Introduction: Stenoses in the path of arteriovenous fistulas (AVF) for hemodialysis are a very prevalent problem and there is long experience in their treatment by percutaneous angioplasty (PTA). These procedures, however, involve non-negligible equipment requirements, exposure to radiation and intravenous contrast that are not beneficial for the patient and make their performance more complex. This study reviews our initial experience with Doppler ultrasound-guided angioplasty. Methods: Prospective cohort of patients with native AVF dysfunction due to significant venous stenosis treated by Doppler echo-guided PTA. AVF puncture, lesion catheterization, balloon localization and inflation, and outcome verification were performed under ultrasound guidance. Only one fistulography was performed before and another one after dilatation. As a control, the cases performed during the same period by the usual angiographic method were also collected. Results: Between February 2015 and September 2018, 51 PTAs were performed on native AVF, of which 27 were echogenic (mean age, 65.3 years; 63% male). The technical success rate was 96%. In 26% of cases, PTA was repeated due to residual stenosis after angiographic imaging. There were 7.3% periprocedural complications. 92% of the AVFs were punctured at 24 hours. Primary patency at 1 month, 6 months and 1 year was 100%, 64.8% and 43.6%, and assisted patency was 100%, 87.2% and 74.8%. There were no significant differences in immediate or late results with respect to angiographically guided AVF angioplasty. Conclusions: AVF-PTA can be performed safely and effectively guided by Doppler ultrasound, which simplifies the logistics required for its performance, although we still need to improve the capacity for early verification of the result with this imaging technique.

Iran has one of the oldest civilizations in the world, and many elements of today’s urban planning and design have their origins in the country. However, mass country-city migration from the 1960s onwards brought enormous challenges for the country’s main cities in the provision of adequate housing and associated services, resulting in a range of sub-standard housing solutions, particularly in Tehran, the capital city. At the same time, and notably in the past decade, Iran’s main cities have had significant involvement in the smart city movement. The Smart Tehran Program is currently underway, attempting to transition the capital towards a smart city by 2025. This study adopts a qualitative, inductive approach based on secondary sources and interview evidence to explore the current housing problems in Tehran and their relationship with the Smart Tehran Program. It explores how housing has evolved in Tehran and identifies key aspects of the current provision, and then assesses the main components of the Smart Tehran Program and their potential contribution to remedying the housing problems in the city. The article concludes that although housing related issues are at least being raised via the new smart city technology infrastructure, any meaningful change in housing provision is hampered by the over centralized and bureaucratic political system, an out of date planning process, lack of integration of planning and housing initiatives, and the limited scope for real citizen participation.

This study rigorously investigates the Starlink Project’s impact on Thailand’s legal frameworks, regulatory policies, and national security concerns. Utilising a well-structured online questionnaire, we collected responses from 1378 Thai participants, meticulously selected to represent diverse demographics, technology usage patterns, and social media interactions. Our analytical approach integrated binary regression analysis to dissect the intricate relationships between various predictor variables and the project’s potential effects. Notably, the study unveils critical insights into how factors such as age, gender, education level, income, as well as specific technology and social media usage (including laptop, smartphone, tablet, home and mobile Internet, and TikTok), influence perceptions of Starlink’s impact. Intriguingly, certain variables like Twitter and YouTube usage emerged as non-significant. These nuanced findings offer a robust empirical basis for stakeholders to forge targeted strategies and policies, ensuring that the advent of the Starlink Project aligns with Thailand’s national security, legal, and regulatory harmony.

The technological development and growth of the telecommunications industry have had a great positive impact on the education, health, and economic sectors, among others. However, they have also increased rivalry between companies in the market to keep and acquire new customers. A lower level of market concentration is related to a higher level of competitiveness among companies in the sector that drives a country’s socioeconomic development. To guarantee and improve the level of competition, it is necessary to monitor the concentration level in the telecommunications market to plan and develop appropriate strategies by governments. With this in mind, the present work aims to analyze the concentration prediction in the telecommunications market through recurrent neural networks and the Herfindahl-Hirschman index. The results show a slight gradual increase in competition in terms of traffic and access, while a more stable concentration level is observed in revenues.

Introduction: Many detrimental effects on employees’ health and wellbeing might result from inadequate illumination in the workplace. Headaches and trouble focusing can result from eye strain brought on by inadequate illumination. The purpose of this study was to simulate and optimize workplace illumination in the ceramic industry. Materials and methods: A common Luxmeter ST-1300 was used to measure the illumination in seven workplaces at a height of 100 cm above the floor. DIALux evo version 7.1 software was used to simulate the illumination of workplaces. To optimize the illumination conditions, a numerical experiment design consisting of 16 scenarios was used for each of the workplaces. Four factors were considered for each scenario: luminaire height, number of luminaires, luminous flux, and light loss factor. The Design-Expert program version 13.0.5.0 was applied for developing the scenarios. Finally, by developing quadratic models for each workplace, the optimization process was implemented. Results: Every workplace had illumination levels that were measured to be between 250 and 300 lux. Instead of using compact fluorescent luminaires, LED technology was recommended to maximize the illumination conditions for the workers. Following optimization, 376 lux of illumination were visible at each workstation in every workspace. For the majority of the workspaces, the simulated illumination was expected to have a desirability degree greater than 0.9. The uniformity and illumination of the workplace were significantly impacted by the two factors of luminaire height and luminaire count. Conclusion: The primary outcomes of this optimization were the environmental, political, and socioeconomic ones, including reduced consumption power, high light flux, and environmental compatibility. Nonetheless, the optimization technique applied in this work can be applied to the design of similar situations, such as residential infrastructure.

Resisting the adoption of medical artificial intelligence (AI), it is suggested that this opposition can be overcome by combining AI awareness, AI risks, and responsibility displacement. Through effective integration of public AI dangers and displacement of responsibility, some of these major concerns can be alleviated. The United Kingdom’s National Health Service has adopted the use of chatbots to provide medical advice, whereas heart disease diagnoses can be made by IBM’s Watson. This has the ability to improve healthcare by increasing accuracy, efficiency, and patient outcomes. The resistance may be due to concerns about losing jobs, anxieties about misdiagnosis or medical mistakes, and the consciousness of AI systems drifting more responsibility away from medical professionals. There is hesitancy among healthcare professionals and the general public about the deployment of AI, despite the fact that healthcare is being revolutionised by AI, its uses are pervasive. Participants’ awareness of AI in healthcare, AI risk, resistance to AI, responsibility displacement and ethical considerations were gathered through questionnaires. Descriptive statistics, chi-square tests and correlation analyses were used to establish the relationship between resistance and medical AI. The study’s objective seeks to collect data on primary and public AI awareness, perceptions of risk and feelings of displacement that the professionals have regarding medical AI. Some of these concerns can be resolved when AI awareness is effectively integrated and patients, healthcare providers, as well as the general public are well informed about AI’s potential advantages. Trust is built when, AI related issues such as bias, transparency, and data privacy are critically addressed. Another objective is to develop a seamless integration of risk management, communication and awareness of AI. Lastly to assess how this comprehensive approach has affected hospital settings’ ambitions to use medical AI. Fusing AI awareness, risk management, and effective communication can be used as a comprehensive strategy to address and promote the application of medical AI in hospital settings. An argument made by Chen et al. is that providing training in AI can improve adoption intentions while lowering complexity through the awareness of AI.