bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence of Comorbidity between Dry Eye and Allergic Conjunctivitis: A Systematic Review and Meta-Analysis
Authors: Akasaki Yasutsugu , Inomata Takenori , Sung Jaemyoung , Nakamura Masahiro , Kitazawa Koji , Shih Kendrick Co , Adachi Takeya , Okumura Yuichi , Fujio Kenta , Nagino Ken , Midorikawa-Inomata Akie , Kuwahara Mizu , Hirosawa Kunihiko , Huang Tianxiang , Morooka Yuki , Shokirova Hurramhon , Eguchi Atsuko , Murakami Akira
Published: June 2022

This systematic review aimed to determine the comorbid dry eye (DE) and allergic conjunctivitis (AC) prevalence. We searched PubMed and EMBASE for articles published until 22 March 2022, combining the terms “(dry eye OR keratoconjunctivitis sicca) AND allergic conjunctivitis.” Study-specific estimates (DE and AC incidence rates among patients with AC and DE, respectively) were combined using the one-group meta-analysis in a random-effects model. The initial search yielded 700 studies. Five articles reporting AC incidence among individuals with DE and six articles reporting DE incidence among individuals with AC were included in the qualitative synthesis. In these nine articles, the total sample size was 7254 patients. The DE incidence among individuals with AC was 0.9–97.5%; the AC incidence among individuals with DE was 6.2–38.0%. One-group meta-analysis using a random-effects model showed that 47.2% (95% confidence interval: 0.165–0.779; 320/1932 cases) of patients with AC had comorbid DE and 17.8% (95% confidence interval: 0.120–0.236; 793/4855 cases) of patients with DE had comorbid AC, as defined by each article. Complimentary screening and treatment for patients with DE and AC may improve long-term outcomes and prevent chronic ocular damage in highly susceptible populations.
Extra Proximal-Gradient Network with Learned Regularization for Image Compressive Sensing Reconstruction
Authors: Zhang Qingchao , Ye Xiaojing , Chen Yunmei
Published: June 2022

Learned optimization algorithms are promising approaches to inverse problems by leveraging advanced numerical optimization schemes and deep neural network techniques in machine learning. In this paper, we propose a novel deep neural network architecture imitating an extra proximal gradient algorithm to solve a general class of inverse problems with a focus on applications in image reconstruction. The proposed network features learned regularization that incorporates adaptive sparsification mappings, robust shrinkage selections, and nonlocal operators to improve solution quality. Numerical results demonstrate the improved efficiency and accuracy of the proposed network over several state-of-the-art methods on a variety of test problems.
Investigation of Vortex Structure Modulation by Spume Droplets in the Marine Atmospheric Boundary Layer by Numerical Simulation
Authors: Druzhinin Oleg A. , Tsai Wu-Ting
Published: June 2022

Direct numerical simulation (DNS) of a droplet-laden, turbulent Couette airflow over a waved water surface is performed modeling the marine atmospheric boundary (MABL) layer carrying idealized spume droplets. Both the instantaneous and mean flow properties, the characteristics of the vortex structures and the momentum exchange between air turbulence and waved water surface and droplet-mediated momentum transfer are investigated. A Eulerian–Lagrangian approach is employed in DNS where full, 3D Navier–Stokes equations for the carrier air are solved in a Eulerian frame, and the trajectories of individual droplets are simultaneously tracked in a Lagrangian frame. The impact of the droplets on the carrier air flow is modeled via a point force approximation. The droplets size is considered in the range of spume droplet sizes observed in MABL. Various water surface roughness and droplet injection scenarios are considered, and both instantaneous and phase-averaged flow fields, the Reynolds stresses and the eigenvalues of the local air velocity gradient tensor are evaluated in DNS. Numerical results show a strong dependence of the droplet-mediated airflow modification on-the-droplet injection mechanism. Droplets injected with the surrounding air velocity effectively mitigate the vortex structures by reducing their swirling strength and suppress the momentum flux from air turbulence to water surface by weakening both ejections and sweeping events, and thus accelerating the mean flow as compared to the droplet-free flow. On the other hand, droplets injected with the velocities of the Lagrangian particles of the water surface enhance both the swirling strength of the vortex structures and air-flow turbulent stresses and decelerate the mean wind. The results also show that these effects of droplet-mediated flow modification become less pronounced as the water surface wave steepness increases.
3D Numerical Modeling and Quantification of Oblique Wave Forces on Coastal Bridge Superstructures
Authors: Jia Lei , Zhang Yu , Zhu Deming , Dong You
Published: June 2022

