bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of Transformational Leadership, Organizational Innovation, Work Stressors, and Creativity on Employee Performance in SMEs
Authors: Nasir Jawaria , Ibrahim Rashidah M. , Sarwar Muhammad Arslan , Sarwar Binesh , Al-Rahmi Waleed Mugahed , Alturise Fahad , Samed Al-Adwan Ahmad , Uddin Mueen
Published: April 2022

Purpose of the Study

The significance of creativity and performance in the workplace has been illustrated on various occasions. This study aims to find out if there is a link between transformative leadership, organizational innovation, psychological issues such as hindrance and challenge stressors, and employee creativity and employee performance. There is still a lack of awareness of the factors that influence employee performance in small and medium businesses (SMEs) in Pakistan. Pakistan’s SMEs have struggled to survive in their early years, with an initial failure rate of 90 percent to 95 percent.

Methodology

The relationship between hindrance and challenge stressors, organizational innovation, transformational leadership, employee creativity, and their effect on overall employee performance is established through employing Structural Equation Modeling (SEM). In this study, constructs were developed from existing theories, hypotheses were generated, data were collected from 424 SME employees, and SEM analysis was conducted to prove the suggested hypothesis. The employees of SMEs are the research study’s unit of analysis.

Findings

The findings of this study demonstrated that challenge stressors, transformational leadership, and employee creativity all had positive and significant effects on employee performance.

Originality/Value

This is one of the first studies to study and extends existing understanding of psychological research in this manner and following correlations in a developing country, Pakistan: the links between transformational leadership and employees’ perception of creativity and performance along with organizational innovation and work stressors. Based on theoretical considerations, a model is proposed, and hypotheses are established and explored. The findings of this study can help businesses increase employee performance by informing employee performance improvement methods. Business executives might learn more about how to engage and motivate employees to improve their performance.
New Working Capabilities for Coping With COVID Time Challenges
Authors: Fregnan Ezio , Scaratti Giuseppe , Ciocca Leonardo , Ivaldi Silvia
Published: April 2022

The COVID-19 pandemic played as a booster to the cultural, social, and economic transformations triggered by the 4.0 Industrial Revolution, increasing the diffusion and employment of technological devices and requiring to reconsider the traditional approach to work and organization. Dealing with an emblematic organizational case, the article highlights the main key capabilities requested to face the current scenario, suggesting transformed attitudes needed to cope with the unfolding complex, uncertain, changing digital and blended world. The findings, gathered through an extensive survey involving 500 people who started working at a distance during the 2020 lockdown period, underline the main actionable skills to be achieved for enhancing agile work, hybrid professional roles and new work, and organizational and managerial cultures.
Understanding the Role of Users’ Psychological Needs on Relationship Quality in Short Video Applications
Authors: Huangfu Zhounan , Zhou Lei , Zhao Jing , Kotchasit Sombat , Chen Wanmei
Published: April 2022

Along with the rapid development of big data, artificial intelligence, and information technology, the relationship quality (RQ) between short video applications and users is important for the sustainable development of short video applications. However, the existing studies have explored the mechanism of the role of RQ in a limited way. In order to respond to this critical issue, this study constructs a theoretical model based on attachment theory and combined with self-determination theory, with autonomy needs (AN), competence needs (CN), and relationship needs (RN) as influencing factors, emotional attachment (EA) as mediating variables and relationship quality as outcome variables, and the moderating role of attachment anxiety (AA) in which this study also analyzes the mechanism of short video applications users’ psychological needs on relationship quality by combining the moderating role of AA. In this study, a sample of 512 university students using short video applications was used. The results of the data analysis indicated that EA was significantly influenced by psychological needs that played a positive role in relationship quality and mediated the relationship between psychological needs and relationship quality. The results of further analysis also revealed that attachment anxiety plays a moderating role in the relationship between emotional attachment and relationship quality. This study examines the intrinsic mechanism by which psychological needs affect relationship quality through emotional attachment, reveals the practical effects of short video applications users’ sustained use behavior, and provides a reference for innovative management and business practices of short video applications.
Content Analysis of Warning Signs Identified as Part of Crisis Response Planning in a Community Sample of Gun Owners and Non-owners
Authors: Bauder Christina Rose , Hay Jarrod M. , McClung James G. , Starkey Austin G. , Bryan Craig J.
Published: April 2022

Background

Assessing for and identifying those at imminent risk for suicide continues to present challenges, especially as many who die do not interact with specialty mental health treatment preceding suicide. Suicide-specific interventions in healthcare settings have been found to improve suicide-related outcomes, yet little is known about the confluence of behavioral, cognitive, emotional, and physiological indicators of emotional distress as they correspond to other key risk characteristics and high-risk groups like gun owners.

Aim

The purpose of this content analysis was to examine self-identified warning signs of distress between gun owners and non-owners through crisis response planning (CRP).

Methods

Participants completed a collaborative CRP. Warning signs were categorized as being either behavioral, cognitive, emotional, or physiological in nature. Bivariate logistic regression models were used to examine associations between firearm ownership and variables of interest. Participants were evenly split between men (n = 44) and women (n = 44) and were predominantly white (67.1%) with a mean age of 35.9 (SD = 13.6).

