bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and prioritization of security challenges of big data on cloud computing based on SLR: A fuzzy‐TOPSIS analysis approach
Authors: Khan Abdul Wahid , Khan Maseeh Ullah , Khan Javed Ali , Khan Javed , Gul Wresham 
Published: November 2021

AbstractNowadays, data is increasing exponentially, although cloud computing is an eminent approach for the organization, processing, and availability of data for organizational growth over the internet. Besides, a lot of advantages of cloud computing, yet it is suffered from security challenges, which affect big data while using cloud services on the internet. For this purpose, we conducted a detailed systematic literature review (SLR) study, to identify and capture the security challenges of big data on the cloud computing platform. Our research findings determine and develop a taxonomy, based on the prioritization of the security challenges of big data on cloud computing. We identified a total of 15 critical security challenges using the proposed SLR, with the frequency of each challenge >25%, and are further validated by the industrial specialists using a questionnaire survey study. The identified security challenges are data secrecy issue, geographical data location issue, unauthorized data access issue, lack of control, lack of data management, network‐level issues, data integrity issue, data recovery issue, lack of trust, data sharing issue, data availability, asset issues, legal amenabilities, lack of quality issues, and lack of consistency. The security challenges identified and captured through the SLR study are categorized into four levels, namely, steadiness, management, control, and eminence. Conclusively, we applied the fuzzy‐TOPSIS approach to prioritize and identify the significance of each identified security challenge for the big data usage on cloud computing. Based on our proposed approach, the “data secrecy issue” has been identified as the most prominent security challenge with the captured value of “0.765.” The fuzzy TOPSIS is an effective and innovative research approach in the field of computer science. It has been applied positively to other research areas to address and identify the fuzziness and uncertainty of multiple decision‐making glitches. The findings of the research paper will assist the software vendor organization when using the cloud platform for big data security. Also, using the proposed approach, software vendors can prioritize and analyze the uncertainty and ambiguousness among these security challenges.
Angularity in DIS at next-to-next-to-leading log accuracy
Authors: Zhu Jiawei , Kang Daekyoung , Maji Tanmay 
Published: November 2021

Abstract
Angularity is a class of event-shape observables that can be measured in deep-inelastic scattering. With its continuous parameter a one can interpolate angularity between thrust and broadening and further access beyond the region. Providing such systematic way to access various observables makes angularity attractive in analysis with event shapes. We give the definition of angularity for DIS and factorize the cross section by using soft-collinear effective theory. The factorization is valid in a wide range of a below and above thrust region but invalid in broadening limit. It contains an angularity beam function, which is new result and we give the expression at $$ \mathcal{O} $$
O
(αs). We also perform large log resummation of angularity and make predictions at various values of a at next-to-next-to-leading log accuracy.
Phosphorylation of Na+,K+-ATPase at Tyr10 of the α1-Subunit is Suppressed by AMPK and Enhanced by Ouabain in Cultured Kidney Cells
Authors: Petrič Metka , Vidović Anja , Dolinar Klemen , Miš Katarina , Chibalin Alexander V. , Pirkmajer Sergej 
Published: November 2021

AbstractNa+,K+-ATPase (NKA) is essential for maintenance of cellular and whole-body water and ion homeostasis. In the kidney, a major site of ion transport, NKA consumes ~ 50% of ATP, indicating a tight coordination of NKA and energy metabolism. AMP-activated protein kinase (AMPK), a cellular energy sensor, regulates NKA by modulating serine phosphorylation of the α1-subunit, but whether it modulates other important regulatory phosphosites, such as Tyr10, is unknown. Using human kidney (HK-2) cells, we determined that the phosphorylation of Tyr10 was stimulated by the epidermal growth factor (EGF), which was opposed by inhibitors of Src kinases (PP2), tyrosine kinases (genistein), and EGF receptor (EGFR, gefitinib). AMPK activators AICAR and A-769662 suppressed the EGF-stimulated phosphorylation of EGFR (Tyr1173) and NKAα1 at Tyr10. The phosphorylation of Src (Tyr416) was unaltered by AICAR and increased by A-769662. Conversely, ouabain (100 nM), a pharmacological NKA inhibitor and a putative adrenocortical hormone, enhanced the EGF-stimulated Tyr10 phosphorylation without altering the phosphorylation of EGFR (Tyr1173) or Src (Tyr416). Ouabain (100–1000 nM) increased the ADP:ATP ratio, while it suppressed the lactate production and the oxygen consumption rate in a dose-dependent manner. Treatment with ouabain or gene silencing of NKAα1 or NKAα3 subunit did not activate AMPK. In summary, AMPK activators and ouabain had antagonistic effects on the phosphorylation of NKAα1 at Tyr10 in cultured HK-2 cells, which implicates a role for Tyr10 in coordinated regulation of NKA-mediated ion transport and energy metabolism.
Graphical Abstract
Detection of invisible cracks in ceramic materials using by pre-trained deep convolutional neural network
Authors: Nogay Hidir Selcuk , Akinci Tahir Cetin , Yilmaz Musa 
Published: November 2021

