Abstract: The fall of droplets of an aqueous NaCl solution in a vertical channel, filled with heated dry air, is studied. Water from the droplets evaporates quickly, and crystals of a solid salt crust form on their surface. At a later stage of the process, the remaining solution is removed from the droplet using a jet of water vapor that passes through the pores of the polycrystalline crust. It was first observed that some of the drying droplets suddenly shifted to one side under the influence of the reactive force generated by the vapor jet. The resulting salt particles are weakly porous and consist of many crystals. It has been proven that these particles don’t have a central cavity. The use of seawater and the role of salt particles in protecting against thermal radiation from fires are briefly discussed. Calculations based on Mie theory have shown that the contribution of light scattering by hollow sea salt particles formed above the ocean surface during relatively slow evaporation of seawater droplets can be significant in the ocean's heat balance.

Abstract: Physics makes two questionable assumptions: (1) Distant galaxies are accelerating relative to Earth. (2) Entangled objects are spatially separated from each other. Why questionable? Acceleration relative to Earth has never been observed in a single galaxy. Observers perceive entangled objects as spatially separated, yet 3D space is relative. We show that physical realities are projections of a mathematical background reality: 4D Euclidean space (ES). In Euclidean relativity (ER), all objects move through ES at the speed C. There is no time coordinate in ES. All action is due to a monotonically increasing, absolute, external evolution parameter θ. An observer experiences two projections of ES as space and time. The axis of his current 4D motion is his proper time τ. Three orthogonal axes form his 3D space x₁, x₂, x₃. His physical reality is his spacetime x₁(ϑ), x₂(ϑ), x₃(ϑ), τ(ϑ), where τ is a natural time coordinate and θ converts to absolute parameter time ϑ. Without gravity, his spacetime is Minkowski-like. As in general relativity (GR), gravity in ER is the curvature of spacetime. Since coordinates in GR are merely labels, the Einstein field equations also hold in systems that use τ as the time coordinate. ER predicts time’s arrow, relativistic effects, galactic motion, the Hubble tension, and entanglement. Remarkably, ER manages without cosmic inflation, expanding space, dark energy, and non-locality. ER tells us: (1) Distant galaxies maintain their recession speeds. (2) From their perspective, entangled objects have never been spatially separated, yet their proper time flows in opposite 4D directions.

Abstract: Let k be a positive integer. A polynomial A∈F_2[x] is called k-unitary perfect if the sum of the k-th powers of its distinct unitary divisors equals A^k. In this paper, we focus on the case k=2^n and prove that every 2^n-unitary perfect polynomial over F_2 is necessarily even. Moreover, we obtain a complete classification of all even 2^n-unitary perfect polynomials having at most three distinct irreducible factors. In particular, we characterize all such polynomials of the formA=x^a (x+1)^b P^h, where P is a Mersenne prime over F_2 and a, b, and h are positive integers. As a consequence, several explicit infinite families of k-unitary perfect polynomials over F_2 are obtained.

Abstract: Abstract—In-vehicle intrusion detection systems (IDSs) are increasingly proposed to protect automotive networks, yet most prior work emphasizes detection accuracy while overlooking system-level constraints that determine real-world deployability. This paper addresses the mismatch between IDS design assumptions and the computational, architectural, and real-time limitations of production automotive electronic control units (ECUs). This issue is particularly critical in safety-critical automotive systems, where security mechanisms must operate within strict timing and resource bounds without interfering with control functions. The objective of this work is to provide a deploymentaware feasibility analysis of in-vehicle IDS techniques across heterogeneous automotive computing platforms. We introduce a baseline-driven methodology that defines two representative ECU tiers: microcontroller-based safety ECUs operating under AUTOSAR Classic and higher-performance domain or zonal controllers based on AUTOSAR Adaptive and POSIX-compliant operating systems. IDS approaches are evaluated against nonnegotiable constraints including processing capacity, memory availability, worst-case execution time, operating system compatibility, and in-vehicle network technology. The results show that microcontroller-based ECUs support only lightweight, messagelevel IDS mechanisms with strictly bounded execution behavior, while machine learning–based IDSs require controller-class platforms and remain constrained by determinism and interference requirements. This work demonstrates that feasibility, rather than accuracy alone, must be treated as a first-class criterion in automotive IDS design.

