Generalized Energy Storage Model-in-the-Loop Suitable for Energy Star and CTA-2045 Control Types

The paper proposes a generalized energy storage (GES) model for battery energy storage systems (BESS), electric water heaters (EWH) and heating, ventilation, and air-conditioning (HVAC) systems. The analogies, including state of charge versus water temperature differential, are identified and explained, and models-in-the-loop (MIL) are introduced, which are compatible with the Energy Star and CTA-2045 general specifications and command types. Emphasis is placed on the proposed EWH model as it needfully fulfills a gap in present literature. The corresponding MIL has been implemented in the DER integration testbed, which was originally developed by EPRI, and satisfactorily validated against experimental results. A case study is included to illustrate that the daily “energy content” and “energy take” for BESS and EWH with mixing valve technology are comparable for typical residential ratings. The BESS, which requires more initial investment, has advantages in terms of flexibility for contributing to grid services, which are illustrated through a combined simulation and experimental study based on data collected from a field demonstration site with four smart homes

Large-Scale Modeling and DR Control of Electric Water Heaters With Energy Star and CTA-2045 Control Types in Distribution Power Systems

The paper proposes a generalized energy storage (GES) model for battery energy storage systems (BESS), electric water heaters (EWH) and heating, ventilation, and air-conditioning (HVAC) systems to enable demand response control complying to Energy Star and CTA-2045 standards. The demand response control has been implemented in the DER integration testbed, which was originally developed by EPRI, to demonstrate that the “energy content” and “energy take” for BESS and EWH with mixing valve technology are comparable for typical residential ratings. A distribution power system was modeled using the modified IEEE 123-bus feeder system, measured residential loads, and EWH power simulated based on realistic hot water draws from CBECC-Res software. The demand response control, which complies to CTA-2045 standards was implemented to the EWHs considering the energy take values. Results demonstrate that the EWHs can be controlled to postpone the peak power at the distribution system level and provide a large amount of energy storage, while maintaining system robustness. The impact on occupant comfort was also analyzed

Smart Fraud Detection in Smart Metering System of AMI Networks

Advanced metering infrastructure (AMI) is a critical part of modern smart grids. It performs the delivery of sensitive power information such as smart metering data of power consumption. While smart meter data helps to improve the overall performance of the grid in terms of efficient energy management, it has also made the AMI an attractive target of cyberattackers with a goal of stealing energy. This is performed through the physical or cyber tampering of the meters, as well as by manipulating the network infrastructure to alter collected data. Proper technology is required for the identification of energy fraud. We propose a Machine Learning based technique to detect fraudulent data from smart meters based on energy consumption patterns of the consumers by utilizing both supervised and unsupervised techniques. We analyze the performance of our proposed technique and show the correctness of the models in identifying the suspicious smart meter data

Remarks on the second neighborhood problem

Myostatin (MSTN) gene plays a key role in skletal muscle homeostasis such as inducing muscle athrophy, poliferation of myoblast, increasing ubiquitin-proteasomal, downregulating IGF pathway, and glucolysis. Myostatin gene expression is controled by CpG island located in promoter region. The objectives of this research were to identify polymorphism of MSTN promoter gene and to associate the polymorphism of SNP with growth and muscling traits in Bali cattle. A total of 48 Bali cattle from BPTU-HMT Bali island was screened to identify genetic polymorphisms in MSTN promoter region using sequencing method. The growth and muscling traits were measured at 12 months of age. The muscling traits were evaluated using ultrasound console with linear transducer having frequency 6.5 Hz and scaning we conducted at 130 mm in deep. Analysis of polymorphism was conducted by using PopGen 1.32 software. The association of MSTN with growth and muscling traits were analyzed by using General Linear Model (GLM) procedure. This result showed that a total of 20 polymorphic SNPs (seven SNPs in CpG island) were detected in this region. Although, only 3 SNPs (g.-8078C>T, g.-7996G>C, and g.-7930A>G) had equilibrium condition in Hardy-Weinberg analysis. The association result showed that 2 SNPs (g.-7799T>C and g.-7941C>T) were significantly associated with intramuscular fat percentage (P≤0.05) in Bali cattle. Although the 2 SNPs were nominally significant at nominal P≤0.05 threshold, they were not significant after Bonferroni correction for multiple testing. It could be concluded that MSTN promoter gene was polymorphic in Bali cattle and there were 2 SNPs associated with carcass quality

