perpendicular to the surface of the antenna has the gain equal to −5.34 dB, because most of the antenna radiation field is perpendicular to the surface of the antenna. The most unsuitable degree is 90° angle, which is equal to −14.59 dB and shows that radiation from the sides of the antenna does not occur.
HDPE/Chitosan Blends Modified with Organobentonite Synthesized with Quaternary Ammonium Salt Impregnated Chitosan

In this study, blends based on a high density polyethylene (HDPE) and chitosan (CS) were successfully prepared by melt processing, in a laboratory internal mixer. The CS biopolymer content effect (up to maximum of 40%), and, the addition of bentonite clay modified with quaternary ammonium salt (CTAB) impregnated chitosan as a compatibilizing agent, on the properties of the blends was analyzed by Fourier transform-infrared spectroscopy (FT-IR), wide angle X-ray diffraction (WAXD), differential scanning calorimetry (DSC), thermogravimetric analyses (TG), tensile strength, and scanning electron microscopy (SEM). The use of clay modified with CTAB impregnated chitosan, employing a method developed here, improved the compatibility of HDPE with chitosan, and therefore the thermal and some of the mechanical properties were enhanced, making HDPE/chitosan blends suitable candidates for food packaging. It was possible to obtain products of synthetic polymer, HDPE, with natural polymer, chitosan, using a method very used industrially, with acceptable and more friendly properties to the environment, when compared to conventional synthetic polymers. In addition, due to the possibility of impregnated chitosan with quaternary ammonium salt exhibit higher antibacterial activity than neat chitosan, the HDPE/chitosan/organobentonite blends may be potentially applied in food containers to favor the preservation of food for a longer time in comparison to conventional materials.
Interaction platform-orientated perspective in designing novel applications

The lack of HCI offerings in the invention of novel software applications and the bias of design knowledge towards desktop GUI make it difficult for us to design for novel scenarios and applications that leverage emerging computational technologies. These include new media platforms such as mobiles, interactive TV, tabletops and large multi-touch walls on which many of our future applications will operate. We argue that novel application design should come not from user-centred requirements engineering as in developing a conventional application, but from understanding the interaction characteristics of the new platforms. Ensuring general usability for a particular interaction platform without rigorously specifying envisaged usage contexts helps us to design an artifact that does not restrict the possible application contexts and yet is usable enough to help brainstorm its more exact place for future exploitation.
Coenzyme A–mediated degradation of pyruvate dehydrogenase kinase 4 promotes cardiac metabolic flexibility after high-fat feeding in mice

Cardiac energy is produced primarily by oxidation of fatty acids and glucose, with the relative contributions of each nutrient being sensitive to changes in substrate availability and energetic demand. A major contributor to cardiac metabolic flexibility is pyruvate dehydrogenase (PDH), which converts glucose-derived pyruvate to acetyl-CoA within the mitochondria. PDH is inhibited by phosphorylation dependent on the competing activities of pyruvate dehydrogenase kinases (PDK1–4) and phosphatases (PDP1–2). A single high-fat meal increases cardiac PDK4 content and subsequently inhibits PDH activity, reducing pyruvate utilization when abundant fatty acids are available. In this study, we demonstrate that diet-induced increases in PDK4 are reversible and characterize a novel pathway that regulates PDK4 degradation in response to the cardiac metabolic environment. We found that PDK4 degradation is promoted by CoA (CoASH), the levels of which declined in mice fed a high-fat diet and normalized following transition to a control diet. We conclude that CoASH functions as a metabolic sensor linking the rate of PDK4 degradation to fatty acid availability in the heart. However, prolonged high-fat feeding followed by return to a low-fat diet resulted in persistent in vitro sensitivity of PDH to fatty acid–induced inhibition despite reductions in PDK4 content. Moreover, increases in the levels of proteins responsible for β-oxidation and rates of palmitate oxidation by isolated cardiac mitochondria following long-term consumption of high dietary fat persisted after transition to the control diet. We propose that these changes prime PDH for inhibition upon reintroduction of fatty acids.
Emergence of rmtC and rmtF 16S rRNA methyltransferase in clinical isolates of Pseudomonas aeruginosa

