Abstract: Background/Objectives: Pleural mesothelioma (PM) frequently recurs despite multimodal therapy. Here, we aimed to retrospectively evaluate the safety and potential clinical benefit of radiofrequency ablation (RFA) for recurrent PM. Methods: Fourteen consecutive patients underwent CT-guided RFA between July 2019 and June 2025. The cohort comprised 13 men and 1 woman, with a median age of 69 (range, 54–77) years. All patients had previously received systemic therapy and 12 had undergone surgery. Seven patients (50%) presented with multiple lesions, and 25 tumors (median diameter 1.8 cm; range, 0.5–7.0 cm) were treated in 23 sessions. Outcomes assessed were local tumor control, complications, and survival. Local progression and overall survival were estimated using Kaplan–Meier analysis. Adverse events were classified according to the Society of Interventional Radiology guidelines. Results: Technical success was achieved in all sessions. Two tumors showed local recurrence, corresponding to 1- and 2-year local progression rates of 10.6%. Seven patients showed distant metastases, most of whom subsequently received systemic therapy. Three patients died, two from disease progression and one from treatment-related gastrointestinal perforation during therapy for an unrelated cancer. The overall survival rates were 100%, 100%, and 60% at 1, 3, and 5 years, respectively. Major and minor complications occurred in one case each (4.3%): a refractory skin ulcer and retroperitoneal hematoma, respectively. Conclusions: RFA was technically feasible and generally well tolerated, and helped achieve encouraging local control and survival in patients with recurrent PM, warranting further evaluation of RFA as a complementary approach in multimodal treatment strategies.

Abstract: The microbiota–gut–brain axis (GBA) is a bidirectional communication system integrating neural, endocrine, immune, and metabolic pathways to coordinate gastrointestinal and central nervous system (CNS) function. As the majority of human microbes reside in the gastrointestinal tract, their metabolic activity and immunomodulatory roles are essential for systemic homeostasis, cognitive processes, mood regulation, and neuroprotection. Increasing evidence highlights the vagus nerve as a primary conduit of microbiota–brain signaling, with germ-free mice demonstrating reduced vagal tone that is restored following microbial colonization. Key microbial metabolites—including short-chain fatty acids (SCFAs), bile acids, indoles, and neurotransmitter precursors—activate vagal afferents, regulate neuroimmune responses, and influence microglial maturation and synaptic function. Disruption of microbial community structure, or dysbiosis, is now recognized as a contributing factor in numerous neurological and psychiatric disorders. Neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) exhibit distinct microbial alterations, chronic neuroinflammation, and impaired gut and blood–brain barrier integrity. PD patients, for example, consistently show increased Enterobacteriaceae and reduced Prevotellaceae. Dysbiosis also contributes to mood disorders by disrupting microbial production of GABA, serotonin, and tryptophan metabolites. Although microbial biomarkers vary across studies due to disease heterogeneity, integrative multi-omics approaches have begun identifying shared metabolic patterns and therapeutic targets. Microbiota-derived metabolites such as butyrate show neuroprotective and anti-inflammatory effects, while fecal microbiota transplantation (FMT), prebiotics, probiotics, and next-generation probiotics (NGPs) are emerging as promising modulators of the GBA. Advances in metagenomics, metabolomics, and machine-learning–based patient profiling further support the development of personalized, microbiome-driven interventions for neurological disorders.

Abstract:

This study conducts a multi-dimensional evaluation of Energy Performance Contracts (EPCs) applied to solar photovoltaic (PV) systems in public institutions, emphasizing their technical efficiency, governance structure, and policy accountability. Within the broader context of solar resource utilization and sustainable energy transition, EPCs are increasingly recognized as strategic mechanisms to enhance energy efficiency and reduce emissions without imposing immediate fiscal burdens on public budgets. Using a mixed-methods approach, the research integrates quantitative assessments of photovoltaic system performance—based on SCADA-verified production data and CO₂ mitigation outcomes—with qualitative evaluations of contract design, stakeholder coordination, and institutional transparency. The case of a 1710.72 kWp university-based PV installation in Türkiye demonstrates that EPCs can effectively deliver high operational reliability (performance ratio: 83%) and substantial environmental benefits (1168.64 tons of CO₂ avoided annually). However, the study also reveals that EPC success is critically shaped by the coherence of regulatory frameworks, administrative capacity, and accountability mechanisms. Institutional fragmentation, limited data integration, and insufficient governance oversight remain significant barriers to scaling EPC adoption in the public sector. The research concludes by proposing an integrated policy framework that aligns technical performance monitoring with transparent governance and policy coherence. This approach supports real-time performance tracking, multi-level coordination, and enhanced institutional accountability—key enablers for accelerating the solar energy transition through scalable and financially sustainable EPC models in public infrastructure.

