Pre-Pilot Usability Study of the Take-A-Breath Project: A Personalized Platform for Respiratory Disease Management.

This study aims to evaluate the patient's platform of the Take-A-Breath project-a Greek project for personalized respiratory disease support. The pre-pilot usability study, involving 11 participants, employed a mixed-methods approach. While calculated scores indicate overall acceptance, concerns are identified, particularly regarding the learning curve needed for the guided inhalation feature, the application's core functionality.

Physicians' Views of a Digital Intervention to Support Respiratory Patients: Take-a-Breath Pre-Pilot Usability Study.

Although eHealth interventions are increasingly recognized as a useful tool to support healthcare, relatively few studies focus on the physician-end's usability. This study aims to evaluate the Healthcare Professional's (HCP) platform of the Take-A-Breath project, a Greek initiative for personalized respiratory disease monitoring, training and self-management. The pre-pilot usability study, involving 10 participants, combines qualitative methods, behavioral observations, and standardized measures of user experience and usability.

Nanoindentation Creep Behavior of Additively Manufactured H13 Steel by Utilizing Selective Laser Melting Technology.

Nowadays, H13 hot work steel is a commonly used hot work die material in the industry; however, its creep behavior for additively manufactured H13 steel parts has not been widely investigated. This research paper examines the impact of volumetric energy density (VED), a critical parameter in additive manufacturing (AM), and the effect of post heat-treatment nitrification on the creep behavior of H13 hot work tool steel, which is constructed through selective laser melting (SLM), which is a powder bed fusion process according to ISO/ASTM 52900:2021. The study utilizes nanoindentation tests to investigate the creep response and the associated parameters such as the steady-state creep strain rate.

Smartwatch interventions in healthcare: A systematic review of the literature.

Objective: The use of smartwatches has attracted considerable interest in developing smart digital health interventions and improving health and well-being during the past few years. This work presents a systematic review of the literature on smartwatch interventions in healthcare. The main characteristics and individual health-related outcomes of smartwatch interventions within research studies are illustrated, in order to acquire evidence of their benefit and value in patient care.

Metal 3D-Printed Bioinspired Lattice Elevator Braking Pads for Enhanced Dynamic Friction Performance.

The elevator industry is constantly expanding creating an increased demand for the integration of high technological tools to increase elevator efficiency and safety. Towards this direction, Additive Manufacturing (AM), and especially metal AM, is one of the technologies that could offer numerous competitive advantages in the production of industrial parts, such as integration of complex geometry, high manufacturability of high-strength metal alloys, etc. In this context, the present study has 3D designed, 3D printing manufactured, and evaluated novel bioinspired structures for elevator safety gear friction pads with the aim of enhancing their dynamic friction performance and eliminating the undesired behavior properties observed in conventional pads.

A cascading model for nudging employees towards energy-efficient behaviour in tertiary buildings.

Energy-related occupant behaviour in the built environment is considered crucial when aiming towards Energy Efficiency (EE), especially given the notion that people are most often unaware and disengaged regarding the impacts of energy-consuming habits. In order to affect such energy-related behaviour, various approaches have been employed, being the most common the provision of recommendations towards more energy-efficient actions. In this work, the authors extend prior research findings in an effort to automatically identify the optimal Persuasion Strategy (PS), out of ten pre-selected by experts, tailored to a user (i.

LP-OPTIMA: A Framework for Prescriptive Maintenance and Optimization of IoT Resources for Low-Power Embedded Systems.

Low-power embedded systems have been widely used in a variety of applications, allowing devices to efficiently collect and exchange data while minimizing energy consumption. However, the lack of extensive maintenance procedures designed specifically for low-power systems, coupled with constraints on anticipating faults and monitoring capacities, presents notable difficulties and intricacies in identifying failures and customized reaction mechanisms. The proposed approach seeks to address the gaps in current resource management frameworks and maintenance protocols for low-power embedded systems.

Data-Driven AI Models within a User-Defined Optimization Objective Function in Cement Production.

