bluuebunny/crossref_metadata_2025 huggingface dataset:
Examining the Impact of E-Government on Corporate Social Responsibility Performance: The Mediating Effect of Mandatory Corporate Social Responsibility Policy, Corruption, and Information and Communication Technologies Development During the COVID era
Authors: Avotra Andrianarivo Andriandafiarisoa Ralison Ny , Chengang Ye , Sandra Marcelline Tsimisaraka Raymondo , Asad Ali , Yingfei Yang
Published: October 2021

During the Covid-19 era, this research will explore and analyze the link between e-government and corporate social responsibility. In addition, mandatory corporate social responsibility, institutional quality, information and communication technology, and corruption as mediators will also be explored in this study. This research seeks to answer the issue of how e-government affects corporate social responsibility and how other mediating variables might influence this connection. Furthermore, this study developed a total of 13 hypotheses based on these questions, 4 of which have mediating effects. The theoretical underpinning for the proposed study paradigm is provided by stakeholder theory, which has been established based on prior literature. The general philosophy is positivism, and the research has a deductive nature. The information was gathered from 305 managers across four industries: information technology, online services, online education, and logistics and supply chain. Data was collected using a random convenience sampling approach. The Partial Least Square Sequential Equation Modeling (PLS-SEM) research analysis approach was applied in this study for the analysis. The measurement step demonstrated that all constructs and indicators are valid and trustworthy enough to be utilized in the future. The results of the structural model evaluation revealed that e-government had a negative influence on corporate social responsibility, with three of the four mediating roles proving to be completely mediated. As a result, the government and relevant stakeholders should take these results into account when formulating e-government policies.
Investigating Cognitive Flexibility in Preschool Children With Autism Spectrum Disorder
Authors: Zacharov Oleg , Huster Rene Jürgen , Kaale Anett
Published: October 2021

The current study investigated cognitive flexibility in preschool children with Autism Spectrum Disorder (ASD) and those with typical development using the Reverse Categorization (RC) task and the Dimensional Change Card Sort (DCCS) task. We further examined the relationship between non-verbal mental age (NVMA) and the performance on the two tasks. While no significant difference in performance on the RC task between the two groups was found, significantly more children in the typical developing group passed the DCCS task than children in the ASD group. NVMA was found to correlate with performance in both tasks in the typical developing group but not in the ASD group. When the children were matched on NVMA, no differences in task performance between the two groups were found. The current study found the disparity in performance in two groups on the RC and the DCCS tasks, hence illuminating the importance related to the selection of tasks when studying cognitive flexibility in preschool children with ASD. The study also cast some light on the involvement of NVMA in the performance on the RC and DCCS tasks.
A New Opinion Polarization Index Developed by Integrating Expert Judgments
Authors: Koudenburg Namkje , Kiers Henk A. L. , Kashima Yoshihisa
Published: October 2021

Opinion polarization is increasingly becoming an issue in today’s society, producing both unrest at the societal level, and conflict within small scale communications between people of opposite opinion. Often, opinion polarization is conceptualized as the direct opposite of agreement and consequently operationalized as an index of dispersion. However, in doing so, researchers fail to account for the bimodality that is characteristic of a polarized opinion distribution. A valid measurement of opinion polarization would enable us to predict when, and on what issues conflict may arise. The current study is aimed at developing and validating a new index of opinion polarization. The weights of this index were derived from utilizing the knowledge of 58 international experts on polarization through an expert survey. The resulting Opinion Polarization Index predicted expert polarization scores in opinion distributions better than common measures of polarization, such as the standard deviation, Van der Eijk’s polarization measure and Esteban and Ray’s polarization index. We reflect on the use of expert ratings for the development of measurements in this case, and more in general.
Prevalence and Risk Factors of Post-traumatic Stress Disorder Symptoms in Students Aged 8–18 in Wuhan, China 6 Months After the Control of COVID-19
Authors: Chen Yue , Zhu Zhuohong , Lei Fei , Lei Shulan , Chen Jing
Published: October 2021

Objectives: To explore the prevalence of post-traumatic stress disorder (PTSD) symptoms and the factors influencing mental health symptoms in students aged 8–18 in Wuhan, China at 6 months after the COVID-19 pandemic was controlled.

Methods: Questionnaires were distributed to students aged 8–18 in Wuhan through an online platform from September to October 2020, and 15,993 valid surveys were returned, resulting in a response rate of 75.4%. The data related to symptoms of PTSD, anxiety, depression, stress and psychological inflexibility levels, as well as demographic information about the population. Hierarchical multiple regression analyses were performed to examine the predictive effects.

Results: In total, 11.5% of the students met the criteria for clinically concerning PTSD symptoms. Psychological inflexibility was associated with PTSD symptoms, depression, anxiety, and stress symptoms (β = 0.45, 0.63, 0.65 and 0.69, respectively, with ΔR2 = 0.16, 0.32, 0.34 and 0.39, respectively, p < 0.001) in children and adolescents.