Abstract: Guardrail systems for large language models (LLMs) are designed under a foundational but rarely examined assumption: that safety is a property of individual input–output exchanges. This assumption is adequate for single-turn deployments but fails structurally in multi-turn conversational systems, where risk does not reside in any single message but emerges from the accumulated trajectory of a session. We formalize this failure mode as Conversational Risk Accumulation (CRA), a class of adversarial and incidental threat patterns in which individually policy-compliant turns collectively produce outcomes that violate safety intent. We propose a stateful guardrail architecture, the CRA Framework, comprising three novel constructs: (1) a Semantic Drift Monitor that tracks divergence from declared session intent; (2) an Information Accumulation Graph (IAG) that models cross-turn entity and attribute disclosure as a growing knowledge structure; and (3) a Compliance Gradient Detector that identifies progressive erosion of refusal behavior across turns. These three signals are fused into a session-level CRA Score, which triggers guardrail intervention at the conversation layer rather than the message layer. We formalize the threat taxonomy, define the mathematical properties of the CRA Score, and derive theoretical bounds on detection latency. The framework is domain-agnostic and architecturally composable with existing single-turn guardrail systems. We discuss instantiation across the enterprise RAG deployments, agentic pipelines, and educational AI systems, and identify open problems in stateful safety that the framework surfaces.

Abstract: Background/Objectives: In laparoscopic and robot-assisted surgery, bleeding may rapidly impair operative-field readability and procedural safety. In the broader Robin Heart teleoperation framework, interpretation of such events is relevant not only for scene understanding, but also as a potential prerequisite for future safety-oriented supervisory functions under communication-degraded conditions. The aim of this study was to assess whether a deep learning model for blood segmentation could provide outputs suitable for preliminary image-level temporal characterization of visible blood-region behavior in laparoscopic video. Methods: The model was first trained on a simulated bleeding dataset prepared under controlled conditions and then fine-tuned on annotated frames from robot-assisted laparoscopic hysterectomy video. Additional limited adaptation and held-out evaluation were performed on annotated bleeding-related episodes derived from the public GynSurg dataset. Segmentation performance was assessed using the Dice coefficient and Intersection over Union (IoU). Temporal analysis was performed on representative internal and external sequences using mask-derived descriptors and auxiliary optical-flow-based motion descriptors computed after camera-motion compen-sation within the detected blood ROI. Results: The model achieved Dice/IoU values of 0.94/0.89 on the simulated validation set, 0.907/0.830 on the internal operative validation set, and 0.764/0.626 on the annotated external GynSurg subset. The combined descriptor set differentiated more dynamic and unstable progression profiles from more spatially coherent ones across both datasets. Peak dA/dt reflected abrupt visible blood-area ex-pansion, temporal IoU described mask stability over time, and optical-flow-based de-scriptors provided additional information on local motion activity. A peak-only descrip-tion was insufficient to fully characterize the observed progression patterns. Conclusions: The results support the feasibility of combining deep-learning-based blood segmentation with temporal and optical-flow-based descriptors for exploratory image-level character-ization of visible blood-region behavior in laparoscopic video. Within the Robin Heart development pathway, such descriptors may in the future serve as candidate components of image-analysis support modules for safety-oriented teleoperative scenarios. At this stage, they should be interpreted as exploratory image-derived indicators rather than clinically validated markers of bleeding severity.

Abstract: Manual compliance auditing in cloud environments consumes up to 40% of IT security budgets annually, yet existing approaches verify control presence rather than effectiveness, leaving institutions vulnerable to adversarial evasion. This paper presents an AI-augmented hybrid ML–LLM compliance auditing system evaluated on a national cybersecurity standards framework (143 controls, 200,000 training events). The system combines multi-label XGBoost classification with LLM-based semantic log analysis, grounded in a formal effectiveness model. Key findings: XGBoost achieves 99.88% F1 after 5% domain fine-tuning but collapses to 7.98% zero-shot, a 92-point generalization gap bridged by the hybrid LLM path; adversarial validation exposes effectiveness deficits invisible to checkbox auditing (SI-3: 20%detection rate; SI-10: 32% XSS bypass); GPT-4o-mini achieves 93.5% zero-shot accuracy across four log types (n=200), while Llama-3.2-3B on CPU-only hardware achieves 84.0%, validating on-premise deployment viability. A vocabulary-coverage gating router achieves 94.5% accuracy at $0.15/10K logs. The system runs at 2.0 CPU cores, $50/month, producing audit reports in 0.77s, demonstrating that effectiveness-based compliance auditing is accessible without enterprise-grade infrastructure.

