bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trends and challenges in hydrogen production for a sustainable energy future
Authors: da Silva Sousa Patrick , Neto Francisco Simão , de França Serpa Juliana , de Lima Rita Karolinny Chaves , de Souza Maria Cristiane Martins , Melo Rafael Leandro Fernandes , de Matos Filho José Roberto , dos Santos José Cleiton Sousa 
Published: October 2024

AbstractRecurring environmental challenges and the global energy crisis have led to intensified research on alternative energy sources. Hydrogen has emerged as a promising solution, produced through electrochemical, thermochemical, and biological methods. This study presents the advantages and disadvantages of these technologies. It also provides pertinent data on hydrogen production, identifying world‐leading countries in hydrogen production, such as the USA, Japan, and China, and the government policies that they have adopted. It reports market trends such as hydrogen synthesis by water electrolysis, the high cost of the electrolyzers used, and incentives for the carbon market to become competitive with other alternative energy sources. It also highlights startups from around the world that are developing innovative methodologies for producing hydrogen. The study concludes that integrating hydrogen production concepts with social, environmental, and industry interests is essential.
Activism as education in and through the youth climate justice movement
Authors: Trott Carlie D. 
Published: October 2024

AbstractYoung people worldwide are increasingly participating in a global movement for climate justice, yet to date, little research has examined how youth climate justice activists conceive of and experience activism as education. The present study used in‐depth, semi‐structured interviews with 16 US climate justice activists (aged 15–17) to address the research question: How do youth climate justice activists explain and experience the educative power of their activism? The results of reflective thematic analysis bring to light youths' dual roles as ‘learners of the movement’ and ‘climate justice educators’. As learners, youth described gaining awareness of climate justice directly from the movement, as well as learning a variety of skills (e.g., organising, communication, conflict resolution) through their activist engagement. Simultaneously, youth described their role as educators through a range of activities intended to raise awareness among adult and youth audiences, including educational workshops and trainings, school visits, teach‐ins, curriculum development, talk shows and interviews, creating digital resources, social media outreach and public protest (e.g., strikes, marches and demonstrations). Beyond spreading knowledge of climate in/justice, youth activists were also educators of action and social change processes—noting that learning about governmental institutions and political processes enabled them to exercise their democratic citizenship and equip and embolden other young people to do the same (e.g., via political advocacy trainings). The findings of the present study have implications for creating climate justice curricula that not only attend to the scientific and technological dimensions of the climate crisis, but also enable learners' justice‐driven action and democratic participation.
A Highly Sensitive Inclusion Complex Based Spectrofluorimetric Method for the Determination of Certain Sodium Glucose Cotransporter‐2 Inhibitors: Greenness Assessment and Application to Different Biological Fluids
Authors: Rushdy Doaa H. , Atia Noha N. , Ali Marwa F. B. , El‐Gizawy Samia M. 
Published: October 2024

ABSTRACTThis study introduces a remarkably simple, green, and highly sensitive inclusion complex based spectrofluorimetric method for analyzing two sodium glucose cotransporter‐2 (SGLT2) inhibitors: empagliflozin (EGF) and dapagliflozin (DGF). The method utilizes beta‐cyclodextrin (β‐CD) complexation to enhance the native fluorescence of EGF and DGF in aqueous solutions, resulting in 11.0‐fold and 9.0‐fold intensity increases, respectively. Fluorescence measurements were conducted at 301 nm emission following 230 nm excitation for both drugs. The method demonstrates excellent linearity (0.9994 for EGF and 0.9993 for DGF) over concentration ranges of 5.0–250.0 ng/mL and 10.0–300.0 ng/mL, with low detection limits of 1.05 and 1.38 ng/mL for EGF and DGF, respectively. The method's versatility was validated through successful application in pharmaceutical formulations, content uniformity testing, and biological fluids. This eco‐friendly approach primarily uses water as a solvent and requires minimal reagents. The method's environmental impact was comprehensively evaluated using the analytical eco‐scale, green analytical procedure index (GAPI), and analytical greenness metric (AGREE).
A Hybrid Model Simulating Multi‐Stage Continuous Fermentation of Saccharomyces cerevisiae
Authors: Zhu Huidong , Xia Jianye 
Published: October 2024

