Abstract: In this project, we study the optimization methods impacts on deep learning tasks, where we particularly focus on adaptive learning rate optimizers (e.g., AdaGrad, RMSProp, and Adam) and describe them, stating their strengths, weaknesses, and scenarios where they excel or underperform. We employ an experimental approach to analyze their performance, generalization, computational efficiency, and hyperparameter sensitivity. The study compares the performance of adaptive optimizers against a traditional method (SGD) and a non-tuning machine learning model (LDA). Our empirical results show that Adam performs best both on the train and test set in terms of accuracy, speed, generalization, and computational efficiency.

Abstract: Effective management of infectious healthcare waste at the Military Medical Academy (VMA) depends on reliable forecasting in order to ensure adequate treatment capacity (e.g., sterilization facilities), optimize logistics, maintain regulatory compliance, and minimize environmental impact. However, conventional statistical approaches often struggle to capture the complex and heterogeneous patterns of waste generation ob-served across clinical departments with different medical specializations. The aim of this study is to develop and comparatively evaluate six models for predict-ing annual infectious waste generation across 24 clinical departments of the Military Medical Academy in Belgrade, Serbia. The analysis is based on an 11-year real-world panel dataset (2011–2021), which is further used to produce forecasts for the period 2022–2031. The modeling framework includes both traditional statistical methods (OLS, Ridge, and Lasso regression) and machine learning techniques (Random Forest, Gradient Boosting, and multilayer perceptron). Model performance is assessed using k-fold cross-validation and standard evaluation metrics (RMSE, MAE, and R²). The results indicate that machine learning models, particularly Gradient Boosting and Random Forest, achieve better predictive performance compared to traditional approaches. In addition, the analysis of feature importance provides insight into key factors influencing waste generation, which may support more informed planning and resource allocation within hospital systems. Although the findings are based on data from a single hospital complex, they offer a useful empirical basis for understanding and forecasting infectious healthcare waste in large, multi-department healthcare institutions.

Abstract: We present a full operational formulation of Quantum Information Copy Time cosmology in which the infrared scale entering the dark sector is defined by the largest distance over which a fundamental information unit can be copied within one Hubble time. Evaluating the Cohen–Kaplan–Nelson collapse bound at that copy horizon yields a falsifiable effective dark sector with 0 < c_Q ≤ 1. The homogeneous source is formulated through a Hermitian reduced-state quadrature, placing the dependence on ℜ[α] squarely within standard open-system quantum mechanics. In a local monitored Markovian universality class we recover diffusive copy transport and the familiar late-time branch with leading source ρ_Q ∝ H, and we identify the precise open-system structure that promotes this baseline branch into a quantum-limited saturation regime. Rather than introducing a pole-like regulator or an additive constant latency, we promote the late-time response ratio Ξ = c_Q²/D_∞ to a two-component response consisting of an asymptotic saturation floor and a switched transport contribution. This yields a background source of the form ρ_Q = ρ_sat + νHS (z;z_t,∆z), where the activation function is motivated by the same logistic open-system kinetics that controls the copy-sector transition. We further derive the four effective background parameters analytically within the QICT effective theory: the transport amplitude follows from the copy horizon plus the CKN bound, the transition redshift from quantum-speed-limit onset, the transition width from logistic open-system relaxation, and the matter fraction from flatness plus late-time equality. We further derive a Green–Kubo interpretation of the asymptotic transport plateau and present an explicit de Sitter/KMS locking scenario for D_⋆. The manuscript includes validated late-time geometric diagnostics, Pantheon+SH0ES covariance-ready supernova handling, effective perturbative stability conditions, semi-analytic growth and matter-power forecasts, and a concrete precision-cosmology implementation path through CLASS/CAMB and CMB/lensing/LSS likelihoods.

Abstract: In this paper, 32 complete genomic sequences of human-origin Nipah viruses registered in GenBank® from 1999 to 2025 are analyzed by tracking distributions of ATG triplets using a recently developed search method by us. The trajectories of these triplets are constructed, and their divergence parameter is calculated, revealing an increased value typical of highly mutated viruses that can form separate families with distinct properties. This conclusion aligns with the large deviation observed in the fractal dimension parameters of the distribution of inter-ATG-triplet distances in genomic sequences. The simulation results are compared with earlier data obtained for SARS-CoV-2, MERS-CoV, dengue, and Ebola viruses.