Conclusion: This study investigated the impacts of COVID-19 on the mental health status among students aged 8–18 in Wuhan. Even at 6 months after the outbreak was brought under control, some students were still affected. Psychological inflexibility was correlated with psychological symptoms in students. Therefore, methods to reduce psychological inflexibility may help improve the mental health states of students as part of psychological interventions.
Challenges and Resilience-Building: A Narrative Inquiry Study on a Mid-Career Chinese EFL Teacher
Authors: Xue Lina
Published: October 2021

With a high rate of attrition and burnout of teachers as a global concern, teacher resilience has become a trendy topic in the research of their professional development as one of the pillars of positive psychology (positive character traits). However, the literature reveals that little research has been done on the mid-career teachers in the Chinese context, especially on how resilience may be nurtured, sustained, or eroded over time. Focusing on a mid-career EFL female teacher (the author) in China as a case study, this longitudinal self-reflective study employs a narrative inquiry to investigate the challenges that the experienced teacher was encountered with and to depict her trajectories of resilience-building by fleshing out the interaction between challenges, resources, and coping strategies in her three different scenarios. “Hard data,” such as teaching journals, reflective field notes, and messages with students were collected and analyzed inductively by using thematic analysis, and “soft data,” like memory was also referred to. The findings unfolded challenges confronting the experienced teacher peculiar to the Chinese context and charted a detailed bumpy journey of resilience building in three phases, accompanied by her growing emotional, intellectual, and psychological capacities. Implications are drawn out for teacher resilience building, school leaders, and policymakers.
Using Games to Promote English as a Foreign Language Learners’ Willingness to Communicate: Potential Effects and Teachers’ Attitude in Focus
Authors: Liu Fei , Vadivel Balachandran , Rezvani Ehsan , Namaziandost Ehsan
Published: October 2021

This study aims to find out the role of games in promoting students’ willingness to communicate (WTC) and their teachers’ attitude toward it. In order to collect the data, the researchers employed a 28-item questionnaire which was given to 60 English as a Foreign Language (EFL) learners in an English institute. Then, the students were randomly divided into two groups of 30 learners functioning as control and experimental groups. The students in the experimental group received games in their language lessons and classes, while control group learners did not. At the end of the term, the same questionnaire was given to the students to know if playing games had a significant impact on their WTC. In addition, the teachers were asked to answer a 30-item questionnaire to investigate their attitudes toward playing games in language classes. The results showed that most of the teachers in this study believe that games have a positive influence on the students’ attitudes towards learning English and that using them in class serves many educational purposes. In addition, games played a significant role in improving the EFL leaners’ willingness to communicate. In the light of these findings, the researchers suggested using games as energizers and practical activities at the end of class not only to improve enthusiasm for learning, but also to improve the learners’ WTC.
Is the Severity of the Clinical Expression of Anorexia Nervosa Influenced by an Anxiety, Depressive, or Obsessive-Compulsive Comorbidity Over a Lifetime?
Authors: Riquin Elise , Raynal Agathe , Mattar Lama , Lalanne Christophe , Hirot France , Huas Caroline , Duclos Jeanne , Berthoz Sylvie , Godart Nathalie ,   EVHAN group
Published: October 2021

Purpose: The relationship between anxiety or depressive comorbidities, their chronology of onset, and the severity of anorexia nervosa (AN) is not well-studied. We hypothesize that the existence of a comorbidity, particularly before the onset of AN, is associated with greater severity of AN.

Methods: One hundred seventy-seven subjects were assessed. The prevalence of major depressive disorder (MDD), obsessive-compulsive disorder (OCD), generalized anxiety disorder (GAD), and social phobia (SP) as well as their chronology of onset were studied. The assessment criteria of AN severity were the overall clinical condition, body mass index (BMI) on admission, lowest BMI, intensity of the eating symptoms, age at the onset of AN, illness duration, number of hospitalizations, and quality of life.

Results: Patients with AN had the greatest clinical severity when they had a comorbid disorder over their lifetime, such as MDD, GAD, or SP. These comorbidities along with OCD were associated with a higher level of eating symptoms and a more altered quality of life. A profile of maximum severity was associated with a higher prevalence of MDD and GAD. Concerning the chronology of onset, the age at the start of AN was later in cases of MDD or GAD prior to AN.

Conclusion: There seems to be an association between severity of AN and both MDD and GAD. The chronology of onset of the comorbidity did not seem to be associated with the severity.
Long-Term Effects of the Individual Placement and Support Intervention on Employment Status: 6-Year Follow-Up of a Randomized Controlled Trial
Authors: Pichler Eva-Maria , Stulz Niklaus , Wyder Lea , Heim Simone , Watzke Birgit , Kawohl Wolfram
Published: October 2021

