Distinct Influence Research Articles

Exploring the Relationship Between Video Game Engagement and Creative Thinking in Academic Environments: Cross-Sectional Study

This study explores the relationship between video game engagement and creative thinking among university students in an academic setting. Utilizing a descriptive cross-sectional qualitative approach, semi-structured interviews were conducted with 40 university students aged 17–25 years, from various academic disciplines. The sample, predominantly female (57.5%) and aged 22 years (27.5%), provided diverse perspectives on the impact of video games on their academic and creative capabilities. The thematic analysis of the interviews revealed significant insights into how video games may enhance creative problem-solving skills and overall creative thinking in an educational context. The study found that a high percentage of participants (47.5%) had a grade point average (GPA) of 4.0, suggesting a potential link between academic performance and video gaming habits. The results highlight the need for further research into specific game genres and their distinct influences on creativity among different demographics. This study contributes to the growing body of literature on the cognitive benefits of video games and their potential to foster creative skills in higher education environments.

Drag Artists in Shanghai: Balancing Local and Global Influences in Queer Cultural Production

This article discusses a case study of a group of local and expat drag artists based in Shanghai, China. Theoretical perspectives of “global gay” discourse, queer temporality and Chinese-centric queer theories were employed to question how Shanghai’s drag artists navigate drag’s growing popularity, Chinese state restrictions and Western dominance. Through analysing semi-structured interviews and performance video samples of seven drag artists and one LGBTQ+ venue owner, queer cultural productions in China were explored to ask how they offer new possibilities for queer knowledge production, and propose futurities that are simultaneously transnational and rooted in China. While the influence of Euro-American LGBTQ+ discourse was documented and acknowledged, other perspectives revealed more nuanced conceptualisations of the binary between copy/original, the frictions inherent in cultural exchange, and diverse forms of resistance. Shanghai’s drag scene is evolving in distinct ways, incorporating both global and local influences and cultural traditions. With queer knowledge still largely attributed to the West, and non-Western experiences vastly underrepresented, it is important to recognise what underground cultural productions such as those in Shanghai offer global queer cultural exchange.

Mediating Role of Sustainability Reporting Quality on the Relationship Between Green Banking and Firm Value

Abstract The mounting environmental concerns have become a pressing issue across industries. Nevertheless, the banking sector has a distinct influence in shaping economic growth and development. This study sought to evaluate the impact of green banking in strengthening corporate value through its level of sustainability reporting in order to address these concerns. A research framework was developed based on theoretical support. The sampled data was collected from banks listed on the Indonesian Stock Exchange from 2018-2021. An empirical analysis was performed through hierarchical regression. The study’s findings indicated that green banking positively and significantly impacts firm value. Furthermore, there is a mediating effect between green banking and business value due to the quality of sustainability reporting. The empirical test revealed that the quality of sustainability reporting has a mediating effect to some extent. The results also showed that there is an interaction between business size (assets) and correlations between firm value and green banking. By undertaking a data-driven research that explains the impact of green banking on business value, this study aims to fill a significant gap in the body of knowledge on green banking and sustainability reporting.

Multi-omics analysis of the molecular response to glucocorticoids - insights into shared genetic risk from psychiatric to medical disorders

BackgroundAlterations in the effects of glucocorticoids have been implicated in mediating some of the negative health effects associated with chronic stress, including increased risk for psychiatric disorders as well as cardiovascular and metabolic diseases. This study investigates how genetic variants influence gene expression and DNA methylation (DNAm) in response to glucocorticoid receptor (GR)-activation, and their association with disease risk. MethodsWe measured DNAm (n=199) and gene expression (n=297) in peripheral blood before and after GR-activation with dexamethasone, with matched genotype data available for all samples. A comprehensive molecular quantitative trait locus (QTL) analysis was conducted, mapping GR-response methylation (me)QTLs, GR-response expression (e)QTLs, and GR-response expression quantitative trait methylation (eQTM). A multi-level network analysis was employed to map the complex relationships between the transcriptome, epigenome, and genetic variation. ResultsWe identified 3,772 GR-response meCpGs corresponding to 104,828 local GR-response meQTLs that did not strongly overlap with baseline meQTLs. eQTM and eQTL analyses revealed distinct genetic influences on gene expression and DNAm. Multi-level network analysis uncovered GR-response network trio QTLs, characterized by SNP-CpG-transcript combinations where meQTLs act as both eQTLs and eQTMs. GR-response trio variants were enriched in GWAS for psychiatric, respiratory, autoimmune and cardiovascular diseases and conferred a higher relative heritability per SNP than GR-response meQTL and baseline QTL SNP. ConclusionsGenetic variants modulating the molecular effects of glucocorticoids are associated with psychiatric as well as medical diseases and not uncovered in baseline QTL analyses.

