Abstract: A program package for calculating regularized classical trajectories for Coulomb n−body problem is developed. The Coulomb singularities from the equations of motion are removed by transformations of variables including the time. This effectively conserves the energy of the time-independent systems to a high accuracy for long time propagation. Sample calculations are shown for the cases of 2,3,4, and 5 particle systems giving comparisons with the un-regularized trajectories. The program can be used for general purposes including the classical-trajectory Monte-Carlo simulations for charged-particle collisions in free or laser environments.

Abstract: This research examines how companies incorporate sustainability into their core strategies to build lasting competitive advantages and improve long-term resilience. The study uses a detailed case analysis of International Business Machines Corporation (IBM) to illustrate that when environmental, social, and governance (ESG) priorities are central to business planning, sustainability shifts from being a regulatory expense to a major contributor to corporate value. Evidence from the analysis shows that an active, strategic posture leads to measurable advantages, such as lower operational expenses, income generated from environmentally-focused technologies and services, and more robust risk mitigation frameworks. Simultaneously, the investigation highlights continuing difficulties common across the sector, including the significant energy demands of artificial intelligence and data center infrastructure, alongside the logistical and reporting hurdles associated with indirect, Scope 3 emissions throughout worldwide supply networks. The final argument posits that for technology companies and the wider business community, a sustainability strategy woven deeply into corporate fabric is essential for securing operations against future disruptions and preserving a leading position in the market.

Abstract: Type -2 (T2) low asthma in children represents a clinically important yet still insufficiently recognized endotype. Current data suggest that it is more prevalent than previously thought and is defined by low type 2 biomarkers, non-allergic clinical profiles, and a high burden of comorbidities such as obesity and passive smoke exposure, while remaining largely understudied phenotype in terms of validated biomarkers and specific targeted therapies. This review aims to highlight and clarify T2-low asthma in children by summarizing emerging evidence on risk factors, pathophysiological mechanisms, bi-omarkers, and treatment strategies, with the goal of informing and improving future care for affected children.

Abstract: This paper presents a novel multi-faceted approach to the Riemann Hypothesis (RH) through the synthesis of quantum operator theory, conformal geometry, and spectral analysis. We construct a quantum helical system whose Hamiltonian spectrum, when transformed by a conformal map Phi(z) = alpha * arcsinh(beta * z) + gamma, shows remarkable numerical correspondence with the imaginary parts of non-trivial zeros of zeta(s) to precision 10^{-12} for the first 2000 zeros. We further develop an analytical framework consisting of six interconnected theorems that establish constraints on possible zero locations based on conformal symmetry and functional equation properties. While these results provide substantial evidence and new insights, we present them as a significant step toward rather than a final resolution of RH. The work opens new connections between spectral theory, quantum physics, and analytic number theory.

Abstract: Berries are an excellent source of bioactive compounds such as polyphenols and widely used in folklore medicine, particularly by Mapuches people in southern of Chile. The objective of this study was to conduct a phytochemical composition analysis of a hydroalcoholic extract of Berberis congestiflora Gay (BE) and to evaluate its potential as an antioxidant, the vasorelaxant effect as relaxation effects in rat aorta, plus the inhibitory enzyme potential in relation to chronic non-communicable diseases, including a possible underlying vasodilatory mechanism in isolated rat aorta. Antioxidant activities were assayed by oxygen radical absorbance capacity (ORAC), by scavenging DPPH (2,2-diphenyl-1-picrylhydrazyl), ABTS (2,2-azinobis-(3-ethylbenzothioazolin-6-sulfonic acid) radicals, and ferric reducing antioxidant power (FRAP). Vascular response of Berberis extract was studied by means of isometric tension recording experiments in ex vivo rat thoracic aortic rings model. Identification of the chemical compounds present in BE was determined by HPLC-DAD-MS for the first time. The BE caused, per se, a dose-dependent contraction at 100 and 1000 µg/mL, and relaxation of the aorta pre-contracted with phenylephrine at 100 and 1000 µg/ml, with maximum contraction of 71% and relaxation of 70% both at 1000 µg/mL. The extract induces calcium-mediated contraction, mainly by calcium release from the sarcoplasmic reticulum and, to a lesser extent, by extracellular Ca2+ influx. The relaxation mechanism was found to depend on the NO/cGMP pathway and the endothelium. The extract also demonstrated cholinesterase, glucosidase and amylase enzyme inhibitor capacities (IC50: 7.33 ± 0.32, 243.23 ± 0.3 and 27.21 ± 0.03 µg/mL, respectively). Docking calculations were additionally performed for a selection of compounds in the berries. These results demonstrate that berries are an excellent source of bioactive compounds with potential antioxidants and endothelium-dependent vasodilator effect, providing evidence for its traditional use and for the inhibition of enzymes, making it a promising candidate for the development of phytotherapeutic products, especially as a supplement against chronic diseases.

