In an era characterized by technological advancement and innovation, the emergence of Electronic Government (e-Government) and Mobile Government (m-Government) represents significant developments. Previous studies have explored acceptance models in this domain. This research presents a novel acceptance model tailored to the context of m-Government adoption in Jordan, integrating the Information System (IS) Success Factor Model, Hofstede’s Cultural Dimensions Theory, and considerations for law enforcement factors. The primary objective of this study is to investigate the strategies for promoting and enhancing the adoption of m-Government applications within Jordanian society. Data collection involved the distribution of 203 electronic questionnaires, with subsequent analysis conducted using SPSS. The findings reveal the acceptance and significance of three hypotheses: Information Quality, Service Quality, and Power Distance. Additionally, the study incorporates the influence of Law Enforcement factors, contributing to a comprehensive understanding of the multifaceted determinants shaping the adoption of m-Government services in Jordan.

The purpose of this study is to investigate customer satisfaction with quality of service known as SERVQUAL improvement or service quality competitiveness in emerging markets. Using Indonesian government medical care as an example the author examines the satisfaction of patients. Information and data were collected through a survey of 399 BPJS users in Indonesia. All data were analyzed using Smart PLS. This study demonstrates that there is a negative value associated with the five-dimensional gap. As a result, the care provided to BPJS patients is below par. Specifically, the sensitivity dimension has the largest disparity at 0.15, while the physical evidence dimension has the smallest at 0.49. In order to raise the level of service provided, it may be necessary to take direct measures or examine tangible evidence. This study develops the relationship between different quality service models. There appears to be a substantial increase in the body of literature in the area of service quality, allowing for constant updates and the incorporation of the lessons learned from the experiences of the departed. These revised guidelines are intended to aid SERVQUAL study participants. The study gives practical support to academics and practitioners in directing service quality improvement through the use of data collected from large-scale surveys of patients and medical professionals as doctors in Indonesia.

To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.

Aiming at the problem of incompatibility of biomass models of forest organs, taking Chinese fir in Fujian Jiangle State-owned Forest Farm as the research object, based on selecting the optimal independent model of each organ, the biomass compatibility model of Chinese fir was established with a three-level joint control scheme. The results show that the compatibility equation system based on the whole plant biomass can effectively solve the problem of incompatibility in the whole plant biomass, each sub-biomass and between sub-biomass. Besides, except for the leaf biomass model, all other biomass models have good fitting effect, which is of great significance to the guidance of the analysis of local Chinese fir biomass.

Forest is the main carbon sink of terrestrial ecosystem. Due to the unique growth characteristics of plants, the response of their growth status and physiological activities to climate change will affect the carbon cycle process of forest ecosystem. Based on the local scale CO₂ flux and temperature observation data recorded by the FLUXNET registration site and Harvard Forest FLUX observation tower from 2000 to 2012, combined with the phenological model, this paper analyzes the impact of temperature changes on CO₂ flux in temperate forest ecosystems. The results show that: (1) the maximum NEE in 2000–2012 was 298.13 g·m^-2·a^-1, which occurred in 2010. Except in the 2010 and 2011, the annual NEE in other years was negative. (2) NEE, GPP, temperature and phenology models have good fitting effects (R² > 0.8), which shows that the stable period of photosynthesis in temperate mixed forest ecosystem is mainly concentrated in summer, and vegetation growth is the dominant factor of carbon cycle in temperate mixed forest ecosystem. (3) The linear fitting results of the change time points of air temperature (maximum point, minimum point and 0 point date) and the change time points of NEE and GPP (maximum point, minimum point and 0 point date) show that there is a significant positive correlation between air temperature and CO₂ flux (P < 0.01), and the change of air temperature affects the carbon cycle process of temperate mixed forest ecosystem.

Plasma thermal gasification can be one of the most relevant and environmentally friendly technologies for waste treatment and has gained interest for its use in thethermos-conversion of biomass. In this perspective, the objective of this study is to evaluate the gasification of sugarcane bagasse by studying the effective areas of operation of this process and to establish a comparison with conventional autothermal gasification. A thermochemical equilibrium model was used to calculate the indicators that characterize the performance of the process on its own and integrated with a combined cycle. As a result, it was obtained that plasma and gasification of bagasse is technically feasible for the specific net electrical production of 4 MJ with 30 % electrical efficiency, producing a gas with higher calorific value than autothermal gasification. The operating points where the electrical energy production and the cold gas efficiency reach their highest values were determined; then the effects of the operational parameters on these performance indicators were analyzed.