bluuebunny/crossref_metadata_2025_split huggingface dataset:
Defected Photonic Crystal Array Using Porous GaN as Malaria Sensor
Authors: Tammam M.T. , Zaky Zaky A. , Sharma Arvind , Matar Z.S. , Aly Arafa H. , Mohaseb M.A. 
Published: August 2021

Abstract
A defective one-dimensional photonic crystal is investigated as a biosensor to detect malaria disease. The proposed photonic structure is air/(GaN/Porous GaN)N/Sample/(GaN/Porous GaN)N/Substrate. The red blood cells sample of the human being is used as a sample defect in the proposed optical device. The pioneer transfer matrix method is used to analyze the transmittance spectra. A change in sample refractive index highly affects the transmittance resonant peak and this shift in the peak plays a key role in the operation of the device. The relatively high figure of merit of 1022 RIU−1 with a sensitivity of 1472 nm/RIU and quality factor of 1076 is detected. The proposed sensor is relatively better than others available to detect malaria disease.
V-Trough Optimization for a Multipurpose Integrated Solar Energy Project in Helwan of Egypt
Authors: Abdel-Hadi Yasser A , Sabry Mohamed , Ghitas Ahmed , Singh Harjit , Redpath David 
Published: August 2021

Abstract
A solar concentrator of the type V-Trough is designed for a multipurpose integrated solar energy project in Helwan of Egypt. A suitable place in the NRIAG is selected. A concentration ratio matching the stability of the unconventional cooling technique for PV module 2.3 is chosen. A new cooling system with heat pipes for the module is manufactured. The optimum angles of setting the system for a maximum performance during the year are calculated using a ray tracing technique. The optimum dimensions of the PV module are 100 cm × 35 cm with an output voltage of 11.4 V and an output current of 4.29 A. The results show that establishing a solar thermal PV project with these conditions is promising for providing energy for off-grid local multipurpose integrated solar energy projects in that area.
Study Of The Optimum Conditions And Parameters To Perform Simulation Of Low Temperature Capacitive Radio Frequency Argon Discharge
Authors: Shihab M , Elsheikh M G , El-Ashram T , Moslem W M 
Published: August 2021

Abstract
Capacitively coupled plasma (CCP) is used extensively in plasma processing, such as, plasma etching, deposition, and sputtering. Particle-in-Cell (PIC) is used to explore the discharge dynamics microscopically. Considering all species in PIC simulation is challenging. Also, considering various atomic transitions, e.g., ionization, recombination, excitation, and deexcitation is not doable. The state of the art is to carry out fluid simulation. We compare between PIC and fluid simulation for radio frequency CCP to reveal the effect of various approximations as assuming constant temperature, simplifying Navier-Stokes equations in terms of particles mobility and diffusivity, and considering artificial boundary conditions at the electrodes. The fluid model predicts qualitatively PIC results in few minutes. For Argon discharge in geometrically symmetric CCP, the plasma bulk is quasineutral. Over the electrodes, two sheaths are built up due to the difference between ion and electron fluxes. The dynamics of two sheaths are out of phase. In the fluid model, chemical reactions and atomic processes can be considered. Argon metastable states density is maximum in the plasma bulk. In semi dark sheaths, metastable states concentration is small. The proposed fluid model could be used as a simulation platform to find the optimum conditions and to interpret experimental results.
Low-temperature Hydrothermal Synthesis of Titanium Dioxide Nanoparticles for Photocatalytic Applications
Authors: Shahat Abdelhamid M , El-Hossary F M , Ghitas Ahmed , Abd El-Rahman A M , Ebnalwaled A A 
Published: August 2021

Abstract
Titanium dioxide nanoparticles (TiO2 NPs) were synthesized by a surfactant-templated hydrothermal method at low temperature (75 °C) for photocatalytic applications. Investigation of structural, optical and photocatalytic properties of TiO2 NPs were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM), FT-IR and UV – vis absorption spectroscopy. The structural analysis confirmed a polycrystalline tetragonal anatase TiO2 phase with nanocrystalline structure and almost regular spherical shape. It has been found that the synthesized TiO2 NPs have an energy bandgap value between 4.42 and 4.46 eV; achieving a photodegradation efficiency of methyl orange dye of 81% to 88 % under UV visible light.
Comparative neutronic study for heterogeneous and homogeneous fuel assembly in a lead-cooled fast reactor
Authors: Ibrahim Mohammed , Ibrahim Amr , Aziz Moustafa , Saudi H A , Hassaan M Y 
Published: August 2021