Abstract: We present a joint multifractal and phase-coherence analysis of the WMAP 9-year W-band CMB temperature anisotropy map, using a framework based on the τ(q) multifractal spectrum and the phase-coherence envelope Rℓ. A suite of Gaussian Monte Carlo simulations matched to the empirical Cℓ distribution provides percentile confidence intervals for both statistics. The observed WMAP data exhibit significant deviations from Gaussian expectations at three scales: (i) a low-ℓ phase-coherence excess (ℓ ≲ 40), (ii) a structured acoustic-peak-scale coherence depression and recovery (100 ≲ ℓ ≲ 400), and (iii) a sustained high-ℓ excess (ℓ ≳ 600). These features correlate with departures in the τ(q) multifractal spectrum, particularly for q > 0, where the observed τ(q) lies persistently above the Monte Carlo median envelope. The combined statistical evidence suggests that the WMAP temperature field contains non-Gaussian structure that cannot be reproduced by phase-randomized or Gaussian ΛCDM surrogates with identical angular power spectra. The results demonstrate the sensitivity of multifractal and phase-coherence diagnostics to subtle higher-order correlations and motivate re-examination of the assumptions underlying Gaussian initial conditions and mode independence.

Abstract: Financial fraud represents a growing challenge for financial institutions and e-commerce, requiring increasingly sophisticated detection methods. Traditional machine learning models, while effective, can reach limitations when facing complex fraud patterns and highly imbalanced datasets. This paper proposes a novel ensemble approach, KAN-XGBoost, which combines the power of Kolmogorov-Arnold Networks (KAN) for learning complex relationships with the robustness of the Extreme Gradient Boosting (XGBoost) algorithm for high-performance classification. Using the synthetic PaySim dataset, we demonstrate the effectiveness of our approach. To address the severe class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied to the training data. Our experimental results show that the KAN-XGBoost ensemble model, in soft voting configuration, significantly outperforms the individual models, achieving a performance metrics of 99%. This high performance suggests that the hybridization of KANs with established boosting algorithms constitutes a promising avenue for enhancing the security of financial transactions.

Abstract: Detecting anomalous events in high-dimensional behavioral data is a fundamental challenge in modern cybersecurity, particularly in scenarios involving stealthy advanced persistent threats (APTs). Traditional anomaly-detection techniques rely on heuristic notions of distance or density, yet rarely offer a mathematically coherent description of how sparse events can be formally separated from the dominant behavioral structure. This study introduces a density-metric manifold framework that unifies geometric, topological, and density-based perspectives into a single analytical model. Behavioral events are embedded in a five-dimensional manifold equipped with a Euclidean metric and a neighborhood-based density operator. Anomalies are formally defined as points whose local density falls below a fixed threshold, and we prove that such points occupy geometrically separable regions of the manifold. The theoretical foundations are supported by experiments conducted on openly available cybersecurity datasets, including ADFA-LD and UNSW-NB15, where we demonstrate that low-density behavioral patterns correspond to structurally rare attack configurations. The proposed framework provides a mathematically rigorous explanation for why APT-like behaviors naturally emerge as sparse, isolated regions in high-dimensional space. These results offer a principled basis for high-dimensional anomaly detection and open new directions for leveraging geometric learning in cybersecurity.

Abstract: This project aims to develop a basic predictive maintenance model for aviation sensors, especially the ones that are directly related to flight safety. The study first uses SCAPS-1D to simulate a simple semiconductor structure and observe how electrical parameters such as Voc and Jsc change with temperature and material conditions. After getting these results, a simple state-space model is built in MATLAB to represent the relation between temperature input and device output. The idea is that many aircraft sensors, like the Angle of Attack (AOA) sensor, also contain small pn junction electronics inside, and their failures often begin with small drifts in electrical behavior. By comparing the SCAPS results with the state-space model, the project shows how these changes can be used as early indicators of degradation. This work gives a starting framework for future predictive maintenance studies by connecting semiconductor modeling with aviation sensor health monitoring.