Results

Emotional warning signs of distress (68.2%) were reported slightly more often than behavioral (65.9%) followed by physiological (52.3%), and cognitive (46.6%). Firearm owners were significantly more likely to be male (OR = 2.5, 95%CI [1.07–6.0]). All participants were about a fourth as likely to report both a behavioral and physiological warning sign concurrently (OR = 0.26, 95% CI [0.09–0.67]).

Conclusion

Similarities and departures in warning signs of emotional distress may inform future research exploring both self-reported warning signs and related self-management strategies identified through suicide-specific interventions, particularly among high-risk groups such as gun owners.
The Dynamic Impact of COVID-19 Pandemic on Stock Returns: A TVP-VAR-SV Estimation for G7 Countries
Authors: Tan Xiaoyu , Ma Shiqun , Wang Xuetong , Zhao Yang , Wang Zhimeng , Xiang Lijin
Published: April 2022

The COVID-19 pandemic has profoundly and negatively impacted the global stock markets. Hence, we investigated the time-varying impact of the COVID-19 pandemic on stock returns during the period from January 27, 2020 to December 23, 2021 using the TVP-VAR-SV model and used G7 countries as our research sample. Our results imply that (i) the spread of the COVID-19 pandemic has a significant negative impact on stock returns, but the impact decreases as the time window increases; (ii) the timeliness, compulsoriness, and effectiveness of anti-epidemic policies implemented by governments are the important adjustment factors for stock returns; (iii) the impact of the early stage of the COVID-19 pandemic on the stock market trend gradually weakens as the intermediate time interval increases. In addition, over time, the duration of the negative impact of the COVID-19 pandemic on the stock returns became shorter, and the recovery rate of the impact became faster; (iv) under the managed floating exchange rate regime, the stock returns changed synchronously with the pressures of exchange rate appreciation and depreciation, and under the free-floating exchange rate regime, the effect of the exchange rate on stock returns was almost zero, while the impact of exchange rate channels in eurozone countries was related to the characteristics of national economies. Thus, governments should make greater efforts to improve the compulsion and effectiveness of epidemic prevention policies and strengthen their control over exchange rate fluctuations to alleviate the negative impact of the COVID-19 pandemic on the stock markets.
How the Brain Dynamically Constructs Sentence-Level Meanings From Word-Level Features
Authors: Aguirre-Celis Nora , Miikkulainen Risto
Published: April 2022

How are words connected to the thoughts they help to express? Recent brain imaging studies suggest that word representations are embodied in different neural systems through which the words are experienced. Building on this idea, embodied approaches such as the Concept Attribute Representations (CAR) theory represents concepts as a set of semantic features (attributes) mapped to different brain systems. An intriguing challenge to this theory is that people weigh concept attributes differently based on context, i.e., they construct meaning dynamically according to the combination of concepts that occur in the sentence. This research addresses this challenge through the Context-dEpendent meaning REpresentations in the BRAin (CEREBRA) neural network model. Based on changes in the brain images, CEREBRA quantifies the effect of sentence context on word meanings. Computational experiments demonstrated that words in different contexts have different representations, the changes observed in the concept attributes reveal unique conceptual combinations, and that the new representations are more similar to the other words in the sentence than to the original representations. Behavioral analysis further confirmed that the changes produced by CEREBRA are actionable knowledge that can be used to predict human responses. These experiments constitute a comprehensive evaluation of CEREBRA's context-based representations, showing that CARs can be dynamic and change based on context. Thus, CEREBRA is a useful tool for understanding how word meanings are represented in the brain, providing a framework for future interdisciplinary research on the mental lexicon.
Psychosocial Safety Climate Moderates the Effect of Demands of Hospital Accreditation on Healthcare Professionals: A Longitudinal Study
Authors: Alshamsi Amna I. , Santos Angeli , Thomson Louise
Published: April 2022

Hospital accreditation has been studied comprehensively, yet few studies have observed its impacts on the burnout and work engagement levels of frontline healthcare professionals (HCPs). With a sample of 121 HCPs working in the United Arab Emirates' public hospitals, this study used a two-wave, cross-lagged panel design to examine the direct effects of job demands and job resources during hospital accreditations on burnout and work engagement and the moderating roles of psychosocial safety climate (PSC) on burnout and work engagement 3 months after accreditation. The data were analyzed using moderated structural equation modeling. As expected, we found that job demands (i.e., accreditation demands) had a direct effect on burnout, while job resources (i.e., social support) predicted work engagement. PSC moderated both relationships; however, it was not able to directly predict burnout or work engagement. Findings from this study show a positive relationship between accreditation demands and HCPs' health. Future research needs to examine the link between PSC and job demands-resources concepts before and after hospital accreditation more closely by using multiple time points to assess the causality relationships between predictor and outcome variables.
Recycling, Norms, and Convenience: A Bivariate Probit Analysis of Household Data From a Swedish City
Authors: Berglund Christer , Söderholm Patrik , Hage Olle
Published: April 2022

