The transition of migratory patterns in medium-sized cities

"The authors attempt to present some empirical findings regarding a phenomenon which they chose to call the 'transition in migratory patterns'.... The general hypothesis states that: changes in migratory patterns are due to an interaction between those economic, political and social processes which affect the distribution of the population; and that this interaction is also highly influenced by macroeconomic politics--an arena where technology plays a dominant role." Data are for Guadalajara and the state of Jalisco in Mexico. (SUMMARY IN ENG)     

Mitochondrial DNA error prophylaxis: assessing the causes of errors in the GEP'02-03 proficiency testing trial

A qualitative and quantitative analytical method was developed and validated for the determination of 49 licit and illicit drugs in oral fluid. Small oral fluid samples, volume 1mL, were collected from volunteers using a modified Omni-Sal device and the analytes were extracted from an oral fluid/buffer mixture using a single Bond Elut Certify solid phase extraction cartridge. Liquid chromatography-tandem mass spectrometry (LC-MS-MS) and gas chromatography-repetitive full scan mass spectrometry (GC-MS) were used in parallel to analyze the extracts for the targeted drugs. Extracts were analyzed by GC-MS in their underivatized form and as their pentafluoropropionyl derivatives. Deuterated internal standards were used for quantification of drugs of abuse by LC-MS-MS to minimize matrix effects. Methadone-d(9) and tumoxetine were used as the internal standards for quantification of non-derivatized and derivatized analytes respectively by GC-MS. Linearity was demonstrated over the range 5-200 ng/mL and limits of detection were less than 4 ng/mL for each drug analyzed. The method demonstrated acceptable recoveries for most of the analytes and good intra- and inter-day precision. Acquisition of data by repetitive full scan GC-MS allows the addition of further analytes to the target menu.     

The role of `the resources of the power hypothesis' in explaining the Spanish welfare state between 1975–1995

Abstract There are two clearly differentiated parts to this work. The first consists of a review of the theoretical arguments that underlie the so–called 'resources of power hypothesis' . That theory has been used to explain the growth and development of the Welfare State in several European countries. The findings of a number of empirical works backing up that theory have also been included in this review. The intention of the second part is to check the theory against the Spanish case between 1975 and 1995. The conclusion of this work is that if, besides considering the ideological persuasion of the party controlling the government, we take into account the other relevant factors encompassed by the theory, then the 'resources of power hypothesis' is valid in explaining and interpreting the make–up and scope of the Spanish Welfare State.     

Evaluation of the Simultaneous Analysis of Organic and Inorganic Gunshot Residues Within a Large Population Data Set Using Electrochemical Sensors*,†

The increasing demand for rapid methods to identify both inorganic and organic gunshot residues (IGSR and OGSR) makes electrochemical methods, an attractive screening tool to modernize current practice. Our research group has previously demonstrated that electrochemical screening of GSR samples delivers a simple, inexpensive, and sensitive analytical solution that is capable of detecting IGSR and OGSR in less than 10 min per sample. In this study, we expand our previous work by increasing the number of GSR markers and applying machine learning classifiers to the interpretation of a larger population data set. Utilizing bare screen-printed carbon electrodes, the detection and resolution of seven markers (IGSR; lead, antimony, and copper, and OGSR; nitroglycerin, 2,4-dinitrotoluene, diphenylamine, and ethyl centralite) was achieved with limits of detection (LODs) below 1 µg/mL. A large population data set was obtained from 395 authentic shooter samples and 350 background samples. Various statistical methods and machine learning algorithms, including critical thresholds (CT), naïve Bayes (NB), logistic regression (LR), and neural networks (NN), were utilized to calculate the performance and error rates. Neural networks proved to be the best predictor when assessing the dichotomous question of detection of GSR on the hands of shooter versus nonshooter groups. Accuracies for the studied population were 81.8 % (CT), 88.1% (NB), 94.7% (LR), and 95.4% (NN), respectively. The ability to detect both IGSR and OGSR simultaneously provides a selective testing platform for gunshot residues that can provide a powerful field-testing technique and assist with decisions in case management.     

Biochemical changes of the synovial liquid in corpses with regard to the cause of death. 1: Calcium, inorganic phosphorus, glucose, cholesterol, urea nitrogen, uric acid, proteins, and albumin

We present in this work a study about biochemical changes of the synovial liquid in 100 corpses with regard to the cause of death. The results obtained in the different groups of causes of death show that the biochemical parameters were modified postmortem although we think that this modification is related more directly to the duration of the pathological process that leads to death than with the nature of the process itself.     

An improved method for subtyping Pi in old bloodstains.

Immunofixation procedures were used for detecting alpha-1 antitrypsin protease inhibitor (Pi) phenotypes in bloodstains. Neuraminidase elution of bloodstains, together with isoelectric focusing, immunofixation, and silver staining techniques, makes possible Pi subtyping in old bloodstains. No extra bands appear when the storage time is no longer than three months.     

Evaluation and classification of fentanyl-related compounds using EC-SERS and machine learning

Multiple analytical techniques for the screening of fentanyl-related compounds exist. High discriminatory methods such as GC–MS and LC–MS are expensive, time-consuming, and less amenable to onsite analysis. Raman spectroscopy provides a rapid, inexpensive alternative. Raman variants such as electrochemical surface-enhanced Raman scattering (EC-SERS) can provide signal enhancements with 10¹⁰ magnitudes, allowing for the detection of low-concentration analytes, otherwise undetected using conventional Raman. Library search algorithms embedded in instruments utilizing SERS may suffer from accuracy when multicomponent mixtures involving fentanyl derivatives are analyzed. The complexing of machine learning techniques to Raman spectra demonstrates an improvement in the discrimination of drugs even when present in multicomponent mixtures of various ratios. Additionally, these algorithms are capable of identifying spectral features difficult to detect by manual comparisons. Therefore, the goal of this study was to evaluate fentanyl-related compounds and other drugs of abuse using EC-SERS and to process the acquired data using machine learning—convolutional neural networks (CNN). The CNN was created using Keras v 2.4.0 with Tensorflow v 2.9.1 backend. In-house binary mixtures and authentic adjudicated case samples were used to evaluate the created machine-learning models. The overall accuracy of the model was 98.4 ± 0.1% after 10-fold cross-validation. The correct identification for the in-house binary mixtures was 92%, while the authentic case samples were 85%. The high accuracies achieved in this study demonstrate the advantage of using machine learning to process spectral data when screening seized drug materials comprised of multiple components.     

High resolution Y chromosome typing: 19 STRs amplified in three multiplex reactions

Nineteen Y-specific short tandem repeat (STR) loci have been amplified in 768 samples from the Iberian Peninsula in order to evaluate their usefulness in forensic casework. Two previously published multiplex reactions by Thomas et al. [Hum. Genet. 6 (1999) 577] (MS1, modified here: DYS19, DYS388, DYS390, DYS391, DYS392 and DYS393) and by Ayub et al. [Nucl. Acids Res. 28 (2000) e8] (CTS: DYS434, DYS435, DYS436, DYS437, DYS438 and DYS439) plus a novel one reported here (EBF: DYS385, DYS389, DYS460, DYS461, DYS462 and amelogenin) have been used. DYS385, DYS439 and DYS391 were the most informative loci with allele diversities of 0.7997, 0.6683 and 0.5940, respectively. A total of 635 different haplotypes were observed, of which 573 (90.24%) were found in single individuals. The overall haplotype diversity was 0.9988 and that obtained by each multiplex system was 0.9812 for EBF, 0.9292 for MS1 and 0.9089 for CTS.