ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Relational diversity in social portfolios predicts well-being

We document a link between the relational diversity of one's social portfolio-the richness and evenness of relationship types across one's social interactions-and well-being. Across four distinct samples, respondents from the United States who completed a preregistered survey (n = 578), respondents to the American Time Use Survey (n = 19,197), respondents to the World Health Organization's Study on Global Aging and Adult Health (n = 10,447), and users of a French mobile application (n = 21,644), specification curve analyses show that the positive relationship between social portfolio diversity and well-being is robust across different metrics of well-being, different categorizations of relationship types, and the inclusion of a wide range of covariates. Over and above people's total amount of social interaction and the diversity of activities they engage in, the relational diversity of their social portfolio is a unique predictor of well-being, both between individuals and within individuals over time.
SATE: Providing Stable and Agile Adaptation in HTTP-Based Video Streaming

Online video streaming service, such as Youtube and Netflix, is emerging as a killer application that constitutes most IP traffic. Users want high-quality video streaming service; however, network band-width cannot keep up user's demand. In the HTTP-based video streaming technology, the video provider divides the video into multiple chunks, encodes it at various bitrates, and stores it in the media server. The client requests a video chunk using an adaptive bitrate (ABR) algorithm, considering the network conditions. While there are many works to maximize user satisfaction, the state-of-the-art ABR algorithms are still vulnerable to rebuffering due to inaccurate estimates and decisions. To address this problem, we first analyze the real-world traces and find several design inferences for an efficient ABR algorithm. Then, we introduce SATE, an ABR algorithm that provides a stable and agile adaptation even in bandwidth constraint and dramatically changing network conditions. We evaluate the performance of SATE in various network settings and demonstrate its efficacy in practice. SATE provides a stable adaptation and dramatically reduced rebuffering while delivering a similar average bitrate compared to the state-of-the-art ABR algorithms.
A Survey on Wearable Technology: History, State-of-the-Art and Current Challenges

Technology is continually undergoing a constituent development caused by the appearance of billions new interconnected "things"and their entrenchment in our daily lives. One of the underlying versatile technologies, namely wearables, is able to capture rich contextual information produced by such devices and use it to deliver a legitimately personalized experience. The main aim of this paper is to shed light on the history of wearable devices and provide a state-of-the-art review on the wearable market. Moreover, the paper provides an extensive and diverse classification of wearables, based on various factors, a discussion on wireless communication technologies, architectures, data processing aspects, and market status, as well as a variety of other actual information on wearable technology. Finally, the survey highlights the critical challenges and existing/future solutions.
Wireless Power Transmission for Power Supply: State of Art

The wireless power supply is motivated by simple and comfortable use of many small electric appliances with low power input. This paper reviews the concepts that are suitable for wireless power transmission with respect to power supply of such appliances in small areas. The categorization of the concepts is made. The efficiency of the concepts is discussed on general base. The reference levels for exposure to electric and magnetic fields are mentioned, and maximal power delivered to an appliance by fulfillment of these levels is considered.
Current Issues within the Perinatal Mental Health Care System in Aichi Prefecture, Japan: A Cross-Sectional Questionnaire Survey

Mental illnesses commonly occur in the reproductive age. This study aimed to identify the issues that exist within the perinatal mental health care system. A cross-sectional survey was conducted in Aichi Prefecture in central Japan. Questionnaires on the situation between 2016 and 2018 were mailed to the head physicians of 128 maternity care units, 21 neonatal intensive care units (NICUs), and 40 assisted reproductive technology (ART) units. A total of 82 (52.6 per 100,000 births) women were admitted to mental health care units during the perinatal period, and 158 (1.0 per 1000 births) neonates born to mothers with mental illness were admitted to NICUs. Approximately 40% of patients were hospitalized in psychiatric hospitals without maternity care units. Eighty-four (71.1%) and 76 (64.4%) maternity care units did not have psychiatrists or social workers, respectively. Moreover, 20-35% of the head physicians in private clinics, general hospitals, and ART units endorsed the discontinuation of psychotropic drug use during pregnancy. However, the corresponding figures were only 5% among those in maternal-fetal centers. Resources for perinatal mental illness might be limited. Perspectives on psychotropic drug use differed based on the type of facilities where the doctors were working.
Toward Compact ConvNets via Structure-Sparsity Regularized Filter Pruning

