Hasil untuk "General. Including alchemy"

Umme Salma Khanam, Hyeon Teak Jeong, Rahim Mutlu et al.

Alginate hydrogels offer distinct advantages as ionically crosslinked, biocompatible networks that can be shaped into spherical beads with high compositional flexibility. These spherical architectures provide isotropic geometry, modularity and the capacity for encapsulation, making them ideal platforms for scalable, stimuli-responsive actuation. Their ability to respond to thermal, magnetic, electrical, optical and chemical stimuli has enabled applications in targeted delivery, artificial muscles, microrobotics and environmental interfaces. This review examines recent advances in alginate sphere-based actuators, focusing on fabrication methods such as droplet microfluidics, coaxial flow and functional surface patterning, and strategies for introducing multi-stimuli responsiveness using smart polymers, nanoparticles and biologically active components. Actuation behaviours are understood and correlated with physical mechanisms including swelling kinetics, photothermal effects and the field-induced torque, supported by analytical and multiphysics models. Their demonstrated functionalities include shape transformation, locomotion and mechano-optical feedback. The review concludes with an outlook on the existing limitations, such as the material stability, cyclic durability and integration complexity, and proposes future directions toward the development of autonomous, multifunctional soft systems.

Robert L. Kobrin, Siena M. Mantooth, Abigail L. Mulry et al.

Intratumoral injections of macromolecules, such as biologics and immunotherapeutics, show promise in overcoming dose-limiting side effects associated with systemic injections and improve treatment efficacy. However, the retention of injectates in the tumor microenvironment is a major underappreciated challenge. High interstitial pressures and dense tumor architectures create shear forces that rapidly expel low-viscosity solutions post-injection. Injectable hydrogels may address these concerns by providing a viscoelastic delivery vehicle that shields loaded therapies from rapid expulsion from the tumor. A chitosan–glycerol hydrogel was thus developed and characterized with the goal of improving the injection retention of loaded therapeutics. The gelation parameters and mechanical properties of the hydrogel were explored to reveal a shear-thinning gel that is injectable through a 27-gauge needle. Biocompatibility studies demonstrated that the chitosan–glycerol hydrogel was nontoxic. Retention studies revealed significant improvements in the retention of model therapeutics when formulated with the chitosan–glycerol hydrogel compared to less-viscous solutions. Finally, release studies showed that there was a sustained release of model therapeutics of various molecular sizes from the hydrogel. Overall, the chitosan–glycerol hydrogel demonstrated injectability, enhanced retention, biocompatibility, and sustained release of macromolecules, indicating its potential for future clinical use in intratumoral macromolecule delivery.

Dimitra Tseneklidou, Raimon Luna, Pablo Cerdá-Durán et al.

The gravitational wave signature from core-collapse supernovae (CCSNe) is dominated by quadrupolar oscillation modes of the newly born proto-neutron star (PNS), and could be detectable at galactic distances. We have developed a framework for computing the normal oscillation modes of a PNS in general relativity, including, for the first time, the presence of an accretion flow and a surrounding stalled accretion shock. These new ingredients are key to understand PNS oscillation modes, in particular those related to the standing-accretion-shock instability (SASI). Their incorporation is an important step towards accurate PNS asteroseismology. For this purpose, we perform linear and adiabatic perturbations of a spherically symmetric background, in the relativistic Cowling approximation, and cast the resulting equations as an eigenvalue problem. We discretize the eigenvalue problem using collocation Chebyshev spectral methods, which is then solved by means of standard and efficient linear algebra methods. We impose boundary conditions at the accretion shock compatible with the Rankine-Hugoniot conditions. We present several numerical examples to assess the accuracy and convergence of the numerical code, as well as to understand the effect of an accretion flow on the oscillation modes, as a stepping stone towards a complete analysis of the CCSNe case.

