Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments.

Recent advances in Deep convolutional Neural Networks (DNNs) have enabled unprecedentedly accurate computational models of brain representations, and present an exciting opportunity to model diverse cognitive functions. State-of-the-art DNNs achieve human-level performance on object categorisation, but it is unclear how well they capture human behavior on complex cognitive tasks. Recent reports suggest that DNNs can explain significant variance in one such task, judging object similarity. Here, we extend these findings by replicating them for a rich set of object images, comparing performance across layers within two DNNs of different depths, and examining how the DNNs' performance compares to that of non-computational "conceptual" models. Human observers performed similarity judgments for a set of 92 images of real-world objects. Representations of the same images were obtained in each of the layers of two DNNs of different depths (8-layer AlexNet and 16-layer VGG-16). To create conceptual models, other human observers generated visual-feature labels (e.g., "eye") and category labels (e.g., "animal") for the same image set. Feature labels were divided into parts, colors, textures and contours, while category labels were divided into subordinate, basic, and superordinate categories. We fitted models derived from the features, categories, and from each layer of each DNN to the similarity judgments, using representational similarity analysis to evaluate model performance. In both DNNs, similarity within the last layer explains most of the explainable variance in human similarity judgments. The last layer outperforms almost all feature-based models. Late and mid-level layers outperform some but not all feature-based models. Importantly, categorical models predict similarity judgments significantly better than any DNN layer. Our results provide further evidence for commonalities between DNNs and brain representations. Models derived from visual features other than object parts perform relatively poorly, perhaps because DNNs more comprehensively capture the colors, textures and contours which matter to human object perception. However, categorical models outperform DNNs, suggesting that further work may be needed to bring high-level semantic representations in DNNs closer to those extracted by humans. Modern DNNs explain similarity judgments remarkably well considering they were not trained on this task, and are promising models for many aspects of human cognition

Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares.

Object similarity, in brain representations and conscious perception, must reflect a combination of the visual appearance of the objects on the one hand and the categories the objects belong to on the other. Indeed, visual object features and category membership have each been shown to contribute to the object representation in human inferior temporal (IT) cortex, as well as to object-similarity judgments. However, the explanatory power of features and categories has not been directly compared. Here, we investigate whether the IT object representation and similarity judgments are best explained by a categorical or a feature-based model. We use rich models (>100 dimensions) generated by human observers for a set of 96 real-world object images. The categorical model consists of a hierarchically nested set of category labels (such as "human", "mammal", and "animal"). The feature-based model includes both object parts (such as "eye", "tail", and "handle") and other descriptive features (such as "circular", "green", and "stubbly"). We used non-negative least squares to fit the models to the brain representations (estimated from functional magnetic resonance imaging data) and to similarity judgments. Model performance was estimated on held-out images not used in fitting. Both models explained significant variance in IT and the amounts explained were not significantly different. The combined model did not explain significant additional IT variance, suggesting that it is the shared model variance (features correlated with categories, categories correlated with features) that best explains IT. The similarity judgments were almost fully explained by the categorical model, which explained significantly more variance than the feature-based model. The combined model did not explain significant additional variance in the similarity judgments. Our findings suggest that IT uses features that help to distinguish categories as stepping stones toward a semantic representation. Similarity judgments contain additional categorical variance that is not explained by visual features, reflecting a higher-level more purely semantic representation

Fetal and maternal non-glucose carbohydrates and polyols concentrations in normal human pregnancies at term

The objective of the present investigation was to determine fetal and maternal plasma concentrations of nonglucose carbohydrates and polyols in normal human pregnancies at term. Uncomplicated human pregnancies (n = 50) were studied at > or =37 wk gestation. Blood samples were obtained from umbilical artery, umbilical vein, and maternal peripheral blood at the time of elective cesarean section. Plasma concentrations of inositol, glycerol, erythritol, sorbitol, and mannose were determined by HPLC analysis. Differences between umbilical venous, umbilical arterial, and maternal concentration were tested by the two-tailed t test for paired samples. Correlations between umbilical and maternal concentration and between umbilical venoarterial concentration difference and umbilical arterial concentration were assessed by Pearson's correlation and multiple regression analysis. All newborns were appropriate for gestational age, and oxygenation and acid-base balance were within the normal range for all fetuses studied. For most of the polyols (inositol, sorbitol, and erythritol), the fetal concentration was significantly higher than the maternal concentration. The umbilical venoarterial concentration difference for inositol was -10.5 +/- 3.6 microM, for glycerol was 10 +/- 1.7 microM, for sorbitol was 3.8 +/- 0.5 microM (p < 0.001), and for mannose was 7.6 +/- 0.7 microM. There was a significant correlation between maternal concentration and umbilical venous concentration of mannose (UV(MAN) = 15.38 + 0.69 M(MAN); R(2) = 0.46; p < 0.001). These results indicate that in normal human pregnancies at term, inositol is produced by the fetus, sorbitol is produced by the placenta, and there is a significant umbilical uptake of mannose from the maternal circulation