The purpose of this article is to investigate the role of norms and convenience for households' packaging waste sorting activities. The theoretical point of departure is a simple economic model that integrates norm-motivated behavior into neoclassical utility theory by assuming that the individual has a preference for maintaining a self-image as a morally responsible (norm-compliant) person. The empirical analysis rests on survey responses from 398 households in the city of Eskilstuna, Sweden. Self-reported information on recycling contributions and personal norms is analyzed in a bivariate probit model, which estimates the probability of pursuing high-performing recycling efforts as an endogenously determined decisions to the activation of a personal norm for waste sorting. The results suggest that norm activation is an important driver for households' recycling contributions, as is convenience in the form of access to property-close collection schemes. Personal norms are in turn primarily activated by the presence of social, legal, and descriptive norms. One important implication is that policy needs to build on well-aligned policy instrument mixes that combine references to the moral significance of households' recycling contributions with various infrastructural measures that facilitate such contributions.
Evaluating the Possibility of Transfusion Medicine, Through Crossmatching in Juvenile Galapagos Sea Lions (Zalophus wollebaeki)
Authors: Gregory Taylor M. , Parker Maryanna , Deresienski Diane , Alarcón-Ruales Daniela , Muñoz-Pérez Juan Pablo , Torres Jorge , Gavilanes Gabriela I. , Lewbart Gregory A. , Páez-Rosas Diego
Published: April 2022

The Galapagos sea lion (Zalophus wollebaeki) is an endemic pinniped to the Galapagos archipelago, and like most wild mammals, is at risk for anemia due to trauma, infectious disease, and poor nutrition. This study evaluated the health status of 26 juvenile Galapagos sea lions on the island of San Cristobal prior to evaluating 100 crossmatch combinations. On evaluation, all but one sea lion had no major systemic abnormalities. Of the 100 crossmatches performed, 23% had minor reactions. The most significant reaction was weak macroscopic agglutination found in 4% of samples. The small percentage of agglutination reactions suggests a small proportion of naturally occurring alloantibodies in this species and may be consistent with a low risk of acute immune-mediated hemolytic transfusion reaction.
Patient Selection for Downstaging of Hepatocellular Carcinoma Prior to Liver Transplantation—Adjusting the Odds?
Authors: Seehofer Daniel , Petrowsky Henrik , Schneeberger Stefan , Vibert Eric , Ricke Jens , Sapisochin Gonzalo , Nault Jean-Charles , Berg Thomas
Published: April 2022

Background and Aims: Morphometric features such as the Milan criteria serve as standard criteria for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC). Since it has been recognized that these criteria are too restrictive and do not adequately display the tumor biology, additional selection parameters are emerging.

Methods: Concise review of the current literature on patient selection for downstaging and LT for HCC outside the Milan criteria.

Results: The major task in patients outside the Milan criteria is the need for higher granularity with patient selection, since the benefit through LT is not uniform. The recent literature clearly shows that beneath tumor size and number, additional selection parameters are useful in the process of patient selection for and during downstaging. For initial patient selection, the alpha fetoprotein (AFP) level adds additional information to the size and number of HCC nodules concerning the chance of successful downstaging and LT. This effect is quantifiable using newer selection tools like the WE (West-Eastern) downstaging criteria or the Metroticket 2.0 criteria. Also an initial PET-scan and/or tumor biopsy can be helpful, especially in the high risk group of patients outside the University of California San Francisco (UCSF) criteria. After this entry selection, the clinical course during downstaging procedures concerning the tumor and the AFP response is of paramount importance and serves as an additional final selection tool.

Conclusion: Selection criteria for liver transplantation in HCC patients are becoming more and more sophisticated, but are still imperfect. The implementation of molecular knowledge will hopefully support a more specific risk prediction for HCC patients in the future, but do not provide a profound basis for clinical decision-making at present.
The Effect of Sowing Density and Different Harvesting Stages on Yield and Some Forage Quality Characters of the White Sweet Clover (Melilotus albus)
Authors: Sowa-Borowiec Patrycja , Jarecki Wacław , Dżugan Małgorzata
Published: April 2022

White sweet clover (Melilotus albus) cultivation, despite its many positive features such as the high yield of green mass, as well as protein content, is currently not widespread. This study aimed to determine the effect of the different sowing densities (500, 1000, and 1500 seeds per m2) and harvesting at different growth stages (before budding, budding, and full flowering) on the quality of fodder from the white sweet clover (Adela variety). The field experiment was carried out in the years 2018–2020 in a split-plot design. Plant biometric measurements, green and dry yield, the content of total protein, crude fat, crude fiber, ash, macro and microelements, and coumarin content were determined. The results show that an increase in the sowing density significantly increased the plant population after emergence and green and dry matter. However, it does not affect the total protein, crude fat, crude fiber, ash, macro and microelements, and coumarin content. Harvesting plants at the flowering stage increased plant height and green fodder yield. Plants harvested at the prebudding phase were characterized by the highest share of leaves (40.3%) and were the most abundant in protein (21.7%) and minerals (ash content 12.71%). Unfortunately, sweet clover at this growth stage contained the highest level of coumarin, which limits its use in animal feed.
Fermentation Quality and Bacterial Diversity of Broussonetia papyrifera Leaves Ensiled with Lactobacillus plantarum and Stored at Different Temperatures
Authors: Zheng Mingyang , Zhou Wei , Zou Xuan , Wu Shuo , Chen Xiaoyang , Zhang Qing
Published: April 2022