Abstract: Background and Aim: Liver disease in patients receiving chronic hemodialysis (HD) is frequently underrecognized and may contribute to adverse outcomes. Its evaluation is complicated by dialysis-related changes in volume status that can influence noninvasive measurements. We aimed to assess the prevalence and determinants of Metabolic Dysfunction–Associated Steatotic Liver Disease (MASLD) and liver fibrosis using transient elastography (TE), with particular attention to metabolic, volume-related, and dialysis-specific factors, and to examine the effect of a single HD session on Controlled Attenuation Parameter (CAP) and liver stiffness measurement (LSM). Methods: In this prospective cross-sectional study, adult patients receiving maintenance HD for ≥3 months were enrolled. TE (FibroScan®) was performed immediately before (pre-HD) and after (post-HD) a midweek HD session. Steatosis was defined as CAP >257 dB/m and significant fibrosis as LSM ≥8 kPa. Volume status was assessed using interdialytic weight gain (IDWG) and ultrafiltration (UF) volume. Associations with clinical, biochemical, and dialysis-related variables were analyzed. Results: Forty patients were included (mean age, 63.5 ± 17.3 years; 70% male; 30% diabetic). MASLD prevalence was 25% pre-HD and 22.5% post-HD. The prevalence of significant fibrosis decreased from 17.5% pre-HD to 10% post-HD, while mean LSM did not change significantly, suggesting that volume removal may influence fibrosis classification in a subset of patients. CAP correlated positively with body mass index, IDWG, UF volume, and triglyceride levels, and inversely with serum albumin. Post-HD LSM showed a significant inverse association with serum albumin and positive associations with alanine aminotransferase, total cholesterol, and low-density lipoprotein cholesterol, whereas pre-HD LSM was mainly associated with age and bilirubin. The FIB-4 index did not correlate with LSM. Conclusions: In maintenance HD patients, hepatic steatosis is closely associated with metabolic burden and fluid overload, whereas fibrosis assessment is substantially influenced by nutritional status. Dialysis-related volume changes may modify LSM-based fibrosis estimates, supporting post-dialysis TE for more reliable assessment. TE provides clinically informative evaluation and appears superior to surrogate indices such as FIB-4 in this population.

Abstract: Retrofitting existing residential buildings is a critical strategy for achieving urban decarbonization while addressing public health disparities, particularly in communities disproportionately affected by environmental and socioeconomic stressors. This study presents a scalable urban building energy modeling framework that integrates physics-based simulations with machine learning to evaluate and prioritize health-driven retrofit strategies across residential building stocks. Synthetic datasets were generated through parametric simulations of representative building archetypes and retrofit scenarios, capturing variations in envelope performance, HVAC systems, infiltration rates, and ventilation strategies. Machine learning models were trained as surrogate predictors of building energy performance, enabling rapid evaluation of retrofit impacts. A range of algorithms—including decision trees, random decision forests, gradient boosting machines, support vector machines, k-nearest neighbors, and artificial neural networks—were evaluated. An artificial neural network implemented as a multilayer perceptron was selected for further analysis due to its strong predictive performance (R² = 0.94) and ability to capture complex nonlinear relationships among retrofit variables. The final model used the Port optimization algorithm for stable convergence and improved generalization. The framework is applied to Seattle’s Duwamish Valley, a community experiencing disproportionate environmental and health burdens. The results highlight retrofit priorities—particularly infiltration reduction, HVAC upgrades, and improved envelope performance—that deliver co-benefits for energy efficiency, indoor environmental quality, and occupant health. The results demonstrate that machine learning–enhanced physics-based UBEM can significantly accelerate retrofit evaluation while preserving the interpretability of simulation-based approaches. The proposed framework provides a scalable approach for identifying health-informed retrofit pathways that support equitable urban decarbonization.

Abstract:

Antimicrobial resistance (AMR) is one of the most serious threats to global public health, driven in part by extensive antibiotic use in food-producing animals. The poultry industry, a major contributor to global animal protein supply, has depended on antibiotics for growth promotion and disease control, thereby contributing to the emergence and dissemination of AMR zoonotic bacteria. This review synthesizes current evidence on the potential of phytochemicals (PCs), plant-derived bioactive compounds, as sustainable non-antibiotic alternatives for controlling bacterial foodborne pathogens in poultry. Relevant literature including in vitro and in vivo studies assessing PCs against major poultry-associated zoonotic bacteria, including Salmonella enterica, Campylobacter spp., Clostridium perfringens, Listeria monocytogenes, and pathogenic Escherichia coli, is examined. Evidence indicates that PCs exert antimicrobial and anti-virulence effects through mechanisms like bacterial membrane disruption, inhibition of quorum sensing and virulence gene expression, modulation of gut microbiota, and enhancement of host immune responses. In vivo studies demonstrate reductions in pathogen colonization and improvements in gut health and performance metrics in poultry. Despite these promising findings, challenges remain in bioavailability, dose optimization, standardization, and regulatory approval. Overall, PCs represent a promising component of integrated antimicrobial stewardship strategies in poultry production, with significant implications for mitigating zoonotic AMR transmission.

