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Religious Education as Covenant Kinship: Catechesis of the Good Shepherd in Adolescent Faith Formation
Full text linkUA.01.034 Records of the Division of Student Affairs
Full text linkCollection Number: UA.01.034
Repository: La Salle University Archives
Title: Records of the Division of Student Affairs
Date [inclusive]: 1980s-2000s
Extent: 9.0 Linear feet
Language: English
Scope and Contents: The records of the Division of Student Affairs are in bulk made up of the working files of Kathy Schrader from her time as Director of Student Affairs. Those files comprise the University Life series and includes files on individual clubs and other student organizations, events planning materials, correspondence, and ephemera. The Publications sub-series contains newsletters, events calendars, directories of student organizations and policy documentation. The Administrative Services series consists of annual reports and self studies made by the Student Affairs division as a whole. The Multicultural Center sub-series and Career and Employment Services, Counseling and Health Services, University and Ministry series all consist of annual and other reports, events flyers, correspondence, and other ephemera related to those offices.https://digitalcommons.lasalle.edu/finding_aids/1044/thumbnail.jp
Educational Process Improvement Program for Novice Anesthesia Providers Learning Safe Management of The Anesthesia Workstation
Full text linkPatient safety is at the cornerstone of the delivery of quality anesthesia. A historically pervasive patient safety threat related to the field of anesthesia has been the anesthesia workstation. Although anesthesia delivery improvements are based on refining physical engineering principles, they are also based on preventing human error. This DNP project uses an educational process improvement design to generate an evidence-based simulation educational activity for novice anesthesia providers to better prepare themselves for the reality of anesthesia workstation malfunction and human error
The Creation of an Evidence-Based Educational Intervention for Preceptor Development of the Novice Certified Registered Nurse Anesthetist
Full text linkNovice certified registered nurse anesthetists (CRNA) are responsible for precepting student registered nurse anesthetists (SRNA) while simultaneously caring for patients in the operating room (OR). SRNAs rely on CRNAs for the majority of clinical training by preceptorship. Well-defined best precepting practices do not exist. The ability to teach others is a learned skill, and the lack of such skill can lead to undue stress for both the novice CRNA and the SRNA. This may lead to reduced job satisfaction of the CRNA and diminished educational experience of the SRNA. The primary purpose of this Doctor of Nursing Practice (DNP) project is to create an educational intervention for novice CRNAs who have yet to precept. The intervention will utilize educational modules with role-play videos to describe evidence-guided best practice strategies for novice CRNA preceptors
A socio-economic and environmental vulnerability assessment model with causal relationships in electric power supply chains
No full textThe electric power industry is uniquely vulnerable to natural and human-made risks such as natural disasters, climate change, and cybersecurity. This study proposes a vulnerability assessment framework to identify and assess the risks associated with the electric power supply chain in the United Kingdom and study the causal relationship among them with the neutrosophic revised decision-making trial and evaluation laboratory (NR-DEMATEL) method. We further introduce a novel hesitant expert selection model (HESM) to assist decision-makers with expert selection and weight determination. We present a case study in the United Kingdom power supply chain to demonstrate the applicability and efficacy of the proposed method in this study. This is the first comprehensive risk interdependence analysis of the United Kingdom\u27s power supply chain. The findings reveal natural disasters and climate change are the most crucial risks followed by industrial action, affordability, political instability, and sabotage/terrorism
A multi-distance interval-valued neutrosophic approach for social failure detection in sustainable municipal waste management
No full textDeveloping sustainable municipal waste management systems requires an in-depth analysis and synthesis of economic, environmental, and social sustainable development indicators. However, despite its profound impact on organizational performance, social sustainability has received little attention in previous studies compared to economic and environmental sustainability. Although a few studies have been conducted to analyze and measure the impact of social sustainability indicators, most of these endeavors fail to consider many indicators that must be evaluated under uncertain and incomplete information. This study proposes a new decision model that implements Interval-Valued Neutrosophic Sets (IVNS) within a multi-distance measure defined with respect to an ideal reference solution. IVNS allows decision-makers to reliably express their opinions using truth, indeterminacy, and falsity membership functions. A linguistic framework is developed to categorize indicators based on their performance and suggest potential solutions when detecting indicators with relatively weak performances. Social sustainability failures in the municipal waste management system of Istanbul are investigated to show the applicability and efficacy of the proposed approach. We identify salary satisfaction and health insurance as the most significant social indicators determining the success of the system, while freedom of association and citizen participation are categorized as the worst-performing ones. The stability of the proposed methodology is illustrated by performing a comparative analysis with Single-Valued Neutrosophic Sets and Interval-Valued Fuzzy Pythagorean Sets
A dynamic location-arc routing optimization model for electric waste collection vehicles
