A multitracer approach to assess the spatial contamination pattern of hake (Merluccius merluccius) in the French Mediterranean

Chemical contamination levels and stable isotope ratios provide integrated information about contaminant exposure, trophic position and also biological and environmental influences on marine organisms. By combining these approaches with otolith shape analyses, the aim of the present study was to document the spatial variability of Hg and PCB contamination of the European hake (Merluccius merluccius) in the French Mediterranean, hypothesizing that local contaminant sources, environmental conditions and biological specificities lead to site-specific contamination patterns. High Hg concentrations discriminated Corsica (average: 1.36 ± 0.80 μg g− 1 dm) from the Gulf of Lions (average values < 0.5 μg g− 1 dm), where Rhône River input caused high PCB burdens. CB 153 average concentrations ranged between 4.00 ± 0.64 and 18.39 ± 12.38 ng g− 1 dm in the Gulf of Lions, whatever the sex of the individuals, whereas the highest values in Corsica were 6.75 ± 4.22 ng g− 1 dm. Otolith shape discriminated juveniles and adults, due to their different habitats. The use of combined ecotracers was revealed as a powerful tool to discriminate between fish populations at large and small spatial scale, and to enable understanding of the environmental and biological influences on contamination patterns.

Leveraging Multiple Features for Image Retrieval and Matching

The goal of image retrieval and matching is to find and locate object instances in images from a large-scale image database. While visual features are abundant, how to combine them to improve performance by individual features remains a challenging task. In this work, we focus on leveraging multiple features for accurate and efficient image retrieval and matching. We first propose two graph-based approaches to rerank initially retrieved images for generic image retrieval. In the graph, vertices are images while edges are similarities between image pairs. Our first approach employs a mixture Markov model based on a random walk model on multiple graphs to fuse graphs. We introduce a probabilistic model to compute the importance of each feature for graph fusion under a naive Bayesian formulation, which requires statistics of similarities from a manually labeled dataset containing irrelevant images. To reduce human labeling, we further propose a fully unsupervised reranking algorithm based on a submodular objective function that can be efficiently optimized by greedy algorithm. By maximizing an information gain term over the graph, our submodular function favors a subset of database images that are similar to query images and resemble each other. The function also exploits the rank relationships of images from multiple ranked lists obtained by different features. We then study a more well-defined application, person re-identification, where the database contains labeled images of human bodies captured by multiple cameras. Re-identifications from multiple cameras are regarded as related tasks to exploit shared information. We apply a novel multi-task learning algorithm using both low level features and attributes. A low rank attribute embedding is joint learned within the multi-task learning formulation to embed original binary attributes to a continuous attribute space, where incorrect and incomplete attributes are rectified and recovered. To locate objects in images, we design an object detector based on object proposals and deep convolutional neural networks (CNN) in view of the emergence of deep networks. We improve a Fast RCNN framework and investigate two new strategies to detect objects accurately and efficiently: scale-dependent pooling (SDP) and cascaded rejection classifiers (CRC). The SDP improves detection accuracy by exploiting appropriate convolutional features depending on the scale of input object proposals. The CRC effectively utilizes convolutional features and greatly eliminates negative proposals in a cascaded manner, while maintaining a high recall for true objects. The two strategies together improve the detection accuracy and reduce the computational cost.

Multiple-Retrieval Case-Based Reasoning for Course Timetabling Problems

The structured representation of cases by attribute graphs in a Case-Based Reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organised as a decision tree and the retrieval process chooses those cases which are sub attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependant upon problem specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialisation method for local search methods such as Hill Climbing, Tabu Search and Simulated Annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialisation method for these approaches.

Multiple-retrieval case-based reasoning for course timetabling problems

The structured representation of cases by attribute graphs in a Case-Based Reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organised as a decision tree and the retrieval process chooses those cases which are sub attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependant upon problem specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialisation method for local search methods such as Hill Climbing, Tabu Search and Simulated Annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialisation method for these approaches.

Hierarchical clustering with multiple-height branch-cut applied to short time-series gene expression data.

Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automated or semi-automated methods, we developed a visual analytics approach for performing hierarchical clustering analysis of short time-series gene expression data. Dynamic sliders control parameters such as the similarity threshold at which clusters are merged and the level of relative intra-cluster distinctiveness, which can be used to identify "weak-edges" within clusters. An expert user can drill down to further explore the dendrogram and detect nested clusters and outliers. This is done by using the sliders and by pointing and clicking on the representation to cut the branches of the tree in multiple-heights. A prototype of this tool has been developed in collaboration with a small group of biologists for analysing their own datasets. Initial feedback on the tool has been positive.

