bluuebunny/crossref_metadata_2025_split huggingface dataset:
BioLLMBench: A Comprehensive Benchmarking of Large Language Models in Bioinformatics
Authors: Mangul Serghei , Sarwal Varuni , Munteanu Viorel , Suhodolschi Timur , Ciorba Dumitru , Eskin Eleazar , Wang Wei 
Published: January 2024

Abstract
Large Language Models (LLMs) have shown great promise in their knowledge integration and problem-solving capabilities, but their ability to assist in bioinformatics research has not been systematically evaluated. To bridge this gap, we present BioLLMBench, a novel benchmarking framework coupled with a scoring metric scheme for comprehensively evaluating LLMs in solving bioinformatics tasks. Through BioLLMBench, we conducted a thorough evaluation of 2,160 experimental runs of the three most widely used models, GPT-4, Bard and LLaMA, focusing on 36 distinct tasks within the field of bioinformatics. The tasks come from six key areas of emphasis within bioinformatics that directly relate to the daily challenges and tasks faced by individuals within the field. These areas are domain expertise, mathematical problem-solving, coding proficiency, data visualization, summarizing research papers, and developing machine learning models. The tasks also span across varying levels of complexity, ranging from fundamental concepts to expert-level challenges. Each key area was evaluated using seven specifically designed task metrics, which were then used to conduct an overall evaluation of the LLM’s response. To enhance our understanding of model responses under varying conditions, we implemented a Contextual Response Variability Analysis. Our results reveal a diverse spectrum of model performance, with GPT-4 leading in all tasks except mathematical problem solving. GPT4 was able to achieve an overall proficiency score of 91.3% in domain knowledge tasks, while Bard excelled in mathematical problem-solving with a 97.5% success rate. While GPT-4 outperformed in machine learning model development tasks with an average accuracy of 65.32%, both Bard and LLaMA were unable to generate executable end-to-end code. All models faced considerable challenges in research paper summarization, with none of them exceeding a 40% score in our evaluation using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) score, highlighting a significant area for future improvement. We observed an increase in model performance variance when using a new chatting window compared to using the same chat, although the average scores between the two contextual environments remained similar. Lastly, we discuss various limitations of these models and acknowledge the risks associated with their potential misuse.
Evaluating the impacts of earthquake in Ezgele, Kermanshah (Iran)(occurred on 2017/11/12)
Authors: Ganjaeian Hamid , Yamani Mojtaba , Gorabi Abolghasem , Maghsodi Mehran 
Published: January 2024

Abstract

Earthquake is one of the most important environmental hazards associated with massive casualties and pecuniary losses. The earthquake of November 12th, 2017 in Ezgele, Kermanshah has been one of the most destructive earthquakes ever happened in Iran; in this study, considering the importance of the issue, we have evaluated its tangible and intangible effects. Our research data include radar images from Sentinel 1, statistical information on earthquake stress and damage estimates obtained via extensive fieldworks. ARCGIS and GMT software were used as research tools. Interferometric synthetic aperture radar (InSAR) was also used to analyze data. To achieve the desired goals, first the tangible effects of earthquakes were estimated using results obtained from fieldwork and documentary data from relevant organizations. Then, radar images were used to evaluate the intangible effects of earthquakes and the effects of stresses on urban areas, plains and slopes. The obtained results show that longitudinal cracks, slips and building collapses have been the most significant reported tangible impacts. Also, the most important intangible impacts of the earthquake across the study area are +917 to -613 mm vertical displacement, in cities, plains and slopes, which can cause a lot of damage in the near future.
Diagnostic performance of magnetic resonance imaging features to differentiate adrenal pheochromocytoma from adrenal tumors with positive biochemical testing results
Authors: Huang Rukun , Lin Tingsheng , Chen Mengxia , Li Xiaogong , Guo Hongqian 
Published: January 2024

