Detection and Operation of Unintentional Islands in the Presence of Distributed Generation Units

The complexities and challenges for reliable operation of power system have increased due to various types of Distributed Generators (DG) in the Distribution Network (DN) to supply the increasing load demand. It necessitates a comprehensive approach in planning the system towards effective and reliable operation of the system. During the operation of the system, detection of unintentional islanding is critical as non-detection of islanding event could lead to cascaded failure of the system due to active or reactive power imbalance leading to frequency, angle or voltage instability. If undetected, the instability in the islanded part can cascade into the stable part of the system resulting in complete failure of the system. A robust Modified Islanding Detection Technique (MIDT) has been proposed for identifying the islanding event early and accurately in the distribution networks with DGs installed for multiple objectives and is compared with existing passive Islanding Detection Techniques (IDT). A rank-based load shedding scheme is proposed for stable and reliable operation of the identified island, which sheds only the most vulnerable loads in the island for regaining the frequency and voltage stabilities. The proposed MIDT and rank based load shedding schemes were tested on 11kV IEEE 118 Bus Test system

ARTIFICIAL NEURAL NETWORKS AND ADAPTIVE NEURO FUZZY INFERENCE SYSTEM FOR WHEAT YIELD ANALYSIS AND PREDICTION

The current study evaluated the prediction of the yield of wheat crops in the Bagalkot district of Karnataka State, India. The study aimed to provide crop yield predictions to help farmers optimize their cultivation and marketing strategies. The model used various independent variables, such as temperature, humidity of air, and water resources, to predict growth in the yield of wheat crops. The correlation analysis helps determine the strength and direction of the relationship between the variables based on the results. The statistical analysis identifies the variables that have a significant impact on crop yield growth. The work developed and tested two different models (the Artificial Neural Network (ANN) model and the Adaptive Neuro-fuzzy Interference System (ANFIS) to predict crop yield growth based on the selected independent variables. The ANFIS model was particularly interesting as it can predict a mapping between the input and output parameters, which can be useful for understanding the relationships between different variables. ANFIS was considered a better predictor than ANN as the error percentage ranged from 0-3%. Overall, the work highlighted the importance of crop yield predictions and the potential benefits that simulations can generate for farmers and the agriculture sector in general

A comparative study of the fracture union between long and short proximal femoral intramedullary nails antirotation in the treatment of intertrochanteric femur fractures in the elderly: a multicentric analysis

Background: The objective of the study was to compare the fracture union of long vs. short proximal femoral intramedullary nail antirotation (PFNA) in the treatment of intertrochanteric fractures in elderly patients who was more than 60 years old.Methods: A retrospective analysis of 170 cases of intertrochanteric fractures of the femur (AO type A1 and A2) in the elderly was conducted. There were 64 males (37.6%) and 106 females (62.3%) with the age of 60–90 (mean age 75) years. The general demographic data of patients, operation time, intraoperative blood loss, length of hospital stay, blood transfusion rate, anterior thigh pain, postoperative complications like periprosthetic fractures, infections were recorded.Results: The short nail group also had a significantly shorter operation time (41.5±15.3 minutes vs. 62.5±25.3 minutes, p=0.002) and lower rate of postoperative transfusion (31.3% vs. 58.7%, p=0.041). However the length of hospital stay showed no significant differences. After surgery in short group there were 03 cases of periprosthetic fracture with a total incidence of 03%, however there were none in long nail group. At the end of the follow-up, all patients achieved bony union. The average fracture union time of the long nail group was (8.5±3.2) months, and the short nail group was (7.8±4.7) months, revealing no significant differences (p=0.09).Conclusions: Both the proximal femoral intramedullary long and short nail fixation has a good result in the form of fracture union in treating intertrochanteric femur fractures in the elderly. They showed no significant difference in terms of fracture union, hospital stay, and postoperative complications. The incidence of periprosthetic fractures and anterior thigh pain was slightly high in short nail group. In short intramedullary nailing group there was obvious decrease in the intraoperative blood loss, operation time and postoperative blood transfusion

Use of a tandem affinity purification assay to detect interactions between West Nile and dengue viral proteins and proteins of the mosquito vector

AbstractWest Nile and dengue viruses are (re)emerging mosquito-borne flaviviruses that cause significant morbidity and mortality in man. The identification of mosquito proteins that associate with flaviviruses may provide novel targets to inhibit infection of the vector or block transmission to humans. Here, a tandem affinity purification (TAP) assay was used to identify 18 mosquito proteins that interact with dengue and West Nile capsid, envelope, NS2A or NS2B proteins. We further analyzed the interaction of mosquito cadherin with dengue and West Nile virus envelope protein using co-immunoprecipitation and immunofluorescence. Blocking the function of select mosquito factors, including actin, myosin, PI3-kinase and myosin light chain kinase, reduced both dengue and West Nile virus infection in mosquito cells. We show that the TAP method may be used in insect cells to accurately identify flaviviral–host protein interactions. Our data also provides several targets for interrupting flavivirus infection in mosquito vectors

Functional Role and Affinity of Inorganic Cations in Stabilizing the Tetrameric Structure of the KcsA K+ Channel

