Cold atmospheric plasma: Its time-dependent effects on the elimination of bacterial colony on periodontal manual scalers.

Background: This in vitro study investigated the time-dependent bactericidal effects of cold atmospheric argon plasma treatment of periodontal hand scalers as well as the scanning electron microscopic view of the scaler tip surfaces before and after plasma treatment. Materials and Methods: The study used 34 periodontal hand scalers which were divided into test and control groups. The scaler tips were inoculated with Escherichia coli and Staphylococcus aureus bacteria, following which the scalers in the control and test groups were subjected to conventional sterilization and argon plasma sterilization, respectively. Varying exposure times of plasma treatment were done on the test group samples to evaluate the minimum time required for complete sterilization. Subsequently, streaks were made on plate count agar using each of these instruments. The agar plates were then kept in an incubator for 24 h, following which bacterial colony count was assessed (colony-forming units/mL). Furthermore, the scanning electron microscopic (SEM) view of the scaler tip was studied before and after plasma treatment. Results: A complete elimination of bacterial load (Gram-positive as well as Gram-negative) from the instrument surface was achieved by the plasma exposure time of 15-20 s. SEM analysis did not show a significant difference before and after plasma treatment as not many organic residues were present on the scaler tip. Conclusion: Cold atmospheric pressure plasma is an efficient and time-saving method of sterilization, capable of destroying both Gram-positive and Gram-negative bacteria.

A Novel Dielectric Modulated Gate-Stack Double-Gate Metal-Oxide-Semiconductor Field-Effect Transistor-Based Sensor for Detecting Biomolecules.

In this article, the performance of n-type junctionless (JL) double-gate (DG) MOSFET-based biosensors with and without gate stack (GS) has been studied. Here, the dielectric modulation (DM) method is applied to detect biomolecules in the cavity. The sensitivity of n-type JL-DM-DG-MOSFET and n-type JL-DM-GSDG-MOSFET-based biosensors have also been evaluated. The sensitivity (ΔVth) improved in JL-DM-GSDG MOSFET/JL-DM-DG-MOSFET-based biosensors for neutral/charged biomolecules is 116.66%/66.66% and 1165.78%/978.94%, respectively, compared with the previously reported results. The electrical detection of biomolecules is validated using the ATLAS device simulator. The noise and analog/RF parameters are compared between both biosensors. A lower threshold voltage is observed in the GSDG-MOSFET-based biosensor. The Ion/Ioff ratio is higher for DG-MOSFET-based biosensors. The proposed GSDG-MOSFET-based biosensor demonstrates higher sensitivity than the DG-MOSFET-based biosensor. The GSDG-MOSFET-based biosensor is suitable for low-power, high-speed, and high sensitivity applications.

Simulation Study of Novel Charge-Plasma Based ArcTFET for Sensing the Breast Cancer Biomarker (C-erbB-2) in Serum.

In this work, a novel design of ArcTFET based on Charge-Plasma and Gate-Stack (CP-GS-ArcTFET) is proposed for the first time. The precise detection of breast cancer biomarker (C-erbB-2) through serum should not be limited by HEMT devices but should be explored with other novel devices also. In this regard, investigation in above-mentioned device is carried out for the detection of C-erbB-2 protein. In CP-GS-ArcTFET, various central angles ( θ ) are considered for observing the electrical parameters e.g., drain current ( [Formula: see text]), threshold voltage ( [Formula: see text]), and subthreshold slope (SS). The transconductance ( [Formula: see text]), its derivatives ( [Formula: see text] and [Formula: see text]), and analog performance indicators such as cut-off-frequency ( [Formula: see text]), gain-bandwidth-product (GBP), intrinsic-device-delay ( τ ), and transconductance-frequency-product (TFP) have also been analysed for these [Formula: see text]. The drain current, SS, and [Formula: see text] has been improved with the central angles. In the proposed device, the concept of charge equivalence of C-erbB-2 with its quantities (in [Formula: see text]/ml) is used for analysing sensitivity in Silvaco ATLAS TCAD. The device sensing is observed by changing C-erbB-2 concentrations in serum. The sensitivity concerning ON-current, OFF-current and current-ratio has been addressed for healthy and diseased individuals. The impact of θ on sensitivity is also observed. With increasing θ , the sensitivities [Formula: see text] and [Formula: see text] decrease; whereas, the sensitivity [Formula: see text] increases for the C-erbB-2 concentration of [Formula: see text]/ml. The [Formula: see text] and SS in CP-GS-ArcTFET are 4.5 ×109 and 35.97 mV/decade, respectively. The capability of CP-GS-ArcTFET to boost the performance is established with the decrease in leakage, enhancing [Formula: see text], steeper SS with the aids of [Formula: see text] reduction.

