bluuebunny/crossref_metadata_2025 huggingface dataset:
Water and Nitrogen Management at the Booting Stage Affects Yield, Grain Quality, Nutrient Uptake, and Use Efficiency of Fragrant Rice Under the Agro-Climatic Conditions of South China
Authors: Deng Siying , Ashraf Umair , Nawaz Mohsin , Abbas Ghulam , Tang Xiangru , Mo Zhaowen
Published: June 2022

The present study was conducted to assess the effects of water and nitrogen applications at the booting stage on yield, grain quality, and nutrient use efficiencies in fragrant rice in the early (March–July) and late (July–November) seasons of 2013. The experiment was comprised of two fragrant rice cultivars, i.e., Nongxiang 18 and Basmati; three nitrogen levels, i.e., 0 kg N ha−1 (N0), 30 kg N ha−1 (N1), and 60 kg N ha−1 (N2); and three water levels, i.e., 2–4 cm water layer well-watered (W0), water with a soil water potential of −15 ± 5 kPa (W1), and water with a soil water potential of −25 ± 5 kPa (W2), which were randomized in a split-split plot design. Results showed that Basmati produced a higher grain yield than Nongxiang 18 (16.20 and 9.61% in the early and late season, respectively), whereas the W1 exhibited the maximum grain yield and harvest index. The moderate application of nitrogen (N1) at the booting stage resulted in higher grain yield, nevertheless, cultivar, water, and nitrogen revealed different trends for some of the grain quality attributes, i.e., brown rice rate, milled rice rate, head milled rice rate, protein content, and amylose content as well as nutrient uptake and use efficiencies in the double rice production system. Basmati had a higher nitrogen harvest index (NHI; 18.28–20.23%) and P harvest index (PHI; 3.95–12.42%) but lower physiological P use efficiency for biomass (PPUEB; 7.66–23.66%) and physiological K use efficiency for biomass (PKUEB; 2.53–7.10%) than Nongxiang 18 in both seasons. Furthermore, the grain number per panicle, biomass yield, grain P uptake, and the whole plant P uptake were significantly related to the grain yield of fragrant rice. In both seasons, the interaction of water and nitrogen (W × N) had a significant effect on panicle number, grain quality attributes, and N, P uptake of straw, as well as the physiological N, P use efficiency for grain and the physiological N, K use efficiency for biomass. Overall, results suggest that moderate nitrogen and irrigation input at the booting stage could be feasible to improve the productivity and quality of the double rice production system with improved nutrient use efficiency under the agro-climatic conditions of South China.
Integrating Multiculturalism Into Artificial Intelligence-Assisted Programming Lessons: Examining Inter-Ethnicity Differences in Learning Expectancy, Motivation, and Effectiveness
Authors: Tsai Chia-Wei , Ma Yi-Wei , Chang Yao-Chung , Lai Ying-Hsun
Published: June 2022

Given the current popularization of computer programming and the trends of informatization and digitization, colleges have actively responded by making programming lessons compulsory for students of all disciplines. However, students from different ethnic groups often have different learning responses to such lessons due to their respective cultural backgrounds, the environment in which they grew up, and their consideration for future employment. In this study, an AI-assisted programming module was developed and used to compare the differences between multi-ethnic college students in terms of their theoretical and actual learning expectancy, motivation, and effectiveness. The module conducted analysis through the deep learning network and examined the relevant processes that the students underwent during programming lessons, as well as the types of errors they had committed. Their learning motivation for and actual learning performance in programming were then examined based on the cognitive learning theory. The results of the experiment, which involved 96 multi-ethnic college students, indicated that the two groups had dissimilar theoretical performance in terms of their expectancy and motivation for learning programming. The indigenous students’ main concern was whether programming would affect their families or tribes, and this concern affected and was reflected in their learning outcomes. In contrast, the learning motivation and goals of Han Chinese students were driven by the cognition of the value of programming to themselves. The research findings can contribute toward the cognition and understanding of multi-ethnic students when learning computer programming and development of the appropriate teaching methods, and serve as a reference for subsequent research on integrating multiculturalism into computer programming lessons.
Characteristics and Trends in Unethical Pro-organizational Behavior Research in Business and Management: A Bibliometric Analysis
Authors: Li Zhihong
Published: June 2022

Unethical pro-organizational behavior is one of the core factors that affect organizational development. Although enterprises and researchers have done a lot of work, a quantitative and systematic assessment of unethical pro-organizational behavior research is still lacking, this review conducts a bibliometric analysis to describe the characteristics and trends of unethical pro-organizational behavior research in business and management, such as publication trend analysis, co-citation analysis, keywords co-occurrence analysis, and citation burst analysis. The results show that 89 articles and 4,523 references from 49 journals contributed by 254 authors are identified. The number of publications has increased significantly since 2019. The China and United States are the most productive country. Umphress E and Yam C are the most influential authors. “Journal of Business Ethics and Frontiers in Psychology” are the most influential journal, 26 words in 516 keywords constitute the strongest set of terms available, Keyword co-occurrence analysis found ethical decision-making, the measurement, and impact of unethical pro-organizational behavior, the antecedents of ethical leadership are worthy and prospective potential trends. These findings provide a systematically, transparently, and visually reviewed the landscape and development process of unethical pro-organizational behavior research, which may help researchers and practitioners to understand unethical pro-organizational behavior in business management and provide a new perspective for future research.
Emotional Activity Is Negatively Associated With Cognitive Load in Multimedia Learning: A Case Study With EEG Signals
Authors: Guo Xiang , Zhu Tianshui , Wu Chennan , Bao Zongliang , Liu Yang
Published: June 2022