Morphological evidence of an explosive eruption event in October 2023 at Sofu Seamount in the Izu-Bonin Arc

Sofu Seamount is one of the poorly studied submarine edifices in the Izu-Bonin Arc. There is no known historical record of volcanic activity, thus its eruptive history and volcanic features are completely unknown. However, on October 9, 2023, at least 14 T-phases originating near Sofu Seamount were observed. An 80 km-long raft of floating pumice was observed off Sofu Seamount on October 20. These spatially and temporally coherent observations indicate that an eruption occurred from a deep seafloor vent somewhere near Sofu Seamount. In order to investigate the origin of this submarine eruption, we collected new bathymetric data in 2024 and compared it with older bathymetric data collected in 2022, 2007 and 1987. The bathymetric comparison revealed evidence for explosive eruptions at Sofu Seamount between 2022 and 2024. During this time, a crater, 1.6 km wide and 400 m deep, was formed at the pre-existing central cone on the western part of Sofu Seamount, whose pre-eruption summit depth was 737 m. The maximum negative depth change was 451 m and a volume of 430 × 106 m3 was removed due to the crater formation. A dome-like structure, 1 km wide and 100 m high was constructed northeast of the crater, part of which collapsed as a result of the crater formation. The volcanic products were transported over 6 km downslope and emplaced on the adjacent seafloor where positive depth changes up to 75 m were observed. Landslides also occurred around the crater. The largest slide on the northern flank formed a slide scar that is 3.8 km long and 1 km wide. Here, the maximum negative depth change was 148 m and 140 × 106 m3 of material was removed. The slide materials were deposited downslope where positive depth changes up to 61 m were observed. Considering the occurrence of the earthquake swarm on October 2–8, 2023 and T-phase swarm on October 9, the timing of the eruption can be constrained within October 2023.An analysis of volcanic and tectonic morphology reveals a distinct tectonic influence on volcanism at Sofu Seamount. Sofu Seamount is located in a back-arc rift zone where the N–S trending Torishima and Sofu Rifts have formed. The new bathymetric data showed that the rifts have an asymmetric structure and can be divided into two segments, which are identified here as inner and outer rifts. The inner rifts are bounded by steeper fault scarps that have experienced more subsidence than the outer rifts. The western part of Sofu Seamount, where the eruption occurred, is located within the inner rifts, and is heavily dissected by rifting-related normal faults, while the eastern part is located outward of the inner rifts and is not dissected by faults. The October earthquake swarm was more concentrated in the area of the inner rifts and some large earthquakes showed normal fault focal mechanisms with a tension axis approximately in E–W direction. Our morphological observations combined with recent seismic events show that the inner rifts are the currently active tectonic structures and young volcanism at Sofu Seamount is controlled by the back-arc rifting of the Izu-Bonin Arc.

The quorum-sensing TraI/TraR system contributes to the release of Fe and Al from biotite by Agrobacterium pusense SX41

The quorum-sensing (QS) system in Rhizobiaceae has been studied, however, the mechanisms of QS system-mediated mineral dissolution by bacteria remain poorly understood. Here, the mineral-solubilizing Agrobacterium pusense SX41 harboring the QS system (responsible for N-acyl homoserine lactone (AHL) production) was characterized for QS system-mediated Al and Fe release from biotite. Whole-genome sequence analysis revealed that SX41 contains the QS TraI/TraR system. SX41 and the SX41∆traI, SX41∆traR, and SX41∆traI/R mutants were constructed from SX41 and compared for QS TraI/R system-mediated Fe and Al release from biotite in the solution and the underlying mechanisms. The SX41∆traI, SX41∆traR, and SX41∆traI/R mutants significantly decreased the Al and Fe concentrations in the medium by 24 % to 54 % on day 1 and 25 % to 42 % on day 5, while these mutants significantly reduced exopolysaccharide (EPS) concentrations in the medium by 21 % to 55 % on day 5, compared with those of SX41. Furthermore, these mutants demonstrated decreased cell counts and biofilm formation on biotite surfaces compared with SX41. Notably, the SX41∆traR mutant exhibited more pronounced effects on Al and Fe release from biotite, EPS production, and cell adsorption and biofilm formation on biotite surfaces compared with the SX41∆traI mutant. Moreover, the addition of biotite significantly upregulated the expression of traI and traR in SX41 and the complemented strains SX41∆traIR and SX41∆traRR. These findings underscore the pivotal role of the TraI/R system in the interactions between SX41 and biotite and highlight the distinct influences of traI and traR on Al and Fe release from biotite by SX41.

