Abstract: To investigate the interaction between mine ventilation and the thermal en-vironment in a fully mechanized longwall face, a Computational Fluid Dy-namics (CFD) model was developed for the 11-3107 working face of Menkeqing Coal Mine based on field-measured data. The model was used to analyze the effects of ventilation mode, electromechanical equipment layout, roadway length, airflow velocity, and inlet air temperature on the thermal environment of the working face. The results show that changing the ventilation mode alone has only a limited effect on reducing the maximum face temperature, although the U-shaped system provides a comparatively practical ventilation arrange-ment under the studied conditions. Locating major electromechanical equipment in the return airway helps reduce the temperature in the intake airway and working face. Shorter ventilation routes, higher airflow velocity, and lower inlet air temperature all contribute to improved thermal conditions. Considering both simulation results and operational constraints, cooling equipment should be installed near the intake airway to effectively lower the working-face temper-ature. Based on psychrometric analysis and ventilation parameters, the required cooling load for the 11-3107 fully mechanized working face was determined to be 2417 kW under normal conditions and 3082 kW under critical conditions, in-cluding a 20% safety margin. The study provides a numerical basis for venti-lation optimization, cooling-system design, and heat-hazard control in deep underground coal mines.

Abstract: Fusarium spp. are active producers of mycotoxins that enter the food chain and pose risks to human health. Identifying pathogenic agents is a key step in developing disease management strategies. For the first time in Bulgaria, we identified Fusarium species in wheat, harvest 2024÷2025, through the application of DNA barcoding. For genetic marker and construction of phylogenetic tree, the protein-coding gene β-tub was chosen. Among 26 identified isolates, F. sporotrichioides (42.3%) dominated, followed by F. proliferatum 23.1%), F. avenaceum (7,7%), F. armeniacum (7.7%), аnd F. poae (7,7%). F. tricinctum (3.8%), F. oxisporum (3.8%), and F. equiaseti (3.9%) were weakly expressed. Phylogenetic analysis classified the isolates into 5 species complexes: FSAMSC, FFSC, FTSC, FIESC, and FOSC and highlighted the genetic distances between them.Molecular genetic analysis showed that 84.6% of the wheat samples contained only one species of Fusarium, and in 15.4% the co-presence of two species was established. The largest share was in samples with low infestation 2÷4%, which represented 35% (n=32) of all positives. No statistically significant difference was found between the varieties and the level of contamination, as well as between the origin of the selected varieties and the level of contamination.

Abstract: This study examines household demand for drinking water in rural central India using a revealed preference framework applied to a stratified sample of households across villages with and without piped water supply. Departing from the contingent valuation methods prevalent in earlier literature, the study employs a discrete choice model to identify the determinants of water source selection. In settlements without piped supply, distance to the water source and female educational attainment emerge as the principal determinants of safe water preference, whilst household income is not significant. Where piped supply exists, income, price, and household size shape the decision to opt for a private yard connection. The monetary value of time spent collecting water indicates a substantial willingness to pay. The findings demonstrate that rural households already behave as rational economic agents in their water decisions, undermining paternalistic assumptions embedded in India's supply-driven policy framework. The paper argues for a tiered service model that guarantees a minimum standard of provision for all whilst permitting enhanced service levels for those willing and able to pay, thereby reconciling equity commitments with financial sustainability.

Abstract: Climate change is making it more difficult for farmers in Nigeria to grow crops, ensure food security, and compete in global agricultural markets. One main, however often overlooked, factor including strain to food crops is ultraviolet (UV) radiation. This study examines how introducing UV radiation sensors to Nigeria's climate information system could make agriculture trade more climate-resilient and support the SDGs. The study discovered seasonal and regional UV variations that correspond to Nigeria's cropping cycles and agricultural trade activities using satellite UV data, agricultural production, crop calendars, and export records from 2021 to 2024. This paper also found that precise UV monitoring can notify farmers and exporters of any weather threats. This may also help them to make better planting, crop growth, and harvest decisions with this knowledge. The study also emphasizes that expanding UV sensors in crop production and trade, the value of integration, data availability, and technical competence must be addressed. The study concludes that Nigeria needs an enhanced UV sensor to increase weather adaptation to satisfy international crop standards, food production and protection, and to stay competitive in agricultural global markets despite climate change. This UV sensing integration into the climatic system is important to Nigeria's agricultural crop growth and trade sustainability.

