Real-Time Hand Shape Classification

The problem of hand shape classification is challenging since a hand is characterized by a large number of degrees of freedom. Numerous shape descriptors have been proposed and applied over the years to estimate and classify hand poses in reasonable time. In this paper we discuss our parallel framework for real-time hand shape classification applicable in real-time applications. We show how the number of gallery images influences the classification accuracy and execution time of the parallel algorithm. We present the speedup and efficiency analyses that prove the efficacy of the parallel implementation. Noteworthy, different methods can be used at each step of our parallel framework. Here, we combine the shape contexts with the appearance-based techniques to enhance the robustness of the algorithm and to increase the classification score. An extensive experimental study proves the superiority of the proposed approach over existing state-of-the-art methods.Comment: 11 page

A proteasome-resistant fragment of NIK mediates oncogenic NF-κB signaling in schwannomas

Schwannomas are common, highly morbid and medically untreatable tumors that can arise in patients with germ line as well as somatic mutations in neurofibromatosis type 2 (NF2). These mutations most commonly result in the loss of function of the NF2-encoded protein, Merlin. Little is known about how Merlin functions endogenously as a tumor suppressor and how its loss leads to oncogenic transformation in Schwann cells (SCs). Here, we identify nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB)-inducing kinase (NIK) as a potential drug target driving NF-κB signaling and Merlin-deficient schwannoma genesis. Using a genomic approach to profile aberrant tumor signaling pathways, we describe multiple upregulated NF-κB signaling elements in human and murine schwannomas, leading us to identify a caspase-cleaved, proteasome-resistant NIK kinase domain fragment that amplifies pathogenic NF-κB signaling. Lentiviral-mediated transduction of this NIK fragment into normal SCs promotes proliferation, survival, and adhesion while inducing schwannoma formation in a novel in vivo orthotopic transplant model. Furthermore, we describe an NF-κB-potentiated hepatocyte growth factor (HGF) to MET proto-oncogene receptor tyrosine kinase (c-Met) autocrine feed-forward loop promoting SC proliferation. These innovative studies identify a novel signaling axis underlying schwannoma formation, revealing new and potentially druggable schwannoma vulnerabilities with future therapeutic potential

Hydrogen bonding of nitroxide spin labels in membrane proteins

On the basis of experiments at 275 GHz, we reconsider the dependence of the continuous-wave EPR spectra of nitroxide spin-labeled protein sites in sensory- and bacteriorhodopsin on the micro-environment. The high magnetic field provides the resolution necessary to disentangle the effects of hydrogen bonding and polarity. In the gxx region of the 275 GHz EPR spectrum, bands are resolved that derive from spin-label populations carrying no, one or two hydrogen bonds. The gxx value of each population varies hardly from site to site, significantly less than deduced previously from studies at lower microwave frequencies. The fractions of the populations vary strongly, which provides a consistent description of the variation of the average gxx and the average nitrogen-hyperfine interaction Azz from site to site. These variations reflect the difference in the proticity of the micro-environment, and differences in polarity contribute marginally. Concomitant W-band ELDOR- detected NMR experiments on the corresponding nitroxide in perdeuterated water resolve population-specific nitrogen-hyperfine bands, which underlies the interpretation for the proteins

Seasonal Flight Activity and Distribution of Metallic Woodboring Beetles (Coleoptera: Buprestidae) Collected in North Carolina and Tennessee

Distribution records and seasonal flight activity information for metallic woodboring beetle (Coleoptera: Buprestidae) species have not been compiled for North Carolina and Tennessee. Institutional, research, and private collections in North Carolina and Tennessee were reviewed to provide seasonal activity data of 5 subfamilies of buprestid beetle species. Label information was checked for 15,217 specimens of 135 species collected between 1901 and 2013 (North Carolina) and between 1934 and 2013 (Tennessee). These collections provided data on adult seasonal activity and county records for 121 species (4,467 specimens) and 105 species (10,750 specimens) from North Carolina and Tennessee, respectively. Two species, Agrilus carpini Knull and A. pensus Horn, are reported as New State Records for North Carolina. The data reveal key geographic areas in both states where few to no collections have been made, highlighting opportunities to validate species distributions and locations where future collecting efforts can be matched with the occurrence of larval and adult host plant resources. Seasonal activity records will inform future biosurveillance efforts for invasive and endemic pests and facilitate predictions of buprestid species that are likely to be active within the hunting flight season of Cerceris fumipennis (Say) (Hymenoptera: Crabronidae) wasps. Activity periods of the buprestids also can focus the management of selected economic pest species to times of the year when treatment efforts, particularly through use of contact insecticides, are likely to be most effective

Map Supplements for The Metallic Woodboring Beetles (Coleoptera: Buprestidae) of Tennessee

Following compilation of distribution records and seasonal flight activity information for 106 metallic wood-boring beetle (Coleoptera: Buprestidae) species for Tennessee, maps were updated to provide county-level collection notations for 10,543 published records and specimen collections made from 1934 to 2013. County collection tallies across the ecoregions in Tennessee are also presented. Maps for individual species highlight gaps in key geographic areas where specimens have not been collected and can be valuable for future biosurveillance, monitoring and management efforts for these economically and ecologically important insects

Adaptations in a hierarchical food web of southeastern Lake Michigan

Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts fromone time point to a second time point in response to multiple perturbations. To construct our foodweb for southeastern Lake Michigan,we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993.Improving foodwebs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second onewas that a system’s properties change at a slower rate than its subsystems’ properties. We used Shannon’s equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density).We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account.We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure (p \u3c 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystemwithmore non-overlapping distributions in foodweb propertieswas the subsystemthat contained primarily benthic taxa, contrary to expectations that the identifiedmajor perturbations (lower phosphorous inputs and invasive species) would more greatly affect the subsystem containing primarily pelagic taxa. Future food-web research shouldemploy rigorous statistical analysis and incorporate uncertainty in food web properties for a better understanding of how ecological networks adapt

Virtual reality-based parallel coordinates plots enhanced with explainable ai and data-science analytics for decision-making processes

We present a refinement of the Immersive Parallel Coordinates Plots (IPCP) system for Virtual Reality (VR). The evolved system provides data-science analytics built around a well-known method for visualization of multidimensional datasets in VR. The data-science analytics enhancements consist of importance analysis and a number of clustering algorithms including a novel SuMC (Subspace Memory Clustering) solution. These analytical methods were applied to both the main visualizations and supporting cross-dimensional scatter plots. They automate part of the analytical work that in the previous version of IPCP had to be done by an expert. We test the refined system with two sample datasets that represent the optimum solutions of two different multi-objective optimization studies in turbomachinery. The first one describes 54 data items with 29 dimensions (DS1), and the second 166 data items with 39 dimensions (DS2). We include the details of these methods as well as the reasoning behind selecting some methods over others.</jats:p

Structure-guided design and optimization of small molecules targeting the protein-protein interaction between the von hippel-lindau (VHL) E3 ubiquitin ligase and the hypoxia inducible factor (HIF) alpha subunit with in vitro nanomolar affinities

E3 ubiquitin ligases are attractive targets in the ubiquitin-proteasome system, however, the development of small-molecule ligands has been rewarded with limited success. The von Hippel-Lindau protein (pVHL) is the substrate recognition subunit of the VHL E3 ligase that targets HIF-1α for degradation. We recently reported inhibitors of the pVHL:HIF-1α interaction, however they exhibited moderate potency. Herein, we report the design and optimization, guided by X-ray crystal structures, of a ligand series with nanomolar binding affinities

Explainable Predictive Maintenance

Explainable Artificial Intelligence (XAI) fills the role of a critical interface fostering interactions between sophisticated intelligent systems and diverse individuals, including data scientists, domain experts, end-users, and more. It aids in deciphering the intricate internal mechanisms of ``black box'' Machine Learning (ML), rendering the reasons behind their decisions more understandable. However, current research in XAI primarily focuses on two aspects; ways to facilitate user trust, or to debug and refine the ML model. The majority of it falls short of recognising the diverse types of explanations needed in broader contexts, as different users and varied application areas necessitate solutions tailored to their specific needs. One such domain is Predictive Maintenance (PdM), an exploding area of research under the Industry 4.0 \& 5.0 umbrella. This position paper highlights the gap between existing XAI methodologies and the specific requirements for explanations within industrial applications, particularly the Predictive Maintenance field. Despite explainability's crucial role, this subject remains a relatively under-explored area, making this paper a pioneering attempt to bring relevant challenges to the research community's attention. We provide an overview of predictive maintenance tasks and accentuate the need and varying purposes for corresponding explanations. We then list and describe XAI techniques commonly employed in the literature, discussing their suitability for PdM tasks. Finally, to make the ideas and claims more concrete, we demonstrate XAI applied in four specific industrial use cases: commercial vehicles, metro trains, steel plants, and wind farms, spotlighting areas requiring further research.Comment: 51 pages, 9 figure

A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy

A real-world newspaper distribution problem with recycling policy is tackled in this work. In order to meet all the complex restrictions contained in such a problem, it has been modeled as a rich vehicle routing problem, which can be more specifically considered as an asymmetric and clustered vehicle routing problem with simultaneous pickup and deliveries, variable costs and forbidden paths (AC-VRP-SPDVCFP). This is the first study of such a problem in the literature. For this reason, a benchmark composed by 15 instances has been also proposed. In the design of this benchmark, real geographical positions have been used, located in the province of Bizkaia, Spain. For the proper treatment of this AC-VRP-SPDVCFP, a discrete firefly algorithm (DFA) has been developed. This application is the first application of the firefly algorithm to any rich vehicle routing problem. To prove that the proposed DFA is a promising technique, its performance has been compared with two other well-known techniques: an evolutionary algorithm and an evolutionary simulated annealing. Our results have shown that the DFA has outperformed these two classic meta-heuristics