2,099 research outputs found

    Integrated membrane systems for toxic cyanobacteria removal

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    Blue-green algae (cyanobacteria) provide a major problem for the water industry as they can produce metabolites toxic to humans in addition to taste and odour (T&O) compounds that make drinking water aesthetically displeasing. This problem is likely to be intensified by the effects of climate change through reservoir warming. Microfiltration (MF) provides a potential solution for dealing with blooms of toxic blue green algae. In the past, coagulation and sand filtration have been successfully used for removal of cyanobacteria, however as membrane technology has become more economically viable, the demand for information on the application of membranes for cyanobacterial metabolite removal has increased. MF pore size is a key matter as cyanobacterial metabolites should permeate such membranes. However, if cyanobacterial metabolites remain within the algal cells MF might be effective through the removal of these intact cells. This study investigated an integrated membrane system incorporating coagulation, powdered activated carbon and MF for the removal of intracellular and extracellular cyanobacterial metabolites. A laboratory scale MF unit was designed and studied. It utilised PVDF fibres with a nominal 0.02 micron pore size. Three species of blue-green algae were tested and three different coagulants were used on each species for removal of intact cells. Powdered activated carbon (PAC) was dosed prior to the MF at 20mg/L to remove extracellular metabolites. Cell counts as well as analysis for total and extracellular toxin and T&O were undertaken to assess each stage of the IMS. The results of this study are promising.Mike Dixon, Brian O'Neill, Yann Richard, Lionel Ho, Chris Chow and Gayle Newcombehttp://www.chemeca2010.com/abstract/460.as

    Proving Determinacy of the PharOS Real-Time Operating System

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    International audienceExecutions in the PharOS real-time system are deterministic in the sense that the sequence of local states for every process is independent of the order in which processes are scheduled. The essential ingredient for achieving this property is that a temporal window of execution is associated with every instruction. Messages become visible to receiving processes only after the time window of the sending message has elapsed. We present a high-level model of PharOS in TLA+ and formally state and prove determinacy using the TLA+ Proof System

    FroDO: From Detections to 3D Objects

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    Object-oriented maps are important for scene understanding since they jointly capture geometry and semantics, allow individual instantiation and meaningful reasoning about objects. We introduce FroDO, a method for accurate 3D reconstruction of object instances from RGB video that infers their location, pose and shape in a coarse to fine manner. Key to FroDO is to embed object shapes in a novel learnt shape space that allows seamless switching between sparse point cloud and dense DeepSDF decoding. Given an input sequence of localized RGB frames, FroDO first aggregates 2D detections to instantiate a 3D bounding box per object. A shape code is regressed using an encoder network before optimizing shape and pose further under the learnt shape priors using sparse or dense shape representations. The optimization uses multi-view geometric, photometric and silhouette losses. We evaluate on real-world datasets, including Pix3D, Redwood-OS, and ScanNet, for single-view, multi-view, and multi-object reconstruction

    Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

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    Objective: Conventional magnetic resonance imaging (MRI) of the multiple sclerosis spinal cord is limited by low specificity regarding the underlying pathological processes, and new MRI metrics assessing microscopic damage are required. We aim to show for the first time that neurite orientation dispersion (i.e., variability in axon/dendrite orientations) is a new biomarker that uncovers previously undetected layers of complexity of multiple sclerosis spinal cord pathology. Also, we validate against histology a clinically viable MRI technique for dispersion measurement (neurite orientation dispersion and density imaging,NODDI), to demonstrate the strong potential of the new marker. Methods: We related quantitative metrics from histology and MRI in four post mortem spinal cord specimens (two controls; two progressive multiple sclerosis cases). The samples were scanned at high field, obtaining maps of neurite density and orientation dispersion from NODDI and routine diffusion tensor imaging (DTI) indices. Histological procedures provided markers of astrocyte, microglia, myelin and neurofilament density, as well as neurite dispersion. Results: We report from both NODDI and histology a trend toward lower neurite dispersion in demyelinated lesions, indicative of reduced neurite architecture complexity. Also, we provide unequivocal evidence that NODDI-derived dispersion matches its histological counterpart (P < 0.001), while DTI metrics are less specific and influenced by several biophysical substrates. Interpretation: Neurite orientation dispersion detects a previously undescribed and potentially relevant layer of microstructural complexity of multiple sclerosis spinal cord pathology. Clinically feasible techniques such as NODDI may play a key role in clinical trial and practice settings, as they provide histologically meaningful dispersion indices

