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  • Four-parameter turbulence model improves lead-bismuth heat transfer prediction

    What the study found

    The study developed a four-parameter turbulence heat transfer model for liquid lead-bismuth eutectic (LBE) systems and a solver called LBEHMTFoam. The authors report that the model was validated against direct numerical simulation (DNS) data for planar flow heat transfer and then applied to LBE fuel assemblies.

    Why the authors say this matters

    The authors say LBE is a coolant with good thermo-hydraulic properties and chemical inertness for fast reactors, but its low Prandtl number and nonlinear local turbulent Prandtl number make constant-Prandtl-number approaches difficult for complex turbulent heat transfer. They conclude that more accurate prediction tools have significant engineering value and could be useful for predicting thermo-hydraulic coupled corrosion behavior in LBE systems.

    What the researchers tested

    The researchers systematically derived the four-parameter turbulence heat transfer model and its boundary conditions under a constant heat flux boundary. They implemented the model in the open-source CFD (computational fluid dynamics) software OpenFOAM as the solver LBEHMTFoam, then compared planar flow heat transfer simulations with DNS data and compared fuel-assembly heat and mass transfer simulations with empirical correlations.

    What worked and what didn't

    The abstract says the model's accuracy was validated by agreement with DNS data for planar flow heat transfer. It also says simulations for LBE fuel assemblies were compared with empirical correlations, but it does not provide specific numerical performance results in the abstract.

    What to keep in mind

    The available summary does not report detailed quantitative results, error measures, or limitations. It also does not specify how broadly the model applies beyond the tested planar flow case and the 19-pin fuel assembly context in LBE-cooled reactors.

    • A four-parameter turbulence heat transfer model was developed for liquid lead-bismuth eutectic systems.
    • The model was implemented in OpenFOAM as a solver named LBEHMTFoam.
    • Planar flow heat transfer simulations were validated against direct numerical simulation data.
    • Fuel-assembly heat and mass transfer simulations were compared with empirical correlations.
    • The abstract says the tool may be useful for predicting thermo-hydraulic coupled corrosion behavior in LBE systems.

  • Permafrost thaw drives old dissolved carbon into Siberian lakes

    What the study found

    The study found that permafrost thaw affects dissolved and particulate organic matter in different ways in Siberian thermokarst lakes. Up to 75% of dissolved organic carbon in recent lakes and early-Holocene lakes modified by recent thermokarst came from thawing permafrost, and these lakes had the highest concentrations of old dissolved organic carbon reported for this type of lake.

    Why the authors say this matters

    The authors say this matters because understanding permafrost thaw requires knowing how much dissolved and particulate organic carbon is released and how much becomes greenhouse gases. The study suggests that much of the permafrost-derived dissolved organic carbon accumulates rather than being fully converted into carbon dioxide or methane.

    What the researchers tested

    The researchers examined old and recent thermokarst lakes in Central Yakutia, Siberia. They compared dissolved organic carbon and particulate organic carbon to assess their origins, how much came from permafrost thaw, and how the carbon was converted into greenhouse gases.

    What worked and what didn't

    Particulate organic carbon was largely modern and came from lake primary production. In contrast, dissolved organic carbon was often old and permafrost-derived, with up to 75% traced to thaw in the recent and early-Holocene lakes studied. Despite the high lability of this dissolved carbon, it fueled only a fraction of carbon dioxide emissions; methane and the remaining carbon dioxide emissions came from recently produced carbon.

    What to keep in mind

    The findings are based on thermokarst lakes in Central Yakutia, Siberia, so the study’s scope is regional. The abstract does not describe specific limitations beyond noting that the conversion of dissolved and particulate organic carbon into greenhouse gases remains critically underexplored.

    • Up to 75% of dissolved organic carbon in some lakes came from permafrost thaw.
    • The highest concentrations of old dissolved organic carbon reported in thermokarst lakes were found in the studied lakes.
    • Particulate organic carbon was mostly modern and linked to lake primary production.
    • Permafrost-derived dissolved organic carbon fueled only a fraction of carbon dioxide emissions.
    • Methane and the remaining carbon dioxide emissions came from recently produced carbon.

  • Sports tokens show spillover risk and portfolio benefits

    What the study found

    The study found that sports tokens and sports equities are connected to risk spillovers with traditional assets. It also found that the minimum connectedness portfolio suggests possible portfolio benefits from using sports tokens.

    Why the authors say this matters

    The authors conclude that the findings provide information for market participants to manage asset risk. The study suggests that understanding these spillovers may help in curbing asset management risk.

    What the researchers tested

    The researchers examined risk spillover across sports tokens, sports equities, and other traditional assets using a quantile-VAR model, which is a model for analyzing relationships across different parts of the return distribution. They also used a minimum connectedness portfolio analysis.

