Objective: To investigate the value of differential diagnosis of hepatocellular carcinoma (HCC) and cirrhotic nodules via radiomics models based on magnetic resonance images. Background: This study is to distinguish hepatocellular carcinoma and cirrhotic nodules using MR-radiomics features extracted from four different phases of MRI images, concluded T1WI, T2WI, T2 SPIR and delay phase of contrast MRI. Methods: In this study, the four kind of magnetic resonance images of 23 patients with hepatocellular carcinoma (HCC) were collected. Among them, 12 patients with liver cirrhosis were used to obtain cirrhotic nodules (CN). The dataset was used to extract MR-radiomics features from regions of interest (ROI). The statistical methods of MRradiomics features could distinguish HCC and CN. And the ability of radiomics features between HCC and CN was estimated by receiver operating characteristic curve (ROC). Results: A total of 424 radiomics features were extracted from four kind of magnetic resonance images. 86 features in delay phase of contrast MRI，86 features in spir phase of T2WI，86 features in T1WI and 88 features in T2WI showed statistical difference (p < 0.05). Among them, the area under the curves (AUC) of these features larger than 0.85 were 58 features in delay phase of contrast MRI, 54 features in spir phase of T2WI, 62 features in T1WI and 57 features in T2WI. Conclusions: Radiomics features extracted from MRI images have the potential to distinguish HCC and CN.

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.

Plum (Prunus domestica) is a seasonal nutraceutical fruit rich in many functional food nutrients such as vitamin C, antioxidants, total phenolic content, and minerals. Recently, researchers have focused on improvised technologies for the retention of bioactive compounds during the processing of perishable fruits; plum is one of these fruits. This study looked at how the percentage of moisture content and percentage of acidity were affected by conventional drying and osmotic dehydration. Total phenolic content (mg GA/100 g of plum), total anthocyanin content (mg/100 g), and vitamin C (mg/100 g) Conventional drying of fruit was carried out at 80.0 ℃ for 5 h. At various temperatures (45.0 ℃, 50.0 ℃, and 55.0 ℃) and hypertonic solution concentrations (65.0 B, 70.0 B, and 75.0 B), the whole fruit was osmotically dehydrated. It was observed that the osmotically treated fruit retains more nutrients than conventionally dried fruit. The total phenolic content of fruit significantly increased with the increase in process temperature. However, vitamin C and total anthocyanin content of the fruit decreased significantly with process temperature, and hypertonic solution concentration was observed. Hence, it was concluded that osmodehydration could be employed for nutrient retention in plum fruit over conventional drying. This process needs to be further refined, improvised, and optimised for plum processing.

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.