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Background: Traumatic brain injury (TBI) is one of the leading causes of disability and death worldwide. Most TBI cases occur in older people, because they are at a higher risk of accidental falling. As the population ages, the use of anticoagulants is increasing. Some serious complications of TBI, such as intracranial hemorrhage (ICH), may occur even in mild cases. According to the current guidelines regarding managing mild TBI patients, a CT head scan is recommended for all patients receiving anticoagulation. We aim to assess the incidence of ICH in patients with mild TBI taking oral anticoagulants. Methods: Our systematic review and meta-analysis were performed using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) checklist. The protocol was registered in PROSPERO (CRD42024503086). Twenty-eight studies evaluating patients with a mild TBI from ten countries with a total sample size of 11,172, 5671 on DOACs, and 5501 on VKAs were included in our meta-analysis. Results: The random-effects overall incidence of ICH among oral anticoagulated patients with mild TBI was calculated to be 9.4% [95% CI 7.2–12.1%, I2 = 89%]. The rates of immediate ICH for patients taking DOACs and VKAs were 6.4% and 10.5%, respectively. The overall rate of immediate ICH in anticoagulated mild TBI patients was 8.5% [95% CI 6.6–10.9%], with a high heterogeneity between studies (I2 = 88%). Furthermore, the rates of delayed ICH in patients with mild TBI taking DOACs and VKAs were 1.6% and 1.9%, respectively. The overall incidence of delayed ICH among oral anticoagulated mild TBI patients was 1.7% [95% CI 1–2.8%, I2 = 79%]. The overall rate of ICH among mild TBI patients taking DOAC was calculated to be 7.3% [95% CI 5.2–10.3%], with significant heterogeneity between studies (I2 = 79%). However, the overall ICH rate is higher in patients who take only VKAs 11.3% [95% CI 8.6–14.7%, I2 = 83%]. Patients on DOACs were at lower risk of ICH after mild TBI compared to patients on VKAs (OR = 0.64, 95% CI 0.48–0.86, p < 0.01, I2 = 28%). Conclusion: Our meta-analysis confirms the need for performing brain CT scan in patients with mild TBI patients who receive oral anticoagulants before injury. Due to limited data, further multi-center, prospective studies are warranted to confirm the true incidence of traumatic ICH in patients on anticoagulants. [ABSTRACT FROM AUTHOR]

Summary Multilevel inverters are known as essential converters in renewable sources. First, in this paper, a new submodule is presented, and based on it, a new sub‐multilevel inverter is presented. The proposed sub‐multilevel inverter consists of several unidirectional and bidirectional switches and DC voltage sources. Then, the generalized topology, developed in two modular and cascaded modes, is presented to increase production levels. The proposed submodules are connected in series in the modular topology, increasing production levels. The proposed topology to produce the maximum output levels has the minimum number of IGBTs, drivers, DC voltage sources, etc. Mathematical analyses for conduction and switching losses are provided, and mathematical analyses for the number of devices and voltage across the switches are also presented. In addition to the mathematical analysis of losses, the simulation results are also presented. A general comparison of proposed topology components is presented to demonstrate their advantages. This comparison shows that the proposed topology has the minimum number of power electronic devices. In this paper, nearest level modulation is used to control the proposed topology. The simulation and experimental results of the proposed sub‐multilevel verify the performance of the proposed topology. [ABSTRACT FROM AUTHOR]

In this paper, a new topology is introduced for capacitor-based multi-level inverters. The proposed topology is based on combination of two Cross-Square-Switched T-Type inverters. This structure can be generalized in two modular and cascaded modes. In the cascaded mode, higher voltage levels are produced with low power switches. The main features of the proposed topology include the level generation without the utilization of the H-bridge module, the low number of switching components, a lower number of DC voltage sources, and low total blocking voltage. Besides, in the proposed topology, the number of conducting switches in the current path for each different voltage level is low, which leads to a conduction loss decrement. The loss simulations are performed, and the results are presented. A study provides a detailed comparison of the proposed topology in terms of various parameters. In this paper, the nearest level modulation switching, which is low-frequency switching, is utilized to generate voltage levels. To confirm the performance of the proposed topology, a simulation was performed with MATLAB/Simulink software, and a laboratory sample was implemented. Comparative results, simulation results, and implementation results indicate the appropriate performance of the proposed structure in different steady-state and dynamic conditions. [ABSTRACT FROM AUTHOR]

This paper introduces a new structure of a multi-level inverter (MLI) to generate high-level AC voltages using a low number of switches with a quasi-sine waveform. The small number of driver circuits utilised in bidirectional switches is a salient characteristic of this inverter. Also, the number of conducting switches at each voltage level is low in this structure. This results in lower conduction losses of the switches. The proposed topology can be used as the cascaded structure with different approaches to select the value of voltage sources. Power losses are discussed for the proposed structure. To compare the proposed multi-level inverter and demonstrate its superiority, a comparison has been made with some recently presented topologies. According to the comparison results, the advantage of the proposed structure is producing high voltage levels with a smaller number of switches and driver circuits. To prove the suitable performance of the proposed MLI, a 21-level symmetric and 37-level asymmetric inverter containing 14 switches are designed and simulated in the MATLAB/Simulink program. A laboratory prototype for each of these inverters is implemented. The experimental results finely verify the simulations. Besides, an accurate comparison with recently introduced multilevel inverters has been carried out to confirm the effectiveness and superiority of the proposed structure. [ABSTRACT FROM AUTHOR]

