bluuebunny/crossref_metadata_2025_split huggingface dataset:
The heating and storage of structured acylglycerols with succinyl-linked stigmasterol residue does not affect their chemical and biological negative changes
Authors: Rudzińska Magdalena , Grygier Anna , Olejnik Anna , Kowalska Katarzyna , Kmiecik Dominik , Chojnacka Anna , Gładkowski Witold , Grudniewska Aleksandra , Przybylski Roman 
Published: August 2023

Abstract
Four structured acylglycerols with stigmasterol bonded by succinyl linker were investigated and their stability were analyzed. Samples were heated at 60°C which simulated storage test and at 180°C simulated a frying conditions. The degradation of synthesized compounds and formed derivatives were determined. Also their cytotoxicity and genotoxicity on normal human cells from digestive system were analyzed. Heating at 180°C resulted in greater degradation of the tested compounds than at 60°C. In all the tested samples, compounds containing oleic acid in the structure were the most stable. At 60°C this was DO2SSt, and at 180°C it was DO3SSt. The results showed that the type of fatty acid residue in the molecule is more important than its position in the glycerol structure. All analyzed DASStGs, before and after heating, did not exhibit the cytotoxic and genotoxic potential of the analyzed compounds to the small intestine and colon mucosa cells.
Unsupervised machine learning combined with 4D scanning transmission electron microscopy for bimodal nanostructural analysis
Authors: Kimoto Koji , Kikkawa Jun , Harano Koji , Cretu Ovidiu , Shibazaki Yuki , Uesugi Fumihiko 
Published: August 2023

Abstract
Unsupervised machine learning techniques have been combined with scanning transmission electron microscopy (STEM) to enable comprehensive crystal structure analysis with nanometer spatial resolution. In this study, we investigated large-scale data obtained by four-dimensional (4D) STEM using dimensionality reduction techniques such as non-negative matrix factorization (NMF) and hierarchical clustering with various optimization methods. We developed software scripts incorporating knowledge of electron diffraction and STEM imaging for data preprocessing, NMF, and hierarchical clustering. Hierarchical clustering was performed using cross-correlation instead of Euclidean distances, resulting in rotation-corrected diffractions and shift-corrected maps of major components. An experimental analysis was conducted on a high-pressure-annealed metallic glass, Zr-Cu-Al, revealing an amorphous matrix and crystalline precipitates with an average diameter of approximately 7 nm, which were challenging to detect using conventional STEM techniques. Combining 4D-STEM and optimized unsupervised machine learning enables comprehensive bimodal (i.e., spatial and reciprocal) analyses of material nanostructures.
Causal Associations of Insomnia and Postpartum Depression: A Two-Sample Mendelian Randomization Study
Authors: Shen Xiao , Qiao Dongyan , Wang Yixiao , Tao Yuchen , Yu Hong 
Published: August 2023

Abstract
Background
Postpartum depression (PPD), a prevalent social mental condition, impacts not only the mother and the newborn but also several facets of their lives. It has been suggested that insomnia is related to both the occurrence and progression of PPD. However, because to lingering confounding and bias, it is impossible to determine the cause of this connection using observational analysis. In this study, we evaluate the causal importance of insomnia on postpartum depression using Mendelian randomization (MR).
Methods
Utilizing summary data from genome-wide association studies (GWAS), a two-sample MR study was conducted. A GWAS dataset of IEU study of the United Kingdom Biobank phenotypes comprising of 462,341 people of European heritage yielded 38 single-nucleotide polymorphisms (SNPs) for insomnia. The PPD data were provided by the FinnGen project and comprised 7604 cases and 59601 controls. Inverse variance weighting (IVW) was utilized for the primary MR analysis, with weighted median and MR-Egger serving as sensitivity analyses.
Results
As a result, we found that genetically predicted insomnia was positively associated with postpartum depression. The odds ratios (OR) of PPD were 1.849 (95% (confidence interval) CI: 1.011–3.381; p = 0.046).
Conclusion
For the first time, the causative role of sleeplessness for postpartum depression has been extensively evaluated in the current two-sample MR investigation. Our findings show that insomnia and PPD are related in a causal way.
Identification of novel NLRP3 Inhibitors: a comprehensive approach using 2D-QSAR, molecular docking, molecular dynamics simulation and drug-likeness evaluation
Authors: Mouhsin Mouad , Abchir Oussama , otmani Faical Sbai El , oumghar Ayoub Ait , Oubenali Mustapha , Chtita Samir , Mbarki Mohamed , Gamouh Ahmed 
Published: August 2023