We aimed to investigate the relationship between emotional activity and cognitive load during multimedia learning from an emotion dynamics perspective using electroencephalography (EEG) signals. Using a between-subjects design, 42 university students were randomly assigned to two video lecture conditions (color-coded vs. grayscale). While the participants watched the assigned video, their EEG signals were recorded. After processing the EEG signals, we employed the correlation-based feature selector (CFS) method to identify emotion-related subject-independent features. We then put these features into the Isomap model to obtain a one-dimensional trajectory of emotional changes. Next, we used the zero-crossing rate (ZCR) as the quantitative characterization of emotional changes ZCREC. Meanwhile, we extracted cognitive load-related features to analyze the degree of cognitive load (CLI). We employed a linear regression fitting method to study the relationship between ZCREC and CLI. We conducted this study from two perspectives. One is the frequency domain method (wavelet feature), and the other is the non-linear dynamic method (entropy features). The results indicate that emotional activity is negatively associated with cognitive load. These findings have practical implications for designing video lectures for multimedia learning. Learning material should reduce learners’ cognitive load to keep their emotional experience at optimal levels to enhance learning.
Factors Affecting Human Visual Behavior and Preference for Sneakers: An Eye-Tracking Study
Authors: Chen Zihao , Song Wenfang
Published: June 2022

Human visual behavior on a product significantly affects their purchasing behavior during online shopping. In this study, two experimental studies were performed to investigate human visual behavior and preference for sneakers using an eye tracking technology. The first study discovered that shoelace and vamp areas of interests (AOIs) attracted more attention than the other AOIs. The second study explored the factors affecting human behavior on sneakers, which employed 30 students from different professional backgrounds (i.e., such as fashion and non-fashion disciplines), and examined 24 sneakers, i.e., combinations of four shoelace styles and six vamp materials. The results showed that both genders irrespective of their professional backgrounds were more concerned about the shoelaces than vamps. The shoelace AOI gained more attention of females than males, while the vamp AOI was more concerned by males than females. The vamp AOI was more concerned by non-professionals than professionals, while the shoelace AOI was paid more attention by professionals than non-professionals. Besides, flat or round shoelaces, canvas, and cow leather or cotton flannel vamp materials were more preferred by the participants than the other types. The findings are of great help for the fashion product designers, the manufacturers, and the sellers to provide the product required by the customers.
Neurobiological Alterations in Females With PTSD: A Systematic Review
Authors: Eder-Moreau Elizabeth , Zhu Xi , Fisch Chana T. , Bergman Maja , Neria Yuval , Helpman Liat
Published: June 2022

Most females experience at least one traumatic event in their lives, but not all develop PTSD. Despite considerable research, our understanding of the key factors that constitute risk for PTSD among females is limited. Previous research has largely focused on sex differences, neglecting within group comparisons, thereby obviating differences between females who do and do not develop PTSD following exposure to trauma. In this systematic review, we conducted a search for the extent of existing research utilizing magnetic resonance imaging (MRI) to examine neurobiological differences among females of all ages, with and without PTSD. Only studies of females who met full diagnostic criteria for PTSD were included. Fifty-six studies were selected and reviewed. We synthesized here findings from structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), and resting state functional connectivity (rs-FC MRI) studies, comparing females with and without PTSD. A range of biopsychosocial constructs that may leave females vulnerable to PTSD were discussed. First, the ways timing and type of exposure to trauma may impact PTSD risk were discussed. Second, the key role that cognitive and behavioral mechanisms may play in PTSD was described, including rumination, and deficient fear extinction. Third, the role of specific symptom patterns and common comorbidities in female-specific PTSD was described, as well as sex-specific implications on treatment and parenting outcomes. We concluded by identifying areas for future research, to address the need to better understand developmental aspects of brain alterations, the differential impact of trauma types and timing, the putative role of neuroendocrine system in neurobiology of PTSD among females, and the impact of social and cultural factors on neurobiology in females with PTSD.
“I Want to Be Stepping in More” - Professional Online Forum Moderators' Experiences of Supporting Individuals in a Suicide Crisis
Authors: Perry Amanda , Lamont-Mills Andrea , Preez Jan du , Plessis Carol du
Published: June 2022

Introduction

Individuals experiencing suicidal crises increasingly turn to online mental health forums for support. Support can come from peers but also from online moderators, many of whom are trained health professionals. Much is known about users' forum experiences; however, the experiences of professional moderators who work to keep users safe has been overlooked. The beneficial nature of online forums cannot be fully realized until there is a clearer understanding of both parties' participation. This study explored the experiences of professional online forum moderators engaged in suicide prevention.

