Exploring STR signal in the single‐ and multicopy number regimes: Deductions from an in silico model of the entire DNA laboratory process

Short tandem repeat (STR) profiling from DNA samples has long been the bedrock of human identification. The laboratory process is composed of multiple procedures that include quantification, sample dilution, PCR, electrophoresis, and fragment analysis. The end product is a short tandem repeat electropherogram comprised of signal from allele, artifacts, and instrument noise. In order to optimize or alter laboratory protocols, a large number of validation samples must be created at significant expense. As a tool to support that process and to enable the exploration of complex scenarios without costly sample creation, a mechanistic stochastic model that incorporates each of the aforementioned processing features is described herein. The model allows rapid in silico simulation of electropherograms from multicontributor samples and enables detailed investigations of involved scenarios. An implementation of the model that is parameterized by extensive laboratory data is publically available. To illustrate its utility, the model was employed in order to evaluate the effects of sample dilutions, injection time, and cycle number on peak height, and the nature of stutter ratios at low template. We verify the model's findings by comparison with experimentally generated data.     

Emulsions of Heavy Crude Oils. II. Viscous Responses and Their Influence on Emulsion Stability Measurements

The stability of 30 heavy crude oil emulsions was studied in a parallel-plate laboratory coalescer (DC field). Particularly, viscous responses and their influence on the emulsion stability measurements were investigated. In addition to highlighting previous results from the same experimental setup and discussing these based on recent experience, new results at different temperatures and volume fractions of water were presented. A new semi-empirical model for the characteristic time of the destabilization process was presented. The electrical forces were modelled with a point-dipole approximation and the hydrodynamic resistance to droplet transport was modelled with an empirical term including the logarithmic viscosity of the oil phase. The new model clearly performed much better than the previous model, particularly for very viscous crude oils. Studies of the performance of industrial electrocoalescers have showed that simple electrostatic theory can potentially explain complex separation phenomena when the resistance to the coalescence step is reduced by an efficient demulsifier. The ultimate goal is to build a model for both the laboratory setup and the industrial coalescer so that laboratory experiments can be used to predict the behavior of the industrial process.     

Model selection for partial least squares calibration and implications for analysis of atmospheric organic aerosol samples with mid‐infrared spectroscopy

In developing partial least squares calibration models, selecting the number of latent variables used for their construction to minimize both model bias and model variance remains a challenge. Several metrics exist for incorporating these trade‐offs, but the cost of model parsimony and the potential for underfitting on achievable prediction errors are difficult to anticipate. We propose a metric that penalizes growing model variance against decreasing bias as additional latent variables are added. The magnitude of the penalty is scaled by a user‐defined parameter that is formulated to provide a constraint on the fractional increase in root mean square error of cross‐validation (RMSECV) when selecting a parsimonious model over the conventional minimum RMSECV solution. We evaluate this approach for quantification of four organic functional groups using 238 laboratory standards and 750 complex atmospheric organic aerosol mixtures with mid‐infrared spectroscopy. Parametric variation of this penalty demonstrates that increase in prediction errors due to underfitting is bounded by the magnitude of the penalty for samples similar to laboratory standards used for model training and validation. Imposing an ensemble of penalties corresponding to a 0–30% allowable increase in RMSECV through sum of ranking differences leads to the selection of a model that increases the actual RMSECV up to 20% for laboratory standards but achieves an 85% reduction in the mean error in predicted concentrations for environmental mixtures. Partial least squares models developed with laboratory mixtures can provide useful predictions in complex environmental samples, but may benefit from protection against overfitting. © 2015 The Authors. Journal of Chemometrics published by John Wiley & Sons Ltd.     

Digital simulation of the effect of dispatching rules on the performance of a routine laboratory for structural analysis

Several output characteristics of a laboratory for structural analysis are shown to be identical with the output of a model of that laboratory, e.g. the histograms of the input and output density (samples/day), the histograms of the number of samples present in the laboratory, the histograms of the delays and several cross-correlations. The effect of various strategies concerning priorities between various groups of samples is forecast, e.g. samples with a different expected analysis time, samples from various sources, samples with a different history in the laboratory. The effects of the introduction of an adaptable routing procedure, several technician assignment decisions and strategies on the termination of the analysis are simulated.     

