bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Nevertheless, it is still painful”: Use of Over-the-Counter analgesics, pain, stress, and HRQOL in Norwegian adolescents: a cross sectional study.
Authors: Skarstein Siv , Helseth Sølvi , Cvancarova Milada Smaastuen , Haraldstad Kristin , Rohde Gudrun , Mikkelsen Hilde Timenes , Grasaas Erik 
Published: December 2023

Abstract

Background
Approximately 20% of Norwegian adolescents are frequently using over-the-counter analgesics (OTCA). The WHO emphasizes the need for research to identify the key determinants of health problems in adolescence. Thus, our purpose is to study and describe pain, stress, and health-related quality-of-life (HRQOL) in Norwegian adolescents and investigate possible associations between these two variables upon high/low usage of OTCA.
Methods
This cross-sectional study included 315 adolescents (92 boys, 223 girls) with an average age of 14.1 years (13–15 years). All participants reported using OTCA. Weekly usage was categorized as high and less than weekly as low. Using a validated questionnaire, we explored the following variables: pain, as measured using the Brief Pain Inventory, stress (Perceived Stress Questionnaire) and HRQOL (KIDSSCREEN-27). Binary logistic regression models were conducted using SPSS software.
Results
Our descriptive findings revealed that high users of OTCA reported higher pain intensity of 3.4 (SD = 1.9) and perceived stress of 0.38 (SD = 0.18) than low users (2.5 (SD = 1.9) and 0.32 (SD = 0.16) respectively. OTCA high users reported lower average scores than low users across all HRQOL subscales. Binary logistic regression revealed 30% higher odds for higher levels of pain intensity (95% CI [1.11 to 1.51]) and 14 times higher odds of perceived stress (95% CI [1.03 to 204.) associated with being a high user of OTCA compared to a low user.
Conclusions
This study shows significant higher odds for experiencing pain and stress among adolescents using OTCA daily-to-weekly, compared to those seldom using such medicines. Health professionals should be aware of young people who have a high consumption of OTCA and investigate whether the use is related to pain or stress. This might be important in designing a personalized and appropriate intervention. Parents and caregivers have an important responsibility in supporting adolescents appropriate pain management. More observational and longitudinal studies are needed to understand predicative factors for adolescents OTCA usage.
Partitioned Problem Space (PaPS) Ensemble For Zero-day Intrusion Detection
Authors: Tiwary Priya , Madhubalan Akshayraj , Gautam Amit 
Published: December 2023

Abstract
The low cost and easy availability of cloud data storage have led to a massive increase in data being generated and stored for analytics, simultaneously amplifying challenges in data security. Detecting and stopping a data breach before it can cause any material damage and legal repercussions has become crucial. The volume and speed of data moving around the clouds make traditional intrusion detection systems ineffective. However, deep learning ensembles are a type of machine learning technique that combines the predictions of multiple deep learning models to produce a more accurate and reliable prediction. Particularly adept at identifying novel or sophisticated intrusions, these ensembles uncover patterns overlooked by individual models. In this work, we propose a novel partitioned problem space deep-learning ensemble approach wherein the base model’s problem space is constrained by limiting the number of classes and number of features visible to each during their training. The output probabilities of these base models are fed as input to the final meta-learner model along with a selective subset of important features. Our exper- imentation demonstrates that this ensemble approach outperforms known approaches in zero-day intrusion detection tasks. Our work aims to partition a complex problem space into smaller, more manageable sub-spaces. We propose a multi-stage deep learning ensemble model where base models are trained on a subset of classes and features, and their predictions are aggregated by a meta-learner model. This approach improves the model’s ability to generalize to unseen data, including zero-day attacks.
Associations between Body Mass Index (BMI) and Dyslipidemia: Results from the PERSIAN Guilan cohort study (PSCS)
Authors: Shahraz Jahangir , Joukar Farahnaz , Yeganeh Sara , Sheida Fateme , Maroufizadeh Saman , Baghaei Masood , Naghipour Mohammadreza , Mansour-Ghanaei Fariborz 
Published: December 2023