Summary: Multilevel inverters have many applications, such as the grid integration of photovoltaic cells, FACTSs devices, electric vehicles, variable speed drives, and smart grids. In this paper, a new bidirectional diode‐based unit is proposed for a symmetric single‐phase modular inverter topology that can achieve high output levels by using a small number of switching and circuit devices. The basic structure can generate nine‐level voltage with only nine IGBTs and two diodes. Another advantage of the proposed topology is the utilization of a half‐bridge module to change the voltage polarity and the low number of its voltage sources. Additionally, the proposed topology can be used as the cascaded structure with different approaches to select the value of voltage sources. The power losses are discussed for the proposed basic module. A comparison has been made with some recently presented topologies to compare the proposed multilevel inverter and demonstrate its superiority. The comparison is performed for the basic module and its generalized structure. In this paper, the pulse width modulation technique is utilized to achieve a voltage waveform with low harmonic content. The proposed basic structure has an efficiency of 58.98% in 5KW power. Finally, the operation of the proposed basic module is simulated, and the laboratory prototype results confirm the accuracy of the simulation results. [ABSTRACT FROM AUTHOR]

Background: The principal aim of this study was to determine the prevalence of intracranial pressure (ICP) monitoring and intracranial hypertension (IHT) in patients treated for moderate traumatic brain injury (TBI). A secondary objective was to assess factors associated with ICP monitoring. Methods: We conducted a systematic review of the literature to identify studies that assessed ICP monitoring in moderate TBI. The meta-analysis was performed by using a random-effects model. Results: A total of 13 studies comprising 116,714 patients were pooled to estimate the overall prevalence of ICP monitoring and IHT (one episode or more of ICP > 20 mm Hg) after moderate TBI. The prevalence rate for ICP monitoring was 18.3% (95% confidence interval 8.1–36.1%), whereas the proportion of IHT was 44% (95% confidence interval 33.8–54.7%). Three studies were pooled to estimate the prevalence of ICP monitoring according to Glasgow Coma Scale (GCS) (≤ 10 vs. > 10). ICP monitoring was performed in 32.2% of patients with GCS ≤ 10 versus 15.2% of patients with GCS > 10 (p = 0.59). Both subgroups were highly heterogeneous. We found no other variables associated with ICP monitoring or IHT. Conclusions: The prevalence of ICP monitoring in moderate TBI is low, but the prevalence of IHT is high among patients undergoing ICP monitoring. Current literature is limited in size and quality and does not identify factors associated with ICP monitoring or IHT. Further research is needed to guide the optimal use of ICP monitoring in moderate TBI. [ABSTRACT FROM AUTHOR]

Multi‐level inverters (MLIs) for medium or high power and voltage utilization have acceptable application in industry and are utilized commercially. The performance of MLIs is considerably preferable to traditional two‐level inverters due to their negligible harmonic content, small filter size, utilization of lower‐rated voltage devices, low electromagnetic interference (EMI), and so on. However, in the face of these many advantages, few disadvantages can be expressed such as more device count and a sophisticated control strategy. This paper presents an improved switched‐ladder topology to enhance the performance of multi‐level inverters by improving the above drawbacks. Compared to existing inverter topologies, the proposed extendable diode‐containing bidirectional structure requires fewer switches and driver circuits. The proposed topology is compared with other similar topologies, and its superiority is examined. Fundamental switching frequency modulation technique is utilized to obtain high‐quality output voltage waveforms with lower harmonic contents and reduced switching losses. This converter, despite the use of diodes, can supply the low power factor inductive‐resistive loads, bidirectionally. To demonstrate the performance of the proposed topology, in addition to simulation with the nearest level modulation technique, a prototype of the proposed structure has been implemented and tested. The results display the proper performance of the proposed topology in the real‐time environment. [ABSTRACT FROM AUTHOR]

Multilevel inverters are a new generation of DC–AC converters at medium and high voltage and power levels. In this paper, a new single-phase cascaded multilevel inverter is presented. For this purpose, a new basic cell is presented at first. Then, the new multilevel inverter structure is yielded by series connection of these cells. The proposed new cell is only capable of generating positive voltage levels, and therefore, to produce zero and negative voltage levels, the proposed structure is constructed based on H-bridge module. In order to reduce the maximum blocking voltage especially on H-bridge switches, the cascaded connection of the proposed converter is investigated. A comprehensive comparison is carried out between the proposed multilevel inverter with the classical and recently introduced structures in terms of the number of switching devices, the number of drivers, the total blocking voltage of the switches as well as the loss and efficiency. The accuracy of the proposed inverter's performance is simulated in MATLAB/Simulink in symmetric and asymmetric topologies for a 17-level and 23-level output voltage respectively, and then evaluated by the laboratory prototype. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a bidirectional diode containing multilevel inverter is introduced to reduce the number of switching elements especially in the case of a high number of output voltage levels. In comparison with classic and recently introduced symmetrical topologies, which are trying to reduce the switch count, this topology has a lower number of semiconductor switches in the same number of output voltage levels. This makes the proposed inverter to be a suitable choice for medium voltage applications like renewable energy applications as well as medium voltage electric drives. Moreover, it can be used in a cascaded configuration for high voltage levels. To depict the performance of the proposed structure, a comprehensive comparison is made between this topology and classic and recently proposed symmetric topologies in terms of switch and gate driver count, power losses, and cost. The performance of the proposed symmetrical 11‐level converter is analyzed and simulated in MATLAB/Simulink for both PWM and selective harmonic elimination switching methods. Not only the results are desirable but also the experimental results of laboratory prototype validate the simulation results. [ABSTRACT FROM AUTHOR]

