Abstract: As the reliability and validity of forensic evidence, particularly in feature comparison disciplines, confront on-going scrutiny, forensic practitioners must ensure their processes, whether for investigative, intelligence or evidential purposes are robust, scientifically grounded, and validated. In forensic facial identification, morphological analysis is internationally recognized as the preferred method for facial image comparison, and is applied during the analysis and comparison steps of the Analysis, Comparison, Evaluation, Verification (ACE-V) process, commonly applied in feature comparison. While several international proficiency tests have assessed forensic facial examiners’ accuracy in comparing mated and non-mated pairs (black box tests), fewer opportunities have focused on evaluating inter-laboratory procedures and methods. To address this gap, members of a small border and immigration focused expert working group participated in an inter-laboratory collaborative exercise designed to analyse and harmonize best practices across member laboratories. There are limited published validation studies of facial image comparison methods. This paper presents the results of a collaborative exercise that compares the methodologies of three different agencies, highlighting key similarities and differences in examiner process and decision making, and provides a foundation for the development of similar future initiatives.

Abstract: Lipid sources are essential components in modern swine nutrition, not only due to their high energy density but also because of their positive effects on palatability, feed efficiency, and micronutrient absorption. However, rising raw material costs have encouraged the use of oxidized fats and oils (OxFO) as a cost-effective alternative in pig diets. These lipids, degraded by thermal and handling factors, undergo chemical alterations that negatively affect digestibility, energy metabolism, and animal health. This review critically examines the current scientific evidence regarding the impact of oxidized fat consumption in swine production systems. The physiological and biochemical mechanisms by which lipid oxidation products impair mitochondrial β-oxidation, cellular oxidative balance, energy efficiency, and meat quality are discussed. Moreover, the practical consequences on productive performance, muscle oxidative stability, and the expression of inflammatory and antioxidant markers are explored. Findings suggest that although the use of oxidized fats may offer economic savings, their metabolic and productive repercussions can compromise profitability and sustainability. The need to define safe inclusion thresholds (when replacement is not feasible), standardize analytical methods to assess oxidation status, and consider nutritional alternatives to mitigate adverse effects is emphasized.

Abstract: Gibson’s concept of optic flow established that perception is grounded in lawful, action-generated structure rather than in discrete sensory signals. While optic flow specifies self-motion visually, no corresponding framework has been formally established for the mechanical and kinesthetic information generated during skilled action. This study introduces haptic flow as a screw-structured, symmetry-bearing invariant that specifies kinesthetic information in human movement. Using screw theory, we model haptic flow as the continuous evolution of instantaneous screw axes and pitch, capturing the coupled rotational–translational dynamics of the body–object system. This framework is applied to the golf swing as a paradigmatic case of skilled manipulation. Motion data from proficient and novice performers reveal clear geometric differences: proficient performance is characterized by coherent alignment between instantaneous screw axes and the club’s principal inertia axis, stabilization of pitch through impact, and the emergence of harmonic screws lying on a common cylindroid. In contrast, novice performance exhibits fragmented screw organization, elevated pitch variability, and pronounced geometric asymmetry. These results demonstrate that skilled manipulation is structured by a continuous, internally generated flow of mechanical information that is invariant across critical phases of action. Interpreted in Gibsonian terms, harmonic screws function as perceivable affordances—symmetry-stabilized modes that couple inertia and potential and guide action without reliance on explicit feedback or internal models. The proposed concept of haptic flow thus extends ecological perception–action theory into the mechanical domain and provides a quantitative symmetry-based framework for analyzing skilled human movement.