Materials and Methods

A purposive sample of professionally qualified moderators was recruited from three online mental health organizations. In-depth semi-structured, video-recorded interviews were conducted with 15 moderators (3 male, 12 female), to explore their experiences and perceptions of working in online suicide prevention spaces. Data was analyzed using inductive thematic analysis.

Results

Five themes were identified related to the experiences and challenges for moderators. These were the sense of the unknown, the scope of the role, limitations of the written word, volume of tasks, and balancing individual vs. community needs.

Discussion

Findings indicate that the professionally qualified moderator role is complex and multifaceted, with organizations failing to recognize these aspects. Organizations restrict moderators from using their full therapeutic skill set, limiting them to only identifying and re-directing at-risk users to crisis services. The benefits of moderated online forums could be enhanced by allowing moderators to use more of their skills. To facilitate this, in-situ research is needed that examines how moderators use their skills to identify at-risk users.
BUB1 Is Identified as a Potential Therapeutic Target for Pancreatic Cancer Treatment
Authors: Li Ming , Duan Xiaoyang , Xiao Yajie , Yuan Meng , Zhao Zhikun , Cui Xiaoli , Wu Dongfang , Shi Jian
Published: June 2022

Pancreatic cancer is one of the most challenging cancer types in clinical treatment worldwide. This study aimed to understand the tumorigenesis mechanism and explore potential therapeutic targets for patients with pancreatic cancer. Single-cell data and expression profiles of pancreatic cancer samples and normal tissues from multiple databases were included. Comprehensive bioinformatics analyses were applied to clarify tumor microenvironment and identify key genes involved in cancer development. Immense difference of cell types was shown between tumor and normal samples. Four cell types (B cell_1, B cell_2, cancer cell_3, and CD1C+_B dendritic cell_3) were screened to be significantly associated with prognosis. Three ligand–receptor pairs, including CD74-MIF, CD74-COPA, and CD74-APP, greatly contributed to tumorigenesis. High expression of BUB1 (BUB1 Mitotic Checkpoint Serine/Threonine Kinase) was closely correlated with worse prognosis. CD1C+_B dendritic cell_3 played a key role in tumorigenesis and cancer progression possibly through CD74-MIF. BUB1 can serve as a prognostic biomarker and a therapeutic target for patients with pancreatic cancer. The study provided a novel insight into studying the molecular mechanism of pancreatic cancer development and proposed a potential strategy for exploiting new drugs.
Short-Term Nationwide Airport Throughput Prediction With Graph Attention Recurrent Neural Network
Authors: Zhu Xinting , Lin Yu , He Yuxin , Tsui Kwok-Leung , Chan Pak Wai , Li Lishuai
Published: June 2022

With the dynamic air traffic demand and the constrained capacity resources, accurately predicting airport throughput is essential to ensure the efficiency and resilience of air traffic operations. Many research efforts have been made to predict traffic throughputs or flight delays at an airport or over a network. However, it is still a challenging problem due to the complex spatiotemporal dynamics of the highly interacted air transportation systems. To address this challenge, we propose a novel deep learning model, graph attention neural network stacking with a Long short-term memory unit (GAT-LSTM), to predict the short-term airport throughput over a national air traffic network. LSTM layers are included to extract the temporal correlations in the data, while the graph attention mechanism is used to capture the spatial dependencies. For the graph attention mechanism, two graph modeling methods, airport-based graph and OD-pair graph are explored in this study. We tested the proposed model using real-world air traffic data involving 65 major airports in China over 3 months in 2017 and compared its performance with other state-of-the-art models. Results showed that the temporal pattern was the dominate factor, compared to the spatial pattern, in predicting airport throughputs over an air traffic network. Among the prediction models that we compared, both the proposed model and LSTM performed well on prediction accuracy over the entire network. Better performance of the proposed model was observed when focusing on airports with larger throughputs. We also conducted an analysis on model interpretability. We found that spatiotemporal correlations in the data were learned and shown via the model parameters, which helped us to gain insights into the topology and the dynamics of the air traffic network.
Case Report: Technetium-99m Pertechnetate Scintigraphy Findings in a Dog With Iodine Deficiency-Induced Goitrous Hypothyroidism
Authors: Yun Taesik , Na Yejin , Lee Dohee , Koo Yoonhoi , Chae Yeon , Nam Hyeyeon , Kang Byeong-Teck , Yang Mhan-Pyo , Kim Hakhyun
Published: June 2022

