ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Lossless compression of hyperspectral images using lookup tables

In this letter, we propose a new algorithm for lossless compression of hyperspectral images. The proposed method searches the previous band for a pixel of equal value to the pixel co-located to the one to be coded. The pixel in the same position as the obtained pixel in the current band is used as the predictor. Lookup tables are used to speed up the search. The algorithm is suitable for compression of hyperspectral image data in the band-interleaved-by-line (BIL) format. The method outperforms other state-of-the-art compression algorithms for the BIL data, at a lower time complexity level. Moreover, its compression ratios for the band sequential format data are within a few percentage points of the current state-of-the-art methods.
Explicit shift-invariant dictionary learning

In this article we give efficient solutions to the construction of structured dictionaries for sparse representations. We study circulant and Toeplitz structures and give fast algorithms based on least squares solutions. We take advantage of explicit circulant structures and we apply the resulting algorithms to shift-invariant learning scenarios. Synthetic experiments and comparisons with state-of-the-art methods show the superiority of the proposed methods.
Experimental and numerical study on DCB specimens bonded with similar and dissimilar materials

In this paper, the influence of the bonding materials on the failure modes and the critical energy release rate (CERR) is studied through the double cantilever beam (DCB) test. The test results show that the failure mode and CERR of the bonded structure are closely related to the bonding materials, and three failure modes, i.e., the cohesive failure, the interface failure and the mixed-mode failure are identified on the bonding surface. The finite element method is used to simulate the interface debonding behavior of the DCB test specimens, and the influence of material randomness on the interface failure is introduced. A XFEM/CZM coupled approach is proposed to model the crack migration phenomena. The predicted results have a good agreement with the experimental results.
New developments in the radiocarbon dating of mud wasp nests

This paper reports on the development of radiocarbon dating of mud wasp nests to provide age estimates for rock art and other anthropogenic modifications to the surfaces of open rock shelters. Over 150 rock shelters in the remote Kimberley region of Western Australia were visited in five field seasons. Mud wasp nest samples were collected from 108 sites. Thirty newly constructed wasp nests were collected to understand their initial composition and to determine the major sources of carbon. Charcoal-rich fractions extracted from 9 modem nests were radiocarbon dated and, whilst most were of zero age, some were found to be up to 1000 years old with the mean age being 255 years. Of the old wasp nest samples, 120 were utilised in the experiments reported here. A variety of different physical and chemical pretreatment methods were explored but small sample sizes and low carbon concentrations limit the range of techniques that can be used in practice. The radiocarbon ages measured on the 75 nest samples that contained sufficient carbon for analysis ranged from Modern to just over 20 cal ka BP. Half of these nests were older than 8 cal ka BP and 20% were older than 11 cal ka BP. Even allowing for the inherent uncertainties due to any inbuilt carbon age, the method is capable of producing useful age estimates for rock art and other features of archaeological interest, in relatively open rock shelters.
Development of redox stable fuel electrode supported solid oxide cells

A novel solid oxide cell concept, named as redox solid oxide cell, is proposed in this work. To demonstrate the concept, solid oxide cells with doped-SrTiO3 fuel electrodes and modified NiO-3YSZ fuel electrode support were developed to realize the redox-stable solid oxide cells. By modifying the particle characteristics of NiO, 3YSZ, slurry composition and sintering profile, a redox stable and multifunctional NiO-3YSZ fuel electrode support was successfully developed. Furthermore, two different types of doped-SrTiO3 (Sr0.94Ti0.9Nb0.1O3 and La0.49Sr0.31Fe0.03Ni0.03Ti0.94O3) fuel electrode materials were successfully integrated in to the half-cells with redox stable NiO-3YSZ support. Defect free solid oxide cells of 12 cm x 12 cm size were fabricated. The redox stability of these cells was evaluated and compared with the state-of-the-art NiO-3YSZ solid oxide cells at 850 degrees C. It was clearly demonstrated that the newly developed redox solid oxide cells have superior stability compared to the state-of-the-art cells. In order to establish the potential of the newly developed redox solid oxide cells, the evaluation of the electrochemical performance is required. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Some new results on Cox-Czanner divergence and their applications in survival studies

