Alignment by Maximization of Mutual Information

A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. In our derivation, few assumptions are made about the nature of the imaging process. As a result the algorithms are quite general and can foreseeably be used in a wide variety of imaging situations. Experiments are presented that demonstrate the approach registering magnetic resonance (MR) images with computed tomography (CT) images, aligning a complex 3D object model to real scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2D object model to real images. The method is based on a formulation of the mutual information between the model and the image called EMMA. As applied here the technique is intensity-based, rather than feature-based. It works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust than traditional correlation. Additionally, it has an efficient implementation that is based on stochastic approximation. Finally, we will describe a number of additional real-world applications that can be solved efficiently and reliably using EMMA. EMMA can be used in machine learning to find maximally informative projections of high-dimensional data. EMMA can also be used to detect and correct corruption in magnetic resonance images (MRI).

Archaeological evidence for the first Mesolithic occupation of the Western Isles of Scotland

The examination of eroding coastal dunes at the prehistoric site of Northton, Harris, has produced the first archaeological evidence of Mesolithic activity in the Western Isles in the form of two midden-related deposits. The first phase of Mesolithic activity is dated to 7060-6650 cal. Bc based on AMS dating of charred hazelnut shells. This discovery appears to validate the frequent pollen-based inferences of Mesolithic impact for the area and, as predicted, allows the Atlantic fringe of Scotland to become part of the European Mesolithic mainstream. A detailed pedological analysis also suggests that these early midden layers may have been amended during the Neolithic period as part of a possible phase of cultivation.

Investigação de contatos elétricos e propriedades de filmes finos de SnO2 dopados com os íons terras raras Eu3+ e Ce3+

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Blood aspiration as a vital sign detected by postmortem computed tomography imaging

Blood aspiration is a significant forensic finding. In this study, we examined the value of postmortem computed tomography (CT) imaging in evaluating findings of blood aspiration. We selected 37 cases with autopsy evidence of blood in the lungs and/or in the airways previously submitted to total-body CT scanning. The CT-images were retrospectively analyzed. In one case with pulmonary blood aspiration, biopsy specimens were obtained under CT guide for histological examination. In six cases, CT detected pulmonary abnormalities suggestive of blood aspiration, not mentioned in the autopsy reports. CT reconstructions provided additional data about the distribution and extent of aspiration. In one needle-biopsied case, the pulmonary specimens showed blood in the alveoli. We suggest the use of CT imaging as a tool complementary to traditional techniques in cases of blood aspiration to avoid misdiagnosis, to guide the investigation of lung tissue, and to allow for more evidence-based inferences on the cause of death.

A Cox Model for Biostatistics of the Future

Professor Sir David R. Cox (DRC) is widely acknowledged as among the most important scientists of the second half of the twentieth century. He inherited the mantle of statistical science from Pearson and Fisher, advanced their ideas, and translated statistical theory into practice so as to forever change the application of statistics in many fields, but especially biology and medicine. The logistic and proportional hazards models he substantially developed, are arguably among the most influential biostatistical methods in current practice. This paper looks forward over the period from DRC's 80th to 90th birthdays, to speculate about the future of biostatistics, drawing lessons from DRC's contributions along the way. We consider "Cox's model" of biostatistics, an approach to statistical science that: formulates scientific questions or quantities in terms of parameters gamma in probability models f(y; gamma) that represent in a parsimonious fashion, the underlying scientific mechanisms (Cox, 1997); partition the parameters gamma = theta, eta into a subset of interest theta and other "nuisance parameters" eta necessary to complete the probability distribution (Cox and Hinkley, 1974); develops methods of inference about the scientific quantities that depend as little as possible upon the nuisance parameters (Barndorff-Nielsen and Cox, 1989); and thinks critically about the appropriate conditional distribution on which to base infrences. We briefly review exciting biomedical and public health challenges that are capable of driving statistical developments in the next decade. We discuss the statistical models and model-based inferences central to the CM approach, contrasting them with computationally-intensive strategies for prediction and inference advocated by Breiman and others (e.g. Breiman, 2001) and to more traditional design-based methods of inference (Fisher, 1935). We discuss the hierarchical (multi-level) model as an example of the future challanges and opportunities for model-based inference. We then consider the role of conditional inference, a second key element of the CM. Recent examples from genetics are used to illustrate these ideas. Finally, the paper examines causal inference and statistical computing, two other topics we believe will be central to biostatistics research and practice in the coming decade. Throughout the paper, we attempt to indicate how DRC's work and the "Cox Model" have set a standard of excellence to which all can aspire in the future.

