基于线上线下结合的无机定性分析实验教学

针对在实验室开设定性分析实验受到的制约,设计并开设了"无机化合物的性质与鉴定"虚拟实验,以作为常规无机定性分析实验的重要补充和扩展。虚拟实验和传统实验一并开设,构成线上线下结合的教学模式,完善知识体系,全面培养学生的无机定性分析能力。     

自动化质谱图解卷积和鉴定系统用于鉴定含痕量杂原子的石油馏分（英文）

Here we present a simple yet effective gas chromatography-mass spectrometry (GC-MS) identification approach for the detection of heteroatom-containing compounds (HACCs) in petroleum fractions. The MS/AMDIS (Automated Mass Spectral Deconvolution and Identification System) program was used to identify parts per million (ppm) HACC concentrations in petroleum fractions in place of traditional techniques (extraction and standard injection). Polycyclic aromatic sulfur heterocycles (S-PAHs) were used as model compounds to confirm the validity of the AMDIS identifiers, which were compared with extracted results using the off-line X-calibur software. AMDIS was able to identify ppm concentrations of S-PAHs in oil condensate. There was good agreement between experimental and AMDIS identification results for S-PAHs in oil condensate. AMDIS was also used to detect nitrogen-containing compounds (NCCs) and alkylphenols in oil condensate. Our results confirmed the presence of 2-methylbenzothiazole, carbazole, and 2,4-ditertbutyl phenol. In a crude oil sample, AMDIS identification of m/z=191 biomarkers was consistent with empirical results. Therefore, AMDIS can help to reduce the number of experimental steps in identification protocols.     

A data-driven,high-throughput methodology to determine tissue-specific differentially methylated regions able to discriminate body fluids

Tissue-specific differentially methylated regions (tDMRs) are regions of the genome with methylation patterns that modulate gene expression in those tissue types. The detection of tDMRs in forensic evidence can permit the identification of body fluids at trace levels. In this report, we have performed a bioinformatic analysis of an existing array dataset to determine if new tDMRs could be identified for use in body fluid identification from forensic evidence. Once these sites were identified, primers were designed and bisulfite modification was performed. The relative methylation level for each body fluid at a given locus was then determined using qPCR with high-resolution melt analysis (HRM). After screening 127 tDMR's in multiple body fluids, we were able to identify four new markers able to discriminate blood (2 markers), vaginal epithelia (1 marker) and buccal cells (1 marker). One marker for each target body fluid was also tested with pyrosequencing showing results consistent with those obtained by HRM. This work successfully demonstrates the ability of in silico analysis to develop a novel set of tDMRs capable of being differentiated by real time PCR/HRM. The method can rapidly determine the body fluids left at crime scenes, assisting the triers of fact in forensic casework.     

Breaking chaotic shift key communication via adaptive key identification

This paper proposes an adaptive parameter identification method for breaking chaotic shift key communication from the transmitted signal in public channel. The sensitive dependence property of chaos on parameter mismatch is used for chaos adaptive synchronization and parameter identification. An index function about the synchronization error is defined and conjugate gradient method is used to minimize the index function and to search the transmitter's parameter (key). By using proposed method, secure key is recovered from transmitted signal generated by low dimensional chaos and hyper chaos switching communication. Multi-parameters can also be identified from the transmitted signal with noise.     

Perspective methods of human identification: Ear biometrics

Geometrical methods of feature extraction from ear images in order to perform human identification are presented. Geometrical approach is motivated by the actual procedures used by police and forensic experts (so-called ear otoscopy). In their work, geometrical features of ears such as size, height, width, and shapes of earlobe are useful and valid proofs of identity. The contribution of the article is development of the new and original methods of geometrical feature extraction from 2D ear images. Four novel algorithms of ear feature extraction from contour images are described in detail. Moreover, identification results obtained for each of the methods, based on the distance of feature vectors in the feature space, are presented.     

Adaptive generalized projective synchronization of two different chaotic systems with unknown parameters

This paper presents a general method of the generalized projective synchronization and the parameter identification between two different chaotic systems with unknown parameters. This approach is based on Lyapunov stability theory, and employs a combination of feedback control and adaptive control. With this method one can achieve the generalized projective synchronization and realize the parameter identifications between almost all chaotic （hyperchaotic） systems with unknown parameters. Numerical simulations results are presented to demonstrate the effectiveness of the method.     

Transient Nutation EPR Spectroscopy of Condensed Media (Review)

The application of transient nutations in EPR spectroscopy of condensed media is considered. The main methods of formation and observation of transient nutations are presented. The laws governing this phenomenon in twolevel and multilevel spin systems and also in inhomogeneous broadening of EPR lines are described. Recent advances in the use of transient nutations to separate overlapping spectra, identify quantum numbers and quantum transitions, investigate the kinetics of photoinduced paramagnetic centers, and determine relaxation times for a wide range of crystalline and disordered media are presented.     

Parameter identification and synchronization of spatiotemporal chaos in an uncertain Gray-Scott system

The zero-asymptotic property of sliding variables in discrete systems is extended to a continuous one and applied to partial differential equations which describe spatiotemporal chaos. A method of chaos synchronization and parameter identification is proposed. The synchronization controllers and the parameter recognizers are designed. The uncertain Gray-Scott system is taken as an example to verify the effectiveness of the method. Simulation results show that the identification variables in the parameter recognizers may take the place of the unknown parameters in both target and response systems. Global synchronization of the two spatiotemporal chaotic systems with uncertain parameters may be realized quickly after controllers are added. Supported by the Natural Science Foundation of Liaoning Province, China (Grant No. 20052151) and the Innovative Team Program of Liaoning Educational Committee     

Minimal dynamic characterization of tree-like multibody systems

The dynamic model of tree-like multibody systems is linear with respect to the parameters of mass distribution for instance when barycentric parameters are used. Thus, assuming that the parameters related to the kinematics are perfectly known, these quantities can be estimated through linear regression techniques. The necessary data are obtained by measuring the joint forces and/or torques and the resulting motion given in terms of positions, velocities and accelerations. An alternative method uses measurements of the reaction forces and torques applied to the bedplate.The linearity of the dynamic and reaction models with respect to the barycentric quantities does not however imply that the latter constitute the minimum set of parameters characterizing the mass distribution of the system. In other words, some barycentric parameters may disappear from the models or may be redundant in the sense that they appear only via linear combinations. In the first case they are not identifiable, while in the second case the linear regression technique leads to estimated values which are correct for the combinations but can be erroneous for the individual parameters.The various options taken to derive the dynamic and reaction models by use of the ROBOTRAN programme are briefly reviewed. Then the rules leading to the minimal parametrization are presented and illustrated by means of a practical example related to a robot calibration problem.     

Oil spill identification by high-speed HPLC

The use of high-speed HPLC in oil spill identification problems has been evaluated in terms of analysis time and reliability. The aromatic fraction was analyzed by reverse-phase chromatography on a 3 μm packing, with detection at 210 and 287 nm, in less than 20 minutes. The profiles exhibited by several Spanish and Middle East crude oils were differentiated by simple statistical parameters. The effect of environmental weathering on the samples has also been investigated. An Arabian light crude oil was still identifiable after four months' simulated marine weathering.