Graphene growth on Ge(100)/Si(100) substrates by CVD method

The successful integration of graphene into microelectronic devices is strongly dependent on the availability of direct deposition processes, which can provide uniform, large area and high quality graphene on nonmetallic substrates. As of today the dominant technology is based on Si and obtaining graphene with Si is treated as the most advantageous solution. However, the formation of carbide during the growth process makes manufacturing graphene on Si wafers extremely challenging. To overcome these difficulties and reach the set goals, we proposed growth of high quality graphene layers by the CVD method on Ge(100)/Si(100) wafers. In addition, a stochastic model was applied in order to describe the graphene growth process on the Ge(100)/Si(100) substrate and to determine the direction of further processes. As a result, high quality graphene was grown, which was proved by Raman spectroscopy results, showing uniform monolayer films with FWHM of the 2D band of 32 cm−1

The operational window of carbon nanotube electrical wires treated with strong acids and oxidants

Conventional metal wires suffer from a significant degradation or complete failure in their electrical performance, when subjected to harsh oxidizing environments, however wires constructed from Carbon Nanotubes (CNTs) have been found to actually improve in their electrical performance when subjected to these environments. These opposing reactions may provide new and interesting applications for CNT wires. Yet, before attempting to move to any real-world harsh environment applications, for the CNT wires, it is essential that this area of their operation be thoroughly examined. To investigate this, CNT wires were treated with multiple combinations of the strongest acids and halogens. The wires were then subjected to conductivity measurements, current carrying capacity tests, as well as Raman, microscopy and thermogravimetric analysis to enable the identification of both the limits of oxidative conductivity boosting and the onset of physical damage to the wires. These experiments have led to two main conclusions. Firstly, that CNT wires may operate effectively in harsh oxidizing environments where metal wires would easily fail and secondly, that the highest conductivity increase of the CNT wires can be achieved through a process of annealing, acetone and HCl purification followed by either H2O2 and HClO4 or Br2 treatment

Technology and performances of silicon oxynitride waveguides for optomechanical sensors fabricated by plasma-enhanced chemical vapour deposition

The technology and performances of a micromachined channel waveguides, based on PECVD deposition of silicon oxynitride (SiOxNy) thin films, is presented. The deposition parameters of the PECVD process are studied in connection with their optical, mechanical and chemical properties. Waveguide deign is optimized allowing single mode, low loss propagation and high efficiency of coupling with single mode optical fiber. The proposed technology is applied to fabricate the pigtailed Mach-Zehnder interferometers, where the coupling from optical fiber to waveguide is based on the etch of U-grooves, supporting fibers in the same substrate as the waveguide substrate

The spatiotemporal neural dynamics underlying perceived similarity for real-world objects.

The degree to which we perceive real-world objects as similar or dissimilar structures our perception and guides categorization behavior. Here, we investigated the neural representations enabling perceived similarity using behavioral judgments, fMRI and MEG. As different object dimensions co-occur and partly correlate, to understand the relationship between perceived similarity and brain activity it is necessary to assess the unique role of multiple object dimensions. We thus behaviorally assessed perceived object similarity in relation to shape, function, color and background. We then used representational similarity analyses to relate these behavioral judgments to brain activity. We observed a link between each object dimension and representations in visual cortex. These representations emerged rapidly within 200 ms of stimulus onset. Assessing the unique role of each object dimension revealed partly overlapping and distributed representations: while color-related representations distinctly preceded shape-related representations both in the processing hierarchy of the ventral visual pathway and in time, several dimensions were linked to high-level ventral visual cortex. Further analysis singled out the shape dimension as neither fully accounted for by supra-category membership, nor a deep neural network trained on object categorization. Together our results comprehensively characterize the relationship between perceived similarity of key object dimensions and neural activity

