ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Alternative caregivers` role in food choices for young children in semi-urban and urban Mexico

Alternative caregivers (i.e., someone besides the primary caregiver who also takes care of children) make food choices for children. This study investigated what alternative caregivers consider when making food choices for children and their perspectives on their role in making food choices to feed children. In-depth interviews were conducted with 16 alternative caregivers of children aged 1-5 years old in semi-urban and urban areas of the State of Mexico in Mexico. Interviews were recorded, transcribed, coded, and analyzed using constant comparative method. Alternative caregivers described spaces and situations that exposed children to food while under their care. Alternative caregivers who spent longer periods of time with the child described more involvement in what the child ate. Healthy or nutritious food, cost of food and affection for children were important considerations for alternative caregivers when deciding what to feed the child. Alternative caregivers had a substantial role in child feeding, decisions about cooking, and advising mothers on how to feed their children. Efforts to promote healthy food choices for children should include targeting of alternative caregivers.
A molecular characterization of marsupial filarioid nematodes of the genus Breinlia

Here we present the genetic relationships of 26 specimens of the genus Breinlia (Nematoda: Filarioidea) from a range of Australian marsupials using markers in the small subunit of nuclear ribosomal RNA and mitochondrial cytochrome c oxidase subunit 1 (cox1) genes and compare them with morphological determinations. The molecular data support the validity of most of the morpho-species included in the study and provide provisional insights into the phylogeny of the genus in Australian mammals, with dasyuroid marsupials appearing to be the original hosts. The recent discovery of Breinlia annulipapillata in the eye of a human brings this genus of parasites into the group of emerging infectious parasitic diseases.
Meal patterns and the quality of breakfast and snacks in relation to adolescents' dental health in southeast of Iran

Aim: The objective was to determine the frequency pattern and nutritional quality of breakfast and snacks in Iranian adolescents and to investigate these dietary habits in relation to tooth decay and tooth erosion. Methods: A multistage cluster random sampling method was adopted to recruit 600 adolescents with equal sex distribution in the city of Kerman/southeast of Iran. Decayed, Missing and Filled Teeth (DMFT) and Tooth Wear Index (TWI) were recorded for each subject. Snacking and breakfast quality, frequency of snacking and regular/irregular use of main meals were also recorded. Poisson regression and Firth's bias-reduced penalized-likelihood logistic regression were used for data analysis. Results: DMFT score of adolescents who consumed low-quality snacks were 1.13 times more than those who consumed high-quality snacks. Regular use of all three main meals was associated with a lower DMFT score. DMFT score of adolescents who did not have regular use of breakfast was 1.19 times more than those who consumed breakfast on a regular basis. Also, regarding adolescents who had an irregular use of lunch, the DMFT score was 1.3 times more than those who had a regular lunch schedule. In addition, participants with irregular dinner consumption had 1.24 times more DMFT scores compared to those with a regular dinner schedule. Conclusions: Regular breakfast consumption, decreased snacking occasions, use of higher nutritional quality snacks, and increased nutritional education are important in order to prevent a higher chance of dental caries and promote dental health status.
SBAUPT: Azimuth SBUPT for Frequent Full Attitude Correction of Smartphone-Based PDR

The growing market of smart devices make them appealing for various applications. Motion tracking can be achieved using such devices, and is important for various applications such as navigation, search and rescue, health monitoring, and quality of life-style assessment. Step detection is a crucial task that affects the accuracy and quality of such applications. In this paper, a new step detection technique is proposed, which can be used for step counting and activity monitoring for health applications as well as part of a Pedestrian Dead Reckoning (PDR) system. Inertial and Magnetic sensors measurements are analyzed and fused for detecting steps under varying step modes and device pose combinations using a free-moving handheld device (smartphone). Unlike most of the state of the art research in the field, the proposed technique does not require a classifier, and adaptively tunes the filters and thresholds used without the need for presets while accomplishing the task in a real-time operation manner. Testing shows that the proposed technique successfully detects steps under varying motion speeds and device use cases with an average performance of 99.6% and outperforms some of the state of the art techniques that rely on classifiers and commercial wristband products.
Improvement of ascorbic acid delivery into human skin via hyaluronic acid-coated niosomes

Hyaluronic acid (HA) as a covering agent was incorporated into the ascorbic acid (AA)-niosomes to improve the performance of AA delivery systems into the skin. The preparation method: Thin film hydration. Characterisation tests: Field emission scanning electron microscopy, fourier transform infra-red spectroscopy, dynamic light scattering, UV-Visible, zeta potential, Franz diffusion cell, and flowcytometry. The niosomes with 10% w/w HA possessed the largest mean particle diameter of 341.0 ± 48.09 nm with PDI value of 0.29 ± 0.05, and the lowest zeta potential of -38.70 ± 0.27 mv. The drug encapsulation efficiency of this sample was 56.55 ± 0.99%, and in-vitro drug release test showed AA released in two slow and fast phases. Moreover, the highest amount of drug penetration and accumulation was related to this sample, recorded 116.55 ± 7.54 and 134.8 ± 10.04 µg/cm2, respectively. Niosomes coated with 10% w/w HA showed the greatest potential for improving the antioxidant activity of AA penetration into the skin.
METAMORPHOSE European Doctoral Programs on Metamaterials - State-of-the-art

