GIS-Based Probabilistic Approach for Assessing and Enhancing Infrastructure Data Quality

The task of preserving and improving infrastructure systems is becoming extremely challenging because these systems are decaying due to aging and over utilization, have limited funding, and are complex in nature (geographically spread, and affect and are affected by technological, environmental, social, security, political, and economic factors). The infrastructure management paradigm has emerged to assist in the challenging task of managing infrastructure systems in a systematic and cost-effective manner. Infrastructure management is a data-driven process. It relies on large databases that contain information on the system’s inventory, condition, maintenance and rehabilitation (M&R) history, utilization, and cost. This data feeds into analytical models that assess infrastructure current conditions, predict future conditions, and develop optimal M&R strategies. Thus, complete and accurate data is essential to a reliable infrastructure management system. This study contributes to advancing the infrastructure management paradigm (with focus on pavement management) in two primary ways: (a) it provides in-depth understanding of the impact of errors in condition data on the outputs of infrastructure management systems, and (b) it provides efficient computational methods for improving infrastructure data quality. First, this research provides a quantitative assessment of the effects of error magnitude and type (both systematic and random) in pavement condition data on the accuracy of PMS outputs (i.e., forecasted needed budget and M&R activities in a multi-year planning period). Second, a new technique for detecting gross outliers and pseudo outliers in pavement condition data was developed and tested. Gross outliers are data values that are likely to be erroneous, whereas pseudo outliers are pavement sections performing exceptionally well or poor due to isolated local conditions. Third, a new technique for estimating construction and M&R history data from pavement condition data was developed and tested. This technique is especially beneficial when M&R data and condition data are stored in disparate heterogeneous databases that are difficult to integrate (i.e., legacy databases). The main merit of the developed techniques is their ability to integrate methods and principles from Bayesian and spatial statistics, GIS, and operations research in an efficient manner. The application of these techniques to a real-world cases study (pavement network in Bryan district) demonstrated the potential benefits of these techniques to infrastructure managers and engineers

A study on the type and frequency of unacceptable collocations in the English-Persian translations of Hemingway’s Masterpiece: For Whom the Bell Tolls

Collocations are clusters of words that are acquired together and are subject to constraints in co-occurrence with their adjacent words. The inadequate acquaintance with collocations emerges into the formation of unacceptable collocations from the viewpoint of native speakers. The present study is a descriptive quantitative study of the translation of collocations in literary texts from English into Persin. The study sought to identify the most frequent types of unacceptable collocations in the Persian translated versions. For the purpose of the study, the four Persian translated versions of Hemingway’s “For Whom the Bell Tolls” were investigated precisely and all the unacceptable collocations were compiled and clustered into English patterns based on Benson’s theory, in an aim to decode the groups of patterns which are most frequently leading to bearing of unacceptable collocations in translation of English texts to Persian. A detailed SPSS analysis was conducted and the findings including frequency and percentage of each type of the unacceptable collocations were recorded. The most frequent types of unacceptable collocations spotted in the translated versions of the novel were as follows: 1. Adjective + Noun 23.3%, 2. Subject + Verb 11%, 3. Verb + Object 10.3% patterns

Cost-Effectiveness of Endovascular Aneurysm Repair Versus Open Surgical Repair for Ruptured Abdominal Aortic Aneurysms: A Systematic Review

Context: If the diameter of an aneurysm increases by more than 6 cm, the risk of aortic rupture increases by 50 within 10 years. Therefore, rupture of aneurysm, which is usually asymptomatic, can lead to severe complications and increase the risk of mortality. The current study aimed to systematically review studies comparing the cost-effective endovascular aneurysm repair (EVAR) and open surgical repair (OSR) as the primary treatment options for patients with ruptured abdominal aortic aneurysms (AAAs). Methods: An electronic search was conducted in PubMed, EMBASE, Science Direct, Scopus, and other scientific economic databases. Relevant articles were searched from 1999 to 2020 using keywords, such as "abdominal aortic aneurysm", "endovascular", "open surgery", "rupture", "economic evaluation", and "cost-effectiveness". The quality of articles was assessed using the Quality of Health Economic studies (QHES) checklist; finally, five articles were included in this review. Results: The results of the QHES checklist showed that most studies had a good quality. A third-party payer's perspective was the dominant perspective in all selected studies, comparing EVAR with OSR. All studies considered the direct medical costs and did not disclose any discount rates, except for one study, reporting a 3.5 discount rate. Almost all included studies found EVAR to be a costeffective intervention; only one study concluded that EVAR, with a cost-effectiveness ratio of 424,542, was not the best treatment option. Conclusion: In patients with ruptured AAAs, the EVAR intervention improved the quality of life, decreased the mortality rate, and shortened the hospital stay as compared to OSR

The Rate of Physicochemical Incompatibilities, Administration Errors. Factors Correlating with Nurses' Errors

Medication errors are commonly encountered in hospital setting. Intravenous medications pose particular risks because of their greater complexity and the multiple steps required in their preparation, administration and monitoring. We aimed to determine the rate of errors during the preparation and administration phase of intravenous medications and the correlation of these errors with the demographics of nurses involved in the process. One hundred patients who were receiving IV medications were monitored by a trained pharmacist. The researcher accompanied the nurses during the preparation and administration process of IV medications. Collected data were compared with the acceptable guidelines. A checklist was filled for each IV medication. Demographic data of the nurses were collected as well. A total of 454 IV medications were recorded. Inappropriate administration rate constituted a large proportion of errors in our study (35.3%). No significant or life threatening drug interaction was recorded during the study. Evaluating the impact of the nurses' demographic characteristics on the incidence of medication errors showed that there is a direct correlation between nurses' employment status and the rate of medication errors, while other characteristics did not show a significant impact on the rate of administration errors. Administration errors were significantly higher in temporary 1-year contract group than other groups (p-value < 0.0001). Study results show that there should be more vigilance on administration rate of IV medications to prevent negative consequences especially by pharmacists. Optimizing the working conditions of nurses may play a crucial role