Effective suppression of beta oscillation in Parkinsonian state via a noisy direct delayed feedback control scheme

This work explores the function of the noisy direct delayed feedback(NDDF)control strategy in suppressing the pathological oscillations in the basal ganglia(BG)with Parkinson’s disease(PD).Deep brain stimulation(DBS)alleviates the PD state fantastically.However,due to its unclear mechanism and open-loop characteristic,it is challenging to further improve its effects with lower energy expenditure.The noise stimulus performs competitively in alleviating the PD state theoretically,but it cannot adapt to the neural condition timely and automatically due to its open-loop control scheme.The direct delayed feedback(DDF)control strategy is able to disturb excessive synchronous effectively.Therefore,the NDDF control strategy is proposed and researched based on a BG computational model,which can reflect the intrinsic properties of the BG neurons and their connections with thalamic neurons.Simulation results show that the NDDF control strategy with optimal parameters is effective in removing the pathological beta oscillations.By comparison,we find the NDDF control strategy performs more excellent than DDF in alleviating PD state.Additionally,we define the multiple-NDDF control strategy and find that the multiple-NDDF with appropriate parameters performs better than NDDF.The obtained results contribute to the cure for PD symptoms by optimizing the noise-induced improvement of the BG dysfunction.     

Spiking patterns of a hippocampus model in electric fields

We develop a model of CA3 neurons embedded in a resistive array to mimic the effects of electric fields from a new perspective. Effects of DC and sinusoidal electric fields on firing patterns in CA3 neurons are investigated in this study. The firing patterns can be switched from no firing pattern to burst or from burst to fast periodic firing pattern with the increase of DC electric field intensity. It is also found that the firing activities are sensitive to the frequency and amplitude of the sinusoidal electric field. Different phase-locking states and chaotic firing regions are observed in the parameter space of frequency and amplitude. These findings are qualitatively in accordance with the results of relevant experimental and numerical studies. It is implied that the external or endogenous electric field can modulate the neural code in the brain. Furthermore, it is helpful to develop control strategies based on electric fields to control neural diseases such as epilepsy.     

Using Reduced Graphene Oxide to Generate Q-Switched Pulses in Er-Doped Fiber Laser

Using the reduced graphene oxide(rGO) as a saturable absorber(SA) in an Er-doped fiber(EDF) laser cavity,we obtain the Q-switching operation. The rGO SA is prepared by depositing the GO on fluorine mica(FM) using the thermal reduction method. The modulation depth of rGO/FM is measured to be 3.2%. By incorporating the rGO/FM film into the EDF laser cavity, we obtain stable Q-switched pulses. The shortest pulse duration is3.53 μs, and the maximum single pulse energy is 48.19 nJ. The long-term stability of working is well exhibited.The experimental results show that the rGO possesses potential photonics applications.     

Reduced graphene oxide as saturable absorbers for erbium-doped passively mode-locked fiber laser

We demonstrate a nanosecond mode-locked erbium-doped fiber laser(EDFL)based on a reduced graphene oxide(RGO)saturable absorber(SA).The RGO SA is prepared by depositing the graphene oxide(GO)on fluorine mica through thermal reduction of GO.A scanning electron microscope(SEM),Raman spectrometer,and x-ray photoelectron spectroscopy(XPS)are adopted to analyze the RGO characteristics.The results show that the reduction degree of graphene oxide is very high.By embedding the RGO SA into the EDFL cavity,a stable mode-locked fiber laser is achieved with a central wavelength of 1567.29 nm and repetition rate of 12.66 MHz.The maximum output power and the minimum pulse duration are measured to be 18.22 mW and 1.38 ns respectively.As far as we know,the maximum output power of18.22 mW is higher than those of other nanosecond mode-locked oscillators reported.Such a nanosecond pulse duration and megahertz repetition rate make this mode-locked erbium-doped fiber laser a suitable seed oscillator for high-power applications and chirped pulse amplifications.     