AbstractCeramic materials are an indispensable part of our lives. Today, ceramic materials are mainly used in construction and kitchenware production. The fact that some deformations cannot be seen with the naked eye in the ceramic industry leads to a loss of time in the detection of deformations in the products. Delays that may occur in the elimination of deformations and in the planning of the production process cause the products with deformation to be excessive, which adversely affects the quality. In this study, a deep learning model based on acoustic noise data and transfer learning techniques was designed to detect cracks in ceramic plates. In order to create a data set, noise curves were obtained by applying the same magnitude impact to the ceramic experiment plates by impact pendulum. For experimental application, ceramic plates with three invisible cracks and one undamaged ceramic plate were used. The deep learning model was trained and tested for crack detection in ceramic plates by the data set obtained from the noise graphs. As a result, 99.50% accuracy was achieved with the deep learning model based on acoustic noise.
Quality assessment of drinking water of Multan city, Pakistan in context with Arsenic and Fluoride and use of Iron nanoparticle doped kitchen waste charcoal as a potential adsorbent for their combined removal
Authors: Earnest Iris , Nazir Rabia , Hamid Almas 
Published: November 2021

AbstractIn majority cities of Pakistan, ground water is the main source of drinking water supply in the taps. Studies from different areas of Pakistan reported the presence of arsenic (As3/5+) and fluoride (F−) in drinking water supplies and can be envisaged as a deep-rooted cause of daily exposure of these in humans. The present study was planned with three way approach, i.e., to assess drinking water quality in Multan city, a highly populated and industrial activity area; synthesis of nano-adsorbent for simultaneous, effective and low-cost removal of fluoride and arsenic and manage waste by utilization of kitchen waste for synthesis of the nano-adsorbent. Out of 30 samples collected, 80% and 73% samples were found exceeding maximum residual limits (MRL) for F− and As3/5+, respectively, while 53% samples had both As3/5+ and F− concentrations greater than MRL. All these water samples were then treated with prepared nano-adsorbent, i.e., iron nanoparticles doped kitchen waste charcoal after evaluating the optimized experimental parameters and application of adsorption, kinetics and thermodynamic models. The nano-adsorbent showed high removal efficacy 81–100% for F− and 13–100% for As3+.
Aging weakens Th17 cell pathogenicity and ameliorates experimental autoimmune uveitis in mice
Authors: Li He , Zhu Lei , Wang Rong , Xie Lihui , Ren Jie , Ma Shuai , Zhang Weiqi , Liu Xiuxing , Huang Zhaohao , Chen Binyao , Li Zhaohuai , Feng Huyi , Liu Guang-Hui , Wang Si , Qu Jing , Su Wenru 
Published: November 2021

