Cloud Computing with Artificial Intelligence Techniques for Effective Disease Detection

With the current rapid advancement of cloud computing (CC) technology, which enabled the connectivity of many intelligent objects and detectors and created smooth data interchange between systems, there is now a strict need for platforms for data processing, the Internet of Things (IoT), and data management. The field of medicine in CC is receiving a lot of attention from the scientific world, as well as the private and governmental sectors. Thousands of individuals now have a digital system due to these apps where they may regularly obtain helpful medical advice for leading a healthy life. The use of artificial intelligence (AI) in the medical field has several advantages, including the ability to automate processes and analyze large patient databases to offer superior medicine more quickly and effectively. IoT-enabled smart health tools provide both internet solutions and a variety of features. CC infrastructure improves these healthcare solutions by enabling safe storage and accessibility. We suggest a novel Cloud computing and artificial intelligence (CC-AI) premised smart medical solution for surveillance and detecting major illnesses to provide superior solutions to the users. For disease detection, we suggested AI-based whale optimization (WO) and fuzzy neural network (FNN) (WO-FNN). Patients' IoT wearable sensor data is gathered for detection. The accuracy, sensitivity, specificity, and computation time are evaluated and compared with existing techniques

RAPD-based genetic relationships in different Bougainvillea cultivars

The present study deals with authenticating existing knowledge about 21 Bougainvillea cultivars comprisingof 9 hybrids and their parents through RAPD analysis. The 19 degenerate primer sets generated 234 bands from which 158(67.5%) were polymorphic. The UPGMA based dendrogram divided 21 cultivars into two major groups with Jaccard’ssimilarity coefficient ranging from 0.51 to 0.942. Group A had three cultivars namely Trinidad, Formosa and Dr. H. B. Singhin which Dr. H.B. Singh was confirmed as a hybrid of other two cultivars. Group B was sub divided into 8 clusters. Theparentages of 7 out of 8 hybirds have been confirmed based on clusters. The study concluded that the RAPD technique issuitable for confirmation of parent-hybrid relationship

Effect of hydroxyl alkyl amines on the solubility behavior of calcium sulphate dihydrate (gypsum) in the aqueous sodium chloride system at 35 °C

The solubility behavior of calcium sulphate dihydrate (gypsum, CaSO4·2H2O) in aqueous NaCl solutions upon addition of hydroxyl alkyl amines, such as, ethanolamine (EA), diethanolamine (DEA), or triethanolamine (TEA) at 35 °C is reported.  The addition of hydroxyl alkyl amines alters the solubility of CaSO4·2H2O in NaCl solutions significantly. At any equal concentration of hydroxyl alkyl amines in the solution, the order of CaSO4·2H2O solubility enhancement is found to be: EA < DEA < TEA. A three-fold increase in CaSO4·2H2O solubility maximum is observed in the solutions containing 15 wt% TEA. The addition of hydroxyl alkyl amines shifts the solubility maximum of CaSO4·2H2O towards higher concentration of NaCl in solution. Solution properties such as density (ρ) and speed of sound (u) data have been measured for the quaternary systems (CaSO4·2H2O+NaCl+hydroxyl alkyl amines+H2O). All the measurements have been carried out at 35 °C under atmospheric pressure. Solution isentropic compressibility (κS) values have been derived from u and ρ data. Solubility, density, speed of sound, and isentropic compressibility data have been fitted with suitable polynomial equations in these systems

Modeling the effect of deforestation caused by human population pressure on wildlife species

The increase in human population has posed several problems for the ecosystem. One of these problems is the decrease in forestry resources, which leads to decline in forest area and thus threaten the survival of wildlife species as the intraspecific competition among the wildlife species increases. Moreover, these wildlife species can also be apprehended easily by poachers and smugglers. This affects the biodiversity across the globe. In this paper, we have proposed and analyzed a nonlinear mathematical model to see the effect of deforestation caused by population and its pressure on wildlife species. The analysis of proposed model reveals that, as the parameters in respect to the increase in population pressure increase, wildlife species decrease. To support analytical findings, we have done numerical simulation