In the present communication, we propose a quantile-based measure for the divergence between two survival functions. This can also be used in a dynamic way where the divergence between survival functions varies with time. Several new properties of the proposed measure are investigated with suitable examples. The behavior of the measure for various reliability models is also investigated. A real data analysis is employed to compare the relative efficacy of two treatment groups using the proposed divergence measure.
Effects of a Specialist-Led, School Physical Education Program on Bone Mass, Structure, and Strength in Primary School Children: A 4-Year Cluster Randomized Controlled Trial

This 4-year cluster randomized controlled trial of 365 boys and 362 girls (mean age 8.1 ± 0.3 years) from grade 2 in 29 primary schools investigated the effects of a specialist-taught physical education (PE) program on bone strength and body composition. All children received 150 min/week of common practice (CP) PE from general classroom teachers but in 13 schools 100 min/week of CP PE was replaced by specialized-led PE (SPE) by teachers who emphasized more vigorous exercise/games combined with static and dynamic postural activities involving muscle strength. Outcome measures assessed in grades 2, 4, and 6 included: total body bone mineral content (BMC), lean mass (LM), and fat mass (FM) by DXA, and radius and tibia (4% and 66% sites) bone structure, volumetric density and strength, and muscle cross-sectional area (CSA) by pQCT. After 4-years, gains in total body BMC, FM, and muscle CSA were similar between the groups in both sexes, but girls in the SPE group experienced a greater gain in total body LM (mean 1.0 kg; 95% CI, 0.2 to 1.9 kg). Compared to CP, girls in the SPE group also had greater gains in cortical area (CoA) and cortical thickness (CoTh) at the mid-tibia (CoA, 5.0% [95% CI, 0.2% to 1.9%]; CoTh, 7.5% [95% CI, 2.4% to 12.6%]) and mid-radius (CoA, 9.3% [95% CI, 3.5% to 15.1%]; CoTh, 14.4% [95% CI, 6.1% to 22.7%]), whereas SPE boys had a 5.2% (95% CI, 0.4% to 10.0%) greater gain in mid-tibia CoTh. These benefits were due to reduced endocortical expansion. There were no significant benefits of SPE on total bone area, cortical density or bone strength at the mid-shaft sites, nor any appreciable effects at the distal skeletal sites. This study indicates that a specialist-led school-based PE program improves cortical bone structure, due to reduced endocortical expansion. This finding challenges the notion that periosteal apposition is the predominant response of bone to loading during the prepubertal and early-pubertal period.
Factors Affecting Learners' Academic Success in Online Liberal Arts Courses Offered by a Traditional Korean University

This study aimed to empirically examine the factors affecting full-time undergraduate students' satisfaction and academic performance measured by grades using an existing large administrative dataset. The sample consisted of 21,662 undergraduate students who took online liberal arts courses offered by a large traditional Korean university in the spring semester of 2020. The theoretical framework of this study was formulated by selectively adopting and slightly modifying some of the factors from Choi's conceptual model for adult dropout from online degree programs. The findings indicated that gender, previous GPA, campus, type of online course, the relevance of the course, adequacy of assignments and assessments, learner-instructor interaction, and learner-content interaction significantly affect students' degree of satisfaction with online liberal arts courses. This study also found that students who considered the course less relevant to their goals or interests, had a low previous GPA, had frequent learner-instructor interactions, few learner-content interactions, and a low level of course satisfaction are more likely to earn a grade of B, C, or lower than to receive an A in online liberal arts courses.
Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID-19 patients comorbidly affected by Type 2 diabetes