Broussonetia papyrifera has increasingly been used as a high-quality feedstuff for ruminants due to its advantageous characteristics. The storage temperature can influence the fermentation quality of silage; however, the effect of temperature on B. papyrifera leaves (BPL) silage has not been reported. In the present study, the fermentation quality and bacterial community of BPL, stored at 15 °C and 30 °C, were investigated during ensiling (day 3, 7, 14, 30) with or without Lactobacillus plantarum strain (LP) added. The pH and the coliform bacteria counts were significantly lower in silage stored at 30 than 15 °C (p < 0.01), while the lactic acid content increased significantly (p < 0.05). Adding LP decreased the dry matter loss, pH, coliform bacteria count, and ammonia-N and butyric acid contents at 30 °C. The relative abundance of Lactobacillus increased, while the bacterial diversity decreased in the silage stored at 30 °C when LP was added. During silage, the high abundance of Lactobacillus decreased gas and carbon dioxide (CO2) production, and the lowest gas and CO2 production were detected in silage stored at 30 °C when LP was added. In conclusion, adding LP and storing it at 30 °C could effectively improve the quality of BPL silage.
Progress in Expression Pattern and Molecular Regulation Mechanism of LncRNA in Bovine Mastitis
Authors: Jia Li , Wang Jinpeng , Luoreng Zhuoma , Wang Xingping , Wei Dawei , Yang Jian , Hu Qichao , Ma Yun
Published: April 2022

Bovine mastitis is an inflammatory disease caused by pathogenic microbial infection, trauma, or other factors. Its morbidity is high, and it is difficult to cure, causing great harm to the health of cows and the safety of dairy products. Susceptibility or resistance to mastitis in individual cows is mainly determined by genetic factors, including coding genes and non-coding genes. Long non-coding RNAs (lncRNAs) are a class of endogenous non-coding RNA molecules with a length of more than 200 nucleotides (nt) that have recently been discovered. They can regulate the immune response of humans and animals on three levels (transcription, epigenetic modification, and post-transcription), and are widely involved in the pathological process of inflammatory diseases. Over the past few years, extensive findings revealed basic roles of lncRNAs in inflammation, especially bovine mastitis. This paper reviews the expression pattern and mechanism of long non-coding RNA (lncRNA) in inflammatory diseases, emphasizes on the latest research progress of the lncRNA expression pattern and molecular regulatory mechanism in bovine mastitis, analyzes the molecular regulatory network of differentially expressed lncRNAs, and looks forward to the research and application prospect of lncRNA in bovine mastitis, laying a foundation for molecular breeding and the biological therapy of bovine mastitis.
Classification and Analysis of Multiple Cattle Unitary Behaviors and Movements Based on Machine Learning Methods
Authors: Li Yongfeng , Shu Hang , Bindelle Jérôme , Xu Beibei , Zhang Wenju , Jin Zhongming , Guo Leifeng , Wang Wensheng
Published: April 2022

The behavior of livestock on farms is the primary representation of animal welfare, health conditions, and social interactions to determine whether they are healthy or not. The objective of this study was to propose a framework based on inertial measurement unit (IMU) data from 10 dairy cows to classify unitary behaviors such as feeding, standing, lying, ruminating-standing, ruminating-lying, and walking, and identify movements during unitary behaviors. Classification performance was investigated for three machine learning algorithms (K-nearest neighbors (KNN), random forest (RF), and extreme boosting algorithm (XGBoost)) in four time windows (5, 10, 30, and 60 s). Furthermore, feed tossing, rolling biting, and chewing in the correctly classified feeding segments were analyzed by the magnitude of the acceleration. The results revealed that the XGBoost had the highest performance in the 60 s time window with an average F1 score of 94% for the six unitary behavior classes. The F1 score of movements is 78% (feed tossing), 87% (rolling biting), and 87% (chewing). This framework offers a possibility to explore more detailed movements based on the unitary behavior classification.
Identification of Genes Related to Squab Muscle Growth and Lipid Metabolism from Transcriptome Profiles of Breast Muscle and Liver in Domestic Pigeon (Columba livia)
Authors: Yin Zhaozheng , Zhou Wei , Mao Haiguang , Dong Xinyang , Huang Xuan , Zhang Haiyang , Liu Honghua
Published: April 2022