Abstract: Traumatic exposure does not uniformly lead to persistent posttraumatic symptoms, suggesting that vulnerability depends on more than event intensity alone. The Symbolic Objectification Hypothesis (SOH) proposes that an important determinant of traumatic outcome is the representational form in which threat is processed during activation. Specifically, risk increases when threat cannot be maintained as a bounded, identifiable, and cognitively manipulable object while executive continuity remains intact. Under these conditions, threat is more likely to become immersive, increasing the probability of defensive capture. SOH integrates findings showing that threat activation is graded and can coexist with organized cognition, and it proposes a mechanism linking representational failure to persistent re-experiencing. When symbolic objectification breaks down during encoding or reactivation, attentional narrowing increases, sequential processing becomes less stable, and temporal and contextual integration are weakened. Subsequent retrieval may therefore be more likely to evoke a present-oriented reliving state rather than an autobiographically situated memory. The hypothesis is operationalized through repeated indicators of symbolic objectification maintenance and restoration during activation, together with performance-based markers of discontinuity and recovery that index defensive capture. SOH generates falsifiable predictions regarding trauma vulnerability, symptom persistence, and treatment response. Clinically, the model suggests that trauma-focused interventions may be strengthened by pairing exposure-based engagement with explicit training in symbolic objectification, with the goal of reducing immersive threat experience while preserving executive continuity.

Abstract: The integration of artificial intelligence (AI) and algorithmic decision-making into international relations represents a significant evolution that current theoretical frameworks have not fully accommodated. Established International Relations (IR) paradigms—realism, liberalism, and constructivism—typically conceptualize technology as a tool for statecraft rather than as an influential factor actively shaping the decision-making environment. This paper asserts that such a conceptual omission is increasingly untenable. Utilizing an integrative analysis spanning IR theory, AI ethics, security studies, and political economy, this work examines three principal aspects of "algorithmic diplomacy": (1) the ways in which algorithmic bias within systems operated by international organizations perpetuates structural inequalities between North and South; (2) the impact of AI incorporation into nuclear command and control systems on the logic of Mutually Assured Destruction (MAD) and crisis management timelines; and (3) the emergence of computational power imbalances in trade and climate negotiations as a novel form of diplomatic influence. The conclusion presents an initial framework for machine-mediated international relations and emphasizes the necessity for normative and governance responses at both national and multilateral levels.

Abstract: Universal Accessibility in Astronomy requires a paradigm shift from visual-centric communication to multisensory data interaction. This article explores the development and evaluation of a low-cost, multimodal tool designed to represent complex astronomical concepts—specifically stellar magnitude and color—through tactile and auditory stimuli. Unlike traditional methods, our approach focuses on the haptic-cognitive link, allowing users to "feel" data through physical relief models. We present a structured impact study involving a heterogeneous group of blind, low-vision, and sighted participants.The methodology followed a mixed-methods approach, including a participatory workshop with 20 individuals and a detailed usability assessment with a core group (N=6) of participants. Preliminary results from this pilot phase demonstrate that the multimodal integration effectively reduces the perceived mental effort for complex spatial data comprehension. Quantitative and qualitative feedback suggests that tactile-auditory sensory substitution not only improves accessibility but also enhances engagement and information retention across all user groups. These findings highlight the potential of multimodal models in transforming public scientific environments, such as museums and observatories, into inclusive, interactive spaces.

Abstract: This paper addresses the challenges of evidence dispersion, attention shift, and inference inconsistency in long text and multi-document reasoning scenarios. It investigates the problems that large language models often encounter under conditions of extremely long contexts, multi-source information conflict, and structural complexity, and proposes a hierarchical, curriculum-based fine-tuning algorithm framework. This framework organizes the input into a hierarchical structure of questions and multi-document contexts. At the representation level, it constructs a three-level convergence path of tokens, fragments, and documents to form structured memory and mitigate semantic drift caused by context expansion. At the reasoning level, it introduces a question-guided evidence scoring and weight aggregation mechanism to achieve differentiable selection across document fragments and global evidence vector construction, thereby strengthening the alignment of key evidence and suppressing redundant interference. At the training organization level, it employs a curriculum strategy, progressively scheduling samples according to difficulty levels, enabling the model's capabilities to gradually transition from local consistency to cross-document evidence integration and overall induction. Comparative experimental results show that this method exhibits more stable performance in multi-document evidence localization and inference consistency evaluation, validating the effectiveness of hierarchical modeling and curriculum scheduling in shaping multi-document reasoning capabilities.

