Ensuring Reliable Network Communication and Data Processing in Internet of Things Systems with Prediction-Based Resource Allocation.

The distributed nature of IoT systems and new trends focusing on fog computing enforce the need for reliable communication that ensures the required quality of service for various scenarios. Due to the direct interaction with the real world, failure to deliver the required QoS level can introduce system failures and lead to further negative consequences for users. This paper introduces a prediction-based resource allocation method for Multi-Access Edge Computing-capable networks, aimed at assurance of the required QoS and optimization of resource utilization for various types of IoT use cases featuring adaptability to changes in users' requests.

An FPGA-Based SiNW-FET Biosensing System for Real-Time Viral Detection: Hardware Amplification and 1D CNN for Adaptive Noise Reduction.

Impedance-based biosensing has emerged as a critical technology for high-sensitivity biomolecular detection, yet traditional approaches often rely on bulky, costly impedance analyzers, limiting their portability and usability in point-of-care applications. Addressing these limitations, this paper proposes an advanced biosensing system integrating a Silicon Nanowire Field-Effect Transistor (SiNW-FET) biosensor with a high-gain amplification circuit and a 1D Convolutional Neural Network (CNN) implemented on FPGA hardware. This attempt combines SiNW-FET biosensing technology with FPGA-implemented deep learning noise reduction, creating a compact system capable of real-time viral detection with minimal computational latency.

Analysis of Autonomous Penetration Testing Through Reinforcement Learning and Recommender Systems.

Conducting penetration testing (pentesting) in cybersecurity is a crucial turning point for identifying vulnerabilities within the framework of Information Technology (IT), where real malicious offensive behavior is simulated to identify potential weaknesses and strengthen preventive controls. Given the complexity of the tests, time constraints, and the specialized level of expertise required for pentesting, analysis and exploitation tools are commonly used. Although useful, these tools often introduce uncertainty in findings, resulting in high rates of false positives.

Issues and Limitations on the Road to Fair and Inclusive AI Solutions for Biomedical Challenges.

Objective: In this paper, we explore the correlation between performance reporting and the development of inclusive AI solutions for biomedical problems. Our study examines the critical aspects of bias and noise in the context of medical decision support, aiming to provide actionable solutions. Contributions: A key contribution of our work is the recognition that measurement processes introduce noise and bias arising from human data interpretation and selection.

Multi-Scale Contrastive Learning with Hierarchical Knowledge Synergy for Visible-Infrared Person Re-Identification.

Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality retrieval task to match a person across different spectral camera views. Most existing works focus on learning shared feature representations from the final embedding space of advanced networks to alleviate modality differences between visible and infrared images. However, exclusively relying on high-level semantic information from the network's final layers can restrict shared feature representations and overlook the benefits of low-level details.

Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning.

Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time.

Retrieving and Identifying Remnants of Artefacts on Local Devices Using Sync.com Cloud.

Most current research in cloud forensics is focused on tackling the challenges encountered by forensic investigators in identifying and recovering artifacts from cloud devices. These challenges arise from the diverse array of cloud service providers as each has its distinct rules, guidelines, and requirements. This research proposes an investigation technique for identifying and locating data remnants in two main stages: artefact collection and evidence identification.

Comparative Analysis of Edge Detection Operators Using a Threshold Estimation Approach on Medical Noisy Images with Different Complexities.

The manuscript conducts a comparative analysis to assess the impact of noise on medical images using a proposed threshold value estimation approach. It applies an innovative method for edge detection on images of varying complexity, considering different noise types and concentrations of noise. Five edges are evaluated on images with low, medium, and high detail levels.

Characterizing Surface Deformation of the Earthquake-Induced Daguangbao Landslide by Combining Satellite- and Ground-Based InSAR.

The Daguangbao landslide (DGBL), triggered by the 2008 Wenchuan earthquake, is a rare instance of super-giant landslides globally. The post-earthquake evolution of the DGBL has garnered significant attention in recent years; however, its deformation patterns remain poorly characterized owing to the complex local topography. In this study, we present the first observations of the surface dynamics of DGBL by integrating satellite- and ground-based InSAR data complemented by kinematic interpretation using a LiDAR-derived Digital Surface Model (DSM).

Event-Based Visual/Inertial Odometry for UAV Indoor Navigation.

