bluuebunny/crossref_metadata_2025_split huggingface dataset:
Supply Chain Fraud Prediction with Machine Learning and Artificial intelligence
Authors: Lokanan Mark , Maddhesia Vikas 
Published: September 2022

Abstract

The increasing complexity of supply chains is putting pressure on businesses to find new ways to optimize efficiency and cut costs. One area that has seen a lot of recent development is machine learning (ML) and artificial intelligence (AI) to help manage supply chains. This paper employs machine learning (ML) and artificial intelligence (AI) algorithms to predict fraud in the supply chain. Supply chain data for this project was retrieved from real-world business transactions. The findings show that ML and AI classifiers did an excellent job predicting supply chain fraud. In particular, the AI model was the highest predictor across all performance measures. These results suggest that computational intelligence can be a powerful tool for detecting and preventing supply chain fraud. ML and AI classifiers can analyze vast amounts of data and identify patterns that may evade manual detection. The findings presented in this paper can be used to optimize supply chain management (SCM) and make predictions of fraudulent transactions before they occur. While ML and AI classifiers are still in the early stages of development, they have the potential to revolutionize SCM. Future research should explore how these techniques can be refined and applied to other domains.
A Comprehensive Molecular Survey of Viral Pathogens Associated with Canine Gastroenteritis
Authors: Dema Anusha , Tallapally Mounika Reddy , Ganji Vishweshwar Kumar , Buddala Bhagyalakshmi , Kodi Haritha , Ramidi Ashwini , Yella Narasimha Reddy , Putty Kalyani 
Published: September 2022

Abstract
Viral pathogens account for the major aetiology of canine gastroenteritis. However, structured comprehensive studies on viral aetiology of canine gastroenteritis are sparse. To this end, 475 rectal swabs collected over a period of three years (2018–2021) from clinical canine gastroenteritis cases were screened for the presence of six majorly known enteric viruses (CPV-2, CDV, CAdV-2, CCoV, CaAstV, CRV), by real-time PCR. The overall incidence rate for each virus was found highest at 64.8% for CPV-2/2a/2b/2c (2a: 21.1%, 2b: 77.4%, 2c: 1.5%), followed by 8% for CDV, 7.2% for CaAstV, 5.9% for CCoV and 4.6% for CAdV-2 with 16.8% incidence for coinfections ranging from two to four viruses in different combinations; no incidence of CRV was reported. The whole-genome sequences of CDV, CCoV and CaAstV Indian isolates were reported for the first time and phylogenetic analysis was performed. This study highlights the need for relevant and routine vaccine prophylactic measures. It is alarming to note that 70.3% of animals vaccinated with DHPPIL were found positive for at least one virus. Hence, regular molecular analysis of the prevalent viruses is crucial to address vaccination failures.
Quantification of microfibre release from textiles during domestic laundering
Authors: Hazlehurst Alice , Tiffin Lucy , Sumner Mark , Taylor Mark 
Published: September 2022

Abstract
This study explores three major factors that influence the quantification of microfibres released from domestic laundering of textiles; test methodologies, laundering variables, and fabric variables. A review of different test methods is presented, highlighting the variation in quantification created by using different methodologies. A reliable and reproducible method for quantifying microfibre release from domestic laundering is used to explore the impact of laundering and fabric variables experimentally. Our results show that the increasing wash liquor ratio and wash agitation results in a greater mass of microfibres released, but we found that fabric variables can have a greater influence on microfibre release than the laundering variables tested in this study. However, no single fabric variable appeared to have a dominant influence. Using the data obtained and assumptions for washing load size and frequency, an estimate of the annual microfibre release from untreated domestic laundering in the UK is presented. Depending on different laundering and fabric variables, estimates range from 6,490 tonnes to 87,165 tonnes of microfibre discharged in the UK each year.
Dynamic changes in cytokine profiles and their impact on tumour recurrence following thermal ablation in hepatocellular carcinoma
Authors: Guo Dandan , Qin Ling , Sun Jianping , Li Kang , Zang Chaoran , Wang Qi , Qiao Wenying , Liu Biyu , Zhao Yan , Zhang Yonghong 
Published: September 2022

