Abstract: Artificial intelligence is fast expanding in clinical research and medicinal development. In response, a considerable governance literature has arisen, characterised by ambitious theoretical frameworks but persisting gaps in practical implementation. This critical analysis assesses the underlying assumptions, organisational constraints, and institutional flaws that undermine responsible AI governance in healthcare and clinical research. The analysis combines findings from AI ethics, organisational governance, computational toxicology, clinical trial methodology, and patient safety science. The core thesis is that, despite significant agreement among governments, corporations, and academia on stated objectives, the responsible AI field has persistently failed to bridge the gap between normative goals and organisational realities. In clinical settings, this failure has direct consequences for patient safety. The analysis is structured around five interconnected critiques: the conceptual inadequacy of the performance-centric evaluation paradigm, which conflates statistical reliability with clinical safety; the inadequacy of explainability methods as substitutes for genuine accountability; the practical unimplementability of principled administrative frameworks in most healthcare research institutions; and the characterisation of regulatory fragmentation as a political economy. Drawing on a large body of research, the review suggests that solving the governance gap in clinical AI requires facing more fundamental assumptions than current studies acknowledges.

Abstract: The transition toward sustainable biorefinery processes requires efficient strategies for lignocellulosic biomass deconstruction and valorization. In this study, an integrated enzymatic system combining fungal holocellulases and laccases with a bacterial galactolipase was developed and evaluated. The consortium, composed of Trametes hirsuta GMA-01, Mycothermus thermophilus CBS 619.91, and Burkholderia lata BL02, was produced using agro-industrial substrates and applied to the hydrolysis of different lignocellulosic biomasses. The incorporation of galactolipase activity enhanced saccharification yields for leaf-derived substrates, reaching up to 292.0 mg/g for spinach leaves and 236.0 mg/g for corn straw, compared to fungal systems alone. This effect is associated with the selective hydrolysis of membrane-associated galactolipids, improving substrate accessibility to holocellulolytic enzymes. Proteomic analysis and structural modeling identified the BL02 enzyme as a versatile ester hydrolase with features compatible with accommodating bulky polar substrates. In addition, the enzyme catalyzed the synthesis of sugar fatty acid esters with conversion yields above 50% for glucose and xylose in binary solvent systems. These findings support the role of galactolipases as accessory enzymes and highlight their potential application in integrated and sustainable biorefinery processes.

Abstract: Tropical lignocellulosic residues offer regionally abundant feedstocks for lignin-containing nanocellulose composites, but their value cannot be inferred from biomass origin or bulk lignin content alone. This review reframes the field as an interphase engineering problem, distinguishing between residual-lignin nanofibrils, redeposited-lignin systems, lignin-nanoparticle assemblies, compatibilized thermoplastic hybrids, and all-lignocellulosic sheets. The evidence is weighted according to feedstock geography, lignin state, nanocellulose morphology, moisture history, shaping route, and application-relevant testing. The synthesis indicates that tropicality matters through ash, extractives, contamination, water retention, storage stability, and processing logistics. Mill-concentrated residues, especially oil palm streams and sugarcane bagasse, offer the most credible near-term platforms because wet preprocessing and fractionation can be integrated locally. Decentralized residues, including pineapple leaf fiber and banana pseudostem, remain promising only when stabilization and contamination control are solved near the source. Finely distributed lignin often enhances UV shielding, antioxidant response, oil resistance, and selective wetting, whereas coarse or redeposited lignin often compromises fibrillation, transparency, and interphase continuity. Packaging layers, paper-like structures, coatings, and selected porous media emerge as high-confidence product windows; thermoplastics are medium-confidence, and biomedical, additive-manufacturing, and nano-reactor claims remain conditional.

