Aerogels Based on Chitosan and Collagen Modified with FeO and FeO Nanoparticles: Fabrication and Characterization.

The necessity to mitigate the intrinsic issues associated with tissue or organ transplants, in order to address the rising prevalence of diseases attributable to increased life expectancy, provides a rationale for the pursuit of innovation in the field of biomaterials. Specifically, biopolymeric aerogels represent a significant advancement in the field of tissue engineering, offering a promising solution for the formation of temporary porous matrices that can replace damaged tissues. However, the functional characteristics of these materials are inadequate, necessitating the implementation of matrix reinforcement methods to enhance their performance.

Porosity Tunable Metal-Organic Framework (MOF)-Based Composites for Energy Storage Applications: Recent Progress.

To solve the energy crisis and environmental issues, it is essential to create effective and sustainable energy conversion and storage technologies. Traditional materials for energy conversion and storage however have several drawbacks, such as poor energy density and inadequate efficiency. The advantages of MOF-based materials, such as pristine MOFs, also known as porous coordination polymers, MOF composites, and their derivatives, over traditional materials, have been thoroughly investigated.

Post-Marketing Pharmacovigilance of Canakinumab from the FDA Adverse Event Reporting System (FAERS).

Canakinumab, a humanized anti-IL-1β monoclonal antibody, is known for its ability to suppress IL-1β-mediated inflammation. However, continuous monitoring of its safety remains essential. Thus, we comprehensively evaluated the safety signals of canakinumab by data mining from FAERS.

Targeting Cytokine-Mediated Inflammation in Brain Disorders: Developing New Treatment Strategies.

Cytokine-mediated inflammation is increasingly recognized for playing a vital role in the pathophysiology of a wide range of brain disorders, including neurodegenerative, psychiatric, and neurodevelopmental problems. Pro-inflammatory cytokines such as interleukin-1 (IL-1), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) cause neuroinflammation, alter brain function, and accelerate disease development. Despite progress in understanding these pathways, effective medicines targeting brain inflammation are still limited.

In Vivo Assessment of Healing Potential of Ointments Containing Bee Products, Vegetal Extracts, and Polymers on Skin Lesions.

The present experiment aimed to formulate four ointments that included mixtures of plant extracts (, , , and ), apitherapy products (honey, propolis, and apilarnil) and natural polymers (collagen, chitosan, and the lyophilisate of egg white) in an ointment base. : In order to investigate the therapeutic properties of the ointments, experimental in vivo injury models (linear incision, circular excision, and thermal burns) were performed on laboratory animals, namely Wistar rats. The treatment was applied topically, once a day, for 21 days.

Current Insight of Peptide-Based Hydrogels for Chronic Wound Healing Applications: A Concise Review.

Chronic wounds present a substantial healthcare obstacle, marked by an extended healing period that can persist for weeks, months, or even years. Typically, they do not progress through the usual phases of healing, which include hemostasis, inflammation, proliferation, and remodeling, within the expected timeframe. Therefore, to address the socioeconomic burden in taking care of chronic wounds, hydrogel-based therapeutic materials have been proposed.

Chemical Characterization and Differential Lipid-Modulating Effects of Selected Plant Extracts from Côa Valley (Portugal) in a Cell Model for Liver Steatosis.

Background/objectives: Côa Valley, located in the northeast of Portugal, harbors more than 500 medicinal plant species. Among them, four species stand out due to their traditional uses: Desf. (hemorrhages, urethritis, hepatitis), L.

Hybrid Carbohydrate-Lipid Nanocarriers: In Vitro Efficacy Gene-Rated by Association of UV-Absorbers and Raspberry Polyphenols Rich-Fraction.

The study aims to investigate an improved version of lipid nanocarriers (NLCs) (formulated with functional coconut butter and marula oil) by designing hyaluronic acid (HA) decorated NLC co-loaded with dual UVA (butyl methoxy dibenzoyl methane, BMDBM), UVB absorbers (ethyl-hexyl-salicylate, EHS) and a Raspberry rich polyphenols fraction (RPRF) for development of more natural NLC-based to-pical formulations. : Quality and quantitative attributes of classic- and HA-NLC have been assigned based on particle size, electrokinetic potential, encapsulation efficiency, spectroscopic characteristics, and high-resolution mass spectrometry. To establish the performance profile of antioxidant activity, release of active substances, sun blocking action, and photostability, in vitro studies were conducted.