Abstract

Background
It is extremely essential to accurately differentiate pheochromocytoma from Adrenal incidentalomas (AIs) before operation, especially biochemical tests were inconclusive. We aimed to evaluate the value of magnetic resonance imaging (MRI) features to differentiate pheochromocytomas among adrenal tumors, among which the consequences of biochemical screening tests of catecholamines and/or catecholamine metabolites are positive.
Methods
With institutional review board approval, this study retrospectively compared 35 pheochromocytoma (PHEO) patients with 27 non-pheochromocytoma(non-PHEO) patients between January 2022 to September 2023, among which the consequences of biochemical screening tests of catecholamines and/or catecholamine metabolites are positive. T test was used for the independent continuous data and the chi-square test was used for categorical variables. Univariate and multivariate logistic regression were applied to find the independent variate of the features to differentiate PHEO from non-PHEO and ROC analysis was applied to evaluate the diagnostic value of the independent variate.
Results
We found that the T2-weighted (T2W) signal intensity in patients with pheochromocytoma was higher than other adrenal tumors, with greatly significant (p <​ 0.001). T2W signal intensity ratio (T2W nodule-to-muscle SI ratio) was an independent risk factor for the differential diagnosis of adrenal PHEOs from non-PHEOs. This feature alone had 91.4% sensitivity and 81.5% specificity to rule out pheochromocytoma based on optimal threshold, with an area under the receiver operating characteristics curve (AUC‑ROC) of 0.910(95% C I: 0.833–0.987).
Conclusion
Our study confirms that T2W signal intensity ratio can differentiate PHEO from non-PHEO, among which the consequences of biochemical screening tests of catecholamines and/or catecholamine metabolites are positive.
Association study between biomarkers of metabolites and its relevance genes for hypertension in Korean adults
Authors: Hwang Dahyun , Jung Jaemee 
Published: January 2024

Abstract
Metabolites are the intermediate and end-products of metabolic pathways that reflect ongoing biological processes. Unlike genes and proteins, metabolites are closely related to biochemical activities and clinical phenotypes, which can serve as indicators and characterize their impact on disease. Hypertension (HTN) is among the most important preclinical conditions of metabolic syndrome and remains the top risk factor for cardiovascular diseases. Pathophysiological mechanisms for the development of HTN are well known. However, there is a lack of knowledge regarding the metabolite changes that promote disease development. Therefore, we investigated HTN-related metabolites using the cohort data of the Korean Genome and Epidemiology Study (KoGES). As a result, phosphatidylcholine (PC)-derived metabolites were found to have the highest correlation with HTN. In linear regression analysis between metabolites and single nucleotide polymorphisms (SNPs), the SNPs belonging to the HECT domain E3 ubiquitin protein ligase 4 (HECTD4), myelin regulatory factor (MYRF), and fatty acid desaturase 1 (FADS1) genes showed a significant correlation. Among them, rs11066280 of the HECTD4 gene was found to be related to HTN (p = 0.03). This result was consistent with the reported association of HECTD4 with systolic and diastolic blood pressure. In conclusion, PC-derived metabolites and HECTD4 are associated with HTN in the Korean population. With the identification of HTN-related metabolites, the results of this study could be very useful in the early detection, diagnosis, and treatment of HTN. Finally, if in vitro and in vivo data are added in the future could help in the formulation of new guidelines for the treatment of HTN.
Salinity Distribution in a Tropical River-Estuary Continuum through Numerical Modelling: Case of the Wouri-Nkam River Estuary, Cameroon
Authors: Besack Felix , Ebonji Seth Rodrigue , Ajonina Gordon , Tchogom Josué Manga , Essome Landry Mbang , Onguene Raphael , Tomedi Minette , Olesugun Dada 
Published: January 2024

