bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sulfophenylated centimeter-size graphene membrane in a direct methanol fuel cell
Authors: Schneider Gregory , Zhang Weizhe , Makurat Max , Liu Xue , Liu Xiaoting , Li Yanglizhi , Kock Thomas , Jiao Andy , Jiang Guangya , Leist Christopher , Maheu Clément , Sezen Hikmet , Calvani Dario , Eren Ismail , Buda Francesco , Qi Haoyuan , Feng Xinliang , Heine Thomas , Kuc Agnieszka , Hofmann Jan , Kaiser Ute , Sun Luzhao , Jiang Lin , Liu Zhongfan 
Published: September 2024

Abstract

An ideal proton exchange membrane should only permeate protons and be leak-tight for fuels. Graphene is impermeable to water and poorly conducting to protons. Next to long-term stability an ideal and optimized proton exchange membrane therefore needs to fulfil two main criteria: proton permeability and selectivity. Within methanol fuel cells, the first ensures a high-power density, while the second prevents fuel cross-over between the electrodes, which deteriorates catalyst performance and, thereby, drastically lowers performance. However, proton conductivity and selectivity are antagonistic in polymer membranes concerning their performance1. Long channel length in state-of-the-art membranes such as Nafion 117 is therefore a prerequisite to obtaining proton selectivity, at the cost of an additional ionic resistance through such long channels. Pristine graphene2 already fulfils these two criteria, partly as the graphene basal plane is impermeable to water and other molecules3, and exhibits a certain degree of proton conductivity4, influenced by nanoscaled ripples5, corrugations6, particularly in monolayer graphene oxide7 and hydrogenated graphene8. Here, we chemically functionalized monolayer graphene to install sulfophenylated sp3 dislocations by diazotization. Selective to protons, transmembrane areal conductances surpass those of polymer membranes, while providing proton selectivity over methanol through such an atomically thin layer. By creating proton-conductive and selective paths through graphene, we unveil a covalent chemical route to rationalize transmembrane proton transport through 2D materials.
Unveiling Sensory Quality in Coffee: A Data-driven Exploration
Authors: Oliveira Bruno Pereira , Buozzi Mário Trama , Pinto Vinicius Pereira , Yasuoka Fatima Maria Mitsue , Neto Jarbas C. Castro 
Published: September 2024

Abstract

The coffee market is projected to reach approximately US$468.2 billion by 2024. Coffee farms are found on practically all continents, with Brazil being the world's largest producer, accounting for approximately 60% of global coffee sales volume. Brazil boasts 35 distinct regions that certify, protect, and characterize their coffee based on specific aspects such as Sul de Minas, Mogiana, and Amazonia. Coffee pricing is determined by taste characteristics and is evaluated through sensory analysis, where human tasters assess the coffee using the SCAA cupping protocol. This protocol involves assigning scores. This complex system necessitates a large and dedicated workforce to evaluate samples from farms worldwide. This analysis aims to evaluate and compare the coffee sample scores from around the globe. By analyzing the scores and the characteristics of the sample, we can gain insights into coffee behavior and potentially identify statistically significant differences between samples.
Complexity and mediating factors in farmers' climate perceptions and agricultural adaptation strategies in the Guatemalan Dry Corridor
Authors: Anderson Talia , Pons Diego , Taylor Matthew , Xuruc Antonia , Salvatierra Hugo Rodríguez , Guido Zack , Sullivan Jonathan , Liverman Diana , Anchukaitis Kevin 
Published: September 2024