Is there a health risk concerning the children´s consumption of cereal-based products? A cumulative mycotoxin risk assessment approach

Historically, the health risk of mycotoxins had been evaluated on the basis of single-chemical and single-exposure pathway scenarios. However, the co-contamination of foodstuffs with these compounds is being reported at an increasing rate and a multiple-exposure scenario for humans and vulnerable population groups as children is urgently needed. Cereals are among the first solid foods eaten by child and thus constitute an important food group of their diet. Few data are available relatively to early stages child´s exposure to mycotoxins through consumption of cereal-based foods. The present study aims to perform the cumulative risk assessment of mycotoxins present in a set of cereal-based foods including breakfast cereals (BC), processed cereal-based foods (PCBF) and biscuits (BT), consumed by children (1 to 3 years old, n=75) from Lisbon region, Portugal. Children food consumption and occurrence of 12 mycotoxins (aflatoxins, ochratoxin A, fumonisins and trichothecenes) in cereal-based foods were combined to estimate the mycotoxin daily intake, using deterministic and probabilistic approaches. Different strategies were used to treat the left censored data. For aflatoxins, as carcinogenic compounds, the margin of exposure (MoE) was calculated as a ratio of BMDL (benchmark dose lower confidence limit) and aflatoxin daily exposure. For the remaining mycotoxins, the output of exposure was compared to the dose reference values (TDI) in order to calculate the hazard quotients (HQ, ratio between exposure and a reference dose). The concentration addition (CA) concept was used for the cumulative risk assessment of multiple mycotoxins. The combined margin of exposure (MoET) and the hazard index (HI) were calculated for aflatoxins and the remaining mycotoxins, respectively. Main results revealed a significant health concern related to aflatoxins and especially aflatoxin M1 exposure according to the MoET and MoE values (below 10000), respectively. HQ and HI values for the remaining mycotoxins were below 1, revealing a low concern from a public health point of view. These are the first results on cumulative risk assessment of multiple mycotoxins present in cereal-based foods consumed by children. Considering the present results, more research studies are needed to provide the governmental regulatory bodies with data to develop an approach that contemplate the human exposure and, particularly, children, to multiple mycotoxins in food. The last issue is particularly important considering the potential synergistic effects that could occur between mycotoxins and its potential impact on human and, mainly, children health.

A review of the dissociative disorders: from multiple personality disorder to the posttraumatic stress

In this paper we review the idea of dissociation, dissociative disorders and their relationship with the processes of consciousness. We will deal specifically with multiple personality disorder and posttraumatic stress disorder. Both polarize the discussion of diagnostic categories with dissociative symptoms. This review compares the initial ideas (one century old) with the current scenario and emerging trends in research, which are relating cognitive processes and dissociative phenomena and disorders from a neuroscientific approach. We discuss the ideas on dissociation, hypnosis and suicide associated with these disorders. There seems to be a lack of consensus as to the nature of dissociation with theoretical, empirical and clinical implications.

Multiple Imputation of missing values in exploratory factor analysis of multidimensional scales: estimating latent trait scores

ABSTRACT Researchers frequently have to analyze scales in which some participants have failed to respond to some items. In this paper we focus on the exploratory factor analysis of multidimensional scales (i.e., scales that consist of a number of subscales) where each subscale is made up of a number of Likert-type items, and the aim of the analysis is to estimate participants' scores on the corresponding latent traits. We propose a new approach to deal with missing responses in such a situation that is based on (1) multiple imputation of non-responses and (2) simultaneous rotation of the imputed datasets. We applied the approach in a real dataset where missing responses were artificially introduced following a real pattern of non-responses, and a simulation study based on artificial datasets. The results show that our approach (specifically, Hot-Deck multiple imputation followed of Consensus Promin rotation) was able to successfully compute factor score estimates even for participants that have missing data.

