22 research outputs found

    Ethnicity, consanguinity, and genetic architecture of hypertrophic cardiomyopathy

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    AIMS: Hypertrophic cardiomyopathy (HCM) is characterized by phenotypic heterogeneity that is partly explained by the diversity of genetic variants contributing to disease. Accurate interpretation of these variants constitutes a major challenge for diagnosis and implementing precision medicine, especially in understudied populations. The aim is to define the genetic architecture of HCM in North African cohorts with high consanguinity using ancestry-matched cases and controls. METHODS AND RESULTS: Prospective Egyptian patients (n = 514) and controls (n = 400) underwent clinical phenotyping and genetic testing. Rare variants in 13 validated HCM genes were classified according to standard clinical guidelines and compared with a prospective HCM cohort of majority European ancestry (n = 684). A higher prevalence of homozygous variants was observed in Egyptian patients (4.1% vs. 0.1%, P = 2 Ă— 10-7), with variants in the minor HCM genes MYL2, MYL3, and CSRP3 more likely to present in homozygosity than the major genes, suggesting these variants are less penetrant in heterozygosity. Biallelic variants in the recessive HCM gene TRIM63 were detected in 2.1% of patients (five-fold greater than European patients), highlighting the importance of recessive inheritance in consanguineous populations. Finally, rare variants in Egyptian HCM patients were less likely to be classified as (likely) pathogenic compared with Europeans (40.8% vs. 61.6%, P = 1.6 Ă— 10-5) due to the underrepresentation of Middle Eastern populations in current reference resources. This proportion increased to 53.3% after incorporating methods that leverage new ancestry-matched controls presented here. CONCLUSION: Studying consanguineous populations reveals novel insights with relevance to genetic testing and our understanding of the genetic architecture of HCM

    Comparative Study of Load Frequency Controller Designs for Interconnected Power Systems

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    This paper presents a comparative study of three different load frequency (LF) controller designs for interconnected power systems. They are the conventional integral controller, a controller based on the pole-placement technique, and a controller based on optimal control law. Each controller has been designed to improve the dynamic response of system frequency and tie line power flow under a sudden load change. The results obtained using a MATALB computer program show the effectiveness of the LF controller designs. The results also show that the combined optimal controller with conventional integral controller can provide good damping to the system and reduce the overshoot. 

    Marine Predator Algorithm-Based Optimal PI Controllers for LVRT Capability Enhancement of Grid-Connected PV Systems

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    Photovoltaic (PV) systems are becoming essential to our energy landscape as renewable energy sources become more widely integrated into power networks. Preserving grid stability, especially during voltage sags, is one of the significant difficulties confronting the implementation of these technologies. This attribute is referred to as low-voltage ride-through (LVRT). To overcome this issue, adopting a Proportional-Integral (PI) controller, a control system standard, is proving to be an efficient solution. This paper provides a unique algorithm-based approach of the Marine Predator Algorithm (MPA) for optimized tuning of the used PI controller, mainly focusing on inverter control, to improve the LVRT of the grid, leading to improvements in the overshoot, undershoot, settling time, and steady-state response of the system. The fitness function is optimized using the MPA to determine the settings of the PI controller. This process helps to optimally design the controllers optimally, thus improving the inverter control and performance and enhancing the system’s LVRT capability. The methodology is tested in case of a 3L-G fault. To test its validity, the proposed approach is compared with rival standard optimization-based PI controllers, namely Grey Wolf Optimization and Particle Swarm Optimization. The comparison shows that the used algorithm provides better results with a higher convergence rate with overshoot ranging from 14% to 40% less in the case of DC-Link Voltage and active power and also settling times in the case of MPA being less than PSO and GWO by 0.76 to 0.95 s

    P17.34 * CONCURRENT CHEMORADIOTHERAPY IN GLIOBLASTOMA MULTIFORME: RETROSPECTIVE STUDY

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    This Article highlights that individuals who suffer from mental health problems can be particularly defenseless against an attack on their liberty through criminal and civil law. Specifically, it delineates how the current laws allow for a potential indefinite commitment of a person who may not have even committed a single crime. The Article explains that constitutionally mandated standards should be required to protect individuals who face losing their liberty due to the perceived threat of future harm. The authors posit that, while preventing individuals from harming themselves or others is an honorable goal, the state should only be able to intervene when the threat is truly imminent. Further, the Article argues that the ability to commit individuals with fewer protections than those offered under criminal law and use a lower burden of proof without a jury, is a powerful weapon of oppression that no government should wield. This Article concludes that leaving these decisions in the hands of largely unsupervised state agents, who rarely face appeal, is an injustice to the afflicted, and this essentially unrestrained power must change

    Voltage stability evaluation of real power transmission system using singular value decomposition technique

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    Voltage stability is an important factor that needs to be taken into consideration during the planning and operation of power systems in order to avoid voltage collapse and subsequently partial or full system blackout. This paper presents singular value decomposition (SVD) technique to assess voltage stability of Qatar power transmission system. A MATLAB program has been developed for SVD technique. The voltage stability of the system has been analyzed during the peak load condition of summer 2007. The SVD results obtained by the developed MATLAB programs confirm that the Qatar power transmission system is "voltage stable". The critical load buses that could lead the system to voltage instability have been identified and the computer results have shown that there are critical load buses in the system. These critical load buses are located in an industrial area feeding from Qatar power system. The results of the critical load buses obtained by SVD have been verified by Q-V sensitivity

    Estimation of Parameters of Triple Diode Photovoltaic Models Using Hybrid Particle Swarm and Grey Wolf Optimization

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    The quality of the photovoltaic (PV) cell model impacts many simulation studies for PV systems, such as maximum power point tracking and other assessments. Moreover, due to limited information found in the datasheets of the PV cells, several parameters of the model are unavailable. Thus, this paper introduces a novel approach using a hybrid Particle Swarm and Grey Wolf Optimization algorithm to figure out these parameters under different environmental conditions. The proposed algorithm is used with two types of PV cells–Kyocera KC200GT and Canadian solar cell CS6K-280M–and can be used with any commercial type of PV module needing only parameters in the datasheet. The absolute error of the model’s simulation results is compared to the actual results collected from sites in Egypt, in an attempt to investigate the effectiveness of the suggested approach

    Estimation of Parameters of Triple Diode Photovoltaic Models Using Hybrid Particle Swarm and Grey Wolf Optimization

    No full text
    The quality of the photovoltaic (PV) cell model impacts many simulation studies for PV systems, such as maximum power point tracking and other assessments. Moreover, due to limited information found in the datasheets of the PV cells, several parameters of the model are unavailable. Thus, this paper introduces a novel approach using a hybrid Particle Swarm and Grey Wolf Optimization algorithm to figure out these parameters under different environmental conditions. The proposed algorithm is used with two types of PV cells–Kyocera KC200GT and Canadian solar cell CS6K-280M–and can be used with any commercial type of PV module needing only parameters in the datasheet. The absolute error of the model’s simulation results is compared to the actual results collected from sites in Egypt, in an attempt to investigate the effectiveness of the suggested approach
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