Dosimetric impact of geometric errors due to respiratory motion prediction on dynamic multileaf collimator-based four-dimensional radiation delivery

The synchronization of dynamic multileaf collimator (DMLC) response with respiratory motion is critical to ensure the accuracy of DMLC-based four dimensional (4D) radiation delivery. In practice, however, a finite time delay (response time) between the acquisition of tumor position and multileaf collimator response necessitates predictive models of respiratory tumor motion to synchronize radiation delivery. Predicting a complex process such as respiratory motion introduces geometric errors, which have been reported in several publications. However, the dosimetric effect of such errors on 4D radiation delivery has not yet been investigated. Thus, our aim in this work was to quantify the dosimetric effects of geometric error due to prediction under several different conditions. Conformal and intensity modulated radiation therapy (IMRT) plans for a lung patient were generated for anterior-posterior/posterior-anterior (AP/PA) beam arrangements at 6 and 18 MV energies to provide planned dose distributions. Respiratory motion data was obtained from 60 diaphragm-motion fluoroscopy recordings from five patients. A linear adaptive filter was employed to predict the tumor position. The geometric error of prediction was defined as the absolute difference between predicted and actual positions at each diaphragm position. Distributions of geometric error of prediction were obtained for all of the respiratory motion data. Planned dose distributions were then convolved with distributions for the geometric error of prediction to obtain convolved dose distributions. The dosimetric effect of such geometric errors was determined as a function of several variables: response time (0-0.6 s), beam energy (6/18 MV), treatment delivery (3D/4D), treatment type (conformal/IMRT), beam direction (AP/PA), and breathing training type (free breathing/audio instruction/visual feedback). Dose difference and distance-to-agreement analysis was employed to quantify results. Based on our data, the dosimetric impact of prediction (a) increased with response time, (b) was larger for 3D radiation therapy as compared with 4D radiation therapy, (c) was relatively insensitive to change in beam energy and beam direction, (d) was greater for IMRT distributions as compared with conformal distributions, (e) was smaller than the dosimetric impact of latency, and (f) was greatest for respiration motion with audio instructions, followed by visual feedback and free breathing. Geometric errors of prediction that occur during 4D radiation delivery introduce dosimetric errors that are dependent on several factors, such as response time, treatment-delivery type, and beam energy. Even for relatively small response times of 0.6 s into the future, dosimetric errors due to prediction could approach delivery errors when respiratory motion is not accounted for at all. To reduce the dosimetric impact, better predictive models and/or shorter response times are required.

Modeling of diesel particulate filter filtration and regeneration for transient driving schedules

Due to their high thermal efficiency, diesel engines have excellent fuel economy and have been widely used as a power source for many vehicles. Diesel engines emit less greenhouse gases (carbon dioxide) compared with gasoline engines. However, diesel engines emit large amounts of particulate matter (PM) which can imperil human health. The best way to reduce the particulate matter is by using the Diesel Particulate Filter (DPF) system which consists of a wall-flow monolith which can trap particulates, and the DPF can be periodically regenerated to remove the collected particulates. The estimation of the PM mass accumulated in the DPF and total pressure drop across the filter are very important in order to determine when to carry out the active regeneration for the DPF. In this project, by developing a filtration model and a pressure drop model, we can estimate the PM mass and the total pressure drop, then, these two models can be linked with a regeneration model which has been developed previously to predict when to regenerate the filter. There results of this project were: 1 Reproduce a filtration model and simulate the processes of filtration. By studying the deep bed filtration and cake filtration, stages and quantity of mass accumulated in the DPF can be estimated. It was found that the filtration efficiency increases faster during the deep-bed filtration than that during the cake filtration. A “unit collector” theory was used in our filtration model which can explain the mechanism of the filtration very well. 2 Perform a parametric study on the pressure drop model for changes in engine exhaust flow rate, deposit layer thickness, and inlet temperature. It was found that there are five primary variables impacting the pressure drop in the DPF which are temperature gradient along the channel, deposit layer thickness, deposit layer permeability, wall thickness, and wall permeability. 3 Link the filtration model and the pressure drop model with the regeneration model to determine the time to carry out the regeneration of the DPF. It was found that the regeneration should be initiated when the cake layer is at a certain thickness, since a cake layer with either too big or too small an amount of particulates will need more thermal energy to reach a higher regeneration efficiency. 4 Formulate diesel particulate trap regeneration strategies for real world driving conditions to find out the best desirable conditions for DPF regeneration. It was found that the regeneration should be initiated when the vehicle’s speed is high and during which there should not be any stops from the vehicle. Moreover, the regeneration duration is about 120 seconds and the inlet temperature for the regeneration is 710K.

