Optimization of W-band interaction structure developed using three different micro-fabrication techniques.

In this paper, an experimental investigation has been performed for the three different micro-fabrication techniques for optimization in the development process of the W-band planar beam-wave interaction structure. The W-band planar beam-wave interaction structure has been developed using three different micro-fabrication methods, namely micro-EDM (electric discharge milling), wire-EDM, and micro-milling. The effect of each fabrication method on the developed structure is analyzed using scanning electron microscopy and ZETA 3D optical microscopy for their optimization.

A multiplex DNA probe-based method for simultaneous identification of adulteration in meat samples.

Meat adulteration and admixing are prevalent malpractices observed in processed and raw meat samples, where the consumption of adulterated meat has been associated with food allergies, financial losses, and consumer distrust. Meat authentication is pivotal to address these concerns. The meat authenticity can be determined through genetic, protein, and immunological markers and advanced detection methods.

Breath-based biosensors and system development for noninvasive detection of diabetes: A review.

Background And Aims: In recent years, noninvasive techniques are becoming conspicuous for diabetes detection. Sweat, tear, saliva, urine and breath-based methods showing prominent results in breath acetone detection which is considered as a biomarker of diabetes. A concrete relationship between breath acetone and BG helps in the development of devices for diabetes detection.

Flexible piezo-resistive strain sensors using all-polydimethylsiloxane based hybrid nanocomposites for wearable electronics.

We report flexible piezo-resistive strain sensors composed of silver nanoparticle (Ag NP), graphene nanoplatelet (GNP), and multi walled carbon nanotube (MWCNT)-based ternary conductive hybrid nanocomposites as an active sensing layer fabricated using a simple solution processing method on flexible polydimethylsiloxane (PDMS) substrates. The electrical characteristics have been studied in PDMS-based flexible devices having three different kinds of structures, namely Ag NPs/MWCNT/PDMS, GNP/PDMS and Ag NPs/GNP/PDMS. The microscopic analysis of the hybrid nanocomposites is undertaken using field emission scanning electron microscopy.

Bandwidth Enhancement of a V-Band Klystron with Stagger-Tuned Multiple Radial Re-Entrant Cavities.

The V-band frequencies are becoming popular due to their application potential towards secure high data rate communications. This article reports bandwidth enhancement of an 11-cavity V-band Klystron amplifier employing staggered tuning. A systematic approach is presented to stagger-tune the periodically allocated multiple cavities of the Klystron operating at 60.

Facial expression recognition in videos using hybrid CNN & ConvLSTM.

The three-dimensional convolutional neural network (3D-CNN) and long short-term memory (LSTM) have consistently outperformed many approaches in video-based facial expression recognition (VFER). The image is unrolled to a one-dimensional vector by the vanilla version of the fully-connected LSTM (FC-LSTM), which leads to the loss of crucial spatial information. Convolutional LSTM (ConvLSTM) overcomes this limitation by performing LSTM operations in convolutions without unrolling, thus retaining useful spatial information.

Rational Molecular Designing of Aggregation-Enhanced Emission (AEE) Active Red-Emitting Iridium(III) Complexes: Effect of Lipophilicity and Nanoparticle Encapsulation on Photodynamic Therapy Efficacy.

Two "aggregation-enhanced emission" (AEE) active cyclometalated phosphorescent iridium(III) complexes, SM2 and SM4, were synthesized to evaluate the influence of lipophilicity on photodynamic therapy efficacy. Compared to SM2, SM4 had a higher logP due to the presence of naphthyl groups. As observed by confocal microscopy, this increased lipophilicity of SM4 significantly enhanced its cellular uptake in breast cancer cells.

Modular pulsed power supply for characterization of high-power microwave devices.

Developing a robust and reliable high-voltage (HV) pulse power system (PPS) is essential for the characterization and testing of microwave tubes and industrial applications. This paper presents the design, simulation, and implementation of a modular and versatile high-voltage pulse power supply used in microwave device characterization and testing. A microcontroller-based digitally controlled pulse generation unit is also developed to generate the trigger pulses for high-voltage switching modules to control the turn-ON and turn-OFF of the switching devices.

High sensitivity label-free detection of HER2 using an Al-GaN/GaN high electron mobility transistor-based biosensor.

