An intercontinental comparison of chironomid palaeotemperature inference models: Europe vs North America

Chironomid-temperature inference models based on North American, European and combined surface sediment training sets were compared to assess the overall reliability of their predictions. Between 67 and 76 of the major chironomid taxa in each data set showed a unimodal response to July temperature, whereas between 5 and 22 of the common taxa showed a sigmoidal response. July temperature optima were highly correlated among the training sets, but the correlations for other taxon parameters such as tolerances and weighted averaging partial least squares (WA-PLS) and partial least squares (PLS) regression coefficients were much weaker. PLS, weighted averaging, WA-PLS, and the Modern Analogue Technique, all provided useful and reliable temperature inferences. Although jack-knifed error statistics suggested that two-component WA-PLS models had the highest predictive power, intercontinental tests suggested that other inference models performed better. The various models were able to provide good July temperature inferences, even where neither good nor close modern analogues for the fossil chironomid assemblages existed. When the models were applied to fossil Lateglacial assemblages from North America and Europe, the inferred rates and magnitude of July temperature changes varied among models. All models, however, revealed similar patterns of Lateglacial temperature change. Depending on the model used, the inferred Younger Dryas July temperature decrease ranged between 2.5 and 6°C.

GMM Based Inference with Standard Stratified Samples when the Aggregate Shares are Known

We show how to do efficient moment based inference using the generalized method of moments (GMM) when data is collected by standard stratified sampling and the maintained assumption is that the aggregate shares are known.

Polytomies and bayesian phylogenetic inference

Bayesian phylogenetic analyses are now very popular in systematics and molecular evolution because they allow the use of much more realistic models than currently possible with maximum likelihood methods. There are, however, a growing number of examples in which large Bayesian posterior clade probabilities are associated with very short edge lengths and low values for non-Bayesian measures of support such as nonparametric bootstrapping. For the four-taxon case when the true tree is the star phylogeny, Bayesian analyses become increasingly unpredictable in their preference for one of the three possible resolved tree topologies as data set size increases. This leads to the prediction that hard (or near-hard) polytomies in nature will cause unpredictable behavior in Bayesian analyses, with arbitrary resolutions of the polytomy receiving very high posterior probabilities in some cases. We present a simple solution to this problem involving a reversible-jump Markov chain Monte Carlo (MCMC) algorithm that allows exploration of all of tree space, including unresolved tree topologies with one or more polytomies. The reversible-jump MCMC approach allows prior distributions to place some weight on less-resolved tree topologies, which eliminates misleadingly high posteriors associated with arbitrary resolutions of hard polytomies. Fortunately, assigning some prior probability to polytomous tree topologies does not appear to come with a significant cost in terms of the ability to assess the level of support for edges that do exist in the true tree. Methods are discussed for applying arbitrary prior distributions to tree topologies of varying resolution, and an empirical example showing evidence of polytomies is analyzed and discussed.

Moment Based Inference with Stratified Data

Many datasets used by economists and other social scientists are collected by stratified sampling. The sampling scheme used to collect the data induces a probability distribution on the observed sample that differs from the target or underlying distribution for which inference is to be made. If this effect is not taken into account, subsequent statistical inference can be seriously biased. This paper shows how to do efficient semiparametric inference in moment restriction models when data from the target population is collected by three widely used sampling schemes: variable probability sampling, multinomial sampling, and standard stratified sampling.

Polytomies and bayesian phylogenetic inference

Bayesian phylogenetic analyses are now very popular in systematics and molecular evolution because they allow the use of much more realistic models than currently possible with maximum likelihood methods. There are, however, a growing number of examples in which large Bayesian posterior clade probabilities are associated with very short edge lengths and low values for non-Bayesian measures of support such as nonparametric bootstrapping. For the four-taxon case when the true tree is the star phylogeny, Bayesian analyses become increasingly unpredictable in their preference for one of the three possible resolved tree topologies as data set size increases. This leads to the prediction that hard (or near-hard) polytomies in nature will cause unpredictable behavior in Bayesian analyses, with arbitrary resolutions of the polytomy receiving very high posterior probabilities in some cases. We present a simple solution to this problem involving a reversible-jump Markov chain Monte Carlo (MCMC) algorithm that allows exploration of all of tree space, including unresolved tree topologies with one or more polytomies. The reversible-jump MCMC approach allows prior distributions to place some weight on less-resolved tree topologies, which eliminates misleadingly high posteriors associated with arbitrary resolutions of hard polytomies. Fortunately, assigning some prior probability to polytomous tree topologies does not appear to come with a significant cost in terms of the ability to assess the level of support for edges that do exist in the true tree. Methods are discussed for applying arbitrary prior distributions to tree topologies of varying resolution, and an empirical example showing evidence of polytomies is analyzed and discussed.

