Magnetic resonance imaging-radiomics evaluation of response to chemotherapy for synchronous liver metastasis of colorectal cancer

BACKGROUND Synchronous liver metastasis(SLM)is an indicator of poor prognosis for colorectal cancer(CRC).Nearly 50%of CRC patients develop hepatic metastasis,with 15%-25%of them presenting with SLM.The evaluation of SLM in CRC is crucial for precise and personalized treatment.It is beneficial to detect its response to chemotherapy and choose an optimal treatment method.AIM To construct prediction models based on magnetic resonance imaging(MRI)-radiomics and clinical parameters to evaluate the chemotherapy response in SLM of CRC.METHODS A total of 102 CRC patients with 223 SLM lesions were identified and divided into disease response(DR)and disease non-response(non-DR)to chemotherapy.After standardizing the MRI images,the volume of interest was delineated and radiomics features were calculated.The MRI-radiomics logistic model was constructed after methods of variance/Mann-Whitney U test,correlation analysis,and least absolute shrinkage and selection operator in feature selecting.The radiomics score was calculated.The receiver operating characteristics curves by the DeLong test were analyzed with MedCalc software to compare the validity of all models.Additionally,the area under curves(AUCs)of DWI,T2WI,and portal phase of contrast-enhanced sequences radiomics model(Ra-DWI,Ra-T2WI,and Ra-portal phase of contrast-enhanced sequences)were calculated.The radiomicsclinical nomogram was generated by combining radiomics features and clinical characteristics of CA19-9 and clinical N staging.RESULTS The AUCs of the MRI-radiomics model were 0.733 and 0.753 for the training(156 lesions with 68 non-DR and 88 DR)and the validation(67 lesions with 29 non-DR and 38 DR)set,respectively.Additionally,the AUCs of the training and the validation set of Ra-DWI were higher than those of Ra-T2WI and Ra-portal phase of contrast-enhanced sequences(training set:0.652 vs 0.628 and 0.633,validation set:0.661 vs 0.575 and 0.543).After chemotherapy,the top four of twelve deltaradiomics features of Ra-DWI in the DR group belonged to gray-level run-length matrices radiomics parameters.The radiomics-clinical nomogram containing radiomics score,CA19-9,and clinical N staging was built.This radiomics-clinical nomogram can effectively discriminate the patients with DR from non-DR with a higher AUC of 0.809(95%confidence interval:0.751-0.858).CONCLUSION MRI-radiomics is conducive to predict chemotherapeutic response in SLM patients of CRC.The radiomics-clinical nomogram,involving radiomics score,CA19-9,and clinical N staging is more effective in predicting chemotherapeutic response.

Novel Adaptive Neural Controller Design Based on HVDC Transmission System to Damp Low Frequency Oscillations and Sub Synchronous Resonance

This paper presents the effect of the high voltage direct current (HVDC) transmission system based on voltage source converter (VSC) on the sub synchronous resonance (SSR) and low frequency oscillations (LFO) in power system. Also, a novel adaptive neural controller based on neural identifier is proposed for the HVDC which is capable of damping out LFO and sub synchronous oscillations (SSO). For comparison purposes, results of system based damping neural controller are compared with a lead-lag controller based on quantum particle swarm optimization (QPSO). It is shown that implementing adaptive damping controller not only improves the stability of power system but also can overcome drawbacks of conventional compensators with fixed parameters. In order to determine the most effective input of HVDC system to apply supplementary controller signal, analysis based on singular value decomposition is performed. To evaluate the performance of the proposed controller, transient simulations of detailed nonlinear system are considered.

Dynamics of firing patterns,synchronization and resonances in neuronal electrical activities:experiments and analysis

Recent advances in the experimental and theoretical study of dynamics of neuronal electrical firing activities are reviewed. Firstly, some experimental phenomena of neuronal irregular firing patterns, especially chaotic and stochastic firing patterns, are presented, and practical nonlinear time analysis methods are introduced to distinguish deterministic and stochastic mechanism in time series. Secondly, the dynamics of electrical firing activities in a single neuron is concerned, namely, fast-slow dynamics analysis for classification and mechanism of various bursting patterns, one- or two-parameter bifurcation analysis for transitions of firing patterns, and stochastic dynamics of firing activities （stochastic and coherence resonances, integer multiple and other firing patterns induced by noise, etc.）. Thirdly, different types of synchronization of coupled neurons with electrical and chemical synapses are discussed. As noise and time delay are inevitable in nervous systems, it is found that noise and time delay may induce or enhance synchronization and change firing patterns of coupled neurons. Noise-induced resonance and spatiotemporal patterns in coupled neuronal networks are also demonstrated. Finally, some prospects are presented for future research. In consequence, the idea and methods of nonlinear dynamics are of great significance in exploration of dynamic processes and physiological functions of nervous systems.