    Self-repair ability of evolved self-assembling systems in cellular automata

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    Self-repairing systems are those that are able to reconfigure themselves following disruptions to bring them back into a defined normal state. In this paper we explore the self-repair ability of some cellular automata-like systems, which differ from classical cellular automata by the introduction of a local diffusion process inspired by chemical signalling processes in biological development. The update rules in these systems are evolved using genetic programming to self-assemble towards a target pattern. In particular, we demonstrate that once the update rules have been evolved for self-assembly, many of those update rules also provide a self-repair ability without any additional evolutionary process aimed specifically at self-repair

    JAB1 deletion in oligodendrocytes causes senescence-induced inflammation and neurodegeneration in mice

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    Oligodendrocytes are the primary target of demyelinating disorders, and progressive neurodegenerative changes may evolve in the CNS. DNA damage and oxidative stress are considered key pathogenic events, but the underlying molecular mechanisms remain unclear. Moreover, animal models do not fully recapitulate human diseases, complicating the path to effective treatments. Here we report that mice with cell-autonomous deletion of the nuclear COP9 signalosome component CSN5 (JAB1) in oligodendrocytes develop DNA damage and defective DNA repair in myelinating glial cells. Interestingly, oligodendrocytes lacking JAB1 expression underwent a senescence-like phenotype that fostered chronic inflammation and oxidative stress. These mutants developed progressive CNS demyelination, microglia inflammation, and neurodegeneration, with severe motor deficits and premature death. Notably, blocking microglia inflammation did not prevent neurodegeneration, whereas the deletion of p21CIP1 but not p16INK4a pathway ameliorated the disease. We suggest that senescence is key to sustaining neurodegeneration in demyelinating disorders and may be considered a potential therapeutic target

    An empirical approach towards the efficient and optimal production of influenza-neutralizing ovine polyclonal antibodies demonstrates that the novel adjuvant CoVaccine HT(TM) is functionally superior to Freund's adjuvant

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    Passive immunotherapies utilising polyclonal antibodies could have a valuable role in preventing and treating infectious diseases such as influenza, particularly in pandemic situations but also in immunocompromised populations such as the elderly, the chronically immunosuppressed, pregnant women, infants and those with chronic diseases. The aim of this study was to optimise current methods used to generate ovine polyclonal antibodies. Polyclonal antibodies to baculovirus-expressed recombinant influenza haemagglutinin from A/Puerto Rico/8/1934 H1N1 (PR8) were elicited in sheep using various immunisation regimens designed to investigate the priming immunisation route, adjuvant formulation, sheep age, and antigen dose, and to empirically ascertain which combination maximised antibody output. The novel adjuvant CoVaccine HT™ was compared to Freund’s adjuvant which is currently the adjuvant of choice for commercial production of ovine polyclonal Fab therapies. CoVaccine HT™ induced significantly higher titres of functional ovine anti-haemagglutinin IgG than Freund’s adjuvant but with fewer side effects, including reduced site reactions. Polyclonal hyperimmune sheep sera effectively neutralised influenza virus in vitro and, when given before or after influenza virus challenge, prevented the death of infected mice. Neither the age of the sheep nor the route of antigen administration appeared to influence antibody titre. Moreover, reducing the administrated dose of haemagglutinin antigen minimally affected antibody titre. Together, these results suggest a cost effective way of producing high and sustained yields of functional ovine polyclonal antibodies specifically for the prevention and treatment of globally significant diseases.Natalie E. Stevens, Cara K. Fraser, Mohammed Alsharifi, Michael P. Brown, Kerrilyn R. Diener, John D. Haybal

    Automated Validation of State-Based Client-Centric Isolation with TLA <sup>+</sup>

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    Clear consistency guarantees on data are paramount for the design and implementation of distributed systems. When implementing distributed applications, developers require approaches to verify the data consistency guarantees of an implementation choice. Crooks et al. define a state-based and client-centric model of database isolation. This paper formalizes this state-based model in, reproduces their examples and shows how to model check runtime traces and algorithms with this formalization. The formalized model in enables semi-automatic model checking for different implementation alternatives for transactional operations and allows checking of conformance to isolation levels. We reproduce examples of the original paper and confirm the isolation guarantees of the combination of the well-known 2-phase locking and 2-phase commit algorithms. Using model checking this formalization can also help finding bugs in incorrect specifications. This improves feasibility of automated checking of isolation guarantees in synthesized synchronization implementations and it provides an environment for experimenting with new designs.</p