Abstract

Background: Given the high prevalence of obesity and its relationship with dyslipidemia, both as risk factors for cardiovascular diseases, this study was conducted with the aim of investigating the relationship between BMI and dyslipidemia in the Prospective Epidemiological Research Studies in Iran (PERSIAN) Guilan cohort study (PGCS) population.
Methods: In this cross-sectional study, demographic and biochemical data were collected from 10519 participants of the PGCS population aged 35-70 years in Some’e Sara County, Guilan, Iran. Participants were divided into two groups with and without dyslipidemia and were compared based on different levels of BMI. All data were analyzed using SPSS version 16 software with a significance level<0.05.
Results: The average age of the participants is 51.52 ± 8.90 years. The prevalence of dyslipidemia in all participants was equal to 75.8 %. Most of the people with dyslipidemia were in the age group of 45-54 years. Among those with dyslipidemia, 41.2 % and 35.5 % had overweight and obesity, respectively. Furthermore, individuals with dyslipidemia demonstrated higher proportions of women, employed individuals, rural residents, those with higher socio-economic status, elevated BMI, and lower levels of physical activity, (P<0.001). In the unadjusted model, there was a positive association between BMI and the prevalence of dyslipidemia (OR=1.09, 95% confidence interval (CI): 1.08-1.10), indicating that for one-unit increase in participants' BMI, the probability of having dyslipidemia increased by 9%, which was remained statistically significant even after adjusting (OR=1.07, 95% CI: 1.06-1.08) (P<0.001).
Conclusion: The risk of dyslipidemia increases in the group with high BMI and low physical activity compared to others. Therefore, weight loss should be recommended for all those with a high BMI. Also, community-based education would be helpful to increase public knowledge.
Effect of sodium pyruvate on inflammation, peroxidative damage, and energy metabolism in scalded wounds of diabetic rats
Authors: Meng Xiang-Xi , Mi Qian , He Ze , Sun Kui 
Published: December 2023

Abstract
Objective
The aim of our study was to determine the effect of sodium pyruvate solution on the healing, inflammation, peroxidative damage, and energy metabolism of deep second-degree scald wounds in diabetic rats.
Methods
Fifty male Sprague Dawley (SD) rats were randomly divided into the scald normal salinegroup(SN group), the diabetes scald normal saline group(DSN group), the diabetes scald low-dose sodium pyruvate group(DSL group), the diabetes scald medium-dose sodium pyruvate group(DSM group), the diabetes scald high-dose sodium pyruvategroup(DSH group). The diabetic rat model was replicated by intraperitoneal injection of streptozotocin (STZ), and after successful modelling, a 4 cm diameter deep second-degree wound was prepared on the back of the rat. Different doses of sodium pyruvate were administered by gavage in the sodium pyruvate groups, and equal amounts of normal saline were administered once a day in the SN and DSN group. At 1, 3, 7, 14 and 21d after scald, the wound healing rate, body weight and blood glucose level of rats were observed, and the levels of NAD+/NADH, malondialdehyde (MDA), superoxide dismutase (SOD), interleukin 6 (IL-6), and tumour necrosis factor alpha (TNF-α) were detected in the wound tissue by ELISA.
Results
Compared with SN group, the levels of blood glucose, MDA, IL-6, and TNF-α were significantly higher and the level of SOD was significantly lower from 1d post-injury, the body weight was significantly reduced and the level of NAD+/NADH was significantly lower from 3d post-injury, and the healing rate of wounds was significantly lower from 14d post-injury in DSN group; compared with DSN group, sodium pyruvate treatment improved the blood glucose level, increased the metabolic level, inhibited the inflammatory response and peroxidative damage in the wound tissue, and significantly increased the wound healing rate.
Conclusion
Sodium pyruvate can promotes healing of deep second-degree scald wound in diabetic rats and may play a role via inhibiting wound tissue inflammation, peroxidative damage, and improving energy metabolism
Enhanced upgrading of lignocellulosic substrates by coculture of Saccharomyces cerevisiae and Acinetobacter baylyi ADP1
Authors: Liu Changshuo , Choi Bohyun , Efimova Elena , Nygård Yvonne , Santala Suvi 
Published: December 2023

