Abstract: Cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride channel in humans and other vertebrates, whose mutation leads to cystic fibrosis. CFTR inhibitory factor — Cif — is a recently discovered bacterial epoxide hydrolase that downregulates CFTR protein upon the bacterial infection. However, its cleaving activity towards fatty acid epoxides — epoxygenase-derived oxylipins — has been recently characterized. We identified a list of host-associated bacteria with putative Cif proteins, identified their most prevalent ecological functions by systematic literature review, and performed similar review for the previously assembled list of host-associated bacteria carrying lipoxygenase (LOX). Both Cif and LOX showed the association with pathogenesis and symbiosis in broad host range, and similar ecological profiles of their carriers suggested that they both might target oxylipin signaling in hosts. We also described the association of Cif with plant hormone biosynthesis and plant growth promotion — which indirectly supports our previous model of bacterial LOX action in plant and vertebrate hosts.

Abstract: Lower-limb rehabilitation exoskeletons must balance biomechanical compatibility, structural safety, and low mass to enable practical, repeatable gait assistance. This paper proposes a planar pantograph-derived exoskeleton leg driven by a Chebyshev Lambda linkage and develops an integrated workflow from mechanism synthesis to manufac-turable optimization and experimental verification. A mannequin-coupled multibody model was built in MSC ADAMS to evaluate joint kinematics, end-point (foot) trajec-tories, and joint reaction forces under multiple scenarios (fixed-frame, ramp, stair as-cent, and inclined-plane walking). The extracted joint loads were transferred to a par-ametric finite element model in ANSYS Workbench, where response-surface surrogates and a multi-objective genetic algorithm (MOGA) were used to minimize mass under stiffness and strength constraints. For the optimized load-bearing link, the selected minimum-mass design reached a component mass of 0.542 kg while respecting the imposed structural limits, i.e., a maximum total deformation below 0.2 mm and a maximum equivalent (von Mises) stress below 55 MPa (e.g., ~0.188 mm deformation and ~39 MPa stress in the optimal candidate). A rapid prototype was manufactured by 3D printing and experimentally evaluated using CONTEMPLAS high-speed video tracking, providing measured X_M(t) and Y_M(t) trajectories and joint-angle histories for quantita-tive comparison with simulations via RMSE metrics.

Abstract: Consequent behavioral effects are documented at both individual and market levels: elevated turnover, revenge trading, impaired calibration and amplified volatility. Cross-domain findings from pedagogy, neuroscience and decision-support research are marshalled to show that process-focused training, biofeedback, explainable analytics and carefully engineered platform feedback can foster rule-governed behavior and attenuate affect-driven mispricing. The paper specifies concrete proxy measures for procedural fidelity, describes scalable training and platform interventions, and emphasizes the need to match interventions to trader segment, platform design and market regime. Proxy process measures often seem to demand institutional access, technical integration and continuous data streams, and may therefore be costly, vulnerable to gaming, and poorly scalable for dispersed retail traders. These limitations may undermine the feasibility and fidelity of many otherwise promising interventions. By contrast, a simple, intra-psychic proxy may offer a cost-free, accessible signal that redirects attention. This narrative review examines the psychological dynamics of outcome-focused trading and advances a process-oriented alternative for stabilizing trader behavior and improving learning. Drawing on experimental, physiological, neuroscientific and large-scale field evidence, the review characterizes outcome fixation as an attentional and affective orientation toward realized short-term profits and losses that amplifies emotional reactivity, promotes impulsive and compensatory risk-taking, and undermines adherence to pre-specified decision rules. The review then identifies proximal cognitive and biophysiological mechanisms such as loss salience, anticipatory reward signaling, stress-related endocrine effects and capacity limits on deliberative processing, that link momentary feedback to departures from disciplined practice. In this review, we introduce a hypothetical construct termed the “discipline coin” (DISC). DISC integrates the key features discussed above—simplicity, cost-free use, independence from outcome-based feedback and accessibility—and can be employed as an intrapsychic signal to shift attention from short-term profits and losses to consistent adherence to a trading process. However, further research is needed to validate these assumptions empirically.

