bluuebunny/crossref_metadata_2025_split huggingface dataset:
Barriers to programming education in UAE primary schools: A Qualitative review from ICT teachers' perspectives.
Authors: Elsawah Wafaa , Hill Christopher 
Published: February 2023

Abstract
Purpose: Demonstrate the importance of programming, discuss the pedagogical philosophy of how programming is taught, identify the barriers to the proper implementation of programming education in UAE primary schools, and find solutions to overcome these barriers.
Methodology: The study adopted a qualitative approach. Thirteen ICT teachers, from different schools in the UAE, were interviewed to investigate their perception of the teaching of programming to primary students.
Findings: The good application of programming education in UAE schools is yet to be accomplished. There is a need to reform the teaching of programming in primary schools in the UAE and to raise awareness about it and its importance in the school domain (school principals, teachers, and students).
Implications: One significant implication is that teaching programming should be taken seriously by educational policymakers and school leaders as a core subject that should be taught to all students. The study also contributed to the growing body of literature on the value of programming skills and the role of the appropriate curriculum in developing these skills.
Originality/ value: This study provides new insights at both practical and scholarly levels. It can shed light on the field's expansion prospects. The outcomes of this study may assist educational policymakers in better implementing programming education, particularly in primary school. Moreover, it helps teachers better prepare for the problems that primary students may encounter with learning programming in schools.
Identifying immune cell infiltration and constructing a ceRNA network to explore novel diagnostic biomarkers and therapeutic targets in atopic dermatitis
Authors: Chen Chunli , Lu Jianyun , yan Siyu , Peng Fen , Zhong Xiaoxiao , Gao Lihua , Wang Dan , Zeng Jinrong , Tan Lina 
Published: February 2023

Abstract
Background
Atopic dermatitis (AD) is a chronic, recurrent, itchy skin disease characterized by inflammatory imbalance.
Objective
To identify novel diagnostic biomarkers and potential therapeutic targets for AD.
Methods
Two test microarray datasets (GSE63741, GSE60709) and a validated dataset (GSE75890) were downloaded from the Gene Expression Omnibus database. We explored the hub genes by analysis of immune coexpression and protein–protein interaction. We also constructed a competing endogenous RNA (ceRNA) network to explore the new therapeutic targets. We estimated immune cell types by ImmucellAI and the relevance between hub genes and immune cells. Functional analysis was also performed. Finally, we validated the hub genes through real-time quantitative PCR (RT-qPCR), immunohistochemistry (IHC) and western blotting (WB).
Results
A significantly altered proportion of 24 immune-cell types was found between healthy controls (HCs) and AD patients, and each of the hub genes was significantly correlated with the main infiltrating cells. Expression of S100A7, APOE and KRT15 in skin tissues differed significantly between AD patients and HCs. hsa-miR-365a-3p and NPSR1-AS1 were identified as potential new therapeutic targets of AD.
Conclusion
S100A7, APOE and KRT15 were associated with immune cells and could become new diagnostic biomarkers and hsa-miR-365a-3p and NPSR1-AS1 might be new therapeutic targets of AD.
Algorithm for Using Dual Energy Computed Tomography to Determine Chemical Composition: A Feasibility Study
Authors: Choi Dong Hyeok , Ahn Sohyun , Park Kwangwoo , Han Min Cheol , Kim Jin Sung 
Published: February 2023

