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A quick grasp of the rules that governs the selection of the dose and its repetition is only feasible if the physician know the concept of posology ie. Susceptibility, remedy reaction and the law of dynamics.

Antenna is the key device of communication on stealth platform. It is the greatest contributor to the overall RCS. So, it is desired to reduce the radar signature of the antenna. In this paper, a novel antenna is designed using polarization converter metasurface. The polarization converter metasurface converts the polarization of the incident wave into its orthogonal component. This PCM structure is loaded around patch antenna to reduce the RCS of the antenna over wide frequency range. With this novel design, the overall RCS reduction bandwidth of 140.57% is obtained for the frequency range of 3.49 GHz – 20 GHz. In addition to this, the 10 dB RCS reduction bandwidth is obtained for the frequency ranges of 8.84 GHz – 10.42 GHz (16.41%) and 16.99 GHz – 17.81 GHz (4.71%). The design shows excellent angular stability for both TE and TM polarization. Discernible Bistatic Radar Cross Section reduction is obtained over a wide frequency range. Simulation and experimental results show that there is no degradation in antenna radiation pattern and other parameters. So, with this novel design the problem of obtaining wideband RCS reduction of a microstrip patch antenna is addressed without degradation in radiation pattern along with excellent angular stability for both the polarization modes.

Diltiazem hydrochloride (DLH) is a calcium channel blocker useful for the treatment of angina pectoris, arrhythmia, and hypertension. DLH having a short half-life needs frequent administration for successful treatment but this poses a problem of poor patient compliance. These requirements are served by elementary osmotic pump tablets (EOP) based controlled-release (CR) systems. Quality by design (QbD) approach assists in screening various factors with subsequent assessment of critical parameters that can have a major impact on the scalability of EOP. Tablets were formulated using wet granulation method followed by osmotic coating. Factorial design based QbD strategy aided in defining the risk assessment of influential variables such as hydrophilic polymers and osmotic coat component on the in-vitro release kinetics of the designed EOP tablets. These formulated EOP systems followed zero-order kinetics, a characteristic feature of EOPs. EOP tablets were formulated applying a systematic QbD statistical approach. The formulated DLH EOP systems with improved concentration-independent behavior helped to address the challenges of IR formulation. Application of QbD strategy in ascertaining the scalability of DLH EOP formulation would help pharmaceutical industries in the translation of EOP based drug delivery systems from R&D to market.

2-Pyrone-4,6-dicarboxylic acid (PDC) is a chemically stable metabolic intermediate of lignin that can be produced on a large scale by transforming bacteria. Novel biomass-based polymers based on PDC were synthesized by Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) and fully characterized by nuclear magnetic resonance, infrared spectroscopies, thermal analysis, and tensile lap shear strength measurements. The onset decomposition temperatures of these PDC-based polymers were all above 200 °C. In addition, the PDC-based polymers exhibited strong adhesive properties to various metal plates, with the highest adhesion to a copper plate of 5.73 MPa. Interestingly, this result was in contrast to our previous findings that PDC-based polymers weakly adhere to copper. Furthermore, when bifunctional alkyne and azide monomers were polymerized in situ under hot-press conditions for 1 h, the resulting PDC-based polymer displayed a similar adhesion to a copper plate of 4.18 MPa. The high affinity of the triazole ring to copper ions improved the adhesive ability and selectivity of the PDC-based polymers to copper while still maintaining the strong adhesive ability to other metals, which is conducive to enhancing the versatility of PDC-based polymers as adhesives.

The COVID-19 pandemic has caused large-scale outbreaks in more than 150 countries worldwide, causing massive damage to the livelihood of many people. The capacity to identify contaminated patients early and get unique treatment is quite possibly the primary stride in the battle against COVID-19. One of the quickest ways to diagnose patients is to use radiography and radiology images to detect the disease. Early studies have shown that chest X-rays of patients infected with COVID-19 have unique abnormalities. To identify COVID-19 patients from chest X-ray images, we used various deep learning models based on previous studies. We first compiled a data set of 2,815 chest radiographs from public sources. The model produces reliable and stable results with an accuracy of 91.6%, a Positive Predictive Value of 80%, a Negative Predictive Value of 100%, specificity of 87.50%, and Sensitivity of 100%. It is observed that the CNN-based architecture can diagnose COVID19 disease. The parameters’ outcomes can be further improved by increasing the dataset size and by developing the CNN-based architecture for training the model.