Strategies for constructing the calibration set for a near infrared spectroscopic quantitation method

Three strategies for the construction of calibration sets have been tried, with the objective to develop and to validate a NIR quantitation method.The first two approaches consist of the use of two types of samples, named: samples of laboratory obtained by mixing the ingredients that compose the drug, and doped samples obtained by under- and over-dosed production samples. In order to improve the prediction results, production samples have been added to each calibration model. The ensuing models were validated with a view to determine their fitness for purpose. However, spectral differences between the laboratory samples and doped samples resulted in spurious predictions in quantifying samples of one type using the model developed from samples of the other.Such differences were studied in depth and a third procedure has been proposed, based on a calibration model constructed with an unique type of sample (laboratory sample) for later to correct it with a few doped samples. This corrected model has a good predictive ability on production samples.     

EVALUATION OF SKIN CANCER RISK RESULTING FROM LONG TERM OCCUPATIONAL EXPOSURE TO RADIATION FROM ULTRAVIOLET LASERS IN THE RANGE FROM 190 TO 400 nm

The relative risk of occupational exposure to radiation from UV lasers was estimated using a mathematical model based on both epidemiological data and animal experiments. Calculations were performed for the 193 nm ArF excimer laser cornea shaping, the 308 nm XeCl excimer laser for coronary angioplasty, and other UV lasers in a laboratory environment. The model included the effects of direct exposure and exposure to scattered radiation. The results show that for the two medical applications the increase in the relative risk is comparable to that of one additional day of sunbathing per year. For subjects exposed to UV lasers in a laboratory setting, the relative risk may increase to a value comparable to that of people with an outdoor profession.     

Gel Filtration of Model Albumin-Analgin Mixture through Sephadex To Isolate Albumin

The preparative isolation of albumin from a model albumin-analgin mixture by filtration through Sephadex G-25 was studied. The conditions providing optimal protein decontamination to remove low-molecular-weight impurities were established, and recommendations on both laboratory and industrial application of this technique were made. Based on laboratory experiments, a commercial installation for production of refined vaccines was designed.     

Introduction for the special issue on the Antwerp Conferences

Quality management of laboratory medicine has become a hot topic at many conferences. Also, many national and international organizations have created working groups and committees with the task of working out standards, guidelines or recommendations for quality management of medical laboratories. We have observed that there is a great deal of interest not only from professional and scientific organizations directly involved in medical laboratory tests, but also from accreditation and certification bodies, from test laboratories in general, from in vitro diagnostic devices (IVD) manufacturers and their associations, and from other medical laboratory suppliers. However, we found that all these parties were discussing from their own point of view, without taking into account the position of other involved partners and that there was a need for creating a discussion forum for quality management in clinical laboratories. So in 1995, we started the Antwerp conferences on quality (r)evolution in clinical laboratories. The aim was to bring together all concerned partners and to establish a forum for brainstorming, independently of any pressure group. The leitmotif for the Antwerp conferences (Fig. 1) is a chain model showing the interfaces and relationships between all the partners involved in laboratory tests. During the conferences, this chain model has been examined from different angles and a summary of the concepts evolving from the discussions can be found in the conference abstracts and conference review reports in this journal. A Selection of ideas emerging from these conferences are presented below. Received: 5 October 1998 · Accepted: 20 October 1998     

Probability of Detection (POD) as a statistical model for the validation of qualitative methods

A statistical model is presented for use in validation of qualitative methods. This model, termed Probability of Detection (POD), harmonizes the statistical concepts and parameters between quantitative and qualitative method validation. POD characterizes method response with respect to concentration as a continuous variable. The POD model provides a tool for graphical representation of response curves for qualitative methods. In addition, the model allows comparisons between candidate and reference methods, and provides calculations of repeatability, reproducibility, and laboratory effects from collaborative study data. Single laboratory study and collaborative study examples are given.     

