Automated zebrafish chorion removal and single embryo placement: optimizing throughput of zebrafish developmental toxicity screens

The potential of the developing zebrafish model for toxicology and drug discovery is limited by inefficient approaches to manipulating and chemically exposing zebrafish embryos-namely, manual placement of embryos into 96- or 384-well plates and exposure of embryos while still in the chorion, a barrier of poorly characterized permeability enclosing the developing embryo. We report the automated dechorionation of 1600 embryos at once at 4 h postfertilization (hpf) and placement of the dechorionated embryos into 96-well plates for exposure by 6 hpf. The process removed ≥95% of the embryos from their chorions with 2% embryo mortality by 24 hpf, and 2% of the embryos malformed at 120 hpf. The robotic embryo placement allocated 6-hpf embryos to 94.7% ± 4.2% of the wells in multiple 96-well trials. The rate of embryo mortality was 2.8% (43 of 1536) from robotic handling, the rate of missed wells was 1.2% (18 of 1536), and the frequency of multipicks was <0.1%. Embryo malformations observed at 24 hpf occurred nearly twice as frequently from robotic handling (16 of 864; 1.9%) as from manual pipetting (9 of 864; 1%). There was no statistical difference between the success of performing the embryo placement robotically or manually.     

Assessing Optimal Digital Elevation Model Selection for Active River Area Delineation Across Broad Regions

Water Resources Management - The Active River Area (ARA) is a spatial approach for identifying the extent of functional riparian area. Given known limitations in terms of input elevation data...     

A quantitative comparison of the effects of modeling approaches on system verification using a controlled challenge problem

Requirements Engineering - To reduce program risks, engineering methods capitalizing on modeling and machine assistance have been extensively investigated within systems engineering (and more...     

A new model of job design: Initial evidence and implications for future research

Clegg and Spencer's (2007) model of job design synthesizes and extends recent conceptions of the job design process by incorporating variables such as knowledge, motivation, and trust into a cyclical and dynamic system. The objective of this study was to examine the sequential organization of variables that comprise the model, as a basis from which to justify further investigations of the model's dynamic properties. Data were collected via questionnaires from 432 participants in two work organizations. Results obtained from structural equation modeling are broadly supportive of the proposed relationships between the variables. Implications of this initial study for future research and practice are discussed. © 2011 Wiley Periodicals, Inc.     

Nodal ant colony optimization for solving profit based unit commitment problem for GENCOs

This paper proposes a nodal ant colony optimization (NACO) technique to solve profit based unit commitment problem (PBUCP). Generation companies (GENCOs) in a competitive restructured power market, schedule their generators with an objective to maximize their own profit without any regard for system social benefit. Power and reserve prices become important factors in decision process. Ant colony optimization that mimics the behavior of ants foraging activities is suitably implemented to search the UCP search space. Here a search space consisting of optimal combination of binary nodes for unit ON/OFF status is represented for the movement of the ants to maintain good exploration and exploitation search capabilities. The proposed model help GENCOs to make decisions on the quantity of power and reserve that must be put up for sale in the markets and also to schedule generators in order to receive the maximum profit. The effectiveness of the proposed technique for PBUCP is validated on 10 and 36 generating unit systems available in the literature. NACO yields an increase of profit, greater than 1.5%, in comparison with the basic ACO, Muller method and hybrid LR-GA.     

Fourth International Conference on Durability of Building Materials and Components

RILEM Bulletin

Fourth International Conference on Durability of Building Materials and Components     

RelativizedNC

This paper introduces a notion of relativized depth for circuit families and discusses issues regarding uniform families of relativized circuits. This allows us to define a version of relativizedNC and compare it under various oracles with relativizedL, NL, andP. We see thatNC ₁ is properly contained inL if and only if there exists an oracleA such thatNC ₁ ^A is properly contained inL ^A . There is an oracleA where the hierarchy collapses,NC ₁ ^A = NC ^A , and another whereNC ₁ ^A NC ₂ ^A NC ^A P ^A . We then construct anA so that, for anyk, NC ₁ ^A contains a set not inNSPACE ^A (O(n ^k )), suggesting that the notion of relativized space is too weak or that of relativized depth is too strong.     

The Shape Boltzmann Machine: A Strong Model of Object Shape

A good model of object shape is essential in applications such as segmentation, detection, inpainting and graphics. For example, when performing segmentation, local constraints on the shapes can help where object boundaries are noisy or unclear, and global constraints can resolve ambiguities where background clutter looks similar to parts of the objects. In general, the stronger the model of shape, the more performance is improved. In this paper, we use a type of deep Boltzmann machine (Salakhutdinov and Hinton, International Conference on Artificial Intelligence and Statistics, 2009) that we call a Shape Boltzmann Machine (SBM) for the task of modeling foreground/background (binary) and parts-based (categorical) shape images. We show that the SBM characterizes a strong model of shape, in that samples from the model look realistic and it can generalize to generate samples that differ from training examples. We find that the SBM learns distributions that are qualitatively and quantitatively better than existing models for this task.