People with mental illness often experience difficulties with reintegration into the workplace, although employment is known to assist these individuals in their recovery process. Traditional approaches of “first train, then place” have been recently replaced by supported employment (SE) methods that carry strategy of “first place, then train.” Individual placement and support (IPS) is one of the best-studied methods of SE, which core principles are individualized assistance in rapid job search with consequent placement in a paid employment position. A considerable amount of high-quality evidence supported the superiority of IPS over conventional methods in providing improved employment rates, longer job tenure, as well as higher salaries in competitive job markets. Nonetheless, our knowledge about the IPS-mediated long-term effects is limited. This non-interventional follow-up study of a previously published randomized controlled trial (RCT) called ZhEPP aimed to understand the long-term impact of IPS after 6 years since the initial intervention. Participants from the ZhEPP trial, where 250 disability pensioners with mental illnesses were randomized into either IPS intervention group or treatment as usual group (TAU), were invited to face-to-face interviews, during which employment status, job tenure, workload, and salaries were assessed. One hundred and fourteen individuals agreed to participate in this follow-up study. Although during the first 2 years post-intervention, the IPS group had higher employment rates (40% (IPS) vs. 28% (TAU), p < 0.05 at 24 months), these differences disappeared by the time of follow-up assessments (72 months). The results indicated no substantial differences in primary outcome measures between IPS and TAU groups: employment rate (36 vs. 33%), workload (10.57 vs. 10.07 h per week), job tenure (29 vs. 28 months), and salary (20.21CHF vs. 25.02 CHF). These findings provide important insights regarding the long-term effects of IPS among individuals with mental health illnesses. Further research is required to advance the current knowledge about IPS intervention and its years-long impact.
Machine Learning-Based Electroencephalographic Phenotypes of Schizophrenia and Major Depressive Disorder
Authors: Jang Kuk-In , Kim Sungkean , Kim Soo Young , Lee Chany , Chae Jeong-Ho
Published: October 2021

Background: Psychiatric diagnosis is formulated by symptomatic classification; disease-specific neurophysiological phenotyping could help with its fundamental treatment. Here, we investigated brain phenotyping in patients with schizophrenia (SZ) and major depressive disorder (MDD) by using electroencephalography (EEG) and conducted machine-learning-based classification of the two diseases by using EEG components.

Materials and Methods: We enrolled healthy controls (HCs) (n = 30) and patients with SZ (n = 34) and MDD (n = 33). An auditory P300 (AP300) task was performed, and the N1 and P3 components were extracted. Two-group classification was conducted using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Positive and negative symptoms and depression and/or anxiety symptoms were evaluated.

Results: Considering both the results of statistical comparisons and machine learning-based classifications, patients and HCs showed significant differences in AP300, with SZ and MDD showing lower N1 and P3 than HCs. In the sum of amplitudes and cortical sources, the findings for LDA with classification accuracy (SZ vs. HCs: 71.31%, MDD vs. HCs: 74.55%), sensitivity (SZ vs. HCs: 77.67%, MDD vs. HCs: 79.00%), and specificity (SZ vs. HCs: 64.00%, MDD vs. HCs: 69.67%) supported these results. The SVM classifier showed reasonable scores between SZ and HCs and/or MDD and HCs. The comparison between SZ and MDD showed low classification accuracy (59.71%), sensitivity (65.08%), and specificity (54.83%).

Conclusions: Patients with SZ and MDD showed deficiencies in N1 and P3 components in the sum of amplitudes and cortical sources, indicating attentional dysfunction in both early and late sensory/cognitive gating input. The LDA and SVM classifiers in the AP300 are useful to distinguish patients with SZ and HCs and/or MDD and HCs.
Fischer Linear Discrimination and Quadratic Discrimination Analysis–Based Data Mining Technique for Internet of Things Framework for Healthcare
Authors: Hasan Mohammad Kamrul , Ghazal Taher M. , Alkhalifah Ali , Abu Bakar Khairul Azmi , Omidvar Alireza , Nafi Nazmus S. , Agbinya Johnson I.
Published: October 2021

The internet of reality or augmented reality has been considered a breakthrough and an outstanding critical mutation with an emphasis on data mining leading to dismantling of some of its assumptions among several of its stakeholders. In this work, we study the pillars of these technologies connected to web usage as the Internet of things (IoT) system's healthcare infrastructure. We used several data mining techniques to evaluate the online advertisement data set, which can be categorized as high dimensional with 1,553 attributes, and the imbalanced data set, which automatically simulates an IoT discrimination problem. The proposed methodology applies Fischer linear discrimination analysis (FLDA) and quadratic discrimination analysis (QDA) within random projection (RP) filters to compare our runtime and accuracy with support vector machine (SVM), K-nearest neighbor (KNN), and Multilayer perceptron (MLP) in IoT-based systems. Finally, the impact on number of projections was practically experimented, and the sensitivity of both FLDA and QDA with regard to precision and runtime was found to be challenging. The modeling results show not only improved accuracy, but also runtime improvements. When compared with SVM, KNN, and MLP in QDA and FLDA, runtime shortens by 20 times in our chosen data set simulated for a healthcare framework. The RP filtering in the preprocessing stage of the attribute selection, fulfilling the model's runtime, is a standpoint in the IoT industry.

Index Terms: Data Mining, Random Projection, Fischer Linear Discriminant Analysis, Online Advertisement Dataset, Quadratic Discriminant Analysis, Feature Selection, Internet of Things.
Bioethical Concerns During the COVID-19 Pandemic: What Did Healthcare Ethics Committees and Institutions State in Spain?
Authors: Ruiz-Hornillos Javier , Hernández Suárez Pilar , Marín Martínez Juana María , Miguel Beriain Íñigo de , Nieves Vázquez María Auxiliadora , Albert Marta , Herrera Abián María , Pacheco-Martínez Pedro A. , Trasmontes Victoria , Guillén-Navarro Encarna
Published: October 2021

Objectives: Each new wave of the COVID-19 pandemic invites the possible obligation to prioritize individuals' access to vital resources, and thereby leads to unresolved and important bioethical concerns. Governments have to make decisions to protect access to the health system with equity. The prioritization criteria during a pandemic are both a clinical and legal-administrative decision with ethical repercussion. We aim to analyse the prioritization protocols used in Spain during the pandemic which, in many cases, have not been updated.

