Numerical approach for the evolution of spin-boson systems and its application to the Buck–Sukumar model

We study the evolution properties of spin-boson systems by a systematic numerical iteration approach, which performs well in the whole coupling regime. This approach evaluates a set of coefficients in the formal expression of the time-dependent Schr?dinger equation by expanding the initial state in Fock space. This set of coefficients is unique for the spin-boson Hamiltonian studied, allowing one to calculate the time evolution from different initial states. To complement our numerical calculations, we apply the method to the Buck–Sukumar model. We find that when the ground-state energy of the model is unbounded and no ground state exists in a certain parameter space, the time evolution of the physical quantities is naturally unstable.     

暗怪波的相互作用

以耦合非线性薛定谔方程为理论模型,数值研究了两个一阶暗怪波在正常色散单模光纤中的相互作用.基于一阶暗怪波精确解,采用分步傅里叶数值模拟法,从间距、相位差和振幅系数比方面讨论相邻两个一阶暗怪波之间的相互作用.基于二阶暗怪波精确解,讨论了两个一阶暗怪波的非线性相互作用.研究结果表明:同相位情况下,间距参数T1为0、5、20时,相邻两个一阶暗怪波相互作用激发产生“扭结型”暗怪波.相比较于单个暗怪波发生能量的弥散,“扭结型”暗怪波分裂形成多个次暗怪波.反相位情况下,间距参数T1为2、7、12时,相邻两个一阶暗怪波相互作用也可以激发产生“扭结型”暗怪波.并且“扭结型”暗怪波初始激发的空间位置偏离原始单个暗怪波的位置5.振幅系数比越大,该空间位置越接近5.二阶暗怪波可以看作是两个一阶暗怪波的非线性叠加,复合型和三组分型二阶暗怪波与相邻两个一阶暗怪波的相互作用略有相似.     

On the Variability of Heart Rate Variability—Evidence from Prospective Study of Healthy Young College Students

Heart rate variability (HRV) has been widely used as indices for autonomic regulation, including linear analyses, entropy and multi-scale entropy based nonlinear analyses, and however, it is strongly influenced by the conditions under which the signal is being recorded. To investigate the variability of healthy HRV under different settings, we recorded electrocardiograph (ECG) signals from 56 healthy young college students (20 h for each participant) at campus using wearable single-lead ECG device. Accurate R peak to R peak (RR) intervals were extracted by combing the advantages of five commonly used R-peak detection algorithms to eliminate data quality influence. Thorough and detailed linear and nonlinear HRV analyses were performed. Variability of HRV metrics were evaluated from five categories: (1) different states of daily activities; (2) different recording time period in the same day during free-running daily activities; (3) body postures of sitting and lying; (4) lying on the left, right and back; and (5) gender influence. For most of the analyzed HRV metrics, significant differences (p < 0.05) were found among different recording conditions within the five categories except lying on different positions. Results suggested that the standardization of ECG data collection and HRV analysis should be implemented in HRV related studies, especially for entropy and multi-scale entropy based analyses. Furthermore, this preliminary study provides reference values of HRV indices under various recording conditions of healthy young subjects that could be useful information for different applications (e.g., health monitoring and management).     

An improved evaluation of the neutron background in the PandaX-Ⅱ experiment

In dark matter direct detection experiments,neutron is a serious source of background,which can mimic the dark matter-nucleus scattering signals.In this paper,we present an improved evaluation of the neutron background in the PandaX-II dark matter experiment by a novel approach.Instead of fully relying on the Monte Carlo simulation,the overall neutron background is determined from the neutron-induced high energy signals in the data.In addition,the probability of producing a dark-matter-like background per neutron is evaluated with a complete Monte Carlo generator,where the correlated emission of neutron(s)andγ(s)in the(α,n)reactions and spontaneous fissions is taken into consideration.With this method,the neutron backgrounds in the Run 9(26-ton-day)and Run 10(28-ton-day)data sets of PandaX-II are estimated to be(0.66±0.24)and(0.47±0.25)events,respectively.     

Establishment of the tension stress model considering metal lateral flow for foil rolling

In rolling production, the foil flatness quality is judged by detecting the lateral distribution of the front tension stress. Currently, because of the inaccuracy of the tension control model, there are still many flatness defects in foil rolling production. For the tension stress model of foil rolling, the primary problem is the inaccuracy of the metal lateral flow model. Therefore, based on Fleck’s foil rolling theory, a new model of the lateral displacement in the foil deformation region is established by using the principle of minimum potential energy. Next, a tension stress model is established, which takes the effect of the metal lateral flow into account. Last, using a laboratory 20-high rolling mill as the research object, the finite element model of foil rolling is established, and the accuracy of the new model is demonstrated by comparing the theoretical calculations with the simulation results.