Abstract: Background: Routine cardiac catheterization has traditionally been considered mandatory prior to the bidirectional Glenn procedure in patients with single-ventricle physiology, aiming to assess pulmonary artery anatomy, pulmonary pressures, and ventricular filling. However, invasive assessment carries procedural risk and cumulative radiation exposure, while advances in non-invasive imaging have challenged this paradigm. Main Body: This review synthesizes historical practice, contemporary evidence, and evolving guideline recommendations regarding pre-Glenn assessment. Landmark randomized data, most notably from Brown et al., demonstrated that cardiac magnetic resonance provides equivalent surgical decision-making and early outcomes compared with routine catheterization, while significantly reducing adverse events, hospital stay, and cost. Subsequent institutional experiences and international guidelines (2020–2023) have reinforced a selective approach, favoring non-invasive imaging—particularly cardiac magnetic resonance —unless an intervention is anticipated or non-invasive findings are equivocal. Furthermore, we propose a phenotype-guided strategy for a subset of patients with favorable ventricular morphology and shunt-dependent pulmonary blood flow, in whom targeted echocardiography with adjunctive computed tomography angiography may suffice. Conclusion: Accumulating evidence supports a shift from universal invasive assessment toward individualized, risk-stratified pre-Glenn evaluation. A selective imaging-driven strategy may safely reduce procedural burden while preserving diagnostic accuracy in carefully chosen patients.

Abstract: Virtual Power Plants (VPPs) face significant challenges in managing the uncertainty and variability of distributed energy resources (DERs), which can result in high trading risk and deter investment. This paper proposes and evaluates two advanced optimisation techniques—stochastic programming and robust optimisation—to derive risk-aware bidding strategies for VPP participation in the day-ahead and balancing electricity markets. These methods are benchmarked against a deterministic, expectation-based model. The novelty of this work lies in the comparative application of stochastic and robust frameworks to VPP bidding strategy design under real-world uncertainty, the introduction of scenario-based wind and conventional generation models, and the integration of energy storage into the optimisation framework to assess its impact on profitability and risk mitigation. Through a series of simulations using actual market data from the UK (Elexon), we evaluate three generation portfolio configurations—conventional, renewable, and aggregated. The results show that while stochastic optimisation consistently achieves the highest expected profit, the robust model ensures the highest minimum profit under worst-case conditions. Moreover, combining DER types and integrating battery storage further enhances profitability and reduces exposure to imbalance penalties. These findings provide valuable insights for the development of intelligent, risk-aware trading strategies for VPP operators.

Abstract: A cornerstone in transferring a classical Liquid Chromatography (LC) with UltraViolet/Visible (UV/Vis) detector into a greener and, beyond, towards a sustainable analytical method should consider the safety and health of the used organic solvent in the method. Toxic organic solvent portions used in the mobile phase can be replaced by an eco-friendly green solvent that is ideally bio-based and biodegradable to increase the greenness index of the method. However, the implementation of a new organic solvent for High Performance Liquid Chromatography (HPLC-UV/Vis) and/or UltraHigh Performance Liquid Chromatography (UHPLC-UV/Vis) requires not only a simple consideration of its environmental and health impact, cost-effectiveness, user-friendliness, and impact on the analytical performance of the method but rather a systematic evaluation of its chromatographic suitability. Existing greenness, blueness, and redness metrics expressing whiteness for evaluating the sustainability of liquid chromatographic methods after solvent replacement overlook the chromatographic suitability of the selected green solvent, potentially leading to suboptimal solvent replacement and an incomplete view of its capabilities. In this work, the authors present a Universal Suitability and Sustainability Index (USSI), a sixteen-parameter scoring system that quantifies four main factors for complete evaluation of a new solvent for implementation in liquid chromatography. This index is even beyond the white analytical chemistry principle. The four main factors are chromatographic suitability, greenness, blueness, and redness. Three of these factors, namely greenness, blueness, and redness, are based on available tools and metrics to evaluate the environmental and health, impact on the practicability, and the analytical performance of the method. The fourth factor is added as an important criterion to judge the suitability of the solvent to liquid chromatographic analysis and to give an overview about its analytical chromatography-oriented applicability. The new index has been used to evaluate traditional solvent-based liquid chromatographic methods as well as those based on alternative emerging green solvents and compare the factors together to give a universal overview that aids users to drive a rapid imprison on the weakness and strength aspects and makes it easier to judge the selection of the solvent and the evaluation of the overall method sustainability.