Rafael Ceja Ayala, Isaac Harris, General Ozochiawaeze

This work extends the factorization method to the inverse scattering problem of reconstructing the shape and location of an absorbing penetrable scatterer embedded in a thin infinite elastic (Kirchhoff--Love) plate. With the assumption that the plate thickness is small compared to the wavelength of the incident wave, the propagation of flexural perturbations is modeled by the two--dimensional biharmonic wave equation in the frequency domain. Within this setting, we provide a rigorous justification of the factorization method and demonstrate that it yields a binary criterion for distinguishing whether a sampling point lies inside or outside the scatterer, using only the spectral data of the far--field operator. In addition, we numerically analyze the Born approximation for weak scatterers in this biharmonic scattering context and compute the relative error against exact far--field data for sample weak scatterers, thereby quantifying its validity as a limited but useful approximation.

C. Nicolaidis, D. Raymaker, D. Raymaker et al.

Yantao Wang, Zhenpeng Shen, Huili Wang et al.

Alginate is an important natural biopolymer and metal ion-induced gelation is one of its most significant functional properties. Alginate-based hydrogels crosslinked with metal ions are commonly utilized in the food, biomedical, tissue engineering, and environment fields. The process of metal ion-induced alginate gelation has been the subject of thorough research over the last few decades. This review aims to summarize the mechanisms of alginate hydrogels induced by different cations (primarily including Ca²⁺, Ba²⁺, Cu²⁺, Sr²⁺, Fe²⁺/Fe³⁺, and Al³⁺). Metal ion-induced alginate gelation shows different preferences for α-L-guluronic acid (G), β-D-mannuronic acid (M), and GM blocks. Some metal ions can also selectively bind to the carboxyl groups of guluronic acid. The properties and applications of these alginate-based hydrogels are also discussed. The primary objective of this review is to provide useful information for exploring the practical applications of alginate.

Sofia Milenkova, Rita Ambrus, Mahwash Mukhtar et al.

Chitosan, being a biocompatible and mucoadhesive polysaccharide, is one of the most preferred hydrogel-forming materials for drug delivery. The objectives of the present study are to obtain spray-dried microparticles based on low-molecular-weight chitosan and study their potential application as cargo systems for the orally active drug benzydamine hydrochloride. Three types of particles are obtained: raw chitosan particles (at three different concentrations), cross-linked with sodium tripolyphosphate (NaTPP) particles (at three different chitosan:NaTPP ratios), and particles coated with mannitol (at three different chitosan:mannitol ratios), all of them in the size range between 1 and 10 µm. Based on the loading efficiency and the yields of the formulated hydrogel particles, one model of each type is chosen for further investigation of the effect of the cross-linker or the excipient on the properties of the gel structures. The morphology of both empty and benzydamine hydrochloride-loaded chitosan particles was examined by scanning electron microscopy, and it was quite regular and spherical. Interactions and composition in the samples are investigated by Fourier-transformed infrared spectroscopy. The thermal stability and phase state of the drug and drug-containing polymer matrixes were tested by differential scanning calorimetry and X-ray powdered diffraction, revealing that the drug underwent a phase transition. A drug release kinetics study of the chosen gel-based structures in simulated saliva buffer (pH = 6.8) and mathematical modeling of the process were performed, indicating the Weibull model as the most appropriate one.

Yoana Sotirova, Yoana Kiselova-Kaneva, Deyana Vankova et al.

The wound-healing effect of St. John’s Wort (SJW) is mainly attributed to hyperforin (HP), but its low stability restricts its topical administration. This study investigates how “free” HP-rich SJW extract (incorporated into a bigel; B/SJW) and extract “protected” by nanostructured lipid carriers (also included in a biphasic semisolid; B/NLC-SJW) affect tissue regeneration in a rat skin excision wound model. Wound diameter, histological changes, and tissue gene expression levels of fibronectin (Fn), matrix metalloproteinase 8 (MMP8), and tumor necrosis factor-alpha (TNF-α) were employed to quantify the healing progress. A significant wound size reduction was achieved after applying both extract-containing semisolids, but after a 21-day application period, the smallest wound size was observed in the B/NLC-SJW-treated animals. However, the inflammatory response was affected more favorably by the bigel containing the “free” SJW extract, as evidenced by histological studies. Moreover, after the application of B/SJW, the expression of Fn, MMP8, and TNF-α was significantly higher than in the positive control. In conclusion, both bigel formulations exhibited beneficial effects on wound healing in rat skin, but B/SJW affected skin restoration processes in a comprehensive and more efficient way.

Vasily Smirnov, Daria Khramova, Elizaveta Chistiakova et al.

Hardness is one of the dominant sensory characteristics of food. This study estimated the effect of sensitivity to hardness on the texture perception and chewing function using 2, 4, and 6% agar gels. Increasing the concentration of agar resulted in an increase in gel hardness and springiness, measured by texture profile analysis. Non-trained participants (<i>n</i> = 95) reported more subjective hardness and springiness during chewing gel samples as the agar concentration increased. Based on the relationship value of the instrumental and sensory data, all participants were divided into low-, medium-, and high-sensitivity groups (<i>n</i> = 25, 44, and 26). Low sensitivity to hardness was associated with low sensitivity to brittleness, springiness, chewiness, moisture, and swallowability. In all three groups, enhanced agar gel hardness increased the temporal chewing characteristics in a similar manner. However, in those with a high hardness sensitivity, the area amplitude of the masseter and temporalis muscles grew to a lesser extent than in those with a low or medium sensitivity. The activity of the suprahyoid muscles increased with the increasing agar gel hardness, regardless of sensitivity. All groups showed a similar salivation and bolus fragmentation while chewing gel. Thus, people’s sensitivity to hardness was associated with different perceptions of the gel’s textural properties and changes in masticatory muscle activity.

Weidong Liu, Chuying Yao, Daohang Wang et al.

Chinese herbal medicine has offered an enormous source for developing novel bio-soft materials. In this research, the natural polysaccharide isolated from the Chinese herbal medicine <i>Dendrobium</i> was employed as the secondary building block to fabricate a “hybrid” hydrogel with synthetic poly (vinyl alcohol) (PVA) polymers. Thanks to the presence of mannose units that contain cis-diol motifs on the chain of the <i>Dendrobium</i> polysaccharides, efficient crosslinking with the borax is allowed and reversible covalent borate ester bonds are formed. Eventually, highly dynamic and double-networked hydrogels were successfully prepared by the integration of <i>Dendrobium</i> polysaccharides and PVA. Interestingly, the introduction of polysaccharides has given rise to more robust and dynamic hydrogel networks, leading to enhanced thermal stability, mechanical strength, and tensile capacity (>1000%) as well as the rapid self-healing ability (<5 s) of the “hybrid” hydrogels compared with the PVA/borax single networked hydrogel. Moreover, the polysaccharides/PVA double network hydrogel showed selective antibacterial activity towards <i>S. aureus</i>. The reported polysaccharides/PVA double networked hydrogel would provide a scaffold to hybridize bioactive natural polysaccharides and synthetic polymers for developing robust but dynamic multiple networked hydrogels that are tailorable for biomedical applications.

Amina Mazeri, Achraf Khaldi, Mehdi Kheira et al.

The main objectives of this study were to determine the chemical composition of the essential oil of Marrubium deserti de Noé (EOMD) from Bechar (Algeria), and to evaluate its physicochemical properties, antibacterial and antifungal activities. The yield of EOMD was 0.29±0.008%, with the main components being α-phellandrene (25.05%), β-pinene (14.05%), and α-pinene (12.83%). Both gram-negative and gram-positive bacteria were significantly inhibited by EOMD with inhibition zones ranging from 7.00±0.00 mm to 22±1.33 mm, and with minimum inhibitory concentrations (MICs) and minimum bactericidal concentration values ranging from 0.0022 to 0.014 v/v; likewise, intriguing antifungal activity against pathogen fungi was noticed with MICs and minimum fungicidal concentration values ranging from 0.00125 to 0.006 v/v. Furthermore, the studied essential oil demonstrated a total suppression of the sporulation and germination of spores at concentrations as from 0.002 v/v. These results emphasize the bactericidal and fungicidal characteristics of EOMD and their prospective usage as a substitute for synthetic bactericides and fungicides.