Simply supported bridges comprise the majority of bridge systems in coastal communities and are susceptible to severe damage from extreme waves induced by storms or tsunamis. However, the effects of oblique wave impacts have been less investigated due to the lack of appropriate numerical models. To address this issue, this study investigates the effects of wave incident angles on coastal bridge superstructures by developing an advanced computational fluid dynamics (CFD) model. Different wave scenarios, including wave height, relative clearance, incident angle, and wavelength are tested. It is found that the maximum wave forces in the horizontal and longitudinal directions could reach 1901 and 862 kN under extreme conditions, respectively, destroying bearing connections. Three surrogate models, i.e., the Gaussian Kriging surrogate model, the Artificial Neural Network (ANN), and the Polynomial Chaos Expansion (PCE), are established by correlating the wave parameters with the maximum wave forces. Through comparisons among the three surrogate models, it is found that the 3-order PCE model has better performance in predicting loads in vertical and horizontal directions, while the ANN model is more suitable for results in the longitudinal direction. This study contributes to the optimized design of coastal bridges and also offers an opportunity for future studies to investigate hazard damage-mitigation measures.
Phylogeny and Diversity of the Genus Pseudohydnum (Auriculariales, Basidiomycota)
Authors: Zhou Hong-Min , Liu Hong-Gao , Gates Genevieve M. , Wu Fang , Dai Yu-Cheng , Cooper Jerry A.
Published: June 2022

The toothed jelly fungus Pseudohydnum gelatinosum was originally described from Europe. The name has a broad sense and the species has been widely reported almost all over the world. We have studied samples of so-called P. gelatinosum from Asia and Oceania. Based on morphology, hosts, geography, and phylogenetic analysis using the internal transcribed spacer regions (ITSs) and the large subunit of nuclear ribosomal RNA gene (nLSU), four new species, P. himalayanum, P. orbiculare, P. sinogelatinosum, and P. tasmanicum, from China, New Zealand, and Australia are described and illustrated, and a new combination, Pseudohydnum totarae, is proposed. The five new taxa can be differentiated by the shape of their basidiomata, pileal surface color when fresh, spine size, basidiospore dimensions, shape of hyphidia, hosts, and biogeography. Phylogenetically, most of these taxa are distantly related, and different base pairs among these taxa mostly account for >2% nucleotides in the ITS regions.
Development of Machine Learning Models Predicting Estimated Blood Loss during Liver Transplant Surgery
Authors: Park Sujung , Park Kyemyung , Lee Jae Geun , Choi Tae Yang , Heo Sungtaik , Koo Bon-Nyeo , Chae Dongwoo
Published: June 2022

The incidence of major hemorrhage and transfusion during liver transplantation has decreased significantly over the past decade, but major bleeding remains a common expectation. Massive intraoperative hemorrhage during liver transplantation can lead to mortality or reoperation. This study aimed to develop machine learning models for the prediction of massive hemorrhage and a scoring system which is applicable to new patients. Data were retrospectively collected from patients aged >18 years who had undergone liver transplantation. These data included emergency information, donor information, demographic data, preoperative laboratory data, the etiology of hepatic failure, the Model for End-stage Liver Disease (MELD) score, surgical history, antiplatelet therapy, continuous renal replacement therapy (CRRT), the preoperative dose of vasopressor, and the estimated blood loss (EBL) during surgery. The logistic regression model was one of the best-performing machine learning models. The most important factors for the prediction of massive hemorrhage were the disease etiology, activated partial thromboplastin time (aPTT), operation duration, body temperature, MELD score, mean arterial pressure, serum creatinine, and pulse pressure. The risk-scoring system was developed using the odds ratios of these factors from the logistic model. The risk-scoring system showed good prediction performance and calibration (AUROC: 0.775, AUPR: 0.753).
Deep Learning to Detect Triangular Fibrocartilage Complex Injury in Wrist MRI: Retrospective Study with Internal and External Validation
Authors: Lin Kun-Yi , Li Yuan-Ta , Han Juin-Yi , Wu Chia-Chun , Chu Chi-Min , Peng Shao-Yu , Yeh Tsu-Te
Published: June 2022

Objective: To use deep learning to predict the probability of triangular fibrocartilage complex (TFCC) injury in patients’ MRI scans. Methods: We retrospectively studied medical records over 11 years and 2 months (1 January 2009–29 February 2019), collecting 332 contrast-enhanced hand MRI scans showing TFCC injury (143 scans) or not (189 scans) from a general hospital. We employed two convolutional neural networks with the MRNet (Algorithm 1) and ResNet50 (Algorithm 2) framework for deep learning. Explainable artificial intelligence was used for heatmap analysis. We tested deep learning using an external dataset containing the MRI scans of 12 patients with TFCC injuries and 38 healthy subjects. Results: In the internal dataset, Algorithm 1 had an AUC of 0.809 (95% confidence interval—CI: 0.670–0.947) for TFCC injury detection as well as an accuracy, sensitivity, and specificity of 75.6% (95% CI: 0.613–0.858), 66.7% (95% CI: 0.438–0.837), and 81.5% (95% CI: 0.633–0.918), respectively, and an F1 score of 0.686. Algorithm 2 had an AUC of 0.871 (95% CI: 0.747–0.995) for TFCC injury detection and an accuracy, sensitivity, and specificity of 90.7% (95% CI: 0.787–0.962), 88.2% (95% CI: 0.664–0.966), and 92.3% (95% CI: 0.763–0.978), respectively, and an F1 score of 0.882. The accuracy, sensitivity, and specificity for radiologist 1 were 88.9, 94.4 and 85.2%, respectively, and for radiologist 2, they were 71.1, 100 and 51.9%, respectively. Conclusions: A modified MRNet framework enables the detection of TFCC injury and guides accurate diagnosis.
Investor Perception, Market Reaction, and Post-Issue Performance in Bank Seasoned Equity Offerings
Authors: Krishnan CNV , He Yu
Published: June 2022