A new European Doctoral Program on Metamaterials has been initiated by the European Union (EU) Network of Excellence METAMORPHOSE. So far, twenty European academic institutions have established a consortium that operates a geographically distributed doctoral school in the emerging and multidisciplinary field of metamaterials.
The Secret to That Old Black Magic: Mastering the Art of Sparkless Commutation

DC machines have been in operation for more than 100 years. Engineers and technicians understand the dc-motor structure and components since they have experience rebuilding, testing, and making performance adjustments to them. Those that understand commutation, [2], [4] the commutation zone (CZ), and the characteristics of the carbon brush are few in number. Traditionally, the lack of a visible arc has been the defining quality of good commutation; hence, the term "black." The knowledge gap and relatively high-level physical science involved with commutation have led to an art known as "black magic" for achieving the invisible-arc condition [5], [6]. Black magic refers to both the brush coloration and commutation. The purpose of this article is to define the CZ and present the critical components that create it. An explanation of specific brush properties and their contribution to successful commutation is included.
A deep neural network approach to QRS detection using autoencoders*,**

Objective: In this paper, a stacked autoencoder deep neural network is proposed to extract the QRS complex from raw ECG signals without any conventional feature extraction phase. Methods: A simple architecture has been deeply trained on many datasets to ensure the generalization of the network at inference. Results: The proposed method achieved a QRS detection accuracy of 99.6% using more than 1042000 beats which is competitive with all state-of-the-art QRS detectors. Moreover, the proposed method produced only 0.82% of Detection Error Rate using six unseen datasets containing more than 1470000 beats. Thus confirms the high performance of our method to detect QRSs. Conclusion: Stacked autoencoder neural networks are very effective in QRS detection. At inference, our algorithm processes 1042309 beats in less than 25.32 s. Thus, it is favorably comparable with state-of-the-art deep learning methods. Significance: The stacked autoencoder is an efficient tool for QRS detection, which could replace conventional systems to help practitioners make fast and accurate decisions.
Lipid binding protein response to a bile acid library: a combined NMR and statistical approach

Primary bile acids, differing in hydroxylation pattern, are synthesized from cholesterol in the liver and, once formed, can undergo extensive enzyme-catalysed glycine/taurine conjugation, giving rise to a complex mixture, the bile acid pool. Composition and concentration of the bile acid pool may be altered in diseases, posing a general question on the response of the carrier (bile acid binding protein) to the binding of ligands with different hydrophobic and steric profiles. A collection of NMR experiments (H/D exchange, HET-SOFAST, ePHOGSY NOESY/ROESY and (15) N relaxation measurements) was thus performed on apo and five different holo proteins, to monitor the binding pocket accessibility and dynamics. The ensemble of obtained data could be rationalized by a statistical approach, based on chemical shift covariance analysis, in terms of residue-specific correlations and collective protein response to ligand binding. The results indicate that the same residues are influenced by diverse chemical stresses: ligand binding always induces silencing of motions at the protein portal with a concomitant conformational rearrangement of a network of residues, located at the protein anti-portal region. This network of amino acids, which do not belong to the binding site, forms a contiguous surface, sensing the presence of the bound lipids, with a signalling role in switching protein-membrane interactions on and off.
Aqua-(2-formylbenzoato)triphenyltin(IV) induces cell cycle arrest and apoptosis in hypoxic triple negative breast cancer cells

Hypoxia plays a vital role in tumor microenvironment by allowing development and maintenance of cancer cells thereby led to major hindrance for effective anticancer therapy and main reason for failure of most anticancer drugs. We herein investigated the therapeutic efficacy and molecular mechanism of action of aqua-(2-formylbenzoato) triphenyltin (IV) compound (OTC) in MDA-MB-231 cell line. Cobalt chloride induced hypoxic MDA-MB-231 cells treated with OTC were used to access cytotoxicity, ROS, cellular apoptosis, and cell cycle progression. Further, expression of HIF-1α and VEGF, as well as apoptotic proteins like p53, Bax, Bcl-2 and caspase 3 were assessed. The findings indicated that OTC is more effective towards CoCl2 induced hypoxic cells when compared to normoxic cells and the results are far superior to doxorubicin. Additionally, our study revealed that OTC facilitates more ROS production induced cell cycle arrest and promote apoptosis. Furthermore, OTC significantly down regulates the expression of Hif-1α, VEGF and Bcl-2 in hypoxic condition and elevates the level of p53, Bax, cytochrome-C and Caspase 3. Our in vitro studies demonstrated that OTC showed better efficacy than doxorubicin, corroborating that OTC could be a promising compound for hypoxic cancer that also display multi drug resistant.
Understanding ART-based neural algorithms as statistical tools for manufacturing process quality control