This work reports rapid, label-free and specific detection of the HER2 antigen using a gallium nitride (GaN) high electron mobility transistor (HEMT). Thiol-based chemistry has been utilized to immobilize the corresponding HER2 antibody in the sensing area of the sensor. The formation of a gold-sulfur complex has been confirmed through Raman spectroscopy, giving a peak at around a wavelength of 260 cm.

A non-invasive ultrasensitive diagnostic approach for COVID-19 infection using salivary label-free SERS fingerprinting and artificial intelligence.

Clinical diagnostics for SARS-CoV-2 infection usually comprises the sampling of throat or nasopharyngeal swabs that are invasive and create patient discomfort. Hence, saliva is attempted as a sample of choice for the management of COVID-19 outbreaks that cripples the global healthcare system. Although limited by the risk of eliciting false-negative and positive results, tedious test procedures, requirement of specialized laboratories, and expensive reagents, nucleic acid-based tests remain the gold standard for COVID-19 diagnostics.

Selectivity enhancement for metal oxide (MOX) based gas sensor using thermally modulated datasets coupled with golden section optimization and chemometric techniques.

The ever-increasing demand for smart sensors for internet of things applications drove the change in outlook toward smart sensor system design. This paper focuses on using low-cost gas sensors [Metal Oxide (MOX)] for detection of more than one gas, which is otherwise complex due to poor selectivity of MOX sensors. In this work, detection of two gases, namely, ammonia (NH) and carbon monoxide (CO), using a single metal oxide (pristine tin oxide) sensor is demonstrated.

Emerging innovations in cold plasma therapy against cancer: A paradigm shift.

Cancer is one of the major causes of mortality, accounting for ∼ 9.5 million deaths globally in 2018. The spectrum of conventional treatment for cancer includes surgery, chemotherapy and radiotherapy.

Configurable switching behavior in polymer-based resistive memories by adopting unique electrode/electrolyte arrangement.

The difference in resistive switching characteristics by modifying the device configuration provides a unique operating principle, which is essential for both fundamental studies and the development of future memory devices. Here, we demonstrate the poly(methyl methacrylate) (PMMA)-based resistive switching characteristics using four different combinations of electrode/electrolyte arrangement in the device geometry. From the current-voltage () measurements, all the PMMA-based devices revealed nonvolatile memory behavior with a higher ON/OFF resistance ratio (∼10-10).

Three-dimensional DenseNet self-attention neural network for automatic detection of student's engagement.

Today, due to the widespread outbreak of the deadly coronavirus, popularly known as COVID-19, the traditional classroom education has been shifted to computer-based learning. Students of various cognitive and psychological abilities participate in the learning process. However, most students are hesitant to provide regular and honest feedback on the comprehensiveness of the course, making it difficult for the instructor to ensure that all students are grasping the information at the same rate.

Temporal deep learning architecture for prediction of COVID-19 cases in India.

To combat the recent coronavirus disease 2019 (COVID-19), academician and clinician are in search of new approaches to predict the COVID-19 outbreak dynamic trends that may slow down or stop the pandemic. Epidemiological models like Susceptible-Infected-Recovered (SIR) and its variants are helpful to understand the dynamics trend of pandemic that may be used in decision making to optimize possible controls from the infectious disease. But these epidemiological models based on mathematical assumptions may not predict the real pandemic situation.

Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays.

SARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems. Earlier in the pandemic, the absence of sufficient training data prevented effective deep learning (DL) solutions for the diagnosis of COVID-19 based on X-Ray data. Here, addressing the lacunae in existing literature and algorithms with the paucity of initial training data; we describe CovBaseAI, an explainable tool using an ensemble of three DL models and an expert decision system (EDS) for COVID-Pneumonia diagnosis, trained entirely on pre-COVID-19 datasets.

CSITime: Privacy-preserving human activity recognition using WiFi channel state information.

Human activity recognition (HAR) is an important task in many applications such as smart homes, sports analysis, healthcare services, etc. Popular modalities for human activity recognition involving computer vision and inertial sensors are in the literature for solving HAR, however, they face serious limitations with respect to different illumination, background, clutter, obtrusiveness, and other factors. In recent years, WiFi channel state information (CSI) based activity recognition is gaining momentum due to its many advantages including easy deployability, and cost-effectiveness.

