Semi-supervised medical image segmentation via weak-to-strong perturbation consistency and edge-aware contrastive representation.

Despite that supervised learning has demonstrated impressive accuracy in medical image segmentation, its reliance on large labeled datasets poses a challenge due to the effort and expertise required for data acquisition. Semi-supervised learning has emerged as a potential solution. However, it tends to yield satisfactory segmentation performance in the central region of the foreground, but struggles in the edge region.

Bioinspired Smart Triboelectric Soft Pneumatic Actuator-Enabled Hand Rehabilitation Robot.

Quantitative assessment for post-stroke spasticity remains a significant challenge due to the encountered variable resistance during passive stretching, which can lead to the widely used modified Ashworth scale (MAS) for spasticity assessment depending heavily on rehabilitation physicians. To address these challenges, a high-force-output triboelectric soft pneumatic actuator (TENG-SPA) inspired by a lobster tail is developed. The bioinspired TENG-SPA can generate approximately 20 N at 0.

Empowering People with Disabilities in Smart Homes Using Predictive Informing.

The possibilities of the Ambient Assisted Living (AAL)/Enhanced Living Environments (ELE) concept in the environment of a smart home were investigated to improve accessibility and improve the quality of life of a person with disabilities. This paper focuses on the concept of predictive information for a person with disabilities in a smart home environment concept where artificial intelligence (AI) and machine learning (ML) systems use data on the user's preferences, habits, and possible incident situations. A conceptual mathematical model is proposed, the purpose of which is to provide predictive user information from defined data sets.

Personalized Federated Learning Scheme for Autonomous Driving Based on Correlated Differential Privacy.

In the era of big data, advanced data processing devices and smart sensors greatly benefit us in many areas. As for each individual user, data sharing can be an essential part of the process of data collection and transmission. However, the issue of constant attacks on data privacy arouses huge concerns among the public.

Resilient Privacy Preservation Through a Presumed Secrecy Mechanism for Mobility and Localization in Intelligent Transportation Systems.

An intelligent transportation system (ITS) offers commercial and personal movement through the smart city (SC) communication paradigms with hassle-free information sharing. ITS designs and architectures have improved via information and communication technologies in recent years. The information shared through the communication medium in SCs is exposed to adversary risk, resulting in privacy issues.

Temperature Uniformity Control of 12-Inch Semiconductor Wafer Chuck Using Double-Wall TPMS in Additive Manufacturing.

In semiconductor inspection equipment, a chuck used to hold a wafer is equipped with a cooling or heating system for temperature uniformity across the surface of the wafer. Surface temperature uniformity is important for increasing semiconductor inspection speed. Triply periodic minimal surfaces (TPMSs) are proposed to enhance temperature uniformity.

The Potential for High-Priority Care Based on Pain Through Facial Expression Detection with Patients Experiencing Chest Pain.

Background And Objective: Cardiovascular disease (CVD), one of the chronic non-communicable diseases (NCDs), is defined as a cardiac and vascular disorder that includes coronary heart disease, heart failure, peripheral arterial disease, cerebrovascular disease (stroke), congenital heart disease, rheumatic heart disease, and elevated blood pressure (hypertension). Having CVD increases the mortality rate. Emotional stress, an indirect indicator associated with CVD, can often manifest through facial expressions.

Assessing Vegetation Canopy Growth Variations in Northeast China.

Studying climate change's impact on vegetation canopy growth and senescence is significant for understanding and predicting vegetation dynamics. However, there is a lack of adequate research on canopy changes across the lifecycles of different vegetation types. Using GLASS LAI (leaf area index) data (2001-2020), we investigated canopy development (April-June), maturity (July-August), and senescence (September-October) rates in Northeast China, focusing on their responses to preseason climatic factors.

Design of an improved model using federated learning and LSTM autoencoders for secure and transparent blockchain network transactions.

With the advancement of this digital era and the emergence of DApps and Blockchain, secure, robust and transparent network transaction has become invaluable today. These traditional methods of securing the transactions and maintaining transparency have encountered many challenges. It includes some such issues as follows: data privacy, centralized vulnerability, inefficiency in fraud detection and much more.

Smart Insulin Pen in Pregnant Women with Type 1 Diabetes: An Encouraging Case Series.

The management of type 1 diabetes in pregnancy with new technologies is challenging. Sometimes the complexity of new-generation systems such as "continuous subcutaneous insulin infusion, CSII" and patient or provider preference do not allow their use, so women with type 1 diabetes in pregnancy continue to be treated with subcutaneous multiple-injection insulin therapy using pens. Smart insulin pens are new tools that allow for data collection on insulin dose and time of administration and have additional connectivity features.

Empirical and methodological foundations on the impact of climate-smart agriculture on food security studies: Review.

The progress of Ethiopia's agriculture is constrained by climate change leaving smallholder farmers vulnerable. As a panacea to the challenge, development institutions, governments, and research organizations are progressively promoting climate-smart agriculture (CSA) to maximize productivity, increase the resilience of livelihoods and farming systems (adaptation), and minimize or stop greenhouse gas emissions to the atmosphere (mitigation). This review synthesized knowledge on the prospects of CSA and climate change in addressing the adverse effects of climate change and variability by revising 99 peer-reviewed journal articles.

Resistive memory-based zero-shot liquid state machine for multimodal event data learning.

The human brain is a complex spiking neural network (SNN) capable of learning multimodal signals in a zero-shot manner by generalizing existing knowledge. Remarkably, it maintains minimal power consumption through event-based signal propagation. However, replicating the human brain in neuromorphic hardware presents both hardware and software challenges.

Smart crop disease monitoring system in IoT using optimization enabled deep residual network.

