Search Results (19,383)

Central heating systems often rely on uniform regulation, making it difficult to meet the differentiated comfort demands of users and frequently leading to overheating. This paper proposes an end-to-end, data-driven framework that systematically couples density-adaptive clustering with dynamic response modeling for precision heating control. First, an adaptive DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm is developed, which automatically determines its parameters via k-distance graph initialization, differential evolution optimization, and hierarchical clustering post-processing. Without requiring a pre-set cluster number, it consistently identifies four typical daily room temperature fluctuation patterns. Validated on 120-day data from a residential community in Luoyang, the first four clusters cover over 80% of users, and the clustering quality approaches that of manually optimized conventional methods. Second, multi-input ARX (Autoregressive with Exogenous Inputs) models are built for the representative user of each cluster to characterize dynamic responses to supply water temperature, flow rate, and outdoor temperature. Rolling prediction for the entire community achieves an RMSE of 0.24 °C and an R² of 0.93. Finally, a differentiated regulation strategy combining main-cluster supply temperature control and small-cluster flow compensation is designed. Simulation results demonstrate that this strategy drives the room temperatures of all clusters significantly toward the 20 °C comfort target, with a marked reduction in standard deviation. The primary contribution of this study lies in the construction of a reproducible, closed-loop pipeline—from raw room temperature data to demand-based regulation logic—offering a quantitative basis for central heating systems transitioning from passive balancing to data-driven, classified control. Full article

The core predicament of energy transition lies not in the availability of clean technologies, but in whether an economy possesses the institutional capacity and social foundation to systematically regulate its carbon-energy metabolic processes. Drawing upon co-evolutionary theory from evolutionary economics, this paper constructs a composite indicator of Low-Carbon Green Energy Eco-Co-evolution (LCEE) encompassing three functional dimensions: efficiency advancement, kinetic energy replacement, and boundary adherence. Concurrently, by integrating innovation ecosystem theory with inclusive development theory, we propose the concept of “Inclusive Potential of Regional Innovation Ecosystems” (IEP), characterizing the systemic potential for transforming innovation outcomes into social welfare across four dimensions: Knowledge Matrix Abundance (KMF), Cultural Capillary Permeation (CCP), Technological Community Succession (TCS), and Social Root Nourishment (SRN). Taking China’s 2016 intellectual property (IP) powerhouse construction pilot as the institutional prototype of Industrial Intellectual Property Upgrading Reform (IPR), we incorporate IPR, IEP, and LCEE into a unified causal analytical framework, proposing a testable transmission logic of ‘institutional supply → ecological development → co-evolutionary synergy. Using panel data from 30 Chinese provincial-level administrative regions over 2010–2022, we employ a Spatial Durbin Difference-in-Differences (SDM-DID) model to identify the direct and spatial spillover effects of IPR on LCEE, and embed a Double Machine Learning (DML) framework to test the mediating mechanism of IEP while controlling for high-dimensional nonlinear interference. The findings reveal that IPR exerts a significant and robust direct promoting effect on LCEE, generating positive spatial spillovers to neighboring regions through the public disclosure of patent information. IEP significantly promotes local LCEE, yet its spatial spillover lacks statistical support due to structural conflicts in inter-dimensional transmission attributes. IEP plays a significant partial mediating role between IPR and LCEE, with the indirect effect accounting for over one-third of the total effect, a finding robust to alternative machine learning algorithms, sample split adjustments, and exclusion of contemporaneous competing policies. Sub-path tests reveal that KMF bears the strongest mediating efficacy, serving as the primary transmission channel, while CCP exhibits full mediation—the institutional effect on LCEE in the cultural dimension depends almost entirely on the mediating transformation through the public cultural service system. Heterogeneity analysis further demonstrates full mediation in the Low-Carbon Green Energy Eco-Kinetic Replacement (KER) dimension, indicating that the institutional catalytic effect on clean energy substitution must be realized through IEP transformation. This paper provides empirical evidence for the proposed causal pathway through which institutional public goods indirectly enhance the synergistic quality of carbon-energy transition via the inclusive potential of innovation ecosystems, providing theoretical foundations and policy implications that, while grounded in China’s institutional context, may offer valuable reference points for emerging market economies facing similar dual pressures of technological constraints and green transition. Full article