Using a large sample of bank seasoned equity offerings (SEO) from 2002 to 2017, we first documented detailed descriptive statistics, and showed that nonperforming assets ratio, our primary measure of bank asset quality, reached the highest value immediately after the 2008 economic crisis, which also corresponds to a higher number of SEOs around these years because banks needed to recapitalize. The capital ratio, which is required to be at least at a minimum level (relative to risk-weighted assets) for banks by regulation, also increased after the economic crisis, which may be due to a higher requirement for banks as well as banks’ desire to hold more capital. The SEO announcement period abnormal stock-returns reached the lowest number around the economic crisis, as did the longer-run 6-month, post-SEO cumulative abnormal returns and buy-and-hold abnormal returns. Examining the differences between banks, we found, in both univariate and multivariate regression results controlling for other variables, that the bank capital ratio as at the time of the SEO announcement is significantly and positively associated with announcement period abnormal returns, while nonperforming assets ratio of the bank as at the time of SEO announcements is not. However, the nonperforming assets ratio as at the time of the SEO announcements had a significantly negative association with post-SEO, 6-month longer-run abnormal stock returns, while the capital ratio did not have any significant association. The nonperforming assets ratio as at the time of SEO announcement was also significantly and negatively related to bank return on assets 6 months and 12 months after SEO, while the capital ratio was not. Thus, investors appear to perceive a well-ingrained, well-publicized regulatory norm—the capital ratio—as indicative of value creation as at the time of bank SEO announcements, while loan asset quality, which may be relatively more opaque, may determine post-SEO performance.
Strategy and Practice for Sustainability in Businesses in the Middle East and North Africa in a Global Perspective
Authors: Ismail Ayman , Boutaleb Fatima , Karadeniz Esra E. , Menipaz Ehud , Bouhaddioui Chafik , Rahman Widad A. , Sanchez-Ruiz Lidia , Schøtt Thomas
Published: June 2022

A business may adopt a strategy for sustainability and may implement its strategy in its practice. Our question is, how are strategy and practice coupled and shaped by entrepreneurs and businesses embedded in national eco-systems in the Middle East and North Africa and around the world? Businesses were randomly sampled and surveyed in 2021, and national conditions were assessed by experts in ten countries in the Middle East and North Africa and in Spain and other countries around the world, as part of the Global Entrepreneurship Monitor. Strategy and practice are found to have a loose coupling but are tighter in the Middle East and North Africa than in Spain. Strategy is promoted by support from businesses and governments, but support depends on national wealth. Strategy and practice by entrepreneurs and businesses are promoted by the entrepreneurs’ human and social capital and the value of making a difference in the world and continuing a family tradition. Findings contribute to understanding business engagement with sustainability, specifically in the Middle East and North Africa, as compared to Spain and in a global perspective.
Preferred Attributes for Sustainable Wetland Management in Mpologoma Catchment, Uganda: A Discrete Choice Experiment
Authors: Bunyangha Jackson , Muthumbi Agnes. W. N. , Egeru Anthony , Asiimwe Robert , Ulwodi Dunston W. , Gichuki Nathan. N. , Majaliwa Mwanjalolo. J. G.
Published: June 2022

Sustainable wetland management is a focus of many countries worldwide. These mainly use protection as a key policy directive for conservation. However, avoidance directives tend to disenfranchise local populations. Thus, such management is often resisted and rarely effective. Tailoring management strategies to user preferences allows conservation to support community livelihoods for sustainable development. This study employed a discrete choice experiment to determine the wetland management attributes preferred by residents of Mpologoma catchment as a prelude to developing a co-management system. Listed in descending order, attribute preferences were paddy farmers’ schemes, fish farming, education and research, protected wetland area, and recreation and tourism. Respondents’ characteristics influenced their choices. Older adults were more likely to support fish farming. In contrast, existing paddy farmers tended to resist such focuses and an increase in protected wetland area. Additionally, respondents with higher education were opposed to paddy farmers’ schemes, and the preference for education and research was positively influenced by respondents’ income. Respondents were willing to pay between $0.64 and $1.76 per household for each unit improvement in the preferred attribute. Our results underscore the role of DCEs in unlocking individuals’ attribute preferences, whose integration into co-management systems can be important for sustainable wetland conservation.
Impact of Ecological Compensation on Farmers’ Livelihood Strategies in Energy Development Regions in China: A Case Study of Yulin City
Authors: Wen Qi , Fang Jie , Li Xia , Su Fang
Published: June 2022

