Denoising ECG Signal Using DWT with EAVO

Cardiovascular diseases are the leading cause of death across the world, and traditional methods for determining cardiac health are highly invasive and expensive. Detecting CVDs early is critical for effective treatment, yet traditional detection methods lack accessibility, accuracy, and cost-effectiveness – leaving patients with little hope of taking control of their own cardiac health. Noisy ECG signals make it difficult for health practitioners to accurately read and determine heart health. Unreliable readings can lead to misdiagnosis and needless expense. Despite the importance of ECG analysis, traditional methods of signal denoising are inefficient and can produce inaccurate results. This means that medical practitioners are struggling to obtain reliable readings, leaving them unable to accurately treat their patients and leading to a lack of confidence in the medical field. The Enhanced African Vulture Optimization (AVO) algorithm with Discrete Wavelet Transform (DWT) optimized by adaptive switching mean filtration (SMF) is proven to provide accurate denoising of the ECG signal. With this reliable method, medical professionals can quickly and accurately diagnose patients. Obtaining accurate ECG signals and interpreting them quickly is a challenge for healthcare professionals. Not only it takes a lot of time and skill but also requires specialized software to interpret the signals accurately. Healthcare professionals are facing a serious challenge when it comes to obtaining accurate ECG signals and interpreting them quickly. It requires them to spend extra time and effort, as well as specialize in the field with expensive software. Time is of the essence in healthcare and ECG readings can mean the difference between life and death. Specialized software can be expensive and time-consuming for those who don't have the resources or expertise. Our easy-to-use platform allows healthcare professionals to quickly interpret ECG signals, saving time, money, and lives! Get accurate readings. The EAVO algorithm and MIT-BIH dataset provide an effective solution to this problem. With the proposed filter built using EAVO, businesses can attain significant enhancements in reliable parameters and obtain accurate testing results in terms of SNR, MD, MSE and NRMSE

Optimal ECG Signal Denoising Using DWT with Enhanced African Vulture Optimization

Cardiovascular diseases (CVDs) are the world's leading cause of death; therefore cardiac health of the human heart has been a fascinating topic for decades. The electrocardiogram (ECG) signal is a comprehensive non-invasive method for determining cardiac health. Various health practitioners use the ECG signal to ascertain critical information about the human heart. In this paper, the noisy ECG signal is denoised based on Discrete Wavelet Transform (DWT) optimized with the Enhanced African Vulture Optimization (AVO) algorithm and adaptive switching mean filter (ASMF) is proposed. Initially, the input ECG signals are obtained from the MIT-BIH ARR dataset and white Gaussian noise is added to the obtained ECG signals. Then the corrupted ECG signals are denoised using Discrete Wavelet Transform (DWT) in which the threshold is optimized with an Enhanced African Vulture Optimization (AVO) algorithm to obtain the optimum threshold. The AVO algorithm is enhanced by Whale Optimization Algorithm (WOA). Additionally, ASMF is tuned by the Enhanced AVO algorithm. The experiments are conducted on the MIT-BIH dataset and the proposed filter built using the EAVO algorithm, attains a significant enhancement in reliable parameters, according to the testing results in terms of SNR, mean difference (MD), mean square error (MSE), normalized root mean squared error (NRMSE), peak reconstruction error (PRE), maximum error (ME), and normalized root mean error (NRME) with existing algorithms namely, PSO, AOA, MVO, etc

Image Processing based Plant Disease Detection and Classification

Generally, it has been observed that due to lack of proper knowledge of disease intensity, the farmer is not able to use the pesticide in proper quantity to treat the diseases. The use of pesticide mostly becomes more than necessary, due to which there is not only a loss of money, but also it causes soil and environmental pollution. If diseases severity-wise labelled data sets are available, it can be used to develop pesticide recommendation systems. Images with least infection severity can be used to train and validate a DL model to capture the plant diseases at very initial stage. Classification techniques may be viewed as variations of detection systems; however, instead of attempting to identify only one particular illness among several diseases, classification methods detect and name the diseases harming the plant. This presents various classification and plant disease detection methods based on image processing with results

Classification Models for Plant Diseases Diagnosis: A Review

Plants are important source of our life. Crop production in a good figure and good quality is important to us. The diagnosis of a disease in a plant can be manual or automatic. But manual detection of disease in a plant is not always correct as sometimes it can be not be seen by naked eyes so an automatic method of detection of plant diseases should be there. It can make use of various artificial intelligence based or machine learning based methods. It is a tedious task as it needs to be identified in earlier stage so that it will not affect the entire crop. Disease affects all species of plant, both cultivated and wild. Plant disease occurrence and infection severity vary seasonally, regarding the environmental circumstances, the kinds of crops cultivated, and the existence of the pathogen. This review attempts to provide an exhaustive review of various plant diseases and its types, various methods to diagnose plant diseases and various classification models used so as to help researchers to identify the areas of scope where plant pathology can be improved

