Improving circuit miniaturization and its efficiency using Rough Set Theory

High-speed, accuracy, meticulousness and quick response are notion of the vital necessities for modern digital world. An efficient electronic circuit unswervingly affects the maneuver of the whole system. Different tools are required to unravel different types of engineering tribulations. Improving the efficiency, accuracy and low power consumption in an electronic circuit is always been a bottle neck problem. So the need of circuit miniaturization is always there. It saves a lot of time and power that is wasted in switching of gates, the wiring-crises is reduced, cross-sectional area of chip is reduced, the number of transistors that can implemented in chip is multiplied many folds. Therefore to trounce with this problem we have proposed an Artificial intelligence (AI) based approach that make use of Rough Set Theory for its implementation. Theory of rough set has been proposed by Z Pawlak in the year 1982. Rough set theory is a new mathematical tool which deals with uncertainty and vagueness. Decisions can be generated using rough set theory by reducing the unwanted and superfluous data. We have condensed the number of gates without upsetting the productivity of the given circuit. This paper proposes an approach with the help of rough set theory which basically lessens the number of gates in the circuit, based on decision rules.Comment: The International Conference on Machine Intelligence Research and Advancement,ICMIRA-201

Primary Non-Hodgkin's Malignant Lymphoma of the Sinonasal Tract

Primary non-Hodgkin’s lymphomas (NHL) of the sinonasal tract are rather uncommon entities. Morphologically and radiographically, sinonasal lymphomas are difficult to distinguish from other malignant neoplasms or non- neoplastic processes. They have a variable presentation from fulminant destructive manifestations to chronic indolent type of disease and may mimic as carcinomas and invasive fungal infection respectively. We report a case of primary NHL involving sinonasal tract in elderly female, which was clinically and radiologically mimicking as sinonasal malignany and was proven as NHL on histological examination and confirmed by immunohistochemistry. A high index of suspicion, appropriate histopathological examination and immunohistochemistry is necessary to differentiate sinonasal lymphomas from other possibilities. Failure to do so may miss the diagnosis and delay appropriate treatmen

Optimization and Characterization of Thermostable Endo and Exocellulases by Humicola sp. SKESMBKU03

Humicola sp. SKESMBKU03, a cellulase producer was isolated from horse dung manure collected from Hyderabad, Telangana. In the present study, endo and exoglucanase production from Humicola sp. SKESMBKU03 was studied and optimization of the cultural conditions to enhance production of enzymes has been reported. Among the twenty fungal cellulase producers isolated from different thermogenic habitats, the fungal strain ‘HD3’ identified as Humicola sp. SKESMBKU03 exhibited highest cellulase activity by plate screening assay. To enhance the production level of the enzyme, different cultural conditions were optimized and observed that optimum pH and temperature for endo and exoglucanase production was 5.0 and 45oC respectively. Maximum growth as well as enzyme production was recorded on 3rd day of incubation period in shake flask (100RPM) containing Mandel’s Weber medium. Urea and malt extract among the organic nitrogen sources while ammonium chloride as inorganic nitrogen source were found to be the best nitrogen source (0.2%) for endo and exoglucanase production. The endo and exoglucanase activities are higher in media containing glucose as their carbon source (1%) followed by xylose and lactose. The organism showed maximum dry weight in pH of 9.0-10.0, temperature of 45oC, cellulose as carbon sources, yeast extract and malt extract of nitrogen source. The endo and exocellulases produced by the Humicola sp. SKESMBKU03 are highly stable at pH 8.0 and temperature of 750C. The results indicate that the endo and exocellulases produced by Humicola sp. SKESMBKU03 are more stable at high temperature and alkaline pH

Himalayan P waves in COPD - A Rare Feature

Himalayan or giant P-waves (amplitude =5 mm) are often known to be classically associated with congenital heart diseases with right to left shunt like tricuspid atresia, Ebstein anomaly, combined tricuspid and pulmonic stenosis, etc, where they indicate a dilated right atrium and tend to be persistent. These type P waves are rarely seen in chronic obstructive pulmonary disease (COPD) and in this condition it may be due to structural right atrial changes or hypoxemia or combination of both. Here we report a case of COPD with Himalayan P waves which is a rare entity

Blockchain and Reinforcement Neural Network for Trusted Cloud-Enabled IoT Network

The rapid integration of Internet of Things (IoT) services and applications across various sectors is primarily driven by their ability to process real-time data and create intelligent environments through artificial intelligence for service consumers. However, the security and privacy of data have emerged as significant threats to consumers within IoT networks. Issues such as node tampering, phishing attacks, malicious code injection, malware threats, and the potential for Denial of Service (DoS) attacks pose serious risks to the safety and confidentiality of information. To solve this problem, we propose an integrated autonomous IoT network within a cloud architecture, employing Blockchain technology to heighten network security. The primary goal of this approach is to establish a Heterogeneous Autonomous Network (HAN), wherein data is processed and transmitted through cloud architecture. This network is integrated with a Reinforced Neural Network (RNN) called ClouD_RNN, specifically designed to classify the data perceived and collected by sensors. Further, the collected data is continuously monitored by an autonomous network and classified for fault detection and malicious activity. In addition, network security is enhanced by the Blockchain Adaptive Windowing Meta Optimization Protocol (BAWMOP). Extensive experimental results validate that our proposed approach significantly outperforms state-of-the-art approaches in terms of throughput, accuracy, end-to-end delay, data delivery ratio, network security, and energy efficiency

The Reliability of Histamine Pharmacodynamic Response Phenotype Classification in Children With Allergic Disease.