Characterization of RAP Signal Patterns, Temporal Relationships, and Artifact Profiles Derived from Intracranial Pressure Sensors in Acute Traumatic Neural Injury.

Goal: Current methodologies for assessing cerebral compliance using pressure sensor technologies are prone to errors and issues with inter- and intra-observer consistency. RAP, a metric for measuring intracranial compensatory reserve (and therefore compliance), holds promise. It is derived using the moving correlation between intracranial pressure (ICP) and the pulse amplitude of ICP (AMP).

Intelligent Intrusion Detection System Against Various Attacks Based on a Hybrid Deep Learning Algorithm.

The Internet of Things (IoT) has emerged as a crucial element in everyday life. The IoT environment is currently facing significant security concerns due to the numerous problems related to its architecture and supporting technology. In order to guarantee the complete security of the IoT, it is important to deal with these challenges.

Identifying the Primary Kinetic Factors Influencing the Anterior-Posterior Center of Mass Displacement in Barbell Squats: A Factor Regression Analysis.

Barbell squats are commonly used in strength training, but the anterior-posterior displacement of the Center of Mass (COM) may impair joint stability and increase injury risk. This study investigates the key factors influencing COM displacement during different squat modes.; Methods: This study recruited 15 male strength training enthusiasts, who performed 60% of their one-repetition maximum (1RM) in the Front Barbell Squat (FBS), High Bar Back Squat (HBBS), and Low Bar Back Squat (LBBS).

Computer-Aided Supporting Models of Customized Crack Propagation Sensors for Analysis and Prototyping.

The range of sensor technologies for structural health monitoring (SHM) systems is expanding as the need for ongoing structural monitoring increases. In such a case, damage to the monitored structure elements is detected using an integrated network of sensors operating in real-time or periodically in frequent time stamps. This paper briefly introduces a new type of sensor, called a Customized Crack Propagation Sensor (CCPS), which is an alternative for crack gauges, but with enhanced functional features and customizability.

Action Recognition in Basketball with Inertial Measurement Unit-Supported Vest.

In this study, an action recognition system was developed to identify fundamental basketball movements using a single Inertial Measurement Unit (IMU) sensor embedded in a wearable vest. This study aims to enhance basketball training by providing a high-performance, low-cost solution that minimizes discomfort for athletes. Data were collected from 21 collegiate basketball players, and movements such as dribbling, passing, shooting, layup, and standing still were recorded.

The Application of Supervised Machine Learning Algorithms for Image Alignment in Multi-Channel Imaging Systems.

This study presents a method for aligning the geometric parameters of images in multi-channel imaging systems based on the application of pre-processing methods, machine learning algorithms, and a calibration setup using an array of orderly markers at the nodes of an imaginary grid. According to the proposed method, one channel of the system is used as a reference. The images from the calibration setup in each channel determine the coordinates of the markers, and the displacements of the marker centers in the system's channels relative to the coordinates of the centers in the reference channel are then determined.

The SPICE Modeling of a Radiation Sensor Based on a MOSFET with a Dielectric HfO/SiO Double-Layer.

We report on a procedure for extracting the SPICE model parameters of a RADFET sensor with a dielectric HfO/SiO double-layer. RADFETs, traditionally fabricated as PMOS transistors with SiO, are enhanced by incorporating high-k dielectric materials such as HfO to reduce oxide thickness in modern radiation sensors. The fabrication steps of the sensor are outlined, and model parameters, including the threshold voltage and transconductance, are extracted based on experimental data.

GravelSens: A Smart Gravel Sensor for High-Resolution, Non-Destructive Monitoring of Clogging Dynamics.

Engineers, geomorphologists, and ecologists acknowledge the need for temporally and spatially resolved measurements of sediment clogging (also known as colmation) in permeable gravel-bed rivers due to its adverse impacts on water and habitat quality. In this paper, we present a novel method for non-destructive, real-time measurements of pore-scale sediment deposition and monitoring of clogging by using wire-mesh sensors (WMSs) embedded in spheres, forming a smart gravel bed (GravelSens). The measuring principle is based on one-by-one voltage excitation of transmitter electrodes, followed by simultaneous measurements of the resulting current by receiver electrodes at each crossing measuring pores.

Symmetry Breaking as a Basis for Characterization of Dielectric Materials.

