Toward automated evaluation of interactive segmentation

We previously described a system for evaluating interactive segmentation by means of user experiments (McGuinness and O’Connor, 2010). This method, while effective, is time-consuming and labor-intensive. This paper aims to make evaluation more practicable by investigating if it is feasible to automate user interactions. To this end, we propose a general algorithm for driving the segmentation that uses the ground truth and current segmentation error to automatically simulate user interactions. We investigate four strategies for selecting which pixels will form the next interaction. The first of these is a simple, deterministic strategy; the remaining three strategies are probabilistic, and focus on more realistically approximating a real user. We evaluate four interactive segmentation algorithms using these strategies, and compare the results with our previous user experiment-based evaluation. The results show that automated evaluation is both feasible and useful

A comparative evaluation of interactive segmentation algorithms

In this paper we present a comparative evaluation of four popular interactive segmentation algorithms. The evaluation was carried out as a series of user-experiments, in which participants were tasked with extracting 100 objects from a common dataset: 25 with each algorithm, constrained within a time limit of 2 min for each object. To facilitate the experiments, a “scribble-driven” segmentation tool was developed to enable interactive image segmentation by simply marking areas of foreground and background with the mouse. As the participants refined and improved their respective segmentations, the corresponding updated segmentation mask was stored along with the elapsed time. We then collected and evaluated each recorded mask against a manually segmented ground truth, thus allowing us to gauge segmentation accuracy over time. Two benchmarks were used for the evaluation: the well-known Jaccard index for measuring object accuracy, and a new fuzzy metric, proposed in this paper, designed for measuring boundary accuracy. Analysis of the experimental results demonstrates the effectiveness of the suggested measures and provides valuable insights into the performance and characteristics of the evaluated algorithms

Measurement-induced disturbance and thermal negativity of qutrit-qubit mixed spin chain

We investigate the quantum correlation in a qutrit-qubit mixed spin chain based on measurement-induced disturbance (MID) [S. Luo, Phys. Rev. A, 77, (2008) 022301]. We also compare MID and thermal entanglement measured by negativity and illustrate their different characteristics.Comment: 1 text and 3 eps figures;accepted by solid state communication

Clinical-pathological study on β-APP, IL-1β, GFAP, NFL, Spectrin II, 8OHdG, TUNEL, miR-21, miR-16, miR-92 expressions to verify DAI-diagnosis, grade and prognosis

Traumatic brain injury (TBI) is one of the most important death and disability cause, involving substantial costs, also in economic terms, when considering the young age of the involved subject. Aim of this paper is to report a series of patients treated at our institutions, to verify neurological results at six months or survival; in fatal cases we searched for βAPP, GFAP, IL-1β, NFL, Spectrin II, TUNEL and miR-21, miR-16, and miR-92 expressions in brain samples, to verify DAI diagnosis and grade as strong predictor of survival and inflammatory response. Concentrations of 8OHdG as measurement of oxidative stress was performed. Immunoreaction of β-APP, IL-1β, GFAP, NFL, Spectrin II and 8OHdG were significantly increased in the TBI group with respect to control group subjects. Cell apoptosis, measured by TUNEL assay, were significantly higher in the study group than control cases. Results indicated that miR-21, miR-92 and miR-16 have a high predictive power in discriminating trauma brain cases from controls and could represent promising biomarkers as strong predictor of survival, and for the diagnosis of postmortem traumatic brain injury

Activated Ion Electron Capture Dissociation (AI ECD) of proteins: synchronization of infrared and electron irradiation with ion magnetron motion.

Here, we show that to perform activated ion electron capture dissociation (AI-ECD) in a Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer equipped with a CO(2) laser, it is necessary to synchronize both infrared irradiation and electron capture dissociation with ion magnetron motion. This requirement is essential for instruments in which the infrared laser is angled off-axis, such as the Thermo Finnigan LTQ FT. Generally, the electron irradiation time required for proteins is much shorter (ms) than that required for peptides (tens of ms), and the modulation of ECD, AI ECD, and infrared multiphoton dissociation (IRMPD) with ion magnetron motion is more pronounced. We have optimized AI ECD for ubiquitin, cytochrome c, and myoglobin; however the results can be extended to other proteins. We demonstrate that pre-ECD and post-ECD activation are physically different and display different kinetics. We also demonstrate how, by use of appropriate AI ECD time sequences and normalization, the kinetics of protein gas-phase refolding can be deconvoluted from the diffusion of the ion cloud and measured on the time scale longer than the period of ion magnetron motion

