Rodent Models of Conditioned Fear: Behavioral Measures of Fear and Memory

Pavlovian fear conditioning is a robust technique for examining behavioral and cellular components of fear learning and memory. In fear conditioning, the subject learns to associate a previously neutral stimulus with an inherently noxious co-stimulus. The learned association is reflected in the subjects' behavior upon subsequent re-exposure to the previously neutral stimulus or the training environment. Using fear conditioning, investigators can obtain a large amount of data that describe multiple aspects of learning and memory. In a single test, researchers can evaluate functional integrity in fear circuitry, which is both well characterized and highly conserved across species. Additionally, the availability of sensitive and reliable automated scoring software makes fear conditioning amenable to high-throughput experimentation in the rodent model; thus, this model of learning and memory is particularly useful for pharmacological and toxicological screening. Due to the conserved nature of fear circuitry across species, data from Pavlovian fear conditioning are highly translatable to human models. We describe equipment and techniques needed to perform and analyze conditioned fear data. We provide two examples of fear conditioning experiments, one in rats and one in mice, and the types of data that can be collected in a single experiment. © 2012 Springer Science+Business Media, LLC.

Towards discrimination of challenging conditions for UGVs with visual and infrared sensors

This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

Open access for scholarly books : policy and practice

Fierce debates have characterised 2013 as the implications of government mandates for open access have been debated and pathways for implementation worked out. There is no doubt that journals will move to a mix of gold and green and there will be an unsettled relationship between the two. But what of books? Is it conceivable that in those subjects, such as in the humanities and social sciences, where something longer than the journal article is still the preferred form of scholarly communications that these will stay closed? Will it be acceptable to have some publicly funded research made available only in closed book form (regardless of whether print or digital) while other subjects where articles are favoured go open access? Frances Pinter is in the middle of these debates, having founded Knowledge Unlatched (see www.knowledgeunlatched.org). KU is a global library consortium enabling open access books. Knowledge Unlatched is helping libraries to work together for a sustainable open future for specialist academic books. Its vision is a healthy market that includes free access for end users. In this session she will review all the different models that are being experimented with around the world. These include author-side payments, institutional subsidies, research funding body approaches etc. She will compare and contrast these models with those that are already in place for journal articles. She will also review the policy landscape and report on how open access scholarly books are faring to date Frances Pinter, Founder, Knowledge Unlatched, UK

Resection-intersection bundle adjustment revisited

Bundle adjustment is one of the essential components of the computer vision toolbox. This paper revisits the resection-intersection approach, which has previously been shown to have inferior convergence properties. Modifications are proposed that greatly improve the performance of this method, resulting in a fast and accurate approach. Firstly, a linear triangulation step is added to the intersection stage, yielding higher accuracy and improved convergence rate. Secondly, the effect of parameter updates is tracked in order to reduce wasteful computation; only variables coupled to significantly changing variables are updated. This leads to significant improvements in computation time, at the cost of a small, controllable increase in error. Loop closures are handled effectively without the need for additional network modelling. The proposed approach is shown experimentally to yield comparable accuracy to a full sparse bundle adjustment (20% error increase) while computation time scales much better with the number of variables. Experiments on a progressive reconstruction system show the proposed method to be more efficient by a factor of 65 to 177, and 4.5 times more accurate (increasing over time) than a localised sparse bundle adjustment approach.

Practical aspects of frequency-domain identification of dynamic models of marine structures from hydrodynamic data

The motion response of marine structures in waves can be studied using finite-dimensional linear-time-invariant approximating models. These models, obtained using system identification with data computed by hydrodynamic codes, find application in offshore training simulators, hardware-in-the-loop simulators for positioning control testing, and also in initial designs of wave-energy conversion devices. Different proposals have appeared in the literature to address the identification problem in both time and frequency domains, and recent work has highlighted the superiority of the frequency-domain methods. This paper summarises practical frequency-domain estimation algorithms that use constraints on model structure and parameters to refine the search of approximating parametric models. Practical issues associated with the identification are discussed, including the influence of radiation model accuracy in force-to-motion models, which are usually the ultimate modelling objective. The illustration examples in the paper are obtained using a freely available MATLAB toolbox developed by the authors, which implements the estimation algorithms described.