Deconstructing the Retained Austenite Stability: In Situ Observations on the Austenite Stability in One- and Two-Phase Bulk Microstructures During Uniaxial Tensile Tests

Given the critical role that metastable retained austenite (RA) plays in advanced high-strength steel (AHSS), there is significant interest in obtaining a comprehensive understanding of its stability, to achieve excellent mechanical properties. Despite considerable attention and numerous studies, the significance of individual contributions of various microstructural factors (size, crystallographic orientation, surrounding phases, etc.) on the stability of RA remain unclear, partly due to the difficulty of isolating the direct effects of these factors. In this study, we examined the influence of microstructural factors while minimizing the effect of chemical composition on the mechanical stability of RA. We accomplished this by comparing the austenite (γ) stability in two distinct microstructures: a two-phase RA/martensite microstructure and a one-phase γ microstructure, both with nearly identical γ compositions. We employed in situ high-energy X-ray diffraction during uniaxial tensile testing conducted at both room temperature and 100 °C, facilitating the continuous monitoring of microstructural changes during the deformation process. By establishing a direct correlation between the macroscopic tensile load, phase load partitioning, and the γ/RA transformation, we aimed to understand the significance of the microstructural factors on the mechanical stability of the RA. The results indicate that very fine RA size and the surrounding hard martensitic matrix (aside from contributing to load partitioning) contribute less significantly to RA stability during deformation than expected. The findings of this study emphasize the critical and distinct influence of microstructure on γ/RA stability.

Effect of Different Welding Modes on Morphology and Property of SS316L Stainless Steel Deposition by Robotic Metal-Inert Gas Welding.

The widespread adoption of arc additive manufacturing techniques across various industries has advanced the field of SS316L stainless steel manufacturing. It is crucial to acknowledge that different welding modes exert distinct influences on the forming and mechanical performance. This study analyzed the thermal input associated with four specific welding modes in LORCH MIG welding, clarifying the transition dynamics of molten droplets through waveform analysis and examining the resultant effects on microstructure and performance characteristics. The Pulse, Speed-Pulse-XT, and Twin-Pulse modes were found to induce spatter during the manufacturing process, consequently reducing molding efficiency in comparison to the SA-XT mode. Notably, the Twin-Pulse mode, characterized by double-pulse agitation, generated fish scale patterns along the lateral surfaces of the fabricated parts, promoting anisotropic grain growth. This microstructural refinement, compared to single-pulse samples with equivalent thermal input, resulted in enhanced mechanical properties. Nevertheless, the horizontal tensile strength of the three pulse modes was lower than the industrial standard for SA-XT mode and forging. In contrast, the SA-XT mode with an average hardness of 168.1 ± 6.9 HV and a tensile strength of 443.58 ± 5.7 MPa. Therefore, while three pulse modes offer certain microstructural advantages, the SA-XT mode demonstrates superior overall performance.

Emotional processing in binge drinking, tobacco use disorder and their comorbidity in youth: A preregistered PRISMA scoping review

BackgroundBinge drinking (BD) and tobacco use disorder (TUD) are prevalent among youth, with significant social and health implications. However, research into the emotional impairments associated with BD and TUD during adolescence is sparse and lacks integration within a comprehensive model of emotional processes. Moreover, the impact of comorbid BD and TUD on emotional deficits remains largely unexplored. We propose the first review focused on the variation of emotional deficits in BD, TUD, or their comorbidity among adolescents and we systematically explore differences across various emotional abilities. MethodsFollowing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines (PRISMA-ScR), we conducted a preregistered review of existing literature on emotional processing impairments in BD and/or TUD among adolescents. From 481 papers initially identified, 7 were included in this review. Additionally, we proposed experimental avenues for future research based on identified shortcomings in current literature. ResultsOur scoping review indicates that emotional deficits are likely prevalent in both BD and TUD populations, affecting emotional appraisal/identification, response, and regulation. However, further investigation is necessary to ascertain the magnitude and scope of these deficits in adolescents and adults, as well as to delineate the distinct or combined influence of BD and TUD on emotional disturbances. ConclusionWhile some emotional deficits are apparent, we contend that examining emotional deficits in BD and TUD separately, as well as together, would offer a more comprehensive understanding of their nature and inform the development of novel treatment strategies.