Fabrication, Characterization, and Modeling of an Aluminum Oxide-Gate Ion-Sensitive Field-Effect Transistor-Based pH Sensor.

The ion-sensitive field-effect transistor (ISFET) is a popular technology utilized for pH sensing applications. In this work, we have presented the fabrication, characterization, and electrochemical modeling of an aluminum oxide (AlO)-gate ISFET-based pH sensor. The sensor is fabricated using well-established metal-oxide-semiconductor (MOS) unit processes with five steps of photolithography, and the sensing film is patterned using the lift-off process.

Simulation and machine learning modelling based comparative study of InAlGaN and AlGaN high electron mobility transistors for the detection of HER-2.

The detection of the cancer biomarker human epidermal growth factor receptor 2 (HER-2) has always been challenging at the early stages of cancer due to its very small presence. A systematic study of biosensors to achieve optimum sensitivity is of paramount significance. Thus, in this paper, we report a simulation study and machine learning (ML) based model for the comparative analysis of indium aluminum gallium nitride (InAlGaN) and aluminum gallium nitride (AlGaN) based high electron mobility transistors (HEMTs) for the detection of HER-2.

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity.

Rapid and accurate nucleobase detection using FnCas9 and its application in COVID-19 diagnosis.

Rapid detection of DNA/RNA pathogenic sequences or variants through point-of-care diagnostics is valuable for accelerated clinical prognosis, as witnessed during the recent COVID-19 outbreak. Traditional methods relying on qPCR or sequencing are tough to implement with limited resources, necessitating the development of accurate and robust alternative strategies. Here, we report FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that utilizes a direct Cas9 based enzymatic readout for detecting nucleobase and nucleotide sequences without trans-cleavage of reporter molecules.

Chemical-free and scalable process for the fabrication of a uniform array of liquid-gated CNTFET, evaluated by KCl electrolyte.

Biosensors based on liquid-gated carbon nanotubes field-effect transistors (LG-CNTFETs) have attracted considerable attention, as they offer high sensitivity and selectivity; quick response and label-free detection. However, their practical applications are limited due to the numerous fabrication challenges including resist-based lithography, in which after the lithography process, the resist leaves trace level contaminations over the CNTs that affect the performance of the fabricated biosensors. Here, we report the realization of LG-CNTFET devices using silicon shadow mask-based chemical-free lithography process on a 3-in.

Highly selective sensor for the detection of Hg ions using homocysteine functionalised quartz crystal microbalance with cross-linked pyridinedicarboxylic acid.

This study reports an insightful portable vector network analyser (VNA)-based measurement technique for quick and selective detection of Hg ions in nanomolar (nM) range using homocysteine (HCys)-functionalised quartz-crystal-microbalance (QCM) with cross-linked-pyridinedicarboxylic acid (PDCA). The excessive exposure to mercury can cause damage to many human organs, such as the brain, lungs, stomach, and kidneys, etc. Hence, the authors have proposed a portable experimental platform capable of achieving the detection in 20-30 min with a limit of detection (LOD) 0.

Silicon Shadow Mask Technology for Aligning and Sorting of Semiconducting SWNTs for Sensitivity Enhancement: A Case Study of NO Gas Sensor.

Single-walled carbon nanotubes (SWNTs) are incorporated in different device configurations such as chemiresistors and field-effect transistors (FETs) as a sensing element for the fabrication of highly sensitive and specific biochemical sensors. For this purpose, sorting and aligning of semiconducting SWNTs between the electrodes is advantageous. In this work, a silicon shadow mask fabricated using conventional semiconductor processes and silicon bulk micromachining was used to make metal contacts over SWNTs with a minimum feature of 1 μm gap between the electrodes.

Hierarchical Doped Gelatin-Derived Carbon Aerogels: Three Levels of Porosity for Advanced Supercapacitors.

Nitrogen-doped graphene-based aerogels with three levels of hierarchically organized pores were prepared via a simple environmentally friendly process, and successfully tested in supercapacitor applications. Mesopores and macropores were formed during the aerogel preparation followed by carbonization and its chemical activation by potassium hydroxide (KOH). These mesopores and macropores consist of amorphous carbon and a 3D graphene framework.