Abstract

In estuaries environments, the distribution of salinity controls the resourcing of freshwater for agriculture, aquaculture and human consumption; it also regulates the functioning of critical natural habitats. Consequently, there is a particular need for a better understanding of the salinity distribution along river estuaries continuum and for simple predictive relationships linking salinity to estuarine characters and hence environmental conditions. Despite numerous global insightful studies, there are limited studies regarding the spatial patterns of salinity distribution in African estuarine systems. The present study fills this gap using idealized 1-dimentional (1-D) modelling of the Wouri-Nkam River Estuary, Cameroon under various seasonal and tidal conditions. The model results reveal a seasonal tidal excursions varying from 21.4 km (dry season), 18.1 km (transition season), and 14.66 km (wet season). The model performs best during the wet and transition seasons. The year 2050 and 2100 predictions reveal salt intrusion distance of 21 km and 41 km, respectively, indicating that the whole estuary and its surrounding environment will be polluted by marine water in the latter year. The results of this study are important for the region's water resource managers and decision-makers in mitigating the effects of climate change and associated Sea Level Rise (2100 scenario) on the coastal ecosystems since their continuous modification will negatively impact the living standard of Cameroon’s growing population, and the sub region at large.
Multi-trait ridge regression BLUP with de novo GWAS improves genomic prediction for haploid induction ability and agronomic traits of haploid inducers in maize
Authors: Chen Yu-Ru , Frei Ursula , Lübberstedt Thomas 
Published: January 2024

Abstract

Key message Employing multi-trait and de novo GWAS in a ridge regression BLUP model increases the predictive ability of haploid induction rate of haploid inducers in maize. Ridge regression BLUP (rrBLUP) is a widely used model for genomic selection. Different genomic prediction (GP) models have their own niches depending on the genetic architecture of traits and computational complexity. Haploid inducers have unique trait performances, relevant for doubled haploid (DH) technology in maize (Zea mays L.). We herein compared the performance of single-trait (ST) and multi-trait (MT) GP models (rrBLUP, BayesB, Random Forest, and xGBoost) and employed multi-trait and de novo GWAS in the ridge regression BLUP model for four traits of interest (Days to flowering, DTF; haploid induction rate, HIR; plant height, PHT; primary branch length, PBL) of the multifamily DH inducers (DHIs), and next tested the GP models in multi-parent advanced generation inter-cross (MAGIC) DHIs. The average predictive abilities (PA) of different GP methods across traits were 0.44 to 0.65 in multifamily DHIs. ST/MT de novo GWAS rrBLUP methods increased PA of HIR when using five-fold cross-validation. In addition, MT GP models improved PA by 13% on average across traits relative to ST GP models in MAGIC DHIs. These results provide empirical evidence that employing multi-trait and de novo GWAS in rrBLUP model in genomic selection could benefit the genetic improvement of haploid inducers.
Liquid-liquid extraction equilibrium study of vanadium(V) from nitrate medium by technical grade D2EHPA dissolved in kerosene
Authors: Karmakar Aneek Krishna , Hossen Amzad 
Published: January 2024

Abstract
The titled system was investigated as functions of aqueous pH, [V (V)] and [NO3−], and organic [D2EHPA]. The system is non-ideal as the log D value decreases with [V (V)]. Two types of mechanisms were identified through the pH dependence study; below pH 2.5, the log D value increases with increasing pH value with a limiting slope of 0.35, whereas, above pH 2.5, the limiting slope is -0.32. The extractant dependence is 0.24. The extraction ratio increases with increasing [NO3−], showing the salting out effect. Kerosene appears as a suitable diluent. The system is exothermic with ΔH =-12.34 kJ/mol. The loading capacity was 6.11 g V (V)/100 g extractant. A 0.5 mol/L H2SO4 solution appeared to be a suitable stripping agent.
Artificial Neural Networks Applied in the Classification of Radionuclides from Gamma Spectroscopy and Computational Simulation
Authors: de Azevedo Ary Machado , Silva Márcio Magalhães de Andrade , Nunes Wallace Vallory , Morales Rudnei Karam , Cardoso Domingos D'Oliveira , Monteiro Sérgio Neves 
Published: January 2024

Abstract

The present study seeks to develop a classifier of radioactive sources based on gamma spectroscopy and artificial intelligence, which makes use of Keras and TensorFlow [, both free and open-source technologies. Through these technologies, an artificial neural network (ANN) was developed, which makes use of supervised machine learning and the backpropagation algorithm. The neural network was trained with a dataset of spectra from simulations performed by the Monte Carlo N-Particle 5 code (MCNP5). To achieve the objective of functioning as a classifier within the proposed scope, several versions of the neural network were evaluated, to study its performance, to determine important parameters such as a learning rate, and the optimizer used, among others, where RNA performance was evaluated by analyzing the network accuracy and loss curves. The generalization capacity was assessed by submitting spectra raised experimentally by an apparatus composed of a NaI(Tl) detector, a multichannel analyzer, and the Maestro software for the experimental data acquisition, which were used with the use of sealed radioactive sources of Co-60, Cs-137, and Eu-152. Six versions of the ANN were selected, capable of solving the proposed problem, with accuracy greater than 95%.
Metabolic abnormalities in the bone marrow cells of young offspring born to obese mothers
Authors: Alina Maloyan , Phillips Elysse , Alharithi Yem , Kadam Leena , Coussens Lisa , Kumar Sushil 
Published: January 2024

