Search Results (703)

Filled elastomers often exhibit a low-frequency power-law storage modulus (G-prime), yet quantitative links between molecular interfacial structure and macroscopic reinforcement remain unresolved. This gap is addressed using a hierarchical multiscale framework that integrates coarse-grained molecular dynamics (MD) and dynamic mechanical analysis (DMA). Overall, MD contributes transferable structural descriptors rather than direct macro-rheology prediction. MD simulations yield a bound-layer scaling relation for chain length $N=50$ in coarse-grained simulations serving as a structural probe. For EPDM master curves, the single-phase fractional Maxwell model is statistically preferred (Delta AICc > 147, n = 56), reflecting limited statistical power; larger datasets (e.g., PC/ABS, n = 952) favor the dual-phase formulation. For cross-scale prediction, an MD-derived effective-volume-fraction baseline (MAPE = 54.1%) provides a structural prior; the regime-partitioned bridge model absorbs relaxation physics not resolved at the MD scale, reducing error to 7.3% (blocked-CV MAPE = 9.5%, with a 2.3% fold-to-fold spread). Linear-viscoelastic constraints improve nonlinear PTT calibration, reducing die-swell error by 87%. Full article

This study evaluated protein hydrolysates from fish collagen (Col) and sheep keratin (Ker) as potential biostimulants in the hydro-priming of coriander (Coriandrum sativum L.) seeds. Seeds treated with low, non-nutritional doses of Col (0.5%) and Ker (1%) were compared with non-primed (C) and water-primed (H) controls under optimal conditions and after high-temperature stress (35 °C, 9 days). After stress removal, H-Col and H-Ker seeds achieved ~90% germination, whereas H and C reached 78% and 60%, respectively, confirming improved seed quality and post-stress recovery. Seedlings from Col- and Ker-treated seeds showed enhanced growth, higher biomass, and increased chlorophyll and precursor content. High-temperature stress also acted as a priming factor, modifying elemental profiles and stimulating carotenoid antioxidant synthesis. ATR–FTIR analyses indicated changes in cell wall composition and protein structure, particularly in the H-Ker variant. The results demonstrate that collagen and keratin hydrolysates, as industrial by-products, possess strong phytobiostimulatory potential and can be applied in sustainable strategies to improve seed quality and plant stress resilience. Full article

This study investigated the α-glucosidase inhibitory potential of enzymatic/alkaline treatments from Palmaria palmata using different proteases and pairwise combinations thereof. Treatments prepared with Alcalase^®, Flavourzyme^®, and Formea^® Prime, alone or in combination, were evaluated for dose-dependent inhibitory activity. Alcalase^®-derived treatments exhibited the highest α-glucosidase inhibition, achieving an IC₅₀ of 2.48 mg·mL⁻¹, outperforming other treatments and combinations. Membrane fractionation of the Alcalase^®-derived treatment into >5 kDa, 3–5 kDa, 1–3 kDa, and <1 kDa fractions revealed a size-dependent trend, with the <1 kDa fraction showing the strongest inhibition (IC₅₀ of 1.94 mg·mL⁻¹). Three peptides, RADIPFRRA, DGIAEAWLG, and FWSQIFGVAF, from the <1 kDa fraction were identified as potential α-glucosidase inhibitors using the BIOPEP-UWM database and were further selected based on a Peptide Ranker score above 0.6 for in silico docking analyses. Docking revealed distinct binding modes: RADIPFRRA and DGIAEAWLG occupied the catalytic cleft, interacting with key residues (Asp518, Asp616, Trp481, Trp613) consistent with competitive inhibition, whereas FWSQIFGVAF bound to a peripheral site, suggesting potential allosteric modulation. Physicochemical analysis further highlighted differences in charge and isoelectric point correlating with their binding behavior. Together, these findings demonstrate that low-molecular-weight peptides derived from P. palmata proteins, particularly those generated by Alcalase^®, possess significant α-glucosidase inhibitory activity, and provide structural insights for the rational design of peptide-based modulators of carbohydrate metabolism. Full article

