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  • Low-temperature lithium batteries improved by hierarchical solvation chemistry

    What the study found

    The study found that a hierarchically solvating electrolyte helped lithium-metal batteries perform better at low temperatures. The electrolyte used a weakly coordinating ether, tetrahydropyran, a strongly coordinating ester, methyl propionate, lithium difluoro(oxalato)borate, and trifluorotoluene as a non-solvating diluent.

    Why the authors say this matters

    The authors conclude that these findings offer design principles for tailoring solvation chemistry to enable high-performance lithium-metal batteries in extreme environments. The study suggests this approach may help address the poor low-temperature performance caused by slow lithium-ion transport and high desolvation energy penalties.

    What the researchers tested

    The researchers engineered a hierarchically solvating electrolyte system and examined how its composition changed the local solvation structure and solid electrolyte interphase, or SEI, which is the layer that forms on the battery interface. They tested Li||Li symmetric cells and Li||LiCoO2 full cells at low temperatures, including -25°C and -45°C.

    What worked and what didn't

    The electrolyte produced an anion-enriched primary solvation sheath that lowered the activation energy needed for lithium-ion desolvation. The addition of trifluorotoluene promoted aggregate-dominant solvation, and the resulting SEI was described as compact, homogeneous, and mechanically balanced with organic and inorganic components. Li||Li symmetric cells cycled for over 6000 hours at -25°C, and Li||LiCoO2 full cells retained 85.5% of nominal room-temperature capacity at -25°C and 66.2% at -45°C after 400 stable cycles.

    What to keep in mind

    The available summary does not describe broader testing beyond the reported cell types and temperatures. It also does not provide comparison details for all possible electrolyte formulations, only the hierarchically tuned system described in the abstract.

    • A hierarchically solvating electrolyte was designed for lithium-metal batteries.
    • The system combined tetrahydropyran, methyl propionate, LiDFOB, and trifluorotoluene.
    • The electrolyte formed an anion-enriched solvation sheath and a compact SEI.
    • Li||Li symmetric cells cycled for over 6000 hours at -25°C.
    • Li||LiCoO2 full cells kept 85.5% of nominal room-temperature capacity at -25°C and 66.2% at -45°C after 400 cycles.

  • Inertial active chains show multiple dynamical crossovers

    What the study found

    The study found that inertial active particles in a one-dimensional chain can show multiple crossovers between ballistic, diffusive, and subdiffusive behavior. It also found non-Gaussian fluctuations in active Brownian particles, with probability distributions that can be heavy-tailed, finite-support, or bimodal over time.

    Why the authors say this matters

    The authors conclude that this framework connects multiparticle interactions to microscopic dynamics. They also say it reveals experimentally accessible signatures of inertia in active matter, where active matter refers to systems of self-propelled particles.

    What the researchers tested

    The researchers studied inertial active particles arranged in a one-dimensional chain with harmonic nearest-neighbor interactions. Using a Green's function approach, they derived the mean-squared displacement and mean-squared change in velocity, and they analyzed excess kurtosis, a measure of how much a distribution differs from a Gaussian, for active Brownian particles.

    What worked and what didn't

    The analysis produced analytic expressions for scaling coefficients and crossover times. It also showed time-dependent probability distributions with distinct data collapses in different temporal regimes, which the authors say confirms the scaling behavior. The abstract does not report any failed tests or negative findings.

    What to keep in mind

    The summary does not describe experimental validation, so the scope here is theoretical analysis. It is also limited to a one-dimensional chain with harmonic nearest-neighbor interactions, and the abstract does not list additional limitations.

    • Inertial active particles can show ballistic, diffusive, and subdiffusive motion in one-dimensional chains.
    • The study derives mean-squared displacement and mean-squared change in velocity using a Green's function approach.
    • Non-Gaussian fluctuations were captured with excess kurtosis in active Brownian particles.
    • Probability distributions evolved into heavy-tailed, finite-support, or bimodal forms over time.
    • The authors say the framework reveals experimentally accessible signatures of inertia in active matter.

  • Hierarchical eco-zonation identified five ecoregions in Uganda

    What the study found

    The study found that a hierarchical eco-zonation framework could delineate five ecoregions in Uganda and subdivide them into three finer bioregion levels. The coarsest levels showed stronger ecological coherence than the finer levels.