Abstract: Background: Food insecurity is a modifiable social determinant that may accelerate cognitive decline in later life. However, longitudinal evidence is complicated by time-varying confounding, and limited research has examined whether Supplemental Nutrition Assistance Program (SNAP) participation modifies domain-specific cogni-tive outcomes. Objectives: To evaluate the longitudinal associations between food in-security and cognitive function using marginal structural models (MSMs), and to as-sess whether SNAP participation buffers these associations for total cognition, episodic memory, and mental status. Methods: Data came from 30,641 adults aged ≥50 in the 1998–2020 Health and Retirement Study, contributing 156,066 person-year observa-tions. Food insecurity and SNAP participation were assessed biennially. Stabilized in-verse probability of treatment weights accounted for time-varying socioeconomic, health, and cognitive confounding. Weighted pooled linear regression MSMs estimated the marginal effects of food insecurity, SNAP, and their interaction. Analyses were stratified by race/ethnicity. Results: In MSMs, both moderate and high food insecurity were associated with lower overall cognition (moderate: b = -0.36; high: b = -0.71; p< 0.001). Similar graded associations were observed for episodic memory (moderate: b = -0.22; high: b = -0.43; p< 0.001) and mental status (moderate: b = -0.15; high: b = -0.28); p< 0.001). SNAP participation significantly attenuated these associations, with positive interaction terms indicating substantial buffering effects. Race-stratified analyses showed consistent patterns across non-Hispanic White, non-Hispanic Black, and His-panic older adults, with particularly strong SNAP buffering among minority groups. Conclusions: The findings suggest that strengthening food assistance access may help reduce cognitive health disparities in aging populations.

Abstract: This study presents the Structural–Typological–Value Sensitivity Model (STVSM), a multi-dimensional framework for evaluating vulnerability in historic buildings where fragility cannot be explained by structural indicators alone. Existing models prioritise load-bearing behaviour but overlook typological discontinuity, spatial fragmentation and erosion of cultural or architectural value. STVSM addresses this through three weighted sub-indices—structural vulnerability (SV), typological degradation (TV) and heritage value (HV)—each calibrated using expert-derived micro–macro coefficients. Field-based deterioration scores (0–1) are multiplied by these final weights to produce SV, TV and HV values, then merged into a Conservation Priority Index (CPI).The model is applied to twenty-five buildings in three heritage contexts: Cumalıkızık traditional houses, vernacular dwellings in Balıkesir–Karesi and nineteenth-century Greek Orthodox churches in Bursa. The churches yield the highest CPI values due to roof loss, wall deformation and spatial discontinuity, reinforced by cultural significance. Vernacular houses show moderate structural deterioration but marked typological distortion linked to later additions and façade alterations. Cumalıkızık houses present heterogeneous conditions, combining preserved structures with material decay.By quantifying structural behaviour, typological integrity and heritage value within a single analytical system, STVSM offers a transparent and repeatable basis for conservation prioritisation across diverse historic building stocks.

