Simultaneous Classification of Objects with Unknown Rejection (SCOUR) Using Infra-Red Sensor Imagery.

Recognizing targets in infra-red images is an important problem for defense and security applications. A deployed network must not only recognize the known classes, but it must also reject any new or objects without confusing them to be one of the known classes. Our goal is to enhance the ability of existing (or pretrained) classifiers to detect and reject unknown classes.

High-Performance Optical Fiber Displacement Sensor with Extended Linear Range and Sensitivity.

Optical Fiber Displacement Sensors (OFDSs) provide several advantages over conventional sensors, including their compact size, flexibility, and immunity to electromagnetic interference. These features make OFDSs ideal for use in confined spaces, such as turbines, where direct laser access is impossible. A critical aspect of OFDS performance is the geometry of the fiber bundle, which influences key parameters such as sensitivity, range, and dead zones.

Novel Visualization of Building Earthquake Response Recorded by a Dense Network of Sensors.

The strong motion records collected in full-scale structures provide the ultimate evidence of how real structures, in situ, respond to earthquakes. This paper presents a novel method for visualization, in three dimensions (3D), of the collective motion by a dense array of sensors in a building. The method is based on one- and two-dimensional biharmonic spline interpolation of the motion recorded by multiple sensors on the same or multiple floors.

Image-Driven Hybrid Structural Analysis Based on Continuum Point Cloud Method with Boundary Capturing Technique.

Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure.

An Enhanced Approach Using AGS Network for Skin Cancer Classification.

Skin cancer accounts for over 40% of all cancer diagnoses worldwide. However, accurately diagnosing skin cancer remains challenging for dermatologists, as multiple types of skin cancer often appear visually similar. The diagnostic accuracy of dermatologists ranges between 62% and 80%.

Blockchain-Facilitated Cybersecurity for Ubiquitous Internet of Things with Space-Air-Ground Integrated Networks: A Survey.

This article presents a systematic review on blockchain-facilitated cybersecurity solutions for Internet of Things (IoT) devices in space-air-ground integrated networks (SAGIN). First, we identify the objectives and the context of the blockchain-based solutions for SAGIN. Although, typically, the blockchain is primarily used to enhance the trustworthiness of some systems or operations, it is necessary to document exactly in what context the blockchain is used that is specific to the IoT and SAGIN.

Application of Additive Manufacturing and Deep Learning in Exercise State Discrimination.

With the rapid development of sports technology, smart wearable devices play a crucial role in athletic training and health management. Sports fatigue is a key factor affecting athletic performance. Using smart wearable devices to detect the onset of fatigue can optimize training, prevent excessive fatigue and resultant injury, and increase efficiency and safety.

A Review on Face Mask Recognition.

This review offers a comprehensive and in-depth analysis of face mask detection and recognition technologies, emphasizing their critical role in both public health and technological advancements. Existing detection methods are systematically categorized into three primary classes: feaRture-extraction-and-classification-based approaches, object-detection-models-based methods and multi-sensor-fusion-based methods. Through a detailed comparison, their respective workflows, strengths, limitations, and applicability across different contexts are examined.

Evaluation of Semantic Segmentation Performance for a Multimodal Roadside Vehicle Detection System on the Edge.

Discretely monitoring traffic systems and tracking payloads on vehicle targets can be challenging when traversal occurs off main roads where overhead traffic cameras are not present. This work proposes a portable roadside vehicle detection system as part of a solution for tracking traffic along any path. Training semantic segmentation networks to automatically detect specific types of vehicles while ignoring others will allow the user to track payloads present only on certain vehicles of interest, such as train cars or semi-trucks.

Efficient Multi-Task Training with Adaptive Feature Alignment for Universal Image Segmentation.

Universal image segmentation aims to handle all segmentation tasks within a single model architecture and ideally requires only one training phase. To achieve task-conditioned joint training, a task token needs to be used in the multi-task training to condition the model for specific tasks. Existing approaches generate the task token from a text input (e.

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.

Inductive Power Transfer Coil Misalignment Perception and Correction for Wirelessly Recharging Underground Sensors.

Field implementations of fully underground sensor networks face many practical challenges that have limited their overall adoption. Power management is a commonly cited issue, as operators are required to either repeatedly excavate batteries for recharging or develop complex underground power infrastructures. Prior works have proposed wireless inductive power transfer (IPT) as a potential solution to these power management issues, but misalignment is a persistent issue in IPT systems, particularly in applications involving moving vehicles or obscured (e.

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.

Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models.

Wheat is a globally cultivated cereal crop with substantial protein content present in its seeds. This research aimed to develop robust methods for predicting seed protein concentration in wheat seeds using bench-top hyperspectral imaging in the visible, near-infrared (VNIR), and shortwave infrared (SWIR) regions. To fully utilize the spectral and texture features of the full VNIR and SWIR spectral domains, a computer-vision-aided image co-registration methodology was implemented to seamlessly align the VNIR and SWIR bands.

State of the Art of Primary PCI: Present and Future.

Primary percutaneous coronary intervention (PCI) has revolutionized the management of ST-elevation myocardial infarction (STEMI), markedly improving patient outcomes. Despite technological advancements, pharmacological innovations, and refined interventional techniques, STEMI prognosis remains burdened by a persistent incidence of cardiac death and heart failure (HF), with mortality rates plateauing over the last decade. This review examines current practices in primary PCI, focusing on critical factors influencing patient outcomes.