ABSTRACTThe performance of industrial strains has gradually improved with the rapid development of synthetic biotechnology. The production efficiency of traditional batch and fed‐batch culture is limited and product quality varies since both are dynamic processes, whereas multi‐stage continuous culture can maximise the production efficiency of specific fermentation processes and achieve consistent product quality. However, each single‐stage fermentation under multi‐stage continuous fermentation requires accurate steady‐state control, and a model with adequate accuracy is required for designing and controlling a multi‐stage continuous fermentation process. At present, there are few reports on kinetic models for the control of multi‐stage continuous fermentation. In this work, we constructed a hybrid model for Saccharomyces cerevisiae multi‐stage continuous culture, taking both oxygen limitation and Crabtree effect. The accuracy of the model was ∼80%, the advantages and limitations of the model are discussed and a potential improvement strategy is proposed.
Temporal Effect on PD‐L1 Detection and Novel Insights Into Its Clinical Implications in Non–Small Cell Lung Cancer
Authors: Pathak Gopal P. , Shah Rashmi , Castonguay Mathieu , Cheng Angela , Fris John , Murphy Rowan , Darling Gail , Ednie Alexander , French Daniel , Henteleff Harry , Mujoomdar Aneil , Plourde Madelaine , Wallace Alison , Xu Zhaolin 
Published: October 2024

ABSTRACTObjectivesSeveral studies rely on archived tissue blocks to assess the PD‐L1 scores; however, a detailed analysis of potential variations of scores between fresh and archived tissue blocks still lacks. In addition, the prognostic implications of PD‐L1 in lung cancers have not yet been completely understood. Here, we aimed to investigate the temporal variation in PD‐L1 scores from clinical samples and the clinical implications of PD‐L1 in non–small cell lung cancer (NSCLC).MethodsNSCLC cases from January 2005 to June 2023 were considered for this study, and PD‐L1 scores in archived and fresh tissue blocks were analyzed. Association of PD‐L1 with various driver mutations was explored, and implications of PD‐L1 in progression‐free survival (PFS) and overall survival (OS) were analyzed.ResultsOur study revealed a significant disparity in PD‐L1 scores between archived and fresh tissue blocks, and a temporal variation in scores within 6 months of tissue acquisition. Advanced‐stage primary tumors, metastatic lymph nodes, and visceral pleural invasion revealed higher PD‐L1 expression as presented by tumor proportion score (TPS). Notably, in fully resected stage I/II NSCLC cases, OS was better in the high PD‐L1 (≥ 50% TPS) cohort with driver mutations compared to cases without driver mutations (hazard ratio—0.5129, 95% confidence interval 0.2058–1.084, p = 0.0779). In contrast, high PD‐L1 was associated with worse OS compared to no PD‐L1 (< 1% TPS) (hazard ratio—2.431, 95% confidence interval 1.144–6.656, p = 0.0242) in the cohort without driver mutations. Furthermore, the presence of a KRAS mutation favored the outcome of anti‐PD‐L1/PD1 immunotherapy in advanced NSCLC.ConclusionPD‐L1 detection from tissue blocks was found to vary temporally, urging for a prioritized consideration for patients with marginal scores when archived blocks are employed for its detection. Prognostic roles of PD‐L1 were associated with driver mutations, and KRAS mutations favored the outcome of anti‐PD‐L1/PD1 therapy in advanced NSCLC.
Exploring the Utility of the Modified Hospitalized‐Patient One‐Year Mortality Risk Score to Trigger Referrals to Palliative Care for Inpatients With Cancer
Authors: Ghoshal A. , Prince R. , Downar J. , Lapenskie J. , Subramaniam S. , Wegier P. , Le L. W. , Hannon B. 
Published: October 2024

