با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
Implementation of a standardized voiding management protocol to reduce unnecessary re-catheterization - A quality improvement project
اجرای یک پروتکل استاندارد مدیریت تخلیه برای کاهش دوباره کاتتریزاسیون غیر ضروری - یک پروژه بهبود کیفیت-2020
Objective. To design and implement a standardized postoperative voiding management protocol that accurately identifies patients with urinary retention and reduces unnecessary re-catheterization. Methods. A postoperative voiding management protocol was designed and implemented in patients undergoing major, inpatient, non-radical abdominal surgery with a gynecologic oncologist. No patients had epidural catheters. The implemented quality improvement (QI) protocol included: 1) Foley removal at six hours postoperatively; 2) universal bladder scan after the first void; and 3) limiting re-catheterization to patientswith bladder scan volumes N150 ml. A total of 96 patients post-protocol implementation were compared to 52 patients preprotocol. Along with baseline demographic data and timing of catheter removal,we recorded the presence or absence of urinary retention and/or unnecessary re-catheterization and postoperative urinary tract infection rates. Fishers exact test and students t-tests were performed for comparisons. Results. The overall rate of postoperative urinary retention was 21.6% (32/148). The new voiding management protocol reduced the rate of unnecessary re-catheterization by 90% (13.5% vs 2.1%, p = 0.01), without overlooking true urinary retention (23.1% vs 20.8%, p = 0.83). Additionally, there was a significant increase in hospital-defined early discharge prior to 11:00 AM (4.0% vs 22.0%, p = 0.022). There was no difference in the postoperative urinary tract infection rate between the groups (p=1.00). Risk factors associatedwith urinary retention included older age (p b 0.01), use of medications with anticholinergic properties (p b 0.01), and preexisting urinary dysfunction (p b 0.01). Conclusions. Implementation of this new voiding management protocol reduced unnecessary recatheterization, captured and treated true urinary retention, and facilitated early hospital discharge
Keywords: Quality improvement | Bladder voiding | Urinary retention | Postoperative management | Gynecologic Oncology surgery | Urinary tract infection
IMPROVING PAIN REASSESSMENT AND DOCUMENTATION RATES: A QUALITY IMPROVEMENT PROJECT IN A TEACHING HOSPITAL’S EMERGENCY DEPARTMENT
بهبود نرخ مستند سازی و ارزیابی مجدد : یک طرح ارتقاء کیفی در بخش آمادگی دانشگاه علوم پزشکی-2020
ED pain score reassessment and documentation rates were drastically low according to sampled data from the St. Margaret Hospital Emergency Department leading to difficult pain management encounters for clinicians. The purpose of this project was to improve pain score reassessment rates in ED patients who were discharged with extremity pain. Methods: This project was an 8-month, prepostinterventional (preintervention: September-November 2018, intervention: December 2018-January 2019, and postintervention: February-April 2019) quality improvement project that took place in a community hospital emergency department. Emergency nurses participated in 6 focus groups, allowing for the creation of focus group-themed interventions at the request of the nursing staff. Daily audits of pain reassessment and documentation rates for individual nurses took place during the month of January 2019. In addition, a weekly newsletter was created and reported the ED pain reassessment and documentation rates. Results: All patient encounters (581) were reviewed over the 8-month period. Baseline pain score reassessment and documentation rates were 36.2% (confidence interval, 30.3%-42.3%) in the emergency department. Pain reassessment and documentation rates increased to 62.3% (confidence interval, 56.8%-67.6%) during the 3-month postintervention period. Discussion: Implementing daily audits and weekly newsletters that created transparency of individual and group performances increased pain score reassessment and documentation rates.
