Capacity withholding assessment of power systems considering coordinated strategies of virtual power plants and generation companies

This paper presents a multi-level optimization framework for power system operators' joint electricity markets capacity-withholding assessment. The main contribution of this research is that three capacity-withholding indices are introduced for day-ahead, intra-day, and real-time scheduling of the system that detect the capacity withholding and arbitrage opportunities of Virtual Power Plants (VPPs) and non-utility fossil-fueled GENeration COmpanies (GENCOs) in an ex-ante procedure. A three-level optimization process is used so that the system operator can estimate the coordinated bidding of VPPs/GENCOs in different energy and ancillary services markets to prevent the formation of withholding groups. The first level problem consists of two stages. The first stage estimates the optimal capacity withholding and arbitrage bidding strategy of VPPs/GENCOs, and the second stage determines the optimal system scheduling for the day-ahead horizon. A full competition algorithm is also carried out to evaluate the competition states of VPPs/GENCOs. The second and third level problems consist of two optimization stages for the intra-day and real-time optimization horizons. At the first stage of each level, the process estimates the coordinated bidding of VPPs/GENCOs, and at the second stage of each level, the system resources are optimally dispatched. The proposed method is applied to 30-bus and 118-bus IEEE test systems. The proposed algorithm reduced the maximum locational marginal prices of 30-bus and 118-bus test systems by about 57.04% and 44.73% compared to the normal and the worst-case contingency operating conditions, respectively. Furthermore, the proposed method reduced the average values of day-ahead, intra-day and real-time dynamic capacity withholding indices of the 118-bus test system by about 32.92%, 40.1%, and 46.85%, respectively.© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

A Dynamic Collusion Analysis Framework Considering Generation and Transmission Systems Maintenance Constraints

Capacity withholding of generation companies is an important issue in market monitoring procedures. The capacity withholding can be intensified in the transmission and generation constrained system. The strategic maintenance of market participants can impose multiple constraints on the system and changes the wholesale electricity market prices. The strategic maintenance of transmission and generation facilities is known as dynamic capacity withholding (DCW) and all of the market-monitoring units need algorithms to detect and reduce DCW. In this paper, a new dynamic capacity withholding index is presented. The method is analyzed on the IEEE 30, 57-bus test system. The numerical results show the effectiveness of the proposed index.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Comparison of the Antibacterial Effect of 810 nm Diode Laser and Photodynamic Therapy in Reducing the Microbial Flora of Root Canal in Endodontic Retreatment in Patients With Periradicular Lesions

Introduction: The aim of this study was to compare the antibacterial efficacy of diode laser 810nm and photodynamic therapy (PDT) in reducing bacterial microflora in endodontic retreatment of teeth with periradicular lesion.Methods: In this in vivo clinical trial, 20 patients who needed endodontic retreatment were selected. After conventional chemo mechanical preparation of root canals, microbiological samples were taken with sterile paper point (PP), held in thioglycollate broth, and then were transferred to the microbiological lab. In the first group, PDT with methylene blue (MB) and diode laser (810 nm, 0.2 W, 40 seconds) was performed and in the second group diode laser (810 nm, 1.2 W, 30 seconds) was irradiated. Then second samples were taken from all canals.Results: CFU/ml amounts showed statistically significant reduction in both groups (P < 0.001). CFU/ml amounts were compared between the two groups and there was no statistical difference.Conclusion: PDT and diode laser 810 nm irradiation are effective methods for root canal disinfection. PDT is a suitable alternative for diode laser 810 nm irradiation, because of lower thermal risk on root dentin

Comparison of the performances of GEP, ANFIS, and SVM artifical intelligence models in rainfall simulaton