Abnormal expression of p27kip1 protein in levator ani muscle of aging women with pelvic floor disorders – a relationship to the cellular differentiation and degeneration

BACKGROUND: Pelvic floor disorders affect almost 50% of aging women. An important role in the pelvic floor support belongs to the levator ani muscle. The p27/kip1 (p27) protein, multifunctional cyclin-dependent kinase inhibitor, shows changing expression in differentiating skeletal muscle cells during development, and relatively high levels of p27 RNA were detected in the normal human skeletal muscles. METHODS: Biopsy samples of levator ani muscle were obtained from 22 symptomatic patients with stress urinary incontinence, pelvic organ prolapse, and overlaps (age range 38–74), and nine asymptomatic women (age 31–49). Cryostat sections were investigated for p27 protein expression and type I (slow twitch) and type II (fast twitch) fibers. RESULTS: All fibers exhibited strong plasma membrane (and nuclear) p27 protein expression. cytoplasmic p27 expression was virtually absent in asymptomatic women. In perimenopausal symptomatic patients (ages 38–55), muscle fibers showed hypertrophy and moderate cytoplasmic p27 staining accompanied by diminution of type II fibers. Older symptomatic patients (ages 57–74) showed cytoplasmic p27 overexpression accompanied by shrinking, cytoplasmic vacuolization and fragmentation of muscle cells. The plasma membrane and cytoplasmic p27 expression was not unique to the muscle cells. Under certain circumstances, it was also detected in other cell types (epithelium of ectocervix and luteal cells). CONCLUSIONS: This is the first report on the unusual (plasma membrane and cytoplasmic) expression of p27 protein in normal and abnormal human striated muscle cells in vivo. Our data indicate that pelvic floor disorders are in perimenopausal patients associated with an appearance of moderate cytoplasmic p27 expression, accompanying hypertrophy and transition of type II into type I fibers. The patients in advanced postmenopause show shrinking and fragmentation of muscle fibers associated with strong cytoplasmic p27 expression

Precision surface characterization for finish cylindrical milling with dynamic tool displacements model

In this work a new approach to surface roughness parameters estimation during finish cylindrical end milling is presented. The proposed model includes the influence of cutting parameters, the tool’s static run out and dynamic phenomena related to instantaneous tool deflections. The modeling procedure consists of two parts. In the first stage, tool working part instantaneous displacements are estimated using an analytical model which considers tool dynamic deflections and static errors of the machine – tool-holder – tool system. The obtained height of the tool’s displacement envelope is then applied in the second stage to the calculation of surface roughness parameters. These calculations assume that in the cylindrical milling process, two different mechanisms of surface profile formation exist. Which mechanism is present is dependent on the feed per tooth and the maximum height of the tool’s displacement envelope. The developed model is validated during cylindrical milling of hardened hot-work tool steel 55NiCrMoV6 using a stylus profiler and scanning laser vibrometer over a range of cutting parameters. The surface roughness values predicted by the developed model are in good agreement with measured values. It is found that the employment of a model which includes only the effect of static displacements gives an inferior estimation of surface roughness compared to the model incorporating dynamic tool deflection

RSV-specific airway resident memory CD8+ T cells and differential disease severity after experimental human infection

In animal models, resident memory CD8+ T (Trm) cells assist in respiratory virus elimination but their importance in man has not been determined. Here, using experimental human respiratory syncytial virus (RSV) infection, we investigate systemic and local virus-specific CD8+ T cell responses in adult volunteers. Having defined the immunodominance hierarchy, we analyze phenotype and function longitudinally in blood and by serial bronchoscopy. Despite rapid clinical recovery, we note surprisingly extensive lower airway inflammation with persistent viral antigen and cellular infiltrates. Pulmonary virus-specific CD8+ T cells display a CD69+CD103+ Trm phenotype and accumulate to strikingly high frequencies into convalescence without continued proliferation. These are more highly differentiated but express fewer cytotoxicity markers than in blood, but their abundance prior to infection correlates with protection from more severe disease