This paper explores the energy-intensive cement industry, focusing on a plant in Greece and its mill and kiln unit. The data utilized include manipulated, non-manipulated, and uncontrolled variables. The non-manipulated variables are computed based on the machine learning (ML) models and selected by the minimum value of the normalized root mean square error () across nine (9) methods.

RoBétArmé Project: Human-robot collaborative construction system for shotcrete digitization and automation through advanced perception, cognition, mobility and additive manufacturing skills.

The importance of construction automation has grown worldwide, aiming to deliver new machineries for the automation of roads, tunnels, bridges, buildings and earth-work construction. This need is mainly driven by (i) the shortage and rising costs of skilled workers, (ii) the tremendous increased needs for new infrastructures to serve the daily activities and (iii) the immense demand for maintenance of ageing infrastructure. Shotcrete (sprayed concrete) is increasingly becoming popular technology among contractors and builders, as its application is extremely economical and flexible as the growth in construction repairs in developed countries demand excessive automation of concrete placement.

Exploration of Methodologies for Developing Antimicrobial Fused Filament Fabrication Parts.

Composite 3D printing filaments integrating antimicrobial nanoparticles offer inherent microbial resistance, mitigating contamination and infections. Developing antimicrobial 3D-printed plastics is crucial for tailoring medical solutions, such as implants, and cutting costs when compared with metal options. Furthermore, hospital sustainability can be enhanced via on-demand 3D printing of medical tools.

Enhanced Growth of Bacterial Cells in a Smart 3D Printed Bioreactor.

In the last decade, there has been a notable advancement in diverse bioreactor types catering to various applications. However, conventional bioreactors often exhibit bulkiness and high costs, making them less accessible to many researchers and laboratory facilities. In light of these challenges, this article aims to introduce and evaluate the development of a do-it-yourself (DIY) 3D printed smart bioreactor, offering a cost-effective and user-friendly solution for the proliferation of various bioentities, including bacteria and human organoids, among others.

IoT-Based Agro-Toolbox for Soil Analysis and Environmental Monitoring.

The agricultural sector faces numerous challenges in ensuring optimal soil health and environmental conditions for sustainable crop production. Traditional soil analysis methods are often time-consuming and labor-intensive, and provide limited real-time data, making it challenging for farmers to make informed decisions. In recent years, Internet of Things (IoT) technology has emerged as a promising solution to address these challenges by enabling efficient and automated soil analysis and environmental monitoring.

Promoting Obesity Prevention and Healthy Habits in Childhood: The OCARIoT Experience.

Objective: Long term behavioural disturbances and interventions in healthy habits (mainly eating and physical activity) are the primary cause of childhood obesity. Current approaches for obesity prevention based on health information extraction lack the integration of multi-modal datasets and the provision of a dedicated Decision Support System (DSS) for health behaviour assessment and coaching of children.

Methods: Continuous co-creation process has been applied in the frame of the Design Thinking Methodology, involving children, educators and healthcare professional in the whole process.

Mobile App Interventions for Parkinson's Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review.

Central nervous system diseases (CNSDs) lead to significant disability worldwide. Mobile app interventions have recently shown the potential to facilitate monitoring and medical management of patients with CNSDs. In this direction, the characteristics of the mobile apps used in research studies and their level of clinical effectiveness need to be explored in order to advance the multidisciplinary research required in the field of mobile app interventions for CNSDs.

Development of biodegradable customized tibial scaffold with advanced architected materials utilizing additive manufacturing.

In the last decade, the development of customized biodegradable scaffolds and implants has attracted increased scientific interest due to the fact that additive manufacturing technologies allow for the rapid production of implants with high geometric complexity constructed via commercial biodegradable polymers. In this study, innovative designs of tibial scaffold in form of bone-brick configuration were developed to fill the bone gap utilizing advanced architected materials and bio-inspired diffusion canals. The architected materials and canals provide high porosity, as well as a high surface area to volume ratio in the scaffold facilitating that way in the tissue regeneration process and in withstanding the applied external loads.

DSF Core: Integrated Decision Support for Optimal Scheduling of Lifetime Extension Strategies for Industrial Equipment.