In the current context of environmental sustainability and reduced agricultural inputs, biostimulants represent one of the most efficient, eco-friendly and innovative strategies to preserve plants from biotic and abiotic stresses and to ensure sustainable agriculture. Ranging from benefic microorganisms, seaweed extracts, and humic acids to complex carbohydrates such as polysaccharides and oligosaccharides, these biostimulants are able to increase plant growth, photosynthetic efficiency, root development and nutrient uptake when they are applied during seed priming as foliar sprays or as liquid and solid soil amendments. The mechanisms underlying their effective action on plants are mainly related to the enhancement of antioxidant defenses and the regulation of hormonal pathways, particularly auxin homeostasis and transport. Several studies reported the relevance of biostimulant application in promoting root growth. In plants, roots play crucial roles, performing a variety of functions such as nutrients and water uptake, mediating stress perception and adaptation, influencing the rhizosphere microbiome, and providing structural support. The effectiveness and perception of polysaccharide-based biostimulants (PBs) are highly dependent on crucial factors, including the degree of depolymerization and the chemical modifications such as acetylation, methylation, sulfation, and oxidation. Furthermore, not all receptors and co-receptors involved in the recognition of PBs have yet been identified. However, there remain many gaps in our understanding regarding the interaction between biostimulants and roots, which is still far from fully elucidated. For these reasons, the present review provides a comprehensive overview of current research on biostimulants–root interactions, with a particular focus on polysaccharide-based biostimulants. It highlights the mechanisms involved in their recognition by plants roots, from perception to response, and the subsequent signaling cascades and the molecular pathways activated, with special emphasis on existing knowledge gaps and future research perspectives. Full article

Electrophysiology, mechanobiology, and the study of soft matter within cells demonstrate increasing amounts of evidence that neuronal signaling arises from interactions between membrane potential, force, and phase. Herein, we have attempted to collect and organize the evidence for each of these areas of study into an approximate structure called the electromechanical connectome: a three-way state–space (membrane potentials, nanoscale mechanical forces, and cytoplasmic rheology, including phase-separated liquid–liquid droplets) where membrane potentials, nanoscale mechanical forces, and cytoplasmic rheology, and phase-separated liquid–liquid droplets are likely to influence one another, influencing synaptic processing, plasticity and network stability. We will also attempt to illustrate the following: how changes in electrostatic fields can be used to alter the arrangement of lipids, hydration, and dielectric microdomains, and the contact geometry between organelles and activity dependent transcription; how mechanical dynamics associated with spines, axons, and the active zone of synapses may be used to modify the energy landscape of channels, the docking and priming of vesicles, and the transport of cytoskeletons; and how viscosity corridors, along with phase-separated micro-reactors, can be used to regulate the kinetics of signaling, molecular trafficking and metabolic processes in local environments. With these connections in mind, we will propose a multiphysical attractor model in which cognition is the result of navigating through metastable manifolds, while neurodegenerative disease may be a result of the progressive loss of electromechanical coherence, phase boundary control and energetic flexibility. Finally, we will present testable hypotheses and use AI-enabled digital twin methods to potentially quantify the early deformation of manifolds and provide precision biomarkers and therapeutic options. Full article

Let p be a prime with $p\notin \{2,5\}$ and let $q=p^m$. This paper studies cyclic and self-orthogonal linear codes of length n over the finite local non-Frobenius ring $R_{p,u,v}={\mathbb{F}}_q+u{\mathbb{F}}_q+v{\mathbb{F}}_q, u^2=v^2=uv=vu=0.$ We define an ${\mathbb{F}}_q$-linear Gray map ${\pi }_n:R_{p,u,v}^n\to {\mathbb{F}}_q^{6n}$ and investigate the structural properties of Gray images of cyclic codes under this map. It is shown that ${\pi }_n$ preserves self-orthogonality and, when $gcd(n,p)=1$, transforms any cyclic code over $R_{p,u,v}$ into a quasi-cyclic code over ${\mathbb{F}}_q$ of length $6n$ with index dividing 6. Moreover, we completely characterize the possible quasi-cyclic indices of the Gray images, proving that only the values $l\in \{1,3,6\}$ can occur, and we establish necessary and sufficient conditions for each case in terms of the generators of the associated cyclic code. Several explicit examples are provided to illustrate the theoretical results and the resulting quasi-cyclic structures. Full article