Indoor navigation is becoming increasingly essential for multiple applications. It is complex and challenging due to dynamic scenes, limited space, and, more importantly, the unavailability of global navigation satellite system (GNSS) signals. Recently, new sensors have emerged, namely event cameras, which show great potential for indoor navigation due to their high dynamic range and low latency.

Advanced Brain Tumor Classification in MR Images Using Transfer Learning and Pre-Trained Deep CNN Models.

Background/objectives: Brain tumor classification is a crucial task in medical diagnostics, as early and accurate detection can significantly improve patient outcomes. This study investigates the effectiveness of pre-trained deep learning models in classifying brain MRI images into four categories: Glioma, Meningioma, Pituitary, and No Tumor, aiming to enhance the diagnostic process through automation.

Methods: A publicly available Brain Tumor MRI dataset containing 7023 images was used in this research.

Cell Membrane Fatty Acids and PIPs Modulate the Etiology of Pancreatic Cancer by Regulating AKT.

Pancreatic ductal adenocarcinoma (PDAC) is one of the worst solid malignancies in regard to outcomes and metabolic dysfunction leading to cachexia. It is alarming that PDAC incidence rates continue to increase and warrant the need for innovative approaches to combat this disease. Due to its relatively slow progression (10-20 years), prevention strategies represent an effective means to improve outcomes.

Edible Coating Combining Liquid Smoke from Oil Palm Empty Fruit Bunches and Turmeric Extract to Prolong the Shelf Life of Mackerel.

This research aimed to evaluate the use of edible coating from a combination of liquid smoke and turmeric extract as a preservative for mackerel at room temperature. Liquid smoke was obtained from the pyrolysis of oil palm empty fruit bunches (OPEFB) at a temperature of 380 °C and purified by distillation at 190 °C. Liquid smoke with a concentration of 3% was combined with turmeric extract at a ratio of 2, 4, 6, and 8 g/L (CLS 2:1, CLS 4:1, CLS 6:1 and CLS 8:1).

Reducing Plate Waste in Latvian Schools: Evaluating Interventions to Promote Sustainable Food Consumption Practices.

Food waste (FW) threatens food security, environmental sustainability, and economic efficiency, with about one-third of global food production lost or wasted. Schools play a crucial role in addressing FW, representing lost resources and missed educational opportunities. The present research assessed three interventions to reduce plate waste (PW) in Rezekne City schools, namely (S1) a plate waste tracker, (S2) an awareness and educational campaign, and (S3) organizational changes, including larger plates, extended lunch breaks, and teacher supervision.

Biocomposite Active Whey Protein Films with Thyme Reinforced by Electrospun Polylactic Acid Fiber Mat.

Electrospinning is a versatile technique for obtaining nano/micro fibers which are able to significantly change the active properties of composite materials and bring in new dimensions to agri-food applications. Composite bio-based packaging materials obtained from whey proteins, functionalized with thyme essential oil (TEO) and reinforced by electrospun polylactic acid (PLA) fibers, represent a promising solution for developing new active food packaging using environmentally friendly materials. The aim of this study is to obtain and characterize one-side-active composite films covered with a PLA fiber mat: (i) WF/G1, WF/G2, and WF/G3 resulting from electrospinning with one needle at different electrospinning times of 90, 150, and 210 min, respectively, and (ii) WF/G4 obtained with two face-to-face needles after 210 min of electrospinning.

Assessing the Potential of Brewer's Spent Grain to Enhance Cookie Physicochemical and Nutritional Profiles.

Brewers' spent grain (BSG), the major by-product of the brewery industry, has high nutritional value, making it suitable for upcycling into products such as healthy, and sustainable cookies. Nonetheless, the incorporation of BSG in cookies can impact their quality, given the increased fiber and protein content. This work explored the effect of replacing wheat flour with BSG at 50% and 75% in cookie formulations, focusing on physical, chemical, and sensory properties.

Improved Functionality, Quality, and Shelf Life of -Type Camel Sausage Fortified with Spirulina as a Natural Ingredient.

The objective of the present work was to examine the effect of incorporating spirulina powder (SP) in -type sausages made exclusively with camel meat, as well as to evaluate its physicochemical, microbiological, and sensory quality attributes and its prebiotic potential. The final purpose was to offer an innovative meat product to increase camel meat consumption. Several innovative fresh sausage formulations were developed using SP (00, 100, 250, and 500 mg/kg) and stored under vacuum conditions with refrigeration at 1 ± 1 °C for 35 days.

