bluuebunny/crossref_metadata_2025_split huggingface dataset:
Triple tandem trimer immunogens for HIV-1 and influenza nucleic acid-based vaccines
Authors: del Moral-Sánchez Iván , Wee Edmund G. , Xian Yuejiao , Lee Wen-Hsin , Allen Joel D. , Torrents de la Peña Alba , Fróes Rocha Rebeca , Ferguson James , León André N. , Koekkoek Sylvie , Schermer Edith E. , Burger Judith A. , Kumar Sanjeev , Zwolsman Robby , Brinkkemper Mitch , Aartse Aafke , Eggink Dirk , Han Julianna , Yuan Meng , Crispin Max , Ozorowski Gabriel , Ward Andrew B. , Wilson Ian A. , Hanke Tomáš , Sliepen Kwinten , Sanders Rogier W. 
Published: April 2024

AbstractRecombinant native-like HIV-1 envelope glycoprotein (Env) trimers are used in candidate vaccines aimed at inducing broadly neutralizing antibodies. While state-of-the-art SOSIP or single-chain Env designs can be expressed as native-like trimers, undesired monomers, dimers and malformed trimers that elicit non-neutralizing antibodies are also formed, implying that these designs could benefit from further modifications for gene-based vaccination approaches. Here, we describe the triple tandem trimer (TTT) design, in which three Env protomers are genetically linked in a single open reading frame and express as native-like trimers. Viral vectored Env TTT induced similar neutralization titers but with a higher proportion of trimer-specific responses. The TTT design was also applied to generate influenza hemagglutinin (HA) trimers without the need for trimerization domains. Additionally, we used TTT to generate well-folded chimeric Env and HA trimers that harbor protomers from three different strains. In summary, the TTT design is a useful platform for the design of HIV-1 Env and influenza HA immunogens for a multitude of vaccination strategies.
Large language model enhanced corpus of CO2 reduction electrocatalysts and synthesis procedures
Authors: Chen Xueqing , Gao Yang , Wang Ludi , Cui Wenjuan , Huang Jiamin , Du Yi , Wang Bin 
Published: April 2024

AbstractCO2 electroreduction has garnered significant attention from both the academic and industrial communities. Extracting crucial information related to catalysts from domain literature can help scientists find new and effective electrocatalysts. Herein, we used various advanced machine learning, natural language processing techniques and large language models (LLMs) approaches to extract relevant information about the CO2 electrocatalytic reduction process from scientific literature. By applying the extraction pipeline, we present an open-source corpus for electrocatalytic CO2 reduction. The database contains two types of corpus: (1) the benchmark corpus, which is a collection of 6,985 records extracted from 1,081 publications by catalysis postgraduates; and (2) the extended corpus, which consists of content extracted from 5,941 documents using traditional NLP techniques and LLMs techniques. The Extended Corpus I and II contain 77,016 and 30,283 records, respectively. Furthermore, several domain literature fine-tuned LLMs were developed. Overall, this work will contribute to the exploration of new and effective electrocatalysts by leveraging information from domain literature using cutting-edge computer techniques.
Vectorized dataset of silted land formed by check dams on the Chinese Loess Plateau
Authors: Zeng Yi , Jing Tongge , Xu Baodong , Yang Xiankun , Jian Jinshi , Zong Renjie , Wang Bing , Dai Wei , Deng Lei , Fang Nufang , Shi Zhihua 
Published: April 2024

AbstractCheck dams on the Chinese Loess Plateau (CLP) have captured billions of tons of eroded sediment, substantially reducing sediment load in the Yellow River. However, uncertainties persist regarding the precise sediment capture and the role of these dams in Yellow River flow and sediment dynamics due to the lack of available spatial distribution datasets. We produced the first vectorized dataset of silted land formed by check dams on the CLP, combining high-resolution and easily accessible Google Earth images with object-based classification methods. The accuracy of the dataset was verified by 1947 collected test samples, and the producer’s accuracy and user’s accuracy of the dam lands were 88.9% and 99.5%, respectively. Our dataset not only provides fundamental information for accurately assessing the ecosystem service functions of check dams, but also helps to interpret current changes in sediment delivery of the Yellow River and plan future soil and water conservation projects.
A novel approach towards web browser using the concept of a complex spherical fuzzy soft information
Authors: Shao Wenkai , Hussain Shoukat , Khan Sami Ullah , Awwad Fuad A. , Ismail Emad A. A. 
Published: April 2024

