A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series.

Understanding the regulatory mechanisms that are responsible for an organism's response to environmental change is an important issue in molecular biology. A first and important step towards this goal is to detect genes whose expression levels are affected by altered external conditions. A range of methods to test for differential gene expression, both in static as well as in time-course experiments, have been proposed. While these tests answer the question whether a gene is differentially expressed, they do not explicitly address the question when a gene is differentially expressed, although this information may provide insights into the course and causal structure of regulatory programs. In this article, we propose a two-sample test for identifying intervals of differential gene expression in microarray time series. Our approach is based on Gaussian process regression, can deal with arbitrary numbers of replicates, and is robust with respect to outliers. We apply our algorithm to study the response of Arabidopsis thaliana genes to an infection by a fungal pathogen using a microarray time series dataset covering 30,336 gene probes at 24 observed time points. In classification experiments, our test compares favorably with existing methods and provides additional insights into time-dependent differential expression.

Fish and habitat community assessments on North Carolina shipwrecks: potential sites for detecting climate change in the graveyard of the Atlantic

The Monitor National Marine Sanctuary (MNMS) was the nation’s first sanctuary, originally established in 1975 to protect the famous civil war ironclad shipwreck, the USS Monitor. Since 2008, sanctuary sponsored archeological research has branched out to include historically significant U-boats and World War II shipwrecks within the larger Graveyard of the Atlantic off the coast of North Carolina. These shipwrecks are not only important for their cultural value, but also as habitat for a wide diversity of fishes, invertebrates and algal species. Additionally, due to their unique location within an important area for biological productivity, the sanctuary and other culturally valuable shipwrecks within the Graveyard of the Atlantic are potential sites for examining community change. For this reason, from June 8-30, 2010, biological and ecological investigations were conducted at four World War II shipwrecks (Keshena, City of Atlanta, Dixie Arrow, EM Clark), as part of the MNMS 2010 Battle of the Atlantic (BOTA) research project. At each shipwreck site, fish community surveys were conducted and benthic photo-quadrats were collected to characterize the mobile conspicuous fish, smaller prey fish, and sessile invertebrate and algal communities. In addition, temperature sensors were placed at all four shipwrecks previously mentioned, as well as an additional shipwreck, the Manuela. The data, which establishes a baseline condition to use in future assessments, suggest strong differences in both the fish and benthic communities among the surveyed shipwrecks based on the oceanographic zone (depth). In order to establish these shipwrecks as sites for detecting community change it is suggested that a subset of locations across the shelf be selected and repeatedly sampled over time. In order to reduce variability within sites for both the benthic and fish communities, a significant number of surveys should be conducted at each location. This sampling strategy will account for the natural differences in community structure that exist across the shelf due to the oceanographic regime, and allow robust statistical analyses of community differences over time.

Detecting lineage-specific adaptive evolution of brain-expressed genes in human using rhesus macaque as outgroup

Comparative genetic analysis between human and chimpanzee may detect genetic divergences responsible for human-specific characteristics. Previous studies have identified a series of genes that potentially underwent Darwinian positive selection during huma

Detecting positive darwinian selection in brain-expressed genes during human evolution

To understand the genetic basis that underlies the phenotypic divergence between human and non-human primates, we screened a total of 7176 protein-coding genes expressed in the human brain and compared them with the chimpanzee orthologs to identity genes

Social sensing in the field: Challenges in detecting social interactions in construction sites

Construction industry is a sector that is renowned for the slow uptake of new technologies. This is usually due to the conservative nature of this sector that relies heavily on tried and tested and successful old business practices. However, there is an eagerness in this industry to adopt Building Information Modelling (BIM) technologies to capture and record accurate information about a building project. But vast amounts of information and knowledge about the construction process is typically hidden within informal social interactions that take place in the work environment. In this paper we present a vision where smartphones and tablet devices carried by construction workers are used to capture the interaction and communication between workers in the field. Informal chats about decisions taken in the field, impromptu formation of teams, identification of key persons for certain tasks, and tracking the flow of information across the project community, are some pieces of information that could be captured by employing social sensing in the field. This information can not only be used during the construction to improve the site processes but it can also be exploited by the end user during maintenance of the building. We highlight the challenges that need to be overcome for this mobile and social sensing system to become a reality. © 2012 ACM.

Detecting air pockets for architectural concrete quality assessment using visual sensing

Air pockets, one kind of concrete surface defects, are often created on formed concrete surfaces during concrete construction. Their existence undermines the desired appearance and visual uniformity of architectural concrete. Therefore, measuring the impact of air pockets on the concrete surface in the form of air pockets is vital in assessing the quality of architectural concrete. Traditionally, such measurements are mainly based on in-situ manual inspections, the results of which are subjective and heavily dependent on the inspectors’ own criteria and experience. Often, inspectors may make different assessments even when inspecting the same concrete surface. In addition, the need for experienced inspectors costs owners or general contractors more in inspection fees. To alleviate these problems, this paper presents a methodology that can measure air pockets quantitatively and automatically. In order to achieve this goal, a high contrast, scaled image of a concrete surface is acquired from a fixed distance range and then a spot filter is used to accurately detect air pockets with the help of an image pyramid. The properties of air pockets (the number, the size, and the occupation area of air pockets) are subsequently calculated. These properties are used to quantify the impact of air pockets on the architectural concrete surface. The methodology is implemented in a C++ based prototype and tested on a database of concrete surface images. Comparisons with manual tests validated its measuring accuracy. As a result, the methodology presented in this paper can increase the reliability of concrete surface quality assessment

Detecting bipedal motion from correlated probabilistic trajectories

This paper is about detecting bipedal motion in video sequences by using point trajectories in a framework of classification. Given a number of point trajectories, we find a subset of points which are arising from feet in bipedal motion by analysing their spatio-temporal correlation in a pairwise fashion. To this end, we introduce probabilistic trajectories as our new features which associate each point over a sufficiently long time period in the presence of noise. They are extracted from directed acyclic graphs whose edges represent temporal point correspondences and are weighted with their matching probability in terms of appearance and location. The benefit of the new representation is that it practically tolerates inherent ambiguity for example due to occlusions. We then learn the correlation between the motion of two feet using the probabilistic trajectories in a decision forest classifier. The effectiveness of the algorithm is demonstrated in experiments on image sequences captured with a static camera, and extensions to deal with a moving camera are discussed. © 2013 Elsevier B.V. All rights reserved.

A simple ac bridge for detecting small resistance change

A simple ac resistance bridge is proposed. The stability of the design is better than 10(-6), which is especially suitable for detecting tiny changes of resistance. An example of magnetoresistance measurement for a 220 nm Au film shows the good performance of the bridge. (C) 2009 American Institute of Physics. [DOI: 10.1063/1.3202284]

Detecting quantum entanglement by means of local operations and classical communication

Based on the positive maps separability criterion, we present a method for the detection of quantum entanglement of a shared bipartite quantum state, within the "distant labs" paradigm, using only local operations and classical communication.

Detecting a set of entanglement measures in an unknown tripartite quantum state by local operations and classical communication

We propose a more general method for detecting a set of entanglement measures, i.e., negativities, in an arbitrary tripartite quantum state by local operations and classical communication. To accomplish the detection task using this method, three observers do not need to perform partial transposition maps by the structural physical approximation; instead, they only need to collectively measure some functions via three local networks supplemented by a classical communication. With these functions, they are able to determine the set of negativities related to the tripartite quantum state.