Studies on Soil-Aggregate-Sodium Chloride Stabilized Roads in Franklin County, Iowa, HR-33

This investigation was conducted to study the performance characteristics of low cost roadway surfaces of soil-aggregate-sodium chloride mixtures. Many roads have been successfully stabilized with sodium chloride. However, little information is available on either the properties of the road materials or the effects of sodium chloride on the materials. The performance of some of the sodium chloride stabilized roads in Franklin County, Iowa, and the performance of some near-by nonchemically treated roads has been studied. The study of sodium chloride stabilized roads was restricted to the roads in which the binder soil used in construction came from the same source. The effects of sodium chloride on some of the engineering properties of the soil and soil-aggregate mixtures used were studied in the laboratory.

On the relationship between performance-approach goals and cognitive performance : when the desire to outperform others becomes interfering

Cette thèse explore dans quelle mesure la poursuite d'un but de performance-approche (i.e., le désir de surpasser autrui et de démontrer ses compétences) favorise, ou au contraire endommage, la réussite et l'apprentissage-une question toujours largement débattue dans la littérature. Quatre études menées en laboratoire ont confirmé cette hypothèse et démontré que la poursuite du but de performance-approche amène les individus à diviser leur attention entre d'une part la réalisation de la tâche évaluée, et d'autre part la gestion de préoccupations liées à l'atteinte du but-ceci empêchant une concentration efficace sur les processus de résolution de la tâche. Dans une deuxième ligne de recherche, nous avons ensuite démontré que cette distraction est exacerbée chez les individus les plus performants et ayant le plus l'habitude de réussir, ceci dérivant d'une pression supplémentaire liée au souhait de maintenir le statut positif de « bon élève ». Enfin, notre troisième ligne de recherche a cherché à réconcilier ces résultats-pointant l'aspect distractif du but de performance-approche-avec le profil se dégageant des études longitudinales rapportées dans la littérature-associant ce but avec la réussite académique. Ainsi, nous avons mené une étude longitudinale testant si l'adoption du but de performance-approche en classe pourrait augmenter la mise en oeuvre de stratégies d'étude tactiquement dirigées vers la performance-favorisant une réussite optimale aux tests. Nos résultats ont apporté des éléments en faveur de cette hypothèse, mais uniquement chez les élèves de bas niveau. Ainsi, l'ensemble de nos résultats permet de mettre en lumière les processus cognitifs à l'oeuvre lors de la poursuite du but de performance-approche, ainsi que d'alimenter le débat concernant leur aspect bénéfique ou nuisible en contexte éducatif. -- In this dissertation, we propose to investigate whether the pursuit of performance-approach goals (i.e., the desire to outperform others and appear talented) facilitates or rather endangers achievement and learning-an issue that is still widely discussed in the achievement goal literature. Four experiments carried out in a laboratory setting have provided evidence that performance- approach goals create a divided-attention situation that leads cognitive resources to be divided between task processing and the activation of goal-attainment concerns-which jeopardizes full cognitive immersion in the task. Then, in a second research line, we found evidence that high- achievers (i.e., those individuals who are the most used to succeed) experience, under evaluative contexts, heightened pressure to excel at the task, deriving from concerns associated with the preservation of their "high-achiever" status. Finally, a third research line was designed to try to reconcile results stemming from our laboratory studies with the overall profile emerging from longitudinal research-which have consistently found performance-approach goals to be a positive predictor of students' test scores. We thus set up a longitudinal study so as to test whether students' adoption of performance-approach goals in a long-term classroom setting enhances the implementation of strategic study behaviors tactically directed toward goal-attainment, hence favoring test performance. Our findings brought support for this hypothesis, but only for low-achieving students. Taken together, our findings shed new light on the cognitive processes at play during the pursuit of performance-approach goals, and are likely to fuel the debate regarding whether performance-approach goals should be encouraged or not in educational settings.

FastEpistasis: a high performance computing solution for quantitative trait epistasis.