Separation of triacylglycerol (TAG) isomers by cyclic ion mobility mass spectrometry

Triacylglycerols (TAGs), a major lipid class in foods and the human body, consist of three fatty acids esterified to a glycerol backbone. They can occur in various isomeric forms, including sn-positional, cis/trans configurational, acyl chain length, double bond positional, and mixed type isomers. Separating isomeric mixtures is of great interest as different isomers can have distinct influence on mechanisms, such as digestibility, oxidative stability, or lipid metabolism. However, TAG isomer separation remains challenging with established analytical methodologies such as liquid-chromatography coupled to mass spectrometry (LC-MS). In this study, we developed a method with cyclic ion mobility mass spectrometry (cIMS-MS) for the separation and identification of all types of TAG isomers. First, the influence of different adducts (Li+, NH4+, Na+, and K+) on the separation was studied. Overall, it was concluded that the sodium adduct is the best choice to efficiently separate all types of TAG isomers. In addition, trends were found in the influence of specific structural features on the drift time order. An order of relative influence (from high to low) was established; (1) degree of unsaturation of the fatty acid(s) on an exterior position (if the total degree of unsaturation(s) is equal in both TAGs), (2) acyl chain length on the exterior positions, (3) cis/trans configuration, and (4) double bond (DB)-position. Finally, various cIMS-MS strategies were developed for the separation of mixtures containing four, five, and six isomers. To conclude, the developed methods can be used for separation of complex mixtures of TAG isomers and have great potential to be expanded to isomers of similar types of lipids such as di- and monoacylglycerols. This study also shows the potential of cIMS-MS to be used for the application on real TAG samples.

Interplay of coulomb and exciton-phonon coupling controls singlet fission dynamics in two pentacene polymorphs.

Pentacene is an important model organic semiconductor in both the singlet exciton fission (SF) and organic electronics communities. We have investigated the effect of changing crystal structure on the SF process, generating multiple triplet excitons from an initial singlet exciton, and subsequent triplet recombination. Unlike for similar organic semiconductors that have strong SF sensitive to polymorphism, we find almost no quantitative difference between the kinetics of triplet pair (TT) formation in the two dominant polymorphs of pentacene. Both pairwise dimer coupling and momentum-space crystal models predict much faster TT formation from the bright singlet excited state of the Bulk vs ThinFilm polymorph, contrasting with the experiment. GW and Bethe-Salpeter equation calculations, including exciton-phonon coupling, reveal that ultrafast phonon-driven transitions in the ThinFilm polymorph compensate the intrinsically slower purely Coulomb-mediated TT formation channel, rationalizing the similarity in observed rates. Taking into account the influence of subtle structural distinctions on both the direct and phonon-mediated SF pathways reveals a predictive capability to these methods, expected to be applicable to a wide variety of molecular crystals.

Construction and verification of an innovative immune-related and hallmark gene sets prognostic model for bladder cancer.