The improvements in muscle growth rate and meat quality are the major breeding aims in pigeon industry. Liver and muscle are recognized as important sites for fatty acid metabolism; understanding the role of specific transcripts in the breast muscle and liver might lead to the elucidation of interrelated biological processes. In this study, RNA-Sequencing (RNA-Seq) was applied to compare the transcriptomes of breast muscle and liver tissues among pigeons at five developmental periods (0, 1, 2, 3, 4 weeks post-hatching) to identify candidate genes related to muscle growth and lipid metabolism. There were 3142 differentially expressed genes (DEGs) identified in the breast muscle libraries; 1794 genes were up-regulated while 1531 genes were down-regulated. A total of 1323 DEGs were acquired from the liver libraries, with 791 up-regulated genes and 591 down-regulated genes. By pathway enrichment analysis, a set of significantly enriched pathways were identified for the DEGs, which are potentially involved in cell proliferation and differentiation, lipid metabolism and energy metabolism in pigeon breast muscle and liver. Our results are consistent with previous partial reports from domestic animals and poultry and provide some unidentified genes involved in muscle growth and lipid metabolism. The reliability of the sequencing data was verified through qPCR analysis of 16 genes from eight comparison groups (two genes per group). The findings from this study could contribute to future investigations of muscle growth and lipid metabolism mechanisms and establish molecular approaches to improve muscle growth rate and meat quality in domestic pigeon breeding.
Dynamic of Hepatitis E Virus (HEV) Shedding in Pigs
Authors: Ianiro Giovanni , Monini Marina , De Sabato Luca , Chelli Eleonora , Cerini Natalino , Ostanello Fabio , Di Bartolo Ilaria
Published: April 2022

Genotype 3 of hepatitis E virus (HEV-3) is the most common in Europe in both humans and pigs. HEV-3 strains are zoonotic, and foodborne cases associated with consumption of raw and undercooked pork products, mainly liver sausages, have been described. HEV-3 circulates largely in European pig farms, maybe due to its long persistence in the environment. Animals get infected around 3–4 months of age; shortly after, the infection starts to decline up to the age of slaughtering (8–9 months of age in Italy). With the purpose to understand the duration in farmed pigs of the shedding of the virus and its quantity, HEV-RNA detection was performed by Real-time RT-PCR from feces collected individually from two groups of 23 pigs. Sampling was conducted for 4 months shortly before slaughtering age. At 4-months-old, all animals were shedding HEV-3 to high load around 105 genome copies per gram (GC/g). Prevalence was higher in growers than in fatteners, with most of the pigs still positive around 166 days of age. Beyond some difference among individual pigs, the amount of HEV in feces decreased with the age of animals. The longest fattening period should ensure a lower risk of HEV shedder animals at slaughter, reducing the risk of food contamination.
Characterization of Salmonella spp. and E. coli Strains Isolated from Wild Carnivores in Janos Biosphere Reserve, Mexico
Authors: López-Islas Jonathan J. , Méndez-Olvera Estela T. , Martínez-Gómez Daniel , López-Pérez Andrés M. , Orozco Libertad , Suzan Gerardo , Eslava Carlos
Published: April 2022

Enterobacteriaceae are considered one the most important zoonotic pathogens. In this study, we analyzed the characteristics of E. coli and Salmonella spp. strains present in carnivores from Janos Biosphere Reserve, Mexico. These microorganisms had been isolated from a wide range of domestic and free-range animals, including wild carnivores. Fifty-five individuals were sampled, and the presence of Salmonella and E. coli was determined by bacteriological standard methods. Strains isolated were characterized by molecular methods and in vitro infection assays. Eight different species of carnivores were captured, including coyotes (Canis latrans), gray fox (Urocyon cinereoargenteus), desert foxes (Vulpes macrotis), striped skunks (Mephitis mephitis), hooded skunks (Mephitis macroura), lynxes (Lynx rufus), raccoons (Procyon lotor), and badgers (Taxidea taxus). Salmonella spp. and E. coli were isolated from four species of carnivores. Five Salmonella spp. strains were isolated, and their molecular characterization revealed in three of them the presence of fimbrial and virulence genes associated with cell invasion. In vitro evaluation of these strains showed their capability to invade human Hep2 cells. Sixty-one E. coli strains were isolated; different serotypes and phylogroups were observed from these strains. Additionally, the presence of virulence genes showed differently.
The Possibility of Including Donkey Meat and Milk in the Food Chain: A Southern African Scenario
Authors: Hassan Zahra Mohammed , Manyelo Tlou Grace , Nemukondeni Ndivho , Sebola Amenda Nthabiseng , Selaledi Letlhogonolo , Mabelebele Monnye
Published: April 2022

Animal proteins are essential for the optimal growth and health of humans. Meat and milk are common sources of protein, mostly produced by ruminants. The agrarian challenges experienced around the world warrant sourcing alternative proteins from animals that can withstand harsh environmental conditions to produce quality proteins. Donkeys (Equus asinus) are known to survive on low husbandry and inferior quality forage to produce meat and milk, which have been used since ancient times. However, the commercialisation of these products has not flourished due to product scarcity, low production rates, and consumer preferences. Recent discoveries and the quest to look for alternative sources of protein have sparked studies on donkey products. In addition, milk and meat from donkeys have active ingredients that could also contribute to curing diseases. Donkey milk is believed to contain antioxidant, antimicrobial, antiproliferative, and antidiabetic properties. In many countries, particularly in Africa, the consumption of donkey meat and milk has not been fully adopted due to a lack of knowledge and legislation regarding production.
An Up-To-Date Review Regarding Cutaneous Benefits of Origanum vulgare L. Essential Oil
Authors: Bora Larisa , Avram Stefana , Pavel Ioana Zinuca , Muntean Delia , Liga Sergio , Buda Valentina , Gurgus Daniela , Danciu Corina
Published: April 2022