Dyslipidaemia & Framingham risk score: Tools for prediction of cardiovascular diseases as public health problem

Background: According to WHO, CVD is the number one cause of death globally and an estimated 17.5 million people died from CVDs in 2012, representing 31% of all global deaths. Dyslipidaemia with other cardio-metabolic risk factors are one of the major risk factors for cardiovascular diseases. This study was under taken to assess the prevalence of cardiovascular risk factors among the urban population aged 18 to 40 years. Methodology: This cross-sectional study was done at UHTC (Multan Nagar) in Meerut district from May 2014 to June 2015. 150 study participants aged 18 to 40 years of both sexes were recruited using simple random sampling. Data was collected using WHO’s STEPS criteria and modified close ended questionnaire. Data was analysed using Statistical Package for Social Sciences (SPSS v19).  Results: Overall prevalence of dyslipidaemia was, low HDL-c 58.7%, hypertriglyceridemia 36%, high TC:HDL-c ratio 24%, hypercholesterolemia 14.7% and high LDL cholesterol 8.0% & Framingham risk score of developing Coronary artery disease was 8.6% risk of 6% & above and 91.4% risk of 5% or less. Conclusion: The prevalence of two cardio-metabolic risk factors was quite high in both males and females and the association between Framingham risk score & dyslipidaemias were also statistically significant. Clearly indicating that those who were having dyslipidaemia in any form were at a higher risk of having coronary artery disease in the future

Study of 2D ion chamber array for angular response and QA of dynamic MLC and pretreatment IMRT plans

AbstractAimTo study of 2 Dimensional ion chamber array for angular response and its utility for quality assurance of dynamic multileaf collimator and pretreatment intensity modulated radiotherapy plans.Materials and MethodsThe MLC QA test patterns and IMRT plans were executed on 2D ion chamber array having 1020 vented pixel ionization chambers. The dynamic MLC QA test patterns were chair test, x–wedge, pyramid, open swipe field, garden fence and picket fence. Performance of Dynamic wedges was compared with physical wedges. For IMRT verification, five patients with localized prostate carcinoma were planned using dynamic IMRT technique. Angular response of MatriXX was measured by exposing the system from different gantry angles.ResultsDynamic MLC QA tests such as chair, x-wedge, pyramid, and open swipe field were successfully verified. MatriXX was not able to recognize the bar pattern of picket test and garden fence test. The response of MatriXX gradually decreases from 0° to 180° angles and it was 7.7% less at 180° angle. The dynamic wedge profiles were matching with corresponding physical wedge profiles. For pretreatment IMRT QA, the average dose difference between planned and measured dose was 1.26% with standard deviation of 1.06.ConclusionI'mRT MatriXX can be used for routine dynamic MLC and IMRT pretreatment QA but care should be taken while taking measurements in penumbra region because of its limited spatial resolution

Acute leukemia after cytotoxic treatment in a child with nephrotic syndrome

Renal involvement in acute lymphoblastic leukemia (ALL) occurs due to several factors including leukemic infiltration of the kidneys, therapy-related side effects such as tumor lysis syndrome, nephrotoxic drugs, and septicemias. A 3-year-old boy with nephrotic syndrome (NS) who was previously treated with prednisolone and cyclosporine A for 14 months after the initial diagnosis of NS, presented to the emergency department with fever, breathing difficulty, generalized edema, and body pain with pallor, without evidence of lymphadenopathy, hepatosplenomegaly, petechiae, or purpura. On investigation, peripheral blood smear showed blast cells >80% and bone marrow aspiration showed complete replacement of the marrow with L1 lymphoblasts, consistent with a diagnosis of ALL. The exact mechanism of developing acute leukemia after cytotoxic treatment has not been established; the possibility must be considered that the incidence of this malignant disease is increased after cytotoxic treatment for nonmalignant diseases