Bayesian inference and its application to meta-analysis of epidemiologic data

In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayesian method are illustrated. Part Two applies the Bayesian meta-analysis program, the Confidence Profile Method (CPM), to clinical trial data and evaluates the merits of using Bayesian meta-analysis for overviews of clinical trials.^ The Bayesian method of meta-analysis produced similar results to the classical results because of the large sample size, along with the input of a non-preferential prior probability distribution. These results were anticipated through explanations in Part One of the mechanics of the Bayesian approach. ^

Simultaneous induction of NKG2D and NKG2D ligand for promoting immune surveillance by IL-12 plus doxorubicin treatment

NKG2D (natural killer group 2, member D) and its ligands interaction in tumor microenvironment directs tumor infiltrating immune cells to recognize tumor cells, stimulate cytotoxic effector immune cells, and therefore eradicate tumor cells. IL-12, a cytokine produced by antigen presenting cells, has remarkable antitumor effect by activating innate and adaptive immunity. Doxorubicin, a commonly used chemotherapeutic agent also boosts the host antitumor immune response to cause tumor cell death. Our previous publication suggests that IL-12 plus doxorubicin enhances NKG2D function-dependent inhibition of tumor progression and promotes CD8+T cells infiltrating into tumors. The purpose of this study is to determine the underlying mechanism. Our study reveals a novel function of doxorubicin, which is to augment IL-12–induced NKG2D expression in CD8+T cells but not in NK or CD4+T cells. This observation was further validated by NK and CD8+T cell-depletion studies, in which only depletion of CD8+T cells abolished the expression of NKG2D in lymphocytes. The induced NKG2D expression in CD8+T cells is tightly associated with tumor-specific localization of CD8+T cells and improved antitumor efficacy. The IL-12 plus doxorubicin treatment-induced antitumor efficacy is also due to NKG2D ligand Rae-1 induction in tumors. Rae-1 induction in tumors is a long term effect in multiple tumor models, but not in normal tissues. A novel CD8+T cell direct contact dependent mechanism accounts for Rae-1 induction in vivo and in vitro, and CD80 is the receptor through which CD8+T cells interplay with tumor cells to upregulate Rae-1 on tumor cells. In summary, increased NKG2D expression in CD8+T cells in response to IL-12 plus doxorubicin was closely associated with tumor-specific localization of CD8+T cells and greater antitumor efficacy of the combined regimen than either agent alone. NKG2D ligand Rae-1 induction is triggered by the interaction of CD80 on tumor cells with tumor infiltrating CD+8 T cells.

Fases en la derivación e interpretación semántico pragmática

En trabajos anteriores (Romero, 2008a y b, Alabart Lago, L., P. Díaz y G. Herrera, 2012, Alabart Lago, L. y Herrera, G., 2013) se intentó mostrar que el mecanismo interpretativo que propone la TR podría resultar adecuado como uno de los sistemas externos (también interpretativos) postulados por la GG, más precisamente, el sistema llamado CI. La relación que intentamos establecer tendrá en cuenta lo siguiente como marco teórico: a) En TR se afirma que la interpretación de un enunciado se deriva de las estructuras sintácticas, y esta derivación se realiza "en paralelo" con la derivación de estructuras llevada a cabo por las operaciones del componente sintáctico. b) En las últimas propuestas de la GG, extensiones y revisiones del PM propuesto en Chomsky (1995) no solo se dejan de lado los niveles de representación internos SP y ES sino también se considera prescindible la interfaz FL (Chomsky, 2005). Las estructuras generadas se transfieren a los sistemas externos en cuanto rasgos formales de las Categorías Funcionales son valorados. Mantendremos la noción de que el sistema computacional es relativamente irrestricto y que sus operaciones son condicionadas solo por Atracción y las llamadas "condiciones de legibilidad" impuestas por los sistemas externos, fundamentalmente el Principio de Interpretación Completa (PIC). c) Tendremos en cuenta la propuesta de Leonetti y Escandell Vidal (2004), que sostiene que las CCFF de la GG pueden considerarse equivalentes a las Categoría Procedimentales propuestas por la TR. En este sentido consideraremos válida la afirmación de Chomsky (1998) acerca de que las CCFF centrales (C, T, v y D) tienen propiedades semánticas. d) Otro factor que tendremos en cuenta es la noción de fase en la derivación, considerándola correcta en los términos expuestos en Chomsky (2001 y 2005) y Gallego (2007 y 2009), con ciertas modificaciones. Nuestra hipótesis puede resumirse en lo siguiente: Las operaciones de extracción de inferencias propuestas por TR se aplican durante la derivación sintáctica independientemente de que se haya transferido o no una fase. Es más, esperamos poder demostrar que algunos mecanismos inferenciales imponen ciertas condiciones que afectan a la valoración de los rasgos de las CCFF. Pretendemos también intentar mostrar que además de los núcleos de fase reconocidos, C y v, debe considerarse fase a SD, porque contiene rasgos específicos de cuyo cotejo y valoración se desprende el valor que recibirán otros rasgos en el curso de la derivación. Con estos fundamentos esperamos poder elaborar una descripción de cómo interactúan ambos sistemas en la derivación de una oración y la asignación (casi simultánea) de significado