Unresolved Problems with the "I", the "A" and the "T": Logical and Psychometric Critique of the Implicit Association Test (IAT)

The Implicit Association Test (IAT) had already gained the status of a prominent assessment procedure before its psychometric properties and underlying task structure were understood. The present critique addresses five major problems that arise when the IAT is used for diagnostic inferences: (1) the asymmetry of causal and diagnostic inferences; (2) the viability of the underlying association model; (3) the lack of a testable model underlying IAT-based inferences; (4) the difficulties of interpreting difference scores; and (5) the susceptibility of the IAT to deliberate faking and strategic processing. Based on a theoretical reflection of these issues, and a comprehensive survey of published IAT studies, it is concluded that a number of uncontrolled factors can produce (or reduce) significant IAT scores independently of the personality attribute that is supposed to be captured by the IAT procedure.

Challenges in using siliceous subfossils as a tool for inferring past water level and hydroperiod in Everglades marshes

Successfully rehabilitating drained wetlands through hydrologic restoration is dependent on defining restoration targets, a process that is informed by pre-drainage conditions, as well as understanding linkages between hydrology and ecosystem structure. Paleoecological records can inform restoration goals by revealing long-term patterns of change, but are dependent on preservation of biomarkers that provide meaningful interpretations of environmental change. In the Florida Everglades, paleohydrological hind-casting could improve restoration forecasting, but frequent drying of marsh soils leads to poor preservation of many biomarkers. To determine the effectiveness of employing siliceous subfossils in paleohydrological reconstructions, we examined diatoms, plant and sponge silico-sclerids from three soil cores in the central Everglades marshes. Subfossil quality varied among cores, but the abundance of recognizable specimens was sufficient to infer 1,000–3,000 years of hydrologic change at decadal to centennial resolution. Phytolith morphotypes were linked to key marsh plant species to indirectly measure fluctuations in water depth. A modern dataset was used to derive diatom-based inferences of water depth and hydroperiod (R2 = 0.63, 0.47; RMSE = 14 cm, 120 days, respectively). Changes in subfossil quality and abundances at centennial time-scales were associated with mid-Holocene climate events including the Little Ice Age and Medieval Warm Period, while decadal-scale fluctuations in assemblage structure during the twentieth century suggested co-regulation of hydrology by cyclical climate drivers (particularly the Atlantic Multidecadal Oscillation) and water management changes. The successful reconstructions based on siliceous subfossils shown here at a coarse temporal scale (i.e., decadal to centennial) advocate for their application in more highly resolved (i.e., subdecadal) records, which should improve the ability of water managers to target the quantity and variability of water flows appropriate for hydrologic restoration.

Distribution of Diatoms Along Environmental Gradients in the Charlotte Harbor, Florida (USA), Estuary and Its Watershed: Implications for Bioassessment of Salinity and Nutrient Concentrations

The relative abundance of diatom species in different habitats can be used as a tool to infer prior environmental conditions and evaluate management decisions that influence habitat quality. Diatom distribution patterns were examined to characterize relationships between assemblage composition and environmental gradients in a subtropical estuarine watershed. We identified environmental correlates of diatom distribution patterns across the Charlotte Harbor, Florida, watershed; evaluated differences among three major river drainages; and determined how accurately local environmental conditions can be predicted using inference models based on diatom assemblages. Sampling locations ranged from freshwater to marine (0.1–37.2 ppt salinity) and spanned broad nutrient concentration gradients. Salinity was the predominant driver of difference among diatom assemblages across the watershed, but other environmental variables had stronger correlations with assemblages within the subregions of the three rivers and harbor. Eighteen indicator taxa were significantly affiliated with subregions. Relationships between diatom taxon distributions and salinity, distance from the harbor, total phosphorus (TP), and total nitrogen (TN) were evaluated to determine the utility of diatom assemblages to predict environmental values using a weighted averaging-regression approach. Diatom-based inferences of these variables were strong (salinity R 2 = 0.96; distance R 2 = 0.93; TN R 2 = 0.83; TP R 2 = 0.83). Diatom assemblages provide reliable estimates of environmental parameters on different spatial scales across the watershed. Because many coastal diatom taxa are ubiquitous, the diatom training sets provided here should enable diatom-based environmental reconstructions in subtropical estuaries that are being rapidly altered by land and water use changes and sea level rise.

