DNA microsatellite analysis using ion-pair reversed-phase high-performance liquid chromatography

Genotyping based on short tandem repeat (STR) regions is used in human identification and parentage testing, gene mapping studies, cancer diagnostics, and diagnosis of hereditary diseases. Analysis of STR systems using slab gel electrophoresis requires lengthy and labor-intensive procedures. Therefore, alternative methods such as capillary electrophoresis or ion-pair reversed-phase high-performance liquid chromatography (IPRP HPLC) have been used to analyze DNA. IPRP HPLC offers an attractive substitute to gel electrophoresis for STR analysis because of the reduced analysis time, and there is no need for the waste disposal associated with radioisotopic, enzyme-linked, or fluorescence detection systems. We evaluated the use of IPRP HPLC for the sizing and typing of STR alleles from the HUMTHO1 locus. The IPRP HPLC conditions (column temperature, flow rate, percent organic modifier per minute) were optimized for the separation of PCR products. Using the optimized separation conditions, the alleles of the HUMTHO1 system were sized in their native state (double standard) with the use of internal markers. The typing results correlated 100% to accepted methods of DNA typing. The analysis time for the HUMTHO1 locus was less than 14 min, and the alleles could be peak captured for further examination following such as sequencing.     

Integrated portable polymerase chain reaction-capillary electrophoresis microsystem for rapid forensic short tandem repeat typing

A portable forensic genetic analysis system consisting of a microfluidic device for amplification and separation of short tandem repeat (STR) fragments as well as an instrument for chip operation and four-color fluorescence detection has been developed. The microdevice performs polymerase chain reaction (PCR) in a 160-nL chamber and capillary electrophoresis (CE) in a 7-cm-long separation channel. The instrumental design integrates PCR thermal cycling, electrophoretic separation, pneumatic valve fluidic control, and four-color laser excited fluorescence detection. A quadruplex Y-chromosome STR typing system consisting of amelogenin and three Y STR loci (DYS390, DYS393, DYS439) was developed and used for validation studies. The multiplex amplification of these 4 loci with 35 PCR cycles followed by CE separation and 4-color fluorescence detection was completed in 1.5 h. All the amplicons can be detected with a limit of detection of 20 copies of male standard DNA in the reactor. Real-world forensic analyses of oral swab and human bone extracts from case evidence were also successfully performed. Mixture analysis demonstrated that a balanced profile can be obtained even at a male-to-female template ratio of 1:10. The successful development and operation of this portable PCR-CE system establishes the feasibility of rapid point-of-analysis DNA typing of forensic casework, of mass disaster samples or of individuals at a security checkpoint.     

Arbitrary Lagrangian–Eulerian finite element simulation and experimental investigation of wavy interfacial morphology during high velocity impact welding

Finite element simulations of high strain rate forming processes are of significant interest to industry, but are challenging due to the coupled physics and dynamic nature of the processes. For instance, in high velocity impact welding, extremely high plastic strain regions develop. Thus, a traditional pure Lagrangian analysis is not able to accurately model the process due to excessive element distortion near the contact zone. In this study, the Arbitrary Lagrangian–Eulerian method (ALE) was used to simulate an impact welding process for two Al6061-T6 plates. The ALE method was able to numerically predict the temperature at the interface as well as the necessary process parameters to achieve a wavy morphology at the interface of the materials which is assumed to be a characteristic of a quality impact weld. This allowed the prediction of a weldability window, including separate regions for melting and purely solid state welds. To validate the proposed numerical model and wavy morphology regions, experimental tests with a Vaporizing Foil Actuator Welding (VFAW) process were conducted including Photon Doppler Velocimetry (PDV) measurements of the impact velocity. The numerical results were in good agreement with the experimental tests including the temperature prediction and interfacial melting observed through microstructural analyses.     