Abstract

Purpose
Using dual-energy computed tomography (CT), this study aims to develop an algorithm to identify the chemical constituents of an unknown material (compound or mixture) and improve the accuracy of material discrimination.
Methods
The algorithm requires mass attenuation coefficients that were obtained using a dual energy CT as an input, identifies the elemental composition, and then calculates its weight fraction. To evaluate the functionality of the developed algorithm, it was used to determine the chemical constituents for human tissues. Furthermore, the results were compared with those provided by the National Institute of Standards and Technology (NIST). We used dual energies 80/140 kVp for spectral CT scans, as inputs to the algorithm, in addition to a set of 50/80 and 80/100 keV for mono-energetic X-rays.
Results
The algorithm correctly determined the chemical constituent elements of unknown materials. Results were obtained for the fractional weights of each component for mono-energetic X-rays and spectral X-ray use. For mono-energetic X-rays, the differences were < 0.01% for compounds and 6.02% for mixture, respectively. For the spectral X-rays, the differences in 2.98% for compounds and 6.03% for mixtures, respectively.
Conclusions
We developed an algorithm to determine the type and weight fraction of an element using the MAC of dual-energy CT. The algorithm can exclude the inherent uncertainty of SPR calculations and improve the accuracy of dose calculations in radiation therapy planning.
Efficacy of therapy by MK-28 PERK activation in the Huntington's disease R6/2 mouse model
Authors: Shacham Talya , Offen Daniel , Lederkremer Gerardo 
Published: February 2023

Abstract
There is currently no disease-modifying therapy for Huntington’s disease (HD) and two recent clinical trials testing antisense oligonucleotides failed. We recently described a small molecule, MK-28, which restored homeostasis in HD models by specifically activating PKR‐like ER kinase (PERK) and thus boosting neuroprotection by the unfolded protein response (UPR), and reducing endoplasmic reticulum (ER) stress, a central cytotoxic mechanism in HD and other neurodegenerative diseases. Here we have tested the long-term effects of MK-28 in HD model mice. R6/2 CAG (160) mice were treated by lifetime IP injection, 3 times a week. CatWalk measurements of motor function showed significant improvement after only two weeks of MK-28 treatment and continued with time, most significantly at 1 mg/kg MK-28, approaching WT values. Seven weeks treatment significantly improved paw grip strength. Body weight recovered and glucose levels, which are elevated in HD mice, were significantly lowered. Treatment with another PERK activator, CCT020312, also caused amelioration, although less significant than with MK-28 in some of the parameters. Lifespan, measured in more resilient R6/2 CAG (120) mice with daily IP injection, was significantly extended by 16 days (20%) with 0.3 mg/kg MK-28, and by 38 days (46%) with 1 mg/kg MK-28. No toxicity, measured by weight, blood glucose levels and blood liver function markers, was detectable in WT mice treated for 6 weeks with 6 mg/kg MK-28. Boosting of PERK activity by long-term treatment with MK-28 appears to be a safe and promising therapeutic approach for HD.
Task-Residual Effective Connectivity of Motor Network in Transient Ischemic Attack and its Association with
Risk Factor of Stroke
Authors: Chu Truc , Lee Seonjin , Jung Il-Young , Song Youngkyu , Kim Hyun Ah , Shin Jong Wook , Tak Sungho 
Published: February 2023

Abstract
Transient ischemic attack (TIA) is a transient episode of neurological dysfunction caused by focal brain ischemia. Although TIA symptoms are quickly resolved, patients with TIA have a high risk of stroke and persistent impairments in multiple domains of cognitive and motor functions. In this study, using spectral dynamic causal modelling, we investigated the changes in task-residual effective connectivity of patients with TIA during fist-closing movements and associated them with risk factors of stroke. 28 healthy participants and 15 age-matched patients with TIA underwent functional magnetic resonance imaging at 7T. Our results showed that during motor movement, patients with TIA had significantly higher effective connectivity toward the ipsilateral primary motor cortex and lower connectivity to the supplementary motor area than healthy controls. These changes in connectivity strength were positively correlated with ABCD2 scores indicating higher risk of stroke. The leave-on-out cross-validation analysis further confirmed the reliability of using effective connectivity in prediction of stroke risk after TIA. Our results imply that (i) TIA patients have disrupted connections among motor regions that are closely related to the risk of stroke, and (ii) these changes may reflect the neural dedifferentiation in the motor system.
A New Iterative Method To Find The Moore-Penrose Inverse
Authors: Sheikhi Salman , Esmaeili Hamid 
Published: February 2023