Ecological compensation affects farmers’ livelihoods, as well as sustainability and social equity. Yulin City is the core area of the energy “Golden Triangle” in China. The farmers livelihood strategy model was used to analyse data from a household survey and interviews with selected farmers. The paper analyses the current livelihood strategies of farmers and impact of ecological compensation from the perspective of participation and income. The results showed that: (1) the significant difference between the coal resource development and oil and gas resource development was agricultural planting. Migrant work and non-agricultural self-employment in the coal resource development region were higher than that of the oil and gas resource development region. (2) The income from agricultural planting in the coal resource development region was significantly lower than that of the oil and gas resource development region. The labour, non-agricultural self-employment, and transfer incomes were higher in the coal resource development region than that in the oil and gas resource development region. (3) Ecological compensation has a significant negative effect on participation and income from agricultural planting, as well as a positive effect on participation and income from non-agricultural self-employment. We have proposed measures to strengthen ecological compensation mechanisms and improve the farmers’ livelihoods, in order to inform decision-making and high-quality sustainable development in energy development region.
Quality of Multicenter Studies Using MRI Radiomics for Diagnosing Clinically Significant Prostate Cancer: A Systematic Review
Authors: Bleker Jeroen , Kwee Thomas C. , Yakar Derya
Published: June 2022

Background: Reproducibility and generalization are major challenges for clinically significant prostate cancer modeling using MRI radiomics. Multicenter data seem indispensable to deal with these challenges, but the quality of such studies is currently unknown. The aim of this study was to systematically review the quality of multicenter studies on MRI radiomics for diagnosing clinically significant PCa. Methods: This systematic review followed the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Multicenter studies investigating the value of MRI radiomics for the diagnosis of clinically significant prostate cancer were included. Quality was assessed using the checklist for artificial intelligence in medical imaging (CLAIM) and the radiomics quality score (RQS). CLAIM consisted of 42 equally important items referencing different elements of good practice AI in medical imaging. RQS consisted of 36 points awarded over 16 items related to good practice radiomics. Final CLAIM and RQS scores were percentage-based, allowing for a total quality score consisting of the average of CLAIM and RQS. Results: Four studies were included. The average total CLAIM score was 74.6% and the average RQS was 52.8%. The corresponding average total quality score (CLAIM + RQS) was 63.7%. Conclusions: A very small number of multicenter radiomics PCa classification studies have been performed with the existing studies being of bad or average quality. Good multicenter studies might increase by encouraging preferably prospective data sharing and paying extra care to documentation in regards to reproducibility and clinical utility.
Experimental Investigation and Parametric Optimization of the Tungsten Inert Gas Welding Process Parameters of Dissimilar Metals
Authors: Assefa Anteneh Teferi , Ahmed Gulam Mohammed Sayeed , Alamri Sagr , Edacherian Abhilash , Jiru Moera Gutu , Pandey Vivek , Hossain Nazia
Published: June 2022

Special attention is required when joining two materials with distinct chemical, physical and thermal properties in order to make the joint bond robust and rigid. The goal of this study was to see how significantly different tungsten inert gas (TIG) welding process parameters (welding current, gas flow rate, root gap, and filler materials) affect mechanical properties (tensile, hardness, and flexural strength), as well as the bead width and microstructural properties, of dissimilar welds In comparison to SS 316 and AISI 1020 low-carbon steel. TIG welding parameters were optimized in this study using a Taguchi-based desirability function analysis (DFA). From the experimental results, it was observed that welded samples employing ER-309L filler wires had a microstructure consisting of a delta ferrite network in an austenite matrix. The tensile strength experimental results revealed that welding current, followed by GFR, was a highly influential parameter on tensile strength. Weld metals had higher hardness and flexural strength than stainless steel and carbon steel base metals. This was supported by the fact that the results of our tests had hardness ratings greater than a base for the FZ and HAZ, and that no crack was observed in the weld metal following U-shape flexural bending. Welding current has a significant impact on the bead width of welded specimens, followed by root gap. Furthermore, the dissimilar welded sample responses were optimized with a composite desirability percentage improvement of 22.90% by using a parametric setting of (A2B4C4D2). Finally, the validation of the experiment was validated by our confirmation test results, which agreed with the predictive optimum parameter settings.
Creep Life Prediction of 10CrMo9–10 Steel by Larson–Miller Model
Authors: Guštin Agnieszka Zuzanna , Žužek Borut , Podgornik Bojan
Published: June 2022

Creep is defined as the permanent deformation of materials under the effect of sustained stress and elevated temperature for long periods of time, which can essentially lead to fracture. Due to very time-consuming and expensive testing requirements, existing experimental creep data are often analyzed using derived engineering parameters and models to predict and find the correlations between creep life (time to rupture), temperature and stress. The objective of this study was to analyze and compare different numerical algorithms by using the Larson–Miller parameter (LMP) extrapolation model. Calculations were performed using the classical LMP equation where different values of parameter C were selected, as well as using a modified LMP equation in which parameter C was stress dependent C(σ). The impact of two different approaches of extrapolation and correlation functions (linear and polynomial) applied to fit the LMP model was also investigated. A detailed analysis was performed to choose the best extrapolation fit function and error tolerance. The numerical algorithm implemented was validated through creep rupture testing performed on 10CrMo9–10 steel at 600 °C (873 K) and 80 MPa. Creep model behavior analysis proved that different values of C can significantly change the estimated time to rupture. An excellent response of the LMP model was obtained by considering polynomial dependency when parameter C was assumed to be 18, especially for the temperature range from 773 to 873 K. Promising results were also achieved when parameter C was taken as stress-dependent, but only for linear fitting, which requires further analysis. However, at validation stage it turned out that only the linear extrapolation function and C taken as a constant value provided adequate time-to-rupture prediction. In the case of C = 18, estimated time was slightly overestimated (~8%) and for C = 20 it was underestimated by 27%. In all other cases error largely exceeded 50%.
A New Model Supporting Stability Quality of Materials and Industrial Products
Authors: Siwiec Dominika , Pacana Andrzej
Published: June 2022

