bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing Seed‐Induced Nucleation for Enhanced Al(OH)3 Crystal Precipitation from Supersaturated Potassium Aluminate Solution
Authors: Liu Chenglin , Xue Jin , Fang Xiaoning , Luo Mengjie 
Published: July 2024

AbstractPotassium alunite is a potential mineral resource of potassium and aluminum that can serve as a valuable resource. An effective potassium and aluminum recovery method is developed using gradient leaching with a KOH sub‐molten salt. The key part of this process is seeded precipitation of the potassium aluminate leach solution. Therefore, this study aims to optimize the seeded precipitation process by investigating the effects of alkali concentration, molecular ratio, stirring rate, temperature, and seed coefficient on the precipitation ratio and particle size of Al(OH)3. The results show that alkali concentration, molecular ratio, temperature, and seed coefficient are key factors influencing seeded precipitation. Furthermore, the process is optimized by using these four identified factors as variables. A 9L(34) orthogonal experiment determines optimal conditions for maximizing the precipitation ratio and achieves the desired average particle size. Under the optimal condition of 200 g L−1 alkali concentration, 1.5 molecular ratio, 1.0 seed coefficient, and 343.15 K temperature, the precipitation ratio reaches 54% and the average Al(OH)3 particle size is 114 µm. Further work is required to scale up this optimized seeded precipitation process and evaluate applications of the Al(OH)3 product.
Population size and structure of beisa oryx and gerenuk in Geralle National Park, southeastern Ethiopia
Authors: Aychew Melkamu , Girma Zerihun 
Published: July 2024

AbstractThe study was conducted to determine the population size of endangered Oryx beisa (Rüppell, 1835), and near‐threatened Litocranius walleri (Brooke, 1878) of uncertain global population estimates in Geralle National Park, southeastern Ethiopia. Systematic line transects were established with a transect length range of 2.3 to 6.8 km long (a total of 165.4 km long with a sighting distance of 150 m after truncation). The combination of AIC and chi‐square p‐values was used as model selection criteria for density/population size estimation in distance sampling software. The lowest AIC, ∆AIC (close to zero), and Chi‐square tests (p‐value > .05) were selected with adequate model fit. The minimum observation was 67 individuals of beisa oryx in the dry season. The maximum observation was 349 individuals of gerenuk during the wet season. The minimum detection probability of oryx was in the wet season (pâ = 76 ± 26), and the minimum detection probability of gerenuk was (pâ = 75 ± 1) in both seasons. The two‐season pooled density analyzed for studied species indicated (0.85 ± 0.34, 1.24 ± 0.47, beisa oryx/km2), and (3.82 ± 0.6, 4.88 ± 0.7 gerenuk/km2) in dry and wet seasons, respectively. It can be concluded from the results of the study that GNP is home to previously undiscovered healthy populations of the endangered beisa oryx and near‐threatened gerenuk. So it is recommended to undergo in‐depth population studies, including other species available in the national park and their habitat components, so as to design sound, sustainable conservation measures for the wildlife resources in the area.
Thirty years of forest productivity in a mountainous landscape: The Yin and Yang of topography
Authors: Perry David A. , Oetter Doug R. 
Published: July 2024

AbstractWe measured light‐related patterns of primary productivity within a topographically complex Oregon watershed over a 30‐year period. Second‐growth conifer densities were experimentally altered in 1981. Plots receiving at least 3434 MJ m−2 over a 6‐month growing season averaged 40% greater aboveground net primary productivity (ANPP) than those receiving less light (p = 0.000). Unthinned stands potentially built enough LAI to compensate for low light, but risked mortality that exceeded resilience. The two light levels acted as basins of attraction for other physiological and ecological processes, including size–density relationships and limiting foliar nutrients. Initial (1981) LAI and the irradiation step (above or below 3434 MJ m−2) explained 60% of variation in a 30‐year ANPP. Irradiation within each light group did not affect ANPP. At high irradiation, foliar N/Ca and slope steepness (both negative) explained 58% of the variation in residuals from the initial models, while at low irradiation on north, east, and west aspects, 83% of residual variation was explained by foliar Mg (+), understory cover (+), and 30‐year mortality (−). Light use efficiency (LUE) of fully stocked stands correlated with LAI and foliar N/K. Results suggest that understory influence on tree foliar N (+ or −) enhances ANPP by regulating critical nutrient ratios. Mortality reduced or eliminated differences among thinning levels, which did not vary at low light and only between unthinned and heavily thinned at high light. Values associated with relatively open forests (biodiversity, resilience) may be attained without large sacrifice of long‐term carbon sinks. In our study, light interacts with topography to produce nonlinear dynamics in which small changes in irradiation can have large consequences. Reduced sunlight has been suggested as a geoengineering option to combat global warming. Ecological changes out of proportion to lowered irradiation are a distinct possibility, including sharp reductions in terrestrial carbon sinks.
A test of the gleaner–opportunist trade‐off among photosynthetic traits in cryptophyte algae
Authors: Swanson Jake A. , Greenwold Matthew J. , Richardson Tammi L. , Dudycha Jeffry L. 
Published: July 2024

