Today, air pollution is the biggest environmental health problem in the world. Air pollution leads to adverse effects on human health, climate and ecosystems. Air is contaminated by toxic gases released by industry, vehicle emissions and the increased concentration of harmful gases and particulate matter in the atmosphere. Air pollution can cause many serious health problems such as respiratory, cardiovascular and skin diseases in humans. Nowadays, where air pollution has become the largest environmental health risk, the interest in monitoring air quality is increasing. Recently, mobile technologies, especially the Internet of Things, data and machine learning technologies have a positive impact on the way we manage our health. With the production of IoT-based portable air quality measuring devices and their widespread use, people can monitor the air quality in their living areas instantly. In this study, e-nose, a real-time mobile air quality monitoring system with various air parameters such as CO2, CO, PM10, NO2 temperature and humidity, is proposed. The proposed e-nose is produced with an open source, low cost, easy installation and do-it-yourself approach. The air quality data measured by the GP2Y1010AU, MH-Z14, MICS-4514 and DHT22 sensor array can be monitored via the 32-bit ESP32 Wi-Fi controller and the mobile interface developed by the Blynk IoT platform, and the received data are recorded in a cloud server. Following evaluation of results obtained from the indoor measurements, it was shown that a decrease of indoor air quality was influenced by the number of people in the house and natural emissions due to activities such as sleeping, cleaning and cooking. However, it is observed that even daily manual natural ventilation has a significant improving effect on air quality.

An important part of our life, internet has enabled many machines and devices we use in everyday life to be monitored and controlled remotely through Internet of Things (IOT) technology. Thanks to IOT technology, smart health applications have become a rapidly growing sector. For individuals with heart disease, the Heart Rate (HR), Heart Rate Variability (HRV) and Body Temperature (BT) values are considered vital signs that must be measured regularly. In this study, an android-based application is developed that can monitor HR, HRV and CT parameters for cardiovascular patients who should be under constant observation. The measuring system, which consists of wearable sensors, constantly measures patient signs. Then send the measured signals to android interface via wireless connection. If the predetermined critical values for the patient are exceeded, the HR, HRV, CT values and also the realtime location of patient is sent both to family members and doctor as e-mail and twitter notification. The wearable measurement system allows patients to be mobile in their own social environment, allowing them to live their lives in confidence.

What is already known on this topic? Hyponatremia is caused by the combination of excess ADH-induced water retention and secondary solute loss in patients with inappropriate antidiuretic hormone syndrome. Vaptans, arginine-vasopressin receptor antagonists are alternatively used for SIADH in adults. In children, vaptan treatment has not been approved for SIADH. What this study adds? Here, we report a successful tolvaptan treatment in a child with SIADH. Furthermore, we report that only one dose of tolvaptan in triphasic episode is sufficient efficiency. This data is the first child patient from Turkey.

Global climate change and COVID-19 have changed our social and business life. People spend most of their daily lives indoors. Low-cost devices can monitor indoor air quality (IAQ) and reduce health problems caused by air pollutants. This study proposes a real-time and low-cost air quality monitoring system for smart homes based on Internet of Things (IoT). The developed IoT-based monitoring system is portable and provides users with real-time data transfer about IAQ. During the COVID-19 period, air quality data were collected from the kitchen, bedroom and balcony of their home, where a family of 5 spend most of their time. As a result of the analyzes, it has been determined that indoor particulate matter is mainly caused by outdoor infiltration and cooking emissions, and the CO2 value can rise well above the permissible health limits in case of insufficient ventilation due to night sleep activity. The obtained results show that the developed measuring devices may be suitable for measurement-based indoor air quality management. In addition, the proposed low-cost measurement system compared to existing systems; It has advantages such as modularity, scalability, low cost, portability, easy installation and open-source technologies.

The aim of this study is to investigate the electrical energy consumption for different material processing methods. In these experiments, ferrous powder metals, bulk iron and bulk graphite materials are used. These different materials are heated, sintered and welded by using processes of ultra-high frequency induction heating (UHFIH), ultra-high frequency induction heating sintering (UHFIHS) and ultra-high frequency induction heating welding (UHFIHW), respectively. For all experiments, 2.8 kW, 900 kHz ultra-high frequency induction heating system is used. The experiments are conducted by LabVIEWTM based measurement and control system. Finally, all data are analyzed to show the energy efficiency of each process.