Abstract
Background
Thermal ablation is widely accepted as a radical HCC therapy. However, the 5-year recurrence rate is high, and whether this local treatment induces a systemic immune response remains unclear. Herein, we investigated the effects of thermal ablation on HCC patients’ immune cytokine profiles and explored predictive biomarkers of tumour recurrence.
Methods
Twenty-two HCC patients were enrolled. We collected peripheral blood before ablation (baseline) and 5–7 days (week 1) and 28–30 days (week 4) after ablation and measured 27 cytokine/chemokine levels at the three time points. Dynamic changes in cytokine profiles and impacts on tumour recurrence were observed.
Results
We found that most cytokines/chemokines (12/27) in HCC patients at baseline were significantly decreased, while MCP-1 was elevated compared to that in healthy controls. IL-6 was significantly elevated at week 1 and decreased at week 4 after ablation, and there were positive correlations between IL-6 levels and ALT and WBC at week 1. IL-10 was slightly decreased at week 1 and dramatically decreased at week 4. The MCP-1, MIP-1β and TNF-α dynamics were similar (decreasing at week 1, increasing at week 4). IL-17, PDGF-BB and RANTES were significantly elevated at week 4 compared with baseline and week 1. We also found that patients with high levels of IL-10 at baseline and low levels of TNF-α, PDGF-BB and RANTES at week 4 were at risk of tumour recurrence.
Conclusion
Our results suggest that thermal ablation relieves tumour immune suppression and activates systemic immune responses by circulating cytokines linked to tumour recurrence.
Bumblebees sense rootstock-mediated nutrition and fertilization regime in tomato
Authors: Martínez-Andújar Cristina , Benyoussef Rim , Prudencio Ángela Sánchez , Ormazabal Maialen , Martín-Rodriguez José Ángel , Albacete Alfonso , Martínez-Melgarejo Purificación Andrea , Pérez-Alfocea Francisco 
Published: September 2022

Abstract
AimsSince producing more with less is required for increasing agricultural sustainability and reducing its environmental impact, breeding varieties with increased yield stability under reduced fertilizer application is an important goal, particularly in high valued horticultural crops such as tomato (Solanum lycopersicum L.) because of the difficulties to conciliate yield and fertilizer use efficiency. However, the graft-compatible genetic biodiversity existing in horticultural species offers the possibility to directly approach this objective in high-yielding elite varieties through improving nutrient capture and promoting ecosystem services such as insect pollination. MethodsFifteen experimental rootstocks from different genetic background were grafted to a scion tomato variety and cultivated under optimal and reduced (25% of optimal) P and NPK fertilization in the presence of managed bumblebee pollinators (Bombus terrestris). ResultsRootstocks generated up to 2-fold yield variability that was associated with leaf nutrition and photosynthesis, influenced by the fertilization regime. Interestingly, fertilization regime and the rootstock genotype influenced the pollinator foraging decisions since bumblebees showed feeding preference for plants cultivated under low P, and for the most yielding and nutritious graft combinations under reduced but not under optimal fertilization. Bumblebees can sense the optimized source-sink relations, as supported by the consistent relationship between leaf carbon concentration and pollinator preferences, and influenced by nitrogen, potassium and zinc nutritional status. ConclusionsThis study opens new perspectives for using pollinators as natural “phenotypers” to select the most resilient plants under suboptimal conditions and/or genotypes that synergistically increase crop productivity by promoting the ecosystem service provided by the insects.
Effect of Cryogenic and Electrolytic passivation treatment on Wear Resistance of M2 High-Speed Steel
Authors: Chen Zhi , Zhang Yangwei , Yan Xianguo , Li Jiale , Li Fan 
Published: September 2022