Abstract: In 2014, NASA measured that the universe has a Euclidean shape. This discovery suggests that the curvature of space is merely a mathematical description of some more basic physical property of space. By extending the principle of equality of mass and energy to the space occupied by dark energy, a model of gravity was developed, where the gravitational force is due to the variable energy density of dark energy. The more curved the space, the lower the energy density of dark energy. A black hole, like any other stellar object, reduces the energy density of dark energy at its center in proportion to its mass and energy. In the centre of a black hole, the gravitational force is zero, as it is in all stellar objects. There are no wormholes in space, and there is no gravitational singularity at the center of a black hole. Gravity inside black holes follows Newton's physics. Reduced energy density of dark energy inside black holes diminishes the value of the Planck constant, which causes atoms and nuclei to decay. Gravitational collapse is replaced by electric collapse.

Abstract: A familiar intuition holds that determinism creates an epistemically adverse context. This paper gives that intuition a formal shape by developing a new epistemic transcendental argument (ETA) grounded in the notion of epistemic risk. First, we formalise epistemic risk through a metric space W equipped with two metrics, D and N, corresponding to distinct theories of risk. Drawing on the notions of modal closeness and normalcy, we argue that these metrics better capture our intuitions about risk than traditional similarity-based accounts. Building on these insights, we articulate an argument based on five axioms. The axioms are philosophically motivated using the two metrics, their independence is verified in Mace4, and the derivation of the denial of determinism is formally carried out in Lean 4.

Abstract: Explainable artificial intelligence (XAI) plays a central role in strengthening security, privacy, and trust in AI-driven 5G and future 6G networks. In this review, we first re-fine the concepts of transparency and interpretability, and introduce the notions of marginal transparency and marginal interpretability to describe the diminishing re-turns that arise from progressively deeper disclosure of model internals. We then survey key XAI methods, including LIME, SHAP, interpretable neural networks, and federated, privacy-preserving techniques, and assess their suitability for wireless re-source management, intrusion detection, and regulatory auditing in next-generation networks. Building on these foundations, we outline a 2025–2030 research roadmap that integrates XAI into Zero Trust architectures, edge intelligence, and self-explaining 6G systems. Across these layers, we argue that explainability should be built in as a design-time requirement, enabling wireless infrastructures that are not only high performance but also auditable, accountable, and resilient.

Abstract: Advanced Air Mobility (AAM), having drones (aerial robots) as a core, is becoming an integral additional part of Disaster Management (DM) systems in metropolitan regions, and of future smart urban development and systems. Unmanned Aircraft Systems (UAS) are able to transport efficiently high added value goods and to provide efficient monitoring during the disaster events and their development. This paper provides a foresight on the overall System of Systems (SoS) needed including the UAS application in the studied use cases, as well as the crucial integration of relevant advanced communication systems (ACS), for the safe and sustainable UAS operation. In the evolving AAM, ACS is a crucial enabler and core element of a functioning SoS -- for the purposes of UAS navigation and operations safety, DM data collection and processing. The emphasised SoS enables emergency goods deliveries and the complete and efficient deployment and operation of an entire DM system (meant for monitoring, search and rescue, and decision making support), where UASs are used as logistic tools, and simultaneously for the monitoring of the environment and the disaster events in the affected regions. AAM is being operated mainly in the third dimension (airspace), which enables us to be minimally dependent on any types of ground transport infrastructure. Due to this, its precise navigation and management as well as relevant data streams transfer are crucial for the operational efficiency and safety. This foresight study provides a comprehensive, SUDEM (EU), REGUAS (DE), 5G!Drones (EU), and ETHER (EU) projects' lessons learnt-based path for understanding and efficiently deploying the SUDEM SoS including AAM and ACS for the purpose of the described 2 combined use cases: (i) high-added value goods transport and (ii) live monitoring, and the necessary educational model.