Introduction: Residency applications via virtual-interview could potentially mitigate the extensive cost and time required for customary in-person interviews. We outline the perception of medical students and residents on the use of virtual-interview for residency applications in lieu of in-person interviews. Methods: We obtained 1824 responses from medical students and residents through an online questionnaire between March2019-Feb2020 in Texas-United States. The survey had 11 statements (five in favor of in-person interviews and 6 in favor of virtual interviews) that respondents could rank on a 5-point Likert scale. All statements' scores were summed based on the response given by each participant to create a total score between 11 and 55. The perception of the two groups was analyzed using an independent sample T-test and ANOVA. Results: We received a total of 1711 responses from medical students and 113 from medical residents. Respondents were more female (82.2% of medical students and 47.8% of residents), with a mean age of 22.87±3.42 years old for medical students and 28.72±4.35 years old for residents. Both groups preferred in-person interviews; however, the residents were significantly more in favor (P = 0.03). Both groups agree that virtual-interviews should be as an option, though this was considerably higher in the medical students (P = 0.001). In the multivariate analysis, "travel distance" and "type of medical school" had a significant impact on choosing the virtual-interviews in both groups (p<0.01). Conclusions: In-person interviews are favored by both medical students and residents compared to virtual-interview services in normal circumstances. However, both groups agree that programs should offer the option of having virtual-interviews as an available choice. Distance to an interview location and the type of medical school were the factors that had a significant impact on perception of using virtual-interviews. Knowing about the applicants' attitude toward residency interviews and the national circumstances are essential when preparing the interview guides. Our findings are limited by the small sample size and the low response rate. Further extensive studies are warranted to better understand the perception of residency applicants toward virtual-interviews to improve the interview process in the United States. [ABSTRACT FROM AUTHOR]

In this paper, a novel Cascaded H-Bridge (CHB)-based multilevel inverter for symmetric/asymmetric configurations is presented. The proposed MLI can be utilized in medium-voltage applications such as electrical machine drives as well as grid connection of renewable energy resources. The proposed structure uses fewer count of semiconductor devices at the same voltage level in comparison with classic and advanced structures. Cascaded connection of the proposed basic cells leads to reduce complexity and increase efficiency of the proposed structure. In order to investigate the capability and superiority of the proposed structure, a comprehensive comparison is conducted between this structure and the advanced ones in terms of efficiency, switch and gate driver count, and total blocking voltage (TBV). The fundamental frequency switching method is employed to generate proper switching pulses. The performance of the proposed multilevel inverter is investigated by simulating in MATLAB/Simulink environment. The experimental implementation for proposed 15-level symmetric and 33-level asymmetric structures validates the correctness of simulation results. [ABSTRACT FROM AUTHOR]

In this paper, a quadruple boost switched-capacitor multi-level inverter is proposed. The proposed structure utilizes a DC source, 11 switches, and a diode to achieve 17-level output voltage levels. This structure consists of three capacitors with the ability for self-balancing voltages. The capacitors achieve automatic voltage balancing through a series/parallel connection with the input voltage source. To control the switching pulses of the switches, level-shifted pulse width modulation (LS-PWM) strategy has been employed. A comparative evaluation has been performed between the proposed structure and structures presented in recent articles, considering various parameters such as voltage gain, number of DC sources, number of semiconductor devices, maximum blocking voltage (MBV), and total standing voltage (TSV). Considering this comparison, the lower number of semiconductor devices for generating a 17-level output with suitable voltage gain, and especially the cost-effectiveness of the structure, are the main advantages of the proposed configuration. In addition, a soft charging method has been employed to limit the inrush current of capacitors. Moreover, the power losses of the proposed structure have been investigated, indicating its acceptable efficiency. Finally, for the analysis and validation of the proposed structure's performance, an experimental prototype has been implemented and evaluated under various conditions. The results indicate satisfactory performance of the proposed structure under various stable and dynamic operating conditions. [ABSTRACT FROM AUTHOR]

Today, multilevel inverters are widely utilized in various applications. Reducing the number of components in the design of these converters is one of the crucial goals so that they have less volume and cost. This paper presents a single‐source structure for a multilevel switched‐capacitor inverter with voltage boost capability. The proposed structure can generate 25 sinusoidal‐like step voltage levels with a six times amplitude increase compared to the input. This converter uses only one direct current (DC) power source, 14 switches, and four capacitors. The nearest level control switching method has been used to control the converter, create voltage levels, and select the switching modes. A comprehensive comparison has been made with other recently presented structures to demonstrate the efficiency of the proposed structure. The advantages of the proposed structure include using only one DC voltage source, the ability to increase the output voltage six times compared to the input, the use of fewer power electronics components compared to the number of voltage levels, proper efficiency, self‐balancing of capacitors, and as a result, the lower cost. The performance accuracy of the proposed converter has been simulated in the MATLAB Simulink environment and then evaluated by a laboratory prototype. [ABSTRACT FROM AUTHOR]

The NIS is mainly based on the ICD codes that the clinicians selected for their patients, and it is essentially based on the clinical workups that they have done for the patients to come up with these diagnoses, such as TC and ICH. As we have mentioned in our article, specifically in the Methods section, the I International Classification of Diseases, Tenth Revision i (ICD-10) diagnosis codes were used to include patients with ICH and a coexisting diagnosis of TC. In your letter to the editor, it is commented that our article did not mention the basis of inclusion criteria to select the patients with takotsubo cardiomyopathy (TC). [Extracted from the article]

Abstract This study presents a self-constructing fuzzy neural network (SCFNN) based static synchronous series control (SSSC) to mitigate the inter-area oscillations in interconnected power systems. The proposed intelligent system includes an on-line trained fuzzy neural network (FNN) controller with adaptive learning rates (ALRs) and self-constructing mechanism. The Lyapunov scheme is employed to obtain the adaptive learning rates. Therefore, convergence of the suggested controller can be ensured. The proposed approach is such that, at first, originally, no neurons exist in the structure of FNN. In fact, they are automatically created and if it is required, they will be created. Therefore, the total time for training algorithm is significantly reduced and the speed of controller is considerably increased. In addition, the Prony technique is utilized to guesstimate the damping ratio of oscillations. The results confirm the usefulness of the suggested controller. [ABSTRACT FROM AUTHOR]

Due to increasing of uncertainty in nowaday power systems, probabilistic security assessment has become one of the challenging issues in power systems. This paper, proposes a new real-time approach for calculating probabilistic critical clearing time (CCT) which is applicable to probabilistic transient stability assessment. The proposed method aims to provide a low computational burden and high-accuracy to calculate the probabilistic density function (PDF) of CCT in two stages. In the first stage, proposed method presents a novel sensitivity based approach, which calculates CCT in the first step of the simulation. Determination of CCT by taking structure preserving into account, guarantees the accuracy of the proposed method. In the second stage, by applying Quasi Monte Carlo (QMC) simulation, the PDF of CCT is obtained. Several different parameters that affect uncertainty of CCT such as load and generation and also fault location are considered in order to obtain the PDF of CCT. Several case studies have been conducted on IEEE 9 bus and 68 bus test systems to show the efficiency of the proposed method. Simulation results indicate that the proposed method has notable accuracy along with substantial speed in performing the required calculations. [ABSTRACT FROM AUTHOR]

This paper investigates energy flow of Multi-Carrier Energy Systems using Point Estimate Method and Monte Carlo simulation considering uncertainties, which may happen in the Electrical, Natural Gas, and District Heating Networks all together. These uncertainties could occur from the probabilistic behavior of loads or unforeseen faults. An innovative probabilistic energy flow of Multi-Carrier Energy Systems based on Point Estimate Method has been presented in this paper. Results for two different case studies are investigated and compared against those achieved from the Monte Carlo simulation. The results prove that the presented point estimate schemes have precise results, smaller computational burden, and time, comparing than Monte Carlo simulation method. [ABSTRACT FROM AUTHOR]

In this paper, a new approach is recommended for damping out power system oscillations. In this approach, a new fuzzy neural proportional–integral (PI) controller (FNPIC) based static synchronous series compensator (SSSC) and a fuzzy-power system stabilizer (fuzzy-PSS) with a new structure are simultaneously employed. Adaptive learning rates based on the Lyapunov stability theory to enhance the convergence speed of the proposed controller are obtained. In the structure of fuzzy-PSS, a pattern search algorithm is used to adjust four gains. A two-area four-machine power system and a three-area, three-machine power system are employed to investigate the efficiency of the proposed method. Simulations results confirm the capabilities of proposed controller in suppressing the power system oscillations. [ABSTRACT FROM AUTHOR]

This paper analyzes the energy consumption of buildings considering the uncertainty of structural and environmental parameters. To this end, two-point estimate method (2PEM) is used to model the uncertainties. EnergyPlus software is used in this paper to evaluate the energy consumption, the thermal comfort, and the energy cost of a building. We examine the proposed method in a retail building to show the effectiveness of the method in comparison with the Monte-Carlo Simulation and deterministic methods. The results show that the 2PEM method although may cause a bit accuracy loss, it can considerably reduce the simulation time by more than 97%. In addition, a sensitivity analysis is effectuated in this paper to investigate the impacts of different climate zones on the results of energy consumption analysis. [ABSTRACT FROM AUTHOR]

In this paper, an optimization technique based on time-varying acceleration particle swarm optimization (TVAC-PSO) is applied for optimizing economic dispatch and emission reduction problems in a system consisting of CHP units. At first algorithm is used for deterministic model that for comparison with previous works. Besides, its convergence speed is adequately high. Then Monte Carlo method is implemented to solve the stochastic model providing real situation. In the Monte Carlo simulation you have a range of values as a result, and you are able to understand the risk and uncertainty in the model. Deterministic models used for conventional economic dispatch problems are not able to address some real conditions in practical applications. Deterministic models of power system applications are incapable to express the uncertainties that come from energy demand and supply of intermittent renewable systems. Due to the presence of these various uncertain variables stochastic attitude is inevitable in practical applications. Therefore, solving economic dispatch and emission reduction problems simultaneously and stochastically that is the main objective of this paper has a great level of importance. For modeling accurately, both power transmission losses and nonlinear fuel cost function are considered. The proposed method is applied to a 7-unit test system. [ABSTRACT FROM AUTHOR]

Decaying DC component has considerable effect on both accuracy and speed of convergence in numerical and digital relays for estimating fundamental phasor. Basically, this component causes unwanted and undesired oscillations in the time response of the fundamental phasor. As a result, it extremely affects decision making of the protective relay, which operates according to fundamental phasor component. In this study, a novel hybrid algorithm based on integration and half-cycle discrete Fourier transform (HDFT) is presented. Proposed method of this study is able to efficiently estimate fundamental frequency component by taking different parameters, including DC offset in the fault current, DC offset in a current transformer secondary side and off-nominal frequency condition into account. Moreover, in this study, modified DFT-based method for phasor estimation that is called combined integration and HDFT (CIHDFT) is put forward, which accurately estimates the original value of fundamental frequency phasor in half-cycle by considering the presence of harmonics in the waveforms. The proposed method is successfully applied to different test cases, followed by discussion on the results. Analysing the simulation results, it can be concluded that CIHDFT algorithm has remarkable performance in comparison with previous phasor estimation algorithms. [ABSTRACT FROM AUTHOR]

Decaying DC component has considerable effect on both accuracy and speed of convergence in numerical and digital relays for estimating fundamental phasor. Basically, this component causes unwanted and undesired oscillations in the time response of the fundamental phasor. As a result, it extremely affects decision making of the protective relay, which operates according to fundamental phasor component. In this study, a novel hybrid algorithm based on integration and half‐cycle discrete Fourier transform (HDFT) is presented. Proposed method of this study is able to efficiently estimate fundamental frequency component by taking different parameters, including DC offset in the fault current, DC offset in a current transformer secondary side and off‐nominal frequency condition into account. Moreover, in this study, modified DFT‐based method for phasor estimation that is called combined integration and HDFT (CIHDFT) is put forward, which accurately estimates the original value of fundamental frequency phasor in half‐cycle by considering the presence of harmonics in the waveforms. The proposed method is successfully applied to different test cases, followed by discussion on the results. Analysing the simulation results, it can be concluded that CIHDFT algorithm has remarkable performance in comparison with previous phasor estimation algorithms. [ABSTRACT FROM AUTHOR]