Key words: Pain reassessment | Pain documentation | Practice improvement | Quality improvement | Pain management
Internet-of-things-based optimal smart city energy management considering shiftable loads and energy storage
مدیریت انرژی بهینه شهر هوشمند مبتنی بر اینترنت اشیا با توجه به بارهای قابل تغییر و ذخیره انرژی-2020
Formulating a novel mixed integer linear programing problem, this paper introduces an optimal Internet-of-Things-based Energy Management (EM) framework for general distribution networks in Smart Cities (SCs), in the presence of shiftable loads. The system’s decisions are optimally shared between its two main designed layers; a “core cloud” and the “edge clouds”. The EM of a Microgrid (MG), covered by an edge cloud, is directly done by its operator and the Distribution System Operator (DSO) is responsible for optimising the EM of the core cloud. Changing the load consumption pattern, based on market energy prices, for the edge clouds and their peak load hours, the framework results in decreasing the total operation cost of the edge clouds. Using the optimal trading power of the MGs aggregators as the input parameters of the core cloud optimisation problem, the DSO optimises the network’s total operation cost addressing the optimal scheduling of the energy storages. The energy storages are charged in low energy prices through the purchasing power from the market and discharged in high energy prices to meet the demand of the network and to satisfy the energy required by the edge clouds. As a result, the shiftable loads and the energy storages are used by the DSO and the MGs to meet the energy balance with the minimum cost.
Keywords: Energy management | Internet-of-Things | Microgrids | Optimal scheduling | Renewable energy sources
Predicted direct solar radiation (ECMWF) for optimized operational strategies of linear focus parabolic-trough systems
تابش مستقیم خورشیدی پیش بینی شده (ECMWF) برای استراتژی های عملیاتی بهینه شده سیستم های سهموی-تمرکز خطی -2020
Day-ahead forecasts of direct normal irradiance (DNI) from the Integrated Forecasting System (IFS), the global model of the European Centre for Medium-Range Weather Forecasts (ECMWF), are used to simulate a concentrating solar power (CSP) plant through the System Advisor Model (SAM) to assess the potential value of the IFS in the electricity market. Although DNI forecasting from the IFS still demands advances towards cloud and aerosol representation, present results show substantial improvements with the new operational radiative scheme ecRad (cycle 43R3). A relative difference of approximately 0.12% for the total annual energy availability is found between forecasts and local measurements, while approximately 10.6% is obtained for the previous version. Results of electric energy injection to the grid from a simulated linear focus parabolic-trough system shows correlations coefficients of approximately 0.87 between hourly values of electric energy based on forecasted and measured DNI, while 0.92 are obtained for the daily values. In the context of control strategy, four operational strategies are given for different weather scenarios to handle the energy management of a CSP plant, including the effect of thermal energy storage capacity. Charge and discharge operational strategies are applied accordingly to the predicted energy availability.
Keywords: Short-term forecasts | ECMWF | Direct normal irradiance | Concentrating solar power | System advisor model | Operational strategies
Influence of different time horizon-based battery energy management strategies on residential microgrid profitability
تأثیر استراتژیهای مختلف مدیریت انرژی باتری مبتنی بر افق زمان بر سودآوری میکروگریدهای مسکونی-2020
The growing share of renewable sources in future residential microgrids generates variability as well as price volatility on European electricity markets. Therefore, to handle this issue and enhance the system profitability, advanced energy management strategies should be developed. To that end, this paper proposes to assess the relevance of an energy management strategy based on 48-hour horizon compared to a 24-hour horizon one in order to perform energy arbitrage. This study considers a residential microgrid based on photovoltaic generation and storage connected to the main grid. Proposed 48-hour energy management strategy provides additional management possibilities such as the ability to delay trades (charge today, discharge tomorrow) and a larger range of hours to use the storage. Particle Swarm Optimizer is used to solve the optimization part. Besides, a sensitivity analysis is investigated to assess the economic impact of forced storage of solar surplus power in order to increase self-consumption rate and storage size. Obtained results demonstrates better profitability by using proposed strategy. Profitability was improved by more than 11% compared to classical algorithms for the tested scenarios. The findings of this study illustrate that the use of 48-hour horizon-based energy management strategy can be more profitable and lead residential microgrids to decrease their operation cost and increase power balance for all grid stakeholders through feed-in price leverage.