Abstract

Projected precipitation decreases due to anthropogenic climate change will have serious consequences for the millions of households in Central America that rely on rainfed agriculture. However, a signal of anthropogenic climate change is not yet clear in regional precipitation data despite observations from many farmers throughout Central America who report recent changes in rainfall and associated losses to crop production and food security. Given the role of climate perceptions on adaptation and the substantial variability in regional climate, it is important to study uncertainties in both climate and social data and their implications for decision-making. We use a combination of satellite-based climate data and over 700 household surveys from two departments in Guatemala to better understand rainy season climate patterns over recent decades. Climate data reveal variable trends depending on the time period and location. Farmers' perceptions of rainfall trends are vary widely and we identify factors that may contribute to this lack of consensus. We also assess how farmers' observations and household characteristics influence agricultural practices. Our findings suggest that regional differences, including off-farm income sources, mediate farmers' modification to their agricultural practices, irrespective of whether a trend in rainfall is perceived or not. However, adjustments to agricultural maize practices are significantly associated with perceived rainfall changes where there is greater dependence on income derived from smallholder agriculture. Reconciling household- and community-level perceptions with observed and anticipated climate variability and change is therefore critical in these regions to ensure appropriate adaptation interventions and strategies.
Simulation of summer climate over East China by convection-permitting regional air-sea coupled model
Authors: Jiang Zhiyu , Tang Jianping , Wang Shuguang , Dong Guangtao , Wang Shuyu 
Published: September 2024

Abstract

In this research, the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Model was utilized to study the summer climate over eastern China and its adjacent ocean from 2009 to 2018. The COAWST model, equipped with a convection-permitting resolution of approximately 4km, effectively replicated the patterns of precipitation for both land and ocean, including sub-daily extreme precipitation, and the diurnal cycle. The COAWST model offers accurate simulations of the land-sea contrast in terms of the diurnal cycle of precipitation, showing the peaks of rainfall over land and sea in the afternoon and morning respectively. The model exhibited higher skill in extreme precipitation intensity over the ocean, while it was more skillful in wet frequency over the land. The overestimation of land precipitation can be attributed to stronger water vapor flux convergence and latent heat flux in the model. The inclusion of ocean module affects the ocean condition through fresh water injection, which contribute to the sea surface temperature (SST) bias in the simulation. This article highlights the strong performance of the coupled atmosphere-ocean model in simulating coastal precipitation of eastern China.
A model for classifying information objects using neural networks and fuzzy logic
Authors: Mukhin Vadym , Zavgorodnii Valerii , Liskin Viacheslav , Syrota Sergiy , Czupryna-Nowak Aleksandra , Rusyn Bohdan , Banasik Arkadiusz , Woloszyn Jacek , Kempa Wojciech 
Published: September 2024

Abstract

This work is aimed at developing intelligent systems capable of automatically classifying types of educational materials. This will allow students to find the resources they need faster, and it will make it easier for teachers to manage content in educational platforms. The solution of the problem of recognition of information objects using fuzzy output systems and neural networks is considered. This approach combines the advantages of neural machine learning with the flexibility and efficiency of fuzzy logic, making these systems effective tools for solving problems related to fuzzy or uncertain data. An information model of a neural network for classifying information objects in e-learning systems has been developed. Experimental testing of the proposed approach was carried out on a data set, which consists of information objects from real e-learning systems, namely such as manuals, lectures, syllabuses, and textbooks. The results of experimental studies have shown that a neural network built based on fuzzy logic is able to classify various information objects efficiently and correctly in e-learning systems. It is shown that the integration of neural networks based on fuzzy logic into e-learning systems to improve the processes of classification of information objects makes it possible to increase the efficiency of educational resources management, ensuring accuracy and flexibility in processing various data.
Oryza rufipogon (Griff.), a conduit for rapid evolution of rice under stress-prone environments: a test case of UV-B resistance and exoferalization
Authors: Senapati Preetam Kumar , Kariali Ekamber , Kisan Kuntala , Mohapatra Pravat Kumar 
Published: September 2024