The success of convolutional neural networks (CNNs) in computer vision applications has been accompanied by a significant increase of computation and memory costs, which prohibits their usage on resource-limited environments, such as mobile systems or embedded devices. To this end, the research of CNN compression has recently become emerging. In this paper, we propose a novel filter pruning scheme, termed structured sparsity regularization (SSR), to simultaneously speed up the computation and reduce the memory overhead of CNNs, which can be well supported by various off-the-shelf deep learning libraries. Concretely, the proposed scheme incorporates two different regularizers of structured sparsity into the original objective function of filter pruning, which fully coordinates the global output and local pruning operations to adaptively prune filters. We further propose an alternative updating with Lagrange multipliers (AULM) scheme to efficiently solve its optimization. AULM follows the principle of alternating direction method of multipliers (ADMM) and alternates between promoting the structured sparsity of CNNs and optimizing the recognition loss, which leads to a very efficient solver (2.5x to the most recent work that directly solves the group sparsity-based regularization). Moreover, by imposing the structured sparsity, the online inference is extremely memory-light since the number of filters and the output feature maps are simultaneously reduced. The proposed scheme has been deployed to a variety of state-of-the-art CNN structures, including LeNet, AlexNet, VGGNet, ResNet, and GoogLeNet, over different data sets. Quantitative results demonstrate that the proposed scheme achieves superior performance over the state-of-the-art methods. We further demonstrate the proposed compression scheme for the task of transfer learning, including domain adaptation and object detection, which also show exciting performance gains over the state-of-the-art filter pruning methods.
Single-cell analysis of skeletal muscle macrophages reveals age-associated functional subpopulations

Tissue-resident macrophages represent a group of highly responsive innate immune cells that acquire diverse functions by polarizing toward distinct subpopulations. The subpopulations of macrophages that reside in skeletal muscle (SKM) and their changes during aging are poorly characterized. By single-cell transcriptomic analysis with unsupervised clustering, we found 11 distinct macrophage clusters in male mouse SKM with enriched gene expression programs linked to reparative, proinflammatory, phagocytic, proliferative, and senescence-associated functions. Using a complementary classification, membrane markers LYVE1 and MHCII identified four macrophage subgroups: LYVE1-/MHCIIhi (M1-like, classically activated), LYVE1+/MHCIIlo (M2-like, alternatively activated), and two new subgroups, LYVE1+/MHCIIhi and LYVE1-/MHCIIlo. Notably, one new subgroup, LYVE1+/MHCIIhi, had traits of both M2 and M1 macrophages, while the other new subgroup, LYVE1-/MHCIIlo, displayed strong phagocytic capacity. Flow cytometric analysis validated the presence of the four macrophage subgroups in SKM and found that LYVE1- macrophages were more abundant than LYVE1+ macrophages in old SKM. A striking increase in proinflammatory markers (S100a8 and S100a9 mRNAs) and senescence-related markers (Gpnmb and Spp1 mRNAs) was evident in macrophage clusters from older mice. In sum, we have identified dynamically polarized SKM macrophages and propose that specific macrophage subpopulations contribute to the proinflammatory and senescent traits of old SKM.
Epilepsy and innate immune system: A possible immunogenic predisposition and related therapeutic implications