Prediction and control of surface roughness for the milling of Al/SiC metal matrix composites based on neural networks

In recent years, there has been a significant increase in the utilization of Al/SiC particulate composite materials in engineering fields, and the demand for accurate machining of such composite materials has grown accordingly. In this paper, a feed-forward multi-layered artificial neural network (ANN) roughness prediction model, using the Levenberg-Marquardt backpropagation training algorithm, is proposed to investigate the mathematical relationship between cutting parameters and average surface roughness during milling Al/SiC particulate composite materials. Milling experiments were conducted on a computer numerical control (CNC) milling machine with polycrystalline diamond (PCD) tools to acquire data for training the ANN roughness prediction model. Four cutting parameters were considered in these experiments: cutting speed, depth of cut, feed rate, and volume fraction of SiC. These parameters were also used as inputs for the ANN roughness prediction model. The output of the model was the average surface roughness of the machined workpiece. A successfully trained ANN roughness prediction model could predict the corresponding average surface roughness based on given cutting parameters, with a 2.08% mean relative error. Moreover, a roughness control model that could accurately determine the corresponding cutting parameters for a specific desired roughness with a 2.91% mean relative error was developed based on the ANN roughness prediction model. Finally, a more reliable and readable analysis of the influence of each parameter on roughness or the interaction between different parameters was conducted with the help of the ANN prediction model.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00326-x     

Biodegradation of Direct Red 5B, a textile dye by newly isolated Comamonas sp. UVS

Soil samples collected from the vicinity of "Manpasand textile industry", located near Ichalkaranji, India were studied for screening and isolation of bacterial strains capable of degradation of textile dyes. A potential strain was selected on the basis of rapid dye degradation and later identified as Comamonas sp. UVS. Comamonas sp. UVS showed 100% decolorization of Direct Red 5B (DR5B) dye at 40 degrees C and pH 6.5. The maximum Direct Red 5B concentration decolorized was 1100mg/l in nutrient broth within 125h. A numerical simulation with the Michaelis-Menten kinetics model gives an optimal value of 16.01+/-0.36mgdye/gcell/h for maximum rate (V(max)) and 7.97+/-0.21mg/l for the Michaelis constant (K(m)). The induction in the activities of laccase and LiP was observed during decolorization. These enzymes were inhibited by the addition of sodium azide. The biodegradation was monitored by UV-vis, FTIR spectroscopy and HPLC. The GCMS analysis indicated the presence of 7-benzoylamino-3-diazenyl-4-hydroxy-naphthalene-2-sulfonic acid in degraded product of the dye. The germination of Triticum aestivum seeds was inhibited with DR5B treatment but not with the treatment of dye degradation products.     

Effects of the local environment on CNT-based nanoelectronics: development of a microenvironment probe station

In this study, we report the development of a microenvironment probe station capable of detecting the effect of small changes to the local environment around a carbon nanotube conduction channel. The microenvironment probe station is highly versatile and is used to characterize alterations in carbon nanotube field effect transistor electrical behavior in response to changes in temperature, gas species, infrared and ultraviolet light. All devices were electrically characterized in atmospheric, ultrahigh vacuum and oxygen-rich environments. The results suggest that devices could be changed from n-type at 1 x 10(-8) torr through an intermediate ambipolar state at 1 x 10(-4) torr to p-type at atmosphere solely by increasing the oxygen concentration. The average resistance of these carbon nanotube field effect transistors after annealing was observed to decrease by approximately 54% from their initial value under ultrahigh vacuum to their final value in the presence of pure oxygen while corresponding threshold voltages shifts were also observed. Illumination with infrared light resulted in a approximately 10% increase in drain current with an estimated response time <1 fs due to photon-induced electron-hole pair generation. Illumination with ultraviolet light resulted in approximately 5-15% reduction in drain current due to photon-induced desorption of oxygen adsorbate.     

Quantitative measurements of loss on ignition in iron ore using laser-induced breakdown spectroscopy and partial least squares regression analysis

Laser-induced breakdown spectroscopy (LIBS) and partial least squares regression (PLSR) have been applied to perform quantitative measurements of a multiple-species parameter known as loss on ignition (LOI), in a combined set of run-of-mine (ROM) iron ore samples originating from five different iron ore deposits. Global calibration models based on 65 samples and their duplicates from all the deposits with LOI ranging from 0.5 to 10 wt% are shown to be successful for prediction of LOI content in pressed pellets as well as bulk ore samples. A global independent dataset comprising a further 60 samples was used to validate the model resulting in the best validation R(2) of 0.87 and root mean square error of prediction (RMSEP) of 1.1 wt% for bulk samples. A validation R(2) of 0.90 and an RMSEP of 1.0 wt% were demonstrated for pressed pellets. Data preprocessing is shown to improve the quality of the analysis. Spectra normalization options, automatic outlier removal and automatic continuum background correction, which were used to improve the performance of the PLSR method, are discussed in detail.     

A Model of Prediction of Forest‐Fire Hazard

A rather simple and physically substantiated deterministicprobabilistic expert system of prediction of forestfire hazard, which can be used in practice, is suggested. Results of the calculation by the verified model of drying of forest combustibles, which allows for partial pressure of water vapor, are compared with results obtained by different models and experimental data.     