Cardiac and diabetic diseases are common and troublesome complications, leading to increased morbidity and mortality rate across the world. The proposed system performs stress analysis for cardiac health assessment from, heart rate variability (HRV) parameters of electrocardiogram (ECG) data. Data from 15 diabetic, 18 cardiac diseased, and 17 healthy subjects were collected in sitting position for imposing stress on the heart and supine position for stress-less data. Analysis is performed using HRV time domain values of sampled ECG data separately on three class of subjects. For this purpose, the mean of the difference (MoD) between sitting to supine is calculated. Our results shows that cardiac diseased subjects handle less stress with MoD value lowest among said three classes. The MoD values are highest and are positive for healthy subjects, and are moderate for diabetic subjects. Also NN50 and TINN parameters provide significant results as compared to other parameters. The results are cross verified with the help of diagnostic medical report in the hospital.

In this paper, the authors propose a human body model with the final goal of developing non-invasive blood glucose measurement. Most wearable devices today include antennas and signal processing circuitry capable of non-invasive measurements. Authors plan to extend this circuitry for non-invasive blood glucose measurement with microwave technique. An optimum design of a proposed system needs a human body model. The authors have studied and compared various proposed methods in the published literature for non-invasive blood glucose measurement. Comparative study has concluded that the published human body models have dielectric-based tissue modelling and it is difficult to change the blood glucose concentration in it. Hence, a new human body model is derived and implemented in this work. The proposed model has provision to imitate the human blood flow and can vary blood glucose concentration for simulation purposes. Its accuracy has been defined and the proposed model was compared with standard dataset. It is established in simulation that with changes in blood glucose concentration the dielectric constant, electrical conductivity and other electrical parameters of blood also vary. Based on this, the parameters of the antenna mounted on body are affected. An antenna is fabricated to compare the simulation results with the actual test. It is found that blood glucose variation on extreme ends of the glucose concentration has return loss variation in range of 4–6 dB, while in 170 mg/dL–450 mg/dL range the variation is in between 1 and 3 dB values.

A simulation environment is presented in this paper for the autonomous driving of a car, along with its respective obstacles, tracks and tests. Unity 3D, which is a cross-platform game development platform and engine, powers this environment by providing basic navigation controls along with the functions for creating and recording the car’s parameters as an input dataset. Using a convolutional neural network, the system predicts the future output, thus achieving complete autonomous navigation, compatible with any environment.

Cardiac health issues are severe and cause maximum death according to the survey done by “World Health Organization” (WHO). Cardiac diseases are caused due to family history, living style, diabetes, etc. Diagnosis of cardiac health prior to pathological conditions is highly important. Heart Rate Variability (HRV) is the technique used to study the cardiac abnormalities, which are related to fluctuation in the sympathetic and parasympathetic activities. In this paper, we compare the time domain, frequency domain and nonlinear parameters of heart rate variability for 73 subjects. Our results show that HRV parameters are high for normal subjects compared to diabetic subjects and lowest for cardiac subjects. The results are validated by diagnosis done through clinical processes. Thus non-invasive ECG and HRV techniques help to diagnose the subject before it causes the cardiac arrest.

This literature survey attempts to clarify different approaches considered to study the impact of the musical stimulus on the human brain using EEG Modality. Glancing at the field through various aspects of such studies specifically an experimental protocol, the EEG machine, number of channels investigated, feature extracted, categories of emotions, the brain area, the brainwaves, statistical tests, machine learning algorithms used for classification and validation of the developed model. This article comments on how these different approaches have particular weaknesses and strengths. Ultimately, this review concludes a suitable method to study the impact of the musical stimulus on brain and implications of such kind of studies.