Abstract
ALFRED (Advanced Lead-cooled Fast Reactor European Demonstrator) is a (300 MW
th
) pool-type reactor with closed hexagonal Fuel Assemblies (FAs) which are divided into two radial zones (inner and outer core zones). In this work two three dimensional models (3D-heterogenous and 3D-homogeneous) for inner assembly (IA) and outer assembly (OA) have been designed using MCNPX transport code to simulate the neutronic behavior and to study the fuel performance and the effect of homogenization inside the fuel assemblies. The results of the present work for power distribution and fuel burn-up show good agreement between 3D-homogeneous and 3D-heterogeneous models.
Coherent states for a system of an electron moving in a plane
Authors: Aremua Isiaka , Gouba Laure 
Published: August 2021

Abstract
In this paper, we construct the coherent states for a system of an electron moving in a plane under uniform external magnetic and electric fields. These coherent states are built in the context of both discrete and continuous spectra and satisfy the Gazeau-Klauder coherent state properties Gazeau and Klauder (1999 J. Phys. A: Math. Gen.
32, 123–132).
Historical trends of riverine nitrogen loading from land to the East China Sea: a model-based evaluation
Authors: Nishina K , Ito A , Zhou F , Yan X , Hayashi S , Winiwarter W 
Published: August 2021

Abstract
East Asia is the one of the hotspot regions with too much reactive nitrogen (N) inputs from anthropogenic sources. Here, we evaluated historical total inorganic N (TIN) load from land to sea through the rivers surrounding the East China sea using biogeochemical model ‘VISIT’ combined with a newly developed VISIT Off-line River Nitrogen scheme (VISIToRN). VISIT calculated N cycling in both natural and agricultural ecosystems and VISIToRN calculated inorganic N transport and riverine denitrification through the river channels at half degree spatial resolution. Between 1961 and 2010, the estimated TIN load from land to the sea surrounding the East China Sea increased from 2.7 Tg-N Year−1 to 5.5 Tg-N Year−1, a twofold increase, while the anthropogenic N input to the East China Sea basin (N deposition, N fertilizer, manure, and human sewage) increased from 12.9 Tg-N Year−1 to 36.9 Tg-N Year−1, an increase of about 3 times. This difference in the rate of increase is due in large part to the terrestrial nitrogen budget, and the results of the model balance indicate that TIN load to rivers has been suppressed by improvements in fertilizer application rates, harvesting on agricultural land, and nitrogen accumulation in forests. The results of the model balance showed that the increase rate of nitrogen runoff from Chinese rivers has been declining since 2000. In our estimation by VISIToRN, the amount of nitrogen removed by river denitrification in the river channel before the mouth is not negligible, ranging from 1.6 Tg-N Year−1 to 2.16 Tg-N Year−1. The N load from agricultural sources is still significant and needs to be further reduced. TIN load tended to increase in years with high precipitation. In order to effectively reduce TIN load, it is necessary to consider climate change-adaptive agricultural N management.
Residual stress determination using full-field optical methods
Authors: Nelson Drew V 
Published: August 2021

Abstract
Residual stresses are created in engineering components during fabrication and processing. Such stresses can strongly influence structural behavior. They are generally found by experimental means. A widely used way of finding residual stresses is removal of a small volume of material containing stresses and measurement of the strains that develop in surrounding material as a result of stresses being released. The strains can then be used to compute residual stresses. Drilling a small shallow hole is the most common way of implementing this approach, with strains measured by nearby strain gages adhered to the surface. This paper provides an overview of how full-field optical methods can be used instead of strain gages with hole drilling, overcoming limitations associated with gages and expanding capabilities of the hole drilling approach. The methods considered are holographic and electronic speckle pattern interferometry, Moire interferometry and digital image correlation. Advantages of using optical methods to find residual stresses are shown. A variety of applications is presented, ranging from determination of stresses in underground piping to stresses in microscale specimens. In addition, optical approaches employing different ways of material removal for stress release are reviewed, as well as several non-destructive optical methods for determining residual stresses.
Edge to quantum: hybrid quantum-spiking neural network image classifier
Authors: Ajayan A , James A P 
Published: August 2021

