Artificial Intelligence (AI) Model: Adaptive Neuro-Fuzzy Inference System (ANFIS) for Diagnosis of COVID-19 Influenza

The COVID-19 influenza became a curse on the world. It has been around for two years, so no one needs to make a big introduction of it. It has became a significant challenge around the world. Owing to this, we made dynamic networks using an amalgamating of fuzzy logic and neural networks for the prediction of sufferers of COVID-19. These hybrid networks serve for the assessment of the COVID-19 victims and usefully serve for the assessment of the medical resources needed for future victims. This manuscript proposed Sugeno Adaptive Neuro-Fuzzy Inference System (SANFIS) prediction model for COVID-19 prediction in Andhra Pradesh, India. We gathered data on positive COVID-19 sufferers in Andhra Pradesh for this purpose. The data can be separated into three categories: training set, testing set and checking set. We have utilized Root Mean Square Deviation (RMSD) for prediction precision. If the prediction model has a lower RMSD value, it is regarded as the best forecast. In this study, we concluded that the 3 Triangular MFns for each input were excellent with the extreme precision for all of the districts based on our expertise. In the end, we deployed seven SANFIS replicas in Andhra Pradesh, but we discovered that SANFIS6 and SANFIS7 provided excellent COVID-19 prediction results. These findings will assist the government, healthcare agencies, and medical organizations in planning for future COVID-19 victims' medical requirements. These sorts of Sugeno Adaptive Neuro-Fuzzy Inference System (SANFIS) prediction models based on Artificial Intelligence (AI) will be beneficial in overcoming the COVID-19

Towards Augmenting Federated Wireless Sensor Networks

AbstractEnvironmental Monitoring (EM) has witnessed significant improvements in recent years due to the great utility of Wireless Sensor Networks (WSNs). Nevertheless, due to harsh operational conditions in such applications, WSNs often suffer large scale damage in which nodes fail concurrently and the network gets partitioned into disjoint sectors. Thus, reestablishing connectivity between the sectors, via their remaining functional nodes, is of utmost importance in EM; especially in forestry. In this regard, considerable work has been proposed in the literature tackling this problem by deploying Relay Nodes (RNs) aimed at re-establishing connectivity. Although finding the minimum relay count and positions is NP-Hard, efficient heuristic approaches have been anticipated. However, the majority of these approaches ignore the surrounding environment characteristics and the infinite 3-Dimensional (3-D) search space which significantly degrades network performance in practice. Therefore, we propose a 3-D grid-based deployment for relay nodes in which the relays are efficiently placed on grid vertices. We present a novel approach, named FADI, based on a minimum spanning tree construction to re-connect the disjointed WSN sectors. The performance of the proposed approach is validated and assessed through extensive simulations, and comparisons with two main stream approaches are presented. Our protocol outperforms the related work in terms of the average relay node count and distribution, the scalability of the federated WSNs in large scale applications, and the robustness of the topologies formed

Polyunsaturated fatty acids in the pathogenesis and treatment of multiple sclerosis

Epidemiological, biochemical, animal model and clinical trial data described in this overview strongly suggest that polyunsaturated fatty acids, particularly n-6 fatty acids, have a role in the pathogenesis and treatment of multiple sclerosis (MS). Data presented provides further evidence for a disturbance in n-6 fatty acid metabolism in MS. Disturbance of n-6 fatty acid metabolism and dysregulation of cytokines are shown to be linked and a "proof of concept clinical trial" further supports such a hypothesis. In a randomised double-blind, placebo controlled trial of a high dose and low dose selected GLA (18:3n-6)-rich oil and placebo control, the high dose had a marked clinical effect in relapsing-remitting MS, significantly decreasing the relapse rate and the progression of disease. Laboratory findings paralleled clinical changes in the placebo group in that production of mononuclear cell pro-inflammatory cytokines (TNF-alpha, IL-1 beta) was increased and anti-inflammatory TGF-beta markedly decreased with loss of membrane n-6 fatty acids linoleic (18:2n-6) and arachidonic acids (20:4n-6). In contrast there were no such changes in the high dose group. The improvement in disability (Expanded Disability Status Scale) in the high dose suggests there maybe a beneficial effect on neuronal lipids and neural function in MS. Thus disturbed n-6 fatty acid metabolism in MS gives rise to loss of membrane long chain n-6 fatty acids and loss of the anti-inflammatory regulatory cytokine TGF-beta, particularly during the relapse phase, as well as loss of these important neural fatty acids for CNS structure and function and consequent long term neurological deficit in MS

