Abstract: Background: Direct annual national series on AI adoption in higher education are not consistently available for Uzbekistan, yet the diffusion of AI-enabled learning depends on measurable digital and economic preconditions. Methods: Using annual data for 2000–2023, this study models tertiary enrollment as a macro-level proxy for the expansion of AI-ready higher education, with internet use, mobile subscriptions, and real GDP per capita as explanatory factors in a trend-augmented ARDL/UECM framework. Trend-aware unit-root testing, lag selection, bounds testing, and residual diagnostics are implemented as one closed empirical sequence. Results: The preferred ARDL(1,3,1,1) specification supports cointegration, a significant error-correction mechanism, a positive long-run role for mobile access, and a negative internet coefficient after controlling for mobile inclusion, income, and structural trend. Conclusions: AI readiness in higher education should be interpreted as a conversion problem rather than a simple connectivity problem.

Abstract: This research answers the knowledge gap regarding the explanation of the quantum jump of the electron. This scientific paper aims to complete Einstein’s research regarding general relativity and attempt to link general relativity to quantum laws.

Abstract:

Phycobiliproteins (PBPs) are a family of pigment-proteins renowned for their exceptional light-harvesting, fluorescent, and antioxidant properties. Among cyanobacteria, Spirulina stands out as one of the richest natural sources of PBPs, particularly phycocyanin (PC) and allophycocyanin (APC), yet the large-scale production of analytical-grade PBPs remains hampered by an inherently complex downstream process that relies on multiple purification steps, compromising both yield and scalability. This work presents a streamlined strategy to obtain analytical-grade PC, combining ultrasound-assisted extraction (UAE) with an aqueous ionic liquid (IL) solution and a single hydrophobic interaction chromatography (HIC) step, integrated within a biorefinery framework. The proposed approach yielded analytical-grade PC with a recovery of up to 50.44% and enhanced APC purity up to 10.57-fold. Therefore, the IL was successfully reused in both extraction and purification steps without compromising yield or purity. The environmental performance of the proposed process was assessed through a cradle-to-gate life cycle assessment (LCA), with system boundaries encompassing the following biorefinery stages: cultivation, harvesting and drying, PC extraction and purification, post-processing, and spent biomass valorization via anaerobic digestion. The LCA identified the main environmental hotspots and guided the proposal of targeted process improvements—particularly HIC salt substitution and increased IL recovery—which reduced environmental impacts by 65.9–89.8% across most categories. The proposed strategy was further benchmarked against two model scenarios for analytical-grade PC production, one conventional and one innovative, revealing its relative advantages and limitations. Overall, this work demonstrates a viable pathway for producing high-purity PC that balances process efficiency with environmental sustainability, supporting the development of greener microalgae-based bioprocesses.

Abstract: Most theories of emotion assume that emotional experiences arise from the interaction between bodily states, cognitive processes, and the surrounding environment. Despite this convergence, a central empirical problem remains insufficiently explained: similar physiological states can give rise to markedly different emotional experiences depending on context.Existing approaches provide partial accounts of this variability. Biological models characterise the role of bodily signals, predictive and constructivist frameworks emphasise inference and conceptual knowledge, and socio-cultural theories highlight the influence of norms and shared meaning. However, these perspectives often fail to distinguish between two levels of top-down organisation: conceptual knowledge, which provides the categories used to interpret affective states, and socio-cultural constraints, which regulate which interpretations become plausible and stable in a given context.In this article, we propose a tri-directional framework in which emotion emerges from the ongoing interaction between bodily signals, predictive processes, and socio-cultural constraints. Within this perspective, emotional experience is conceptualised as a process of constrained selection under uncertainty: bodily signals generate ambiguous affective input, predictive processes organise candidate interpretations, and socio-cultural constraints bias their stabilisation.A central implication of this framework concerns the role of stress. Rather than producing a uniform increase or decrease in emotional responding, stress is conceptualised as a constraint on regulatory dynamics that reduces the range of accessible interpretations and amplifies the system’s dominant mode of stabilisation. This leads to the prediction that, under stress, emotional responses will diverge rather than converge depending on contextual and socio-cultural factors.By integrating biological, inferential, and socio-cultural perspectives within a unified framework, this approach provides a more precise account of emotional variability and generates testable predictions regarding the dynamics of emotion under conditions of uncertainty.