Abstract: Background/Objectives: Congenital heart defects (CHD) are the most common structural birth defects that exhibit high heritability. Emerging evidence suggested that CHD are as-sociated with disruptions in one-carbon metabolism. In a family-based trio design, we in-vestigated whether maternal, paternal, and child plasma concentrations of choline, beta-ine, and folate were associated with CHD severity. Subjects and Methods: The study in-cluded 72 children with CHD, 69 mothers and 64 fathers of the children. CHD severity was classified according to the European network of population-based registries for the epidemiological surveillance of congenital anomalies (EUROCAT) system and the Ger-man PAN study (Prevalence of Congenital Heart Defects in Newborns). Plasma and urine concentrations of choline and betaine and plasma folate vitamers were quantified using ultra-performance liquid chromatography–tandem mass spectrometry. Results: The chil-dren [mean (SD) age 3.1 (3.2) years, 59.7% males] presented with varying CHD severities according to EUROCAT (62.5% severe and 37.5% mild) and PAN classifications (45.8% severe, 30.6% moderate and 23.6% mild). Plasma concentrations of choline were < 10 µmol/L in 38 (66.7%) of the mothers and 27 (62.8%) of the fathers who provided blood samples. Maternal plasma choline concentrations < 10 µmol/L were associated with hav-ing a child with severe CHD [adjusted odds ratio (aOR) 3.7; 95% confidence intervals (95%CI) = 1.1, 12.2 compared to mothers with choline concentrations ≥ 10 µmol/L]. Low-ered paternal plasma choline concentrations were also associated with severe CHD (aOR 7.4; 95% CI = 1.7, 31.5). Plasma concentrations of choline in the children and those of be-taine and folate vitamers in parents and children were not associated with CHD severity. Conclusions: Lower plasma concentrations of choline in the parents detectable several years after conception, were related to having a child with severe CHD compared with families of children with higher plasma choline. These findings support a potential role for maternal and paternal choline metabolism in modulating CHD severity. Etiological studies aiming at prevention of prevalent congenital anomalies should focus on maternal and paternal risk factors.

Abstract:

The superconducting transition temperature of CaC₆ is investigated within the Roeser–Huber (RH) formalism using both rhombohedral and hexagonal crystallographic representations. While these two descriptions are crystallographically equivalent, they differ in their geometric construction of superconducting paths and near-atom environments. In the rhombohedral representation, only translationally closed Ca–Ca vectors consistent with the primitive lattice are considered, yielding three symmetry-distinct RH paths. In the hexagonal representation, the same superconducting channels are expressed in an expanded conventional cell, where some paths appear as unfolded or symmetry-related sublattice connections. For each representation, the RH path lengths and effective near-atom counts are evaluated and used to compute the superconducting transition temperature. The rhombohedral description yields $T_c^{\rm(calc)} = 10.35$ K, while the hexagonal representation gives $T_c^{\rm(calc)} = 10.91$ K, both in good agreement with the experimental value $T_c^{\rm(exp)} = 11.5$ K. The difference between the calculat\( {The superconducting transition temperature of CaC$_6$ is investigated within the Roeser–Huber (RH) formalism using both rhombohedral and hexagonal crystallographic representations. While these two descriptions are crystallographically equivalent, they differ in their geometric construction of superconducting paths and near-atom environments. In the rhombohedral representation, only translationally closed Ca–Ca vectors consistent with the primitive lattice are considered, yielding three symmetry-distinct RH paths. In the hexagonal representation, the same superconducting channels are expressed in an expanded conventional cell, where some paths appear as unfolded or symmetry-related sublattice connections. For each representation, the RH path lengths and effective near-atom counts are evaluated and used to compute the superconducting transition temperature. The rhombohedral description yields $T_c^{\rm(calc)} = 10.35$ K, while the hexagonal representation gives $T_c^{\rm(calc)} = 10.91$ K, both in good agreement with the experimental value $T_c^{\rm(exp)} = 11.5$ K. The difference between the calculated values amounts to approximately 5.4\%. These results show that the underlying RH superconducting channels and their near-atom environments are representation independent, while minor quantitative differences in $T_c^{\rm(calc)}$ arise from metric redistribution of equivalent paths. This directly confirms that the RH formalism captures intrinsic structural features of superconductivity rather than artifacts of unit-cell representation. \)d values amounts to approximately 5.4\%. These results show that the underlying RH superconducting channels and their near-atom environments are representation independent, while minor quantitative differences in $T_c^{\rm(calc)}$ arise from metric redistribution of equivalent paths. This directly confirms that the RH formalism captures intrinsic structural features of superconductivity rather than artifacts of unit-cell representation.