Due to the plethora of pharmacological activities reported in the literature, Origanum vulgare L. is a valuable aromatic plant for the medicine of the XXI century. Recent studies highlight that Origanum vulgare L. essential oil (OvEo) has gained attention in the dermatological field due to the cosmeceutical potential correlated with the presence of thymol and carvacrol. As a result of the fulminant expansion of bacterial resistance to antibiotics and the aggressiveness of skin infections, OvEo was extensively studied for its antimicrobial activity against Staphyloccocus spp. and Pseudomonas aeruginosa. Moreover, researchers have also assessed the anti-inflammatory activity of OvEo, suggesting its tissue remodeling and wound healing potential. Whereas OvEo comprises important biological activities that are used in a wide range of pathologies, recently, essential oils have shown great potential in the development of new therapeutic alternatives for skin disorders, such as acne, wounds or aging. Furthermore, substantial efforts have been committed to the development of modern formulations, such as microemulsions and nanoemulsions, in order to create the possibility for topical application. The review brings to the fore the most recent findings in the dermatological field regarding potential plant-based therapies involving OvEo, emphasizing the modern pharmaceutical formulation approaches and the cutaneous benefits in skin disorders.
Values and Risk Perception Shape Canadian Dairy Farmers’ Attitudes toward Prudent Use of Antimicrobials
Authors: Cobo-Angel Claudia , Gohar Basem , LeBlanc Stephen J.
Published: April 2022

Antimicrobial resistance (AMR) is an important challenge in public health. Ensuring rational antimicrobial use (AMU) on farms is one of the key components of antimicrobial stewardship. We aimed to describe a sample of Canadian dairy farmers’ personal factors for AMUand their AMR risk perception, and to associate these factors with their attitude toward promotion of prudent AMU. We distributed an online survey among dairy farmers in Ontario and Atlantic Canada (New Brunswick, Nova Scotia, and Prince Edward Island). The questionnaire was designed to solicit information on dairy farmers’ AMU decision-making process, attitudes toward AMU reduction, awareness of AMR, and individual values. We performed a factor analysis on 15 statements related to AMR awareness and AMU reduction and used a logistic regression model to identify variables associated with the probability of disagreeing with the need to increase promotion of responsible AMU in the dairy industry. Respondents’ (n = 193) previous experience was the main reason to select an antimicrobial treatment for their cattle. We identified four groups of factors related to knowledge, risk perception, and emotional states among respondents. To the question “Should there be more initiatives to promote responsible use of antibiotics in the dairy industry?” 23% of respondents answered no, which was associated in a logistic regression model with being a farm owner, having a tie-stall barn, and considering their own experience as the most important factor in selecting antimicrobial treatments. The score for the conservation value dimension and score for a factor described as sense of responsibility when using antimicrobials were also retained in the final model. Our results indicate that tailored strategies to promote prudent AMU on dairy farms may be preferable to a generic strategy because there are individual differences in attitudes, values, and AMR awareness that shape AMR risk perception and willingness to modify current AMU practices.
Melatonin Maintains Fruit Quality and Reduces Anthracnose in Postharvest Papaya via Enhancement of Antioxidants and Inhibition of Pathogen Development
Authors: Fan Silin , Li Qian , Feng Shujie , Lei Qiumei , Abbas Farhat , Yao Yulin , Chen Weixin , Li Xueping , Zhu Xiaoyang
Published: April 2022

Papaya fruit is widely grown in tropical regions because of its sweet taste, vibrant color, and the huge number of health benefits it provides. Melatonin is an essential hormone that governs many plants′ biological processes. In the current study, the impact of melatonin on fruit ripening and deterioration in postharvest papaya fruit was explored. An optimum melatonin dose (400 μmol L−1, 2 h) was found to be effective in delaying fruit softening and reducing anthracnose incidence. Melatonin enhanced antioxidant activity and decreased fruit oxidative injury by lowering superoxide anion, hydrogen peroxide, and malondialdehyde content by enhancing the enzymatic and non-enzymatic antioxidants, and by improving the antioxidant capacity of papaya fruit. Melatonin increased catalase, ascorbate peroxidase, NADH oxidase, glutathione reductase, polyphenol oxidase, superoxide dismutase, and peroxidase activity, as well as induced total phenol, total flavonoid, and ascorbic acid accumulation. Melatonin also enhanced the activity of defense-related enzymes, such as chitinase, 4-coumaric acid-CoA-ligase, and phenylalanine ammonia lyase, while it repressed lipid metabolism. Additionally, melatonin inhibited the development of anthracnose in vitro and in vivo. These findings suggest that exogenous melatonin application improves papaya fruit quality by boosting antioxidant and defense-related mechanisms.
The Source of Protein or Its Value? Consumer Perception Regarding the Importance of Meat(-like) Product Attributes
Authors: Antoniak Marcin Adam , Szymkowiak Andrzej , Pepliński Benedykt
Published: April 2022