Physical-layer security (PLS) provides an information-theoretic framework for securing wireless communications by exploiting channel and signal-structure asymmetries, thereby avoiding reliance on computational hardness assumptions. Within this setting, lattice codes and their algebraic constructions play a central role in achieving secrecy over Gaussian and fading wiretap channels. This article offers a comprehensive survey of lattice-based wiretap coding, covering foundational concepts in algebraic number theory, Construction A over number fields, and the structure of modular and unimodular lattice families. We review key secrecy metrics, including secrecy gain, flatness factor, and equivocation, and consolidate classical and recent results to provide a unified perspective that links wireless-channel models with their underlying algebraic lattice structures. In addition, we review a newly proposed family of p-modular lattices in Khodaiemehr, H., 2018 constructed from cyclotomic fields $\mathbb{Q}\left({\zeta }_p\right)$ for primes $p\equiv 1\left(\mathrm{mod}4\right)$ via a generalized Construction A framework. We characterize their algebraic and geometric properties and establish a non-existence theorem showing that such constructions cannot be extended to prime-power cyclotomic fields $\mathbb{Q}\left({\zeta }_{p^n}\right)$ with $n>1$. Finally, motivated by the fact that these p-modular lattices naturally yield mixed-signature structures for which classical theta series diverge, we integrate recent advances on indefinite theta series and modular completions. Drawing on Vignéras’ differential framework and generalized error functions, we outline how modularly completed indefinite theta series provide a principled analytic foundation for defining secrecy-relevant quantities in the indefinite setting. Overall, this work serves both as a survey of algebraic lattice techniques for PLS and as a source of new design insights for secure wireless communication systems. Full article

All rings considered are commutative with identity, and all modules are assumed to be unital. In this paper, we study R-modules in which every quasi-primary submodule is also primary; we refer to such modules as satisfying condition (*). We present several structural properties of these modules and investigate when the direct sum of two modules $M_1$ and $M_2$ inherits condition (*). In addition, we focus on prime ideals P of a ring R with the property that any P-quasi-primary submodule of an R-module M is automatically P-primary. Prime ideals exhibiting this behaviour are introduced as weak $sM$-prime ideals relative to M. Our results provide a framework for understanding the interaction between the quasi-primary structure of modules and the prime spectrum of the underlying ring. Full article

Phytohormones are key regulators of specialized metabolism, yet hormone-specific and time-dependent phenolic reprogramming in woody species remains poorly resolved. This study evaluated the phenolic responses of juvenile Quercus sideroxyla leaves grown under controlled greenhouse conditions to salicylic acid (SA), jasmonic acid (JA), and abscisic acid (ABA) using a pulse-based elicitation design combined with targeted metabolite profiling. Aqueous acetone extracts exhibited high phenolic diversity, including phenolic acids (20 compounds), flavonoids (15 compounds), and hydrolyzable tannins (27 compounds). Partial least squares–discriminant analysis (PLS-DA), multivariate statistics (MANOVA), and Random Forest classification were employed to resolve hormone-specific phenolic signatures across time. Distinct regulatory trajectories were identified for each hormone. SA elicitation triggered a high-amplitude, pulsatile phenolic response primarily affecting precursor-associated phenolic acids and ellagic-related structures, consistent with transient metabolic priming. JA induced a gradual and sustained modulation of flavonoids and tannin pools, within which advanced caffeoylquinic esters, flavonol conjugates, and ellagitannins emerged as key discriminant markers. ABA treatment promoted progressive and stabilized accumulation across phenolic classes, supporting a role in metabolic homeostasis rather than stress induction. Biweekly sampling was essential to discriminate transient, adaptive, and stabilizing responses. Overall, the results demonstrate that Q. sideroxyla differentiates hormonal signals and translates them into distinct phenolic reprogramming patterns. The integration of time-resolved metabolomics with multivariate and machine-learning approaches provides a robust framework for hormone-guided modulation of phenolic metabolism in woody plants. Full article

As human space exploration advances towards establishing sustainable Martian habitats, achieving autonomous food production is a critical requirement. The potato (Solanum tuberosum L.), with its notable environmental resilience and nutritional efficiency, is a prime candidate crop. This study develops a conceptual framework for Martian potato cultivation by systematically analyzing the profound disparities between Martian conditions and plant physiology. We identify and evaluate seven fundamental challenges: atmospheric composition, extreme temperatures, water scarcity, soil properties, nutrient deficiencies, absent microbiota, and radiation/gravity effects. To address these challenges, we propose a phased, testable roadmap comprising four stages: (I) screening and bio-engineering of multi-stress-tolerant potato genotypes; (II) phased domestication via Earth-based analog experiments to define adaptability thresholds; (III) deployment of a controlled cultivation module within a Martian habitat, integrating targeted technological interventions; and (IV) conceptual exploration of extra-habitat agricultural potential. The primary contribution of this work is a structured set of hypotheses and key performance indicators for each stage, translating visionary goals into a defined research agenda to guide future empirical work in extraterrestrial agronomy. Full article

Southern pine beetle infestations impact ecosystems throughout the southeastern US. Our understanding of hydrologic and biogeochemical impacts on ecosystem structure and function is largely guided by severe outbreaks occurring in the western US. A simulated mortality experiment was conducted on loblolly pine trees via girdling with and without blue-stain fungi inoculation to mimic a small-scale infestation. We measured whole-tree water use, canopy-derived hydrologic and biogeochemical fluxes, soil moisture, and soil respiration for two years following treatments to quantify the impacts of tree mortality on water, carbon, and nitrogen cycles. In the second year of our study, a significant drought occurred, subjecting study trees to a secondary stressor. We found that compared to control trees, girdled trees exhibited reduced water uptake within 6 months and succumbed to mortality within 18 months. We found that by the time trees reached the gray phase of attack, stemflow was 1.7-times lower in girdled trees compared to control trees. Stemflow from girdled trees had up to 7.2-times higher concentrations of ammonium and 2.8-times higher concentrations of total nitrogen. Although stemflow carbon concentrations were indistinguishable between treatments, total carbon flux in stemflow was 2.0-times greater in non-girdled trees (p = 0.030). Finally, even though soil moisture and respiration were not different between treatments, it was not possible to isolate the response of these to mortality versus drought. Our results present the connection between bark beetle outbreaks and the initial impacts on forest biogeochemistry. Changes in the distribution of canopy-derived water inputs, coupled with altered carbon and nitrogen fluxes, serve as hot spots around bark beetle-killed trees. Further research is necessary to understand whether these isolated hot spots may prime the system, alter microbial and invertebrate communities, and lead to changes in decomposition processes at larger scales. Full article

Let p be a prime number and r a positive integer. This paper investigates the construction and classification of finite commutative rings of order $p^{6r}$ in which the set of zero-divisors J forms an ideal satisfying the conditions $J^3=0$, $J^2\ne 0$ with $J^2$ being principal. Under these conditions, the rings considered are precisely the Frobenius local rings. A Frobenius local (completely primary) ring R with these properties is referred to as a ring with property (P). These rings naturally divide into three classes according to their characteristic: p, $p^2$, or $p^3$. In the case of characteristic $p^2$, a further distinction is made depending on whether p lies in $J^2$ or in $J\setminus J^2$, where J denotes the Jacobson radical of R. The classification is achieved by associating to each ring a canonical matrix corresponding to a bilinear form and then applying matrix congruence techniques to reduce the problem to linear algebra over finite fields. This yields a complete and explicit description of all Frobenius local rings with property (P) of order $p^{6r}$, including their algebraic structure and enumeration. Full article

