Assess the Nurses Knowledge and Standard Practice Regarding the Prevention of Infection in Neutropenic Patients

Neutropenia-associated infections can prolong hospitalization, increase re-admission, mortality and morbidity rates. Aim of research is to determine nurses' knowledge and infection control care practices in neutropenic patients. This descriptive study was conducted between January 2020 and April 2020, at tertiary hospital Lahore, Pakistan. Sample consisted of 150 staff nurses. Data were collected by a form included socio-demographic characteristics, neutropenia knowledge questions, and infection control care practices. Each nurse was observed by researcher for infection control care practices. For observation hand hygiene adherence was found low both in medication preparation, administration and vital signs assessment. Sterility disrupted in almost all preparation of parenteral medications. Even nurses' knowledge related with neutropenia and care of neutropenic patient was found above average their infection control care practices were found insufficient.Infected patients are a source of infection transmission to other patients, health care workers and visitors, in health care facilities. Healthcare-related infections have a significant influence on the morbidity and mortality rates in the hospital environment, resulting in an increase in the time spent in hospitalization, and are thus recognized as a serious world public health problem Neutropenia is one of the most common risk factors of serious infections in immune suppressed patients and can be the result of a variety of consequences, including from certain types of drugs, environmental toxins, vitamin deficiencies, metabolic abnormalities, as well as cancer or infections. In spite of the way that neutropenia bring about contaminations, numerous preventive treatment and care conventions are demonstrated to decrease the disease rates, and improve personal satisfaction. The counteraction and control of diseases are critical for a well-functioning health system. World Health Organization in 2011 defined infection control as infection prevention and control measures that aims to confirm the defense of those who might be susceptible to obtaining an infection both in the general community and in hospitals while obtaining care due to health problems. Keywords: Nurses, Knowledge, practice, prevention, neutropenic patients. DOI: 10.7176/JHMN/77-05 Publication date:July 31st 202

Fault detection through discrete wavelet transform in overhead power transmission lines

Transmission lines are a very important and vulnerable part of the power system. Power supply to the consumers depends on the fault-free status of transmission lines. If the normal working condition of the power system is disturbed due to faults, the persisting fault of long duration results in financial and economic losses. The fault analysis has an important association with the selection of protective devices and reliability assessment of high-voltage transmission lines. It is imperative to devise a suitable feature extraction tool for accurate fault detection and classification in transmission lines. Several feature extraction techniques have been used in the past but due to their limitations, that is, for use in stationary signals, limited space in localizing nonstationary signals, and less robustness in case of variations in normal operation conditions. Not suitable for real-time applications and large calculation time and memory requirements. This research presents a discrete wavelet transform (DWT)-based novel fault detection technique at different parameters, that is, fault inception and fault resistance with proper selection of mother wavelet. In this study, the feasibility of DWT using MATLAB software has been investigated. It has been concluded from the simulated data that wavelet transform together with an effective classification algorithm can be implemented as an effective tool for real-time monitoring and accurate fault detection and classification in the transmission lines.© 2023 The Authors. Energy Science & Engineering published by Society of Chemical Industry and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Mitigation of Power Losses and Enhancement in Voltage Profile by Optimal Placement of Capacitor Banks With Particle Swarm Optimization in Radial Distribution Networks

The prime purpose of placing a capaci- tor bank in a power system is to provide reactive power, reduce power losses, and enhances voltage profile. The main challenge is to determine the optimum capacitor position and size that reduces both system power losses and the overall cost of the sys- tem with rigid constraints. For this purpose, different optimization techniques are used, for example Particle Swarm Optimization (PSO) which converges the com- plex non-linear problem in a systematic and method- ological way to find the best optimal solution. In this paper, the standard IEEE 33-bus and 69-bus systems are used to find the optimum location and size of the capacitors bank. These power networks are simu- lated in Siemens PSS®E software. For the optimum solution of capacitor banks, the PSO algorithm is used. The PSO fitness function is modelled in such a way which contains the high average bus voltage, the small size of capacitor banks, and low power losses. The fitness function used is a weighted type to reduce the computation time and multi-objective function complexity

Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in practice. These internet-based applications can run on the distributed healthcare sensing system, which combines mobile computing, edge computing and cloud computing. Offloading and scheduling are the required methods in the distributed network. However, a security issue exists and it is hard to run different types of tasks (e.g., security, delay-sensitive, and delay-tolerant tasks) of IoMT applications on heterogeneous computing nodes. This work proposes a new healthcare architecture for workflow applications based on heterogeneous computing nodes layers: an application layer, management layer, and resource layer. The goal is to minimize the makespan of all applications. Based on these layers, the work proposes a secure offloading-efficient task scheduling (SEOS) algorithm framework, which includes the deadline division method, task sequencing rules, homomorphic security scheme, initial scheduling, and the variable neighbourhood searching method. The performance evaluation results show that the proposed plans outperform all existing baseline approaches for healthcare applications in terms of makespan

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

An Antecedence Graph Approach for Fault Tolerance in a Multi-Agent

In this paper, we propose a strategy to implement fault-tolerance in a multi-agent system. We have based our strategy on the concept of antecedence graphs, used in causal logging and as used by the manetho protocol for distributed systems. Each agent in the multi-agent system keeps an antecedence graph of all the collaborating agents in the system. If one or more agents fail due to any reason, the other agents can reconstruct the same agent state in a partial or comprehensive manner by using their own antecedence graphs. The recovering agents then regenerate their antecedence graphs and message logs and replay the messages to achieve a global consistent state, after which normal operation continues. We believe that introducing fault tolerance in a multi-agent system through antecedence graphs is novel and provides a low overhead and effective solution for fault-tolerance in a multi-agent system