AbstractAging-induced changes in the immune system are associated with a higher incidence of infection and vaccination failure. Lymph nodes, which filter the lymph to identify and fight infections, play a central role in this process. However, careful characterization of the impact of aging on lymph nodes and associated autoimmune diseases is lacking. We combined single-cell RNA sequencing (scRNA-seq) with flow cytometry to delineate the immune cell atlas of cervical draining lymph nodes (CDLNs) of both young and old mice with or without experimental autoimmune uveitis (EAU). We found extensive and complicated changes in the cellular constituents of CDLNs during aging. When confronted with autoimmune challenges, old mice developed milder EAU compared to young mice. Within this EAU process, we highlighted that the pathogenicity of T helper 17 cells (Th17) was dampened, as shown by reduced GM-CSF secretion in old mice. The mitigated secretion of GM-CSF contributed to alleviation of IL-23 secretion by antigen-presenting cells (APCs) and may, in turn, weaken APCs’ effects on facilitating the pathogenicity of Th17 cells. Meanwhile, our study further unveiled that aging downregulated GM-CSF secretion through reducing both the transcript and protein levels of IL-23R in Th17 cells from CDLNs. Overall, aging altered immune cell responses, especially through toning down Th17 cells, counteracting EAU challenge in old mice.
Association of spousal violence and women’s empowerment status among the rural women of sub-Saharan Africa
Authors: Anik Asibul Islam , Towhid Muhammad Ibrahim Ibne , Haque M Atiqul 
Published: November 2021

AbstractSpousal violence (SV) is a global problem for women and its elimination is one of the prime targets of Sustainable Development Goal-5. Data from the Demographic and Health Surveys of seventeen countries, representing two sub-Saharan Africa (SSA) regions (East and Southern Africa [ESA] and West and Central Africa [WCA]), were used to examine the relationship between all types of SV and women’s empowerment status among rural married women aged 15–49 years. Multivariate logistic regression analysis was used to explore adjusted associations, and a relative index of inequality (RII) and slope index of inequality (SII) were used to measure the inequality in experiencing SV by rural women based on their overall empowerment position. Within the period 2015–2019, the reported rate of SV was higher in the ESA (physical SV: 33.55%; sexual SV: 16.96%; any type of SV: 46.14%) than the WCA countries (physical SV: 27.80%; sexual SV: 7.63%; any type of SV: 40.83%), except for emotional SV (WCA: 31.28% vs ESA: 29.35%). In terms of overall empowerment status, rural WCA women were slightly ahead of their counterparts in the ESA region (46.09% and 44.64%, respectively). For both ESA and WCA countries, women who didn’t justify violence and who had access to health care (except physical SV in WCA) showed negative but significant association with all types of SV in the adjusted analysis. Conversely, economic empowerment significantly increased the odds of experiencing physical and any type of SV in both regions. The significant risk ratios obtained from RII, for any SV were 0.83 and 1.09, and theβ-coefficients from SII were –0.082 and 0.037 units, respectively, in ESA and WCA. Multi-sectoral microfinance-based intervening programmes and policies should be implemented regionally to empower women, especially in the economic, socio-culture, health care accessibility dimensions, and this will eventually reduce all types of spousal violence in rural SSA.
Do policy clashes between the judiciary and the executive affect public opinion? Insights from New Delhi’s odd–even rule against air pollution
Authors: Beiser-McGrath Liam F. , Bernauer Thomas , Prakash Aseem 
Published: November 2021

AbstractPolicy processes are affected by how policymakers assess public support for a policy. But is public support for a given policy itself affected by characteristics of the policy process, such as cooperation or confrontation amongst policy actors? Specifically, if different branches of government hold conflicting positions on a given policy, do clashes affect public support for the policy? To address this question, we exploit an unexpected clash amongst the executive and judiciary in New Delhi, between survey waves, over exemptions for women in the context of the odd–even rule, a policy intervention to reduce air pollution from transportation. We find that public support for the contested policy was not undermined by the executive–judiciary clash. However, the clash polarised public opinion by gender, based upon the policy exemptions. Our findings shed new light on the broader question of how conflicts amongst different parts of government influence mass public policy preferences.
Early adversity and depressive symptoms among early adolescent girls: the mediating role of exposure to recent interpersonal acute stress
Authors: Stroud Catherine B. , Chen Frances R. , Dunning Erin E. , Cheng Julia , Marr Carey , Vrshek-Schallhorn Suzanne 
Published: November 2021