Occurrence of aminoglycoside (AG) resistance in clinical isolates of Pseudomonas aeruginosa is investigated in this study. Antimicrobial susceptibility test and minimum inhibitory concentration (MIC) for amikacin and gentamicin were performed followed by polymerase chain reaction amplifications of AG modifying enzyme genes (aac(6´)-I, aac(6´)-II, aac(3)-II/VI, ant(2´´)-I, aph(3´)-VI) and 16S methylases (rmtA-D, rmtF and armA). MIC50and MIC90were 64, 128 and > 256, >256 for amikacin and gentamicin, respectively. Four types of genes (aac(6´)-I, aac(3)-II/VI, ant(2´´)-I and aph(3´)-VI) were found in 53 (57.6%) isolates. ant(2´´)-I was the most predominant gene (28 isolates) followed by aac(6´)-I (23 isolates). Nineteen (20.6%) isolates were positive for 16S RMTases (rmtB, rmtC, rmtF and armA) and two isolates co-harboured rmtB + rmtC + rmtF.
Computational advances in sparse L1-norm principal-component analysis of multi-dimensional data

We consider the problem of extracting a sparse Li-norm principal component from a data matrix X ∊ R<sup>D×N</sup> of N observation vectors of dimension D. Recently, an optimal algorithm was presented in the literature for the computation of sparse L<inf>1</inf>-norm principal components with complexity O(N<sup>S</sup>) where S is the desired sparsity. In this paper, we present an efficient suboptimal algorithm of complexity O(N<sup>2</sup>(N + D)). Extensive numerical studies demonstrate the near-optimal performance of the proposed algorithm and its strong resistance to faulty measurements/outliers in the data matrix.
Long-term effects of stimulant treatment on ADHD symptoms, social–emotional functioning, and cognition

Abstract Background Methodological and ethical constraints have hampered studies into long-term lasting outcomes of stimulant treatment in individuals with attention-deficit/hyperactivity disorder (ADHD). Lasting effects may be beneficial (i.e. improved functioning even when treatment is temporarily ceased) or detrimental (i.e. worse functioning while off medication), but both hypotheses currently lack empirical support. Here we investigate whether stimulant treatment history predicts long-term development of ADHD symptoms, social–emotional functioning or cognition, measured after medication wash-out. Methods ADHD symptoms, social–emotional functioning and cognitive test performance were measured twice, 6 years apart, in two ADHD groups (stimulant-treated versus not stimulant-treated between baseline and follow-up). Groups were closely matched on baseline clinical and demographic variables (n = 148, 58% male, age = 11.1). A matched healthy control group was included for reference. Results All but two outcome measures (emotional problems and prosocial behaviour) improved between baseline and follow-up. Improvement over time in the stimulant-treated group did not differ from improvement in the not stimulant-treated group on any outcome measure. Conclusions Stimulant treatment is not associated with the long-term developmental course of ADHD symptoms, social–emotional functioning, motor control, timing or verbal working memory. Adolescence is characterised by clinical improvement regardless of stimulant treatment during that time. These findings are an important source to inform the scientific and public debate.
Greedy phase retrieval with reference points and bounded sparsity

The phase retrieval problem of recovering a data vector from the squared magnitude of its Fourier transform in general can not be solved uniquely, since the magnitude of the Fourier transform is invariant to a global phase shift, cyclic spatial shift and the conjugate reversal of the signal. We discuss a method of introducing reference points in the signal to resolve aforementioned ambiguities. After specifying requirements for these reference points we present a modification of the GESPAR algorithm to solve the obtained problem.
Repellents Inhibit P450 Enzymes in Stegomyia (Aedes) aegypti