    Accuracy of dementia diagnosis—a direct comparison between radiologists and a computerized method

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    There has been recent interest in the application of machine learning techniques to neuroimaging-based diagnosis. These methods promise fully automated, standard PC-based clinical decisions, unbiased by variable radiological expertise. We recently used support vector machines (SVMs) to separate sporadic Alzheimer's disease from normal ageing and from fronto-temporal lobar degeneration (FTLD). In this study, we compare the results to those obtained by radiologists. A binary diagnostic classification was made by six radiologists with different levels of experience on the same scans and information that had been previously analysed with SVM. SVMs correctly classified 95% (sensitivity/specificity: 95/95) of sporadic Alzheimer's disease and controls into their respective groups. Radiologists correctly classified 65–95% (median 89%; sensitivity/specificity: 88/90) of scans. SVM correctly classified another set of sporadic Alzheimer's disease in 93% (sensitivity/specificity: 100/86) of cases, whereas radiologists ranged between 80% and 90% (median 83%; sensitivity/specificity: 80/85). SVMs were better at separating patients with sporadic Alzheimer's disease from those with FTLD (SVM 89%; sensitivity/specificity: 83/95; compared to radiological range from 63% to 83%; median 71%; sensitivity/specificity: 64/76). Radiologists were always accurate when they reported a high degree of diagnostic confidence. The results show that well-trained neuroradiologists classify typical Alzheimer's disease-associated scans comparable to SVMs. However, SVMs require no expert knowledge and trained SVMs can readily be exchanged between centres for use in diagnostic classification. These results are encouraging and indicate a role for computerized diagnostic methods in clinical practice

    Potential of heart fatty-acid binding protein, neurofilament light, interleukin-10 and S100 calcium-binding protein B in the acute diagnostics and severity assessment of traumatic brain injury

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    Background: There is substantial interest in blood biomarkers as fast and objective diagnostic tools for traumatic brain injury (TBI) in the acute setting. Methods: Adult patients (≥18) with TBI of any severity and indications for CT scanning and orthopaedic injury controls were prospectively recruited during 2011–2013 at Turku University Hospital, Finland. The severity of TBI was classified with GCS: GCS 13–15 was classified as mild (mTBI); GCS 9–12 as moderate (moTBI) and GCS 3–8 as severe (sTBI). Serum samples were collected within 24 hours of admission and biomarker levels analysed with high-performance kits. The ability of biomarkers to distinguish between severity of TBI and CT-positive and CT-negative patients was assessed. Results: Among 189 patients recruited, neurofilament light (NF-L) was obtained from 175 patients with TBI and 40 controls. S100 calcium-binding protein B (S100B), heart fatty-acid binding protein (H-FABP) and interleukin-10 (IL-10) were analysed for 184 patients with TBI and 39 controls. There were statistically significant differences between levels of all biomarkers between the severity classes, but none of the biomarkers distinguished patients with moTBI from patients with sTBI. Patients with mTBI discharged from the ED had lower levels of IL-10 (0.26, IQR=0.21, 0.39 pg/mL), H-FABP (4.15, IQR=2.72, 5.83 ng/mL) and NF-L (8.6, IQR=6.35, 15.98 pg/mL) compared with those admitted to the neurosurgical ward, IL-10 (0.55, IQR=0.31, 1.42 pg/mL), H-FABP (6.022, IQR=4.19, 20.72 ng/mL) and NF-L (13.95, IQR=8.33, 19.93 pg/mL). We observed higher levels of H-FABP and NF-L in older patients with mTBI. None of the biomarkers or their combinations was able to distinguish CT-positive (n=36) or CT-negative (n=58) patients with mTBI from controls. Conclusions: S100B, H-FABP, NF-L and IL-10 levels in patients with mTBI were significantly lower than in patients with moTBI and sTBI but alone or in combination, were unable to distinguish patients with mTBI from orthopaedic controls. This suggests these biomarkers cannot be used alone to diagnose mTBI in trauma patients in the acute setting. Data availability statement: Data are available on reasonable request. De-identified clinical, imaging and biochemical data not published within the article can be shared with a qualified investigator by request
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