Abstract
This research, employing computational methodologies, aimed to discover potential inhibitors for the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3), an intracellular sensor pivotal in inflammation and various disease processes. Despite NLRP3's critical role, there remains a research gap in the identification of novel inhibitors, making this study's objective significant. Through statistical techniques such as principal component analysis (PCA) and K-means clustering, data refinement and division was conducted in this research, leading to a more targeted set of potential inhibitors. By employing stepwise and subset multiple linear regression, a two-dimensional quantitative structure-activity relationship (2D-QSAR) model was developed, revealing six essential molecular descriptors for inhibitory activity. The interpretation of these descriptors led to the proposition of five potential compounds. One of these proposed compounds demonstrated remarkable binding affinity through molecular docking studies, marking it as a promising inhibitor of NLRP3. Further verification of this compound's potential was conducted via molecular dynamics simulations, affirming its stability and interactions within the protein-ligand system. Compliance with lipinski's rule of five indicated the drug-like properties of the proposed compounds and their potential for oral bioavailability. Consequently, these findings present a comprehensive methodology for the discovery and evaluation of novel NLRP3 inhibitors, significantly contributing to potential therapeutic advancements.
Surgical Healing Beyond the Scalpel: Exploring the Impact of Depressive Symptoms on Functional Recovery in Total Knee Arthroplasty Patients
Authors: Neelaraju Harshith , G Mahesh , Mittal Prabhat 
Published: August 2023

Abstract
Introduction: Numerous recent studies have explored the association between the mental health condition of patients before surgery and the outcomes of total knee arthroplasty. The principal objective of this study was to determine the prevalence of depressive symptoms among individuals undergoing total knee arthroplasty. Additionally, the study aimed to investigate the impact of pre-operative depressive symptoms as a significant and independent predictor on various health-related quality of life measures for patients undergoing knee surgery. Material and Methods: During the period spanning from August 2019 to May 2020, an orthopaedic database was established for the purpose of assessing patients' conditions before their surgeries. The data collection process occurred at three distinct intervals: prior to the surgery, as well as at the third and sixth months following the surgical procedure. In this study, we undertook an evaluation of both preoperative and postoperative depressive symptoms, as well as functional status, utilizing various self-report measures. These measures included the Becks Depression Scale, the Western Ontario and McMaster Universities Osteoarthritis Index, and the Knee Society Clinical Rating System. Results: Over the course of the study, the proportion of distressed patients decreased from 99% at the baseline assessment to 85% classified as normal, with 15% displaying mild distress levels during the 6-month follow-up period. Conclusions: Patients experiencing depression exhibited notable enhancements in various outcome measures. The findings from this study underscore a two-way relationship between mental health and surgical outcomes. Specifically, the surgical intervention yielded significant improvements in mental health status. Conversely, poorer preoperative mental health status emerged as a predictive factor for comparatively less favorable outcomes stemming from the surgery.
Fault analysis and research on SCR denitrification system in thermal power plants
Authors: WANG Yawen , LU Wanpeng , ZONG Shaoliang 
Published: August 2023

Abstract
The failure probability analysis of Selective Catalytic Reduction(SCR) denitrification system in thermal power plants has practical significance for the safe operation of denitrification system. After classifying the causes of the denitrification system failure, a fault tree analysis with the abnormal ammonia nitrogen molar ratio as the main indicator is established. The Boolean algebra operation method is used to analyze the path set of the fault indicator fault tree analysis, a total of 11 minimum cut sets and 5 minimum path sets are obtained. Analyze the combination mode and propagation path of the impact of each basic event on the top event, put forward the evaluation method of judging the system safety hazards according to the confidence degree. Based on the operation big data of a 300MW unit boiler denitrification system, the failure probability analysis of a specific fault inside the reactor was carried out, and the conclusion that the relative error between the confidence degree of the minimum cut set K7 and the confidence degree in the reliability evaluation method was only 0.694% was reached. Taking another 20 fault events, it was found that the relative error was all within 1%. The results show that the evaluation method of minimum cut set confidence is accurate and feasible.
Distribution of ℓ-regular partitions with distinct odd parts
Authors: Chiranjit Ray 
Published: August 2023