Abstract
Through cryogenic treatment and electrolytic passivation treatment of M2 high-speed steel(HSS), the effect of electrolytic passivation process parameters on the life of M2 HSS taps and the combined effect of cryogenic treatment and electrolytic passivation treatment on the wear resistance of the M2 HSS were investigated by using a scanning electron microscope (SEM) and energy dispersive spectrometer (EDS). The results show that the life of M2 HSS tap after electrolytic passivation treatment increases most significantly under the theoretical edge radius, the functional relationship between the charge consumption (y) and the tap edge radius (x) is as follows: y = 8.135x-48.842. The wear resistance of the sample after cryogenic and electrolytic passivation treatment is the highest, which is 1.52 times higher than those of the traditional heat treatment sample. This is due to the increase of the number of carbides on the surface of the specimens after cryogenic treatment, the distribution and size of carbides are relatively uniform, the average size of carbides is reduced by 60.4%. There is a carbon layer on the surface of the sample after passivation, which can effectively improve the wear condition. The size and number of carbides in the surface layer of the sample remain unchanged after passivation treatment, indicating that cryogenic treatment plays a key role in the performance of the material.
Enantioselective Transition-Metal Catalysis via an Anion-Binding Approach
Authors: Jacobsen Eric , Ovian John , Vojáčková Petra 
Published: September 2022

Abstract
Asymmetric transition-metal catalysis represents a powerful strategy for accessing enantiomerically enriched molecules. Here, we report a new approach for inducing enantioselectivity in transition-metal-catalyzed reactions that relies on neutral hydrogen-bond donors (HBDs) that bind anions of transition-metal complexes to achieve enantiocontrol and rate enhancement through ion pairing in concert with other noncovalent interactions. A cooperative anion-binding effect of a chiral bis-thiourea HBD is demonstrated to lead to high enantioselectivity (up to 99% enantiomeric excess) in intramolecular ruthenium-catalyzed propargylic substitution reactions. Experimental and computational mechanistic studies reveal the attractive interactions between electron-deficient arene components of the HBD and the metal complex that underlie enantioinduction and the acceleration effect.
Machine learning to predict ceftriaxone resistance using single nucleotide polymorphisms within a global database of Neisseria gonorrhoeae genomes
Authors: Ha Sung Min , Lin Eric , Klaunser Jeffrey , Adamson Paul 
Published: September 2022

Abstract
Antimicrobial resistance in Neisseria gonorrhoeae is an urgent global health issue 1. Resistance to ceftriaxone, the mainstay of gonorrhea treatment, is increasing2,3. Many genotypic mutations are associated with decreased susceptibility to ceftriaxone 4,5. In this study, N. gonorrhoeae genomes from the PathogenWatch database were downloaded and used to train and test different machine learning (ML) models to predict ceftriaxone susceptibility/decreased susceptibility (S/DS). We evaluated seven different ML algorithms with 97 SNPs that are known to be associated with ceftriaxone resistance. After identifying the ML algorithm with the highest performance metrics, the impact score of individual SNPs were calculated. The algorithm was then retrained using various combinations of top scoring SNPs to measure performance. The study identified 5 SNPs that performed well to predict decreased susceptibility and might be promising targets for molecular assays to predict S/DS to ceftriaxone. The ML methods reported here might have applications for predicting AMR within other pathogens.
Learning styles of medical students from a university in China
Authors: Liu Hai-ping , Liu Yue-hui 
Published: September 2022