An Efficient and Robust Digital Fractional Order Differentiator Based ECG Pre-Processor Design for QRS Detection.

This paper presents an efficient infinite impulse response type digital fractional order differentiator (DFOD) based electrocardiogram (ECG) pre-processor to detect QRS complexes. First, an efficient optimizer namely, Antlion optimization algorithm is employed to solve the proposed DFOD design problem. Then, the designed DFOD is deployed in the pre-processing stage of a threshold independent R-peak detection technique. Finally, the proposed QRS complex detector is thoroughly assessed on the standard ECG datasets of MIT/BIH Arrhythmia, MIT/BIH ST Change, MIT/BIH Supraventricular Arrhythmia, European ST-T, QT, and T-Wave Alternans Challenge databases to show the wide sense practicability of the proposed DFOD-based QRS detector. The root-means-square magnitude error (RMSME) and the average group delay (τDD) metrics of the proposed DFOD are as low as -38.17 dB and 0.04 samples, respectively. The percentage of improvement in terms of RMSME metric compared to the best-reported approach is 15%. The overall sensitivity of 99.89% and positive predictivity of 99.88% are incurred by considering all the six databases. To the best of the authors' knowledge, it is the first time when the evolutionary algorithm based IIR-type DFOD is employed for the QRS complex detection and establishing its performance superiority. The results so obtained are compared with the results of all the recently reported QRS detectors. The proposed DFOD based ECG pre-processor has a great potential to robustly generate the feature signal related to the ECG QRS complex irrespective of the ECG morphology. Thus, the proposed DFOD based QRS detector can be employed in clinical ECG monitoring devices to augment the QRS detection performance.

Cat Swarm Optimization algorithm for optimal linear phase FIR filter design.

In this paper a new meta-heuristic search method, called Cat Swarm Optimization (CSO) algorithm is applied to determine the best optimal impulse response coefficients of FIR low pass, high pass, band pass and band stop filters, trying to meet the respective ideal frequency response characteristics. CSO is generated by observing the behaviour of cats and composed of two sub-models. In CSO, one can decide how many cats are used in the iteration. Every cat has its' own position composed of M dimensions, velocities for each dimension, a fitness value which represents the accommodation of the cat to the fitness function, and a flag to identify whether the cat is in seeking mode or tracing mode. The final solution would be the best position of one of the cats. CSO keeps the best solution until it reaches the end of the iteration. The results of the proposed CSO based approach have been compared to those of other well-known optimization methods such as Real Coded Genetic Algorithm (RGA), standard Particle Swarm Optimization (PSO) and Differential Evolution (DE). The CSO based results confirm the superiority of the proposed CSO for solving FIR filter design problems. The performances of the CSO based designed FIR filters have proven to be superior as compared to those obtained by RGA, conventional PSO and DE. The simulation results also demonstrate that the CSO is the best optimizer among other relevant techniques, not only in the convergence speed but also in the optimal performances of the designed filters.

Optimized hyper beamforming of linear antenna arrays using collective animal behaviour.

A novel optimization technique which is developed on mimicking the collective animal behaviour (CAB) is applied for the optimal design of hyper beamforming of linear antenna arrays. Hyper beamforming is based on sum and difference beam patterns of the array, each raised to the power of a hyperbeam exponent parameter. The optimized hyperbeam is achieved by optimization of current excitation weights and uniform interelement spacing. As compared to conventional hyper beamforming of linear antenna array, real coded genetic algorithm (RGA), particle swarm optimization (PSO), and differential evolution (DE) applied to the hyper beam of the same array can achieve reduction in sidelobe level (SLL) and same or less first null beam width (FNBW), keeping the same value of hyperbeam exponent. Again, further reductions of sidelobe level (SLL) and first null beam width (FNBW) have been achieved by the proposed collective animal behaviour (CAB) algorithm. CAB finds near global optimal solution unlike RGA, PSO, and DE in the present problem. The above comparative optimization is illustrated through 10-, 14-, and 20-element linear antenna arrays to establish the optimization efficacy of CAB.