Abstract
Let $pod_{\ell}(n)$ be the number of $\ell$-regular partitions of $n$ with distinct odd parts. In this article, we prove that for any positive integer $k$, the set of non-negative integers $n$ for which $pod_{\ell}(n)\equiv 0 \pmod{p^{k}}$ has density one. We also exhibit several multiplicative identities for $pod_{3}(n)$, $pod_{5}(n)$ and $pod_{7}(n)$ using the Hecke eigenforms, and some results of Ono, Robins, and Wahl.
2010 Mathematics Subject Classification. Primary: 05A17, 11P83, 11F11, 11F20
Association of TNF-α, IGF-1, and IGFBP-1 levels with the severity of osteopenia in mice with non-alcoholic fatty liver disease
Authors: Wang Tong-Hao , Li Jian-Biao , Tian Yong-Gang , Zheng Jin-Xin , Li Xiao-Dong , Guo Shu-zhang 
Published: August 2023

Abstract
Backgrounds: Nonalcoholic fatty liver disease (NAFLD) exhibits a close association with osteoporosis. This work aims to assess the potential effects of NAFLD on the progression of osteopenia in animal models.
Methods: Forty-eight C57BL/6 female mice were randomly divided to wild-type (WT) group and high fat diet (HFD) group. The corresponding detections were performed after sacrifice at 16, 24 and 32 weeks, respectively .
Results: At 16 weeks, an remarkable increase of body weight and lipid aggregation in the hepatocytes of HFD group was observed compared to the WT group, while the bone structure parameters showed no significant difference. At 24 weeks, the levels of TNF-α and IL-6 in NAFLD mice were significantly increased, while the level of Osteoprotegerin (OPG) mRNA in bone tissue was decreased, and the level of receptor activator of nuclear factor Kappa-B ligand (RANKL) mRNA was increased. Meanwhile, the function of osteoclasts was increased, and the bone microstructure parameters showed significant changes. At 32 weeks, in the HFD mice, the mRNA levels of insulin-like growth factor-1 (IGF-1), Runt-related transcription factor 2 (Runx2), and Osterix (OSX) mRNA were reduced, while the insulin-like growth factor binding protein-1 (IGFBP-1) level was increased. Meanwhile, the osteoblast function was decreased, and the differences in bone structure parameters were more significant, showing obvious osteoporosis.
Conclusions: The bone loss in HFD mice is pronounced as NAFLD progresses, and the changes of the TNF-α, IL-6, IGF-1, and IGFBP-1 levels may play critical roles at the different stages of NAFLD in HFD.
A Warning Feedback Model Based on Online Learning Engagement Evaluation Under Interval-valued q-rung Orthopair Fuzzy
Authors: Wan Benting , Xie Jin , Pierre Bilivogui 
Published: August 2023

Abstract
When real-time detection indicates a low level of student engagement in online classrooms, selecting an appropriate time for feedback can enhance learner engagement. To address this issue, this study proposes an Interval-valued q-rung orthopair fuzzy warning feedback model based on the evaluation of online learning engagement. The designed warning feedback model utilizes a sliding window to capture the linguistic evaluation results of facial expressions, eye gaze, and limb states of online learners. By employing the developed IVq-ROFWDBM operator, as well as feature weight derivation and sample point weight derivation methods, the fuzzy comprehensive evaluation of sample points within the sliding window is conducted. When the evaluation result indicates low engagement, timely feedback is provided to the learners. The implementation of case studies demonstrates that the proposed warning feedback model can provide timely and effective feedback, avoiding the contradiction between excessive and untimely feedback. Comparative analysis results indicate that the proposed operator can obtain more accurate feedback outcomes.
Pregnancy prediction via ultrasound-detected endometrial blood for hormone replacement therapy-frozen embryo transfer: a prospective observational study
Authors: Ke Xue , Liang Xue-fei , Lin Yong-hong , Wang Fang 
Published: August 2023