Abstract: The synthesis of hydroxamic acids from sterically hindered substrates, such as abietane-type resin acids, remains a significant challenge due to the extreme congestion of the tricyclic skeleton. This study reports an efficient one-pot protocol for the direct conversion of abietic and dehydroabietic acids into their corresponding hydroxamic derivatives, achieving 65% and 74% isolated yields, respectively. Systematic screening of activating agents identified diethyl chlorophosphate (DCP) as the superior reagent for the hydroxy-amidation. A critical finding of this work is that the optimization of the isolation process specifically minimizing the water amount during aqueous work-up was essential to recover these polar products and prevent significant yield loss. The reaction proceeds through diethyl phosphate mixed anhydride intermediate, which was successfully isolated, providing direct experimental evidence of the activation pathway. The reaction mechanism was further elucidated using density functional theory (DFT) calculations at the M062X/6-31G** level, identifying a concerted transition state for the simultaneous addition of hydroxylamine and expulsion of the phosphate group. Furthermore, the study rationalizes the observed chemoselectivity: although the ester is the more stable thermodynamic product, the formation of the N-hydroxy amide is kinetically favored through a substantially lower activation barrier. This combined experimental and theoretical approach establishes a robust and scalable methodology for the functionaliza-tion of abundant similar natural terpenoids.

Abstract: This study applies Data Envelopment Analysis (DEA) framework to examine the economic, managerial, technological, and environmental performance of three major Swedish forestry firms—SCA, Södra, and Holmen—over the period 2018–2024. The analysis employs input-oriented CCR and BCC models, super-efficiency analysis, the Malmquist Productivity Index, and an environmental DEA model incorporating transformed undesirable outputs to provide a multidimensional assessment of efficiency and productivity. In addition, a second-stage regression analysis is conducted to examine whether structural firm characteristics are associated with efficiency variation. A robustness check is performed using an output-oriented DEA specification to assess the sensitivity of efficiency results to orientation choice. The results indicate differences in performance patterns across firms and dimensions. Södra frequently operates near the estimated efficiency frontier, SCA shows improvements in environmental efficiency over time alongside scale-related constraints, and Holmen exhibits greater variability across efficiency and productivity measures. The regression results suggest that efficiency variation is not strongly associated with the included structural variables, while the robustness analysis indicates consistent firm rankings across model orientations The study provides an integrated DEA-based framework for assessing combined economic and environmental performance in resource-intensive industries and highlights the usefulness of multidimensional efficiency analysis for benchmarking purposes.

Abstract: Accurate reconstruction of epidemic dynamics is challenging when reported infection data are incomplete or affected by significant under-reporting. Excess mortality indicators provide an alternative source of information that can be used to infer epidemic trajectories. In this study, we propose a regularized inverse calibration framework for a SEIRD epidemi-ological model using excess mortality data. The calibration problem is formulated as an inverse problem and stabilized through a Gaussian functional regularization that constrains the admissible epidemic trajectories. This approach reduces sensitivity to noise in mortality observations and prevents oscillatory solutions typically associated with ill-posed param-eter estimation. The model is numerically integrated using a fourth-order Runge–Kutta scheme and calibrated against mortality data from Catalonia. Cross-context validation is further performed using mortality data from Ecuador to assess the structural robust-ness of the approach. The results show that the regularized calibration produces smooth and epidemiologically consistent epidemic trajectories while maintaining agreement with observed mortality patterns. The proposed framework provides a robust methodology for reconstructing epidemic dynamics from mortality indicators and may contribute to improved epidemiological surveillance in situations where case reporting is limited or unreliable.

Abstract: Linear momentum conservation, rooted in the spatial invariance of physical laws and formalized by Noether's theorem, requires that systems with spatial translational symmetry conserve linear momentum. This work examines how this principle applies to a charged retarded field engine, where the rate of change of total mechanical linear momentum and field linear momentum is balanced. Using electric and magnetic field expressions from a Taylor expansion to incorporate retardation effects, we analyze the linear momentum equation order by order for two arbitrary charged bodies. Our results show that total linear momentum is conserved, with mechanical and field linear momentum changes exactly balanced. Consequently, the linear momentum lost by the internal electromagnetic field precisely equals the engine's gained mechanical linear momentum, addressing the central focus of this study.