Panic disorder is a highly prevalent and impairing diagnosis in veterans. Despite consistent efficacy findings in community samples, few studies have investigated evidence-based psychotherapies in veterans with panic disorder, limiting the understanding of their utility and deployment in Veterans Affairs (VA) settings. The present study preliminarily investigated cognitive behavioral therapy (CBT) for panic disorder via a non-controlled design in a treatment-seeking veteran sample with panic disorder at the VA. Of the 41 veterans initiating treatment, 28 (68.3%) participants completed at least eight sessions of psychotherapy. In general, participants evidenced medium-to-large post-treatment effects across disorder-specific symptoms (panic and anxiety symptomatology), comorbid presentations (symptoms of depression and posttraumatic stress disorder), and overall functioning. Disorder-specific symptom effects remained stable for six months after psychotherapy was terminated. In addition, the delivery of CBT for panic disorder was further supported by positive indices of treatment feasibility, including treatment engagement, homework completion and engagement, and high participant satisfaction ratings. While recognizing that this study did not include a control group, the findings provide limited support for CBT treatment of panic disorder in veterans’ settings, findings that will require confirmation in a multisite controlled clinical trial. Full article

Background: Pain is a multidimensional experience shaped not only by nociceptive input but also by cognitive, emotional, and social processes. In musculoskeletal (MSK) rehabilitation, outcome variability among patients with similar clinical presentations suggests that determinants beyond tissue pathology may influence pain perception and recovery. Contextual factors (CFs)—communication, therapeutic relationship, patient expectations, and environmental cues—are increasingly recognized yet remain inconsistently integrated into routine practice. Objective: To map how CFs are represented in the physiotherapy literature indexed under that terminology, and to identify where empirical evidence in MSK rehabilitation is present and where it is absent. Methods: A narrative review with a systematic search strategy, reported following SANRA, was conducted in PubMed and Scopus, searched on 31 March 2026. Records were screened against predefined eligibility criteria, including publication from 2006 onwards and English language. Two reviewers independently screened records and resolved disagreements by consensus. Methodological quality was appraised using the Cochrane RoB2 tool for randomized controlled trials and an adapted Newcastle–Ottawa Scale for observational and cross-sectional studies. Conceptual publications were not formally appraised. Each publication was classified as direct clinical evidence (Tier A), indirect mechanistic or implementation-level evidence (Tier B), or conceptual contribution (Tier C). Results: Eight publications were included: no source provided direct clinical evidence in a musculoskeletal rehabilitation population (Tier A), five provided indirect mechanistic or implementation-level evidence (Tier B), and three were conceptual contributions (Tier C). The single randomised controlled trial retrieved was conducted in asymptomatic volunteers and was at high risk of bias for the between-group comparisons of all reported outcomes. Findings are organised as contextual domains, mediating mechanisms, and outcomes. No direct clinical evidence was retrieved; claims regarding expectations, therapeutic alliance, non-verbal communication, and the clinical environment rest on indirect or conceptual sources. Conclusions: CFs may contribute to pain and rehabilitation variability through cognitive, emotional, and relational pathways, complementing rather than replacing evidence-based care. The scarcity of direct clinical evidence within the literature indexed under this terminology is itself a finding. Construct-level searches and pragmatic trials are required to clarify the contribution of individual contextual domains. Full article

The discrepancy between in situ microbial abundance and actual metabolic performance represents a critical challenge for interpreting microbial function from meta-omic data. Here, we integrated metagenomic and metatranscriptomic sequencing to investigate this decoupling between microbial abundance and cultivation-based physiological potential in Shanxi aged vinegar (SAV) solid-state fermentation. Lactobacillus acetotolerans dominated the community at both the genomic (40.89%) and transcriptomic (55.36%) levels, whereas Pediococcus acidilactici accounted for only 0.11%—a canonical rare-biosphere member. Source tracking via Sankey analysis showed that genes involved in acetate production were primarily attributed to Acetobacter pasteurianus, whereas genes involved in lactate production were predominantly associated with Lactobacillus spp. However, L. acetotolerans exhibited limited acid tolerance and lactic acid production, whereas the low-abundance P. acidilactici AAF1-5 displayed robust stress tolerance and superior lactic acid production under fermentation-relevant conditions—a striking contrast between microbial abundance and physiological performance. Metabolic interaction network analysis predicted that P. acidilactici may be co-inhibited by L. acetotolerans (I_xy = −2.737, resource competition) and A. pasteurianus (I_xy = −1.887, acid stress). To test whether ecological constraints, rather than intrinsic metabolic capacity, underlie this low abundance, we heterologously expressed the heat shock co-chaperone gene grpE from A. pasteurianus in P. acidilactici AAF1-5 as an experimental tool. The recombinant strain P. acidilactici-grpE exhibited significantly enhanced viability under acetic acid stress and, in simulated SAV fermentation, lactic acid content increased by 23.63% compared with the wild-type control. These results demonstrate that meta-omic abundance does not necessarily predict physiological performance and that low abundance may reflect ecological constraints rather than intrinsic functional deficiency. Our study provides an ecological framework for linking microbial abundance with physiological function beyond sequence-based abundance inference in complex fermentation microbiomes. Full article