Abstract
Background
This study aimed to assess the predictive value of endometrial blood flow branches on pregnancy outcomes after hormone replacement therapy-frozen embryo transfer (HRT-FET).
Methods
This prospective observational study involved 174 reproductive-aged women who underwent endometrial receptivity assessment in a tertiary care academic medical center in southwest China using power Doppler ultrasonography during HRT-FET. On the day of endometrial transformation and the day before embryo transfer, three-dimensional power Doppler ultrasound was performed. The endometrial blood flow branches of endometrial and subendometrial regions were compared in non-pregnant and pregnant groups at the two time points above.
Results
The endometrial blood flow branches were higher in pregnant patients than in non-pregnant patients on the day of endometrial transformation (P = 0.025) and the day before embryo transfer (P = 0.009). Changes in endometrial blood flow pattern and endometrial blood flow branches at the two time points did not differ among the pregnancy outcome samples. After adjusting for age, antral follicles, and embryos transferred, the endometrial blood flow branches on the day before embryo transfer was the independent factor influencing the chance of clinical pregnancy, with an odds ratio of 2.745 (95% confidence interval: 1.054–7.153, P = 0.039).
Conclusions
Endometrial blood flow perfusion during the peri-transplantation period of the HRT-FET cycle is a good indicator of pregnancy outcomes, suggesting that valuation of endometrial branches via power Doppler ultrasound is a simple and effective approach for achieving indicator measurements.
I Have a Dream…Altering New Zealand Medical Students’ Interpretation Bias of Māori in Healthcare Using Cognitive Bias Modification (CBM)
Authors: Hsu Che-Wei , Akuhata-Huntington Zaine 
Published: August 2023

Abstract
Health inequity is commonly experienced by marginalized populations and is a risk factor for developing health problems. One major contributor to health inequity is implicit (unconscious) bias. Many existing bias trainings aim to shift individuals' stereotype beliefs and evaluations of marginalized groups (the ‘what’ training), which can be challenging as these beliefs and evaluations are intrinsic. Here, we developed and tested a novel digital bias training tool called cognitive bias modification for stereotype (CBM-S), a tool designed to address more malleable context-dependent thinking patterns (the ‘how’ training). CBM-S uses an implicit learning task designed to force a less biased interpretation of situations involving Māori patients, an indigenous population of Aotearoa New Zealand. Using a pre-post training design, we tested the effectiveness of a single session 59-item CBM-S training session delivered via a web application against an active-reading control group. We adopted three implicit bias measures at pre- and post-test: two interpretation bias tests and one beliefs/evaluation assessment. Additionally, explicit bias measures were administered at post-test. Following CBM-S training, we found a reduction over time in stereotype interpretation bias scores with moderate practical significance (n2p= .11). Further analysis revealed a similar reduction in post-training stereotype bias scores after adjusting for baseline bias scores (n2p= .07). We found no significant differences in the beliefs/evaluation test scores or the explicit bias measures between the intervention and control groups but observed positive correlations between interpretation bias and explicit bias scores. Implications and potential applications are discussed.
Popular Events Detection from Blogs/Forums and Analyzing the Pattern of Users' Opinionwith Stock Market Movement
Authors: Ray Paramita , Chakrabarti Amlan 
Published: August 2023