The primary defence against mosquitoes and other disease vectors is often the application of a repellent. Despite their common use, the mechanism(s) underlying the activity of repellents is not fully understood, with even the mode of action of DEET having been reported to be via different mechanisms; e.g. interference with olfactory receptor neurones or actively detected by olfactory receptor neurones on the antennae or maxillary palps. In this study, we discuss a novel mechanism for repellence, one of P450 inhibition. Thirteen essential oil extracts from Colombian plants were assayed for potency as P450 inhibitors, using a kinetic fluorometric assay, and for repellency using a modified World Health Organisation Pesticide Evaluations Scheme (WHOPES) arm-in cage assay with Stegomyia (Aedes) aegypti mosquitoes. Bootstrap analysis on the inhibition analysis revealed a significant correlation between P450-inhibition and repellent activity of the oils.
Vehicle boundary improvement and passing vehicle detection in driver assistance by flow distribution

Research in advanced driver assistance system (ADAS) is an important step towards achieving the goal of autonomous intelligent vehicle. Vehicle detection and its distance estimation is an important solution of ADAS for forward collision warning applications. Partial occlusions of passing vehicles makes their detections tedious yet the accuracy of vehicle detection in all its forms in the scene and their corresponding distance estimation is a vital factor to deploy the solution. A small deviation in detection and distance accuracy could end up in a greater mishap in ADAS and AV (Autonomous Vehicle). The proposed framework addresses the aforementioned problems of detection of passing vehicles and perfecting distance measurement by accurate lower bound estimation through Inter and Intra-Frame Flow Correspondence (I2F2C). The proposed generic framework of 12F2C could be employed as a plug-in for the existing machine learning (ML) [1]/ deep learning (DL) [2] based algorithms for improving accuracy of distance estimation of vehicles and also improve accuracy and performance of passing vehicle detection with a detailed mathematical model of motion confidence.
2 Epidemiology of Erectile Dysfunction

Erectile dysfunction (ED) is a highly prevalent condition among men all over the world. It has a significant negative impact on the quality of life of the patients and their partners. Its prevalence and incidence are associated with aging as well as important comorbidities, such as cardiovascular disease, diabetes, metabolic syndrome, hyperlipidemia, depression, pelvic surgery, side effects of medications, neurological disorders, trauma, symptoms of benign prostate hyperplasia, and psychological and interpersonal problems. Furthermore, lifestyle choices of major public health impact are also associated with ED. These include preventable causes of disease such as obesity, smoking, alcohol abuse, and sedentary lifestyle. Recent studies have revealed that ED is not only a correlate of cardiovascular disease, diabetes, and metabolic syndrome; it is rather an early warning symptom. Studies on treatment-seeking behavior revealed significant barriers to seeking treatment for this condition and its important correlates.
An Efficient Chaotic Image Encryption Algorithm Based on Self-adaptive Model and Feedback Mechanism

In recent years, image encryption algorithms have been developed rapidly in order to ensure the security of image transmission. With the assistance of our previous work, this paper proposes a novel chaotic image encryption algorithm based on self-adaptive model and feedback mechanism to enhance the security and improve the efficiency. Different from other existing methods where the permutation is performed by the self-adaptive model, the initial values of iteration are generated in a novel way to make the distribution of initial values more uniform. Unlike the other schemes which is on the strength of the feedback mechanism in the stage of diffusion, the piecewise linear chaotic map is first introduced to produce the intermediate values for the sake of resisting the differential attack. The security and efficiency analysis has been performed. We measure our scheme through comprehensive simulations, considering key sensitivity, key space, encryption speed, and resistance to common attacks, especially differential attack.
Freeze-deicing salt resistance of concrete