Fases en la derivación e interpretación semántico pragmática

En trabajos anteriores (Romero, 2008a y b, Alabart Lago, L., P. Díaz y G. Herrera, 2012, Alabart Lago, L. y Herrera, G., 2013) se intentó mostrar que el mecanismo interpretativo que propone la TR podría resultar adecuado como uno de los sistemas externos (también interpretativos) postulados por la GG, más precisamente, el sistema llamado CI. La relación que intentamos establecer tendrá en cuenta lo siguiente como marco teórico: a) En TR se afirma que la interpretación de un enunciado se deriva de las estructuras sintácticas, y esta derivación se realiza "en paralelo" con la derivación de estructuras llevada a cabo por las operaciones del componente sintáctico. b) En las últimas propuestas de la GG, extensiones y revisiones del PM propuesto en Chomsky (1995) no solo se dejan de lado los niveles de representación internos SP y ES sino también se considera prescindible la interfaz FL (Chomsky, 2005). Las estructuras generadas se transfieren a los sistemas externos en cuanto rasgos formales de las Categorías Funcionales son valorados. Mantendremos la noción de que el sistema computacional es relativamente irrestricto y que sus operaciones son condicionadas solo por Atracción y las llamadas "condiciones de legibilidad" impuestas por los sistemas externos, fundamentalmente el Principio de Interpretación Completa (PIC). c) Tendremos en cuenta la propuesta de Leonetti y Escandell Vidal (2004), que sostiene que las CCFF de la GG pueden considerarse equivalentes a las Categoría Procedimentales propuestas por la TR. En este sentido consideraremos válida la afirmación de Chomsky (1998) acerca de que las CCFF centrales (C, T, v y D) tienen propiedades semánticas. d) Otro factor que tendremos en cuenta es la noción de fase en la derivación, considerándola correcta en los términos expuestos en Chomsky (2001 y 2005) y Gallego (2007 y 2009), con ciertas modificaciones. Nuestra hipótesis puede resumirse en lo siguiente: Las operaciones de extracción de inferencias propuestas por TR se aplican durante la derivación sintáctica independientemente de que se haya transferido o no una fase. Es más, esperamos poder demostrar que algunos mecanismos inferenciales imponen ciertas condiciones que afectan a la valoración de los rasgos de las CCFF. Pretendemos también intentar mostrar que además de los núcleos de fase reconocidos, C y v, debe considerarse fase a SD, porque contiene rasgos específicos de cuyo cotejo y valoración se desprende el valor que recibirán otros rasgos en el curso de la derivación. Con estos fundamentos esperamos poder elaborar una descripción de cómo interactúan ambos sistemas en la derivación de una oración y la asignación (casi simultánea) de significado

Land based mesocosm experiment studying the simultaneous impact of warming and acidification on the planktonic food web of the Eastern Mediterranean

A land based mesocosm experiment focusing on the study of the simultaneous impact of warming and acidification on the planktonic food web of the Eastern Mediterranean took place in August-September 2013 at the mesocosm facilities of HCMR in Crete (CRETACOSMOS). Two different pCO2 (present day and predicted for year 2100) were applied in triplicate mesocosms of 3 m**3. This was tested in two different temperatures (ambient seawater T and ambient T plus 3°C). Twelve mesocosms in total were incubated in two large concrete tanks. Temperature was controlled by sophisticated, automated systems. A large variety of chemical, biological and biochemical variables were studied, including salinity, temperature, light and alkalinity measurements, inorganic and organic, particulate and dissolved, nutrient analyses, biological stock (Chla concentration, enumeration and community composition of microbial, phyto- and zooplankton organisms) and rate (primary, bacterial, viral production, copepod egg production, zooplankton grazing, N2 fixation, P uptake) measurements, bacterial DNA extraction and phytoplankton transcriptomics, calcifiers analyses. Twenty three scientists from 6 Institutes and 5 countries participated in this experiment.

European mink (Mustela lutreola) and American mink (Neovison vison) detection histories in Northern Spain between 2000 and 2011

Understanding changes over time in the distribution of interacting native and invasive species that may be symptomatic of competitive exclusion is critical to identify the need for and effectiveness of management interventions. Occupancy models greatly increase the robustness of inference that can be made from presence/absence data when species are imperfectly detected, and recent novel developments allow for the quantification of the strength of interaction between pairs of species. We used a two-species multi-season occupancy model to quantify the impact of the invasive American mink on the native European mink in Spain through the analysis of their co-occurrence pattern over twelve years (2000 - 2011) in the entire Spanish range of European mink distribution, where both species were detected by live trapping but American mink were culled. We detected a negative temporal trend in the rate of occupancy of European mink and a simultaneous positive trend in the occupancy of American mink. The species co-occurred less often than expected and the native mink was more likely to become extinct from sites occupied by the invasive species. Removal of American mink resulted in a high probability of local extinction where it co-occurred with the endemic mink, but the overall increase in the probability of occupancy over the last decade indicates that the ongoing management is failing to halt its spread. More intensive culling effort where both species co-exist as well as in adjacent areas where the invasive American mink is found at high densities is required in order to stop thedecline of European mink.

Desing and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.d

Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling

Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.