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At least 1,135 records · Page 63

Neural net diagnostics for VLSI test

This paper discusses the application of neural network pattern analysis algorithms to the IC fault diagnosis problem. A fault diagnostic is a decision rule combining what is known about an ideal circuit test response with information about how it is distorted by fabrication variations and measurement noise. The rule is used to detect fault existence in fabricated circuits using real test equipment. Traditional statistical techniques may be used to achieve this goal, but they can employ unrealistic a priori assumptions about measurement data. Our approach to this problem employs an adaptive pattern analysis technique based on feedforward neural networks. During training, a feedforward network automatically captures unknown sample distributions. This is important because distributions arising from the nonlinear effects of process variation can be more complex than is typically assumed. A feedforward network is also able to extract measurement features which contribute significantly to making a correct decision. Traditional feature extraction techniques employ matrix manipulations which can be particularly costly for large measurement vectors. In this paper we discuss a software system which we are developing that uses this approach. We also provide a simple example illustrating the use of the technique for fault detection in an operational amplifier.

Lin, T.↗

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig ( Sus scrofa ) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. In conclusion, knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.

59 BASIC BIOLOGICAL SCIENCES↗

Imaging crossing fibers in mouse, pig, monkey, and human brain using small-angle X-ray scattering

Myelinated axons (nerve fibers) efficiently transmit signals throughout the brain via action potentials. Multiple methods that are sensitive to axon orientations, from microscopy to magnetic resonance imaging, aim to reconstruct the brain's structural connectome. As billions of nerve fibers traverse the brain with various possible geometries at each point, resolving fiber crossings is necessary to generate accurate structural connectivity maps. However, doing so with specificity is a challenging task because signals originating from oriented fibers can be influenced by brain (micro)structures unrelated to myelinated axons. X-ray scattering can specifically probe myelinated axons due to the periodicity of the myelin sheath, which yields distinct peaks in the scattering pattern. Here, in this work, we show that small-angle X-ray scattering (SAXS) can be used to detect myelinated, axon-specific fiber crossings. We first demonstrate the capability using strips of human corpus callosum to create artificial double- and triple-crossing fiber geometries, and we then apply the method in mouse, pig, vervet monkey, and human brains. We compare results to polarized light imaging (3D-PLI), tracer experiments, and to outputs from diffusion MRI that sometimes fails to detect crossings. Given its specificity, capability of 3-dimensional sampling and high resolution, SAXS could serve as a ground truth for validating fiber orientations derived using diffusion MRI as well as microscopy-based methods.

59 BASIC BIOLOGICAL SCIENCES↗

1 H NMR-based metabolomics of antimalarial plant species traditionally used by Vha-Venda people in Limpopo Province, South Africa and isolation of antiplasmodial compounds

The Vha-Venda people living in rural areas of Limpopo Province of South Africa regularly use traditional plant-based medicines to treat malaria. In our earlier publication, twenty indigenous plant species used to treat malaria or its symptoms by Vha-Venda people were evaluated for antiplasmodial activity. The main objective of the current paper was to assess the robustness of NMR-based metabolomics in discriminating classes of secondary compounds that are responsible for the observed antimalarial activity and the isolation of antiplasmodial compounds. Twenty dichloromethane extracts were reconstituted in CDCl 3 , subjected to 1 H NMR-based metabolomic analysis on a Varian 600 MHz spectrometer and the acquired 1 H NMR spectra were then evaluated collectively using multivariate data analysis (MDA). Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures–Discriminant Analysis (OPLS-DA) were used to ‘globally’ discern antiplasmodial profiles. A contribution plot was then generated from the OPLS-DA scoring plot in an attempt to determine the classes of compounds that are responsible for the observed grouping. Further phytochemical analyses were conducted on the lipophilic extracts of Tabernaemontana elegans and Vangueria infausta subsp. infausta. These best candidates were fractionated, purified and their isolated compounds identified based on conventional chromatographic and spectroscopic techniques. The PCA did not separate the acquired profiles according to the detected antiplasmodial bioactivity. Application of a supervised OPLS-DA on the 1 H NMR profiles resulted in a discrimination pattern that could be correlated to the observed antimalarial bioactivity. A contribution plot generated from the OPLS-DA scoring plot illustrated the classes of compounds responsible for the observed grouping. Prominent peaks were observed in the aromatic, sugar-based/N-containing and aliphatic spectral regions of the contribution plot. Two known indole alkaloids were isolated from T. elegans, and identified as tabernaemontanine (IC 50 = 12.0±0.8 µM) and dregamine (IC 50 = 62.0±2.4 µM). Friedelin (IC 50 = 7.20±0.5 µM) and morindolide (IC 50 = 107.1±0.6 µM) were isolated from V. infausta subsp. infausta. This is the first report of the rare iridoid lactone, morindolide's antimalarial activity. While these two compounds have been previously identified, this is the first account of their occurrence in the genus Vangueria. The study illustrated the potential of NMR-based metabolomics in discriminating classes of compounds that may be attributed to antiplasmodial activity. Finally and additionally, the study demonstrated the potential of discovering novel antiplasmodial scaffolds from medicinal plants and the rationale for the bioprospecting antimalarial plant species used by Vha-Venda people.