Integrated sensing and communication (ISAC) systems are envisioned as a key enabler for next-generation wireless networks. To simultaneously achieve multi-function of communication and sensing for this system, a hybrid reconfigurable intelligent surface (RIS) comprising both active and passive reflecting elements is proposed. An index-wise importance score matrix and a factorized representation of complex reflection coefficients are optimized by introducing a communication-sensing controllable coefficient. A novel ISAC system is investigated, which exploits the low-power advantage of passive reflecting elements while retaining the signal amplification capability of active reflecting elements. In the multiple-input multiple-output (MIMO) communication networks, the RIS reflection coefficient matrix is adaptively optimized via a Riemannian Hessian-based method. At the same time, the transmit precoding matrix is obtained using an extended weighted minimum mean square error (WMMSE) and Lagrange multiplier methods. Compared with baseline schemes including active-only RIS, passive-only RIS, random-phase RIS, and non-RIS, the proposed scheme enables multi-mode adjustability of communication and sensing which can be easily transplanted in current ISAC system. Under the constraint of transmit power, it exhibits more robust performance on communication-sensing with varying number of RIS elements and different signal-to-noise ratios (SNRs). Full article

This paper presents an adaptive event-triggered nonsingular fast terminal sliding-mode control (AETSMC) framework for quadrotor unmanned aerial vehicles subject to aerodynamic disturbances, actuator loss of effectiveness (LOE) of up to 60%, and intermittent denial-of-service (DoS) attacks. First, a nonsingular fast terminal sliding-mode (NFTSM) surface is constructed using fractional powers of the tracking error rather than fractional-order derivatives. This design ensures finite-time convergence while avoiding the singularity associated with conventional terminal sliding-mode schemes. Second, a smooth positive-semidefinite barrier function (Smooth-PSBF) is incorporated into the adaptive gain law. The resulting law provides only the compensation required to maintain the prescribed bound, thereby limiting gain overestimation and chattering. Third, a dual-mode event-triggering mechanism combines an exponentially decaying threshold with a zero-order hold. A positive lower bound on the inter-event interval is derived from the closed-loop dynamics, which excludes Zeno behaviour. Simulations under matched conditions show that the proposed method reduces the pitch-channel root-mean-square error by 79.4% and the integral squared error by 95.8% relative to the first reproduced baseline. In a separate 15-s communication experiment sampled at 1 kHz, the controller generated 128 transmissions instead of 15,000 periodic updates, corresponding to a 99.15% reduction. These results indicate that the proposed framework can improve fault-tolerant tracking while reducing communication demand under intermittent DoS attacks. Full article

This study examines how gay-Mizrahi men in Israel navigate the communicative processes through which workplace subjectivities are constructed, negotiated, and legitimized. Mizrahiness refers to a Jewish ethno-cultural position associated with Middle Eastern and North African ancestry, historically shaped by unequal relations with Ashkenazi hegemony and intersecting class, geographic, cultural, and gendered hierarchies. Based on semi-structured interviews with self-identified gay-Mizrahi men across diverse occupational sectors, this study examines how sexuality, ethnicity and professionalism are read together in everyday organizational interactions. The findings reveal three strategic mechanisms: identity calibration, hyphenated subjectivity, and compensatory professionalism. Identity calibration refers to the ongoing tuning of identity visibility, timing, intensity, and communication. Hyphenated subjectivity captures the relational process through which gayness and Mizrahiness are not simply combined but continuously negotiated in relation to social expectations and organizational norms. Compensatory professionalism describes intensified investment in excellence, credentials and self-control to counter anticipated devaluation. These mechanisms show that organizational belonging is not a static outcome of diversity or inclusion but an advanced communicative achievement. Thus, this study contributes to workplace communication and Diversity, Equity and Inclusion (DEI) scholarship by illustrating how marked workers achieve professional legibility. We argue that DEI practice must move beyond visible categories of diversity towards affective and communicative dimensions through which inequality is reproduced. Full article