Abstract: Comorbid bipolar I disorder, obsessive–compulsive disorder and attention-deficit/​hyperactivity disorder form a notoriously unstable clinical constellation. Conventional stimulants risk precipitating mania, whereas high-dose antidepressants seldom quell the mood-linked obsessions and may themselves cause switching. We detail the course of a 31-year-old man who illustrated these pitfalls. After methylphenidate produced early hypomanic signs—fragmented sleep, increased impulsive spending and heightened drive—his treatment was redirected toward a fully oral glutamatergic strategy. The regimen combined dextromethorphan for NMDA antagonism, pharmacokinetically extended by the mild, reversible CYP2D6 inhibition provided by melitracen within Deanxit, with piracetam to potentiate AMPA signalling and L-glutamine to support presynaptic glutamate balance. All adjustments were made in routine outpatient follow-up. Across three months the patient showed steady gains: depressive affect lifted, intrusive ruminations quieted and impulse control improved, while the need for methylphenidate fell from daily dosing to occasional use without loss of attentional capacity. When he later stopped dextromethorphan and piracetam on his own initiative—yet continued valproate and antipsychotic cover—both low mood and obsessive thinking re-emerged, then abated rapidly once the glutamatergic agents were reinstated. This single case suggests that a multi-target oral glutamatergic approach can stabilise mood, reduce obsessions and preserve attention in a comorbidity cluster where traditional pharmacotherapy frequently destabilises the illness. Further systematic study is warranted to confirm the safety and durability of NMDA/AMPA modulation as a non-stimulant alternative in complex bipolar-spectrum presentations.

Abstract: Prolonged +Gz acceleration during high-performance flight exposes pilots to the risk of G-induced loss of consciousness (G-LOC), a dangerous condition that compromises operational safety. To enable early detection without intrusive sensors, we present a vision-based warning system that analyzes facial action units (AUs) as physiological indicators of impending G-LOC. Our approach combines computer vision with physiological modeling to capture subtle facial microexpressions associated with cerebral hypoxia using widely available RGB cameras. We propose a novel Graph Convolution-Augmented Vision Transformer (GC-ViT) network architecture that effectively captures dynamic AU variations in pilots under G-LOC conditions by integrating global context modeling with vision Transformer. The proposed framework integrates a vision-semantics collaborative Transformer for robust AU feature extraction, where EfficientNet-based spatiotemporal modeling is enhanced by Transformer attention mechanisms to maintain recognition accuracy under high-G stress. Building upon this, we develop a graph-based physiological model that dynamically tracks interactions between critical AUs during G-LOC progression. By learning the characteristic patterns of AU co-activation during centrifugal training. Experimental validation on centrifuge training datasets demonstrates strong performance, achieving an AUC-ROC of 0.898 and an AP score of 0.96, confirming the system’s ability to reliably identify characteristic patterns of AU co-activation during G-LOC events. Overall,this contact-free system offers an interpretable solution for rapid G-LOC detection, or as a complementary enhancement to existing aeromedical monitoring technologies. The non-invasive design demonstrates significant potential for improving safety in aerospace physiology applications without requiring modifications to current cockpit or centrifuge setups.

Abstract: Background: Erectile dysfunction (ED) affects approximately 52% of men aged 40–70 years in population-based cohorts and is strongly associated with vascular and metabolic disease, particularly diabetes mellitus.[1] In Saudi Arabia, diabetes prevalence in adults is estimated at over 20%, magnifying the burden of vasculogenic ED.[2] Phosphodiesterase-5 inhibitors (PDE5i) improve erectile function but have limitations in patients with endothelial dysfunction, neurogenic compromise, or contraindications to nitrates.[3]Hypothesis: Helospectins I and II are 37–38–amino-acid peptides isolated from Heloderma (Gila monster and Mexican beaded lizard) venom that belong to the glucagon/VIP superfamily and exhibit potent vasodilatory, smooth muscle–relaxant, and hypotensive effects.[4,5] Building on the successful translation of the venom peptide exendin-4 into the antidiabetic drug exenatide,[6,7] we hypothesize that synthetic helospectin analogues could serve as selective agonists at VPAC1/VPAC2 receptors in genital vascular smooth muscle, promoting corpus cavernosum and clitoral vasodilation independent of endothelial nitric oxide (NO), and thereby treating ED and clitoral engorgement (female sexual arousal disorder, FSAD).[8–10]Methods (theoretical proposal): We outline (i) a biochemical and physiological rationale based on helospectin/VIP homology, distribution of VIP-family peptides in male and female genital tissues, and venom-derived pharmacology; (ii) a conceptual mechanism of action centred on cAMP/PKA-mediated relaxation of cavernosal and clitoral smooth muscle; and (iii) a Phase I/IIa randomized, double-blind, placebo-controlled crossover trial of intranasal synthetic helospectin in men with ED and women with FSAD.Expected outcomes: We anticipate that helospectin analogues could augment genital blood flow and erection/engorgement responses in a manner that is at least partly independent of endothelial NO, potentially benefiting patients with diabetic and neurogenic ED. Safety concerns include systemic hypotension, off-target vasodilation, and theoretical effects on exocrine pancreas and gut. This preprint is offered as a hypothesis-generating framework to encourage collaborative medicinal chemistry and preclinical work, not as evidence for clinical use