Abstract

Intrauterine metabolic reprogramming occurs in obese mothers during gestation, putting the offspring at high risk of developing obesity and associated metabolic disorders even before birth. We have generated a mouse model of maternal high-fat diet-induced obesity that recapitulates the metabolic changes seen in humans born to obese women. Here, we profiled and compared the metabolic characteristics of bone marrow cells of newly weaned 3-week-old offspring of dams fed either a high-fat (Off-HFD) or a regular diet (Off-RD). We utilized a state-of-the-art targeted metabolomics approach coupled with a Seahorse metabolic analyzer. We revealed significant metabolic perturbation in the offspring of HFD-fed vs. RD-fed dams, including utilization of glucose primarily via oxidative phosphorylation. We also found a reduction in levels of amino acids, a phenomenon previously linked to bone marrow aging. Using flow cytometry, we identified a unique B cell population expressing CD19 and CD11b in the bone marrow of three-week-old offspring of high-fat diet-fed mothers, and found increased expression of Cyclooxygenase-2 (COX-2) on myeloid CD11b, and on CD11bhi B cells. Altogether, we demonstrate that the offspring of obese mothers show metabolic and immune changes in the bone marrow at a very young age and prior to any symptomatic metabolic disease.
Novel hydrogel based on natural hybrid backbones: Optimized synthesis and effective adsorbent for the removal of dye from an aqueous solution
Authors: Kumawat Yogesh Kumar , Nair Abhigith , Choudhary Sonal , Nath Jyotendra , Sharma Kashma , Rasool Tanveer , Sharma Vishal , Mishra Yogendra , Kumar Vijay 
Published: January 2024

Abstract
In this study, we synthesized a novel hydrogel, GG/LBG-g-poly(AAm), utilizing a hybrid backbone composed of guar gum, locust bean gum, and acrylamide. The cross-linker N, N-Methylene-bis-acrylamide, and the initiator ammonium persulfate were employed in the synthesis process. Response surface methodology and a full factorial rotatable central composite design were used to optimize various reaction parameters to enhance the percentage swelling of the synthesized hydrogel. This optimization resulted in a notable increase in swelling capacity, reaching 1050%. The incorporation of acrylamide chains onto the guar-locust bean gum-based hybrid backbone, as well as crosslinking between different polymeric chains, was confirmed through various characterization techniques, including FTIR, TGA, XRD, FE-SEM, wettability studies, and zeta potential analysis. We investigated the hydrogel’s adsorption performance for malachite green (MG), varying pH, contact time, adsorbent dose, and dye concentration. Under ambient conditions, GG/LBG-g-poly(AAm) demonstrated a maximum adsorption capacity of 52.96 mg g− 1 and achieved a removal efficiency of 98%. The adsorption data best fit the Freundlich model (R2 = 0.99) and followed pseudo-second-order kinetics, indicating a consistent agreement. Positive values for ΔHo (61.23 KJ/mol) and ΔSo (239.80 J/mol. K) suggest an endothermic adsorption process with a strong affinity for dye molecules. Overall, the synthesized material exhibits significant potential for effectively removing toxic dyes from wastewater.
Validation of the Chinese Version of the Revised Community Advancing Resilience Toolkit (CART) Survey Instrument: Evidence from Three Chinese Provinces
Authors: Yan Cunling , Zhang Ning , Ning Ning , Liu Ying , Wang Bingjie , Liu Xiaoyu , Sun Caihong , Tang Yunli , Qi Yue , Yu Bingyan , Zhang Luhao 
Published: January 2024