Antidiabetic potential of Lantana aculeata root extract in alloxan-induced diabetic rats

The present study investigates the antidiabetic potential of dried mature roots of Lantana aculeata, a weed belonging to verbenaceae family on biochemical profile in alloxan-induced diabetic rats. The effects of an ethanolic extract of the dried mature roots of Lantana aculeata on serum glucose, total cholesterol, triglycerides, plasma insulin and liver glycogen were examined in control and experimental groups. Lantana aculeata root extract reduced the serum glucose concentration at 24, 48 and 72 hours. To verify the activity sub-chronically, the extract administered orally in the doses of 25, 50 and 100 mg/kg to diabetic rats for 30 days, that significantly reduced the level of glucose, total cholesterol and triglycerides with an increase in insulin and glycogen concentration to near normal levels in a dose-dependent manner. The results indicate that roots of Lantana aculeata possess antidiabetic potential in alloxan-induced diabetic rats. The activity might be due to high concentration of oleanolic acid present in the roots.Keywords: Antidiabetic activity, Lantana aculeata roots, Oleanolic aci

Plasma factor XIII level variations during menstrual cycle

Factor XIII (FXIII) has an important role in the control of bleeding through fibrin cross-linking; however, its effect within the menstrual cycle is not fully understood. The aim of this study was to examine changes in FXIII activity during the normal menstrual cycle and correlate FXIII activity with menstrual blood loss. A total of 32 healthy normal women of reproductive age were recruited. Menstrual blood loss was measured using the pictorial blood-assessment chart (PBAC). A bleeding score questionnaire was also completed. Blood samples were taken during the menstrual, proliferative, periovulatory, secretory and premenstrual phase for assessment of FXIII level. The mean ± SD FXIII level was lowest during menstrual and periovulatory phases (114 ± 23 and 114 ± 21 IU/dl, respectively). Mean FXIII level during the secretory and premenstrual phases were higher than the menstrual phase (P = 0.036). Mean secretory phase FXIII was also significantly higher compared with the periovulatory phase (P = 0.02). There was no significant correlation between FXIII level during the menstrual phase and age (P = 0.53) or PBAC score (P = 0.53). There were no significant differences in FXIII level during the menstrual phase between women with PBAC scores of at least 100 (n = 14; mean 116 IU/dl) and women with PBAC scores less than 100 (n = 18; mean 113 IU/dl). There was no correlation between FXIII level and bleeding score. FXIII activity was lower during menstrual and periovulatory phases of the cycle. However, the small difference between mean values (8 IU/dl) would be unlikely to have a significant impact on diagnosis of FXIII deficiency and clinical management

Herbal mediated silver nanoparticles: A new horizon of antineoplastic drug delivery system

Cancer is a disease characterized by the uncontrolled growth and spread of abnormal cells, and is still the second most common cause of death worldwide. Several classes of drugs are available to treat different types of cancer. Currently, researchers are paying significant attention to the development of drugs at the nanoscale level to increase their target specificity and to reduce their side effects. Silver nanoparticles are the topics of researchers because of their distinctive properties (e.g., size and shape and electrical properties). Synthesis of herbal mediated silver nanoparticles targeting biological pathways has become tremendously prominent due to the higher efficacy and fewer side effects as compared to other commercial cancer drugs. A variety of preparation techniques have been reported for the synthesis of silver nanoparticles such as physical, chemical and biological methods. In this review, different medicinal plants and their active compounds, as well as synthesized silver nanoparticles from medicinal plants, are discussed in relation to their anticancer activities. Keywords: Silver nanoparticles, Medicinal plants and Anti-cancer activities