AbstractThe modern technology is the practical application of scientific knowledge, whether in industry or daily life, for goals or purposes. More quickly than any other technological advancement in human history, digital technologies have advanced. The technology sector is expanding and provides both new educational opportunities and innovative, exciting products. Right now, one of the most widely used and fascinating technologies is the web browser. This article introduced the novel concepts of complex spherical fuzzy soft relations (CSFSRs) by using the Cartesian Product (CP) of two complex spherical fuzzy soft sets (CSFSSs). Additionally, examples are used to clarify various types of relations. Because it discusses all levels of membership, abstinence, and non-membership with multidimensional variables, the CSFSRs have a detailed structure. The CSFSR-based modelling tools developed in this research, which primarily rely on the score function, can be used to choose the best Web browser. The transaction could be as easy as users sharing records via a functional web browser. Finally, the advantages of this suggested structure are illustrated by contrasting it with alternative structures.
Biochar aided priming of carbon and nutrient availability in three soil orders of India
Authors: Purakayastha T. J. , Bera Tanumoy , Dey Saptaparnee , Pande Pooja , Kumari Savita , Bhowmik Arpan 
Published: April 2024

AbstractIn recent years biochar (BC) has gained importance for its huge carbon (C) sequestration potential and positive effects on various soil functions. However, there is a paucity of information on the long-term impact of BC on the priming effect and nutrient availability in soil with different properties. This study investigates the effects of BC prepared from rice husk (RBC4, RBC6), sugarcane bagasse (SBC4, SBC6) and mustard stalk (MBC4, MBC6) at 400 and 600 °C on soil C priming and nitrogen (N), phosphorus (P), and potassium (K) availability in an Alfisol, Inceptisol, and Mollisol. BC properties were analyzed, and its decomposition in three soil orders was studied for 290 days in an incubation experiment. Post-incubation, available N, P, and K in soil were estimated. CO2 evolution from BC and soil alone was also studied to determine the direction of priming effect on native soil C. Increasing pyrolysis temperature enhanced pH and EC of most of the BC. The pyrolysis temperature did not show clear trend with respect to priming effect and nutrient availability across feedstock and soil type. MBC6 increased C mineralization in all the soil orders while RBC6 in Alfisol and SBC6 in both Inceptisol and Mollisol demonstrated high negative priming, making them potential amendments for preserving native soil C. Most of the BC showed negative priming of native SOC in long run (290 days) but all these BC enhanced the available N, P, and K in soil. SBC4 enhanced N availability in Alfisol and Inceptisol, RBC4 improved N and P availability in Mollisol and P in Alfisol and MBC6 increased K availability in all the soils. Thus, based on management goals, tailored BC or blending different BC can efficiently improve C sequestration and boost soil fertility.
Plackett–Burman screening of physico-chemical variables affecting Citrus peel-mediated synthesis of silver nanoparticles and their antimicrobial activity
Authors: Mickky Bardees , Elsaka Heba , Abbas Muhammad , Gebreil Ahmed , Eldeen Reham Shams 
Published: April 2024

AbstractWith the growing resistance of pathogenic microbes to traditional drugs, biogenic silver nanoparticles (SNPs) have recently drawn attention as potent antimicrobial agents. In the present study, SNPs synthesized with the aid of orange (Citrus sinensis) peel were engineered by screening variables affecting their properties via Plackett–Burman design. Among the variables screened (temperature, pH, shaking speed, incubation time, peel extract concentration, AgNO3 concentration and extract/AgNO3 volume ratio), pH was the only variable with significant effect on SNPs synthesis. Therefore, SNPs properties could be enhanced to possess highly regular shape with zeta size of 11.44 nm and zeta potential of − 23.7 mV. SNPs purified, capped and stabilized by cloud point extraction technique were then checked for their antimicrobial activity against Bacillus cereus, Listeria innocua, Listeria monocytogenes, Staphylococcus aureus, Enterobacter cloacae, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella typhimurium and Candida albicans. The maximum antimicrobial activity of SNPs was recorded against E. coli, L. monocytogenes and C. albicans with clear zone diameter of 33.2, 31.8 and 31.7 mm, respectively. Based on minimum inhibition concentration and minimum bactericidal concentration of SNPs (300 mg/l) as well as their effect on respiratory chain dehydrogenases, cellular sugar leakage, protein leakage and lipid peroxidation of microbial cells, E. coli was the most affected. Scanning electron microscopy, protein banding and DNA fragmentation proved obvious ultrastructural and molecular alterations of E. coli treated with SNPs. Thus, biogenic SNPs with enhanced properties can be synthesized with the aid of Citrus peel; and such engineered nanoparticles can be used as potent antimicrobial drug against E. coli.
A new type of C+⋯Hδ−(C=) bond in adducts of vinyl carbocations with alkenes
Authors: Stoyanov Evgenii S. , Bagryanskaya Irina Yu. , Stoyanova Irina V. 
Published: April 2024

