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A Sigma-Delta modulator (SDM) realized with a fully differential third-order single-loop cascaded integrator feedforward (CIFF) architecture is proposed. A pair of low-frequency chopper switches are nested outside the chopper amplifier to further reduce the residual offset voltage. To reduce the power consumption and ensure linearity, a high-speed dynamic comparator is also used to implement a one-bit quantizer. The proposed architecture and the corresponding functionality are first simulated in MATLAB Simulink at the behavioral level. The results show that the designed modulator has an SNDR of 124.9 dB corresponding to an ENOB of 20.46 bits at a clock frequency of 256 kHz and 312.5 Hz input with a differential-mode voltage of 700 mV sinusoidal waveform. Based on SMIC 180 nm/1.8 V standard CMOS process on the Cadence platform, the subcircuit-level simulation is also performed, while the result shows that the proposed modulator can effectively achieve 115.52 dB SNDR, 18.90-bit ENOB, and 8.40 mW power consumption, which correspond to FoM W and FoM schreier of 0.067 pJ/step and 163.27 dB, respectively. The proposed modulator shows a significant advantage to be applied for high-precision analog-to-digital conversion applications such as high-quality equipment for audio, ECG and EEG signal sensing. [ABSTRACT FROM AUTHOR]

In the application of classical graph theory, there always are various indeterministic factors. This study studies the indeterministic factors in the connected graph by employing the uncertainty theory. First, this study puts forward two concepts: generalized uncertain graph and its connectivity index. Second, it presents a new algorithm to compute the connectivity index of an uncertain graph and generalized uncertain graph and verify this algorithm with typical examples. In addition, it proposes the definition and algorithm of α -connectivity index of generalized uncertain graph and verifies the stability and efficiency of this new algorithm by employing numerical experiments. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "A 1.8 V 115.52 dB Third-Order Discrete-Time Sigma-Delta Modulator Using Nested Chopper Technology" published in the Journal of Circuits, Systems & Computers. The correction addresses an error in the early published version where the same figures were used for both Fig. 11 (a) and (b). The correct Fig. 11 (b) is provided in the correction notice. The article was authored by Jinchan Wang, Gefan Wang, Kai Li, and Bo Liu from the College of Information Engineering at Henan University of Science and Technology in China. [Extracted from the article]

Abstract: The static polarization wind imaging interferometer (SPWII) is a device used to measure wind velocity and temperature of the upper atmosphere. In this paper, the principle of SPWII is expounded. Using the four-side pyramid prism and polarizer array, four intensity interferograms of different phase differences form on the four subareas of the CCD which is located at the focal plane of the imaging lens. The wind velocity and temperature can be derived from the interferograms. Using the approximation and the antitheses, we analyze the influences of the wavelength bandwidth on the measured wind velocity and atmospheric temperature. According to the design requirements of the SPWII, the errors of the wind velocity and the atmospheric temperature are less than 5m/s and 5K when the incident wavelength bandwidth is in the range of [−3.08, 3.08] nm. The range is estimated and verified by simulations. These results are helpful for the realization and data processing of the SPWII. [Copyright &y& Elsevier]

Abstract  A total of 124 fecal specimens were collected from four deer farms in Zhengzhou City, China and examined for Cryptosporidium by Sheather’s sugar flotation technique. Cryptosporidim oocysts were detected in two 1-year-old sika deer, and one of the two specimens was genotyped by sequence and phylogenetic analyses of the small subunit ribosomal RNA (rRNA) (18S rRNA), 70-kDa heat shock protein (HSP70), actin, and Cryptosporidium oocyst wall protein (COWP) genes. Results obtained suggested that the Cryptosporidium studied belonged to Cryptosporidium cervine genotype, although slight sequence differences were noticed at the three loci. The similarities between this isolate and other Cryptosporidium cervine genotype isolates were 99.1–99.8%, 9.8%, 99.7%, and 100% at the 18S rRNA, HSP70, actin, and COWP loci, respectively. This study is the first report of Cryptosporidium infection in sika deer in China. [ABSTRACT FROM AUTHOR]

Abstract: Printable carbon nanotubes field emission displays with shadow mask (Shadow Mask CNT-FED) is suggested. A layer of insulator is screen printed on the upper surface of shadow mask, and address electrodes are fabricated on it. MgO film is deposited on shadow mask by electron beam evaporation. Secondary emission electrons escape from MgO film under the bombardment of primary electrons. In the simulation, 93% of the landing electrons are found to be secondary emission electrons. The modulating amplitude of the voltage on the address electrodes is low (∼250 V) because of the low-energy secondary emission electrons. The comparable results are also got from the experiments. The modulating amplitude of the voltage is found to increase with the thickness of the insulator. The optimized thickness (40∼50 μm) and the fabrication process of the insulator are suggested in this research report. [Copyright &y& Elsevier]

