Gating Technique Research Articles

Deep learning for improving ZTE MRI images in free breathing

IntroductionDespite a growing interest in lung MRI, its broader use in a clinical setting remains challenging. Several factors limit the image quality of lung MRI, such as the extremely short T2 and T2* relaxation times of the lung parenchyma and cardiac and breathing motion. Zero Echo Time (ZTE) sequences are sensitive to short T2 and T2* species paving the way to improved “CT-like” MR images. To overcome this limitation, a retrospective respiratory gated version of ZTE (ZTE4D) which can obtain images in 16 different respiratory phases during free breathing was developed. Initial performance of ZTE4D have shown motion artifacts. To improve image quality, deep learning with fully convolutional neural networks (FCNNs) has been proposed. CNNs has been widely used for MR imaging, but it has not been used for improving free-breathing lung imaging yet. Our proposed pipeline facilitates the clinical work with patients showing difficulties/uncapable to perform breath-holding, or when the different gating techniques are not efficient due to the irregular respiratory pace. Materials and methodsAfter signed informed consent and IRB approval, ZTE4D free breathing and breath-hold ZTE3D images were obtained from 10 healthy volunteers on a 1.5 T MRI scanner (GE Healthcare Signa Artist, Waukesha, WI). ZTE4D acquisition captured all 16 phases of the respiratory cycle. For the ZTE breath-hold, the subjects were instructed to hold their breath in 5 different inflation levels ranging from full expiration to full inspiration. The training dataset consisting of ZTE-BH images of 10 volunteers was split into 8 volunteers for training, 1 for validation and 1 for testing. In total 800 ZTE breath-hold images were constructed by adding Gaussian noise and performing image transformations (translations, rotations) to imitate the effect of motion in the respiratory cycle, and blurring from varying diaphragm positions, as it appears for ZTE4D. These sets were used to train a FCNN model to remove the artificially added noise and transformations from the ZTE breath-hold images and reproduce the original quality of the images. Mean squared error (MSE) was used as loss function. The remaining 2 healthy volunteer's ZTE4D images were used to test the model and qualitatively assess the predicted images. ResultsOur model obtained a MSE of 0.09% on the training set and 0.135% on the validation set. When tested on unseen data the predicted images from our model improved the contrast of the pulmonary parenchyma against air filled regions (airways or air trapping). The SNR of the lung parenchyma was quantitatively improved by a factor of 1.98 and the CNR lung- blood, which is indicating the visibility of the intrapulmonary vessels, was improved by 4.2%. Our network was able to reduce ghosting artifacts, such as diaphragm movement and blurring, and enhancing image quality. DiscussionFree-breathing 3D and 4D lung imaging with MRI is feasible, however its quality is not yet acceptable for clinical use. This can be improved with deep learning techniques. Our FCNN improves the visual image quality and reduces artifacts of free-breathing ZTE4D. Our main goal was rather to remove ghosting artifacts from the ZTE4D images, to improve diagnostic quality of the images. As main results of the network, diaphragm contour increased with sharper edges by visual inspection and less blurring of the anatomical structures and lung parenchyma. ConclusionWith FCNNs, image quality of free breathing ZTE4D lung MRI can be improved and enable better visualization of the lung parenchyma in different respiratory phases.

Four-input-C-element-based multiple-node-upset-self-recoverable latch designs

As microelectronics technology has continued to progress, the multiple-node upset (MNU), caused by the single-particle and charge-sharing effects, has gradually become one of the most important factors affecting chip reliability. To enhance the reliability of these latches, a TNU completely self-recoverable (TNUCR) latch is first proposed in this paper, mainly consisting of five interlocked four-input C-elements (CEs) and inverters, which are cross-connected to form a ring. For any individual CE, due to the presence of a feedback loop, the value of its output is inverted and becomes the input to the other four CEs, which enables the latch to self-recover from all TNUs. Second, we propose an improved low-cost TNU completely self-recoverable (LCTNUCR) latch. This latch replaces the inverter with a four-input CE and uses a high-speed transmission path (HSTP), which can more rapidly self-recover from all TNU situations. It is demonstrated by experimental results that the two proposed latches are not only TNU tolerant but also TNU self-recoverable. Moreover, based on special design and the adoption of clock gating techniques, the proposed TNUCR latch has a delay-power-area product reduction of about 41.05%, while the proposed LCTNUCR latch has a DPAP reduction of about 71.30% compared to the latest representative TNU hardened latch.