Stabilizing the quality of industrial product materials remains a challenge. This applies mainly to new or significantly modified materials. It also refers to special processes. The tests of product quality can stabilize the quality of industrial product materials. The popular method for this is using the non-destructive testing (NDT). The NDT identifies incompatibility but does not determine the cause of its occurrence. Hence, it was necessary to support the process of identifying causes of incompatibilities in products. The purpose of the article was to develop a model based on a new approach to determine the ranking of actions that are possible as part of the process of stabilizing the quality of industrial products. The model was developed to improve quality through sequential and systematic methods of identification (and reduce) and incompatibility. The quality management techniques and decision method were applied and combined in this model, i.e., SMART(-ER) the method, method of selecting a team of experts, brainstorming (BM), Ishikawa diagram with the 5M rule, Likert scale validation technique, arithmetic average, and Grey Relational Analysis (GRA). The test of this model was carried out to find cracks in the outer hull of 418 alloy four-point bearing (CPW-S 5616), which was identified by NDT (magnetic-powder method). As a result, a ranking of activities was obtained to stabilize the quality of the product and the main cause of incompatibility was indicated, i.e., the cause which can influence to the most degree influence on occurrence the incompatibility. The originality of the proposed model is an application in the right order of specially selected and combined qualitative methods and supporting decision methods. The finding of causes of incompatibility of products is the basis of product improvement in the area of stabilizing the quality of materials, mainly by the occurrence of special processes. The universality of the model refers to the possibility of its application for any material, processes of its formation, and processes of products, and any incompatibilities where the model can be integrated with quality control.
Thermal-Mechanical Coupling Model Based on the Hybrid Finite Element Method for Solving Bipolar the Plate Deformation of Hydrogen Fuel Cells
Authors: Chen Wenxing , Dai Shuyang , Zheng Baojuan
Published: June 2022

New energy is the focus of attention all over the world, and research into new energy can inject new vitality into the industrial system. Hydrogen fuel cells are not only environmentally friendly, but also rich in reserves that can be used as a strategic resource for the entire country. The difficulty lies in the safe design of application equipment and the batch generation and storage of hydrogen. In addition, fuel cells have the disadvantage of a slow start-up. Based on the above problems, this paper proposes a hybrid-element method to solve the thermal-mechanical coupling model of fuel cell plate, which can effectively solve the thermal stress change, temperature field distribution and displacement change of the battery plate when working. Firstly, the hybrid-element algorithm is given for 2D plate deformation. Then, the deformation application of a 3D fuel cell plate is given. The 2D numerical results show that the hybrid finite element method (FEM) is more flexible for realizing the flexible combination of sub-mesh and finite element basis functions, and has a better mesh quality compared to the traditional constant strain triangular element (CST) adaptive FEM and quadrilateral isoparametric element (Q4) adaptive FEM. This method achieves a balance between numerical accuracy and solving efficiency for the multi-porous elastic plate. In addition, a deformation control formula is given which can display the displacement deformation and stress merge to same graph, since it is convenient to quickly compare the regions where the displacement and stress extremum appear. In short, the hybrid finite element method proposed in this paper has good mesh evaluation results, and when the number of discrete elements is equivalent, the hybrid element converges faster and the solution efficiency is higher. This paper also provides a good numerical theory and simulation reference for industrial mechanics and new energy applications.
Wearable Inductive Sensing of the Arm Joint: Comparison of Three Sensing Configurations
Authors: Byberi Armanda , K. Amineh Reza , Ravan Maryam
Published: June 2022

Currently, there is a rapidly growing interest and demand for wearable textile sensors that can monitor human motions in a naturalistic environment. Some potential applications for this technology include research on measuring the motor skill performance of patients with motor disabilities such as autism spectrum disorder, Parkinson’s disease, cerebral palsy, and stroke and evaluating the efficacy of applied treatments. Among wearable sensors, inductive sensors that are made from highly conductive threads are attractive due to their easy development process, high reliability, and low cost. In this study, we analyzed and compared the performance of three inductive wearable sensor configurations—(1) single planar rectangular coil, (2) two separated coils connected in series, and (3) two helical coils connected in series—in terms of the change in the resonant frequency of the tank circuit they comprised as a result of the change in elbow joint angle through simulations. Three parameters of length, width, and the number of turns were considered to calculate sensor sensitivity to the joint angle. The coil with the highest sensitivity was then fabricated and measured, and its performance was compared with the simulation results. The proposed methodology can be extended to sensing other joints in the body such as the shoulders, fingers, and knees.
Breaking of Odd Chirality in Magnetoelectrodeposition
Authors: Mogi Iwao , Morimoto Ryoichi , Aogaki Ryoichi , Takahashi Kohki
Published: June 2022