There is only one previous report of canine goitrous hypothyroidism caused by iodine deficiency from 1986. The present case report describes the novel diagnostic methods and long-term outcomes of a dog diagnosed with goitrous hypothyroidism caused by iodine deficiency. A 4-year-old neutered, female Pomeranian dog presented with a cervical mass, lethargy, and inactivity. The dog had a history of eating home-cooked diets sold by a private seller for 1 year. The physical examination and ultrasonography showed two bilaterally symmetric masses in the mid-cervical area (left, 1.8 × 1.4 cm; right, 2.3 × 1.8 cm), and they were suspected to be the thyroid glands. To identify the function of the thyroid gland, the basal concentrations of thyroid hormones [total T4 (tT4) and thyroid-stimulating hormone (TSH)] were measured and a TSH stimulation test was performed: baseline tT4, 0.5 μg/dL (reference interval, 1–4 μg/dL), baseline TSH, 0.81 μg/dL (reference interval, 0.05–0.42 μg/dL), and post-tT4, 1 μg/dL (6 h after the injection of TSH). The values indicated primary hypothyroidism. The urinary iodine concentration was 302 μg/L, which was markedly lower than that of normal dogs (1,289 μg/L). Thyroid scintigraphy with technetium-99m pertechnetate was also performed to quantify the activity of the thyroid gland, and the thyroid-to-salivary ratio was 3.35. Based on the results of these examinations and patient history, the dog was diagnosed with diet-induced (iodine deficiency) goitrous hypothyroidism. The dog was treated with iodine (62.5 μg/day). At 31 days after treatment, clinical signs and thyroid hormones were normalized (tT4, 1.3 μg/dL; TSH, 0.24 μg/dL). One year after treatment, the dog was well with normal concentrations of thyroid hormones (tT4, 1.8 μg/dL; TSH, 0.27 μg/dL) and a partially reduced goiter (left, 1.6 × 1.1 cm; right, 1.2 × 0.9 cm). This is the first case to describe novel diagnostic methods and long-term outcomes of a dog diagnosed with goitrous hypothyroidism caused by iodine deficiency.
Europe’s Large-Scale Land Acquisitions and Bibliometric Analysis
Authors: Rasva Marii , Jürgenson Evelin
Published: June 2022

The agricultural sector in the European Union is largely characterized by a declining number of farms and an increasing size of surviving farms. The land is concentrating under the usage of fewer large agricultural producers. Meanwhile, a broad distribution of land ownership is the basis for the welfare of local economies and rural communities. Land distribution is one important component that guarantees our right to food, human rights, and sustainability in agriculture. The aim of this paper was to compile a systematic review of the existing literature on large-scale land acquisitions in Europe. The results are based on two different search methods. Firstly, documents and articles on large-scale land acquisitions were studied and, secondly, keyword research from the SCOPUS database and analysis using VOSviewer where performed. This study shows that large-scale land acquisitions are closely related to food security, human rights, global governance and international law, land tenure, biofuel production, and financialization through European Union common agricultural policy subsidies and foreign direct investments.
Grape Quality Zoning and Selective Harvesting in Small Vineyards—To Adopt or Not to Adopt
Authors: Rendulić Jelušić Ivana , Šakić Bobić Branka , Grgić Zoran , Žiković Saša , Osrečak Mirela , Puhelek Ivana , Anić Marina , Karoglan Marko
Published: June 2022

The practical application of grape quality zoning and selective harvesting in small vineyards (<1 ha) has not yet gained much importance worldwide. However, winegrowers with small vineyards are looking for ways to improve wine quality and maximise profit. Therefore, the aim of this study was to identify the most predictive vegetation index for grape quality zoning among three vegetation indices—NDVI, NDRE, and OSAVI—at three grapevine growth stages for the efficient use in small vineyards for the selective harvesting and production of different wine types from the same vineyard. Multispectral images were used to delineate two vigour zones at three different growth stages. The target vines were sampled, and the most predictive vegetation index was determined by overlapping the quality and vigour structures for each site and year. A differential economic analysis was performed, considering only the costs and revenues associated with grape quality zoning. The results show that OSAVI is the least predictive, while NDVI and NDRE are useful for grape quality zoning and selective harvesting. Multi-year monitoring is required to determine the ideal growth stage for image acquisition. The use of grape quality zoning and selective harvesting can be economically efficient for small wineries producing two different “super-premium” wines from the same vineyard.
Calcined Oyster Shell-Humic Complex as Soil Amendment to Remediate Cd- and As-Contaminated Soil
Authors: Yuan Guodong , Bi Dongxue , Wei Jing , Xiao Liang
Published: June 2022

Soil acidification in the subtropical region reduces soil productivity and increases the bioavailability of heavy metal(loid)s in soil. Here 800 °C-calcined oyster shell and leonardite-derived humic substance were combined to form a Ca-humic complex to remediate an acidic soil contaminated by cadmium (Cd) and arsenic (As) for safe vegetable production. In the pot experiment, the complex was added to soil as a soil amendment at 0%, 0.5%, 1.0%, 2.0%, and 5.0%. A 2.0% dose reduced Cd and As contents of the vegetable bok choy by 98% and 71%, respectively, alleviating the human health risk of Cd and As from the food chain. The unified bio-accessibility method (UBM) was followed to estimate the bio-accessibility of Cd and As. The complex at a 2.0% dose lowered soil Cd and As bio-accessibility in simulated gastric (BioG) and intestine (BioGI) compartments by 15.5% for BioG-Cd, 39.2% for BioGI-Cd, 28.8% for BioG-As, and 45.0% for BioGI-As, thus reducing the human health risk of Cd and As from soil ingestion. The use of oyster shell waste to produce Ca-humic complex as a soil amendment is a practical means of achieving dual agronomic and environmental benefits, from the remediation of soil contamination to the safe disposal of shell waste.
Agrivoltaic Systems Enhance Farmers’ Profits through Broccoli Visual Quality and Electricity Production without Dramatic Changes in Yield, Antioxidant Capacity, and Glucosinolates
Authors: Chae Seung-Hun , Kim Hye Joung , Moon Hyeon-Woo , Kim Yoon Hyung , Ku Kang-Mo
Published: June 2022