In this paper, evaluation the performances of GEP (gene expression programming), ANFIS ( adaptive fuzzy interference system), and SVM (support vector machine) artificial intelligence models in two scales of daily and monthly rainfall data from Urmia meteorological station (Iran) and monthly rainfall data from Diata meteorological station (India) was used in rainfall simulation. The correlation coefficient of observed and simulated values was evaluated by the R2 criterion, simulation error was evaluated by the root mean square error (RMSE), and MB criteria and model efficiency were evaluated by the Nash-Sutcliffe method. The results show that the correlation coefficients in the GEP model based on daily data from Urmia station and monthly data from Diata station are 23 and 58%, respectively, and R2 in simulation with GEP is estimated to be 55% lower than with the other two models. The R2 range in both ANFIS and SVM models varies from 91 to 93%. On average, the RMSE values in the GEP simulation are 50% and 55% higher than the ANFIS ratio for daily and monthly data at the two stations, respectively, and the RMSE values of ANFIS model are 1% and 3% higher than those of the SVM at Urmia and Diata stations, respectively. The bias values of the GEP model are 72% and 60% higher than those of ANFIS at Urmia and Diata stations, respectively. The GEP efficiency factors are 56% and 61% lower than those of ANFIS at Urmia and Diata stations, respectively. And the ANFIS efficiency ratio is 1 and 2% lower than SVM in Urmia and Diata stations, respectively. Therefore, rainfall simulation with the SVM model is associated with a lower error rate and better efficiency, the ANFIS model is close to the efficiency of SVM, and the GEP model is not suitable for rainfall simulation

Investigation of metabonomics technique by analyze of NMR data, which method is better? Mean center or auto scale?

The factors such as disease can disrupt homeostasis, resulting in perturbations of endogenous biochemicals that are involved in key metabolic profiles. Metabonomics is useful technique to quantitative description of endogenous metabolites present in a biological sample such as urine, plasma and tissue. High resolution 1H nuclear magnetic resonance (NMR)-based metabonomics is a technique used to analyze and interpret multivariate metabolic data that correlate with changes of physiological conditions. Before any explanation for metabolite data, preprocessing the spectroscopic data is essential. In this paper, we show scaling effects in metabonomics investigation of patients diagnosed with Crohn's and Celiac disease. two techniques of scaling were applied as follows: mean centering and auto scaling. Results reveal that the mean centering is more useful to segregate patients from healthy subjects in the data set of Crohn's and Celiac disease

Potential of Acid-Activated Bentonite and SO3H-Functionalized MWCNTs for Biodiesel Production From Residual Olive Oil Under Biorefinery Scheme

Application of acid-activated bentonite and SO3H-functionlized multiwall carbon nanotubes (SO3H-MWCNTs) for lowering free fatty acids (FFAs) content of low-quality residual olive oil, prior to alkali-catalyzed transesterification was investigated. The used bentonite was first characterized by Scanning Electron Microscopy (SEM), Inductively Coupled Plasma mass spectrometry (ICP-MS), and X-ray fluorescence (XRF), and was subsequently activated by different concentrations of H2SO4 (3, 5, and 10 N). Specific surface area of the original bentonite was measured by Brunauer, Emmett, and Teller (BET) method at 45 m2/g and was best improved after 5 N-acid activation (95–98°C, 2 h) reaching 68 m2/g. MWCNTs was synthesized through methane decomposition (Co-Mo/MgO catalyst, 900°C) during the chemical vapor deposition (CVD) process. After two acid-purification (HCl, HNO3) and two deionized-water-neutralization steps, SO3H was grafted on MWCNTs (concentrated H2SO4, 110°C for 3 h) and again neutralized with deionized water and then dried. The synthesized SO3H-MWCNTs were analyzed using Fourier-Transform Infrared Spectroscopy (FTIR) and Transmission Electron Microscopy (TEM). The activated bentonite and SO3H-MWCNTs were utilized (5 wt.% and 3 wt.%, respectively), as solid catalysts in esterification reaction (62°C, 450 rpm; 15:1 and 12:1 methanol-to-oil molar ratio, 27 h and 8 h, respectively), to convert FFAs to their corresponding methyl esters. The results obtained revealed an FFA to methyl ester conversion of about 67% for the activated bentonite and 65% for the SO3H-MWCNTs. More specifically, the acid value of the residual olive oil was decreased significantly from 2.5 to 0.85 and 0.89 mg KOH/g using activated bentonite and SO3H-MWCNTs, respectively. The total FFAs in the residual olive oil after esterification was below 0.5%, which was appropriate for efficient alkaline-transesterification reaction. Both catalysts can effectively pretreat low-quality oil feedstock for sustainable biodiesel production under a biorefinery scheme. Overall, the acid-activate bentonite was found more convenient, cost-effective, and environment-friendly than the SO3H-MWCNTs