AbstractEarly adversity confers risk for depression in part through its association with recent (i.e., proximal) acute stress. However, it remains unresolved whether: a) early adversity predicts increases in recent acute stress over time; b) all – or only certain types – of recent events mediate the relationship between early adversity and depression; and c) early adversity places individuals at greater risk for depression via greater exposure to independent (i.e., fateful) interpersonal events or via greater generation of dependent (i.e., partially self-initiated) interpersonal events (i.e., stress generation) or both. These questions were examined in a 3-wave longitudinal study of early adolescent girls (N = 125; M = 12.35 years [SD = .77]) with no history of diagnosable depression using contextual life stress and diagnostic interviews. Path analyses indicated that increases in past-year acute interpersonal, but not non-interpersonal, stress mediated the link between early adversity and depressive symptoms. The mediating role of interpersonal events was limited to independent ones, suggesting increases in interpersonal event exposure, not interpersonal stress generation, acted as a mediator. Finally, findings support prior evidence that early adversity may not directly predict future depressive symptoms. Implications for understanding the role of recent stress in the association between early adversity and adolescent depression are discussed.
Beyond words: An analysis of skills underlying reading and vocabulary acquisition in three foreign languages
Authors: van den Boer Madelon , Zeguers Maaike H. T. 
Published: November 2021

AbstractTo capture the complexity of foreign language literacy acquisition, we investigated cognitive skills underlying word reading, sentence reading, word vocabulary and sentence vocabulary in three different foreign languages. Students fluent in Dutch simultaneously acquired three foreign languages that differed in orthographic transparency and writing system (Spanish, French, Chinese). Cognitive skills at the start of literacy acquisition (Grade 7) were longitudinally related to literacy attainment in each of the foreign languages after two years of instruction (end of Grade 8). Structural equation regression models indicated that three areas (word and sentence vocabulary, and sentence reading) related most strongly to verbal and nonverbal intelligence, indicating the involvement of academic skills. For word reading the influence of cognitive skills appeared language specific. Across languages, native reading skills seemed to be employed to varying degrees of efficiency to decipher foreign words, more so for foreign languages with a smaller orthographic distance from the native language.
International humanitarian law and the criminal justice response to terrorism: From the UN Security Council to the national courts
Authors: Sarfati Agathe 
Published: November 2021

AbstractSince the adoption of the first United Nations Security Council (UNSC) counterterrorism resolution after the 9/11 attacks, the UNSC has increasingly required the domestic criminalization of “terrorism” acts and ancillary activities. Without the inclusion of an explicit international humanitarian law (IHL) or humanitarian exception, the UNSC has – so far – failed to harmonize the counterterrorism legal framework with IHL, leaving it up to States to define the interaction between the two. In their national legislation and courts, States’ interpretations have varied but counterterrorism legislations have been used to adjudicate conducts in armed conflicts, regardless of their legality under IHL. As the domestication of UNSC offences is ongoing, good practices are highlighted in this paper and recommendations are offered to ensure the development of international customary law in accordance with IHL.
Improved High Resolution Ocean Reanalyses Using a Simple Smoother Algorithm
Authors: Dong Bo , Haines Keith , Martin Matthew 
Published: November 2021

AbstractWe present a simple smoother designed for smooth data adjustments in sequentially generated reanalysis products by utilizing knowledge of future assimilation increments. A decay time parameter is applied to the smoother increments to account for memory decay timescales in the ocean. The result is different from simply time smoothing the reanalysis itself as only the increments are smoothed so the reanalysis product can retain high frequency variability that is being internally generated by the model and the atmospheric forcing. The smoother is applied first to the Lorenz 1963 model and then to the daily Met Office GloSea5 Global ¼° ocean reanalysis during 2016. Results show significant improvement over the original reanalysis in the 3D temperature and salinity state and variability, as well as in the sea surface height (SSH) and ocean currents. Comparisons are made directly against temperature, salinity and SSH observations, as well as independent 15 m drifter velocities. The impact on the time variability of conservative quantities, particularly ocean heat and salt content, as well as kinetic energy and the Atlantic Meridional Overturning Circulation (AMOC), is also demonstrated.
Modeling of Ultraviolet Aurora Intensity Associated With Interplanetary and Geomagnetic Parameters Based on Neural Networks
Authors: Hu Ze‐Jun , Han Bing , Zhang Yisheng , Lian Huifang , Wang Ping , Li Guojun , Li Bin , Chen Xiang‐Cai , Liu Jian‐Jun 
Published: November 2021

