bluuebunny/crossref_metadata_2025 huggingface dataset:
A study on the effects of language and visual art integrated teaching on language learning performance and satisfaction of ethnic minority students in China
Authors: Zhang Yao , Jia Simeng
Published: November 2022

Innovative technological products are present in students' environments. Information explosion and popularity are affecting their thoughts, and there is a large amount of information fuel in life through the Internet, television, movies, and advertisements. This phenomenon transforms reading from pure words into image. The current study was conducted using an experimental design model. A total of 188 ethnic minority students in the Hebei Province participated in the experimental study. The experimental group went through language and visual art integrated instruction, while the control group underwent traditional teaching. The experimental study lasted for 20 weeks (3 h per week). The research results showed that (1) spoken and written artistic conception was displayed through artistic expression. Ethnic minority students' differences in language skills and artistic expression were found to be the major factors that were effective in the production process. These aspects made the work richer and even more diversified. (2) After joining the classes and covering several lessons, ethnic minority students were found to be getting increasingly better in terms of integrating art vocabulary into their conversation. (3) Language and visual art integrated teaching input was a story content, which was received through “listening”, while the outputs were individual opinions through “speaking”. Their thoughts were presented through “painting”. The creation process operated in the brain and reflected differences in terms of their thinking skills, vocabulary organizational skills, language use, and creativity. Based on the results, this study is expected to improve the language proficiency of ethnic minority students, enhance their artistic culture, and pave the way for their understanding and attitude toward language and literature.
Examining the effects of stroke on students’ L2-grit levels in an EFL context: A case of Northern Iraq
Authors: Mohammed Diyar J. M. , Mohammadzadeh Behbood , Kılıç Yalın
Published: November 2022

This article investigates the effects of stroke on students’ L2-grit levels in an EFL context in Northern Iraq. A model was created to find how various components such as verbal, non-verbal, valuing, and activities that determine stroke levels affect students’ grit. This study adopted the L2- Grit scale and a language domain-specific grit scale to measure the learners’ L2-grit levels. Also, the Students’ Stroke Scale (SSS) was used to measure the participants’ stroke levels. The study’s sample consisted of 199 participants from various academic levels, undergraduate, graduate, and postgraduate at several Northern Iraq universities. The results reveal a positive and statistically significant association between the score on the L2-Grit scale and the score on the Stroke scale; more specifically, as the scores on the L2-grit scale rise, so do the scores on the Stroke scale. The mean of low stroke is lower than the means of medium stroke and high stroke indicating that as people’s stroke levels grow, so does their L2-grit status. The regression coefficients estimated within the framework of the regression model structured with the logit, the link function, are the same in each category of the dependent variable, satisfying the parallel curves assumption. The overall results show that positive stroke helps learners’ L2-grit levels to arise and lead to a better learning process.
How physical exercise impacts academic burnout in college students: The mediating effects of self-efficacy and resilience
Authors: Chen Kai , Liu Feiyang , Mou Liu , Zhao Peiting , Guo Liya
Published: November 2022

Background and aims

Academic burnout is harmful to college students, their institutions of learning, and society at large. While research has shown that physical exercise may be associated with reduced academic burnout, the underlying mechanisms require further exploration. This study explored the relationship between physical exercise and academic burnout in a sample of college students, with a focus on the serial mediating roles of self-efficacy and resilience.

Methods

This study adopted a cross-sectional survey approach among a sample of undergraduate college students in China. We recruited 1,270 participants in the second half of the 2021–2022 academic year (476 men and 794 women), all of whom completed questionnaires containing the Physical Activity Rating Scale, Academic Burnout Scale for College Students, 10-item General Self-Efficacy Scale, and 25-item Connor-Davidson Resilience Scale. We then subjected the collected data to a series of statistical analyses.

Results and conclusion

Physical exercise was significantly and negatively associated with academic burnout and its three subfactors (i.e., emotional exhaustion, improper behavior, and low personal achievement). Participants in the high physical exercise group showed lower levels of academic burnout than those in the moderate and low physical exercise groups. Finally, our serial mediation model showed that physical exercise had a significant direct effect on academic burnout (β = −0.1104, 95% CI = [−0.1421, −0.0791]) in addition to significant indirect effects on academic burnout via self-efficacy and resilience (β = −0.0802, 95% CI = [−0.1088, −0.0527]); the more exercise participation, the lower the academic burnout among college students. These findings suggest that physical exercise is an important interventional target when aiming to reduce academic burnout.
Burdens and psychosocial consequences of the COVID-19 pandemic for Austrian children and adolescents
Authors: Eigl Esther-Sevil , Widauer Sebastian Stefan , Schabus Manuel
Published: November 2022

Objectives

The negative psychosocial effects of the COVID-19 pandemic are becoming increasingly apparent. Children and adolescents in particular, were affected and torn away from their daily life routines. The aim of our survey is to evaluate the psychosocial burden and impairments of children and adolescents in Austria during the COVID-19 pandemic by using cross-sectional analysis.

Setting

An Austrian-wide online survey was conducted from 21 February to 19 April 2021 for children and adolescents. The questionnaire was distributed widely using the national press agency and public media.