Joint strengthening of the existing RC frames with smooth bars (plain bars) built before the 1970s, protects beam-column joints against shear failure and increases the lateral load resistance of these frames; but due to the inherent flexural weakness of the columns, and the lack of strong column-weak beam mechanism, the occurrence of soft storey is probable in these frames under lateral loads, thereby making them vulnerable. In order to find a suitable solution for the seismic retrofitting of these frames, different retrofit strategies were investigated. NSM technique was utilized for the flexural strengthening of columns as an effective and practicable method, and for the seismic retrofitting of joints, FRP jackets were considered due to their compatibility with the NSM technique. Consequently, by combining these techniques, different retrofit strategies were proposed. To evaluate these strategies, first the proposed physical models for columns, beams, and joints were extracted based on the experimental results, and the analytical model of the frames was created by assembling these physical models. Afterwards, nonlinear static and incremental dynamic analyses were conducted. The results indicate that in the frames with strengthened joints and columns, strong column-weak beam concept is achieved, soft storey mechanism is eliminated, and the lateral load capacity and the dissipated energy increase considerably. Therefore, the seismic performance of the frames improves. Also, the flexural strengthening of columns is adequate to be performed up to the storey in which soft storey mechanism may occur, and the flexural strengthening of the columns at other storeys does not have a major effect. [ABSTRACT FROM AUTHOR]

In this paper, an effective numerical method to solve the Cauchy type singular Fredholm integral equations (CSFIEs) of the first kind is proposed. The collocation technique based on Bernstein polynomials is used for approximation the solution of various cases of CSFIEs. By transforming the problem into systems of linear algebraic equations, we see that this approach is computationally simple and attractive. Then the approximate solution of the problem in truncated series form is obtained by using the matrix form of this method. Convergence and error analyses of the presented method are mentioned. Finally, numerical experiments show the validity, accuracy, and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive self-tuning PID fuzzy sliding mode controller (ASPFSM) with a PID switching surface is proposed to damp power system oscillations. To overcome the problems in the design of a sliding-mode controller, which are the supposition of known uncertainty bounds and the chattering phenomenon in the control effort, an adaptive self-tuning PID based Lyapunov theory is studied. An adaption law is obtained from the Lyapunov stability theory, so the stability of the closed-loop system can be guaranteed. Then, the effectiveness of the ASPFSM is studied under different situations of a two-area four-machine power system. The simulation results confirm that performance of ASPFSM is much better than conventional power system stabilizer (CPSS). [ABSTRACT FROM AUTHOR]

A multi-carrier energy network is a system consists of several energy carriers such as electricity, natural gas, heat, etc . Generally, each transmission network is optimized separately but it could overshadow the actual optimal operation of the whole energy network. An integrated viewpoint opens a new window on optimization analysis. Among various networks, district heating networks are very promising for energy saving and carbon emission reduction. In this paper, effects of utilizing this network on optimization of a multi-carrier energy system are shown. However, such a problem has a considerable number of variables that makes a non-linear, non-convex, non-smooth, and high-dimension optimization problem and the optimal solution cannot be achieved by conventional mathematical techniques. Therefore, it is better to use evolutionary algorithms instead. In this paper, the well-known modified teaching-learning based optimization algorithm is used to solve the problem. Various simulations on a typical system show the impacts of a district heating network in the multi-carrier energy system. [ABSTRACT FROM AUTHOR]

The authors discuss the professional and ethical aspects of wearing scrubs outside a clinical setting. Topics include the foundational principles of antiseptic surgery established by surgeon Joseph Lister, patients' perceptions and visual representation of scrubs, and the speculation within the healthcare industry over global awareness of hospital-acquired infections.

In this paper, an integrated approach to optimize electrical, natural gas, and district heating networks simultaneously is studied. Several interdependencies between these infrastructures are considered in details including a nonlinear part-load performance for boilers and CHPs besides the valve-point effect for generators. A novel approach based on selecting an appropriate set of state-variables for the problem is proposed that eliminates the addition of any new variable to convert irregular equations into a regular set while the optimization problem is still solvable. As a large optimization problem, the optimal solution cannot be achieved by conventional mathematical techniques. Hence, it is better to use evolutionary algorithms instead. In this paper, the well-known modified teaching–learning based optimization algorithm is utilized to solve the multi-period optimal power flow problem of multi-carrier energy networks. The proposed scheme is implemented and applied to a typical multi-carrier energy network. Results are compared with some other conventional heuristic algorithms and the applicability and superiority of the proposed methodology is verified. [ABSTRACT FROM AUTHOR]

Environmental concerns besides fuel costs are the predominant reasons for unprecedented escalating integration of wind turbine on power systems. Operation and planning of power systems are affected by this type of energy due to the intermittent nature of wind speed inputs with high uncertainty in the optimization output variables. Consequently, in order to model this high inherent uncertainty, a PRPO (probabilistic reactive power optimization) framework should be devised. Although MC (Monte-Carlo) techniques can solve the PRPO with high precision, PEMs (point estimate methods) can preserve the accuracy to attain reasonable results when diminishing the computational effort. Also, this paper introduces a methodology for optimally dispatching the reactive power in the transmission system, while minimizing the active power losses. The optimization problem is formulated as a LFP (linear fuzzy programing). The core of the problem lay on generation of 2m + 1 point estimates for solving PRPO, where n is the number of input stochastic variables. The proposed methodology is investigated using the IEEE-14 bus test system equipped with HVDC (high voltage direct current), UPFC (unified power flow controller) and DFIG (doubly fed induction generator) devices. The accuracy of the method is demonstrated in the case study. [ABSTRACT FROM AUTHOR]

