bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resourcing Circular Economy Enterprises for Sustainable Development: Determinants of Circular Economy Job Acceptance
Authors: Asamoah Ama Nyarko , Hongbing You , Adu‐Gyamfi Gibbson , Nketiah Emmanuel , Obuobi Bright , Duah Harris Kwaku 
Published: January 2025

ABSTRACTTransitioning to a circular economy (CE) from the “take–make–dispose” system creates jobs and positions that must be occupied to foster environmental protection and waste minimization. However, research has yet to investigate what motivates the acceptance of these jobs. Consequently, this study explores the factors affecting CE job acceptance to address this gap. With the self‐determination theory as the foundational model, this study explored the impact of intrinsic and extrinsic motivators on CE job acceptance. Four hundred and sixty‐nine responses were analyzed using a partial least‐squares structural equation model (PLS‐SEM). Analysis evidenced that green values, self‐congruity, and financial benefits positively influenced CE job acceptance. Social influence impacted attitude negatively but was insignificant toward CE job acceptance. Attitude also mediated the effects of other constructs on acceptance. The study provides key industry actors and decision‐makers with comprehensive policy recommendations, including public sensitization and financial incentives to guarantee the promotion, adoption, and CE job acceptance.
Exploring the Interplay Among Environmental Knowledge, Green Purchase Intention, and Pro‐Environmental Behavior in Greenfluencing Scenarios: The Mediating Effect of Self‐Congruity
Authors: de Silva Marianny Jessica Brito , de Lima Maria Izabel Cordeiro , dos Santos Mayara Dayane , da Silva Santos Anne Karolinne , da Costa Marconi Freitas , Melo Francisco Vicente Sales , de Farias Salomão Alencar 
Published: January 2025

ABSTRACTThis study aims to understand how followers' perceptions of environmental knowledge conveyed by greenfluencers and mediated by real and ideal self‐congruence affects followers' intentions to make environmentally friendly purchases and engage in pro‐environmental behaviors. Employing a quantitative research approach, data were collected from 224 followers of greenfluencers through nonprobabilistic sampling. Structural equation modeling (SEM) was utilized for analysis. Contrary to prior assumptions, our findings indicate that ideal self‐congruity does not significantly predict pro‐environmental intentions or behaviors. However, real self‐congruence emerged as a significant mediator, influencing both pro‐environmental behavior and the intention to engage in green consumption. This research contributes to understanding virtual relationships involving greenfluencers by highlighting the importance of real self‐congruence in crafting persuasive content and selecting influencers for effective promotion of green brands. We conclude that the use of greenfluencers can indirectly encourage pro‐environmental actions, promoting sustainability objectives and ecological awareness in society.
Experimental and Mathematical Methods for Monitoring Dicyandiamide as an Inhibitor for Carbon Steel Corrosion in an Acidic Solution
Authors: Al Jahdaly Badreah A. 
Published: January 2025

AbstractThe inhibition effect of dicyandiamide (DCDA) on the carbon steel (CS) corrosion in 0.5 M HCl solution was evaluated using chemical and electrochemical methods. The maximum inhibition efficiency (%IE) and the optimal dose were 95.7% and 0.30 mg/L of DCDA inhibitor, respectively. The temperature effect in the %IE is measured using chemicals by gravimetric loss tests. Potentiodynamic polarization (PD‐P) tests clarified that DCDA is a mixed‐type inhibitor, while EIS tests revealed that the charge transfer resistance (Rct) increased with inhibitor concentration. The mixed (chemical and physical) adsorption mode appears on the CS surface following a Langmuir isotherm. UV–vis spectra revealed the chemical interaction of DCDA with the CS surface. Atomic force microscopy (AFM) examination revealed the creation of a protective film from DCDA molecules on the metal surface. Correlations between experimental data and theoretical energies derived from DFT analysis were computed using the density functional theory (DFT) method. Additionally, explore the favorite active sites of the DCDA molecule and their interactions with the CS surface.
Inhibitory Mechanisms of β‐Glucuronidase by Hibiscus syriacus Phenolics: Integrating Computational and Experimental Approaches
Authors: Alqhtani Haifa A. , Othman Sarah I. , Alkhayl Faris F. Aba , Altoom Naif G. , Lamsabhi Al Mokhtar , Kamel Emadeldin M. 
Published: January 2025