Femtosecond measurements of two-photon absorption coefficients at lambda = 264 nm in glasses,crystals, and liquids

Using ultraviolet femtosecond pulses with high irradiance stability, we measured the two-photon absorption (TPA) coefficients in a number of substances with a total accuracy of approximately 10%. Six commercial fused-silica samples (KU-1, Coming 7940, SQ, Suprasil, Herasil, and Infrasil) possess TPA coefficients (beta values) of approximately 2 x 10(-11) cm/W. For crystalline quartz and sapphire, the following beta values were obtained: (1.2 +/- 0.2) x 10(-11) and (9.4 +/- 1.2) x 10(-11) cm/W, respectively. In beta-barium borate crystal the TPA coefficient depends on crystal cut, beam polarization, or both and varies from (47 +/- 5) x 10(-11) to (68 +/- 6) x 10(-11) cm/W. For eight liquids that were studied (water, heavy water, ethanol, methanol, hexane, cyclohexane, 1,2-dichloroethane, and chloroform) the beta value lies from (34 +/- 3) x 10(-11) to (95 +/- 11) x 10(-11) cm/W.     

Analysis of polymerase chain reaction products by on-line liquid chromatography-mass spectrometry for genotyping of polymorphic short tandem repeat loci.

Capillary ion-pair reversed-phase high-performance liquid chromatography (IP-RP-HPLC) was used to separate and purify DNA fragments amplified by the polymerase chain reaction (PCR) prior to their characterization by electrospray ionization mass spectrometry (ESI-MS). The investigation by ESI-MS of single- or double stranded species could be effortlessly selected by chromatography of the nucleic acids under either nondenaturing or denaturing conditions, which were realized by proper adjustment of the column temperature. ESI-MS detection sensitivity was improved by a factor of 10 upon replacement of 25 mM triethylammonium bicarbonate as ion-pair reagent by 25 mM butyldimethylammonium bicarbonate because of the applicability of higher acetonitrile concentrations to elute the DNA from the monolithic, poly(styrene/divinylbenzene)-based capillary columns. For fragments ranging in size from 67 to 84 base pairs, the mass accuracies and mass reproducibilities were typically better than 0.02 and 0.008%, respectively, which enabled the characterization and identification of the PCR products with high confidence. The hyphenated method was applied to the genotyping of polymorphic short tandem repeat (STR) loci from the human tyrosine hydroxylase gene (humTH01). The different alleles both in homo- and heterozygotes were identified on the basis of the masses of the single-stranded amplicons and were in full accordance with the alleles identified by conventional capillary electrophoretic sizing.     

基于回归分析与BP神经网络的风机噪声预测

针对能源问题和风力发电机组噪声检测过程复杂的现状,研究IEC 61400-11风力发电机组噪声测量技术标准,提出一种回归分析和BP神经网络相结合的方法,对风电机组噪声的A计权声压级进行预测。由风电现场采集的数据建立多元线性回归方程,求取回归系数,分析简化后,用较少的输入量训练BP神经网络,建立机组的噪声预测模型。将模型应用于新疆某风电场的实际测试过程中,效果良好,验证该方法的可行性和有效性。     

基于灰色模型的电动助力车车架耐振性试验寿命预测

选取了4款踏板式电动助力车车架,每款10个试件,采用JS-49整车振动试验机对每个试件进行耐振性测试,获取每个试件断裂时的振动循环次数。建立了各款车架的有限元振动分析模型,对振动试验进行仿真,提取了各款车架危险位置单元的Von Mises应力峰值,每款车架对应一个应力水平。将疲劳应力与振动循环次数的关系看作一个灰色系统,运用灰色系统方法建立了GM(1,1)模型,并求解了灰色系统模型的微分方程,得到了车架在振动试验中的疲劳寿命预测模型。为了对该模型的效果进行检验,另外选取了3款同类车架进行相同条件下的耐振性测试,每款车架6个试件。通过与试验结果进行对比,发现灰色模型预测的平均相对误差为4.08%,且相对于多项式拟合更能反映真实的应力-寿命的变化趋势。结果表明,可用灰色模型对此类产品的设计进行指导。     