In this paper, a multi-objective optimization approach for multi-carrier energy networks is discussed. A multi-carrier energy network is a system consists of various types of energy carrier such as electricity, natural gas, and heat. Minimizing the total cost of operation of such a system is a typical objective for optimization while another important objective is to minimize the total emission generated by the whole network. It is shown in the paper that the cost and emission functions are two opposite objectives that decreasing one of them would increase the other one and vice versa. Therefore, a multi-objective optimization should be utilized to obtain the global optima of the problem based on the priority of each objective. According to the large size of the problem in actual networks, this could be a non-linear, non-convex, non-smooth, and high-dimension optimization problem that mathematical techniques could be trapped in local minima. Hence, it is better to use evolutionary techniques instead. To do so, a fuzzy decision making method is proposed in this paper which is merged with the well-known modified teaching-learning based optimization algorithm. This approach is implemented and applied to a typical multi-carrier energy network to verify the proposed methodology. [ABSTRACT FROM AUTHOR]

Introduction of the International Classification of Diseases, Tenth Revision (ICD-10) in 2015 was aimed for a more detailed classification of mortality statistics of diseases, such as classifying the anatomical locations for intracerebral hemorrhage (ICH). We aimed to describe the demographics and in-hospital mortality of specified ICH locations based on ICD-10 classification. Patients with a principal diagnosis of spontaneous ICH in the United States, extracted from the Nationwide Inpatient Sample (NIS) from 2015 to 2018. Subgroups of ICH locations were analyzed individually for age, gender, ethnicity, in-hospital mortality, hospital length of stay (LOS), hospital cost, and EVD placement. During the study period, there were 408,285 ICH patients with a mean age of 66.28 (17.11) years, 52.09% male, mainly Intraventricular (21.87%) and cortical hemispheres (19.83%). Total ICH in-hospital mortality was 21.07%, while brainstem was associated with the highest in-hospital mortality (40.68%) followed by intraventricular (33.08%) and multiple localized locations (30.16%). The mean hospital length of stay was 9.56(14.10) days, and the mean hospital cost was $32,453.38(56,851.59). Intraventricular Hemorrhage had the highest hospital LOS 12.39(17.44) and the highest hospital cost $47,385.25(76,187.5). Our results characterized the demographics of ICH in the US with in-hospital mortality of one out of five patients. Detail breakdown of ICH locations can improve the mortality statistics and provide more information about the ICH locations with higher hospital expenses. • Intracerebral Hemorrhage in the US has in-hospital mortality of 21.07%, which is one out of every five patients. • Intraventricular hemorrhage and cortical hemorrhages are the most reported specified locations in the ICD-10 coding system. • The highest reported mortality was in the brain stem intracerebral hemorrhage, and the highest hospital expenses belong to intraventricular hemorrhages. [ABSTRACT FROM AUTHOR]

The concurrent expansion of both electrical and thermal energy distribution systems has been addressed in this paper. The EEP (energy expansion planning) is formulated as a multi-objective optimization problem which is subjected to reduced I&O (investment and operation) costs as well as to improve the system reliability. As a result, apart from the total costs, the reliability measures of SAIFI (system average interruption frequency index), SAIDI (system average interruption duration index), and AENS (average energy not supplied) have been included in the objective function. Moreover the ability of the system reconfiguration in enhancing the system reliability has also been employed as a failure rate reduction strategy. The proposed EEP problem tries to minimize the objective function with respect to system constraints by means of rewiring, network reconfiguration, installation of new lines and also new electrical/thermal generating units. Such complex large-scale optimization problem mandates the utilization of an effective optimization tool to find the global optimum solution. The well-known TLO (Teaching Learning Optimization) is the core of exploited optimization method, ITLO (Improved TLO), in solving the proposed static EEP problem. In order to evaluate the proposed algorithm, two modified test systems are used as case studies. [ABSTRACT FROM AUTHOR]

Simultaneous expansion of the electrical and thermal energies collected with conventional expansion options is scrutinised. A robust, bio‐inspired evolutionary optimisation method is proposed, to handle the complex expansion planning of a system consisting of both electrical and thermal forms of energy. Rewiring, network reconfiguration, installation of new lines and also new electrical and thermal generation units are considered as the traditional alternatives in expansion planning. To solve the problem, overall generation requirements of a network are assigned along the planning horizon. The allocation problem is formulated as a mixed‐integer non‐linear programming problem that minimises the overall system cost owing to generation capacity among the grid nodes and the newly added or upgraded lines. The performance of the original shuffled frog leaping (SFL) optimisation algorithm is advanced to overcome the complexity of the proposed expansion planning problem. Two modification steps were added to the original SFL technique to enable the proposed modified SFL algorithm to extricate from local minima. The two modification phases pledge a fast convergence rate by achieving a rapid adaptive algorithm, besides a better diversification which is the key to extricate from local minima. The efficacy and robustness of the proposed methodology are verified by applying the method to two modified standard test systems. [ABSTRACT FROM AUTHOR]

This study suggests a new algorithm based on a combination of fuzzy logic and genetic algorithm (GA) to improve voltage profile and reduce loss in a microgrid. Considered microgrid includes control variables such as onload tap changer (OLTC), active power output of distributed generators (DG) and reactive power output of feeder switched capacitors that are controlled in a microgrid controller (MGC) through communication links. The proposed method was used to obtain the optimum value of control variables to reduce the loss and improve the voltage profile. The problem formulations consider three distinct objectives related to cost of loss, cost of injected active power by infinity bus and cost of injected active power by DG. The novel formulation is a multi-objective and non-differentiable optimization problem. The control variables were changed base on fuzzy logic and the GA was employed for finding the optimum shape of membership functions. In order to verify the proposed method, a 34 bus microgrid was analyzed in varying load condition and was compared with previous works. Finally it has been tested on 33-buses system to be investigated the control variables status, cost function status and voltage fluctuation during one day. [ABSTRACT FROM AUTHOR]