Electrodeposition under magnetic fields (magnetoelectrodeposition; MED) can induce surface chirality on copper films. The chiral signs of MED films should depend on the magnetic field polarity; namely, the reversal of the magnetic field causes the opposite chiral sign. This represents odd chirality for the magnetic field polarity. However, odd chirality was broken in several MED conditions. This paper makes a survey of breaking of odd chirality in the MED conditions such as low magnetic fields, specific adsorption of chloride ions, micro-electrode, and cell rotation. These results indicate that the ordered fluctuation of magnetohydrodynamic micro-vortices induces the breaking of odd chirality and that the random fluctuation results in the disappearance of surface chirality.
Hyers–Ulam Stability of a System of Hyperbolic Partial Differential Equations
Authors: Marian Daniela , Ciplea Sorina Anamaria , Lungu Nicolaie
Published: June 2022

In this paper, we study Hyers–Ulam and generalized Hyers–Ulam–Rassias stability of a system of hyperbolic partial differential equations using Gronwall’s lemma and Perov’s theorem.
Stochastic Transcription with Alterable Synthesis Rates
Authors: Zhu Chunjuan , Chen Zibo , Sun Qiwen
Published: June 2022

Background: Gene transcription is a random bursting process that leads to large variability in mRNA numbers in single cells. The main cause is largely attributed to random switching between periods of active and inactive gene transcription. In some experiments, it has been observed that variation in the number of active transcription sites causes the initiation rate to vary during elongation. Results: We established a mathematical model based on the molecular reaction mechanism in single cells and studied a stochastic transcription system consisting of two active states and one inactive state, in which mRNA molecules are produced with two different synthesis rates. Conclusions: By calculation, we obtained the average mRNA expression level, the noise strength, and the skewness of transcripts. We gave a necessary and sufficient condition that causes the average mRNA level to peak at a limited time. The model could help us to distinguish an appropriate mechanism that may be employed by cells to transcribe mRNA molecules. Our simulations were in agreement with some experimental data and showed that the skewness can measure the deviation of the distribution of transcripts from the mean value. Especially for mature mRNAs, their distributions were almost able to be determined by the mean, the noise (or the noise strength), and the skewness.
Examining Consumer’s Intention to Adopt AI-Chatbots in Tourism Using Partial Least Squares Structural Equation Modeling Method
Authors: Rafiq Farrukh , Dogra Nikhil , Adil Mohd , Wu Jei-Zheng
Published: June 2022

Artificial intelligence (AI) is an important link between online consumers and the tourism industry. AI-chatbots are the latest technological advancement that have shaped the tourism industry. AI-chatbots are a relatively new technology in the hospitality and tourism industries, but little is known about their use. The study aims to identify factors influencing AI-chatbot adoption and their use in improving customer engagement and experiences. Using an offline survey, researchers collected data from 530 respondents. Using the structural equation modeling technique, the conceptual model was empirically tested. According to the results, the S-O-R theoretical framework is suitable for evaluating chatbot adoption intentions. Additionally, the structural model supported the ten hypotheses, validating the suggested directions of substantial impacts. In addition to practitioners and tourism managers, this study also has broad implications for scholars.
Developing Prospective Teachers’ Beliefs about Digital Tools and Digital Feedback
Authors: Speer Annabelle , Eichler Andreas
Published: June 2022

In classrooms today, teachers are asked to support their teaching with digital tools. For this purpose, teachers require not only technological knowledge but also corresponding beliefs about the advantages of digital tools. The development of those beliefs should already be embedded in the university education of teachers. To this end, we developed a university seminar aimed at fostering prospective teachers’ confidence in the utility of digital tools, using the digital tool STACK as an example. The seminar is based on learning mathematics with the digital tool STACK, independently designing digital tasks with said tool, and finally, reflecting on a teaching experiment with school students using STACK. To make the development of prospective teachers’ beliefs visible throughout the seminar, we worked with different qualitative methods. The results of this case study show that there are four developmental phases of prospective teachers’ beliefs which include an initial situation, a purely positive phase, a disillusionment, and a phase of differentiated beliefs. It becomes apparent that it is possible to develop prospective teachers’ beliefs about digital tools in a positive way.
The Torsional Rigidity of a Rectangular Prism
Authors: Tsai Cho-Liang , Wang Chih-Hsing , Hwang Sun-Fa , Chen Wei-Tong , Cheng Chin-Yi
Published: June 2022