Abstract: Galectin-3 (Gal-3) is a β-galactoside-binding lectin implicated in metabolic inflammation, cardiovascular and renal dysfunction, neurodegenerative disorders, and obesity-related pathologies. Although Gal-3 is recognized as a clinically relevant biomarker, the mechanisms controlling its tissue expression and circulating abundance remain poorly defined. O-GlcNAcase (Oga; encoded by Mgea5), the enzyme that removes O-linked β-N-acetylglucosamine (O-GlcNAc) from proteins, regulates nutrient-sensitive signaling and transcriptional processes that overlap with Gal-3 associated disease pathways. To investigate the relationship between metabolic status and Gal-3 expression, male mice were fed a high fat diet (HFD) for eight weeks to induce obesity. HFD-fed mice exhibited significant increases in body weight and fasting and fed blood glucose levels compared with lean controls, confirming metabolic dysregulation. ELISA revealed approximately threefold higher serum and plasma Gal-3 concentrations in obese mice, indicating enhanced Gal-3 production in diet-induced obesity. To determine whether Oga regulates Gal-3 expression, Oga wild-type (WT), heterozygous (HET), and knockout (KO) mice were analyzed. Circulating Gal-3 protein levels were significantly reduced in Oga KO mice, with intermediate levels in Oga HET animals. RT-qPCR revealed genotype-dependent modulation of Gal-3 (Lgals3) mRNA expression across multiple tissues, demonstrating tissue-specific regulation by Oga. These findings establish Oga as a critical regulator of Gal-3 expression and systemic abundance. The data reveal a mechanistic link between O-GlcNAc signaling and lectin-mediated metabolic inflammation, suggesting that Oga activity influences Gal-3 homeostasis and may affect its interpretation as a biomarker in metabolic disease.

Abstract: In Türkiye, where agriculture consumes 75% of available water and national irrigation efficiency is only 51.3%, irrigation modernization—the conversion of classical open-channel irrigation systems to pressurized pipe systems—presents a primary strategy to achieve significant water savings. This study provides a comprehensive economic assessment of the potential of this strategy. A twofold methodology was employed: first, a cost-benefit analysis (CBA) of the 36,108 ha Ivriz irrigation project, and second, a national model to simulate the economic impact of modernizing nation’s 4.9 million hectares currently irrigated by such classical systems. The Ivriz case study reveals that project viability is entirely contingent on the on-farm efficiency achieved post-modernization. At 60% efficiency, water savings are insufficient to make the project economically feasible, whereas at 90% efficiency, substantial water savings render the project highly profitable. At the national level, the analysis indicates that the conserved water could be used to expand Türkiye’s irrigated area by 1.77-2.98 million hectares, generating an additional $3.47-$5.84 billion in annual agricultural income. The findings conclude that while modernization represents a powerful investment, its success requires a comprehensive policy framework that not only funds infrastructure conversion but also mandates integrated support programs to ensure farmers adopt the high-efficiency technologies needed to achieve these savings.

Abstract: Over-the-air (OTA) updates in edge computing systems face practical challenges due to unstable network conditions and heterogeneous node capacities. To address this, we propose a task scheduling framework that integrates Deep Q-Network (DQN) reinforcement learning with a genetic algorithm. The model was tested with 120 OTA tasks across 50 industrial edge nodes. Results show that the proposed method reduces average scheduling latency by 23.9% and energy use by 18.5% compared to static baseline methods. Under network delays up to 300 ms, the task success rate remained at 99.2%, significantly outperforming FIFO and fixed-priority schedulers by 27.6%. The load distribution, measured by the coefficient of variation (COV), improved from 0.42 to 0.17. This indicates better task balancing among nodes. The framework adapts to fluctuating network conditions and provides a reliable solution for industrial and vehicle-mounted systems. However, long-term deployment effects and scalability in real-world environments require further investigation.

Abstract: OCR systems are increasingly being used in high-stakes and form-based applications, such as employment onboarding and voter registration, where accuracy is crucial to ensure system reliability. The paper introduces a test modeling and evaluation framework for Smart OCR applications that combines decision tables, context trees, and component-level complexity analysis to permit complete and automated validation. The proposed approach models document structure, environment (lighting, angle, and quality of images), and completeness of the input used to produce representative test cases of different operational situations. Accuracy and coverage measures are also used together to measure fidelity of recognition and structural completeness of multiple form components at the multimodal level, such as text fields, tables, checkboxes, radio buttons, and signatures. The framework is confirmed with an empirical case study of the application of employment and voter registration forms with three commercial OCR tools, such as Microsoft Lens, Amazon Textract, and Parsio.io. The experimental findings show the apparent trade-offs between accuracy and coverage and indicate considerable differences in symbolic and contextual extraction abilities by tools. Parsio.io scores the best on the criteria of balanced performance, as it has a high coverage and multimodal recognition strength among the tested systems.

