ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Unmatched Case-Control Study on Late Presentation of HIV Infection in Santiago, Cape Verde (2004-2011)

Access to free antiretroviral therapy (ART) in Sub-Saharan Africa has been steadily increasing over the past decade. However, the success of large-scale ART programmes depends on timely diagnosis and early initiation of HIV care. This study characterizes late presenters to HIV care in Santiago (Cape Verde) between 2004 and 2011, and identifies factors associated with late presentation for care. We defined late presentation as persons presenting to HIV care with a CD4 count below 350 cells/mm(3). An unmatched case-control study was conducted using socio-demographic and behavioural data of 368 individuals (191 cases and 177 controls) collected through an interviewer-administered questionnaire, comparing HIV patients late and early presented to care. Logistic regression was performed to estimate odds ratio and 95% confidence intervals. Results show that 51.9% were late presenters for HIV. No differences were found in gender distribution, marital status, or access to health services between cases and controls. Participants who undertook an HIV test by doctor indication were more likely to present late compared with those who tested for HIV by their own initiative. Also, individuals taking less time to initiate ART are more likely to present late. This study highlights the need to better understand reasons for late presentation to HIV care in Cape Verde. People in older age groups should be targeted in future approaches focused on late presenters to HIV care.
Site-to-site cross-talk in OST-B glycosylation of hCEACAM1-IgV

N-glycosylation is a common posttranslational modification of secreted proteins in eukaryotes. This modification targets asparagine residues within the consensus sequence, N-X-S/T. While this sequence is required for glycosylation, the initial transfer of a high-mannose glycan by oligosaccharyl transferases A or B (OST-A or OST-B) can lead to incomplete occupancy at a given site. Factors that determine the extent of transfer are not well understood, and understanding them may provide insight into the function of these important enzymes. Here, we use mass spectrometry (MS) to simultaneously measure relative occupancies for three N-glycosylation sites on the N-terminal IgV domain of the recombinant glycoprotein, hCEACAM1. We demonstrate that addition is primarily by the OST-B enzyme and propose a kinetic model of OST-B N-glycosylation. Fitting the kinetic model to the MS data yields distinct rates for glycan addition at most sites and suggests a largely stochastic initial order of glycan addition. The model also suggests that glycosylation at one site influences the efficiency of subsequent modifications at the other sites, and glycosylation at the central or N-terminal site leads to dead-end products that seldom lead to full glycosylation of all three sites. Only one path of progressive glycosylation, one initiated by glycosylation at the C-terminal site, can efficiently lead to full occupancy for all three sites. Thus, the hCEACAM1 domain provides an effective model system to study site-specific recognition of glycosylation sequons by OST-B and suggests that the order and efficiency of posttranslational glycosylation is influenced by steric cross-talk between adjoining acceptor sites.
Iterative Multiresolution Bayesian CS for Microwave Imaging

A new compressive sensing (CS) imaging method is proposed to exploit, during the inversion process and unlike state-of-the-art CS-based approaches, additional information besides that on the target sparsity. More specifically, such an innovative multiresolution (MR) Bayesian CS scheme profitably combines: 1) the a priori knowledge on the class of targets under investigation and 2) the progressively acquired information on the scatterer location and size to improve the accuracy, the robustness, and the efficiency of both standard (i.e., uniform-resolution) CS techniques and MR/synthetic-zoom approaches. Toward this end, a new MR-based information-driven relevance vector machine (RVM) is derived and implemented. Selected results from an extensive numerical and experimental validation are shown to give the interested readers some indications on the effectiveness and the reliability of the proposed method also in comparison with state-of-the-art deterministic and Bayesian inversion techniques.
Efficient Phase Estimation for Interferogram Stacks

Signal decorrelation poses a limitation to multipass SAR interferometry. In pursuit of overcoming this limitation to achieve high-precision deformation estimates, different techniques have been developed, with short baseline subset, SqueeSAR, and CAESAR as the overarching schemes. These different analysis approaches raise the question of their efficiency and limitation in phase and consequently deformation estimation. This contribution first addresses this question and then proposes a new estimator with improved performance, called Eigendecomposition-based Maximum-likelihood-estimator of Interferometric phase (EMI). The proposed estimator combines the advantages of the state-of-the-art techniques. Identical to CAESAR, EMI is solved using eigendecomposition; it is therefore computationally efficient and straightforward in implementation. Similar to SqueeSAR, EMI is a maximumlikelihood-estimator; hence, it retains estimation efficiency. The computational and estimation efficiency of EMI renders it as an optimum choice for phase estimation. A further marriage of EMI with the proposed Sequential Estimator by Ansari et al. provides an efficient processing scheme tailored to the analysis of Big InSAR Data. EMI is formulated and verified in relation to the state-of-the-art approaches via mathematical formulation, simulation analysis, and experiments with time series of Sentinel-1 data over the volcanic island of Vulcano, Italy.
Holistic approach to effects of foods, human physiology, and psychology on food intake and appetite (satiation & satiety)