Abstract: In the past year, the medical regulation of psilocybin-assisted therapy has expanded across additional international jurisdictions, requiring an update to the original medico-legal synthesis. Newly established or clarified regulatory pathways in New Zealand, Germany, Switzerland, the Czech Republic, and at the United States federal level reflect continued evolution in therapeutic governance. Within the United States, Utah and New Mexico have now joined Oregon and Colorado in establishing lawful medical access pathways. These developments build upon earlier reforms in Alberta, Canada and Australia, where structured psychiatric prescribing frameworks were implemented.This update consolidates recent statutory amendments and regulatory decisions to provide a current comparative overview of jurisdictions permitting lawful medical use of psilocybin. By distinguishing comprehensive medical regulation from restricted or exceptional access schemes, this revised analysis maintains clarity within an increasingly dynamic global regulatory landscape.

Abstract: Large language model (LLM) inference in multi-tenant clouds is becoming an increasingly important contributor to data-center carbon emissions, yet existing carbon-aware scheduling techniques target long-running training jobs and are ill-suited for the short, bursty, SLO-sensitive nature of online serving. We propose CAPS (Carbon–Aware Prompt Scheduling), an online bi-objective scheduler that jointly optimizes goodput and per-request carbon cost for multi-tenant LLM inference. CAPS first employs a lightweight prompt complexity predictor to estimate token generation cost and latency risk for each incoming request. It then combines real-time grid carbon intensity, GPU energy profiles, and per-tenant SLO tiers to route each request to one of three execution pools: a low-latency pool, a low-carbon pool, or a delay-tolerant batch pool. A composite reward function balances goodput, carbon emissions, and SLO violation rate. In trace-driven simulations using public conversation traces and regional carbon intensity data, CAPS reduces average carbon emissions per 1K generated tokens by 26.8% compared to round-robin scheduling while achieving an SLO attainment rate that matches or exceeds a dedicated SLO-aware baseline.

Abstract: Megacity mobility research has long relied on aggregate statistical indicators — composite traffic-planning indices and accessibility surfaces — that capture the system at rest but are disconnected from the operational decisions shaping mobility minute to minute. In parallel, Agentic AI, articulated in the Web of Agents narrative of [28], offers a reference paradigm of semantically interoperable autonomous agents that negotiate and coordinate across open networks. We propose a unifying Agentic AI reference architecture for urban transportation that maps any composite traffic index and any accessibility surface onto agent utility functions, negotiation-protocol primitives, and shared semantic ontologies. The architecture is instantiated in simulation only: no live A2A/MCP endpoints, no runtime LLMs, no cross-organisation interoperability experiment; these are explicitly listed as next steps.A 12-borough London case study, evaluated over N = 30 seeds on an origin-destination matrix calibrated to the 2021 UK Census commuter-flow aggregates [24], benchmarks four regimes (historic, adaptive, MaxPressure, and our Agentic policy) across four scenarios covering equity, corridor prioritisation, incident response, and their combination. The Agentic regime reduces the accessibility-deficit Gini coefficient by 23–58 %, travel-time CV by up to 41 % and mean travel time by 4–9 % relative to the historic baseline, and is the one regime in our four-way comparison that sits near the per-column best on all three objectives simultaneously when equity and incident-response interact. A microscopic SUMO testbed on a 4×4 signalised grid (120 runs across three demand regimes and five peripheral-boost values) traces an explicit equity–efficiency Pareto frontier on which the agentic policy matches or beats a SCOOT-style adaptive controller on mean travel time and throughput at every operating point, while reducing travel-time variance by up to a third.

