Blockchain technology has become significant for financial sectors, especially digital payment systems, offering enhanced security, transparency, and efficiency. However, there is limited research on the factors influencing user trust in and acceptance of blockchain adoption in digital payment systems. This systematic review provides insight into the key factors impacting consumers’ perceptions and behaviours towards embracing blockchain technology. A total of 1859 studies were collected, with 48 meeting the criteria for comprehensive analysis. The results showed that security, privacy, transparency, and regulation are the most significant factors influencing trust for blockchain adoption. The most influential factors identified in the Unified Theory of Acceptance and Use of Technology (UTAUT) model include performance expectancy, effort expectancy, social influence, and facilitating conditions. Incorporating a trust and acceptance model could be a viable approach to tackling obstacles and ensuring the successful integration of blockchain technology into digital payment systems. Understanding these factors is crucial for creating a favourable atmosphere for adopting blockchain technology in digital payments. User-perspective research on blockchain adoption in digital payment systems is still insufficient, and this aspect still requires further investigation. Blockchain adoption in digital payment systems has not been sufficiently conducted from the user’s perspective, and there is a scope for it to be carried out. This review aims to shed light on the factors of trust in and acceptance of blockchain adoption in digital payment systems so that the full potential of blockchain technology can be realised. Understanding these factors and their intricate connections is imperative in fostering a conducive environment for the widespread acceptance of blockchain technology in digital payments.

Porous carbon derived from grape marc (GM) was synthesized via carbonization and chemical activation processes. Extrinsic nitrogen (N)-dopant in GM, activated by KOH, could render its potential use in supercapacitors effective. The effects of chemical activators such as potassium hydroxide (KOH) and zinc chloride (ZnCl₂) were studied to compare their activating power toward the development of pore-forming mechanisms in a carbon electrode, making them beneficial for energy storage. GM carbon impregnated with KOH for activation (KAC), along with urea as the N-dopant (KAC_urea), exhibited better morphology, hierarchical pore structure, and larger surface area (1356 m² g⁻¹) than the GM carbon activated by ZnCl₂ (ZnAC). Moreover, density functional theory (DFT) investigations showed that the presence of N-dopant on a graphite surface enhances the chemisorption of O adsorbates due to the enhanced charge-transfer mechanism. KAC_urea was tested in three aqueous electrolytes with different ions (LiOH, NaOH, and NaClO₄), which delivered higher specific capacitance, with the NaOH electrolyte exhibiting 139 F g⁻¹ at a 2 mA current rate. The NaOH with the alkaline cation Na⁺ offered the best capacitance among the electrolytes studied. A multilayer perceptron (MLP) model was employed to describe the effects of synthesis conditions and physicochemical and electrochemical parameters to predict the capacitance and power outputs. The proposed MLP showed higher accuracy, with an R² of 0.98 for capacitance prediction.

In this paper, a model for controlling paddy drying by incorporating accumulated temperature is introduced and defined. Drying experiments using freshly harvested paddy were conducted at different levels of drying air parameters including temperature (T = 27°C, 31°C, 35°C, 39°C, and 43°C), relative humidity (RH = 45%, 50%, 55%, 60%, and 65%), initial moisture content (M₀ = 17%, 19%, 21%, 23%, and 25%) and airspeed (V = 0.4, 0.5, 0.6, 0.7, and 0.8 m s⁻¹). When T = 31°C, RH = 60%, M₀ = 19%, and V = 0.5 ms⁻¹, the crack additional percentage reached a minimum value of 0.508%, with the average precipitation rate at 0.719%·h. Further, an accumulated temperature and quality chart was provided in this paper. The x-coordinate of this chart is temperature, and the initial moisture content represents the y-coordinate. It covers the drying conditions of the actual dryer well and has a wide range of applicability for real-world environment. The model developed in this study not only provides a scientific reference for precise drying and intelligent control of paddy but also guide the actual drying operation.

Due to the nonlinearity, strong coupling and hysteresis of the parameters used in measuring the grain drying process, it is always a challenge to perform accurate control of the drying system. The purpose of this paper is to describe the design of a suitable neural network model to control the grain dryer more effectively. First, the operating mechanism of a continuous grain dryer and the principle of the heat and mass transfer that can be used in the process of grain drying was analyzed before an intelligent control system was designed accordingly. Second, an intelligent control system based on the Back Propagation Neural Network (BPNN) was developed. The BPNN was the optimal model selected based on a series of comparative test results. According to the BPNN prediction of the moisture content of dried rice, the system could adjust the rate of grain discharge of the dryer, and then control the drying process accurately. Finally, the neural network control model was simulated using computer simulation technology, and was optimized by comparing analysis results with experimental results. The results showed that the optimized intelligent control system using BPNN has the advantage of strong stability and good noise handling, and could have great potential for future implementation studies.

This scoping review summarises the literature on resilience interventions that use interactive technology. Resilience refers to a person’s mental ability to adaptively deal with challenging situations and is a key skill for dealing with challenges in life. Types of interactive technology used in resilience interventions included serious video games, virtual reality simulations, social robots and commercial off-the-shelf video games. Searching a range of multidisciplinary databases, this review identified 27 publications that evaluated 17 unique interventions. Peer-reviewed papers and conference proceedings published in English and released after 2000 were included in the review. This scoping review finds that interactive technology can be used as an effective intervention to increase resilience. The review identified two types of resilience intervention: stress inoculation and therapeutic treatment. The interventions were analysed using the eight dimensions identified in the gameful experience questionnaire. Providing players with challenging experiences and guiding behaviour while providing feedback were the two most used dimensions. Social experience was underutilised and competition was not used, except in commercial off-the-shelf video games. This review has shown that interactive technologies can deliver effective resilience interventions in an accessible, cost-effective and flexible manner.