Abstract: Terminal glial cells (TGCs) are integral components of cutaneous end-organ com-plexes (CEOCs) and have traditionally been regarded as structural and trophic elements. However, increasing evidence suggests their involvement in mechanosensation and mechanotransduction. This study aimed to investigate the expression of mechanosensitive ion channel-related proteins in TGCs and axons of human Meissner and Pacinian cor-puscles from glabrous skin at different anatomical sites. Using immunohistochemistry and immunofluorescence, we analysed the distri-bution of ASICs, ENaC subunits, PIEZO channels, and TRP family members. Axonal terminals showed widespread expression of these proteins, including PIEZO1/2, ASIC2, TRPC6, and TRPV4, consistent with their role in mechanotransduction. In contrast, TGCs displayed a more restricted and heterogeneous profile. ASIC2 and TRPV4 were con-sistently detected in Meissner corpuscles, whereas PIEZO1/2 and TRPA1 showed site-dependent expression. In Pacinian corpuscles, TGCs were positive for ASIC2, PIE-ZO2, TRPA1, and TRPV4. Notably, TRPA1 expression in TGCs is reported here for the first time. These findings support the idea that TGCs may modulate mechanosensory input, although their functional role remains to be elucidated.

Abstract: During the continuous casting of high-titanium steel, traditional fluorine-containing mold fluxes are prone to causing fluoride contamination, equipment corrosion, and intensified slag-metal interface reactions. There is an urgent need to develop highly adaptable fluorine-free mold flux systems. In this study, titanium-containing blast furnace slag was used as the primary base material, while borax, soda ash, and witherite were selected as fluoride-substituting mineral raw materials. The effects of these mineral raw materials on the melting properties, crystallization behavior, crystalline phases, and microstructure of fluorine-free mold fluxes were systematically investigated, and an optimized mold flux design suitable for continuous casting of high-titanium steel was further developed. The results indicate that borax significantly reduces the melting temperature and viscosity and markedly suppresses the growth of crystalline phases such as calcium borosilicate, nepheline, and perovskite by weakening the polymerization degree of the silicate network, thereby substantially decreasing the crystallization ability of the mold flux. Soda ash primarily acts as a strong fluxing and network-depolymerizing agent, promoting the formation of low-polymerized structural units. It also enhances the tendency toward ordered atomic arrangement, thereby markedly increasing nepheline precipitation and the overall crystallization ratio. Witherite exerts a relatively mild effect on slag structure and phase evolution; its moderate addition helps synergistically reduce the melting point, viscosity, and crystallization ratio, thereby supporting performance stability. The optimized fluorine-free mold flux, designed on the basis of these findings, maintains a suitable initial crystallization temperature and critical crystallization cooling rate while exhibiting lower melting temperature, viscosity, and crystallization ratio than conventional fluorine-bearing flux. Moreover, the introduction of TiO2 reduces the chemical potential difference between Ti in the molten steel and the fluorine-free mold flux, thereby slowing down the rate of slag-metal interface reactions and improving compositional stability. The research results provide a theoretical basis for the industrial design of environmentally friendly mold fluxes for high-titanium steel and for improving billet quality.

Abstract: The outermost region of the Solar System is called Oort cloud which is the Solar systems’ reservoir of long-period comets that extends to distances up to 200 000 au from the Sun. Long-period comets can be injected towards the inner Solar System due to galactic tides and passing stars. While galactic tides are effective on long time scales, perturbations of stellar flybys are short-term effects that have not only occurred in the past. Gaia observations confirmed that the solar system will experience a close flyby of the K-type star Gliese 710 in about 1.3 Myrs. This star will probably pass at a distance of about 10500 au to the Sun. When crossing the Oort cloud this 0.6 solar mass star will perturb the long-period comets especially those objects that are close to Gliese 710’s trajectory. In this numerical investigation, we use our recently developed GPU based N-body code GANBISS and study the orbits of some hundred million test-comets for the time of the stellar flyby which takes about 64000 years. The simulations show that the stellar passage generates cometary streams - which either transport comets into the inner solar system or scatter a huge amount of comets into interstellar space.