ABSTRACTBackgroundEstimating prognosis can be a barrier to timely palliative care involvement. The modified Hospitalized‐patient One‐year Mortality Risk (mHOMR) score uses hospital admission data to calculate the risk of death within 12 months and may be a useful tool to trigger a referral to palliative care.MethodsThe mHOMR tool was retrospectively applied to consecutive acute admissions to a quaternary cancer center in Toronto, Canada from March 1 to May 31, 2018. The study aimed to investigate the association between dichotomized mHOMR scores (the cohort median score of 0.27 and the developer‐recommended score of 0.21) and the risk of death, and whether these could be used to identify patients who may benefit from timely palliative care involvement.ResultsOf 269 inpatients, 87 were elective admissions and excluded from further analyses. At the median mHOMR score of 0.27, 91/182 patients (50%) were categorized as high‐risk of death within 12 months (mHOMR+), 53 (58%) were referred to palliative care. At the lower cut‐off of 0.21, 103 patients were mHOMR+, of whom 57 (55.3%) were referred to palliative care. The higher mHOMR was significantly associated with mortality (29.7% mHOMR− vs. 39.8% mHOMR+ at 12 months, log‐rank p < 0.05). The association between the developer‐recommended mHOMR cut‐off (≥ 0.21) and mortality was not significant (p = 0.15).ConclusionsA higher mHOMR score was significantly associated with the risk of mortality in patients with advanced cancer. However, the developer‐recommended mHOMR cut‐off of 0.21 failed to identify a statistically significant difference between patients with advanced cancer at low versus high scores. While mHOMR may be a useful tool to augment clinical judgment and identify inpatients with advanced cancer at high risk of death, who in turn may benefit from referral to palliative care, the optimal mHOMR cutoff may warrant adjustment for this population.
Targeting Mitochondria: Influence of Metabolites on Mitochondrial Heterogeneity
Authors: Joof Amie N. , Ren Fangyuan , Zhou Yan , Wang Mengyu , Li Jiani , Tan Yurong 
Published: October 2024

ABSTRACTMitochondria are vital organelles that provide energy for the metabolic processes of cells. These include regulating cellular metabolism, autophagy, apoptosis, calcium ions, and signaling processes. Despite their varying functions, mitochondria are considered semi‐independent organelles that possess their own genome, known as mtDNA, which encodes 13 proteins crucial for oxidative phosphorylation. However, their diversity reflects an organism's adaptation to physiological conditions and plays a complex function in cellular metabolism. Mitochondrial heterogeneity exists at the single‐cell and tissue levels, impacting cell shape, size, membrane potential, and function. This heterogeneity can contribute to the progression of diseases such as neurodegenerative diseases, metabolic diseases, and cancer. Mitochondrial dynamics enhance the stability of cells and sufficient energy requirement, but these activities are not universal and can lead to uneven mitochondria, resulting in heterogeneity. Factors such as genetics, environmental compounds, and signaling pathways are found to affect these cellular processes and heterogeneity. Additionally, the varying roles of metabolites such as NADH and ATP affect glycolysis's speed and efficiency. An imbalance in metabolites can impair ATP production and redox potential in the mitochondria. Therefore, this review will explore the influence of metabolites in shaping mitochondrial morphology, how these changes contribute to age‐related diseases and the therapeutic targets for regulating mitochondrial heterogeneity.
Exploring the Role of Titanate Perovskites in the Oxidation of Amines via Photocatalysis
Authors: Lopes Joana C. , Sampaio Maria J. , Silva Cláudia G. , Faria Joaquim L. 
Published: October 2024

AbstractConsidering that structural differences could affect the photocatalytic efficiency of titanate perovskites, cubic SrTiO3 (STO) and tetragonal CaTiO3 (CTO) were synthesised as models to elucidate the structure‐activity relationship. STO and CTO materials were produced through hydrothermal approaches, adjusting parameters such as temperature and pressure to optimise material purity. Among the perovskite photocatalysts, two stand out for their exceptional photocatalytic capacity and crystalline purity: CaTiO3, prepared at 180 °C for 36 h, and SrTiO3, synthesised at 200 °C for 24 h. Notably, we explore the selective ability of these materials for the photocatalytic oxidative self‐coupling of benzylamine (BZA) to produce N‐benzylidenebenzylamine (BZI), with CaTiO3 emerging as the most efficient catalyst for this reaction. The CTO material prepared at 180 °C for 36 h (CTO180T‐36) achieved a peak BZI production of 0.5 mM, with a total conversion of BZA after 7 h of irradiation. This study also emphasises the crucial role of reaction conditions and perovskite morphologies in fine‐tuning photocatalytic performance. These findings highlight opportunities for developing efficient and selective photocatalytic processes, holding the compromise for applications in organic synthesis and sustainable green chemistry.
Engineering Interfacial Molecular Interactions on Ag Hollow Fibre Gas Diffusion Electrodes for High Efficiency in CO2 Conversion to CO
Authors: Kuang Yizhu , Chen Guoliang , Mudiyanselage Dimuthu Herath , Rabiee Hesamoddin , Ma Beibei , Dorosti Fatereh , Nanjundan Ashok Kumar , Zhu Zhonghua , Wang Hao , Ge Lei 
Published: October 2024