From the human rights-based approach to an ecological approach on how to achieve successful inclusion in international disability education

The barriers that people with disabilities face around the world are not only inherent to the limitations resulting from the disability itself, but, more importantly, these barriers rest with the societal technologies of exclusion. Using a mixed methodology approach, I conduct a quest to revealing several societal factors that limit full participation of people with disabilities in their communities, which will contribute to understanding and developing a more comprehensive framework for full inclusion of people with disabilities into the society. First, I conduct a multiple regression analysis to seek whether there is a statistical relationship between the national level of development, the level of democratization, and the level of education within a country’s population on one hand, and expressed concern for and preparedness to improve the quality of life for people of disabilities on another hand. The results from the quantitative methodology reveal that people without disabilities are more prepared to take care of people with disabilities when the level of development of the country is higher, when the people have more freedom of expression and hold the government accountable for its actions, and when the level of corruption is under control. However, a greater concern for the well-being of people with disabilities is correlated with a high level of country development, a decreased value of political stability and absence of violence, a decreased level of government effectiveness, and a greater level of law enforcement. None of the dependent variables are significantly correlated with the level of education from a given country. Then, I delve into an interpretive analysis to understand multiple factors that contribute to the construction of attitudes and practices towards people with disabilities. In doing this, I build upon the four main principles outlined by the United Nations as strongly recommended to be embedded in all international programmes: (1) identification of claims of human rights and the corresponding obligations of governments, hence, I assess and analyze disability rights in education, looking at United Nation, United States, and European Union Perspectives Educational Rights Provisions for People with Disabilities (Ch. 3); (2) estimated capacity of individuals to claim their rights and of governments to fulfill their obligations, hence, I look at the people with disabilities as rights-holders and duty-bearers and discuss the importance of investing in special capital in the context of global development (Ch. 4); (3) programmes monitor and evaluate the outcomes and the processes under the auspices of human rights standards, hence, I look at the importance of evaluating the UN World Programme of Action Concerning People with Disabilities from multiple perspectives, as an example of why and how to monitor and evaluate educational human rights outcomes and processes (Ch. 5); and (4) programming should reflect the recommendations of international human rights bodies and mechanisms, hence, I focus on programming that fosters development of the capacity of people with disabilities, that is, planning for an ecology of disabilities and ecoducation for people with disabilities (Ch. 6). Results from both methodologies converge to a certain point, and they further complement each other. One common result for the two methodologies employed is that disability is an evolving concept when viewed in a broader context, which integrates the four spaces that the ecological framework incorporates. Another common result is that factors such as economic, social, legal, political, and natural resources and contexts contribute to the health, education and employment opportunities, and to the overall well-being of people with disabilities. The ecological framework sees all these factors from a meta-systemic perspective, where bi-directional interactions are expected and desired, and also from a human rights point of view, where the inherent value of people is upheld at its highest standard.

Mapping tissue inhomogeneity in acute myocarditis: a novel analytical approach to quantitative myocardial edema imaging by T2-mapping

BACKGROUND: The purpose of the present study was to investigate the diagnostic value of T2-mapping in acute myocarditis (ACM) and to define cut-off values for edema detection. METHODS: Cardiovascular magnetic resonance (CMR) data of 31 patients with ACM were retrospectively analyzed. 30 healthy volunteers (HV) served as a control. Additionally to the routine CMR protocol, T2-mapping data were acquired at 1.5 T using a breathhold Gradient-Spin-Echo T2-mapping sequence in six short axis slices. T2-maps were segmented according to the 16-segments AHA-model and segmental T2 values as well as the segmental pixel-standard deviation (SD) were analyzed. RESULTS: Mean differences of global myocardial T2 or pixel-SD between HV and ACM patients were only small, lying in the normal range of HV. In contrast, variation of segmental T2 values and pixel-SD was much larger in ACM patients compared to HV. In random forests and multiple logistic regression analyses, the combination of the highest segmental T2 value within each patient (maxT2) and the mean absolute deviation (MAD) of log-transformed pixel-SD (madSD) over all 16 segments within each patient proved to be the best discriminators between HV and ACM patients with an AUC of 0.85 in ROC-analysis. In classification trees, a combined cut-off of 0.22 for madSD and of 68 ms for maxT2 resulted in 83% specificity and 81% sensitivity for detection of ACM. CONCLUSIONS: The proposed cut-off values for maxT2 and madSD in the setting of ACM allow edema detection with high sensitivity and specificity and therefore have the potential to overcome the hurdles of T2-mapping for its integration into clinical routine.