Participants

Using an online questionnaire, 5,483 children and adolescents between 6 and 18 years of age were sampled.

Outcome measure

Quantitative responses to questions regarding the children’s feelings, worries, and needs concerning the COVID-19 pandemic were measured. Furthermore, the children were sampled for subjective risk perception as well as their sleep quality.

Results

Most children reported a high degree of fear due to the pandemic, especially female (48.1%) participants being under more emotional strain than their male (35.9%) counterparts. Associated with this, we found a strong overestimation of COVID-19-associated hospitalization likelihood (>100-fold) across all age groups. In addition, an alarming lack of positive perspective during the ongoing pandemic is evident across all age groups, including the youngest participants aged 6–10 years. Feelings of anger and annoyance (58.2%), loneliness (46%), and sadness (42.7%) are reported much more frequently than before the pandemic. On the other hand, only 15.6% reported feeling well (or even better; 2%) since the COVID-19 pandemic. Last but not least, our study shows an alarming 37% of children and adolescents who now report poorer sleep quality than before the pandemic.

Conclusion

The results of this survey indicate the high burden and emotional strain for children and adolescents during the pandemic. Personal contact with friends and family is mentioned as the most protective factor for their mental health. The study results underscore the need for immediate action to limit the collateral damage that has already occurred on a psychosocial and developmental level among younger generations worldwide.
Psychosocial correlates of fertility-related quality of life among infertile women with repeated implantation failure: The mediating role of resilience
Authors: Ni Ying , Huang Limin , Zhang Enming , Xu Lianying , Tong Chenye , Qian Wen , Zhang Aijun , Fang Qiong
Published: November 2022

Objective

This study aimed to examine associations between psychosocial factors and fertility-related quality of life (FertiQoL) among infertile women with repeated implantation failure (RIF), and to identify the possible role of resilience in mediating the effect of social support on FertiQoL.

Materials and methods

A cross-sectional study was conducted with 234 infertile women with RIF in total. Fertility quality of life scale (FertiQoL), perceived social support scale (PSSS), and Connor-Davidson Resilience Scale (CD-RISC) were used to evaluate the patients. Data were described by univariate and multivariate analyses. Stepwise regression method was performed to analyse the mediating effect of resilience.

Results

Social support had a positive predictive effect on FertiQoL (β = 0.757, P < 0.001), also positive on resilience (β = 0.847, P < 0.001). After both variables were added to the regression equation, resilience was found to have a significant positive predictive effect on FertiQoL (β = 0.798, P < 0.001), while the predictive effect of social support on FertiQoL was no longer significant (β = 0.081, P > 0.05). The results indicated that resilience played a complete mediating role between social support and FertiQoL.

Conclusion

This study preliminarily verified the mediating role of resilience between social support and FertiQoL among infertile women with RIF. Interventions that consider enhancing resilience and building social support will likely improve their FertiQoL.
Establishment and psychometric characteristics of emotional words list for suicidal risk assessment in speech emotion recognition
Authors: Shen Juan , Zhang Shuo , Tong Yongsheng , Dong Xiangmin , Wang Xuelian , Fu Guanghui , Zhao Liting , Wu Mengjie , Yin Yi , Wang Yuehua , Liu Nancy H. , Wu Jianlan , Li Jianqiang
Published: November 2022

Background

Emotional disturbance is an important risk factor of suicidal behaviors. To ensure speech emotion recognition (SER), a novel technique to evaluate emotional characteristics of speech, precision in labeling emotional words is a prerequisite. Currently, a list of suicide-related emotional word is absent. The aims of this study were to establish an Emotional Words List for Suicidal Risk Assessment (EWLSRA) and test the reliability and validity of the list in a suicide-related SER task.

Methods

Suicide-related emotion words were nominated and discussed by 10 suicide prevention professionals. Sixty-five tape-recordings of calls to a large psychological support hotline in China were selected to test psychometric characteristics of the EWLSRA.

Results

The results shows that the EWLSRA consists of 11 emotion words which were highly associated with suicide risk scores and suicide attempts. Results of exploratory factor analysis support one-factor model of this list. The Fleiss’ Kappa value of 0.42 indicated good inter-rater reliability of the list. In terms of criteria validities, indices of despair (Spearman ρ = 0.54, P < 0.001), sadness (ρ = 0.37, P = 0.006), helplessness (ρ = 0.45, P = 0.001), and numbness (ρ = 0.35, P = 0.009) were significantly associated with suicidal risk scores. The index of the emotional word of numbness in callers with suicide attempt during the 12-month follow-up was significantly higher than that in callers without suicide attempt during the follow-up (P = 0.049).