The increase in world population by an average rate of 2% per year causes critical issues on energy and foods. By 2050, food demand will increase to 35~56% more than in 2010 due to the growing population. Agrivoltaic systems allow us to reach sustainable food and electricity-production goals with high land-use efficiency. In this study, the yield, antioxidant capacity, and secondary metabolite of broccoli and electricity production were analyzed under an agrivoltaic system over 3 cultivation periods. Based on energy production, an economic analysis of agrivoltaic was carried out. In addition, our study also reported that agrivoltaic with additional shading treatment produced greener broccoli with a higher level of consumer preference than open-field grown ones. The yield, antioxidant capacity, some glucosinolates and hydrolysis products of broccoli grown under an agrivoltaic system were not significantly different from those of broccoli grown in the open-field.
Modelling the Impact of Water Stress during Post-Veraison on Berry Quality of Table Grapes
Authors: Temnani Abdelmalek , Berríos Pablo , Conesa María R. , Pérez-Pastor Alejandro
Published: June 2022

The aims of this work were modelling the effect of water stress intensity during post-veraison on table grape quality and yield, as well as predicting berry quality at harvest using a machine learning algorithm. The dataset was obtained by applying different irrigation regimes in two commercial table grape vineyards during seven growing seasons. From these data, it was possible to train and validate the predictive models over a wide range of values for the independent (water stress intensity and fruit load) and dependent (firmness and berry color) variables. The supervised learning algorithm Gaussian Process Regression allowed us to predict the variables with high accuracy. It was also determined that a reduction in irrigation of up to 40% during post-veraison, compared to vines without water limitations, and the accumulation of the water stress integral of up to 30 MPa per day, linearly increase the irrigation water use efficiency (IWUE) and promote higher berry color and firmness. The severe water scarcity and the increasing uncertainty about the irrigation water availability for the season that farmers are facing highlight the advantage of incorporating these validated techniques into agricultural decision making, as they allow for the planning of cultural practices and criteria to increase the IWUE and crop sustainability.
Utilization of Thermophilic Aerobic Oxidation and Electrocoagulation to Improve Fertilizer Quality from Mixed Manure Influent
Authors: Halder Joshua Nizel , Lee Myung-Gyu , Kim Soo-Ryang , Hwang Okhwa
Published: June 2022

Thermophilic aeration and electrochemical reactions are well-established methods for wastewater treatment to reduce metallic content, organic and inorganic matter, turbidity, coloration, and nutrient levels. In this study, thermophilic aerobic oxidation (TAO) and electrocoagulation (EC) were implemented together to improve the quality of liquid fertilizer by reducing the nutrient load and toxicity of swine manure. The influent in this study was prepared by mixing anaerobic digestate and liquid swine manure at a 1:9 ratio and treating it for 3 days at 50–60 °C in a field-scale TAO system. The TAO effluent was then processed in an EC reactor for 180 min with a 30 V electric supply through two sets of iron and aluminum hybrid electrodes. The combined TAO and EC processes led to a germination index of 133% using the final efflux. The high retention of important nutrients such as total nitrogen and potassium, combined with the 100% reduction in heavy metals, over 60% reduction in trace minerals, and 89% reduction in pollutants in the final product, helped to achieve a higher germination index. Overall, the combination of TAO and EC was demonstrated to be an effective technique for enhancing the quality of liquid fertilizer derived from swine manure.
Functional Identification of Porcine DLK1 during Muscle Development
Authors: Fu Yu , Hao Xin , Shang Peng , Chamba Yangzom , Zhang Bo , Zhang Hao
Published: June 2022

DLK1 is paternally expressed and is involved in metabolism switching, stem cell maintenance, cell proliferation, and differentiation. Porcine DLK1 was identified in our previous study as a candidate gene that regulates muscle development. In the present study, we characterized DLK1 expression in pigs, and the results showed that DLK1 was highly expressed in the muscles of pigs. In-vitro cellular tests showed that DLK1 promoted myoblast proliferation, migration, and muscular hypertrophy, and at the same time inhibited muscle degradation. The expression of myogenic and fusion markers and the formation of multinucleated myotubes were both upregulated in myoblasts with DLK1 overexpression. DLK1 levels in cultured myocytes were negatively correlated with the expression of key factors in the Notch pathway, suggesting that the suppression of Notch signaling pathways may mediate these processes. Collectively, our results suggest a biological function of DLK1 as an enhancer of muscle development by the inhibition of Notch pathways.
Niacin Status Indicators and Their Relationship with Metabolic Parameters in Dairy Cows during Early Lactation
Authors: Petrović Kosta , Djoković Radojica , Cincović Marko , Hristovska Talija , Lalović Miroslav , Petrović Miloš , Majkić Mira , Došenović Marinković Maja , Anđušić Ljiljana , Devečerski Gordana , Stojanović Dragica , Štrbac Filip
Published: June 2022