AbstractExploring the intricate mechanisms of β‐glucuronidase inhibition is essential to advancing the development of novel therapeutic agents. This study extensively evaluated the inhibitory potential of phenolics from Hibiscus syriacus against β‐glucuronidase using a combination of in vitro and computational approaches. in vitro assays demonstrated that chlorogenic acid and dactylifric acid exhibited significant inhibitory activity, with low IC50 values of 1.32 ± 0.08 and 10.02 ± 1.38 µM, respectively. Enzyme kinetics analyses revealed that dactylifric acid and the positive control, EGCG, followed a mixed inhibition mechanism, while chlorogenic acid displayed competitive inhibition, as indicated by the intersecting lines in the Lineweaver–Burk plots. Docking studies supported these in vitro findings, with chlorogenic acid and dactylifric acid showing the lowest binding affinities, extensive polar interactions, and occupancy of identical binding sites as the reference drug. A 30 ns molecular dynamics simulation was performed to explore the interaction dynamics between isolated phenolic compounds and β‐glucuronidase. Evaluation of multiple MD parameters revealed that chlorogenic acid and dactylifric acid exhibited stable trajectories and substantial energy stabilization in their binding with β‐glucuronidase. These computational findings are consistent with experimental data, supporting chlorogenic acid and dactylifric acid as potential inhibitors of β‐glucuronidase.
Thermal Stability and Electrical Conductivity of Polyvinyl Alcohol Composites Reinforced with Mn2O3–rGO
Authors: Gamal R. , Soliman T. S. , Khalid A. 
Published: January 2025

AbstractThe current work is concerned with the study and examination of the thermal and electrical characteristics of polyvinyl alcohol (PVA)/Mn2O3–reduced graphene oxide (rGO) nanocomposite. The Mn2O3–rGO composite was synthesized using a hydrothermal approach technique, and then PVA films were strengthened with varying amounts of Mn2O3–rGO nanoparticles (NP) prepared by the casting method. Raman analysis was applied to polymer films to ensure the complexation between the PVA and Mn2O3–rGO. Thermogravimetric analysis (TGA) and electrical analysis are used to investigate the effect of Mn2O3–rGO NP on the thermal stability and electrical conductivity of the polymer films. The films' thermal stability was raised by increasing the Mn2O3–rGO content in the PVA matrix. The polymer films exhibit an increase in electrical conductivity from 2.023 × 10⁻⁸ S·cm⁻¹ for pure PVA to 1.895 × 10⁻⁵ S·cm⁻¹ for PVA‐1.5% Mn2O3–rGO, which arises from the rise in free charge carrier mobility and hopping ionic hopping. Furthermore, in accordance with the Arrhenius relation, conductivity increases with temperature. The results nominated the present composite in flexible electronic applications.
Thiourea as a Promising Scaffold for Development of Agents Toward TriTryp Diseases
Authors: Souza Alessandra Mendonça Teles , Abrahim‐Vieira Bárbara de A. , Assumpção Paloma Wetler , da Conceição Raissa Alves , Viana Gil Mendes , Bedor Bárbara , Cavalcanti Milena Mota Bastos , da Silva Honorio Thiago , Rodrigues Carlos Rangel , Cabral Lucio Mendes 
Published: January 2025

AbstractThiourea has emerged as a versatile scaffold and a promising candidate for developing novel therapeutics against TriTryp diseases. This review explores the medicinal chemistry aspects of thiourea derivatives, highlighting their potential for Chagas Disease, African trypanosomiasis/sleeping sickness, and leishmaniasis. The discussion encompasses general synthetic approaches, physicochemical properties, and updates readers on the diverse structural substitutions on the thiourea scaffold governing potent molecules. The thiourea derivatives reviewed here demonstrated equipotent or superior activities compared to current chemotherapeutic agents. Early preclinical in silico assessments suggest favorable pharmacokinetic profiles and low toxicological potential. However, elucidating the molecular mechanisms and targets of these compounds remains a critical knowledge gap. Expanding the use of in silico tools is proposed as an effective strategy for designing novel antiparasitic drugs. Leveraging existing knowledge on thiourea derivatives holds promise in addressing TriTryp diseases more effectively.
Synthesis, Characterization, Hirshfeld Surface Analysis, Bandgap Evaluation and Biological Activity of a CuI‐1,2‐Dithioether Coordination Complex
Authors: Das Ratan , Dutta Tanmoy , Ghosh Narendra Nath , Mandal Vivekananda , Mandal Vivekananda , Sinha Biswajit , Biswas Kinkar 
Published: January 2025

