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This paper presents a comprehensive review of symmetrically shaped antennas in terms of antenna size, dielectric materials, resonating band, peak gain, radiation pattern, simulating tools, and their applications. In this article, flower shape, leaf shape, tree shape, fan shape, Pi shape, butterfly shape, bat shape, wearable, multiband, monopole, and fractal antennas are discussed. Further, a survey of previously reported bandwidth enhancement techniques of microstrip patch antenna like introduction of thick and lower permittivity substrate, multilayer substrate, parasitic elements, slots and notches, shorting wall, shorting pin, defected ground structure, metamaterial-based split ring resonator structure, fractal geometry, and composite right-hand/left-handed transmission line approach is presented. The physics of these techniques has been discussed in detail which is supported by circuit theory model approach.

This work implements a 1-bit FA circuit with the CMOS logic with XOR-XNOR combinations. For sum and carry, pass transistors are used to generate the output by combining with XOR, XNOR and CMOS design, and the optimised full adder is implemented with the help of LECTOR technique to control the leakage power. As scaling of CMOS technology has shown improvement in the speed but the leakage power are left to act as major effect. low power VLSI is a new discipline in which high power consumption is becoming an important criteria. But when refers to battery life, high power dissipation is not recommended for device applications. It affects performance, raises cooling expenses, and shortens battery capacity. The switching, dynamic and leakage power changes the inputs significantly. There are several typical reduction strategies available to lower the energy of circuits. By implementing the reduced FA with the leakage power control technique the number of transistors reduced than the normal full adder. The proposed design has static and total power of 5.08nw and 8.33uw for XNOR and for XOR of 12.36nw and 8.56uw. A FA is designed using these technique the obtained results for static and total power are 12.38uw 8.58uw. For the above circuits, a comparison of various static and total power dissipations is conducted. CADENCE-VIRTUOSO is used to simulate circuits using 90nm technology with a 1.2V power supply.

Cancer continues to be a leading cause of mortality worldwide, emphasizing the importance of early detection for effective treatment. Macroscopic methods like X‐ray and CT scans offer limited resolution and pose risks due to ionizing radiation exposure. In contrast, microscopic techniques such as histopathology require invasive biopsy samples and lack real‐time diagnostic capabilities. Bridging this gap, THz research offers a promising solution, utilizing nonionizing terahertz radiation to achieve superior resolution. To this end, a proposed microstrip antenna emerges as a cost‐effective and high‐resolution tool for enabling the accurate diagnosis and detection of superficial cancers. This novel approach could revolutionize medical involvement, leading to earlier cancer detection and improved patient outcomes. The THz antenna of size 526 μm × 536 μm designed using Computer Simulation Technology (CST) software radiates at 0.3 THz with a gain of 5 dB. The antenna, when placed in the model replicating human tissue (Phantom model) radiates at 0.88 THz with a return loss of −27 dB and a gain 10 dB. Whereas, the same antenna was designed and simulated with a model replicating human tissue with tumor, radiating at 0.88 THz with a return loss of −38 dB and gain of 9.6 dB. The optimization of the decision was done using the combination of K‐means and logistic regression algorithm to determine 95.06% efficiency. THz research offers a promising solution, utilizing nonionizing terahertz radiation to achieve superior resolution. To this end, a proposed Microstrip antenna emerges as a cost‐effective and high‐resolution tool for enabling the accurate diagnosis and detection of superficial cancers.

The vehicle emission is an important effectiveness measurement of any sustainable transportation development. Geometric and surface characteristics of pavement play an important role in reduction in fuel-economy and greenhouse gas emission. Deterioration of pavement surface is considered as the basic problem, which increases in fuel consumption, which leads to increase in emissions. The aim of the present research work is to provide better understanding on the role of pavement characteristics in green transportation initiates. Evaluating the effects of these emissions based on the roughness characteristics and the effect of gradient is the objective of the research. The field data collection surveys were conducted on two stretches in and around OU campus, viz., (i) OUCT road and (ii) DD colony A-lane. Roughness measurement surveys were conducted on these selected stretches by using MERLIN. The vehicular emissions of ALTO and SWIFT petrol cars were measured by using AVL Di-gas 444 analyzer. Comparisons were made for emissions on these different stretches against roughness and gradient of these two roads. The comparisons show considerable percentage increase in emissions on the stretches with higher roughness and gradient. As the objectives intended, the impact of pavement roughness on vehicular emission is related to roughness and gradient and the regression equations were developed to estimate four types of vehicular emissions. Based on the impact of gradient on vehicular emissions, the geometric design engineer can adopt the minimum level of gradient to be used while designing new roads.