Conclusion

This study demonstrated that the EWLSRA has adequate psychometric performance in identifying suicide-related emotional words of recording of hotline callers to a national wide suicide prevention line. This list can be useful for SER in future studies on suicide prevention.
Research on the dynamic spillover of stock markets under COVID-19—Taking the stock markets of China, Japan, and South Korea as an example
Authors: Zhou Baicheng , Yin Qingshu , Wang Shu , Li Tianye
Published: November 2022

Examining stock market interactions between China (mainland China and Hong Kong), Japan, and South Korea, this study employs a framework that includes 239 economic variables to identify the spillover effects among these three countries, and empirically simulates the dynamic time-varying non-linear relationship between the stock markets of different countries. The findings are that in recent decades, China's stock market relied on Hong Kong's as a window to the exchange of price information with Japan and South Korea. More recently, the China stock market's spillover effect on East Asia has expanded. The spread of the crisis has strengthened co-movement between the stock markets of China, Japan, and South Korea.
On the wrong track: Sustainable and low-emission blue food diets to mitigate climate change
Authors: Atalah Javier , Sanchez-Jerez Pablo
Published: November 2022

Seafood and other aquatic food (blue food) are often advocated as sustainable protein sources crucial to meeting global food demand. Consumption choices allow citizens to take actions that reduce the environmental burden of food production and tackle the climate crisis. Here we used a high-resolution Spanish national-level dataset collected from 12,500 households between 1999 and 2021 as a study case to assess trends in blue food consumption concerning sources, types and stressors resulting from their production. By aggregating species groups according to source, we found an overall reduction in the consumption of most wild species. For farmed species, we found a pronounced increase in the consumption of carnivorous fish and an overall decrease in low trophic-level species consumption, such as bivalves. Using published studies, we estimated greenhouse gases, nitrogen, and phosphorus emissions to assess trends in environmental footprint. Low performance was associated with the consumption of high trophic-level species intensively farmed in distant regions, such as carnivorous fish, due to high stressor emissions related to their production and transport. Across all groups, consumption of locally farmed bivalves conduced to the lowest stressor emissions, providing an example of ‘net-zero' blue food. Our analysis identified historical trends in the environmental footprint of blue food consumption and consumers' choices that promote environmentally sustainable diets. It also highlights vast differences in the ecological footprint associated with the consumption of aquaculture-sourced protein. Based on our assessment, we recommend refocusing consumption patterns toward farmed species with small environmental footprints, such as locally produced low trophic-level species, and implementing policies that increase consumers' environmental awareness and minimize food production systems' footprints. Considering global blue food demand is predicted to nearly double by mid-century, consumers' choices can significantly impact sustainable production practices and mitigate climate change.
Comparison of percutaneous transforaminal endoscopic discectomy and open lumbar discectomy for lumbar disc herniations: A systematic review and meta-analysis
Authors: Zhang Jian , Gao Yangyang , Zhao Bin , Li Haoyang , Hou Xuening , Yin Liqiang
Published: November 2022

Purpose

In order to compare the outcomes of percutaneous transforaminal endoscopic discectomy (PTED) and open lumbar discectomy (OLD) for lumbar disc herniation (LDH).

Methods

The Pubmed, Cochrane Library, Web of Sience, Embase, Clinicaltrials.gov, CBM, CNKI, VIP, Wangfang databases were searched from inception to April 30, 2022 to collect the published studies about PTED vs. OLD for treatment of LDH. The Revman 5.2 was used for data analysis. The primary outcomes were excellent rates, complication rates and reoperation rates. The secondary outcomes were length of incision, length of operation, length of hospital stay, and the amount of intraoperative blood loss.

Results

A total of nine studies were included, of which, eight randomized controlled trials and one retrospective study involving 1,679 patients with LDH (755 patients for PTED, and 924 patients for OLD) were included. According to meta-analysis, there were no significant difference in excellent rates (odds ratio [OR] = 1.47, 95% confidence intervals [CI]: 0.94–2.28, P = 0.09), reoperation rates (OR = 0.96, 95% CI: 0.50–1.84, P = 0.90), length of operation [standardized mean differences (SMD) = −17.97, 95%CI: −54.83–18.89, P = 0.34], and the amount of intraoperative blood loss (SMD = −128.05, 95%CI: −258.67–2.57, P = 0.05), respectively. There were significant differences in complication rates (OR = 0.22, 95% CI: 0.14–0.33, P < 0.001), length of incision (SMD = −2.76, 95%CI: −2.88–−2.65, P < 0.001), and length of hospital stay (SMD = −5.19, 95%CI: −5.36–−5.01, P < 0.001), respectively.

Conclusions

PTED can achieve better outcomes with respect to the complication rates, length of incision, and length of hospital stay compared with OLD.
Vetinformatics from functional genomics to drug discovery: Insights into decoding complex molecular mechanisms of livestock systems in veterinary science
Authors: Pathak Rajesh Kumar , Kim Jun-Mo
Published: November 2022

