nils-herrmann/clean_scirepeval huggingface dataset:
Research of CMOS biosensor IC for extracellular electrophysiological signal recording and pH value measuring

In this paper an integrated monolithic mixed signal biosensor circuit for both extracellar Electrophysiological signal recording and extracellular solution pH value measuring is designed and researched based on standard 0.6 ¿m CMOS technology. The extracellular bioelectrical signal recording module is consisted of 4×4 active electrical potential sensor array, analog multiplexer, reference sources, digital control circuits and output amplifier. Each sensor unit is 60 ¿m × 60 ¿m in area including a 15 ¿m × 15 ¿m sensing electrode. A correlated double sampling circuit is utilized to remove the common-mode noise. The sensor can linearly amplify signals with peak to peak values from 100 ¿V to 10 mV. The pH sensor module consists of silicon nitride film as pH sensitive layer and field effect transistor with multi-floating gate (MFGFET) structure. The output of the circuit is proportional to the pH value using constant source-drain voltage and current control scheme. The difference of pH-MFGFET and RE-MFGFET is sent to output which reduces the fixed pattern noise existed in the solution and circuits. The testing result shows the pH sensor has an average sensitivity of 35.8 mV/pH for pH1 to pH13 with linearity better than 5%. A temperature sensor with PTAT (Proportional to absolute temperature) is also integrated with this pH sensor. This biosensor can be used for recording bioelectrical activity of in-vitro electrogenic cells. It also can be used for exploring the relationship between cell membrane potential and its nearby solution pH value and temperature.
Magnetoelastic Performance of <110> Aligned Polycrystalline Tb0.3Dy0.7Fe2 in an Actuator

In this paper, we report the magnetoelasticity of <110> aligned polycrystalline Tb<sub>0.3</sub>Dy<sub>0.7</sub>Fe<sub>2</sub> (Terfenol-D) magnetostrictive alloy in an actuator.
Stable robustness analysis for temperature control system of state feedback merging PID regulators

The stabilization is the target of a control system designing and the chief condition to improve control performance. The system stability proving is an important work of control theory research. And it has guidance meaning to control system design and application. This paper aim at control strategy of state feedback based on incremental function observer(IFO-KDeltax) merging with conventional PID controller, to investigate stable robustness of several different control systems formed of the strategy, and its stable conditions with corresponding theoretical proof are given for the control systems by mathematical analysis. Parameters adjustment and system commissioning methods for the different control scheme are also proposed. The results of theory research and engineering application show that IFO-KDeltax has strong stable robustness. When PID control is merged with state feedback, it plays a different role. The main function of PID regulator here is compensation for control error which generated by deviation between IFO-KDeltax and controlled object. And it provides with steady operation points for the control systems.
The research of RGD-conjugated PLA-PLL nanoparticles carriers on targeted delivery to tumor

The development of a more precise targeted delivery system is critical for the advancement of cancer chemotherapy. In this study, we evaluated the effects of RGD-conjugated poly (lactic acid-co-lysine)-(Arginine-Glycine-Aspartic) nanoparticles (PLA -PLL-RGD NPs) on targeted drug delivery for BACP-37 breast cancer. PLA-PLL-RGD NPs were prepared by using the emulsion method. A subsequent MTT assay indicated that the NPs were non-toxic. In vitro, the results of Confocal Laser Scanning Microscopy (CLSM) and Flow cytometry analyses indicated that the PLA-PLL-RGD NPs can bind more significantly to human umbilical vein endothelial cells (HUVECs) compared with PLA-PLL NPs. In vivo, the results of targeted imaging showed that PLA-PLL-RGD can significantly target to BACP-37 breast cancer. These results showed that PLA-PLL-RGD NPs have the potential to be used as targeted delivery carrier.
A hidden Markov model applied to Chinese four-tone recognition

In this paper, we present a probabilistic approach to Chinese four-tone recognition in which the well-known technique of a hidden Markov model is used. For each tone, a distinct hidden Markov model (HMM) is produced by using the Baum's forward-backward algorithm based upon the artificial (simulated) training sequences. Classification can be made by computing the probability of generating the test utterance with each tone model and choosing as the recognized tone the one corresponding to the model with the highest probability score. The recognition accuracies were found to be 98% for 35 Chinese phonetic alphabets pronounced by standard Chinese speakers and 96% for Chinese digits pronounced by our research group.
Study on Propagation Characteristics of Ultrasonic Guided Waves along the Pipe

Ultrasonic guided wave is introduced as a promising pipe inspection tool for its long inspection distance and 100% pipe wall examination. The inspection range could reach 180m at single direction from one transducer when the pipe is in ideal condition. During the process of long-range pipe inspection, guided waves may go through many girth welds and elbows. When geometry characteristics of the pipe were changed, much energy of ultrasonic guided waves would be reflected and the inspection range may decrease due to energy attenuation of guided waves. Longitudinal wave was used to study propagation characteristics of ultrasonic guided waves along an experimental steel pipe. Research was carried out on energy attenuation of guided waves when it went through seven girth welds and a piece of elbow. And its ability of sensitivity and location precision of defects, such as notch, burr and branch was investigated
Construction and Practice for Interaction in Networked Learning Situation

Rapid development of informational technology has brought the reform of learning style. Networked learning has become increasingly accessible and familiar to us and has played more and more important role. In actual life the ability to communicate with others is essential to the achievement of its objectives. This is all the same to learn in the networked learning situation. Good interaction will facilitate learners to cooperate with others and fulfill learning tasks. Finally, they can improve themselves. Based on the research existed, this paper restudies the interaction in networked learning situation and explains what the interaction is, which factors affect it and how to design the interaction in networked learning situation. In the last part, we give an example based on our ideas.
Robust estimation of structured covariance matrix for heavy-tailed distributions

In this paper, we consider the robust covariance estimation problem in the non-Gaussian set-up. In particular, Tyler's M-estimator is adopted for samples drawn from a heavy-tailed elliptical distribution. For some applications, the covariance matrix naturally possesses certain structure. Therefore, incorporating the prior structure information in the estimation procedure is beneficial to improving estimation accuracy. The problem is formulated as a constrained minimization of the Tyler's cost function, where the structure is characterized by the constraint set. A numerical algorithm based on majorization-minimization is derived for general structures that can be characterized as a convex set, where a sequence of convex programming is solved. For the set of matrices that can be decomposed as the sum of rank one positive semidefinite matrices, which has a wide range of applications, the algorithm is modified with much lower complexity. Simulation results demonstrate that the proposed structure-constrained Tyler's estimator achieves smaller estimation error than the unconstrained case.
Assessing learning emotion for both the cognitive styles of visualizer and verbalizer distributed to different types of multimedia learning materials

Learning emotion frequently generates variation in learning processes due to the affection of different learning materials or scenes. Many education scholars have pointed out that emotions are directly related to and affect learning performance. Few studies investigated the relationship between the learning emotion with learning materials owing to the difficulty of on-line assessing learning emotion. With the rapid development of emotion recognition technologies, the study focuses on the evaluation of learning emotion variation for the cognitive learning styles of visualizer and verbalizer who are distributed to different types of multimedia materials based on the emotion assessment instrument emWave developed by HeartMath. To identify the cognitive learning style of individual learners, the Style of Processing (SOP) scale was employed to divide all participants who took part in the teaching experiment into the cognitive learning styles of visualizer and verbalizer. Meanwhile, three types of the designed multimedia materials including the static text and image-based materials, video-based materials, and animation interaction-based materials were randomly distributed to those participants with different cognitive learning styles for learning. Experimental results indicate that the difference of learning emotion variation of the cognitive learning styles of visualizer and verbalizer who are distributed to different types of multimedia materials for learning reaches significant level.
Forecast of regional logistics demand based on set pair analysis

Many factors may affect the demand of regional logistics. But we could not list all the factors and could not quantitatively analysis the influencing degree of each factor. In traditional forecast methods, many influence factors may be ignored or predigested, which may warp the forecasting result. Set pair clustering analysis may solve the problem of neglecting some influencing factors. In this paper, the historical GDP data of primary, secondary and tertiary industry in North-East China are listed. Based on the increasing rate of GDP data, volume of goods turnover in the coming years is forecasted. The result of empirical study proved that Set pair clustering analysis is reasonable and feasible.
Analysis of Output Characteristic Model of Magnetostrictive Displacement Sensor Under a Helical Magnetic Field and Stress

An output characteristic model is developed to predict the response of the output voltage obtained from the magnetostrictive displacement sensor, which is simultaneously subjected to stress and helical magnetic fields. The model is based on the consideration of the Wiedemann effect, the piezomagnetic effect, and the Jiles-Atherton model. This research predicts and investigates the effects of the stress properties and the helical magnetic field on the magnetostrictive displacement sensor output characteristics. The induced voltage increases with an increasing magnetic field and decreases with increasing stress. These results prove that the magnetic field and stress have significant effects on the sensor's output. They provide important guidance in designing magnetostrictive displacement sensors.
Digital watermarking algorithm based on hyperchaos and fractional Fourier transform

In this paper, a novel digital image watermarking algorithm is proposed based on the hyperchaos system and fractional Fourier transform (FRFT) for copyright protection. The method making use of hyperchaotic key sequence to weak the correlation among the pixels of the watermark, in order to reinforce the security of the watermarking, and the watermark is also encrypted in the FRFT transform domain. Furthermore, this paper proposes an improved embedding scheme, in which the encrypted watermarking is embedded into the middle frequency of the original image with different strength. Simulations under several conditions are performed to verify the effectiveness of the proposed method, and the results show that the proposed algorithm is quite robust under either non-geometry or geometry attacks.
A measurement-based technique for incipient anomaly detection

Fault detection is essential for safe operation of various engineering systems. Principal component analysis (PCA) has been widely used in monitoring highly correlated process variables. Conventional PCA-based methods, nevertheless, often fail to detect small or incipient faults. In this paper, we develop new PCA-based monitoring charts, combining PCA with multivariate memory control charts, such as the multivariate cumulative sum (MCUSUM) and multivariate exponentially weighted moving average (MEWMA) monitoring schemes. The multivariate control charts with memory are sensitive to small and moderate faults in the process mean, which significantly improves the performance of PCA methods and widen their applicability in practice. Using simulated data, we demonstrate that the proposed PCA-based MEWMA and MCUSUM control charts are more effective in detecting small shifts in the mean of the multivariate process variables, and outperform the conventional PCA-based monitoring charts.
Research on energy micro grid control system based on the structure of FREEDM

Recent years, solar energy and wind energy, the most common new energy sources, have becoming the most important ways of distributed generations. FREEDM system is an Energy Internet model which is proposed by Professor Alex Q. Huang from North Carolina State University and solid state transformer (SST) is the core of it. Based on the concepts of photovoltaic (PV) power generation, wind power generation, energy storage technology and FREEDM system, this paper presents an energy micro grid control system based on the structure of FRDDEM. With the help of Matlab/Simulink software, we have built the models of inverter, PV array, wind turbine, storage device, and filter. We use SVPWM control technology to obtain the simulations of islanding operation mode and grid-connected operation mode.
Electrical and Acoustic Parameters of Wire-Guided Discharges in Water: Experimental Determination and Phenomenological Scaling

This paper is focused on investigation of the electrical, hydrodynamic, and acoustic parameters of underwater plasma discharges, stabilized with thin copper wires. The experimental current and acoustic waveforms have been obtained using different combinations of the circuit capacitance, charging voltage, and wire length. The resistances of plasma discharges have been calculated for all combinations of electrical and topological parameters, based on the constant resistance approach. Phenomenological scaling relationships that link the plasma resistance and the total energy delivered to the plasma, the period of discharge cavity oscillation and the peak magnitude of the acoustic impulse have been obtained. These relationships can be used in optimization of the acoustic output from the wire-guided discharges for different practical applications.
A microprocessor-based wrist pulse simulator for pulse diagnosis in traditional Chinese medicine

The pulse diagnostics has been an important practice in traditional Chinese medicine for diagnosing various diseases. It is based on the patterns of blood pressure pulses at the wrist felt with three fingers. The device developed in this study mimics the outward forces generated by blood flows through the radial artery. The embedded system platform allows for the implementation of various pulse patterns in response to the depression pressure of the fingers. The resulting pulse simulator is useful for demonstrating and teaching the art of pulse diagnosis.
Research on grid-connected photovoltaic power generation technology based on FREEDM system

Solar is a kind of new energy, and photovoltaic power generation is an important way of distributed generation; FREEDM system is a kind of Energy Internet model, which is presented by Professor Alex Q. Huang from North Carolina State University in 2008. Combining the advantages of photovoltaic power generation and FREEDM system, this paper proposes a kind of grid-connected photovoltaic power generation technology based on FREEDM system. With the help of MATLAB/simulink software, we build the model of photovoltaic array and solid state transformer that is the core part of FREEDM system, and realize the goal of maximum power point tracking. The output of photovoltaic array can not only be connected into the low voltage AC power grid through single phase inverter, but also can be connected into 10 Kv grid through solid state transformer and three phase inverter. Among them, we adopt active frequency drift method in the model of single phase inverter, high-frequency transformer in DC/DC converter and voltage source converter topology based on d-q vector control system in the model of three phase inverter.
Coordinated switching controller design for the power system with SVC and steam valve

For the single-machine infinite-bus steam valve system, the coordinated control problem of SVC and steam valve sliding mode is addressed by means of backstepping method with the control input constraints. In the design process, the non-linear features are kept without any linearization used here, thus improving effectively the transient stability of power system even under the effect of the mechanical disturbance and short-circuit faults in power system. Also by introducing switching mechanism, we solve the problem of the control input constraints. Simulation results prove the effectiveness of the proposed controller in this paper.
Distributed nonconvex multiagent optimization over time-varying networks