Population-based incidence and 5-year survival for hospital-admitted traumatic brain and spinal cord injury, Western Australia, 2003-2008

This study aimed at analysing first-time hospitalisations for traumatic brain injury (TBI) and spinal cord injury (SCI) in Western Australia (WA), in terms of socio-demographic profile, cause of injury, relative risks and survival, using tabular and regression analyses of linked hospital discharge and mortality census files and comparing results with published standardised mortality rates (SMRs) for TBI. Participants were all 9,114 first hospital admissions for TBI or SCI from 7/2003 to 6/2008, linked to mortality census data through 12/2008, and the main outcome measures were number of cases by cause, SMRs in hospital and post-discharge by year through year 5. Road crashes accounted for 34 % of hospitalised TBI and 52 % of hospitalised SCI. 8,460 live TBI discharges experienced 580 deaths during 24,494 person-years of follow-up. The life-table expectation of deaths in the cohort was 164. Post-discharge SMRs were 7.66 in year 1, 3.86 in year 2 and averaged 2.31 in years 3 through 5. 317 live SCI discharges experienced 18 deaths during 929 years of follow-up. Post-discharge SMRs were 7.36 in year 1 and a fluctuating average of 2.13 in years 2 through 5. Use of data from model systems does not appear to yield biased SMRs. Similarly no systematic variation was observed between all-age studies and the more numerous studies that focused on those aged 14 to 16 and older. Based on two studies, SMRs for TBI, however, may be higher in year 2 post-discharge in Australia than elsewhere. That possibility and its cause warrant exploration. Expanding public TBI/SCI compensation in WA from road crash to all causes might triple TBI compensation and double SCI compensation

TNF induces increased production of extracellular amyloid-β- and α-synuclein-containing aggregates by human Alzheimer’s disease neurons

In addition to increased aberrant protein aggregation, inflammation has been proposed as a key element in the pathogenesis and progression of Alzheimer’s disease. How inflammation interacts with other disease pathways and how protein aggregation increases during disease are not clear. We used single molecule imaging approaches and membrane permeabilisation assays to determine the effect of chronic exposure to TNF, a master proinflammatory cytokine, on protein aggregation in human induced pluripotent stem cell-derived neurons harbouring monogenic Alzheimer’s disease mutations. We report that exposure of Alzheimer’s disease, but not control, neurons to TNF induces substantial production of extracellular protein aggregates. Aggregates from Alzheimer’s disease neurons are composed of amyloid-β and α-synuclein and induce significant permeabilisation of lipid membranes in an assay of pathogenicity. These findings provide support for a causal relationship between two crucial processes in Alzheimer’s disease pathogenesis, and suggest that targeting inflammation, particularly TNF, may have beneficial downstream effects on ameliorating aberrant protein aggregation and accumulation

Residual alignment and its effect on weld strength in material-extrusion 3D-printing of polylactic acid

Gaining a molecular understanding of material extrusion (MatEx) 3D printing is crucial to predicting and controlling part properties. Here we report the direct observation of distinct birefringence localised to the weld regions between the printed filaments, indicating the presence of molecular orientation that is absent from the bulk of the filament. The value of birefringence at the weld increases at higher prints speeds and lower nozzle temperatures, and is found to be detrimental to the weld strength measured by tensile testing perpendicular to the print direction. We employ a molecularly-aware non-isothermal model of the MatEx flow and cooling process to predict the degree of alignment trapped in the weld at the glass transition. We find that the predicted residual alignment factor is linearly related to the extent of birefringence. Thus, by combining experiments and molecular modelling, we show that weld strength is not limited by inter-diffusion, as commonly expected, but instead by the configuration of the entangled polymer network. We adapt the classic molecular interpretation of glassy polymer fracture to explain how the measured weld strength decreases with increasing print speed and decreasing nozzle temperature