Incremental Structure from Motion for Small-Scale Scenes Based on Auxiliary Calibration.

Scarce feature points are a critical limitation affecting the accuracy and stability of incremental structure from motion (SfM) in small-scale scenes. In this paper, we propose an incremental SfM method for small-scale scenes, combined with an auxiliary calibration plate. This approach increases the number of feature points in sparse regions, and we randomly generate feature points within those areas.

Opportunities and Challenges for Clinical Practice in Detecting Depression Using EEG and Machine Learning.

Major depressive disorder (MDD) is associated with substantial morbidity and mortality, yet its diagnosis and treatment rates remain low due to its diverse and often overlapping clinical manifestations. In this context, electroencephalography (EEG) has gained attention as a potential objective tool for diagnosing depression. This study aimed to evaluate the effectiveness of EEG in identifying MDD by analyzing 140 EEG recordings from patients diagnosed with depression and healthy volunteers.

Evaluating the Performance Characteristics of Pressure Monitoring Systems.

Measuring interface pressure is currently used in a variety of settings, e.g., automotive or clinical, to evaluate pressure distribution at support surface interfaces.

Image-Based Detection and Classification of Malaria Parasites and Leukocytes with Quality Assessment of Romanowsky-Stained Blood Smears.

Malaria remains a global health concern, with 249 million cases and 608,000 deaths being reported by the WHO in 2022. Traditional diagnostic methods often struggle with inconsistent stain quality, lighting variations, and limited resources in endemic regions, making manual detection time-intensive and error-prone. This study introduces an automated system for analyzing Romanowsky-stained thick blood smears, focusing on image quality evaluation, leukocyte detection, and malaria parasite classification.

Research on End-Effector Position Error Compensation of Industrial Robotic Arm Based on ECOA-BP.

Industrial robotic arms are often subject to significant end-effector pose deviations from the target position due to the combined effects of nonlinear deformations such as link flexibility, joint compliance, and end-effector load. To address this issue, a study was conducted on the analysis and compensation of end-position errors in a six-degree-of-freedom robotic arm. The kinematic model of the robotic arm was established using the Denavit-Hartenberg (DH) parameter method, and a rigid-flexible coupled virtual prototype model was developed using ANSYS and ADAMS.

DynamicVLN: Incorporating Dynamics into Vision-and-Language Navigation Scenarios.

Traditional Vision-and-Language Navigation (VLN) tasks require an agent to navigate static environments using natural language instructions. However, real-world road conditions such as vehicle movements, traffic signal fluctuations, pedestrian activity, and weather variations are dynamic and continually changing. These factors significantly impact an agent's decision-making ability, underscoring the limitations of current VLN models, which do not accurately reflect the complexities of real-world navigation.

Reusable Biosensor for Easy RNA Detection from Unfiltered Saliva.

Biosensors are transforming point-of-care diagnostics by simplifying the detection process and enabling rapid, accurate testing. This study introduces a novel, reusable biosensor designed for direct viral RNA detection from unfiltered saliva, targeting SARS-CoV-2. Unlike conventional methods requiring filtration, our biosensor leverages a unique electrode design that prevents interference from saliva debris, allowing precise measurements.

Structural Fatigue Life Monitoring with Piezoelectric-Based Sensors: Fundamentals, Current Advances, and Future Directions.

Structural fatigue can lead to catastrophic failures in various engineering applications and must be properly monitored and effectively managed. This paper provides a state-of-the-art review of recent developments in structural fatigue monitoring using piezoelectric-based sensors. Compared to alternative sensing technologies, piezoelectric sensors offer distinct advantages, including compact size, lightweight design, low cost, flexible formats, and high sensitivity to dynamic loads.

Performance Evaluation of Deep Learning Image Classification Modules in the MUN-ABSAI Ice Risk Management Architecture.

The retreat of Arctic sea ice has opened new maritime routes, offering faster shipping opportunities; however, these routes present significant navigational challenges due to the harsh ice conditions. To address these challenges, this paper proposes a deep learning-based Arctic ice risk management architecture with multiple modules, including ice classification, risk assessment, ice floe tracking, and ice load calculations. A comprehensive dataset of 15,000 ice images was created using public sources and contributions from the Canadian Coast Guard, and it was used to support the development and evaluation of the system.