Abstract: Accurate estimation of crop yield from remote sensing remains challenging due to the crop-specific nature of yield drivers and the difficulty of interpreting spectral indicators across agronomic systems. While many studies prioritise predictive accuracy through complex models, fewer explicitly examine the stability and physiological relevance of in-dividual spectral and phenological indicators under controlled analytical conditions. This study investigates yield–spectral relationships in wheat and cotton using a harmonised Sentinel-2 indicator framework applied across multiple growing seasons in a Mediterra-nean agricultural environment. A consistent set of spectral and thermal indicators was derived from two phenologically targeted Sentinel-2 acquisitions per season and analysed using correlation analysis, univariate regression, constrained multivariate modelling, and recurrence analysis within an identical workflow for both crops. Distinct crop-specific patterns were observed. Wheat yield was most strongly associated with water-sensitive and canopy-related indicators, with NDWI-based metrics reaching Pearson correlations up to r = 0.85 and multivariate models explaining a substantial proportion of yield varia-bility (up to R² ≈ 0.82) under controlled analytical conditions. In contrast, cotton yield var-iability was dominated by thermal accumulation, with growing degree day indicators showing correlations up to |r| = 0.59 and multivariate performance reaching R² = 0.76. Recurrence analysis confirmed the stability of these indicator families across analytical stages. Overall, the results indicate that parsimonious, physiologically interpretable indi-cator combinations can account for a substantial proportion of yield variability without reliance on black-box modelling, supporting crop-aware indicator selection for precision agriculture applications.

Abstract: Oxidative stress is an important component of cancer biology with an imbalance between the production of reactive oxygen species (ROS) and antioxidant defense systems. Excess ROS can cause molecular damage and genomic instability. At the same time, ROS signaling remains necessary for normal cellular function. Redox homeostasis is of particular importance in this balance. The role of dietary antioxidants in cancer prevention is complex, depending on the biological context. This narrative review used preclinical and clinical studies to synthetize the current literature. We performed an extensive literature search of Scopus, Web of Science, and PubMed. We focused on articles published between 2021 and 2026. Dietary antioxidants influence redox biology in cancer. It focuses on major redox-sensitive pathways, including Nrf2-Keap1-ARE signaling, AMPK-mTOR regulation, NF-κB-mediated inflammation, mitochondrial quality control (autophagy and mitophagy), and inflammasome activation. These pathways involved in tumor initiation and progression link oxidative stress to metabolic and inflammatory processes. Current evidence suggests that dietary antioxidants act primarly by supporting endogenous defense systems. This may help explain the “antioxidant paradox,” in which antioxidant-rich dietary patterns are associated with a lower risk of cancer. In some studies, high-dose supplementation with isolated antioxidants has produced inconsistent or sometimes adverse results. These effects depend on dose, chemical form, metabolic context, and initial redox state. The gut microbiota is also an important mediator of antioxidant bioactivity. The gut microbiota modulates systemic redox balance by converting dietary polyphenols into bioactive metabolites, not acting only as simple scavengers. This contributes to inter-individual variability. Dietary antioxidants act as modulators of redox signaling. Personalized redox modulation may guide future cancer prevention strategies, emphasizing whole-diet approaches and biomarkers.

Abstract: Biological regulation is inherently recursive. Genes give rise to proteins that circle back to shape transcription, stress responses activate programs that later dampen the same response, and chromosomal dosage changes ripple through development until they settle into recognizable disease states. This paper repositions Reflexive Category Theory (RCT) as a biology-centered descriptive framework for that kind of recurrent causality. Rather than presenting RCT as a mathematical structure applied from the outside, we treat it as a disciplined way to represent how molecular systems repeatedly act on the conditions that produced them. The concept is developed through three disease-relevant settings: the p53-MDM2-BRCA1 damage-response network, the MYC-TERT telomerase reactivation axis, and the dosage-rewired hematopoietic landscape of trisomy 21. Across these examples, the central claim is that reflexive modeling is valuable not because it replaces experiment, but because it preserves mechanistic continuity across multi-step, feedback-rich biology. In that sense, RCT is proposed here as a conceptual bridge between molecular evidence and system-level interpretation in oncology and genetic disease.