59 BASIC BIOLOGICAL SCIENCES↗

Nondestructive ultrasonic characterization of a triple-weld-bead wire arc additively manufactured ER70S-6 S-curved wall

Understanding build-scale microstructural variation in wire arc additive manufacturing (WAAM) of low-carbon steels is essential for ensuring consistent structure–property relationships throughout large components. Conventional destructive characterization techniques, such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), are time-intensive and limited to localized regions, making comprehensive evaluation of large WAAM structures challenging. In this study, a nondestructive ultrasonic approach was employed to characterize a 252 mm tall ER70S-6 S-curved WAAM wall produced using a triple-bead deposition strategy. Optical and SEM analysis revealed a repeating dual-region microstructure consisting of uniform polygonal ferrite at melt pool centers and heterogeneous ferrite with coarse and fine grains near melt pool boundaries, attributed to cyclic thermal conditions. Longitudinal ultrasonic backscatter imaging was used to evaluate the continuity of this periodicity along the full build height. The ultrasonic response exhibited a consistent repeating pattern that correlated with the observed layer-wise microstructural variation. X-ray computed tomography confirmed the absence of detectable porosity, indicating that ultrasonic contrast is primarily governed by grain morphology. Overall, the results indicate that longitudinal backscatter ultrasound is a promising nondestructive characterization technique for validating microstructural variations along the s-curved WAAM wall, with significant potential for microstructure optimization and process control.

36 MATERIALS SCIENCE↗

Intrinsic Century-Scale Variability in Tropical Pacific Sea Surface Temperatures and Their Influence on Western US Hydroclimate

Hydroclimate variability of the southwest United States (SWUS) is influenced by the tropical Pacific Ocean, particularly through the teleconnection to El Nino/Southern Oscillation (ENSO), which is expected to be altered by climate change. Natural variability in this teleconnection has not been robustly quantified, complicating the detection of anthropogenic climate change. Here, we use a linear inverse model (LIM) to quantify natural variability in the ENSO-SWUS teleconnection. The LIM yields realistic teleconnection patterns with century-scale variability comparable to simulations from the Last Millennium Ensemble project and the Climate Model Intercomparison Project Phases 5 and 6. The variability quantified by the LIM illuminates two aspects of our understanding of ENSO and its impacts: the inherent statistics of the observable system can produce century-long periods with a wide range of correlations to SWUS hydroclimate, including nonsignificant correlations, and thus that detecting changes in ENSO-related hydroclimate variability is challenging in a changing climate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

THz Radar Observations of Hydrometeors in a Spray Chamber

Abstract A THz radar, with its wide bandwidth, is capable of high‐resolution imaging down to the centimeter scale. In this study, a THz radar is applied to detect hydrometeors generated in a spray chamber. The observed backscattering signals show fluctuations at centimeter scales, indicating various hydrometeor distribution patterns along the radar beam. A co‐located High‐Speed Imaging (HSI) sensor is used to measure the Drop Size Distributions (DSD) in the spray chamber. The radar sampling beam is well aligned with the HSI probes, allowing an objective comparison between the remote sensing and in situ observations. In this study, the observed radar power is compared with the power estimated from the HSI measurements. Results show great consistency, with power difference smaller than 0.5 dB. This study demonstrates the feasibility and great potential of using a THz radar for ultra‐high‐resolution observations of clouds in a laboratory facility, and in the real atmosphere.