Abstract: Autophagy is an evolutionarily conserved degradation and recycling process through which cells deliver cytoplasmic components such as toxic or defective proteins and organelles to lysosomes for clearance. Unlike dividing cells, neurons depend on degradative pathways to prevent the buildup of cellular waste and to sustain nutrient and energy homeostasis. Emerging evidence indicates that autophagy is particularly critical during early development when neuronal circuits are being established, synaptic connections refined, and activity-dependent mechanisms sculpt overall network architecture. Accordingly, loss of key autophagy-related genes in newly formed neurons disrupts differentiation, synaptic formation and neurotransmission. Despite these insights, the developmental regulation of autophagy genes remains poorly understood, and the composition of the autophagic machinery at synapses is still largely unresolved. To address this, we performed genome-wide transcriptomic analyses of the cortical brain region to characterize the maturation-dependent dynamics of autophagy–lysosomal genes. In parallel, we examined the autophagy-associated proteome within synaptosomes to better understand how autophagic proteins contribute to synaptic processes during critical stages of network formation. Together, these complementary approaches reveal new aspects of autophagy regulation during development and provide a foundation for identifying therapeutic targets for neurological disorders linked to impaired synaptic and cellular homeostasis.

Abstract: The rapid evolution of Large Language Models (LLMs) from static text generators to autonomous agents has revolutionized their ability to perceive, reason, and act within complex environments. However, this transition from single-model inference to System Engineering Security introduces unique structural vulnerabilities—specifically instruction-data conflation, persistent cognitive states, and untrusted coordination—that extend beyond traditional adversarial robustness. To address the fragmented nature of the existing literature, this article presents a comprehensive and systematic survey of the security landscape for LLM-based agents. We propose a novel, structure-aware taxonomy that categorizes threats into three distinct paradigms: (1) External Interaction Attacks, which exploit vulnerabilities in perception interfaces and tool usage; (2) Internal Cognitive Attacks, which compromise the integrity of reasoning chains and memory mechanisms; and (3) Multi-Agent Collaboration Attacks, which manipulate communication protocols and collective decision-making. Adapting to this threat landscape, we systematize existing mitigation strategies into a unified defense framework that includes input sanitization, cognitive fortification, and collaborative consensus. In addition, we provide the first in-depth comparative analysis of agent-specific security evaluation benchmarks. The survey concludes by outlining critical open problems and future research directions, aiming to foster the development of next-generation agents that are not only autonomous but also provably secure and trustworthy.

Abstract: Chronic and hard-to-heal wounds remain a major clinical burden, yet many synthetic nanocarriers used in advanced dressings are constrained by limited biomimicry and concerns over inflammatory risk and off-target toxicity. Here we report porcine skin–derived reconstituted lipid nanoparticles (PS-rLNPs) as a tissue-origin, composition-preserving nanoplatform for wound repair. Total lipids extracted from fresh porcine skin were assembled into nanoparticles via a facile solvent-injection process. Lipidomics revealed a triglyceride- and phosphatidylcholine-dominant composition accompanied by minor membrane-relevant lipid species, suggesting a biocompatible, multi-lipid milieu. PS-rLNPs formed a stable nanoscale dispersion and maintained colloidal stability in physiologically relevant and serum-containing media. In vitro, PS-rLNPs showed no cytotoxicity across the tested dose range and exhibited pronounced intrinsic pro-healing bioactivity, significantly enhancing fibroblast viability and accelerating cell motility in both scratch-closure and Transwell migration assays. Collectively, these results establish PS-rLNPs as a biocompatible, serum-stable, and intrinsically pro-regenerative lipid nanoparticle system, providing a scalable route to tissue-derived nanomedicines that may complement next-generation wound-care strategies.