Abstract: Heatwaves are intensifying across the southern United States, particularly in Texas, placing unprecedented stress on electric distribution networks and increasing power outage risk. Yet the relationship between heatwave characteristics and observed outages remains poorly quantified at multi-year, statewide scales. This study develops an event-based, spatiotemporal framework to quantify heatwave-induced outage risk across 254 Texas counties from 2014–2021 by integrating county-level EAGLE-I outage records with reanalysis-derived heat index measurements. An adaptive percentile-based threshold identifies heatwave days and constructs multi-day events, from which event-level metrics duration, mean heat index, and maximum customers affected are derived. Across 3,048 identified heatwave events, 51% involved at least one outage, revealing widespread heat-related reliability challenges. Spatial indicators show substantial heterogeneity: some counties experience frequent minor outages, while major population exposure is concentrated in large urban load centers. Outage severity and duration exhibit heavy-tailed distributions, with a small number of extreme events disproportionately affecting customers. Logistic regression models under three severity definitions (P90, P95, and ≥500 customers) demonstrate that heat intensity is a significant probabilistic driver of major outages, with each +1 °F increase in mean event heat index raising the odds by approximately 43–52%. These findings offer a scalable methodology for climate-related reliability assessment, supporting grid hardening, resource planning, and public-health preparedness.

Abstract: Invasive alien species threaten agricultural and natural ecosystems security. Aethina tumida Murray (Coleoptera: Nitidulidae), a globally recognized quarantine pest of honeybees, poses severe threats to colony health and apicultural sustainability. Whereas Steinernema carpocapsae (Weiser, 1955), an entomopathogenic nematode, exhibits biocontrol potential agent of this pest. This study used MaxEnt and CLIMEX models to predict the global potential distribution under different climate change scenarios. Result indicate that temperature and precipitation are the core environmental factors that constrain their distribution. Under current climatic conditions, both models demonstrate that suitable habitats for A. tumida is primarily located in South America, southern Africa, and South Asia, whereas S. carpocapsae exhibits a broader, spread almost globally. Notably, CLIMEX predicts a more extensive suitable range than the MaxEnt model for two species. MaxEnt predict result indicate suitable habitat of A. tumida expansion into North America, Europe and central Australia, while S. carpocapsae is expected to expand to Asia, North America, and Africa. Under both the A1B and A2 climate scenarios, the highly suitable habitat for both pests decreases significantly, whereas moderately and marginally increases markedly. Collectively, the results provide key scientific basis and decision-making support for the precise prevention and control of invasive pests.

Abstract: In this research we analyzed land cover/use processes and their impact on biodiversity in the Megalopolis of Mexico City. We used land cover/use databases from 1976 and 2018, both validated, improved and adapted for conducting landscape dynamic analysis. We also included records of 159 threatened species of fungi, vascular plants and vertebrates to construct spatially explicit biodiversity richness models based upon niche ecological algorithms. The results showed that human settlement encroachment was the main factor driving land cover/use changes, significantly affecting rural and natural landscapes. The extent and location of the dramatic shrinking of agricultural lands was clearly demonstrated. Afforestation was the second most important land cover/use process occurring mainly on native grasslands and shrublands. Biodiversity richness was depleted substantially, affecting about 35 % of the most important biodiversity hot spots and rendering the remainder more vulnerable due to extensive fragmentation of native ecosystems. The results are discussed in the light of the implications of the value of interdisciplinary methodological approaches, potential water recharge, governance of territorial disputes, loss of cultural heritage and poorly implemented environmental policies. Furthermore, the study highlights the urgent need to generate an innovative model for development which gives equal importance to the conservation of natural and rural landscapes as a fundamental form of subsistence for human settlements. Protecting biocultural heritage is of paramount importance. The region's genetic resources and cultural diversity are unique and have played a fundamental role in providing various benefits from nature to urban and rural inhabitants. These findings can serve as a guide for other similar megacities around the world.

Abstract: We present Color-in-Context, a dataset of 12,086 photographs annotated along two complementary dimensions: color (Black, Blue, Gray, Orange, Pink, Purple, Skyblue, White, Yellow) and illumination (fluorescentLight, indoor, indoorNight, sunLight). The dataset is organized into 36 joint categories (9 colors × 4 illumination conditions) using a consistent folder hierarchy and normalized labels. We provide summary counts across colors, illuminations, and selected joint buckets, and an optional manifest file to support deterministic indexing and integrity checking. This Data Descriptor documents dataset construction, label normalization, duplicate screening, and file-integrity checks, and provides usage guidance for split generation and reporting under varied illumination.