Abstract: Active mobility in peri-urban areas is influenced by sprawl, limited public transportation, and reliance on private vehicles. This study redefines active mobility in peri-urban and low-density contexts from a territorial perspective informed by the Veneto Region and reframes micro-hubs as socially oriented, network-integrated elements rather than scaled-down urban hubs. This study adopts a qualitative, theory-driven methodology combining a multidisciplinary review of the active mobility concept with thematic analysis to identify mobility hub characteristics, followed by analytical synthesis, the classification of mobility hub types, and a set of social indicators for analyzing their performance. These methods are used to develop a framework for understanding mi-cro-hubs as socio-spatial components of active mobility networks. Results indicate that a network of minor roads and micro-hubs can support shifts toward active mobility when aligned with daily mobility patterns and supported by multi-level governance. The study outlines the socio-spatial roles of micro-hubs and defines them as nodes that link local networks and everyday mobility systems, distinguishing three roles: network, welfare, and civic. Socio-spatially integrated micro-hubs can be effective in reducing car dependence while providing transferable policy-oriented actions for similar peri-urban and low-density areas.

Abstract: Wearable systems for rehabilitation monitoring often rely on complex sensor configurations and produce outputs that are difficult to interpret. This limits their practical use. This study investigates whether movement-quality assessment can be achieved accurately and transparently using a reduced set of signals. Using wearable sensor data from lower-limb rehabilitation tasks performed under correct and intentionally erroneous conditions, we extracted a small set of rotation-based features and evaluated them within a supervised ML framework. The results show that these features can reliably distinguish correct from incorrect movement, with classification accuracy around 0.70, while preserving clear biomechanical interpretation. Reduced sensor configurations retained, and in some cases improved, performance, with balanced accuracy reaching 0.947 and 0.917 in the examined tasks. A proof-of-concept real-time formulation further showed that movement deviations can be detected early within repetitions, while limiting false feedback on correct executions to approximately 9%. Overall, the findings show that movement-quality assessment can be achieved with minimal sensing, while also supporting early error detection and practical feedback. These properties are relevant to wearable rehabilitation systems, including IoT applications that depend on efficient sensing, interpretable analysis, and timely feedback.

Abstract: Qilian sheep are an important local breed of Tibetan sheep with strong adaptation to cold and hypoxic environments. To identify candidate genes related to nutrient metabolism in Qilian sheep, this study compared liver transcriptomes between Qilian sheep and Oula sheep raised under the same grazing and feeding conditions. Six 10-month-old ewes were selected from each breed, and three liver samples with high RNA quality from each group were used for transcriptome sequencing. Differential expression analysis identified 1640 differentially expressed genes under the thresholds of |log2FoldChange| > 1 and false discovery rate < 0.05, including 718 upregulated and 922 downregulated genes. KEGG enrichment analysis showed that these genes were mainly involved in lipid metabolism- and amino acid metabolism-related pathways, especially the peroxisome proliferator-activated receptor signaling pathway, fatty acid synthesis, and fatty acid beta-oxidation. qRT-PCR validation confirmed that RGN, LPGAT1, and BHMT2 were significantly upregulated, whereas SDS, GK, PC, MIOX, HMGCS2, PNPLA3, ACAA2, and HADHA were downregulated in Qilian sheep. These results indicate clear differences in liver nutrient metabolism-related gene expression between Qilian sheep and Oula sheep and provide a molecular basis for understanding the liver metabolic characteristics and adaptive metabolic mechanisms of Qilian sheep.

Abstract: Inclusion has become a central concept in disability policy, education, and welfare state reform, yet its practical implementation remains ambivalent. While inclusion is promoted as a rights-based ideal grounded in equality, it can also function as an administrative label that obscures persistent exclusion. Drawing on critical disability studies, this article analyses inclusion as a contested, power-laden concept and develops a three-stage framework—access, participation, and agency—to distinguish formal inclusion from substantive belonging and influence. The framework is applied to key domains of disabled people’s lives—education, housing, service systems, working life, crises, and digitalised everyday life—showing how ableist norms, managerial governance, and institutional logics can reproduce exclusion within ‘inclusive’ reforms, including forms of transformed institutionalisation. The article argues that meaningful inclusion requires dismantling ableist norms, addressing structural power relations, resourcing supports, and strengthening disabled people’s agency in decision-making.