Evaluation of factors affecting speed perception in a driving simulator

The present study was conducted to determine the effects of different variables on the perception of vehicle speeds in a driving simulator. The motivations of the study include validation of the Michigan Technological University Human Factors and Systems Lab driving simulator, obtaining a better understanding of what influences speed perception in a virtual environment, and how to improve speed perception in future simulations involving driver performance measures. Using a fixed base driving simulator, two experiments were conducted, the first to evaluate the effects of subject gender, roadway orientation, field of view, barriers along the roadway, opposing traffic speed, and subject speed judgment strategies on speed estimation, and the second to evaluate all of these variables as well as feedback training through use of the speedometer during a practice run. A mixed procedure model (mixed model ANOVA) in SAS® 9.2 was used to determine the significance of these variables in relation to subject speed estimates, as there were both between and within subject variables analyzed. It was found that subject gender, roadway orientation, feedback training, and the type of judgment strategy all significantly affect speed perception. By using curved roadways, feedback training, and speed judgment strategies including road lines, speed limit experience, and feedback training, speed perception in a driving simulator was found to be significantly improved.

Highlands College Students' Driving Habits

The purpose of this study is to understand driving habits of college students. The study demonstrates potential inappropriate behaviors.

The etiology of liver damage imparts cytokines transforming growth factor beta1 or interleukin-13 as driving forces in fibrogenesis

It is unknown whether transforming growth factor beta1 (TGF-beta1) signaling uniformly participates in fibrogenic chronic liver diseases, irrespective of the underlying origin, or if other cytokines such as interleukin (IL)-13 share in fibrogenesis (e.g., due to regulatory effects on type I pro-collagen expression). TGF-beta1 signaling events were scored in 396 liver tissue samples from patients with diverse chronic liver diseases, including hepatitis B virus (HBV), hepatitis C virus (HCV), Schistosoma japonicum infection, and steatosis/steatohepatitis. Phospho-Smad2 staining correlated significantly with fibrotic stage in patients with HBV infection (n = 112, P < 0.001) and steatosis/steatohepatitis (n = 120, P < 0.01), but not in patients with HCV infection (n = 77, P > 0.05). In tissue with HBx protein expression, phospho-Smad2 was detectable, suggesting a functional link between viral protein expression and TGF-beta1 signaling. For IL-13, immunostaining correlated with fibrotic stage in patients with HCV infection and steatosis/steatohepatitis. IL-13 protein was more abundant in liver tissue lysates from three HCV patients compared with controls, as were IL-13 serum levels in 68 patients with chronic HCV infection compared with 20 healthy volunteers (72.87 +/- 26.38 versus 45.41 +/- 3.73, P < 0.001). Immunohistochemistry results suggest that IL-13-mediated liver fibrogenesis may take place in the absence of phospho-signal transducer and activator of transcription protein 6 signaling. In a subgroup of patients with advanced liver fibrosis (stage > or =3), neither TGF-beta nor IL-13 signaling was detectable. Conclusion: Depending on the cause of liver damage, a predominance of TGF-beta or IL-13 signaling is found. TGF-beta1 predominance is detected in HBV-related liver fibrogenesis and IL-13 predominance in chronic HCV infection. In some instances, the underlying fibrogenic mediator remains enigmatic.

Consensus statement of the European Heart Rhythm Association: updated recommendations for driving by patients with implantable cardioverter defibrillators

Patients with an implantable cardioverter defibrillator (ICD) have an ongoing risk of sudden incapacitation that might cause harm to others while driving a car. Driving restrictions vary across different countries in Europe. The most recent recommendations for driving of ICD patients in Europe were published in 1997 and focused mainly on patients implanted for secondary prevention. In recent years there has been a vast increase in the number of patients with an ICD and in the percentage of patients implanted for primary prevention. The EHRA task force on ICD and driving was formed to reassess the risk of driving for ICD patients based on the literature available. The recommendations are summarized in the following table and are further explained in the document. [table: see text] Driving restrictions are perceived as difficult for patients and their families, and have an immediate consequence for their lifestyle. To increase the adherence to the driving restrictions, adequate discharge of education and follow-up of patients and family are pivotal. The task force members hope this document may serve as an instrument for European and national regulatory authorities to formulate uniform driving regulations.

