Staphylococcus aureus infections in children in an Iranian referral pediatric Hospital

Introduction. Staphylococcus aureus is associated with various infections ranging from skin and soft tissues such as surgical site infections and abscesses to lower respiratory tracts and blood- stream. The aim of this study was to evaluate underlying condi- tion of patients with S. aureus infections in an Iranian referral pediatric Hospital. Material and methods. Information was extracted retrospec- tively from the medical records of patients who were diagnosed with S. aureus infections. Data obtained about the study subjects included basic demographics, reason for admission, culture site, length of hospital stay, and methicillin susceptibility. Results. The underlyning condition of of patients with S.aureus infection during November 2011 and March 2013 were included in the study. The most frequent diagnosis in patients with S. aureus infection was jaundice (12%), abscess (10%), cellulitis (10%), wound infection (8%), septic arthritis (7%) and sezeire (5%). Wound was the most common infection sites among all subjects 34/98 (35%) following by blood (20/98, 20%) as well as skin and soft tissue (19/98, 19%). The proportion of MRSA infections among all S. aureus isolates was 79% (77/98) during the study period. In addition, 58/74 (78%) met the definition of Hospital-Associated Methicillin-Resistant S. aureus (HA- MRSA) infections and the rest; 20/24 patients (83%), were classified as Community-Associated Methicillin-Resistant S. aureus (CA- MRSA). Conclusion. In our study, the high frequency of MRSA was found not only in HA S. aureus but also in CA S. aureus isolates; there- fore, the strategic goals to optimize antimicrobial use includin

The Role of Doctor-Patient Communication Skills in Predicting Treatment Adherence

Background and Objective: The level of patient adherence to treatment and medication orders is one of the important factors influencing the effectiveness of medical treatments. The aim of this study is to investigate the relationship between doctor-patient communication skills and the level of adherence to medication orders after discharge from the hospital. Methods: This cross-sectional study was conducted on 284 patients admitted to the surgery and urology departments of Shahid Beheshti Hospital in Babol, where at least 48 hours had passed since their admission. Patients completed two questionnaires of doctor-patient communication skills (range 21-70) and Burton communication skills (range 18-90) in the hospital. Then, two weeks after discharge, the patients answered the two questionnaires of general adherence and the Morisky Medication Adherence Scale online or by telephone contact, and the results were analyzed. Findings: The mean age of the participating patients was 50.65±18.20 years and the score of general adherence to treatment orders was 24.26±5.77 (range 7-30) and medication adherence was 8.54±2.91 (range 1-11). 222 patients (78.2%) had high adherence to treatment orders. Stepwise regression analysis showed that doctors’ communication skills were a positive factor in medication adherence (p<0.001, ß=0.336) and adherence to treatment orders (p<0.001, ß=0.331). Moreover, patients’ communication skills had a positive effect on medication adherence (p=0.01, ß=0.137) and general adherence to treatment orders (p<0.001, ß=0.205). Conclusion: The results of the study showed that the communication skills of doctors and patients is a positive predictor of adherence to treatment and medication orders after discharge from the hospital

The Role of Doctor-Patient Communication Skills in Predicting Treatment Adherence

Background and Objective: The level of patient adherence to treatment and medication orders is one of the important factors influencing the effectiveness of medical treatments. The aim of this study is to investigate the relationship between doctor-patient communication skills and the level of adherence to medication orders after discharge from the hospital. Methods: This cross-sectional study was conducted on 284 patients admitted to the surgery and urology departments of Shahid Beheshti Hospital in Babol, where at least 48 hours had passed since their admission. Patients completed two questionnaires of doctor-patient communication skills (range 21-70) and Burton communication skills (range 18-90) in the hospital. Then, two weeks after discharge, the patients answered the two questionnaires of general adherence and the Morisky Medication Adherence Scale online or by telephone contact, and the results were analyzed. Findings: The mean age of the participating patients was 50.65±18.20 years and the score of general adherence to treatment orders was 24.26±5.77 (range 7-30) and medication adherence was 8.54±2.91 (range 1-11). 222 patients (78.2%) had high adherence to treatment orders. Stepwise regression analysis showed that doctors’ communication skills were a positive factor in medication adherence (p<0.001, ß=0.336) and adherence to treatment orders (p<0.001, ß=0.331). Moreover, patients’ communication skills had a positive effect on medication adherence (p=0.01, ß=0.137) and general adherence to treatment orders (p<0.001, ß=0.205). Conclusion: The results of the study showed that the communication skills of doctors and patients is a positive predictor of adherence to treatment and medication orders after discharge from the hospital

Determination of Metallic Materials Toughness Using Acoustic Emission Monitoring Technique

No abstract available

LP-MAB:improving the energy efficiency of LoRaWAN using a reinforcement-learning-based adaptive configuration algorithm

Abstract In the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) are designed to provide low energy consumption while maintaining a long communications’ range for End Devices (EDs). LoRa is a communication protocol that can cover a wide range with low energy consumption. To evaluate the efficiency of the LoRa Wide-Area Network (LoRaWAN), three criteria can be considered, namely, the Packet Delivery Rate (PDR), Energy Consumption (EC), and coverage area. A set of transmission parameters have to be configured to establish a communication link. These parameters can affect the data rate, noise resistance, receiver sensitivity, and EC. The Adaptive Data Rate (ADR) algorithm is a mechanism to configure the transmission parameters of EDs aiming to improve the PDR. Therefore, we introduce a new algorithm using the Multi-Armed Bandit (MAB) technique, to configure the EDs’ transmission parameters in a centralized manner on the Network Server (NS) side, while improving the EC, too. The performance of the proposed algorithm, the Low-Power Multi-Armed Bandit (LP-MAB), is evaluated through simulation results and is compared with other approaches in different scenarios. The simulation results indicate that the LP-MAB’s EC outperforms other algorithms while maintaining a relatively high PDR in various circumstances

ADR-Lite:a low-complexity adaptive data rate scheme for the LoRa network

Abstract The long-range and low energy consumption re-quirements in Internet of Things (IoT) applications have led to a new wireless communication technology known as Low Power Wide Area Network (LPWANs). In recent years, the Long Range (LoRa) protocol has gained a lot of attention as one of the most promising technologies in LPWAN. Choosing the right combination of transmission parameters is a major challenge in the LoRa networks. In LoRa, an Adaptive Data Rate (ADR) mechanism is executed to configure each End Device’s (ED) trans-mission parameters, resulting in improved performance metrics. In this paper, we propose a link-based ADR approach that aims to configure the transmission parameters of EDs by making a decision without taking into account the history of the last received packets, resulting in a relatively low space complexity approach. In this study, we present four different scenarios for assessing performance, including a scenario where mobile EDs are considered. Our simulation results show that in a mobile scenario with high channel noise, our proposed algorithm’s Packet Delivery Ratio (PDR) is 2.8 times outperforming the original ADR and 1.35 times that of other relevant algorithms