This paper introduces a novel method for measuring the dielectric permittivity of materials within the microwave and millimeter wave frequency ranges. The proposed approach, classified as a guided wave transmission system, employs a periodic transmission line structure characterized by mirror/glide symmetry. The dielectric permittivity is deduced by measuring the transmission properties of such structure when presence of the dielectric material breaks the inherent symmetry of the structure and consequently introduce a stopband in propagation characteristic.

Web Real-Time Communications-Based Unmanned-Aerial-Vehicle-Borne Internet of Things and Stringent Time Sensitivity: A Case Study.

The currently observed development of time-sensitive applications also affects wireless communication with the IoT carried by UAVs. Although research on wireless low-latency networks has matured, there are still issues to solve at the transport layer. Since there is a general agreement that classical transport solutions are not able to achieve end-to-end delays in the single-digit millisecond range, in this paper, the use of WebRTC is proposed as a potential solution to this problem.

An Approach to Fall Detection Using Statistical Distributions of Thermal Signatures Obtained by a Stand-Alone Low-Resolution IR Array Sensor Device.

Infrared array sensor-based fall detection and activity recognition systems have gained momentum as promising solutions for enhancing healthcare monitoring and safety in various environments. Unlike camera-based systems, which can be privacy-intrusive, IR array sensors offer a non-invasive, reliable approach for fall detection and activity recognition while preserving privacy. This work proposes a novel method to distinguish between normal motion and fall incidents by analyzing thermal patterns captured by infrared array sensors.

A Comprehensive Analysis of a Social Intelligence Dataset and Response Tendencies Between Large Language Models (LLMs) and Humans.

In recent years, advancements in the interaction and collaboration between humans and have garnered significant attention. Social intelligence plays a crucial role in facilitating natural interactions and seamless communication between humans and Artificial Intelligence (AI). To assess AI's ability to understand human interactions and the components necessary for such comprehension, datasets like Social-IQ have been developed.

Investigation of Sliding Mode Control in the Nonlinear Modeling of Cordless Jigsaws.

The aim of this paper was to reduce the current spikes in battery-powered saw motors by designing and implementing a sliding mode model-following adaptive controller. The proposed controller reduces overcurrent consumption, improves system energy efficiency, and effectively maximizes battery runtime, especially under high-load conditions. By applying nonlinear compensation techniques, the controller can ensure smooth motor operation, reduce mechanical stress, and prolong tool life.

Developing a Health Support System to Promote Care for the Elderly.

In light of the demographic shift towards an aging population, there is an increasing prevalence of dementia among the elderly. The negative impact on mental health is preventing individuals from taking proper care of themselves. For individuals requiring hospital care, those receiving home care, or as a precaution for a specific individual, it is advantageous to utilize monitoring equipment to track their biological parameters on an ongoing basis.

A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain-Computer Interfaces to Enhance Motor Imagery Classification.

Enhancing motor disability assessment and its imagery classification is a significant concern in contemporary medical practice, necessitating reliable solutions to improve patient outcomes. One promising avenue is the use of brain-computer interfaces (BCIs), which establish a direct communication pathway between users and machines. This technology holds the potential to revolutionize human-machine interaction, especially for individuals diagnosed with motor disabilities.

Incorporating Multimodal Directional Interpersonal Synchrony into Empathetic Response Generation.

This study investigates how interpersonal (speaker-partner) synchrony contributes to empathetic response generation in communication scenarios. To perform this investigation, we propose a model that incorporates multimodal directional (positive and negative) interpersonal synchrony, operationalized using the cosine similarity measure, into empathetic response generation. We evaluate how incorporating specific synchrony affects the generated responses at the language and empathy levels.

Polarization-Insensitive, High-Efficiency Metasurface with Wide Reception Angle for Energy Harvesting Applications.

This research presents an innovative polarization-insensitive metasurface (MS) harvester designed for energy harvesting applications at 5 GHz, capable of operating efficiently over wide reception angles. The proposed MS features a novel wheel-shaped resonator array whose symmetrical structure ensures insensitivity to the polarization of incident electromagnetic (EM) waves, enabling efficient energy absorption and minimizing reflections. Unlike conventional designs, the metasurface achieves near-unity harvesting efficiency, exceeds 94% under normal incidence, and maintains superior performance across various incident angles for TE and TM polarizations.