COMPARISON STUDY OF VITAMIN-B12 FOR ITS EFFICACY AND BIOAVAILABILITY OF VARIOUS FORMULATIONS IN THE TREATMENT OF PERNICIOUS ANEMIA

VitaminB12 helps your body to use fat and carbohydrates for energy and makes new protein. It is also important for normal blood, cells, and nerves. Most people get enough vitaminB12 in their diet, but a deficiency may occur in certain health conditions (e. g., poor nutrition, stomach/intestinal problems, infection, cancer). Serious VitaminB12 deficiency results in anemia and nerve damage if left untreated. VitaminB12 deficiency usually treated by parenteral and oral dosage forms, but these routes of administration is associated with absorption and compliance issue. More recently, it has been demonstrated that the function of this missing intrinsic factor is to aid the absorption of Vitamin B12 and deficiency termed as pernicious anemia. Pernicious anemia may be satisfactorily treated by parenteral administration of the extrinsic factor, Vitamin B12is only slightly absorbed when given by mouth to patients with pernicious anemia, but a hematological response may be obtained if relatively large doses are given by this route. The objective of this study was to compare the efficacy and safety profile of appropriate vitamin B12formulation in the treatment of pernicious anemia.Â

Detection of fumonisin among different strains of Fusarium spp. associated with bakanae disease of rice (Oryza sativa L.) using molecular markers

Bakanae disease caused by Fusarium fujikuroi of basmati rice causes huge economic losses varying with varieties produced, with a frequency of 3.0-95.4%. The Fusarium spp. associated with bakanae disease produce fumonisins, a group of structurally similar sphingosine analogue mycotoxins, among which Fumonisin B1 is the most prevalent and active (FB1). The worst harm to both people and animal wellbeing is created by fumonisins, which infect feed and food sources. IARC, a global organization dedicated to cancer research, classified FB1 as a potential causing human cancer (Group 2B). Altogether 26 strains of Fusarium spp. from bakanae infected  samples of various popular basmati rice varieties collected from Hisar, Jind, Fatehabad, Bhiwani, Sirsa, Panipat, Sonipat, Karnal, Yamunanagar, Kaithal and Kurukshetra (eleven) districts of Haryana state. Two specific primers namely VERTF and polyketide synthase (PKS) (involved in fumonisin biosynthesis) FUM (rp 32 and rp 33) were utilized in this investigation to differentiation between fumonisin-producing and non-producing strains employing PCR technique. Twenty-two strains were significant for the VERTF primer and showed the capacity to generate fumonisin, while four isolates evaluated negative for both primers. The FUM specific primer displayed positive respose only in nine strains and rest were negative. The present study provides a rapid and specific method that helped in accurate differentiation between fumonisin-producing and non-producing strains.

Dynamin Functions and Ligands: Classical Mechanisms Behind

ABSTRACT Dynamin is a GTPase that plays a vital role in clathrin-dependent endocytosis and other vesicular trafficking processes by acting as a pair of molecular scissors for newly formed vesicles originating from the plasma membrane. Dynamins and related proteins are important components for the cleavage of clathrin-coated vesicles, phagosomes, and mitochondria. These proteins help in organelle division, viral resistance, and mitochondrial fusion/fission. Dysfunction and mutations in dynamin have been implicated in the pathophysiology of various disorders, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, Charcot-Marie-Tooth disease, heart failure, schizophrenia, epilepsy, cancer, dominant optic atrophy, osteoporosis, and Down's syndrome. This review is an attempt to illustrate the dynamin-related mechanisms involved in the above-mentioned disorders and to help medicinal chemists to design novel dynamin ligands, which could be useful in the treatment of dynamin-related disorders

Combinational effect of angiotensin receptor blocker and folic acid therapy on uric acid and creatinine level in hyperhomocysteinemia-associated hypertension

© 2019 International Union of Biochemistry and Molecular Biology, Inc. Homocysteine [HSCH2CH2CH(NH2)COOH] (Hcy) is a sulfur-containing amino acid of 135.18 Da of molecular weight, generated during conversion of methionine to cysteine. If there is a higher accumulation of Hcy in the blood, that is usually above 15 µmol/L, it leads to a condition referred to as hyperhomocysteinemia. A meta-analysis of observational study suggested an elevated concentration of Hcy in blood, which is termed as the risk factors leading to ischemic heart disease and stroke. Further experimental studies stated that Hcy can lead to an increase in the proliferation of vascular smooth muscle cells and functional impairment of endothelial cells. The analyses confirmed some of the predictors for Hcy presence, such as serum uric acid (UA), systolic blood pressure, and hematocrit. However, angiotensin-converting enzyme inhibitors angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) alone are inadequate for controlling UA and creatinine level, although the addition of folic acid may be beneficial in hypertensive patients who are known to have a high prevalence of elevated Hcy. We hypothesized that combination therapy with an ARB (olmesartan) and folic acid is a promising treatment for lowering the UA and creatinine level in hyperhomocysteinemia-associated hypertension