Isolated attosecond pulse generation from the interaction of intense laser pulse with solid density plasma

This article gives an overview on recent progress in the generation of isolated attosecond pulse and isolated half-cycle attosecond pulse. As an isolated attosecond pulse is preferred in the pump-probe experiments for the dynamics of electrons in atom, molecule, or solid, we focus on the isolated attosecond pulses generation from the intense laser pulses interaction with solid density plasma, which have higher intensity and narrower pulse width than that generated in the interaction of laser pulse with gas target. We have firstly discussed the physical mechanism of isolated attosecond pulse generation, such as polarization gating, two-color laser pulses, attosecond light houses, and capacitor target mechanism. In the polarization gating mechanism, we have discussed the physical mechanism that the higher-order harmonic efficiency decreases with the increase of ellipticity. Both the coherent synchrotron radiation mechanism and the relativistic oscillation mechanism can control the intensity of high-order harmonic generation by controlling ellipticity of the incident laser pulse. We also discussed other mechanism to enhance the isolated attosecond pulse bursts in detail. Secondly, we focus on the isolated half-cycle attosecond pulses, which can also be generated from the intense laser pulses interaction with solid density plasma by double foil target mechanism, gas-foil target mechanism, cascaded generation mechanism, microstructured target mechanism, and three-color laser pulse mechanism. The half-cycle attosecond pulses can be useful for probing ultrafast electron dynamics in matter via asymmetric manipulation. Accordingly we discussed the physcial mechanism, experimental feasibility, calibration measurement, and application prospect of half-cycle attosecond pulse in this article. The above mechanism can directly generate ultra-intense isolated attosecond pulses in the transmission direction without requiring extra filters and gating techniques. The dense electron sheet is crucial for the generation of intense attosecond pulses in different mechanisms, such as coherent wake emission (CWE), relativistic oscillating mirror (ROM) and coherent synchrotron emission (CSE). In this article, all the mechanism for half-cycle attosecond pulses generation can ensure only one electron sheet contributing to the transmitted radiation. We discuss the theoretical model of nanobunching of the electron sheet, which shows that the relativistic oscillation is crucial for the formation of electron sheet.

Unusual similarity of DNA solvation dynamics in high-salinity crowding with divalent cations of varying concentrations.

Double-stranded DNA bears the highest linear negative charge density (2e- per base-pair) among all biopolymers, leading to strong interactions with cations and dipolar water, resulting in the formation of a dense 'condensation layer' around DNA. Interactions involving proteins and ligands binding to DNA are primarily governed by strong electrostatic forces. Increased salt concentrations impede such electrostatic interactions - a situation that prevails in oceanic species due to their cytoplasm being enriched with salts. Nevertheless, how these interactions' dynamics are affected in crowded hypersaline environments remains largely unexplored. Here, we employ steady-state and time-resolved fluorescence Stokes shifts (TRFSS) of a DNA-bound ligand (DAPI) to investigate the static and dynamic solvation properties of DNA in the presence of two divalent cations, magnesium (Mg2+), and calcium (Ca2+) at varying high to very-high concentrations of 0.15 M, 1 M and 2 M. We compare the results to those obtained in physiological concentrations (0.15 M) of monovalent Na+ ions. Combining data from fluorescence femtosecond optical gating (FOG) and time-correlated single photon counting (TCSPC) techniques, dynamic fluorescence Stokes shifts in DNA are analysed over a broad range of time-scales, from 100 fs to 10 ns. We find that while divalent cation crowding strongly influences the DNA stability and ligand binding affinity to DNA, the dynamics of DNA solvation remain remarkably similar across a broad range of five decades in time, even in a high-salinity crowded environment with divalent cations, as compared to the physiological concentration of the Na+ ion. Steady-state and time-resolved data of the DNA-groove-bound ligand are seemingly unaffected by ion-crowding in hypersaline solution, possibly due to ions being mostly displaced by the DNA-bound ligand. Furthermore, the dynamic coupling of cations with nearby water may possibly contribute to a net-neutral effect on the overall collective solvation dynamics in DNA, owing to the strong anti-correlation of their electrostatic interaction energy fluctuations. Such dynamic scenarios may persist within the cellular environment of marine life and other biological cells that experience hypersaline conditions.