AbstractBy X-ray diffraction analysis and IR spectroscopy, it was established here that vinyl carbocations C3H5+/C4H7+ with carborane counterion CHB11Cl11− form stable monosolvates C3H5+⋅C3H6/C4H7+⋅C4H8 with molecules of alkenes C3H6/C4H8. They contain molecular group =C+⋯Hδ−–Cδ+= with a new type of bond formed by the H atom of the H–C= group of the alkene with the C atom of the C+=C group of the carbocation. The short C+----Cδ+ distance, equal to 2.44 Å, is typical of that of X----X in proton disolvates (L2H+) with an quasi-symmetrical X–H+⋯X moiety (where X = O or N) of basic molecule L. The nature of the discovered bond differs from that of the classic H–bond by an distribution of electron density: the electron–excessive Hδ− atom from the (=)C–H group of the alkene is attached to the C+ atom of the carbocation, on which the positive charge is predominantly concentrated. Therefore, it can be called an inverse hydrogen bond.
Hibiscus manihot L. flower extract induces anticancer activity through modulation of apoptosis and autophagy in A549 cells
Authors: Xu Minglu , Zhao Mengxia , Zhu Miaomiao , Yuan Hongmei , Li Zhongzheng , Yan Peishuo , Ma Chi , Zhao Huabin , Wang Shenghui , Wan Ruyan , Wang Lan , Yu Guoying 
Published: April 2024

AbstractLung cancer is a major public health issue and heavy burden in China and worldwide due to its high incidence and mortality without effective treatment. It’s imperative to develop new treatments to overcome drug resistance. Natural products from food source, given their wide-ranging and long-term benefits, have been increasingly used in tumor prevention and treatment. This study revealed that Hibiscus manihot L. flower extract (HML) suppressed the proliferation and migration of A549 cells in a dose and time dependent manner and disrupting cell cycle progression. HML markedly enhanced the accumulation of ROS, stimulated the dissipation of mitochondrial membrane potential (MMP) and that facilitated mitophagy through the loss of mitochondrial function. In addition, HML induced apoptosis by activation of the PTEN-P53 pathway and inhibition of ATG5/7-dependent autophagy induced by PINK1-mediated mitophagy in A549 cells. Moreover, HML exert anticancer effects together with 5-FU through synergistic effect. Taken together, HML may serve as a potential tumor prevention and adjuvant treatment for its functional attributes.
Distress and neuroticism as mediators of the effect of childhood and adulthood adversity on cognitive performance in the UK Biobank study
Authors: Pflanz Chris Patrick , Künzi Morgane , Gallacher John , Bauermeister Sarah 
Published: April 2024

AbstractChildhood adversity and adulthood adversity affect cognition later in life. However, the mechanism through which adversity exerts these effects on cognition remains under-researched. We aimed to investigate if the effect of adversity on cognition was mediated by distress or neuroticism. The UK Biobank is a large, population-based, cohort study designed to investigate risk factors of cognitive health. Here, data were analysed using a cross-sectional design. Structural equation models were fitted to the data with childhood adversity or adulthood adversity as independent variables, distress and neuroticism as mediators and executive function and processing speed as latent dependent variables that were derived from the cognitive scores in the UK Biobank. Complete data were available for 64,051 participants in the childhood adversity model and 63,360 participants in the adulthood adversity model. Childhood adversity did not show a direct effect on processing speed. The effect of childhood adversity on executive function was partially mediated by distress and neuroticism. The effects of adulthood adversity on executive function and processing speed were both partially mediated by distress and neuroticism. In conclusion, distress and neuroticism mediated the deleterious effect of childhood and adulthood adversity on cognition and may provide a mechanism underlying the deleterious consequences of adversity.
Trend and projection of non-communicable diseases risk factors in Iran from 2001 to 2030
Authors: Farzadfar Farshad , Yousefi Moein , Jafari-Khounigh Ali , Khorrami Zahra , Haghdoost AliAkbar , Shadmani Fatemeh Khosravi 
Published: April 2024