Appetite (satiation and satiety) is an essential element for the control of eating behavior, and as a consequence human nutrition, body weight, and chronic disease risk. A better understanding of appetite mechanisms is necessary to modulate eating behavior and food intake, and also provide a practical approach for weight management. Although many researchers have investigated the relationships between satiation/satiety and specific factors including human physiology, psychology, and food characteristics, limited information on the interactions between factors or comparisons between the relative importance of factors in contributing to satiation/satiety have been reported. This article reviews progress and gaps in understanding individual attributes contributing to perceived satiation/satiety, the advantages of considering multiple factors together in appetite experiments, as well as the applications of nondestructive sensing in evaluating human factors contributing to relative appetite perception. The approaches proposed position characterization of appetite (satiation and satiety) for personalized and precision nutrition in relation to human status and healthy diets. In particular, it is recommended that future studies of appetite perception recognize the inter-dependence of food type and intake, appetite (satiation and satiety), and individual status.
Human health risk assessment related to contaminated land: state of the art

Exposure of humans to contaminants from contaminated land may result in many types of health damage ranging from relatively innocent symptoms such as skin eruption or nausea, on up to cancer or even death. Human health protection is generally considered as a major protection target. State-of-the-art possibilities and limitations of human health risk assessment tools are described in this paper. Human health risk assessment includes two different activities, i.e. the exposure assessment and the hazard assessment. The combination of these is called the risk characterization, which results in an appraisal of the contaminated land. Exposure assessment covers a smart combination of calculations, using exposure models, and measurements in contact media and body liquids and tissue (biomonitoring). Regarding the time frame represented by exposure estimates, biomonitoring generally relates to exposure history, measurements in contact media to actual exposures, while exposure calculations enable a focus on exposure in future situations. The hazard assessment, which is different for contaminants with or without a threshold for effects, results in a critical exposure value. Good human health risk assessment practice accounts for tiered approaches and multiple lines of evidence. Specific attention is given here to phenomena such as the time factor in human health risk assessment, suitability for the local situation, background exposure, combined exposure and harmonization of human health risk assessment tools.
MUSEUM AS AN OBJECT OF LIGHT DESIGN

The article reviews the problem of light design of a modern museum not only as a place for conservation and demonstration of art works but also as a leisure place. Contemporary lighting technologies applied in museums are reviewed, advantages of adoption of LED lighting in museums are described, major problems and objectives specific for lighting of exhibits in museums as well as possible methods and ways of their solution by light designers are described.
A New Low-Rank Representation Based Hyperspectral Image Denoising Method for Mineral Mapping

Hyperspectral imaging technology has been used for geological analysis for many years wherein mineral mapping is the dominant application for hyperspectral images (HSIs). The very high spectral resolution of HSIs enables the identification and the diagnosis of different minerals with detection accuracy far beyond that offered by multispectral images. However, HSIs are inevitably corrupted by noise during acquisition and transmission processes. The presence of noise may significantly degrade the quality of the extracted mineral information. In order to improve the accuracy of mineral mapping, denoising is a crucial pre-processing task. By leveraging on low-rank and self-similarity properties of HSIs, this paper proposes a state-of-the-art HSI denoising algorithm that implements two main steps: (1) signal subspace learning via fine-tuned Robust Principle Component Analysis (RPCA); and (2) denoising the images associated with the representation coefficients, with respect to an orthogonal subspace basis, using BM3D, a self-similarity based state-of-the-art denoising algorithm. Accordingly, the proposed algorithm is named Hyperspectral Denoising via Robust principle component analysis and Self-similarity (HyDRoS), which can be considered as a supervised version of FastHyDe. The effectiveness of HyDRoS is evaluated in a series of mineral mapping experiments using noise-reduced AVIRIS and Hyperion HSIs. In these experiments, the proposed denoiser yielded systematically state-of-the-art performance.
Comparative phylogeography of two commensal rat species ( Rattus tanezumi and Rattus norvegicus) in China: Insights from mitochondrial DNA, microsatellite, and 2b-RAD data