    Why the authors say this matters

    The authors conclude that the framework offers a flexible, open-data and open-software approach for ecological stratification and biogeographical analysis in data-scarce Afrotropical landscapes. They say it supports biodiversity assessment, conservation planning, and ecological management applications.

    What the researchers tested

    The researchers tested a machine-learning workflow that combined multiple algorithms with open-source software and globally accessible datasets. Using Uganda as a case study, they modeled eco-zonation with climate, topography, and hydrological variables, then compared the results with potential natural vegetation using spatially dispersed 10-fold cross-validation.

    What worked and what didn't

    Predictive accuracy declined from 80.35% at the ecoregion level to 52.69% at bioregion level III. The two coarsest tiers, ecoregions and bioregion I, showed strong ecological coherence, while bioregion II and bioregion III showed weak coherence.

    What to keep in mind

    The finer tiers lacked empirical ecological validation and were described as experimental abiotic subdivisions meant to capture theoretical fine-scale heterogeneity. The abstract says that the limited thematic resolution of available biota datasets is a key constraint for robust finer-scale ecological stratification.

    • Five ecoregions were delineated for Uganda.
    • Those ecoregions were subdivided into three bioregion levels.
    • Ecological coherence was stronger at the two coarsest tiers than at finer tiers.
    • Predictive accuracy fell from 80.35% to 52.69% across the hierarchy.
    • The authors link weaker fine-scale results to limited thematic resolution in available datasets.

  • Human activity, snow cover, and precipitation shape Altai mammal and bird ranges

    What the study found

    The study found that most of the 27 animal species analyzed are predicted to occur mainly in the northwest of the Altai Mountains under current conditions. It also found that, in future scenarios, habitats in the central region may be largely lost and many species may shift toward higher altitudes or latitudes.

    Why the authors say this matters

    The authors say the findings matter because ongoing global climate change and human activities are altering potentially suitable habitats in the Altai Mountains. They conclude that a transboundary protected area across China, Kazakhstan, Mongolia, and Russia, along with reduced human impacts on wildlife and habitats, is warranted.

    What the researchers tested

    The researchers evaluated and predicted the distribution dynamics of 27 animal species and the resulting changes in species richness in the Altai Mountains. They used the MaxEnt model, a species distribution modeling approach, for current and future periods and examined human activity, snow cover, and precipitation of the coldest quarter as predictors.

    What worked and what didn't

    Human activities, snow cover, and precipitation of the coldest quarter were identified as the most important predictors for the potential distributions of most species. Most species were predicted to be concentrated in the northwest under current conditions, while central habitats were projected to be lost in the future. The study also reports a tendency for range shifts toward higher altitudes or latitudes.

    What to keep in mind

    The abstract does not describe detailed limitations, uncertainty ranges, or model performance measures. The summary is limited to the 27 species studied in the Altai Mountains and to the current and future periods analyzed with the MaxEnt model.

    • Most of the 27 species are predicted to be mainly distributed in the northwest of the Altai Mountains now.
    • Future habitats in the central Altai Mountains may be largely lost.
    • Many species are expected to shift toward higher altitudes or latitudes.
    • Human activity, snow cover, and coldest-quarter precipitation were the strongest predictors reported.
    • The authors recommend a transboundary protected area across China, Kazakhstan, Mongolia, and Russia.

  • Book reviews epidemic institutions across seven centuries

    What the study found

    The text says the book explores seven centuries of history to examine how human societies dealt with epidemic disease. It highlights institutional features that made responses to epidemics better coordinated and helped institutions improve societal learning.

    Why the authors say this matters

    The abstract says the book highlights features that have made institutional frameworks better at coordinating responses to epidemics and better at devising innovations to improve societal learning. The study suggests this historical review is relevant for understanding how institutions handle epidemic disease.

    What the researchers tested

    This is a review of Sheilagh Ogilvie's book by Vellore Arthi. The Econlit abstract describes the book as examining seven centuries of history, from the Black Death to Covid-19, to investigate how societies dealt with epidemic disease.

    What worked and what didn't

    The only results described in the available text are that the book identifies institutional frameworks as better at coordinating epidemic responses and at devising innovations that improve societal learning. No specific cases, comparisons, or negative findings are given in the abstract.

    What to keep in mind

    The available summary is very brief and does not describe the book's detailed arguments, evidence, or limitations. It also does not provide specific findings beyond the broad claims about institutions and epidemic response.