AbstractThis study aims to investigate the trends and project the major risk factors of Non-communicable Diseases (NCDs) in Iran. We obtained the trend of prevalence of main risk factors related to NCDs in 30 to 70-year-old-individuals. The data were extracted from WHO STEP wise approach to NCDs risk factor surveillance (STEPS) survey. Also,the previous studies conducted at national and subnational levels from 2001 to 2016 were employed. The prevalence of risk factors was projected by 2030 using Bayesian Model Averaging (BMA) and Spatio-temporal model stratified by sex and province. The percent change for the age-standardized prevalence of smoking in men between 2001 and 2016 was calculated to be − 27.0. Also, the corresponding values for the risk factors of diabetes, hypertension, obesity and overweight, physical inactivity (PI), and mean of salt intake were − 26.1, 29.0, 70.0, 96.8, 116.6, and 7.5, respectively. It is predicted that smoking and these risk factors will undergo a change to show values of − 1.26, 38.7, 43.7, 2.36, and 15.3 by 2030, respectively. The corresponding values in women for the time interval of 2001–2016 were − 27.3, 26.3, 82.8, 1.88, 75.2, and 4.2, respectively. Plus, projections indicate that the 2030 variation values are expected to be − 25.0, 16.7, 37.5, 28.7, 26.7, and 10.9 respectively. This study showed that the prevalence of four risk factors of PI, overweight and obesity, hypertension, and diabetes is increasing in Iran. Therefor, it is necessary to carry out effective interventions to adopt a healthy lifestyle and reduce the risk factors.
Physical and structural characterization of bis-acryl composite resin
Authors: Rodríguez-Guardado Wendy E. , Rivera-Muñoz Eric M. , Serrano-Bello Janeth , Alvarez-Perez Marco A. , Domínguez-Pérez Rubén A. , Salmerón-Valdés Elias Nahum , Vázquez Vázquez Febe C. , Chanes-Cuevas Osmar A. , Millán-Malo Beatriz , Peza-Ledesma Carmen L. , Correa-Prado Rodrigo 
Published: April 2024

AbstractDuring the preparation of fixed prosthesis (including individual bridges and crowns) it is important to select the materials that have the best features and properties to predict a successful clinical treatment. The objective of this study was to determine if the chemical and structural characteristics could cause to increase the fracture resistance, we used four bis-acryl resins Luxatemp, Protemp, Structur and Telio. Three-points bending by Flexural test were performed in ten bars and they were carried out to compare with Anova test. In addition, the bis-acryl resins were analyzed by scanning electron microscopy, to analyze microstructure and morphology and the molecular structure were performed by Infrared Spectroscopy through Attenuated Total Reflectance. A higher flexural strength was found in Luxatemp and Structur with, no significant differences between this study groups. Regarding Protemp and Telio, these study groups showed a lower flexural strength when were compared with Luxatemp and Structur. These results corroborate SEM and ATR analysis because Luxatemp sample showed a regular size particle on the surface and chemically presents a long cross-linkage polymer chain. The presence of CO3, SiO2 and N–H groups as a fillers particle interacting with OH groups cause a higher flexural strength compared with another groups.
Utilizing direct and indirect information to improve the COVID-19 vaccination booster scheduling
Authors: Dery Yotam , Yechezkel Matan , Ben-Gal Irad , Yamin Dan 
Published: April 2024