Effect of Brewers' Spent Grain Addition to a Fermented Form on Dough Rheological Properties from Different Triticale Flour Cultivars.

Triticale grains and brewers' spent grain (BSG) can be new sources to develop food products. From a socio-economical point of view, this fact is important since triticale is easily adapted to the climatic changes and BSG is a low-cost material which may lead to a "zero-waste" desiderate. In this study, dough rheological properties obtained from different triticale cultivars (Ingen 33, Ingen 35, Ingen 54, and Ingen 93) cultivated in the Republic of Moldova and BSG in a fermented form (BSF) in an addition level of 10% and 17.

Ligand-Independent Vitamin D Receptor Actions Essential for Keratinocyte Homeostasis in the Skin.

Recently, we demonstrated that the alopecia observed in vitamin D receptor gene-deficient (-KO) rats is not seen in rats with a mutant VDR(R270L/H301Q), which lacks ligand-binding ability, suggesting that the ligand-independent action of VDR plays a crucial role in maintaining the hair cycle. Since -KO rats also showed abnormalities in the skin, the relationship between alopecia and skin abnormalities was examined. To clarify the mechanism of actions of vitamin D and VDR in the skin, protein composition, and gene expression patterns in the skin were compared among -KO, -R270L/H301Q, and wild-type (WT) rats.

Proteomic Profile of in Response to Heavy Metal Pollution in Lakes of Northern Patagonia.

Over recent decades, Northern Patagonia in Chile has seen significant growth in agriculture, livestock, forestry, and aquaculture, disrupting lake ecosystems and threatening native species. These environmental changes offer a chance to explore how anthropization impacts zooplankton communities from a molecular-ecological perspective. This study assessed the anthropogenic impact on by comparing its proteomes from two lakes: Llanquihue (anthropized) and Icalma (oligotrophic).

Bioactive Phenolics of L. Subsp. Falezlez: A Molecular and Biochemical Approach to Antioxidant and Urease Inhibitory Activities.

This study examines the chemical composition, antioxidant properties, and urease inhibitory effects of L. subsp. falezlez (Coss.

Data Mining Approach to Melatonin Treatment in Alzheimer's Disease: New Gene Targets and .

Melatonin is a hormone released by the pineal gland that regulates the sleep-wake cycle. It has been widely studied for its therapeutic effects on Alzheimer's disease (AD), particularly through the amyloidosis, oxidative stress, and neuroinflammation pathways. Nevertheless, the mechanisms through which it exerts its neuroprotective effects in AD are still largely unknown.

The Emerging Predictive and Prognostic Role of Aggressive-Variant-Associated Tumor Suppressor Genes Across Prostate Cancer Stages.

Aggressive variant prostate cancer (AVPC) is characterized by a molecular signature involving combined defects in , , and/or (AVPC-TSGs), identifiable through immunohistochemistry or genomic analysis. The reported prevalence of AVPC-TSG alterations varies widely, reflecting differences in assay sensitivity, treatment pressure, and disease stage evolution. Although robust clinical evidence is still emerging, the study of AVPC-TSG alterations in prostate cancer (PCa) is promising.

Design and Characterization of Novel Polymeric Hydrogels with Protein Carriers for Biomedical Use.

Hydrogels are three-dimensional polymeric matrices capable of absorbing significant amounts of water or biological fluids, making them promising candidates for biomedical applications such as drug delivery and wound healing. In this study, novel hydrogels were synthesized using a photopolymerization method and modified with cisplatin-loaded protein carriers, as well as natural extracts of nettle () and chamomile ( L.).

Disrupting SARS-CoV-2 Spike Protein Activity: A Virtual Screening and Binding Assay Study.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a respiratory virus that emerged in late 2019 and rapidly spread worldwide, causing the COVID-19 pandemic. The spike glycoprotein (S protein) plays a crucial role in viral target recognition and entry by interacting with angiotensin, converting enzyme 2 (ACE2), the functional receptor for the virus, via its receptor binding domain (RBD). The RBD availability for this interaction can be influenced by external factors, such as fatty acids.