Experimental Results: In this paper, a mathematical model is proposed in the paper for calculating the strength of neural signal conduction. The average neural signal conduction of diabetic cohort is found to be reduced compared to the non-diabetic cohort. The diabetic cohort with myocardial ischemia/infarction is found to have with least average neural signal conduction followed by the diabetic and hypertensive cohort. In case of hypertensive cohorts, the average neural signal conduction is found to be equal to that of the normal cohort. The effect of the neural conduction can be observed on the total power spectral density from the frequency domain AR analysis of R-R intervals. The average Left Ventricular Ejection Fraction (LVEF) index retrieved from the echocardiogram in all the cohorts is found to be consistent with the reduced neural signal conduction.

This paper presents the design of an Ultrawideband (UWB) multiple-input-multiple-output (MIMO) microstrip patch antenna array with Defected Ground Structures (DGS) to reduce the mutual coupling between the antenna array elements. Parametric study of the DGS dimension is done to deduce the optimum results. This technique gives low mutual coupling less than −17 dB over the frequency band of 3 to 11 GHz, good quality, spectrum efficiency, and reliability for Mobile communication. The antenna has been designed and simulated on Agilent Advanced Design System (ADS) EM simulator 2011.

In this paper, a novel antenna design for improvement of patch antenna gain and bandwidth has been proposed.The proposed antenna design is a V-slotted rectangular microstrip patch antenna for yielding improved gain bandwidth product suitable for WLAN and Wi-Max applications. The antenna operates at 5.9 GHz and has the maximum achievable bandwidth obtained about 1.04Ghz and gain of 6.22dBi .The microstrip patch is constructed using a single layer RT/duroid (5880) substrate, having dielectric constant er = 2.2 and loss tangent tan δ =0.001.A co-axial feed is used and the antenna is simulated using IE3D software from Zeland based on method of moments.

A Study on Soil and Vegetation Changes After Landslide in Kumaun Himalaya

Cardiac diseases are more prevalent in diabetics, hypertensives and diabetics with hypertentension. Prevention is possible if they are diagnosed at the preclinical stage. Such diagnostic practises can control mrotality and morbidity rate. Methods and subjects: Study is conducted with 27 normal subjects, 40 diabetic subjects with and without myocardial ischemia/infaction and 23 hypertensive subjects with and without diabetes. An attempt is made to find out the sympathetic power and it’s correlation to Left Ventricular Ejection Fraction in the diabetic subjects and hypertensive subjects with and without diabetes. All the cases are recorded at Fortis-S.L.Raheja hospital Mahim (W). ECG samples of 3-5 minute duration in sittng and supine position are collected. Randomness in age, class, sex and other parameters in ensured on the basis of the data collection as per the registration of the subjects.

Aspect-oriented modeling (AOM) has been developed to modularize crosscutting concerns appropriately in UML models. In software engineering, aspects are concerns that cut across multiple modules. In requirements modeling, we analyze interactions and potential inconsistencies. We use UML to model requirements in a use case driven approach. During requirements specification a structural model of the problem domain is captured with a class diagram. Use cases refined by activities are the join points to compose crosscutting concerns. Graph transformation systems provide analysis support for detecting potential conflicts and dependencies between rule-based transformations.

With the current trend of ever scaling up of computing power, the processing power of scientific computers will be in the range of petafl ops if the computing power obeys Moore’s law [5]. The systems with about one lakh parallel processors can be a reality.

Left ventricular diastolic dysfunction precipitates to cardiac disorders like myocardial infarction, left ventricular hypertrophy and cardiac artery disease. Raised diastolic left ventricular pressure results in inefficient pumping of the oxygenated blood, leads to LVDD modifying the heart structurally and functionally. An index computed from R-R interval, derived from two-lead, 3–5 minute ECG samples, provides a guideline to the echo-cardiologist. The index values of the diabetic subjects with LVDD are observed to be the lowest, that of diabetic subjects without LVDD are lower than the control group. The index proves to be early, safe, deployable, cost-effective and non-invasive confirmative diagnostic tool.