Bladder cancer (BC) is a life-threatening malignancy with high mortality rates. Current prognostic models are insufficient in accurately predicting clinical outcomes, impeding personalized treatment strategies. This study aimed to identify BC subtypes and prognostic gene sets by analyzing changes in immune and hallmark gene sets activity in tumor and adjacent non-tumor tissues to enhance patient outcomes. Utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), gene set variation analysis (GSVA) was applied to C7 immune-related and hallmark gene sets from the Molecular Signatures Database (MSigDB). The CancerSubtype R package was utilized for clustering these gene sets into three categories, from which 109 candidate sets were identified using Venn diagrams. A refined subset of seven gene sets was selected through least absolute shrinkage and selection operator (LASSO) regression for the construction of a risk model. Model validity was confirmed with receiver operating characteristic (ROC) and calibration curves, and a nomogram was constructed to integrate risk scores with clinical parameters. Finally, genes from the gene sets of the model were acquired and analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interactions (PPI) via plugin Molecular Complex Detection (MCODE) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) in Cytoscape in both tumor and non-tumor tissues. Three BC subtypes were characterized by immunologic and hallmark gene sets, with subtype 1 patients showing worse survival. The prognostic model, based on seven gene sets, effectively stratified risk, with high-risk patients having significantly shorter survival. GO, KEGG, and PPI analyses indicated distinct influences of non-tumor and tumor tissues on the prognosis of BC patients. We constructed and validated a novel prognostic model for risk stratification in BC based on immunologic and hallmark genes sets, which presents a novel perspective on rational treatment approaches and accurate prognostic evaluations for BC by considering both tumor and adjacent non-tumor tissues. This highlights the importance of focusing on alterations in both tumor and adjacent non-tumor tissues, rather than solely on the tumor itself.

Distinct influences of altitude on microbiome and antibiotic resistome assembly in a glacial river ecosystem of Mount Everest

The profound influences of altitude on aquatic microbiome were well documented. However, differences in the responses of different life domains (bacteria, microeukaryotes, viruses) and antibiotics resistance genes (ARGs) in glacier river ecosystems to altitude remain unknown. Here, we employed shotgun metagenomic and amplicon sequencing to characterize the altitudinal variations of microbiome and ARGs in the Rongbu River, Mount Everest. Our results indicated the relative influences of stochastic processes on microbiome and ARGs assembly in water and sediment were in the following order: microeukaryotes < ARGs < viruses < bacteria. Moreover, distinct assembly patterns of the microbiome and ARGs were found in response to differences in altitude, the latter of which shift from deterministic to stochastic processes with increasing differences in altitude. Partial least squares path modeling revealed that mobile genetic elements (MGEs) and viral β-diversity were the major factors influencing the ARG abundances. Taken together, our work revealed that altitude-caused environmental changes led to significant changes in the composition and assembly processes of the microbiome and ARGs, while ARGs had a unique response pattern to altitude. Our findings provide novel insights into the impacts of altitude on the biogeographic distribution of microbiome and ARGs, and the associated driving forces in glacier river ecosystems.

Improving Module Temperature Prediction Models for Floating Photovoltaic Systems: Analytical Insights from Operational Data

Floating photovoltaic (FPV) systems are gaining popularity as a valuable means of harnessing solar energy on unused water surfaces. However, a significant gap persists in our comprehension of their thermal dynamics and the purported cooling benefits they provide. The lack of comprehensive monitoring data across different climatic regions and topographies aggravates this uncertainty. This paper reviews the applicability of established module temperature prediction models, originally developed for land-based PV systems, to FPVs. It then details the refinement of these models using FPV-specific data and their subsequent validation through large-scale, ongoing FPV projects. The result is a significant improvement in the accuracy of temperature predictions, as evidenced by the reduced Mean Absolute Error (MAE) and improved R-squared (R2) after parameter optimisation. This reduction means that the tailored models better reflect the distinct environmental influences and cooling processes characteristic of FPV systems. The results not only confirm the success of the proposed method in refining the accuracy of current models, but also indicate significant post-tuning changes in the parameters representing wind and convective effects. These adjustments highlight the increased responsiveness of FPVs to convective actions, especially when compared to ground-based systems, possibly due to the evaporative cooling effect of bodies of water. Through this research, we address a critical gap in our understanding of heat transfer in FPV systems and aim to enrich the knowledge surrounding the acknowledged cooling effect of FPVs.

Do performance goals and fixed mindset explicate the relations between stereotype threat and achievement? Examining differences between racially marginalized and White students in STEM

