Rafael Advanced Defense Systems (Israel)

[This corrects the article DOI: 10.3389/fpain.2026.1722394.].

Burn injuries are common presentations in emergency departments (EDs) and require rapid evaluation and early intervention to prevent complications and reduce morbidity and mortality. Initial management focuses on airway stabilization, fluid resuscitation, pain control, burn assessment, wound care, and appropriate patient disposition. Standardized algorithms such as Advanced Burn Life Support (ABLS) emphasize systematic evaluation based on trauma principles, including airway, breathing, circulation, disability, and exposure. Accurate estimation of burn depth and total body surface area (TBSA) is essential to guide fluid resuscitation and determine the need for specialized burn center referral. Early analgesia, prevention of hypothermia, and evidence-based wound care are critical elements of ED management. Prehospital care and coordination with emergency medical services also play an important role in improving patient outcomes. In addition, special considerations are required for pediatric patients, rural healthcare settings, and mass casualty scenarios. Recent literature highlights the importance of standardized protocols, early multidisciplinary involvement, and improved prehospital training to optimize burn care delivery. This review summarizes key steps in emergency department burn management and discusses recent evidence guiding early stabilization, assessment, and referral decisions.

Accurate wildfire prediction is becoming increasingly critical as climate change drives warmer and drier conditions worldwide. The complex, non-linear interactions among meteorological factors, fuel characteristics, and landscape structure make wildfire risk a strong candidate for advanced machine learning (ML) approaches that integrate Earth Observation (EO) and climate data. Recent progress on this front has already led to significant improvement on operational systems, such as the ECMWF wildfire forecast, demonstrating clear advantages over traditional, meteorology-only indicators. However, most current ML models are based on single pixel predictions that lack essential spatial context. This limits their ability to capture how static forest connectivity interacts with dynamic fire processes, including spread, intensity, and likelihood of occurrence. To overcome these constraints, we propose a Convolutional Neural Network (CNN) architecture designed to explicitly learn and exploit the additional predictability from these complex spatial relationships. The model fuses multiscale inputs by processing high-resolution landscape variables (e.g., above-ground biomass, land cover, soil moisture, topography) alongside coarse-resolution meteorological fields. To represent the full spectrum of wildfire risk, we experiment with multiple target variables including probability of burn, fire severity, and fire extent. Through these experiments, the CNN is forced to learn connectivity patterns directly from historical wildfire events. The successful implementation of this approach would constitute a major step toward operational, high-resolution, context-aware wildfire risk mapping, strengthening both early-warning capabilities and long-term resilience planning.

The phenomenon of stable lift oscillations occurring on an elliptic wing section utilizing circulation control at transonic speeds was evaluated using numerical simulations. As the momentum of the jet increases beyond a prescribed magnitude, periodic detachment occurs from the trailing edge. This behavior conforms to a bistable state, consistent with prior experimental observations. Analysis by both steady and unsteady Reynolds-averaged Navier–Stokes calculations showed that the effect is decoupled from the dominant upstream shock wave. This indicates that the jet can no longer augment the wing’s circulation, marking the termination of circulation control. Furthermore, the results confirm that the absence of the downstream separation bubble acts as the catalyst for this detachment. Dynamic mode decomposition analysis revealed that the bistability is driven by a pressure feedback between the trailing-edge shock wave and a downstream pressure bubble. Secondary feedback governs the pressure redistribution during the detachment cycle. It was concluded that the pressure-dominant nature of the bistability allows it to be captured using relatively simple methods and even approximated through a reduced-order model comprising only 2% of the total modes, encapsulating 25% of the modal influence and reconstructing the pressure field with 98% accuracy.

La deserción escolar en el nivel superior representa una de las problemáticas más significativas que enfrenta el sistema educativo, ya que su impacto trasciende el ámbito académico y repercute directamente en el desarrollo social, económico y cultural de un estado o país. Este fenómeno limita las oportunidades laborales de los individuos, incrementa problemáticas como la desigualdad social y refleja deficiencias en las estrategias orientadas a la permanencia estudiantil. La deserción escolar es un fenómeno multicausal, determinado por factores socioeconómicos, familiares, institucionales y académicos, donde predominan las limitaciones económicas, la falta de orientación vocacional y el escaso acompañamiento institucional. Se concluye que la atención a esta problemática requiere la implementación de políticas públicas integrales y el fortalecimiento de programas de apoyo académico, psicológico y financiero, que favorezcan la permanencia y el egreso exitoso de los estudiantes en la educación superior.

