Slow Well-Being Gardening: Creating a Sensor Network for Radiation Therapy Patients via Horticultural Therapeutic Activity.

Well-being can reflect people's psychological conditions and be used alongside physiological parameters to evaluate patients' physical and mental health. The modern medical environment increasingly incorporates digital carriers, human-computer interaction devices, sensible spaces, and the execution of suitable algorithms. Slow design in healthy human-computer interaction is often used to reflect people's dependence on or support from behaviors or objects, promoting the stability of behaviors as well as meaningful and positive changes. Therefore, in this study, we propose a slow sensing model, develop a Slow Well-Being Gardening system, and use it to evaluate behavioral data from radiation therapy patients during treatment sessions and horticultural therapy. This study is based on SENS and slow design, setting the hospital lounge as a sensible space and establishing a sensor system. After a 10-day inspection, the process was evaluated and verified. Ultimately, data from facial detection (smile) and HRV showed that the patients in the experimental group experienced a significant improvement in their well-being, feeling better than those in the control group who maintained the most common state in normal treatment. Therefore, it can be inferred that the Slow Well-Being Gardening model is indeed valid and can be further developed.

Dietary supplements: clinical cholesterol-lowering efficacy and potential mechanisms of action.

This review aims to analyse the efficacy of dietary supplements in reducing plasma cholesterol levels. Focusing on evidence from meta-analyses of randomised controlled clinical trials, with an emphasis on potential mechanisms of action as supported by human, animal, and cell studies. Certain dietary supplements including phytosterols, berberine, viscous soluble dietary fibres, garlic supplements, soy protein, specific probiotic strains, and certain polyphenol extracts could significantly reduce plasma total and low-density lipoprotein (LDL) cholesterol levels by 3-25% in hypercholesterolemic patients depending on the type of supplement. They tended to be more effective in reducing plasma LDL cholesterol level in hypercholesterolemic individuals than in normocholesterolemic individuals. These supplements worked by various mechanisms, such as enhancing the excretion of bile acids, inhibiting the absorption of cholesterol in the intestines, increasing the expression of hepatic LDL receptors, suppressing the activity of enzymes involved in cholesterol synthesis, and activating the adenosine monophosphate-activated protein kinase signalling pathway.

SENS+: A Co-Existing Fabrication System for a Smart DFA Environment Based on Energy Fusion Information.

In factories, energy conservation is a crucial issue. The co-fabrication space is a modern-day equivalent of a new factory type, and it makes use of Internet of Things (IoT) devices, such as sensors, software, and online connectivity, to keep track of various building features, analyze data, and produce reports on usage patterns and trends that can be used to improve building operations and the environment. The co-fabrication user requires dynamic and flexible space, which is different from the conventional user's usage. Because the user composition in a co-fabrication space is dynamic and unstable, we cannot use the conventional approach to assess their usage and rentals. Prototyping necessitates a specifically designed energy-saving strategy. The research uses a "seeing-moving-seeing" design thinking framework, which enables designers to more easily convey their ideas to others through direct observation of the outcomes of their intuitive designs and the representation of their works through design media. The three components of human behavior, physical manufacture, and digital interaction are primarily the focus of this work. The computing system that connects the physical machine is created through communication between the designer and the digital interface, giving the designer control over the physical machine. It is an interactive fabrication process formed by behavior. The Sensible Energy System+ is an interactive fabrication process of virtual and real coexistence created by combining the already-existing technology, the prototype fabrication machine, and SENS. This process analyzes each step of the fabrication process and energy, fits it into the computing system mode to control the prototype fabrication machine, and reduces the problem between virtual and physical fabrication and energy consumption.

A Network Sensor Fusion Approach for a Behaviour-Based Smart Energy Environment for Co-Making Spaces.

User behaviour and choice is a significant parameter in the consumption patterns of energy in the built environment. This paper introduces a behavior-based approach for developing smart energy applications. With the rapid development of wireless sensor networks and the Internet of Things (IoT), human-computer interfaces can be created through the mapping of user experiences. These applications can provide users with dynamic feedback on their energy consumption patterns in their built environment. The paper describes a "Sensible Energy System" (SENS) that is based on user experience design methods with sensor network technology. Through SENS, solar energy simulation is combined with device consumption data in order to achieve an IoT network to facilitate the interaction between user behaviors and electricity consumption. The interaction between users and devices through SENS can not only optimize power consumption, but also provide consumers with additional choice and dynamic decision making regarding their consumption. This article provides an (1) understanding and analysis of users' spatial interaction, explains the (2) planning of the new smart environment design and user experiences, discusses (3) designing a suitable Wireless sensor network (WSN) agent and energy connection, describes (4) the information that has been collected, and (5) incorporates a rooftop solar potential simulation for predicting energy outputs into the sensor network model.