103 resultados para Acoustic modelling
Resumo:
PURPOSE: We investigated the influence of beam modulation on treatment planning by comparing four available stereotactic radiosurgery (SRS) modalities: Gamma-Knife-Perfexion, Novalis-Tx Dynamic-Conformal-Arc (DCA) and Dynamic-Multileaf-Collimation-Intensity-Modulated-radiotherapy (DMLC-IMRT), and Cyberknife. MATERIAL AND METHODS: Patients with arteriovenous malformation (n = 10) or acoustic neuromas (n = 5) were planned with different treatment modalities. Paddick conformity index (CI), dose heterogeneity (DH), gradient index (GI) and beam-on time were used as dosimetric indices. RESULTS: Gamma-Knife-Perfexion can achieve high degree of conformity (CI = 0.77 ± 0.04) with limited low-doses (GI = 2.59 ± 0.10) surrounding the inhomogeneous dose distribution (D(H) = 0.84 ± 0.05) at the cost of treatment time (68.1 min ± 27.5). Novalis-Tx-DCA improved this inhomogeneity (D(H) = 0.30 ± 0.03) and treatment time (16.8 min ± 2.2) at the cost of conformity (CI = 0.66 ± 0.04) and Novalis-TX-DMLC-IMRT improved the DCA CI (CI = 0.68 ± 0.04) and inhomogeneity (D(H) = 0.18 ± 0.05) at the cost of low-doses (GI = 3.94 ± 0.92) and treatment time (21.7 min ± 3.4) (p<0.01). Cyberknife achieved comparable conformity (CI = 0.77 ± 0.06) at the cost of low-doses (GI = 3.48 ± 0.47) surrounding the homogeneous (D(H) = 0.22 ± 0.02) dose distribution and treatment time (28.4min±8.1) (p<0.01). CONCLUSIONS: Gamma-Knife-Perfexion will comply with all SRS constraints (high conformity while minimizing low-dose spread). Multiple focal entries (Gamma-Knife-Perfexion and Cyberknife) will achieve better conformity than High-Definition-MLC of Novalis-Tx at the cost of treatment time. Non-isocentric beams (Cyberknife) or IMRT-beams (Novalis-Tx-DMLC-IMRT) will spread more low-dose than multiple isocenters (Gamma-Knife-Perfexion) or dynamic arcs (Novalis-Tx-DCA). Inverse planning and modulated fluences (Novalis-Tx-DMLC-IMRT and CyberKnife) will deliver the most homogeneous treatment. Furthermore, Linac-based systems (Novalis and Cyberknife) can perform image verification at the time of treatment delivery.
Resumo:
Aims: To assess the potential distribution of an obligate seeder and active pyrophyte, Cistus salviifolius, a vulnerable species in the Swiss Red List; to derive scenarios by changing the fire return interval; and to discuss the results from a conservation perspective. A more general aim is to assess the impact of fire as a natural factor influencing the vegetation of the southern slopes of the Alps. Locations: Alps, southern Switzerland. Methods: Presence-absence data to fit the model were obtained from the most recent field mapping of C. salviifolius. The quantitative environmental predictors used in this study include topographic, climatic and disturbance (fire) predictors. Models were fitted by logistic regression and evaluated by jackknife and bootstrap approaches. Changes in fire regime were simulated by increasing the time-return interval of fire (simulating longer periods without fire). Two scenarios were considered: no fire in the past 15 years; or in the past 35 years. Results: Rock cover, slope, topographic position, potential evapotranspiration and time elapsed since the last fire were selected in the final model. The Nagelkerke R-2 of the model for C. salviifolius was 0.57 and the Jackknife area under the curve evaluation was 0.89. The bootstrap evaluation revealed model robustness. By increasing the return interval of fire by either up to 15 years, or 35 years, the modelled C. salviifolius population declined by 30-40%, respectively. Main conclusions: Although fire plays a significant role, topography and rock cover appear to be the most important predictors, suggesting that the distribution of C. salviifolius in the southern Swiss Alps is closely related to the availability of supposedly competition-free sites, such as emerging bedrock, ridge locations or steep slopes. Fire is more likely to play a secondary role in allowing C. salviifolius to extend its occurrence temporarily, by increasing germination rates and reducing the competition from surrounding vegetation. To maintain a viable dormant seed bank for C. salviifolius, conservation managers should consider carrying out vegetation clearing and managing wild fire propagation to reduce competition and ensure sufficient recruitment for this species.
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Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.
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Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.