Abstract

In general, wild relatives of cultivated rice are a repository of stress-tolerant genes and have been used to introduce resistance into cultivated rice. Compared to other abiotic stresses like drought, heat, cold, salinity, and disease resistance, UV stress emerged late in the biosphere, and there has been minuscule research on its trait location for resistance among rice genotypes for a possible way of introgression into cultivated species. Wild rice O. rufipogon (Griff.) which is sensitive to UV stress was facilitated to cross-pollinate naturally with a UV stress-resistant traditional cultivated rice Meghadambaru and the hybridization impact on stress tolerance was assessed on the progeny as well as the progenitors. UV stress affects vegetative growth by the downregulation of photosynthetic activity of leaf, lemma + palea, and awns because of its inhibitory effects on SPAD index, Fv/Fm ratio, and ETR (rel), photochemical quenching qP (rel), maximal fluorescence Fm (rel) and release of fluorescence energy (OJIP curve) in all three genotypes. However, these indices in O. rufipogon were found more vulnerable. The Intergrade genotype resulted from the parental cross-inherited weedy characters of O. rufipogon and UV tolerance attributes of Meghadambaru of the F1 generation followed by the F2 generation. O. rufipogon exhibited rapid evolution to gain UV stress resistance in the natural cross, while Meghadambaru resurged in exo-feralization and resurrected to devolution to weedy attributes.
Diet, Metabolic Biomarkers, and Sensorineural Hearing Loss: A Mendelian Randomization and Mediation Analysis
Authors: Yang Haoxiang , Luo Yaxin , Chen Bing 
Published: September 2024

Abstract

Sensorineural hearing loss (SNHL) is influenced by genetic and environmental factors. This study explores the causal relationships between dietary choices, circulating metabolic biomarkers, and SNHL using Mendelian Randomization (MR) analysis. We utilized summary statistics from genome-wide association studies (GWAS) on dietary choices and metabolic biomarkers as exposures, with SNHL as the outcome. Two-sample MR analysis and mediation analysis were conducted to identify causal links and metabolic pathways. The MR analysis revealed that fish, oily fish, healthy food, and vegetable consumption significantly reduce the risk of SNHL. The mediation analysis further indicated that these protective effects are mediated by the ratios of DHA, omega-3, and polyunsaturated fatty acids to total fatty acids, with DHA mediating approximately 10.57% of the protective effect of oily fish consumption. Significant causal pathways link dietary choices and metabolic biomarkers to SNHL, suggesting that dietary modifications, particularly increasing the intake of fish, healthy foods, and vegetables, could serve as effective preventive strategies against SNHL. This study provides valuable insights into the interplay between diet, metabolism, and hearing health, guiding future preventive strategies.
Plasmodium SEY1 is a novel druggable target that contributes to imidazolopiperazine mechanism of action
Authors: Winzeler Elizabeth , Carolino Krypton , De Souza Mariana Laureano , Chen Daisy , Farre Jean-Claude , Blauwkamp James , Absalon Sabrina , Ghidelli-Disse Sonja , Morano Alexander , Dvorin Jeffrey , Lafuente-Monasterio Maria Jose , Gamo Francisco-Javier 
Published: September 2024

Abstract

The precise mode of action of ganaplacide (KAF156), a phase III antimalarial candidate, remains elusive. Here we employ omics-based methods with the closely related chemical analog, GNF179, to search for potential Plasmodium targets. Ranking potential targets derived from chemical genetics and proteomic affinity chromatography methodologies identifies SEY1, or Synthetic Enhancement of YOP1, which is predicted to encode an essential dynamin-like GTPase implicated in homotypic fusion of endoplasmic reticulum (ER) membranes. We demonstrate that GNF179 decreases Plasmodium SEY1 melting temperature. We further show that GNF179 binds to recombinant Plasmodium SEY1 and subsequently inhibits its GTPase activity, which is required for maintaining ER architecture. Using ultrastructure expansion microscopy, we find GNF179 treatment changes parasite ER and Golgi morphology. We also confirm that SEY1 is an essential gene in P. falciparum. These data suggest that SEY1 may contribute to the mechanism of action of imidazolopiperazines and is a new and attractive druggable target.
Optimizing Droplet Condensation for Eco-Friendly Cooling: Experimental and CFD Validation
Authors: Kothari Prafull , Pachouri Vikrant , Yadav Indrajit N 
Published: September 2024