Abstract
Background: Investigating students’ learning styles can generate useful information that can improve the curriculum design. This study adopts diverse measures to identify the learning styles of the students, though, there is limited literature related to clinical medical students in China. Hence, we utilized Felder’s Index of Learning Styles to examine the learning style characteristics of clinical medical students at Inner Mongolia Minzu University.Methods: This cross-sectional study investigated clinical medicine students for their learning style preference and the difference across genders. This study also analyzed data collected from other published studies. A total of 411 students from medical school at Inner Mongolia Minzu University furnished the Index of Learning Styles Questionnaire. The proposed questionnaire assesses the learning styles of students from four dimensions; namely visual-verbal learning; sequential-global learning; active-reflective leaning; and sensing-intuitive learning.Results: Analysis result shows that clinical medicine students choose to receive visual information (chose by 73.97% of the sample student) instead of verbal information. These students prioritize sensory information (67.15%) rather than intuitive information, and process reflective information (51.82%) rather than active information. They prefer to process information sequentially (59.85%) instead of globally. Our results also show that male students present a higher preference for an active learning style over a reflective learning style, while females seem to present a higher preference for a reflective learning style over an active learning style. These preferences varied between cohorts (gender), but the difference was not statistically significant. Compared to data collected from other published studies, sensing and visual are the most popular styles of learning adopted by medical science students; however, preferences in other dimensions vary by group.Conclusions: In general, the study findings conclude that Inner Mongolia Minzu University clinical medicine students prefer visual, sensing, and sequential learning styles. Gender has no significant effect on medical students' learning styles. Compared to data collected from other published studies, research consistently shows that sensing and visual are the most famous learning styles among medical students.
A low-cost smartphone fluorescence microscope for research, life science education, and STEM outreach
Authors: Schaefer Madison A , Nelson Heather N , Butrum John L , Gronseth James R , Hines Jacob H 
Published: September 2022

Abstract
Much of our understanding of cell and tissue development, structure, and function stems from fluorescence microscopy. The acquisition of colorful and glowing images engages and excites users ranging from seasoned microscopists to STEM students. Fluorescence microscopes range in cost from several thousand to several hundred thousand US dollars. Therefore, the use of fluorescence microscopy is typically limited to well-funded institutions and biotechnology companies, research core facilities, and medical laboratories, but is financially impractical at many universities and colleges, primary and secondary schools (K-12), and in science outreach settings. In this study, we developed and characterized components that when used in combination with a smartphone or tablet, perform fluorescence microscopy at a cost of less than $50 US dollars per unit. We re-purposed recreational LED flashlights and theater stage lighting filters to enable viewing of green and red fluorophores including EGFP, DsRed, mRFP, and mCherry on a simple-to-build frame made of wood and plexiglass. These devices, which we refer to as glowscopes, were capable of 10 µm resolution, imaging fluorescence in live specimens, and were compatible with all smartphone and tablet models we tested. In comparison to scientific-grade fluorescence microscopes, glowscopes may have limitations to sensitivity needed to detect dim fluorescence and the inability to resolve subcellular structures. We demonstrate capability of viewing fluorescence within zebrafish embryos, including heart rate, rhythmicity, and regional anatomy of the central nervous system. Due to the low cost of individual glowscope units, we anticipate this device can help to equip K-12, undergraduate, and science outreach classrooms with fleets of fluorescence microscopes that can engage students with hands-on learning activities.
APOE Genotype and Biological Sex Regulate Astroglial Interactions with Amyloid Plaques in Alzheimer’s Disease Mice
Authors: Stephen Terri , Breningstall Bayla , Suresh Sharanya , McGill Cassandra , Pike Christian 
Published: September 2022

Abstract
The most significant genetic risk factor for developing late-onset Alzheimer’s disease (AD) is the ε4 allele of apolipoprotein E (APOE4). APOE genotype and biological sex are key modulators of microglial and astroglial function, which exert multiple effects on AD pathogenesis. Here we show astroglial interactions with amyloid plaques in the EFAD transgenic mouse model of AD. Using confocal microscopy, we observed significantly lower levels of astrocytic plaque coverage and plaque compaction (beneficial effects of glial barrier formation) with APOE4 genotype and female sex. Conversely, neurite damage and astrocyte activation in the plaque environment were significantly higher in APOE4 carriers and female mice. Astrocyte coverage of plaques was highest in APOE3 males and poorest in APOE4 females. Collectively, our findings provide new insights into the roles of astroglia and highlight the importance of addressing independent and interactive effects of APOE genotype and biological sex in understanding processes contributing to AD pathogenesis.
Effect of eugenol on lipid profile, oxidative stress, sex hormone, liver injury, ovarian failure, and expression of COX-2 and PPAR-α genes in a rat model of diabetes
Authors: Kokabiyan Zahra , Yaghmaei Parichehreh , Jameie Seyed Behnamedin , Hajebrahimi Zahra 
Published: September 2022