     

Development of a Genus-Universal Nucleotide Signature for the Identification and Supervision of Ephedra-Containing Products

Ephedra plants generally contain ephedrine alkaloids, which are the critical precursor compounds of methamphetamine (METH). METH could cause serious physical and mental damage, and therefore Ephedra materials are strictly in supervision internationally. However, unlawful utilization of Ephedra herbs and its products still exist. Thus, it is imperative to establish a universal method for monitoring Ephedra ingredients in complex mixtures and processed products. In this study, 224 ITS2 sequences representing 59 taxa within Ephedra were collected, and a 23-bp genus-level nucleotide signature (GTCCGGTCCGCCTCGGCGGTGCG) was developed for the identification of the whole genus. The specific primers MH-1F/1R were designed, and 125 individuals of twelve Ephedra species/varieties were gathered for applicability verification of the nucleotide signature. Additionally, seven batches of Chinese patent medicines containing Ephedra herbs were used to test the application of the nucleotide signature in complex and highly processed materials. The results demonstrated that the 23-bp molecular marker was unique to Ephedra and conserved within the genus. It can be successfully utilized for the detection of Ephedra components in complex preparations and processed products with severe DNA degradation. The method developed in this study could undoubtedly serve as a strong support for the supervision of illegal circulation of Ephedra-containing products.     

Molecular Weight Distribution Control for Polymerization Processes Based on the Moment-Generating Function

The molecular weight distribution is an important factor that affects the properties of polymers. A control algorithm based on the moment-generating function was proposed to regulate the molecular weight distribution for polymerization processes in this work. The B-spline model was used to approximate the molecular weight distribution, and the weight state space equation of the system was identified by the subspace state space system identification method based on the paired date of B-spline weights and control inputs. Then, a new performance criterion mainly consisting of the moment-generating function was constructed to obtain the optimal control input. The effectiveness of the proposed control method was tested in a styrene polymerization process. The molecular weight distribution of the styrene polymers can be approximated by the B-spline model effectively, and it can also be regulated towards the desired one under the proposed control method.     

Side-by-side comparison of disposable microchips with commercial capillary cartridges for application in capillary isoelectric focusing with whole column imaging detection

Simple-structured, well-functioned disposable poly(dimethylsiloxane) (PDMS) microchips were developed for capillary isoelectric focusing with whole column imaging detection (CIEF-WCID). Side-by-side comparison of the developed microchips with well-established commercial capillary cartridges demonstrated that the disposable microchips have comparable performance as well as advantages such as absence of lens effect and possibility of high-aspect-ratio accompanied with a dramatic reduction in cost.     

Crystal structures and thermal decomposition kinetics of lanthanide complexes with 3,4,5-trimethoxybenzoic acid and 1,10-phenanthroline

A series of lanthanide complexes with the 3,4,5-trimethoxybenzoic acid(3,4,5-tmoba) and 1,10-phenanthroline(phen),[Ln(3,4,5-tmoba) 3 phen] 2(Ln = Pr(1),Nd(2) and Ho(3)),have been synthesized and characterized by a series of techniques including elemental analysis,IR spectra,X-ray crystallography and TG/DSC-FTIR technology.The three complexes have two kinds of coordination modes,in which the Pr 3+ and Nd 3+ cations are nine-coordinated and the Ho 3+ cation is eight-coordinated.The three-dimensional IR accumulation spectra of gaseous products for complexes 1-3 were analyzed and the gaseous products were identified by the typical IR spectra obtained from the 3D surface graphs.Meanwhile,we obtained the activation energy E of the first steps of complexes 1-3 by the integral isoconversional non-linear(NL-INT) method and discussed the non-isothermal kinetics of complexes 1-3 using the Malek method.Finally,SB(m,n) was defined as the kinetic method of the first-step thermal decomposition.The thermodynamic parameters △G≠,△H≠ and △S≠ of activation at the peak temperature were also calculated.     

Multi-Sensor Vibration Signal Based Three-Stage Fault Prediction for Rotating Mechanical Equipment

In order to reduce maintenance costs and avoid safety accidents, it is of great significance to carry out fault prediction to reasonably arrange maintenance plans for rotating mechanical equipment. At present, the relevant research mainly focuses on fault diagnosis and remaining useful life (RUL) predictions, which cannot provide information on the specific health condition and fault types of rotating mechanical equipment in advance. In this paper, a novel three-stage fault prediction method is presented to realize the identification of the degradation period and the type of failure simultaneously. Firstly, based on the vibration signals from multiple sensors, a convolutional neural network (CNN) and long short-term memory (LSTM) network are combined to extract the spatiotemporal features of the degradation period and fault type by means of the cross-entropy loss function. Then, to predict the degradation trend and the type of failure, the attention-bidirectional (Bi)-LSTM network is used as the regression model to predict the future trend of features. Furthermore, the predicted features are given to the support vector classification (SVC) model to identify the specific degradation period and fault type, which can eventually realize a comprehensive fault prediction. Finally, the NSF I/UCR Center for Intelligent Maintenance Systems (IMS) dataset is used to verify the feasibility and efficiency of the proposed fault prediction method.