Andrea Osmokrovic, Ivan Jancic, Zeljko Zizak et al.

Antimicrobial resistance (AMR) is a global public health threat that affects cancer patients more than the general population. In this work, a composite system based on Zn-alginate hydrogel and activated charcoal (AC) particles that, upon contact with physiological fluids, simultaneously releases bioactive agents (Zn²⁺ and AC particles impregnated with povidone–iodine) was designed to locally address specific problems characteristic for malignant wounds (MWs). This composite was comprehensively investigated in vitro regarding its morphology (field-emission scanning electron microscopy), Zn²⁺ release (flame atomic absorption spectrometry), iodine adsorption and desorption from AC particles (energy dispersive X-ray analysis and UV–visible spectroscopy) as well as its antimicrobial and antitumor activity. With respect to the ongoing AMR crises, antimicrobial activity was tested against a wide range of wild multi-drug resistant bacterial and yeast strains, all isolated from patient wounds. Since Zn²⁺ ions proved to be selectors of resistant strains of bacteria, the synergistic activity of AC particles and adsorbed iodine was shown to be crucial for excellent antibacterial activity. On the other hand, the synergy of AC particles and Zn²⁺ ions showed an equally strong antifungal effect. In addition, antimicrobial concentrations of Zn²⁺ ions showed cytotoxic activity against two cancer cell lines derived from cancers affecting skin either as metastatic cancer (breast cancer MDA-MB-453 cell line) or primary cancer of the skin (malignant melanoma Fem-X cell line), which enables Zn²⁺ ions to be further investigated as potent local agents targeting malignant cells.

Andrea Perin, Stephane Deny

Symmetries (transformations by group actions) are present in many datasets, and leveraging them holds considerable promise for improving predictions in machine learning. In this work, we aim to understand when and how deep networks -- with standard architectures trained in a standard, supervised way -- learn symmetries from data. Inspired by real-world scenarios, we study a classification paradigm where data symmetries are only partially observed during training: some classes include all transformations of a cyclic group, while others -- only a subset. In the infinite-width limit, where kernel analogies apply, we derive a neural kernel theory of symmetry learning. The group-cyclic nature of the dataset allows us to analyze the Gram matrix of neural kernels in the Fourier domain; here we find a simple characterization of the generalization error as a function of class separation (signal) and class-orbit density (noise). This characterization reveals that generalization can only be successful when the local structure of the data prevails over its non-local, symmetry-induced structure, in the kernel space defined by the architecture. We extend our theoretical treatment to any finite group, including non-abelian groups. Our framework also applies to equivariant architectures (e.g., CNNs), and recovers their success in the special case where the architecture matches the inherent symmetry of the data. Empirically, our theory reproduces the generalization failure of finite-width networks (MLP, CNN, ViT) trained on partially observed versions of rotated-MNIST. We conclude that conventional deep networks lack a mechanism to learn symmetries that have not been explicitly embedded in their architecture a priori. Our framework could be extended to guide the design of architectures and training procedures able to learn symmetries from data.

David D. Nguyen, David Liebowitz, Surya Nepal et al.