Abstract:

Hepatitis delta (HDV) infection affects 5% of hepatitis B (HBV)-positive patients, is associated with an increased risk of cirrhosis and hepatocellular carcinoma but remains underdiagnosed. The first part of our « Delta Describe » study highlighted insufficient screening of HDV patients in metropolitan France. We report here their real-world management. Patients with at least one positive HDV RNA test performed in 2019 were identified through the main French public and private laboratories. In 2024, informed patients were interviewed and physicians supplemented the collected data. 547 patients were included, median age 44 years, mainly originated from Africa or Eastern Europe. HIV and Hepatitis C coinfections were reported in 15.2% and 4.6% respectively. Liver stiffness was assessed by FibroScan® (75.3%) primarily. Most patients knew the year of diagnosis and 69% their fibrosis stage. Liver related events occurred in 14.3% of patients, mainly cirrhosis decompensation (67.9%) and hepatocellular carcinoma (28.3%). Forty-five patients underwent liver transplantation. In 2024, 47.5% had undetectable HDV RNA. Among treated patients (n=387), 37.4% received bulevirtide with or without pegylated-interferon, and 62.6% nucleos(t)ide analogues (NUCs) only. In metropolitan France, HDV patients had access to specialized follow-up, to innovative therapies (bulevirtide), were mostly on NUCs and demonstrated good disease awareness.

Abstract: The pharmaceutical industry is undergoing a significant transformation driven by digitalization and the adoption of Industry 4.0 principles. Among the most promising innovations is digital twin technology, which creates dynamic virtual replicas of physical manufacturing processes that enable real-time simulation, monitoring, prediction, and optimization. This review article examines the convergence of digital twin technology with established process validation frameworks in pharmaceutical manufacturing, with particular emphasis on the three-stage lifecycle approach outlined in the United States Food and Drug Administration (FDA) Process Validation Guidance and the International Council for Harmonisation (ICH) quality guidelines Q8 (R2), Q9 (R1), Q10, and Q13. The paper explores how digital twins can enhance each stage of process validation, from process design (Stage 1) through process qualification (Stage 2) to continued process verification (Stage 3), by providing mechanistic and data-driven models that improve process understanding, reduce development timelines, and support real-time decision-making. Key enabling technologies, including Process Analytical Technology (PAT), Internet of Things (IoT) sensor networks, machine learning algorithms, and cloud computing platforms, are discussed in the context of their integration with digital twin architectures. Case studies from both small molecule and biologic manufacturing are presented to illustrate practical applications. The article further addresses regulatory considerations, data integrity requirements, model validation challenges, and the ethical implications of adopting AI-augmented digital twins in GMP-regulated environments. Finally, future research directions, including the integration of quantum computing, multi-omics data, and federated learning approaches, are proposed. This review aims to provide pharmaceutical scientists, engineers, and regulatory professionals with a comprehensive roadmap for leveraging digital twin technology to achieve robust, compliant, and efficient manufacturing processes.

Abstract: Background: Splenic marginal zone lymphoma (SMZL) is a rare indolent lymphoma with extremely limited population level evidence on social and treatment correlates of survival. Methods: We conducted a retrospective cohort study using SEER (2000 to 2022) to evaluate OS in primary SMZL (ICD O 3 9689; spleen C42.2). We summarized baseline features and treatments and used Kaplan Meier and Cox regression. Results: The cohort included 3,548 patients (mean age 68.2 years; 53.6% female). Most were White (89.8%) and non Hispanic (92.1%). Ann Arbor stage was missing or blank in 39.4%. Initial therapy included chemotherapy in 26.4%, beam radiation in 0.7%, and primary site surgery in 21.4%. At last follow up, 56.8% were alive; non Hodgkin lymphoma accounted for 15.8% of the full cohort, with substantial competing causes including heart disease (6.1%). In multivariable Cox analysis, OS was independently associated with age (HR 1.073 per year, 95% CI 1.067 to 1.079), male sex (HR 1.337, 95% CI 1.203 to 1.486), Hispanic ethnicity (HR 1.426, 95% CI 1.194 to 1.703), chemotherapy (HR 1.246, 95% CI 1.118 to 1.390), year of diagnosis (HR 0.983 per category, 95% CI 0.973 to 0.993), marital status (married vs divorced HR 0.720, 95% CI 0.600 to 0.863), and race (Asian or Pacific Islander vs White HR 3.210, 95% CI 1.164 to 8.853). Conclusions: In our large population based analysis, OS in SMZL tracks with demographic and social variables and competing risks. Stage missingness and treatment selection limit causal inference for management effects.