Abstract: Sulforaphane (SFN), a bioactive compound sourced from cruciferous vegetables, offers significant antioxidant and anti-inflammatory benefits yet, its stability in animal feed is a challenge. Nanotechnology-based encapsulation, specifically ionic gelation, has demonstrated efficacy in improving the stability and bioavailability of SFN. This review examines the application of natural polymers such as chitosan and alginate in ionic gelation for the encapsulation of SFN. It also discusses how these polymers can prevent SFN from degrading while traversing the digestive tract. Encapsulated SFN has shown enhanced nutritional absorption, elevated immune responses, and reduced oxidative stress in animals. However, challenges persist in identifying optimal methods for encapsulating various species, including enhancing encapsulation effectiveness, particle size, and controlled release mechanisms. Additionally, regulatory concerns regarding the safety and environmental impacts of nanoparticles in feed must be addressed. Future research should focus on improving encapsulation techniques and ensuring the safe application of SFN-loaded nanocarriers in livestock feed.

Abstract: Cardiovascular disease is the leading cause of death in women, yet prevention and management have historically relied on male-centered models. Sex and gender critically influence risk, clinical presentation, and outcomes. Depression, anxiety, and psychosocial stress, more prevalent in women, act as key amplifiers of cardiovascular risk. We conducted a clinically oriented narrative review based on a broad, non-systematic search of major databases, integrating evidence selected for relevance and methodological robustness to clarify biological and psychosocial mechanisms linking mental health and cardiovascular disease in women. Affective disorders and stress contribute to cardiovascular risk through interconnected pathways, including hormonal fluctuations, autonomic and neuroendocrine dysregulation, inflammation, endothelial dysfunction, and heightened platelet reactivity. These mechanisms interact with gender-related exposures such as caregiving burden, occupational stress, and interpersonal violence. Stress-related phenotypes, including mental stress, induced ischemia and takotsubo syndrome, exemplify the heart-brain axis and its clinical implications. Incorporating mental health into cardiovascular risk assessment is essential for precision prevention in women. A women-centered approach should include systematic psychosocial evaluation, multidisciplinary care, and tailored strategies to improve risk control, adherence, and outcomes.

Abstract: Silver nanoparticles (AgNPs) have attracted significant attention due to their remarkable antimicrobial, antibacterial, and catalytic properties, enabling widespread applications in consumer products, biomedical fields, and environmental systems. Conventional chemical and physical synthesis routes, however, often involve toxic reagents and generate hazardous byproducts, raising environmental and health concerns. In response, green synthesis approaches employing biological entities such as plant extracts, bacteria, and fungi have emerged as sustainable and eco-friendly alternatives. These methods utilize natural reducing and stabilizing agents, minimizing toxicity while enhancing biocompatibility. This review comprehensively examines green-mediated synthesis strategies for AgNP-based composites, highlighting their physicochemical properties and functional performance. Additionally, the potential toxicity and environmental implications of AgNPs are critically discussed. Particular emphasis is placed on their applications in environmental remediation, including water purification, pollutant degradation, and antimicrobial treatments. Overall, green-synthesized AgNP composites offer a promising pathway toward sustainable nanotechnology for environmental pollution control.