Having played important roles in human growth and development, livestock animals are regarded as integral parts of society. However, industrialization has depleted natural resources and exacerbated climate change worldwide, spurring the emergence of various diseases that reduce livestock productivity. Meanwhile, a growing human population demands sufficient food to meet their needs, necessitating innovations in veterinary sciences that increase productivity both quantitatively and qualitatively. We have been able to address various challenges facing veterinary and farm systems with new scientific and technological advances, which might open new opportunities for research. Recent breakthroughs in multi-omics platforms have produced a wealth of genetic and genomic data for livestock that must be converted into knowledge for breeding, disease prevention and management, productivity, and sustainability. Vetinformatics is regarded as a new bioinformatics research concept or approach that is revolutionizing the field of veterinary science. It employs an interdisciplinary approach to understand the complex molecular mechanisms of animal systems in order to expedite veterinary research, ensuring food and nutritional security. This review article highlights the background, recent advances, challenges, opportunities, and application of vetinformatics for quality veterinary services.
RELSA—A multidimensional procedure for the comparative assessment of well-being and the quantitative determination of severity in experimental procedures
Authors: Talbot Steven R. , Struve Birgitta , Wassermann Laura , Heider Miriam , Weegh Nora , Knape Tilo , Hofmann Martine C. J. , von Knethen Andreas , Jirkof Paulin , Häger Christine , Bleich André
Published: November 2022

Good science in translational research requires good animal welfare according to the principles of 3Rs. In many countries, determining animal welfare is a mandatory legal requirement, implying a categorization of animal suffering, traditionally dominated by subjective scorings. However, how such methods can be objectified and refined to compare impairments between animals, subgroups, and animal models remained unclear. Therefore, we developed the RELative Severity Assessment (RELSA) procedure to establish an evidence-based method based on quantitative outcome measures such as body weight, burrowing behavior, heart rate, heart rate variability, temperature, and activity to obtain a relative metric for severity comparisons. The RELSA procedure provided the necessary framework to get severity gradings in TM-implanted mice, yielding four distinct RELSA thresholds L1<0.27, L2<0.59, L3<0.79, and L4<3.45. We show further that severity patterns in the contributing variables are time and model-specific and use this information to obtain contextualized between animal-model and subgroup comparisons with the severity of sepsis > surgery > restraint stress > colitis. The bootstrapped 95% confidence intervals reliably show that RELSA estimates are conditionally invariant against missing information but precise in ranking the quantitative severity information to the moderate context of the transmitter-implantation model. In conclusion, we propose the RELSA as a validated tool for an objective, computational approach to comparative and quantitative severity assessment and grading. The RELSA procedure will fundamentally improve animal welfare, data quality, and reproducibility. It is also the first step toward translational risk assessment in biomedical research.
System Dynamic Model Simulates the Growth Trend of Diabetes Mellitus in Chinese Population: Implications for Future Urban Public Health Governance
Authors: Li Hao , Chang Guo-Ying , Jiang Yi-Hong , Xu Li , Shen Long , Gu Zhi-Chun , Lin Hou-Wen , Shi Fang-Hong
Published: November 2022

Objectives: To simulate the growth trend of diabetes mellitus in Chinese population.

Methods: The system dynamic modeling methodology was used to establish a population prediction model of diabetes with or without cardiovascular diseases. Lifestyle therapy and the use of metformin, acarbose, and voglibose were assumed to be intervention strategy. The outcomes will be examined at 5, 15, and 30 years after 2020.

Results: The projected number of diabetic population in China would increase rapidly from 141.65 million in 2020 to 202.84 million in 2050. Diabetic patients with cardiovascular disease would rapidly increase from 65.58 million in 2020 to 122.88 million by 2050. The annual cost for the entire population with diabetes mellitus in China would reach 182.55 billion by 2050. When the treatment of cardiovascular disease was considered, expenditure was 1.5–2.5-fold higher. Lifestyle therapy and the use of metformin, acarbose and voglibose could effectively slow the growth of the diabetic population.

Conclusion: The diabetic population in China is expected to increase rapidly, and diabetic patients with cardiovascular disease will increase greatly. Interventions could delay it.
Long-Term Effects of Compost Amendments and Brassica Green Manures in Potato Cropping Systems on Soil and Crop Health and Productivity
Authors: Larkin Robert P.
Published: November 2022

Beneficial soil and crop management practices, such as longer rotations, cover crops and green manures, organic amendments, and reduced tillage, may improve soil and crop health and productivity when incorporated into cropping systems. Long-term trials are needed to assess the full impacts and effects of these systems. In field trials originally established in 2004, three different 3-yr potato cropping systems focused on management goals of soil conservation (SC), soil improvement (SI), and disease suppression (DS) were evaluated and compared to a standard 2-yr rotation (SQ) and a nonrotation control (PP). After 12–15 years and results compiled over a four-year period (2015–2018), the SI system (with history of compost amendments) increased total and marketable tuber yields relative to all other systems, with yields averaging 26 to 36% higher than the standard SQ system and 36 to 59% greater than PP. SI also improved soil properties such as organic matter and soil water content, nutritional characteristics, and microbial activity compared to the other systems. The SI system continued to provide these improvements several years after compost amendments ended, indicating the long-term benefits. The DS system, which included a disease-suppressive green manure rotation crop and fall cover crops, also improved yield (by 16–20%), had higher organic matter content (by 12%), and increased microbial activity (by 22%) relative to SQ, as well as reducing the soilborne tuber diseases black scurf and common scab by 10–30%. The nonrotation PP system resulted in the notable degradation of soil properties and yield over time. These results demonstrate that soil health management practices can be effectively incorporated into viable potato cropping systems to improve soil properties and crop health, and may enhance long-term sustainability.
Prevalence and Factors Associated with Working Equid Lameness in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis
Authors: Merridale-Punter Mathilde S. , Wiethoelter Anke K. , El-Hage Charles M. , Hitchens Peta L.
Published: November 2022