Abstract

Background: Lignocellulosic biomass as feedstock has a huge potential for biochemical production. Still, efficient utilization of hydrolysates derived from lignocellulose is challenged by their complex and heterogeneous composition and the presence of inhibitory compounds, such as furan aldehydes. Using microbial consortia where two specialized microbes complement each other could serve as a potential approach to improve the efficiency of lignocellulosic biomass upgrading.
Results: This study describes the simultaneous inhibitor detoxification and production of lactic acid and wax esters from a synthetic lignocellulosic hydrolysate by a defined coculture of engineered Saccharomyces cerevisiaeand Acinetobacter baylyi ADP1. A. baylyi ADP1 showed efficient bioconversion of furan aldehydes present in the hydrolysate, namely furfural and 5-hydroxymethyl furfural, and did not compete for substrates with S. cerevisiae, highlighting its potential as a coculture partner. Furthermore, the remaining carbon sources and byproducts of S. cerevisiae were directed to wax ester production by A. baylyi ADP1. The lactic acid productivity of S. cerevisiae was improved approximately 1.5-fold (to 0.41 ± 0.08 g/L/h) in the coculture with A. baylyi ADP1, compared to a monoculture of S. cerevisiae.
Conclusions: The coculture of yeast and bacteria was shown to improve the consumption of lignocellulosic substrates and the productivity of lactic acid from a synthetic lignocellulosic hydrolysate. The high detoxification capacity and the ability to produce high-value products by A. baylyi ADP1 demonstrates the strain to be a potential candidate for coculture to increase production efficiency and economics of S. cerevisiaefermentations.
Effect and Mechanism of Anlotinib on the Malignant Biological Behavior of Cisplatin-resistant Cells in Cervical Cancer
Authors: Xia Nana , Chen Siying , Li Yu , Yu， Minmin 
Published: December 2023

Abstract
Purpose
To explore the effect of anlotinib on the proliferation, apoptosis, migration and invasion of cisplatin-resistant cervical cancer cells and study the changes of gene transcriptome of cisplatin-resistant cervical cancer cell lines after intervention with anlotinib.
Materials and Methods
In this study, cisplatin was used to induce the establishment of a drug-resistant cervical cancer cell line Siha/DDP. Then we use CCK-8 test, cell cloning test, flow cytometry test and western blotting test to explore the effect of anlotinib on the proliferation and apoptosis of Siha/DDP cells. Cell scratch test and transwell test were used to explore the effect of anlotinib on the migration and invasion of Siha/DDP cells. Finally transcriptome sequencing was used to detect changes in the gene expression profile of Siha/DDP cells under the action of anlotinib.
Results
Compared with the control group, the anlotinib group was able to dose-dependently inhibit Siha/DDP cell proliferation, migration, and invasion and significantly inhibit Siha/DDP cell clone formation; it was also able to dose-dependently promote Siha/DDP cell apoptosis and block Siha/DDP cells in the G2/M phase. Anlotinib significantly upregulated Bax, P21, E-cadherin protein expression and significantly downregulated Bcl-2, CDK1 and CyclinB1, VEGF, MMP-9 protein and drug resistance-associated protein P-gp protein expression in Siha/DDP cells. The gene expression profile of Siha/DDP cells caused changes after treatment with anlotinib. SQLE, MSMO1, LSS, FDFT1 and HMGCS1 were obtained as key hub gene
Conclusion
Anlotinib can inhibit the proliferation, migration and invasion of Siha/DDP cells and promote their apoptosis. The gene expression profile of Siha/DDP cells was altered after treatment with anlotinib, causing differential expression of several genes including SQLE, MSMO1, LSS, FDFT1 and HMGCS1.
Bioinformatics Analysis Of Hub Genes And Pathways In Congenital Hypothyroidism
Authors: Shan Mingliang , Zhuo Xiumei , Sui Lili , Sun Ping , Liu Shiguo , Cui Zhaoqing 
Published: December 2023