A Reconfigurable CNN-Based Accelerator Design for Fast and Energy-Efficient Object Detection System on Mobile FPGA

In limited-resource edge computing circumstances such as on mobile devices, IoT devices, and electric vehicles, the energy-efficient optimized convolutional neural network (CNN) accelerator implemented on mobile Field Programmable Gate Array (FPGA) is becoming more attractive due to its high accuracy and scalability. In recent days, mobile FPGAs such as the Xilinx PYNQ-Z1/Z2 and Ultra96, definitely have the advantage of scalability and flexibility for the implementation of deep learning algorithm-based object detection applications. It is also suitable for battery-powered systems, especially for drones and electric vehicles, to achieve energy efficiency in terms of power consumption and size aspect. However, it has the low and limited performance to achieve real-time processing. In this article, optimizing the accelerator design flow in the register-transfer level (RTL) will be introduced to achieve fast programming speed by applying low-power techniques on FPGA accelerator implementation. In general, most accelerator optimization techniques are conducted on the system level on the FPGA. In this article, we propose the reconfigurable accelerator design for a CNN-based object detection system on the register-transfer level on mobile FPGA. Furthermore, we present RTL optimization design techniques that will be applied such as various types of clock gating techniques to eliminate residual signals and to deactivate the unnecessarily active block. Based on the analysis of the CNN-based object detection architecture, we analyze and classify the common computing operation components from the Convolutional Neuron Network, such as multipliers and adders. We implement a multiplier/adder unit to a universal computing unit and modularize it to be suitable for a hierarchical structure of RTL code. The proposed system design was tested with Resnet-20 which has 23 layers and it was trained with the dataset, CIFAR-10 which provides a test set of 10,000 images in several formats, and the weight data we used for this experiment was provided from Tensil. Experimental results show that the proposed design process improves the power efficient consumption, hardware utilization, and throughput by 16%, up to 58%, and 15%, respectively.

A New Technology for Reducing Dynamic Power Consumption in 8-Bit ALU Design

Clock gating is an effective way to decrease dissipated power in synchronous design. The most effective way to do this is by masking the clock that turns toward the unused part of design. In this paper, a comparative evaluation of power consumption in existing clock gating techniques in Arithmetic Logical Unit (ALU) design was achieved. an innovative signal clock gating method offers extra immunity in the direction of the present issue in an accessible mechanism. A Gated Clock Generation designs using a tri-state connection and logic gate, generated by the set of bubbled input with NAND gate, is used for the latest suggested clock gating. This design saves power even when the clock is at applying to the target module. Complete power analysis reveals that the proposed technique has an effect on the dynamic power that decreases total power consumption up to 24.90% relative to traditional power. All experiments are done in arithmetic logic unit design. 130 nm standard logic libraries have been used for implementation in order to achieve ALU frameworks. The ALU design architecture was developed using the Verilog HDL, and the simulations are performed utilizing ModelSim-Altera 10.0c (Quartus II 11.1) Starter Version.

Reducing PTV margins for prostate SBRT with motion compensation and gating techniques.