Lameness is an important concern in working equids of low- and middle-income communities (LMICs) with significant One Welfare implications. This study aims to determine the prevalence and influencing factors of lameness in working equids of LMICs. A systematic review and meta-analysis were performed to investigate pooled outcome prevalence using a random intercept regression model. Subgroup and sensitivity analysis were performed through meta-regression. A meta-analysis of study factors for lameness prevalence was performed. Sixty-four studies were included in the review. The pooled prevalence of lameness was 29.9% (n = 42, 95% CI 17–47%), while the pooled prevalence of gait abnormality was 62.9% (n = 12; 95% CI 31–87%). When considering both outcomes together, the pooled prevalence was 38.4% (n = 46; 95% CI 23–57%) with a significant (p = 0.02) difference between lameness (29.5%; 95% CI 16–48%) and gait abnormality (78.8%; 95% CI 40–95%). Species, country income level, gait assessed, and risk of bias did not significantly affect the pooled prevalence. Lower body condition scores, unresponsive attitudes, and old age were the most frequently reported factors positively associated with lameness-related outcomes. Working 7 days per week was positively associated with lameness. The standardization of outcome terminology, grading systems, and study factor categorization is recommended to enable more accurate interpretation and comparison between studies.
Effects of Dietary Phosphorus Levels on Growth Performance, Phosphorus Utilization and Intestinal Calcium and Phosphorus Transport-Related Genes Expression of Juvenile Chinese Soft-Shelled Turtle (Pelodiscus sinensis)
Authors: Wang Yue , Geng Yiran , Shi Xueying , Wang Siqi , Yang Zhencai , Zhang Peiyu , Liu Haiyan
Published: November 2022

A 60-day feeding trial was performed to assess the effects of dietary phosphorus levels on growth performance, body composition, phosphorus utilization, plasma physiological parameters and intestinal Ca and P transport-related gene expression of juvenile Chinese soft-shelled turtle (P. sinensis). Four diets containing available P at graded levels of 0.88%, 1.00%, 1.18% and 1.63% (termed as D0.88, D1.00, D1.18 and D1.63, respectively) were formulated and each diet was fed to turtles (5.39 ± 0.02 g) in sextuplicate. The turtles were randomly distributed to 24 tanks with 8 turtles per tank. The results indicated that final body weight, specific growth rate, feed conversion ratio and protein efficiency ratio performed best in turtles fed 1.00% available P diet. The crude lipids of the whole body exhibited a decreasing trend with the dietary available P, whereas the calcium and phosphorus of the whole body and bone phosphorus showed an opposite tendency. The apparent digestibility coefficient of phosphorus declined with the dietary available P. Turtles fed 1.00% available phosphorus had the highest phosphorus retention ratio compared with other treatments. Simultaneously they had significantly lower phosphorus loss than turtles fed D1.18 and D1.63 and had no differences in this respect from turtles fed a low-phosphorus diet. It was noteworthy that the lowest plasma calcium concentrations, and alkaline phosphatase activities in plasma and liver, were discovered in turtles fed the diet containing 1.63% available phosphorus. In addition, the high-phosphorus diet resulted in significantly down-regulated expression of intestinal phosphorus and calcium transport-related key genes. In conclusion, the available phosphorus requirement of juvenile P. sinensis was determined at 1.041% (total phosphorus was 1.80%) based on quadratic regression of weight gain rate, and excessive dietary phosphorus stunted turtle growth possibly via inhibiting intestinal calcium absorption.
Clinical Animal Behaviour: Paradigms, Problems and Practice
Authors: Mills Daniel S.
Published: November 2022

Both the public and clinicians are interested in the application of scientific knowledge concerning problem animal behaviour and its treatment. However, in order to do this effectively it is essential that individuals have not only scientific literacy but also an appreciation of philosophical concepts underpinning a particular approach and their practical implications on the knowledge generated as a result. This paper highlights several common misunderstandings and biases associated with different scientific perspectives relevant to clinical animal behaviour and their consequences for how we determine what may be a useful treatment for a given patient. In addition to more reflective evaluation of results, there is a need for researchers to report more information of value to clinicians; such as relevant treatment outcomes, effect sizes, population characteristics. Clinicians must also appreciate the limitations of population level study results to a given case. These challenges can however be overcome with the careful critical reflection using the scientific principles and caveats described.
Lactose Content and Selected Quality Parameters of Sheep Milk Fermented Beverages during Storage
Authors: Czyżak-Runowska Grażyna , Wójtowski Jacek Antoni , Łęska Bogusława , Bielińska-Nowak Sylwia , Pytlewski Jarosław , Antkowiak Ireneusz , Stanisławski Daniel
Published: November 2022