基于IPSO-BP的船舶航迹预测研究

目的 面对复杂的海上交通及密集的物流交通流,及时有效地对船舶航迹进行跟踪预测显得尤为重要,针对传统船舶航迹预测方法精确度低且效率低下的问题,提出一种改进方法。方法 在船舶自动识别系统（AutomaticIdentificationSystem,AIS）数据的基础上,建立改进粒子群算法（IPSO）与BP神经网络相结合的船舶轨迹预测模型,利用船舶历史航行轨迹数据,实现对未来船舶运动的预测。选取宁波舟山港的船舶历史轨迹数据进行实验,并将IPSO-BP模型的实验结果与其他模型进行比较。结果 不同模型航迹预测对比结果表明,IPSO-BP模型的性能较好,其预测精度较高,适用于船舶轨迹预测。结论 使用IPSO-BP模型能够更加精准地预测船舶航迹,在船舶危险预警、船舶异常监测等方面具有重要的指导作用。     

Calibration transfer for solving the signal instability in quantitative headspace-mass spectrometry

It is reported that calibration transfer is able to compensate the variations in sensitivity in direct coupling of a headspace sampler to a mass spectrometer when used for quantification purposes using multivariate calibration techniques. This strategy of signal stability compensation allows the use of models constructed from large calibration standard sets without having to repeat their measurement even though variations occur in sensitivity, which may or may not be constant along the mass range. This technique offers advantages over the use of internal standards in this methodology and only requires the measurement of a small number of transfer samples with each set of unknown samples. The results obtained in the determination of six volatile organic compounds-benzene, toluene, ethylbenzene, and m-xylene (BTEX), methyl tert-butyl ether (MTBE), and mesitylene-are reported. To obtain an appropriate calibration set, a Plackett-Burman design with five levels of concentration for each component was employed. A PLS multivariate calibration model was constructed with a group of 25 samples. For selection of the optimum number of principal components, an external validation set (5 samples) was used and the prediction capacity of this set was checked with an additional group of samples that had not been used either in the construction or in the validation of the model. The results obtained can be considered highly satisfactory, and the methodology was successfully tested with natural matrixes (river and tap water).     

Electrogenerated chemiluminescence detection of amino acids based on precolumn derivatization coupled with capillary electrophoresis separation

A novel method for highly sensitive detection of primary and secondary amino acids with selective derivatization using acetaldehyde as a new derivatization reagent was proposed by capillary electrophoresis (CE) coupled with electrogenerated chemiluminescence (ECL) of tris(2,2'-bipyridine)ruthenium(II). The precolumn derivatization of these amino acids with acetaldehyde was performed in aqueous solution at room temperature for 1 h. Upon optimized derivatization, the ECL intensities and detection sensitivities of the amino acids were significantly enhanced by 20-70 times. Using four amino acids, arginine, proline, valine, and leucine, as model compounds, their derivatives could be completely separated by CE and sensitively detected by ECL within 22 min. The linear ranges were 0.5-100 microM for arginine and proline and 5-1000 microM for valine and leucine with the detection limits of 1 x 10(-7) (0.5 fmol, arginine), 8 x 10(-8) (0.4 fmol, proline), 1 x 10(-6) (5 fmol, valine), and 1.6 x 10(-6) M (8 fmol, leucine) at a signal-to-noise ratio of 3. The derivatization reactions and ECL process of amino acids were also proposed based on in situ Fourier transform infrared and ultraviolet spectrometric analyses.     

NIST mixed stain study 3: signal intensity balance in commercial short tandem repeat multiplexes

Short-tandem repeat (STR) allelic intensities were collected from more than 60 forensic laboratories for a suite of seven samples as part of the National Institute of Standards and Technology-coordinated 2001 Mixed Stain Study 3 (MSS3). These interlaboratory challenge data illuminate the relative importance of intrinsic and user-determined factors affecting the locus-to-locus balance of signal intensities for currently used STR multiplexes. To varying degrees, seven of the eight commercially produced multiplexes used by MSS3 participants displayed very similar patterns of intensity differences among the different loci probed by the multiplexes for all samples, in the hands of multiple analysts, with a variety of supplies and instruments. These systematic differences reflect intrinsic properties of the individual multiplexes, not user-controllable measurement practices. To the extent that quality systems specify minimum and maximum absolute intensities for data acceptability and data interpretation schema require among-locus balance, these intrinsic intensity differences may decrease the utility of multiplex results and surely increase the cost of analysis.     