Abstract: Rheumatoid arthritis (RA) is a chronic, systemic autoimmune pathology characterized by symmetric synovitis, pannus formation, and the potential for severe extra-articular manifestations. Despite historical associations with high morbidity, the 'treat-to-target' strategy has revolutionized patient outcomes. This review analyzes the pharmacological evolution of RA management over the last decade. We examine the foundational role of Methotrexate (MTX)—specifically its adenosine-mediated mechanism—and the stratification of biologic disease-modifying antirheumatic drugs (b-DMARDs), including TNF inhibitors, IL-6 receptor antagonists, and B-cell depleting agents. Crucially, we discuss the recent paradigm shift in the use of Janus Kinase (JAK) inhibitors following the 2021 ACR Guidelines and emerging safety data regarding cardiovascular and malignancy risks (the ORAL Surveillance trial). Finally, we explore the horizon of RA treatment, including GM-CSF inhibition, the complex management of difficult-to-treat (D2T) phenotypes, and the increasing integration of biosimilars to improve global treatment access.

Abstract: Background: Germany's pioneering energy policy, the Energiewende, seeks to fundamentally transform its energy landscape by shifting from conventional fossil fuels to renewable sources.Aim: This current study examined the economic and social impact of Germany’s transition to renewable energy (Energiewende) since it officially started in 2000 when the Renewable Energy Sources Act (EEG – Erneuerbare-Energien-Gesetz) was passed.Method: Data was collected from nine renewable energy experts using semi-structured interviews. The views of the diverse experts were analyzed using a thematic approach.Results: The findings indicate that early policy instruments and subsidy schemes were critical in accelerating renewable energy deployment and improving cost competitiveness, especially for wind and solar technologies, though their relevance has evolved as the sector matured. Energy communities emerged as a central pillar of the transition, enhancing local participation, social acceptance, and socio-economic benefits through diverse ownership models. Economically, the Energiewende is widely perceived to have stimulated job creation, investment, and technological innovation, while also contributing to job losses in fossil fuel–dependent sectors, particularly coal. Social inequalities were identified as a significant challenge, driven by employment displacement and rising energy affordability concerns for low-income households. Public acceptance was found to vary by technology, with solar projects generally favored over wind due to noise-related concerns.Conclusion: This present research contributes to a more profound understanding of Germany's journey towards a green energy future and highlights the need for adaptive policy frameworks and socially inclusive strategies to support a just and sustainable energy transition.

Abstract: Rising numbers of wolf populations make traditional, resource-intensive methods of wolf monitoring increasingly challenging and often insufficient. This study explores how wolf howls can be used as a new monitoring tool fro wolves by applying AI methods to detect and classify wolf howls from acoustic recordings, thereby improving the effectiveness of wolf population monitoring. Three AI approaches are evaluated: BirdNET, Yellowstone's Cry-Wolf project system, and BioLingual. Data were collected using SM4 audio recorders in a known wolf territory in Klelund Dyrehave, Denmark, and manually validated to establish a ground truth of 260 wolf howls. Results demonstrate that while AI solutions currently do not achieve the complete precision or overall accuracy of expert manual analysis, they offer tremendous efficiency gains, significantly reducing processing time. BirdNET achieved the highest recall at 78.5% (204/260 howls detected), though with a low precision of 0.007 (resulting in 28,773 false positives). BioLingual detected 61.5% of howls (160/260) with 0.005 precision (30,163 false positives), and Cry-Wolf detected 59.6% of howls (155/260) with 0.005 precision (30,099 false positives). Crucially, a combined ap-proach utilizing all three models achieved a 96.2% recall (250/260 howls detected). This suggests that while AI solutions primarily function as powerful human-aided data re-duction tools rather than fully autonomous detectors, they represent a valuable, scalable, and non-invasive complement to traditional methods in wolf research and conservation, making large-scale monitoring more feasible.