AbstractAs photosynthetic producers, phytoplankton form the foundation of aquatic food webs. Understanding the relationships among photosynthetic traits in phytoplankton is essential to revealing how diversification of these traits allows phytoplankton to harvest energy from different light environments. We investigated whether the diversification of 15 species of cryptophytes, a phylum of phytoplankton with diverse light‐capturing pigments, showed evidence of trade‐offs among photosynthetic performance traits as predicted by the gleaner–opportunist resource exploitation framework. We constructed photosynthesis versus irradiance (P–E) curves and rapid light curves (RLCs) to estimate parameters characterizing photosynthetic performance and electron transport rate. We inferred the evolutionary relationships among the 15 species with ultraconserved genomic elements and used a phylogenetically controlled approach to test for trade‐offs. Contrary to our prediction, we observed a positive correlation between maximum photosynthetic rate, Pmax, and P–E , an indicator of a species' sensitivity to increases in light intensity when light is a scarce resource. This result could not be explained by electron transfer traits, which were uncorrelated with photosynthetic rate. Together, our results suggest that ecological diversification of light exploitation in cryptophytes has escaped the constraints of a gleaner–opportunist trade‐off. Photosynthetic trade‐offs may be context‐ or scale‐dependent, thereby only emerging when investigated in situations different from the one used here.
Assessing the genotoxicity of N‐nitrosodiethylamine with three in vivo endpoints in male Big Blue® transgenic and wild‐type C57BL/6N mice
Authors: Zhang Shaofei , Coffing Stephanie L. , Gunther William C. , Homiski Michael L. , Spellman Richard A. , Van Phu , Schuler Maik 
Published: July 2024

AbstractThe detection of N‐nitrosamines in drug products has raised global regulatory interest in recent years due to the carcinogenic potential of some nitrosamines in animals and a need to identify a testing strategy has emerged. Ideally, methods used would allow for the use of quantitative analysis of dose–response data from in vivo genotoxicity assays to determine a compound‐specific acceptable intake for novel nitrosamines without sufficient carcinogenicity data. In a previous study we compared the dose–response relationships of N‐nitrosodiethylamine (NDEA) in three in vivo genotoxicity endpoints in rats. Here we report a comparison of NDEA's genotoxicity profile in mice. Big Blue® mice were administered NDEA at doses of 0.001, 0.01, 0.1, 1 and 3 mg/kg/day by oral gavage for 28 days followed by 3 days of expression. Statistically significant increases in the NDEA induced mutations were detected by both the transgenic rodent mutation assay (TGR) using the cII endpoint and by duplex sequencing in the liver but not bone marrow of mice. In addition, administration of NDEA for two consecutive days in male C57BL/6N mice caused elevated DNA damage levels in the liver as measured by % tail DNA in comet assay. The benchmark dose (BMD) analysis shows a BMDL50 of 0.03, 0.04 and 0.72 mg/kg/day for TGR, duplex sequencing and comet endpoints, respectively. Overall, this study demonstrated a similar genotoxicity profile of NDEA between mice and rats and provides a reference that can be used to compare the potential potency of other novel nitrosamines for the induction of gene mutations.
Conventional and artificial intelligence based maximum power point tracking techniques for efficient solar power generation
Authors: Khan Malhar , Raza Muhammad Amir , Faheem Muhammad , Sarang Shahjahan Alias , Panhwar Madeeha , Jumani Touqeer Ahmed 
Published: July 2024