Abstract: Concurrent chemoradiation (cCRT) is standard for unresectable, locally advanced non–small cell lung cancer (NSCLC), but the preferred concurrent chemotherapy backbone is uncertain. Cisplatin–etoposide (EP) and weekly carboplatin–paclitaxel (PC) are commonly used. Background/Objectives: Retrospective single-institution cohort of adults with histologically confirmed, inoperable AJCC stage II–III NSCLC treated 2015–2023 with definitive thoracic radiation plus concurrent EP or PC. Methods: We collected clinical characteristics, treatment completion, best radiographic response, adverse events (AEs), progression, and death. Primary endpoints were progression-free survival (PFS) and overall survival (OS); secondary endpoints were overall response rate (ORR) and AEs. Kaplan–Meier survival estimates were generated and compared using log-rank testing; hazard ratios (HRs) were estimated using Cox proportional hazards models. Results: Among 177 patients (EP, n = 43; PC, n = 134), stage III disease comprised 91% in the EP cohort and 90% in the PC cohort. ORR favored EP (63% vs 52%), and primary progressive disease as best response was less frequent with EP (7% vs 21%, p = 0.04). Median PFS was 48.07 vs 14.93 months (HR 0.65, 95% CI 0.43–0.90; p = 0.05). Median OS numerically favored EP (76.97 vs 34.60 months; HR 0.70, 95% CI 0.44–1.12; p = 0.17). Any-grade AEs occurred at similar rates (34.9% vs 34.3%), whereas grade 3–4 AEs were more frequent with EP (25.6% vs 9.7%; p = 0.02). Conclusion: EP-based cCRT was associated with longer PFS and higher grade 3–4 toxicity than PC; findings support individualized selection and need validation, especially in the immunotherapy era.

Abstract: Vegetation spatial heterogeneity is fundamental to biodiversity management and ecosystem service provision, yet detailed phytosociological mapping of forest vegetation remains largely unresolved in the Colombian Orinoquia. This study characterized the geographic distribution of forest vegetation through the integration of 178 field surveys, environmental complex variables defined by geomorphological and bioclimatic gradients, and multi-sensor satellite imagery combining Landsat-8 optical bands and Sentinel-1 dual-polarization data, processed within a Random Forest classification framework in Google Earth Engine. Classifications achieved overall accuracies between 0.910 and 0.975 and Kappa coefficients above 0.93, identifying 24 phytosociological alliances or geobotanical formations distributed across approximately 7,565,696 ha, representing 34.63% of the region. Forest cover ranges from 10.95% in the Floodplain to 55.22% in La Macarena, with the High Plain concentrating the greatest formation diversity. The spatial organization of forest vegetation is primarily governed by the geomorphological gradient — fluvial, denudational, and structural — and limiting bioclimatic factors, together with their associated edaphic-hydrological regimes, with anthropic transformation driven by cattle ranching and agricultural expansion constituting the principal threat to forest cover. These results advance beyond existing land cover surrogates, providing an empirically validated cartographic framework for biodiversity assessment, habitat modeling, and natural capital management in the Colombian Orinoquia.

Abstract: Tropical forests in southwestern Ethiopia are increasingly shaped by land-use systems that integrate biodiversity conservation with agricultural production, particularly semi-coffee forest management. This study compared woody species diversity, composition, forest structure, and regeneration status between natural forest and adjacent semi-coffee forest in Kersa District, Jimma Zone. A systematic stratified sampling design using 60 plots (20 m × 20 m) was employed. Vegetation data were analyzed using the Shannon–Wiener diversity index, species richness, Sørensen similarity index, Importance Value Index (IVI), and regeneration status. A total of 75 woody species from 45 families were recorded, with 69 species in natural forest and 55 in semi-coffee forest. Floristic similarity was high (0.79), but natural forest retained more unique species (29%) than semi-coffee forest (10.9%). Shannon diversity was higher in natural forest (3.79) than semi-coffee forest (2.55), though not statistically significant. Stem density was significantly greater in natural forest. Regeneration was good in natural forest and fair in semi-coffee forest, with significantly higher seedling and sapling densities. Overall, semi-coffee forests maintain species similarity but show reduced structural complexity and regeneration potential due to management practices.