Abstract: Obstructive Sleep Apnea is a prevalent condition characterized by recurrent upper airway collapse during sleep, leading to intermittent hypoxemia and sleep fragmentation, with significant implications for cardiovascular health (Yeghiazarians et al., 2021). Alarmingly, between 40% and 80% of individuals with cardiovascular diseases, including acute coronary syndrome, ischemic heart disease, chronic heart failure, cerebrovascular accidents, and arrhythmias, also suffer from OSA (Nguyen et al., 2024). This high comorbidity underscores the critical need for understanding the intricate pathophysiological links between OSA and cardiovascular morbidity (Deviaene et al., 2017). Despite its significant prevalence, OSA remains underdiagnosed in a substantial portion of the population, particularly in middle-aged cohorts, where cardiovascular disease risk begins to escalate (Peker et al., 2002). The presence of OSA is a significant risk factor for various cardiovascular comorbidities, including hypertension, coronary artery disease, and heart failure, with its prevalence ranging from 2% to 26% in the general population depending on demographic factors (Ivanovski et al., 2023; Jaswal et al., 2024). Furthermore, global epidemiological data indicate a rising prevalence of OSA, largely attributed to the increasing rates of obesity and the enhanced sensitivity of diagnostic methodologies like advanced polysomnography (Frangopoulos et al., 2021). This rise in prevalence contributes to a significant burden of associated comorbidities, including neuropsychiatric dysfunction and metabolic syndrome, beyond the well-established cardiovascular and cerebrovascular risks (Bikov et al., 2020). Given this context, our cross-sectional analysis aims to elucidate the specific relationships between OSA severity and various indicators of cardiovascular morbidity within a middle-aged cohort.

Abstract: Background/Objective: Existing abbreviated Geriatric Depression Scales (GDS), derived via Classical Test Theory (CTT), often sacrifice accuracy for brevity and retain non-specific items. We aimed to develop a minimum-item GDS maintaining diagnostic performance equivalent to the full 30-item scale (GDS30) using Item Response Theory (IRT). Methods: This cross-sectional study employed rigorous 5:5 split-sample cross-validation. Participants included 6,525 older adults (aged ≥60 years) from community-based (Korean Longitudinal Study on Cognitive Aging and Dementia) and clinical settings (geropsychiatry clinic). Depression was diagnosed through standardized clinical interviews based on DSM-IV criteria. Two-parameter logistic IRT models estimated item discrimination and difficulty parameters. Sequential item reduction with DeLong tests identified the minimum number of items required to maintain GDS30-equivalent area under the curve (AUC). Results: The 10-item IRT-optimized scale (GDS10-IRT) achieved an AUC of 0.856 (95% CI: 0.809–0.895) in the validation set, showing no significant difference from GDS30 (AUC=0.883; p=0.396). Conversely, the 15-item GDS (GDS15) demonstrated significantly lower AUC than GDS30 (p< 0.001) despite having more items. GDS10-IRT achieved a 234% improvement in efficiency ratio (AUC/items) over GDS30. Notably, Item 16 ("feeling downhearted and blue"), identified as the most discriminating symptom (a=2.53), is absent from the GDS15 but included in GDS10-IRT. Conclusion: IRT-based item selection achieves GDS30-equivalent diagnostic accuracy with only 10 items, outperforming the widely used GDS15. By recovering high-discrimination items excluded by CTT, the GDS10-IRT offers a more efficient, specific screening tool for late-life depression.

Abstract:

Efficiently separating propene and propane is paramount for the chemical industry but notoriously difficult due to their minimal size and volatility differences. Here, we demonstrate a powerful strategy to overcome this separation challenge by designing bimetallic Zeolitic Imidazolate Framework (ZIF)-based mixed-matrix membranes (MMMs). We fabricated thin-film composites (TFCs) by integrating monometallic ZIF-8, ZIF-67, and a synergistic bimetallic ZIF-8-67 into a uniquely formulated ionic liquid-cellulose acetate (IL-CA) polymer matrix. Structural and morphological analyses confirmed the high crystallinity of the ZIF fillers and their seamless integration within the polymer. The resultant ZIF-8-67/IL-CA membrane exhibited exceptional separation performance, surpassing its monometallic counterparts by a threefold increase in both C₃H₆ permeance and C₃H₆/C₃H₈ ideal selectivity relative to the base membrane. Under industrially relevant mixed-gas testing, the membrane achieved an impressive separation factor of 8 for propene over propane. These findings reveal that the strategic integration of bimetallic nodes in ZIFs can unlock synergistic properties unattainable with single-metal frameworks. This work presents a robust and scalable platform for developing next-generation membranes that defy conventional performance trade-offs, a way for efficient membrane-based olefin/paraffin separations.

