Optimization of Residential Load Consumption during Energy Peaks using Smart Metering

Abstract. Recently smart demand side management (DSM) is a very important tool that permits customers to take right decisions for their energy consumption and helps the energy utilities to decrease the over load demand and reshape the load curve. This paper proposes an optimized DSM technique based on smart metering uses different techniques such as load shifting and peak clipping to minimize domestic power consumption especially during load peaks. A new optimization technique (Bat Algorithm) is applied on proposed system and then compares results with other optimization techniques (Genetic Algorithm and Interior point Algorithm) to optimize the minimum consumption during peak hours according to load type. A control algorithm is applied to the proposed system to achieve the load shifting and load clipping according to the optimization results

Relation between microRNAs and Apoptosis in Hepatocellular Carcinoma

AIM: To determine the relation between serum microRNAs and apoptotic markers as regards development of HCC to understand the underlying mechanism of HCV related hepatocarcinogenesis. PATIENTS AND METHODS: A total of 65 serum samples (25 samples from controls, 20 samples from hepatitis and 20 samples from HCC patients) were collected for miRNAs (mir 21, mir 199-a, and mir 155) detection. Human Programmed cell death protein-4 (PDCD-4) and Human Cytochrome-C (CYT-C) were determined. RESULTS: miRNAs 21 and 155 were over expressed in sera of patients with HCC compared to patients with chronic hepatitis (p < 0.0001). While serum means values of miR 199a was significantly decreased among HCC group patients when compared to patients with chronic hepatitis (p < 0.0001). The serum levels of PCDC4 and CYTC were increased in patients with HCC when compared to chronic hepatitis patients. They were also increased in patients with chronic hepatitis when compared to controls (p < 0.05, significant). There was direct correlations between apoptotic markers and oncomirs miRNAs 21 and 155 while apoptotic markers were inversely correlated with miRNA 199-a. CONCLUSION: Both microRNAs and apoptotic markers have roles in HCC pathogenesis. It seems that oncogenic microRNAs induce liver carcinogenesis in HCV patients irrespective of suppression of apoptosis.AIM: To determine the relation between serum microRNAs and apoptotic markers as regards development of HCC to understand the underlying mechanism of HCV related hepatocarcinogenesis. PATIENTS AND METHODS: A total of 65 serum samples (25 samples from controls, 20 samples from hepatitis and 20 samples from HCC patients) were collected for miRNAs (mir 21, mir 199-a, and mir 155) detection. Human Programmed cell death protein-4 (PDCD-4) and Human Cytochrome-C (CYT-C) were determined. RESULTS: miRNAs 21 and 155 were over expressed in sera of patients with HCC compared to patients with chronic hepatitis (p < 0.0001). While serum means values of miR 199a was significantly decreased among HCC group patients when compared to patients with chronic hepatitis (p < 0.0001). The serum levels of PCDC4 and CYTC were increased in patients with HCC when compared to chronic hepatitis patients. They were also increased in patients with chronic hepatitis when compared to controls (p < 0.05, significant). There was direct correlations between apoptotic markers and oncomirs miRNAs 21 and 155 while apoptotic markers were inversely correlated with miRNA 199-a. CONCLUSION: Both microRNAs and apoptotic markers have roles in HCC pathogenesis. It seems that oncogenic microRNAs induce liver carcinogenesis in HCV patients irrespective of suppression of apoptosis

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Integrated Framework of Departure Time Choice, Mode Choice, and Route Assignment for Optimal Design of Time-dependent Transit Pricing Strategies

Modern travel demand management (TDM) strategies, such as time and distance-based congestion pricing, require evidence-based quantitative assessment to measure the potential effects on the transportation network performance and people’s responses to the dynamic consequences of such applications. This thesis focuses on building an integrated framework of departure time choice, mode choice, and dynamic multi-modal route assignment for optimal design of TDM strategies applied to large-scale transportation networks, with the focus on time-based transit pricing. The proposed platform integrates a simulation-based dynamic multi-modal multi-user-class route assignment model with an econometric model that jointly estimates departure time and mode choices and a genetic algorithm engine. The proposed platform has been used in optimizing time-dependent fares as a potential strategy to manage peak-hour transit crowding. Considering the traffic and transit networks as one system, the objective is to minimize travel times during peak periods by influencing travellers to alter their choice of transport mode, departure time, and/or route. The anticipated effect is to pace and spread out demand across space and time to yield the optimal spatio-temporal distribution of demand that minimizes end-to-end travel time. The control variables are the time-dependent transit fares. As a large and realistic use case, a model of the Greater Toronto Area has been developed to demonstrate and validate the results of this research. The main contributions of this research include: (1) developing a simulation-based large-scale dynamic route assignment model that captures the interactions between the traffic and transit sides; (2) integrating the route assignment model with a joint econometric model of departure time and mode choice to build a comprehensive model (the METRO platform) that can be used to assess dynamic TDM strategies; (3) integrating the METRO model with a cloud-based genetic algorithm engine to enable optimizing the design of TDM policies with emphasis on transit fares; and lastly (4) optimizing time-dependent transit fares in Toronto to minimize average weighted door-to-door travel time of all individuals in the system using all driving and transit modes, and quantitatively assessing the impacts of the resulting time-dependent fares as a policy and its strengths and weaknesses in addressing transit crowding.Ph.D