Topology estimation for thousand-camera surveillance networks

Copyright © 2007 IEEESurveillance camera technologies have reached the point whereby networks of a thousand cameras are not uncommon. Systems for collecting and storing the video generated by such networks have been deployed operationally, and sophisticated methods have been developed for interrogating individual video streams. The principal contribution of this paper is a scalable method for processing video streams collectively, rather than on a per camera basis, which enables a coordinated approach to large-scale video surveillance. To realise our ambition of thousand camera automated surveillance networks, we use distributed processing on a dedicated cluster. Our focus is on determining activity topology - the paths objects may take between cameras' fields of view. An accurate estimate of activity topology is critical to many surveillance functions, including tracking targets through the network, and may also provide a means for partitioning of distributed surveillance processing. We present several implementations using the exclusion algorithm to determine activity topology. Measurements reported for the key system component demonstrate scalability to networks with a thousand cameras. Whole-system measurements are reported for actual operation on over a hundred camera streams (this limit is based on the number of cameras and computers presently available to us, not scalability). Finally, we explore how to scale our approach to support multi-thousand camera networks. ©2007 IEEE

Expanding the phenotype in argininosuccinic aciduria: need for new therapies

OBJECTIVES: This UK-wide study defines the natural history of argininosuccinic aciduria and compares long-term neurological outcomes in patients presenting clinically or treated prospectively from birth with ammonia-lowering drugs. METHODS: Retrospective analysis of medical records prior to March 2013, then prospective analysis until December 2015. Blinded review of brain MRIs. ASL genotyping. RESULTS: Fifty-six patients were defined as early-onset (n = 23) if symptomatic < 28 days of age, late-onset (n = 23) if symptomatic later, or selectively screened perinatally due to a familial proband (n = 10). The median follow-up was 12.4 years (range 0-53). Long-term outcomes in all groups showed a similar neurological phenotype including developmental delay (48/52), epilepsy (24/52), ataxia (9/52), myopathy-like symptoms (6/52) and abnormal neuroimaging (12/21). Neuroimaging findings included parenchymal infarcts (4/21), focal white matter hyperintensity (4/21), cortical or cerebral atrophy (4/21), nodular heterotopia (2/21) and reduced creatine levels in white matter (4/4). 4/21 adult patients went to mainstream school without the need of additional educational support and 1/21 lives independently. Early-onset patients had more severe involvement of visceral organs including liver, kidney and gut. All early-onset and half of late-onset patients presented with hyperammonaemia. Screened patients had normal ammonia at birth and received treatment preventing severe hyperammonaemia. ASL was sequenced (n = 19) and 20 mutations were found. Plasma argininosuccinate was higher in early-onset compared to late-onset patients. CONCLUSIONS: Our study further defines the natural history of argininosuccinic aciduria and genotype-phenotype correlations. The neurological phenotype does not correlate with the severity of hyperammonaemia and plasma argininosuccinic acid levels. The disturbance in nitric oxide synthesis may be a contributor to the neurological disease. Clinical trials providing nitric oxide to the brain merit consideration

Measuring patient compliance with remote monitoring following discharge from hospital after major surgery (DREAMPath): protocol for a prospective observational study

Background: The incidence of major surgery is on the rise globally, and more than 20% of patients are readmitted to hospital following discharge from hospital. During their hospital stay, patients are monitored for early detection of clinical deterioration, which includes regularly measuring physiological parameters such as blood pressure, heart rate, respiratory rate, temperature, and pulse oximetry. This monitoring ceases upon hospital discharge, as patients are deemed clinically stable. Monitoring after discharge is relevant to detect adverse events occurring in the home setting and can be made possible through the development of digital technologies and mobile networks. Smartwatches and other technological devices allow patients to self-measure physiological parameters in the home setting, and Bluetooth connectivity can facilitate the automatic collection and transfer of this data to a secure server with minimal input from the patient. Objective: This paper presents the protocol for the DREAMPath (Domiciliary Recovery After Medicalization Pathway) study, which aims to measure compliance with a multidevice remote monitoring kit after discharge from hospital following major surgery. Methods: DREAMPath is a single-center, prospective, observational, cohort study, comprising 30 patients undergoing major intracavity surgery. The primary outcome is to assess patient compliance with wearable and interactive smart technology in the first 30 days following discharge from hospital after major surgery. Secondary outcomes will explore the relation between unplanned health care events and physiological data collected in the study, as well as to explore a similar relationship with daily patient-reported outcome measures (Quality of Recovery–15 score). Secondary outcomes will be analyzed using appropriate regression methods. Cardiopulmonary exercise testing data will also be collected to assess correlations with wearable device data. Results: Recruitment was halted due to COVID-19 restrictions and will progress once research staff are back from redeployment. We expect that the study will be completed in the first quarter of 2022. Conclusions: Digital health solutions have been recently made possible due to technological advances, but urgency in rollout has been expedited due to COVID-19. The DREAMPath study will inform readers about the feasibility of remote monitoring for a patient group that is at an increased risk of acute deterioration. Trial Registration: ISRCTN Registry ISRCTN62293620; https://www.isrctn.com/ISRCTN62293620 International Registered Report Identifier (IRRID): DERR1-10.2196/3063