Honeyfiles are security assets designed to attract and detect intruders on compromised systems. Honeyfiles are a type of honeypot that mimic real, sensitive documents, creating the illusion of the presence of valuable data. Interaction with a honeyfile reveals the presence of an intruder, and can provide insights into their goals and intentions. Their practical use, however, is limited by the time, cost and effort associated with manually creating realistic content. The introduction of large language models has made high-quality text generation accessible, but honeyfiles contain a variety of content including charts, tables and images. This content needs to be plausible and realistic, as well as semantically consistent both within honeyfiles and with the real documents they mimic, to successfully deceive an intruder. In this paper, we focus on an important component of the honeyfile content generation problem: document charts. Charts are ubiquitous in corporate documents and are commonly used to communicate quantitative and scientific data. Existing image generation models, such as DALL-E, are rather prone to generating charts with incomprehensible text and unconvincing data. We take a multi-modal approach to this problem by combining two purpose-built generative models: a multitask Transformer and a specialized multi-head autoencoder. The Transformer generates realistic captions and plot text, while the autoencoder generates the underlying tabular data for the plot. To advance the field of automated honeyplot generation, we also release a new document-chart dataset and propose a novel metric Keyword Semantic Matching (KSM). This metric measures the semantic consistency between keywords of a corpus and a smaller bag of words. Extensive experiments demonstrate excellent performance against multiple large language models, including ChatGPT and GPT4.

Aydin Zaboli, Seong Lok Choi, Junho Hong

This study addresses critical challenges of cybersecurity in digital substations by proposing an innovative task-oriented dialogue (ToD) system for anomaly detection (AD) in multicast messages, specifically, generic object oriented substation event (GOOSE) and sampled value (SV) datasets. Leveraging generative artificial intelligence (GenAI) technology, the proposed framework demonstrates superior error reduction, scalability, and adaptability compared with traditional human-in-the-loop (HITL) processes. Notably, this methodology offers significant advantages over machine learning (ML) techniques in terms of efficiency and implementation speed when confronting novel and/or unknown cyber threats, while also maintaining model complexity and precision. The research employs advanced performance metrics to conduct a comparative assessment between the proposed AD and HITL-based AD frameworks, utilizing a hardware-in-the-loop (HIL) testbed for generating and extracting features of IEC61850 communication messages. This approach presents a promising solution for enhancing the reliability of power system operations in the face of evolving cybersecurity challenges.

Yigit Demirag

As neural computation is revolutionizing the field of Artificial Intelligence (AI), rethinking the ideal neural hardware is becoming the next frontier. Fast and reliable von Neumann architecture has been the hosting platform for neural computation. Although capable, its separation of memory and computation creates the bottleneck for the energy efficiency of neural computation, contrasting the biological brain. The question remains: how can we efficiently combine memory and computation, while exploiting the physics of the substrate, to build intelligent systems? In this thesis, I explore an alternative way with memristive devices for neural computation, where the unique physical dynamics of the devices are used for inference, learning and routing. Guided by the principles of gradient-based learning, we selected functions that need to be materialized, and analyzed connectomics principles for efficient wiring. Despite non-idealities and noise inherent in analog physics, I will provide hardware evidence of adaptability of local learning to memristive substrates, new material stacks and circuit blocks that aid in solving the credit assignment problem and efficient routing between analog crossbars for scalable architectures.

Diana Pelinescu, Mihai Anastasescu, Veronica Bratan et al.

Nanostructured oxides (SiO₂, TiO₂) were synthesized using the sol–gel method and modified with noble metal nanoparticles (Pt, Au) and ruthenium dye to enhance light harvesting and promote the photogeneration of reactive oxygen species, namely singlet oxygen (¹O₂) and hydroxyl radical (•OH). The resulting nanostructures were embedded in a transparent polyvinyl alcohol (PVA) hydrogel. Morphological and structural characterization of the bare and modified oxides was performed using scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), UV–Vis spectroscopy, and X-ray photoelectron spectroscopy (XPS). Additionally, electrokinetic potential measurements were conducted. Crystallinity data and elemental analysis of the investigated systems were obtained through X-ray diffraction and X-ray fluorescence analyses, while the chemical state of the elements was determined using XPS. The engineered materials, both as simple powders and embedded in the hydrogel, were evaluated for their ability to generate reactive oxygen species (ROS) under visible and simulated solar light irradiation to establish a correlation with their antibacterial activity against <i>Staphylococcus aureus</i>. The generation of singlet oxygen (¹O₂) by the samples under visible light exposure can be of significant importance for their potential use in biomedical applications.