AbstractHerein we report the synthesis, characterization, Hirshfeld surface analysis, bandgap evaluation, and antibacterial activity towards Gram‐positive bacteria of 2D copper‐based coordination polymers derived from 1,2‐dithioether ligands. In this work, the Cu‐1,2‐dithioether coordination complex was synthesized easily and characterized using UV‐Vis, FTIR, NMR spectroscopies, high‐resolution mass spectrometry (HRMS), and single crystal XRD techniques. The structural optimization and bandgap evaluation were determined through a Density Functional Theory (DFT) study. Hirshfeld surface analysis was used to visualize the interactions on the surface of the synthesized crystal and the π–π interactions in the two‐dimensional framework of the complex. The free space, i.e., 13.07% in the unit cell of the crystal indicated the good compactness and mechanical stability of the crystal packing. Finally, the antibacterial activity of the Cu‐1,2‐dithioether coordination complex against two Gram‐positive bacteria was also observed.
Application of Inorganic Carrier‐Loaded Chiral Catalysts in Asymmetric Catalysis
Authors: Zhang Heng , Liu Shucheng , Zhang Qiuxin , Hong Kun , Li Jiuling , Yan Xingchen , Pan Jianming 
Published: January 2025

AbstractChiral substances play a pivotal role in numerous contemporary fields, and their synthesis heavily relies on chiral catalysts. However, traditional homogeneous catalysts suffer from significant drawbacks, including difficulty in separation from products and nonrecyclability. Immobilization of homogeneous catalysts onto a specific carrier offers an excellent solution to these challenges, significantly reducing the production cost. Consequently, this approach has emerged as an inevitable trend in the development of chiral catalysts. This review comprehensively summarizes representative examples of an asymmetric catalytic reactions using chiral catalysts immobilized on inorganic carriers over the last decade, classifies them according to the type of carrier, and elucidates the loading techniques and recycling methods associated with these carriers.
Investigation on in‐situ geopolymer coatings: A comparative analysis of lycopodium powder and polydimethylsiloxane as functional additives
Authors: Krishna R. S. , Prasad V. Durga , Sethy Neha , Panda Biranchi , Boopathy R. , Mustakim Syed Mohammed , Rawat S. 
Published: January 2025

AbstractGeopolymer‐based inorganic coatings provide an effective alternative to conventional chemical‐based solutions. However, the coatings are not universally applicable, especially in critical applications such as underwater. This research aims to investigate and enhance geopolymer‐based coating through specific utilization of functional additives such as reduced graphene oxide (rGO), lycopodium powder (LCP), and polydimethylsiloxane (PDMS) for underwater applications. These additives were incorporated in limited dosages (<3 wt.% of binder), and their potential is further assessed in improving the coating material in terms of the resulting water resistance, mechanical properties, and durability against NaCl, MgSO4, HNO3, and H2SO4 attacks. The introduction of rGO facilitated a 35% increase in the 28‐day compressive strength and 33.83% in the scratch hardness, whereas (rGO + LCP) improved the water contact angle by 125%. Additionally, the developed coatings were further analyzed using an optical microscope and x‐ray diffractometer to understand their bonding potential with steel or cementitious substrates and phase formation. Life cycle cost analysis was also conducted to evaluate the economic viability of the geopolymer coatings, revealing a potential cost reduction of approximately 16%–42% with the sourcing of locally available materials.
From everyday language to disciplinary discourse: Culturally and linguistically sustaining dialogic instruction with multilingual learners
Authors: Qin Kongji , Wolf Jordan , Llosa Lorena 
Published: January 2025

AbstractResearch indicates that dialogic teaching promotes students content understanding, learning engagement, and democratic participation in classroom discussion. However, dialogic teaching is often misconstrued as a challenge for multilingual learners because there is a tendency to view them as lacking English language proficiency for sustained interaction and discussion. In this article, the authors introduce one instructional approach aimed at designing and implementing dialogic teaching specifically for multilingual learners, termed From Everyday Language to Disciplinary Discourse. Grounded in the theoretical frameworks of culturally and linguistically sustaining pedagogies, this asset‐based approach capitalizes on multilingual learners' everyday language practices, lived experiences, and funds of knowledge to support their active participation in classroom discussion and develop their disciplinary literacy. The authors begin by providing an overview of dialogic teaching and its potential for multilingual learners. They then discuss the conceptual foundations of this instructional approach to dialogic teaching with multilingual learners. Building off the conceptual discussions, they illustrate this approach with instructional examples from one U.S. high school multilingual science classroom and by analyzing the teacher's dialogic design, dialogic strategy, and dialogic stance. They conclude the article with a call for culturally and linguistically sustaining dialogic instruction with multilingual learners.
The association of cholesterol levels with memory and memory change over a 14‐year period in a US national cohort
Authors: Miramontes Silvia , Khan Umair , Ferguson Erin L. , Sirota Marina , Glymour M. Maria 
Published: January 2025

