Scorpion stings are a common and important health problem in Iran, particularly in south and southwestern Iran, including the province of Khuzestan. In the area of Khuzestan near the city of Ramhormoz, Hemiscorpius lepturus (Scorpionida: Hemiscorpioiidae) and Androctonus crassicauda (Buthidae) are present. Ramhormoz is in southwestern Iran and is one of the most important foci of the scorpion sting problem. The current study was carried out to gain both epidemiological and medical information about scorpion stings in and around the city of Ramhormoz. In total, 179 people who were admitted to the Emergency Department of Ramhormoz Imam Khomeini Hospital during 2008 and 2009 after being stung by scorpions were monitored. Epidemiological and medical parameters including sex of the victim; the part of the body stung; the month when stung; the biochemical parameters comprising blood sugar (BS), blood urea nitrogen (BUN), and creatinine (CR); hematological parameters including white blood cells (WBC), count blood cells (CBC), red blood cells (RBC), hemoglobin (Hb), hematocrit (HCT), platelet (PLT); and urine analysis including hemoglobinuria were recorded. The current study showed that most of the victims were stung by H. lepturus, while very few were stung by A. crassicaud, but in over half of the cases the species was not known. Stings were most common from May to Aguust. 73% of the victims were female. The limbs were the part of the body most likely to be stung. Hemogobinuria was very common in H. lepturus victims.

In this paper, we focus on one-bit precoding approach for downlink massive multipleinput multiple-output (MIMO) systems, where we exploit the concept of constructive interference (CI) employing deep learning (DL) techniques. One of the main performance limiting factors in wireless communication systems is interference, which needs to be minimized or mitigated. By controlling the interference signals in order to add up constructively at the receiver side, there is a possibility to improve the system performance. This paper presents a DL-based one-bit precoding scheme that improves the massive MIMO performance via CI exploitation in the presence of one-bit digital to analog converters (DAC) as a hardware impairment. More precisely, for phase shift keying signaling, we first formulate the optimization problem in order to maximize the CI effects in the case of a base station equipped with one-bit DACs. Then, after solving the optimization problem and creating a large enough dataset, a DL network is trained to do the precoding. Numerical results show that the DL-based solution approaches the performance of the conventional interference exploitation one-bit precoding schemes in the massive MIMO systems while having an order of magnitude less complexity.