Comparison of 2D and 3D gamma evaluation method in patient specific intensity-modulated radiotherapy quality assurance

Background: In this study we have compared 2D and 3D gamma pass percentage for a variety of acceptance criteria for 40 step-and-shoot IMRT (intensity-modulated radiotherapy) plans. Methods: Treatment planning was done for 40 patient including head and neck, abdomen and pelvis simulated on the Siemens Healthcare GmBH CT simulator with images of 3 mm slice thickness using treatment planning system (TPS) (Monaco Version 5.11.03, Elekta medical system) using Monte Carlo algorithm. The gamma evaluation was done using PTW VeriSoft 8.1 which allowed us to perform 2D and 3D gamma index calculation, slice-by-slice comparison of measured and calculated dose distributions, measured dose was compared against the calculated DICOMRT dose on the OCTAVIUS 3D phantom from TPS. Results: The average 3D and 2D gamma passing in coronal planes were 96.61±0.45% and 96.27±0.78% for 5 mm/5% criteria, 93.74±4.17% and 91.9±4.88% for 3 mm/3% criteria, 85.83±7.58% and 82.41±8.06% for 2 mm/2% criteria and 62.8±9.42% and 59.18±9.52% for 1 mm/1% criteria respectively for all cases. The average gamma passing rate for 3D gamma analysis was 0.35%, 1.97 %, 3.97% and 5.78% higher when compared with 2D coronal planar analyses for 5 mm/5%, 3 mm/3%, 2 mm/2% and 1 mm/1% DTA criteria respectively. Conclusions: It is concluded in the study that 3 D gamma passing rate is higher compared to 2D gamma passing for head and neck, abdomen and pelvis cases

Effect of application of some organic amendments on soil properties, extractable micronutrients and their chemical fractions in a sandy loam soil

In a 120-day incubation study, farmyard manure (FYM), mushroom compost (MC), poultry manure (PM), vermi-compost (VC), biogas slurry (BS) and biochar from Lantana sp.; a common weed (BC) each added at 15 t ha-1 significantly increased soil electrical conductivity and organic C content, however, only VC failed to increase soil organic C content significantly but increased soil pH when compared with the control sample. Among organic amendments, FYM, MC, VC and BS increased DTPA-extractable Zn and Mn in soil significantly when compared with the control sample, while BC was significantly effective in regard to increasing both DTPA-extractable Mn and hot water soluble B when compared with the control sample. Application of FYM and MC significantly increased DTPA-extractable Cu and Fe, respectively when compared with the control sample. Simple correlation and path coefficient analysis were performed to identify key chemical fractions of micronutrients in soil having the direct and indirect effects on availability of micronutrients in organically amended soils. Based on soil extractable concentrations of micronutrients in organically amended soils, FYM appeared to be the best source of Zn, Cu and Mn, while MC could serve as the best source of Fe. Biochar from Lantana sp. may serve as a good source of B

Phishing Detection using Base Classifier and Ensemble Technique

Phishing attacks continue to pose a significant threat in today's digital landscape, with both individuals and organizations falling victim to these attacks on a regular basis. One of the primary methods used to carry out phishing attacks is through the use of phishing websites, which are designed to look like legitimate sites in order to trick users into giving away their personal information, including sensitive data such as credit card details and passwords. This research paper proposes a model that utilizes several benchmark classifiers, including LR, Bagging, RF, K-NN, DT, SVM, and Adaboost, to accurately identify and classify phishing websites based on accuracy, precision, recall, f1-score, and confusion matrix. Additionally, a meta-learner and stacking model were combined to identify phishing websites in existing systems. The proposed ensemble learning approach using stack-based meta-learners proved to be highly effective in identifying both legitimate and phishing websites, achieving an accuracy rate of up to 97.19%, with precision, recall, and f1 scores of 97%, 98%, and 98%, respectively. Thus, it is recommended that ensemble learning, particularly with stacking and its meta-learner variations, be implemented to detect and prevent phishing attacks and other digital cyber threats