The mortality of coronavirus disease 2019 (COVID-19) disease is very high among the elderly or individuals having comorbidities such as obesity, cardiovascular diseases, lung infections, hypertension, and/or diabetes. Our study characterizes the metagenomic features in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-infected patients with or without type 2 diabetes, to identify the microbial interactions associated with its fatal consequences.This study compared the baseline nasopharyngeal microbiome of SARS-CoV-2-infected diabetic and nondiabetic patients with controls adjusted for age and gender. The metagenomics based on next-generation sequencing was performed using Ion GeneStudio S5 Series and the data were analyzed by the Vegan-package in R. All three groups possessed significant bacterial diversity and dissimilarity indexes (p < 0.05). Spearman's correlation coefficient network analysis illustrated 183 significant positive correlations and 13 negative correlations of pathogenic bacteria (r = 0.6-1.0, p < 0.05), and 109 positive correlations between normal flora and probiotic bacteria (r > 0.6, p < 0.05). The SARS-CoV-2 diabetic group exhibited a significant increase in pathogens and secondary infection-causing bacteria (p < 0.05) with a simultaneous decrease of normal flora (p < 0.05). The dysbiosis of the bacterial community might be linked with severe consequences of COVID-19-infected diabetic patients, although a few probiotic strains inhibited numerous pathogens in the same pathological niches. This study suggested that the promotion of normal flora and probiotics through dietary supplementation and excessive inflammation reduction by preventing secondary infections might lead to a better outcome for those comorbid patients.
Machine learning algorithms to automate differentiating cardiac amyloidosis from hypertrophic cardiomyopathy

Cardiac amyloidosis has a poor prognosis, and high mortality and is often misdiagnosed as hypertrophic cardiomyopathy, leading to delayed diagnosis. Machine learning combined with speckle tracking echocardiography was proposed to automate differentiating two conditions. A total of 74 patients with pathologically confirmed monoclonal immunoglobulin light chain cardiac amyloidosis and 64 patients with hypertrophic cardiomyopathy were enrolled from June 2015 to November 2018. Machine learning models utilizing traditional and advanced algorithms were established and determined the most significant predictors. The performance was evaluated by the receiver operating characteristic curve (ROC) and the area under the curve (AUC). With clinical and echocardiography data, all models showed great discriminative performance (AUC > 0.9). Compared with logistic regression (AUC 0.91), machine learning such as support vector machine (AUC 0.95, p = 0.477), random forest (AUC 0.97, p = 0.301) and gradient boosting machine (AUC 0.98, p = 0.230) demonstrated similar capability to distinguish cardiac amyloidosis and hypertrophic cardiomyopathy. With speckle tracking echocardiography, the predictive performance of the voting model was similar to that of LightGBM (AUC was 0.86 for both), while the AUC of XGBoost was slightly lower (AUC 0.84). In fivefold cross-validation, the voting model was more robust globally and superior to the single model in some test sets. Data-driven machine learning had shown admirable performance in differentiating two conditions and could automatically integrate abundant variables to identify the most discriminating predictors without making preassumptions. In the era of big data, automated machine learning will help to identify patients with cardiac amyloidosis and timely and effectively intervene, thus improving the outcome.
A guiding framework for creating a comprehensive strategy for mHealth data sharing, privacy, and governance in low- and middle-income countries (LMICs)

With the numerous advances and broad applications of mobile health (mHealth), establishing concrete data sharing, privacy, and governance strategies at national (or regional) levels is essential to protect individual privacy and data usage. This article applies the recent Health Data Governance Principles to provide a guiding framework for low- and middle-income countries (LMICs) to create a comprehensive mHealth data governance strategy. We provide three objectives: (1) establish data rights and ownership to promote equitable benefits from health data, (2) protect people through building trust and addressing patients' concerns, and (3) promote health value by enhancing health systems and services. We also recommend actions for realizing each objective to guide LMICs based on their unique mHealth data ecosystems. These objectives require adopting a regulatory framework for data rights and protection, building trust for data sharing, and enhancing interoperability to use new datasets in advancing healthcare services and innovation.
High-Performance UV-Vis Broad-Spectra Photodetector Based on a β-Ga2O3/Au/MAPbBr3 Sandwich Structure