Abstract: Artificial intelligence (AI) has rapidly advanced as a key analytical tool for processing complex datasets across disciplines, including environmental and health research. Meteorological data is increasingly used to understand and mitigate health risks, often linked to climate change. This rapid review aims to synthesise studies involving AI for meteorological data applications in health research to better understand its use. PubMed, Web of Science, and Scopus were systematically searched from 2020 to 2025 following a standardised framework in line with PRISMA-RR guidelines. Eligible studies included any empirical design involving human-related health research where AI techniques were applied to meteorological data. Two reviewers independently screened studies, extracted data, and synthesised findings narratively. Twelve studies met eligibility criteria. Despite heterogeneity in study design and sample size, most examined the impact of extreme pollution levels and temperature variations on the prevalence and severity of respiratory, bacterial, and other diseases. AI methods primarily included Random Forest models, as well as time-series and clustering analyses. Model performance was commonly evaluated using sensitivity; however, methodological justification was often insufficiently recorded. Overall, findings suggest that incorporating meteorological variables enhances the prediction of health outcomes, although detailed population characteristics were frequently underreported. This restricts the generalisability and applicability of AI-driven health models incorporating meteorological data, with stronger methodological rigour and clearer reporting standards needed to support reliable future development.

Abstract: Healthcare communication during crisis moments imposes profound responsibilities on providers, extending beyond clinical disclosure to encompass the psychosocial and ethical dimensions of patient interaction. The statement, "Go to Court if Not Satisfied," commonly deployed in institutional responses to adverse medical outcomes, raises serious ethical concerns that transcend mere legal defensibility. This paper argues that such language violates core bioethical principles of beneficence, nonmaleficence, and patient autonomy, while simultaneously reflecting a broader culture of defensive medicine that undermines therapeutic relationships. Drawing on the case of missing twins at the 37 Military Hospital in Ghana, we critically interrogate the ethical dimensions of adversarial language in bad-news delivery, foregrounding its psychological harm to already-vulnerable patients and relatives. Beyond existing critique, this paper offers a novel analytical framework: positioning the "Go to Court" discourse as an institutional manifestation of power asymmetry and defensive communication culture, antithetical to the values of patient-centred care. We propose that open disclosure frameworks, therapeutic alliance theory, and the patient-is-always-right principle together offer a more ethically robust alternative. The paper calls on healthcare institutions to move from legally motivated damage-limitation communication toward accountability-driven, empathic engagement.

Abstract: This review explores the modulation of the host cellular flexibility “kinome" (protein kinases) and "phosphatome" (protein phosphatases) by dietary nutrients and gut microbiota metabolites, proposing a potential paradigm in the strategies for healthy aging and metabolic disease prevention. While mainstream nutrition approaches focus on population-wide guidelines, precision nutrition exploits the innovations in personal molecular networks and systems medicine, integrating genomics and metabolomics to address "metabolic rigidity"—the cell inability to switch between fuel sources. The review examines how master molecular regulators like AMPK and mTOR, and "metabolic brakes" like PTP1B and PTEN, are affected by single nucleotide polymorphisms (SNPs) and microbial signals (SCFAs, secondary bile acids, indoles). Specifically, the "microbial kinomic interference" hypothesis is discussed, where gut metabolites act as remote ligands for host signaling enzymes. Finally, the potential role of a personalized phosphoproteomics strategy is highlighted as an effective functional readout to guide nutritional interventions, aiming to restore metabolic plasticity through a gut microbiota/multi-omics approach.