Abstract: Cable theft is a major infrastructure security issue in South Africa, especially in Gauteng municipalities, where poverty is spatially concentrated to the extent that it has given rise to large-scale theft of electricity distribution infrastructure components. This essay focuses on the complexity of the reasons behind cable theft, including unemployment-related desperation, organized crime syndicates, governmental corruption, and international commodity markets. The study involved 19,919 reported cases from around the country and 5,914 cases from Gauteng since April 2019. It is found that cable theft is not limited to property crime, but also poses a threat to basic service delivery in the electricity, water, health, and education systems. The study reveals that effective mitigation should involve combined interventions using advanced technology (intrusion detection systems, smart meters, and mechanical barriers), enhanced law enforcement and prosecution, community involvement, and socioeconomic development measures. Evidence-based policies, such as special detection offices, scrapyard control, dedicated prosecution, and legitimacy programs that integrate infrastructure security and affordability approaches, are proposed as critical elements of sustainable reduction strategies. This study concludes that the solution to cable theft is closely connected to the constitutional obligation of South Africa to progressively fulfil socioeconomic rights; thus, municipal, provincial, and national governments must act in collaboration to address this issue.

Abstract: Over-the-air (OTA) update systems are used to deliver software in real time for fields such as aviation, railway systems, and medical devices. This study builds a cloud-based OTA setup using Kubernetes and Istio to improve update speed and system stability across different types of devices. The system includes rolling updates, blue-green switching, gRPC transmission, and message queue scheduling. Tests were run on 72 terminals from vehicle, avionics, and medical settings. Results show that the average image transfer time dropped from 842 ms to 493 ms, and the failure rate was reduced from 3.6% to 0.8%. In 500 failure tests, the average time to restore service became 38.7% shorter. These results confirm that using containers and service-level routing helps shorten delays and reduce errors in OTA processes. The method can be applied in real-world embedded systems but may require extra tuning on older hardware or unstable networks.

Abstract: Background: Cognitive aging is highly heterogeneous, not only in performance but also in how individuals perceive their own aging. Such self-perceptions may shape emotional reactions and adaptation to memory difficulties, yet little is known about their organization in patients referred to a memory clinic for a first diagnostic consultation. The primary aim of this study was to identify the internal configuration of self-perceptions of aging in such patients. A secondary aim was to compare these patterns with those observed in older adults recruited in a research unit of experimental psychology, who reported subjective complaints but had no medical referral. Methods: In total, 130 memory clinic patients and 84 laboratory participants completed, prior to the same neuropsychological testing, a psychosocial questionnaire assessing four domains: self-perceptions of memory deficits, attitudes toward aging, aging stereotypes, and multiple facets of subjective age. Network analysis was applied to examine how these variables were interrelated and to determine their relative importance in each group. Results: Across both samples, network analyses revealed distinct organizational patterns. Patients showed a unified representational system characterized by more positive associations and centered on subjective age variables. By contrast, the laboratory group showed a two-cluster network with more negative connections, organized around negative aging stereotypes. Conclusions: These findings provide novel insights into the psychosocial profile of memory clinic patients, highlighting the central integrative role of subjective age in integrating emotional responses, aging beliefs and perceptions of memory difficulties, and underline the value of network approaches in capturing heterogeneity in cognitive aging.

Abstract: It is still an open question that how the masses are formed for charged leptons. The widely accepted Yukawa coupling mechanism generally have quite randomized coupling constants for their masses. In this paper, we tried to build a simple model to calculate the masses of charged leptons. We assumed that the masses are formed by coupling of the plasma characteristic energy from the particle-antiparticle pairs in the background sea, and the electric potential inside the Compton ball. The internal structure of the charged leptons is thought to have three states, i.e. the negative charge, the positive charge and the Planck scale Kerr black hole. For electron and muon, the zitterbewegung is formed by positive charge and negative charge, but for tau, the excited zitterbewegung is formed by negative charge and the Planck scale Kerr black hole. The calculations of this simple model give quite close values for the charged leptons as compared with the lab results. We think we may need pay more attention on the internal structure of a particle.

