The effect of external flow on the feeding currents of sessile microorganisms

Microscopic sessile suspension feeders live attached to surfaces and, by consuming bacteria-sized prey and by being consumed, they form an important part of aquatic ecosystems. Their environmental impact is mediated by their feeding rate, which depends on a self-generated feeding current. The feeding rate has been hypothesized to be limited by recirculating eddies that cause the organisms to feed from water that is depleted of food particles. However, those results considered organisms in still water, while ambient flow is often present in their natural habitats. We show, using a point-force model, that even very slow ambient flow, with speed several orders of magnitude less than that of the self-generated feeding current, is sufficient to disrupt the eddies around perpendicular suspension feeders, providing a constant supply of food-rich water. However, the feeding rate decreases in external flow at a range of non-perpendicular orientations due to the formation of recirculation structures not seen in still water. We quantify the feeding flow and observe such recirculation experimentally for the suspension feeder Vorticella convallaria in external flows typical of streams and rivers.     

A vectorized <Emphasis Type="Italic">k-means</Emphasis> algorithm for compressed datasets: design and experimental analysis

Clustering algorithms (i.e., Gaussian mixture models, k-means) tackle the problem of grouping a set of elements in such a way that elements from the same group (or cluster) have more similar properties to each other than to those elements in other clusters. This simple concept turns out to be the basis in complex algorithms from many application areas, including sequence analysis and genotyping in bioinformatics, medical imaging, antimicrobial activity, market research, social networking, etc. However, as the data volume continues to increase, the performance of clustering algorithms is heavily influenced by the memory subsystem. In this paper, we propose a novel and efficient implementation of Lloyd’s k-means clustering algorithm to substantially reduce data movement along the memory hierarchy. Our contributions are based on the fact that the vast majority of processors are equipped with powerful Single Instruction Multiple Data (SIMD) instructions that are, in most cases, underused. SIMD improves the CPU computational power and, if used wisely, can be seen as an opportunity to improve on the application data transfers by compressing/decompressing the data, specially for memory-bound applications. Our contributions include a SIMD-friendly data layout organization, in-register implementation of key functions and SIMD-based compression. We demonstrate that using our optimized SIMD-based compression method, it is possible to improve the performance and energy of k-means by a factor of 4.5x and 8.7x, respectively, for a i7 Haswell machine, and 22x and 22.2x for Xeon Phi: KNL, running a single thread.     

Use of numerical modeling in design for co-firing biomass in wall-fired burners

Co-firing biomass with coal or gas in the existing units has gained increasing interest in the recent past to increase the production of environmentally friendly, renewable green power. This paper presents design considerations for co-firing biomass with natural gas in wall-fired burners by use of numerical modeling. The models currently used to predict solid fuel combustion rely on a spherical particle shape assumption, which may deviate a lot from reality for big biomass particles. A sphere gives a minimum in terms of the surface-area-to-volume ratio, which impacts significantly both motion and reaction of a particle. To better understand the biomass combustion and thus improve the design for co-firing biomass in wall-fired burners, non-sphericity of biomass particles is considered. To ease comparison, two cases are numerically studied in a long gas/biomass co-fired burner model. (1) The biomass particles are assumed as solid or hollow cylinders in shape, depending on the particle group. To model accurately the motion of biomass particles, the forces that could be important are all considered in the particle force balance, which includes a drag for non-spherical particles, an additional lift due to particle non-sphericity, and a “virtual-mass” force due to relatively light biomass particles, as well as gravity and a pressure-gradient force. Since the drag and lift forces are both shape factor- and orientation-dependent, coupled particle rotation equations are resolved to update particle orientation. To better model the reaction of biomass particles, the actual particle surface area available and the average oxygen mass flux at particle surface are considered, both of which are shape factor-dependent. (2) The non-spherical biomass particles are simplified as equal-volume spheres, without any modification to the motion and reaction due to their non-sphericity. The simulation results show a big difference between the two cases and indicate it is very significant to take into account the non-sphericity of biomass particles in order to model biomass combustion more accurately. Methods to improve the design for co-firing biomass in wall-fired burners are finally suggested.     