Motivation: Genome-wide association studies have become widely used tools to study effects of genetic variants on complex diseases. While it is of great interest to extend existing analysis methods by considering interaction effects between pairs of loci, the large number of possible tests presents a significant computational challenge. The number of computations is further multiplied in the study of gene expression quantitative trait mapping, in which tests are performed for thousands of gene phenotypes simultaneously. Results: We present FastEpistasis, an efficient parallel solution extending the PLINK epistasis module, designed to test for epistasis effects when analyzing continuous phenotypes. Our results show that the algorithm scales with the number of processors and offers a reduction in computation time when several phenotypes are analyzed simultaneously. FastEpistasis is capable of testing the association of a continuous trait with all single nucleotide polymorphism ( SNP) pairs from 500 000 SNPs, totaling 125 billion tests, in a population of 5000 individuals in 29, 4 or 0.5 days using 8, 64 or 512 processors.

Iowa State Highway 92 Over Drainage Ditch #25: Performance Evaluation - Galvanized Reinforcing Bars -- Louisa County, Iowa, 2015

Several strategies are available to the Iowa Department of Transportation (IaDOT) for limiting deterioration due to chloride-induced corrosion of embedded reinforcing bars in concrete bridge decks. While the method most commonly used throughout the Midwestern United States is to construct concrete bridge decks with fusion-bonded epoxy-coated reinforcing bars, galvanized reinforcing bars are an available alternative. Previous studies of the in situ performance of galvanized reinforcing bars in service in bridge decks have been limited. IaDOT requested that Wiss, Janney, Elstner Associates, Inc. (WJE) perform this study to gain further understanding of the long-term performance of an Iowa bridge deck reinforced with galvanized reinforcing bars. This study characterized the condition of a bridge deck with galvanized reinforcing bars after about 36 years of service and compared that performance to the expected performance of epoxy-coated or uncoated reinforcing bars in similar bridge construction. For this study, IaDOT selected the Iowa State Highway 92 bridge across Drainage Ditch #25 in Louisa County, Iowa (Structure No. 5854.5S092), which was constructed using galvanized reinforcing bars as the main deck reinforcing. The scope of work for this study included: field assessment, testing, and sampling; laboratory testing and analysis; analysis of findings; service life modeling; and preparation of this report. In addition, supplemental observations of the condition of the galvanized reinforcing bars were made during a subsequent project to repair the bride deck.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Virulent bacterial infection improves aversive learning performance in Drosophila melanogaster.

Virulent infections are expected to impair learning ability, either as a direct consequence of stressed physiological state or as an adaptive response that minimizes diversion of energy from immune defense. This prediction has been well supported for mammals and bees. Here, we report an opposite result in Drosophila melanogaster. Using an odor-mechanical shock conditioning paradigm, we found that intestinal infection with bacterial pathogens Pseudomonas entomophila or Erwinia c. carotovora improved flies' learning performance after a 1h retention interval. Infection with P. entomophila (but not E. c. carotovora) also improved learning performance after 5 min retention. No effect on learning performance was detected for intestinal infections with an avirulent GacA mutant of P. entomophila or for virulent systemic (hemocoel) infection with E. c. carotovora. Assays of unconditioned responses to odorants and shock do not support a major role for changes in general responsiveness to stimuli in explaining the changes in learning performance, although differences in their specific salience for learning cannot be excluded. Our results demonstrate that the effects of pathogens on learning performance in insects are less predictable than suggested by previous studies, and support the notion that immune stress can sometimes boost cognitive abilities.

Waste management policies for industrial symbiosis development: case studies in European countries

Industrial symbiosis (IS) emerged as a self-organizing business strategy among firms that are willing to cooperate to improve their economic and environmental performance. The adoption of such cooperative strategies relates to increasing costs of waste management, most of which are driven by policy and legislative requirements. Development of IS depends on an enabling context of social, informational, technological, economical and political factors. The power to influence this context varies among the agents involved such as the government, businesses or coordinating entities. Governmental intervention, as manifested through policies, could influence a wider range of factors; and we believe this is an area which is under-researched. This paper aims to critically appraise the waste policy interventions from supra-national to sub-national levels of government. A case study methodology has been applied to four European countries i.e. Denmark, the UK, Portugal and Switzerland, in which IS emerged or is being fostered. The findings suggest that there are commonalities in policy instruments that may have led to an IS enabling context. The paper concludes with lessons learnt and recommendations on shaping the policy context for IS development.