Are discourse comprehension and cognitive processes influenced by the type of language language (English and Spanish)? A cross-language study based on elaborative inferences generation

Resumen basado en el de la publicación

Carbohydrate-based micelle clusters which enhance hydrophobic drug bioavailability by up to 1 order of magnitude

Amphiphilic chitosan-based polymers (M-w < 20 kDa) self-assemble in aqueous media at low micromolar concentrations to give previously unknown micellar clusters of 100-300 nm in size. Micellar clusters comprise smaller 10-30 nm aggregates, and the nanopolarity/drug incorporation efficiency of their hydrophobic domains can be tailored by varying the degree of lipidic derivatization and molecular weight of the carbohydrate. The extent of drug incorporation by these novel micellar clusters is 1 order of magnitude higher than is seen with triblock copolymers, with molar polymer/drug ratios of 1:48 to 1:67. On intravenous injection, the pharmacodynamic activity of a carbohydrate propofol formulation is increased by 1 order of magnitude when compared to a commercial emulsion formulation, and on topical ocular application of a carbohydrate prednisolone formulation, initial drug aqueous humor levels are similar to those found with a 10-fold dose of prednisolone suspension.

Time correlated anomaly detection based on inferences

Anomaly detection techniques are used to find the presence of anomalous activities in a network by comparing traffic data activities against a "normal" baseline. Although it has several advantages which include detection of "zero-day" attacks, the question surrounding absolute definition of systems deviations from its "normal" behaviour is important to reduce the number of false positives in the system. This study proposes a novel multi-agent network-based framework known as Statistical model for Correlation and Detection (SCoDe), an anomaly detection framework that looks for timecorrelated anomalies by leveraging statistical properties of a large network, monitoring the rate of events occurrence based on their intensity. SCoDe is an instantaneous learning-based anomaly detector, practically shifting away from the conventional technique of having a training phase prior to detection. It does acquire its training using the improved extension of Exponential Weighted Moving Average (EWMA) which is proposed in this study. SCoDe does not require any previous knowledge of the network traffic, or network administrators chosen reference window as normal but effectively builds upon the statistical properties from different attributes of the network traffic, to correlate undesirable deviations in order to identify abnormal patterns. The approach is generic as it can be easily modified to fit particular types of problems, with a predefined attribute, and it is highly robust because of the proposed statistical approach. The proposed framework was targeted to detect attacks that increase the number of activities on the network server, examples which include Distributed Denial of Service (DDoS) and, flood and flash-crowd events. This paper provides a mathematical foundation for SCoDe, describing the specific implementation and testing of the approach based on a network log file generated from the cyber range simulation experiment of the industrial partner of this project.

A chrysophyte stomatocyst-based reconstruction of cold-season air temperature from Alpine Lake Silvaplana (AD 1500–2003); methods and concepts for quantitative inferences

Relatively little is known about past cold-season temperature variability in high-Alpine regions because of a lack of natural cold-season temperature proxies as well as under-representation of high-altitude sites in meteorological, early-instrumental and documentary data sources. Recent studies have shown that chrysophyte stomatocysts, or simply cysts (sub-fossil algal remains of Chrysophyceae and Synurophyceae), are among the very few natural proxies that can be used to reconstruct cold-season temperatures. This study presents a quantitative, high-resolution (5-year), cold-season (Oct–May) temperature reconstruction based on sub-fossil chrysophyte stomatocysts in the annually laminated (varved) sediments of high-Alpine Lake Silvaplana, SE Switzerland (1,789 m a.s.l.), since AD 1500. We first explore the method used to translate an ecologically meaningful variable based on a biological proxy into a simple climate variable. A transfer function was applied to reconstruct the ‘date of spring mixing’ from cyst assemblages. Next, statistical regression models were tested to convert the reconstructed ‘dates of spring mixing’ into cold-season surface air temperatures with associated errors. The strengths and weaknesses of this approach are thoroughly tested. One much-debated, basic assumption for reconstructions (‘stationarity’), which states that only the environmental variable of interest has influenced cyst assemblages and the influence of confounding variables is negligible over time, is addressed in detail. Our inferences show that past cold-season air-temperature fluctuations were substantial and larger than those of other temperature reconstructions for Europe and the Alpine region. Interestingly, in this study, recent cold-season temperatures only just exceed those of previous, multi-decadal warm phases since AD 1500. These findings highlight the importance of local studies to assess natural climate variability at high altitudes.