Abstract
In this paper, we introduce a new efficient iterative method to find the Moore-Penrose inverse of a singular or rectangular real (or complex) matrix, which has five matrix-matrix multiplications per iteration. It is proved that the proposed method is fourth-order convergent to the Moore-Penrose inverse. Numerical results are obtained using random matrices of sizes n × n and n × (n + 10), n = 100, 200, 300, 400. The average number of iterations, the average total number of matrix-matrix multiplications, the average precision, and the average elapsed execution time of compared methods are computed using ten matrices in each dimension. Based on this comparison, our new method can be considered as an efficient fastest method with low computational cost.
Whole-exome sequencing analysis of idiopathic hypogonadotropic hypogonadism: comparison of varicocele and non-obstructive azoospermia
Authors: Ma Ziyang , Dai Yi , Jin Lei , Luo Yi , Guo Chen , Qu Rui , He Shengyin , Liu Yugao , Xia Yu , Liu Huan , Kong Lingnan , Xu Miaomiao , Zhang Lanlan , Zhao Yue , Yushanjiang Suliya , Yuan Dongzhi , Yang Luo 
Published: February 2023

Abstract
Background
As a rare disease leading to male infertility, A has strong heterogeneity of clinical phenotype and gene mutation. At present, there is no effective diagnosis and treatment method for this disease, and the research on its pathogenesis is not exhaustive
Objectives
To explore the possible new pathogenic gene of idiopathic hypogonadotrophic hypogonadism and the pathological mechanism affecting its occurrence.
Patients and methods:
We performed a whole-exome sequencing on 9 patients with normosmic idiopathic hypogonadotropic hypogonadism (nIHH), 19 varicocele patients with weak sperm, oligospermia or azoospermia and 5 patients with simple nonobstructive azoospermia and carried out comparative analysis, channel analysis, etc.
Results
After preliminary sequencing screening, 309–431 genes harbouring variants, including SNPs and indels, were predicted to be harmful per single patient in each group. In genetic variations of nIHH patients’ analysis, variants were detected in 10 loci and nine genes in nine patients. And in co-analysis of the three patient groups, nine nIHH patients, 19 VC patients, and five SN patients shared 116 variants, with 28 variant-harbouring genes detected in five or more patients. After that, we found that many genes crossed among groups and selected the highest number of 17 genes for analysis.
Conclusion
We found that the NEFH, CCDC177 and PCLO genes and the Gene Ontology pathways GO:0051301: cell division and GO:0090066: regulation of anatomical structure size may be key factors in the pathogenic mechanism of IHH. Our results suggest the pathogenic mechanism of IHH is not limited to the central nervous system effects of GnRH but may involve other heterogeneous pathogenic genetic variants that affect peripheral organs.
Multi-Layer Stochastic Block Interaction driven by Logistic Regression (MLSBI-LR) for Efficient Link Recommendation in Intra-Layer Linkage Graphs
Authors: Bolorunduro Janet Oluwasola , Zou Zhaonian 
Published: February 2023

Abstract
Link Recommendation (LR) in complex networks has caught across-the-network interest in social and computer science communities. Numerous networks, such as recommendation systems and social networks (which facilitate user contact), are probabilistic rather than deterministic due to the uncertainty surrounding the presence of links. Evaluating the various measures has frequently been tricky as the Intra-Layer Linkage Graph requires that at least two nodes be in the same layer. Moreover, many existing LR methods mainly operate well on Single-Layer Graphs (SLGs) compared to Multi-Layer Graphs (MLGs) when nodes traverse Multi-Layers in a network of Intra-Layer linkages. Considering this drawback and others, this paper proposes a Multi-Layer Stochastic Block Interaction method driven by Logistic Regression (MLSBI-LR) to exploit the bi-directional resources associated with Intra-Layer linkages is inherent dependence on Knowledge-based systems use multi-criteria recommender systems to accommodate additional criteria and can modify neighborhood-based approaches. Neighborhood approaches are used since they are more well-accepted and have available experimental data set in MLGs toward recommending links that would efficiently enrich users’ experience. The accuracy and robustness of the proposed MLSBI-LR method compared to existing LR methods were extensively investigated using three distinct benchmark data sets and four evaluation metrics. Based on experimental results across the databases and metrics, the proposed MLSBI-LR method performed significantly better (recording up to 17\% increment in accuracy), recommending potential links in MLGs. Consequently, the proposed method may revolutionize link recommendation tasks in social networks by maximizing users’ overall experience
Mapping the forage nitrogen, phosphorus, and potassium contents of alpine grasslands by integrating Sentinel-2 and Tiangong-2 data
Authors: Zhang Xuanfan , Liang Tiangang , Gao Jinlong , Zhang Dongmei , Liu Jie , Feng Qisheng , Wu Caixia , Wang Zhiwei 
Published: February 2023

