10 resultados para Dynamic state

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Attractive business cases in various application fields contribute to the sustained long-term interest in indoor localization and tracking by the research community. Location tracking is generally treated as a dynamic state estimation problem, consisting of two steps: (i) location estimation through measurement, and (ii) location prediction. For the estimation step, one of the most efficient and low-cost solutions is Received Signal Strength (RSS)-based ranging. However, various challenges - unrealistic propagation model, non-line of sight (NLOS), and multipath propagation - are yet to be addressed. Particle filters are a popular choice for dealing with the inherent non-linearities in both location measurements and motion dynamics. While such filters have been successfully applied to accurate, time-based ranging measurements, dealing with the more error-prone RSS based ranging is still challenging. In this work, we address the above issues with a novel, weighted likelihood, bootstrap particle filter for tracking via RSS-based ranging. Our filter weights the individual likelihoods from different anchor nodes exponentially, according to the ranging estimation. We also employ an improved propagation model for more accurate RSS-based ranging, which we suggested in recent work. We implemented and tested our algorithm in a passive localization system with IEEE 802.15.4 signals, showing that our proposed solution largely outperforms a traditional bootstrap particle filter.

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Background: The cerebral network that is active during rest and is deactivated during goal-oriented activity is called the default mode network (DMN). It appears to be involved in self-referential mental activity. Atypical functional connectivity in the DMN has been observed in schizophrenia. One hypothesis suggests that pathologically increased DMN connectivity in schizophrenia is linked with a main symptom of psychosis, namely, misattribution of thoughts. Methods: A resting-state pseudocontinuous arterial spin labeling (ASL) study was conducted to measure absolute cerebral blood flow (CBF) in 34 schizophrenia patients and 27 healthy controls. Using independent component analysis (ICA), the DMN was extracted from ASL data. Mean CBF and DMN connectivity were compared between groups using a 2-sample t test. Results: Schizophrenia patients showed decreased mean CBF in the frontal and temporal regions (P < .001). ICA demonstrated significantly increased DMN connectivity in the precuneus (x/y/z = -16/-64/38) in patients than in controls (P < .001). CBF was not elevated in the respective regions. DMN connectivity in the precuneus was significantly correlated with the Positive and Negative Syndrome Scale scores (P < .01). Conclusions: In schizophrenia patients, the posterior hub-which is considered the strongest part of the DMN-showed increased DMN connectivity. We hypothesize that this increase hinders the deactivation of the DMN and, thus, the translation of cognitive processes from an internal to an external focus. This might explain symptoms related to defective self-monitoring, such as auditory verbal hallucinations or ego disturbances.

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BACKGROUND AND PURPOSE: Nonconvulsive status epilepticus (NCSE) is associated with a mortality rate of up to 18%, therefore requiring prompt diagnosis and treatment. Our aim was to evaluate the diagnostic value of perfusion CT (PCT) in the differential diagnosis of NCSE versus postictal states in patients presenting with persistent altered mental states after a preceding epileptic seizure. We hypothesized that regional cortical hyperperfusion can be measured by PCT in patients with NCSE, whereas it is not present in postictal states. MATERIALS AND METHODS: Nineteen patients with persistent altered mental status after a preceding epileptic seizure underwent PCT and electroencephalography (EEG). Patients were stratified as presenting with NCSE (n = 9) or a postictal state (n = 10) on the basis of clinical history and EEG data. Quantitative and visual analysis of the perfusion maps was performed. RESULTS: Patients during NCSE had significantly increased regional cerebral blood flow (P > .0001), increased regional cerebral blood volume (P > .001), and decreased (P > .001) mean transit time compared with the postictal state. Regional cortical hyperperfusion was depicted in 7/9 of patients with NCSE by ad hoc analysis of parametric perfusion maps during emergency conditions but was not a feature of postictal states. The areas of hyperperfusion were concordant with transient clinical symptoms and EEG topography in all cases. CONCLUSIONS: Visual analysis of perfusion maps detected regional hyperperfusion in NCSE with a sensitivity of 78%. The broad availability and short processing time of PCT in an emergency situation is a benefit compared with EEG. Consequently, the use of PCT in epilepsy may accelerate the diagnosis of NCSE. PCT may qualify as a complementary diagnostic tool to EEG in patients with persistent altered mental state after a preceding seizure.

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Dynamic models for electrophoresis are based upon model equations derived from the transport concepts in solution together with user-inputted conditions. They are able to predict theoretically the movement of ions and are as such the most versatile tool to explore the fundamentals of electrokinetic separations. Since its inception three decades ago, the state of dynamic computer simulation software and its use has progressed significantly and Electrophoresis played a pivotal role in that endeavor as a large proportion of the fundamental and application papers were published in this periodical. Software is available that simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. This has been employed to show the detailed mechanisms of many of the fundamental phenomena that occur in electrophoretic separations. Dynamic electrophoretic simulations are relevant for separations on any scale and instrumental format, including free-fluid preparative, gel, capillary and chip electrophoresis. This review includes a historical overview, a survey of current simulators, simulation examples and a discussion of the applications and achievements of dynamic simulation.