AbstractThe increasing global need for renewable energy sources, driven by environmental concerns and the limited availability of traditional energy, highlights the significance of solar energy. However, weather fluctuations challenge the efficiency of solar systems, making maximum power point tracking (MPPT) systems crucial for optimal energy harvesting. This study compares ten MPPT approaches, including both conventional and artificial intelligence (AI)‐based techniques. These controllers were designed and implemented using MATLAB Simulink, and their performance was evaluated under real environmental conditions with fluctuating irradiance and temperature. The results demonstrate that conventional techniques, such as incremental conductance (INC), Perturb and Observe (P&O), Incremental conductance and Particle Swam Optimization (INC‐PSO), Fuzzy Logic Control and Particle Swam Optimization (FLC‐PSO), and Perturb and Observe and Particle Swam Optimization (P&O‐PSO), achieved accuracies of 94%, 97.6%, 98.9%, 98.7%, and 99.3% respectively. In contrast, AI‐based intelligent techniques, including Artificial Neural Network (ANN), Artificial Neural Fuzzy Interference System (ANFIS), Fuzzy Logic Control (FLC), Particle Swam Optimization (PSO), and Artificial Neural Network and Particle Swam Optimization (ANN‐PSO), outperform achieving higher accuracies of 97.8%, 99.9%, 98.9%, 99.2%, and 99%, respectively. Compared to available research, which often reports lower accuracies for conventional techniques, our study highlights the enhanced performance of AI‐based methods. This study provides a comprehensive comparative analysis, delivering critical analysis and practical guidance for engineers and researchers in selecting the most effective MPPT controller optimized to specific environmental conditions. By improving the efficiency and reliability of solar power systems, our research supports the advancement of sustainable energy solutions.
Incorporation of natural and synthetic polymers into honey hydrogel for wound healing: A review
Authors: Chin Siau Wui , Azman Adzzie‐Shazleen , Tan Ji Wei 
Published: July 2024

AbstractBackground and AimsThe difficulty in treating chronic wounds due to the prolonged inflammation stage has affected a staggering 6.5 million people, accompanied by 25 billion USD annually in the United States alone. A 1.9% rise in chronic wound prevalence among Medicare beneficiaries was reported from 2014 to 2019. Besides, the global wound care market values were anticipated to increase from USD 20.18 billion in 2022 to USD 30.52 billion in 2030, suggesting an expected rise in chronic wounds financial burdens. The lack of feasibility in using traditional dry wound dressings sparks hydrogel development as an alternative approach to tackling chronic wounds. Since ancient times, honey has been used to treat wounds, including burns, and ongoing studies have also demonstrated its wound‐healing capabilities on cellular and animal models. However, the fluidity and low mechanical strength in honey hydrogel necessitate the incorporation of other polymers. Therefore, this review aims to unravel the characteristics and feasibility of natural (chitosan and gelatin) and synthetic (polyvinyl alcohol and polyethylene glycol) polymers to be incorporated in the honey hydrogel.MethodsRelevant articles were identified from databases (PubMed, Google Scholar, and Science Direct) using keywords related to honey, hydrogel, and polymers. Relevant data from selected studies were synthesized narratively and reported following a structured narrative format.ResultsThe importance of honey's roles and mechanisms of action in wound dressings were discussed. Notable studies concerning honey hydrogels with diverse polymers were also included in this article to provide a better perspective on fabricating customized hydrogel wound dressings for various types of wounds in the future.ConclusionHoney's incapability to stand alone in hydrogel requires the incorporation of natural and synthetic polymers into the hydrogel. With this review, it is hoped that the fabrication and commercialization of the desired honey composite hydrogel for wound treatment could be brought forth.
Gestational weight gain as a mediator of the relationship between pre‐pregnancy body mass index and the risk of preterm birth: A four‐way decomposition analysis
Authors: Niknam Atrin , Behboudi‐Gandevani Samira , Rahmati Maryam , Firouzi Faegheh , Azizi Fereidoun , Ramezani Tehrani Fahimeh 
Published: July 2024