Abstract: This paper studies a quantized implementation of a Gramian-based distributed observer for discrete-time systems observed by a network of sensor nodes. The starting point is a distributed observer based on local information matrices obtained from a distributed constructibility Gramian recursion. In order to account for limited communication, the information matrices and information vectors exchanged among neighboring nodes are quantized by means of a uniform quantizer with saturation. The resulting algorithm preserves the original distributed structure and requires only one communication round per sampling instant. A simple perturbation argument shows that the estimation error induced by quantization depends on the perturbation of the local information matrix and information vector, and therefore on the quantization resolution. Numerical results illustrate a sharp practical threshold on the number of communication bits: in the considered example the estimator remains stable for 25 bits, while 23 bits already lead to divergence.

Abstract: The contemporary education landscape is often marred by escalating costs and centralized pedagogical structures, which collectively create significant barriers to entry for millions of potential learners worldwide. This paper presents \textbf{Skill Link}, a sophisticated decentralized platform designed to democratize skill acquisition through a specialized credit-based barter system. Unlike conventional e-learning platforms that rely on traditional currency transactions, Skill Link enables a frictionless exchange of knowledge by utilizing a virtual credit economy where participants earn and spend "learning credits." To address the critical issue of credential fraud in decentralized environments, the platform integrates Ethereum-based blockchain technology to ensure the absolute immutability and verifiable authenticity of all earned certificates. Key innovations include a multi-tiered course classification system, an automated mock assessment framework with negative marking capabilities, an intelligent context-aware AI assistant powered by advanced language models, and a rigorous verification mechanism for professional social links (LinkedIn, GitHub, Indeed). Developed using the robust Django framework, Python-based Web3 utilities, and a secure PostgreSQL/SQLite back-end, Skill Link provides a highly secure, transparent, and scalable ecosystem for peer-to-peer knowledge sharing, ultimately fostering a global community of experts and lifelong learners. The system's architecture emphasizes data integrity through atomic transactions and cryptographic verification, ensuring a trustless environment for global skill exchange.

Abstract: Background: Sacroiliac joint (SIJ) disruption alters posterior pelvic ring stability and may result in abnormal sacral stress redistribution. The biomechanical effects of different fixation strategies on sacral load transfer remain controversial. This study aimed to compare sacral stress patterns under unilateral and bilateral SIJ instability using three fixation techniques in a three-dimensional finite element model. Methods: A three-dimensional lumbosacral–pelvic finite element model was reconstructed from computed tomography data of a healthy adult and validated against previously published pelvic biomechanical data. SIJ instability was simulated by reducing the friction coefficient to represent ligamentous failure. Three fixation constructs were analyzed: anterior plate with posterior screw fixation, spinopelvic fixation, and hybrid fixation. A 750 N axial compressive load was applied to simulate static standing conditions; dynamic loading scenarios such as walking or sitting were not included. Peak sacral von Mises stress and stress amplification factors were calculated and compared with the intact model. Results: Anterior plate combined with posterior screw fixation produced the highest sacral stress amplification (SAF = 3.46 under unilateral instability; peak stress 265.40 MPa), exceeding three times the intact value, particularly under unilateral left instability (SAF = 3.46). Spinopelvic fixation significantly reduced peak sacral stress (125.66 MPa under bilateral instability; SAF = 1.64) but remained above physiological levels. Hybrid fixation demonstrated sacral stress values closest to the intact condition (81.64 MPa; SAF = 1.06), with minimal amplification and near-symmetrical load distribution. Conclusions: Fixation strategy significantly influences sacral load redistribution following SIJ disruption. Hybrid fixation most effectively restored near-physiological sacral stress patterns, whereas anterior plate with posterior screw fixation resulted in excessive stress concentration. Hybrid stabilization may provide a biomechanically balanced approach for unstable posterior pelvic injuries.