Investigation of AASHTOWare Pavement ME Design/DARWin-ME Performance Prediction Models for Iowa Pavement Analysis and Design, 2015

The Mechanistic-Empirical Pavement Design Guide (MEPDG) was developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A as a novel mechanistic-empirical procedure for the analysis and design of pavements. The MEPDG was subsequently supported by AASHTO’s DARWin-ME and most recently marketed as AASHTOWare Pavement ME Design software as of February 2013. Although the core design process and computational engine have remained the same over the years, some enhancements to the pavement performance prediction models have been implemented along with other documented changes as the MEPDG transitioned to AASHTOWare Pavement ME Design software. Preliminary studies were carried out to determine possible differences between AASHTOWare Pavement ME Design, MEPDG (version 1.1), and DARWin-ME (version 1.1) performance predictions for new jointed plain concrete pavement (JPCP), new hot mix asphalt (HMA), and HMA over JPCP systems. Differences were indeed observed between the pavement performance predictions produced by these different software versions. Further investigation was needed to verify these differences and to evaluate whether identified local calibration factors from the latest MEPDG (version 1.1) were acceptable for use with the latest version (version 2.1.24) of AASHTOWare Pavement ME Design at the time this research was conducted. Therefore, the primary objective of this research was to examine AASHTOWare Pavement ME Design performance predictions using previously identified MEPDG calibration factors (through InTrans Project 11-401) and, if needed, refine the local calibration coefficients of AASHTOWare Pavement ME Design pavement performance predictions for Iowa pavement systems using linear and nonlinear optimization procedures. A total of 130 representative sections across Iowa consisting of JPCP, new HMA, and HMA over JPCP sections were used. The local calibration results of AASHTOWare Pavement ME Design are presented and compared with national and locally calibrated MEPDG models.

A Continuous Span Aluminum Girder Concrete Deck Bridge - Part 1 of 2: Field Test Performance and Evaluation, 1996

This report addresses the field testing and analysis of those results to establish the behavior of the original Clive Road Bridge that carried highway traffic over Interstate 80 (I-80) in the northwest region of Des Moines, Iowa. The bridge was load tested in 1959, shortly after its construction and in 1993, just prior to its demolition. This report presents some of the results from both field tests, finite element predictions of the behavior of aluminum bridge girders, and load distribution studies.

Correlation of Locally-Based Performance of Asphalts with Their Physicochemical Parameters, Progress Report 2, HR-298, 1989

This project was undertaken to study the relationships between the performance of locally available asphalts and their physicochemical properties under Iowa conditions with the ultimate objective of development of a locally and performance-based asphalt specification for durable pavements. Physical and physicochemical tests were performed on three sets of asphalt samples including: (a) twelve samples from local asphalt suppliers and their TFOT residues, (b) six core samples of known service records, and (c) a total of 79 asphalts from 10 pavement projects including original, lab aged and recovered asphalts from field mixes, as well as from lab aged mixes. Tests included standard rheological tests, HP-GPC and TMA. Some specific viscoelastic tests (at 5 deg C) were run on b samples and on some a samples. DSC and X-ray diffraction studies were performed on a and b samples. Furthermore, NMR techniques were applied to some a, b and c samples. Efforts were made to identify physicochemical properties which are correlated to physical properties known to affect field performance. The significant physicochemical parameters were used as a basis for an improved performance-based trial specification for Iowa to ensure more durable pavements.

Development of Craniofacial Bone Defect Reconstruction Implant Based on Fibre-Reinforced Composite with Photopolymerisable Resin Systems. Experimental studies in vitro and in vivo.