Coherence Resonance and Noise-Induced Synchronization in Hindmarsh-Rose Neural Network with Different Topologies

In this paper, we investigate coherence resonance （CR） and noise-induced synchronization in Hindmarsh- Rose （HR） neural network with three different types of topologies： regular, random, and small-world. It is found that the additive noise can induce CR in HR neural network with different topologies and its coherence is optimized by a proper noise level. It is also found that as coupling strength increases the plateau in the measure of coherence curve becomes broadened and the effects of network topology is more pronounced simultaneously. Moreover, we find that increasing the probability p of the network topology leads to an enhancement of noise-induced synchronization in HR neurons network.

Stochastic resonance and synchronization behaviors of excitatory-inhibitory small-world network subjected to electromagnetic induction

The phenomenon of stochastic resonance and synchronization on some complex neuronal networks have been investigated extensively.These studies are of great significance for us to understand the weak signal detection and information transmission in neural systems.Moreover,the complex electrical activities of a cell can induce time-varying electromagnetic fields,of which the internal fluctuation can change collective electrical activities of neuronal networks.However,in the past there have been a few corresponding research papers on the influence of the electromagnetic induction among neurons on the collective dynamics of the complex system.Therefore,modeling each node by imposing electromagnetic radiation on the networks and investigating stochastic resonance in a hybrid network can extend the interest of the work to the understanding of these network dynamics.In this paper,we construct a small-world network consisting of excitatory neurons and inhibitory neurons,in which the effect of electromagnetic induction that is considered by using magnetic flow and the modulation of magnetic flow on membrane potential is described by using memristor coupling.According to our proposed network model,we investigate the effect of induced electric field generated by magnetic stimulation on the transition of bursting phase synchronization of neuronal system under electromagnetic radiation.It is shown that the intensity and frequency of the electric field can induce the transition of the network bursting phase synchronization.Moreover,we also analyze the effect of magnetic flow on the detection of weak signals and stochastic resonance by introducing a subthreshold pacemaker into a single cell of the network and we find that there is an optimal electromagnetic radiation intensity,where the phenomenon of stochastic resonance occurs and the degree of response to the weak signal is maximized.Simulation results show that the extension of the subthreshold pacemaker in the network also depends greatly on coupling strength.The presented results may have important implications for the theoretical study of magnetic stimulation technology,thus promoting further development of transcranial magnetic stimulation（TMS） as an effective means of treating certain neurological diseases.

The correlation between stochastic resonance and the average phase-synchronization time of a bistable system driven by colour-correlated noises

This paper investigates the correlation between stochastic resonance （SR） and the average phase-synchronization time which is between the input signal and the output signal in a bistable system driven by colour-correlated noises. The results show that the output signal-to-noise ratio can reach a maximum with the increase of the average phase- synchronization time, which may be helpful for understanding the principle of SR from the point of synchronization; however, SR and the maximum of the average phase-synchronization time appear at different optimal noise level, moreover, the effects on them of additive and multiplicative noise are different.

Overview of Sub-synchronous Oscillation in Wind Power System

Nowadays with the improvement in the degree of emphasis on new energy, the wind power system has developed more and more rapidly over the world. Usually the wind plants are located in the remote areas which are far from the load centers. Generally series compensated AC transmission and high voltage DC transmission are made use of to improve the transmission capacity as two main effective ways which can solve the problem of large scale wind power transmission. The paper describes the three kinds of impact varieties and impact mechanisms in the sub-synchronous oscillation phenomena of wind power system based on doubly fed induction generator (DFIG) wind generators. At last, we point out the important problem that should be stressed in the wind power system.

Stochastic Resonance in Neural Systems with Small-World Connections

We study the stochastic resonance （SR） in Hodgkin-Huxley （HH） neural systems with small-world （SW） connections under the noise synaptic current and periodic stimulus, focusing on the dependence of properties of SR on coupling strength c. It is found that there exists a critical coupling strength c^＊ such that if c 〈 c^＊, then the SR can appear on the SW neural network. Especially, dependence of the critical coupling strength c^＊ on the number of neurons N shows the monotonic even almost linear increase of c^＊ as N increases and c^＊ on the SW network is smaller than that on the random network. For the effect of the SW network on the phenomenon of SR, we show that decreasing the connection-rewiring probability p of the network topology leads to an enhancement of SR. This indicates that the SR on the SW network is more prominent than that on the random network （p = 1.0）. In addition, it is noted that the effect becomes remarkable as coupling strength increases. Moreover, it is found that the SR weakens but resonance range becomes wider with the increase of c on the SW neural network.