A framework for testing robust autonomy of UAS during design and certification

As the number of Uninhabited Airborne Systems (UAS) proliferates in civil applications, industry is increasingly putting pressure on regulation authorities to provide a path for certification and allow UAS integration into regulated airspace. The success of this integration depends on developments in improved UAS reliability and safety, regulations for certification, and technologies for operational performance and safety assessment. This paper focusses on the last topic and describes a framework for quantifying robust autonomy of UAS, which quantifies the system's ability to either continue operating in the presence of faults or safely shut down. Two figures of merit are used to evaluate vehicle performance relative to mission requirements and the consequences of autonomous decision making in motion control and guidance systems. These figures of merit are interpreted within a probabilistic framework, which extends previous work in the literature. The valuation of the figures of merit can be done using stochastic simulation scenarios during both vehicle development and certification stages with different degrees of integration of hardware-in-the-loop simulation technology. The objective of the proposed framework is to aid in decision making about the suitability of a vehicle with respect to safety and reliability relative to mission requirements.

On evaluation of robust autonomy for uninhabited vehicles and systems

This paper discusses a method to quantify robust autonomy of Uninhabited Vehicles and Systems (UVS) in aerospace, marine, or land applications. Based on mission-vehicle specific performance criteria, we define an system utility function that can be evaluated using simulation scenarios for an envelope of environmental conditions. The results of these evaluations are used to compute a figure of merit or measure for operational efectiveness (MOE). The procedure is then augmented to consider faults and the performance of mechanisms to handle these faulty operational modes. This leads to a measure of robust autonomy (MRA). The objective of the proposed figures of merit is to assist in decision making about vehicle performance and reliability at both vehicle development stage (using simulation models) and at certification stage (using hardware-in-the-loop testing). Performance indices based on dynamic and geometric tasks associated with vehicle manoeuvring problems are proposed, and an example of a two- dimensional y scenario is provided to illustrate the use of the proposed figures of merit.

Some solutions for a compressible isotropic elastic material

In this article we obtain closed-form solutions for the combined inflation and axial shear of an elastic tube in respect of the compressible Isotropic elastic material introduced by Levinson and Burgess. Several other boundary-value problems are also examined, including the bending of a rectangular block and straightening of a cylindrical sector, both coupled with stretching and shearing, and an axially varying twist deformation. Some of the solutions appear in closed form, others are expressible in terms of elliptic functions.

Shared autonomy for close-quarters navigation and control of a VTOL platform

This thesis presents an approach for a vertical infrastructure inspection using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structure such as light and power distribution poles is a difficult task. There are challenges involved with developing such an inspection system, such as flying in close proximity to a target while maintaining a fixed stand-off distance from it. The contributions of this thesis fall into three main areas. Firstly, an approach to vehicle dynamic modeling is evaluated in simulation and experiments. Secondly, EKF-based state estimators are demonstrated, as well as estimator-free approaches such as image based visual servoing (IBVS) validated with motion capture ground truth data. Thirdly, an integrated pole inspection system comprising a VTOL platform with human-in-the-loop control, (shared autonomy) is demonstrated. These contributions are comprehensively explained through a series of published papers.

Metal Skin and the cinema of noise

In traditional communication and information theory, noise is the demon Other, an unwelcome disruption in the passage of information. Noise is "anything that is added to the signal between its transmission and reception that is not intended by the source...anything that makes the intended signal harder to decode accurately". It is in Michel Serres' formulation, the "third man" in dialogue who is always assumed, and whom interlocutors continually struggle to exclude. Noise is simultaneously a condition and a by-product of the act of communication, it represents the ever present possibility of disruption, interruption, misunderstanding. In sonic or musical terms noise is cacophony, dissonance. For economists, noise is an arbitrary element, both a barrier to the pursuit of wealth and a basis for speculation. For Mick (Jeremy Sims) and his mate Kev (Ben Mendelsohn) in David Caesar's Idiot Box (1996), as for Hando (Russell Crowe) and his gang of skinheads in Geoffrey Wright's Romper Stomper (1992), or Dazey (Ben Mendelsohn) and Joe (Aden Young) in Wright's Metal Skin (1994) and all those like them starved of (useful) information and excluded from the circuit - the information poor - their only option, their only point of intervention in the loop, is to make noise, to disrupt, to discomfort, to become Serres' "third man", "the prosopopoeia of noise" (5).

