The introduction of advanced technologies has led to an unprecedented rise in automated appliances in the housing sector. Building new administrative structures to satisfy electrical needs has grown ...more crucial to ensure the safety of residential devices. One of the approaches to achieve this is Demand Side Management (DSM), a key component of both micro-grid and Smart Grid technology. DSM can be accomplished by carefully controlling requirements while upholding the trust of clients. Most of the DS Management which has been covered in the research is aimed at helping households manage their power plan. The innovative HBA+DMO technique inherits Honey Badger Optimization (HBA) and Dwarf Mongoose Optimization (DMO) for executing the DSM program. The groundwork for the proposed framework implemented in this investigation is provided by the Critical-Peak-Price (CPP) and Real-Time-Price (RTP) payment processes. Two operational instances (60 min and 12 min) are being taken into consideration to evaluate client requirements and behavior over the suggested strategy. In accordance with the results from simulations, the suggested strategy arranges the devices in the best possible way, leading to fewer energy expenses while maintaining user comfort (UC). Customers sometimes pay a premium as a result of gadget waiting periods in order to gain the most comfort. As equipment is turned on in response to user comfort, the amount of time spent waiting during an unscheduled situation is close to zero. Tools for lowering energy expenditures and consumption for buildings, communities, or enterprises are frequently provided through energy management software. The three main uses of the energy data that EMS collects are reporting, monitoring, and engagement. The computational time of the proposed approach is (∼213.42). Future testing involving different conditions and control methods for study into HRES microgrid infrastructure may be done on the medium of the experiment bench.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Patients with COVID-19 were recruited from more than 70 institutes in Japan.•Japan experienced 3 waves of COVID-19 during the first year of the pandemic.•The case fatality rate of 3.2% was ...relatively low.•The data will be used for a genome-wide association study.
The coronavirus disease (COVID-19) pandemic is having a devastating effect worldwide. Host genome differences between populations may influence the severity of COVID-19.
The Japan COVID-19 Task Force is conducting host genome analysis of hospitalized patients with COVID-19 from more than 70 institutions nationwide in Japan. This report describes the clinical characteristics of patients enrolled to date.
The median (interquartile range) age of the 1674 patients included in the analysis was 59 (45–71) years, and more than half of the patients (66.2%) were male. Less than half of the patients (41.2%) had severe disease. The case fatality rate was 3.2%.
Since this is a hospital-based study, the number of severe cases was relatively high, but the case fatality rate was relatively low, when compared to that of other countries. In the future, we will continue to enroll patients and conduct genome analyses of patients with COVID-19.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Dear Editor, Allergic bronchopulmonary aspergillosis (ABPA) is an immunological pulmonary disorder caused by hypersensitivity to Aspergillus fumigatus. Patients with asthma who present with ABPA ...typically report symptoms such as chronic mucus hypersecretion, and previous research has indicated that ABPA is a risk factor for accelerated loss of lung function. However, the pathogenesis of ABPA is not fully understood. In the present report, we discuss a case of ABPA occurring after eosinophilic pneumonia (CEP).
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The main aim of this paper is to design a local controller for DC/DC converter in a battery energy storage system (BESS) and a controller based on a virtual synchronous generator (VSG) for ...photovoltaic (PV) converter connected to AC grid. In the DC/DC converter design, the state feedback method is used so that the voltage and current control loops are combined, leading to higher flexibility and improved damping. This flexibility, which maintains the state of charge (SOC) of BESS, is supported by the design of virtual resistance and virtual capacitor statically and dynamically. In this design method, the BESS can be independently connected to each DC bus node and detect disturbances through local measurements. In addition, the improved Pre-Parallelism (PREP) method has been used to improve the transient performance caused by the disconnection and connection of additional loads, the existence of faults, and the inherent inertia difference in parallel operation between VSG and synchronous generator (SG). In this method, the problem of phase jump caused by transient disturbances is solved by considering a cosine function in VSG design. Also, to solve the problem of inertia difference between the units, a small signal model has been presented, in which, by considering the capacity ratio of the units on the AC side, the necessary inertia for VSG can be included in the design. The proposed method is simulated by considering different scenarios in MATLAB software, so the results demonstrate the superiority of the proposed controller compared to other existing methods.