Purpose: High-speed Indium Phosphide (InP) HBTs have been widely used to design high-speed analog, digital and mixed-signal integrated circuits. The purpose of this study is to propose a new parameter extraction procedure for determining an improved T-topology small-signal equivalent circuit of InP heterojunction bipolar transistors (HBTs). Design/methodology/approach: The alternating current crowding effect is considered through adding the intrinsic base capacitance in the small-signal equivalent circuit. All of the circuit parameters are extracted directly without using any approximation. Findings: The extraction technique is more easily understood and clearer than other extraction methods, as the equations are derived from the S-parameters by peeling peripheral elements from small-signal models to get reduced ones and extracting each equivalent-circuit parameter using each equation. Originality/value: To validate the presented parameter extraction technology, an n-p-n emitter-up InP HBT was analyzed adopting the method. Excellent agreement between measured and modeled S-parameters is obtained up to 40 GHz. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is an irreversible neurodegenerative disease, and the early diagnosis and effective intervention of AD is essential for patients and doctors. Intelligence diagnosis based on magnetic resonance imaging and deep learning has become one of the useful methods for AD identification. To improve the diagnosis effect of AD in early stages, a novel multi‐scale classification model of AD, called MSFNet‐2SE, is proposed. First, a new multi‐scale fusion (MSF) feature extraction module is designed based on the idea of the feature maps split into feature subsets of Res2Net. Second, a channel attention module is embedded into the MSF module through integrating two Squeeze‐and‐Excitation (SE) blocks. Finally, a gradient centralization Adam optimizer is used to improve the model classification performance. Experimental results illustrate that, compared with other available state‐of‐the‐art classification models of AD, the proposed model has excellent classification performance. It is helpful to improve the clinical diagnosis efficiency. [ABSTRACT FROM AUTHOR]

A novel algorithm is proposed for optimal extraction of GaN HEMT small-signal model parameters. The proposed Quantum Genetic Algorithm (QGA) exploits the superposition, entanglement and interference of quantum states, which solves the problems of high number of iterations and slow convergence when obtaining optimal solutions using Genetic Algorithms (GA). Meanwhile, it is solved that the Particle Swarm Optimisation (PSO) algorithm produces premature convergence and easily falls into the local optimum solution. In order to avoid the influence of distributed parasitic effects in large size devices under high-frequency conditions, a suitable frequency range is determined and combined with direct extraction techniques to determine the range of parameter values. The model parameter values are optimised step by step using QGA. In order to verify the superiority of QGA, QGA and PSO algorithms are both used to optimise GaN HEMT small-signal model parameters. By comparing the modelled S-parameter effects of the QGA and the PSO algorithm, it can be found that the QGA has better consistency with the measured data. [ABSTRACT FROM AUTHOR]

The effects of gamma irradiation on the DC and AC characteristics of InGaP/GaAs single heterojunction bipolar transistors (SHBTs) are investigated comprehensively for the first time, which is based on experimental data before irradiation, after irradiation and after annealing. A simplified VBIC device model is developed to describe the DC and AC characteristics of the devices. The model parameters are extracted from experimental data before irradiation, after irradiation and after annealing. Finally, the degraded rates of model parameters are used to study the radiation-induced degradation of the device performance. [ABSTRACT FROM AUTHOR]

The single-objective and single-parameter optimization method is commonly used in the structure optimization of TSV to improve the transmission characteristics, for which a structure design scheme that simultaneously satisfies multiple target requirements is difficult to obtain. Moreover, the method cannot simultaneously optimize different design parameters. Aiming at the above problems, a global optimization method based on the grey wolf optimization (GWO) algorithm and artificial neural network (ANN) model is proposed. With the presented mixed dielectric coaxial-annular TSV model, firstly six key design parameters A-F are selected as optimization variables by the control variable method. The L 25 (56) orthogonal experiment is designed for Taguchi analysis and analysis of variance (ANOVA). Then, three prediction models, ANN, support vector machine (SVM), and extreme learning machine (ELM), are developed with the extended orthogonal data as the training sets. It is found that the ANN model performed best. To search for the global optimal solution, the genetic algorithm (GA) and GWO algorithm, combined with the ANN model are applied, respectively. The results show that the GWO algorithm is more successful in solving the problem of falling into the local optimum than GA, and the convergence speed is faster and more stable. After GWO-ANN optimization, the performance of each S -parameter index is greatly improved, S 11 reduces by 14.05 dB, S 21 increases by 0.33 dB, and S 31 reduces by 12.50 dB at 30 GHz. • To achieve multi-objective and multi-parameter optimization of TSV, a global optimization model with GWO and ANN is proposed. • The L 25 (56) orthogonal experiment is designed to assess the effects of six key structural parameters on S -parameters. • The global optimal structural parameters are obtained with GWO and ANN, and the S -parameters performance is greatly improved. [ABSTRACT FROM AUTHOR]

The Genetic Algorithm-Extreme Learning Machine (GA-ELM) neural network algorithm is proposed to model the relevant characteristics of GaN pseudomorphic high electron mobility transistor (P-HEMT) large signal. This algorithm solves the over-fitting problem of the Back Propagation (BP) neural network algorithm in the prediction data. It has the characteristics of fast calculation speed, so it can greatly save calculation processing time. It can also randomly generate the connection weights of the input layer, the hidden layer and the threshold of the hidden layer neurons, avoiding errors in parameter selection. In order to verify the superiority of the algorithm, the modeling effects of the BP neural network algorithm model, the Genetic Algorithm-Back Propagation (GA-BP) neural network algorithm model and the GA-ELM neural network algorithm model are compared in this paper. The results show that the proposed GA-ELM neural network algorithm model has the highest accuracy. [ABSTRACT FROM AUTHOR]

The influences of ion bombardment on the field emission performance of tetrapod ZnO nanostructures are reported. As the scanning electron microscopy images and photoluminescence spectrum show, the tips of the field emitters are destroyed and the surface state of the field emitters is also changed after the ion bombardment. The ion bombardment has a considerable effect on the field emission properties of the tetrapod ZnO field emitters. After Ar+ ion bombardment with the energy of 3 keV and the ion current of 0.05 μA for 30 min, the turn-on field increases about 63% and the threshold field increases about 77%, respectively. There are two main reasons for the variation in field-emission property: (1) the decrement of the field enhancement factor β, which is caused by the variation in morphology of field emitter; (2) the increment of work function φ, which is caused by the changed concentration of the surface oxygen vacancy. [ABSTRACT FROM AUTHOR]

In this paper, the study of a Ka-band GaAs HBT VCO is reported with particular emphasis on achieving low-phase noise while using direct coupled varactor. A push–push cross-coupled VCO configuration is employed to achieve high oscillation frequency and low-phase noise. The measured oscillation bandwidth spans from 30.2 to 28.6 GHz with a tuning range of 1.6 GHz, while the phase noise at 1 MHz of frequency offset from the carrier at 29.3 GHz is − 1 1 1. 5 dBc/Hz. The VCO consumes 28.2 mW from 3 V supply and occupies an area of 0. 8 2 mm × 0. 6 2 mm. The FOM of the VCO achieves − 1 8 6. 3 dBc/Hz. [ABSTRACT FROM AUTHOR]

In this paper, a fully integrated Ku-band voltage controlled oscillator (VCO) with low phase noise is presented in a GaAs heterojunction bipolar transistor (HBT) technology. A cross-coupled configuration is employed to achieve low phase noise, and to achieve high output power, the largest HBT and higher bias current are adopted. The implemented VCO demonstrates that the oscillation frequency is from 13.77GHz to 14.8GHz, with a maximum 4.83dBm output power at 13.77GHz. The phase noise of the VCO is 100.2dBc/Hz at 1MHz offset from 14.36GHz oscillation frequency. The VCO consumes 61.2mW from 6V supply and occupies an area of 0.51mmmm. Finally, the figure-of-merits (FOMs) for VCOs are discussed. [ABSTRACT FROM AUTHOR]

—In this paper, an improved genetic algorithm-based hybrid direct-optimal extraction method for small-signal model of GaN HEMT devices is proposed. Simulated annealing algorithm and fuzzy adaptive strategy are incorporated into genetic algorithm for model parameter optimization, to overcome the shortcoming of conventional genetic algorithm that tend to fall into local optimum solutions. The validity of proposed algorithm is verified by using a 20-element GaN HEMT small-signal equivalent circuit model under different operating conditions. The results show that the modeled S-parameters agree well with the measured S-parameters in the frequency range of 0.5–20.5 GHz. [ABSTRACT FROM AUTHOR]