Abstract: From the mid-nineteenth to the early twentieth century, both Great Britain and the United States implemented large-scale child-emigration schemes aimed at relocating so-called «surplus» children—impoverished but considered «of good stock»—from major urban centres to rural households overseas or in the American interior. These programmes emerged from a shared diagnosis: industrial and agricultural economies in metropolitan areas were allegedly unable to absorb growing populations of poor children, who were framed as both a social burden and a latent threat to urban order. Emigration was thus promoted as a form of social reform—an intervention that would simultaneously relieve urban poverty and overcrowding while promising the children a healthier, morally improving environment on the farm.Central to this policy logic was the belief that agricultural labour and rural domesticity would function as vehicles of knowledge acquisition, moral rehabilitation, and civic formation. By learning farm work and rural norms, the children were expected to develop the dispositions necessary for productive adulthood and responsible citizenship, thereby securing redemption from an otherwise bleak urban future. Yet the historical record complicates this narrative of benevolent rescue. Although some children undoubtedly escaped severe deprivation, many migrant youths struggled to adapt to rural life, faced abuse, exploitation or isolation, and carried the consequences of these ruptures into adulthood. Rather than straightforward instruments of uplift, these schemes often reproduced existing inequalities under the guise of paternalistic reform.

Abstract: Substance use disorders (SUD) arising during neurobiologically sensitive developmental windows may constitute a structurally distinct diagnostic category, fundamentally different from SUD with adult onset. This concept paper proposes the term Complex Addiction-Developmental Disorder (CADD) to name and frame this clinical entity. The argument draws an analogy with the distinction between PTSD and Complex PTSD (C-PTSD): just as repeated developmental trauma does not produce the same disorder as adult trauma, repeated substance use during childhood or adolescence does not produce the same disorder as adult addiction. What it produces instead is a structurally different psychopathology — one with its own risk profiles, longitudinal characteristics, and treatment logic. The core of CADD is the constitution of substance-bound self- and identity-components through repeated pharmacological exposure during active neuroplastic phases of personality development. This gives rise to three defining clinical features: a relationship to the substance that functions like attachment rather than hedonic craving; an abstinence phenomenology resembling identity rupture rather than withdrawal; and a therapeutic priority of identity integration over detoxification. The concept has not yet been empirically validated and is offered here as a hypothesis for scientific discussion.

Abstract: Background: Microcirculatory dysfunction is a key feature of septic shock and contributes to organ failure despite the apparent normalization of systemic hemodynamic parameters. Extracorporeal blood purification (EBP) therapies aim to modulate the dysregulated inflammatory response through removal of endotoxins and cytokines; however, their impact on tissue-level perfusion remains unclear. Direct bedside assessment of microcirculation may provide mechanistic insight into the effects of EBP beyond macrohemodynamic stabilization. Methods: This structured narrative review summarizes current evidence on direct microcirculatory assessment during EBP therapy in sepsis. A literature search of PubMed, Web of Science, and Scopus was performed using combinations of the terms “microcirculation” and “blood purification” or “hemoadsorption.” Studies published between 2015 and 2026 evaluating direct sublingual microcirculation using sidestream dark field (SDF) or incident dark field (IDF) videomicroscopy during EBP were included. Both experimental and clinical studies were considered. Results: Eight studies met the inclusion criteria. Selective endotoxin adsorption with polymyxin B hemoperfusion (PMX-HP) demonstrated improvements in perfused vessel density and small vessel density in both animal and clinical settings. Non-selective cytokine adsorption devices (CytoSorb and HA380) were associated with increases in microvascular flow index (MFI), perfused vessel density (PVD), and proportion of perfused vessels (PPV), although most data derive from small observational studies. Across studies, improvements in microcirculatory parameters were observed during or following hemoadsorption therapy; however, heterogeneity in design, timing, and concomitant treatments limits definitive interpretation. Conclusions: Current evidence suggests that EBP may positively influence microvascular perfusion in septic shock when assessed using direct videomicroscopy. Nevertheless, data remain limited and predominantly observational. Larger randomized controlled trials incorporating predefined microcirculatory endpoints are required to determine whether mediator removal translates into sustained restoration of tissue perfusion and improved clinical outcomes.