Reconstruction of defects in the craniomaxillofacial (CMF) area has mainly been based on bone grafts or metallic fixing plates and screws. Particularly in the case of large calvarial and/or craniofacial defects caused by trauma, tumours or congenital malformations, there is a need for reliable reconstruction biomaterials, because bone grafts or metallic fixing systems do not completely fulfill the criteria for the best possible reconstruction methods in these complicated cases. In this series of studies, the usability of fibre-reinforced composite (FRC) was studied as a biostable, nonmetallic alternative material for reconstructing artificially created bone defects in frontal and calvarial areas of rabbits. The experimental part of this work describes the different stages of the product development process from the first in vitro tests with resin-impregnated fibrereinforced composites to the in vivo animal studies, in which this FRC was tested as an implant material for reconstructing different size bone defects in rabbit frontal and calvarial areas. In the first in vitro study, the FRC was polymerised in contact with bone or blood in the laboratory. The polymerised FRC samples were then incubated in water, which was analysed for residual monomer content by using high performance liquid chromatography (HPLC). It was found that this in vitro polymerisation in contact with bone and blood did not markedly increase the residual monomer leaching from the FRC. In the second in vitro study, different adhesive systems were tested in fixing the implant to bone surface. This was done to find an alternative implant fixing system to screws and pins. On the basis of this study, it was found that the surface of the calvarial bone needed both mechanical and chemical treatments before the resinimpregnated FRC could be properly fixed onto it. In three animal studies performed with rabbit frontal bone defects and critical size calvarial bone defect models, biological responses to the FRC implants were evaluated. On the basis of theseevaluations, it can be concluded that the FRC, based on E-glass (electrical glass) fibres forming a porous fibre veil enables the ingrowth of connective tissues to the inner structures of the material, as well as the bone formation and mineralization inside the fibre veil. Bone formation could be enhanced by using bioactive glass granules fixed to the FRC implants. FRC-implanted bone defects healed partly; no total healing of defects was achieved. Biological responses during the follow-up time, at a maximum of 12 weeks, to resin-impregnated composite implant seemed to depend on the polymerization time of the resin matrix of the FRC. Both of the studied resin systems used in the FRC were photopolymerised and the heat-induced postpolymerisation was used additionally.

Business Development Efforts and Performance Improvements in SMEs Case Study of Business Development Projects Implemented in SME

Under the circumstances of the increasing market pressure, enterprises try to improve their competitive position by development efforts, and a business development project is one tool for that. There are not many answers to the question of how the development projects launched to improve the business performance in SMEs have succeeded. Theacademic interest in the business development project success has mainly focused on projects implemented in larger organisations rather than in SMEs. The previous studies on the business success of SMEs have mainly focused on new business ventures rather than on existing SMEs. However, nowadays a large number of business development projects are undertaken in existing SMEs, where they can pose a great challenge. This study focuses on business development success in SMEs thathave already established their business. The objective of the present study is to gain a deep understanding on business development project success in the SME-context and to identify the dimensions and factors affecting the project success. Further, the aim is to clarify how the business development projects implemented in SMEs have affected their performance. The empirical evidence is based on multiple case study. This study builds a framework for a generic theory of business development success in the SME-context, based on literature from the areas ofproject and change management, entrepreneurship and small business management, as well as performance measurement, and on empirical evidence from SMES. The framework consists of five success dimensions: entrepreneurial, project preparation, change management, project management and project success. The framework provides a systematic way for analysing the business development project and its impact on the performance and on the performing company. This case evidence indicates that successful business development projects have a balanced, high performance concerning all the dimensions. Good performance in one dimension is not enoughfor the project success, but it gives a good ground for the other dimensions. The other way round, poor performance in one success dimension affects the others, leading to poor performance of the project. In the SME-context the business development project success seems to be dependent on several interrelated dimensions and factors. Success in one area leads to success in other areas, and so creates an upward success spiral. Failure in one area seems to lead to failure in other areas, creating a downward failure spiral. The study indicates that the internal business development projects have affected the SMEs' performance widely also on areas and functions not initially targeted. The implications cover all thesuccess categories: the project efficiency, the impact on the customer, the business success and the future potentiality. With successful cases, the success tends to spread out to areas and functions not mentioned as the project goals, andwith unsuccessful cases the failure seems to spread out widely to the SMEs' other functions. This study also indicates that the most important key factors for successful business development project implementation are the strength of intention, business ability, knowledge, motivation and participation of the employees, as well as adequate and well-timed training provided to the employees.