Keywords: Residential microgrid | Weather forecast uncertainties | Energy management strategies | Self-consumption | Grid services | Energy storage system
Optimal energy management for a grid connected PV-battery system
مدیریت بهینه انرژی برای سیستم باتری PV متصل به شبکه-2020
The increase demand for electricity and the non-renewable nature of fossil energy makes the move towards renewable energies required. However, the common problem of renewable sources, which is the intermittence, is overcome by the hybridization of complementary sources. Thus, whenever the load demand is not fully covered by the primary source, the second one will absolutely support it. Furthermore, the production, the interaction with the grid and the storage system must be managed by the grid-connected hybrid renewable energy system, which is the main objective of this paper. Indeed, we propose a new system of a grid-connected PV-battery, which can manage its energy flows via an optimal management algorithm. The DC bus source connection topology in our proposed hybrid architecture tackles the synchronization issues between sources when the load is powered. We consider in this work that choosing a battery discharge and charge limiting power provides an extension of the battery life. On the other hand, we simulated the dynamic behavior of the architecture’s various components according to their mathematical modeling. Following this, an energy management algorithm was proposed, and simulated using MATLAB/SIMULINK to serve the load. The results have shown that the load was served in all cases, taking into account the electrical behavior of the inhabitants as well as the weather changes on a typical day. Indeed, the load was served either by instant solar production between sunrise and sunset, or the recovery from sunset to 10pm, which could be a stored or injected energy without exceeding the 1000W per hour
Keywords: Renewable energy | PV-battery | Hybrid renewable system | Energy management | Hybrid architecture
Application of optimized Artificial and Radial Basis neural networks by using modified Genetic Algorithm on discharge coefficient prediction of modified labyrinth side weir with two and four cycles
استفاده از شبکه های عصبی بهینه سازی شده مصنوعی و شعاعی با استفاده از الگوریتم ژنتیک اصلاح شده بر پیش بینی ضریب تخلیه ریزگرد سمت اصلاح شده با دو و چهار چرخه-2020
Determining the discharge coefficient is one of the most important processes in designing side weirs. In this study, the structure of Artificial Neural Network (ANN) and Radial Basis Neural Network (RBNN) methods are optimized by a modified Genetic Algorithm (GA). So two new hybrid methods of Genetic Algorithm Artificial neural network (GAA) and Genetic Algorithm Radial Basis neural network (GARB), were introduced and compared with each other. The modified GA was used to find the neuron number in the hidden layers of the ANN and to find the spread value and the neuron number of the RBNN method, as well. GAA and GARB were tested for predicting the discharge coefficient of a modified labyrinth side weir he GARB method could successfully predict the accurate discharge coefficient even in cases where there is a limited number of train datasets available.
Keywords: Artificial neural network | Discharge coefficient | Hybrid model | Labyrinth side weir | Modified | Genetic algorithm | Radial basis neural network
Facilitating high levels of wind penetration in a smart grid through the optimal utilization of battery storage in microgrids: An analysis of the tradeoffs between economic performance and wind generation facilitation
تسهیل سطح بالای نفوذ باد در یک شبکه هوشمند از طریق استفاده بهینه از باتری در ریز شبکه ها : تجزیه و تحلیل مبادلات بین عملکرد اقتصادی و تسهیل تولید باد-2020
The aim of this paper was to investigate the trade-offs that can be achieved between optimizing the electricity costs of a building integrated microgrid, while simultaneously facilitating high levels of wind penetration in a smart grid. This study applied multi-objective optimization to obtain a daily charge and discharge schedule of a battery bank, which was used to both store electricity from the microgrid and smart grid and could also provide electricity to the building and the smart grid. Multi-objective optimization was employed due to the independent objectives of minimizing building operating cost and maximizing the facilitation of wind energy from the smart grid. The trade-offs between the two objectives were simulated, evaluated and analyzed. A priority weighting factor (α) was applied to each objective. The purpose of α was to vary the importance of each objective relative to the other in an inversely proportional manner. This enabled the algorithm to optimize the battery operating schedule for the economic performance of the microgrid, the facilitation of wind generation on the smart grid or for trade-offs in between. The results present a comprehensive evaluation of 96 scenarios with varying daily weather conditions, building electricity demand, electricity pricing, microgrid output and wind penetration from the smart grid. A multi-objective optimization approach was then applied for each of the 96 scenarios with 11 α values to determine optimal trade-offs in these scenarios. Generally for the 96 scenarios analyzed, when the α value was 20% or higher, the amount of extra wind generation facilitation obtained was negligible while microgrid operating costs continued to increase. The results showed that when changing from an α value of 0% to an α value of 20%, there was a large increase in wind generation facilitation compared to the corresponding increase in cost, with wind generation facilitation increasing from its minimum value to within 89% of its maximum value (10.7% to 14.3% of facilitated wind generation). The corresponding building cost increased from its minimum value to within 13% of its maximum value (€1.14/day to €1.37/day). This produced a cost of approximately €0.06 for every 1% increase in wind generation facilitation. In comparison to this, changing from an α value of 20% to an α value of 100% implied a cost of approximately €3.64 for every 1% increase in wind generation facilitation. These results indicated that smart grids with large percentages of wind penetration may be substantially aided by utilizing the storage capacity of building integrated microgrids for a relatively low monetary cost.