Neural networks have recently received a great deal of attention in the field of manufacturing process quality control, where statistical techniques have traditionally been used. In this paper, a neural-based procedure for quality monitoring is discussed from a statistical perspective. The neural network is based on Fuzzy ART, which is exploited for recognising any unnatural change in the state of a manufacturing process. Initially, the neural algorithm is analysed by means of geometrical arguments. Then, in order to evaluate control performances in terms of errors of Types I and II, the effects of three tuneable parameters are examined through a statistical model. Upper, bound limits for the error rates are analytically computed, and then numerically illustrated for different combinations of the tuneable parameters. Finally, a criterion for the neural network designing is proposed and validated in a specific test case through simulation. The results demonstrate the effectiveness of the proposed neural-based procedure for manufacturing quality monitoring. (c) 2005 Elsevier Ltd. All rights reserved.
Compressive Sensing of Electrocardiogram Signals by Promoting Sparsity on the Second-Order Difference and by Using Dictionary Learning

A new algorithm for the reconstruction of electrocardiogram (ECG) signals and a dictionary learning algorithm for the enhancement of its reconstruction performance for a class of signals are proposed. The signal reconstruction algorithm is based on minimizing the l(p) pseudo-norm of the second-order difference, called as the l(p)(2d) pseudo-norm, of the signal. The optimization involved is carried out using a sequential conjugate-gradient algorithm. The dictionary learning algorithm uses an iterative procedure wherein a signal reconstruction and a dictionary update steps are repeated until a convergence criterion is satisfied. The signal reconstruction step is implemented by using the proposed signal reconstruction algorithm and the dictionary update step is implemented by using the linear least-squares method. Extensive simulation results demonstrate that the proposed algorithm yields improved reconstruction performance for temporally correlated ECG signals relative to the state-of-the-art l(p)(1d)-regularized least-squares and Bayesian learning based algorithms. Also for a known class of signals, the reconstruction performance of the proposed algorithm can be improved by applying it in conjunction with a dictionary obtained using the proposed dictionary learning algorithm.
A 36.7 mW, 28 GHz receiver frontend using 40 nm RFCMOS technology with improved Figure of Merit

High carrier frequency requirement (Sub 6, 28 GHz) to accomplish the high bandwidth specification for millimeter wave band wireless communication, has reduced the ratio of operating carrier frequency (f(c)) and unity current gain frequency (f(t)) of MOSFETs in state of the art RFCMOS technology. This poses a challenge for designing a high gain and low noise receiver with better linearity. In an attempt to realize such receiver, this paper presents a 28 GHz receiver front-end in 40 nm RFCMOS technology. It includes 3-stage low noise amplifier incorporating push pull topology, current bleeding down converting gilbert cell based mixer with common gate transconductance stage followed by a standard Gm-C filter. By incorporating these techniques, the performance of the proposed receiver improved in terms of linearity as compared to the state of the art designs. For a comprehensive analysis, the combined effect of performance parameters has been compiled into a single metric i.e. Figure of Merit (FOM). The proposed receiver exhibits conversion gain of 30.5 dB and 2.15 dB noise figure with linearity parameter IIP3 being -21.7 dBm while consuming 36.7mW power resulting in FOM value of 0.27.
Development of Pyrazine-Anilinobenzamides as Histone Deacetylase HDAC1-3 Selective Inhibitors and Biological Testing Against Pancreas Cancer Cell Lines

Class I histone deacetylase (HDAC) enzymes are key regulators of cell proliferation and are frequently dysregulated in cancer cells. Here we describe the synthesis of a novel series of class-I selective HDAC inhibitors containing anilinobenzamide moieties as ZBG connected with a central (piperazin-1-yl)pyrazine moiety. Compounds were tested in vitro against class-I HDAC1, 2, and 3 isoforms. Some highly potent HDAC inhibitors were obtained and were tested in pancreatic cancer cells and showed promising activity. Moreover, we summarize how the growth-inhibitory effects of these compounds can be determined in murine pancreatic cancer cell lines.
Pipelines for HDR Video Coding Based on Luminance Independent Chromaticity Preprocessing