Rattus norvegicus and Rattus tanezumi are dominant species of Chinese house rats, but the colonization and demographic history of two species in China have not been thoroughly explored. Phylogenetic analyses with mitochondrial DNA including 486 individuals from 31 localities revealed that R. norvegicus is widely distributed in China, R. tanezumi is mainly distributed in southern China with currently invading northward; northeast China was the natal region of R. norvegicus, while the spread of R. tanezumi in China most likely started from the southeast coast. A total of 123 individuals from 18 localities were subjected to 2b-RAD analyses. In neighbor-joining tree, individuals of R. tanezumi grouped into geographic-specific branches, and populations from southeast coast were ancestral groups, which confirmed the colonization route from southeast coast to central and western China. However, individuals of R. norvegicus were generally grouped into two clusters instead of geographic-specific branches. One cluster comprised inland populations, and another cluster included both southeast coast and inland populations, which indicated that spread history of R. norvegicus in China was complex; in addition to on-land colonization, shipping transportation also have played great roles. ADMIXTURE and principal component analyses provided further supports for the colonization history. Demographic analyses revealed that climate changes at ~40,000 to 18,000 years ago and ~4000 years ago had led to population declines of both species; the R. norvegicus declined rapidly while the population of R. tanezumi continuously expanded since ~1500 years ago, indicating the importance of interspecies' competition in their population size changes. Our study provided a valuable framework for further investigation on phylogeography of two species in China.
Recent advances in local drug delivery to the inner ear

Inner ear diseases are not adequately treated by systemic drug administration mainly because of the blood-perilymph barrier that reduces exchanges between plasma and inner ear fluids. Local drug delivery methods including intratympanic and intracochlear administrations are currently developed to treat inner ear disorders more efficiently. Intratympanic administration is minimally invasive but relies on diffusion through middle ear barriers for drug entry into the cochlea, whereas intracochlear administration offers direct access to the colchlea but is rather invasive. A wide range of drug delivery systems or devices were evaluated in research and clinic over the last decade for inner ear applications. In this review, different strategies including medical devices, hydrogels and nanoparticulate systems for intratympanic administration, and cochlear implant coating or advanced medical devices for intracoclear administration were explored with special attention to in vivo studies. This review highlights the promising systems for future clinical applications as well as the current hurdles that remain to be overcome for efficient inner ear therapy.
A Zn8 Double-Cavity Metallacalix[8]arene as Molecular Sieve to Realize Self-Cleaning Intramolecular Tandem Transformation of Li-S Chemistry

Toward the well-explored lithium-sulfur (Li-S) catalytic chemistry, the slow adsorption-migration-conversion kinetics of lithium polysulfides on catalytic materials and Li2 S deposition-induced passivation of active sites limit the rapid and complete conversion of sulfur. Conceptively, molecular architectures can provide atom-precise models to understand the underlying active sites responsible for selective adsorption and conversion of LiPSs and Li2 S2 /Li2 S species. Here, an octanuclear Zn(II) (Zn8 ) cluster is presented, which features a metallacalix[8]arene with double cavities up and down the Zn8 ring. The central Zn8 ring and the specific double cavities with organic ligands of different electronegativity and bonding environments render active sites with variable steric hindrance and interaction toward the sulfur-borne species. An intramolecular tandem transformation mechanism is realized exclusively by Zn8 cluster, which promotes the self-cleaning of active sites and continuous electrochemical reaction. Notably, the external azo groups and internal Zn/O sites of Zn8 cluster in sequence stimulate the adsorption and conversion of long chain Li2 Sx (x ≥ 4) and short chain Li2 S/Li2 S2 , contributing to remarkable rate performance and cycling stability. This work pioneers the application of metallacalix[n]arene clusters with atom-precise structure in Li-S batteries, and the proposed mechanism advances the molecule-level understanding of Li-S catalytic chemistry.
PHM SURVEY: Implementation of Prognostic Methods for Monitoring Industrial Systems

Prognostics and Health Management (commonly called PHM) is a field that focuses on the degradation mechanisms of systems in order to estimate their health status, anticipate their failure and optimize their maintenance. PHM uses methods, tools and algorithms for monitoring, anomaly detection, cause diagnosis, prognosis of the remaining useful life (RUL) and maintenance optimization. It allows for permanently monitoring the health of the system and provides operators and managers with relevant information to decide on actions to be taken to maintain the system in optimal operational conditions. This paper aims to present the emergence of the PHM thematically to describe the subjacent processes, particularly prognosis, how it supplies the different maintenance strategies and to explain the benefits that can be anticipated. More specifically, this paper establishes a state of the art in prognostic methods used today in the PHM strategy. In addition, this paper shows the multitude of possible prognostic approaches and the choice of one among them that will help to provide a framework for industrial companies.
Brain Tumour Image Segmentation Using Deep Networks