In the recent trends, advancement in robotics and smartphone-based technology is creating a huge demand in the application areas of these technologies. These two technologies have already conquered many business and defense domains with increase in economic impact of the country. As per the statistics, the robotic service market rate is about to grow more than $713 million from 2018–2020. On the other side, the number of mobile app downloaded in 2018 is more than 197 billion. This paper presents an impact of integrating these two technologies with its existing status. The proposed system is mainly focused on designing and developing android app for controlling autonomous vehicles. Finally, this paper concludes with the advantages, disadvantages and some applications of the integration of these technologies.

BACKGROUND AND OBJECTIVESDengue fever presents with a diverse clinical spectrum. Although liver is not a major target organ, hepatic dysfunction is a well recognized feature. In this study we attempted to study the pattern of hepatic involvement in children with dengue and its association with disease severity.METHODOLOGYThis was a cross sectional study conducted at Cheluvamba hospital during the period of 1 year. Children <18 years of age with dengue Ns1 Ag and IgM positive were included in this study. After obtaining informed consent, a pre structured proforma was used to record the relevant information from each subject. After detailed clinical examination and haematological investigation children were categorized into three groups as dengue fever with no warning signs(DNWS), dengue fever with warning signs(DWWS) and severe dengue fever(SDF) according to WHO classification. Statistical analysis was done to know the strength of association between different clinical and biochemical variables and outcome of the disease.RESULTSThe mean age of the study population was 8.65 years with male preponderance. The mean total bilirubin, serum albumin, SGOT, SGPT, ALP, PT and INR were 0.76 mg/dl, 3.8g/dl, 233.18U/L, 118.15U/L, 200.65 U/L, 12.9s and 1.09 respectively. The mean SGOT was significantly higher than SGPT. The degree of deranged LFTs was significantly more in SDF group than DNWS and DWWS groups. Serum albumin was significantly decreased in children with SDF group correlating with disease severity, prognosis and outcome.CONCLUSIONHepatic dysfunction was present in all forms of dengue infection, with SGOT rising significantly more than SGPT. All biochemical liver parameters were significantly deranged in patients with severe dengue fever indicating prolonged illness and poor prognosis.

Sitting in the audience, their father Madhava Rao, a retired commander of the Indian Air Force, and mother Jyothsna, looked on with pride.

[...]the photographers have seen a big dip in their earnings.

Image classification is a machine learning task that involves assigning a label or class to an input image. In the context of the Infrared Solar Modules dataset, image classification can be used to identify anomalies in solar panel imagery. To achieve this goal, A convolutional neural network (CNN) model trained from scratch and fine-tuned on the Infrared Solar Modules dataset from ai4earthscience. Model includes techniques such as dropout and image data generation to enhance its accuracy on this specific dataset. With these methods, Model can achieve high accuracy in identifying solar panel anomalies even with low-size images.

Environmental and public health risks may arise from the presence of antibiotic residues, and specifically chloramphenicol in food samples. Therefore, it is quite important for researchers to detect chloramphenicol. In this work, PDA@CuFe 2 O 4 nanoparticles were synthesized and characterizsed. The PDA@CuFe 2 O 4 nanoparticles that had been prepared were used to create PDA@CuFe 2 O 4 /GCE, which was then used to detect chloramphenicol electrochemically in a 0.1 M phosphate buffer solution (pH 7). The study focused on the electrochemical properties, including changes in scan rate, sensing, and pH influence. Compared to the unmodified electrode, the PDA@CuFe 2 O 4 /GCE electrode exhibits better sensing properties. The advantage of the PDA@CuFe 2 O 4 /GCE electrode is that it shows unique electrochemical sensing toward individual and chloramphenicol detection; for instance, it has a low detection of 0.12µM for chloramphenicol detection and a high sensitivity of 16.25A µM −1  cm −2 for chloramphenicol detection. Graphical abstract