We consider the chromaticity in high dynamic range (HDR) video coding and show the advantages of a constant luminance color space for encoding. For this, we introduce two constant luminance HDR video coding pipelines, which convert the source video to linear Y u' v'. A content dependent scaling of the chromaticity components serves as color quality parameter. This reduces perceivable color artifacts while remaining fully compatible with core High Efficiency Video Coding or other video coding standards. One of the pipelines further combines the scaling with a dedicated chromaticity transform to optimize the representation of the chromaticity components for encoding. We validate both pipelines with subjective user studies in addition to an objective comparison to the other state-of-the-art methods. The user studies show a significant improvement in perceived color quality at medium to high compression rates without sacrificing luminance quality compared with current standard coding pipelines. The objective evaluation suggests that both pipelines perform at least comparable to the current state-of-the-art methods.
High-rate activated sludge system for carbon management--Evaluation of crucial process mechanisms and design parameters

The high-rate activated sludge (HRAS) process is a technology suitable for the removal and redirection of organics from wastewater to energy generating processes in an efficient manner. A HRAS pilot plant was operated under controlled conditions resulting in concentrating the influent particulate, colloidal, and soluble COD to a waste solids stream with minimal energy input by maximizing sludge production, bacterial storage, and bioflocculation. The impact of important process parameters such as solids retention time (SRT), hydraulic residence time (HRT) and dissolved oxygen (DO) levels on the performance of a HRAS system was demonstrated in a pilot study. The results showed that maximum removal efficiencies of soluble COD were reached at a DO > 0.3 mg O2/L, SRT > 0.5 days and HRT > 15 min which indicates that minimizing the oxidation of the soluble COD in the high-rate activated sludge process is difficult. The study of DO, SRT and HRT exhibited high degree of impact on the colloidal and particulate COD removal. Thus, more attention should be focused on controlling the removal of these COD fractions. Colloidal COD removal plateaued at a DO > 0.7 mg O2/L, SRT > 1.5 days and HRT > 30 min, similar to particulate COD removal. Concurrent increase in extracellular polymers (EPS) production in the reactor and the association of particulate and colloidal material into sludge flocs (bioflocculation) indicated carbon capture by biomass. The SRT impacted the overall mass and energy balance of the high-rate process indicating that at low SRT conditions, lower COD mineralization or loss of COD content occurred. In addition, the lower SRT conditions resulted in higher sludge yields and higher COD content in the WAS.
The impact of the art-ICA control technology on the performance, energy consumption and greenhouse gas emissions of full-scale wastewater treatment plants

Advanced real time - Instrumentation, Control, and Automation (Art-ICA) controllers are an advanced control solution for biological nutrient removal wastewater treatment plants. Art-ICA has been previously shown to be capable of enhancing nutrient removal performance in BNR plants, at lower energy expenditures. However, the impact that this control solution has on the greenhouse gas emissions from full-scale wastewater treatment plants has not previously been addressed. This work addresses the effect of art-ICA on the performance, energy consumption and greenhouse gas emissions of two full-scale WWTPs, Chelas and Castelo Branco (Portugal). The raw wastewater, nitrous oxide emissions, energy consumption and water discharges were quantified in two independent trains operated under different operational modes, conventional operation and art-ICA control. The implementation of the art-ICA strategy improved the effluent quality and reduced the operational costs, resulting in a better performance of these WWTPs. The art-ICA controllers activation led to a reduction of 54% and 7-10% of the total nitrogen effluent and in the specific energy consumption, respectively. Moreover, process control with art-ICA did not have a negative impact on the N2O emissions of the plants, and contributed to lower global warming potential by the facilities. The lower indirect carbon dioxide production due to lower energy consumption contributes to the observation that art-ICA control is environmentally preferable to conventional control. (C) 2018 Elsevier Ltd. All rights reserved.
Multidimensional study of factors influencing sustainable construction adoption in Yemen: insights for implementing sustainable practices

Despite political volatility, Yemen's construction sector is gradually progressing to satisfy the country's housing needs. Most construction projects, however, employ traditional construction methods and have yet to be able to adopt sustainable construction, which is economically feasible, socially responsible, and environmentally beneficial. To support sustainable construction, this study analyzes various factors that might drive sustainable practices in construction projects in Yemen. These drivers are discovered from the literature and validated by experts using grey Delphi. Forty-four drivers were approved across three dimensions: economic, social, and environmental. These drivers are assessed using grey AHP. The economic factor is determined to be the most crucial in the adoption of sustainable construction. Competitiveness, improved well-being, and improved indoor environmental quality are rated as the top economic, social, and environmental dimensions, respectively. Overall, competitiveness is acknowledged as the most important driver for the implementation of sustainable practices in Yemen's construction projects. The study's findings were discussed with the experts who were involved in the evaluation. The findings were agreed upon, and it was underlined that a proactive approach from both construction project participants and public authorities can increase the competitiveness of sustainable construction. Additional policies to promote competitiveness of sustainable construction are also advocated.