[Interdisciplinary Application of Smart Technology in Psychiatric Care].

The popularization of smart technology is a global phenomenon. The increasing ubiquity of smartphones offers the potential to apply smart technology in areas such as healthcare and behavioral change interventions. Mobile health services may enhance the effectiveness and resolve the shortcomings of traditional medical services, which cannot continuously and instantly track changes in disease symptoms. The popularity of mobile phones has led to the emergence of mobile health applications. Mobile health applications use active and passive methods to collect data and transmit information. Studies have confirmed the feasibility and acceptance of these applications in assessing and detecting diseases and in mental health interventions. In this article, the limitations of traditional psychiatric medical diagnosis and the opportunity to develop mobile health using information and communication technology are discussed, and related empirical research on using smart technology to evaluate and detect symptoms is explored using the example of bipolar disorders. In addition, the benefits and future prospects of onset alert and the development of healthcare models for action are highlighted. In the future, we look forward to developing mobile health applications that meet the needs of healthcare in Taiwan. Furthermore, we recommend more research and investment in related fields to accumulate more extensive empirical evidence.

An RFID Based Smart Feeder for Hummingbirds.

We present an interdisciplinary effort to record feeding behaviors and control the diet of a hummingbird species (Phaethornis longirostris, the long-billed hermit or LBH) by developing a Radio Frequency Identification (RFID) based smart feeder. The system contains an RFID reader, a microcontroller, and a servo-controlled hummingbird feeder opener; the system is presented as a tool for studying the cognitive ability of the LBH species. When equipped with glass capsule RFID tags (which are mounted on the hummingbird), the smart feeder can provide specific diets for predetermined sets of hummingbirds at the discretion of biologists. This is done by reading the unique RFID tag on the hummingbirds and comparing the ID number with the pre-programmed ID numbers stored in the smart feeder. The smart feeder records the time and ID of each hummingbird visit. The system data is stored in a readily available SD card and is powered by two 9 V batteries. The detection range of the system is approximately 9-11 cm. Using this system, biologists can assign the wild hummingbirds to different experimental groups and monitor their diets to determine if they develop a preference to any of the available nectars. During field testing, the smart feeder system has demonstrated consistent detection (when compared to detections observed by video-recordings) of RFID tags on hummingbirds and provides pre-designed nectars varying water and sugar concentrations to target individuals. The smart feeder can be applied to other biological and environmental studies in the future.

Large-scale renewable energy brings regionally disproportional air quality and health co-benefits in China.

Developing renewable energy could jointly reduce air pollution, greenhouse gas emissions, and bring air pollution-related health co-benefits. However, the temporal and sub-national distributions of investment costs and human health co-benefits from renewable energy deployment remain unclear. To investigate this gap, we linked multiple models for a more comprehensive assessment of the economic-environmental-health co-benefits of renewable energy development in China. The results show that developing renewable energy can avoid 0.6 million premature mortalities, 151 million morbidities, and 111 million work-loss days in 2050. Meanwhile, the human health and economic co-benefits vary substantially across regions in China. Renewable energy can undoubtedly bring health and economic co-benefits. Nevertheless, the economic benefits lag considerably behind the high initial investment cost, first negative in 2030 (-0.6 trillion Yuan) and then positive in 2050 (2.9 trillion Yuan). Hence, renewable energy deployment strategy must be carefully designed considering the regional disparities.

Renewable-to-ammonia: Configuration strategy and technoeconomic analysis.

The increasing demand for chemical raw materials has provided opportunities for the ammonia (NH3) industry. However, little attention has been devoted to the economic feasibility of renewable-to-ammonia (RE2A). Therefore, this paper proposes a technoeconomic model to research the optimal capacity configuration and quantify the levelized cost of ammonia (LCOA) for RE2A, which is a retrofitted plant based on coal-to-ammonia (C2A). A cost model of C2A is established as a benchmark to evaluate the economic feasibility of RE2A. A case study in Inner Mongolia is adopted, which shows that the monthly NH3 output is 7-11×103t, which satisfies actual industrial production. The LCOA of RE2A is 469$/t, with investment in wind turbines accounting for 58%, which is lower than the NH3 market price (605$-650$/t). The LCOA of RE2A will equal that of C2A with a carbon tax of 47.1$/t CO2, which confirms the economic advantages of RE2A in the future.

