Hidden-Markov Program Algebra with iteration

We use Hidden Markov Models to motivate a quantitative compositional semantics for noninterference-based security with iteration, including a refinement- or "implements" relation that compares two programs with respect to their information leakage; and we propose a program algebra for source-level reasoning about such programs, in particular as a means of establishing that an "implementation" program leaks no more than its "specification" program. This joins two themes: we extend our earlier work, having iteration but only qualitative, by making it quantitative; and we extend our earlier quantitative work by including iteration. We advocate stepwise refinement and source-level program algebra, both as conceptual reasoning tools and as targets for automated assistance. A selection of algebraic laws is given to support this view in the case of quantitative noninterference; and it is demonstrated on a simple iterated password-guessing attack

Extraction and Classification of Diving Clips from Continuous Video Footage

Due to recent advances in technology, the recording and analysis of video data has become an increasingly common component of athlete training programmes. Today it is incredibly easy and affordable to set up a fixed camera and record athletes in a wide range of sports, such as diving, gymnastics, golf, tennis, etc. However, the manual analysis of the obtained footage is a time-consuming task which involves isolating actions of interest and categorizing them using domain-specific knowledge. In order to automate this kind of task, three challenging sub-problems are often encountered: 1) temporally cropping events/actions of interest from continuous video; 2) tracking the object of interest; and 3) classifying the events/actions of interest. Most previous work has focused on solving just one of the above sub-problems in isolation. In contrast, this paper provides a complete solution to the overall action monitoring task in the context of a challenging real-world exemplar. Specifically, we address the problem of diving classification. This is a challenging problem since the person (diver) of interest typically occupies fewer than 1% of the pixels in each frame. The model is required to learn the temporal boundaries of a dive, even though other divers and bystanders may be in view. Finally, the model must be sensitive to subtle changes in body pose over a large number of frames to determine the classification code. We provide effective solutions to each of the sub-problems which combine to provide a highly functional solution to the task as a whole. The techniques proposed can be easily generalized to video footage recorded from other sports.Comment: To appear at CVsports 201

Association of p60c-src with endosomal membranes in mammalian fibroblasts.

We have examined the subcellular localization of p60c-src in mammalian fibroblasts. Analysis of indirect immunofluorescence by three-dimensional optical sectioning microscopy revealed a granular cytoplasmic staining that co-localized with the microtubule organizing center. Immunofluorescence experiments with antibodies against a number of membrane markers demonstrated a striking co-localization between p60c-src and the cation-dependent mannose-6-phosphate receptor (CI-MPR), a marker that identifies endosomes. Both p60c-src and the CI-MPR were found to cluster at the spindle poles throughout mitosis. In addition, treatment of interphase and mitotic cells with brefeldin A resulted in a clustering of p60c-src and CI-MPR at a peri-centriolar position. Biochemical fractionation of cellular membranes showed that a major proportion of p60c-src co-enriched with endocytic membranes. Treatment of membranes containing HRP to alter their apparent density also altered the density of p60c-src-containing membranes. Similar density shift experiments with total cellular membranes revealed that the majority of membrane-associated p60c-src in the cell is associated with endosomes, while very little is associated with plasma membranes. These results support a role for p60c-src in the regulation of endosomal membranes and protein trafficking

High-Spatial Resolution Laser Doppler Blood Flow Imaging

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.A full-field laser Doppler blood flow imaging (LDI) system based on an FPGA (Field Programmable Gate Array) coupled with a high-speed CMOS (Complementary Metal-Oxide-Semiconductor) camera chip has been developed which provides blood flow images with flexible frame rates and spatial resolution. When a high spatial resolution is required, 1280x1024-pixel blood flow images were obtained by processing up to 2048 samples at 0.2 frames per second (fps). Alternatively, a maximum of 15.5fps was achieved by reducing the spatial resolution and sampling points to 256x256 pixels and 128 samples respectively. This system was applied to a high-spatial resolution flow imaging application in which a mixture of water and polystyrene microspheres was pumped through a micropipette (diameter = 250m) with controlled velocities, and the resulting flow was imaged and processed. The performance was demonstrated by the resulting flow images which are of size 1280×1024 pixels and obtained by processing 2048 samples at each pixel

Multi-exposure laser speckle contrast imaging using a high frame rate CMOS sensor with a field programmable gate array