To explore the optimization effects of fixed aquatic water treatment materials combined with immunomodulatory agents on the ecosystem and farming efficiency of Litopenaeus vannamei in high-water-level ponds, this study established experimental ponds (with fixed aquatic water treatment materials and feed supplemented with chitosan oligosaccharides) and control ponds (no fixed water treatment materials applied, fed with basal feed only). Through a comparative trial over a complete farming cycle, the study systematically analyzed changes in plankton community structure and diversity, water physicochemical factors, shrimp growth performance, immune indicators, and muscle nutritional composition. The results showed that in the experimental group, diatoms (Ditylum brightwellii and Skeletonema) dominated the plankton community, while the density of harmful blue-green algae (Oscillatoria and Trichodesmium) significantly decreased, and planktonic animal diversity improved in the later stages. Among the water physicochemical indicators, the experimental group exhibited a 50% reduction in nitrite levels by the later stages, significantly higher than the 33.33% reduction in the control group. Total ammonia nitrogen levels remained lower than those in the control group, with a smaller increase in the later stages. Total phosphorus levels were significantly lower in the experimental group after 80 days, and the later-stage decline in chemical oxygen demand was 11.65% higher than that in the control group. Shrimp body weight increased significantly by 13.23%, while hepatosomatic index, musculosomatic index, and immune enzyme (acid phosphatase and total antioxidant substances) activity also improved markedly. The content of unsaturated fatty acids (linoleic acid and oleic acid) in the muscles significantly increased. The study demonstrated that the combined application of fixed aquatic water treatment materials and chitosan oligosaccharide preparations can optimize the farming water environment, enhance shrimp growth performance and quality, and provide technical support for the ecological cultivation of Litopenaeus vannamei. Full article

This exploratory randomized trial evaluated an eight-week combined isometric and elastic-resistance program in community-dwelling women aged 70 years or older. Forty-nine participants were randomized to exercise (EG; n = 24) or control (CG; n = 25). Twenty-two EG participants completed the intervention and follow-up; two had no post-intervention measurements because of scheduling conflicts. All randomized participants were included in the intention-to-treat analysis using 50 data sets generated by predictive mean matching and baseline-adjusted analysis of covariance. Compared with the CG, the EG showed lower body weight (adjusted mean difference [AMD], −0.45 kg), BMI (−0.19 kg/m²), 4 m gait time (−0.96 s), and five-repetition chair-stand time (−1.60 s), and higher skeletal muscle mass (0.38 kg), calf circumference (0.80 cm), and handgrip strength (1.01 kg). The corresponding primary 95% confidence intervals excluded zero, although the skeletal-muscle-mass interval narrowly included zero under conservative imputation. Differences in body fat percentage (−0.33 percentage points; 95% CI, −1.24 to 0.58) and tandem-stance time (0.79 s; 95% CI, −0.42 to 2.00) were inconclusive. These preliminary findings suggest that the program may improve selected body-composition and functional outcomes. Larger prospectively powered trials are required to confirm their magnitude, clinical relevance, and durability. Full article

Renewable energy and energy storage stations require frequent updates of monitoring and control logic across heterogeneous devices and changing operating strategies. This paper proposes a rule graph-based reference architecture that combines low-code logic configuration, graph–model semantic binding, and microservice-oriented functional decomposition. A component status matrix separates the target architecture from the implemented subset. The runnable subset comprises a minimal FastAPI backend, REST/WebSocket telemetry interfaces, an in-process queue, and stateful rule evaluators; gateway, authentication, external message bus, time-series database, visual editor, and industrial protocol services remain design-level elements. Beyond the original single-rule example, a priority-ordered multi-device rule is implemented for cooperative BESS dispatch, communication/topology blocking, low-SOC protection, frequency-based load shedding, backup request, and five-sample recovery release. Existing local network benchmarks are complemented by a 600-step software-in-the-loop trace with scripted telemetry fluctuations and communication quality faults and by 500 in-process ASGI timing samples at each of the four point levels. The trace produced no safety dispatch or protected device violations. P99 application path latency ranged from 1.1962 to 5.5287 ms, but one 75.3065 ms outlier exceeded a 50 ms reference deadline, demonstrating that the Windows/FastAPI path is not deterministic. No industrial controller, hardware-in-the-loop facility, field data, or engineer usability study was used. Accordingly, the paper makes no claim of industrial real-time readiness or measured development effort reduction. Full article