The purpose of this study is to investigate the dosimetric accuracy of prostate SBRT when motion is considered. To account for target movement, motion compensation and gating techniques were investigated with PTV margins reduced to 2mm. To allow for dosimetric measurements a Delta4 phantom, Gafchromic film, and Hexamotion motion platform were utilized. Four motion files were utilized that represent a range of motions. Analysis of measured prostate motions for fifteen patients was performed to ensure detected motions were similar to those previously reported and motion files utilized were suitable. Five patient plans were utilized to allow for the effects of MLC and target motion interplay to be investigated. For both motion compensation and gating techniques, plans were delivered to the stationary phantom and for each of four motion types with/without compensation/gating enabled. Using a 3%, 2mm and 80% threshold gamma criteria, film measurements had an average pass rate of 80.5% for uncorrected deliveries versus 96.0% for motion compensated deliveries. For gated techniques average pass rates increased from 89.9% for uncorrected to 94.8% with gating enabled. Measurements with the Delta4 arrays were analyzed with a 3%, 2mm and 10% threshold dose. An average pass rate of 83.8% was measured for uncorrected motions versus 94.8% with motion compensation. For the gated technique an average pass rate of 87.2% was found for uncorrected motions versus 96.9% with gating enabled. These results show that very high gamma pass rates are achievable when motion compensation or gating techniques are applied. When target motion is not accounted for shifts up to 5mm in planned versus delivered isodose distributions were found. However, when motion compensation, or gated techniques were applied, much smaller differences between planned and delivered isodose distributions were found. With these techniques dose delivery accuracy is greatly improved, allowing for PTV margins to be reduced.

Machine Learning-Based Screening and Measurement to Measurement Association for Navigation in GNSS Spoofing Environment

Global navigation satellite system (GNSS) provides reliable positioning across the globe. However, GNSS is vulnerable to deliberate interference problem like spoofing, which can cause fake navigation. This article proposes navigation in a GNSS spoofing environment by taking the received power, correlation distortion function, and pseudorange measurement observation space into account. In the proposed approach, both actual and interference measurements are considered a set. Machine learning screens the authentic measurements from the accessible set using parameters such as received power and correlation function distortion. To maintain the track and navigate the GNSS’s time-varying kinematics, we used a combination of the gating technique within the Kalman filter framework and logic-based track management. The machine learning classifiers like support vector machines (SVMs), neural networks (NNs), ensemble, nearest neighbor, and decision trees are explored, and we observe that linear SVM and NN provide a test accuracy of 98.20%. A time-varying position-pull off strategy is considered, and the metrics like position RMSE and track failure are compared with the conventional M-best algorithm. The results show that for four authentic measurements and spoof injections, there are only a few track failures. In contrast, even with an increase in spoof injections, track failures are zero in the case of six authentic measurements.

Design and Performance Improvement of 10T SRAM Using Sleepy Keeper and Drain Gating Techniques

This paper presents the sleepy keeper and drain gating technique to improve the performance of 10T SRAM cell. The behavior of 10T SRAM cell is evaluated using benchmarked industry standard GPDK 45nm Technology Node of the Cadence Virtuoso EDA tool. The performance is analyzed in terms of dynamic and static parameters of 10T SRAM cell and compared with 6T SRAM, where find the reduction in dynamic power and static power dissipation. Besides this, observed the reduction in leakage current using sleepy keeper and drain gating technique. The proposed modified topology applicable in single-ended write and differential read operation. The read delay product and the write delay product is decreased by 36.7 % and 67.5 %, respectively. The major goal of the suggested architecture is to provide the improved stability, reduction in delay, as well as reduction in leakage current.

Transition to Fast Whole-Body SPECT/CT Bone Imaging: An Assessment of Image Quality.

To investigate the impact of reduced SPECT acquisition time on reconstructed image quality for diagnostic purposes. Data from five patients referred for a routine bone SPECT/CT using the standard multi-bed SPECT/CT protocol were reviewed. The acquisition time was 900 s using gating technique; SPECT date was resampled into reduced data sets of 480 s, 450 s, 360 s and 180 s acquisition duration per bed position. Each acquisition time was reconstructed using a fixed number of subsets (8 subsets) and 4, 8, 12, and 16 iterations, followed by a post-reconstruction 3D Gaussian filter of 8 mm FWHM. Two Nuclear Medicine physicians analysed all images independently to score image quality, noise and diagnostic confidence based on a pre-defined 4-point scale. Our result showed that the most frequently selected categories for 480 s and 450 s images were good image quality, average noise and fair confidence, particularly at lower iteration numbers 4 and 8. For the shortened acquisition time of 360 s and 180 s, statistical significance was observed in most reconstructed images compared with 900 s. The SPECT/CT can significantly shorten the acquisition time with maintained image quality, noise and diagnostic confidence. Therefore, acquiring data over 480 s and 450 s is feasible for WB-SPECT/CT bone scans to provide an optimal balance between acquisition time and image quality.