晶体相场方法模拟纳米孪晶结构

应用双模晶体相场模型,模拟共格纳米孪晶结构.结果表明:球状晶粒生长成的共格孪晶片层,在共格面上的原子排列有变形,容易出现位错;条状晶粒凝固生长成的共格孪晶界,比用球状晶粒长大生成的共格孪晶界的原子排列整齐.应用晶体相场模型,可以精确计算纳米孪晶带的厚度,设计和控制带内的原子层数,实现人工操纵纳米共格孪晶片层结构,指导实验研究纳米孪晶结构及其与性能的关系.     

Modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case studying

Manual acupuncture is widely used for pain treatment and stress control. Previous studies on acupuncture have shown its modulatory effects on functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of threshold, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas characteristic path length is shorter. We provide further support for the presence of "small-world" network characteristics in functional networks by acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of acupuncture effects on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.     

β-氨基酸的合成: 等当体方法的应用

β-氨基酸是一类在药物开发和生物研究中有广泛应用的中间体. 由等当体合成β-氨基酸的方法具有结构定制、合成产物丰富、直观等特点, 是β-氨基酸合成领域中不可或缺的合成方法. 重点介绍近年来该领域具有代表性的工作.     

制备条件影响碳酸羟基磷灰石晶格的计算分析

在碳酸羟基磷灰石(CHA)结构分析中,对A型取代(CO₃^2-取代OH^-)和B型取代(CO₃^2-取代PO₄^3-)2种取代的稳定性仍存有争议。为了研究碳酸取代的可能位置和2种取代稳定性,本文利用计算机辅助手段详细研究了不同反应顺序和不同反应试剂对碳酸羟基磷灰石晶体结构的影响。本实验分别采用含Na和不含Na 2种不同的反应试剂,分别在HA生成过程中和HA生成以后加入CO₃^2-,通过离子共沉淀法制备了4种碳酸羟基磷灰石。通过X射线衍射(XRD)、红外光谱(IR)对他们的结构和基团进行了表征,并用Jade 6.5, Materials Studio 4.0以及Origin 7.0进行了精修、计算和拟合。结果表明,无论工艺过程如何变化,均主要生成晶体能量较低、晶格结构稳定的B型取代碳酸羟基磷灰石;与普通磷灰石相比,由于存在晶格畸变,因此碳酸取代磷灰石的结晶度下降;碳酸根在反应溶液中的浓度影响CHA的晶格畸变程度,较高游离碳酸浓度引起的晶格畸变大;Na⁺的引入,可以降低碳酸羟基磷灰石中的晶格畸变,从而提高结晶度;含Na的B型取代主要是取代Ca(Ⅱ)位置的Ca离子。IR分析结果表明四种碳酸羟基磷灰石中的CO₃^2-均以B型取代为主,通过对870 cm^-1附近峰的拟合,计算出材料中A型取代和B型取代的比值。     

Parkinsonian oscillations and their suppression by closed-loop deep brain stimulation based on fuzzy concept

This paper provides an adaptive closed-loop strategy for suppressing the pathological oscillations of the basal ganglia based on a variable universe fuzzy algorithm. The pathological basal ganglia oscillations in the theta (4-9 Hz) and beta (12-35 Hz) frequency bands have been demonstrated to be associated with the tremor and rigidity/bradykinesia symptoms in Parkinson's disease (PD). Although the clinical application of open-loop deep brain stimulation (DBS) is effective, the stimulation waveform with the fixed parameters cannot be self-adjusted as the disease progresses, and thus the stimulation effects go poor. To deal with this difficult problem, a variable universe fuzzy closed-loop strategy is proposed to modulate different PD states. We establish a cortico-basal ganglia-thalamocortical network model to simulate pathological oscillations and test the control effect. The results suggest that the proposed closed-loop control strategy can accommodate the variation of brain states and symptoms, which may become an alternative method to administrate the symptoms in PD.     

基于粗集理论的组合预测法在无形资产评估中的应用

针对如何评估企业无形资产的问题,运用基于粗集理论的组合预测方法,建立了企业无形资产评估的数量模型。该模型的特点是将组合预测方法中权系数的确定问题转化为粗集理论中的属性重要性评价问题,这样就在很大程度上克服了传统组合预测方法中权系数确定主观性太大的缺陷,而使得权系数的确定更具客观性。最后,结合实例阐述了基于粗集理论的组合预测方法在企业无形资产评估中的应用,进一步说明了该方法的可行性和有效性。