Abstract: This position paper argues that in software-defined dry-lab AI research, the one-person laboratory (OPL) is the relevant minimum accountable unit under compressed coordination and should be treated as a first-class unit of evaluation wherever bounded verification and public contestability hold. We develop three propositions. P1 (descriptive): public research-agent systems and laboratory-shaped benchmarks suggest that the minimum efficient research unit is moving downward in parts of AI research. P2 (causal, conditional): the relevant gains are narrower than common ``AI scientist'' rhetoric implies---not general scientific superiority, but lower iteration latency per admitted claim, stronger provenance, higher replayability, clearer responsibility, and better retention of negative branches when abstention and disclosure are enforced. P3 (normative, conditional): the community should therefore evaluate and support OPLs as claim-producing laboratories rather than only models or PDFs, while simultaneously building public execution interfaces, trace-linked claim standards, benchmark sandboxes, and access institutions. Our empirical anchor is a purposive structured interpretive read of representative public systems and benchmarks; it is not a leaderboard and does not estimate prevalence, causal impact, or superiority. We do not claim that \opl{}s replace strong teams, justify broad scientific claims from a single run, or cleanly extend to wet-lab, clinical, or human-subject domains. The paper's contribution is a falsifiable governance position: if laboratory-shaped systems fail to cohere, if OPL-style runs do not improve admitted-claim speed or auditable process quality, or if access remains closed, the thesis should be weakened or reversed.

Abstract: We present a self-contained exposition of the Lyons carabiner, focusing on the triple obstruction mechanism arising in Section~\ref{sec:triple}. Three independent numerical obstructions---phantom coupling $\pi$, holonomy defect $\rho$, and braid deficit $\beta$---together form the triple $(\pi,\rho,\beta)=(3,4,9)$, which uniquely recovers the MDS code $[6,4,3]_5$ over $\mathbb{F}_5$. This identification is not a postulate but a provable consequence of the weight distribution and the complement involution. We then develop the Pontryagin--Heegner bridge: phantom weights are ``silent frequencies'' in the Pontryagin dual of $\mathbb{R}_+^\times$, and their vacuum generates the $20$-dimensional \emph{inverse Heegner space} $\mathcal{H}_{20}$. This yields a candidate $44$-dimensional lattice $\Lambda_{44} = \Lambda_{24} \oplus \mathcal{H}_{20}$ with Lyons group symmetries. The phantom resolution cascade $\mathrm{Ly}\to\mathrm{HS}\to\mathrm{Ru}$ predicts a chain of lattice dimensions $44\to 34\to 24$, terminating at the Leech lattice $\Lambda_{24}$, with the Rudvalis level providing independent numerical evidence through striking orbit coincidences. All numerical claims are verified by machine-checked computation. ( The Lean~4 formalization is available as the \texttt{HatsuYakitori} library; the key files are \texttt{MachineConstants.lean}, \texttt{LyonsCarabiner.lean}, and \texttt{RudvalisCarabiner.lean}. Remaining \texttt{sorry}s are listed explicitly in Section~\ref{sec:conclusion}.

Abstract: Aging is characterized by a progressive decline in physiological resilience and increased susceptibility to chronic diseases, including neurodegenerative disorders. Emerging evidence indicates that low-dose stressors (collectively termed hormetic stimuli) activate adaptive cellular responses that enhance stress resistance, promote repair mechanisms, and ultimately extend healthspan. This narrative review synthesizes current knowledge on hormesis in the context of aging, with a focus on key molecular pathways including nuclear factor erythroid 2–related factor 2 (Nrf2), sirtuins, autophagy, and mitohormesis. We examine how lifestyle interventions (physical exercise, caloric restriction, mild thermal stress) and emerging pharmacological agents induce beneficial adaptive responses, while critically evaluating their translational potential in clinical and public health settings. Special emphasis is placed on the role of hormesis in counteracting neurodegeneration, the utility of autophagy and systemic aging biomarkers (epigenetic clocks, inflammaging scores) for precision dosing, and the limitations imposed by inter-individual variability, age-related decline in adaptive capacity, and risks of overexposure. Understanding the delicate balance between beneficial and detrimental stress responses is essential for leveraging hormesis as a robust strategy to counteract aging and age-related diseases. We further propose a multilevel framework integrating molecular mechanisms with clinical outcomes, positioning hormesis as a key determinant of adaptive resilience in aging.