Enhanced vibrational resonance in a single neuron with chemical autapse for signal detection

Many animals can detect the multi-frequency signals from their external surroundings.The understanding for underlying mechanism of signal detection can apply the theory of vibrational resonance,in which the moderate high frequency driving can maximize the nonlinear system's response to the low frequency subthreshold signal.In this work,we study the roles of chemical autapse on the vibrational resonance in a single neuron for signal detection.We reveal that the vibrational resonance is strengthened significantly by the inhibitory autapse in the neuron,while it is weakened typically by the excitatory autapse.It is generally believed that the inhibitory synapse has a suppressive effect in neuronal dynamics.However,we find that the detection of the neuron to the low frequency subthreshold signal can be improved greatly by the inhibitory autapse.Our finding indicates that the inhibitory synapse may act constructively on the detection of weak signal in the brain and neuronal system.

Collective stochastic resonance behaviors of two coupled harmonic oscillators driven by dichotomous fluctuating frequency

The collective behaviors of two coupled harmonic oscillators with dichotomous fluctuating frequency are investigated,including stability, synchronization, and stochastic resonance(SR). First, the synchronization condition of the system is obtained. When this condition is satisfied, the mean-field behavior is consistent with any single particle behavior in the system. On this basis, the stability condition and the exact steady-state solution of the system are derived. Comparative analysis shows that, the stability condition is stronger than the synchronization condition, that is to say, when the stability condition is satisfied, the system is both synchronous and stable. Simulation analysis indicates that increasing the coupling strength will reduce the synchronization time. In weak coupling region, there is an optimal coupling strength that maximizes the output amplitude gain(OAG), thus the coupling-induced SR behavior occurs. In strong coupling region, the two particles are bounded as a whole, so that the coupling effect gradually disappears.

Combined resonance of low pressure cylinder-generator rotor system with bending-torsion coupling

A nonlinear model of a low pressure cylinder-generator rotor system is presented to study sub-synchronous resonance and combined resonance. Analytical results are obtained by an averaging method. Transition sets and bifurcation diagrams are obtained based on the singularity theory for the two-state variable system. The bifurcation characteristics are analyzed to provide a basis for the optimal design and fault diagnosis of the rotor system. Finally, the theoretical results are verified with the numerical results.

Bifurcation analysis for an SMIB power system with series capacitor compensation associated with sub-synchronous resonance

In this paper,an introduction to the bifurcation theory and its applicability to the study of sub-synchronous resonance (SSR) phenomenon in power system are presented. The continuation and bifurcation analysis software AUTO97 is adopted to investigate SSR for a single-machine-infinite-bus power system with series capacitor compensation. The investigation results show that SSR is the result of unstable limit cycle after bifurcation. When the system exhibits SSR, some complex periodical orbit bifurcations, such as torus bifurcation and periodical fold bifurcation, may happen with the variation of limit cycle. Furthermore, the initial operation condition may greatly influence the ultimate state of the system. The time-domain simulation is carried out to verify the effectiveness of the results obtained from the bifurcation analysis.

Performance Analysis of PI and Fuzzy Control for Modified LCC Resonant Converter Incorporating Boost Converter

In this paper, the modified LCC type of series-parallel Resonant Converter (RC) was designed and state-space modeling analysis was implemented. In this proposed converter, one leg of full bridge diode rectifier is replaced with Synchronous Rectifier (SR) switches. The proposed LCC converter is controlled using frequency modulation in the nominal state. During hold-up time, the SRswitches control is changed from in-phase to phase-shifted gate signal to obtain high DC voltage conversion ratio. Furthermore, the closed loop PI and fuzzy provide control on the output side without decreasing the switching frequency. The parameter such as conduction loss on primary and secondary side, switching loss, core and copper also reduced. Simultaneously, the efficiency is increased about 94.79 is realized by this scheme. The proposed converter with an input of 40 V is built to produce an output of 235 V with the help of ZVS boost converter [1] even under line and load disturbances. As a comparison, the closed loop fuzzy controller performance is feasible and less sensitive than PI controller.

Effects of Coupling Distance on Synchronization and Coherence in Chaotic Neural Networks

Effects of coupling distance on synchronization and coherence of chaotic neurons in complex networks arenumerically investigated.We find that it is not beneficial to neurons synchronization if confining the coupling distanceof random edges to a limit d_(max),but help to improve their coherence.Moreover,there is an optimal value of d_(max) atwhich the coherence is maximum.