• Particle erosion in impinging jets is predicted using a new Eulerian framework • The framework is extended to polydisperse systems with compressible carrier flows • The Eulerian sectional approach is coupled to an OpenFOAM compressible flow solver • A simplified erosion calculator for polydisperse systems is proposed • Eulerian and Lagrangian erosion predictions match for the BATES rocket engine This study extends a recently developed Eulerian framework for characterizing particle erosion in impinging jets to handle polydisperse systems with compressible carrier flows. The Eulerian mass and momentum conservation equations are solved using a one-way coupled sectional approach. Erosion at the eroded surface is computed using both empirical and experimentally-based erosion models. The framework allows estimating the initial erosion for polydisperse flows by first evaluating the initial erosion in the corresponding monosectional flows. Then, the erosion induced by particles from different sections is linearly added using a simplified calculator with different weights for each section. This calculator generates the initial erosion immediately, eliminating the need to run numerous expensive simulations for different polydisperse flows. Analysis of bisectional systems showed that intermediate erosion profiles are obtained when using different ratios between medium and large Stokes number particles. Finally, we demonstrate that the erosion rates calculated using our Eulerian framework are in agreement with those obtained using the commonly employed Lagrangian approach in the converging section of the BATES rocket engine.

Introducción: La interpretación de troponina I ultrasensible (hs-cTnI) en pacientes con enfermedad renal crónica (ERC) sin síndrome coronario agudo continúa siendo un desafío clínico. Esta investigación busca caracterizar los niveles de hs-cTnI en pacientes con ERC sin patología cardiovascular aguda. Objetivo: Evaluar la distribución de hs-cTnI en pacientes con ERC y su relación con la tasa de filtración glomerular (TFG), excluyendo condiciones agudas o estructurales cardíacas. Métodos: Estudio observacional, retrospectivo y transversal realizado en un hospital de tercer nivel en Panamá durante 2023. Se incluyeron pacientes ≥18 años con diagnóstico de ERC y sin evidencia de isquemia o enfermedad cardiovascular. Se aplicaron análisis descriptivos, regresiones lineales y no lineales, y cálculo de percentiles. Resultados: Se analizaron 99 pacientes. La media de hs-cTnI fue de 52.6 ng/L y de TFG fue de 19.5 ml/min/1.73m². El percentil 99 de troponina fue 80.5 ng/L (hombres: 84.4; mujeres: 75.9). No se encontraron correlaciones significativas entre TFG y hs-cTnI en ningún modelo. El valor de hs-cTnI fue mayor en estadios avanzados de ERC, aunque con alta dispersión. Conclusiones: En pacientes con ERC sin clínica cardiovascular aguda, los niveles de hs-cTnI suelen superar ampliamente los puntos de corte diagnósticos convencionales. Se requiere cautela al interpretar estos valores en urgencias, así como el establecimiento de puntos de corte específicos para esta población.

Inflammation is a biological phenomenon beneficial for homeostasis, but it is unfavorable if dysregulated. Although major progress has been made in characterizing inflammation in specific diseases, a global, holistic understanding is still elusive. This is particularly intriguing, considering its function for human health and the potential for modern medicine if fully deciphered. In this study, we leveraged advances in single-cell transcriptomics to delineate inflammatory processes of circulating immune cells during infection, immune-mediated inflammatory diseases and cancer. Our single-cell atlas of more than 6.5 million peripheral blood mononuclear cells from 1,047 patients (56% female, 43% male) and 19 diseases allowed us to learn a comprehensive model of inflammation in circulating immune cells. The atlas expands current knowledge of the biology of inflammation of immune-mediated diseases, acute and chronic inflammatory diseases, infections and solid tumors and lays the foundation to develop a disease classification framework using unsupervised as well as explainable machine learning. Beyond a disease-centered analysis, we charted altered activity of inflammatory molecules in peripheral blood cells, depicting discriminative inflammation-related genes to further understand mechanisms of inflammation. We present a rich resource for the community and lay the groundwork for learning a classifier for inflammatory diseases, presenting cells in circulation as living biomarkers.

To navigate their environments effectively, animals frequently track time elapsed or distance traveled while seeking food and avoiding threats. The hippocampus is implicated in this process, but the neural mechanisms remain unclear. Using virtual reality tasks that require mice to integrate time or distance to collect a reward, we identified two previously unknown functional subpopulations of CA1 pyramidal neurons. Both subpopulations encode time or distance via distinct ramping dynamics. The first subpopulation exhibits a rapid, synchronous rise in activity upon movement-initiated integration. Subsequently, individual neurons ramp down at heterogeneous rates, creating progressively diverging firing rates that encode elapsed time or distance. Closed-loop optogenetic inactivation of somatostatin-positive (SST) interneurons counterintuitively reduced the ramping activity, leading mice to prematurely attempt reward collection, suggesting impaired time/distance estimation. Conversely, the second CA1 subpopulation shows opposite dynamics — an initial rapid suppression followed by a gradual ramp-up. Inactivating parvalbumin-positive (PV) interneurons diminished this initial suppression, resulting in transient attempts to collect reward near integration onset. These findings reveal parallel hippocampal circuits that initiate and maintain time or distance encoding, controlled by PV and SST interneurons, respectively, and provide insights into the neural computations supporting goal-directed navigation.

Presentamos el caso clínico de un paciente joven con exceso de trabeculación del ventrículo izquierdo y poliposis adenomatosa familiar. La coexistencia de ambas patologías tan poco prevalentes en un único individuo podría sugerir la existencia de una relación entre ambas no descrita hasta ahora.