AbstractObjectiveThe aim of the present study was to examine and quantify whether the association between preterm birth (PTB) and pre‐pregnancy body mass index (BMI) is mediated by gestational weight gain (GWG).MethodsThis is a secondary analysis of a large randomized community non‐inferiority trial using a cohort design. The data of 26 101 pregnant women in their first trimester who sought prenatal care and met eligibility criteria were included. The four‐way decomposition method was applied to screen for all types of association effects of pre‐pregnancy BMI on the risk of PTB. These effects include the total, direct, and various indirect effects including pure mediation via GWG, interactive effects with GWG, and mediated interaction with GWG, all adjusted for potential confounders.ResultsAmong the study participants, 24 461 (93.7%) had term deliveries, while 1640 (6.3%) experienced PTB. The results of the study showed that there was a positive association between pre‐pregnancy BMI among those with BMI more than 25 kg/m2 and the risk of PTB and this association was negatively mediated and interacted by GWG, which differed quantitatively between those who had inadequate, adequate, or excessive GWG. The total association effect showed that the risk was lowest for those who had underweight pre‐pregnancy BMI and adequate GWG (excess relative risk [RR]: 0.06, 95% CI: 0.01–0.11, P value: 0.022) and was highest for those who had obese pre‐pregnancy BMI and excessive GWG (excess RR: 0.67, 95% CI: 0.35–1.00, P value <0.001).ConclusionThe findings of the present prospective population‐based study demonstrated that pre‐pregnancy BMI >25 kg/m2 is directly and positively associated with the risk of preterm birth. The highest risk of preterm birth was observed among individuals with an obese pre‐pregnancy BMI who also experienced excessive GWG.
Infusing Weighted Average Ensemble Diversity for Advanced Breast Cancer Detection
Authors: Abhisheka Barsha , Biswas Saroj Kumar , Purkayastha Biswajit 
Published: July 2024

ABSTRACTBreast cancer is a widespread health threat for women globally, often difficult to detect early due to its asymptomatic nature. As the disease advances, treatment becomes intricate and costly, ultimately resulting in elevated fatality rates. Currently, despite the widespread use of advanced machine learning (ML) and deep learning (DL) techniques, a comprehensive diagnosis of breast cancer remains elusive. Most of the existing methods primarily utilize either attention‐based deep models or models based on handcrafted features to capture and gather local details. However, both of these approaches lack the capability to offer essential local information for precise tumor detection. Additionally, the available breast cancer datasets suffer from class imbalance issue. Hence, this paper presents a novel weighted average ensemble network (WA‐ENet) designed for early‐stage breast cancer detection that leverages the ability of ensemble technique over single classifier‐based models for more robust and accurate prediction. The proposed model employs a weighted average‐based ensemble technique, combining predictions from three diverse classifiers. The optimal combination of weights is determined using the hill climbing (HC) algorithm. Moreover, the proposed model enhances overall system performance by integrating deep features and handcrafted features through the use of HOG, thereby providing precise local information. Additionally, the proposed work addresses class imbalance by incorporating borderline synthetic minority over‐sampling technique (BSMOTE). It achieves 99.65% accuracy on BUSI and 97.48% on UDIAT datasets.
Get Things Done: The Commodification of David Bowie in 1983
Authors: Coley Sam 
Published: July 2024

ABSTRACT1983 was a pivotal point in the career of musician David Bowie. It was a time of personal and artistic renewal, which ultimately transformed him from an “eternal outsider” into a global superstar. The 40thanniversary of his landmark 1983 albumLet's Danceprovides an opportunity to consider the business acumen behind the dramatic repositioning of Bowie's brand, and to reevaluate accusations of ‘selling‐out’ and ‘inauthenticity’ in his quest for mainstream international success.
Proteomic profiling of human plasma extracellular vesicles identifies PF4 and C1R as novel biomarker in sarcopenia
Authors: Aparicio Paula , Navarrete‐Villanueva David , Gómez‐Cabello Alba , López‐Royo Tresa , Santamaría Enrique , Fernández‐Irigoyen Joaquín , Ausín Karina , Arruebo Manuel , Sebastian Victor , Vicente‐Rodríguez Germán , Osta Rosario , Manzano Raquel 
Published: July 2024