Machine learning and statistical classification methods are widely applied to microbiome data for diagnostic, prognostic, and phenotypic insights. However, the complex, multivariate nature of microbiome communities makes it difficult to assess the relative performance of these methods. Most comparisons rely on a small number of published datasets, without considering their underlying ecological properties or how these properties may, in turn, influence classification performance. We introduced a coenocline-based simulation framework to generate synthetic microbiome datasets that incorporate realistic ecological variation arising from species’ responses to host-associated gradients such as disease severity. To evaluate the ecological fidelity of these simulations, we compared synthetic datasets to five widely used real-world microbiome datasets: Cirrhosis, Colorectal Cancer (CRC), Type 2 Diabetes (Chinese and Women cohorts), and the Human Microbiome Project (HMP). Comparisons across α-diversity (species richness), β-diversity (species composition and turnover), and abundance distributions demonstrated that coenocline simulations closely recapitulate the key ecological structures of empirical data. Synthetic datasets exhibited similar richness and abundance patterns to disease-associated microbiomes, with realistic distributions of few dominant and many rare taxa. Moreover, community composition analyses (Bray–Curtis index) revealed that the simulated datasets captured natural levels of compositional dissimilarity among samples, spanning the same variability range observed in real data. When compared against 100 independently simulated datasets, the coenocline model consistently reproduced empirical ranges of species diversity, relative abundance, and between-group compositional differences (ANOSIM-R values), confirming the model’s robustness and reproducibility. This coenocline-based simulation framework provides a novel, flexible, and ecologically grounded approach for generating synthetic microbiome data with controlled complexity. By reproducing realistic ecological gradients and community structures, the framework supplies the controlled test beds needed for systematic future benchmarking of machine learning and statistical classification methods across diverse and biologically meaningful scenarios. In doing so, it will help bridge the gap between ecological realism and computational modeling, thereby supporting more reliable and generalizable inference from microbiome data. Full article

Background: To date, several studies have confirmed the fact that over 700 species of microbiota interacts with host, modulating immunity, controlling the homeostasis environment, and thus maintaining systemic condition. Dysbiosis in the subgingival biofilm can initiate chronic inflammation of the gingiva, potentially progressing to periodontitis. Advances in DNA sequencing analysis of the subgingival microbial community have shown that periodontal treatment causes a microbial shift in subgingival plaque, affecting the taxonomic composition (disease- and health-associated taxa). Yet, none of these have been investigated in Indonesia. Objective: The objective was to profile the composition of oral microbiome in Indonesian population with healthy, gingivitis, and periodontitis status. Further, we analyzed the subgingival bacterial alteration following the therapy in periodontitis group. Methods: Twelve subjects consisting of healthy, gingivitis, and periodontitis patients were included. Additionally, the periodontitis group was observed at baseline, 1-month, and 3-month. Subgingival dental plaque were sampled and 16S rRNA NGS analysis was performed. Alpha (Chao1, Shannon, and Simpson indices) and beta diversity (PCoA plots based on Bray–Curtis dissimilarity) were observed. Microbiota composition at the genus and species levels was analyzed. Results: No statistically significant differences (p > 0.05) were found for Chao1, Shannon, and Simpson indices amongst groups and in periodontitis patients across the observation. At the genus level, PCoA plots based on Bray–Curtis dissimilarity revealed that the clinical status accounted for 21.9% of the total variation (R² = 0.219, p = 0.197), while at the species level, it accounted for 19.8% (R²= 0.198, p = 0.281). Periodontitis samples across all timepoints showed no distinct clustering at either the genus 7.6% (R² = 0.076 p = 0.097) or species levels 9.7% (R² = 0.097 p = 0.995). Top five subgingival microbiota at the genus and species levels in all groups showed definite pattern of composition. Although no significant association was found (p > 0.05), it described that Veillonella parvula, Campylobacter gracilis, and Capnocytophaga granulosa were more abundant in healthy subjects than in gingivitis and periodontitis. Prevotella oris and Selenomonas noxia were less abundant in healthy subject than in gingivitis and periodontitis. In periodontitis subjects, Prevotella intermedia was increased by the therapy at 1 month and reduced again at 3 months. On the other hand, Capnocytophaga granulosa was increased by the therapy at 1 and 3 months. Hoylesella loescheii was reduced by the time. Porphyromonas gingivalis was reduced at 1 month and increased again at 3 months. Discussion: The result showed that the number of alpha diversity was notably higher in the gingivitis and periodontitis groups compared to health group, supporting a trend toward increased community richness and evenness in diseases states. The microbial richness and evenness remained relatively stable across the evaluated periods within periodontitis cohort. Oral microbial composition defines the periodontal status and disease. More abundance of Red Complex bacteria is associated with disease-associated condition. Pathogen re-colonization may occur 3 months after the therapy. Conclusions: These findings suggest that maintaining health-associated microbiome may be beneficial to the clinical status. Periodontal recall may be addressed from 1 to 3 months after the therapy to avoid bacterial re-colonization. Suppressing bacterial dysbiosis and regulating periodontal homeostasis are the main key in managing periodontal treatment. Full article

