A Model for Improving the Quality of Student Internship Placements in Engineering Degrees

Work Internship Placements (WIP) is a new and transversal enterprise internships programme, which is focused on quality improvement, academic control and satisfaction of collaborating enterprises. This programme is addressed to the engineering students of the PolytechnicSchool at the University of Girona (UdG) in Spain. The fundamental WIP infrastructure combines a web-based intranet platform, that provides a complete set of WIP tools, with a protocol of procedures and tasks that are observed and followed at all internship stages by every participating agent, i.e. enterprises, students, coaching professors and administrative staff. Our new programme is centered on a broader, more holistic internship placement procedure than the traditional “career and academic goals” approach. The WIP programme has been found to be a valuable asset in addressing enterprise and student needs in the experiential project

Model-based iterative reconstruction in pediatric chest CT: assessment of image quality in a prospective study of children with cystic fibrosis.

BACKGROUND: The potential effects of ionizing radiation are of particular concern in children. The model-based iterative reconstruction VEO(TM) is a technique commercialized to improve image quality and reduce noise compared with the filtered back-projection (FBP) method. OBJECTIVE: To evaluate the potential of VEO(TM) on diagnostic image quality and dose reduction in pediatric chest CT examinations. MATERIALS AND METHODS: Twenty children (mean 11.4 years) with cystic fibrosis underwent either a standard CT or a moderately reduced-dose CT plus a minimum-dose CT performed at 100 kVp. Reduced-dose CT examinations consisted of two consecutive acquisitions: one moderately reduced-dose CT with increased noise index (NI = 70) and one minimum-dose CT at CTDIvol 0.14 mGy. Standard CTs were reconstructed using the FBP method while low-dose CTs were reconstructed using FBP and VEO. Two senior radiologists evaluated diagnostic image quality independently by scoring anatomical structures using a four-point scale (1 = excellent, 2 = clear, 3 = diminished, 4 = non-diagnostic). Standard deviation (SD) and signal-to-noise ratio (SNR) were also computed. RESULTS: At moderately reduced doses, VEO images had significantly lower SD (P < 0.001) and higher SNR (P < 0.05) in comparison to filtered back-projection images. Further improvements were obtained at minimum-dose CT. The best diagnostic image quality was obtained with VEO at minimum-dose CT for the small structures (subpleural vessels and lung fissures) (P < 0.001). The potential for dose reduction was dependent on the diagnostic task because of the modification of the image texture produced by this reconstruction. CONCLUSIONS: At minimum-dose CT, VEO enables important dose reduction depending on the clinical indication and makes visible certain small structures that were not perceptible with filtered back-projection.

The definition of quality of life in solid organ transplantation: A psychological qualitative model

Quality of life has been extensively discussed in acute and chronic illnesses. However a dynamic model grounded in the experience of patients in the course of transplantation has not been to our knowledge developed. In a qualitative longitudinal study, patients awaiting solid organ transplantation participated in semi-structured interviews: Exploring topics pre-selected on previous research literature review. Creative interview was privileged, open to themes patients would like to discuss at the different steps of the transplantation process. A qualitative thematic and reflexive analysis was performed, and a model of the dimensions constitutive of quality of life from the perspective of the patients was elaborated. Quality of life is not a stable construct in a long lasting illness-course, but evolves with illness constraints, treatments and outcomes. Dimensions constitutive of quality of life are defined, each of them containing different sub-categories depending on the organ related illness co-morbidities and the stage of illness-course.

Tropical terrestrial model ecosystems for evaluation of soil fauna and leaf litter quality effects on litter consumption, soil microbial biomass and plant growth

The aim of this work was to evaluate whether terrestrial model ecosystems (TMEs) are a useful tool for the study of the effects of litter quality, soil invertebrates and mineral fertilizer on litter decomposition and plant growth under controlled conditions in the tropics. Forty-eight intact soil cores (17.5-cm diameter, 30-cm length) were taken out from an abandoned rubber plantation on Ferralsol soil (Latossolo Amarelo) in Central Amazonia, Brazil, and kept at 28ºC in the laboratory during four months. Leaf litter of either Hevea pauciflora (rubber tree), Flemingia macrophylla (a shrubby legume) or Brachiaria decumbens (a pasture grass) was put on top of each TME. Five specimens of either Pontoscolex corethrurus or Eisenia fetida (earthworms), Porcellionides pruinosus or Circoniscus ornatus (woodlice), and Trigoniulus corallinus (millipedes) were then added to the TMEs. Leaf litter type significantly affected litter consumption, soil microbial biomass and nitrate concentration in the leachate of all TMEs, but had no measurable effect on the shoot biomass of rice seedlings planted in top soil taken from the TMEs. Feeding rates measured with bait lamina were significantly higher in TMEs with the earthworm P. corethrurus and the woodlouse C. ornatus. TMEs are an appropriate tool to assess trophic interactions in tropical soil ecossistems under controlled laboratory conditions.