Abstract: Background: Physical activity is a recommended first‑line treatment for chronic low back pain, yet adherence to structured exercise remains poor due to pain, fear, fatigue, and contextual barriers. Snacktivity™, which promotes brief, frequent bouts of movement embedded in daily routines, has emerged as a potentially feasible alternative. However, it remains unclear how, why, and for whom Snacktivity supports engagement in people living with chronic low back pain. Objective: To develop and refine programme theories explaining how Snacktivity‑type interventions support physical activity engagement and related outcomes in adults with chronic low back pain. Methods: A realist review was conducted following RAMESES standards. Initial programme theories were developed and iteratively refined through synthesis of quantitative, qualitative, and mixed‑methods evidence from Snacktivity and related sedentary‑reduction interventions in low back pain and transferable adult populations. Evidence was analysed to identify context–mechanism–outcome (CMO) configurations. Results: Forty‑two studies contributed evidence to programme theory refinement. Five refined programme theories were supported. Snacktivity appears to enable engagement by lowering perceived burden and threat rather than eliminating fear, generating mastery experiences that enhance self‑efficacy, and reducing symptom interference through brief, distributed activity. Education and coaching components supported meaning‑making by reframing movement as legitimate and achievable, while environmental cues and routines promoted habit formation. Psychosocial outcomes (confidence, mood, vitality) and habit formation were more consistently improved than performance‑based outcomes, and engagement was sustained even when pain or fatigue persisted. Conclusions: Snacktivity functions as a participation‑enabling intervention rather than a traditional exercise prescription. Its effectiveness in chronic low back pain is explained by psychosocial and contextual mechanisms that support psychological safety, mastery, and habit formation. These findings support a shift from dose‑response exercise models toward interventions that prioritise feasibility, meaning, and sustained participation in daily life.

Abstract: Recent re-examination of the gravity-dependency of position sense revealed two distinctive proprioceptive pathway generation. One was indeed gravity-dependent as matching and pointing tasks showed, while the other one was suggested to use memory as repositioning demonstrated it in a gravity-independent fashion. The current manuscript puts forward that not only matching and pointing tasks use muscle spindle-dependent position sense, but repositioning as well. Consequently, memory-supported repositioning does not involve peripheral proprioceptor encoding acutely in the context of scene representations, however spatial and episodic memory with critical hippocampal contribution may essentially rely on earlier peripheral intrafusal proprioceptive Piezo2-initiated input source through hippocampal learning and memory. Furthermore, the cingulate cortex and working memory may be involved in this memory process downstream. Accordingly, the underlying proposed two distinctive proprioceptive pathways are the following: the muscle spindle-derived proprioceptive terminal Piezo2-initiated ultrafast signaling may contribute to motoneurons in a monosynaptic fashion through VGLUT1 and to the hippocampus as well through VGLUT2. Delayed onset muscle soreness, with the theorized microdamage of these proprioceptive terminals, impairs the efficiency of proprioceptive integration and body representation process during body-related motor imagery. Body representation is indeed crucial in spatial, episodic and working memory formation. This manuscript puts into perspective how the microdamage of Piezo2 on these proprioceptive terminals may not only miswire proprioception acutely, like in delayed onset muscle soreness, but with chronification as well, leading to spatial, episodic and working memory impairments, and rapid eye movement sleep reduction. This longitudinal trajectory is demonstrated mainly though traumatic brain injury and Alzheimer’s disease.

Abstract: A computational model of anisotropic biomass particle pyrolysis was used to study the influence of particle properties and process conditions. The model couples multicomponent CRECK kinetics with intraparticle heat and mass transport. Particle size and lignocellulosic composition significantly affect conversion time and product yields; aspect ratio was also found to be important for larger-diameter particles. Larger particles (8 mm diameter, 4:1 aspect ratio) showed conversion times more than twice those of 3 mm particles, and char yield increased from about 16% to 23% when comparing small and large particles. Lignin-rich materials (e.g., palm shell) produced higher char and lower volatile yields than cellulose-rich biomass (wood, sugarcane bagasse); for 3 mm particles, char changed from 16% (oak) to 23% (palm shell). Higher reactor temperatures and heating rates substantially shortened particle conversion time—by up to 75%—and noticeably affected product yields. Analysis of the Biot and Pyrolysis numbers indicates millimeter-scale particles operate in a transition regime where internal conduction, external convection, and chemical kinetics occur on comparable timescales, so models must include these phenomena to accurately predict conversion times and final yields for reactor design and optimization.