Near-infrared analysis of ground barley for use as a feedstock for fuel ethanol production

The objective of this study was to explore the potential of near-infrared spectroscopy for determining the compositional quality properties of barley as a feedstock for fuel ethanol production and to compare the prediction accuracy between calibration models obtained using a Fourier transform near-infrared system (FT-NIR) and a dispersive near-infrared system. The total sample set contained 206 samples of three types of barley, hull-less, malt, and hulled varieties, which were grown at various locations in the eastern U.S. from 2002 to 2005 years. A new hull-less barley variety, Doyce, which was specially bred for potential use in ethanol production, was included in the sample set. One hundred and thirty-eight barley samples were used for calibration and sixty-eight were used for validation. Ground barley samples were scanned on both a FTNIR spectrometer (10 000 to 4000 cm(-1) at 4 cm(-1) resolution) and a dispersive NIR spectrometer (400 to 2498 nm at 10 nm resolution), respectively. Six grain components, moisture, starch, beta-glucan, protein, oil, and ash content, were analyzed as parameters of barley quality. Principal component analysis showed that barley samples could be classified by their types: hull-less, malt, and hulled. Partial least squares regression indicated that both FT-NIR and dispersive NIR spectroscopy have the potential to determine quality properties of barley with an acceptable accuracy, except for beta-glucan content. There was no predictive advantage in using a high-resolution FT-NIR instrument over a dispersive system for most components of barley.     

基于遗传BP网络的Mg-Sm-Zn-Zr合金应力预测模型及加工图

利用Gleeble-1500D试验机对新型Mg-Sm-Zn-Zr合金进行等温压缩实验,得到了该合金在350~450℃、0.001~1s-1条件下的真应力-应变曲线,应用遗传算法优化的BP神经网络建立起合金的应力预测模型,并对所建预测模型和考虑应变的Arrhenius本构模型进行了对比,采用预测数据并应用Murthy失稳准则绘制出该合金的热加工图,最后结合微观组织分析所绘制热加工图的合理性。结果表明,GA-BP模型预测值和实验值间的相关性系数为0.999,平均相对误差为1.469%,较应变补偿本构模型预测精度更高;热加工图设计合理,有效确认温度400~450℃、应变速率0.001~0.03s-1是最佳热加工范围,合金在该区域发生了动态再结晶。     

Evanescent fiber-optic chemical sensor for monitoring volatile organic compounds in water

The transport of trichloroethylene, 1,1,1-trichloroethane, and toluene in aqueous solutions through a polydimethylsiloxane film was modeled using a Fickian diffusion model to fit data obtained from an evanescent fiber-optic chemical sensor (EFOCS). The resultant diffusion coefficients for these analytes were respectively 3 × 10(-)(7), 5 × 10(-)(7), and 1 × 10(-)(7) cm(2)/s. Inclusion of an interfacial conductance term, defined as the ratio of the mass transport coefficient across the polymer surface and the analyte diffusion coefficient in the polymer, was required to accurately model the data. It was determined that the interfacial conductance terms were generally of the same order of magnitude for the analytes examined, suggesting a constant transport mechanism for the analytes. Linear chemometric algorithms were used to model the EFOCS response to aqueous mixtures of the three analytes with individual analyte concentrations between 20 and 300 ppm. Both partial least-squares and principal component regression algorithms performed comparably on the calibration sets, with cross-validated root-mean-squared errors of prediction for trichloroethylene, 1,1,1-trichloroethane, and toluene of approximately 26, 29, and 22 ppm, respectively. The resultant prediction model was then used to determine analyte concentrations in an independent data set with comparable precision.     

基于PDV技术的微型雷管爆炸驱动飞片速度测试研究

针对微型装药爆炸驱动飞片速度问题,搭建微型雷管爆炸驱动钛金属飞片速度测试装置,利用光子多普勒测速技术(photonic Doppler velocimetry,简称PDV),对直径0.7 mm的微型雷管爆炸驱动飞片的速度进行测试,获得小飞片的速度历程,可清晰观察到飞片速度成长、保持、降低的过程。研究了防护PDV光探头有机玻璃厚度对飞片速度的影响,结果显示:当增大有机玻璃厚度时,测试的飞片平均速度会减小,测试相对误差增大;研究了光探头端面与飞片表面不同距离对测试结果的影响,对速度曲线进行位移积分,结果显示:距离较小时,测试结果的一致性较好,速度、位移增长拐点出现时机较为一致。针对整个测试系统,分析了高斯光束条纹间距、防护玻璃、金属表面反射率、试验装置振动因素对测试精度的影响。