Design and Lifetime Estimation of Low-Power 6-Input Look-Up Table Used in Modern FPGA

Due to technological advancements and voltage scaling, leakage power has become an important concern in CMOS design. The implementation of a field-programmable gate array (FPGA) circuit utilizes a portion of the FPGA’s resources as compared to an application-specific integrated circuit (ASIC). Both the utilized and unutilized parts of the FPGA dissipate leakage power. In this work, two dynamic power gating techniques, PSG-1 and PSG-2, are proposed, which are able to reduce the leakage power of the 6-input look-up table (LUT) used in the Xilinx Spartan-6 series. The obtained results show that the proposed approaches PSG-1 and PSG-2 reduce average leakage power by 54.61% and 66.69%, respectively, at the expense of nominal area and delay overhead. The proposed method is also capable of lowering the average total power of the 6-input LUT. The suggested PSG-1 and PSG-2 approaches reduce average power by 53.75% and 60.83%, respectively. However, header-based power supply gating is extremely vulnerable to the negative-bias temperature instability (NBTI) aging effect and, due to this, the lifetime of the circuit is reduced considerably. Therefore, in this work, lifetime estimation-based analysis is performed by varying the stress probability of the sleep transistor. The results show that the LUT with PSG-1 and PSG-2 techniques has a lifetime of 4.55 years and 11.13 years, respectively. The stress time of the sleep transistor is 50% for the PSG-1 technique and 25% for the PSG-2 technique, respectively.

PTTS: Power-aware tensor cores using two-sided sparsity

Deep Neural networks (DNNs) have become the compelling solution for a broad range of applications such as automatic translation, advertisement recommendation, and speech recognition. Matrix multiplication is the fundamental operation used in various classes of DNNs. Introduction of tensor cores (TCs) in NVIDIA GPGPUs particularly aims at acceleration of neural networks. A TC is a specialized unit dedicated to compute matrix-multiply-and-accumulate (MMA) operations. State-of-the-art DNNs are known to be power-hungry and compute-intensive due to increasing depth of networks, i.e. multiple layers with massive number of neurons. This causes excessive energy in TCs.Sparse neural networks have emerged as an effective solution to address massive amount of computations in DNNs. While sparsity is widely used for acceleration of DNNs, only a handful of studies focused on energy aspect of sparse DNNs and energy-efficient architectures for TCs are scarce. We exploit sparsity in DNNs and propose power gating multipliers with sparse activations or weights. We show that sparsity occurs in TCs for short intervals and conventional power gating techniques cannot fully exploit these idle intervals mainly due to overhead of power gating. To mitigate the overhead of power gating, we propose power-aware tensor cores using two-sided sparsity (PTTS) which monitors inputs of multipliers and turns them off only if inputs remain sparse for long intervals. We also propose an architectural technique that shuffles multiplications to pack idle intervals and increase opportunities for power gating. We introduce a low-cost and implementation-efficient sparse input operand interconnect to change order of effectual multiplications. Our proposed techniques combined are able to save energy by 68% in Tensor Cores with negligible impact on performance while maintaining accuracy.

Identification of Minimal Residual Disease in B-Acute Lymphoblastic Leukaemia Using Uniform Manifold Approximation Projection