The aim of the research was to evaluate lactose content and rheological, physical, chemical, and organoleptic parameters during the storage of fermented beverages made from sheep’s milk. The research was carried out on natural, probiotic, and Greek-type yogurts, as well as kefir. The products were made using the thermostat method from the milk of 42 East Frisian sheep in the middle lactation period, in duplicate. Lactose contents, active and titratable acidity, color by the L*a*b*C*h* system, and rheological parameters (hardness, consistency, consistency, and viscosity) were tested, and organoleptic assessments were carried out on the first, seventh, fourteenth, and twenty-first days of storing the drinks at 4 °C. Of all drinks, the highest reduction in lactose after 21 days of storage was found to occur in kefir (52% reduction) and, among the yogurts, in the Greek yogurt (41% reduction). The product with the lowest lactose content, regardless of the storage period, was kefir. This indicates that kefir is more suitable than yogurt for people with partial lactose intolerance. Effects of both inoculation type and beverage storage time were shown to exist for all parameters. It was also found that kefirs suffered deterioration in most rheological parameters and, in general organoleptic evaluation in the final period of storage. Based on our analysis, the optimal storage time for natural yogurts and sheep’s milk kefirs at 4 °C was 21 and 14 days, respectively.
Combination of Cinnamaldehyde with Carvacrol or Thymol Improves the Mechanical Properties of Tibia in Post-Peak Laying Hens
Authors: Zhang Huaiyong , Wang Yongshuai , Wang Yilu , Wang Leilei , Lv Xiangyun , Cui Guangya , Ji Longxiang , Huang Yanqun , Michiels Joris , Chen Wen
Published: November 2022

Roles of plant-derived cinnamaldehyde, carvacrol, and thymol in the gut and bone health of laying hens was evaluated in the present study. After acclimation for 2 weeks, a total 384 of 52-week-old laying hens were allocated into three groups for 6 weeks: (1) basal diet group (Ctrl), (2) combination of cinnamaldehyde with carvacrol group (CAR+CIN), and (3) blend of cinnamaldehyde with thymol (THY+CIN). The dietary essential oil level was 100 mg/kg. Each treatment group had eight replicate pens (16 birds/pen). The stiffness and ultimate load of the tibiae from both the CAR+CIN and THY+CIN groups were higher than that of the Ctrl group (p < 0.05), along with comparable tibia ash, calcium, and phosphorus content among groups. At the same time, the manipulation of essential oils upregulated the transcription abundances of intestinal barrier proteins to varying degrees, whereas the experimental treatment failed to affect the composition in phyla of cecal microbiota. When compared to the Ctrl group, birds fed the CAR+CIN and THY+CIN diet displayed decreased bone resorption markers, reduced interleukin-1 concentrations, and increased transforming growth factor beta levels in serum. These findings suggest that cinnamaldehyde with carvacrol or thymol in feed of hens could enhance intestinal barrier and improve the mechanical properties of tibiae through structural modelling but not increase the mineral density, which might be involved in suppressing inflammation-mediated bone resorption.
Active Pattern Classification for Automatic Visual Exploration of Multi-Dimensional Data
Authors: Li Jie , Tan Huailian , Huang Wentao
Published: November 2022

The practice of applying a classifier (called a pattern classifier and abbreviated as PC below) in a visual analysis system to identify patterns from interactively generated visualizations is gradually emerging. Demonstrated cases in existing works focus on ideal scenarios where the analyst can determine all the pattern types in advance without adjusting the classifier settings during the exploration process. However, in most real-world scenarios, analysts know nothing about data patterns before exploring the dataset and inevitably find novel patterns during the exploration. This difference makes the traditional classifier training and application mode less suitable. Analysts have to artificially determine whether each generated visualization contains new data patterns to adjust the classifier setting, thus affecting the automation of the data exploration. This paper proposes a novel PC-based data exploration approach. The core of the approach is an active-learning indicator for automatically identifying visualizations involving new pattern classes. Analysts thus can apply PCs to explore data while dynamically adjusting the PCs using these visualizations. We further propose a PC-based visualization framework that takes full advantage of the PC in terms of efficiency by allowing analysts to explore an exploring space, rather than a single visualization at a time. The results of the quantitative experiment and the performance of participants in the user study demonstrate the effectiveness and usability of the method.
Multi-Channel LSTM-Capsule Autoencoder Network for Anomaly Detection on Multivariate Data
Authors: Elhalwagy Ayman , Kalganova Tatiana
Published: November 2022

Deep learning techniques have recently shown promise in the field of anomaly detection, providing a flexible and effective method of modelling systems in comparison to traditional statistical modelling and signal processing-based methods. However, there are a few issues that Neural Networks (NN)s face, such as generalisation ability, requiring large volumes of labelled data to train effectively, and understanding spatial context in data. This paper introduces a novel NN architecture to tackle these problems, which utilises a Long-Short-Term-Memory (LSTM) encoder and Capsule decoder in a multi-channel input Autoencoder architecture for use on multivariate time series data. Experimental results show that using Capsule decoders increases the resilience of the model to overfitting and improves training efficiency, which is shown by the improvement of Mean Squared Error (MSE) on unseen data from an average of 10.61 to 2.08 for single channel architectures, and 10.08 to 2.05 for multi-channel architectures. Additionally, results also show that the proposed model can learn multivariate data more consistently, and was not affected by outliers in the training data. The proposed architecture was also tested on an open-source benchmark, where it achieved state-of-the-art performance in outlier detection, and performs best overall with a total accuracy of 0.494 over the metrics tested.
A Model of a Limited-Stop and Local Mixed Bus Service with Increased Fares for the Limited-Stop Service
Authors: Guo Chen , Wang Jianjun , Jian Meiying , Liu Zhenyu , Huo Yueying
Published: November 2022