AbstractINTRODUCTIONThe impact of cholesterol on late‐life cognition remains controversial. We investigated the association of high‐density lipoprotein cholesterol (HDL‐C) and non–HDL‐C with memory in a nationally representative cohort.METHODSHealth and Retirement Study (HRS) participants (N = 13,258) aged 50+ (mean age: 67.2 years) followed from 2006 to 2020 provided cholesterol measures every 4 years and cognitive assessments biennially. Linear mixed models predicted memory scores using both baseline and time‐updated cholesterol values.RESULTSHigher baseline HDL‐C (mean: 53.9 mg/dL) predicted better memory scores (β: 0.05, 95% confidence interval [CI]: 0.03 to 0.08), but not memory change. Baseline non–HDL‐C (mean: 143 mg/dL) predicted poorer memory scores (β: −0.01, 95% CI: −0.02 to 0.00), but not memory change. Time‐updated HDL‐C predicted better memory (β: 0.02, 95% CI: 0.00 to 0.04), but non–HDL‐C showed no such associations.DISCUSSIONWhile higher peripheral HDL‐C is linked to better memory, the small effect sizes and absence of associations of HDL‐C and non–HD‐CL with memory change suggests that peripheral cholesterol has a small effect on the variation of memory scores.Highlights
Higher HDL‐C levels predict better memory scores but not memory change across 14 years of follow‐up.
Baseline higher LDL‐C levels predict poorer memory scores across time, but not memory change.
The small effects and absence of consistent association between cholesterol levels and memory change suggest that cholesterol plays a minor role in cognitive decline.
Synergistic effect of graphene oxide on the properties of poly (vinyl alcohol)/carboxymethyl cellulose electrospun nanofiber mats
Authors: Kapila Karanjit , Kirtania Sushen , Nath Kaushik K. , Saikumar Akuleti , Badwaik Laxmikant S. , Ahmed Gazi Ameen 
Published: January 2025

AbstractThe aim of this study was to develop polyvinyl alcohol (PVA)/carboxymethyl cellulose (CMC)/graphene oxide (GO) nanofiber mats using electrospinning fabrication technique. Polymer solutions were prepared with PVA at a concentration of 6% w/v, CMC ranging from 0.5% to 1.5% w/v, in a 1:1 polymer blend ratio, and GO nanofiller from 0.1% to 0.5% w/v. Addition of CMC and GO amend the solution properties such as conductivity and viscosity, leading to notable alteration in nanofiber diameters from 90.514 to 169.225 nm. As evidenced by rheological analysis, addition of GO significantly enhanced the storage moduli and shear stress of PVA/CMC/GO solutions compared to PVA and PVA/CMC. According to tensile properties, the tensile strength of PVA/CMC/GO nanofiber mats was increased by 25.59% to 46.41% at 0.1%–0.3% w/v of GO compared to PVA/CMC mats, contributing to overall mechanical improvements. FTIR spectroscopy revealed interactions between the hydroxyl (OH) groups of PVA and carboxylate groups (COOH) of CMCs, with increased intensity in OH and CH absorption bands. The presence of hydrophilic functional groups increases the wettability of the nanofiber mats, as indicated by reduced water contact angles from 51.321° to 45.924°. The oxygen‐rich structure of GO enhances the barrier properties of nanofiber mats, resulting in reduced water vapor permeability (WVP) from 1.049 to 0.980 g/m.h. Pa and moisture retention capacity (MRC) from 95.68% to 90.854%. Moreover, TGA analysis showed a significant improvement in the decomposition temperature of the hybrid PVA/CMC/GO nanofibers, resulting in reduced mass loss compared to other developed nanofibers. Overall, the obtained results validate the use of CMC biopolymer and GO nanofiller as an additive for the production nanofiber mats with improved structural, mechanical, thermal and barrier properties particularly for industrial, medical and packaging applications.Highlights
Blending of polymers to overcome the properties of single polymer system.
Development of PVA, PVA/CMC and PVA/CMC/GO electrospun nanofiber mats.
Effect of GO nanofiller on the properties of nanofiber mats.
Potential future applications in advanced engineering and material sciences.
Strategies to Boost the Safety and Ionic Conductivity of Lithium‐Ion Batteries Using Solid State Electrolytes: A Review
Authors: Hosamane Savitha , Kottam Nagaraju , Chalil Suresh Aishwarya 
Published: January 2025