Driving the refactoring of Java Enterprise applications by evaluating the distance between application elements

Java Enterprise Applications (JEAs) are complex systems composed using various technologies that in turn rely on languages other than Java, such as XML or SQL. Given the complexity of these applications, the need to reverse engineer them in order to support further development becomes critical. In this paper we show how it is possible to split a system into layers and how is possible to interpret the distance between application elements in order to support the refactoring of JEAs. The purpose of this paper is to explore ways to provide suggestions about the refactoring operations to perform on the code by evaluating the distance between layers and elements belonging those layers. We split JEAs into layers by considering the kinds and the purposes of the elements composing the application. We measure distance between elements by using the notion of the shortest path in a graph. Also we present how to enrich the interpretation of the distance value with enterprise pattern detection in order to refine the suggestion about modifications to perform on the code.

Climate spectrum estimation in the presence of timescale errors

We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation.

Shifted Coupling of EEG Driving Frequencies and fMRI Resting State Networks in Schizophrenia Spectrum Disorders

INTRODUCTION: The cerebral resting state in schizophrenia is altered, as has been demonstrated separately by electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state networks (RSNs). Previous simultaneous EEG/fMRI findings in healthy controls suggest that a consistent spatiotemporal coupling between neural oscillations (EEG frequency correlates) and RSN activity is necessary to organize cognitive processes optimally. We hypothesized that this coupling is disorganized in schizophrenia and related psychotic disorders, in particular regarding higher cognitive RSNs such as the default-mode (DMN) and left-working-memory network (LWMN). METHODS: Resting state was investigated in eleven patients with a schizophrenia spectrum disorder (n = 11) and matched healthy controls (n = 11) using simultaneous EEG/fMRI. The temporal association of each RSN to topographic spectral changes in the EEG was assessed by creating Covariance Maps. Group differences within, and group similarities across frequencies were estimated for the Covariance Maps. RESULTS: The coupling of EEG frequency bands to the DMN and the LWMN respectively, displayed significant similarities that were shifted towards lower EEG frequencies in patients compared to healthy controls. CONCLUSIONS: By combining EEG and fMRI, each measuring different properties of the same pathophysiology, an aberrant relationship between EEG frequencies and altered RSNs was observed in patients. RSNs of patients were related to lower EEG frequencies, indicating functional alterations of the spatiotemporal coupling. SIGNIFICANCE: The finding of a deviant and shifted coupling between RSNs and related EEG frequencies in patients with a schizophrenia spectrum disorder is significant, as it might indicate how failures in the processing of internal and external stimuli, as commonly seen during this symptomatology (i.e. thought disorders, hallucinations), arise.

Vision and night driving abilities of elderly drivers

OBJECTIVE: In this article, we review the impact of vision on older people's night driving abilities. Driving is the preferred and primary mode of transport for older people. It is a complex activity where intact vision is seminal for road safety. Night driving requires mesopic rather than scotopic vision, because there is always some light available when driving at night. Scotopic refers to night vision, photopic refers to vision under well-lit conditions, and mesopic vision is a combination of photopic and scotopic vision in low but not quite dark lighting situations. With increasing age, mesopic vision decreases and glare sensitivity increases, even in the absence of ocular diseases. Because of the increasing number of elderly drivers, more drivers are affected by night vision difficulties. Vision tests, which accurately predict night driving ability, are therefore of great interest. METHODS: We reviewed existing literature on age-related influences on vision and vision tests that correlate or predict night driving ability. RESULTS: We identified several studies that investigated the relationship between vision tests and night driving. These studies found correlations between impaired mesopic vision or increased glare sensitivity and impaired night driving, but no correlation was found among other tests; for example, useful field of view or visual field. The correlation between photopic visual acuity, the most commonly used test when assessing elderly drivers, and night driving ability has not yet been fully clarified. CONCLUSIONS: Photopic visual acuity alone is not a good predictor of night driving ability. Mesopic visual acuity and glare sensitivity seem relevant for night driving. Due to the small number of studies evaluating predictors for night driving ability, further research is needed.