Abstract: In the introduction, a brief history of the body selection that would define the inertial frame of reference in mechanics (and electrodynamics) is given. At the same time, attention has been drawn to Einstein's opinion about the (unrealized) causal relationship which should exist between the frame of reference and the law that is formulated from it. Therefore, parts 2 to 5 gradually present and elaborate the idea that, instead of directly choosing a body of reference, the criterion which will give legitimacy to the selection result should be defined first. And the criterion is such that the reference body is ensured by causality just mentioned by Einstein. Such a criterion for the fields of mechanics and thermodynamics is defined here and called the "criterion of observer's non-involvement in the observed” by a reference body. In the conclusion, as the main result, significant changes in the formulations of mechanics and thermodynamics, which the application of the criterion leads to, are stated. In those improved formulations the contents related to the observer are separated from the contents related to laws of nature.

Abstract: In this study we show that on the basis of simple crystallographic rules applied to the sphere-in-contact model/theorem that we can predict that under ambient conditions of pressure and temperature that the most dense and stable form of lithium in GICs is LiC6 and that two distinct form of LiC8 are possible. We find that other empirical formulas such as MC2, MC3 and M3C8 are possible based on crystallography, but not stable based on intercalate repulsions. The results are based on the unit cell description of GICs with the sphere-in-contact model/theorem that is used to model the intercalation of an arbitrary atom within the AαAα stacking1 of two graphene layers in GICs. We calculate the density and the packing fraction of these materials. This approach offers a simple description of the structure of GICs in which the unit cell can be defined and the diffusion of ions can be estimated on the basis of the void space in these materials. We anticipate that this simple description of GIC will be useful for the rational design of new graphite-based materials that can find use in various energy storage applications such as ion-based batteries but also as an educational tool in which university level education in materials and surface chemistry is directly connected to basic laws in chemistry, physics and mathematics.

Abstract: The automation of Integrated Circuit (IC) physical layout optimization remains a critical challenge, primarily due to the complex interplay between electrical and physical constraints. We propose ChipForm, a framework that reframes this task as a constraint-driven, reinforcement learning-guided graph optimization problem. Unlike perception-based approaches, ChipForm directly processes circuit netlists using a Hierarchical Graph Encoder (HGE) to extract features and predict timing, power, and density constraints. Subsequently, a Reinforcement Learning Placement Agent (RLPA) performs sequential cell placement, optimizing for minimal wirelength while explicitly satisfying these predicted constraints. A key contribution is a unified, end-to-end training strategy that jointly optimizes constraint prediction and placement policy. Extensive experiments on the CircuitNet benchmark demonstrate state-of-the-art performance: ChipForm achieves an 85.2% physical executability rate (DRC/LVS pass) and reduces constraint prediction errors (e.g., 0.11 OOD timing criticality error) compared to prior methods. Ablation studies confirm the necessity of each component, showing that explicit constraint prediction heads improve OOD generalization by 5.7% in executability, and the RL agent outperforms a greedy baseline by 3.9%. ChipForm thus provides a robust, data-driven approach for generating high-quality, manufacturable chip layouts directly from netlist specifications.

Abstract: A decade has elapsed since the first recognized cluster of congenital anomalies associated with Zika virus (ZIKV) was reported in Brazil in 2015, culminating in the formal delineation of Congenital Zika Syndrome (CZS) as a specific pattern of birth defects. This narrative review examines the ten-year trajectory of CZS as a tropical infectious disease, from its initial emergence and public health emergency declaration by the World Health Organization (WHO) in February 2016, through evolving epidemiological, clinical, and scientific understanding. CZS is characterized by a spectrum of severe neurological manifestations—including microcephaly, subcortical calcifications, malformations of cortical development, ventriculomegaly, and corpus callosum abnormalities—alongside ophthalmic, auditory, and musculoskeletal complications. Transmitted primarily by Aedes aegypti mosquitoes in tropical and subtropical regions, ZIKV disproportionately affects low- and middle-income countries in Latin America, Africa, and Southeast Asia, underscoring its nature as a quintessential tropical disease linked to poverty, inadequate vector control, and health inequity. Over ten years, substantial advances have been made in understanding ZIKV pathogenesis, neurodevelopmental outcomes, diagnostic criteria, and multidisciplinary clinical management of affected children. In the therapeutic and preventive domain, over 45 vaccine candidates have been identified, with 16 reaching Phase 1 or 2 clinical trials by late 2025, though no licensed vaccine or specific antiviral therapy yet exists. This review contextualizes CZS within the broader framework of neglected tropical diseases, evaluates its global and family-level burden, and critically appraises progress and remaining gaps in clinical care, vaccination, and vector control over the past ten years.