Previous experimental models on cows have examined the difference in the metabolic adaptation in cows after niacin administration, without identifying the most important mediators between niacin administration and its biological effects, namely active forms of niacin. All tissues in the body convert absorbed niacin into its main metabolically active form, the coenzyme nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP). The aim of this study was to determine the influence of niacin administration in periparturient period on NAD, NADP and the NAD:NADP ratio and to determine relationship between these indicators of an active form of niacin with metabolic parameters in cow blood. The study included 90 healthy cows: 45 cows receiving niacin and 45 cows were negative control. The niacin group was treated with nicotinic acid for two weeks before, as well as two weeks after parturition. Nicotinic acid was applied per os with feed. In cows receiving niacin, there was a significantly higher concentration of NAD and NADP, but the NAD:NADP ratio did not differ compared with control. All three indicators were able to separate cows who received and who did not receive additional niacin. NAD and NADP are good indicators of the availability of niacin from additional sources. The NAD:NADP ratio is a good indicator of the biological effect of applied niacin on metabolites in cows due to its correlation with a number of metabolites: positive correlation with glucose, insulin, glucose to insulin ratio and the revised quantitative insulin sensitivity check index (RQUICKIBHB) of insulin resistance, triglycerides and cholesterol, and a negative correlation with nonesterified fatty acid (NEFA), beta hydroxybutyrate (BHB), gamma-glutamyltranspherase (GGT) and urea in cows receiving niacin. The same amount of added niacin in feed can produce different concentrations of NAD, NADP and NAD:NADP in the blood, and this was not related to their concentration before the addition of niacin. The change in the concentration of the active form of niacin (NAD, NADP and NAD:NADP) further correlates with the concentration of metabolic parameters, which indicates that the intensity of the biological effect of additional niacin can be accurately determined only if we know the concentrations of its active forms in blood. Under basal conditions (without additional niacin), active forms of niacin that already exist in the blood do not show significant correlations with metabolic parameters.
Effect of Milk Thistle (Silybum marianum) Supplementation on Pork Offal Quality
Authors: Kropiwiec-Domańska Kinga , Babicz Marek , Kędzierska-Matysek Monika , Szyndler-Nędza Magdalena , Skrzypczak Ewa , Woliński Bartłomiej
Published: June 2022

The aim of the study was to determine the effect of milk thistle supplementation of fattener pig feeds on physical and chemical properties of pork offal. The experiments were conducted on 60 fatteners (group C—control (30 pigs) and group E—experimental (30 pigs)). The experimental group was supplemented with ground milk thistle (Silybum marianum) at 7 g/kg feed. The offal (tongues, kidneys, hearts, lungs and livers) was analyzed for weight, pH, WHC, water, protein, fat, energy value, fatty acid profile and content of major and trace elements. The present study shows that milk thistle added to fattener pig diets increased pH45 and pH24 values in most of the analyzed offal and significantly (p ≤ 0.01) decreased the weight of heart and lungs and increased the weight of liver and kidneys. Hearts, lungs and kidneys of the experimental group contained more fat and the liver less, than the same offal of the control group. As regards the content of elements, the dietary supplement most often had an effect on the heart and lungs. In general, milk thistle supplemented in fattener diets had modified the physical parameters and chemical composition of the analyzed products.
Levofloxacin Cocrystal/Salt with Phthalimide and Caffeic Acid as Promising Solid-State Approach to Improve Antimicrobial Efficiency
Authors: Islam Noor Ul , Umar Muhammad Naveed , Khan Ezzat , Al-Joufi Fakhria A. , Abed Shaymaa Najm , Said Muhammad , Ullah Habib , Iftikhar Muhammad , Zahoor Muhammad , Khan Farhat Ali
Published: June 2022

To overcome the issue of multidrug resistant (MDR) microbes, the exploration of ways to improve the antimicrobial efficiency of existing antibiotics is one of the promising approaches. In search of synthons with higher efficiency, in current investigations, cocrystal and amorphous salt of levofloxacin hemihydrate (LEV) were developed with phthalimide (PTH) and caffeic acid (CFA). New materials were characterized with the help of FT-IR, Raman spectroscopy, powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Shifting, attenuation, appearance/disappearance and broadening of bands were observed in the FT-IR and Raman spectra of the materials as evidence of the required product. The PXRD diffraction pattern observed for LEV-PTH indicated cocrystal while halo diffractogram of LEV-CFA revealed amorphous nature. DSC/TG analysis confirmed the hydrated nature of the cocrystal/salt. The dissolution rate and antimicrobial activity against selected strains, K.pneumonia, E. coli and S. typhi of parent drug and the new material were compared. The zone of inhibition (ZI) observed for 5 µg LEV-PTH was 30.4 + 0.36 (K. pneumonia), 26.33 + 0.35 (E. coli) and 30.03 + 0.25 mm (S. typhi) while LEV-CFA salt (5 µg) against the same strains inhibited 33.96 ± 0.25, 31.66 ± 0.35 and 27.93 ± 0.40 mm, respectively. These novel formulations enhance the dissolution rate as well as antibacterial efficiency and are expected to be potent against MDR bacterial strains.
AspectNet: Aspect-Aware Anchor-Free Detector for Autonomous Driving
Authors: Liang Tianjiao , Bao Hong , Pan Weiguo , Fan Xinyue , Li Han
Published: June 2022