Food product attributes may significantly influence the general perception of the product itself, as well as the willingness for its consumption. Assessment of the product is based on customers’ beliefs and individual preferences. Because meat-like products are presented as meat substitutes providing sufficient protein values, the present study aimed to determine the effect of protein source and labelling pointing at high protein content on the evaluation of the product. The experimental online study was conducted with a group of 552 respondents. Four versions of product packaging were designed and tested. These packages differed in the presence or absence of the Nutrition Claim and the presence of the text indicating the vegetable or meat origin of the product. Data collected in the experiment were analyzed using a 2 × 2 ANOVA. The study revealed that the source of protein (plant vs. animal) appears to shape consumers’ perception of the product as more eco-friendly (F (1.518) = 38.681, p < 0.001, η2 = 0.069), natural (F (1.518) = 15.518, p < 0.001, η2 = 0.029), and healthy (F (1.518) = 25.761, p < 0.001, η2 = 0.047). Moreover, labelling including a “high-protein” Nutrition Claim increases the willingness to consume the product (F (1.518) = 4.531, p = 0.034, η2 = 0.009), and provides the impression of it being more eco-friendly (F (1.518) = 6.658, p = 0.01, η2 = 0.012) and of a higher quality (F (1.518) = 7.227, p = 0.007, η2 = 0.014). The obtained results may have theoretical significance by improving the understanding of factors determining the perception of food products and the use of meat substitutes.
Evaluation of RGB-D Multi-Camera Pose Estimation for 3D Reconstruction
Authors: de Medeiros Esper Ian , Smolkin Oleh , Manko Maksym , Popov Anton , From Pål Johan , Mason Alex
Published: April 2022

Advances in visual sensor devices and computing power are revolutionising the interaction of robots with their environment. Cameras that capture depth information along with a common colour image play a significant role. These devices are cheap, small, and fairly precise. The information provided, particularly point clouds, can be generated in a virtual computing environment, providing complete 3D information for applications. However, off-the-shelf cameras often have a limited field of view, both on the horizontal and vertical axis. In larger environments, it is therefore often necessary to combine information from several cameras or positions. To concatenate multiple point clouds and generate the complete environment information, the pose of each camera must be known in the outer scene, i.e., they must reference a common coordinate system. To achieve this, a coordinate system must be defined, and then every device must be positioned according to this coordinate system. For cameras, a calibration can be performed to find its pose in relation to this coordinate system. Several calibration methods have been proposed to solve this challenge, ranging from structured objects such as chessboards to features in the environment. In this study, we investigate how three different pose estimation methods for multi-camera perspectives perform when reconstructing a scene in 3D. We evaluate the usage of a charuco cube, a double-sided charuco board, and a robot’s tool centre point (TCP) position in a real usage case, where precision is a key point for the system. We define a methodology to identify the points in the 3D space and measure the root-mean-square error (RMSE) based on the Euclidean distance of the actual point to a generated ground-truth point. The reconstruction carried out using the robot’s TCP position produced the best result, followed by the charuco cuboid; the double-sided angled charuco board exhibited the worst performance.
Application of Light-Emitting Diode Lights to Bluefin Sea Robin (Chelidonichthys spinosus) Catch in Pot Fishery in the South Sea, Korea
Authors: Kim Pyungkwan , Kim Hyungseok , Kim Seonghun
Published: April 2022

The bluefin sea robin (Chelidonichthys spinosus), hereafter BSR, is one of the most important fish species in the South Sea of Korea. The production value of BSR in 2020 was USD 4,733,057. The production volume in Korea has shown an annual mean increase of 8.9% since 2010, but the efficiency of the fishing gear decreased due to excessive use. This has led to a decrease in the profitability of fishery operators, and as compensation, the use of fishing gear has further increased through competitive operations. Alternative measures for improving catch performance and reducing the use of fishing gear are needed. As one such measure, LED (Light-Emitting Diode) lights were attached to the pot, and the effects were determined. The field experiment results showed that the catch of BSR was higher for the experimental groups (n = 10–273) using fishing gear with LED lights (red, green, blue, and white) than for the control group (n = 2) (Kruskal–Wallis test, p < 0.05). Among the experimental groups, the pot with green light achieved the largest catch (n = 273). The use of LED lights was found to enhance the catch efficiency of pot fishing gear for BSR.
Low Temperature Step Annealing Synthesis of the Ti2AlN MAX Phase to Fabricate MXene Quantum Dots
Authors: Akhtar Sophia , Roy Shrawan , Tran Trang Thu , Singh Jaspal , Sharbirin Anir S. , Kim Jeongyong
Published: April 2022

We present the synthesis of the Ti2AlN MAX phase using two-step annealing at temperatures of 600 °C and 1100 °C, the lowest synthesis temperatures reported so far. After the successful synthesis of the Ti2AlN MAX phase, two-dimensional Ti2N MXene was prepared through wet chemical etching and further fragmented into light emitting MXene quantum dots (MQDs) with a size of 3.2 nm by hydrothermal method. Our MQDs displayed a 6.9% quantum yield at a 310 nm wavelength of excitation, suggesting promising nanophotonic applications.
Seizure Prediction Based on Transformer Using Scalp Electroencephalogram
Authors: Yan Jianzhuo , Li Jinnan , Xu Hongxia , Yu Yongchuan , Xu Tianyu
Published: April 2022