Abstract

This study presents a novel cooling system that combines optimum droplet condensation and thermoelectric cooling to reduce energy consumption and environmental impact. With an amalgamation of conventional cooling models, the research adds a new form of nozzle and diffuser layout that increases droplet formation and cooling efficiency. The efficiency of the system was confirmed by experimental tests and modern CFD analysis that proved a 20% enhancement of cooling with a 15% energy saving compared to traditional techniques. The hybrid technique helps the cooler to be environmentally friendly and at the same time points out the possibilities of using the system in high-risk areas like data centers and pharmaceutical facilities. This helps in the development of sustainable cooling technology which goes a long way in providing industries with a probable solution to improving their sustainability and at the same time achieving better performance.
Dynamic Characteristics Analysis and Fault Feature Study of Bearings with Compound Defects
Authors: Ni Wenjun , zhang chang 
Published: September 2024

Abstract

To investigate the dynamic variation patterns of rolling bearings with compound faults, a dynamic finite element model of defective bearings was established in ANSYS based on explicit dynamics algorithms. This model fully considers factors such as bearing rotational speed, load, contact, and friction. The dynamic analysis of rolling bearings with composite faults, involving rolling element and outer raceway dents, was conducted. The study results indicate significant differences in shear stress and vibration acceleration characteristics at different rotational speeds. The higher the speed, the more severe the fluctuations in stress and vibration acceleration, which significantly impacts bearing life. To further extract and analyze fault features, the Variational Mode Decomposition was used to decompose the vibration signals obtained from explicit dynamic simulations, yielding Intrinsic Mode Function (IMF) components at different speeds. By calculating the kurtosis, sample entropy, and envelope entropy of each IMF component, a comprehensive evaluation index was established. The components were then ranked using a weighted average method, selecting those with higher evaluation indices as effective components. After performing a Fast Fourier Transform (FFT) on the effective components, time-domain and frequency-domain analysis successfully extracted crucial information containing bearing fault features. This provides important references for bearing condition monitoring and fault diagnosis.
Abundance and Characterization of Microplastics in Compost Produced in Mazandaran, Iran
Authors: Zazouli Mohammad Ali , Alashti Mahdieh Mohammadi , Dehghan Samaneh , Dehbandi Reza , Fendereski Afsaneh 
Published: September 2024

Abstract

One of the source of plastics and microplastics (MPs) entering the environment and the food chain is waste from various sources. Most plastic resins are utilized in packaging with relatively short lifespans; after consumption, these materials contribute to municipal solid waste. The composting process struggles to completely separate plastics, making microplastics a significant contaminant during composting. MPs are defined as plastic particles smaller than 5 mm. This study aims to examine the frequency, distribution, and characteristics of microplastics found in compost produced by Mazandaran compost factories. MPs in the samples were extracted and separated based on density differences and digestion. Subsequently, a stereomicroscope was used to observe the MPs. This cross-sectional study found an average microplastic content of 16,981 items/kg across all compost samples. Behshahr compost had the highest average at 1,818,622, while Babol had the lowest at 15,744 items/kg. The Kruskal-Wallis test indicated no statistically significant differences between the sampling stations (p > 0.05). The most common shapes were fibers (75%), with the predominant color being transparent-white (56%), and the most frequently observed size range was 500–1000 µm (40%). Additionally, polymers identified included polyurethane, nylon, low-density polypropylene, and polycarbonate. This study reveals the presence of microplastics in compost from Mazandaran's fertilizer and compost factories. To address this issue, it is essential to develop strategies for reducing plastic waste entering composting facilities and to establish effective monitoring programs to detect and identify microplastic hotspots.
Evaluating and Visualization of Renewable and Green Energy Research Productivity and Contribution: A Bibliometric Analysis of ISI Web of Science Databases
Authors: Cheema Waqas Akram , Ahmad Khurshid , Ali Nusrat 
Published: September 2024