Analysis of volatiles associated with industrial scale processing of expanded polystyrene Part II: Identification and quantitation

Expanded polystyrene was pyrolyzed on a laboratory scale hot wire cutter. The resulting volatiles were characterized using GC/MS as the primary analytical tool. Use was also made of retention data from a complex petrochemical standard. In situ bromination of the pyrolysate further helped in structure elucidation. Air samples were collected in the field and compared to the model experiments from a laboratory scale hot wire cutter. The results indicate that alkylbenzene type compounds were the primary compounds in this environment. A few oxygenated substances were also formed. Traces of brominated compounds were detected in the model experiments but not in the samples collected in the field, with one exception. Quantitative data are presented from a typical industrial operation.     

Two-Gaussian excitations model for the glass transition

We develop a modified "two-state" model with Gaussian widths for the site energies of both ground and excited states, consistent with expectations for a disordered system. The thermodynamic properties of the system are analyzed in configuration space and found to bridge the gap between simple two-state models ("logarithmic" model in configuration space) and the random energy model ("Gaussian" model in configuration space). The Kauzmann singularity given by the random energy model remains for very fragile liquids but is suppressed or eliminated for stronger liquids. The sharp form of constant-volume heat capacity found by recent simulations for binary mixed Lennard-Jones and soft-sphere systems is reproduced by the model, as is the excess entropy and heat capacity of a variety of laboratory systems, strong and fragile. The ideal glass in all cases has a narrow Gaussian, almost invariant among molecular and atomic glassformers, while the excited-state Gaussian depends on the system and its width plays a role in the thermodynamic fragility. The model predicts the possibility of first-order phase transitions for fragile liquids. The analysis of laboratory data for toluene and o-terphenyl indicates that fragile liquids resolve the Kauzmann paradox by a first-order transition from supercooled liquid to ideal-glass state at a temperature between T(g) and Kauzmann temperature extrapolated from experimental data. We stress the importance of the temperature dependence of the energy landscape, predicted by the fluctuation-dissipation theorem, in analyzing the liquid thermodynamics.     

A chemometric tool for computer-aided decision making in analytical laboratory management

One of the tasks of management in analytical laboratories is the scheduling of analyses and the organization of the laboratory resources with respect to the workload. By a simulation of the laboratory operations, one can describe and eventually forecast the magnitude of the sample backlog and result delays with respect to the followed strategy to schedule samples and resources. However the design and validation of a simulation model is a lengthy and expensive task, requiring the help of a specialist in the area of operations research. In this paper an expert system is described that guides the laboratory manager through the various stages of the model design. The output of the expert system is a simulation model written in program code (SIMULA) that after compilation can be used to simulate the laboratory.     

仪器分析课程教学模式新探

针对仪器分析课程的特点,将"教研结合"的教学模式用于仪器分析理论教学中。通过对科研实例的深入解析,将涉及的相关教材知识穿插讲解。同时在仪器分析实验教学中采用"翻转课堂"的教学模式,即以"学生讲为主、教师讲为辅"的方式改变传统实验教学的弊端。从理论与实验两方面对仪器分析课程教学模式进行改革。     

Degradation of furan tebufenozide in laboratory and field trials

Furan tebufenozide is a newly developed insect growth regulator and has been applied as a pesticide in agriculture in China. Its degradation under both laboratory and field conditions was investigated, and the degradation kinetics was fitted by simple first order kinetics (SFO) model and first order double exponential (FOD) model. Laboratory studies were conducted with or without light in five simulated media (sterilized deionized water, river water, soil solution, sterilized soil and natural soil). No dissipations of furan tebufenozide were observed in sterilized aqueous and soil media under light prevented conditions, whereas degradation occurred under all the other conditions in the laboratory. Derived from SFO and FOD models, DT₅₀ in the dark and light laboratory conditions was in the range of 39.7–82.5 and 1.1–8.0 days, respectively. These results indicated that microbes and light were the main factors for the degradation of the pesticide in the laboratory. During field trials, derived from the SFO model, DT₅₀ and DT₉₀ were 30.3 and 100.5 days, while derived from the FOD model, DT₅₀ and DT₉₀ were 28.9 and 274.9 days, respectively. Compared with laboratory experiments, field trials were influenced by multiple factors. Therefore, the SFO model could not fit experimental data as well as the FOD model did in field trials.     