Abstract
As crucial quality indicators for forage in alpine natural grasslands, nitrogen (N), phosphorus (P), and potassium (K) contents are closely related to plant growth and reproduction. One of the greatest challenges for the sustainable utilization of grassland resources and the high-quality development of animal husbandry is to efficiently and accurately obtain information about the distribution and dynamic change of N, P, and K contents in alpine grasslands. A new generation of multispectral sensors, the Sentinel-2 multispectral instrument (MSI) and Tiangong-2 moderate-resolution wide-wavelength imager (MWI), is equipped with several spectral bands suitable for specific application scenarios, showing great potential in mapping forage nutrients at the regional scale. This study aims to achieve high-accuracy spatial mapping of the N, P, and K contents in alpine grasslands at the regional scale on the eastern Tibetan Plateau. The Sentinel-2 MSI and Tiangong-2 MWI data, coupled with multiple feature selection algorithms and machine learning models, are applied to develop forage N, P, and K estimation models via a combination of 92 sample sites collected from the vigorous growth stage to the senescent stage. The results show that the spectral bands of both Sentinel-2 MSI and Tiangong-2 MWI have an excellent performance in estimating the forage N, P, and K contents (the R2 are 0.68–0.76, 0.54–0.73, and 0.74–0.82 for forage N, P, and K estimations, respectively). Moreover, the model integrating the spectral bands of these two sensors explains 78%, 74%, and 84% of the variations in the forage N, P, and K contents, respectively. These results indicate that the estimation ability of forage nutrients can be further improved by integrating Tiangong-2 MWI and Sentinel-2 MSI data. In conclusion, integration of the spectral bands of multiple sensors is a promising approach to map the forage N, P, and K contents in alpine grasslands with high accuracy at the regional scale. The study offers valuable information for growth monitoring and real-time determination of forage quality in alpine grasslands.
The structural analysis of secretion in the freshwater mite Limnesia maculata (O.F. Müller, 1776) (Acariformes, Limnesiidae) supports the idea of a new form of arthropod silk
Authors: Shatrov Andrey B. , Soldatenko Elena V. , Benken Konstantin A. , Petrov Anatoly A. 
Published: February 2023

AbstractThe structural characteristics of silk secretion of the freshwater miteLimnesia maculata(O.F. Müller, 1776) (Acariformes, Limnesiidae) are described and analyzed for the first time based on light, atomic force and electron-microscopical approaches. The common dermal glands (14 pairs scattered over the body) produce silk mostly during the warm summer season. The process of silk secretion occupies from several hours to several days. Silk may be detected as barely recognized clouds of a fine whitish substance. An individual silk thread is an infinitely long uniform unbranched and non-stretchable tube, hollow or with a vesicular electron-dense residual content. In the silk bundle, threads may be freely interlaced, bent, curved or occasionally broken. The diameter of the tubes mostly lies within 0.9–1.5 µm. The width of the tube walls varies greatly from 60 to 300 nm. Chaotically interlaced fine fibrils build the tube walls. On the external surface of the tube wall, these fibrils are loosely organized and frequently rising vertically, whereas on the internal side they are packed more tightly sometimes showing a mesh. The walls may reveal a layered structure or, contrary, are quite thinner with through foramens. The revealed organization of silk in the freshwater mites is found to be the simplest among that of other arthropods. The proposed role of such silk is a capture of the potential prey in the summer season. Silk in water mites significantly widen the wholesome area for their life and gives them better chances in competition for potential resources.
Overcoming vaccine hesitancy by multiplex social network targeting: An analysis of targeting algorithms and implications
Authors: Fugenschuh Marzena , Fu Feng 
Published: February 2023