Fostering collective climate action and leadership: Insights from a pilot experiment involving mindfulness and compassion.

Recent research suggests that mindfulness, compassion, and self-compassion relate to inner transformative qualities/capacities and intermediary factors that can support increased pro-environmental behavior and attitudes across individual, collective, organizational, and system levels. However, current insights focus on the individual level, are restricted to certain sustainability fields, and wider experimental evidence is scarce and contradictory. Our pilot study addresses this gap and tests the aforementioned proposition in the context of an intervention: an EU Climate Leadership Program for high-level decision-makers. The intervention was found to have significant effects on transformative qualities/capacities, intermediary factors, and pro-environmental behaviors and engagement across all levels. The picture is, however, more complex for pro-environmental attitudes. With due limitations (e.g., small sample size), this preliminary evidence confirms the feasibility and potential of mindfulness- and compassion-based interventions to foster inner-outer transformation for sustainability and climate action. Aspects that should be taken into account in larger confirmatory trials are discussed.

Framing to reduce present bias in infrastructure design intentions.

Infrastructure professionals (N = 261) were randomly assigned to either a future or present-framed project description and asked to recommend design attributes for an infrastructure project. The future-framed condition led professionals to propose a significantly longer infrastructure design life, useful life to the community, and acceptable return on financial investment. The findings suggest a straightforward and inexpensive way to lessen present bias in various design contexts.

Scavenging ROS to Alleviate Acute Liver Injury by ZnO-NiO@COOH.

Currently, the incidence of acute liver injury (ALI) is increasing year by year, and infection with coronavirus disease 2019 (COVID-19) can also induce ALI, but there are still no targeted therapeutic drugs. ZnO-NiO particles is mainly used to clean up reactive oxygen species (ROS) in industrial wastewater, and it is insoluble in water. Its excellent properties are discovered and improved by adding shuttle-based bonds to make it more water-soluble. ZnO-NiO@COOH particles are synthetically applied to treat ALI. The p-n junction in ZnO-NiO@COOH increases the surface area and active sites, thereby creating large numbers of oxygen vacancies, which can quickly adsorb ROS. The content in tissues and serum levels of L-glutathione (GSH) and the GSH/oxidized GSH ratio are measured to assess the capacity of ZnO-NiO@COOH particles to absorb ROS. The ZnO-NiO@COOH particles significantly reduce the expression levels of inflammatory factors (i.e., IL-1, IL-6, and TNF-α), macrophage infiltration, and granulocyte activation. ZnO-NiO@COOH rapidly adsorb ROS in a short period of time to block the generation of inflammatory storms and gain time for the follow-up treatment of ALI, which has important clinical significance.

IvCDS: An End-to-End Driver Simulator for Personal In-Vehicle Conversational Assistant.

An advanced driver simulator methodology facilitates a well-connected interaction between the environment and drivers. Multiple traffic information environment language processing aims to help drivers accommodate travel demand: safety prewarning, destination navigation, hotel/restaurant reservation, and so on. Task-oriented dialogue systems generally aim to assist human users in achieving these specific goals by a conversation in the form of natural language. The development of current neural network based dialogue systems relies on relevant datasets, such as KVRET. These datasets are generally used for training and evaluating a dialogue agent (e.g., an in-vehicle assistant). Therefore, a simulator for the human user side is necessarily required for assessing an agent system if no real person is involved. We propose a new end-to-end simulator to operate as a human driver that is capable of understanding and responding to assistant utterances. This proposed driver simulator enables one to interact with an in-vehicle assistant like a real person, and the diversity of conversations can be simply controlled by changing the assigned driver profile. Results of our experiment demonstrate that this proposed simulator achieves the best performance on all tasks compared with other models.