AbstractThe electrochemical CO2 reduction reaction (CO2RR) occurs at the nanoscale interface of the electrode‐electrolyte. Therefore, tailoring the interfacial properties in the interface microenvironment provides a powerful strategy to optimise the activity and selectivity of electrocatalysts towards the desired products. Here, the microenvironment at the electrode‐electrolyte interface of the flow‐through Ag‐based hollow fibre gas diffusion electrode (Ag HFGDE) is modulated by introducing surfactant cetyltrimethylammonium bromide (CTAB) as the electrolyte additive. The porous hollow fibre configuration and gas penetration mode facilitate the CO2 mass transfer and the formation of the triple‐phase interface. Through the ordered arrangement of hydrophobic long‐alkyl chains, CTAB molecules at the electrode/electrolyte interface promoted CO2 penetration to active sites and repelled water to reduce the activity of competitive hydrogen evolution reaction (HER). By applying CTAB‐containing catholyte, Ag HFGDE achieved a high CO Faradaic efficiency (FE) of over 95 % in a wide potential range and double the partial current density of CO. The enhancement of CO selectivity and suppression of hydrogen was attributed to the improvement of charge transfer and the CO2/H2O ratio enhancement. These findings highlight the importance of adjusting the local microenvironment to enhance the reaction kinetics and product selectivity in the electrochemical CO2 reduction reaction CO2RR.
Application of MgO based‐nanofluid for controlling the growth of asphaltene flocs under static and micromodel dynamic conditions
Authors: Najjar Pourya A. M. Z. , Mirzayi Behruz , Mohammadi Saber , Hemmat Alimohammad , Mahmoudi Alemi Fatemeh , Ghanbarpour Omid 
Published: October 2024

AbstractIn this study, the impact of magnesium oxide (MgO) nanoparticles on the control of asphaltene aggregates growth was examined. The investigation began with static testing, followed by dynamic testing, where nanofluid was injected into a constructed glass micromodel simulating a porous medium. The results obtained from light microscopy and asphaltene dispersant tests demonstrated that the MgO nanoparticles with an average diameter of 50 nm postpone the asphaltene onset point (AOP) and delay the growth of asphaltene aggregates in crude oil. Also, the results obtained from these experiments illustrated the performance of synthesized nanoparticles in various concentrations on inhibition of asphaltene deposit in the crude oil medium, in the order of 750 > 1500 > 100 > 1000 > 500 ppm. The results from both microscopy and ADT experiments strongly validate the effectiveness of MgO nanoparticles across varying concentrations, highlighting the optimal dosage of 750 ppm. Images of nanofluid flooding at the optimal concentration in the glass micromodel demonstrate effective nanoparticle inhibition and enhanced oil recovery from the porous medium. These findings corroborate the results obtained from ADT and microscopy tests. The results of FT‐IR analysis show the adsorption of asphaltene particles on the surfaces of MgO nanoparticles in wavelengths of 2900–3000 cm−1. Moreover, dynamic light scattering (DLS) analysis results indicated that the average diameter of suspended particles was 3580 nm before adsorption and 6230 nm after adsorption, indicating the controlled adsorption of asphaltene onto the surface of MgO nanoparticles. The findings from this study can be applied to manage asphaltene formation across all stages of oil processing and production.
ASCL: Accelerating semi‐supervised learning via contrastive learning
Authors: Liu Haixiong , Li Zuoyong , Wu Jiawei , Zeng Kun , Hu Rong , Zeng Wei 
Published: October 2024