In this article, we study polycyclic codes over the ring $R={\mathbb{F}}_q\left[v\right]/⟨v^2-1⟩$, where $q=p^m$ with p being an odd prime. First, we introduce polycyclic codes and sequential codes over R, and characterize the structural properties of these polycyclic codes. Next, we analyze the Euclidean dual codes, annihilator dual codes, annihilator self-orthogonal codes, and annihilator linear complementary dual (LCD) codes associated with this family of codes. Finally, some asymmetric entanglement-assisted quantum error-correcting codes (AEAQECCs) are constructed from polycyclic codes over R. Moreover, the parameters of our AEAQECCs are new in the existing literature. Full article

Cancer metastasis, the spread of tumour cells from the primary site to distant organs, is responsible for over 90% of cancer deaths, yet effective treatments remain elusive due to incomplete understanding of the molecular drivers involved. Podocalyxin (PODXL), a protein overexpressed in many aggressive cancers, links the cell membrane to the internal skeleton through its interaction with Ezrin, an actin cytoskeleton cross-linker. Despite its therapeutic relevance, the PODXL–Ezrin interface remains structurally uncharacterised and pharmacologically intractable. Here, we employed an integrated computational approach combining protein–protein docking, molecular dynamics (MD) simulations, and virtual screening to investigate the structural basis of the PODXL–Ezrin interaction. Using AlphaFold-predicted structures, we modelled PODXL and Ezrin complexes, revealing that PODXL’s cytoplasmic domain stabilises upon Ezrin binding, with Arg495 mediating temporally distinct electrostatic interactions essential for initial complex assembly. Particularly, we characterised the R495W missense mutation in PODXL’s Ezrin-binding domain, demonstrating that substitution of arginine with bulky, hydrophobic tryptophan may allosterically destabilise Ezrin’s dormant conformation. This mutation slightly increases the intramolecular distance between the F3 subdomain and C-terminal domain from 2.59 Å to 3.40 Å, thus leading to potential partial unmasking of the Thr567 phosphorylation site that could plausibly prime Ezrin for activation. Molecular dynamics simulations in the WT state with a total simulation time of 100 ns revealed enhanced structural rigidity and reduced radius of gyration fluctuations in the mutant complex, consistent with a potential “locked,” activation-prone state that amplifies oncogenic signalling. Through virtual screening, we identified NSC305787 as a selective destabiliser of the R495W mutant complex by disrupting key Trp495–pre-C-terminal loop Ezrin interactions and causing steric hindrance to PIP2 recruitment. Our findings identified mutation-dependent changes in drug binding that can guide the development and repurposing of compounds for targeting PODXL-related cancers and improve patient outcomes in PODXL-altered malignancies. Full article

With the rapid growth in the scale and complexity of software systems, automated vulnerability detection has become increasingly important. Although Large Language Models (LLMs) demonstrate strong code comprehension capabilities, their abilities in vulnerability detection are still limited by issues such as hallucinations, high fine-tuning costs, and difficulties in effectively leveraging fine-grained historical vulnerability patterns and domain knowledge. To address these challenges, we propose Retrieval-Augmented Semantic Mapping for Vulnerability Detection (RASM-Vul), a retrieval-augmented framework that enhances LLM detection capability through multi-perspective semantic mapping. The core of our approach is the construction of a comprehensive knowledge base composed of vulnerability–fix pairs and structured knowledge. We leverage multi-view (e.g., code, AST, knowledge) similarity retrieval to accurately match the most relevant vulnerability patterns with repair examples for the code under analysis. Our designed Weighted Reciprocal Ranking Fusion (WRRF) algorithm adaptively integrates contributions from different retrieval channels according to the problem type, significantly improving the relevance and accuracy of retrieval. Experiments show that RASM-Vul achieves an F1-score of 66.79%, outperforming existing baselines on the PrimeVul paired dataset. Our study demonstrates that knowledge-enhanced semantic mapping and retrieval can improve the robustness and reliability of automated vulnerability detection. Full article