AbstractThe spatial distribution of aurora intensity is an important manifestation of solar wind‐magnetosphere‐ionosphere energy coupling process, and it oscillates with the change of space environment parameters and geomagnetic index. It is of great significance to establish an appropriate aurora intensity model for the prediction of space weather and the study of magnetosphere dynamics. Based on Ultraviolet Imager (UVI) data of Polar satellite, we constructed two auroral models by using two different neural networks, that is, the generalized regression neural network (GRNN), and the conditional generation adversarial network (CGAN). Input parameters of the models include interplanetary magnetic field, solar wind velocity and density, and the geomagnetic AE index. Output result is the spatial distribution of auroral intensity in altitude adjusted corrected geomagnetic (AACGM) coordinates. The structural similarity index (SSIM) of image quality is used as an evaluation standard of detail similarity between the prediction results of auroral intensity model and corresponding UVI images (complete similarity is 1, dissimilarity is 0, SSIM is generally considered to have good similarity if it is greater than 0.5). Based on the respective training datasets of GRNN and CGAN models, the evaluating results showed that the mean values (standard deviation) of SSIM were 0.5409 (0.0912) and 0.5876 (0.0712), respectively, so the prediction results from both models can restore the auroral intensity distribution of the original images of UVI. In addition, the value of SSIM can increase with the increase of the number of training data. Therefore, more training data will help improve the effectiveness of these models.
Anatomic accuracy, physiologic characteristics, and fidelity of very low birth weight infant airway simulators
Authors: Lengua Hinojosa Patricia , Eifinger Frank , Wagner Michael , Herrmann Jochen , Wolf Monika , Ebenebe Chinedu Ulrich , von der Wense Axel , Jung Philipp , Mai Aram , Bohnhorst Bettina , Longardt Ann Carolin , Hillebrand Georg , Schmidtke Susanne , Guthmann Florian , Aderhold Martina , Schwake Ida , Sprinz Maria , Singer Dominique , Deindl Philipp 
Published: November 2021

Abstract
Background
Medical simulation training requires realistic simulators with high fidelity. This prospective multi-center study investigated anatomic precision, physiologic characteristics, and fidelity of four commercially available very low birth weight infant simulators.

Methods
We measured airway angles and distances in the simulators Premature AirwayPaul (SIMCharacters), Premature Anne (Laerdal Medical), Premie HAL S2209 (Gaumard), and Preterm Baby (Lifecast Body Simulation) using computer tomography and compared these to human cadavers of premature stillbirths. The simulators’ physiologic characteristics were tested, and highly experienced experts rated their physical and functional fidelity.

Results
The airway angles corresponded to those of the reference cadavers in three simulators. The nasal inlet to glottis distance and the mouth aperture to glottis distance were only accurate in one simulator. All simulators had airway resistances up to 20 times higher and compliances up to 19 times lower than published reference values. Fifty-six highly experienced experts gave three simulators (Premature AirwayPaul: 5.1 ± 1.0, Premature Anne 4.9 ± 1.1, Preterm Baby 5.0 ± 1.0) good overall ratings and one simulator (Premie HAL S2209: 2.8 ± 1.0) an unfavorable rating.

Conclusion
The simulator physiology deviated significantly from preterm infants’ reference values concerning resistance and compliance, potentially promoting a wrong ventilation technique.

Impact

Very low birth weight infant simulators showed physiological properties far deviating from corresponding patient reference values.

Only ventilation with very high peak pressure achieved tidal volumes in the simulators, as aimed at in very low birth weight infants, potentially promoting a wrong ventilation technique.

Compared to very low birth weight infant cadavers, most tested simulators accurately reproduced the anatomic angular relationships, but their airway dimensions were relatively too large for the represented body.

The more professional experience the experts had, the lower they rated the very low birth weight infant simulators.