Abstract: Briquette du Kivu (BdK) is a social enterprise operating in Bukavu, eastern Democratic Republic of the Congo, a region facing persistent food insecurity and environmental degradation linked to prolonged conflict. To reduce dependence on wood-derived cooking fuels and associated deforestation, estimated at approximately 300 hectares of forest lost annually, BdK produces clean-burning charcoal briquettes from locally available organic waste. Because food waste cannot be directly carbonized due to its high moisture content, BdK’s process first employs black soldier fly larvae (BSFL, Hermetia illucens; Diptera: Stratiomyidae) to bio-convert organic substrates into a stabilized residue (frass) while substantially reducing substrate volume. The resulting frass is then carbonized in specialized kilns, mixed with a clay binder, extruded into long cylinders and then sun-dried to produce the final fuel product. In addition to providing a renewable cooking fuel, the system generates protein-rich insect larvae that are sold locally as livestock feed, while a portion of the frass is used as fertilizer in BdK’s fruit tree nursery. The nursery supplies grafted trees to regional households, contributing to food production and supplemental income generation. By integrating waste management, insect bioconversion and fuel production, BdK’s model demonstrates how small-scale circular bioeconomy systems can simultaneously address waste accumulation, energy access and livelihood development in conflict-affected regions.

Abstract: Background: Strength-Duration (S-D) assessment is commonly used in clinics to examine the excitability of peripheral nerves and muscles. Yet, how changes in neuromuscular excitability relates to improved athletic and muscular performance in healthy subjects remains poorly understood. Therefore, the aim of the study was to evaluate the electrophysiological changes in neuromuscular excitability in the vastus medialis (VM) muscle, using the S-D assessment, following a back squat conditioning activity (BS-CA) protocol designed to elicit a post-activation potentiation (PAP)/post-activation performance enhancement (PAPE) effect. Methods: Eleven athletic males were included in this study. All subjects performed two trials: one examining their BS one-repetition maximum (1 RM) and a main experiment. During the main experiment, baseline levels of rectangular rheobase (R-RIC), triangular rheobase (R-DIC) and chronaxie was collected from the VM muscle, following a standard warmup. Subsequently, the subjects performed three warmup BS-sets and executed a top set of five repetitions (reps) at 80% of 1RM. Afterwards, R-RIC, R-DIC and chronaxie was reassessed for pre and post analysis. Based on these S-D curve (SDC) parameters, the muscle adjustability quotient (MAQ) and threshold charge (Q) was also computed and compared. Results: The R-RIC, R-DIC and Q were all significantly higher following the BS-CA, compared to pre-intervention (p < 0.001). No significant differences were observed for the chronaxie and MAQ (p > 0.05), although an increasing trend was noted (p = 0.054). Conclusions: Based on the findings from this study, the neuromuscular excitability in the VM muscle can be acutely altered following a BS-CA-protocol. However, these changes seems to be more related to muscle fatigue than PAP/PAPE. Nevertheless, S-D assessment may broaden our understanding of the fatigue process during exercise.