Objectives: To determine the association between myocardial infarction (AMI) and clinical outcome in patients with primary admissions diagnosis of acute cerebral ischemia (ACI) in the US. Methods: Data from Nationwide Inpatient Sample (NIS) was queried from 2002–2011 for inpatient admissions of patients with a primary diagnosis of ACI with and without AMI using International Classification of Diseases, Ninth Revision, Clinical Modification coding (ICD-9). A multivariate stepwise regression analysis was performed to assess the correlation between identifiable risk factors and clinical outcomes. Results: During 10 years the NIS recorded 886,094 ACI admissions with 17,526 diagnoses of AMI (1.98%). The overall cumulative mortality of cohort was 5.65%. In-hospital mortality was associated with AMI (aOR 3.68; 95% CI 3.49–3.88, p≤0.0001), rTPA administration (aOR 2.39 CI, 2.11–2.71, p<0.0001), older age (aOR 1.03, 95% CI, 1.03–1.03, P<0.0001) and women (aOR 1.06, 95% CI 1.03–1.08, P<0.0001). Overall, mortality risk declined over the course of study; from 20.46% in 2002 to 11.8% in 2011 (OR 0.96, 95% CI 0.95–0.96, P<0.0001). Survival analysis demonstrated divergence between the AMI and non-AMI sub-groups over the course of study (log-rank p<0.0001). Conclusion: Our study demonstrates that although the prevalence of AMI in patients hospitalized with primary diagnosis of ACI is low, it negatively impacts survival. Considering the high clinical burden of AMI on mortality of ACI patients, a high quality monitoring in the event of cardiac events should be maintained in this patient cohort. Whether prompt diagnosis and treatment of associated cardiovascular diseases may improve outcome, deserves further study. [ABSTRACT FROM AUTHOR]

Highlights: [•] In this paper an expert energy management system (EEMS) is presented. [•] A power forecasting module for wind generation capacity is presented. [•] The objective functions that must be minimized are operating cost and net emission. [•] A smart energy storage system (EES) for electrochemical batteries is presented. [•] A new modified Bacterial Foraging Optimization (MBFO) algorithm is presented. [Copyright &y& Elsevier]

Highlights: [•] This paper focused on the expansion planning optimization of energy systems. [•] Employing two form of energy: the expansion of electrical and thermal energies. [•] The main objective is to minimize the costs. [•] A new Modified Honey Bee Mating Optimization (MHBMO) algorithm is applied. [Copyright &y& Elsevier]

In this study, a stochastic multi‐objective framework is proposed for energy expansion planning (EEP). The proposed multiobjective framework can concurrently optimise the competing objective functions including total real energy losses, voltage deviation and the total cost of the installation equipments. Also, regarding the uncertainties of the new complicated energy systems, in this study, for the first time, system uncertainties including load uncertainty are explicitly considered in the EEP problem by the use of the probabilistic load flow technique based on the point estimate method. Since the objectives are different and incommensurable, it is difficult to solve the problem by the conventional approaches that may optimise a single objective. Hence, the metaheuristic algorithm is applied to this problem. Here, the particle swarm optimisation (PSO) algorithm as a new evolutionary optimisation algorithm is utilised. To improve the total ability of the PSO for global search and exploration, a new modification adaptive process is suggested in such a way that the algorithm will search the total search space globally. To evaluate the feasibility and the effectiveness of the proposed algorithm, three modified standard distribution systems are used as the case studies. [ABSTRACT FROM AUTHOR]

Highlights: [•] A new modified teaching–learning based algorithm is proposed. [•] A self-adaptive wavelet mutation strategy is used to enhance the performance. [•] To avoid reaching a large repository size, a fuzzy clustering technique is used. [•] An efficiently smart population selection is utilized. [•] Simulations show the superiority of this algorithm compared with other ones. [Copyright &y& Elsevier]

Highlights: [•] A new approach to the problem of optimal reactive power control variables planning is proposed. [•] The energy loss minimization problem has been formulated by modeling the load of system as a Load Duration Curve. [•] To solving the energy loss problem, the classic methods and the evolutionary methods are used. [•] A new proposed fuzzy teaching–learning based algorithm is applied to energy loss problem. [•] Simulations are done to show the effectiveness and superiority of the proposed algorithm compared with other methods. [Copyright &y& Elsevier]

Abstract: Uncertainty analysis of future system operation is the key feature of current study. This paper shows that how subjective differences in representing fuzzy inputs can affect the final outputs. We consider a confined range of forecasted samples in terms of fuzzy membership functions as well as the range of historical forecasting errors in terms of probability density functions. On this basis, this paper proposes a combined fuzzy/probabilistic evaluation of distribution system voltages, considering hybrid fuzzy/probabilistic uncertainties for consumption and generation. The proposed method allows the sampled fuzzy inputs to incorporate in a Monte Carlo-based nonlinear fuzzy load flow including Wind Turbine Generating Units (WTGUs). As a result of hybrid uncertainty representation, the evaluation of fuzzy load flow results will be assessed in probabilistic framework. Numerical simulations are performed on the unbalanced IEEE 34-bus test distribution system equipped with WTGUs. [Copyright &y& Elsevier]