This study designs a limited-stop and local mixed bus service from the perspectives of both transit agencies and passengers based on a proposed optimization model. Close attention was paid to the increase in fares for the limited-stop service in the proposed model to offset the loss in bus fare. The objective function was to minimize the passenger travel time and bus agency costs; the decision variables were the stops for the limited-stop service and the headways of the limited-stop and local services; the constraints included the range of fare increases for the limited-stop service and other factors. The Lingo software and the genetic algorithm were compared in solving the proposed model from the aspects of solving time and results. Because the solutions for the model within the planning time and the influence of the global optimal solution upon parametric analysis were stable, the Lingo software was more suitable for the proposed model. Evaluations of the total costs for the mixed service and local-only service were carried out for different bus corridor lengths. The ratio of the fares for the limited-stop service to the fares for the local service must be within the appropriate range in order to take advantage of the limited-stop service. When the stop spacing and the bus corridor distance were longer, the mixed service was more competitive and noticeable.
A Novel Named Entity Recognition Algorithm for Hot Strip Rolling Based on BERT-Imseq2seq-CRF Model
Authors: Jing Fengwei , Zhang Mengyang , Li Jie , Xu Guozheng , Wang Jing
Published: November 2022

Named entity recognition is not only the first step of text information extraction, but also the key process of constructing domain knowledge graphs. In view of the large amount of text data, complex process flow and urgent application needs in the hot strip rolling process, a novel named entity recognition algorithm based on BERT-Imseq2seq-CRF model is proposed in this paper. Firstly, the algorithm uses the BERT preprocessing language model to mine the dependencies in the domain text and obtain the corresponding representation vector. Then, the representation vector is sent to the encoder layer, and the output vector is input to the decoder at the same time, on the premise that the original model only considers the semantic vector. The Teacher-Forcing mechanism is integrated into the decoder layer to randomly modify the labeling results, and error accumulation is avoided to guarantee the sequence recognition effect. Finally, the validity of the labeling results is checked according to the conditional random field constraints, and the overall labeling quality of the algorithm is improved. The experimental results show that this model can efficiently and accurately predict the physical label of hot strip rolling, and the model performance index is better than other models, with the F1-Score reaching 91.47%. This model further provides technical support for information extraction and domain knowledge graph construction of hot strip rolling.
Machine Learning and Deterministic Methods for Detection Meteorological Phenomena from Ground Measurements: Application for Low-Level Jet and Sea-Breeze Identification in Northern France
Authors: Roy Sayahnya , Sentchev Alexei , Fourmentin Marc , Augustin Patrick
Published: November 2022

This study focused on the detection of mesoscale meteorological phenomena, such as the nocturnal low-level jet (NLLJ) and sea breeze (SB), using automatic deterministic detection wavelet technique algorithms (HWTT and SWT) and the machine learning recurrent neural network (RNN) algorithm. The developed algorithms were applied for detection of NLLJ and SB events from ultrasonic anemometer measurements, performed between January 2018 and December 2019 at a nearshore experimental site in the north of France. Both algorithms identified the SB and NLLJ days successfully. The accuracy of SB event detection by the RNN algorithm attained 95%, and we identified 67 and 78 SB days in 2018 and 2019, respectively. Additionally, a total of 192 and 168 NLLJ days were found in 2018 and 2019, respectively. To demonstrate the capability of the algorithms to detect SB and NLLJ events from near-ground ultrasonic anemometer measurements, analysis of the simultaneous wind lidar measurements available for 86 days were performed. The results show a good agreement between the RNN-based detection method and the lidar observations, detecting 88% of SB. Deterministic algorithms (HWTT and SWT) detected a similar number of NLLJ events and provided high correlation (0.98) with the wind lidar measurements. The meteorological phenomena studied can significantly affect the energy production of offshore wind farms. It was found that the maximum hourly average peak power production could be to 5 times higher than that of the reference day due to higher wind speed observed during NLLJ events. During SB events, hourly average peak power production could be up to 2.5 times higher. In this respect, the developed algorithms applied for analysis, from near-ground anemometer measurements, may be helpful for monitoring and forecasting the meteorological phenomena capable of disturbing the energy production of offshore wind turbines.
Bias Correction and Evaluation of Precipitation Data from the CORDEX Regional Climate Model for Monitoring Climate Change in the Wadi Chemora Basin (Northeastern Algeria)
Authors: Derdour Samiya , Ghenim Abderrahmane Nekkache , Megnounif Abdesselam , Tangang Fredolin , Chung Jing Xiang , Ayoub Afiqah Bahirah
Published: November 2022