54 ENVIRONMENTAL SCIENCES↗

High-resolution studies of the Majorana atomic chain platform

Ordered assemblies of magnetic atoms on the surface of conventional superconductors can be used to engineer topological superconducting phases and realize Majorana fermion quasiparticles (MQPs) in a condensed matter setting. Recent experiments have shown that chains of Fe atoms on Pb generically have the required electronic characteristics to form a one-dimensional topological superconductor and have revealed spatially resolved signatures of localized MQPs at the ends of such chains. Here we report higher-resolution measurements of the same atomic chain system performed using a dilution refrigerator scanning tunnelling microscope (STM). With significantly better energy resolution than previous studies, we show that the zero-bias peak (ZBP) in Fe chains has no detectable splitting from hybridization with other states. The measurements also reveal that the ZBP exhibits a distinctive ‘double eye’ spatial pattern on nanometre length scales. Theoretically we show that this is a general consequence of STM measurements of MQPs with substantial spectral weight in the superconducting substrate, a conclusion further supported by measurements of Pb overlayers deposited on top of the Fe chains. Lastly, we report experiments performed with superconducting tips in search of the particle–hole symmetric MQP signature expected in such measurements.

Electronic properties and materials↗

Hydroacoustic Assessment of Behavioral Responses by Fish Passing Near an Operating Tidal Turbine in the East River, New York

An important environmental issue facing the marine and hydrokinetic energy industry is whether fish that encounter underwater energy devices are likely to be struck and injured by moving components, primarily rotating turbine blades. The automated analysis of nearly 3 weeks of multibeam hydroacoustics data identified about 35,000 tracks of fish passing a tidal turbine in the East River, New York. These tracks included both individual fish and schools during periods with the turbine absent, the turbine present and operating, and the turbine present but not operating. The density of fish in the sampled area when the turbine was absent was roughly twice the density observed when the turbine was in place, particularly when the turbine was operating. This suggests that some avoidance occurred before fish were close enough to the turbine to be observed by the hydroacoustics system. Various measures of swimming behavior (direction, velocity, and linearity) were calculated for each track and evaluated for indication of behavioral responses to turbine presence and operation. Fish tracks were grouped based on tidal cycle, current velocity, and swimming direction and were evaluated with respect to turbine presence and operation and with respect to distance from the turbine. Nonparametric tests (Kolmogorov–Smirnov test) and multivariate analysis (canonical discriminant analysis) found significant differences among groups with respect to turbine presence and operation, suggesting that some fish responded to the turbine by adjusting swimming behavior, such as making small adjustments to swimming direction and velocity as they passed near the turbine. We found no evidence that fish were being struck by rotating blades, but there did appear to be large-scale avoidance initiated out of the range of the hydroacoustics detection system. Furthermore, more study is needed to determine whether such avoidance behavior has significant ramifications for normal fish movement patterns, bioenergetics, seasonal migrations, and predator exposure.