Image quality in CT: From physical measurements to model observers.

Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

Dynamic Competitor Analysis Model Of Welding Quality Management Software

Tämä diplomityö arvioi hitsauksen laadunhallintaohjelmistomarkkinoiden kilpailijoita. Kilpailukenttä on uusi ja ei ole tarkkaa tietoa siitä minkälaisia kilpailijoita on markkinoilla. Hitsauksen laadunhallintaohjelmisto auttaa yrityksiä takaamaan korkean laadun. Ohjelmisto takaa korkean laadun varmistamalla, että hitsaaja on pätevä, hän noudattaa hitsausohjeita ja annettuja parametreja. Sen lisäksi ohjelmisto kerää kaiken tiedon hitsausprosessista ja luo siitä vaadittavat dokumentit. Diplomityön teoriaosuus muodostuu kirjallisuuskatsauksesta ratkaisuliike-toimintaan, kilpailija-analyysin ja kilpailuvoimien teoriaan sekä hitsauksen laadunhallintaan. Työn empiriaosuus on laadullinen tutkimus, jossa tutkitaan kilpailevia hitsauksen laadunhallintaohjelmistoja ja haastatellaan ohjelmistojen käyttäjiä. Diplomityön tuloksena saadaan uusi kilpailija-analyysimalli hitsauksen laadunhallintaohjelmistoille. Mallin avulla voidaan arvostella ohjelmistot niiden tarjoamien primääri- ja sekundääriominaisuuksien perusteella. Toiseksi tässä diplomityössä analysoidaan nykyinen kilpailijatilanne hyödyntämällä juuri kehitettyä kilpailija-analyysimallia.

Model to Build a Service Quality Centric Customer Reference Portfolio in a Software as a Service Company

The goal of the master’s thesis was to develop a model to build a service quality centric customer reference portfolio for a software as a service company. The case company is Meltwater Finland Oy that leverages customer references externally but there is no systematic model to produce good quality customer references that are in line with the company strategy. The project was carried out as a case study, where the primary source of information were seventeen internal interviews with the employees of the case company. The theory part focuses on customer references as assets and service quality in software as a service industry. In the empirical part the research problem is solved. As a result of the case study, the model to build a service quality centric customer reference portfolio was created and further research areas were suggested.

Development of a New Welding Product Quality Control and Management System Model for China

The Chinese welding industry is growing every year due to rapid development of the Chinese economy. Increasingly, companies around the world are looking to use Chinese enterprises as their cooperation partners. However, the Chinese welding industry also has its weaknesses, such as relatively low quality and weak management. A modern, advanced welding management system appropriate for local socio-economic conditions is required to enable Chinese enterprises to enhance further their business development. The thesis researches the design and implementation of a new welding quality management system for China. This new system is called ‗welding production quality control management model in China‘ (WQMC). Constructed on the basis of analysis of a survey and in-company interviews, the welding management system comprises the following different elements and perspectives: a ‗Localized congenital existing problem resolution strategies‘ (LCEPRS) database, a ‗human factor designed training system‘ (HFDT) training strategy, the theory of modular design, ISO 3834 requirements, total welding management (TWM), and lean manufacturing (LEAN) theory. The methods used in the research are literature review, questionnaires, interviews, and the author‘s model design experiences and observations, i.e. the approach is primarily qualitative and phenomenological. The thesis describes the design and implementation of a HFDT strategy in Chinese welding companies. Such training is an effective way to increase employees‘ awareness of quality and issues associated with quality assurance. The study identified widely existing problems in the Chinese welding industry and constructed a LCEPRS database that can be used in efforts to mitigate and avoid common problems. The work uses the theory of modular design, TWM and LEAN as tools for the implementation of the WQMC system.