Using the membrane analogy, in 1934 Timoshenko derived the torsional rigidity of a rectangular prism of isotropic material as a function of its material shear modulus, width and thickness. However, he did not consider the energy conservation criterion, as it could be either unnecessary or replaced by other criteria in Timoshenko’s process. To confirm the correctness of Timoshenko’s solution, this work re-derives the torsional rigidity by considering all the equilibrium conditions, boundary conditions, symmetric and anti-symmetric conditions of displacement and stress, the energy conservation criterion, and even the energy minimization criterion. Using the TSAI technique, exact solutions for the displacements, strains, stresses and the torsional rigidity are derived perfectly. The derived torsional rigidity is in a completely different form from that derived by Timoshenko and is numerically identical. Interestingly, the solutions derived in this work verify that, when the values of the width and thickness of the rectangular prism are swapped, the value of the torsional rigidity remains the same, which makes perfect sense physically but is not discussed in Timoshenko’s process or any other research. This work presents a procedure considering all the mathematical details and the results remain correct when the width and thickness of the prism swap. This fact makes perfect sense physically, though has never been expounded before in Timoshenko’s or other researchers’ solutions, either for torsional rigidity or for the induced shear stresses and displacements.
Bistatic Radar Observations Correlation of LEO Satellites Considering J2 Perturbation
Authors: Huyan Zongbo , Jiang Yu , Li Hengnian , Ma Pengbin , Zhang Dapeng
Published: June 2022

Space debris near Earth severely interferes with the development of space, and cataloging space objects is increasingly important. Since optical telescopes and radars used to detect space debris only provide short-arc observations, mathematical algorithms are needed to solve problems in the correlation of observations. In this work, an efficient mathematical algorithm based on J2 analytic solutions is put forward. Initial orbit determination (IOD) serves as the starter and orbit determination (OD) with the weighted least-squares method (WLSM) is used to improve the accuracy of the estimated orbit. Meanwhile, the effect of the weight of different observation types is analyzed. The correlation criteria for bistatic radar observations are accordingly developed. Lastly, the variation in and evolution of the error of bistatic radar ranging are discussed.
Asymptotic Regularity and Existence of Time-Dependent Attractors for Second-Order Undamped Evolution Equations with Memory
Authors: Wang Xuan , Hu Didi , Gao Chenghua
Published: June 2022

Our purpose in this article is to study the asymptotic behavior of undamped evolution equations with fading memory on time-dependent spaces. By means of the theory of processes on time-dependent spaces, asymptotic a priori estimate and the technique of operator decomposition and the existence and asymptotic regularity of time-dependent attractors are, respectively, established in the critical case. At the same time, we also obtain the asymptotic regularity of the solution.
A Novel Effective Vehicle Detection Method Based on Swin Transformer in Hazy Scenes
Authors: Sun Zaiming , Liu Chang’an , Qu Hongquan , Xie Guangda
Published: June 2022

Under bad weather, the ability of intelligent vehicles to perceive the environment accurately is an important research content in many practical applications such as smart cities and unmanned driving. In order to improve vehicle environment perception technology in real hazy scenes, we propose an effective detection algorithm based on Swin Transformer for hazy vehicle detection. This algorithm includes two aspects. First of all, for the aspect of the difficulty in extracting haze features with poor visibility, a dehazing network is designed to obtain high-quality haze-free output through encoding and decoding methods using Swin Transformer blocks. In addition, for the aspect of the difficulty of vehicle detection in hazy images, a new end-to-end vehicle detection model in hazy days is constructed by fusing the dehazing module and the Swin Transformer detection module. In the training stage, the self-made dataset Haze-Car is used, and the haze detection model parameters are initialized by using the dehazing model and Swin-T through transfer learning. Finally, the final haze detection model is obtained by fine tuning. Through the joint learning of dehazing and object detection and comparative experiments on the self-made real hazy image dataset, it can be seen that the detection performance of the model in real-world scenes is improved by 12.5%.
The Generalized Odd Linear Exponential Family of Distributions with Applications to Reliability Theory
Authors: Jamal Farrukh , Handique Laba , Ahmed Abdul Hadi N. , Khan Sadaf , Shafiq Shakaiba , Marzouk Waleed
Published: June 2022

A new family of continuous distributions called the generalized odd linear exponential family is proposed. The probability density and cumulative distribution function are expressed as infinite linear mixtures of exponentiated-F distribution. Important statistical properties such as quantile function, moment generating function, distribution of order statistics, moments, mean deviations, asymptotes and the stress–strength model of the proposed family are investigated. The maximum likelihood estimation of the parameters is presented. Simulation is carried out for two of the mentioned sub-models to check the asymptotic behavior of the maximum likelihood estimates. Two real-life data sets are used to establish the credibility of the proposed model. This is achieved by conducting data fitting of two of its sub-models and then comparing the results with suitable competitive lifetime models to generate conclusive evidence.
Systematic Review of Patient-Reported Outcome Measures for Patients with Exercise-Induced Leg Pain
Authors: Castillo-Domínguez Alejandro , García-Romero Jerónimo C. , Alvero-Cruz José Ramón , Ponce-García Tomás , Benítez-Porres Javier , Páez-Moguer Joaquín
Published: June 2022