Abstract
Background:
We have found hub genes and dysregulation pathways in congenital hypothyroidism (CH).
Methods:
We found the required samples from the GEO and UCSC Xena databases respectively. The limma and pheatmap packages in R were used for differential gene searching and volcano and heat map mapping. The R package was used to generate GO enrichment analysis plots. Protein interaction network analysis was performed on the dataset through the STRING website, and a confidence level of 0.4 was selected to obtain the protein interaction relationships, and the interaction relationship data were downloaded; First, the genes with the top 20 expressions were screened by R as the core gene set gene1, and secondly, the data were then imported into Cytoscape, manually delete the outlier data, and use the algorithm in cytoHubba to screen out the core gene set gene2, and finally take the intersection of the two parts of gene set gene1 and gene2 obtained earlier by using jvenn to the final hub genes were obtained. Subsequently, Cytoscape was used to map the co-expression network of hub genes with other genes. The WGCNA package in R was used to perform WGCNA analysis on the differential data, and the selected hub genes were tagged, and then Cytoscape was used to map the co-expression network of the hub genes with other genes.
Results:
We identified a total of 250 DEGs, of which 174 genes were up-regulated and 76 genes were down-regulated. GO enrichment analysis showed that CH DEGs were significantly enriched in the trans-Golgi network and the Golgi apparatus subcompartment. The PPI network of the hub DEG has 209 nodes and 257 edges.WGCNA analysis showed that most of the genes were clustered in three major modules and confirmed by experimental analysis that there were close interactions between the screened hub genes, which were all clustered in the same module (blue module).
Conclusion:
HSPB1, PABPC1, and APP - these three hub genes are closely associated with the occurrence of congenital hypothyroidism and may influence the synthesis and secretion of T3 and T4 by affecting the synthesis of proteins in the Golgi apparatus of thyroid cells.
Simulation of Self-Tuning Fuzzy PI Controller for Micro Hydro Power Plants, which are implemented in the Ethiopian Rural Land
Authors: Mengesha Daniel Arega 
Published: December 2023

Abstract
This article addresses the underdeveloped state of micro hydropower in Ethiopia and the absence of locally manufactured, low-cost frequency controllers. To overcome this, the research proposes a novel approach using a fuzzy logic controller in conjunction with a PI controller for precise frequency control in micro hydropower plants. The designed fuzzy logic-based system proves to be simple, cost-effective, and responsive, safeguarding the power system components during low flow rates by isolating loads. Ethiopia's abundance of irrigation dams and water resources offers a strategic opportunity for implementing micro hydropower plants with minimal investment and time, particularly on existing dams. This article emphasizes the significance of parameter variations in micro hydropower systems and employs a detailed dynamic model to develop a fuzzy logic controller. Simulation results demonstrate the superiority of the fuzzy controller over the traditional PI controller, exhibiting significantly reduced overshoot (0.9% for a 35% load change) and faster settling times (26.85s). Even under more challenging conditions, the fuzzy controller outperforms the PI controller, showcasing its efficiency across varying operating conditions. The findings underscore the potential of the proposed fuzzy controller in advancing affordable micro hydropower solutions for rural areas in Ethiopia.
Existence of non-unique neighbor-joining phylogenetic trees of microsatellite markers
Authors: Segura-Alabart Natàlia , Serratosa Francesc , Fernández Alberto 
Published: December 2023

Abstract
Background:
Neighbor-joining (NJ) is a distance-based method used to analyse and visualise data that generates a phylogenetic tree. It is found in a wide range of scientific research and is upstream of all areas of bioinformatics and computational biology. NJ's drawback is the generation of different binary phylogenetic trees if more than two clusters of elements have the same distance in any step of the phylogenetic tree generation process. We analyse the extent of this problem in a particular context: the clustering of microsatellite markers with NJ. For this purpose, we calculate the proportion of publications in the Scopus database in which more than one binary phylogenetic tree is possible.
Results:
We have observed that 13% of articles can produce more than one binary phylogenetic tree; thus, results shown in these articles would have to be deeply analysed or their conclusions revised. To illustrate the problem from a practical point of view, we have selected an example where more than one binary phylogenetic tree solution is possible.
Conclusion:
Articles that show only one phylogenetic tree, although NJ could generate several of them, are somewhat biased and hard to reproduce. The percentage of publications with non-unique NJ phylogenetic trees is large enough to be considered a general problem in our scientific community.
A Performance of Hardened Properties of GGBFS and Micro Silica-Based High-Strength Self- Compacting Concrete
Authors: M Naveen Kumar S , M M Rame Gowda 
Published: December 2023