A system has been developed in which multi-exposure Laser Speckle Contrast Imaging (LSCI) is implemented using a high frame rate CMOS imaging sensor chip. Processing is performed using a Field Programmable Gate Array (FPGA). The system allows different exposure times to be simulated by accumulating a number of short exposures. This has the advantage that the image acquisition time is limited by the maximum exposure time and that regulation of the illuminating light level is not required. This high frame rate camera has also been deployed to implement laser Doppler blood flow processing enabling direct comparison of multi-exposure laser speckle contrast imaging and Laser Doppler Imaging (LDI) to be carried out using the same experimental data. Results from a rotating diffuser indicate that both multi-exposure LSCI and LDI provide a linear response to changes in velocity. This cannot be obtained using single-exposure LSCI unless an appropriate model is used for correcting the response

A face recognition system for assistive robots

Assistive robots collaborating with people demand strong Human-Robot interaction capabilities. In this way, recognizing the person the robot has to interact with is paramount to provide a personalized service and reach a satisfactory end-user experience. To this end, face recognition: a non-intrusive, automatic mechanism of identification using biometric identifiers from an user's face, has gained relevance in the recent years, as the advances in machine learning and the creation of huge public datasets have considerably improved the state-of-the-art performance. In this work we study different open-source implementations of the typical components of state-of-the-art face recognition pipelines, including face detection, feature extraction and classification, and propose a recognition system integrating the most suitable methods for their utilization in assistant robots. Concretely, for face detection we have considered MTCNN, OpenCV's DNN, and OpenPose, while for feature extraction we have analyzed InsightFace and Facenet. We have made public an implementation of the proposed recognition framework, ready to be used by any robot running the Robot Operating System (ROS). The methods in the spotlight have been compared in terms of accuracy and performance in common benchmark datasets, namely FDDB and LFW, to aid the choice of the final system implementation, which has been tested in a real robotic platform.This work is supported by the Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech, the research projects WISER ([DPI2017-84827-R]),funded by the Spanish Government, and financed by European RegionalDevelopment’s funds (FEDER), and MoveCare ([ICT-26-2016b-GA-732158]), funded by the European H2020 program, and by a postdoc contract from the I-PPIT-UMA program financed by the University of Málaga

Low Dose of Propranolol Does Not Affect Rat Osteotomy Healing and Callus Strength

Experimental studies suggest that the β‐blocker propranolol stimulates bone formation but little work has investigated its effect on fracture healing. In this study, we examined if a low dose of propranolol, previously shown to be preventive against bone loss in rats, improves bone repair. Female Wistar rats were injected with saline or propranolol (0.1 mg/kg/day) (n = 20/group), 5 days a week for 8 weeks. Three weeks after the beginning of treatment, all rats underwent a mid‐diaphyseal transverse osteotomy in the left femur. Radiographic analysis of ostetomy healing was performed 2 and 5 weeks after osteotomy. Rats were sacrificed at 5 weeks and femora collected for measurements of fracture strength by torsional testing, callus volume, and mineral content by micro‐CT analysis and histology of fracture callus. Eighty nine percent of osteotomies achieved apparent radiological union by 5 weeks in both groups. Propranolol treatment did not significantly alter the torsional strength of the fractured femur compared with controls. The volume and mineralization of fracture callus at 5 weeks were not significantly different in both groups. Histology showed that endochondral ossification was not affected by propranolol. Altogether, our results demonstrate that propranolol using the regimen described does not significantly improve or inhibit rat osteotomy healing and mechanical strength

Selective hydrogenation of levulinic acid using Ru/C catalysts prepared by sol-immobilsation

A 1% Ru/C catalyst prepared by the sol immobilization method showed a high yield of γ-valerolactone from levulinic acid. We performed an optimization of the catalyst by varying the preparation variables involved in the sol immobilization method and detremined that the ratio of PVA, NaBH4 to Ru and heat treatment conditions play a crucial role in the synthesis of active and selective catalysts. By varying these parameters we have identified the optimum conditions for catalyst preparation by providing well dispersed nanoparticles of RuOx on the carbon support that are reducible under low reaction temperature and in turn gave an enhanced catalytic activity. In contrast to a catalyst prepared without using a PVA stabiliser, the use of a small amount PVA (PVA/Ru = 0.1) provided active nanoparticles, by controlling the steric size of the Ru nanoparticles. An optimum amount of NaBH4 was required in order to provide the reducible Ru species on the surface of catalyst and further increase in NaBH4 was found to cause a decline in activity that was related to the kinetics of nanoparticle formation during catalyst preparation. A variation of heat treatment temperature showed a corresponding decrease in catalytic activity linked with the sintering and an increase in particle size