Background and Objectives: To determine the most commonly used patient-reported outcome measures (PROMs) in exercise-induced leg pain (EILP) and to identify specific PROMs for EILP in order to evaluate their psychometric properties and methodological quality. Materials and Methods: A strategic search was performed in different databases to identify and extract the characteristics of studies based on the use of PROMs in patients with EILP. Specific PROMs were evaluated according to the Terwee et al. and COSMIN criteria. Results: Fifty-six studies were included in the review. The Medial Tibial Stress Syndrome Score (MTSSS), Lower Extremity Functional Scale (LEFS) and Exercise-Induced Leg Pain Questionnaire (EILP-Q) were identified as specific PROMs for EILP. The Visual Analog Scale (VAS) was the most widely used instrument in the assessment of EILP. The methodological quality assessment showed six positive values for the LEFS, four for the MTSSS and three for the EILP-Q for the eight psychometric properties analyzed according to the COSMIN criteria. The evaluation of the nine psychometric properties according to Terwee showed five positive values for the LEFS and MTSSS, and three for the EILP-Q. Conclusions: The overall methodological quality of the PROMs used was low. The VAS was the most widely used instrument in the assessment of EILP, and the LEFS was the highest quality PROM available for EILP, followed by the MTSSS and EILP-Q, respectively.
Elevated Transaminases as Predictors of COVID-19 Pneumonia Severity
Authors: Radonjić Tijana , Milićević Ognjen , Jovanović Igor , Zdravković Marija , Dukić Marija , Mandić Olga Milorad , Bjekić-Macut Jelica , Marković Olivera Borko , Todorović Zoran , Brajković Milica , Nikolić Novica , Klašnja Slobodan , Popadić Višeslav , Divac Anica , Marinković Milica , Alhayek Nabil , Branković Marija Svetislav
Published: June 2022

Background: This study aimed to calculate the frequency of elevated liver enzymes in hospitalized patients with coronavirus disease 2019 (COVID-19) infection and to test if liver enzyme biochemistry levels on admission could predict the computed tomography (CT) scan severity score of bilateral interstitial pneumonia. Methods: This single-center study comprised of 323 patients including their demographic data, laboratory analyses, and radiological findings. All the information was taken from electronic health records, followed by statistical analysis. Results: Out of 323 patients, 115 of them (35.60%) had aspartate aminotransferase (AST) and/or alanine aminotransferase (ALT) over 40 U/L on admission. AST was the best predictor of CT scan severity score of bilateral interstitial pneumonia (R2 = 0.313, Adjusted R2 = 0.299). CT scan severity score in the peak of the infection could be predicted with the value of AST, neutrophils, platelets, and monocytes count (R2 = 0.535, Adjusted R2 = 0.495). Conclusion: AST, neutrophils, platelets, and monocytes count on admission can account for almost half (49.5%) of the variability in CT scan severity score at peak of the disease, predicting the extensiveness of interstitial pneumonia related to COVID-19 infection. Liver enzymes should be closely monitored in order to stratify COVID-19 patients with a higher risk of developing severe forms of the disease and to plan the beforehand step-up treatment.
Effect of Residual Stress on Hydrogen Diffusion in Thick Butt-Welded High-Strength Steel Plates
Authors: Jiang Jinhui , Zeng Wenshuo , Li Liangbi
Published: June 2022

Thick high-strength steel plates are increasingly being used for ship structures. Moreover, hydrogen enters the process of manufacturing and service, and large residual tensile stress occurs near the weld. Such stress can facilitate the diffusion and accumulation of hydrogen in the material, leading to hydrogen embrittlement fracture of the shell. Therefore, residual-stress-induced diffusion and accumulation of hydrogen in the stress concentration region of thick butt-welded high-strength steel plate structures need to be studied. In this study, manual metal arc welding was realized by numerical simulation of residual stress in a thick butt-welded high-strength steel plate model using the thermoelastic–plastic theory and a double ellipsoidal heat source model. To analyze residual stress, a set of numerical simulation methods was obtained through comparative analysis of the test results of relevant literature. Residual and hydrostatic stress distributions were determined based on these methods. Then, hydrogen diffusion parameters in each region of the model were obtained through experimental tests. Finally, the results of the residual stress field were used as the predefined field of hydrogen diffusion to conduct a numerical simulation analysis. The distribution of hydrogen diffusion under the influence of residual stress was obtained based on the theory of stress-induced hydrogen diffusion. The weak area of the welding joint was found to be near the weld toe, which exhibited high hydrostatic stress and hydrogen concentration. Further, the maximum hydrogen concentration value of the vertical weld path was approximately 6.1 ppm, and the maximum value of the path parallel to the weld centerline and 31 mm away from the weld centerline was approximately 6.22 ppm. Finally, the hydrostatic tensile stress in the vertical weld path was maximized (~345 MPa), degrading the material properties and causing hydrogen-related cracking. Hence, a reliable method for the analysis of hydrogen diffusion according to residual stress in thick high-strength steel plates was obtained. This work could provide a research basis for controlling and eliminating the adverse effects of hydrogen on the mechanical properties of ship structures and ensuring the safe service of marine equipment.