    What worked and what didn't

    In the static analysis, token BAR was reported to cause significant shocks to the system. At the lower quantile, the USD was both the highest contributor and the highest receiver in the network, and OG was described as the dominant contributor. The portfolio analysis suggested possible benefits from using sports tokens.

    What to keep in mind

    The abstract does not describe detailed data, sample size, time period, or asset list beyond the examples named. It also does not provide full numerical estimates or specify which particular portfolio settings produced the reported benefits.

    • The study examined risk spillovers across sports tokens, sports equities, and traditional assets.
    • BAR was reported to cause significant shocks in the static analysis.
    • At the lower quantile, the USD was the highest contributor and the highest receiver in the network.
    • OG was described as the dominant contributor to the system.
    • The minimum connectedness portfolio suggested possible portfolio benefits from sports tokens.

  • ESG disclosure rules are becoming more binding and fragmented

    What the study found

    The article finds that environmental, social, and governance (ESG) regulation is developing through a fragmented mix of binding and non-binding rules, with ambiguities and power dynamics shaping how it works. It also finds a shift from voluntary corporate social responsibility (CSR) to more binding legal obligations, especially in the EU compared with the U.S.

    Why the authors say this matters

    The authors conclude that a coherent legal framework and harmonized standard-setting mechanisms are needed to support ESG compliance, transparency, and accountability. They also state that greater interoperability among emerging standards is essential to reduce compliance burdens and support consistent, comparable ESG reporting globally.

    What the researchers tested

    The article uses a legal and comparative analysis of ESG regulation and standardization from a global perspective. It compares disclosure regimes in the U.S. and the EU, categorizes sustainability standards into binding and non-binding forms, and distinguishes between de jure and de facto instruments.

    What worked and what didn't

    The study provides a legally grounded typology of ESG authority and a comparative snapshot of global ESG standard integration and regulatory approaches. It also identifies definitional inconsistencies and methodological challenges in ESG standards, ratings, and frameworks, and it notes divergent disclosure regimes between voluntary ESG disclosure in the U.S. and mandatory reporting frameworks in the EU.

    What to keep in mind

    The abstract does not describe empirical testing or specify a single dataset, and it does not provide detailed limitations. Its scope is legal and comparative, focused on ESG disclosure standards and regulatory approaches rather than on measuring outcomes in organizations.

    • ESG governance is described as fragmented, ambiguous, and shaped by power dynamics.
    • The article traces a shift from voluntary CSR to binding legal ESG obligations.
    • The U.S. and EU are presented as having different ESG disclosure regimes.
    • The study distinguishes binding vs non-binding and de jure vs de facto sustainability standards.
    • The authors say interoperability among standards is needed to reduce compliance burdens.
  • HPO-VMD-BiLSTM improved short-term photovoltaic power prediction

    HPO-VMD-BiLSTM improved short-term photovoltaic power prediction

    What the study found

    The study reports that a photovoltaic power prediction method combining improved K-means clustering, HPO-VMD, and HPO-BiLSTM was effective. The authors say the experimental and analytical results verified the method’s effectiveness and generalization.

    Why the authors say this matters

    The authors say photovoltaic power generation is affected by volatile meteorological factors, which can seriously influence the stability of grid connection. They present their method as a way to improve prediction accuracy under these conditions.

    What the researchers tested

    The researchers built a numerical prediction method for photovoltaic power generation. They used arrangement entropy combined with K-means clustering for weather typing, HPO-VMD for adaptive data decomposition, and a BiLSTM model whose parameters were adjusted using the hunter-prey algorithm (HPO).

    What worked and what didn't

    The abstract says the weather-typing step was used to reduce the influence of data diversity and randomness on prediction accuracy. It also says HPO-VMD was used to handle strong volatility and randomness in photovoltaic power data, and HPO was used to reduce the negative effects of poorly chosen model parameters. The abstract does not report any specific numerical results or failures.

    What to keep in mind

    The available summary does not give quantitative performance measures, comparison baselines, or detailed limitations. The testing described in the abstract was based on actual data from the Alice Springs site, so the stated validation is limited to that data source in the summary provided.

    • The study proposes a short-term photovoltaic power prediction method combining improved K-means, HPO-VMD, and HPO-BiLSTM.
    • Arrangement entropy was combined with K-means clustering to support weather typing.
    • HPO-VMD was used for adaptive data decomposition to address volatility and randomness in photovoltaic power data.
    • A BiLSTM model was used for numerical prediction, with HPO used to adjust model parameters.
    • The abstract says experiments on Alice Springs data verified effectiveness and generalization.

