Hybrid Deep Learning Algorithm for Insulin Dosage Prediction Using Blockchain and IOT

This paper addresses the problem of predicting insulin dosage in diabetes patients using the PSO-LSTM, COA-LSTM, and LOA-LSTM algorithms. Accurate insulin dosage prediction is crucial in effectively managing Diabetes and maintaining blood glucose levels within the desired range. The study proposes a novel approach that combines particle swarm optimization (PSO) with the long short-term memory (LSTM) model. PSO is used to optimize the LSTM's parameters, enhancing its prediction capabilities specifically for insulin dosage. Additionally, two other techniques, COA-LSTM and LOA-LSTM, are introduced for comparison purposes. The algorithms utilize a dataset comprising relevant features such as past insulin dosages, blood glucose levels, carbohydrate intake, and physical activity. These features are fed into the PSO-LSTM, COA-LSTM, and LOA-LSTM models to predict the appropriate insulin dosage for future time points. The results demonstrate the effectiveness of the proposed PSO-LSTM algorithm in accurately predicting insulin dosage, surpassing the performance of COA-LSTM and LOA-LSTM. The PSO-LSTM model achieves a high level of accuracy, aiding in personalized and precise insulin administration for diabetes patients. By leveraging the power of PSO optimization and LSTM modeling, this research improves the accuracy and reliability of insulin dosage prediction. The findings highlight the potential of the PSO-LSTM algorithm as a valuable tool for healthcare professionals in optimizing diabetes management and enhancing patient outcomes

UNDERSTANDING THE TOXICITY AND CONTAMINATION OF MP IN THE WATER OF THE KRISHNA RIVER – A REVIEW

Tiny plastic fragments known as "microplastics" are extremely dangerous to society. Microplastics contaminate rivers because of their sluggish degradation. It became clear that plastic pollution would pose a health risk when more plastic trash started to accumulate in the natural world. Since plastics are long-lasting, incorrectly disposed of plastic items might be detected in the environment for a very long period. Plastic pollution has an impact on human health, animals, and aquatic life. Marine life, including fish, birds, and turtles, can become entangled in plastic debris and swallow it, which can cause severe harm or even death. Since these environments act as accumulation zones, it has been established that plastic litter negatively affects plant species like mangrove forest trees and the wildlife that lives there. Religious offerings, cultural celebrations, and untreated sewage water are the primary contributors of microplastic pollution. Sewage water from nearby settlements finds its way into the river. The disposal of garbage is one of the main human activities contributing to the microplastic burden in the Krishna River. These substances are now just tiny particles

An Enhanced Table Driven Source Routing Protocol for Wireless Ad Hoc Networks

Analysis of MANETs led to the research on network layer. Different routing protocols were designed for numerous objectives and purposes. The way data packets are handled with in a multi-hop wireless network refers to Opportunistic data forwarding. During present research, we propose enhanced table-driven source routing protocol. This protocol maintains additional topology information which is different from Distance Vector (DV) routing protocol. The proposed approach will reduce overhead compared to the ancient Distance Vector based protocols. Base on the test results performed using Computer Simulator (Network Simulator 2) observed that the overhead in the proposed solution is just a fraction of the overhead of the standard proactive protocols. Performance of the current solution is better for transportation of higher information compared to existing proactive routing protocols

Serum magnesium level and QTc interval prolongation in acute myocardial infarction patients and its correlation with arrhythmias

Background: Arrhythmias commonly occur early in acute myocardial infarction and remain a common cause of sudden death in AMI. Magnesium has been implicated in the pathogenesis of acute myocardial infarction and its complication like arrhythmia. Magnesium improves myocardial metabolism, inhibits calcium accumulation and myocardial cell death. It improves vascular tone, peripheral vascular resistance, after load and cardiac output and reduces cardiac arrhythmias. The objective of this study to investigate the serum magnesium level and QTc interval prolongation in AMI and its correlation with arrhythmias.Methods: In this study, 200 patients of AMI were enrolled. ECG and cardiac parameters were examined. Serum magnesium level is measured and the QTc interval was calculated.Results: MI was more prevalent in the male patients (63.3%) and age group of 41-50 years. Hypertension (35.7%), smoking (34.2%), and diabetes (23.1%) were the major risk factor for MI. Mean serum magnesium level was 1.64±0.37 among those having arrhythmia that is significantly low as compared to those having no arrhythmia among which mean serum magnesium level was 2.28±0.31 (p<0.001). Mean QTc was higher (546.88 ms vs. 404.33ms) in patients documented with arrhythmia compared with those who had no arrhythmia (p<0.001).Conclusions: In acute myocardial infarction, patients with low magnesium levels and prolonged QTc interval are more prone to get arrhythmias. So magnesium treatment can be considered in patients of acute myocardial infarction with low magnesium levels

Impact of climate change on yield of different crops grown in Cachar district of Assam, India