13 HYDRO ENERGY↗

Measuring phylogenetic signal between categorical traits and phylogenies

Abstract Motivation Determining whether a trait and phylogeny share some degree of phylogenetic signal is a flagship goal in evolutionary biology. Signatures of phylogenetic signal can assist the resolution of a broad range of evolutionary questions regarding the tempo and mode of phenotypic evolution. However, despite the considerable number of strategies to measure it, few and limited approaches exist for categorical traits. Here, we used the concept of Shannon entropy and propose the δ statistic for evaluating the degree of phylogenetic signal between a phylogeny and categorical traits. Results We validated δ as a measure of phylogenetic signal: the higher the δ-value the higher the degree of phylogenetic signal between a given tree and a trait. Based on simulated data we proposed a threshold-based classification test to pinpoint cases of phylogenetic signal. The assessment of the test’s specificity and sensitivity suggested that the δ approach should only be applied to 20 or more species. We have further tested the performance of δ in scenarios of branch length and topology uncertainty, unbiased and biased trait evolution and trait saturation. Our results showed that δ may be applied in a wide range of phylogenetic contexts. Finally, we investigated our method in 14 360 mammalian gene trees and found that olfactory receptor genes are significantly associated with the mammalian activity patterns, a result that is congruent with expectations and experiments from the literature. Our application shows that δ can successfully detect molecular signatures of phenotypic evolution. We conclude that δ represents a useful measure of phylogenetic signal since many phenotypes can only be measured in categories. Availability and implementation https://github.com/mrborges23/delta_statistic. Supplementary information Supplementary data are available at Bioinformatics online.

Borges, Rui↗

Deep medical image analysis with representation learning and neuromorphic computing

Deep learning is increasingly used in medical imaging, improving many steps of the processing chain, from acquisition to segmentation and anomaly detection to outcome prediction. Yet significant challenges remain: (i) image-based diagnosis depends on the spatial relationships between local patterns, something convolution and pooling often do not capture adequately; (ii) data augmentation, the de facto method for learning three-dimensional pose invariance, requires exponentially many points to achieve robust improvement; (iii) labelled medical images are much less abundant than unlabelled ones, especially for heterogeneous pathological cases; and (iv) scanning technologies such as magnetic resonance imaging can be slow and costly, generally without online learning abilities to focus on regions of clinical interest. To address these challenges, novel algorithmic and hardware approaches are needed for deep learning to reach its full potential in medical imaging.

60 APPLIED LIFE SCIENCES↗

Data-Driven Approaches for Bead Geometry Prediction Via Melt Pool Monitoring

In the realm of additive manufacturing, the selection of process parameters to avoid over and under deposition entails a time-consuming and resource-intensive trial-and-error approach. Given the distinct characteristics of each part geometry, there is a pressing need for advancing real-time process monitoring and control to ensure consistent and reliable part dimensional accuracy. Here, this research shows that support vector regression (SVR) and convolutional neural network (CNN) models offer a promising solution for real-time process control due to the models’ abilities to recognize complex, non-linear patterns with high accuracy. A novel experiment was designed to compare the performance of SVR and CNN models to indirectly detect bead height from a coaxial image of a melt pool from a single-layer, single bead build. The study showed that both SVR and CNN models trained on melt pool data collected from a coaxial optical camera can accurately predict the bead height with a mean absolute percentage error of 3.67% and 3.68%, respectively.

36 MATERIALS SCIENCE↗

Tropospheric Waveguide Teleconnections and Their Seasonality

Abstract One-point correlation maps of the subseasonal variability of 200-hPa meridional wind in nature and an atmospheric general circulation model are systematically analyzed to quantify the impact of the climatological-mean jets on tropospheric covariability as a result of the jets acting as waveguides for the propagation of Rossby waves. As anticipated by linear theory, signatures of jet influence are detected in terms of (i) the geographical position of the strongest teleconnections, (ii) the zonal orientation and extent of prominent patterns of variability, and (iii) the scale of the features that make up those patterns. Further evidence of jet waveguide influence comes from examining the seasonality of these teleconnection attributes. During winter, covariability can be essentially circumglobal, while during summer it tends to be confined within two separate sectors of the globe where the jets are especially strong. Experiments with a multilevel linear planetary wave model confirm that the analyzed characteristics of teleconnections in the waveguides can be attributed to the action of the mean state; no organization to the anomalous forcing of the atmosphere is required to produce these properties. Some attributes, however, depend on the presence of zonal variations in the climatological-mean state that are of similar scale to the teleconnection patterns themselves.

