Continental-scale bias correction and random forest downscaling of CMIP6 precipitation across Europe

This study evaluated bias-correction-based downscaling approaches for precipitation data from 11 high-resolution CMIP6 models across Europe. The empirical quantile mapping technique demonstrated superior performance by aligning the model outputs with observed precipitation data. Random forest-empirical quantile mapping model outperformed the random forest model, particularly for low rainfall intensities (0–5 mm/day), and exhibited residual errors closer to zero across most European regions. Precipitation overestimations by CMIP6 models in Central and Eastern Europe were significantly reduced through the application of empirical quantile mapping, random forest and random forest empirical quantile mapping approaches. Seasonal analysis revealed lower residual errors in summer than in winter for the evaluated methods. Future projections will provide insights into the reduced overestimation of high quantiles, leading to reliable precipitation estimates. The proposed methodological framework suggests that integrating bias correction complemented by machine learning techniques enhances the accuracy of regional precipitation downscaling, which is crucial for climate risk management in Europe.

Thermomechanical Analysis of X-Braces in Steel Structures Under Fire Conditions

Bracing systems in steel structures are crucial for providing stability and resistance against lateral forces such as wind and earthquakes. However, when steel structures are exposed to fire, the bracing systems can also play an important role in maintaining the structural integrity of the building. Under fire conditions, steel members may lose strength due to heating, which can lead to collapse if not properly braced. In this article the effect of different X-braces cross-section in a steel warehouse under fire is analyzed and discussed using a non-linear thermomechanical model. Three fire scenarios have been considered: standard ISO834 fire, wood fire and plastic fire to investigate the influence of different temperature time history curves on the thermomechanical behavior of the structure. It has been found that an increase in the stiffness of the braces leads to a corresponding increase in the stiffness of the frame modifying its structural behavior; furthermore, since the compressed braces reach their buckling load in the initial minutes of a fire, the structure must redistribute its loads accordingly.

Forensic evaluation of detour traffic damage and compensation frameworks for local roads

Highway construction projects often divert traffic onto local roads that are not designed for heavy vehicles, accelerating pavement deterioration and increasing maintenance costs. This study presents a forensic investigation of six Minnesota counties to quantify damage from detour and haul traffic and assess the adequacy of current compensation methods. Traffic monitoring revealed substantial increases in heavy vehicle volumes and Equivalent Single Axle Loads (ESAL), in some cases exceeding 900%. Structural and surface conditions were evaluated using Falling Weight Deflectometer (FWD) testing, dynamic modulus (|E*|) measurements, and MnDOT’s Digital Inspection Vehicle data, generating pavement quality (PQI), ride quality (RQI), and surface distress (SR) indices. Results indicate consistent deterioration in both structural capacity and surface condition. FWD-based moduli decreased after detour operations, while dynamic modulus values were less sensitive to short-term loading. Compensation estimates based on MnDOT and IDOT Gas Tax Methods, the Equivalent Overlay Method, and the Granular Equivalent (GE) Difference Method show that gas tax approaches significantly underestimate costs, whereas engineering-based methods, although more realistic, do not incorporate measured damage. The findings reveal a disconnect between observed deterioration and existing reimbursement practices, underscoring the need for a damage-based compensation framework.

Associative Thinking and Creative Ability in Older Adulthood

Successful problem-solving and enhanced creative ability may improve physical health, cognitive well-being, and overall independence of older adults. In general, older adults who are more creative, may be better able to cope with cognitive decline and navigate everyday tasks. While previous research on creative performance in older adulthood showed age-related stability, open questions remain regarding the specific underlying cognitive basis for this invariability across the lifespan. Mediation analyses showed that intelligence measures served as underlying cognitive mechanisms for the stability of creative thinking in older age. The broader implications of these findings provide insight into the complex relationships supporting age-related preservation in creativity.

From the Editor

Moving Beyond “Hands-On” Instruction: Preservice Elementary Teachers Focusing on Sensemaking

In our elementary science methods courses, we aim to shift our preservice teachers’ view of science instruction beyond teacher-directed, hands-on “touching and telling,” toward a student-centered approach that emphasizes scientific sensemaking. To that end, we have been emphasizing the sensemaking nature of the eight science and engineering practices (SEPs) defined in the Next Generation Science Standards. In this study, we investigated the question: What happens when we ask preservice elementary teachers to explicitly attend to sensemaking as they plan for and reflect on their own science teaching? By analyzing their written lesson planning and reflection documents, we found that: (a) they attended to both the material and intellectual work associated with sensemaking, but didn’t explicitly distinguish between the two, (b) they attended to sensemaking occurring at various “grain sizes,” and (c) some of them improved, refined and/or deepened their understanding of how the various SEPs are used for different kinds of sensemaking as they shifted from the planning process to the reflecting process. Our findings demonstrate that with proper support, preservice teachers are capable of understanding that elementary science instruction can and should move beyond fun, hands-on science activities, in order to engage students in scientific sensemaking.