Impact of climate change on crop yield threatens food security which is detrimental to agricultural sector. Cachar district of Assam is a climate susceptible district due to its unique geographical location and hydrological regime in north-eastern India. So, the present study was carried out to assess impact of climate change on crop yield for sustainability of agriculture. Climatic data&nbsp;viz.,&nbsp;rainfall, maximum-minimum temperature and sunshine hours were collected from an observatory of Tea Research Association, Silcoorie, Cachar district for 2007-2012. Statistical and correlation analysis was employed to evaluate potential climate change impact on productivity of twenty three major crops of the study site. The correlation coefficient (r, Pearson’s Product Moment) between any climatic parameter and crop yield implied that climate has strong linear correlation with yield of crops resulting in twenty-two strong correlations. Among the climatic parameters rainfall was found to have most significant impact on yield. Noteworthy reduction was observed in yield of Autumn Paddy and Winter Paddy by 8.75 and 20.44 during the year 2008-2009 due to 3.98 and 36.22% decrease of rainfall with&nbsp;r&nbsp;values 0.95 and -0.76, respectively. Also, a quantum leap of 145.32% increase of rainfall during&nbsp;Rabi&nbsp;season of 2007-2008 decreased the yield of Potato and&nbsp;Rabi&nbsp;vegetables by 22.96 and 16.89%, respectively. The study revealed that climate change has significant impact on crop yield which could be alleviated by adopting rainwater harvesting technology at the top and foot hills of the hilly areas

Evidence for the characterisation of the C-H …∏ interaction as a weak hydrogen bond: toluene and chlorobenzene solvates of 2,3,7,8-tetraphenyl-1,9,10-anthyridine

The crystal structures of the toluene and chlorobenzene solvates of 2,3,7,8-tetraphenyl-1,9,10-anthyridine are nearly identical save for differences in the mode of solvent inclusion; these differences have an important bearing on the nature of the C-H … ∏ interactions in these structures

Sulfotransferase 1A1 (SULT1A1) Polymorphism and Breast Cancer Risk: A Case-control Study in South India

Introduction: Breast cancer is the most common cancer among women worldwide. Sulfotransferase plays an important role in the formation of estrogen which is usually conferred as a risk factor for breast cancer. The SULT1A1*2 polymorphism is likely to play an important role in the susceptibility to breast cancer. This polymorphism (G638A) in the sulfotransferase 1A1 (SULT1A1) gene may causes Arg213His amino acid change and consequently results in significantly reduced enzyme activity and thermostability.Materials and Methods: In this case-control study, we investigated the role of SULT1A1 G638A polymorphism in breast cancer patients. We genotyped 144 patients with breast cancer and 116 healthy control subjects, using a Polymerase chain reaction –Restriction Fragment length polymorphism (PCR-RFLP) method.Results: The frequencies of SULT1A1 G638G, G638A and A638A were 83.5%, 17.8%, and 1.4% in the breast cancer group and 89.5%, 4.0% and 0.0% in the control group. The results of our study indicate that the SULT1A1 G638A genotype showed 4.6 folds increased risk of breast cancer (p = 0.002).Conclusion: In conclusion, our results suggest that, SULT1A1 G638A variant is significantly associated with risk of breast cancer in south Indian women

Epidemiological Survey of Lumpy Skin Disease of Cattle in Ballari and Vijayanagara Districts, Karnataka, India

The present research is to study the epidemiological survey of Lumpy skin disease (LSD) of cattle caused by Lumpy skin disease virus (LSDV) in Ballari and Vijayanagara districts, Karnataka, India. LSD is an economically significant disease in cattle caused by Lumpy skin disease virus (LSDV), in India. The disease incidence, mortality rate and severity of the disease during the outbreak is the measure of the infection. The impact of this disease is creating problems in the livelihood of farmers as the milk production go down and major loss for dairy and meat industries. The data of total cattle population and disease incidence of LSD in different villages of Ballari district are collected during August 2021-September 2022 from District veterinary hospital, Ballari and Vijayanagara which was analysed statistically. LSD is more prevalent in Ballari and Vijayanagara showing highest morbidity rate of 7.91% and 12.9% respectively with 0% of mortality rate. Further study will be taken up on the present outbreak in 2022 October and molecular characterization of isolated LSD

ExoMol molecular line lists – XXIII. Spectra of PO and PS

Comprehensive line lists for phosphorus monoxide ($^{31}$P$^{16}$O) and phosphorus monosulphide ($^{31}$P$^{32}$S) in their $X$ $^2\Pi$ electronic ground state are presented. The line lists are based on new ab initio potential energy (PEC), spin-orbit (SOC) and dipole moment (DMC) curves computed using the MRCI+Q-r method with aug-cc-pwCV5Z and aug-cc-pV5Z basis sets. The nuclear motion equations (i.e. the rovibronic Schr\"odinger equations for each molecule) are solved using the program Duo. The PECs and SOCs are refined in least-squares fits to available experimental data. Partition functions, $Q(T)$, are computed up to $T=$ 5000 K, the range of validity of the line lists. These line lists are the most comprehensive available for either molecule. The characteristically sharp peak of the $Q$-branches from the spin-orbit split components give useful diagnostics for both PO and PS in spectra at infrared wavelengths. These line lists should prove useful for analysing observations and setting up models of environments such as brown dwarfs, low-mass stars, O-rich circumstellar regions and potentially for exoplanetary retrievals. Since PS is yet to be detected in space, the role of the two lowest excited electronic states ($a$ $^4\Pi$ and $B$ $^2\Pi$) are also considered. An approximate line list for the PS $X - B$ electronic transition, which predicts a number of sharp vibrational bands in the near ultraviolet, is also presented. he line lists are available from the CDS (cdsarc.u-strasbg.fr) and ExoMol (www.exomol.com) databases.Comment: MNRAS (2017