Spatial Characterization of Woody Species Diversity in Tropical Savannas Using GEDI and Optical Data.

Developing the capacity to monitor species diversity worldwide is of great importance in halting biodiversity loss. To this end, remote sensing plays a unique role. In this study, we evaluate the potential of Global Ecosystem Dynamics Investigation (GEDI) data, combined with conventional satellite optical imagery and climate reanalysis data, to predict in situ alpha diversity (Species richness, Simpson index, and Shannon index) among tree species.

A Combined Frame Difference and Convolution Method for Moving Vehicle Detection in Satellite Videos.

To address the challenges of missed detections caused by insufficient shape and texture features and blurred boundaries in existing detection methods, this paper introduces a novel moving vehicle detection approach for satellite videos. The proposed method leverages frame difference and convolution to effectively integrate spatiotemporal information. First, a frame difference module (FDM) is designed, combining frame difference and convolution.

Heat Stroke Warning System Prototype for Athletes: A Pilot Study.

This research has developed a heat stroke warning system prototype for athletes utilizing the following sensors: DHT22, GY-906-BAA MLX90614, MAX30102. The device calculates the heat stroke risk and notifies users. The data is recorded, stored, displayed on a free-access website which graphs body temperature, ambient temperature, humidity, heart rate and heat stroke risk, and provides notifications for athletes engaged in outdoor activities.

Evaluating ChatGPT-4 for the Interpretation of Images from Several Diagnostic Techniques in Gastroenterology.

Several artificial intelligence systems based on large language models (LLMs) have been commercially developed, with recent interest in integrating them for clinical questions. Recent versions now include image analysis capacity, but their performance in gastroenterology remains untested. This study assesses ChatGPT-4's performance in interpreting gastroenterology images.

Explainable AI in Digestive Healthcare and Gastrointestinal Endoscopy.

An important impediment to the incorporation of artificial intelligence-based tools into healthcare is their association with so-called black box medicine, a concept arising due to their complexity and the difficulties in understanding how they reach a decision. This situation may compromise the clinician's trust in these tools, should any errors occur, and the inability to explain how decisions are reached may affect their relationship with patients. Explainable AI (XAI) aims to overcome this limitation by facilitating a better understanding of how AI models reach their conclusions for users, thereby enhancing trust in the decisions reached.

Detection of Acromion Types in Shoulder Magnetic Resonance Image Examination with Developed Convolutional Neural Network and Textural-Based Content-Based Image Retrieval System.

The morphological type of the acromion may play a role in the etiopathogenesis of various pathologies, such as shoulder impingement syndrome and rotator cuff disorders. Therefore, it is important to determine the acromion's morphological types accurately and quickly. In this study, it was aimed to detect the acromion shape, which is one of the etiological causes of chronic shoulder disorders that may cause a decrease in work capacity and quality of life, on shoulder MR images by developing a new model for image retrieval in Content-Based Image Retrieval (CBIR) systems.

Altered Pattern of Serum N-Glycome in Subarachnoid Hemorrhage and Cerebral Vasospasm.

: Subarachnoid hemorrhage is a serious condition caused by ruptured intracranial aneurysms, resulting in severe disability mainly in young adults. Cerebral vasospasm is one of the most common complication of subarachnoid hemorrhage; thus, active prevention is key to improve the prognosis. The glycosylation of proteins is a critical quality attribute which is reportedly altered in patients diagnosed with acute ischemic stroke.

-Derived Near-Infrared Carbon Dots for Bioimaging and Antimicrobial Applications.

The use of biomass feedstocks for producing high-value-added chemicals is gaining significant attention in the academic community. In this study, near-infrared carbon dots (NIR-CDs) with antimicrobial and bioimaging functions were prepared from branches and leaves using a novel green synthesis approach. The spectral properties of the synthesized NIR-CDs were characterized by ultraviolet-visible (UV-Vis) absorption and fluorescence spectroscopy.