Abstract: Convolutional neural networks are increasingly used for photovoltaic fault recognition from RGB imagery, yet high benchmark accuracy can mask shortcut learning induced by heterogeneous backgrounds, viewpoints and class imbalance. Using the Kaggle "PV Panel Defect Dataset" dataset, we compare five architectures (Baseline CNN, VGG16, ResNet50, InceptionV3 and EfficientNetB0) through a complementary explainability pipeline: LIME superpixel surrogates (with kernel-weighted R2 fidelity), occlusion sensitivity (functional relevance under localized masking) and Integrated Gradients (IG) validated by deletion-insertion curves. To reduce reliance on subjective saliency inspection, we quantify localization and concentration using IoU@Top10% against consistent proxy defect masks, Shannon entropy and Hoyer sparsity, and we summarize IG faithfulness with a Faithfulness Gap (AUC_insertion - AUC_deletion) and an accuracy-faithfulness consistency score at class level. ResNet50 attains the best predictive performance (82.3% accuracy), while EfficientNetB0 provides the strongest overall evidence faithfulness (mean Faithfulness Gap ~ 0.019) and stable, panel-centered attributions. InceptionV3 frequently yields diffuse relevance, and VGG16 produces highly concentrated but occasionally brittle hotspots. Bird-drop and Snow-covered show the most consistent alignment between accuracy and faithful evidence, whereas Clean and the two damage classes remain vulnerable to context cues (e.g., borders and background textures). The results support integrating quantitative explainability diagnostics into PV model selection and dataset curation to mitigate shortcuts and improve trustworthiness in vision-based PV monitoring.

Abstract: This research introduces an edge-optimized reinforcement learning (RL) ecosystem engineered for sustainable logistics in the blue economy, spanning maritime shipping, automated port operations, and offshore resource transportation. At its core, the system processes vast streams of real-time data from IoT sensors embedded in vessels, buoys, and drones directly at edge nodes, bypassing cloud latency to enable instantaneous decision-making in unpredictable marine conditions like storms or currents. Carbon capture analytics, derived from spectroscopic sensors quantifying direct air capture (DAC) efficiency and CO2 sequestration rates on ships, dynamically adjusts RL reward functions to favour fuel-efficient paths that maximize emissions offsets, aligning with International Maritime Organization (IMO) mandates for net-zero operations by 2050. The framework exploits 6G networks' terabit speeds, sub-millisecond latency, and non-terrestrial network integration via low-earth-orbit satellites for seamless swarm intelligence orchestration. Autonomous agents unmanned surface vessels (USVs), aerial drones, and autonomous underwater vehicles (AUVs) exhibit flocking behaviour’s inspired by particle swarm optimization, sharing pheromone-like digital signals over holographic beamforming channels to collaboratively resolve complex tasks like dynamic routing, collision avoidance, and load redistribution. Methodologically, proximal policy optimization (PPO) algorithms facilitate stable, lightweight training on resource-constrained edge hardware, augmented by federated learning to aggregate insights across privacy-sensitive multi-operator fleets without central data pooling. Rigorous evaluations in NS-3 for 6G emulation and Gazebo for maritime physics reveal transformative gains: 42% reductions in carbon footprints, 65% lower end-to-end latency versus 5G-cloud hybrids, and 30% improvements in throughput under adverse weather. Scalability tests with 1000+ agents confirm robustness in GPS-denied zones, while ablation studies highlight the synergistic impact of carbon feedback and swarm coordination over siloed baselines like genetic algorithms or centralized RL. By embedding quantum-safe encryption for 6G links and digital twin interfaces for predictive maintenance, this ecosystem not only decarbonizes blue economy logistics but also sets a scalable blueprint for AI-driven sustainability in cyber-physical systems worldwide.

