Referral Physicians’ Knowledge of Radiation Dose: A Cross-sectional Study

AIM: The purpose of the study was to evaluate the knowledge of referring physicians of general practitioners, residents, and medical specialists in Jordan and the Middle East on radiation dose and its impact on vulnerable patients. MATERIALS AND METHODS: The Institutional Review Board approved this study before data collection. A cross-sectional study employed questionnaire that was distributed to respondents (n = 293) of general practitioners, residents, specialists, and therapists. The questionnaire consisted of 29 questions. Nine questions concerned with demographics and the remaining 20 questions were divided into five sections: Radiation dose, ionizing radiation, pediatric radiation, pregnant women radiation, and radiation risks. The mean score was computed out of 20. Chi-squared test of independence was utilized to analyze each question. To compare the responses between the demographic variables groups, Kruskal–Wallis and Mann–Whitney tests were used. RESULTS: Out of the 293 respondents, 128 (43.7%) were aware of radiation. The average score of the questionnaire was 9.5 out of 20 (47.5%). Within each section, the level of knowledge varied. Physicians had the highest level of knowledge in radiation risk (85.7%) followed by ionizing radiation (62.1%). The questionnaire revealed lower levels of knowledge in the areas of pediatric radiation, pregnant women radiation, and radiation dose. The percentages of respondents, (with fair to good level of knowledge), were 47.1%, 34.5%, and 24.6%, respectively. CONCLUSION: The results of this study were consistent with previous studies that demonstrated a poor level of general knowledge in referring physicians regarding radiation dose, ionizing radiation, pediatric radiation, pregnant women radiation, and radiation risks

Autopsy analyses in acute exacerbation of idiopathic pulmonary fibrosis

Background: Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is associated with high mortality. However, few studies have so far reviewed analyses of autopsy findings in patients with AE-IPF.Methods: We retrospectively reviewed 52 consecutive patients with AE-IPF who underwent autopsies at five university hospitals and one municipal hospital between 1999 and 2013. The following variables were abstracted from the medical records: demographic and clinical data, autopsy findings and complications during the clinical course until death.Results: The median age at autopsy was 71 years (range 47-86 years), and the subjects included 38 (73.1%) males. High-dose corticosteroid therapy was initiated in 45 (86.5%) patients after AE-IPF. The underling fibrotic lesion was classified as having the usual interstitial pneumonia (UIP) pattern in all cases. Furthermore, 41 (78.8%) patients had diffuse alveolar damage (DAD), 15 (28.8%) exhibited pulmonary hemorrhage, nine (17.3%) developed pulmonary thromboembolism and six (11.5%) were diagnosed with lung carcinoma. In addition, six (11.5%) patients developed pneumothorax prior to death and 26 (53.1%) developed diabetes that required insulin treatment after the administration of high-dose corticosteroid therapy. In addition, 15 (28.8%) patients presented with bronchopneumonia during their clinical course and/or until death, including fungal (seven, 13.5%), cytomegalovirus (six, 11.5%) and bacterial (five, 9.6%) infections.Conclusions: The pathological findings in patients with AE-IPF represent not only DAD, but also a variety of pathological conditions. Therefore, making a diagnosis of AE-IPF is often difficult, and the use of cautious diagnostic approaches is required for appropriate treatment

MACHINE LEARNING ALGORITHMS and THEIR APPLICATIONS in CLASSIFYING CYBER-ATTACKS on a SMART GRID NETWORK

Smart grid architecture and Software-defined Networking (SDN) have evolved into a centrally controlled infrastructure that captures and extracts data in real-time through sensors, smart-meters, and virtual machines. These advances pose a risk and increase the vulnerabilities of these infrastructures to sophisticated cyberattacks like distributed denial of service (DDoS), false data injection attack (FDIA), and Data replay. Integrating machine learning with a network intrusion detection system (NIDS) can improve the system\u27s accuracy and precision when detecting suspicious signatures and network anomalies. Analyzing data in real-time using trained and tested hyperparameters on a network traffic dataset applies to most network infrastructures. The NSL-KDD dataset implemented holds various classes, attack types, protocol suites like TCP, HTTP, and POP, which are critical to packet transmission on a smart grid network. In this paper, we leveraged existing machine learning (ML) algorithms, Support vector machine (SVM), K-nearest neighbor (KNN), Random Forest (RF), Naïve Bayes (NB), and Bagging; to perform a detailed performance comparison of selected classifiers. We propose a multi-level hybrid model of SVM integrated with RF for improved accuracy and precision during network filtering. The hybrid model SVM-RF returned an average accuracy of 94% in 10-fold cross-validation and 92.75%in an 80-20% split during class classification

Permeation of water contaminative phenols through hairless mouse skin

As a means of determining the risk of absorption of water contaminative phenolic compounds through the skin, the permeation of a number of phenols, all on the U.S. Environmental Protection Agency's list of priority pollutants, through hairless mouse skin has been studied, using in vitro diffusion cell methods. Experimentally determined permeability coefficients through intact skin and stratum corneum denuded skin and permeability coefficients derived therefrom for the viable tissue layer and the stratum corneum, which are the tissue's major contributing substrata, have been correlated with their log K octanol/water partition coefficients. Permeability coefficients for the whole skin and the stratum corneum systematically increased with increasing phenol lipophilicity to limiting values of about 0.15 and 0.30 cm/hr, respectively. The values of the permeability coefficients for the viable tissue were roughly the same for all compounds (≈0.36 cm/hr). Because of the inductive effects of Cl and NO 2 substituents on the aromatic ring, phenolic analogs containing these moieties are acidic and, consequently, their overall skin permeabilities were highly pH-dependent in the range of pH values seen for surface waters. High fluxes were noted for such phenols at low pH, where they exist essentially in a non-ionized state. Though low, fluxes of the compounds were measurable at pH's ≫ pK a 's, indicating that phenolic anions also pass through the skin. With the exceptions of relatively polar phenol and the mono-nitro phenols, the free acid forms of all the phenols studied permeated skin with ease and at rates approaching those of denuded skin. The intact skin permeability coefficient of the free acid form of 4-nitro phenol was exceptionally low, which suggests that it might associate intermolecularly.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48064/1/244_2005_Article_BF01056570.pd