Evaluation of bowel management efficacy and subjects’ satisfaction in people with spinal cord injury (SCI): An Italian multicenter survey via the MENTOR tool

Observational prospective multicenter study. The aim of this study is to evaluate the efficacy of bowel management and subjects’ satisfaction by the Monitoring the Efficacy of Neurogenic Bowel Treatment On Response (MENTOR) tool and the impact of demographic and clinical factors on bowel management. Consecutive patients with SCI were recruited by nine Italian Spinal Units. The MENTOR tool is a three-dimensional questionnaire assessing objective bowel score measures, patient’s subjective perceptions, and “special attention symptoms”; the combination of these results defines the allocation of each subject into one of three categories reflecting the possible therapeutic recommendations (red for “recommend change”, yellow for “further discussion”, and green for “monitoring”). We recruited 352 subjects with subacute or chronic SCI. The NBD average score was 11.7 ± 7.2 with 69.9% that expresses “good” or “adequate” satisfaction. 33.1% had one or more “special attention symptoms (SAS)”. About the MENTOR tool color: 34.6% of the current treatment was adequate (green), 29.7% needed a revaluation (yellow), and 35% required a change (red). While in “green” patients the subjective perception coincided with the score, 24% of “yellow” patients and 34.4% of “red” patients answered they were well managed. None of the clinical or demographic characteristics was associated with patients’ satisfaction or belonging to the three color zones. Effective bowel management in subjects with SCI did not correlate with patient characteristics or satisfaction. Many patients have inappropriate bowel management despite their satisfaction and the chronicity of the injury. This disparity calls for a periodic assessment with an objective tool such as MENTOR to identify the individual that requires intervention.

Neural networks for the prediction of bacterial and fungal infections: current evidence and implications

In the present narrative review, we discuss the use of artificial neural networks (ANNs) for predicting bacterial and fungal infections based on commonly available clinical and laboratory data, focusing on promises and challenges of these machine learning models. For predicting different bacterial or fungal infections from data commonly found in electronical medical records, ANN models may reach, based on current literature, an acceptable performance for discriminating between infected and non-infected patients, and outperformed other machine learning (ML)-based models in 38.3% of the retrieved studies evaluating at least another ML approach. In the near future, as for other ML models, the use of ANNs could be leveraged to provide real-time support to clinicians in clinical decision-making processes, although further research is needed in terms of quality of data and explainability of ANN model predictions to better understand whether and how these techniques can be safely adopted in everyday clinical practice.

Chain mentoring in a U.S. secondary STEM teacher education programme

Chain mentoring is a formal and informal way of mentoring in a STEM teacher education programme in America’s fourth largest city. It builds on the concepts of multi-layered mentoring and generative mentoring already introduced to the literature. This practical research digs deeply into the relationships and shared interests evident between and among faculty members, preservice teachers, and in-service teachers in this Innovative STEM Teacher Education Program (ISTEP). Secondary school students are the ultimate beneficiaries of their teachers’ strong disciplinary knowledge backgrounds and teacher preparation. This narrative inquiry uses participant observation, interviews, and focus groups to determine intricate linkages and connections among those involved in the programme. Broadening, burrowing and storying-restorying are then used to create a narrative exemplar. The exemplar includes embedded figures that visually capture how chain mentoring, this study’s knowledge contribution, came to be. Along with teaching by inquiry, culturally responsive pedagogy, and a strong disciplinary knowledge base, chain mentoring contributes to ISTEP’s 80% teacher retention rate, which exceeds the U.S. average of 56%. The features of the leading-edge STEM teacher education programme, together with its proven success over nearly twenty years (its graduates mostly remain teaching in high-need, urban schools), attracts local, national, and international attention.

Current status and perspective of immunotherapy for head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC), has still a high mortality rate even if several multimodal treatments have been developed in the advanced stages. In recent years, immunotherapy was introduced for the treatment of advanced and metastatic HNSCC with favorable effects on survival and quality of life. Currently, pembrolizumab plus or less chemotherapy is recommended in patients with CPS > 1 in metastatic HNSCC, while nivolumab is used in the second line setting for platinum-refractory disease. However, despite the benefits of these agents, most patients progress after immunotherapy. New approaches to overcome HNSCC immune escape are ongoing, involving antibodies against other immunological locks such as LAG-3, TIGIT, TIM-3, and CD134 (OX40). Moreover, T-lymphocyte activators like GITR and vaccine strategies based on peptides, DNA and RNA against HPV-positive HNSCCs, tumor-associated antigens, dendritic cells, and personalized cancer vaccines have been recently developed. Future research is crucial to determine the optimal setting for treatment with immunological checkpoint inhibitors through the use of new prognostic biomarkers. This review discusses both completed and ongoing clinical trials with PD-1/PDL-1 and new checkpoint inhibitors and immunotherapies. It also addresses mechanisms of resistance to immunotherapy, potential therapeutic strategies to overcome this resistance, biomarkers and side effects.