Diet of the minimal armhook squid (Berryteuthis anonychus) (Cephalopoda: Gonatidae) in the northeast Pacific during spring

The stomach contents of the minimal armhook squid (Berryteuthis anonychus) were examined for 338 specimens captured in the northeast Pacific during May 1999. The specimens were collected at seven stations between 145−165°W and 39−49°N and ranged in mantle length from 10.3 to 102.2 mm. Their diet comprised seven major prey groups (copepods, chaetognaths, amphipods, euphausiids, ostracods, unidentified fish, and unidentified gelatinous prey) and was dominated by copepods and chaetognaths. Copepod prey comprised four genera, and 86% by number of the copepods were from the genus Neocalanus. Neocalanus cristatus was the most abundant prey taxa, composing 50% by mass and 35% by number of the total diet. Parasagitta elegans (Chaetognatha) occurred in more stomachs (47%) than any other prey taxon. Amphipods occurred in 19% of the stomachs but composed only 5% by number and 3% by mass of the total prey consumed. The four remaining prey groups (euphausiids, ostracods, unidentified fish, and unidentified gelatinous prey) together composed <2% by mass and <1% by number of the diet. There was no major change in the diet through the size range of squid examined and no evidence of cannibalism or predation on other cephalopod species.

Different protein tyrosine phosphatase superfamilies resulting from different gene reading frames

Protein tyrosine phosphatases (PTPs) are comprised of two superfamilies, the phosphatase I superfamily containing a single low-molecular-weight PTP (lmwPTP) family and the phosphatase II superfamily including both the higher-molecular-weight PTP (hmwPTP) and the dual-specificity phosphatase (DSP) families. The phosphatase I and H superfamilies are often considered to be the result of convergent evolution. The PTP sequence and structure analyses indicate that lmwPTPs, hmwPTPs, and DSPs share similar structures, functions, and a common signature motif, although they have low sequence identities and a different order of active sites in sequence or a circular permutation. The results of this work suggest that lmwPTPs and hmwPTPs/DSPs are remotely related in evolution. The earliest ancestral gene of PTPs could be from a short fragment containing about 90similar to120 nucleotides or 30similar to40 residues; however, a probable full PTP ancestral gene contained one transcript unit with two lmwPTP genes. All three PTP families may have resulted from a common ancestral gene by a series of duplications, fusions, and circular permutations. The circular permutation in PTPs is caused by a reading frame difference, which is similar to that in DNA methyltransferases. Nevertheless, the evolutionary mechanism of circular permutation in PTP genes seems to be more complicated than that in DNA methyltransferase genes. Both mechanisms in PTPs and DNA methyltransferases can be used to explain how some protein families and superfamilies came to be formed by circular permutations during molecular evolution.

Decentralised minimal-time consensus

This study considers the discrete-time dynamics of a network of agents that exchange information according to the nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically. We present a fully decentralised algorithm that allows any agent to compute the consensus value of the whole network in finite time using only the minimal number of successive values of its own history. We show that this minimal number of steps is related to a Jordan block decomposition of the network dynamics and present an algorithm to obtain the minimal number of steps in question by checking a rank condition on a Hankel matrix of the local observations. Furthermore, we prove that the minimal number of steps is related to other algebraic and graph theoretical notions that can be directly computed from the Laplacian matrix of the graph and from the underlying graph topology. © 2011 IEEE.

Detection of Construction Workers in Video Frames for Automatic Initialization of Vision Trackers

Vision based tracking can provide the spatial location of construction entities such as equipment, workers, and materials in large scale, congested construction sites. It tracks entities in video streams by inferring their locations based on the entities’ visual features and motion histories. To initiate the process, it is necessary to determine the pixel areas corresponding to the construction entities to be tracked in the following consecutive video frames. In order to fully automate the process, an automated way of initialization is needed. This paper presents the method for construction worker detection which can automatically recognize and localize construction workers in video frames. The method first finds the foreground areas of moving objects using a background subtraction method. Within these foreground areas, construction workers are recognized based on the histogram of oriented gradients (HOG) and histogram of the HSV colors. HOG’s have proved to work effectively for detection of people, and the histogram of HSV colors helps differentiate between pedestrians and construction workers wearing safety vests. Preliminary experiments show that the proposed method has the potential to automate the initialization process of vision based tracking.