Abstract
Background: Diabetes is among the leading causes of reproductive system failure and infertility in both women and men. Inflammation and oxidative stress have a main role in the development of diabetes. Eugenol or clove oil is a phenolic monoterpenoid with antioxidant and anti-inflammatory properties. Here, the effects of eugenol on diabetes features and ovarian function were investigated. Methods and Results: Streptozotocin-induced diabetes rats were treated with 12 and 24 mg/kg of eugenol for 4 weeks. The biochemical and histological assay was done to evaluate the effects of eugenol on ovary and pancreas function, liver injury, oxidative status, sex hormones, lipid profile, and mRNA levels of cyclooxygenase-2 (COX-2) and peroxisome proliferator-activated receptor alpha (PPAR-α) genes. Streptozotocin increased levels of serum glucose, total cholesterol, triglyceride, low-density lipoprotein (LDL), aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), malondialdehyde (MDA), pancreas necrosis and inflammation, COX-2 expression, ovarian cystic, and anovulation. It decreased the levels of insulin, high-density lipoprotein (HDL), Superoxide dismutase (SOD), estradiol, progesterone, testosterone, luteinizing hormone (LH), follicle-stimulating hormone (FSH), and PPAR-α expression. Eugenol administration ameliorated diabetes features through the improvement of lipid profile, oxidative status, insulin and glucose levels, sex hormone levels, liver markers, COX-2 and PPAR-α expression, and pancreas histology. It had no effect on ovarian cystic and follicular development. Conclusions Therefore, eugenol may be useful for ameliorating some adverse features of diabetes and used as an adjunct treatment or protective agent accompany by other chemicals in diabetes patients.
A New Method for Identification of Traditional Chinese Medicine Constitutions Based on Data of Tongue features with Machine Learning
Authors: Zhao Mei , Duan Mengyao , Han Dongran , Dong Yihang , Wang Jing , Mao Boyan , Hu Zhixi , Zhang Xiaoqing 
Published: September 2022

Abstract

Background: Different Traditional Chinese medicine (TCM) constitution types have different disease susceptibility and tendency, and TCM constitution identification is of great significance in TCM clinical practice. The TCM constitution identification method based on observation and consultation is subjective, and the objective identification technique opens up a new way to modernize TCM treatment. Our study aimed to build a TCM constitution identification model based on tongue feature data and machine learning algorithms, which provides a new fast and accurate method for TCM constitution identification.Methods: We use TFDA-1 tongue diagnostic instrument to collect standardized tongue images of people with Yang deficiency constitution, Yin deficiency constitution and balanced constitution. and use tongue image analysis software (TDAS) to quantitatively analyze tongue color, tongue texture and tongue coating area. Pearson correlation analysis was used to explore the correlation between tongue characteristics and TCM constitution. Four machine learning algorithms, including SVM, decision tree, random forest, and XGboost were used to build a TCM constitution identification model based on tongue features and evaluate the model's effectiveness.Results: The results show that XGboost has the highest accuracy rate among the four machine learning algorithms and the best performance in model evaluation. Pearson correlation analysis found a specific correlation between TCM constitution and tongue features. Significant correlations existed between the Yang deficiency constitution, Yin deficiency constitution, and the balanced constitution with 16 tongue features. In addition, the model's accuracy for the group 2 containing 16 tongue features was higher than that of the whole feature group (Group 1). XGboost was the most effective in this study for identifying TCM constitution, and the tongue features filtered by correlation analysis led to higher accuracy of TCM constitution identification.Conclusions: Tongue feature information can be an essential reference for TCM constitution identification. Machine learning provides a method for rapid identification of TCM constitution types. The XGboost TCM constitution identification model with good performance gives a new way for clinical " Identifying TCM Constitution by Tongue Image" implementation offers a reference and contributes to the performance of " Preventive Treatment of Disease" of TCM and individualized diagnosis and treatment and health preservation. In addition, Objective identification technology has opened up a new way to modernize TCM diagnosis and treatment.