Automated segmentation of brain tumour from multimodal MR images is pivotal for the analysis and monitoring of disease progression. As gliomas are malignant and heterogeneous, efficient and accurate segmentation techniques are used for the successful delineation of tumours into intra-tumoural classes. Deep learning algorithms outperform on tasks of semantic segmentation as opposed to the more conventional, context-based computer vision approaches. Extensively used for biomedical image segmentation, Convolutional Neural Networks have significantly improved the state-of-the-art accuracy on the task of brain tumour segmentation. In this paper, we propose an ensemble of two segmentation networks: a 3D CNN and a U-Net, in a significant yet straightforward combinative technique that results in better and accurate predictions. Both models were trained separately on the BraTS-19 challenge dataset and evaluated to yield segmentation maps which considerably differed from each other in terms of segmented tumour sub-regions and were ensembled variably to achieve the final prediction. The suggested ensemble achieved dice scores of 0.750, 0.906 and 0.846 for enhancing tumour, whole tumour, and tumour core, respectively, on the validation set, performing favourably in comparison to the state-of-the-art architectures currently available.
Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks

We present Convolutional Oriented Boundaries ( COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neural Networks (CNNs). COB is computationally efficient, because it requires a single CNN forward pass for multi-scale contour detection and it uses a novel sparse boundary representation for hierarchical segmentation; it gives a significant leap in performance over the state-of-the-art, and it generalizes very well to unseen categories and datasets. Particularly, we show that learning to estimate not only contour strength but also orientation provides more accurate results. We perform extensive experiments for low-level applications on BSDS, PASCAL Context, PASCAL Segmentation, and NYUD to evaluate boundary detection performance, showing that COB provides state-of-the-art contours and region hierarchies in all datasets. We also evaluate COB on high-level tasks when coupled with multiple pipelines for object proposals, semantic contours, semantic segmentation, and object detection on MS-COCO, SBD, and PASCAL; showing that COB also improves the results for all tasks.
Waste tire rubber devulcanization technologies: State-of-the-art, limitations and future perspectives

Waste tires management is a serious and global environmental problem. Therefore, searching for low-cost and industrial-scale applicable tire recycling methods is gaining more and more attention. Waste tire rubber is valuable source of secondary raw materials for the circular economy and current trends indicate that application of waste rubbers during manufacturing value-added products should increase in near future. Sustainable development of rubber devulcanization technologies and appropriate design of cradle-to-cradle loops for rubber goods are the most promising strategies for achieving a higher level of rubber recycling.This work presents the state-of-the-art in the patented waste tire rubber devulcanization technologies including dynamic desulfurization, reactive extrusion, microwave treatment, and also other less popular methods. Special attention was focused on the used components, rubber treatment conditions and static me-chanical properties of reclaimed rubbers. Moreover, environmental aspects and limitations related to rubber devulcanization technologies implementation are also discussed.Our findings showed that reclaimed rubbers described in patents are characterized by higher tensile strength and elongation break (depending on devulcanization technology median: 16.6-19.0 MPa and 321-443%, respectively) compared to the literature data (median: 10.3 MPa and 309%) or commercial products (median: 6.8 MPa and 250%). The significant differences observed in performance properties of reclaimed rubbers resulted mainly from devulcanization efficiency related to waste tires composition or source and rubber treatment conditions.Considering environmental and economic aspects, reactive extrusion is the most promising method further development rubber devulcanization technologies.
Perspectives for the application of neurogenetic research in programming Neurorehabilitation

Certain genetic variants underlie the proper functioning of the nervous system. They affect the nervous system in all aspects - molecular, systemic, cognitive, computational and sensorimotor. The greatest changes in the nervous system take place in the process of its maturation in the period of psychomotor development, as well as during neurorehabilitation, the task of which is to rebuild damaged neuronal pathways, e.g. by facilitating movement or training cognitive functions. Certain genetic polymorphisms affect the effectiveness of the processes of reconstruction or restoration of neural structures, which is clearly reflected in the effects of neurorehabilitation. This review presents the perspectives for the application of neurogenetic research in programming neurorehabilitation by determining the relationship of as many as 16 different genetic polymorphisms with specific functions of importance in rehabilitation. Thanks to this broad view, it may be possible to predict the effectiveness of rehabilitation on the basis of genetic testing, which would significantly contribute to the development of personalized medicine and to the optimal management of medical services in healthcare systems.
SUSTAINABLE PRODUCTION OF CLEAN ENERGY CARRIER - HYDROGEN

The state-of-the-art in biological hydrogen production methods is presented with a special focus on the process of the anaerobic fermentation of organic wastes. The recently reported levels of hydrogen yields in laboratory scale bioreactors and main challenges on the way to commercial implementations of biological, fermentative hydrogen production systems are given.