Abstract: We develop a quantitative framework in which black holes function as erasure channels for exterior classical records at the horizon-side Landauer bound. At asymptotic infinity, greybody scattering turns the full radiation channel into a dissipative filter whose entropy efficiency η_∞ ≡ |dS_BH|/dS_rad is field-content dependent; for the spin-2 (graviton) channel in Schwarzschild evaporation, η_∞ ≈ 0.74 (Page 2005). Starting from the Cortês–Liddle result that Hawking evaporation saturates the Landauer principle, we make three contributions. First, we define a Landauer saturation ratio R_L as a bookkeeping diagnostic for horizon thermodynamics: Schwarzschild black holes yield R_L = 1 exactly, while the cosmological apparent horizon yields R_L = 1/2 in Trivedi's quasi-local energy accounting. Second, we show that within the standard Bekenstein–Hawking area law and the discrete transition model of Bagchi, Ghosh, and Sen, one-step Landauer-saturating area transitions select the Bekenstein–Mukhanov spacing ΔA = 4 ln 2 l_P², this discrete compatibility result complements, rather than derives, the continuous holographic scaling S ∝ M². Third, we argue that the black hole scrambling time t_* ~ (ℏ/2πk_BT_H) ln(S_BH/k_B) provides a partial gravitational analogue of the reversibility time τ_c in quantum measurement: for an old black hole it sets the delay after which newly injected information can begin to reappear in Hawking radiation. We formalize the horizon as an effective coarse-grained erasure channel within fixed-charge sectors via a semiclassical proposition that combines a strict exterior coarse-graining definition with GSL-compatible entropy bookkeeping and horizon-side first-law accounting. We check the supporting identities numerically across the Schwarzschild, Kerr, and Reissner–Nordström parameter spaces, and analyze robustness to the memory burden effect. The framework positions black holes as the thermodynamic complement to quantum measurement: measurement creates classical records by paying Landauer costs; horizons erase exterior access to those records at the quasi-static Landauer limit, while the asymptotic Hawking channel is greybody-dissipative.

Abstract: In this study, we compared the effects of microwave-assisted extraction (MAE) and ultrasound-assisted extraction (UAE) on the total phenolic content, antioxidant activity, morphological characteristics, and identification of the bioactive compounds in pomegranate seeds. We conducted a phytochemical characterization of the extracts by determining the total phenolic content and total flavonoids. Antioxidant activity was evaluated using ferric reducing antioxidant power (FRAP) and free radical inhibition methods (DPPH and ABTS). Morphological characteristics were analyzed via scanning electron microscopy, UV-Vis and FTIR of the extracts were recorded. Additionally, the main bioactive compounds were identified using HPLC-MS. Our results demonstrated that MAE was the most efficient technique, yielding a higher content of total phenols (35.47 mg GAE/g), total flavonoids (14.44 mg CAE/g) and antioxidant activity (0.19 and 0.41 mmol TEAC/g, as determined by FRAP and ABTS, respectively). In terms of morphological characteristics, UAE induced more changes in the structure of the plant material compared to MAE. According to HPLC-MS analysis, the extract obtained using MAE notably contained coumaric acid, cyanidin, and quercetin, whereas the UAE extract included coumaric acid, cyanidin, kaempferol, and epicatechin. In conclusion, this study demonstrated that MAE is a more efficient method than UAE for extracting bioactive compounds. Pomegranate seeds may represent a potential source of these compounds for application in various industrial areas.

Abstract: The retail fuel sector in urban areas presents significant environmental risks, requiring systematic sustainability assessments. This study aims to highlight the socio-environmental performance of fuel stations in Mossoró/RN using the Corporate Sustainability Index (ISE). It is a descriptive and exploratory study with a quantitative approach, based on questionnaires administered to managers of 12 licensed fuel stations. The ISE was calculated using 17 equally weighted environmental, legal, social, and operational indicators. The results indicated a predominance of high sustainable performance, with 91.7% of enterprises presenting an ISE above 75%, associated with operational organization, preventive practices, and compliance with legal requirements. However, some actions remain primarily tied to regulatory compliance, revealing a predominantly reactive environmental management profile. The study provides insights for enhancing strategic environmental management in the urban context of the Brazilian Semi-Arid region.