Monitoring bank performance in the presence of risk

This paper proposes a managerial control tool that integrates risk in efficiency scores. Building on existing efficiency specifications, our proposal reflects the real banking technology and accurately models the relationship between desirable and undesirable outputs. Specifically, the undesirable output is defined as non-performing loans to capture credit risk, and is linked only to the relevant dimension of the output set. We empirically illustrate how our efficiency measure functions for managerial control purposes. The application considers a unique dataset of Costa Rican banks during 1998-2012. Efficiency scores? implications are mostly discussed at bank-level, and their interpretations are enhanced by using accounting ratios. We also show the usefulness of our tool for corporate governance by examining performance changes around executive turnover. Results confirm that appointing CEOs from outside the bank significantly improves performance, thus suggesting the potential benefits of new organisational practices.

Evaluation of a piezoelectric system as an alternative to electroencephalogram/ electromyogram recordings in mouse sleep studies.

STUDY OBJECTIVES: Traditionally, sleep studies in mammals are performed using electroencephalogram/electromyogram (EEG/EMG) recordings to determine sleep-wake state. In laboratory animals, this requires surgery and recovery time and causes discomfort to the animal. In this study, we evaluated the performance of an alternative, noninvasive approach utilizing piezoelectric films to determine sleep and wakefulness in mice by simultaneous EEG/EMG recordings. The piezoelectric films detect the animal's movements with high sensitivity and the regularity of the piezo output signal, related to the regular breathing movements characteristic of sleep, serves to automatically determine sleep. Although the system is commercially available (Signal Solutions LLC, Lexington, KY), this is the first statistical validation of various aspects of sleep. DESIGN: EEG/EMG and piezo signals were recorded simultaneously during 48 h. SETTING: Mouse sleep laboratory. PARTICIPANTS: Nine male and nine female CFW outbred mice. INTERVENTIONS: EEG/EMG surgery. MEASUREMENTS AND RESULTS: The results showed a high correspondence between EEG/EMG-determined and piezo-determined total sleep time and the distribution of sleep over a 48-h baseline recording with 18 mice. Moreover, the piezo system was capable of assessing sleep quality (i.e., sleep consolidation) and interesting observations at transitions to and from rapid eye movement sleep were made that could be exploited in the future to also distinguish the two sleep states. CONCLUSIONS: The piezo system proved to be a reliable alternative to electroencephalogram/electromyogram recording in the mouse and will be useful for first-pass, large-scale sleep screens for genetic or pharmacological studies. CITATION: Mang GM, Nicod J, Emmenegger Y, Donohue KD, O'Hara BF, Franken P. Evaluation of a piezoelectric system as an alternative to electroencephalogram/electromyogram recordings in mouse sleep studies.

Correlating trainees' translating performance with the quality of their metacognitive self-evaluation

This paper presents a study of correlations between the performance of trainee translators, according to their teacher’s assessment, and the quality of their self-evaluation, according to their answers to metacognitive questionnaires. Two case-studies of two consecutive editions of a course in general translation from German into Spanish are dealt with. The course involved the use of post-translation metacognitive questionnaires designed to help trainees to evaluate their translating. A selection of the questionnaires (from the strongest and the weakest performances by students for each course edition) is considered. The study focuses on one item in these questionnaires that has to do with identifying translation problems and justifying their solutions. An interpretive analysis of the trainees’ answers for this questionnaire item reveals that the best-performing students were more strategically and translationally aware in self-evaluating their own translating. Our conclusions are based on considering six parameters from the analysis of the trainees’ answers, which are tentatively regarded as indicative of the quality of their self-evaluation.