Alexandra-Diana Diaconu, Corina-Lenuta Logigan, Catalina Anisoara Peptu et al.

Polymer networks based on cyclodextrin and polyethylene glycol were prepared through polyaddition crosslinking using isophorone diisocyanate. The envisaged material properties are the hydrophilic character, specific to PEG and cyclodextrins, and the capacity to encapsulate guest molecules in the cyclodextrin cavity through physical interactions. The cyclodextrin was custom-modified with oligocaprolactone to endow the crosslinked material with a hydrolytically degradable character. SEM, DTG, and FTIR characterization methods have confirmed the morphology and structure of the prepared hydrogels. The influence of the crosslinking reaction feed was investigated through dynamic rheology. Further, thermal water swelling and hydrolytic degradation in basic conditions revealed the connectivity of the polymer network and the particular influence of the cyclodextrin amount in the crosslinking reaction feed on the material properties. Also, levofloxacin was employed as a model drug to investigate the drug loading and release capacity of the prepared hydrogels.

Jorge Lauret, Cynthia E. Will

A generalized metric on a manifold $M$, i.e., a pair $(g,H)$, where $g$ is a Riemannian metric and $H$ a closed $3$-form, is a fixed point of the generalized Ricci flow if and only if $(g,H)$ is Bismut Ricci flat: $H$ is $g$-harmonic and $ric(g)=\tfrac{1}{4} H_g^2$. On any homogeneous space $M=G/K$, where $G=G_1\times G_2$ is a compact semisimple Lie group with two simple factors, under some mild assumptions, we exhibit a Bismut Ricci flat $G$-invariant generalized metric, which is proved to be unique among a $4$-parameter space of metrics in many cases, including when $K$ is neither abelian nor semisimple. On the other hand, if $K$ is simple and the standard metric is Einstein on both $G_1/π_1(K)$ and $G_2/π_2(K)$, we give a one-parameter family of Bismut Ricci flat $G$-invariant generalized metrics on $G/K$ and show that it is most likely pairwise non-homothetic by computing the ratio of Ricci eigenvalues. This is proved to be the case for every space of the form $M=G\times G/ΔK$ and for $M^{35}=SO(8)\times SO(7)/G_2$. A Corrigendum has been added in Appendix A.

Cristina Manferdini, Diego Trucco, Yasmin Saleh et al.

Articular cartilage is known to have limited intrinsic self-healing capacity when a defect or a degeneration process occurs. Hydrogels represent promising biomaterials for cell encapsulation and injection in cartilage defects by creating an environment that mimics the cartilage extracellular matrix. The aim of this study is the analysis of two different concentrations (1:1 and 1:2) of VitroGel^® (VG) hydrogels without (VG-3D) and with arginine-glycine-aspartic acid (RGD) motifs, (VG-RGD), verifying their ability to support chondrogenic differentiation of encapsulated human adipose mesenchymal stromal cells (hASCs). We analyzed the hydrogel properties in terms of rheometric measurements, cell viability, cytotoxicity, and the expression of chondrogenic markers using gene expression, histology, and immunohistochemical tests. We highlighted a shear-thinning behavior of both hydrogels, which showed good injectability. We demonstrated a good morphology and high viability of hASCs in both hydrogels. VG-RGD 1:2 hydrogels were the most effective, both at the gene and protein levels, to support the expression of the typical chondrogenic markers, including collagen type 2, SOX9, aggrecan, glycosaminoglycan, and cartilage oligomeric matrix protein and to decrease the proliferation marker MKI67 and the fibrotic marker collagen type 1. This study demonstrated that both hydrogels, at different concentrations, and the presence of RGD motifs, significantly contributed to the chondrogenic commitment of the laden hASCs.