应用于储能系统的CLLLC谐振变换器控制策略研究

动态性能和运行效率是CLLLC谐振变换器的重要性能指标。针对传统电压闭环控制加入电流驱动同步整流后系统动态性能进一步变差的问题,提出一种谐振电流内环的电压电流双闭环变频控制策略,并给出双环控制和同步整流的综合控制方法。首先根据变换器的增益特性,分析电感比和品质因数对增益曲线和效率的影响,并据此进行谐振参数设计;其次根据不同谐振状态下的谐振电流特性实现同步整流;最后引入谐振电流内环控制,实现双环控制和同步整流的综合控制。仿真结果表明,所提综合控制策略能够产生精确的同步整流驱动信号,相比于传统电压闭环控制,能够显著改善变换器对负载扰动和电压扰动的动态性能。

基于比例谐振内模扩张状态观测器的PMLSM推力波动抑制策略

定位力是永磁同步直线电机(PMLSM)产生推力波动的主要原因,导致振动和噪声,恶化驱动系统运行性能。针对这一问题,该文提出一种基于比例谐振内模扩张状态观测器(PR-IMESO)的PMLSM推力波动抑制策略以提高系统控制精度和运行性能。首先,对PMLSM推力波动进行建模与分析,针对推力波动中占比较大的定位力分量,根据内模原理研究考虑定位力模型的内模扩张状态观测器(IMESO),并在观测器中引入谐振项以加强对二次脉动定位力的抑制。所提出抑制策略对PMLSM定位力具有良好的观测及补偿能力,还可对其余未建模的复杂动子推力波动进行抑制,具有较好的推力波动整体抑制效果。最后,在一台750 W的PMLSM实验平台上验证所提出抑制策略的有效性。

不平衡电网下无刷双馈风电系统的虚拟同步发电机控制

无刷双馈发电机(brushless doubly-fed reluctance generator,BDFG)在风力发电领域有着广阔的应用前景。基于虚拟同步发电机(virtual synchronous generator,VSG)的无刷双馈风电系统具有一定的电网频率支撑能力,但在电网电压不平衡工况下运行性能较差。提出了一种不平衡电网工况下无刷双馈风电系统的虚拟同步发电机策略,来降低不平衡的电网电压对BDFG系统的影响;其核心思想为使用原有BDFG-VSG来控制正序分量,在功率绕组正向同步旋转坐标系下使用基于降阶广义积分器(reduced order generalized integrator,ROGI)的直接谐振控制调节负序分量。详细分析了电网电压不平衡对BDFG各电量的影响,据此提出了5种可供选择的优化目标,最后通过仿真验证了该策略的有效性。所提出的策略可抑制不平衡电网工况下BDFG的各电量中的负序分量或二倍频分量,无需计算负序电流的参考值,对电网具有友好性。

CLLC谐振变换器同步整流软开关失效分析与应对

同步整流(SR)是提高CLLC谐振变换器运行效率的有效方法,但由于功率管寄生电容等因素的影响,同步整流存在软开关失效的风险。因此,为同时实现同步整流和软开关,在变换器副边不控整流的基础上,分析了不同运行状态下同步整流软开关的失效原因,以及软开关实现的有效范围。提出了不同运行状态下的同步整流数字控制方法,可在保证实现同步整流软开关的同时,提高同步整流的运行范围,从而保证变换器在不同运行状态下的运行效率。同时,改进了不同运行状态下同步整流开通和关断时刻的计算方法,使得同步整流的控制无需电流传感器和其他额外硬件电路的参与,可应用于原本无同步整流控制相关硬件的双向CLLC谐振变换器中。搭建了实验平台,验证了所提方法的有效性。

电网次同步振荡对光伏发电系统的影响分析及抑制策略研究

在电网发生次同步振荡(sub-synchronous oscillation,SSO)时,光伏(photovoltaic,PV)并网逆变器的工作性能会受到干扰,影响PV发电系统的稳定性。针对这一问题,文中首先分析锁相环(phase-locked loop,PLL)输出相位扰动对于坐标变换过程的影响,建立计及相位扰动的PV并网逆变器的数学模型,梳理电网SSO对PV并网逆变器产生扰动的机理,并将扰动分为物理扰动量以及误差扰动量;其次,设计改进型PLL以消除相位引起的误差扰动量对PV发电系统的影响;再次,针对不同目标下的抑制效果进行对比分析,同时确定振荡电压特性对控制器产生影响的关键因素。依据上述研究,提出一种基于自适应准谐振控制器的PV发电系统功率振荡抑制策略。最后,通过搭建实验平台,对所提控制策略的有效性进行验证。

基于可变电感的CLLC谐振变换器

针对CLLC谐振变换器调频范围过宽带来的磁性元件设计困难问题,提出一种基于可变电感的CLLC谐振变换器及其控制策略。分析变换器的电压增益特性以及可变电感的工作原理,设计CLLC同步整流控制电路,采用调频加调感的控制方式完成闭环调节。搭建了CLLC原理样机并验证了所提方案,试验表明所提变换器在各极限工况下均可实现零电压开通(ZVS)并完成电压增益调节,在轻载时具有良好的降压特性,可在大幅缩减调频范围的同时,实现变换器的高效率运行。