Abstract: The absence of an indigenous pure chicken breed in Nigeria has a serious negative impact on both the global and domestic economy, as well as per Capita protein consumption and income of their farmers. Moreso the poultry global gene pool is about to loss some fitness traits, due to the fact that they it was raised from very few population. With only 3 poultry breeding companies namely Aviagen, Hendrix and Cobb vantress principally supplying world exotic chicken the importance of a new chicken breed originating from an entirely different gene pool, like Nigerian chicken gene population can never be over emphasized. It is therefore pertinent that the Nigeria's rich natural resources (local chicken) be genetically modified to a Pure Elite Layer Breed to meet FAO 's prediction of Nigeria's potential for global food security Interestingly FAO has predicted the significant role of Nigerian livestock resources in global animal protein insecurity FAO (2022). Responding to this global call Nigerian local genetic breeders at the University of Nigeria Nsukka, in the past decade began selective breeding of the Nigerian local chickens through estimation of genetic parameters of growth and reproductive traits among the inbred chicken ( Ohaghenyi et al 2025, Ohaghenyi et al 2021, Nwankwo 2023, Okoye 2023, Ohagenyi and Okochi 2023, Ohaghenyi and Ezeugwu 2021.). Moreover (Ogbu et al 2019, Agbo et al 2 Corollary the comparative study of the inbred chicken and layer chicken will both provide a concrete information on the genetic progress made so far among the inbred chicken. The objective of this study is the genetic evaluation of reproductive traits of layer birds and Awka Elite chicken (genetically improved inbred chickens) raised in South Eastern Nigeria. The foundation stocks was grouped into 2 categories the layer birds and the genetically improved inbred chicken. They where fed with stater crumbs from day 1 to 8 weeks.l, and they where fed with finisher feeds from 8 to 16 weeks. And we continued with layer mash. Eggs were collected daily with egg crates and stored in a cool and airy room . Parameters that was measured include Reoroductive Traits and Egg internal Qualities The experiment was carried out using Completely Randomized Design (CRD) with the statistical mode] as follows; Xij= μ + Ti + Σij A one-way analysis of variance (ANOVA) was conducted to determine whether there were significant differences in Reproductive Traits and Egg internal Quality among the different chicken genotypes. The analysis compared the mean values of the experimental groups. It is evident from the findings of this study that the Awka Elite Inbred chicken was superior to the Exotic Layer in Albumen weight and Haugh unit. One Sire family (H62) of the Awka was superior to Exotic egg, however the average egg weight of EXOTIC eggs was 1.1g heavier, though not significant (p>0.05).The superior performance of the H62 family implies more homogeneous meat genes as a result of mating of related ancestors over several. Hence more suitable for development of broiler lines.The INBRED achieved similar weight with: more albumen (+1.4g); Larger yolk (+1.0g); Heavier shell (+0.3g). This suggests Awka Elite eggs may be more nutrient-dense per gram. The external egg quality namely Shell thickness and weight were nearly identical. Egg shape (length/width) showed minor variation, which was not meaningful. This research concludes that Selective breeding of local chickens, which expedited significant gains in performance,(growth and egg) traits has resulted in the origin of a new species, known as the Awka Elite Breed. This research breakthrough suggests that Nigeria now has the potential to develop elite poultry, hence reducing reliance on imported Parent stock. Partnership: It is recommended that Partnership from the US, UK, China and Africa to enable the Researchers supply this superior Pure chicken breed to Commercial and Rural farmers all over the world. .018, Udeh et al 2024 ) selectively bred the heavy ecotype chicken.

Abstract: Tropical forests are facing escalating deforestation, while forest degradation, driven by a complex interplay of human-induced factors, emerges as an additional and compounding threat. In this context, regulated selective logging persists as an alternative to conciliate forest protection and economic development. This study synthesizes current knowledge on the impacts of logging, focusing on research trends, geographic distribution, ecological topics, and key variables like logging intensity, time since logging, and number of logging cycles. Since the 1970s, 641 papers listed on the Scopus platform have demonstrated a sharp increase in publication activity over the past five years, followed by a tendency toward stabilization. Papers were concentrated in Brazil and Malaysia, with few papers coming from other countries, particularly from Africa. Notably, 47% of the studies did not report logging intensity, and one-third focused almost exclusively on its impacts on forest physical structure, damage, or biomass—leaving a wide range of other topics largely unexplored until 2022. We refer to 13 topics with less than 20 studies in total, such as nutrient cycling, non-timber forest products, biological invasion, and key biological taxa. Herbs, epiphytes, fish and amphibians were among the least investigated taxa across the regions. Furthermore, when controlling variables like region and logging intensity, most ecological topics had fewer than five dedicated studies. Research remains largely restricted to similar scenarios: first-cycle logging in old-growth forests, leaving substantial knowledge gaps. As logging operations are expected to increase, we argue for a (1) mandatory long-term monitoring in logging regulations; (2) public access to monitoring data, reports and information related to regulated logging; (3) a global platform to exchange experience as long-term monitoring, better practices, silvicultural approaches and sustainability assessment; (4) alignment among regulatory and certification agencies on sustainability standards; (5) capacity building initiatives; and (6) long-term experiments devoted to logging sustainability and better practices.