Background and objective: Acute Lymphoblastic Leukaemia (ALL) is the most common childhood cancer, with B lineage ALL accounting for approximately 85% of cases. Minimal residual disease (MRD) levels during induction therapy are important prognostic biomarkers that allow patient stratification dependent on their risk of relapse. MRD is quantified by molecular analyses of antigen receptor gene rearrangements or by flow cytometric evaluation of aberrant immunophenotypes. The latter method is increasingly being used worldwide, due to its reduced cost, its provision of predictive biomarkers for antigen therapies and the inclusion of both MRD methodologies in contemporary clinical trials. However, accurate detection of MRD by flow cytometry is complex, time-consuming and relies heavily on user training and expertise. Machine learning has been evolving in the field, with the aim of superseding manual analysis of Flow MRD data. This study aimed to test the ability of the unsupervised machine learning dimensional reduction algorithm, Uniform Manifold Approximation Projection, (UMAP) to visualise and accurately quantify 'MRD islands' from normal cell populations with minimal human intervention. Methods: Flow cytometric data from bone marrow samples from children entered on the UKALL2011 clinical trial were used in the study. For B lineage ALL, the protocol included the identification of a leukaemia associated immunophenotype at diagnosis using 2 antibody combinations and 'on treatment' samples were then ran with the most appropriate antibody tube. In this study, we used data from Euro tube 1 which included the antibodies, CD20 FITC, CD38 PE, CD34 PerCP, CD10 PE-Cy7, CD19 APC, CD45 APC-Cy7 and the nuclear dye, Syto 41, tagged with Pacific Blue. FCS files were uploaded to Cytobank and pre-gated for CD19 positive cells prior to running the UMAP algorithm. Each data set was ran alongside data from 10 normal marrows stained with Euro tube 1. Results: Initially, a selection of samples with varying MRD levels (n=6) were ran using UMAP with a range of minimum distance and number of neighbours parameters. A minimum distance of 0.1 and number of neighbours of 13 was the optimal UMAP settings to produce a very clear separation of MRD islands from healthy cells populations across all samples. (Figure 1). These setting were then used for 341 B-ALL MRD samples at different time points day 8 (n=116), day 15 (n=32), days 29 (n=118), weeks 6-20 (n= 75). MRD levels from UMAP were compared to those generated by the gold standard sequential gating. Excellent concordance was seen, as demonstrated by an R2 value of 0.99 (linear correlation). For 'on treatment samples', UMAP showed excellent accuracy with sensitivity and specificity values of 93% and 100%, respectively. Positive predictive values were 100% while negative predictive values were 94% due to UMAP analysis failing to identify an MRD island in 11 'on treatment' samples, 9 at day 8 and 2 at day 28. The average UMAP run time was less than 2 minutes. Conclusion: Detection of MRD using the UMAP algorithm showed an excellent correlation with the gold standard sequential gating technique. False negatives were due to overlap of antigen expression with normal cells and/or low ALL cell numbers. Current Flow MRD methodologies use 8 or more antibodies and higher target cell numbers, which may reduce the false negative UMAP call rate. In summary, UMAP has promising ability to simplify the downstream data analyses of Flow MRD, overcoming the extensive training needed, human subjectivity and will be time and thus cost saving. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Pathological Assessment of Cardiac Radioablation to the Cavotricuspid Isthmus without Gating and Real-Time Tracking in Mini Pigs