The anchor-free-based object detection method is a crucial part in an autonomous driving system because of its low computing cost. However, the under-fitting of positive samples and over-fitting of negative samples affect the detection performance. An aspect-aware anchor-free detector is proposed in this paper to address this problem. Specifically, it adds an aspect prediction head at the end of the detector, which can learn different distributions of aspect ratios between other objects. The sample definition method is improved to alleviate the problem of positive and negative sample imbalance. A loss function is designed to strengthen the learning weight of the center point of the network. The validation results show that the AP50 and AP75 of the proposed method are 97.3% and 93.4% on BCTSDB, and the average accuracies of the car, pedestrian, and cyclist are 92.7%, 77.4%, and 78.2% on KITTI, respectively. The comparison results demonstrate that the proposed algorithm is better than existing anchor-free methods.
Study on Representative Parameters of Reverse Engineering for Maintenance of Ballasted Tracks
Authors: Park Suyeul , Kim Seok , Seo Heechang
Published: June 2022

Reverse engineering (RE) is a technology used to create three-dimensional (3D) models by scanning structures and can be used to examine the current condition of structures. Applying RE to the maintenance of railroad facilities with a high proportion of safety accidents can be an alternative to increase the efficiency of railroad facilities. However, most tasks while constructing Building Information Modeling (BIM) after 3D scanning and extracting two-dimensional (2D) drawings are still performed manually. In particular, denoising, registration, and 3D modeling based on point clouds are labor-intensive and time-consuming tasks, and their efficiency needs to be enhanced by introducing automation technology. In this study, we selected point clouds-based representative parameters for ballasted tracks of a straight single-line section for automating railroad maintenance. Scan data and a BIM of a ballasted track were compared using the selected representative parameters. In addition, the types of damage to ballasted track requiring maintenance were examined. And a testbed was consisted of ballasted a track was selected, and 3D scanning was performed to obtain point cloud data of a testbed. Then, a BIM model was created by measuring the numerical values corresponding to the representative parameters on the scan data. The feasibility of constructing a railroad maintenance BIM based on representative 3D object detection parameters during RE work on the ballasted track was evaluated.
Study on Pore Structure and Mechanical Property of Expansive Soil under Different Dehydration Conditions
Authors: Wang Fenghua , Kong Lingwei , Zhou Zhenhua
Published: June 2022

To study the influence of dehydration conditions on the pore structure and the mechanical property of expansive soil, two experimental conditions with high-temperature drying (temperature 50 °C-humidity 10%) and high-temperature humid (temperature 50 °C-humidity 70%) were carried out. Taking the remolded expansive soil in the province of Anhui in China as the research object, this paper used mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) to analyze the pore size distribution and pore structure of remolded expansive soil samples under different dehydration conditions and duration. After these tests, their mechanical properties were further obtained by uniaxial compression tests. The results showed that the distribution of pore structure of expansive soil was various under different dehydration conditions. Under high temperature and dry environment, the volume of large pores decreased first and then increased with the time of dehydration, while the medium pore volume decreased until the dehydration was stable. Under high temperature and humid environment, the volume of large pore and medium pore both showed a trend of decrease until the dehydration kept stable. The pore volume of expansive soil did not change significantly under the two dehydration conditions. The uniaxial compressive strength (UCS) of remolded expansive soil samples in high temperature and dry environment reached the highest on the 5th day of dehydration, and then the soil strength decreased slightly until it stabilized. The UCS of remolded expansive soil reached the highest on the 15th day of dehydration under high temperature and humidity environment, and the soil strength changed little after continual dehydration. These tests showed that the UCS of dehydrated expansive soil samples under the condition of high temperature and humidity is higher than that of dehydrated expansive soil samples under the condition of high temperature and dry environment.
Extrinsic Behavior Prediction of Pedestrians via Maximum Entropy Markov Model and Graph-Based Features Mining
Authors: Ghadi Yazeed Yasin , Akhter Israr , Aljuaid Hanan , Gochoo Munkhjargal , Alsuhibany Suliman A. , Jalal Ahmad , Park Jeongmin
Published: June 2022

With the change of technology and innovation of the current era, retrieving data and data processing becomes a more challenging task for researchers. In particular, several types of sensors and cameras are used to collect multimedia data from various resources and domains, which have been used in different domains and platforms to analyze things such as educational and communicational setups, emergency services, and surveillance systems. In this paper, we propose a robust method to predict human behavior from indoor and outdoor crowd environments. While taking the crowd-based data as input, some preprocessing steps for noise reduction are performed. Then, human silhouettes are extracted that eventually help in the identification of human beings. After that, crowd analysis and crowd clustering are applied for more accurate and clear predictions. This step is followed by features extraction in which the deep flow, force interaction matrix and force flow features are extracted. Moreover, we applied the graph mining technique for data optimization, while the maximum entropy Markov model is applied for classification and predictions. The evaluation of the proposed system showed 87% of mean accuracy and 13% of error rate for the avenue dataset, while 89.50% of mean accuracy rate and 10.50% of error rate for the University of Minnesota (UMN) dataset. In addition, it showed a 90.50 mean accuracy rate and 9.50% of error rate for the A Day on Campus (ADOC) dataset. Therefore, these results showed a better accuracy rate and low error rate compared to state-of-the-art methods.
Niger Seed Oil-Based Biodiesel Production Using Transesterification Process: Experimental Investigation and Optimization for Higher Biodiesel Yield Using Box–Behnken Design and Artificial Intelligence Tools
Authors: Venkataramana Srikanth Holalu , Shivalingaiah Kanchiraya , Davanageri Mahesh Basetteppa , Selvan Chithirai Pon , Lakshmikanthan Avinash , Chandrashekarappa Manjunath Patel Gowdru , Razak Abdul , Anand Praveena Bindiganavile , Linul Emanoil
Published: June 2022