54 ENVIRONMENTAL SCIENCES↗

MULTICOLOR LIGHT CURVE SIMULATIONS OF POPULATION III CORE-COLLAPSE SUPERNOVAE: FROM SHOCK BREAKOUT TO {sup 56}CO DECAY

The properties of the first generation of stars and their supernova (SN) explosions remain unknown due to the lack of actual observations. Recently, many transient surveys have been conducted and the feasibility of detecting supernovae (SNe) of Pop III stars is growing. In this paper, we study the multicolor light curves for a number of metal-free core-collapse SN models (25–100 M{sub ⊙}) to determine the indicators for the detection and identification of first generation SNe. We use mixing-fallback supernova explosion models that explain the observed abundance patterns of metal-poor stars. Numerical calculations of the multicolor light curves are performed using the multigroup radiation hydrodynamic code stella. The calculated light curves of metal-free SNe are compared with non-zero-metallicity models and several observed SNe. We have found that the shock breakout characteristics, the evolution of the photosphere’s velocity, the luminosity, and the duration and color evolution of the plateau, that is, all of the SN phases from shock breakout to {sup 56}Co decay, are helpful for estimating the parameters of the SN progenitor: the mass, the radius, the explosion energy, and the metallicity. We conclude that the multicolor light curves could potentially be used to identify first-generation SNe in current (Subaru/HSC) and future transient surveys (LSST, James Webb Space Telescope). They are also suitable for identifying low-metallicity SNe in the nearby universe (PTF, Pan-STARRS, Gaia).

79 ASTRONOMY AND ASTROPHYSICS↗

Friction, deformation and fracture of single-crystal silicon carbide

Friction experiments were conducted with hemispherical and conical diamond riders sliding on the basal plane of silicon carbide. The results indicate that, when deformation is primarily elastic, the friction does not depend on crystallographic orientation and there is no detectable fracture or cracking. When, however, plastic deformation occurs, silicon carbide exhibits anisotropic friction and deformation behavior. Surface fracture crack patterns surrounding wear tracks are observed to be of three types. The crack-geometries of two types are generally independent of orientation, the third crack, however, depends on the orientation. All surface cracks extend into subsurface. Anisotropic friction, deformation and fracture on the basal plane are primarily controlled by the slip system and cleavage.

Miyoshi, K.↗

Investigation of LANDSAT imagery on correlations between ore deposits and major shield structures in Finland

The author has identified the following significant results. Several regional lineaments appear to correlate with the distribution of ore deposits and showings. Combined study of LANDSAT summer and winter mosaics and color composites of geological, geomorphological, and geophysical maps makes the correlation more perceptible. The revealed pattern of significant lineaments in northern Finland is fairly regular. The most significant lineaments seen in LANDSAT mosaics are not detectable in single images.

Tuominen, H. V.↗

Friction, deformation and fracture of single-crystal silicon carbide

An investigation was conducted to determine the nature of the deformation and fracture of silicon carbide and its effects on friction properties. Friction experiments were conducted with hemispherical and conical diamond riders sliding on the basal plane of silicon carbide. The results indicate that, when deformation is primarily elastic, the friction does not depend on crystallographic orientation and there is no detectable fracture or cracking. When, however, plastic deformation occurs, silicon carbide exhibits anisotropic friction and deformation behavior. Surface fracture crack patterns surrounding wear tracks are observed to be of three types. The crack-geometries of two types are generally independent of orientation, the third crack, however, depends on the orientation. All surface cracks extend into subsurface.

Miyoshi, K.↗

Description of a computer simulation of an orbital SAR system

A computer simulation of an orbital SAR system has been developed in order to predict SAR performance for a wide variety of system and environmental parameters. The objectives of the simulation are: (1) to assess the effect of various antenna patterns on the SAR image, (2) to assess the effect of various SAR parameters on the system's ability to detect small differences in the radar cross section of adjacent homogeneous areas, and (3) to assess the effect of mapping geometry on SAR image quality. The simulation is implemented as seven programs: (1) simulation control, (2) terrain model, (3) slant range computation, (4) production of IPQ video, (5) motion compensation, (6) Doppler processor, and (7) postprocessor and display.

Crow, G. L.↗