  • Pediatric maxillary mesenchymal chondrosarcoma was confirmed by HEY1::NCOA2 fusion

    What the study found

    The report describes a 13-year-old girl with a destructive right maxillary sinus mass that was ultimately confirmed as mesenchymal chondrosarcoma through detection of a HEY1::NCOA2 gene fusion. The authors present this as a rare pediatric case of maxillary mesenchymal chondrosarcoma with this fusion and sirolimus-based maintenance therapy.

    Why the authors say this matters

    The authors conclude that molecular diagnostics, especially RNA sequencing, are important for identifying mesenchymal chondrosarcoma and separating it from other high-grade pediatric sarcomas with similar appearance. They also suggest that finding the HEY1::NCOA2 fusion may support biologically targeted therapy.

    What the researchers tested

    This is a case report and literature review. The team evaluated imaging, histopathology, immunohistochemistry, comprehensive molecular analysis, and follow-up 18F-FDG PET/CT, and then used multimodal treatment including chemotherapy, radiotherapy, surgery, and maintenance sirolimus.

    What worked and what didn't

    Histopathology initially interpreted the tumor as fibrosarcoma, with diffuse vimentin positivity, a Ki-67 proliferation index of 35%–40%, and CD34 negativity. Molecular analysis confirmed a pathogenic HEY1::NCOA2 fusion and excluded ETV6::NTRK3 fusion; after VAC chemotherapy, radiotherapy, and debulking surgery, follow-up PET/CT showed a partial metabolic response, and sirolimus maintenance was started because disease persisted.

    What to keep in mind

    This is a single case report, so the findings are limited to one patient. The abstract does not provide longer-term outcomes, and it does not describe broader effectiveness of sirolimus-based maintenance therapy beyond this case.

    • A 13-year-old girl had a destructive mass in the right maxillary sinus.
    • The tumor was initially read as fibrosarcoma on histopathology.
    • Comprehensive molecular analysis confirmed a HEY1::NCOA2 gene fusion and excluded ETV6::NTRK3 fusion.
    • Treatment included VAC chemotherapy, radiotherapy, debulking surgery, and sirolimus maintenance.
    • Follow-up 18F-FDG PET/CT showed a partial metabolic response.

  • Review maps economics of climate adaptation research

    What the study found

    The review found that climate adaptation economics has developed into a broad research area with evolving trends, methods, and themes. It also found that adaptation responses differ across households and firms, and that recent work increasingly uses integrated, multi-method analyses.

    Why the authors say this matters

    The authors conclude that adaptation is a critical part of global climate risk management. They also suggest the field should better identify heterogeneous adaptation behaviors, study vulnerable regions, and improve long-term modeling and related theory.

    What the researchers tested

    The researchers conducted a systematic review and bibliometric analysis of 6,248 publications from 1978 to 2025. They also evaluated core methodological approaches used in the field and synthesized theoretical and empirical findings.

    What worked and what didn't

    The review says methods have strengths for capturing behavioral responses, estimating causal effects, and modeling dynamic optimization. It reports a shift away from static frameworks toward integrated, multi-method analyses, and it identifies household responses such as consumption changes, agricultural practices, and migration, as well as firm responses including product diversification, relocation, supply chain reconfiguration, and technological innovation.

    What to keep in mind

    The abstract does not report study-specific limitations beyond noting future research needs. The review’s findings are based on the publications it analyzed and on the topics described in the abstract.

    • The paper is a systematic review and bibliometric analysis of 6,248 publications on climate adaptation economics.
    • The authors describe adaptation as a critical component of global climate risk management.
    • Research methods in the field are described as shifting from static frameworks to integrated, multi-method analyses.
    • Households adapt through consumption changes, agricultural practices, and migration.
    • Firms adapt through product diversification, relocation, supply chain reconfiguration, and technological innovation.
  • Finnish words for light and day are examined in northern seasonal contexts

    Finnish words for light and day are examined in northern seasonal contexts

    What the study found

    The abstract describes a study of Finnish words and expressions for light, day, night, and related ideas in the context of strong seasonal changes in Nordic countries. It indicates that the authors examine how Finnish ways of speaking about these concepts relate to human life rhythms in the high north.

    Why the authors say this matters

    The authors say the changing hours of daylight have profound practical and psychological effects, creating mismatches between natural light and human routines. The study suggests that understanding Finnish semantic patterns may help explain how daily life is maintained through lexical, conceptual, social, and technological scaffolding.

    What the researchers tested

    The researchers used NSM semantic explications and cultural scripts to examine the meanings and uses of Finnish words for light, day, night, and related expressions. They drew on Finnish lexical resources, including the Dictionary of Contemporary Finnish and the Finnish Language Text Bank, research literature, and dialogical discussions between the two authors, who are native speakers of Finnish and English.