A new AS type of salt-scaling resistant admixture was prepared to improve the freeze-deicing salt resistance of concrete.The deicing salt scaling resistance of 3 kinds of concrete were investigated according to CDF test-test method for the freeze-thaw resistance of concrete-tests with sodium chloride solution.The results show that after brushing the AS admixture,the scaled mass of 3 kinds of concrete with water-cement ratio 0.40,0.36 and 0.32 were only 0.09%~0.07% of those of concrete without AS admixture after 56 freeze-thaw cycles,and the reduction was more than 99%,and the loss rate of dynamic elastic modulus of concrete with AS admixture was reduced by 79% to 86% of that of concrete.SEM observations demonstrated that the AS salt-scaling resistant admixture distinctly restrain the formation of cubic NaCl crystals and micro-cracks inside concrete.Compared with reducing the water-cement ratio,adding the air-entraining agent and the mineral admixture the AS salt-scaling resistant admixture improves significantly the freeze-deicing salt resistance of concrete,being in favor of its application in cold regions.
Développement d'un outil d'évaluation performantielle des réglementations incendie en France et dans les pays de l'Union Européenne. (Development of a performantial evaluation tool for fire regulations in France and the countries of the European union)

In order to facilitate the engineers task of evaluating the fire safety level, and to allow the specialists involved in the field to use their preferred languages and tools, we propose to create a language dedicated to the field of fire safety, which automatically generates a simulation, taking into account the specific languages used by the specialists involved in the field. This DSL requires the definition, the formalization, the composition and the integration of several models, regardig to the specific languages used by the specialists involved in the field. The specific language dedicated to the field of fire safety is designed by composing and integrating several other DSLs described by technical and natural languages (as well as natural languages referring to technical ones). These latter are modeled in a way that their components must be precise and based on mathematical foundations, in order to verify the consistency of the system (people and materials are safe) before it implementation. In this context, we propose to adopt a formal approach, based on algebraic specifications, to formalize the languages used by the specialists involved in the generation system, focusing on both syntaxes and semantics of the dedicated languages. In the algebraic approach, the concepts of the domain are abstracted by data types and the relationships between them. The semantics of specific languages is described by the relationships, the mappings between the defined data types and their properties. The simulation language is based on a composition of several specific DSLs previously described and formalized. The DSLs are implemented based on the concepts of functional programming and the Haskell functional language, well adapted to this approach. The result of this work is a software dedicated to the automatic generation of a simulation, in order to facilitate the evaluation of the fire safety level to the engineers. This tool is the property of the Scientific and Technical Center for Building (CSTB), an organization whose mission is to guarantee the quality and safety of buildings by combining
Brain-Inspired technologies: Towards chips that think?

The advent of the Internet-of-Things has introduced a new paradigm that supports a decentralized and hierarchical communication architecture, where a great deal of analytics processing occurs at the edge and at the end-devices instead of in the Cloud. To map the embedded-systems requirements, we present a holistic research approach to the development of low-power architectures inspired by the human brain, where process development and integration, circuit design, system architecture, and learning algorithms are simultaneously optimized. This paper is organized as follows: We begin with a survey of recent research on the human brain and a historical perspective of cognitive neuroscience. Then, artificial intelligence is introduced, and the challenges of Deep Learning systems (in terms of power requirements) are addressed. The key reasons to distribute intelligence over the whole network are discussed. To emphasize the need for low-power solutions, a quantitative benchmark of existing specialized edge platforms that can execute machine-learning algorithms on conventional embedded hardware is presented. The primary focus of this paper will be on the implementation of optimized neuromorphic hardware as a highly promising solution for future ultra-low-power cognitive systems. We show that emerging technologies (such as advanced CMOS, 3D technologies, emerging resistive memories, and Silicon photonics), coupled with novel brain-inspired paradigms, such as spike-coding and spike-time-dependent-plasticity, have extraordinary potential to provide intelligent features in hardware, approaching the way knowledge is created and processed in the human brain. Finally, we conclude with our vision of the enabled future disruptive applications and a discussion of the main challenges which should be tackled to exploit the full potential of brain-inspired technologies.
A heavy-tailed levy distribution for despeckling ultrasound image