Abstract
The building construction industry is continuously exploring innovative methods to advance the properties of concrete and ensure its durability and strength. Self-compacting concrete (SCC) has gained considerable attention due to its ability to flow and compact under its weight, resulting in reduced labour requirements and improved structural integrity. In present investigate the prediction of critical properties of self-compacting concrete using an artificial neural network approach (ANN), and the compressive and split tensile strength of SCC were predicted in the current study. The data from seven sets of a total of concrete samples and the experimentally generated data for self-compacting concrete were used in this study. ANNs are regarded as nonlinear statistical data modeling tools for identifying patterns or modeling complex interactions between inputs and outputs. Eight input parameters are employed in the current ANN model to forecast the compressive and split tensile strength of self-compacting concrete. Cement, M-sand, coarse aggregate, GGBS, Micro silica (MS), water, Super Plasticizer (SP), and Age (days) are among these materials in variable proportions. The concrete's compressive and split tensile strengths are both included in the single output parameter. The study covered the significance of various input parameters for utilizing neural networks to predict strengths at various ages. The compressive strength of SCC predicted by ANN is a perfect match with experimental data and extremely low Mean Square Errors (M.S.E.). Additionally, the ANN model's effectiveness is higher than that of multiple regression analysis (MRA).The ANN model has greater promise than the MRA model for creating an ideal mix percentage for predicting the compressive strength and split tensile strength of concrete without suffering a significant loss in material or time.
Decomposition and insect succession of pig and rabbit cadavers’ corpses buried in the northern Sudanese zone of Burkina Faso
Authors: Zongo David , Romba Rahim , Joseph Kinda  , Waongo Antoine , Drabo Samuel Fogné , Gnankine Olivier 
Published: December 2023

Abstract
Forensic entomology is a science that studies insects and other arthropods in relation to forensic investigations. This study aimed to examine the presence of insects on pig and rabbit carcasses buried at two different depths, 100 and 50 cm, respectively, along nine sampling dates to establish an insect succession database on buried cadavers in the north sudanian zone of Burkina Faso. In addition, we investigated whether environmental parameters influence both the decomposition of buried corpses and the abundance of insects. Nine pigs and nine rabbits were buried at 100 and 50 cm respectively, at two different sites. Carcasses were exhumed after 14, 28, 42, 56, 70, 84, 98, 112 and 126 days of burial, respectively. Approximately 668 larvae, pupae, cocoons and adults of insects were surveyed on the two substrates during the 2020 and 2021 study periods, divided into 5 main orders, Diptera, Coleoptera, Hymenoptera, Dermaptera and Orthoptera. Accarinae and a few spiders were also inventoried. Succession of insects varied with depth. No significant difference in soil temperature (P = 0.9; 0.12) between the 50 and 100 cm depths was observed. However, significant differences were observed between the temperatures of depths and ambient air (P = 2.3e-07; 0.00027). Necrophagous insects were more abundant on the pig substrate than the rabbit. Our data provided precious information in terms of assessing the postburial interval.
MisCaltral: Reducing Numeric Hallucinations of Mistral with Precision Numeric Calculation
Authors: Chen Shih-Wen , Hsu Hsien-Jung 
Published: December 2023

Abstract
This paper introduces MisCaltral, an innovative enhancement to the Mistral 7B large language model (LLM), which integrates an external numeric calculator to address the challenge of numerical precision. Traditional LLMs, including Mistral 7B, struggle with accurately processing numeric data, a limitation that significantly hampers their application in fields requiring exact numeric computations. MisCaltral overcomes this by leveraging a specialized calculator module for precise mathematical operations, synergizing linguistic understanding with numerical accuracy. Through extensive experiments, MisCaltral demonstrates a notable improvement in numeric calculation accuracy, particularly in complex financial scenarios, compared to the un-augmented Mistral model. The study not only highlights the enhanced numeric capabilities of MisCaltral but also discusses the broader implications of such integrations in real-world applications and future LLM development. This research marks a significant step forward in the evolution of LLMs, paving the way for more sophisticated and reliable AI models that can adeptly handle a blend of linguistic and numeric data.