ABSTRACTThe enormous potential of lithium‐ion batteries (LIBs) to provide environmentally sustainable practices and efficient energy storage has led to a rising interest in LIBs. Thermal runaway behaviors in LIBs, including high temperature, ejection, combustion, explosion, and the release of toxic gases, as well as thermal failure propagation in a battery pack, are both possible. Here, briefly mentioned about solid‐state electrolytes (SSE), which may use to make LIBs safer by reducing these risks. However, the SSE's ionic conductivity is subpar when compared to that of other liquid electrolytes, demanding modification. The authors have also focused on several SSE types in this review, including inorganic SSE, solid polymer electrolytes (SPEs), and composite solid electrolytes. Additionally, it was described how to enhance the ionic conductivity of SSEs at ambient temperature.
Deep learning-based pelvimetry in pelvic MRI volumes for pre-operative difficulty assessment of total mesorectal excision
Authors: Baltus Simon C. , Geitenbeek Ritch T. J. , Frieben Maike , Thibeau-Sutre Elina , Wolterink Jelmer M. , Tan Can O. , Vermeulen Matthijs C. , Consten Esther C. J. , Broeders Ivo A. M. J. 
Published: January 2025

Abstract

Background
Specific pelvic bone dimensions have been identified as predictors of total mesorectal excision (TME) difficulty and outcomes. However, manual measurement of these dimensions (pelvimetry) is labor intensive and thus, anatomic criteria are not included in the pre-operative difficulty assessment. In this work, we propose an automated workflow for pelvimetry based on pre-operative magnetic resonance imaging (MRI) volumes.

Methods
We implement a deep learning-based framework to measure the predictive pelvic dimensions automatically. A 3D U-Net takes a sagittal T2-weighted MRI volume as input and determines five anatomic landmark locations: promontorium, S3-vertebrae, coccyx, dorsal, and cranial part of the os pubis. The landmarks are used to quantify the lengths of the pelvic inlet, outlet, depth, and the angle of the sacrum. For the development of the network, we used MRI volumes from 1707 patients acquired in eight TME centers. The automated landmark localization and pelvic dimensions measurements are assessed by comparison with manual annotation.

Results
A center-stratified fivefold cross-validation showed a mean landmark localization error of 5.6 mm. The inter-observer variation for manual annotation was 3.7 ± 8.4 mm. The automated dimension measurements had a Spearman correlation coefficient ranging between 0.7 and 0.87.

Conclusion
To our knowledge, this is the first study to automate pelvimetry in MRI volumes using deep learning. Our framework can measure the pelvic dimensions with high accuracy, enabling the extraction of metrics that facilitate a pre-operative difficulty assessment of the TME.
Stress detection based EEG under varying cognitive tasks using convolution neural network
Authors: Afify Heba M. , Mohammed Kamel K. , Hassanien Aboul Ella 
Published: January 2025

Abstract
One tool for promoting mental health is human stress detection through multitasks of electroencephalography (EEG) recordings. This study proposed a short-term stress detection approach using VGGish as a feature extraction and convolution neural network (CNN) as a classifier based on EEG signals from the SAM 40 dataset. This database was recently available and was collected from 40 patients using 32 channels to identify performance on four tasks including Stroop color-word test (SCWT), answering arithmetic problems, finding mirror-identical images, and relaxing. Each task took 25 s to complete and was then repeated three times to record three trials. This means that the total EEG data contain 480 signals for four tasks recorded using 120 trials per task. The primary objective of this research was to track the amount of short-term stress that patients experienced while they engaged in the four mental tasks. Moreover, the VGGish-CNN model is applied to the SAM 40 dataset using five stages including signal preprocessing, segmentation, filtration, spectrogram, and classification process. We compared the VGGish-CNN model and the VGGish model for stress-based EEG classification to determine the best classification accuracy. The proposed approach for stress detection is the preliminary study that achieved an accuracy of 99.25% using the VGGish-CNN model on the SAM 40 dataset. Next, k-fold cross validation is performed to verify the efficiency of the VGGish-CNN model. This study can advance the application of brain–computer interface (BCI) and its use to identify patterns in EEG data that invoke stress-related inferences to aid in the diagnosis of mental disorders. In the future, investigation of human stress using EEG data will be useful in neurorehabilitation.