This paper proposes a generic algorithm for industries with degrading and/or failing equipment with significant consequences. Based on the specifications and the real-time status of the production line, the algorithm provides decision support to machinery operators and manufacturers about the appropriate lifetime extension strategies to apply, the optimal time-frame for the implementation of each and the relevant machine components. The relevant recommendations of the algorithm are selected by comparing smartly chosen alternatives after simulation-based life cycle evaluation of Key Performance Indicators (KPIs), considering the short-term and long-term impact of decisions on these economic and environmental KPIs.

A Survey of Robotic Harvesting Systems and Enabling Technologies.

This paper presents a comprehensive review of ground agricultural robotic systems and applications with special focus on harvesting that span research and commercial products and results, as well as their enabling technologies. The majority of literature concerns the development of crop detection, field navigation via vision and their related challenges. Health monitoring, yield estimation, water status inspection, seed planting and weed removal are frequently encountered tasks.

A social robot-based platform for health behavior change toward prevention of childhood obesity.

Childhood obesity is a major public health challenge which is linked with the occurrence of diseases such as diabetes and cancer. The COVID-19 pandemic has forced changes to the lifestyle behaviors of children, thereby making the risk of developing obesity even greater. Novel preventive tools and approaches are required to fight childhood obesity.

Design and Development of a Multi-Functional Bioinspired Soft Robotic Actuator via Additive Manufacturing.

The industrial revolution 4.0 has led to a burst in the development of robotic automation and platforms to increase productivity in the industrial and health domains. Hence, there is a necessity for the design and production of smart and multi-functional tools, which combine several cutting-edge technologies, including additive manufacturing and smart control systems.

Real-time stereo reconstruction of intraoperative scene and registration to preoperative 3D models for augmenting surgeons' view during RAMIS.

Purpose: During minimally invansive surgery (MIS) procedures, there exists an ever-growing/apparent need for providing computer generated visual feedback to the surgeon(s), through a visualization device. While multiple solutions have been proposed in the literature, there is limited evidence of such a system performing reliably in practice, and when it does, it is often tailored to a specific operation type. Another important aspect is regarding the usability of such systems, which typically include complicated and time-consuming steps, and often require the assistance of specialized personnel.

Usability of the Virtual Supermarket Test for Older Adults with and without Cognitive Impairment.

This study conducted a preliminary usability assessment of the Virtual Supermarket Test (VST), a serious game-based self-administered cognitive screening test for mild cognitive impairment (MCI). Twenty-four healthy older adults with subjective cognitive decline and 33 patients with MCI self-administered the VST and then completed the System Usability Scale (SUS). The average SUS score was 83.

Privacy-Preserving Partner Notification Service to Control Sexually Transmitted Infections.

Partner Notification (PN) processes are typically part of wider combination prevention efforts and focus on the notification of sexual partners to prevent Sexually Transmitted Infections (STIs), including Human Immunodeficiency Viruses and viral hepatitis. We present a free, voluntary, anonymous and GDPR-compliant Partner Notification service that offers enhanced security and privacy through a web and mobile application via a unique random codes.

Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review.

Background: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose a significant burden on people and health care systems around the globe. Recently, deep learning (DL) has shown great potential for the development of intelligent mobile health (mHealth) interventions for chronic diseases that could revolutionize the delivery of health care anytime, anywhere.

Objective: The aim of this study is to present a systematic review of studies that have used DL based on mHealth data for the diagnosis, prognosis, management, and treatment of major chronic diseases and advance our understanding of the progress made in this rapidly developing field.

Influence of Selective Laser Melting Additive Manufacturing Parameters in Inconel 718 Superalloy.

Selective laser melting (SLM) is one of the most reliable and efficient procedures for Metal Additive Manufacturing (AM) due to the capability to produce components with high standards in terms of dimensional accuracy, surface finish, and mechanical behavior. In the past years, the SLM process has been utilized for direct manufacturing of fully functional mechanical parts in various industries, such as aeronautics and automotive. Hence, it is essential to investigate the SLM procedure for the most commonly used metals and alloys.