Evaluation of Mechanochemically Prepared CePO∙HO Nanoparticles as UV Filter for Photoprotective Formulations.

Rhabdophane, CePO∙HO, nanoparticles were prepared by mechanochemical synthesis with different durations and thoroughly characterized by various characterization techniques. X-ray diffraction analysis showed that the optimal synthesis duration was 15 min, since, in this case, pure rhabdophane is obtained, without traces of contamination by the vessel material. The size of the obtained nanoparticles, as determined from high-resolution transmission electron microscopy images, was around 5 nm.

The General Principle of the Warburg Effect as a Possible Approach for Cancer Immunotherapy: The Regulatory Effect of Plant Extracts Could Change the Game.

The interpretation of the biochemistry of immune metabolism could be considered an attractive scientific field of biomedicine research. In this review, the role of glycolysis in macrophage polarization is discussed together with mitochondrial metabolism in cancer cells. In the first part, the focus is on the Warburg effect and redox metabolism during macrophage polarization, cancer development, and management of the immune response by the cancer cells.

Hemoglobin Variants as Targets for Stabilizing Drugs.

Hemoglobin is an oxygen-transport protein in red blood cells that interacts with multiple ligands, e.g., oxygen, carbon dioxide, carbon monoxide, and nitric oxide.

Mechanism and Characterization of Bicomponent-Filler-Reinforced Natural Rubber Latex Composites: Experiment and Molecular Dynamics (MD).

The incorporation of reinforcing fillers into natural rubber latex (NR) to achieve superior elasticity and mechanical properties has been widely applied across various fields. However, the tendency of reinforcing fillers to agglomerate within NR limits their potential applications. In this study, multi-walled carbon nanotube (MWCNT)-silica (SiO)/NR composites were prepared using a solution blending method, aiming to enhance the performance of NR composites through the synergistic effects of dual-component fillers.

Characteristics of Hydrogels as a Coating for Microneedle Transdermal Delivery Systems with Agomelatine.

Agomelatine (AGM) is an effective antidepressant with low oral bioavailability due to intensive hepatic metabolism. Transdermal administration of agomelatine may increase its bioavailability and reduce the doses necessary for therapeutic effects. However, transdermal delivery requires crossing the barrier.

Resveratrol-Based Carbamates as Selective Butyrylcholinesterase Inhibitors: Design, Synthesis, Computational Study and Biometal Complexation Capability.

Considering our previous experience in the design of new cholinesterase inhibitors, especially resveratrol analogs, in this research, the basic stilbene skeleton was used as a structural unit for new carbamates designed as potentially highly selective butyrylcholinesterase (BChE) inhibitors with excellent absorption, distribution, metabolism, excretion and toxicity ADMET properties. The inhibitory activity of newly prepared carbamates - was tested toward the enzymes acetylcholinesterase (AChE) and BChE. In the tested group of compounds, the leading inhibitors were and , which achieved excellent selective inhibitory activity for BChE with IC values of 0.

Development of New Biosorbent Based on Crosslinked Chitosan Beads with High Brilliant Blue FCF Removal Efficiency.

Effluents containing synthetic anionic dyes can pose a risk to ecosystems, and they must be treated before their release to the environment. Biosorption, a simple and effective process, may be a promising solution for treating these effluents. In this work, chitosan beads were crosslinked with epichlorohydrin to produce a highly stable and performant biosorbent to remove Brilliant Blue FCF dye.

Cross-Regional Elemental Comparison of Mussels Using Total Reflection X-Ray Fluorescence (TXRF).

This study evaluates the effectiveness of Total Reflection X-ray Fluorescence for multi-element analysis in mussels, focusing on sensitivity, precision, and detection limits. Additionally, it offers a cross-regional comparison of elemental composition in mussels from aquaculture farms in Italy, Spain, and Chile. TXRF, using suspensions of mussel samples, proved effective in detecting minor and trace elements, with recovery rates over 80% for Fe, Cu, Zn, As, and Sr.