Method: We carried out a narrative review of 27 protocols of prioritization proposed by healthcare ethics committees, scientific societies and institutions in Spain for this study. The review evaluated shared aspects and unique differences and proffered a bioethical reflection.

Results: The research questions explored patient prioritization, the criteria applied and the relative weight assigned to each criterion. There was a need to use several indicators, being morbidity and mortality scales the most commonly used, followed by facets pertaining to disease severity and functional status. Although age was initially considered in some protocols, it cannot be the sole criterion used when assigning care resources.

Conclusions: In COVID-19 pandemic there is a need for a unified set of criteria that guarantees equity and transparency in decision-making processes. Establishing treatment indications is not the aim of such criteria, but instead prioritizing access to care resources. In protocols of prioritization, the principle of efficiency must vary according to the principle of equity and the criteria used to guarantee such equity.
Machine Learning Detects Anti-DENV Signatures in Antibody Repertoire Sequences
Authors: Horst Alexander , Smakaj Erand , Natali Eriberto Noel , Tosoni Deniz , Babrak Lmar Marie , Meier Patrick , Miho Enkelejda
Published: October 2021

Dengue infection is a global threat. As of today, there is no universal dengue fever treatment or vaccines unreservedly recommended by the World Health Organization. The investigation of the specific immune response to dengue virus would support antibody discovery as therapeutics for passive immunization and vaccine design. High-throughput sequencing enables the identification of the multitude of antibodies elicited in response to dengue infection at the sequence level. Artificial intelligence can mine the complex data generated and has the potential to uncover patterns in entire antibody repertoires and detect signatures distinctive of single virus-binding antibodies. However, these machine learning have not been harnessed to determine the immune response to dengue virus. In order to enable the application of machine learning, we have benchmarked existing methods for encoding biological and chemical knowledge as inputs and have investigated novel encoding techniques. We have applied different machine learning methods such as neural networks, random forests, and support vector machines and have investigated the parameter space to determine best performing algorithms for the detection and prediction of antibody patterns at the repertoire and antibody sequence levels in dengue-infected individuals. Our results show that immune response signatures to dengue are detectable both at the antibody repertoire and at the antibody sequence levels. By combining machine learning with phylogenies and network analysis, we generated novel sequences that present dengue-binding specific signatures. These results might aid further antibody discovery and support vaccine design.
Re-thinking Women's Sport Research: Looking in the Mirror and Reflecting Forward
Authors: Lebel Katie , Mumcu Ceyda , Pegoraro Ann , LaVoi Nicole M. , Lough Nancy , Antunovic Dunja
Published: October 2021

Despite decades of research and advocacy—women's professional sports continue to be considered second class to men's sports. The goal of this paper is to rethink how we state, present, and solve problems in women's sport. To affect true change, the wisdom of a broad stakeholder group was embraced such that varied perspectives could be considered. A three-question survey was developed to examine what key constituents believe is working in women's sports, what they believe the salient challenges are for women's sport, and how they would prioritize the next steps forward in the post-pandemic sport landscape. Results indicated siloed differences of opinion based upon the age and role of the stakeholder in the women's sport ecosystem. We discuss the implications and offer recommendations as to how we as scholars might recalibrate our approach to women's sport scholarship to maximize the impact of our research and affect change.
Restoring Soil Fertility on Degraded Lands to Meet Food, Fuel, and Climate Security Needs via Perennialization
Authors: Mosier Samantha , Córdova S. Carolina , Robertson G. Philip
Published: October 2021

A continuously growing pressure to increase food, fiber, and fuel production to meet worldwide demand and achieve zero hunger has put severe pressure on soil resources. Abandoned, degraded, and marginal lands with significant agricultural constraints—many still used for agricultural production—result from inappropriately intensive management, insufficient attention to soil conservation, and climate change. Continued use for agricultural production will often require ever more external inputs such as fertilizers and herbicides, further exacerbating soil degradation and impeding nutrient recycling and retention. Growing evidence suggests that degraded lands have a large potential for restoration, perhaps most effectively via perennial cropping systems that can simultaneously provide additional ecosystem services. Here we synthesize the advantages of and potentials for using perennial vegetation to restore soil fertility on degraded croplands, by summarizing the principal mechanisms underpinning soil carbon stabilization and nitrogen and phosphorus availability and retention. We illustrate restoration potentials with example systems that deliver climate mitigation (cellulosic bioenergy), animal production (intensive rotational grazing), and biodiversity conservation (natural ecological succession). Perennialization has substantial promise for restoring fertility to degraded croplands, helping to meet future food security needs.
Upfront Brain Treatments Followed by Lung Surgery Improves Survival for Stage IV Non-small Cell Lung Cancer Patients With Brain Metastases: A Large Cohort Analysis
Authors: He Xiaopeng , Yin Shen , Liu Hongyu , Lu Rong , Kernstine Kemp , Gerber David E. , Xie Yang , Yang Donghan M.
Published: October 2021

Background: Current treatment guidelines for stage IV non-small cell lung cancer (NSCLC) with brain metastases recommend brain treatments, including surgical resection and radiotherapy (RT), in addition to resection of the primary lung tumor. Here, we investigate the less-studied impact of treatment sequence on the overall survival.