Extreme ecchymoses in a migraine patient using concomitant treatment with calcitonin gene-related peptide receptor antibodies and fish oil supplements:a case report

BACKGROUND: Erenumab, a monoclonal antibody against the calcitonin gene-related peptide (CGRP) receptor, is registered for migraine prevention. Compared to other conventional migraine prevention medicines (i.e. topiramate, betablockers and amitriptyline) erenumab has better tolerability. Impaired hemostasis has not been reported previously. Here, we report the first case of an increased tendency to bruise in a migraine patient treated with erenumab. CASE PRESENTATION: A 41-year old female migraine patient was treated with erenumab for 12 months, which led to a significant reduction of headache and migraine days. Three months after treatment start, she experienced increased tendency to bruise leading to extreme ecchymosis after 4 months treatment. Platelet counts and aggregation, thromboelastography, activated partial thromboplastin time (APTT) and international normalized ratio (INR) were all normal. Thorough interview revealed intake of fish oil supplements for many years prior to treatment. The increased tendency to bruise subsided after discontinuation of fish oil supplements. CONCLUSION: The combination of fish oil supplements and erenumab may cause increased tendency to bruise. Erenumab has no effect on the platelets per se but may cause impaired wound healing by suppression of CGRP. Thus, small and unnoticeable bruises may be aggravated instead in patients with tendency to bruise caused by for instance fish oil supplements

Kermes oak (Quercus coccifera L.) extract for a biogenic and eco-benign synthesis of silver nanopArticles with efficient biological activities

Green chemistry applications in nanopArticle synthesis using plant extracts is an ecofriendly approach in material science. Metallic nanopArticles with potent bioactivities have been synthesized using plant extracts. Here, we describe an environmental-friendly approach for synthesizing silver nanopArticles (AgNPs) using the aqueous leaf extract of kermes oak (Quercus coccifera L.). The extract was first analyzed for its content, after which it was utilized for the AgNPs synthesis. The synthesis optimization was performed via the adjustment of different parameters such as the concentrations of components and reaction time using UV-visible spectroscopy. The NPs characterization was performed using DLS, SEM, FTIR, XRF, and SEM-EDS techniques. The antibacterial, antioxidant, and antidiabetic effects of AgNPs were tested. Results demonstrated the rich content of the extract in terms of phenolic and flavonoid compounds. AgNPs were spherical-shaped with a size ranging between 50-70 nm. They demonstrated distinct antioxidant (EC50=32.91 mu g/mL) and deglycation (IC50=41.62 mu g/mL) activities as well as a potent antimicrobial activity against various pathogens (Escherichia coli, Staphylococcus aureus, Enterococcus faecium, Staphylococcus epidermidis, Salmonella enteritidis, Salmonella typhimurium, Listeria monocytogenes, Candida albicans). The current findings highlight the potential of Quercus coccifera L. as a biological material for various biomedical applications. (C) 2021 The Authors. Published by Elsevier B.V

Estimating camera overlap in large and growing networks

Large-scale intelligent video surveillance requires an accurate estimate of the relationships between the fields of view of the cameras in the network. The exclusion approach is the only method currently capable of performing online estimation of camera overlap for networks of more than 100 cameras, and implementations have demonstrated the capability to support networks of 1000 cameras. However, these implementations include a centralised processing component, with the practical result that the resources (in particular, memory) of the central processor limit the size of the network that can be supported. In this paper, we describe a new, partitioned, implementation of exclusion, suitable for deployment to a cluster of commodity servers. Results for this implementation demonstrate support for significantly larger camera networks than was previously feasible. Furthermore, the nature of the partitioning scheme enables incremental extension of system capacity through the addition of more servers, without interrupting the existing system. Finally, formulae for requirements of system memory and bandwidth resources, verified by experimental results, are derived to assist engineers seeking to implement the technique.Henry Detmold, Anton van den Hengel, Anthony Dick, Alex Cichowski, Rhys Hill, Ekim Kocadag, Yuval Yarom, Katrina Falkner and David S. Munr