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BACKGROUND Mechanical unloading of failing hearts can trigger functional recovery but results in progressive atrophy and possibly detrimental adaptation. In an unbiased approach, we examined the dynamic effects of unloading duration on molecular markers indicative of myocardial damage, hypothesizing that potential recovery may be improved by optimized unloading time. METHODS Heterotopically transplanted normal rat hearts were harvested at 3, 8, 15, 30, and 60 days. Forty-seven genes were analyzed using TaqMan-based microarray, Western blot, and immunohistochemistry. RESULTS In parallel with marked atrophy (22% to 64% volume loss at 3 respectively 60 days), expression of myosin heavy-chain isoforms (MHC-α/-β) was characteristically switched in a time-dependent manner. Genes involved in tissue remodeling (FGF-2, CTGF, TGFb, IGF-1) were increasingly upregulated with duration of unloading. A distinct pattern was observed for genes involved in generation of contractile force; an indiscriminate early downregulation was followed by a new steady-state below normal. For pro-apoptotic transcripts bax, bnip-3, and cCasp-6 and -9 mRNA levels demonstrated a slight increase up to 30 days unloading with pronunciation at 60 days. Findings regarding cell death were confirmed on the protein level. Proteasome activity indicated early increase of protein degradation but decreased below baseline in unloaded hearts at 60 days. CONCLUSIONS We identified incrementally increased apoptosis after myocardial unloading of the normal rat heart, which is exacerbated at late time points (60 days) and inversely related to loss of myocardial mass. Our findings suggest an irreversible detrimental effect of long-term unloading on myocardium that may be precluded by partial reloading and amenable to molecular therapeutic intervention.

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Highly available software systems occasionally need to be updated while avoiding downtime. Dynamic software updates reduce down-time, but still require the system to reach a quiescent state in which a global update can be performed. This can be difficult for multi-threaded systems. We present a novel approach to dynamic updates using first-class contexts, called Theseus. First-class contexts make global updates unnecessary: existing threads run to termination in an old context, while new threads start in a new, updated context; consistency between contexts is ensured with the help of bidirectional transformations. We show that for multi-threaded systems with coherent memory, first-class contexts offer a practical and flexible approach to dynamic updates, with acceptable overhead.

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OBJECTIVE Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS). METHODS We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.

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The paper analyzes how to comply with an emission constraint, which restricts the use of an established energy technique, given the two options to save energy and to invest in two alternative energy techniques. These techniques differ in their deterioration rates and the investment lags of the corresponding capital stocks. Thus, the paper takes a medium-term perspective on climate change mitigation, where the time horizon is too short for technological change to occur, but long enough for capital stocks to accumulate and deteriorate. It is shown that, in general, only one of the two alternative techniques prevails in the stationary state, although, both techniques might be utilized during the transition phase. Hence, while in a static economy only one technique is efficient, this is not necessarily true in a dynamic economy.

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Over the last two decades, imaging of the aorta has undergone a clinically relevant change. As part of the change non-invasive imaging techniques have replaced invasive intra-arterial digital subtraction angiography as the former imaging gold standard for aortic diseases. Computed tomography (CT) and magnetic resonance imaging (MRI) constitute the backbone of pre- and postoperative aortic imaging because they allow for imaging of the entire aorta and its branches. The first part of this review article describes the imaging principles of CT and MRI with regard to aortic disease, shows how both technologies can be applied in every day clinical practice, offering exciting perspectives. Recent CT scanner generations deliver excellent image quality with a high spatial and temporal resolution. Technical developments have resulted in CT scan performed within a few seconds for the entire aorta. Therefore, CT angiography (CTA) is the imaging technology of choice for evaluating acute aortic syndromes, for diagnosis of most aortic pathologies, preoperative planning and postoperative follow-up after endovascular aortic repair. However, radiation dose and the risk of contrast induced nephropathy are major downsides of CTA. Optimisation of scan protocols and contrast media administration can help to reduce the required radiation dose and contrast media. MR angiography (MRA) is an excellent alternative to CTA for both diagnosis of aortic pathologies and postoperative follow-up. The lack of radiation is particularly beneficial for younger patients. A potential side effect of gadolinium contrast agents is nephrogenic systemic fibrosis (NSF). In patients with high risk of NSF unenhanced MRA can be performed with both ECG- and breath-gating techniques. Additionally, MRI provides the possibility to visualise and measure both dynamic and flow information.

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We tested the predictions of Attentional Control Theory (ACT) by examining how anxiety affects visual search strategies, performance efficiency, and performance effectiveness using a dynamic, temporal-constrained anticipation task. Higher and lower skilled players viewed soccer situations under 2 task constraints (near vs. far situation) and were tested under high (HA) and low (LA) anxiety conditions. Response accuracy (effectiveness) and response time, perceived mental effort, and eye-movements (all efficiency) were recorded. A significant increase in anxiety was evidenced by higher state anxiety ratings on the MRF-L scale. Increased anxiety led to decreased performance efficiency because response times and mental effort increased for both skill groups whereas response accuracy did not differ. Anxiety influenced search strategies, with higher skilled players showing a decrease in number of fixation locations for far situations under HA compared with LA condition when compared with lower skilled players. Findings provide support for ACT with anxiety impairing processing efficiency and, potentially, top-down attentional control across different task constraints.