Abstract:

Ex vivo functional testing for multiple myeloma is rapidly evolving, yet no single assay has reached the level of reliability and clinical utility needed for routine decision-making. Existing approaches generally fall into three categories comprising 2D cultures, 3D models, and dynamic systems. Each contributes valuable but incomplete insight into therapeutic response. Among these, 2D assays remain the most mature, with the most extensive clinical correlations to date, though their simplified architecture limits their ability to reflect the full complexity of the marrow microenvironment. 3D systems, including spheroids and matrix-based organoids, offer improved preservation of tumor heterogeneity and microenvironmental cues. These platforms show emerging clinical relevance and may hold advantages over traditional 2D formats, and validation efforts are developing. Dynamic systems including microfluidic models and perfused bone-marrow mimetics represent the most physiologically ambitious category, yet their technical intricacy and early stage of development have so far limited broad clinical correlation. Altogether, the current landscape highlights substantial progress but lacks an optimal assay. In this review, we take the unique approach of examining published ex vivo tests that have demonstrated a level of clinical correlation. We evaluate their respective formats, strengths and limitations, and discuss considerations for what an ideal future assay may encompass.

Abstract: Since the beginning of modern computer history, the Turing machine has been a dominant architecture for most computational devices, which consists of three essential components: an infinite tape for input, a read/write head, and finite control. In this structure, what the head can read (i.e., bits) is the same as what it has written/outputted. This is actually different from the ways in which humans think or do thought/tool experiments. More precisely, what humans imagine/write on paper are images or texts, and they are not the abstract concepts that they represent in the human brain. This difference is neglected by the Turing machine, but it actually plays an important role in abstraction, analogy, and generalization, which are crucial in artificial intelligence. Compared with this architecture, the proposed architecture uses two different types of heads and tapes, one for traditional abstract bit inputs/outputs and the other for specific visual ones. The mapping rules among the abstract bits and the specific images/texts can be realized by neural networks with a high accuracy rate. Logical reasoning is thus performed through the transfer of mapping rules. The statistical decidability of the Halting Problem with an imperceptibly small error rate in reasoning steps is established for this type of machines. As an example, this paper presents how the new computer architecture (what we call ``Ren machine" for simplicity here) autonomously learns a distributive property/rule of multiplication in the specific domain and further uses the rule to generate a general method (mixed in both the abstract domain and the specific domain) to compute the multiplication of any positive integers based on images/texts. The machine's strong reasoning ability is also corroborated in proving a theorem in Plane Geometry. Moreover, a robotic architecture based on Ren machine is proposed to address the challenges faced by the Vision-Language-Action (VLA) models in unsound reasoning ability and high computational cost.

Abstract: Contemporary accounts of hemispheric asymmetry in cognitive neuroscience predominantlyemphasize neuroanatomical localization and functional specialization, while ofering limitedexplanatory mechanisms for how lateralized neural processes become observable inembodied behavior. The Subjectica Hypothesis proposes a neurophenomenologicalframework in which hemispheric asymmetry is expressed not as a fixed correspondence withbodily sides, but as a dynamic pattern of sensorimotor embodiment manifested throughbodily kinematics.The model introduces four operational constructs—Personal-Oriented Left Side (PO-LS),Society-Oriented Right Side (SO-RS), Asymmetric Neurobehavioral Signal (ANS) and theBody Segments (BS) —designed to link hemispheric functional dominance, cognitiveorientation, and measurable bodily dynamics. These constructs function as interpretativeintermediaries, enabling the analysis of lateralization through continuous patterns of posture,movement, and segment-level motor dominance rather than through discrete anatomicalmappings.Subjectica does not report empirical results; instead, it defines a theoretically coherent andoperationally specified framework intended to guide future experimental, observational, andphenomenological research on lateralized embodiment. The hypothesis generates falsifiablepredictions concerning task-dependent cognitive orientation, hemispheric dominance, andasymmetric sensorimotor expression, extending existing models of hemisphericspecialization within the broader paradigm of embodied cognition.