Abstract: Human language continuously generates patterned mechanical vibrations, yet the cellular consequences of such structured sound remain largely unexplored. Here, we investigate whether acoustic vibration with different degrees of temporal and spectral organization modulates actin cable architecture and polarity in the non auditory eukaryote Saccharomyces cerevisiae. Using a direct contact stimulation setup, yeast cells expressing ABP140- GFP were exposed to sustained tonal sound, broadband white noise, or brief consonant like acoustic bursts designed to isolate speech relevant temporal structures without semantic content. Sustained tonal stimulation, characterized by rhythmic continuity and harmonic coherence similar to vowel like components of speech, increased ABP140- GFP signal intensity,actin branching and actin length and significantly enhanced shmoo formation. In contrast, broadband noise disrupted actin organization and suppressed shmooing, while transient consonant like bursts produced no measurable structural effects. These results indicate that language related acoustic structure, specifically sustained and coherent mechanical vibration, can modulate cytoskeletal organization in yeast, supporting the view of sound and speech as biologically active mechanical inputs rather than purely communicative signals.

Abstract: Eryngium foetidum is classified as an Unconventional Food Plant with socio-economic importance in the Amazon. Its propagation units exhibit low and irregular germination due to dormancy, although the type of dormancy remains unclear. This study aimed to evaluate methods to overcome dormancy and promote germination in E. foetidum propagation units. Treatments included chemical scarification with sulfuric acid (1, 2, and 3 min), mechanical scarification with sandpaper, immersion in room-temperature water and hot water, and a control treatment. Germination percentage, hard and dead propagation units, normal seedlings, first count, germination speed index (GSI), mean germination time (MGT), and relative frequency were evaluated. Data were analyzed using a heat map and a correlation network. The results revealed the formation of two distinct groups. Group I, consisting of chemical scarification treatments, promoted higher germination percentages and GSI, lower MGT, a significant reduction in hard propagation units, and greater germination uniformity, likely due to partial removal of the seed coat. The correlation network showed a strong negative association between hard units and germination, GSI, and first count, reinforcing the role of physical restriction as a determinant of dormancy. Chemical scarification with sulfuric acid was the most effective method for overcoming dormancy in E. foetidum.

Abstract: Transitioning to a circular bioeconomy in agro-environmental systems requires decision-support approaches able to address interdependencies across water, energy, food, and ecosystems (WEFE), especially in Mediterranean regions affected by climate variability, water scarcity, land degradation, and fragmented governance. However, the practical operationalization of the WEFE Nexus remains limited by methodological constraints and insufficient integration of dynamic analysis. This study presents an AI-enabled decision-support tool designed to support the implementation of circular bioeconomy solutions within the WEFE Nexus. The framework integrates participatory multi-criteria assessment, compensation mechanisms, and artificial intelligence-based scenario analysis within the NECADA digital twin environment, enabling the assessment of elements under uncertainty. Developed and applied within the “Ensuring fair NEXUS transition for climate change adaptation and sustainable development implementation based on coupled nature-based systems and bioeconomy (SureNexus)” project, the tool was used to assess two circular bioeconomy solutions, biochar and agroforestry, across Mediterranean agro-environmental contexts. Results show complementary performance profiles: biochar provides targeted benefits for soil restoration, water regulation, and climate mitigation, whereas agroforestry generates broader system-level effects that enhance ecosystem services, resilience, and long-term sustainability. These findings highlight the value of context-specific solution portfolios and show that AI-enabled WEFE tools can support evidence-based policy and planning for sustainability transitions.