SummarySSL (semi‐supervised learning) is widely used in machine learning, which leverages labeled and unlabeled data to improve model performance. SSL aims to optimize class mutual information, but noisy pseudo‐labels introduce false class information due to the scarcity of labels. Therefore, these algorithms often need significant training time to refine pseudo‐labels for performance improvement iteratively. To tackle this challenge, we propose a novel plug‐and‐play method named Accelerating semi‐supervised learning via contrastive learning (ASCL). This method combines contrastive learning with uncertainty‐based selection for performance improvement and accelerates the convergence of SSL algorithms. Contrastive learning initially emphasizes the mutual information between samples as a means to decrease dependence on pseudo‐labels. Subsequently, it gradually turns to maximizing the mutual information between classes, aligning with the objective of semi‐supervised learning. Uncertainty‐based selection provides a robust mechanism for acquiring pseudo‐labels. The combination of the contrastive learning module and the uncertainty‐based selection module forms a virtuous cycle to improve the performance of the proposed model. Extensive experiments demonstrate that ASCL outperforms state‐of‐the‐art methods in terms of both convergence efficiency and performance. In the experimental scenario where only one label is assigned per class in the CIFAR‐10 dataset, the application of ASCL to Pseudo‐label, UDA (unsupervised data augmentation for consistency training), and Fixmatch benefits substantial improvements in classification accuracy. Specifically, the results demonstrate notable improvements in respect of 16.32%, 6.9%, and 24.43% when compared to the original outcomes. Moreover, the required training time is reduced by almost 50%.
Stretch‐Induced Ordering of Prochiral Dimethyl Sulfoxide in Anisotropic Hydrogels Analysed by 1H and 2H Nuclear Magnetic Resonance
Authors: Elliott Stuart J. , Kuchel Philip W. , Eykyn Thomas R. 
Published: October 2024

AbstractNuclear spins in small molecules dissolved in stretched hydrogels typically have population‐averaged residual interactions. The nuclear magnetic resonance (NMR) spectra of these systems often show additional peaks and splittings compared with free solutions. Residual dipolar couplings (RDCs) and quadrupolar couplings (RQCs) are observed for guest 1H and 2H nuclear spins, respectively. Dimethyl sulfoxide (DMSO) is an exquisitely sensitive probe of such biologically relevant environments since it is prochiral and becomes effectively chiral when embedded in anisotropic gelatin‐based hydrogels. Measured 1H RDCs and 2H RQCs were used to estimate bond order parameters over a wide range of stretching extents. At the largest extent of stretching, the 2H splittings were −73.0 and −9.4 Hz, similar to those found for guest molecules in liquid crystals. Inhomogeneous line broadening of the 2H resonances was related to the size of the RQC due to a spatial distribution of RQCs, which was revealed using a one‐dimensional slice selective imaging experiment along the stretching direction. 1H NMR spectra exhibited homogeneous line broadening, with resonance integrals that indicated concealed multiplet structure. Understanding molecular bond ordering in mechanically oriented environments provides a conceptual framework for investigating more complex systems including zeolites and those found in vivo.
Design of PtSn Nanocatalysts for Fuel Cell Applications
Authors: Distaso Monica , Abella Erika 
Published: October 2024

AbstractThe challenges in the fuel cell industry lie in the cost, performance, and durability of the electrode components, especially the platinum‐based catalysts. Alloying has been identified as an effective strategy to reduce the cost of the catalyst and increase its efficiency and durability. So far, most studies focused on the design of PtM bimetallic nanocatalyst, where M is a transition metal. The resulting PtM materials show higher catalytic activity, but their stability remained challenging. In addition, most of the transition metals M are expensive or low abundant. Tin (Sn) has gained attention as alloying element due to its versatility in manufacturing both anode and cathode electrodes. If used as anode catalyst, it is able to overcome poisoning from CO and related intermediates. As cathode catalyst, it improves the kinetics of the oxygen reduction reaction (ORR). Additionally, Sn is an abundant and cheap element. The current contribution outlines the state of the art on the alloy and shape effect on PtSn activity and stability, demonstrating its high potential to develop cheaper, more efficient and durable catalysts for fuel‐cell electrodes. Additionally, in situ analytical and spectroscopic studies can shed light on the elementary steps involved in the use of PtSn catalytic systems. Finally, this intriguing material can be used as a parent system for the synthesis of high‐entropy‐alloys and intermetallics materials.