Abstract: This work develops a Lorentz-invariant variational framework in which Fisher-information geometry appears as an intrinsic structural contribution to quantum dynamics. Motivated by longstanding attempts to connect quantum mechanics with information-theoretic principles, we introduce an action functional depending on the density and phase fields in the Madelung representation. Variation of this action yields a modified Klein–Gordon equation containing a single nonlinear term proportional to the four-dimensional Fisher-information curvature of the probability density. The standard Klein–Gordon equation is recovered when the structural parameter vanishes, ensuring full compatibility with established relativistic dynamics. Taking the nonrelativistic limit, we obtain a uniquely determined nonlinear Schrödinger equation in which the correction term is the functional derivative of the Fisher information. The resulting dynamics preserve probability, maintain the Hamilton–Jacobi correspondence, and contain the linear Schrödinger equation as a special case. Analytical expressions for Gaussian and superposed states demonstrate how the structural modification scales with spatial localization and interference structure, providing clear qualitative signatures that distinguish the model from previous nonlinear extensions and offer a theoretical basis for future experimental verification. The results establish a mathematically transparent link between information geometry and quantum dynamics and provide a foundation for future extensions to fermionic, gauge, and many-body systems.

Abstract: Academic minors provide universities with a flexible mechanism to broaden curricular reach, attract diverse students, and integrate experiential learning. The Wildlife Care and Handling Minor, established at the University of X in 2015, illustrates how a minor can foster professional, academic, and personal growth while preparing students for animal care. The program combines coursework, structured externships, and reflective writing, requiring more than 200 hours of service in institutions managing captive wildlife. This study analyzes 121 student reflections from the capstone externship course. Thematic analysis revealed consistent patterns across four domains. Professionally, students described the Minor as confirming ambitions, redirecting career goals, or expanding horizons to fields such as environmental education, raptor work, or animal law. Academically, it bridged theory and practice, strengthened graduate preparation, clarified interests, and fostered transferable skills in communication and leadership. Personally, students reported growth in resilience, empathy, and ethical awareness, shaped by challenges in living arrangements, cultural adaptation, and compassion fatigue. Advice to future participants emphasized exploration, preparation, professionalism, adaptability, and mentorship, reflecting peer support. Collectively, findings show the WCH Minor as both proving ground and pivot point, enabling students to test identities, integrate learning, and cultivate maturity. The program offers a transferable model for experiential, reflective education that prepares graduates who are thoughtful, resilient, and ethically grounded.

Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across diverse domains and many applications demand a high degree of automation, supported by reliable Conflict Detection and Resolution (CD&R) and Collision Avoidance (CA) systems. At the same time, public mistrust, safety and privacy concerns, the presence of uncooperative airspace users, and rising traffic density are driving a shift toward decentralized concepts such as free flight, in which each actor is responsible for its own safe trajectory. This survey reviews CD&R and CA methods with a particular focus on decentralized automation and encounters with noncooperative intruders. It analyzes classical rule-based approaches and their limitations, then examines Machine Learning (ML)–based techniques that aim to improve adaptability in complex environments. Building on recent regulatory discussions, it further considers how requirements for trust, transparency, explainability, and interpretability evolve with the degree of human oversight and autonomy, addressing gaps left by prior surveys.

Abstract: Basidiomycete mushrooms contain complex -D-glucans which play an important role in immuno-modulating and anti-tumor activities. The present work involves a novel and intrinsic synchronous fluorescent and phosphorescence assay method for -D-glucans. Synchronous fluorescence and phosphorescence spectroscopy was carried out by a spectrofluorometer in the range of 250 to 750 nm with a  range of 5 -30 nm which exhibited peaks at 492, 540 and 550 nm by using -D-glucan from Euglena gracilis as standard. A micro and high throughput method based on 96-well microtiter plate fluorescence was devised with a excitation and emission of 420 nm and 528 nm, respectively . This assay method presented several advantages over the published colorimetric methods since it is a non-invasive assay method that requires only 0.97 g of -D-glucans in samples, greater sensitivity, speed, assay of many samples and very cheap. -D-glucans of several mushrooms (i.e Poria coccus, Auricularia auricula, Ganoderma lucidium, Pleurotus ostreatus , Cordyceps sinensis , Agaricus blazei, Polyporus umbellatus, Inonotus obliquee) were isolated by using a sequence of several extractions and quantified by either spectrofluorometer or fluorescence microtiter plate reader. 3-D spectra measurements were carried out of -D-glucans from medicinal mushroom strains. FTIR spectroscopy was used to study the structural features ofD-glucans in these mushroom samples.