    • The book examines seven centuries of history on epidemic disease.
    • It focuses on how societies and institutions responded to epidemics.
    • The abstract says institutional frameworks were better at coordinating responses and supporting societal learning.
    • The text covers the period from the Black Death to Covid-19.
    • No detailed methods, evidence, or limitations are given in the available abstract.

  • Atypical childhood tuberculosis presented as a mediastinal mass

    What the study found

    The study reports a child with extrapulmonary tuberculosis, meaning tuberculosis outside the lungs, that appeared as a large mediastinal mass. The authors say this was an atypical presentation that mimicked other conditions.

    Why the authors say this matters

    The authors conclude that paediatric tuberculosis can be hard to recognize because symptoms may be non-specific and initial microbiological tests may be negative. They say maintaining a high index of suspicion and obtaining tissue diagnosis are important when extrapulmonary tuberculosis is suspected.

    What the researchers tested

    This is a case report of one child with lethargy, significant weight loss, and no cough, who had reduced air entry on the left side. Laboratory testing showed elevated inflammatory markers, and the child was evaluated for a mediastinal cystic lesion.

    What worked and what didn't

    The child was ultimately proven to have extrapulmonary tuberculosis, despite the initial presentation resembling other pathologies. The abstract does not describe the full diagnostic sequence, treatment details, or comparative outcomes beyond noting that early recognition and appropriate management are important.

    What to keep in mind

    This summary describes a single child, so it is a limited example rather than a broader study of children with tuberculosis. The abstract does not provide detailed limitations or long-term follow-up.

    • A child with tuberculosis presented as a large mediastinal mass.
    • The case was described as extrapulmonary tuberculosis with an atypical appearance.
    • The child had lethargy, significant weight loss, and no cough.
    • Initial microbiological tests were negative, according to the authors.
    • The authors emphasize the importance of tissue diagnosis when extrapulmonary tuberculosis is suspected.

  • Intelligent management framework proposed for cooperative digital libraries

    What the study found

    The study proposes an intelligent management framework for cooperative digital library systems that include AI-based services such as decision-making and recommendation mechanisms. The authors report that participants in their case study considered the approach clear, feasible, and useful for digital transformations.

    Why the authors say this matters

    The authors say the framework addresses management problems in cooperative digital library systems that traditional management systems do not cover. They also state that it may be useful for government organizations undergoing digital transformation.

    What the researchers tested

    The researchers used a top-down design approach based on six abstractions and four refinement techniques to build a management model. They evaluated the approach by designing an intelligent management framework for a cooperative, intelligent digital library system in a government organization and used a qualitative case study with questionnaire data.

    What worked and what didn't

    The abstract says the framework was designed to integrate cooperative models, system behaviors, software architecture, and processes for managing intelligent digital library services. In the case study, participants described the solution as clear, feasible, and useful, and said they would strongly recommend it for other government organizations. The abstract does not describe what did not work.

    What to keep in mind

    The summary is based on one government-organization case study, so the reported findings are limited to that setting. The abstract does not provide detailed quantitative results or describe specific limitations beyond the scope of the case study.

    • The paper proposes an intelligent management framework for cooperative digital library systems with AI services.
    • The framework is designed using a top-down approach with six abstractions and four refinement techniques.
    • A government-organization case study found participants viewed the approach as clear, feasible, and useful.
    • Participants said they would strongly recommend the solution for other government organizations.
    • The abstract says traditional digital collection management systems do not adequately cover these intelligent service management needs.

  • Misconceptions in chemistry were linked to lower self-efficacy

    What the study found

    Students with more chemistry misconceptions reported lower organic chemistry self-efficacy, meaning lower confidence in their ability to do well in the course. Students retaking organic chemistry were also more likely to show misconceptions at the start of the semester.

    Why the authors say this matters

    The authors suggest that addressing common misconceptions early in the semester could support students' self-efficacy and improve course outcomes. They also conclude that organic chemistry instructors may benefit from explicit instruction on foundational chemistry concepts.

    What the researchers tested

    The study examined the relationship between university students' chemistry misconceptions and their organic chemistry self-efficacy during the first semester of the course. Students were surveyed using validated instruments aligned with NGSS, or Next Generation Science Standards, foundational chemistry concepts and established self-efficacy scales, along with demographic questions.

    What worked and what didn't

    The results showed a significant negative correlation between misconceptions and self-efficacy. The study also found that students retaking organic chemistry were more likely to have misconceptions at the beginning of the course.