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The growth rate of acoustic tumors, although slow, varies widely. There may be a continuous spectrum or distinct groups of tumor growth rates. Clinical, audiologic, and conventional histologic tests have failed to shed any light on this problem. Modern immunohistochemical methods may stand a better chance. The Ki-67 monoclonal antibody stains proliferating cells and is used in this study to investigate the growth fraction of 13 skull base schwannomas. The acoustic tumors can be divided into two different growth groups, one with a rate five times the other. The literature is reviewed to see if this differentiation is borne out by the radiologic studies. Distinct growth rates have been reported: one very slow, taking 50 years to reach 1 cm in diameter, a second rate with a diameter increase of 0.2 cm/year, and a third rate five times the second, with a 1.0 cm increase in diameter per year. A fourth group growing at 2.5 cm/year is postulated, but these tumors cannot be followed for long radiologically, since symptoms demand surgical intervention. The clinical implications of these separate growth rates are discussed.
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Previous research has provided inconsistent results regarding the spatial modulation of auditory-somatosensory interactions. The present study reports three experiments designed to investigate the nature of these interactions in the space close to the head. Human participants made speeded detection responses to unimodal auditory, somatosensory, or simultaneous auditory-somatosensory stimuli. In Experiment 1, electrocutaneous stimuli were presented to either earlobe, while auditory stimuli were presented from the same versus opposite sides, and from one of two distances (20 vs. 70cm) from the participant's head. The results demonstrated a spatial modulation of auditory-somatosensory interactions when auditory stimuli were presented from close to the head. In Experiment 2, electrocutaneous stimuli were delivered to the hands, which were placed either close to or far from the head, while the auditory stimuli were again presented at one of two distances. The results revealed that the spatial modulation observed in Experiment 1 was specific to the particular body part stimulated (head) rather than to the region of space (i.e. around the head) where the stimuli were presented. The results of Experiment 3 demonstrate that sounds that contain high-frequency components are particularly effective in eliciting this auditory-somatosensory spatial effect. Taken together, these findings help to resolve inconsistencies in the previous literature and suggest that auditory-somatosensory multisensory integration is modulated by the stimulated body surface and acoustic spectra of the stimuli presented.
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This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.
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Background: Bone health is a concern when treating early stage breast cancer patients with adjuvant aromatase inhibitors. Early detection of patients (pts) at risk of osteoporosis and fractures may be helpful for starting preventive therapies and selecting the most appropriate endocrine therapy schedule. We present statistical models describing the evolution of lumbar and hip bone mineral density (BMD) in pts treated with tamoxifen (T), letrozole (L) and sequences of T and L. Methods: Available dual-energy x-ray absorptiometry exams (DXA) of pts treated in trial BIG 1-98 were retrospectively collected from Swiss centers. Treatment arms: A) T for 5 years, B) L for 5 years, C) 2 years of T followed by 3 years of L and, D) 2 years of L followed by 3 years of T. Pts without DXA were used as a control for detecting selection biases. Patients randomized to arm A were subsequently allowed an unplanned switch from T to L. Allowing for variations between DXA machines and centres, two repeated measures models, using a covariance structure that allow for different times between DXA, were used to estimate changes in hip and lumbar BMD (g/cm2) from trial randomization. Prospectively defined covariates, considered as fixed effects in the multivariable models in an intention to treat analysis, at the time of trial randomization were: age, height, weight, hysterectomy, race, known osteoporosis, tobacco use, prior bone fracture, prior hormone replacement therapy (HRT), bisphosphonate use and previous neo-/adjuvant chemotherapy (ChT). Similarly, the T-scores for lumbar and hip BMD measurements were modeled using a per-protocol approach (allowing for treatment switch in arm A), specifically studying the effect of each therapy upon T-score percentage. Results: A total of 247 out of 546 pts had between 1 and 5 DXA; a total of 576 DXA were collected. Number of DXA measurements per arm were; arm A 133, B 137, C 141 and D 135. The median follow-up time was 5.8 years. Significant factors positively correlated with lumbar and hip BMD in the multivariate analysis were weight, previous HRT use, neo-/adjuvant ChT, hysterectomy and height. Significant negatively correlated factors in the models were osteoporosis, treatment arm (B/C/D vs. A), time since endocrine therapy start, age and smoking (current vs. never).Modeling the T-score percentage, differences from T to L were -4.199% (p = 0.036) and -4.907% (p = 0.025) for the hip and lumbar measurements respectively, before any treatment switch occurred. Conclusions: Our statistical models describe the lumbar and hip BMD evolution for pts treated with L and/or T. The results of both localisations confirm that, contrary to expectation, the sequential schedules do not seem less detrimental for the BMD than L monotherapy. The estimated difference in BMD T-score percent is at least 4% from T to L.