Abstract: Over-the-air (OTA) updates in multi-tenant systems often face task conflicts, cache overlap, and weak fault recovery during parallel updates. This study designed a layered fault-tolerance and isolation method that combines task redundancy, cache separation, and snapshot rollback. Tests were carried out on 120 devices across six tenants with a fault rate of up to 95%. The system kept stable operation, extended the mean time between failures (MTBF) to 182 hours, and raised total availability from 98.2% to 99.7%. The average update delay per tenant stayed below 1.1 seconds, showing that higher reliability did not slow the process. The method effectively avoided tenant interference, reduced recovery time, and improved update stability. It provides a simple and practical solution for dependable OTA updates in industrial, automotive, and IoT systems.

Abstract: The use of light (photons) delivered clinically from laser or light-emitting diodes (LED), is referred to as photobiomodulation therapy (PBMt). Increasingly PBMt is accepted particularly in dental practice for pain or pre-emptive anaesthesia. Understanding its mechanism of effectiveness is the key to its increasing acceptance. Of major importance to this is how PBMt affects not only the neurons but also the Schwann cells and fibroblasts of the peripheral nervous system which are unique in morphology and function. The specific roles of the neuronal cells of the dorsal root and trigeminal ganglia, now include consideration of the axon initial segment responsible for the initiation of the action potential and the T junction from which the distal and proximal axons arise which are complex but central to normal function. This cellular complexity, organization and function is discussed leading to a review of the mechanism of effectiveness of PBMt demonstrated by clinical trials in both medicine and dentistry. This review provides evidence of the involvement of the cytoskeleton, mitochondrial organization particularly related to fast and slow axonal flow and mitochondrial membrane potential in response to light in somatosensory neurons and nerves.

Abstract: The centrosome, long recognized as the primary microtubule-organizing center (MTOC) of animal cells, is re-examined through the lens of information theory and systems biology. This preprint proposes a unifying hypothesis: the mother centriole within the centrosome acts as a non-genetic cellular ledger, a stable structural repository that accumulates molecular records of a cell’s replicative history and environmental exposures. These records—comprising specific post-translational modification (PTM) signatures, retained proteins, and structural alterations—are subsequently “read” by the cell to inform critical decisions regarding proliferation, differentiation, senescence, and apoptosis. We synthesize evidence from cell biology, gerontology, and evolutionary biology to construct the “Centrosomal Ledger Model.” This model positions the centriole not as a passive cytoskeletal component but as an active, heritable information-processing node that integrates temporal data across scales—from circadian rhythms to organismal aging. We detail the molecular mechanisms of information encoding (e.g., tubulin polyglutamylation, oxidative marks) and decoding (via ciliary signaling, proteostatic feedback, and mechanical transduction). The model’s implications challenge genetic determinism by highlighting structural inheritance, provides a material basis for cellular age, and offers novel, falsifiable avenues for experimental interrogation in aging and cancer research. Crucially, it suggests that modulating the “read-write” cycle of the centrosomal ledger could represent a new frontier in regenerative medicine.

Abstract: This study assessed the spatial distribution and composition of airborne particulate matter within a 10-km long urban green corridor in Zacatecas, Mexico, using magnetic biomonitoring with Tillandsia recurvata and SEM-EDS particle characterization. A total of 44 samples were collected from distinct urban park contexts (e.g., commercial zones, malls, bus stop), revealing mass-specific magnetic susceptibility χ values ranging from -6.71 to 61.1 × 10⁻⁸ m³kg-1. Three compositional groups were identified based on a PCA performed using elemental concentrations from SEM-EDS and magnetic data, which are associated with traffic emissions and industrial inputs. SEM-EDS images confirmed abundant magnetite-like particles (1–8 μm) with hazardous metals including Pb (up to 5.6 wt.%), Ba (up to 67.6 wt.%), and Cr (up to 31.5 wt.%). Wind direction data indicated predominant SSW-NNE transport, correlating with hotspots in central and northeast-ern park areas. Overall, vegetated zones displayed significantly lower magnetic loads (mean χ = 8.84 × 10⁻⁸ m³kg⁻¹, σ = 6.65 × 10⁻⁸ m³kg⁻¹) compared to traffic-exposed sites (mean χ = 17.27 × 10⁻⁸ m³kg⁻¹, σ = 12.44 × 10⁻⁸ m³kg⁻¹), emphasizing the pollution mitiga-tion role of green barriers. This research highlights the applicability of combined mag-netic and microscopic techniques for evaluating the dynamics of airborne pollution in urban parks and supports their use as biofunctional filters in cities facing vehicular air pollution.