Abstract: Biological cognition depends on learning structured representations in ambiguous environments. Computational models of structure learning typically frame this as an inference problem, but often overlook the temporally extended dynamics that shape learning trajectories under ambiguity. In this paper, we reframe structure learning as an emergent consequence of constraint-based dynamics. Informed by a literature on the role of constraints in complex biological systems, we develop a constraint-based approach to computational cognitive modelling and provide a proof-of-concept model. The model consists of an ensemble of components, each comprising an individual learning process, whose internal updates are locally constrained by both external observations and system-level relational constraints. This is formalised using Bayesian probability as a description of constraint satisfaction rather than epistemic inference. Representational structure is not encoded directly in the model equations but emerges over time through the interaction, stabilisation, and elimination of components under these constraints. Through a series of simulations in environments with varying degrees of ambiguity, we demonstrate that the model reliably differentiates the observation space into stable representational categories. We further analyse how global parameters controlling internal constraint and initial component precision shape learning trajectories and long-term behavioural alignment with the environment. We discuss the formal relationship between the present approach and Bayesian inference accounts, and argue that a constraint-based approach offers a conceptually distinct foundation for relating computational models to biological systems.

Abstract: This paper proposes a novel speed controller design for a brushless DC motor (BLDCM) under field-oriented control (FOC). The designed novel speed controller combines decision tree theory (DTT) and sliding mode theory (SMT). First, the regression algorithm of the classification and regression tree (CART) within decision tree theory is utilized to divide the speed error between the BLDCM's speed command and actual speed into 10 intervals. Based on this, three parameters of the existing exponential reaching law sliding mode controller (ERLSMC)—the sliding mode dynamic trajectory control gain, the exponential reaching gain, and the constant speed reaching gain—are configured. Next, the mean squared error (MSE) of each node after splitting is calculated to identify the root node. According to the selected split variable and splitting point, the data is divided into two subsets, and this process is repeated for each child node. Consequently, during the operation of the BLDCM, appropriate adjustments for the three gains can be provided to the sliding mode speed controller. Subsequently, a new sliding mode dynamic trajectory control gain is recalculated based on the rate of change of the speed error. This allows the overshoot in the system's speed response, caused by adopting the exponential reaching law (ERL), to be improved under different operating conditions through the modulation of its three gains. It also enables the speed response of the BLDCM drive system to rapidly track the speed command under various operating conditions. Therefore, the proposed control law involves no complex computations and does not require a massive amount of training data, making it easy to implement. Finally, Matlab/Simulink simulation software is used to simulate the application of the proposed control law to the BLDCM drive system. Its control performance is compared with sliding mode controllers (SMCs) utilizing three different reaching laws: the constant speed reaching law (CSRL), the ERL, and the extension theory combined with exponential reaching law (ETERL). The simulation results demonstrate that the proposed novel speed controller outperforms the SMCs with the other three reaching laws in terms of both speed command tracking and load regulation response.