This study examined whether performance goal orientations and mindset beliefs explicate the negative relation of ethnic stereotype threat with achievement and whether these processes vary depending on students' membership in a historically minoritized group. Multigroup analyses of undergraduate chemistry students (N = 1376) indicated that perceived ethnic stereotype threat was associated with lower achievement regardless of whether students were from underrepresented minority groups (URM). For URM students, compared to White students, ethnic stereotype threat more strongly predicted performance-avoidance goals. Further, fixed mindset beliefs moderated the relation of ethnic stereotype threat with performance goals for White students only. The relations of stereotype threat with performance goals were stronger for White students with a greater fixed mindset. Findings imply that while ethnic stereotype threat has the potential to detrimentally impact both URM and White students, motivational beliefs may exert somewhat distinct influences within each group, shaping the outcomes of stereotype threat. Educational relevanceIn our society, there are pervasive stereotypes about who can achieve success in competitive fields. Science learning contexts are no exception. In these contexts, and particularly among racially-marginalized students, anxieties about performing poorly and confirming stereotypes are prevalent, resulting in lower achievement for this student group (i.e., stereotype threat). In this study, we examined the consequences of ethnic stereotype threat for racially-marginalized and White students separately. Results revealed that ethnic stereotype threat led to lower science grades for both racially-marginalized and White students. For racially-marginalized students, ethnic stereotype threat also steered them toward goals focused less on growth and learning and more on avoiding looking incompetent to others (i.e., performance-avoidance goals). Further, for White students, a stronger belief that intelligence is fixed and cannot be improved (i.e., fixed mindset belief) exacerbated the negative effects of stereotype threat on their goal orientations, leading them to prioritize appearing intelligent and avoiding seeming incompetent to others. This research highlights the impact of ethnic stereotype threat on marginalized and non-marginalized students' motivational beliefs and achievement.

Finding emergence in data by maximizing effective information

Abstract Quantifying emergence and modeling emergent dynamics in a data-driven manner for complex dynamical systems is challenging due to emergent behaviors cannot be directly captured by micro-level observational data. Thus, it’s crucial to develop a framework to identify emergent phenomena and capture emergent dynamics at the macro-level using available data. Inspired by the theory of causal emergence (CE), this paper introduces a machine learning framework to learn macro-dynamics in an emergent latent space and quantify the degree of CE. The framework maximizes effective information, resulting in a macro-dynamics model with enhanced causal effects. Experimental results on simulated and real data demonstrate the effectiveness of the proposed framework. It quantifies degrees of CE effectively under various conditions and reveals distinct influences of different noise types. It can learn a one-dimensional coarse-grained macro-state from fMRI data, to represent complex neural activities during movie clip viewing. Furthermore, improved generalization to different test environments is observed across all simulation data.

From Invention to Acquisition: Evolution of an Electronic Sensor Startup Catalyzed by Nanotubes

Nanomaterials have many attractive properties, ranging from electrical to mechanical, that motivate their potential use in diverse applications. Beyond their inherent capabilities, nanomaterials wield a distinctive marketing influence, either catalyzing transformative support or acting as a hindrance for certain applications. Some sectors witness heightened investor and consumer interest when nanomaterials are proposed for product integration, driven by perceived high-tech advantages. Conversely, preconceived notions may diminish enthusiasm in fields citing environmental concerns or scale-up challenges. In this talk, I’ll share two examples of how the marketing dynamics of nanomaterials impacted funding for commercialization. First, I’ll share the story of Tyrata, a tire health sensor company that kicked off in 2017 with a $4.5M Series A investment based on the use of printed carbon nanotubes. While initial interest was enhanced thanks to nanomaterials, the company’s evolution saw a strategic shift in materials and structures. By late 2023, Bridgestone, a goal tire manufacturing giant, acquired Tyrata. I will highlight how a nanotube-based sensor start-up evolved to become a company with sensing systems all over the world, attracting attention from Fortune 500 companies. The second (brief) example I’ll share is regarding the use of nanomaterials in transistors and how the biases and shifting stigmas about their use have impeded progress. Overall, this talk will highlight some practicalities and realities of pursuing commercial applications of nanomaterials in electronic devices.

Microstructural Analysis of Lithium-Ion Battery Cathode Carbon-Binder Domain across Processing Conditions