Experimental investigation of low-level water in waste-oil produced biodiesel-diesel fuel blend

Diminishing fuel resources and stringent emission mandates have demanded cleaner combustion and increased fuel efficiency. Three water addition rates, i.e., 2, 4, and 6 wt% in biodiesel-diesel blend (B5) was investigated herein. Combustion characteristics of the emulsified fuel blends were compared in a naturally-aspirated diesel engine at full load and different engine speeds. More specifically, biodiesel was produced from waste cooking oil (WCO) and to further increase waste utilization, recycled biodiesel wastewater was used as additive in B5. The result obtained showed that low-level water addition (i.e., 2 and 4 wt%) in B5 led to different results from those obtained using higher water addition rates (i.e., >5 wt%) reported by the previous studies. In more details, the findings of the present study revealed that low level water addition in B5 could considerably reduce CO, HC, CO2, and NOx emissions. Among water-containing B5 fuel emulsions, the optimal water addition level in terms of engine performance parameters and emissions was found at 4 wt%. In particular, the emitted CO2, HC, and NOx were decreased by over 8.5%, 28%, and 24%, respectively, at maximum speed of 2500 rpm

International longitudinal registry of patients with atrial fibrillation and treated with rivaroxaban: RIVaroxaban Evaluation in Real life setting (RIVER)

Background Real-world data on non-vitamin K oral anticoagulants (NOACs) are essential in determining whether evidence from randomised controlled clinical trials translate into meaningful clinical benefits for patients in everyday practice. RIVER (RIVaroxaban Evaluation in Real life setting) is an ongoing international, prospective registry of patients with newly diagnosed non-valvular atrial fibrillation (NVAF) and at least one investigator-determined risk factor for stroke who received rivaroxaban as an initial treatment for the prevention of thromboembolic stroke. The aim of this paper is to describe the design of the RIVER registry and baseline characteristics of patients with newly diagnosed NVAF who received rivaroxaban as an initial treatment. Methods and results Between January 2014 and June 2017, RIVER investigators recruited 5072 patients at 309 centres in 17 countries. The aim was to enroll consecutive patients at sites where rivaroxaban was already routinely prescribed for stroke prevention. Each patient is being followed up prospectively for a minimum of 2-years. The registry will capture data on the rate and nature of all thromboembolic events (stroke / systemic embolism), bleeding complications, all-cause mortality and other major cardiovascular events as they occur. Data quality is assured through a combination of remote electronic monitoring and onsite monitoring (including source data verification in 10% of cases). Patients were mostly enrolled by cardiologists (n = 3776, 74.6%), by internal medicine specialists 14.2% (n = 718) and by primary care/general practice physicians 8.2% (n = 417). The mean (SD) age of the population was 69.5 (11.0) years, 44.3% were women. Mean (SD) CHADS2 score was 1.9 (1.2) and CHA2DS2-VASc scores was 3.2 (1.6). Almost all patients (98.5%) were prescribed with once daily dose of rivaroxaban, most commonly 20 mg (76.5%) and 15 mg (20.0%) as their initial treatment; 17.9% of patients received concomitant antiplatelet therapy. Most patients enrolled in RIVER met the recommended threshold for AC therapy (86.6% for 2012 ESC Guidelines, and 79.8% of patients according to 2016 ESC Guidelines). Conclusions The RIVER prospective registry will expand our knowledge of how rivaroxaban is prescribed in everyday practice and whether evidence from clinical trials can be translated to the broader cross-section of patients in the real world

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe