Marr-Hildreth Enhancement of NDE Images

Previous publications [1–5] have demonstrated the usefulness of digital image enhancement techniques for improving visual detection and resolution of features in NDE images. Many of the techniques are high-pass spatial domain convolution filters [6] which are used to enhance the appearance of edges by removing blur. Two of the major advantages of the more popular edge enhancement operators are their ease of implementation and their rapidity of execution [7]. This makes them very useful for rapid “screening” of images. Their major disadvantages are that they emphasize “noise” as well as edges, and some are directionally dependent operators which tend to suppress features that are not aligned in the “preferred” direction

Haptic Edge Detection Through Shear

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals

Towards a General Theory of Neural Computation Based on Prediction by Single Neurons

Although there has been tremendous progress in understanding the mechanics of the nervous system, there has not been a general theory of its computational function. Here I present a theory that relates the established biophysical properties of single generic neurons to principles of Bayesian probability theory, reinforcement learning and efficient coding. I suggest that this theory addresses the general computational problem facing the nervous system. Each neuron is proposed to mirror the function of the whole system in learning to predict aspects of the world related to future reward. According to the model, a typical neuron receives current information about the state of the world from a subset of its excitatory synaptic inputs, and prior information from its other inputs. Prior information would be contributed by synaptic inputs representing distinct regions of space, and by different types of non-synaptic, voltage-regulated channels representing distinct periods of the past. The neuron's membrane voltage is proposed to signal the difference between current and prior information (“prediction error” or “surprise”). A neuron would apply a Hebbian plasticity rule to select those excitatory inputs that are the most closely correlated with reward but are the least predictable, since unpredictable inputs provide the neuron with the most “new” information about future reward. To minimize the error in its predictions and to respond only when excitation is “new and surprising,” the neuron selects amongst its prior information sources through an anti-Hebbian rule. The unique inputs of a mature neuron would therefore result from learning about spatial and temporal patterns in its local environment, and by extension, the external world. Thus the theory describes how the structure of the mature nervous system could reflect the structure of the external world, and how the complexity and intelligence of the system might develop from a population of undifferentiated neurons, each implementing similar learning algorithms

A Role for Drosophila dFoxO and dFoxO 5′UTR Internal Ribosomal Entry Sites during Fasting

One way animals may cope with nutrient deprivation is to broadly repress translation by inhibiting 5′-cap initiation. However, under these conditions specific proteins remain essential to survival during fasting. Such peptides may be translated through initiation at 5′UTR Internal Ribosome Entry Sites (IRES). Here we show that the Drosophila melanogaster Forkhead box type O (dFoxO) transcription factor is required for adult survival during fasting, and that the 5′UTR of dfoxO has the ability to initiate IRES-mediated translation in cell culture. Previous work has shown that insulin negatively regulates dFoxO through AKT-mediated phosphorylation while dFoxO itself induces transcription of the insulin receptor dInR, which also harbors IRES. Here we report that IRES-mediated translation of both dFoxO and dInR is activated in fasted Drosophila S2 cells at a time when cap-dependent translation is reduced. IRES mediated translation of dFoxO and dInR may be essential to ensure function and sensitivity of the insulin signaling pathway during fasting

Early Vegetation Development on an Exposed Reservoir: Implications for Dam Removal

The 4-year drawdown of Horsetooth Reservoir, Colorado, for dam maintenance, provides a case study analog of vegetation response on sediment that might be exposed from removal of a tall dam. Early vegetation recovery on the exposed reservoir bottom was a combination of (1) vegetation colonization on bare, moist substrates typical of riparian zones and reservoir sediment of shallow dams and (2) a shift in moisture status from mesic to the xeric conditions associated with the pre-impoundment upland position of most of the drawdown zone. Plant communities changed rapidly during the first four years of exposure, but were still substantially different from the background upland plant community. Predictions from the recruitment box model about the locations of Populus deltoides subsp. monilifera (plains cottonwood) seedlings relative to the water surface were qualitatively confirmed with respect to optimum locations. However, the extreme vertical range of water surface elevations produced cottonwood seed regeneration well outside the predicted limits of drawdown rate and height above late summer stage. The establishment and survival of cottonwood at high elevations and the differences between the upland plant community and the community that had developed after four years of exposure suggest that vegetation recovery following tall dam removal will follow a trajectory very different from a simple reversal of the response to dam construction, involving not only long time scales of establishment and growth of upland vegetation, but also possibly decades of persistence of legacy vegetation established during the reservoir to upland transition

Gene silencing by RNA interference in the ectoparasitic mite, Psoroptes ovis

Abstract The presence of components of the RNA interference (RNAi) pathway in Psoroptes ovis, an ectoparasitic mite responsible for psoroptic mange, was investigated through interrogation of the P. ovis genome. Homologues of transcripts representing critical elements for achieving effective RNAi in the mite, Tetranychus urticae and the model organisms Caenorhabditis elegans and Drosophila melanogaster were identified and, following the development of a non-invasive immersion method of double stranded RNA delivery, gene silencing by RNAi was successfully demonstrated in P. ovis. Significant reductions in transcript levels were achieved for three target genes which encode the Group 2 allergen (Pso o 2), mu-class glutathione S-transferase (PoGST-mu1) and beta-tubulin (Poβtub). This is the first demonstration of RNAi in P. ovis and provides a mechanism for mining transcriptomic and genomic datasets for novel control targets against this economically important ectoparasite

Principles of sensorimotor learning.

The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities - whether it is snowboarding or ballroom dancing - but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved

A Novel Core Genome-Encoded Superantigen Contributes to Lethality of Community-Associated MRSA Necrotizing Pneumonia

Bacterial superantigens (SAg) stimulate T-cell hyper-activation resulting in immune modulation and severe systemic illnesses such as Staphylococcus aureus toxic shock syndrome. However, all known S. aureus SAgs are encoded by mobile genetic elements and are made by only a proportion of strains. Here, we report the discovery of a novel SAg staphylococcal enterotoxin-like toxin X (SElX) encoded in the core genome of 95% of phylogenetically diverse S. aureus strains from human and animal infections, including the epidemic community-associated methicillin-resistant S. aureus (CA-MRSA) USA300 clone. SElX has a unique predicted structure characterized by a truncated SAg B-domain, but exhibits the characteristic biological activities of a SAg including Vβ-specific T-cell mitogenicity, pyrogenicity and endotoxin enhancement. In addition, SElX is expressed by clinical isolates in vitro, and during human, bovine, and ovine infections, consistent with a broad role in S. aureus infections of multiple host species. Phylogenetic analysis suggests that the selx gene was acquired horizontally by a progenitor of the S. aureus species, followed by allelic diversification by point mutation and assortative recombination resulting in at least 17 different alleles among the major pathogenic clones. Of note, SElX variants made by human- or ruminant-specific S. aureus clones demonstrated overlapping but distinct Vβ activation profiles for human and bovine lymphocytes, indicating functional diversification of SElX in different host species. Importantly, SElX made by CA-MRSA USA300 contributed to lethality in a rabbit model of necrotizing pneumonia revealing a novel virulence determinant of CA-MRSA disease pathogenesis. Taken together, we report the discovery and characterization of a unique core genome-encoded superantigen, providing new insights into the evolution of pathogenic S. aureus and the molecular basis for severe infections caused by the CA-MRSA USA300 epidemic clone