Using high-resolution ellipsometry and stray light intensity measurements, we have investigated during successive heating-cooling cycles the optical thickness and surface roughness of thin dotriacontane (n-C 32 H 66 ) films adsorbed from a heptane (n-C 7 H 16 ) solution onto SiO 2 -coated Si͑100͒ single-crystal substrates. Our results suggest a model of a solid dotriacontane film that has a phase closest to the SiO 2 surface in which the long-axis of the molecules is oriented parallel to the interface. Above this ''parallel film'' phase, a solid monolayer adsorbs in which the molecules are oriented perpendicular to the interface. At still higher coverages and at temperatures below the bulk melting point at T b ϭ341 K, solid bulk particles coexist on top of the ''perpendicular film.'' For higher temperatures in the range T b ϽTϽT s where T s ϭ345 K is the wetting temperature of the bulk phase, the coexisting bulk particles melt into droplets; and for TϾT s , a uniformly thick fluid film wets to the parallel film phase. This structure of the alkane/SiO 2 interfacial region differs qualitatively from that which occurs in the surface freezing effect at the bulk alkane fluid/vapor interface. In that case, there is again a perpendicular film phase adjacent to the air interface but no parallel film phase intervenes between it and the bulk alkane fluid. Similarities and differences between our model of the alkane/SiO 2 interface and one proposed recently will be discussed. Our ellipsometric measurements also show evidence of a crystalline-to-plastic transition in the perpendicular film phase similar to that occurring in the solid bulk particles present at higher coverages. In addition, we have performed high-resolution ellipsometry and stray-light measurements on dotriacontane films deposited from solution onto highly oriented pyrolytic graphite substrates. After film deposition, these substrates proved to be less stable in air than SiO 2 .

Morphological identification of acute leukemia is a powerful tool used by hematologists to determine the family of such a disease. In some cases, experienced physicians are even able to determine the leukemia subtype of the sample. However, the identification process may have error rates up to 40% (when classifying acute leukemia subtypes) depending on the physician’s experience and the sample quality. This problem raises the need to create automatic tools that provide hematologists with a second opinion during the classification process. Our research presents a contextual analysis methodology for the detection of acute leukemia subtypes from bone marrow cells images. We propose a cells separation algorithm to break up overlapped regions. In this phase, we achieved an average accuracy of 95% in the evaluation of the segmentation process. In a second phase, we extract descriptive features to the nucleus and cytoplasm obtained in the segmentation phase in order to classify leukemia families and subtypes. We finally created a decision algorithm that provides an automatic diagnosis for a patient. In our experiments, we achieved an overall accuracy of 92% in the supervised classification of acute leukemia families, 84% for the lymphoblastic subtypes, and 92% for the myeloblastic subtypes. Finally, we achieved accuracies of 95% in the diagnosis of leukemia families and 90% in the diagnosis of leukemia subtypes.

Characterization of lifetime behavioral changes is essential for understanding aging and aging-related diseases. However, such studies are scarce partly due to the lack of efficient tools. Here we describe and provide proof of concept for a stereo vision system that classifies and sequentially records at an extremely fine scale six different behaviors (resting, micro-movement, walking, flying, feeding and drinking) and the within-cage (3D) location of individual tephritid fruit flies by time-of-day throughout their lives. Using flies fed on two different diets, full sugar-yeast and sugar-only diets, we report for the first time their behavioral changes throughout their lives at a high resolution. We have found that the daily activity peaks at the age of 15–20 days and then gradually declines with age for flies on both diets. However, the overall daily activity is higher for flies on sugar-only diet than those on the full diet. Flies on sugar-only diet show a stronger diurnal localization pattern with higher preference to staying on the top of the cage during the period of light-off when compared to flies on the full diet. Clustering analyses of age-specific behavior patterns reveal three distinct young, middle-aged and old clusters for flies on each of the two diets. The middle-aged groups for flies on sugar-only diet consist of much younger age groups when compared to flies on full diet. This technology provides research opportunities for using a behavioral informatics approach for understanding different ways in which behavior, movement, and aging in model organisms are mutually affecting.

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Improving fingerprint matching algorithms is an active and important research area in fingerprint recognition. Algorithms based on minutia triplets, an important matcher family, present some drawbacks that impact their accuracy, such as dependency to the order of minutiae in the feature, insensitivity to the reflection of minutiae triplets, and insensitivity to the directions of the minutiae relative to the sides of the triangle. To alleviate these drawbacks, we introduce in this paper a novel fingerprint matching algorithm, named M3gl. This algorithm contains three components: a new feature representation containing clockwise-arranged minutiae without a central minutia, a new similarity measure that shifts the triplets to find the best minutiae correspondence, and a global matching procedure that selects the alignment by maximizing the amount of global matching minutiae. To make M3gl faster, it includes some optimizations to discard non-matching minutia triplets without comparing the whole representation. In comparison with six verification algorithms, M3gl achieves the highest accuracy in the lowest matching time, using FVC2002 and FVC2004 databases.

Abstract. Service robots are becoming increasingly available and it is expected that they will be part of many human activities in the near future. It is desirable for these robots to adapt themselves to the user's needs, so non-expert users will have to teach them how to perform new tasks in natural ways. In this paper a new teaching by demonstration algorithm is described. It uses a Kinect R sensor to track the movements of a user, eliminating the need of special sensors or environment conditions, it represents the tasks with a relational representation to facilitate the correspondence problem between the user and robot arm and to learn how to perform tasks in a more general description, it uses reinforcement learning to improve over the initial sequences provided by the user, and it incorporates on-line feedback from the user during the learning process creating a novel dynamic reward shaping mechanism to converge faster to an optimal policy. We demonstrate the approach by learning simple manipulation tasks of a robot arm and show its superiority over more traditional reinforcement learning algorithms.

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