Abstract
The extreme parallelism property warrant convergence of neural networks with that of quantum computing. As the size of the network grows, the classical implementation of neural networks becomes computationally expensive and not feasible. In this paper, we propose a hybrid image classifier model using spiking neural networks (SNN) and quantum circuits that combines dynamic behaviour of SNN with the extreme parallelism offered by quantum computing. The proposed model outperforms models in comparison with spiking neural network in classical computing, and hybrid convolution neural network-quantum circuit models in terms of various performance parameters. The proposed hybrid SNN-QC model achieves an accuracy of 99.9% in comparison with CNN-QC model accuracy of 96.3%, and SNN model of accuracy 91.2% in MNIST classification task. The tests on KMNIST and CIFAR-1O also showed improvements.
Determination of Wolbachia Diversity in 23 Cricket Species (Gryllidae) From China
Authors: Li Yue-Yuan , Zeng Yang , Zhu Dao-Hong 
Published: August 2021

Abstract
Wolbachia (Hertig) (Rickettsiales: Anaplasmataceae) are maternally inherited endosymbiotic bacteria that are widely present in nematodes and arthropods. These endosymbiont bacteria receive significant research attention because they can have important effects on the biology of their hosts. Here, we present the first detailed analyses of Wolbachia in crickets from China, with screening of 23 species from eight genera. In total, 21 species from the eight genera were positive for Wolbachia. Significant diversity was observed among Wolbachia strains from the crickets based on five multilocus sequence typing (MLST) genes, with 15 different sequence types (STs), of which 12 STs were new to the MLST database. Five species were infected with Wolbachia of supergroup A, 11 species were infected with Wolbachia of supergroup B, and seven species were infected with Wolbachia of supergroup F. Some of the same host species harbored distinctly different Wolbachia strains, suggesting multiple infections of crickets by Wolbachia. Different cricket hosts also harbored closely related Wolbachia strains, and there were three gene recombinations. Horizontal transmission and gene recombination may allow crickets to acquire new Wolbachia strains and have increased the genetic diversity of Wolbachia.
Healthcare for older people in Asia
Authors: Woo Jean 
Published: August 2021

AbstractPopulations in Asian developed economies are rapidly ageing, such that, currently, Hong Kong and Japan have the longest life expectancy at birth for both men and women. However, extended lifespan is not necessarily accompanied by prolongation of health span, such that there is increasing prevalence of frailty and dependency, which translates into increase in complex health and social needs as well as increase in absolute numbers of older adults that require such needs. Consideration of social determinants of healthy ageing would be important in the design of equitable health and social care systems. There is a trend towards development of integrated medical social care in the community in Asian countries. Long-term care insurance and also philanthropic support play a role in the financing of such care models.
A Cyst-ematic Analysis of the Adrenal Gland: A Compilation of Primary Cystic Lesions From Our Institution and Review of the Literature
Authors: Gubbiotti Maria A , LiVolsi Virginia , Montone Kathleen , Baloch Zubair 
Published: August 2021

AbstractObjectivesAlthough primary adrenal lesions and metastases are most commonly encountered, de novo cysts of the adrenal gland can occasionally occur.MethodsWe analyzed the pathology archives at the Hospital of the University of Pennsylvania for diagnoses of cystic lesions of the adrenal gland between 1998 and 2020. Patient demographics and clinical information were extracted, and pathology slides and stains, as appropriate, were analyzed. The literature between 1998 and 2020 was also searched for large case series involving cystic adrenal lesions.ResultsWe found 18 cystic lesions of the adrenal gland in our archives, categorized as pseudocysts (7), endothelial cysts (5), mesothelial cysts (2), mature teratoma (1), cystic adrenal cortical adenoma (1), cystic pheochromocytoma (1), and cystic metastasis (1). The mean age at time of diagnosis was 52.3 years, and the mean size of the cysts was 6.0 cm. There was a slight female predilection, and cysts were more likely to be found on the left side. All lesions were incidental findings. The cystic metastasis was clear cell renal cell carcinoma. Our findings were also compared with those found in the literature published within the same timeframe.ConclusionsAdrenal cysts are rare entities. Our findings are concordant with other large studies and provide additional cases to the existing literature. In addition, our literature search expands the possible differential diagnoses for cystic lesions arising in the adrenal gland.
Identification of Predictive Factors for Patient-Reported Outcomes in the Prospective Australian Breast Device Registry
Authors: Hansen Jessy , Ahern Susannah , Gartoulla Pragya , Khu Ying , Elder Elisabeth , Moore Colin , Farrell Gillian , Hopper Ingrid , Earnest Arul 
Published: August 2021