The UV-vis photodetector (PD), a detector that can simultaneously detect light in the ultraviolet region and the visible region, has a wide range of applications in military and civilian fields. Currently, it is very difficult to obtain good detection performance in the UV region (especially in the solar-blind range) like in the visible region with most UV-vis PDs. This severely affects the practical application of UV-vis broad-spectra PDs. Here, a simple sandwich structure PD (SSPD) composed of β-Ga2O3, Au electrodes, and the MAPbBr3 perovskite is designed and fabricated to simultaneous enhance the detection performance in the UV and visible light regions. The β-Ga2O3/Au/MAPbBr3 SSPD exhibits enhanced optoelectronic performance with high responsivities of 0.47 and 1.43 A W-1 at 240 and 520 nm under a bias of 6 voltage (V), respectively, which are 8.5 and 23 times than that of the metal-semiconductor-metal (MSM) structure MAPbBr3 PD at 6 V, respectively. The enhanced performance was attributed to the effective suppression of carrier recombination due to the efficient interface charge separation in the device structure. In addition, the self-powered response characteristic is also realized by forming a type-II heterojunction between β-Ga2O3 and MAPbBr3, which gives the β-Ga2O3/Au/MAPbBr3 SSPD superior single-pixel photo-imaging ability without an external power supply. This work provides a simple and effective method for the preparation of high-performance self-powered imaging PDs in the UV-visible region.
LCANet: Learnable Connected Attention Network for Human Identification Using Dental Images

Forensic odontology is regarded as an important branch of forensics dealing with human identification based on dental identification. This paper proposes a novel method that uses deep convolution neural networks to assist in human identification by automatically and accurately matching 2-D panoramic dental X-ray images. Designed as a top-down architecture, the network incorporates an improved channel attention module and a learnable connected module to better extract features for matching. By integrating associated features among all channel maps, the channel attention module can selectively emphasize interdependent channel information, which contributes to more precise recognition results. The learnable connected module not only connects different layers in a feed-forward fashion but also searches the optimal connections for each connected layer, resulting in automatically and adaptively learning the connections among layers. Extensive experiments demonstrate that our method can achieve new state-of-the-art performance in human identification using dental images. Specifically, the method is tested on a dataset including 1,168 dental panoramic images of 503 different subjects, and its dental image recognition accuracy for human identification reaches 87.21% rank-1 accuracy and 95.34% rank-5 accuracy. Code has been released on Github. (https://github.com/cclaiyc/TIdentify)
Review of alternative cooling technologies

This paper provides an update on alternative cooling technologies in the context of a report by Fischer et al. [2], which contains an extensive assessment of "not-in-kind" technologies including their state-of-the-art, development issues, and potentials to replace vapor compression equipment. After nearly 20 years, it is now of interest to update the status of alternative technologies considering regulatory actions aimed at refrigerants with high global warming potential. Several technologies are considered with sorption cooling, desiccant cooling, magnetic cooling, thermoacoustic cooling, thermoelectric cooling, and transcritical CO2 being discussed in some detail. For each technology we present its physical principle, a brief summary of the findings of Fischer et al., the technological advancements since their study leading to the current state-of-the-art, and our assessment as to the potential of each technology to enter the market as a supplement to or replacement of vapor compression equipment in the next 20 year period. (C) 2013 Elsevier Ltd. All rights reserved.
Morphogenetic processes on open-air rock art sites in tropical context: archaeo-geomorpho- logical analysis of the pre-Columbian rock art sites of Trois-Rivieres (Guadeloupe, French West Indies)