Abstract: Background: Women with polycystic ovary syndrome (PCOS) have a substantially increased risk of endometrial cancer (EC), yet the biological mechanisms underpinning this association remain incompletely understood. Insulin-like growth factor (IGF)-associated signaling has been implicated, but existing evidence is conflicting. Methods: This feasibility and hypothesis-generating study combined a small clinical cohort with exploratory transcriptomics, in vitro and in silico analyses. Serum IGF1 and IGFBP-3 were measured in women with PCOS (n = 12 for IGF-1 and n = 6 for IGFBP-3) and controls (n = 24 for IGF1 and n = 7 for IGFBP-3). Pooled serum, stratified by IGF bioactivity, was applied to a human endometrial cancer cell line (HEC1A) to further assess effects on cell viability, cell cycle distribution, and downstream signaling, in addition to exploratory RNA sequencing (n=1 biological replicate per condition). Computational analysis of publicly available endometrial cancer datasets was used to contextualize experimental findings. Results: Serum IGF1 and IGFBP-3 levels did not differ significantly between PCOS and control groups. However, pooled PCOS serum increased EC cell viability and altered cell cycle progression compared with control serum. Pharmacological inhibition of IGF1R partially attenuated these effects, suggesting that IGF-associated pathways may contribute but are unlikely to act in isolation. Exploratory transcriptomic profiling of serum-treated EC cells supported enrichment of IGF-associated metabolic and growth programs (including mTORC1, PI3K/AKT/mTOR, glycolysis and oxidative phosphorylation), consistent with context-dependent modulation rather than IGF-only dependence. In silico analyses demonstrated frequent alterations in PI3K/AKT/mTOR-related genes in endometrial cancer, consistent with pathway-level vulnerability rather than IGF1-specific dependence. Conclusion: As a feasibility study, these findings suggest that PCOS serum contains factors that promote EC cell growth, with partial involvement of IGF signaling. However, multiple metabolic and hormonal pathways are likely to contribute. Larger, better-controlled studies incorporating insulin, sex steroids, and multiple EC models are required before causal inferences can be made.

Abstract: We formulate and derive an uncertainty principle for ultraviolet-complete non-local quantum field theory regulated by an entire function of the d’Alembertian. Under explicit hypotheses on the induced equal-time detector response kernel we prove that the observed localization width obeys an exact variance-addition law. Combining this with the ordinary Heisenberg inequality gives us a non-local uncertainty relation. The bound reduces to the usual local relation in the infrared or local limit when E_M → ∞, while in the ultraviolet it implies a minimal localization length of order L_M. We then explain what this means for locality, microcausality, the interpretation of spacetime points, and the ultraviolet structure of quantum field theory. In this framework spacetime remains a Lorentz-covariant continuum at the level of the manifold description but pointlike localization ceases to be a physically realizable observable notion below the intrinsic non-locality scale.

Abstract: Traditional cosmological arguments are often thought to rely fatally on the Principle of Sufficient Reason (PSR). This paper develops a contingency argument that does not. We adopt a two-sorted first-order logic with predicates for world-membership and symmetric accessibility between possible worlds. Within this framework, we formulate four axioms, each verified to be consistent and independent both from one another and from the PSR. We provide philosophical justification for each axiom. Then, we demonstrate that, if the empty world does not access any non-empty world, the existence of a necessary entity follows from the well-foundedness of a transmundane material condition of possibility.

Abstract: Background/Objectives: Protozoan parasites of the genus Leishmania are causative agents of a group of devastating human diseases, known as leishmaniasis. These microorganisms possess very unusual mechanisms of gene expression that are poorly understood. This study was aimed at analyzing the tRNA repertoire encoded in the Leishmania infantum genome, a species responsible for the most severe form of disease, visceral leishmaniasis. tRNAs are adaptor molecules aimed at decoding mRNAs into proteins. Results: A total of 92 tRNA genes, dispersed on 38 loci were identified; often located in regions where unidirectional gene arrays converge. Putative intronic sequences were inferred for three tRNA genes, and, remarkably, 9 tRNAs were identified within the protein-coding sequences of annotated genes. According to structural predictions, the L. infantum tRNA repertoire covers 49 of the 61 possible anticodons, but because of the well-documented wobble phenomenon, these are sufficient to decode all codons in the 8532 protein-coding genes currently annotated in its genome. As illustrated in this study, codon usage is a well-conserved trait among different Leishmania species but differs substantially regarding the codon usage of its human host. Finally, we analyzed tRNA adaptation index (tAI) parameters, codon usage metrics, and relative protein expression levels. Conclusions: Apart from providing the tRNA gene repertoire and its genome distribution, we have shown the existence of a statistically significant, positive correlation between the tAI scores and protein expression levels in L. infantum promastigotes.