This study aims to provide a brief overview of four regional climate model (RCM) estimations for (Daily, Monthly, Seasonal, and Annual) averaged precipitation over the Wadi Chemora Basin in northeastern Algeria for the historical period (1970–2005) and future forecasts (2006–2100). Data from seven ground stations were compared to data from four RCMs: RCA4 driven by ICHEC-EC-EARTH and NOAA-GFDL-GFDL-ESM2M from MENA-CORDEX domain with intermediate resolution (25 km, 0.22°) and ALADIN and RegCM4 from MED-CORDEX domain with high resolution (12 km, 0.11°). In most time steps (Annual, Seasonal, Monthly, and Daily), the raw RCMs overestimated precipitation, but their performance improved significantly after applying gamma quantile mapping (GQM) bias correction method. The bias-corrected projections indicate decreases of seasonal rainfall for the near future (2010–2039), mid-century (2040–2069), and end of century (2070–2100) periods. Overall decreases in all seasons lead to the projected decrease in annual rainfall of an average of 66% by the end of the 21st century.
Bayesian Inverse Modelling for Probabilistic Multi-Nuclide Source Term Estimation Using Observations of Air Concentration and Gamma Dose Rate
Authors: Tølløse Kasper Skjold , Sørensen Jens Havskov
Published: November 2022

In case of a release of hazardous radioactive matter to the atmosphere from e.g., a nuclear power plant accident, atmospheric dispersion models are used to predict the spatial distribution of radioactive particles and gasses. However, at the early stages of an accident, only limited information about the release may be available. Thus, there is a need for source term estimation methods suitable for operational use shortly after an accident. We have developed a Bayesian inverse method for estimating the multi-nuclide source term describing a radioactive release from a nuclear power plant. The method provides a probabilistic source term estimate based on the early available observations of air concentration and gamma dose rate by monitoring systems. The method is intended for operational use in case of a nuclear accident, where no reliable source term estimate exists. We demonstrate how the probabilistic formulation can be used to provide estimates of the released amounts of each radionuclide as well as estimates of future gamma dose rates. The method is applied to an artificial case of a radioactive release from the Loviisa nuclear power plant in southern Finland, considering the most important dose-contributing nuclides. The case demonstrates that only limited air concentration measurement data may be available shortly after the release, and that to a large degree one will have to rely on gamma dose rate observations from a frequently reporting denser monitoring network. Further, we demonstrate that information about the core inventory of the nuclear power plant can be used to constrain the release rates of certain radionuclides, thereby decreasing the number of free parameters of the source term.
Simultaneous Strain and Temperature Discrimination in 18650 Li-ion Batteries Using Polarization-Maintaining Fiber Bragg Gratings
Authors: Matuck Lucca , Pinto João Lemos , Marques Carlos , Nascimento Micael
Published: November 2022

In this work, a fiber Bragg grating (FBG) sensor network inscribed in a polarization-maintaining (PM) fiber is proposed to proceed with a multipoint simultaneous temperature and strain discrimination in different locations (positive and negative terminals, and middle) on a cylindrical Li-ion battery. The birefringence property of the PM fibers, together with FBG sensors, allowed such an application using only one fiber line fixed to the edges of the battery. The battery was subjected to two different charge/discharge cycles, one with nominal charging and discharging conditions (1.00 C and 1.13 C, respectively) and another with abusive conditions (1.88 C for charge and 2.39 C for discharge). The PM-FBG sensors registered maximum temperature and strain variations at the end of the abusive discharge process of the battery; the positive terminal achieved a 28.7 ± 0.3 °C temperature variation, while the center achieved 221 ± 10 με strain variation. The results indicate a different strain variation behavior in the middle location when compared to the negative and positive terminals, as well as a higher temperature variation in both terminals when compared to the middle location. The use of PM-FBG sensors successfully demonstrates their feasibility in locally tracking and discriminating strain and temperature shifts in a battery surface. To our knowledge, this is the first study using the application of PM-FBG sensors to monitor and discriminate critical safety parameters in Li-ion batteries.
SmartMinutes—A Blockchain-Based Framework for Automated, Reliable, and Transparent Meeting Minutes Management
Authors: Sheikhi Amir Salar Hajy , Iosif Elias , Basov Oleg , Dionysiou Ioanna
Published: November 2022

The aim of this research work was to investigate the applicability of smart contracts in the context of automating the process of managing meeting minutes. To this end, smartMinutes, a proof-of-concept prototype of automating meeting minutes was designed, implemented, and validated with test cases. The smartMinutes framework improves current practices related to the meeting minutes process by providing automation in areas where possible, and doing so in a transparent, flexible, reliable, and tamper-proof manner. The last feature is of paramount importance due to the fact that meeting minutes offer legal protection, as they are considered official records of the actions taken by an organisation. Additionally, smartMinutes supports meeting agendas with non-voting items as well as voting items, offering a pool of three voting schemes, executing under three different configurations. A particular configuration, the hidden mode, provides for secrecy while at the same time guaranteeing transparency.