Abstract: This study investigates the mechanical and thermodynamic effects of the evaporating ocean spray on the structure and dynamics of a hurricane marine atmospheric boundary layer using Eulerian multifluid and mixture model approaches coupled with the E−ϵ turbulence closure. The multifluid framework treats air and spray as interpenetrating phases, enabling a physically consistent representation of air–droplet interactions governing momentum transfer, enthalpy exchange, and turbulence modulation. The mixture approach is based on a simplified description that captures only part of the underlying physics, yet offers an advantage in its ability to yield analytical insight. Mechanically, spray produces competing effects: on one hand, droplet inertia causes wind deceleration, on the other, the spray-induced turbulence attenuation, primarily resulting from the air–droplet friction, leads to strengthening the wind. Analytical and numerical results show that the latter effect prevails for typical spray droplet sizes leading to wind acceleration and drag reduction at hurricane wind speeds. Thermodynamically, evaporating droplets redistribute total heat flux in favor of its latent component, with effects strongly dependent on the droplet size. Small droplets suppress turbulence and reduce the total enthalpy flux, whereas large ones enhance it. Furthermore, spray significantly increases the total enthalpy-to-drag coefficient ratio with wind speed, which agrees with field observations.

Abstract: Background/Objectives: Metabolic dysfunction–associated steatotic liver disease (MASLD) and its progressive inflammatory/fibrotic form, metabolic dysfunction–associated steatohepatitis (MASH), represent a growing global health burden. This progression is driven by complex mechanisms involving metabolic dysregulation, chronic inflammation, oxidative stress, and progressive fibrosis. To date, effective pharmacological therapies remain limited. Pentacyclic triterpenes have attracted increasing attention due to their broad biological activities and ability to modulate multiple molecular pathways implicated in chronic liver disease. This review aims to provide a mechanistic overview of the potential role of pentacyclic triterpenes in MASLD and MASH. Methods: A review of the literature was conducted using major scientific databases (PubMed, and Web of Science) to identify experimental studies investigating pentacyclic triterpenes in metabolic liver diseases. Selected studies were analyzed according to triterpene structural classification, reported bioactivities, molecular targets, and experimental evidence from in vitro and in vivo models of MASLD/MASH or related pathogenic processes. Results: Pentacyclic triterpenes, especially ursolic acid, oleanolic acid, and glycyrrhizin, exhibit hepatoprotective effects including regulation of lipid metabolism, attenuation of oxidative and endoplasmic reticulum stress, suppression of pro-inflammatory signaling, inhibition of inflammasome activation, and reduction of hepatic stellate cell activation and extracellular matrix deposition. These effects involve modulation of signaling pathways such as AMPK, NF-κB, NLRP3, TGF-β, FXR, and MAPK. Preclinical evidence demonstrates improvements in steatosis, inflammation, and fibrosis in experimental models. Conclusions: Pentacyclic triterpenes emerge as multitarget modulators of MASH pathophysiology. However, translation from preclinical evidence to well-designed clinical trials is necessary to validate their safety and efficacy in humans.

Abstract: Background: Differentiating adrenal adenomas from non-adenomatous lesions remains a critical challenge in the management of adrenal incidentalomas. Conventional unenhanced CT relies on attenuation thresholds of 10 HU and 20 HU, which present trade-offs between sensitivity and specificity. Objectives: To evaluate the diagnostic performance of unenhanced Spectral CT using the attenuation difference between 40 keV and 140 keV virtual monoenergetic images for differentiating adrenal adenomas from non-adenomatous lesions. Methods: In this retrospective single-center study, 60 patients with adrenal lesions who underwent unenhanced dual-energy CT were included. Mean attenuation values were measured on conventional images and on virtual monoenergetic images at 40 keV and 140 keV. The spectral attenuation difference (Δ40–140 keV) was calculated. ROC analysis was performed to determine optimal thresholds and diagnostic performance. Results: Forty-nine lesions were adenomas and eleven were non-adenomatous. The optimal threshold for Δ40–140 keV was −17 HU. Diagnostic performance was as follows: HU ≤10 (AUC 0.816, diagnostic accuracy 0.70), HU ≤20 (AUC 0.883, diagnostic accuracy 0.87), and Δ40–140 keV ≤ −17 HU (AUC 0.940, diagnostic accuracy 0.90). The spectral attenuation difference demonstrated the highest overall diagnostic accuracy. Conclusions: Unenhanced Spectral CT using Δ40–140 keV improves discrimination between adrenal adenomas and non-adenomatous lesions compared with conventional attenuation thresholds. This technique may reduce indeterminate findings and limit the need for additional imaging.