Keywords: Multi-objective optimization | Energy management | Wind penetration | Trade-off analysis | Battery | Microgrid
A Distinct Class of Bursting Neurons with Strong Gamma Synchronization and Stimulus Selectivity in Monkey V1
یک کلاس متمایز از پشت سر گذاشتن نورون ها با همگام سازی گاما قوی و انتخاب محرک در میمون V1-2020
Cortical computation depends on interactions between excitatory and inhibitory neurons. The contributions of distinct neuron types to sensory processing and network synchronization in primate visual cortex remain largely undetermined. We show that in awake monkey V1, there exists a distinct cell type (ii30% of neurons) that has narrow-waveform (NW) action potentials and high spontaneous discharge rates and fires in high-frequency bursts. These neurons are more stimulus selective and phase locked to 30- to 80-Hz gamma oscillations than other neuron types. Unlike other neuron types, their gamma-phase locking is highly predictive of orientation tuning. We find evidence for strong rhythmic inhibition in these neurons, suggesting that they interact with interneurons to act as excitatory pacemakers for the V1 gamma rhythm. We did not find a similar class of NW bursting neurons in L2-L4 of mouse V1. Given its properties, this class of NW bursting neurons should be pivotal for the encoding and transmission of stimulus information.
Associations of hospital discharge services with potentially avoidable readmissions within 30 days among older adults after rehabilitation in acute care hospitals in Tokyo, Japan
انجمن خدمات ترخیص بیمارستان با بستری مجدد بالقوه قابل اجتناب در عرض 30 روز در میان سالمندان بعد از توانبخشی در بیمارستانهای مراقبت حاد در توکیو ، ژاپن-2020
OBJECTIVE: To examine the associations of three major hospital discharge services covered under health insurance (discharge planning, rehabilitation discharge instruction, and coordination with community care) with potentially avoidable readmissions within 30 days (30-day PAR) in older adults after rehabilitation in acute care hospitals in Tokyo, Japan.
DESIGN: Retrospective cohort study using a large-scale medical claims database of all Tokyo residents aged ≥75 years. SETTING: Acute care hospitals PARTICIPANTS: Patients who underwent rehabilitation and were discharged to home (n=31,247; mean age: 84.1 years, standard deviation: 5.7 years) between October 2013 and July 2014.
MAIN OUTCOME MEASURE: 30-day PAR.
RESULTS: Among the patients, 883 (2.9%) experienced 30-day PAR. A multivariable logistic generalized estimating equation model (with a logit link function and binominal sampling distribution) that adjusted for patient characteristics and clustering within hospitals showed that the discharge services were not significantly associated with 30-day PAR. The odds ratios were 0.962 (95% confidence interval [CI]: 0.805-1.151) for discharge planning, 1.060 (95% CI: 0.916-1.227) for rehabilitation discharge instruction, and 1.118 (95% CI: 0.817-1.529) for coordination with community care. In contrast, the odds of 30-day PAR among patients with home medical care services were 1.431 times higher than those of patients without these services (P<0.001), and the odds of 30-day PAR among patients with a higher number (median or higher) of rehabilitation units were 2.031 times higher than those of patients with a lower number (below median) (P<0.001). Also, the odds of 30-day PAR among patients with a higher hospital frailty risk score (median or higher) were 1.252 times higher than those of patients with a lower score (below median) (P=0.001).
CONCLUSIONS: The insurance-covered discharge services were not associated with 30-day PAR, and the development of comprehensive transitional care programs through the integration of existing discharge services may help to reduce such readmissions.
Copyright © 2020. Published by Elsevier Inc.
KEYWORDS: Big data; health services for the aged; patient readmission; rehabilitation; transitional care