The present work aims at cost-effective approaches for biodiesel conversion from niger seed (NS) oil by employing the transesterification process, Box–Behnken design (BBD), and artificial intelligence (AI) tools. The performances of biodiesel yield are reliant on transesterification variables (methanol-to-oil molar ratio M:O, reaction time Rt, catalyst concentration CC, and reaction temperature RT). BBD matrices representing the transesterification parameters were utilized for experiment reductions, analyzing factor (individual and interaction) effects, deriving empirical equations, and evaluating prediction accuracy. M:O showed a dominant effect, followed by CC, Rt, and RT, respectively. All two-factor interaction effects are significant, excluding the two interactions (Rt with RT and M:O with RT). The model showed a good correlation or regression coefficient with a value equal to 0.9869. Furthermore, the model produced the best fit, corresponding to the experimental and predicted yield of biodiesel. Three AI algorithms were applied (the big-bang big-crunch algorithm (BB-BC), firefly algorithm (FA), and grey wolf optimization (GWO)) to search for the best transesterification conditions that could maximize biodiesel yield. GWO and FA produced better fitness (biodiesel yield) values compared to BB-BC. GWO and FA experimental conditions resulted in a maximum biodiesel yield equal to 95.3 ± 0.5%. The computation time incurred in optimizing the biodiesel yield was found to be equal to 0.8 s for BB-BC, 1.66 s for GWO, and 15.06 s for FA. GWO determined that the optimized condition is recommended for better solution accuracy with a slight compromise in computation time. The physicochemical properties of the biodiesel yield were tested according to ASTM D6751-15C; the results are in good agreement and the biodiesel yield would be appropriate to use in diesel engines.
Skin Lesion Segmentation Based on Vision Transformers and Convolutional Neural Networks—A Comparative Study
Authors: Gulzar Yonis , Khan Sumeer Ahmad
Published: June 2022

Melanoma skin cancer is considered as one of the most common diseases in the world. Detecting such diseases at early stage is important to saving lives. During medical examinations, it is not an easy task to visually inspect such lesions, as there are similarities between lesions. Technological advances in the form of deep learning methods have been used for diagnosing skin lesions. Over the last decade, deep learning, especially CNN (convolutional neural networks), has been found one of the promising methods to achieve state-of-art results in a variety of medical imaging applications. However, ConvNets’ capabilities are considered limited due to the lack of understanding of long-range spatial relations in images. The recently proposed Vision Transformer (ViT) for image classification employs a purely self-attention-based model that learns long-range spatial relations to focus on the image’s relevant parts. To achieve better performance, existing transformer-based network architectures require large-scale datasets. However, because medical imaging datasets are small, applying pure transformers to medical image analysis is difficult. ViT emphasizes the low-resolution features, claiming that the successive downsampling results in a lack of detailed localization information, rendering it unsuitable for skin lesion image classification. To improve the recovery of detailed localization information, several ViT-based image segmentation methods have recently been combined with ConvNets in the natural image domain. This study provides a comprehensive comparative study of U-Net and attention-based methods for skin lesion image segmentation, which will assist in the diagnosis of skin lesions. The results show that the hybrid TransUNet, with an accuracy of 92.11% and dice coefficient of 89.84%, outperforms other benchmarking methods.
Landslide Susceptibility Assessment by Using Convolutional Neural Network
Authors: Nikoobakht Shahrzad , Azarafza Mohammad , Akgün Haluk , Derakhshani Reza
Published: June 2022

This study performs a GIS-based landslide susceptibility assessment using a convolutional neural network, CNN, in a study area of the Gorzineh-khil region, northeastern Iran. For this assessment, a 15-layered CNN was programmed in the Python high-level language for susceptibility mapping. In this regard, as far as the landside triggering factors are concerned, it was concluded that the geomorphologic/topographic parameters (i.e., slope curvature, topographical elevation, slope aspect, and weathering) and water condition parameters (hydrological gradient, drainage pattern, and flow gradient) are the main triggering factors. These factors provided the landside dataset, which was input to the CNN. We used 80% of the dataset for training and the remaining 20% for testing to prepare the landslide susceptibility map of the study area. In order to cross-validate the resulting map, a loss function, and common classifiers were considered: support vector machines, SVM, k-nearest neighbor, k-NN, and decision tree, DT. An evaluation of the results of the susceptibility assessment revealed that the CNN led the other classes in terms of 79.0% accuracy, 73.0% precision, 75.0% recall, and 77.0% f1-score, and, hence, provided better accuracy and the least computational error when compared to the other models.