Role of E3-ligase parkin in mitochondrial quality control in a cardiotoxicity model to anthracyclines

Dues à leur importance croissante dans la dégénérescence musculaire, les mitochondries sont de plus en plus étudiées en relation à diverses myopathies. Leurs mécanismes de contrôle de qualité sont reconnus pour leur rôle important dans la santé mitochondrial. Dans cette étude, nous tentons de déterminer si le déficit de mitophagie chez les souris déficiente du gène Parkin causera une exacerbation des dysfonctions mitochondriales normalement induite par la doxorubicine. Nous avons analysé l’impact de l’ablation de Parkin en réponse à un traitement à la doxorubicine au niveau du fonctionnement cardiaque, des fonctions mitochondriales et de l’enzymologie mitochondriale. Nos résultats démontrent qu’à l’état basal, l’absence de Parkin n’induit pas de pathologie cardiaque mais est associé à des dysfonctions mitochondriales multiples. La doxorubicine induit des dysfonctions respiratoires, du stress oxydant mitochondrial et une susceptibilité à l’ouverture du pore de transition de perméabilité (PTP). Finalement, contrairement à notre hypothèse, l’absence de Parkin n’accentue pas les dysfonctions mitochondriales induites par la doxorubicine et semble même exercer un effet protecteur.

Assessing the quality of tests : Revision of the EFPA review model

Resumen tomado de la publicación

Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments

MOTIVATION: The accurate prediction of the quality of 3D models is a key component of successful protein tertiary structure prediction methods. Currently, clustering or consensus based Model Quality Assessment Programs (MQAPs) are the most accurate methods for predicting 3D model quality; however they are often CPU intensive as they carry out multiple structural alignments in order to compare numerous models. In this study, we describe ModFOLDclustQ - a novel MQAP that compares 3D models of proteins without the need for CPU intensive structural alignments by utilising the Q measure for model comparisons. The ModFOLDclustQ method is benchmarked against the top established methods in terms of both accuracy and speed. In addition, the ModFOLDclustQ scores are combined with those from our older ModFOLDclust method to form a new method, ModFOLDclust2, that aims to provide increased prediction accuracy with negligible computational overhead. RESULTS: The ModFOLDclustQ method is competitive with leading clustering based MQAPs for the prediction of global model quality, yet it is up to 150 times faster than the previous version of the ModFOLDclust method at comparing models of small proteins (<60 residues) and over 5 times faster at comparing models of large proteins (>800 residues). Furthermore, a significant improvement in accuracy can be gained over the previous clustering based MQAPs by combining the scores from ModFOLDclustQ and ModFOLDclust to form the new ModFOLDclust2 method, with little impact on the overall time taken for each prediction. AVAILABILITY: The ModFOLDclustQ and ModFOLDclust2 methods are available to download from: http://www.reading.ac.uk/bioinf/downloads/ CONTACT: l.j.mcguffin@reading.ac.uk.

Prediction of global and local model quality in CASP8 using the ModFOLD server

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0-an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/.

Benchmarking consensus model quality assessment for protein fold recognition

Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. Many Model Quality Assessment Programs (MQAPs) have been developed which adopt various strategies in order to tackle this problem, ranging from the so called "true" MQAPs capable of producing a single energy score based on a single model, to methods which rely on structural comparisons of multiple models or additional information from meta-servers. However, it is clear that no current method can separate the highest accuracy models from the lowest consistently. In this paper, a number of the top performing MQAP methods are benchmarked in the context of the potential value that they add to protein fold recognition. Two novel methods are also described: ModSSEA, which based on the alignment of predicted secondary structure elements and ModFOLD which combines several true MQAP methods using an artificial neural network. Results: The ModSSEA method is found to be an effective model quality assessment program for ranking multiple models from many servers, however further accuracy can be gained by using the consensus approach of ModFOLD. The ModFOLD method is shown to significantly outperform the true MQAPs tested and is competitive with methods which make use of clustering or additional information from multiple servers. Several of the true MQAPs are also shown to add value to most individual fold recognition servers by improving model selection, when applied as a post filter in order to re-rank models. Conclusion: MQAPs should be benchmarked appropriately for the practical context in which they are intended to be used. Clustering based methods are the top performing MQAPs where many models are available from many servers; however, they often do not add value to individual fold recognition servers when limited models are available. Conversely, the true MQAP methods tested can often be used as effective post filters for re-ranking few models from individual fold recognition servers and further improvements can be achieved using a consensus of these methods.