Abstract

The field of Renewable Energy has seen exponential growth in academic publications. This paper aims to survey and analyze existing research in renewable energy, identifying influential publications, authors, and organizations to delineate key research areas. Data were gathered from Web of Science (Core Collections) using the search query "Renewable Energy OR Green Energy" for publications between 2011 and 2023. Analysis utilized various software tools such as VOSviewer, ScientoPy, R, and MS Excel. Findings indicate that the majority of publications in Renewable Energy or Green Energy are predominantly in English, with a consistent upward trend in publication rates. Adebayo, Tomiwa Sunday emerges as the most prolific author. China emerges as the leading nation in publication output, particularly attributed to North China Electric Power University, a notable institution in the field. Following the United States and India, China has contributed significantly in terms of both article production and citation reception. Elsevier stands out as the primary publishing source, while Renewable Energy is identified as the leading journal in terms of productivity and influence.
Head-on Collisions of Fuzzy/Cold Dark Matter Subhalos
Authors: Koo Hyeonmo 
Published: September 2024

Abstract

We perform head-on collision simulations of compact dark matter subhalos using distinct numerical methods for fuzzy dark matter (FDM) and cold dark matter (CDM) models.For FDM, we solve the Schrodinger-Poisson equations with a pseudospectral solver, while for CDM, we utilize a smoothed particle hydrodynamics N-body code. Our results show that velocity decrease of subhalos is significantly greater in FDM model than in CDM, particularly at lower initial velocities, attributed to gravitational cooling-a unique mechanism of stabilizing in FDM with dissipating kinetic energy.This stark contrast in energy dissipation between two DM models suggests that FDM may offer valuable insights into understanding the dynamic behaviors of DM during galaxy cluster collisions, such as those observed in the Bullet cluster and Abell 520.These findings strongly suggest that FDM is not only capable of explaining these complex astrophysical phenomena but also serves as a compelling alternative to the traditional CDM model, offering resolutions to longstanding discrepancies in DM behavior.
Exploring the needs and preferences of older trauma patients: A qualitative study
Authors: Williams Jill , Chapman Madi , Evans Cath J , Botha Martie , Murad Juvaria , Linde Dieter , Harrington Cindy , Crotty Maria , Laver Kate 
Published: September 2024

Abstract

Background: Trauma in older people is emerging as a major health issue, with falls being the most common cause. Despite existing guidelines for trauma care of older populations, adoption is limited and undertreatment persists. This study aimed to explore the needs and preferences of older people and their families following traumatic injuries and define key components of a trauma care model for older populations.
Methods: This research adopted participatory design principles, engaging older people and their families, who had interacted with local healthcare services, to participate in a workshop which included structured activities and questions designed to facilitate discussion of the participants’ experiences of trauma and subsequent healthcare. Qualitative data were collected, coded, and analyzed using thematic analysis.
Results: Seven patients and six family members attended one of two workshops. Most patient participants were women, with a mean age of 82 years. Participants reported negative feelings following trauma, including uncertainty, shock and fear, decreased confidence, and feeling burdensome. Recovery goals were focused on regaining independence, participating in movement and exercise, and maximizing social connection. Communication, empathy and interpersonal skills in care, and system-related factors were identified as key factors impacting care and recovery experience following trauma. To improve trauma care, participants recommended care coordination, improved access to home support and rehabilitation, investment in staff expertise and training, and a dedicated trauma service for older adults.
Conclusions: This study underscores the importance of a comprehensive and person-centered approach to trauma care for older people, offering valuable insights for healthcare providers and policymakers striving to enhance the quality of care and improve outcomes for this vulnerable population.