Effects of Spinal Cord Stimulation in Patients with Small Fiber and Associated Comorbidities from Neuropathy After Multiple Etiologies.

The aim of this study was to evaluate the effects of spinal cord stimulation (SCS) on pain, neuropathic symptoms, and other health-related metrics in patients with chronic painful peripheral neuropathy (PN) from multiple etiologies. A prospective single center observational longitudinal cohort study assessed SCS efficacy from April 2023 to May 2024, with follow-ups at 2, 4, 6, and 12 months in 19 patients suffering from the painful polyneuropathy of diverse etiologies: diabetic (DPN), idiopathic (CIAP), chemotherapy-induced (CIPN), and others. Patients were implanted with a neurostimulator (WaveWriter Alpha, Boston Scientific Corporation, Valencia, CA, USA) and percutaneous leads targeting the lower limbs (T10-T11) and, if necessary, the upper limbs (C4-C7).

Utilization Trends of Glucose-Lowering Medications Among Adult Kidney Transplant Recipients with Type 2 Diabetes in the United States.

To date, there are limited studies describing the use of glucose-lowering medications (GLMs) in adult kidney transplant recipients (KTRs), and the uptake of sodium glucose cotransporter-2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP1RAs). Thus, we aimed to evaluate the use of GLMs, including SGLT2i and GLP1RA, among adult KTRs with type 2 diabetes (T2D). This is an ecologic study of adult KTR with T2D.

Comprehensive Review of Lipid Management in Chronic Kidney Disease and Hemodialysis Patients: Conventional Approaches, and Challenges for Cardiovascular Risk Reduction.

: Lipid disorders are very prevalent in patients with chronic kidney disease (CKD) and end-stage kidney disease (ESKD), leading to heightened cardiovascular risk. This review examines the effectiveness of lipid-lowering agents in these populations and explores gaps in the current research. The goal of this review is to assess the efficacy of lipid-lowering therapies in CKD and ESRD patients and identify future research needs.

Endoscopic Resection of Large Non-Pedunculated Colonic Polyps Without Submucosal Injection Is Safe and Effective with Adequate Technique.

: Endoscopic resection with lift polypectomy using submucosal injection (SI) for large non-pedunculated colorectal polyps is recommended to facilitate complete mucosal resection and decrease the risk of perforation; however, there are no studies comparing the safety and efficacy of large polypectomies with and without lift polypectomy. We aimed to evaluate the feasibility and safety of the polypectomy technique without SI compared to the routine use of SI. : We performed a single tertiary center retrospective study evaluating all consecutive large non-pedunculated colorectal polyps (≥20 mm) referred to expert endoscopists in polypectomy from 2018 through 2021.

Plasma Endothelin-1 Levels: Non-Predictors of Alzheimer's Disease Reveal Age Correlation in African American Women.

Alzheimer's disease (AD) and related dementias (ADRD) disproportionately impact racial and ethnic minorities. Contributing biological factors that explain this disparity have been elusive. Moreover, non-invasive biomarkers for early detection of AD are needed.

Assessing the Impact of the Prone Position on Acute Kidney Injury.

: Prone positioning is a standard intervention in managing patients with severe acute respiratory distress syndrome (ARDS) and is known to improve oxygenation. However, its effects on other organs, particularly the kidneys, are less well understood. This study aimed to assess the association between prone positioning and the development of acute kidney injury (AKI), specifically in overweight and obese patients.

Revolutionizing Cardiology: The Role of Artificial Intelligence in Echocardiography.

Artificial intelligence (AI) in echocardiography represents a transformative advancement in cardiology, addressing longstanding challenges in cardiac diagnostics. Echocardiography has traditionally been limited by operator-dependent variability and subjective interpretation, which impact diagnostic reliability. This study evaluates the role of AI, particularly machine learning (ML), in enhancing the accuracy and consistency of echocardiographic image analysis and its potential to complement clinical expertise.

Advancing Insights into Pediatric Macular Diseases: A Comprehensive Review.

Pediatric macular disorders are a diverse group of inherited retinal diseases characterized by central vision loss due to dysfunction and degeneration of the macula, the region of the retina responsible for high-acuity vision. Common disorders in this category include Stargardt disease, Best vitelliform macular dystrophy, and X-linked retinoschisis. These conditions often manifest during childhood or adolescence, with symptoms such as progressive central vision loss, photophobia, and difficulty with fine visual tasks.

Avoiding Chest Wall Morbidity in Outpatient Microvascular Free-Flap Breast Reconstruction.

Removal of the rib and adjacent cartilage is a common step for exposure of the recipient chest vessels in free-flap breast reconstructions. However, this adds both short- and long-term morbidity to the procedure. We describe our experience in avoiding rib removal in microvascular breast reconstruction.

Understanding the Prevalence of Medial Arterial Calcification Among Complex Reconstructive Patients: Insights from a Decade of Experience at a Tertiary Limb Salvage Center.

: Medial arterial calcification (MAC), a distinct form of vascular pathology frequently coexisting with peripheral arterial disease (PAD), poses unique challenges in limb salvage among patients with diabetes, chronic kidney disease, and end-stage renal disease. This study examines the incidence of MAC and its impact on limb salvage outcomes over a decade of experience at a tertiary limb salvage center. : A retrospective review of all complex lower extremity (LE) reconstructions using local flap (LF) or free tissue transfer (FTT), performed from July 2011 to September 2022, was conducted.