Abstract:

Haiti is a Caribbean country of about 11 million people with a high burden of mosquito-transmitted disease and limited vector control, thereby making effective operational mosquito control of high import. Previous studies have examined vector-borne disease burden and insecticide resistance markers in Haitian Aedes and Anopheles mosquitoes but not Culex species. In this study, we examined collections of Culex quinquefasciatus from 12 locations in northern and southern Haiti for the presence of markers of insecticide resistance (using a variety of target site mutations and biochemical assays) and pathogens (using a deep sequencing microbiome workflow). The metagenome analysis identified Wolbachia, Rhabdoviridae and Plasmodium infection in all sample pools at relatively high levels along with less frequent findings of other potential pathogens. Resistance marker examination identified variable frequencies of knockdown resistance and acetylcholinesterase resistance mutations, as well as variation in resistance-associated enzymatic activities in these populations, which indicate that insecticide resistance to the primary pyrethroid and organophosphate insecticides is likely. Though there was variation between Culex mosquito populations and no clear activity pattern, enzymatic activity was significantly higher in the southern sites compared to the northern sites. Similar findings in Cx. quinquefasciatus populations in other locations in the Americas strongly suggest that vector control with pyrethroid and organophosphate adulticides may be of limited efficacy.

Abstract: IoT-Infused Pedagogies Empowering Resilient Digital Societies via Next-Gen Smart Campus Innovations presents a transformative vision for education in an interconnected era. This paper explores how Internet of Things (IoT) technologies revolutionize pedagogical approaches within smart campuses, fostering adaptive learning ecosystems that extend beyond classrooms to cultivate robust digital communities. By integrating real-time data from sensors, wearables, and AI-driven analytics, next-generation innovations enable personalized instruction, predictive resource management, and immersive simulations that mirror real-world challenges. Key contributions include conceptual models for IoT-embedded teaching strategies that enhance student engagement, operational efficiency, and crisis resilience such as automated safety protocols and energy-optimized environments. Drawing from evolving smart campus infrastructures, augmented reality integrations, and gamified platforms, the framework addresses implementation hurdles like data privacy and scalability through ethical guidelines and modular designs. Ultimately, these advancements position universities as prototypes for resilient digital societies, equipping learners with skills in data literacy, collaborative innovation, and sustainable digital governance. This work bridges theory and practice, offering actionable strategies for educators and policymakers to harness IoT for equitable, future-proof education amid rapid technological shifts.

Abstract: Maintaining forest ecosystems is critical for climate regulation, biodiversity conservation, and the socio-economic stability of agrarian societies such as Ethiopia. This study presents a spatiotemporal analysis of deforestation and its biophysical feedbacks across Ethiopia from 2001 to 2022. The methodology integrates the Hansen Global Forest Change dataset, Global Forest Watch carbon flux data, and MODIS/CHIRPS environmental products within the Google Earth Engine platform, validated by a 1,000-point accuracy assessment. Over the 22-year study period, the nation recorded a total reduction of 718,351 hectares of forest cover, peaking in 2014. The Oromia, Southern Nations, Nationalities, and Peoples' (SNNP), and Benishangul-Gumuz regions experienced the greatest extent of forest loss. In these regions, deforestation correlated positively with rapid population growth and the expansion of key agricultural commodities, specifically wheat, maize, and coffee. Topographic analysis indicates an upward altitudinal shift in deforestation, reaching a peak mean altitude of 1,924 meters and expanding onto steeper slopes. These land-cover changes coincide with spatially heterogeneous environmental shifts; in the southeastern highlands, deforestation corresponded with land surface warming, whereas in the western humid lowlands, clearing coincided with substantial increases in evapotranspiration without immediate thermal anomalies. Additionally, forest-related activities contributed approximately 222.38 million Mg of CO₂ emissions, with the Oromia region identified as the primary contributor. These findings indicate that evidence-based conservation strategies, alternative energy adoption, and sustainable land management are necessary to mitigate further forest loss and ensure long-term ecological resilience.