A Boundary-Oriented Chinese Segmentation Method Using NGram Mutual Information

This paper describes our participation in the Chinese word segmentation task of CIPS-SIGHAN 2010. We implemented an n-gram mutual information (NGMI) based segmentation algorithm with the mixed-up features from unsupervised, supervised and dictionarybased segmentation methods. This algorithm is also combined with a simple strategy for out-of-vocabulary (OOV) word recognition. The evaluation for both open and closed training shows encouraging results of our system. The results for OOV word recognition in closed training evaluation were however found unsatisfactory.

Alteration of the C-terminal ligand specificity of the Erbin PDZ domain by allosteric mutational effects

Modulation of protein binding specificity is important for basic biology and for applied science. Here we explore how binding specificity is conveyed in PDZ (postsynaptic density protein-95/discs large/zonula occludens-1) domains, small interaction modules that recognize various proteins by binding to an extended C terminus. Our goal was to engineer variants of the Erbin PDZ domain with altered specificity for the most C-terminal position (position 0) where a Val is strongly preferred by the wild-type domain. We constructed a library of PDZ domains by randomizing residues in direct contact with position 0 and in a loop that is close to but does not contact position 0. We used phage display to select for PDZ variants that bind to 19 peptide ligands differing only at position 0. To verify that each obtained PDZ domain exhibited the correct binding specificity, we selected peptide ligands for each domain. Despite intensive efforts, we were only able to evolve Erbin PDZ domain variants with selectivity for the aliphatic C-terminal side chains Val, Ile and Leu. Interestingly, many PDZ domains with these three distinct specificities contained identical amino acids at positions that directly contact position 0 but differed in the loop that does not contact position 0. Computational modeling of the selected PDZ domains shows how slight conformational changes in the loop region propagate to the binding site and result in different binding specificities. Our results demonstrate that second-sphere residues could be crucial in determining protein binding specificity.

On robust face recognition via sparse coding: The good, the bad and the ugly

In the field of face recognition, sparse representation (SR) has received considerable attention during the past few years, with a focus on holistic descriptors in closed-set identification applications. The underlying assumption in such SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such an assumption is easily violated in the face verification scenario, where the task is to determine if two faces (where one or both have not been seen before) belong to the same person. In this study, the authors propose an alternative approach to SR-based face verification, where SR encoding is performed on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which then form an overall face descriptor. Owing to the deliberate loss of spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment and various image deformations. Within the proposed framework, they evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN) and an implicit probabilistic technique based on Gaussian mixture models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, on both the traditional closed-set identification task and the more applicable face verification task. The experiments also show that l1-minimisation-based encoding has a considerably higher computational cost when compared with SANN-based and probabilistic encoding, but leads to higher recognition rates.

Nanoindentation study of the mechanical behavior of TiO2 nanotube arrays

Titanium dioxide (TiO2) nanotube arrays are attracting increasing attention for use in solar cells, lithium-ion batteries, and biomedical implants. To take full advantage of their unique physical properties, such arrays need to maintain adequate mechanical integrity in applications. However, the mechanical performance of TiO2 nanotube arrays is not well understood. In this work, we investigate the deformation and failure of TiO2 nanotube arrays using the nanoindentation technique. We found that the load–displacement response of the arrays strongly depends on the indentation depth and indenter shape. Substrate-independent elastic modulus and hardness can be obtained when the indentation depth is less than 2.5% of the array height. The deformation mechanisms of TiO2 nanotube arrays by Berkovich and conical indenters are closely associated with the densification of TiO2 nanotubes under compression. A theoretical model for deformation of the arrays under a largeradius conical indenter is also proposed.

Critical reflection: Part of everyday practices

Critical reflection is central to improving practices in early years services. It is also a learned skill.