Recent experimental studies and pathological analyses of patient brain tissue samples with refractory epilepsy suggest that inflammatory processes and neuroinflammation plays a key-role in the etiopathology of epilepsy and convulsive disorders. These inflammatory processes lead to the secretion of pro-inflammatory cytokines responsible for blood-brain-barrier disruption and involvement of resident immune cells in the inflammation pathway, occurring within the Central Nervous System (CNS). These elements are produced through activation of Toll-Like Receptors (TLRs) by exogenous and endogenous ligands thereby increasing expression of cytokines and co-stimulatory molecules through the activation of TLRs 2, 3, 4, and 9 as reported in murine studies.It has been demonstrated that IL-1β intracellular signaling and cascade is able to alter the neuronal excitability without cell loss. The activation of the IL-1β/ IL-1β R axis is strictly linked to the secretion of the intracellular protein MyD88, which interacts with other cell surface receptors, such as TLR4 during pathogenic recognition. Furthermore, TLR-signaling pathways are able to recognize molecules released from damaged tissues, such as damage-associated molecular patterns/proteins (DAMPs). Among these molecules, High-mobility group box-1 (HMGB1) is a component of chromatin that is passively released from necrotic cells and actively released by cells that are subject to profound stress. Moreover, recent studies have described models of epilepsy induced by the administration of bicuculline and kainic acid that highlight the nature of HMGB1-TLR4 interactions, their intracellular signaling pathway as well as their role in ictiogenesis and epileptic recurrence.The aim of our review is to focus on different branches of innate immunity and their role in epilepsy, emphasizing the role of immune related molecules in epileptogenesis and highlighting the research implications for novel therapeutic strategies.
Novel One-Dimensional Sampling Method to Calculate Two-Dimensional Diamond-Shaped Discrete Frequency Distributions

A novel 1-D sampling method is proposed to calculate 2-D diamond-shaped discrete frequency distributions, which are often treated in the harmonic balance method. The proposed method fills up the entire 2-D discrete frequency plane with diamond-shaped rhombic tiles and makes the number of sampling points equal to that of the necessary frequency components.
Low Complexity VLSI Architecture Design Methodology for Wigner Ville Distribution

In this brief, we propose a low complexity VLSI architecture design Methodology for Wigner Ville Distribution (WVD) computation. The proposed methodology performs both auto and cross WVD computations using only the half number of Fast Fourier transform (FFT) computations as opposed to the state of the art methodologies. The FPGA implementation for proposed methodology was performed for 16 bit fixed point and 32 bit single precision floating point numbers on the Xilinx Virtex-7 FPGA (XC7vx485tffg). The proposed methodology saves 49% energy consumption when compared with the state of the art methodology. However it can be noted that the proposed methodology is independent of the VLSI implementation platform and technology node.
Tracking fiducial markers with discriminative correlation filters

In the last few years, squared fiducial markers have become a popular and efficient tool to solve monocular local-ization and tracking problems at a very low cost. Nevertheless, marker detection is affected by noise and blur: small camera movements may cause image blurriness that prevents marker detection. The contribution of this paper is two-fold. First, it proposes a novel approach for estimating the location of markers in images using a set of Discriminative Correlation Filters (DCF). The proposed method outperforms state-of-the-art methods for marker detection and standard DCFs in terms of speed, precision, and sensitivity. Our method is robust to blur and scales very well with image resolution, obtaining more than 200fps in HD im-ages using a single CPU thread. As a second contribution, this paper proposes a method for camera localization with marker maps employing a predictive approach to detect visible markers with high precision, speed, and robustness to blurriness. The method has been compared to the state-of-the-art SLAM methods obtaining, better accuracy, sensitivity, and speed. The proposed approach is publicly available as part of the ArUco library. (c) 2020 Elsevier B.V. All rights reserved.
Recognizing shipbuilding parts using artificial neural networks and Fourier descriptors

A pattern recognition system is described for recognizing shipbuilding parts using artificial neural networks and Fourier descriptors. The system uses shape contour information that is invariant of size, translation, and rotation. Fourier descriptors provide information, and the neural networks make decisions about the shapes. A brief review of the current state of the art is included, and results from testing show that the system distinguished between various shapes and proved to be a valid approach.
Nonrigid Registration of Joint Histograms for Intensity Standardization in Magnetic Resonance Imaging