Abstract: This paper undertakes a foundational exploration of the nature of mathematics from both historical and philosophical perspectives, with a primary focus on the Indian intellectual tradition. It traces the evolution of mathematical thought from ancient Vedic texts such as the ´Sulba S¯utras, through the formal grammar of P¯an. ini, to modern abstract mathematics including group theory, automata, and topology. The investigation is rooted in the dual inquiries of ontology and epistemology, examining what it means for mathematics to be and how mathematical knowledge is constructed and validated. Particular emphasis is placed on the Indian concepts of gan. ita (mathematics), ´s¯unya (zero), and ´s¯unyat¯a (emptiness), and their correspondence with Western notions such as the Cartesian dualism, the set-theoretic empty set, and symbolic logic. The paper explores the recursive cosmological cycles found in Indian time theory, mathematical cosmology, and ritual geometry, showing how these ideas anticipated or paralleled developments in modern mathematics, including measure theory, combinatorics, and fractals. With detailed references to logical systems (Ny¯aya), sacred architecture (v¯astu-´s¯astra), cyclic time constructs (kalpas and yugas), and formal structures in linguistic grammar (As.t. ¯adhy¯ay¯ı), the paper argues for a view of mathematics as both a sacred science and a system of abstract formalism. Across these investigations, mathematical structures are treated not merely as tools for calculation but as profound reflections of metaphysical principles, visualizable through mandalas, yantras, and cosmological diagrams. This study invites a reassessment of how different cultures have understood and visualized mathematics as an expression of cosmic and cognitive order.

Abstract:

Leuenbergeria bleo (Kunth) DC. (Cactaceae), previously classified as Pereskia bleo, represents a phylogenetically basal cactus species with a disjunct distribution across Central America, Southeast Asia, and southern China. Phytochemical investigations have traditionally emphasized small-molecule secondary metabolites, including phenolics, alkaloids, and terpenoids, which contribute to antioxidant and anti-inflammatory activities. However, recent peptidomic analyses have expanded this chemical space through the discovery of bleogens, a family of hyper-stable, cysteine-rich microproteins with specific antifungal and wound-healing properties. This review systematically integrates botanical characteristics, ethnomedicinal applications, and pharmacological profiles, providing a comparative analysis of the plant’s small-molecule constituents versus its peptidyl biologics. It identifies the co-existence of these distinct chemical classes as a defining feature of the plant’s efficacy while highlighting the need for future research into their potential interactions.

Abstract: The increasing demand for recombinant proteins has driven innovation in bioprocessing strategies using Komagataella phaffii as a host organism. Conventional fed-batch cultivation with pure methanol induction remains widely used but presents challenges including high methanol consumption, extended downtime, and elevated operational costs. This study evaluates alternative strategies combining mixed induction (methanol/sorbitol) with continuous cultivation to enhance productivity, sustainability, and improved economic outcome. Using KEX2 protease as a model industrial recombinant protein, we compared four cultivation modes: fed-batch with methanol (benchmark), fed-batch with mixed induction, continuous with methanol, and continuous with mixed induction. Cell growth, volumetric yield, and specific productivity were evaluated at 5L scale and then modelled to simulate industrial scales (40 L and 400 L). Results demonstrate that continuous cultivation with mixed induction significantly improves yield up to 9-fold compared to conventional fed-batch and reduces methanol usage and oxygen demand. Techno-economic simulations reveal that a 40 L continuous process can match or exceed the output of two 400 L fed-batch runs, while lowering capital and operating costs and minimising environmental footprint. This integrated strategy offers a scalable, cost-effective, and safer alternative for recombinant protein production, supporting the development of compact and sustainable manufacturing platform