Corn stover (CS), as a major agricultural residue in Northeast China, suffers from inefficient anaerobic digestion (AD) due to its rigid lignocellulosic structure and the generation of inhibitory phenolic compounds during pretreatment. Alkaline hydrogen peroxide (AHP) disrupts lignocellulosic structures while generating methanogenesis-inhibiting phenolic compounds. Current pretreatments only resolve either lignocellulosic rigidity or phenolic toxicity, with no integrated method to mitigate both simultaneously. This work investigated a combined strategy of AHP pretreatment coupled with MnO₂ amendment to improve methane production from CS using laboratory-scale batch AD. Results demonstrated that 3% AHP pretreatment induced structural modifications and altered lignin-related functional groups, while the subsequent addition of 1.0 g MnO₂ significantly (p < 0.05) removed up to 28.4% of the generated total phenolic equivalents and alleviated volatile fatty acid (VFA) accumulation. The Mn-AHP group achieved the highest cumulative methane production of 449.28 ± 13.25 mL/g VS, representing a 14.6% increase compared to the control and a 3.24% improvement over the AHP-only group. Microbial analysis revealed increased relative abundance of acidogenic bacteria (e.g., Synergistota) and a compositional shift in the archaeal community toward a structure dominated by Methanobacterium and Methanothrix. These findings indicate that coupling AHP with MnO₂ is a promising approach to address the dual challenges of lignocellulosic recalcitrance and phenolic inhibition, providing a feasible pathway for agricultural waste valorization. Full article

Maglev trains are susceptible to various types of operational challenges, including track irregularities, load variations, and actuator faults. It is evident that these factors can compromise suspension performance and even pose a serious risk to operational safety. This paper proposes a prescribed performance event-triggered fault-tolerant control method for the electromagnetic suspension system of a maglev train subject to multiple constraints. A projection-based adaptive extended state observer is designed to estimate the unknown gain caused by actuator faults and load variations, as well as the external disturbance. In light of the disparity in upper and lower safety margins inherent to the suspension gap error, arising from track irregularities, an asymmetric prescribed performance function and an error transformation are devised to ensure that the gap tracking error perpetually complies with the asymmetric prescribed performance constraint. In addressing the issue of rapid variations in the suspension gap, the vertical velocity is also constrained through the implementation of prescribed performance, resulting in a joint constraint framework that encompasses both the gap tracking error and the vertical motion. A dynamic event-triggered mechanism has been incorporated into the backstepping design with a view to reducing unnecessary control updates under limited communication resources, while Zeno behavior has been excluded from the closed-loop system. Within this framework, a dynamic gain adjustment mechanism with an explicitly bounded rate of variation is further developed to achieve smoother gain adaptation. The uniform ultimate boundedness of all closed-loop signals is demonstrated through Lyapunov stability analysis under the prescribed multiple constraints. The efficacy of the proposed method is demonstrated through comparative simulation results. Full article