The Internet of Things (IoT) has recently attracted substantial interest because of its diverse applications. In the agriculture sector, automated methods for detecting plant diseases offer numerous advantages over traditional methods. In the current study, a new model is developed to categorize plant diseases within an IoT network.

Machine learning boosts wind turbine efficiency with smart failure detection and strategic placement.

The research study objective seeks to improve the efficiency of wind turbines using state-of-the-art techniques in the domain of ML, making wind energy the key player in fashioning a favorable future. Wind Turbine Health Monitoring (WTHM) is typically achieved through either vibration analysis or by using Supervisory Control and Data Acquisition (SCADA) data of wind turbines, wherein conventional fault pattern identification is a time-consuming, guesswork process. This work proposed an intelligent automated approach to early fault detection through the implementation of the HARO (Huber Adam Regression Optimizer) model, which combines Transformer networks with Lasso Regression and the Adam optimizer.

Reliability of sitting posture between physical therapist video-based evaluation and SMART IMU system using rapid upper limb assessment (RULA).

This study investigates the ergonomic assessment of sitting postures and the potential for work-related musculoskeletal disorders (WMSDs) in office environments by comparing traditional physical therapist evaluations with Inertial Measurement Unit (IMU) technology by determining the reliability and accuracy of sitting posture assessment using the rapid upper limb assessment (RULA) method. In this experiment, neck and body angle data is collected from twenty participants while sitting and working. The study aims to capture and compare the neck and trunk posture score based RULA protocol system to evaluate ergonomic risks.

Smart furniture using radar technology for cardiac health monitoring.

The integration of radar technology into smart furniture represents a practical approach to health monitoring, circumventing the concerns regarding user convenience and privacy often encountered by conventional smart home systems. Radar technology's inherent non-contact methodology, privacy-preserving features, adaptability to diverse environmental conditions, and high precision characteristics collectively establish it a compelling alternative for comprehensive health monitoring within domestic environments. In this paper, we introduce a millimeter (mm)-wave radar system positioned strategically behind a seat, featuring an algorithm capable of identifying unique cardiac waveform patterns for healthy subjects.

Impact of Adding -hexylamine to Nickel Metallophotoredox C-N Coupling to Form Diarylamines.

The mechanistic understanding of how alkylamines impact Ni-metallophotoredox C-N coupling to form diarylamines remains unclear. In this study, 12-alkylamines were evaluated as additives to determine their effects on the synthesis of diarylamines in a flow photochemical system. Notably, -hexylamine demonstrated the most significant promotional effect.

Plug-In Design of the Microneedle Electrode Array for Multi-Parameter Biochemical Sensing in Gouty Arthritis.

Gouty arthritis is one of the most common forms of inflammatory arthritis and has brought a significant burden on patients and society. Current strategies for managing gout primarily focus on long-term urate-lowering therapy. With the rapid advancement of point-of-care testing (POCT) technology, continuous monitoring of gout-related biomarkers like uric acid (UA) or inflammatory cytokines can provide rapid and personalized diagnosis for gout management.

Implications of Biomaterials for Chronic Wounds.

The use of biomaterials in treating and managing chronic wounds represents a significant challenge in global healthcare due to the complex nature of these wounds, which are slow to heal and can lead to complications such as frequent infections and diminished quality of life for patients. Chronic wounds, which can arise from conditions like diabetes, poor circulation, and pressure sores, pose distinct challenges in wound care, necessitating the development of specialized dressings. The pathophysiology of chronic wounds is thoroughly examined in this article, with particular attention paid to the cellular and molecular defects at work and the therapeutic guidelines.

Biomimetic Fingerprint-like Unclonable Optical Anticounterfeiting System with Selectively In Situ-Synthesized Perovskite Quantum Dots Embedded in Spontaneous-Phase-Separated Polymers.

Anticounterfeiting technologies meet challenges in the Internet of Things era due to the rapidly growing volume of objects, their frequent connection with humans, and the accelerated advance of counterfeiting/cracking techniques. Here, we, inspired by biological fingerprints, present a simple anticounterfeiting system based on perovskite quantum dot (PQD) fingerprint physical unclonable function (FPUF) by cooperatively utilizing the spontaneous-phase separation of polymers and selective in situ synthesis PQDs as an entropy source. The FPUFs offer red, green, and blue full-color fingerprint identifiers and random three-dimensional (3D) morphology, which extends binary to multivalued encoding by tuning the perovskite and polymer components, enabling a high encoding capacity (about 10, far surpassing that of biometric fingerprints).

An intelligent attention based deep convoluted learning (IADCL) model for smart healthcare security.

In recent times, there has been rapid growth of technologies that have enabled smart infrastructures-IoT-powered smart grids, cities, and healthcare systems. But these resource-constrained IoT devices cannot be protected by existing security mechanisms against emerging cyber threats. The aim of the paper is to present an improved security for smart healthcare IoT systems by developing an architecture for IADCL.

Chromic Electrospun Polymer Nanofibers: Preparation, Applications, and the Future.

Physical understanding and determination of different analytes without the need for advanced and additional equipment are highly important, which can be achieved by using stimuli-induced chromic materials. Physical and chemical incorporation of responsive chromophores into different polymers results in the fabrication of chromic polymers. Chromic electrospun nanofibers are prepared using the electrospinning technique, and their stimuli-responsivity is improved due to their high surface-to-volume ratio.

Isles of autonomy: the rise of intelligent technologies.

A critical metaphor for the development, implementation and penetration of autonomous machine systems into the world of human work is presented. Most especially, the ' concept is articulated which argues that the expropriation of human pre-eminence will be marked by a series of threshold events, some of which are, even now becoming evident. In particular, it indicates that there will be a watershed event in which differing and distinct expressions of applied autonomous systems will spontaneously coalesce to produce an emergent, general artificial intelligence.