Enhancement of Construction Equipment Detection in Video Frames by Combining with Tracking

Vision-based object detection has been introduced in construction for recognizing and locating construction entities in on-site camera views. It can provide spatial locations of a large number of entities, which is beneficial in large-scale, congested construction sites. However, even a few false detections prevent its practical applications. In resolving this issue, this paper presents a novel hybrid method for locating construction equipment that fuses the function of detection and tracking algorithms. This method detects construction equipment in the video view by taking advantage of entities' motion, shape, and color distribution. Background subtraction, Haar-like features, and eigen-images are used for motion, shape, and color information, respectively. A tracking algorithm steps in the process to make up for the false detections. False detections are identified by catching drastic changes in object size and appearance. The identified false detections are replaced with tracking results. Preliminary experiments show that the combination with tracking has the potential to enhance the detection performance.

Optimized selection of key frames for monocular videogrammetric surveying of civil infrastructure

Videogrammetry is an inexpensive and easy-to-use technology for spatial 3D scene recovery. When applied to large scale civil infrastructure scenes, only a small percentage of the collected video frames are required to achieve robust results. However, choosing the right frames requires careful consideration. Videotaping a built infrastructure scene results in large video files filled with blurry, noisy, or redundant frames. This is due to frame rate to camera speed ratios that are often higher than necessary; camera and lens imperfections and limitations that result in imaging noise; and occasional jerky motions of the camera that result in motion blur; all of which can significantly affect the performance of the videogrammetric pipeline. To tackle these issues, this paper proposes a novel method for automating the selection of an optimized number of informative, high quality frames. According to this method, as the first step, blurred frames are removed using the thresholds determined based on a minimum level of frame quality required to obtain robust results. Then, an optimum number of key frames are selected from the remaining frames using the selection criteria devised by the authors. Experimental results show that the proposed method outperforms existing methods in terms of improved 3D reconstruction results, while maintaining the optimum number of extracted frames needed to generate high quality 3D point clouds.© 2012 Elsevier Ltd. All rights reserved.

Construction Worker Detection in Video Frames for Initializing Vision Trackers

Monitoring the location of resources on large scale, congested, outdoor sites can be performed more efficiently with vision tracking, as this approach does not require any pre-tagging of resources. However, the greatest impediment to the use of vision tracking in this case is the lack of detection methods that are needed to automatically mark the resources of interest and initiate the tracking. This paper presents such a novel method for construction worker detection that localizes construction workers in video frames. The proposed method exploits motion, shape, and color cues to narrow down the detection regions to moving objects, people, and finally construction workers, respectively. The three cues are characterized by using background subtraction, the histogram of oriented gradients (HOG), and the HSV color histogram. The method has been tested on videos taken in various environments. The results demonstrate its suitability for automatic initialization of vision trackers.

Decentralised minimal-time dynamic consensus

This paper considers a group of agents that aim to reach an agreement on individually received time-varying signals by local communication. In contrast to static network averaging problem, the consensus considered in this paper is reached in a dynamic sense. A discrete-time dynamic average consensus protocol can be designed to allow all the agents tracking the average of their reference inputs asymptotically. We propose a minimal-time dynamic consensus algorithm, which only utilises a minimal number of local observations of a randomly picked node in a network to compute the final consensus signal. Our results illustrate that with memory and computational ability, the running time of distributed averaging algorithms can be indeed improved dramatically as suggested by Olshevsky and Tsitsiklis. © 2012 AACC American Automatic Control Council).

Frames, biases, and rational decision-making in the human brain.

Human choices are remarkably susceptible to the manner in which options are presented. This so-called "framing effect" represents a striking violation of standard economic accounts of human rationality, although its underlying neurobiology is not understood. We found that the framing effect was specifically associated with amygdala activity, suggesting a key role for an emotional system in mediating decision biases. Moreover, across individuals, orbital and medial prefrontal cortex activity predicted a reduced susceptibility to the framing effect. This finding highlights the importance of incorporating emotional processes within models of human choice and suggests how the brain may modulate the effect of these biasing influences to approximate rationality.