AbstractCurrent global COVID-19 booster scheduling strategies mainly focus on vaccinating high-risk populations at predetermined intervals. However, these strategies overlook key data: the direct insights into individual immunity levels from active serological testing and the indirect information available either through sample-based sero-surveillance, or vital demographic, location, and epidemiological factors. Our research, employing an age-, risk-, and region-structured mathematical model of disease transmission—based on COVID-19 incidence and vaccination data from Israel between 15 May 2020 and 25 October 2021—reveals that a more comprehensive strategy integrating these elements can significantly reduce COVID-19 hospitalizations without increasing existing booster coverage. Notably, the effective use of indirect information alone can considerably decrease COVID-19 cases and hospitalizations, without the need for additional vaccine doses. This approach may also be applicable in optimizing vaccination strategies for other infectious diseases, including influenza.
Automatic identification of incidents involving potential serious injuries and fatalities (PSIF)
Authors: Parikh Pulkit , Penfield Julia , Juaire Marc 
Published: April 2024

AbstractSafety incidents have always been a crucial risk in work spaces, especially industrial sites. In the last few decades, significant efforts have been dedicated to incident control measures to reduce the rate of safety incidents. Despite all these efforts, the rate of decline in serious injuries and fatalities (SIFs) has been considerably lower than the rate of decline for non-critical incidents. This observation has led to a change of risk reduction paradigm for safety incidents. Under the new paradigm, more focus has been allocated to reducing the rate of critical/SIF incidents, as opposed to reducing the count of all incidents. One of the challenges in reducing the number of SIF incidents is the proper identification of the risk prior to materialization. One of the reasons for risk identification being a challenge is that companies usually only focus on incidents where SIF did occur reactively, and incidents that did not cause SIF but had the potential to do so go unnoticed. Identifying these potentially significant incidents, referred to as potential serious injuries and fatalities (PSIF), would enable companies to work on identifying critical risk and taking steps to prevent them preemptively. However, flagging PSIF incidents requires all incident reports to be analyzed individually by experts and hence significant investment, which is often not affordable, especially for small and medium sized companies. This study is aimed at addressing this problem through machine learning powered automation. We propose a novel approach based on binary classification for the identification of such incidents involving PSIF (potential serious injuries and fatalities). This is the first work towards automatic risk identification from incident reports. Our approach combines a pre-trained transformer model with XGBoost. We utilize advanced natural language processing techniques to encode an incident record comprising heterogeneous fields into a vector representation fed to XGBoost for classification. Moreover, given the scarcity of manually labeled incident records available for training, we leverage weak labeling to augment the label coverage of the training data. We utilize the F2 metric for hyperparameter tuning using Tree-structured Parzen Estimator to prioritize the detection of PSIF records over the avoidance of non-PSIF records being mis-classified as PSIF. The proposed methods outperform several baselines from other studies on a significantly large test dataset.
Performance optimization of interleaved boost converter with ANN supported adaptable stepped-scaled P&O based MPPT for solar powered applications
Authors: Krishnaram K. , Padmanabhan T. Suresh , Alsaif Faisal , Senthilkumar S. 
Published: April 2024

AbstractSolar energy is the most promising among many renewable energy sources to meet the increasing demand. Photovoltaic (PV) based power generating solutions are expected to gain popularity as a power source for different applications, including independent and grid connected loads, due to their cleanliness, high performance, and high dependability. The efficacy of photovoltaic systems is impacted by several elements, including geographical location, positioning, shadowing effects, and local climate conditions. In order to fulfil the demands of loads, an interleaved boost converter is utilized, which has a reduced number of filters with less stress on the devices. Solar powered systems employ several maximum power point tracking (MPPT) methodologies. However, when there is partial shading, many power peaks arise, which complicates the identification of the overall peak. Although MPPT approaches are designed to measure and maintain the global maximum power point (GMPP), there are still significant oscillations observed around the GMPP with subpar settling time, tracking efficiency, and conversion efficiency. In this work, novel hybrid MPPT technique called artificial neural network supported adaptable stepped-scaled perturb and observe (ANN-ASSPO) method and water cycle optimization based perturb and observe (WCO-PO) have been proposed. Artificial neural network (ANN) has been used to determine the best scaling factor in ANN-ASSPO MPPT. Performance is enhanced in ANN-ASSPO MPPT by using the optimum scaling factor, particularly in situations when the irradiance is rapidly changing/partial shading conditions. Similarly, in WCO-PO MPPT water cycle optimization is used to determine the peak power when the PV panel is subjected to partial shading conditions. The performances of proposed hybrid MPPT ANN-ASSPO and WCO-PO techniques have been compared in terms of power generated, output voltage, average settling time and conversion efficiency. The MATLAB/Simulink tool is employed to carry out the experiment for this study.