<h3>Purpose/Objective(s)</h3> Cardiac arrhythmias are usually treated with invasive, time consuming catheter ablation techniques. While recently stereotactic body radiotherapy (SBRT) is an emerging non-invasive treatment in the management of cardiac arrhythmias. Although we used the motion management by compression techniques for the reduction of the internal target volume, we did not use the gating and real-time tracking techniques. We assessed the necessity of the precise target planning and monitoring the complex respiratory and cardiac motion to cardiac radioablation to the cavotricuspid isthmus (CTI) by pathological assessment in mini pigs. <h3>Materials/Methods</h3> All animal procedures were approved by institutional animal care and use committee and performed in full compliance with its guidelines. Four mini pigs underwent magnetic resonance (MR) and electrophysiology assessment using electroanatomic mapping (EAM) before and 3 months after SBRT with single-fraction doses of 25Gy. The target of CTI was defined by cardiologist. We defined the internal margin (IM), respiratory: SI 7 mm, AP 3 mm, LR 3 mm, cardiac motion: 3 mm in all direction and set up margin (SM): 5 mm in all direction. Then, planning target volume (PTV) margin: IM + SM = SI 15 mm, AP 10mm, LR 10 mm were added to the target, defining PTV.MR examination, including diffusion-weighted, dynamic Gd-enhanced, spectroscopy, and T2-weighted images were performed before and 3 months after SBRT, followed by histopathologic examination. Radiation oncologist and radiologist evaluated the detectability and image quality for the irradiated site. MRI findings of the CTI radioablation lesion was compared to electrophysiology and histopathology findings. <h3>Results</h3> A total dose of 25 Gy was successfully delivered to PTV in a single procedure in all mini pigs. EAM visualized the irradiated site and confirmed clockwise conduction block across the CTI. MRI could not detect the radiation injury clearly. Pathological examinations were analyzed after 3 months of follow-up, fibrous hyperplasia and capillary hyperplasia were observed around the nerve bundle beyond CTI in all pigs. The atrophy and necrosis of the nerve bundle itself is scarce. <h3>Conclusion</h3> These data demonstrated the feasibility of SBRT for creating conduction block across the CTI in mini pigs. Fibrosis or scarring around the nerve bundle beyond CTI may affect the radiation injury. Then, precise margins of cardiac radioablation to the cavotricuspid isthmus will reduce the radiation injury. Not only gating and breath-hold, but also including the use of real-time tracking such as MRI-guidance cardiac radiosurgery will open the possibility of treating cardiac arrhythmias patients completely safety and noninvasively.

Design, Synthesis and Assessment of QCA primitives of 5-input Majority gate in field-coupled QCA Nanotechnology

Quantum-dot Cellular Automata (QCA) is an exciting new development in the field of nanoscale-based very large scale integration (VLSI) that has the potential to replace more conventional complementary metal oxide semiconductor (CMOS) technology. In this article, a thorough and detailed description of the novel QCA based 5-input Majority gate is presented. In order to validate the accuracy of a 5-input majority gate, a comprehensive analysis has been carried out, taking into account the location of each and every QCA cell inside a structure. In this paper, a completely new 1-bit full-adder is constructed in order to assess the possible advantages offered by the recently developed 5-input majority gate. The comparative analysis with the reported designs in the literature revealed that the proposed full adder is superior in terms of cell count with a reduction of more than 54.79 %, as well as a decrease in area of more than 25 %, and a reduction in latency of 83.33 %. These findings were derived from the observation that the proposed full adder is better. For the purpose of demonstrating the usefulness and dependability of the strategy, power analysis have been carried out on the proposed full adder design using the QCAPro and QCADesigner 2.0.3 tools, respectively. The new majority gate technique is based on a variety of designs that enjoy the parameters of less area, durable circuit architecture, and optimal clock cycles, as well as the higher performance aspects associated with high-speed computation.

Image Cryptography Design Based on Nano AES Security Algorithm

Abstract: Advanced Encryption Standard (AES) is a specification for electronic data encryption. This standard has become one of the most widely used encryption methodand has been implemented in both software and hardware. A high-secure symmetric cryptography algorithm, implementation on field-programmable gate array (FPGA). The proposed architecture includes 8-bit data path and five main blocks. We design two specified register banks, Key-Register and State-Register, for storing the plain text, keys, and intermediate data. To reduce the area, Shift-Rows is embedded inside the State- Register. To optimize Sub-Bytes, we merge and simplify some parts of the Sub-Bytes. To reduce power consumption, we apply the clock gating technique to the design. This paper presents an Image Cryptography based 128-bit AES design. This Design is implemented in FPGA XC3S 200 TQ-144 using Verilog HDL and simulated by Modelsim 6.4 c and Synthesized by Xilinx tool.