*WINNER* Safety Analysis for UAV Networks

The recent trend of collaborative operations of a network of Unmanned Aerial Vehicles (UAVs) to achieve a common objective has attracted the researchers, as well as commercial vendors. It has revolutionized the means of data collection to maximize mission performances. However, the collaborative UAVs need to be safe from cyberattacks to prevent catastrophe. They need to be able to collaborate with each other to avoid potential failure of a mission. As these smart devices are always targets of adversaries, they need to maintain safe communication with each other while avoiding fuel outage and mid-air collisions, as well as reducing the possibilities of being hacked. In this work, we present the idea of a formal verification tool that takes different UAV parameters, safety requirements, and resource constraints as input and verifies the network's safety

Detecting Malicious Blockchain Transactions Utilizing Anomaly Detection Techniques

"One of the largest emergences in modern technologyis the use of cryptocurrencies, which are recorded transactions in a structure called Blockchain. Of these currencies, one of the largest is called Ethereum, which is a framework built to handle the use of smart contracts, or programs that are run on the Blockchain. Since this is a newer idea, there are many security flaws that come along with the adoption of it. While most of the transactions on the Blockchain can be recorded as legitimate, some are malicious, such as those in the recent DAO attack. In this paper, we want to use anomaly detection to help detect these malicious transactions. We use sites such as etherscan.io, which records all of the transactions on the Ethereum framework, to scrape the necessary data to establish a baseline of what a legitimate transaction should look like. Our goal is to conduct research to find malicious transactions and utilize clustering technology to help us detect when these malicious transactions are taking place.

RNA deep sequencing reveals novel transcripts and pathways involved in the unsaturated fatty acid metabolism in chicken

Fatty acids in chicken meat especially the unsaturated fatty acids (UFA) contribute in the nutritional value, meat quality, and human health. A deeper knowledge in the genomics of fatty acids (FA) is important as it identifies effective markers to be used in marker-assisted breeding in chickens for higher UFA leading to the economic benefits in chicken production industry. Therefore, this study aimed to investigate trancriptome profilling in the liver tissues collected from chicken with divergent UFA contents in the breast muscle tissues using RNA deep-sequencing. Liver tissues from chicken with higher (n = 3) and lower (n = 3) UFA were analysed using Illumina HiSeq 2500. The total number of reads produced for each liver sample ranged from 24.30 to 29.97 million. Approximately 367 genes were differentially regulated with the significance level of p-adjusted value 1.5) in higher UFA group. Differentially regulated genes in high UFA liver samples were enriched in metabolic processes such as heme binding, sodium channel activity, and iron ion binding. Pathway analysis identified the metabolic pathways, ECM receptor interaction, focal adhesion, peroxisome, Wnt signaling and TGF-Beta signaling pathways which may play important roles in UFA metabolism. Differential gene expression analysis identified candidate genes in the ATP synthesis, apovitellenin, cytochrome P450, hydroxysteroid, solute carrier and stearoyl-CoA desaturase family. These differentially expressed genes and pathways may lead to UFA variation and could be used as genetic marker for UFA traits in chickens. However, further validation is required to confirm the effect of these genes in the UFA-related molecules metabolism in other chicken populations

Antibodies and Antibody Fragments Are Therapeutic Tools in the Treatment of Type-II Diabetes Mellitus

Antibody fragments (FABs) are proteins that form part of the antigen recognition site. FABs are produced in genetically modified bacteriophages, bacteria, fungi, or plants and, consequently, can be produced in large quantities at a fraction of the cost of traditional antibodies. Antibody fragments are small and simple structure that today is highly regarded because of the many advantages they have over the use of whole antibodies. Single-domain antibodies are the smallest antigen-binding units of antibodies, consisting either only of one variable domain or one engineered constant domain that solely facilitates target binding. Fibroblast growth factor 21 (FGF21) is a promising drug candidate for the treatment of type 2 diabetes. Clinical use of recombinant fibroblast growth factor 21 (FGF21) for the treatment of type 2 diabetes and other disorders linked to obesity has been proposed; however, its clinical development has been challenging owing to its poor pharmacokinetics