Abstract
Incorporating social factors into disease prevention and control efforts is an important undertaking of behavioral epidemiology. The interplay between disease transmission and human health behaviors, such as vaccine uptake, results in complex dynamics of biological and social contagions. Maximizing intervention adoptions via network-based targeting algorithms by harnessing the power of social contagion for behavior and attitude changes largely remains a challenge. Here we address this issue by considering a multiplex network setting. Individuals are situated on two layers of networks: the disease transmission network layer and the peer influence network layer. The disease spreads through direct close contacts while vaccine views and uptake behaviors spread interpersonally within a potentially virtual network. The results of our comprehensive simulations show that network-based targeting with pro-vaccine supporters as initial seeds significantly influences vaccine adoption rates and reduces the extent of an epidemic outbreak. Network targeting interventions are much more effective by selecting individuals with a central position in the opinion network as compared to those grouped in a community or connected professionally. Our findings provide insight into network-based interventions to increase vaccine confidence and demand during an ongoing epidemic.
Clinicoepidemiology, risk factors and outcome assessment of virus induced acute encephalitis syndrome: A hospital based prospective study in Eastern India.
Authors: Rathore Sushil Kumar , Pati Pallabi , Dwibedi Bhagirathi , Kar Shantanu 
Published: February 2023

Abstract
Background: Acute encephalitis syndrome (AES) is a serious public health problem in India, whose cause has remained unknown for remarkable proportion of cases.
Method: During the study, cases were enrolled from tertiary care hospitals of Cuttack and Bhubaneswar. All the cases were screened for viral cause by serology and molecular diagnostics Subjects were followed up for twelve months to assess disease outcome. Logistic regression analysis was used to identify the risk factors associated with poor outcome.
Results: A total of 345(19.8%) subjects could be diagnosed with viral etiology and HSV-1 was the most common252(14.51 %) followed by HSV-2 (49,2.82%), Measles(36, 2.07%), JEV(18,1.04%),Enterovirus (15),VZV(7),dengue(7),EBV(2) mumps(2) and,HEV(1).Most common symptoms in addition to fever were convulsion (85%) and altered sensorium (95%). Comparison of clinical features among viral AES and undiagnosed AES cases showed that fever, diarrhoea, respiratory problem, rash, convulsion, Vomiting, altered sensorium and meningeal signs were significantly different between these two groups (p<0.05). Also the factors like age(p=0.015),low GCS score(p=0.021),hospital stay(0.024) and ,referral delay (0.03) were significantly associated with poor outcome.
Conclusion: HSV-1 was the commonest virus causing sporadic AES in this part of India. In this investigation low GCS score, longer hospital stay and referral delay were observed to be independent risk factors for poor outcome. Case fatality was observed in 25.75%. Thus immediate detection of HSV-1 and special attention to risk factors could help in proper management of AES cases.
Min-Max Joint Task Offloading and Resource Allocation Optimization in MEC Empowered Air-ground Integrated Networks
Authors: Du Jianbo , Cheng Wenjie 
Published: February 2023

Abstract
Recent years, unmanned aerial vehicle (UAV) has become an important assistant that could act as access points (APs) for communication, and can also act as edge nodes for task offloading in mobile edge computing (MEC), etc., in many scenarios. We consider a multiuser mobile offloading network consisting multiple UAV based MEC nodes. The tasks could be processed locally, or offloaded to the UAV edge nodes, or migrated to the cloud further on. We formulate the offloading problem as the joint optimization of offloading decision making of all the SMEs, the computation resource allocation among the edge-executing applications, and radio resource assignment among all the remote-processing applications, aiming to minimize the maximum total weighted cost of all the SMEs. It is demonstrated that the problem is NP-hard. To tackle this challenge, offloading decisions are obtained using SDR. Next a firework algorithm is adopted novelly in radio resource allocation, and the computation resource is distributed uniformly among all the fog-executing users. Simulation results exhibit that as a result of the collaboration of the fog and cloud, the proposed joint algorithm could achieves nearly optimal performance in the aspects of energy consumption, delay, and a weighted cost of the both compared with others algorithms.