A new homomorphic approached, Bayesian based, filter is proposed for de-noising ultrasound image. The presence of speckle noise degrades the quality and detail structure in ultrasound image. This reduces the signal-to-noise ratio in ultrasound image. A heavy-tailed Levy probability distribution function (PDF) is used to model the wavelet coefficients. The noise variance is estimated by exploiting the orthogonal property of wavelet transform. A Bayesian Minimum Mean Absolute Error (MMAE) estimator is used to estimate the noise free wavelet coefficients. The proposed method in this paper is able to reduce the speckle noise and improves the image assessment and visual evaluation. Quality and performance parameters such as Peak Signal to Noise Ratio (PSNR), Structural similarity index (SSIM) and Correlation coefficient (CoC) are used to evaluate the effectiveness of the proposed method. The improvement of PSNR, SSIM and CoC is 10.11%, 1.5% and 0.4% than the standard wavelet based technique.
Epigenomic and genomic landscape of Drosophila melanogaster heterochromatic genes

Heterochromatin is associated with transcriptional repression. In contrast, several genes in the pericentromeric regions of Drosophila melanogaster are dependent on this heterochromatic environment for their expression. Heterochromatic genes encode proteins involved in various developmental processes. Several studies have shown that a variety of epigenetic modifications is associated with these genes. Here we present a comprehensive analysis of the epigenetic landscape of heterochromatic genes across all the developmental stages of Drosophila using the available histone modification and expression data from modENCODE. We find that heterochromatic genes exhibit combinations of active and inactive histone marks that correspond to their level of expression during development. Thus, we classified these genes into three groups based on the combinations of histone modifications present. We also looked for potential regulatory DNA sequence elements in the genomic neighborhood of these genes. Our results show that Nuclear Matrix Associated Regions (MARs) are prominently present in the intergenic regions of heterochromatic genes during embryonic stages suggesting their plausible role in pericentromeric genome organization. We also find that the intergenic sequences in the heterochromatic regions have binding sites for transcription factors known to modulate epigenetic status. Taken together, our meta-analysis of the various genomic datasets suggest that the epigenomic and genomic landscape of the heterochromatic genes are distinct from that of euchromatic genes. These features could be contributing to the unusual regulatory status of the heterochromatic genes as opposed to the surrounding heterochromatin, which is repressive in nature.
Diagnosis of lethal or prenatal‐onset autosomal recessive disorders by parental exome sequencing

Rare genetic disorders resulting in prenatal or neonatal death are genetically heterogeneous, but testing is often limited by the availability of fetal DNA, leaving couples without a potential prenatal test for future pregnancies. We describe our novel strategy of exome sequencing parental DNA samples to diagnose recessive monogenic disorders in an audit of the first 50 couples referred.
The influence of barefoot and shod running on Triceps-surae muscle strain characteristics

The aim of the current investigation was to determine the effects of barefoot and shod running on the kinematics of the Triceps-Surae muscle group. Twelve male participants ran at 4.0 m.s-1 (± 5%) in both barefoot and shod conditions. Kinematics were measured using an eight-camera motion analysis system. Muscle kinematics from the lateral Gastrocnemius, medial Gastrocnemius and Soleus were obtained using musculoskeletal modelling software (Opensim v3.2). The results showed that muscle strain for the lateral Gastrocnemius (barefoot = 1.10 & shod = 0.33 %), medial Gastrocnemius (barefoot = 1.07 & shod = 0.32 %) and Soleus (barefoot = 3.43 & shod = 2.18 %) were significantly larger for the barefoot condition. Given the proposed association between the extent of muscle strain and the etiology of chronic muscle strain pathologies, the current investigation shows that running barefoot may place runners at greater risk from Triceps-Surae strain injuries.