Epilepsy is a chronic and recurrent brain dysfunction disease. An acute epileptic attack will interfere with a patient’s normal behavior and consciousness, having a great impact on their life. The purpose of this study was to design a seizure prediction model to improve the quality of patients’ lives and assist doctors in making diagnostic decisions. This paper presents a transformer-based seizure prediction model. Firstly, the time-frequency characteristics of electroencephalogram (EEG) signals were extracted by short-time Fourier transform (STFT). Secondly, a three transformer tower model was used to fuse and classify the features of the EEG signals. Finally, when combined with the attention mechanism of transformer networks, the EEG signal was processed as a whole, which solves the problem of length limitations in deep learning models. Experiments were conducted with a Children’s Hospital Boston and the Massachusetts Institute of Technology database to evaluate the performance of the model. The experimental results show that, compared with previous EEG classification models, our model can enhance the ability to use time, frequency, and channel information from EEG signals to improve the accuracy of seizure prediction.
The Influence of Track Irregularity in Front of the Turnout on the Dynamic Performance of Vehicles
Authors: Chang Wenhao , Cai Xiaopei , Wang Qihao , Tang Xueyang , Sun Jialin , Yang Fei
Published: April 2022

While the track irregularity in turnout areas has a significant impact on wheel-rail contact, driving safety, and stability, the impact of track irregularity in front of the incoming turnout on vehicles is often overlooked. This paper fills the gaps in the study. As a result, a rigid-flexible coupled dynamic model of the vehicle and turnout is developed. The effect of various irregularities in front of the turnout on the dynamic performance of a vehicle at high speeds has been investigated based on a random sampling method. The results show that different types of track irregularities in front of the turnout have different effects on the dynamic responses of vehicles. The vehicle dynamic performance is most sensitive to short-wavelength (3 m) irregularities in front of the turnout. The alignment irregularity with long-wavelength (40 m) has a significant effect on the wheelset lateral force and lateral acceleration of the vehicle body, caused by two-point contact between the wheel and rail. The frequency range of the effect of the irregularities on the wheel-rail force, safety indicators, and accelerations of the vehicle is mainly below 200 Hz, 50 Hz, and 20 Hz. In this study, a comprehensive assessment of different irregularities is conducted, as well as a quantitative reflection on the effect of the irregularity on the dynamic indicators, providing a reference for maintenance.
Red Fox Optimizer with Data-Science-Enabled Microarray Gene Expression Classification Model
Authors: Vaiyapuri Thavavel , Liyakathunisa  , Alaskar Haya , Aljohani Eman , Shridevi S. , Hussain Abir
Published: April 2022

Microarray data examination is a relatively new technology that intends to determine the proper treatment for various diseases and a precise medical diagnosis by analyzing a massive number of genes in various experimental conditions. The conventional data classification techniques suffer from overfitting and the high dimensionality of gene expression data. Therefore, the feature (gene) selection approach plays a vital role in handling a high dimensionality of data. Data science concepts can be widely employed in several data classification problems, and they identify different class labels. In this aspect, we developed a novel red fox optimizer with deep-learning-enabled microarray gene expression classification (RFODL-MGEC) model. The presented RFODL-MGEC model aims to improve classification performance by selecting appropriate features. The RFODL-MGEC model uses a novel red fox optimizer (RFO)-based feature selection approach for deriving an optimal subset of features. Moreover, the RFODL-MGEC model involves a bidirectional cascaded deep neural network (BCDNN) for data classification. The parameters involved in the BCDNN technique were tuned using the chaos game optimization (CGO) algorithm. Comprehensive experiments on benchmark datasets indicated that the RFODL-MGEC model accomplished superior results for subtype classifications. Therefore, the RFODL-MGEC model was found to be effective for the identification of various classes for high-dimensional and small-scale microarray data.
Thermal Power Industry Emissions and Their Contribution to Air Quality on the Fen-Wei Plain
Authors: Chen Lei , Wang Tong , Bo Xin , Zhuang Zhi , Qu Jiabao , Xue Xiaoda , Tian Jun , Huang Mantang , Wang Peng , Sang Minjie
Published: April 2022

China has imposed an ultra-low emissions (ULE) standards policy regarding the emission concentrations of the thermal power industry, and the region of the Fen-Wei Plain (China), which is an important area regarding blue-sky protection, is in urgent need of accelerating the transformation of its thermal power units to conform with China’s ULE standards. Based on China’s high-resolution thermal power industry emission inventory, this study used the Comprehensive Air Quality Model with extensions (CAMX) to examine emissions from the thermal power industry and the associated impacts on the atmospheric environment of the Fen-Wei Plain. (1) Spatially, the highest emissions and the greatest air quality contributions were concentrated in the Shanxi and Henan areas, which are regions that have considerable power generation capacity. (2) In terms of species, NOX represented the largest air quality contribution and registered the smallest reduction. (3) Temporally, emission sources presented the greatest contributions in summer. (4) In terms of policy evaluation, implementation of ULE standards resulted in the reduction of the contribution of thermal power industry emissions to air quality by 56.82%, 27.44%, and 44.55% for SO2, NOX, and PM2.5, respectively. The results reflect the current levels of pollution on the Fen-Wei Plain attributable to the thermal power industry and provide insight in relation to decision-making processes regarding regional air quality management.