AbstractBackgroundSarcopenia, the gradual and generalized loss of muscle mass and function with ageing, is one of the major health problems in older adults, given its high prevalence and substantial socioeconomic implications. Despite the extensive efforts to reach consensus on definition and diagnostic tests and cut‐offs for sarcopenia, there is an urgent and unmet need for non‐invasive, specific and sensitive biomarkers for the disease. Extracellular vesicles (EVs) are present in different biofluids including plasma, whose cargo reflects cellular physiology. This work analysed EV proteome in sarcopenia and robust patients in the search for differentially contained proteins that can be used to diagnose the disease.MethodsPlasma small EVs (sEVs) from a total of 29 robust controls (aged 73.4 ± 5.6 years; 11 men and 18 women) and 49 sarcopenic patients (aged 82.3 ± 5.4 years; 15 men and 34 women) aged 65 years and older were isolated and their cargo was analysed by proteomics. Proteins whose concentration in sEVs was different between sarcopenic and robust patients were further validated using ELISA. The concentration of these candidates was correlated to the EWGSOP2 sarcopenia tests for low muscle strength and low physical performance, and receiver operating characteristic (ROC) curve analyses were carried out to evaluate their diagnostic power, sensitivity and specificity.ResultsProteomic analysis identified 157 sEVs proteins in both sarcopenic and robust samples. Among them, 48 proteins had never been reported in the ExoCarta nor Vesiclepedia databases. Statistical analysis revealed eight proteins whose concentration was significantly different between groups: PF4 (log2 FC = 4.806), OIT3 (log2 FC = −1.161), MMRN1 (log2 FC = −1.982), MASP1 (log2 FC = −0.627), C1R (log2 FC = 1.830), SVEP1 (log2 FC = 1.295), VCAN (FC = 0.937) and SPTB (log2 FC = 1.243). Among them, platelet factor 4 (PF4) showed the lowest concentration while Complement C1r subcomponent (C1R) increased the most in sarcopenic patients, being these results confirmed by ELISA (P = 1.07E‐09 and P = 0.001287, respectively). The concentrations of candidate proteins significantly correlated with EWGSOP2 tests currently used. ROC curve analysis showed an area under the curve of 0.8921 and 0.7476 for PF4 and C1R, respectively. Choosing the optimal for PF4, 80% sensitivity and 85.71% specificity was reached while the optimal cut‐off value of C1R would allow sarcopenia diagnosis with 75% sensitivity and 66.67% specificity.ConclusionsOur results support the determination of EV PF4 and C1R as plasma diagnostic biomarkers in sarcopenia and open the door to investigate the role of the content of these vesicles in the pathogeny of the disease.
Pregnant individuals' genetic literacy and decisional conflict about prenatal screening tests: A cross‐sectional study
Authors: Yeşilçinar İlknur , Şahin Eda , Tutar Sadettin Oğuzhan 
Published: July 2024

AbstractUnderstanding the prenatal screening and diagnostic tests performed during pregnancy and making a decision in line with the test results can be a complex process for pregnant individuals and their families. Therefore, this study examined pregnant individuals' genetic literacy and decisional conflict regarding prenatal screening tests. The study was conducted with 328 pregnant individuals who applied to a training and research hospital to receive antenatal care between April 05 and September 30, 2021. Research data were collected by using the “Decisional Conflict Scale,” “SURE Scale,” and “Genetic Literacy and Comprehension Measure.” The mean age of the participants was 28.69 ± 5.48, and the mean gestational week was 25.90 ± 10.43. A statistically significant difference was found between the educational levels of the pregnant individuals and the genetic literacy and comprehension scales (p < 0.001). A statistically significant difference was found between getting information about prenatal screening tests, having a screening test and decisional conflict scale, SURE Scale, and genetic literacy and comprehension scales (p < 0.001). A weak, negative, statistically significant correlation was found between the genetic literacy and comprehension familiarity and decision conflict scales (r = −0.177, p = 0.001). It is well known that pregnant individuals have difficulty understanding and interpreting test results due to prenatal screening tests that include genetic information. In our study, approximately half of the pregnant individuals received information about prenatal screening tests. Therefore, prenatal care must include the necessary information about prenatal screening tests. The study found that as the genetic literacy of pregnant individuals increased, the conflict of decisions they experienced decreased. Accordingly, it is suggested that interventions to increase genetic literacy among pregnant individuals may be effective in reducing decisional conflict regarding prenatal screening tests.