Spectral Doppler estimation utilizing 2-D spatial information and adaptive signal processing

The trade-off between temporal and spectral resolution in conventional pulsed wave (PW) Doppler may limit duplex/triplex quality and the depiction of rapid flow events. It is therefore desirable to reduce the required observation window (OW) of the Doppler signal while preserving the frequency resolution. This work investigates how the required observation time can be reduced by adaptive spectral estimation utilizing 2-D spatial information obtained by parallel receive beamforming. Four adaptive estimation techniques were investigated, the power spectral Capon (PSC) method, the amplitude and phase estimation (APES) technique, multiple signal classification (MUSIC), and a projection-based version of the Capon technique. By averaging radially and laterally, the required covariance matrix could successfully be estimated without temporal averaging. Useful PW spectra of high resolution and contrast could be generated from ensembles corresponding to those used in color flow imaging (CFI; OW = 10). For a given OW, the frequency resolution could be increased compared with the Welch approach, in cases in which the transit time was higher or comparable to the observation time. In such cases, using short or long pulses with unfocused or focused transmit, an increase in temporal resolution of up to 4 to 6 times could be obtained in in vivo examples. It was further shown that by using adaptive signal processing, velocity spectra may be generated without high-pass filtering the Doppler signal. With the proposed approach, spectra retrospectively calculated from CFI may become useful for unfocused as well as focused imaging. This application may provide new clinical information by inspection of velocity spectra simultaneously from several spatial locations.     

Accuracy of carotid strain estimates from ultrasonic wall tracking: a study based on multiphysics simulations and in vivo data

We used a multiphysics model to assess the accuracy of carotid strain estimates derived from a 1-D ultrasonic wall tracking algorithm. The presented tool integrates fluid-structure interaction (FSI) simulations with an ultrasound simulator (Field II), which allows comparison of the ultrasound (US) images with a ground truth. Field II represents tissue as random points on which US waves reflect and whose position can be updated based on the flow field and vessel wall deformation from FSI. We simulated the RF-signal of a patient-specific carotid bifurcation, including the blood pool as well as the vessel wall and surrounding tissue. Distension estimates were obtained from a wall tracking algorithm using tracking points at various depths within the wall, and further processed to assess radial and circumferential strain. The simulated data demonstrated that circumferential strain can be estimated with reasonable accuracy (especially for the common carotid artery and at the lumen-intima and media-adventitia interface), but the technique does not allow to reliably assess intra-arterial radial strain. These findings were supported by in vivo data of 10 healthy adults, showing similar circumferential and radial strain profiles throughout the arterial wall. We concluded that these deviations are present due to the complex 3-D vessel wall deformation, the presence of specular reflections and, to a lesser extent, the spatially varying beam profile, with the error depending on the phase in the cardiac cycle and the scanning location.     

Surface-enhanced Raman spectroscopy to probe reversibly photoswitchable azobenzene in controlled nanoscale environments

We apply in situ surface-enhanced Raman spectroscopy (SERS) to probe the reversible photoswitching of azobenzene-functionalized molecules inserted in self-assembled monolayers that serve as controlled nanoscale environments. Nanohole arrays are fabricated in Au thin films to enable SERS measurements associated with excitation of surface plasmons. A series of SERS spectra are recorded for azobenzene upon cycling exposure to UV (365 nm) and blue (450 nm) light. Experimental spectra match theoretical calculations. On the basis of both the simulations and the experimental data analysis, SERS provides quantitative information on the reversible photoswitching of azobenzene in controlled nanoscale environments.     

Effect of Shot Peening Parameters to Residual Stress Profiles and Barkhausen Noise

The production of gear components includes numerous manufacturing operations which are carried out to ensure proper surface characteristics of components to deal with wear and fatigue. Surface shot peening is one way to increase the compressive residual stresses on the surface and thus ensure better wear and fatigue resistance. An experimental plan for shot peening was conducted to produce samples with varying surface characteristics. Residual stress profile and Barkhausen noise measurements were carried out for the samples. The objective of the study was to evaluate the interactions between the shot peening parameters studied, the residual stress profiles and the Barkhausen noise measurements. A multivariable regression analysis was applied for the task. Some remarkable correlations were found between the shot peening parameters, residual stress profile and Barkhausen noise features. The most important finding was that when the shot peening intensity was high enough, over 0.5 mmA, it dominated the shot peening coverage density parameter and thus no correlations could be gained. On the other hand, if the intensity parameter was lower than the limit of 0.5 mmA, the correlation between residual stress and Barkhausen noise measurements was remarkable. This means that the surface Barkhausen noise measurements could be used for the evaluation of the stress gradient in the shot peening process.