Methods: The National Cancer Database was queried for NSCLC patients with brain metastases who underwent surgical resection of the primary lung tumor (n = 776). Kaplan-Meier survival curves with log-rank test and propensity score stratified Cox regression with Wald test were used to evaluate the associations between various treatment plans and overall survival (OS).

Results: Compared to patients who did not receive any brain treatment (median OS = 6.05 months), significantly better survival was observed for those who received brain surgery plus RT (median OS = 26.25 months, p < 0.0001) and for those who received brain RT alone (median OS = 14.49 months, p < 0.001). Patients who received one upfront brain treatment (surgery or RT) before lung surgery were associated with better survival than those who received lung surgery first (p < 0.05). The best survival outcome (median OS 27.1 months) was associated with the sequence of brain surgery plus postoperative brain RT followed by lung surgery.

Conclusions: This study shows the value of performing upfront brain treatments followed by primary lung tumor resection for NSCLC patients with brain metastases, especially the procedure of brain surgery plus postoperative brain RT followed by lung surgery.
Characteristics of Physiological 18F-Fluoro-2-Deoxy-D-Glucose Uptake and Comparison Between Cats and Dogs With Positron Emission Tomography
Authors: Chae Yeon , Yun Taesik , Koo Yoonhoi , Lee Dohee , Kim Hakhyun , Yang Mhan-Pyo , Kang Byeong-Teck
Published: October 2021

This study aimed to identify the physiological 18F-fluoro-2-deoxy-D-glucose (FDG) uptake in cats using positron emission tomography/computed tomography (PET/CT) and determine its characteristics by comparing physiological differences with dogs. Seven healthy cats and six healthy beagle dogs were examined using FDG-PET/CT. Regions of interest (ROIs) were manually drawn over 41 detailed structures of 5 gross structures (brain, head and neck, musculoskeleton, thorax, and abdomen). The mean and maximum standard uptake values (SUVmean and SUVmax) were calculated for each ROI. Physiological variation was classified as having increased radiopharmaceutical activity with no evidence of abnormal clinical or radiological findings. The brain had the highest SUV, which was observed in the cerebellum of both cats (SUVmean: 4.90 ± 1.04, SUVmax: 6.04 ± 1.24) and dogs (SUVmean: 3.15 ± 0.57, SUVmax: 3.90 ± 0.74). Cats had a significantly higher intracranial uptake than dogs did (P < 0.01). In the digestive system, the SUVs of the duodenum and jejunum were significantly higher in dogs than in cats (P < 0.05). FDG uptake of the submandibular tip, tonsils, neck of the gallbladder, and caudal colliculus were physiologically increased in cats. This study demonstrates physiological FDG uptake in normal tissues, and the differences between cats and dogs were interpreted based on species-specificity. This information contributes to improving the accurate diagnosis of cancer in cats and will aid in understanding glucose metabolism in both cats and dogs.
Supplementing a Clay Mineral-Based Feed Additive Modulated Fecal Microbiota Composition, Liver Health, and Lipid Serum Metabolome in Dairy Cows Fed Starch-Rich Diets
Authors: Pacífico Cátia , Hartinger Thomas , Stauder Alexander , Schwartz-Zimmermann Heidi Elisabeth , Reisinger Nicole , Faas Johannes , Zebeli Qendrim
Published: October 2021

Starch-rich diets are a commonly adopted strategy in order to sustain high milk yields in dairy cows. However, these diets are known to increase the risk of gut dysbiosis and related systemic health disorders. This study aimed to evaluate the effects of supplementing a clay mineral-based feed additive (CM; Mycofix® Plus, BIOMIN) on fecal microbiota structure, fecal short-chain fatty acid (SCFA) fermentation, serum metabolome, and liver health in primiparous (PP, n = 8) and multiparous (MP, n = 16) early-lactation Simmental cows (737 ± 90 kg of live body weight). Cows were randomly assigned to either a control or CM group (55 g per cow and day) and transitioned from a diet moderate in starch (26.3 ± 1.0%) to a high starch diet (32.0 ± 0.8%). Supplementation of CM reversed the decrease in bacterial diversity, richness, and evenness (p < 0.05) during high-starch diet, demonstrating that CM supplementation efficiently eased hindgut dysbiosis. The CM treatment reduced levels of Lactobacillus in PP cows during starch-rich feeding and elevated fecal pH, indicating a healthier hindgut milieu compared with that in control. Butyrate and propionate levels were modulated by CM supplementation, with butyrate being lower in CM-treated MP cows, whereas propionate was lower in MP but higher in PP cows. Supplementing CM during high-starch feeding increased the concentrations of the main primary bile salts and secondary bile acids in the serum and improved liver function in cows as indicated by reduced levels of glutamate dehydrogenase and γ-glutamyl-transferase, as well as higher serum albumin and triglyceride concentrations. These changes and those related to lipid serum metabolome were more pronounced in PP cows as also corroborated by relevance network analysis.
A Comparative Study of Semantic Segmentation Models for Identification of Grape with Different Varieties
Authors: Peng Yun , Wang Aichen , Liu Jizhan , Faheem Muhammad
Published: October 2021