A major disadvantage of magnetic resonance imaging (MRI) compared to other imaging modalities like computed tomography is the fact that its intensities are not standardized. Our contribution is a novel method for MRI signal intensity standardization of arbitrary MRI scans, so as to create a pulse sequence dependent standard intensity scale. The proposed method is the first approach that uses the properties of all acquired images jointly (e.g., T1- and T2-weighted images). The image properties are stored in multidimensional joint histograms. In order to normalize the probability density function (pdf) of a newly acquired data set, a nonrigid image registration is performed between a reference and the joint histogram of the acquired images. From this matching a nonparametric transformation is obtained, which describes a mapping between the corresponding intensity spaces and subsequently adapts the image properties of the newly acquired series to a given standard. As the proposed intensity standardization is based on the probability density functions of the data sets only, it is independent of spatial coherence or prior segmentations of the reference and current images. Furthermore, it is not designed for a particular application, body region or acquisition protocol. The evaluation was done using two different settings. First, MRI head images were used, hence the approach can be compared to state-of-the-art methods. Second, whole body MRI scans were used. For this modality no other normalization algorithm is known in literature. The Jeffrey divergence of the pdfs of the whole body scans was reduced by 45%. All used data sets were acquired during clinical routine and thus included pathologies.
Safety evaluation of the food enzyme β-galactosidase from the non-genetically modified Neobacillus sp. strain AE-LT

The food enzyme β-galactosidase (EC 3.2.1.23) is produced with the non-genetically modified Neobacillus sp. strain AE-LT by Amano Enzyme Inc. The strain is not cytotoxic and does not harbour any known virulence factor or antimicrobial resistance gene. The presence of viable cells of the production strain in the food enzyme could not be excluded, but the likelihood of this being a hazard is considered low. The food enzyme is intended to be used for lactose hydrolysis in milk processing and the manufacture of galacto-oligosaccharides (GOS). The dietary exposure to the food enzyme-total organic solids (TOS) was estimated to be up to 2.971 mg TOS/kg body weight (bw) per day in European populations. Genotoxicity tests did not raise a safety concern. The systemic toxicity was assessed by means of a repeated dose 90-day oral toxicity study in rats. The Panel identified a no observed adverse effect level of 1,223 mg TOS/kg bw per day, the highest dose tested, which when compared with the estimated dietary exposure, results in a margin of exposure of at least 412. A search for similarity of the amino acid sequence of the food enzyme to known allergens was made and no match was found. The Panel considered that, under the intended conditions of use, the risk of allergic reactions by dietary exposure cannot be excluded, but the likelihood for this to occur is low. Based on the data provided, the Panel concluded that this food enzyme does not give rise to safety concerns under the intended conditions of use.
Reconstitution of Human Cytomegalovirus-Specific CD4+ T Cells is Critical for Control of Virus Reactivation in Hematopoietic Stem Cell Transplant Recipients but Does Not Prevent Organ Infection