Crystal structures of the tetrameric KcsA K+ channel reveal seven distinct binding sites for K+ ions within the central pore formed at the fourfold rotational symmetry axis. Coordination of an individual K+ ion by eight protein oxygen atoms within the selectivity filter suggests that ion-subunit bridging by cation–oxygen interactions contributes to structural stability of the tetramer. To test this hypothesis, we examined the effect of inorganic cations on the temperature dependence of the KcsA tetramer as monitored by SDS-PAGE. Inorganic cations known to permeate or strongly block K+ channels (K+, Rb+, Cs+, Tl+, NH4+, Ba2+, and Sr2+) confer tetramer stability at higher temperatures (T0.5 range = 87°C to >99°C) than impermeant cations and weak blockers (Li+, Na+, Tris+, choline+; T0.5 range = 59°C to 77°C). Titration of K+, Ba2+, and other stabilizing cations protects against rapid loss of KcsA tetramer observed in 100 mM choline Cl at 90°C. Tetramer protection titrations of K+, Rb+, Cs+, Tl+, and NH4+ at 85°C or 90°C exhibit apparent Hill coefficients (N) ranging from 1.7 to 3.3 and affinity constants (K0.5) ranging from 1.1 to 9.6 mM. Ba2+ and Sr2+ titrations exhibit apparent one-site behavior (N ≅ 1) with K0.5 values of 210 nM and 11 μM, respectively. At 95°C in the presence of 5 mM K+, titration of Li+ or Na+ destabilizes the tetramer with K0.5 values of 57 mM and 109 mM, respectively. We conclude that specific binding interactions of inorganic cations with the selectivity filter are an important determinant of tetramer stability of KscA

A Framework for Prediction and Storage of Battery Life in IoT Devices using DNN and Blockchain

As digitization increases, the need to automate various entities becomes crucial for development. The data generated by the IoT devices need to be processed accurately and in a secure manner. The basis for the success of such a scenario requires blockchain as a means of unalterable data storage to improve the overall security and trust in the system. By providing trust in an automated system, with real-time data updates to all stakeholders, an improved form of implementation takes the stage and can help reduce the stress of adaptability to complete automated systems. This research focuses on a use case with respect to the real time Internet of Things (IoT) network which is deployed at the beach of Chicago Park District. This real time data which is collected from various sensors is then used to design a predictive model using Deep Neural Networks for estimating the battery life of IoT sensors that is deployed at the beach. This proposed model could help the government to plan for placing orders of replaceable batteries before time so that there can be an uninterrupted service. Since this data is sensitive and requires to be secured, the predicted battery life value is stored in blockchain which would be a tamper-proof record of the data.Comment: Accepted for presentation at IEEE GLOBECOM 202

Synchronous dual malignancy: a rare case report of carcinoma breast with carcinoma gall bladder

Incidence of multiple primary cancers is reported to be between 0.18% to 17.2% in various studies. Occurrence of breast and gall bladder malignancy as synchronous malignancy is very rare. We are reporting one of such rare case. Our patient, a 64 years old lady had a unique presentation. She underwent laparoscopic cholecystectomy for a clinical diagnosis of cholelithiasis. Histopathology turned out to be adenocarcinoma of the gall bladder (Stage II A). A clinical examination done at the time of presentation to our institute revealed suspicious thickening of the skin of the left breast and a subsequent tru-cut biopsy revealed infiltrating ductal carcinoma. Hormone receptor immunohistochemistry revealed oestrogen receptor (ER) negative progesterone receptor (PR) negative and Her2neu negative tumour. Further evaluation revealed a widespread metastatic disease. She was treated with palliative radiotherapy, chemotherapy and zolendronate. She had an aggressive clinical course and succumbed to her illness within four months after diagnosis of dual malignancy. There is a high incidence of gall bladder carcinoma along the Gangetic belt of Northern India. Presence of dual malignancy with gall bladder carcinoma as one primary in these geographic location needs to be further explored for sporadic environmental factors or other genetic alterations as possible causative factors

An Ixodes scapularis protein required for survival of Anaplasma phagocytophilum in tick salivary glands

Anaplasma phagocytophilum is the agent of human anaplasmosis, the second most common tick-borne illness in the United States. This pathogen, which is closely related to obligate intracellular organisms in the genera Rickettsia, Ehrlichia, and Anaplasma, persists in ticks and mammalian hosts; however, the mechanisms for survival in the arthropod are not known. We now show that A. phagocytophilum induces expression of the Ixodes scapularis salp16 gene in the arthropod salivary glands during vector engorgement. RNA interference–mediated silencing of salp16 gene expression interfered with the survival of A. phagocytophilum that entered ticks fed on A. phagocytophilum–infected mice. A. phagocytophilum migrated normally from A. phagocytophilum–infected mice to the gut of engorging salp16-deficient ticks, but up to 90% of the bacteria that entered the ticks were not able to successfully infect I. scapularis salivary glands. These data demonstrate the specific requirement of a pathogen for a tick salivary protein to persist within the arthropod and provide a paradigm for understanding how Rickettsia-like pathogens are maintained within vectors