Accurate fruit segmentation in images is the prerequisite and key step for precision agriculture. In this article, aiming at the segmentation of grape cluster with different varieties, 3 state-of-the-art semantic segmentation networks, i.e., Fully Convolutional Network (FCN), U-Net, and DeepLabv3+ applied on six different datasets were studied. We investigated: (1) the segmentation performance difference of the 3 studied networks; (2) The impact of different input representations on segmentation performance; (3) The effect of image enhancement method to improve the poor illumination of images and further improve the segmentation performance; (4) The impact of the distance between grape clusters and camera on segmentation performance. The experiment results show that compared with FCN and U-Net the DeepLabv3+ combined with transfer learning is more suitable for the task with an intersection over union (IoU) of 84.26%. Five different input representations, namely RGB, HSV, L*a*b, HHH, and YCrCb obtained different IoU, ranging from 81.5% to 88.44%. Among them, the L*a*b got the highest IoU. Besides, the adopted Histogram Equalization (HE) image enhancement method could improve the model’s robustness against poor illumination conditions. Through the HE preprocessing, the IoU of the enhanced dataset increased by 3.88%, from 84.26% to 88.14%. The distance between the target and camera also affects the segmentation performance, no matter in which dataset, the closer the distance, the better the segmentation performance was. In a word, the conclusion of this research provides some meaningful suggestions for the study of grape or other fruit segmentation.
Spatiotemporal Analysis of West Nile Virus Epidemic in South Banat District, Serbia, 2017–2019
Authors: Radojicic Sonja , Zivulj Aleksandar , Petrovic Tamas , Nisavic Jakov , Milicevic Vesna , Sipetic-Grujicic Sandra , Misic Dusan , Korzeniowska Malgorzata , Stanojevic Slavoljub
Published: October 2021

West Nile virus (WNV) is an arthropod-born pathogen, which is transmitted from wild birds through mosquitoes to humans and animals. At the end of the 20th century, the first West Nile fever (WNF) outbreaks among humans in urban environments in Eastern Europe and the United States were reported. The disease continued to spread to other parts of the continents. In Serbia, the largest number of WNV-infected people was recorded in 2018. This research used spatial statistics to identify clusters of WNV infection in humans and animals in South Banat County, Serbia. The occurrence of WNV infection and risk factors were analyzed using a negative binomial regression model. Our research indicated that climatic factors were the main determinant of WNV distribution and were predictors of endemicity. Precipitation and water levels of rivers had an important influence on mosquito abundance and affected the habitats of wild birds, which are important for maintaining the virus in nature. We found that the maximum temperature of the warmest part of the year and the annual temperature range; and hydrographic variables, e.g., the presence of rivers and water streams were the best environmental predictors of WNF outbreaks in South Banat County.
Management of Low Birth Weight in Canine and Feline Species: Breeder Profiling
Authors: Mugnier Amélie , Chastant Sylvie , Saegerman Claude , Gaillard Virginie , Grellet Aurélien , Mila Hanna
Published: October 2021

Low birth weight (LBW) has been identified as a major risk factor for neonatal mortality in many species. The aim of this survey was to determine the profiles of canine and feline breeders concerning their perceptions of, and management practices relating to, LBW individuals. An anonymous online survey was addressed to French cat and dog breeders in September 2019 via social networks. Multiple correspondence analysis and hierarchical clustering were used to explore breeders’ profiles. Three clusters were identified among the 649 breeders included in this analysis. Cluster 1 (49%) included dog and cat breeders who weighed newborns (and thus identified LBW) and controlled nursing by the dam (controlled suckling) but did not warm them up. Cluster 2 breeders (21%) of both species did not weigh puppies or kittens to identify LBW or to monitor the evolution of their weight afterwards. Cluster 3 (30%) including mostly cat breeders who weighed neonates routinely as in Cluster 1, but they practiced artificial feeding rather than controlled suckling. This survey provides a basis for better understanding of perceptions and practices regarding LBW puppies and kittens. It will be useful to provide guidelines for neonatal management to increase their chances of survival.
Daily Administered Dual-Light Photodynamic Therapy Provides a Sustained Antibacterial Effect on Staphylococcus aureus
Authors: Nikinmaa Sakari , Podonyi Anna , Raivio Peter , Meurman Jukka , Sorsa Timo , Rantala Juha , Kankuri Esko , Tauriainen Tuomas , Pätilä Tommi
Published: October 2021

New means to reduce excessive antibiotic use are urgently needed. This study tested dual-light aPDT against Staphylococcus aureus biofilm with different relative ratios of light energy with indocyanine green. We applied single-light aPDT (810 nm aPDT, 405 aBL) or dual-light aPDT (simultaneous 810 nm aPDT and 405 nm aBL), in both cases, together with the ICG photosensitizer with constant energy of 100 or 200 J/cm2. Single-dose light exposures were given after one-day, three-day, or six-day biofilm incubations. A repeated daily dose of identical light energy was applied during biofilm incubations for the three- and six-day biofilms. Using 100 J/cm2 light energy against the one-day biofilm, the dual-light aPDT consisting of more than half of aBL was the most effective. On a three-day maturated biofilm, single-dose exposure to aPDT or dual-light aPDT was more effective than aBL alone. With total light energy of 200 J/cm2, all dual-light treatments were effective. Dual-light aPDT improves the bactericidal effect on Staphylococcus aureus biofilm compared to aPDT or aBL and provides a sustained effect. An increase in the relative ratio of aBL strengthens the antibacterial effect, mainly when the treatment is repeatedly applied. Thus, the light components’ energy ratio is essential with dual-light.
Exploring the Leukemogenic Potential of GATA-1S, the Shorter Isoform of GATA-1: Novel Insights into Mechanisms Hampering Respiratory Chain Complex II Activity and Limiting Oxidative Phosphorylation Efficiency
Authors: Trombetti Silvia , Sessa Raffaele , Catapano Rosa , Rinaldi Laura , Lo Bianco Alessandra , Feliciello Antonio , Izzo Paola , Grosso Michela
Published: October 2021