The relative contribution of human cytomegalovirus (HMCV)-specific CD4(+) and CD8(+) T cells to the control of HCMV infection in hematopoietic stem cell transplant (HSCT) recipients is still controversial. HCMV reactivation and HCMV-specific CD4(+) and CD8(+) T cell reconstitution were monitored for 1 year in 63 HCMV-seropositive patients receiving HSCT. HCMV reactivation was detected in all but 2 patients. In 20 of 63 (31.7%) patients (group 1) HCMV infection resolved spontaneously, whereas 32 of 63 (50.8%) patients (group 2) controlled the infection after a single short-course of pre-emptive therapy and the remaining 9 (14.3%) patients (group 3) suffered from relapsing episodes of HCMV infection, requiring multiple courses of antiviral therapy. The kinetics and magnitude of HCMV-specific CD8(+) T cell reconstitution were comparable among the 3 groups, but HCMV-specific CD4(+) T cells were lower in number in patients requiring antiviral treatment. HCMV-seronegative donors, as well as unrelated donors (receiving antithymocyte globulin) and acute graft-versus-host disease (GVHD) were associated with both delayed HCMV-specific CD4(+) T cell reconstitution and severity of infection. Conversely, these risk factors had no impact on HCMV-specific CD8(+) T cells. Eight patients with previous GVHD suffered from HCMV gastrointestinal disease, although in the presence of HCMV-specific CD4(+) and CD8(+) systemic immunity and undetectable HCMV DNA in blood. Reconstitution of systemic HCMV-specific CD4(+) T cell immunity is required for control of HCMV reactivation in adult HSCT recipients, but it may not be sufficient to prevent late-onset organ localization in patients with GVHD. HCMV-specific CD8(+) T cells contribute to control of HCMV infection, but only after HCMV-specific CD4(+) T cell reconstitution.
Early life exposure to chronic unpredictable stress induces anxiety-like behaviors and increases the excitability of cerebellar neurons in zebrafish

Anxiety is a common emotional disorder in children. To understand its underlying mechanisms, chronic unpredictable stress (CUS) has been established as a stress model in zebrafish. By using the tall tank test, the stress response reliability could be improved in adult fish which has not been confirmed in larvae. In addition, the increasing evidences have shown that cerebellum plays important roles in anxiety. Whether CUS will affect cerebellar neuronal activity remains unknown. We found that CUS exposure to larvae (from 10 to 17 days post fertilization) induced anxiety-like behaviors and social cohesion impairments within 1-2 d after CUS, including a prolonged freezing time, an increased time spent at the bottom of tank, an increased thigmotaxis index, and an increased interindividual distance. Our results showed that the four behavioral tests were homogeneous, especially the tall tank test either anxiety-like behaviors or the basal locomotion. Furthermore, we found that CUS enhanced the excitability of cerebellar neurons, as the amplitude, frequency, time to peak and half-width of spontaneous firing significantly decreased, as well as the amplitude of excitatory post-synaptic current when compared with the control group. CUS also activated hyperpolarization-activated cyclic nucleotide-gated and potassium channels of cerebellar neurons. Multiple linear regression analysis showed that the total distance in bottom (tall tank test) was correlated positively with outward Na+-K+ currents (r = 0.848, P = 0.016), and the thigmotaxis index (open field test) correlated with action potential amplitude (r = 0.854, P = 0.030). Altogether, early life CUS transiently induced an anxiety-like behavior which could be more accurately assessed by combining the tall tank test with other behavior tests in young zebrafish. CUS increased the excitability of cerebellar neurons might provide new targets to treat emotional diseases such as anxiety.
Current and prognostic overview on the strategic exploitation of anaerobic digestion and digestate: A review

The depletion of fossil fuels and increasing demand for energy are encountered by generating renewable biogas. Anaerobic digestion (AD) produces not only biogas, also other value-added products from the digestate using various organic, municipal and industrial wastes which have several benefits like remediating waste, reduces greenhouse gas emissions, renewable energy generation and securing socio-economic status of bio-based industries. This review work critically analyzes the biorefinery approaches on AD process for the production of biogas and digestate, and their direct and indirect utilization. The left-out residue obtained from AD is called 'digestate' which enriched with organic matter, nitrogen, heavy metals and other valuable micronutrients. However, the direct disposal of digestate to the land as fertilizer/landfills creates various environmental issues. Keeping this view, the digestate should be upgraded or transformed into high valued products such as biofertilizer, pyrochar, biodiesel, syngas and soil conditioner that can aid to enrich the soil nutrients and ensures the safe environment as well. In this context, the present review focused to illustrate the current techniques and different strategic exploitations on AD proper management of digestate products for storage and further applications. Such a technology transfer provides a proven strategic mechanism towards the enhancement of the sustainability of bio-based industries, attaining the energy demand, safest waste management, protection of environment and reduces the socio-economic issues of the industrial sector.