    What to keep in mind

    The abstract does not describe detailed study size, setting, or other limitations. The findings are limited to the first semester of the course and to the relationships measured in this study.

    • Students with more chemistry misconceptions reported lower organic chemistry self-efficacy.
    • Students retaking organic chemistry were more likely to show misconceptions at the start of the course.
    • The study used validated surveys on foundational chemistry concepts and self-efficacy.
    • The authors suggest early instruction on misconceptions may support student confidence.

  • Neural activity predicted treatment response in internalizing disorders

    What the study found

    The review found that baseline neural activity during emotion regulation was often linked to treatment response in internalizing disorders such as depressive and anxiety disorders. In general, lower pre-treatment activity in medial and lateral prefrontal cortices during explicit regulation tasks was associated with greater symptom improvement, while higher baseline activity in prefrontal and anterior cingulate regions during implicit regulation tasks was often associated with greater symptom improvement.

    Why the authors say this matters

    The authors conclude that neural predictors of treatment outcome may contribute to precision medicine, meaning treatment could be better matched to patients. They also suggest that these predictors may help improve treatment outcomes in internalizing disorders.

    What the researchers tested

    This was a narrative review of functional magnetic resonance imaging studies, or fMRI studies that measure brain activity. The review examined studies of explicit emotion regulation, such as cognitive reappraisal or effortful regulation, and implicit emotion regulation, such as automatic regulation, in relation to treatment response for negative stimuli in internalizing disorders.

    What worked and what didn't

    Across the reviewed studies, treatments mostly included cognitive behavioral therapy, exposure therapy, and/or pharmacotherapy. For explicit regulation, pre-treatment activity in medial and lateral prefrontal cortices frequently predicted treatment response, and lower baseline activity was generally linked to greater symptom improvement. For implicit regulation, predictors often involved prefrontal cortical regions and the anterior cingulate cortex, with more baseline activity generally predicting greater symptom improvement; findings in other regions, including the amygdala, were less consistent.

    What to keep in mind

    The review notes substantial gaps in the literature. Most explicit regulation studies focused on cognitive reappraisal, and most studies involved major depressive disorder, anxiety disorders, and posttraumatic stress disorder, with insufficient representation of other internalizing disorders.

    • Baseline brain activity during emotion regulation was often associated with treatment response.
    • Lower pre-treatment activity in medial and lateral prefrontal cortices during explicit regulation was generally linked to greater symptom improvement.
    • Higher baseline activity in prefrontal and anterior cingulate regions during implicit regulation was generally linked to greater symptom improvement.
    • Most reviewed studies examined cognitive behavioral therapy, exposure therapy, and/or pharmacotherapy.
    • The literature was limited by a heavy focus on cognitive reappraisal and a few internalizing disorders.

  • AI and ML are reshaping international business research

    What the study found

    The authors argue that AI and ML can transform international business research by making it possible to analyze large-scale, multimodal data and detect patterns relevant to theory and evidence. They also present a structured roadmap for bringing these techniques into international business research.

    Why the authors say this matters

    The study suggests that AI and ML are not just analytical tools but may be transformative for the future of international business research. The authors say this matters because linking methodological innovation with conceptual advancement can support new work on international business topics such as foreignness, legitimacy, and deglobalization.

    What the researchers tested

    This is a research article that reviews AI- and ML-based techniques for international business research. The paper covers supervised methods, unsupervised methods, generative AI, and multimodal approaches, and it discusses how these can be applied to core international business constructs.

    What worked and what didn't

    The paper says these methods can enrich understanding of foreignness, legitimacy, internationalization strategy, corporate governance, distance, and deglobalization. It also notes that the methodological breadth and technical complexity of AI and ML create significant challenges for many international business scholars.

    What to keep in mind

    The abstract does not report empirical testing or specific quantitative results. It also does not provide detailed limitations beyond noting the technical and methodological challenges of integrating AI and ML into international business research.

    • AI and ML are presented as tools that can analyze large-scale, multimodal data in international business research.
    • The paper offers a structured roadmap for integrating AI- and ML-based techniques into the field.
    • The authors review supervised, unsupervised, generative AI, and multimodal approaches.
    • The paper says these methods can enrich constructs such as foreignness, legitimacy, and deglobalization.
    • The abstract notes that AI and ML pose methodological and technical challenges for many scholars.