Abstract:

Mitochondrial dysfunctions are believed to contribute to the pathogenesis of tauopathies, a group of neurodegenerative diseases with abnormal accumulation of microtubule-associated protein tau. The combination of 5-aminolevulinic acid (5-ALA) and sodium ferrous citrate (SFC) is known to improve mitochondrial functions. Here, we report that 5-ALA combined with SFC (5-ALA/SFC) improves mitochondrial functions and mitigates neurodegeneration in transgenic Drosophila expressing human tau. We found that tau reduces ATP levels, decreases mitochondrial distribution to neurites, and increases mitochondrial reactive oxygen species (ROS). Expression of oxidative phosphorylation (OXPHOS) genes was upregulated and activities of complexes I and IV were elevated. Feeding 5-ALA/SFC to tau flies lowers oxidative damages without correcting OXPHOS activities or mitochondrial distribution. 5-ALA/SFC treatment suppressed pathological tau phosphorylation and mitigated tau-induced neurodegeneration. Our results suggest that 5-ALA/SFC decreases a neurodegenerative pathway involving tau, mitochondria, and ROS.

Abstract:

Background: Parkinson’s disease (PD) is clinically heterogeneous, yet the genetic architecture underlying this heterogeneity remains incompletely understood. We examined the genetic correlates of four complementary PD subtyping frameworks: clinical motor subtype (tremor-dominant [TD] vs. postural instability/gait difficulty [PIGD]), alpha-synuclein seed amplification assay status (SAA+ vs. SAA−), pathological subtype (brain-first vs. body-first, based on REM sleep behavior disorder), and data-driven subtype (diffuse malignant [DM] vs. mild-motor predominant [MMP] vs. intermediate [IM]). Methods: We analyzed 1,597 PD patients from the Parkinson’s Progression Markers Initiative (PPMI) with genetic testing for seven PD-associated genes (LRRK2, GBA, SNCA, PRKN, PINK1, PARK7, VPS35), including specific variant resolution (LRRK2 G2019S, R1441G/C/H; GBA N409S, severe variants; SNCA A53T), and APOE genotyping (ε2/ε3/ε4 alleles). Genetic variant frequencies were compared across subtypes using chi-square or Fisher’s exact tests with Benjamini–Hochberg false discovery rate (FDR) correction. Effect sizes were quantified using Cramér’s V. Multivariable logistic regression (statsmodels) estimated adjusted odds ratios with Wald-based 95% confidence intervals. Results: Among 1,390 genotyped PD patients, LRRK2 carriers constituted 13.7% (190/1,390; 170 G2019S, 18 R1441G/C/H), GBA 8.6% (119/1,390; 96 N409S, 23 severe), and SNCA 2.0% (28/1,390; all A53T). APOE ε4 carriers comprised 23.4% (323/1,380). SAA-negative patients were markedly enriched for LRRK2 variants (37.1% vs. 10.2%, P = 3.7 × 10⁻¹⁹, q < 0.001, V = 0.25), driven by G2019S (28.5% vs. 9.6%, P = 4.9 × 10⁻¹¹, q < 0.001) and R1441G/C/H (7.9% vs. 0.5%, P = 2.7 × 10⁻¹², q < 0.001). Body-first PD was enriched for GBA carriers (12.3% vs. 6.7%, P = 0.004, q = 0.021) and depleted for LRRK2 (7.9% vs. 15.0%, P = 0.002, q = 0.013). The DM subtype carried the highest GBA frequency (14.0% vs. MMP 5.9%, P < 0.001, q = 0.003). After FDR correction, 10 of 48 univariate tests remained significant. Clinical subtypes (TD vs. PIGD) showed only nominal LRRK2 differences that did not survive FDR correction. APOE genotype did not differ across any framework. Conclusions: PD subtypes defined by alpha-synuclein pathology (SAA), pathological onset pattern (brain-first/body-first), and data-driven classification (DM/MMP/IM) show distinct genetic profiles that survive multiple comparison correction. LRRK2 variants strongly associate with SAA-negativity (V = 0.25); GBA variants associate with the severe body-first onset and the diffuse malignant subtype.