    What worked and what didn't

    The study reports that close examination of lexical polysemy, meaning a word having multiple related senses, and phraseology is required for this topic. It does not present specific empirical findings in the abstract, but states three goals: to unpack Finnish ways of thinking and speaking about light and life, to compare Finnish semantic molecules with counterparts in other languages, and to explore scaffolding for daily rhythms.

    What to keep in mind

    The abstract does not give detailed results, so the available summary is mainly about the study's aims and approach. It also does not describe sample size, data selection procedures, or specific limitations beyond the need for close lexical analysis.

    • The study examines Finnish words and expressions for light, day, night, and related concepts.
    • It focuses on the effects of strong seasonal daylight changes in Nordic countries, especially at high latitudes.
    • The authors say changing daylight has practical and psychological effects and can conflict with human routines.
    • The study uses NSM semantic explications and cultural scripts, along with Finnish lexical resources and research literature.
    • The abstract does not report specific results beyond the study's aims and analytical focus.

  • TESS observations reveal active flaring in PM J11183+1347

    What the study found

    The study found that PM J11183+1347, an M dwarf star, is strongly magnetically active and shows rotational changes and frequent flaring. The authors report flare energies from 1.59 × 10^32 to 1.05 × 10^34 erg, with several superflares above 10^33 erg.

    Why the authors say this matters

    The findings indicate that the star’s activity is consistent with strong surface magnetism, including spot-related variability and flare behavior. The authors conclude that the flare frequency pattern and flare-duration relationship support magnetic reconnection as the main process behind the flares.

    What the researchers tested

    The researchers analyzed high-cadence light curves from the Transiting Exoplanet Survey Satellite (TESS) across four sectors. They used periodogram analysis to examine rotational modulation and studied detected flare events to measure their durations, energies, and shapes.

    What worked and what didn't

    They detected 21 flare events lasting 15 to 455 minutes. The light curves showed periods from 4.59 to 6.34 days, and the flare morphologies included classical single-peaked flares, complex multipeaked flares, and peak-bump structures.

    What to keep in mind

    The abstract does not describe limitations in detail. The reported period range may be attributed to differential rotation and evolving starspots, but the abstract presents this as a possible explanation rather than a confirmed one.

    • PM J11183+1347 is described as an active dMe-type M dwarf at 24.8 pc.
    • TESS light curves from four sectors showed rotational periods between 4.59 and 6.34 days.
    • The study detected 21 flare events with energies from 1.59 × 10^32 to 1.05 × 10^34 erg.
    • Several flares were classified as superflares with energies above 10^33 erg.
    • The flare frequency distribution followed a power law with index α = 1.57 ± 0.18.
    • Flare duration and energy were strongly correlated, with a correlation of about 0.96.
  • COVID-19 and non-COVID respiratory infections showed similar long-term health effects

    COVID-19 and non-COVID respiratory infections showed similar long-term health effects

    What the study found

    The study found no significant difference in long-term self-rated physical health or work-related functioning between people who tested positive for COVID-19 and people with similar respiratory symptoms who tested negative. Mental health scores were slightly higher in the non-COVID-19 group after adjustment for working status.

    Why the authors say this matters

    The authors conclude that the long-term impact of COVID-19 on self-rated physical health and work-related functioning appears comparable to the impact of other viral respiratory illnesses with similar acute symptoms. The study suggests the need for comprehensive rehabilitation strategies focused on symptom management regardless of the specific viral cause.

    What the researchers tested

    The researchers conducted a questionnaire study about two years after patients were tested for COVID-19 during the first wave of the pandemic in Denmark. They used validated questionnaires for self-assessed health status (SF-12, a general health survey) and work-related functional ability (WORQ), and compared answers between PCR-positive and PCR-negative participants.

    What worked and what didn't

    A total of 463 participants responded, which was a 17% response rate. After adjusting for relevant confounders, there were no significant differences between PCR-positive and PCR-negative participants in work-related functional ability or self-assessed physical health; mental health was slightly higher in the PCR-negative group (49.3 vs. 47.5, p < 0.009) after adjustment for working status.

    What to keep in mind

    The study relies on self-reported questionnaire data collected about two years after testing. The response rate was low at 17%, and the abstract does not describe additional limitations beyond this.

    • The study compared long-term outcomes in PCR-positive and PCR-negative patients with similar respiratory symptoms.
    • No significant differences were found in work-related functional ability or self-assessed physical health after adjustment.
    • Mental health scores were slightly higher in the non-COVID-19 group after adjustment for working status.
    • The study used SF-12 and WORQ questionnaires about two years after testing.
    • The response rate was 17% among 463 participants.