Abstract: The generation of synthetic seismic accelerograms is a critical problem in earth- quake engineering, where the scarcity of strong-motion records, particularly for high-magnitude and near-fault scenarios, limits the reliability of structural analyses and probabilistic seismic hazard assessments. This paper proposes a wavelet-decomposed conditional Generative Adversarial Network (WD-cGAN) for the synthesis of seismic accelerograms that faithfully reproduce the phys- ical and statistical properties of real ground-motion records. Unlike prior GAN-based approaches that rely on Fourier-domain decomposition, the pro- posed architecture decomposes each training signal into N wavelet sub-bands (experimentally N ∈ {5, 6}) using the Daubechies-4 (db4) discrete wavelet transform (DWT), assigning each sub-band to a dedicated discriminator. A novel energy-based weighting scheme αi modulates the relative contribution of each discriminator to the total generator loss, ensuring that physically dominant, low-frequency bands, which carry the bulk of seismic energy, receive proportionally higher training emphasis. Seismic moment magnitude Mw serves as the primary conditioning variable, enabling targeted synthesis for specific hazard scenarios. The model is implemented in Python using PyTorch and trained on accelerograms drawn from the Italian INGV/ITACA v4.0 archive. Qualitative evaluation confirms that the proposed wavelet-domain multi-discriminator scheme improves the realism and physical consistency of synthetic accelerograms relative to a single-discriminator baseline; full quantitative validation on a larger corpus is identified as the principal avenue for future work.

Abstract: Anthropic’s April 2026 Claude Mythos Preview release established a new operational category of frontier AI systems—Mythos-class—whose capability profile (extended-context reasoning over codebases, recursive self-correction, native system-tool integration, and agentic scaffolding at deployable scale) renders the dominant AI safety paradigms insufficient as sole controls. Reinforcement learning from human feedback, post-generation output filtering, contractual access vetting, and human-in-the-loop supervision were each calibrated to a generation of systems that did not exhibit autonomous cyber capability at the levels Mythos-class systems now demonstrate, and each is insufficient as a sole control against the new category under the threat assumptions specified here. This paper develops a defense-in-depth reference architecture for detecting and mitigating Mythos-class capability across enterprise and federal deployment surfaces. Detection is structured as a three-tier framework spanning pre-deployment evaluation, deployment-time access and telemetry, and runtime behavioral signatures. Mitigation is structured as four concentric layers: governance, cryptographic enforcement, architectural isolation, and operational monitoring. The cryptographic enforcement layer specifies an authority-binding architecture using post-quantum-attested provenance to bind output release to a verifiable authority chain. The architecture is mapped to the NIST AI Risk Management Framework, the NIST Cybersecurity Framework (CSF) 2.0, and the CISA Zero Trust Maturity Model, and is demonstrated against three application cases: post-quantum cryptography migration, federal AI supply-chain assurance, and critical-infrastructure operational technology defense. Limitations and a research agenda for empirical calibration are stated explicitly.

Abstract: We address a constructive fractional Lyapunov direct method for Caputo-type incommensurate non-autonomous fractional order systems whenever orders lie in (0,1]. We prove some new fractional Lyapunov theorems by using new ideas of fractional generalized Gronwall inequality and establish higher versions of Lyapunov theorems that give sufficient conditions to predict stability dynamics of equilibrium points of many such systems. We demonstrate the new significance of such a method with five mathematical examples in stability theory.

Abstract: An optimized method of triclosan MIPs using a design of experiments (DOE) strategy was developed. The concentrations of methacrylic acid (MAA, monomer), 2-hydroxyethyl methacrylate (HEMA, co-monomer), and acetonitrile (ACN, solvent) were chosen as the critical parameters for the preparation process since they affect imprinting efficacy, morphological structure, and release profile of the material. A Box-Behnken design was utilized for the evaluation of how these factors influence the imprinting factor (IF). The optimized formulation revealed proper IF value indicating efficient molecular recognition. FTIR analysis validated the presence of acrylate-based bonds in the network structure. In addition, SEM images indicated a porous and aggregated structure of MIPs, which facilitated the accessibility of imprinted cavities. Release kinetics revealed two-phase profiles characterized by a moderate initial stage followed by sustained release up to 48 h. The Korsmeyer-Peppas model represented a better correlation (R² = 0.9754) compared to other kinetic models, implying complex diffusion-controlled release processes. Finally, MD simulations confirmed the experimental findings since MAA exhibited higher binding frequencies with triclosan than HEMA, proving its dominant role in molecular recognition.