We have identified distinct histamine pharmacodynamic response phenotypes in children with allergic disease utilizing histamine iontophoresis with laser Doppler (HILD). These response phenotypes may be relevant in guiding therapeutic decision making for agents targeting the allergic response pathways. However, the reliability of these response phenotypes has not been assessed. Therefore, we performed HILD in children with allergic rhinitis and/or asthma on two to three separate occasions. HILD response-time data were analyzed in NONMEM using a linked effect PKPD model. Examination of observed vs. classified response phenotypes predicted response plots and the sum of residuals. The intraclass correlation coefficient (ICC) was used to determine the reliability of phenotype classification. Eighty-two percent of children exhibited a reliable histamine response phenotype [intraclass correlation coefficient 0.77 (95% CI 0.44–0.93]. These preliminary results suggest moderate reliability of HILD response phenotype in children. Further exploration is needed to determine contributions to phenotype variability

Blockchain inspired secure and reliable data exchange architecture for cyber-physical healthcare system 4.0

A cyber-physical system is considered to be a collection of strongly coupled communication systems and devices that poses numerous security trials in various industrial applications including healthcare. The security and privacy of patient data is still a big concern because healthcare data is sensitive and valuable, and it is most targeted over the internet. Moreover, from the industrial perspective, the cyber-physical system plays a crucial role in the exchange of data remotely using sensor nodes in distributed environments. In the healthcare industry, Blockchain technology offers a promising solution to resolve most securities-related issues due to its decentralized, immutability, and transparency properties. In this paper, a blockchain-inspired secure and reliable data exchange architecture is proposed in the cyber-physical healthcare industry 4.0. The proposed system uses the BigchainDB, Tendermint, Inter-Planetary-File-System (IPFS), MongoDB, and AES encryption algorithms to improve Healthcare 4.0. Furthermore, blockchain-enabled secure healthcare architecture for accessing and managing the records between Doctors and Patients is introduced. The development of a blockchain-based Electronic Healthcare Record (EHR) exchange system is purely patient-centric, which means the entire control of data is in the owner's hand which is backed by blockchain for security and privacy. Our experimental results reveal that the proposed architecture is robust to handle more security attacks and can recover the data if 2/3 of nodes are failed. The proposed model is patient-centric, and control of data is in the patient's hand to enhance security and privacy, even system administrators can't access data without user permission

A retrospective analysis of acute organophosphorus poisoning cases admitted to the tertiary care teaching hospital in South India

Objectives: We have herein reported our experience with the pattern of presentation of cases of acute organophosphorus (OP) poisoning cases in a tertiary care hospital.Materials and Methods: This retrospective study evaluated the hospital records of patients with acute OP poisoning. In a pre-structured proforma, data regarding age, sex, time elapsed after intake, circumstances of poisoning, duration of hospitalization, severity, complications, and outcome of the patients were recorded. The data were presented as mean ± standard deviation, entered in the open office datasheet, and analyzed with PSPP software.Results: A total 101 patients were included in the study. Young adult males were more commonly involved than females (M:F 2.5:1). The mean age of the patients was 28 years (range 2-72 years, SD ± 14.3 years). Mean time to receive treatment was 5.2 ± 7.4 (range 1-48 h). About 45.5% patients received first aid before coming to the hospital. The reason was suicide in 88.1% cases and accident in 12 (11.9%, all children). Seventy-nine  patients received pralidoxime (PAM) and the mean duration was 1.7 ± 1.1 (range 1-4 days). Atropine was given in all patients. Mean duration was 5.1 ± 3.1 (range 1-19 days). Mean hospital stay was 7.5 ± 4.7 days (range 1-26 days). Mortality was 9.9% in the present series.Conclusion: Although the present study contribute substantial information regarding the epidemiology and outcome of acute OP poisoning in a tertiary care teaching hospital at a district level, its relatively small sample size and the retrospective record-based nature are the major limitations of the present study. There is a further need for prospective studies to understand the underlying socio-economic factors responsible for acute OP poisoning in our population, and, accordingly, address the problems to reduce the incidence of acute OP poisoning cases.Keywords: Acute poisoning, organophosphate poisoning pattern, outcome, tertiary care hospita

Occurrence of Gastrointestinal Helminths in rabbits with special Reference to Importance of Giardia spp. as Parasitic Zoonoses

The aim of this study was to detect Giardia spp. as zoonotic helminth as Giardiosis has been recognised as the one of the important parasitic  diarrhoea among children as cross transmission may occur between human  and rabbits. Other helminths in rabbits may causes ill health and sometimes proved fatal. Faecal samples of 42 rabbits of different age group (1-4 years)  from Nagpur and Akola regions, India were examined. The study was  conducted during June to August 2008. Faecal sample examination revealed  presence of mixed infection of eggs of parasites like Giardia spp. (19.04%), Trichostrongyle spp. (28.57%), Graphidium spp. (19.04%), Coccidia spp. (16.66%) and Passaluras spp. (14.28%)