GATA-1 is a key regulator of hematopoiesis. A balanced ratio of its two isoforms, GATA-1FL and GATA-1S, contributes to normal hematopoiesis, whereas aberrant expression of GATA-1S alters the differentiation/proliferation potential of hematopoietic precursors and represents a poor prognostic factor in myeloid leukemia. We previously reported that GATA-1S over-expression correlates with high levels of the succinate dehydrogenase subunit C (SDHC). Alternative splicing variants of the SDHC transcript are over-expressed in several tumors and act as potent dominant negative inhibitors of SDH activity. With this in mind, we investigated the levels of SDHC variants and the oxidative mitochondrial metabolism in myeloid leukemia K562 cells over-expressing GATA-1 isoforms. Over-expression of SDHC variants accompanied by decreased SDH complex II activity and oxidative phosphorylation (OXPHOS) efficiency was found associated only with GATA-1S. Given the tumor suppressor role of SDH and the effects of OXPHOS limitations in leukemogenesis, identification of a link between GATA-1S and impaired complex II activity unveils novel pro-leukemic mechanisms triggered by GATA-1S. Abnormal levels of GATA-1S and SDHC variants were also found in an acute myeloid leukemia patient, thus supporting in vitro results. A better understanding of these mechanisms can contribute to identify novel promising therapeutic targets in myeloid leukemia.
The Role of RBC Oxidative Stress in Sickle Cell Disease: From the Molecular Basis to Pathologic Implications
Authors: Wang Qinhong , Zennadi Rahima
Published: October 2021

Sickle cell disease (SCD) is an inherited monogenic disorder and the most common severe hemoglobinopathy in the world. SCD is characterized by a point mutation in the β-globin gene, which results in hemoglobin (Hb) S production, leading to a variety of mechanistic and phenotypic changes within the sickle red blood cell (RBC). In SCD, the sickle RBCs are the root cause of the disease and they are a primary source of oxidative stress since sickle RBC redox state is compromised due to an imbalance between prooxidants and antioxidants. This imbalance in redox state is a result of a continuous production of reactive oxygen species (ROS) within the sickle RBC caused by the constant endogenous Hb autoxidation and NADPH oxidase activation, as well as by a deficiency in the antioxidant defense system. Accumulation of non-neutralized ROS within the sickle RBCs affects RBC membrane structure and function, leading to membrane integrity deficiency, low deformability, phosphatidylserine exposure, and release of micro-vesicles. These oxidative stress-associated RBC phenotypic modifications consequently evoke a myriad of physiological changes involved in multi-system manifestations. Thus, RBC oxidative stress in SCD can ultimately instigate major processes involved in organ damage. The critical role of the sickle RBC ROS production and its regulation in SCD pathophysiology are discussed here.
Novel Application of Long Short-Term Memory Network for 3D to 2D Retinal Vessel Segmentation in Adaptive Optics—Optical Coherence Tomography Volumes
Authors: Le Christopher T. , Wang Dongyi , Villanueva Ricardo , Liu Zhuolin , Hammer Daniel X. , Tao Yang , Saeedi Osamah J.
Published: October 2021

Adaptive optics—optical coherence tomography (AO-OCT) is a non-invasive technique for imaging retinal vascular and structural features at cellular-level resolution. Whereas retinal blood vessel density is an important biomarker for ocular diseases, particularly glaucoma, automated blood vessel segmentation tools in AO-OCT have not yet been explored. One reason for this is that AO-OCT allows for variable input axial dimensions, which are not well accommodated by 2D-2D or 3D-3D segmentation tools. We propose a novel bidirectional long short-term memory (LSTM)-based network for 3D-2D segmentation of blood vessels within AO-OCT volumes. This technique incorporates inter-slice connectivity and allows for variable input slice numbers. We compare this proposed model to a standard 2D UNet segmentation network considering only volume projections. Furthermore, we expanded the proposed LSTM-based network with an additional UNet to evaluate how it refines network performance. We trained, validated, and tested these architectures in 177 AO-OCT volumes collected from 18 control and glaucoma subjects. The LSTM-UNet has statistically significant improvement (p < 0.05) in AUC (0.88) and recall (0.80) compared to UNet alone (0.83 and 0.70, respectively). LSTM-based approaches had longer evaluation times than the UNet alone. This study shows that a bidirectional convolutional LSTM module improves standard automated vessel segmentation in AO-OCT volumes, although with higher time cost.
Numerical Investigation of Thermal-Flow Characteristics in Heat Exchanger with Various Tube Shapes
Authors: Djeffal Fares , Bordja Lyes , Rebhi Redha , Inc Mustafa , Ahmad Hijaz , Tahrour Farouk , Ameur Houari , Menni Younes , Lorenzini Giulio , Elagan Sayed  K. , Jawa Taghreed M.
Published: October 2021