The urgent need to reduce greenhouse gas emissions to achieve a decarbonized society has led to the active introduction of electric vehicles worldwide. Renewable energy sources that do not emit ...greenhouse gases during charging must also be used. However, the uncertainty in the supply of renewable energy is an issue that needs to be considered in practical applications. Therefore, in this study, we predicted the amount of electricity generated by renewable energy using model predictive control, and we considered the operation of a complete island-operated park and ride EV parking station that does not depend on commercial electricity. To perform appropriate model predictive control, we performed comparative simulations for several different forecast interval cases. Based on the obtained results, we determined the forecast horizon and we simulated the economic impact of implementing EV demand response on the electricity demand side. We found that without demand response, large amounts of electricity are recharged and a very high return on investment can be achieved, but with demand response, the return on investment is faster. The results provide a rationale for encouraging infrastructure development in areas that have not yet adopted electric vehicles.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The clinical course of coronavirus disease (COVID-19) is diverse, and the usefulness of phenotyping in predicting the severity or prognosis of the disease has been demonstrated overseas. This study ...aimed to investigate clinically meaningful phenotypes in Japanese COVID-19 patients using cluster analysis. From April 2020 to May 2021, data from inpatients aged greater than or equal to 18 years diagnosed with COVID-19 and who agreed to participate in the study were collected. A total of 1322 Japanese patients were included. Hierarchical cluster analysis was performed using variables reported to be associated with COVID-19 severity or prognosis, namely, age, sex, obesity, smoking history, hypertension, diabetes mellitus, malignancy, chronic obstructive pulmonary disease, hyperuricemia, cardiovascular disease, chronic liver disease, and chronic kidney disease. We have successfully performed the first phenotyping of COVID-19 patients in Japan, which is clinically useful in predicting important outcomes, despite the simplicity of the cluster analysis method that does not use complex variables.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Electrical microgrids (EMGs) are positioned to play an important role in the future distribution grid as technology advances and distributed energy resources (DERs) emerge. In the event of major ...natural disasters, the functioning capabilities of active distribution systems (DS) face ongoing problems. To assess the resilience of a distribution system, a thorough methodology must be established. This study proposes a methodology that demonstrates how the use of EMGs and DERs, in conjunction with line hardening, can improve resilience in extreme operating situations. The framework examines four separate scenarios, each with its own set of restoration procedures and critical loads. A combination of battery electric vehicles (BEVs), solar photovoltaic distributed generation (SPV-DG), battery energy storage systems (BESS), and distribution static compensators (DSTATCOMs) is being integrated into practical Indian distribution systems consisting of 28 and 52 buses to improve resilience. The goal is to improve the newly specified resilience indices and restore all of the loads that have been affected by the faults. The bald eagle search algorithm (BESA) is used to identify the appropriate allocation of SPV-DG and solve the objective function within the system. The results of our tests show that our proposed technique has the capacity to enhancement the resilience and successfully restore all damaged loads in a distribution system.
Abstract
Background
Computed tomography (CT) imaging and artificial intelligence (AI)-based analyses have aided in the diagnosis and prediction of the severity of COVID-19. However, the potential of ...AI-based CT quantification of pneumonia in assessing patients with COVID-19 has not yet been fully explored. This study aimed to investigate the potential of AI-based CT quantification of COVID-19 pneumonia to predict the critical outcomes and clinical characteristics of patients with residual lung lesions.
Methods
This retrospective cohort study included 1,200 hospitalized patients with COVID-19 from four hospitals. The incidence of critical outcomes (requiring the support of high-flow oxygen or invasive mechanical ventilation or death) and complications during hospitalization (bacterial infection, renal failure, heart failure, thromboembolism, and liver dysfunction) was compared between the groups of pneumonia with high/low-percentage lung lesions, based on AI-based CT quantification. Additionally, 198 patients underwent CT scans 3 months after admission to analyze prognostic factors for residual lung lesions.
Results
The pneumonia group with a high percentage of lung lesions (N = 400) had a higher incidence of critical outcomes and complications during hospitalization than the low percentage group (N = 800). Multivariable analysis demonstrated that AI-based CT quantification of pneumonia was independently associated with critical outcomes (adjusted odds ratio aOR 10.5, 95% confidence interval CI 5.59–19.7), as well as with oxygen requirement (aOR 6.35, 95% CI 4.60–8.76), IMV requirement (aOR 7.73, 95% CI 2.52–23.7), and mortality rate (aOR 6.46, 95% CI 1.87–22.3). Among patients with follow-up CT scans (N = 198), the multivariable analysis revealed that the pneumonia group with a high percentage of lung lesions on admission (aOR 4.74, 95% CI 2.36–9.52), older age (aOR 2.53, 95% CI 1.16–5.51), female sex (aOR 2.41, 95% CI 1.13–5.11), and medical history of hypertension (aOR 2.22, 95% CI 1.09–4.50) independently predicted persistent residual lung lesions.
Conclusions
AI-based CT quantification of pneumonia provides valuable information beyond qualitative evaluation by physicians, enabling the prediction of critical outcomes and residual lung lesions in patients with COVID-19.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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