Abstract

Background Reliable and valid instruments are essential to understand and enhance community resilience in China, especially after the COVID-19 pandemic. This study analyzed the psychometric properties of the Chinese version of the Communities Advancing Resilience Toolkit (CART-C), in order to provide a measurement that can further enhance community resilience in China. Methods A cross-sectional data was collected from three provinces of China from November to December 2022 using an online platform for questionnaire surveys. The total of 1,936 valid questionnaires were collected. Internal consistency reliability and convergent and discriminant validity were assessed, and confirmatory factor analysis was performed. Results The results showed the CART-C had adequate internal consistency, with the sub-scales and total scale presenting with good reliability values (Cronbach’s alpha coefficients ranged from 0.819 to 0.886 and 0.960, respectively), and the results of confirmatory factor analysis showed that adequate fit to data, yielding a 24-item, five-factor structure (all intercorrelated) as follows: χ2/df = 2.812, comparative fit index = 0.992, goodness-of-fit index = 0.981, Tucker-Lewis index = 0.989, Adjusted goodness-of-ft index(AGFI) = 0.973, and root mean square error of approximation = 0.027. Conclusion The findings suggest that CART-C is a valid and reliable measure to assess community resilience and will be useful in policy making for community preparedness for disaster events.
Accurate and efficient boundary method for isogeometric shape design sensitivity analysis considering tangential divergence of non-smooth boundary
Authors: Ko Keun-Hyeong , Kim Hyun-Seok , Cho Seonho 
Published: January 2024

Abstract

Even though the conventional finite element analysis (FEA) based boundary method for shape design sensitivity analysis (DSA) has the advantage of low computation costs, the accuracy of computed sensitivity is not satisfactory due to the inaccurate consideration of boundary geometry. To overcome this difficulty, employing an efficient adjoint method, we propose an isogeometric analysis (IGA) based boundary method for shape DSA that can exactly handle the normal and curvature on a non-smooth boundary. The required computational costs for the boundary method is much less than that of the domain method since the computation is performed only on the boundary. Furthermore, the shape sensitivity of performance measure defined by a boundary functional on the non-smooth boundary can be precisely obtained using the curvature of boundary, the normal component of design velocity, and the tangential divergence of design velocity. Through numerical examples, the accuracy and efficiency of the IGA-based boundary method for DSA are compared with other methods such as FEA-based boundary and domain methods. It is demonstrated that the IGA-based shape design sensitivity of the boundary functional could accurately represent the tangential divergence on the boundary that the linear shape function in the FEA-based one cannot properly represent.
Adequate Completion of Radiology Request Forms: A clinical Audit at Managil Teaching Hospital, Sudan
Authors: Muhammed Abubakr Elsadig Musa , Babiker Mohammed Abdurhman Minallah , AlKheder Mohammed Alsiddig , Awad Mustafa Sabir Abakar 
Published: January 2024

Abstract
Background
Clinical auditing is a technique used to enhance the quality of patient treatment, which involves the thorough examination of a request form. Radiology request forms are essential instruments for facilitating communication between the referring clinician and the radiologist/radiographer.
Objectives
To evaluate the radiology request form and improve the request form content and design at Managil Teaching Hospital, Sudan.
Methods
A retrospective, prospective observational study conducted at Managil Teaching Hospital and three adjacent private radiology clinics. A total of 100 request forms were gathered and compared to the Royal College of Radiologist (RCR) standard structured form, a second cycle was done in which a ready request form was administered. The data were entered to Microsoft Excel 2016 and data were analyzed accordingly then the results were compared to the RCR Standard.
Results
A total of 100 sample were included in the study, 50 in the 1st cycle and 50 in the 2nd cycle. In the first cycle the samples were collected from the radiology department and a 50 request form were compared with the standard. The second cycle included 50 samples and the collected request form were compared with the RCR standards. A significant improving was observed in most areas, for instance the patient’s age was only written in 13% of the request forms in the 1st cycle and 92% in the 2nd cycle.
Conclusion
A significant proportion of radiology request forms are incomplete but after the 2nd cycle of the audit there was massive improvement regarding adequate filling of the radiology request forms. which will aid in effectively diagnosing patients.