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.

Idiomatic phrase are one of the lexical units.Many second-language learners showing great enthusiasm for using idiomatic expressions because of the rich cultural factors inherent in them and the vibrant,hilarious language that is close to life-like.However,  the idiomatic terms are so complicated that they frequently cause foreign learners to struggle with learning and comprehending Chinese.With its own advantages, the idea of lexical chunks has the potential to be a game changer in the teaching of idiomatic.

COVID-19 pandemic has caused many design bid build projects to suffer losses. Design bid build or DBB has the disadvantage of depth partnering. The research purpose is to reveal the depth of partnering of DBB, the characteristics of existing partnering in DBB through detection in each project life cycle in DBB, then efforts to increase DBB partnering to partnering in integrated project delivery (IPD). The methodology used is secondary data from three project DBB, then validation using focused group discussions (FGD) with expert judgment, then the Delphi method to analyse and propose recommendations. This project recommends that DBB project can improve the project performance so stakeholder can increase partnering toward integrated project delivery (IPD) partnering. This research can be used for increasing partnering in DBB projects towards partnering in IPD. This research will produce strategic recommendations that can be utilized by stakeholders (owner, contractor, designer) in improving project performance to generate great value for the project, will result in long-term project sustainability, improve relationships, and learn valuable lessons for future projects. DBB projects usually experience many problems due to the competitive nature of partnering for owners, contractors, and designers, so it is necessary to develop an overall strategy as an option to improve partnering in DBB project contracts. This research will help create a sustainable project by the owner, contractor, and designer.

Google Earth images in the Marche Region of Central Italy revealed a circular structure consisting of a ring system made up of concentric hills and valleys. Cartography, DEM, geological, and available geophysical data were used to constrain the possible origin of the structure. Located in the Messinian foredeep deposits of the Central Apennines, it has a rim diameter of 3.75 km and a central uplift connected to its southernmost part. As it was formed in the clays of the Lower Pliocene, and clays are believed to have emerged definitively after the Upper Pliocene, its age might be constrained to the Lower Pleistocene. Similar concentric structures are usually found in impact craters, sedimentary domes, and volcanic landforms. As salt domes and magmatic activity are not found in this region, this study seeks to validate the results of previous work that it was the result of an ancient impact crater of hydrological, brachyanticline, or clayey diapiric origins. Specifically, an observed second ring portion with a curvature radius about double the first in size will be investigated in this work. This second ring portion appears to be concentric to the first one and is visible along its northern and western parts. Although double concentric rings are usually due to impact craters, the absence of the ring portion in the other two directions and the probable deviation of a river, deduced by studying hydrography, support the hypothesis that it might be of clay diapir origin.

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.