Pulse fluorescence LIDAR system for identification and low concentration measurements of Phaeocystis globosa cells and colonies

A pulse fluorescent LIDAR system (pfLIDAR) for early-warning of Phaeocystis globosa cells and colonies outbreak is developed and demonstrated, which can realize species identification and low concentration measurement of Phaeocystis globosa in water areas. The system utilizes a high-power 532 nm nanosecond pulsed laser as excitation light source and a photomultiplier tube combined with a liquid crystal tunable filter as the detection setup. Measurement of Phaeocystis globosa solitary cells and colonies were performed in a water tank, simulating microalgae distributions and concentrations prior to blooms in real water areas. The concentration of Phaeocystis globosa cells or colonies can be accurately measured based on the received fluorescent echo signals. Obtained echo signals combined with spectral information can be used for species identification of high accuracy using a PCA-SVM method. The system works in staring scanning mode, and a gating technique is used to filter out scattering and background fluorescence noise in water path, which improves the SNR of detected fluorescent echo signals. Experimental demonstration results demonstrate the capability of the system for Phaeocystis globosa identification and biomass assessment, indicating a significant potential of the system for detailed monitoring in aquatic ecosystems.

12-Bit Clock Gated SAR-ADC for Bio-Medical Applications

Background/Objectives: Power optimization is a critical design criterion in modern integrated circuits. The unwanted clock signals are neutralized and the reduction in power consumption is made presumable by using the clock gating technique. Methods: Analog-to-digital converters (ADCs) are important components in these systems. A widely used successive approximation register A/D converter includes an internal clock, reference, and high resolution. The number of redundant cycles is increased with improved resolutions but enhances the consumption of power. Thus, the clock gating strategy is used to substantially lower the circuit’s dynamic power consumption. The clock gating technique is implemented with a reduced number of transistors to minimize the overhead with high switching activity. Also, demonstrate no imperfection on the clock duty cycle. Findings: A 12-bit clock gated SAR register using a D-flip flop with 1.8 V supply voltage is proposed in this study for efficient biomedical applications. SAR without a clock gating technique consumes 54 mW of power and SAR with a clock gating technique consumes a power of 22.68 mW. Novelty: The clock gating technique is stipulated to minimize power consumption of clock gated SAR-ADC and improves the battery life of the portable device. Keywords: Clock gated technique; power consumption; resolution; SARADC; successive approximation register

What factors influence the R value in data-driven respiratory gating technique? A phantom study.

The R value is adopted as a metric for the effectiveness of the respiratory waveform in the Advanced Motion Free implemented in the PET scanner as the data-driven respiratory gating (DDG) algorithm. The effects of changes in various factors on R values were evaluated by phantom analysis. We used a programmable respiratory motion phantom QUASAR with a sphere filled with an 18F solution. Respiratory motion simulation was performed by changing the sphere diameter, radioactivity concentration, amplitude, respiratory cycle, and respiratory waveform shape. Three evaluations were performed. (1) The power spectra calculated from the input waveforms were evaluated. (2) The effects of changes in the factors on the R value were evaluated. (3) DDG waveforms and inspiratory peak intervals were compared with the input waveform data set. The R values were increased and converged to a certain value as sphere diameter, radioactivity concentration, and amplitude gradually increased. The respiratory cycle showed the highest R value at 7.5 s, and the graph showed an upward convex pattern. The R value of the sinusoid waveform was higher than that of the typical waveform. There was a relationship between the power spectrum of the input waveform and R value. The visual score was also lower in the condition with a lower R value. In cases of no sphere, radioactivity, or motion, and a fast respiratory cycle, peak intervals were not accurately acquired. Factors affecting the R value were sphere diameter, radioactivity concentration, amplitude, respiratory cycle, and respiratory waveform shape.

Ultrahigh-amplitude isolated attosecond pulses generated by a two-color laser pulse interacting with a microstructured target.

A unique electron nanobunching mechanism using a two-color laser pulse interacting with a microstructured foil is proposed for directly generating ultraintense isolated attosecond pulses in the transmission direction without requiring extra filters and gating techniques. The unique nanobunching mechanism ensures that only one electron sheet contributes to the transmitted radiation. Accordingly, the generated attosecond pulses are unipolar and have durations at the full width at half-maximum about 5 attoseconds. The emitted ultrahigh-amplitude isolated attosecond pulses have intensities of up to ∼10^{21}W/cm^{2}, which are beyond the limitations of weak attosecond pulses generated by gas harmonics sources and may open a new regime of nonlinear attosecond studies. Unipolar pulses can be useful for probing ultrafast electron dynamics in matter via asymmetric manipulation.