Abstract:

Requirements for robustness and performance in the frequency domain in control theory are usually formulated as constraints on the modulus of complex functions describing the open-loop system, the sensitivity function, and the complementary sensitivity function. These constraints generate circular sets that can be interpreted as admissible or forbidden regions in the complex plane. In engineering practice, they are often treated as method-specific constructions, without clarifying the general geometric mechanism by which they arise. This study develops a geometric approach in which a broad class of frequency domain robustness constraints is represented as level sets of analytic and fractional-linear functions. The resulting circular sets in the Nyquist plane are characterized in a unified manner and transferred to admissible regions in the s-plane through preimage mappings. The approach is formulated entirely using complex transfer functions, without state-space representations, linear matrix inequalities, or optimization methods. Classical robustness measures, including gain margin, phase margin, and constraints on sensitivity and complementary sensitivity, are shown to be special cases of the same geometric structure. This interpretation establishes a direct link between frequency domain constraints and closed-loop pole locations, allowing a qualitative assessment of robustness and dynamic properties of control systems without introducing new stability criteria or design procedures.

Abstract: Over the past decade, Serious Games (SG) and Immersive Virtual Reality (IVR) have gained increasing interest in rehabilitation. However, in IVR the Head-Mounted Displays (HMDs) introduce limitations such as nausea, eye fatigue, and accessibility constraints. As an alternative, low-immersion games using standard monitors can be employed, though they sacrifice spatial correspondence during user interaction with virtual objects. To address it, this paper presents the development of a SG for upper limb (UL) rehabilitation, incorporating a custom wireless wearable device with vibrotactile haptic feedback to restore spatial correspondence. By combining Leap Motion controller (LMC) based on hand tracking, the system enables natural movement interaction in a closed kinematic chain, offering a viable compromise between immersion and usability. Additionally, three virtual scenarios were developed to train pronation/supination, pinch grip, ulnar/radial deviation, as well as wrist, elbow and phalange flexion/extension. User experience (short AttrakDiff), workload (NASA-RTLX), usability (SUS scale), and functionality were evaluated in healthy participants divided into two groups. Group 1 (n=13) used only LMC, while Group 2 (n=9) used LMC and the wearable device. The results shown that the system was perceived as more functional in Group 2, in addition, an increase in usability (from 74.71 to 80.83) and improvements in feedback, movement precision and quick response were observed in this group. These findings indicate that the wearable device signicantly improves spatial correspondence during interaction, making the system a promising option for motor rehabilitation in desktop VR enviroments.

Abstract: We present a self-contained treatment of the dynamic zero principle, the assertion that the element \( 0 \in S = \{-1,0,+1\} \) is not an absorbing terminal state but a compression boundary through which the system transitions without annihilation. Beginning from three pre-numeric modal states and four interaction constraints (closure, totality, boundedness, nontriviality), we derive the unique minimal algebra \( S \), prove that cancellation is forced rather than postulated, and show that Euler’s identity \( e^{i\pi}+1=0 \) emerges as the algebraic termination certificate of the forced completion sequence \( S \to \mathbb{Z} \to \mathbb{Q} \to \mathbb{R} \to \mathbb{C} \). We prove that the primordial states are symmetric under permutation; triadic completion alone admits a symmetric (\( S_3 \)-equivariant) law, but imposing orientation (order sensitivity) forces symmetry breaking. We discuss howthis naturally aligns with the Cayley–Dickson hierarchy through octonions. Modern quantum field theory already rejects the notion of a trivial vacuum: zero-point energy, vacuum polarization, and renormalization reveal that “empty space” is a structured ground state rather than an absence of structure. However, the algebraic status of this structured vacuum is typically introduced through subtraction schemes and regularization procedures that are formally consistent but conceptually layered atop the theory. The dynamic zero principle provides a minimal algebraic model of a non-absorbing ground state in which compression, cancellation, and holonomy arise from closure itself rather than from external adjustment. In this sense, the present work offers a foundational template for thinking about vacuum structure without ad hoc null-state assumptions. We then formalize the dynamic zero as a \( \mathbb{Z}_2 \) holonomy on the spinor cover: the minimal nontrivial loop that returns observables to themselves while inverting the internal state. The paper is organized into three epistemic tiers: Established (results with complete proofs from first principles), Derivable (results contingent on the full Kosmoplex axiom set whose proofs are sketched or referenced), and Open (precisely stated questions whose resolution would strengthen or falsify the framework). No free parameters appear. The dynamic zero is not a number; it is the engine of non-termination.