The Differential Evolution-Support Vector Regression (DE-SVR) algorithm is designed to model the small-signal intrinsic noise behavior of GaN HEMT. It not only overcomes the local minimization shortcoming of the Back Propagation (BP) algorithm, but also uses the DE (Differential Evolution) algorithm to obtain the best parameter c (punishment factor) and parameter g (variance of kernel function) of the Support Vector Regression (SVR) algorithm. In order to validate the superiority of the DE-SVR algorithm, the experiment compares the modeling effects of BP algorithm, SVR algorithm, and DE-SVR algorithm in modeling the small-signal intrinsic noise model of GaN HEMT. The experimental results show that there are obvious advantages for the DE-SVR algorithm in modeling the small-signal intrinsic noise characteristics of GaN HEMT. • The Differential Evolution-Support Vector Regression (DE-SVR) algorithm overcomes the local minimization shortcoming of the Back Propagation (BP) algorithm. •The Differential Evolution-Support Vector Regression (DE-SVR) algorithm uses the DE (Differential Evolution) algorithm to obtain the best parameter c (punishment factor) and parameter g (variance of kernel function) of the Support Vector Regression (SVR) algorithm. [ABSTRACT FROM AUTHOR]

• A low gate voltage technology is used to effectively avoid the phenomenon of high forward grid voltage damaging or destroying the Schottky grid. • In order to model the gate leakage current of the device, gate-source resistance (R gsf) and gate-drain resistance (R gdf) are introduced. • The intrinsic parameter extraction formulas are deduced. In this article, a reliable parameter extraction method for GaN HEMT devices is proposed. When the parasitic capacitances are extracted, the judgment condition of the pinch-off voltage is introduced, which avoids the reduction of the reliability of the extracted parasitic capacitances caused by the random selection of the pinch-off voltage. A low gate voltage technology is used to effectively avoid the phenomenon of high forward grid voltage damaging or destroying the Schottky grid. At the same time, due to the influence of hybrid drain parameters (C d and R d), the extraction formulas of parasitic resistances and parasitic inductances are deduced in this paper. In order to model the gate leakage current of the device, gate-source resistance (R gsf) and gate-drain resistance (R gdf) are introduced and the intrinsic parameter extraction formulas are deduced. The small-signal model for a 1.25-mm GaN HEMT device is established and validated, which show that excellent agreement between measured and modeled S -parameters is obtained in the frequency range of 0.5–20.5 GHz. [ABSTRACT FROM AUTHOR]

Abstract: Field emitters of vertical carbon fibers on a silicon substrate are fabricated by catalytic chemical vapor deposition. After an ageing process of 150min, field emission measurement of the fibers is carried out in a vacuum chamber with a base pressure of 5.0×10−4 Pa. The experimental results display that field emission performance of the carbon fibers depends strongly on the vacuum level during the experiments. After the field emission measurement, damage to the carbon fiber field emitters is observed from the scanning electron microscopic images. [Copyright &y& Elsevier]

Uncertain differential equations are important mathematical models in uncertain environments. This paper investigates uncertain multi-dimensional and multiple-factor differential equations. First, the solvability of the equations is analyzed. The α -path distributions and expected values of solutions are given. Then, structure preserving uncertain differential equations, uncertain Hamiltonian systems driven by Liu processes, which possess a kind of uncertain symplectic structures, are presented. A symplectic scheme with six-order accuracy and a Yao-Chen algorithm are applied to design an algorithm to solve uncertain Hamiltonian systems. At last, numerical experiments are given to investigate four uncertain Hamiltonian systems, which highlight the efficiency of our algorithm. [ABSTRACT FROM AUTHOR]

an improved small-signal model for the GaN pseudomorphic high electron mobility transistor (P-HEMT) process is proposed in this paper. Experimental studies have found that a high positive bias voltage usually damages or destroys the Schottky grid. In order to solve this problem, a method of extracting parasitic inductance and parasitic resistance using low gate bias voltage technology is proposed. Experimental research found that the parasitic circuit parameters will change with the bias voltage. New intrinsic resistance (R L) and intrinsic inductance (L ds) are introduced into the intrinsic equivalent circuit to suppress its bias dependence to solve this problem. At the same time, it is found that there is a time delay phenomenon in the parasitic parameter model, so the RC network (R pds and C pds , R pgd and C pgd) is introduced to represent this phenomenon. It is successfully applied to model a GaN P-HEMT. Excellent agreement between measured and modeled S -parameters is obtained from 0.5 to 20.5 GHz. [ABSTRACT FROM AUTHOR]