Abstract
Frequently, individuals share their thoughts on socialmedia regarding diverse events and policy announcements. The challenge of discerning how news or social events influencefluctuations in stock prices is a prominent one. Many investorshave come to recognize that gauging the impact of an event onstock prices holds a pivotal role in making informed strategicchoices. However, identifying relevant events within the realm ofsocial media presents a formidable obstacle. To address this issue,our study is structured into two distinct phases: In the initial partof our investigation, we have collected data pertaining to economicpolicies from the Government of India’s budget speechesin 2020 and 2021, alongside stock-related information from newspapers,stock blogs, and forums. Subsequently, we harnessed anarray of natural language processing (NLP) techniques to extractaspects and phrases from this textual data. It is worth noting thatconventional NLP methods often encounter difficulties when dealingwith new instances and necessitate substantial training data.To overcome this, we devised a strategy involving a combinationof predefined linguistic patterns with NLP methodologies, therebyenhancing the precision of our approach. This comprehensivedataset facilitated the identification of a diverse array of publicinterest events, encompassing political occurrences and economictrends. The next phase of our study introduces an algorithmdesigned to identify popular events within the realm of socialmedia. Additionally, we examine how sentiments and opinionsrelated to these events can exert influence on movements in thestock market. The strategy most likely includes sentiment analysisand an investigation of the correlations between fluctuations instock prices and social media sentiment. Notably, our proposedmethodology has demonstrated superior performance comparedto prevailing methods, particularly in terms of overall accuracy.
Deubiquitination of UTP14A stabilizes HIF-1α and promotes melanoma angiogenesis
Authors: Ying Yu , Lu Quansheng , Zhang Yaxin , Jiang Guan 
Published: August 2023

Abstract
Objective To discuss the effects of UTP14A on the proliferation, migration and angiogenesis of melanoma, HIF-1α and its downstream pathway, and offer new clues for the diagnosis and treatment of melanoma.
Methods After over expression/knockdown of UTP14A, the effects of UTP14A on proliferation, migration, invasion of melanoma cells and angiogenesis of HUVEC cells were observed by CCK8, plate cloning, transwell and angiogenesis assay. CoIP and immunofluorescence were used to identify the interaction between UTP14A and HIF-1α. The subcutaneous tumorigenesis was performed in nude mice. Tumor size and weight were observed, and angiogenesis mimicry of melanoma tissue was observed by HE staining.
Results The results of CCK8 assay, plate cloning assay and mouse subcutaneous
tumor formation assay showed that UTP14A promoted the proliferation of melanoma in vivo and in vitro. Transwell experiment demonstrated that UTP14A promotes melanoma migration and invasion. HE staining of mouse tumor tissue indicated that UTP14A promotes the angiogenesis. It was found that UTP14A could up-regulate the expression of HIF-1α. The response experiment verified that UTP14A upstream of HIF-1α. IP experiment confirmed that UTP14A stabilizes HIF-1α by deubiquitinating.
Conclusion UTP14A promotes the progression of melanoma, and UTP14A promotes the proliferation, migration, invasion and angiogenesis of melanoma by stabilizing HIF-1α through deubiquitinating.
DrCSE: A New Framework For Software Vulnerability Detection base on An Advanced Computing
Authors: Cong Bui , Xuan Cho Do 
Published: August 2023

Abstract
The detection of software vulnerabilities written in C and C++ languages takes a lot of attention and interest today. This paper proposes a new framework called DrCSE to improve software vulnerability detection. It uses an intelligent computation tech-nique based on the combination of two methods: rebalancing data and representation learning to analyze and evaluate the code property graph (CPG) of the source code for detecting abnormal behavior of software vulnerabilities. To do that, DrCSE performs a combination of 3 main processing techniques: i) building the source code feature profiles, ii) rebalancing data, and iii) contrastive learning. In which, the method i) extracts the source code’s features based on the vertices and edges of the CPG. The method of rebalancing data has the function of supporting the training process by balancing the experimental dataset. Finally, contrastive learning techniques learn the important features of the source code by finding and pulling similar ones together while pushing the outliers away. The experiment part of this paper demonstrates the superiority of the DrCSE Framework for detecting source code security vulnerabil-ities using the Verum dataset. As a result, the method proposed in the article has brought a pretty good performance in all metrics, especially the Precision and Recall scores of 39.35% and 69.07%, respectively, proving the eﬃciency of the DrCSE Framework. It performs better than other approaches, with a 5% boost in Precision and a 5% boost in Recall. Overall, this is considered the best research result for the software vulnerability detection problem using the Verum dataset according to our survey to date