This work deals with the benefits of the archaeomorphological approach in rock art sites located in semi-tropical environment. Such approach was initially developed for studying rock art in caves and is applied here to two engraved pre-Colombian sites of Trois Rivieres (Guadeloupe): the Parc Archeologique des Roches Gravees and the Petit Carbet site. The aim was to identify the processes (gravitational, biological and hydrological) that shaped the current landscape, hence the spatial organization of the engraved rocks. Geomorphological mapping was conducted and supported by a high-resolution terrestrial LiDAR 3D mapping in order to identify landscape evolution processes pre-and post-rock art. Results show that before engraving, differential weathering of the volcanic rocks favored the genesis of monolithic formations. Those were later affected by mechanical processes (flaking and rock falls). Appart from the anthropic influence that affected some blocs (removal and displacement), the study highlights the influence of phytomechanical processes that were not considered until then. The integration of all those observations allows to reconstruct the shape of landscape at the time of the engravings. At another level, large planar spaces were identified on both sites without any rock art. They are the consequence of sediment infills linked with ancient flow paths. These results open new perspectives in terms of geophysical and archaeological investigations that could lead to a better understanding of the morphology of the site at the time of ornamentation, and potentially to the discovery, under the sediments, of ornamented ensembles, preserved from colonial and modern developments.
Long-Term Results of Total Hip Arthroplasty with 28-Millimeter Cobalt-Chromium Femoral Heads on Highly Cross-Linked Polyethylene in Patients 50 Years and Less

Highly cross-linked polyethylene (HXLPE) is the most commonly used bearing surface in total hip arthroplasty (THA) because of its superior wear properties, but long-term results in young patients are limited. We report on the clinical outcome, radiographic wear patterns and survivorship of 72 patients ≤50 years old who had a 28-millimeter cobalt-chromium femoral head on HXLPE acetabular liner. Mean and median true linear wear rates at average ten-year follow-up were 0.0104 and 0.01 mm per year ± 0.07 mm. Mean and median two-dimensional volumetric wear rates were 12.79 mm(3) and 5.834 mm(3) per year ± 26.1mm(3) as determined by Martell analysis. As a result of the minimal wear profile, there was no evidence of radiographic osteolysis and no wear-related revisions.
Forest cover resilience to climate change over India using the MC2 dynamic vegetation model

It is imperative to understand the climate change impact on the forest ecosystem to develop appropriate mitigation and management strategies. We have employed a process-based dynamic vegetation modeling (MAPSS-CENTURY: MC) approach to project change in vegetation life forms under projected climate conditions that attained 81% overall accuracy. The present and projected climate conditions suggested highly resilient/stable forest covers in wet climate regimes and moderately resilient in dry semi-arid regions. Several forested grids in the seasonally dry tropical forest in the Eastern Ghats and dry Deccan peninsula regions are estimated to be less resilient, which may experience a regime shift toward scrub and grassland. The future prediction demonstrated an upward temperature shift in the Western Himalayas and trans-Himalaya, which may facilitate forest spread at higher elevations. Although the forest cover resilience may increase in future climate conditions, the disturbances in several regions in the Deccan Peninsula and the Eastern Ghats may trigger forest to scrub and grassland transition. The inaccuracy in model simulation in the Western Himalayas could be attributed to coarse resolution grids (0.5°) failing to resolve the narrow climate niches. The spatially explicit model simulation provides opportunities to develop long-term climate change adaptation and conservation strategies.
Energy efficiency techniques in machining process: a review

The paper presents an overview of the state of the art in energy-efficient techniques in the domain of discrete part manufacturing, focusing on the techniques including energy assessment model for machining process and the energy efficiency analysis and evaluation for machine tools, important components, and machining systems. The main motivation is to review the existing works related to reduce energy consumption in machining processes, to discuss the challenges towards energy-efficient manufacturing, and identify the major barriers from both technologies and approaches.