Improvement of lithium-ion battery (LIB) energy density and rate capability is necessary to increase adoption of electric vehicles (EVs) and curb transportation emissions. The cathode structure must support facile ion and electron transport, enabling rapid charging while maintaining near-theoretical capacity. Much investigation focuses on active material design for fast-charging cathodes, [1] but less is understood about the effect of electrode processing on carbon-binder domain (CBD) structure and its impact on rate capability. As conductive carbon facilitates electron transfer, slow Li+ diffusion through cathode micropores is rate-limiting and prevents full active material utilization at high charge rates. [2,3] However, efforts to improve Li+ diffusion, such as increasing porosity, introduce charge-transfer limitations. [4] Thus, cathode processing conditions and resulting microstructure must be carefully designed to optimize for both electronic and ionic conductivity. For example, an increase in coating shear rate and decrease in slurry solid content improves long-range electronic pathways [5,6] and calendaring strengthens active material-carbon contacts to reduce charge-transfer resistance. [2] However, the impact of processing variations on ionic transport pathways, which can be described by CBD porosity and tortuosity, is not well understood. Further, because the CBD is traditionally characterized as a single phase, the distinct influences of insulating binder and conductive carbon distributions on structure and performance are poorly defined.In this talk, I will discuss how electrode coating conditions impact pathways available to Li+ and electrons within the CBD with the goal of identifying optimal microstructures for efficient transport. We fabricate cathodes with varying solid content, coating shear rate, and degree of calendaring to explore disparate CBD microstructures. We use electrochemical impedance spectroscopy (EIS) with a symmetric cell & blocking electrolyte to determine cathode resistivity and tortuosity and plasma focused ion beam scanning electron microscopy (PFIB-SEM) to examine CBD morphology over a representative cathode volume (~80 x 80 x 50 µm3). We then use small-angle neutron scattering (SANS) with solvent contrast variation to distinguish between binder and carbon distributions and determine the surface area of each component within the CBD. Relationships between processing conditions, structural variations, and rate capability will be discussed, informing the design of the CBD for facile transport and improved fast charging performance. Further, reducing ionic transport limitations through intentional design of LIB cathodes will enable thicker electrodes to increase cell energy density.

Global existence and uniform boundedness in a diffusive food chain model with direct and indirect prey‐taxis

In this paper, we propose a food chain model in which the primary predator moves directly toward areas of high prey density. Simultaneously, the primary predator, which serves as the prey for the secondary predator, indirectly influences the directional movements of the secondary predator through cues such as chemical signals, scents, or excretions. We investigate whether the distinct influences of direct taxis and indirect taxis, as observed in prey–predator dynamics, are also manifested in the proposed food chain model. Our study demonstrates that the model, which incorporates both direct and indirect prey‐taxis, possesses bounded and global solutions up to three‐dimensional space.

Understanding how governance arrangements within agricultural supply chains influence farmers' SAP adoption for adaptation and mitigation practices

CONTEXTIn order for farmers in developing countries to combat the effects of climate change, sustainable agricultural practices (SAP) have been promoted, but their adoption rate remains modest. Prior research examining psychological and socio-economic issues has identified farmers' limited knowledge and capital contribute to this problem. However, supply chain systems that require farmers to follow formal and informal rules (governance arrangements) have received little attention in previous studies. OBJECTIVEFrom a system thinking standpoint, this article seeks to comprehend farmers decision regarding SAP adoption by examining the influence of governance arrangements on the socioeconomic and psychological aspects of farmers. This paper concentrates specifically on governance arrangements between farmers and midstream actors, to whom farmers sell their products directly. METHODThis study utilises a qualitative research methodology, specifically employing multiple case studies. A system thinking approach utilising a Causal Loop Diagram was applied to comprehend farmers decision regarding SAP adoption. The case studies cover supply chain systems that have different governance arrangements. The study focused on examining the rice supply chains in Indramayu District and the fresh vegetable supply chains in West Bandung District, located in West Java, Indonesia. RESULTS AND CONCLUSIONThis paper found that different governance arrangements exhibit distinct influences, which in turn have varying impacts on farmers' decisions to adopt SAP. Governance arrangements that foster greater market integration and exert influence on the psychological (e.g., knowledge and information) and socio-economic (e.g., provision of production inputs and price assurance) aspects are regarded as the most effective approach to promoting the adoption of SAP by farmers. Furthermore, this paper revealed that midstream actors play a crucial role in promoting the adoption of SAP among farmers. SIGNIFICANCEThis paper contributes to the body of knowledge on how governance arrangements within agricultural supply chains influence farmers decision regarding SAP adoption. Specifically, it investigates the influence of midstream actors in facilitating farmers' adoption of SAP by addressing their psychological and socioeconomic requirements. The findings imply that government supports must be extended to midstream actors that have made efforts to persuade their farmers to implement SAP as a means of addressing climate change, as well as implementing midstream actors-to-farmer extension initiatives alongside the government's existing farmer-to-farmer extension programmes.