No full textWaste collection management plays a crucial role in controlling pandemic outbreaks. Electric waste collection systems and vehicles can improve the efficiency and effectiveness of sanitary processes in municipalities worldwide. The waste collection routing optimization involves designing routes to serve all customers with the least number of vehicles, total traveling distance, and time considering the vehicle capacity. This paper proposes a dynamic location-arc routing optimization model for electric waste collection vehicles. The proposed model suggests an optimal routing plan for the waste collection vehicles and determines the optimal locations of the charging stations, dynamic charging arcs, and waste collection centers. A genetic algorithm and grey wolf optimizer are used to solve the large-sized random generated NP-hard location-arc routing problems. We present a case study for the city of Edmonton in Canada and show the grey wolf optimizer outperforms the genetic algorithm. We further demonstrate the total number of waste collection centers, charging stations, and arcs for dynamic charging needed to ensure a minimum required service for electric vehicles throughout Edmonton\u27s entire waste collection system
A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering
No full textClustering is an ideal tool for working with big data and searching for structures in the data set. Clustering aims at maximizing the similarity between the data within a cluster and minimizing the similarity between the data between different clusters. This study presents a new and improved Particle Swarm Optimization (PSO) algorithm using pattern reduction and reducing the clustering calculation time with Multistart Pattern Reduction-Enhanced PSO (MPREPSO). This method adds two pattern reduction operators and multistart operators into the PSO algorithms. The goal of the pattern reduction operator is to reduce the computational time from the compression of static patterns. The purpose of the multistart operator is to avoid falling into the local optimal by enforcing diversity in the population. Two pattern reduction and multistart operators are combined with the PSO algorithm to evaluate the performance of this method
Analytics under uncertainty: a novel method for solving linear programming problems with trapezoidal fuzzy variables
No full textLinear programming (LP) has long proved its merit as the most flexible and most widely used technique for resource allocation problems in various fields. To solve an LP problem, we have traditionally considered crisp values for the parameters, which are unrealistic in real-world decision-making under uncertainty. The fuzzy set theory has been used to model the imprecise parameter values in LP problems to overcome this shortcoming, resulting in a fuzzy LP (FLP) problem. This paper proposes a new method for solving fuzzy variable linear programming (FVLP) problems in which the decision variables and resource vectors are fuzzy numbers. We show how to use the standard simplex algorithm to solve this problem by converting the fuzzy problem into a crisp one once a linear ranking function is chosen. The novelty of the proposed model resides in that it requires less effort on fuzzy computations as opposed to the existing fuzzy methods. Furthermore, to solve the FVLP problem using the existing methods, fuzzy arithmetic operations and the solution to fuzzy systems of equations are required. By contrast, only arithmetic operations of real numbers and the solution to crisp systems of equations are required to solve the same problem with the method proposed in this study. Finally, a transportation case study in the coal industry is presented to demonstrate the applicability of the proposed algorithm
Perioperative Protocol to Prevent Emergence Delirium in Patients with Post-Traumatic Stress Disorder
Full text linkIntroduction: Ten percent of adults will experience post-traumatic stress disorder (PTSD) at some point during their lifetime, 50% of which remain untreated and undiagnosed. Perioperative management of the patient with PTSD may create significant challenges for the anesthesia provider. Patients with PTSD are more likely to experience emergence delirium (ED), which poses a significant safety threat to patients and staff. Screening for PTSD is routine in the veteran population but has not yet translated into common practice. To our knowledge, no protocol currently exists for anesthetic management of patients with PTSD. Routine screening for PTSD in the preoperative period and utilization of an evidence based anesthetic protocol for this subset of patients may help prevent ED and the associated safety risks.
Methods: Literature review was conducted to search for best practices regarding anesthetic management of patients with PTSD. Database searches included Cochrane Library, CINAHL, Medline, PubMed, HAPI, Trip, Google Scholar, Proquest Dissertations and Theses Global, Psychiatry online, Psychinfo, and Summon. Eighteen studies met inclusion criteria. Directed content analysis was developed from the search, and potential components of protocol were electronically sent to a panel of expert reviewers consisting of anesthesiologists and Certified Registered Nurse Anesthetists (CRNA) in the form of a 4-point rating scale. A comment box was also available for qualitative feedback. A perioperative anesthetic protocol for patients with PTSD was developed based on directed content analysis.
Sample & Setting: Survey was sent electronically via e-mail to 31 anesthesia providers from three different hospital systems affiliated with FJTSA. Fourteen anesthesia providers completed the survey.
Results: Content validity index was performed for each item in the survey. Content validity index (I-CVI) greater than 0.78 was desirable for each item. Four out of eleven items had I-CVIs greater than 0.78.
Conclusion: Content validity scores for protocol items were undesirable despite strong existing literature that certain anesthetic techniques either contribute to ED or help prevent it. This indicates a very evident knowledge deficit regarding current best practices for perioperative management of patients with PTSD or possible PTSD. This knowledge gap suggests that anesthesia providers would benefit from an evidence-based protocol to help guide anesthetic management of patients with PTSD. Keywords: emergence delirium, PTSD, anesthesia, protoco