Abstract

Background
Patient-reported outcome measures (PROMs) are an important tool for evaluating outcomes following breast device procedures and are used by breast device registries. PROMs can assist with device monitoring through benchmarked outcomes but need to account for demographic and clinical factors that may affect PROM responses.

Objectives
This study aimed to develop appropriate risk-adjustment models for the benchmarking of PROM data to accurately track device outcomes and identify outliers in an equitable manner.

Methods
Data for this study were obtained from the Australian Breast Device Registry, which consists of a large prospective cohort of patients with primary breast implants. The 5-question BREAST-Q implant surveillance module was used to assess PROMs at 1 year following implant insertion. Logistic regression models were used to evaluate associations between demographic and clinical characteristics and PROMs separately by implant indication. Final multivariate risk-adjustment models were built sequentially, assessing the independent significant association of these variables.

Results
In total, 2221 reconstructive and 12,045 aesthetic primary breast implants with complete 1-year follow-up PROMs were included in the study. Indication for operation (post-cancer, risk reduction, or developmental deformity) was included in the final model for all reconstructive implant PROMs. Site type (private or public hospital) was included in the final breast reconstruction model for look, rippling, and tightness. Age at operation was included in the reconstruction models for rippling and tightness and in the aesthetic models for look, rippling, pain, and tightness.

Conclusions
These multivariate models will be useful for equitable benchmarking of breast devices by PROMs to help track device performance.

Level of Evidence: 2
Drug–target interaction predication via multi-channel graph neural networks
Authors: Li Yang , Qiao Guanyu , Wang Keqi , Wang Guohua 
Published: August 2021

Abstract
Drug–target interaction (DTI) is an important step in drug discovery. Although there are many methods for predicting drug targets, these methods have limitations in using discrete or manual feature representations. In recent years, deep learning methods have been used to predict DTIs to improve these defects. However, most of the existing deep learning methods lack the fusion of topological structure and semantic information in DPP representation learning process. Besides, when learning the DPP node representation in the DPP network, the different influences between neighboring nodes are ignored. In this paper, a new model DTI-MGNN based on multi-channel graph convolutional network and graph attention is proposed for DTI prediction. We use two independent graph attention networks to learn the different interactions between nodes for the topology graph and feature graph with different strengths. At the same time, we use a graph convolutional network with shared weight matrices to learn the common information of the two graphs. The DTI-MGNN model combines topological structure and semantic features to improve the representation learning ability of DPPs, and obtain the state-of-the-art results on public datasets. Specifically, DTI-MGNN has achieved a high accuracy in identifying DTIs (the area under the receiver operating characteristic curve is 0.9665).
DAMA: a method for computing multiple alignments of protein structures using local structure descriptors
Authors: Daniluk Paweł , Oleniecki Tymoteusz , Lesyng Bogdan 
Published: August 2021

Abstract

Motivation
The well-known fact that protein structures are more conserved than their sequences forms the basis of several areas of computational structural biology. Methods based on the structure analysis provide more complete information on residue conservation in evolutionary processes. This is crucial for the determination of evolutionary relationships between proteins and for the identification of recurrent structural patterns present in biomolecules involved in similar functions. However, algorithmic structural alignment is much more difficult than multiple sequence alignment. This study is devoted to the development and applications of DAMA—a novel effective environment capable to compute and analyze multiple structure alignments.