Optimization of the Ion Source-Mass Spectrometry Parameters in Non-Steroidal Anti-Inflammatory and Analgesic Pharmaceuticals Analysis by a Design of Experiments Approach

The flow rates of drying and nebulizing gas, heat block and desolvation line temperatures and interface voltage are potential electrospray ionization parameters as they may enhance sensitivity of the mass spectrometer. The conditions that give higher sensitivity of 13 pharmaceuticals were explored. First, Plackett-Burman design was implemented to screen significant factors, and it was concluded that interface voltage and nebulizing gas flow were the only factors that influence the intensity signal for all pharmaceuticals. This fractionated factorial design was projected to set a full 2(2) factorial design with center points. The lack-of-fit test proved to be significant. Then, a central composite face-centered design was conducted. Finally, a stepwise multiple linear regression and subsequently an optimization problem solving were carried out. Two main drug clusters were found concerning the signal intensities of all runs of the augmented factorial design. p-Aminophenol, salicylic acid, and nimesulide constitute one cluster as a result of showing much higher sensitivity than the remaining drugs. The other cluster is more homogeneous with some sub-clusters comprising one pharmaceutical and its respective metabolite. It was observed that instrumental signal increased when both significant factors increased with maximum signal occurring when both codified factors are set at level +1. It was also found that, for most of the pharmaceuticals, interface voltage influences the intensity of the instrument more than the nebulizing gas flowrate. The only exceptions refer to nimesulide where the relative importance of the factors is reversed and still salicylic acid where both factors equally influence the instrumental signal. Graphical Abstract ᅟ.

An introduction to mathematical models of coagulation-fragmentation processes: a discrete deterministic mean-field approach

We summarise the properties and the fundamental mathematical results associated with basic models which describe coagulation and fragmentation processes in a deterministic manner and in which cluster size is a discrete quantity (an integer multiple of some basic unit size). In particular, we discuss Smoluchowski's equation for aggregation, the Becker-Döring model of simultaneous aggregation and fragmentation, and more general models involving coagulation and fragmentation.

Influences of change strategies to achieve organizational flexibility: a system dynamics approach.

257 p.

Iterated responsive threshold search for the quadratic multiple knapsack problem

International audience

Contributions to gait recognition using multiple views

Esta tesis se centra en la identificación de personas a través de la forma de caminar. El problema del reconocimiento del paso ha sido tratado mediante diferentes enfoques, en los dominios 2D y 3D, y usando una o varias vistas. Sin embargo, la dependencia con respecto al punto de vista, y por tanto de la trayectoria del sujeto al caminar sigue siendo aún un problema abierto. Se propone hacer frente al problema de la dependencia con respecto a la trayectoria por medio de reconstrucciones 3D de sujetos caminando. El uso de reconstrucciones varias ventajas que cabe destacar. En primer lugar, permite explotar una mayor cantidad de información en contraste con los métodos que extraen los descriptores de la marcha a partir de imágenes, en el dominio 2D. En segundo lugar, las reconstrucciones 3D pueden ser alineadas a lo largo de la marcha como si el sujeto hubiera caminado en una cinta andadora, proporcionando así una forma de analizar el paso independientemente de la trayectoria seguida. Este trabajo propone tres enfoques para resolver el problema de la dependencia a la vista: 1. Mediante la utilización de reconstrucciones volumétricas alineadas. 2. Mediante el uso de reconstrucciones volumétricas no alineadas. 3. Sin usar reconstrucciones. Se proponen además tres tipos de descriptores. El primero se centra en describir el paso mediante análisis morfológico de los volúmenes 3D alineados. El segundo hace uso del concepto de entropa de la información para describir la dinámica del paso humano. El tercero persigue capturar la dinámica de una forma invariante a rotación, lo cual lo hace especialmente interesante para ser aplicado tanto en trayectorias curvas como rectas, incluyendo cambios de dirección. Estos enfoques han sido probados sobre dos bases de datos públicas. Ambas están especialmente diseñadas para tratar el problema de la dependencia con respecto al punto de vista, y por tanto de la dependencia con respecto a la trayectoria. Los resultados experimentales muestran que para el enfoque basado en reconstrucciones volumétricas alineadas, el descriptor del paso basado en entropa consigue los mejores resultados, en comparación con métodos estrechamente relacionados del Estado del Arte actual. No obstante, el descriptor invariante a rotación consigue una tasa de reconocimiento que supera a los métodos actuales sin requerir la etapa previa de alineamiento de las reconstrucciones 3D.