In this study, eight configurations of oval and flat tubes in annular finned-tube thermal devices are examined and compared with the conventional circular tube. The objective is to assess the effect of tube flatness and axis ratio of the oval tube on thermal-flow characteristics of a three-row staggered bank for Re (2600 ≤ Re ≤ 10,200). It has been observed that the thermal exchange rate and Colburn factor increase according to the axis ratio and the flatness, where O1 and F1 provide the highest values. O1 produces the lowest friction factor values of all the oval tubes at all Re, and F4 gives 13.2–18.5% less friction than the other tube forms. In terms of performance evaluation criterion, all of the tested tubes outperformed the conventional circular tube (O5), with O1 and F1 obtaining the highest values. The global performance criterion of O1 has been found to be 9.6–45.9% higher as compared to the other oval tube geometries at lower values of Re, and the global performance criterion increases with the increase in flatness. The F1 tube shape outperforms all the examined tube designs; thus, this tube geometry suggests that it be used in energy systems.
Nonlinear Dynamic Response of Ropeway Roller Batteries via an Asymptotic Approach
Authors: Arena Andrea
Published: October 2021

The nonlinear dynamic features of compression roller batteries were investigated together with their nonlinear response to primary resonance excitation and to internal interactions between modes. Starting from a parametric nonlinear model based on a previously developed Lagrangian formulation, asymptotic treatment of the equations of motion was first performed to characterize the nonlinearity of the lowest nonlinear normal modes of the system. They were found to be characterized by a softening nonlinearity associated with the stiffness terms. Subsequently, a direct time integration of the equations of motion was performed to compute the frequency response curves (FRCs) when the system is subjected to direct harmonic excitations causing the primary resonance of the lowest skew-symmetric mode shape. The method of multiple scales was then employed to study the bifurcation behavior and deliver closed-form expressions of the FRCs and of the loci of the fold bifurcation points, which provide the stability regions of the system. Furthermore, conditions for the onset of internal resonances between the lowest roller battery modes were found, and a 2:1 resonance between the third and first modes of the system was investigated in the case of harmonic excitation having a frequency close to the first mode and the third mode, respectively.
Electrical Response of the Spinel ZnAl2O4 and Its Application in the Detection of Propane Gas
Authors: Guillén-Bonilla Héctor , Guillén-Bonilla José Trinidad , Rodríguez-Betancourtt Verónica María , Jiménez-Rodríguez Maricela , Guillén-Bonilla Alex , Huízar-Padilla Emilio , Sánchez-Morales María Eugenia , Ramírez-Ortega Jorge Alberto , Blanco-Alonso Oscar
Published: October 2021

Nanoparticles of the semiconductor ZnAl2O4 were prepared using a microwave-assisted wet chemistry method in the presence of ethylenediamine and calcination at 250 °C. The material’s crystallinity and purity were verified by X-ray diffraction. The pure phase of the ZnAl2O4 presented a cubic crystalline structure with cell parameters a = 8.087 Å and space group Fd-3m (227). Dynamic tests in propane atmospheres were carried out on pellets (~500 µm in diameter) manufactured with ZnAl2O4 powders. In the tests, the oxide showed variations with time in electrical resistance when injecting air-propane at an operating temperature of 250 °C. The pellets showed good stability, high sensitivity, and an optimal dynamic response as a function of time. On the other hand, a mathematical model was proposed to describe the chemical sensor’s dynamic behavior based on the electrical response and linear systems theory. The sensor’s transient response was obtained with the model by exposing the oxide to air and propane gas; its stability was checked, and the stabilization time was calculated. Subsequently, an operating point was selected, and, with it, a propane gas detector was designed. The sensor operated flawlessly at 250 °C at a concentration of 1000 ppm, with a response time of three seconds. The developed device is inexpensive and easy to implement.
Assessment of Skin Deep Layer Biochemical Profile Using Spatially Offset Raman Spectroscopy
Authors: Vardaki Martha Z. , Seretis Konstantinos , Gaitanis Georgios , Bassukas Ioannis D. , Kourkoumelis Nikolaos
Published: October 2021

Skin cancer is currently the most common type of cancer with millions of cases diagnosed worldwide yearly. The current gold standard for clinical diagnosis of skin cancer is an invasive and relatively time-consuming procedure, consisting of visual examination followed by biopsy collection and histopathological analysis. Raman spectroscopy has been shown to efficiently aid the non-invasive diagnosis of skin cancer when probing the surface of the skin. In this study, we employ a recent development of Raman spectroscopy (Spatially Offset Raman Spectroscopy, SORS) which is able to look deeper in tissue and create a deep layer biochemical profile of the skin in areas where cancer lesions subtly evolve. After optimizing the measurement parameters on skin tissue phantoms, we then adopted SORS on human skin tissue from different anatomical areas to investigate the contribution of the different skin layers to the recorded Raman signal. Our results show that using a diffuse beam with zero offset to probe a sampling volume where the lesion is typically included (surface to epidermis-dermis junction), provides the optimum signal-to-noise ratio (SNR) and may be employed in future skin cancer screening applications.