Results
DAMA is based on local structural similarities, using local 3D structure descriptors and thus accounts for nearest-neighbor molecular environments of aligned residues. It is constrained neither by protein topology nor by its global structure. DAMA is an extension of our previous study (DEDAL) which demonstrated the applicability of local descriptors to pairwise alignment problems. Since the multiple alignment problem is NP-complete, an effective heuristic approach has been developed without imposing any artificial constraints. The alignment algorithm searches for the largest, consistent ensemble of similar descriptors. The new method is capable to capture most of the biologically significant similarities present in canonical test sets and is discriminatory enough to prevent the emergence of larger, but meaningless, solutions. Tests performed on the test sets, including protein kinases, demonstrate DAMA’s capability of identifying equivalent residues, which should be very useful in discovering the biological nature of proteins similarity. Performance profiles show the advantage of DAMA over other methods, in particular when using a strict similarity measure QC, which is the ratio of correctly aligned columns, and when applying the methods to more difficult cases.

Availability and implementation
DAMA is available online at http://dworkowa.imdik.pan.pl/EP/DAMA. Linux binaries of the software are available upon request.

Supplementary information
Supplementary data are available at Bioinformatics online.
Inhibition of METTL3/m6A/miR126 promotes the migration and invasion of endometrial stromal cells in endometriosis
Authors: Li Xiaoou , Xiong Wenqian , Long Xuefeng , Dai Xin , Peng Yuan , Xu Ying , Zhang Zhibing , Zhang Ling , Liu Yi 
Published: August 2021

Abstract
N 6-methyladenosine (m6A), one of the most abundant RNA modifications, is involved in the progression of many diseases, but its role and related molecular mechanisms in endometriosis remain unknown. To address these issues, we detected m6A levels in normal, eutopic, and ectopic endometrium and found the m6A levels decreased in eutopic and ectopic endometrium compared with normal endometrium. In addition, we proved that methyltransferase-like 3 (METTL3) downregulation accounted for m6A reduction in endometriosis. Furthermore, we observed that METTL3 knockdown facilitated the migration and invasion of human endometrial stromal cells (HESCs), whereas METTL3 overexpression exerted opposite effects, suggesting that METTL3 downregulation might contribute to endometriosis development by enhancing cellular migration and invasion. Mechanistically, METTL3-dependent m6A was involved in the DGCR8-mediated maturation of primary microRNA126 (miR126 and pri-miR126). Moreover, miR126 inhibitor significantly enhanced the migration and invasion of METTL3-overexpressing HESCs, whereas miR126 mimics attenuated the migration and invasion of METTL3-silenced HESCs. Our study revealed the METTL3/m6A/miR126 pathway, whose inhibition might contribute to endometriosis development by enhancing cellular migration and invasion. It also showed that METTL3 might be a novel diagnostic biomarker and therapeutic target for endometriosis.
A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation
Authors: Myers Bonnie J E , Weiskopf Sarah R , Shiklomanov Alexey N , Ferrier Simon , Weng Ensheng , Casey Kimberly A , Harfoot Mike , Jackson Stephen T , Leidner Allison K , Lenton Timothy M , Luikart Gordon , Matsuda Hiroyuki , Pettorelli Nathalie , Rosa Isabel M D , Ruane Alex C , Senay Gabriel B , Serbin Shawn P , Tittensor Derek P , Beard T Douglas 
Published: August 2021

Abstract
Biodiversity projections with uncertainty estimates under different climate, land-use, and policy scenarios are essential to setting and achieving international targets to mitigate biodiversity loss. Evaluating and improving biodiversity predictions to better inform policy decisions remains a central conservation goal and challenge. A comprehensive strategy to evaluate and reduce uncertainty of model outputs against observed measurements and multiple models would help to produce more robust biodiversity predictions. We propose an approach that integrates biodiversity models and emerging remote sensing and in-situ data streams to evaluate and reduce uncertainty with the goal of improving policy-relevant biodiversity predictions. In this article, we describe a multivariate approach to directly and indirectly evaluate and constrain model uncertainty, demonstrate a proof of concept of this approach, embed the concept within the broader context of model evaluation and scenario analysis for conservation policy, and highlight lessons from other modeling communities.