We study nonconvex distributed optimization in multiagent networks where the communications between nodes is modeled as a time-varying sequence of arbitrary digraphs. We introduce a novel broadcast-based distributed algorithmic framework for the (constrained) minimization of the sum of a smooth (possibly nonconvex and nonseparable) function, i.e., the agents' sum-utility, plus a convex (possibly nonsmooth and nonseparable) regularizer. The latter is usually employed to enforce some structure in the solution, typically sparsity. The proposed method hinges on Successive Convex Approximation (SCA) techniques coupled with i) a tracking mechanism instrumental to locally estimate the gradients of agents' cost functions; and ii) a novel broadcast protocol to disseminate information and distribute the computation among the agents. Asymptotic convergence to stationary solutions is established. A key feature of the proposed algorithm is that it neither requires the double-stochasticity of the consensus matrices (but only column stochasticity) nor the knowledge of the graph sequence to implement. To the best of our knowledge, the proposed framework is the first broadcast-based distributed algorithm for convex and nonconvex constrained optimization over arbitrary, time-varying digraphs. Numerical results show that our algorithm outperforms current schemes on both convex and nonconvex problems.
Inducing neuronal bursting activity in the CNS of L. stagnalis using Dimethylformamide

Dimethylformamide (DMF) is a hydrophilic aprotic solvent often used in peptide coupling, an essential process in the pharmaceutical industry. Its use in biological study is typically in the role of a peptide solvent when evaluating the efficacy of peptides and their effect on the cellular membrane. In evaluating the effect of the peptide gramicidin on neurons of the central nervous system (CNS) of the pond snail Lymnaea stagnalis, an interesting cellular response was noted when applying DMF without gramicidin. In the presence of DMF alone, the regular beating pattern of neuron VDI, an identified neuron in the dorsal presentation of the visceral ganglion, changed to bursting pattern. A slight lowering of the membrane potential was also noted.
Improved semi-automated segmentation of cardiac CT and MR images

This paper presents a semi-automated segmentation method for short-axis cardiac CT and MR images. The main contributions of this work are: 1) using two different energy functionals for endocardium and epicardium segmentation to account for their distinctive characteristics; 2) proposing a dual-background model that is suitable for representing intensity distributions of the background in epicardium segmentation; 3) designing a novel shape prior term that is robust and controllable; and 4) an improved estimation of myocardium thickness by using edge information. Experimental results on cardiac CT, perfusion and cine MR images show that our method is robust and effective for both CT and MR images.
Low-Complexity Algorithms for Low Rank Clutter Parameters Estimation in Radar Systems

This paper addresses the problem of the clutter subspace projector estimation in the context of a disturbance composed of a low rank heterogeneous (Compound Gaussian) clutter and white Gaussian noise. In such a context, adaptive processing based on an estimated orthogonal projector onto the clutter subspace (instead of an estimated covariance matrix) requires less samples than classical methods. The clutter subspace estimate is usually derived from the eigenvalue decomposition of a covariance matrix estimate. However, it has been previously shown that a direct maximum likelihood estimator of the clutter subspace projector can be obtained for the considered context. In this paper, we derive two algorithms based on the block majorization-minimization framework to reach this estimator. These algorithms are shown to be computationally faster than the state of the art, with guaranteed convergence. Finally, the performance of the related estimators is illustrated on realistic Space Time Adaptive Processing for airborne radar simulations.
A Digital Watermarking Algorithm Based on Discrete Fractional Fourier Transformation

An algorithm of digital watermarking based on hyper chaos sequence and the discrete fractional Fourier transform (DFRFT) is proposed. First, the watermark image is scrambled in the spatial domain. The original image and the watermark image are discrete fractional Fourier transformed respectively with different order. Secondly, the watermark image's real part and imaginary part are encrypted by the cipher sequence, which is generated by the hyper chaos sequence. Thirdly, the secondary visual important part of the original image is chosen for embedding into the watermark. At last, the watermark image is obtained after Fourier inversely transformed. The robustness of the watermark image under different attacks such as noise, JPEG compression, the cropping and gaussian low-pass filter is analyzed and the results demonstrate that the embedding scheme has good performance of robustness.
Auto-detection of dew point using wavelet transformation

In this paper, the Mallat algorithm of wavelet transformation is adopted to determine the deflection point of the temperature curve in the dew-point auto-detection instruments. By this method, the useful signal can be effectively extracted out of intensive background noise, and highly repeatable value of the deflection point can be obtained in only 3-5 measurements. Compared with the traditional method, the approach introduced in this paper can considerably reduce the testing time and increase the accuracy & stableness greatly during dew-point auto-detection measurements.