Examination of the vessel's shape, resistive force and volumetric-aqueous efficiencies to optimize the vessels' foil under noise propagation

There are several parameters in designing undersurface vessel forms, the most important of which is the hull's total strength, which includes the strength of the hull and its attachments. According to studies, 70 % of the total strength of the vessels is related to their hull only without attachments. The hull has three major parts: nose, cylinder, and heel. The advanced vessels' architecture has a parallel shape (cylinder shape). This cylindrical part is important in examining the used volume by pilots and vessel equipment. This paper uses the CFD method to examine the vessel's shape, and the resistive force and volumetric-aqueous efficiencies are extracted. An optimum profile is extracted by the values of resistive force and volumetric-aqueous efficiencies. The results indicate the significant effect of the hull form on the hydro-acoustic noise of the hull. In other words, by optimizing the hydrodynamic form of the hull, the noise propagation can be reduced as much as possible. Also, the linear slope of the optimized hull is not optimized more than the hull. This means that the turbulence caused by the optimized hull has a higher damping potential.

Accuracy and precision in super-resolution MRI: Enabling spherical tensor diffusion encoding at ultra-high b-values and high resolution

Diffusion MRI (dMRI) can probe the tissue microstructure but suffers from low signal-to-noise ratio (SNR) whenever high resolution is combined with high diffusion encoding strengths. Low SNR leads to poor precision as well as poor accuracy of the diffusion-weighted signal; the latter is caused by the rectified noise floor and can be observed as a positive bias in magnitude signal. Super-resolution techniques may facilitate a beneficial tradeoff between bias and resolution by allowing acquisition at low spatial resolution and high SNR, whereafter high spatial resolution is recovered by image reconstruction. In this work, we describe a super-resolution reconstruction framework for dMRI and investigate its performance with respect to signal accuracy and precision. Using phantom experiments and numerical simulations, we show that the super-resolution approach improves accuracy by facilitating a more beneficial trade-off between spatial resolution and diffusion encoding strength before the noise floor affects the signal. By contrast, precision is shown to have a less straightforward dependency on acquisition, reconstruction, and intrinsic tissue parameters. Indeed, we find a gain in precision from super-resolution reconstruction is substantial only when some spatial resolution is sacrificed. Finally, we deployed super-resolution reconstruction in a healthy brain for the challenging combination of spherical b-tensor encoding at ultra-high b-values and high spatial resolution—a configuration that produces a unique contrast that emphasizes tissue in which diffusion is restricted in all directions. This demonstration showcased that super-resolution reconstruction enables a vastly superior image contrast compared to conventional imaging, facilitating investigations that would otherwise have prohibitively low SNR, resolution or require non-conventional MRI hardware.

Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system

This study proposes a neural network (NN) model to predict and simulate the propagation of vehicular traffic noise in a dense residential area at the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia. The proposed model comprises of two main simulation steps: that is, the prediction of vehicular traffic noise using NN and the simulation of the propagation of traffic noise emission using a mathematical model. First, the NN model was developed with the following selected noise predictors: the number of motorbikes, the sum of vehicles, car ratio, heavy vehicle ratio (e.g. truck, lorry and bus), highway density and a light detection and ranging (LiDAR)-derived digital surface model (DSM). Subsequently, NN and its hyperparameters were optimised by a systematic optimisation procedure based on a grid search approach. The noise propagation model was then developed in a geographic information system (GIS) using five variables, namely road geometry, barriers, distance, interaction of air particles and weather parameters. The noise measurement was conducted continuously at 15-min intervals and the data were analysed by taking the minimum, maximum and average values recorded during the day. The measurement was performed four times a day (i.e. morning, afternoon, evening, and midnight) over two days of the week (i.e. Sunday and Monday). An optimal radial basis function NN was used with 17 hidden layers. The learning rate and momentum values were 0.05 and 0.9, respectively. Finally, the accuracy of the proposed method achieved 78.4% with less than 4.02 dB (A) error in noise prediction. Overall, the proposed models were found to be promising tools for traffic noise assessment in dense urban areas.

Assessment of noise level and noise propagation generated by light-lift helicopters in mountain natural environments

The use of helicopter rises discussion about environmental noise propagation especially when it operates in proximity of environmentally sensitive areas (ESAs) for an extended period because of its potential implications in wildlife behaviours. In order to support decisions on helicopter logging operation management in proximity of ESAs, this study focused on (i) analysing the noise spectrum of a light-lift helicopter during logging operations and on (ii) assessing the noise propagation in the surrounding environments. This study investigated a helicopter logging operation for wood fuel extraction in the eastern part of the Italian Alps. The potential disturbance area covered for the entire helicopter logging operation was evaluated by a specific GIS application according to hearing sensitivity of the most sensitive wildlife species in the study area (different strigiform species). The noise level at the ground appeared to be affected by the location regardless both the use of equivalent continuous sound pressures level dB(A) (LAeq) and the single-event level (SEL) noise metrics. The lowest values were recorded when the helicopter was flown over the sound meter level located under the forest canopy, while the highest was recorded when the helicopter was unhooking the loads at the landing. The GIS application highlighted the consistent of the exceeded noise area (weighted to strigiform hearing range and sensitivity) for the lower frequency bands (0.016-0.250 kHz). A more restricted exceeded noise area concerned instead the most sensitive frequency bands" for the strigiform (1-2 kHz). Graphical abstract ᅟ.