Abstract: Ovarian aging (OA) results from senescence of different cell types present in the ovary, decreases female fertility and quality of life and augments the risk of a variety of fertility-unrelated pathological conditions. The changes observed in the ovarian cells are accompanied by those oc-curring in various elements of the hypothalamic-pituitary-ovarian (HPO) axis, the complex endo-crine system that regulates the female reproductive cycle. Issues of the HPO axis were addressed in animal models by hormonal treatments with preparations inhibiting ovarian follicular recruitment at the level of receptors of gonadotropin-releasing hormone (GnRH)-secreting neurons, mainly acting on glutamate- and gamma-aminobutyric acid (GABA)-driven signalling. GnRH agonists and antagonists were also used in women exposed to chemotherapeutics. HPO-independent OA can be delayed by the administration of different antioxidants and mitochondria-protecting agents, among which melatonin was shown to be particularly useful. Other therapeutic approaches used with success in women include hormonal and growth factor (GF) modulators, such as growth hormone (GH), insulin-like growth factor 1 (IGF-1), vascular endothelial growth factors (VEGF) and dehydroepiandrosterone (DHEA), and the development of patient-tailored combination-based therapies (IGF-1 + VEGF + DHEA) was suggested. Intraovarian injection of autologous platelet-rich plasma (PRP), mitochondrial donation through pronuclear transfer, and ovarian tissue cryopre-servation and autotransplantation also gave promising results in women, and their use can protect not only fertility but also the ovarian endocrine function. Personalized mixtures of specific agents (desatinib, quercetin, rapamycin, metformin, resveratrol, melatonin, and coenzyme Q10) targeting different cell types of the ovary are currently under investigation.

Abstract:

Very prevalent respiratory and cardiovascular diseases result in chronic hypoxia, promoting metabolic, kidney, heart, and other malignant diseases. Hypoxia research employs animal models based on chronically breathing hypoxic air (O₂<21%), usually by injecting N₂ into the animal’s chamber. However, continuous high-flow N₂ supply is available only in limited facilities, reducing the capability of widely conducting hypoxia research. Here, we describe an optimized setting for subjecting rodents to chronic normobaric hypoxia by requiring minimal N₂ supply. The setting is based on providing the O₂ consumed by the animals and eliminating the exhaled CO₂ and water vapor. O₂, CO₂, temperature, and humidity in the hypoxic chamber are controlled by an Arduino-based unit activating a pump that introduces room air to restore the metabolized O₂. Another pump continuously recirculates the chamber air through a Peltier-based dryer and CO₂-absorbing soda lime. To correct any deviation in the actual value of hypoxia within the chamber, the control unit allows the injection of N₂ into the chamber from a gas source. The setting performance was successfully tested in vivo when subjecting mice to 11%-O₂ chronic hypoxia. This device, requiring a low N₂ supply, may facilitate in vivo experimental research of hypoxiarelated diseases.