Abstract: In this paper, an IEMS (intelligent energy management system) is proposed for optimal operation of a CHP-based micro-grid over a 24-hour time interval. The IEMS aims to find the optimal set points of DERs (distributed energy resources) and thermal and electrical storage systems, in such a way that the total operation cost and the net emission are minimized, simultaneously. For optimal operation of the micro-grid, a smart ESS (energy storage system) is introduced which consists of electrical and thermal storage systems. A comprehensive mathematical model for the ESS and also the economic and environmental objective functions are formulated. To solve the problem, we propose an efficient MBFO (modified Bacterial Foraging Optimization) algorithm. An interactive fuzzy satisfying method is also used to simulate the trade-off between conflicting objectives (cost and emission). To validate the performance of the proposed algorithm, we compare the MBFO algorithm with some other previously proposed analytical methods. Finally, the proposed IEMS is applied to a micro-grid which consists of various DERs, CHP (combined heat and power) system, ESS and thermal and electrical loads. The results show that the proposed IEMS can smartly cover the total electrical and thermal load demands with respect to economic and environmental criteria. [Copyright &y& Elsevier]

Abstract: Many large cities have their hybrid transmission and distribution networks, while traditionally, transmission and distribution state estimators are studied and developed separately. In order to achieve a global consistent state estimation solution, the balance transmission and unbalance distribution networks are studied as a whole in this paper. A novel master–slave-splitting (MSS) iterative method is developed for calculating large-scale and mixed state estimation (MSE) problem. In the MSS method, with introducing the boundary fictitious measurement, the MSE problem of large scale is split into a balanced transmission state estimation and many unbalanced distribution state estimation sub-problems of small scale. In order to fit the different features between balanced transmission and unbalanced distribution networks, each sub-problem can be solved with different algorithm. Several case studies are carried out, and the accuracy, convergence, efficiency and reliability of the proposed method are validated. [Copyright &y& Elsevier]

Abstract: Reactive power control, which is one of the important issues of power system studies, has encountered some intrinsic changes because of the presence of the hybrid AC/DC systems. The uncertainty in determination of some ill-defined variables and constraints underlines the application of fuzzy set as an uncertainty analysis tool. Herein a fuzzy objective function and some fuzzy constraints have been modeled for the purpose of reactive power optimization then this fuzzy model is dealt with as a linear programming problem to be solved. Contrary to the separate modeling of the conventional AC/DC optimization methods, this study attempts to attain the most optimal solution by the simultaneous employment of the total contributing factors of both AC and DC parts. In this way, the conventional issue of the coordinated control of firing angle and the transformer tap of the DC terminals is resolved, yet the method provides more flexibility to gain the most optimal condition since it uses more control factor for solving the optimization problem. The proposed method is performed on the modified IEEE 14 and 30-bus systems; and it is shown to have less computational burden and further minimized objective function than the conventional method. [Copyright &y& Elsevier]

In this paper, a new transformerless buck–boost converter is proposed. This converter is based on combining two basic converters, including Cuk and traditional buck–boost converters, along with a voltage multiplier (VM) at the output side. The proposed semi‐quadratic buck–boost converter operates in continuous conduction mode (CCM) and provides two operation modes by turning the switches on and off. This converter has some merits such as a wide conversion ratio and continuous input current. The proposed converter consists of two switches with simultaneous operation resulting in simplicity in control. A modular configuration and a wide range of duty cycles are available through the proposed converter, which causes higher or lower output voltage and facilitates the converter maintenance. The calculations of the ideal and the real voltage gain, voltage stress of switches and diodes, efficiency, and design consideration of elements are given in this paper. Finally, a prototype is implemented, and experimental waveforms are obtained to prove and validate the simulation results as well as the theoretical analysis of the proposed converter. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a fuzzy approach load flow for balanced and unbalanced radial distribution systems with incorporating load model. Fuzzy set theory proposes an appropriate way to model inexactly expressed information and data which have uncertainty. In this paper the combination of fuzzy models and techniques for electrical distribution systems is presented. The theories relating to the fuzzy numbers are simplified into a form suitable for practical application. The utilization of fuzzy approach is demonstrated by a radial load flow method where the voltage in the substation and the power demands are represented by fuzzy numbers. [Copyright &y& Elsevier]

• Operation of integrated energy systems in distribution level is modeled. • Constraints of electrical, natural gas, and heating networks are considered. • The electrical network is modeled as an unbalanced three-phase distribution system. • Optimal energy flow of integrated energy distribution system is formulated. • A new method is applied to solve the load flow of unbalanced electrical network. This paper focuses on the operation optimization of the integrated energy distribution systems, including electrical, natural gas, and district heating distribution systems. According to the unbalanced nature of the electrical distribution networks, a comprehensive model of the unbalanced electrical distribution network is established. A non-iterative three-phase load flow method, based on holomorphic-embedding, is proposed and implemented for solving the load flow of the unbalanced radial distribution electrical network. The energy flow of natural gas and heat networks are modeled and solved by a graph theory-based method. Teaching-learning based optimization algorithm is implemented to solve the optimization problem, considering various constraints of the proposed integrated energy distribution system. The objective is minimizing the total operation cost of energy flow in multi-carrier energy networks. The performance of the proposed method is validated in an integrated energy distribution system, including a 19-bus unbalanced radial electrical network, a typical 20-node natural gas, and a 30-node district heating network. The results verify the effectiveness of the proposed integrated energy system operation and applicability of the proposed optimal energy flow. [ABSTRACT FROM AUTHOR]

The present study is devoted to developing a computational collocation technique for solving the Cauchy singular integral equation of the second kind (CSIE-2). Although, several studies have investigated the numerical approximation solution of CSIEs, the strong singularity and accuracy of the numerical methods are still two important challenges for these integral equations. In this paper, we focus on the smooth transformation and implementation of Bessel basis polynomials (BBP). The reduction of the CSIEs-2 into a system of algebraic equations with the Gauss–Legendre collocation points simplifies this technique. The technique of performing numerical approximation of the solution is well presented and illustrated in the matrix form. Also, the convergence and error bound associated with the scheme are established. Finally, several experiments show the reliability and numerical efficiency of the proposed scheme in comparison with other methods. [ABSTRACT FROM AUTHOR]