WE-G-217BCD-11: A New Phantom to Study Combined Effects of In-Plane (x,y) and Z Axis Resolution for 3-D Imaging

PURPOSE

The aim of this work is to develop phantoms that can be used to sample the radial and 3D properties of a CT image, including in-plane (x,y) and z-axis information. The Phantom is amenable to mathematical analysis of the x, y, and z axis resolution properties separately and combined.

METHODS

A periodic pattern of a pair of opposed (30°) angled ramps is configured to produce a waveform profile across the CT image. A perfect CT image (with no loss of resolution) of the test object would produce a consistent geometric pattern of the intersection of a line with the pair of angled ramps. However, due to the finite resolution (x, y and z), the CT waveform profile will not yield the perfect profile; rather it will be influenced by slice thickness, and in-plane resolution (PSF, MTF), as well as noise limitations, and other sources of non-uniformity such as beam hardening etc. Various characteristics of the waveform profile including, amplitude, frequency, and slope (rate of climb) of the peaks, can be studied using mathematical analysis such as the Fourier transform. It will be shown how these performance characteristics are encoded in the wave pattern.

RESULTS

The waveform profiles are visually examined and mathematically analyzed, to demonstrate the effect of Slice Thickness (z axis) and changes of In-Plane (x,y) Resolution and non-uniformity across the image field; moreover, the harmonic analysis of the waveform is used to predict, either the in-plane resolution (MTF), or the z-axis MTF when one of the two is already known.

CONCLUSIONS

The Wave pattern phantom offers a way to consider 3-D imaging characteristics of a CT scanner by scanning a single repetitive test object that encodes both in-plane resolution and z-axis resolution and also offers a way to study non-uniformity effects throughout the CT plane (volume). DJG is a consultant to The Phantom Laboratory and Image OWL, Salem, NY. Funding of other authors is supplied by Image OWL Salem, NY.

WE-G-213CD-05: Beam's-Eye-View Prostate Motion Detection during Arc Radiotherapy

PURPOSE

To track prostate motion during clinical arc radiotherapy using a novel statistical motion tracking algorithm in both phantom and patient systems.

METHODS

For the phantom study, a dynamic phantom with a custom tumor model and radiopaque fiducials was used. For the patient study, the clinical data from two prostate patients were acquired during volumetric modulated arc therapy (VMAT). For each patient, two gold fiducials (X-Mark, 1cm and 2cm in length) were implanted in the prostate. A total of 35 fractions with 2-field full arcs were delivered. Beam's-eye- view (BEV) images were acquired in cine mode every five fractions at a frame rate of 2 fps.The prostate motion was measured by two sequential steps: fiducial detection and motion estimation. In the first step, a wavelet- based block matching filter was used to suppress the noise and enhance the fiducials in the BEV images. A trajectory of detected fiducials was generated along the projection angles. Sequentially, the prostate motion was tracked using a statistical maximum a posteriori (MAP) algorithm. The 3-D fiducial position was estimated by maximizing the probability of displacement of 2-D projections.

RESULTS

A total of 8,400 BEV images were processed for this study. The phantom experiments showed that the baseline accuracy of estimation is 0.69+/-0.56 mm. For patient 1, intra- fraction prostate motion was measured to be 0.98+/-0.51 mm for all fractions, and individual fraction motion less than 1 mm. For patient 2, intra- fraction motion was 1.12+/-0.65 mm for all fractions. However, an exceptionally large displacement was measured as 4.9+/-0.74mm in one of the fractions.

CONCLUSIONS

Prostate motion during arc-therapy can be rigorously tracked to an accuracy of one millimeter. This technique is well suited for in-treatment room target tracking and post-therapy evaluation. Varian Medical Systems Inc.

Phenotypic impact of regulatory noise in cellular stress-response pathways

Recent studies indicate that intrinsic promoter-mediated gene expression noise can confer a selective advantage under acute environmental stress by providing beneficial phenotypic diversity within cell populations. To investigate how extrinsic gene expression noise impacts the fitness of cell populations under stress, we engineered two nearly isogenic budding yeast strains; one carrying a two-step regulatory cascade that allows for precise control of the noise transmitted from a transcriptional regulator to a downstream stress-inducing gene, and one carrying a network with low constant upstream noise. The fitness and gene expression of these strains were compared under acute and prolonged stress exposure. Using a phenomenological modeling approach, we predicted that increased noise should confer a fitness advantage under high stress conditions, but reciprocally reduce the resistance of the population to low stress. The model also predicted that extrinsic noise might serve as a basis for phenotypic plasticity whereby gene expression distributions are modulated in response to prolonged stress. Experimentally, we confirmed the predicted differential fitness advantage of extrinsic noise under acute stress, as well as the predicted modulation of gene expression under prolonged stress. However, contrary to model predictions, strains with low and high extrinsic noise showed very similar adaptive responses to prolonged stress. This suggests that while phenotypic heterogeneity generated by noise in regulatory signals can confer increased robustness to acute stress, it is not a requirement for the observed long-term phenotypic plasticity.