Abstract:

Background: Aging brains are shaped by a persistent dialogue between declining neurogenesis and rising neuroinflammation. Neural stem cells progressively lose regenerative capacity, while microglia and astrocytes shift toward maladaptive states that erode synaptic plasticity and cognition. This convergence defines inflammaging, a slow yet relentless process that undermines resilience. However, the field remains hampered by critical gaps: incomplete mapping of microglial heterogeneity, poorly understood epigenetic scars from inflammasome signaling, lack of longitudinal data, unclear niche-specific immune mechanisms, and uncertain cross-species relevance. This review addresses these pressing barriers, aiming to transform fragmented insights into actionable strategies. Summary: I chart how neurogenesis and neuroinflammation operate in continuous dialogue, identify five major knowledge gaps, and evaluate strategies to reprogram this interaction. Approaches include longitudinal imaging, niche-focused immunomodulation, glial subtype reprogramming, brain-penetrant inflammasome inhibitors, and CRISPR-based epigenetic editing. Each strategy is mapped against translational potential, short-term feasibility, and long-term vision, with emphasis on how mechanistic precision can guide clinical innovation. Conclusion: Here I highlight that neurogenic potential is not entirely lost with age but may be preserved or restored by tuning immune and epigenetic environments. This review proposes a roadmap for reshaping the aging brain’s fate, offering mechanistically grounded strategies to delay cognitive decline. Beyond neurology, the work underscores a broader principle: by integrating cellular plasticity with immune modulation, science edges closer to re-engineering resilience across the lifespan.

Abstract: The action principle, which had successfully guided physicists for centuries, now appears to be leading them into dead ends. The reason for this is conjectured to be its inability to properly represent scale covariant physics. As a result, absolute notions of large and small emerge, with the size of a human observer determining which is which. An alternative to the action principle is proposed, rectifying this relic of anthropocentric bias by postulating that physicists could exist at any scale, all on equal footing. The consistency between their descriptions of physical phenomena severely restricts the set of their possible observations. So much so that the set of well-behaved, scale-dependent and compatible fields, φ(x, λ), representing spacetime phenomena at any scale, λ, could replace the set of fields which are local extrema of an action, in its role as a “physical law". Observations deemed inexplicable or bizarre when analyzed at any given scale become inevitable when viewed as mere constant-scale ‘sections’, φ(x, λ = const), of such ‘scale-orbits’. Among them: Why particles rather than a continuum, and why must they not be represented by mathematical points? Why Einsteinian/Newtonian gravity seem to break down at small accelerations? What is the origin of quantum nonlocality? Quantitative agreement with observations is demonstrated in simple cases while in more complicated cases exact routs to testable predictions are shown.

Abstract: Older adults who live with severe obsessive–compulsive disorder (OCD) complicated by somatic anxiety rarely achieve meaningful relief on conventional serotonergic or antipsychotic regimens, and only a minority have access to intravenous ketamine, the best-validated rapid-acting glutamatergic option. We report the outpatient management of a 68-year-old man who had spent five years trapped in disabling health-related obsessions and reassurance-seeking rituals. Despite trials of mirtazapine, bupropion and several antipsychotics, his baseline burden remained high (PHQ-9 = 13).During routine follow-up, bedtime dextromethorphan 30 mg and piracetam 600 mg were added, with bupropion XL 150 mg retained to prolong dextromethorphan exposure through CYP2D6 inhibition. The patient supplied daily updates through encrypted messaging. By the fourth night he reported uninterrupted sleep, disappearance of morning restlessness and near-total quieting of intrusive health fears; residual daytime fatigue resolved after small downward adjustments of mirtazapine, risperidone and lemborexant. This experience shows that an easily deployed oral "ketamine-like" strategy—combining NMDA antagonism with AMPA potentiation—can bring about remission within days, even in a complex geriatric presentation that had resisted years of standard pharmacotherapy.

Abstract: This study examined the effects of laser shock peening (LSP) and LSP without protective coating (LSPwC) on the microstructure and corrosion behavior of 304L stainless steel using cyclic polarization testing. LSP enhanced corrosion resistance under mild sensitization (650°C; 5hrs) by inducing compressive stress and increasing dislocation density, stabilizing the passive film. Limited improvement was observed under severe sensitization (650°C; 24 hrs). Deformation-induced martensite detected by XRD was attributed to mechanical polishing, not LSP. In contrast, LSPwC reduced corrosion resistance across all conditions due to Fe-rich surface oxides that impaired passivation.