A model for the evaluation of uncertainty in routine multi-element analysis

A model for calculating uncertainty in routine multi-element analysis is described. The model is constructed according to the principles of GUM/EURACHEM. Control chart results are combined with other existing data and results from the actual measurement into a concentration-dependent estimate of combined standard uncertainty. Since possible sources of bias are included in the calculation, overall bias as estimated from the data is used only as a control to identify needs for modification of the model and/or the analytical procedure. For each individual sample, uncertainty can be calculated automatically based on two pre-calculated parameters together with measured concentration and instrumental standard deviation. As an example, the model is demonstrated for inductively coupled plasma-mass spectrometry (ICP-MS) analysis of sewage sludge including laboratory sub-sampling, sample preparation, and instrumental determination.     

U-G-S模式在化学实验教育协同创新中的应用

重视实验教育是培养化学创新人才的必由之路。在分析当今化学实验教育诸多瓶颈问题的基础上,本文提出引入U-G-S模式集合高等师范院校、中学和政府力量共同促进化学实验教育的协同创新,并通过分享代表案例总结了U-G-S模式下化学实验教育创新与化学实验教育人才培养的经验,为科学实验教育在更大范围内的协同创新提供了有价值的参考。     

通过密度函数理论表征炭质吸附剂的孔径分布

通过密度函数理论（DFT-DensityFunctionalTheory）对炭质吸附剂的孔径分布进行了表征。该法以多孔固体上N2吸附分子模型为依据，用一种方法对多孔固体的孔径分布从微孔到大孔范围进行确定。本文用该法对自制的聚丙烯腈活性炭纤维、国产煤质活性炭及日本产活性炭微球等六种炭质吸附剂的孔径分布进行了表征。     

Principles for determining mechanistic pathways from observable quantum control data

Hamiltonian encoding (HE) methods have been used to understand mechanism in computational studies of laser controlled quantum systems. This work studies the principles for extending such methods to extract control mechanisms from laboratory data. In an experimental setting, observables replace the utilization of wavefunctions in computational HE. With laboratory data, HE gives rise to a set of quadratic equations for the interfering transition amplitudes, and the solution to the equations reveals the mechanistic pathways. The extraction of the mechanism from the system of quadratic equations raises questions of uniqueness and solvability, even in the ideal case without noise. Symmetries are shown to exist in the quadratic system of equations, which is generally overdetermined. Therefore, the mechanism is likely to be unique up to these symmetries. Numerical simulations demonstrate the concepts on simple model systems.     

Analytical advances to study the air – water interfacial chemistry in the atmosphere

Formation of aqueous secondary organic aerosol (aqSOA) at the air – liquid interface recently has attracted a lot of attention in atmospheric chemistry. The discrepancies in mass distributions, aerosol oxidative capacity, liquid water content, hygroscopic growth of aerosols, and formation of clouds and fogs suggest that interfacial chemistry play a more important role than previously deemed. However, detailed mechanisms at the air–water interface remain unclear owing to the lack of comprehensive understanding that underpins complicated interfacial phenomena, which are not easily measurable from field campaigns, laboratory measurements, or computational simulations. This review highlights relevant and recent technical advancement employed to study aqSOA encompassing spectroscopy and mass spectrometry. The current knowledge on the aqSOA processes is digested with an emphasis on recent research of interfacial aqSOA formation including laboratory studies and model simulations. Finally, future directions of the interfacial chemistry are recommended for field and laboratory studies as well as theoretical efforts to resolve interfacial challenges in atmospheric chemistry.