Optical control of spin in semiconductors has been pioneered using nanostructures of III-V and II-VI semiconductors, but the emergence of two-dimensional van der Waals materials offers an alternative low-dimensional p...
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We demonstrate tunable, giant, and structure-induced deep-ultraviolet circular dichroism in macroscopically chiral assemblies of racemic carbon nanotubes prepared using two approaches: mechanical-rotation-assisted vac...
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ISBN:
(纸本)9781957171258
We demonstrate tunable, giant, and structure-induced deep-ultraviolet circular dichroism in macroscopically chiral assemblies of racemic carbon nanotubes prepared using two approaches: mechanical-rotation-assisted vacuum filtration and chiral stacking of aligned carbon nanotubes.
The brain modifies its synaptic strengths during learning in order to better adapt to its environment. However, the underlying plasticity rules that govern learning are unknown. Many proposals have been suggested, inc...
ISBN:
(纸本)9781713829546
The brain modifies its synaptic strengths during learning in order to better adapt to its environment. However, the underlying plasticity rules that govern learning are unknown. Many proposals have been suggested, including Hebbian mechanisms, explicit error backpropagation, and a variety of alternatives. It is an open question as to what specific experimental measurements would need to be made to determine whether any given learning rule is operative in a real biological system. In this work, we take a "virtual experimental" approach to this problem. Simulating idealized neuroscience experiments with artificial neural networks, we generate a large-scale dataset of learning trajectories of aggregate statistics measured in a variety of neural network architectures, loss functions, learning rule hyperpa-rameters, and parameter initializations. We then take a discriminative approach, training linear and simple non-linear classifiers to identify learning rules from features based on these observables. We show that different classes of learning rules can be separated solely on the basis of aggregate statistics of the weights, activations, or instantaneous layer-wise activity changes, and that these results generalize to limited access to the trajectory and held-out architectures and learning curricula. We identify the statistics of each observable that are most relevant for rule identification, finding that statistics from network activities across training are more robust to unit undersampling and measurement noise than those obtained from the synaptic strengths. Our results suggest that activation patterns, available from electrophysiological recordings of post-synaptic activities on the order of several hundred units, frequently measured at wider intervals over the course of learning, may provide a good basis on which to identify learning rules.
TAROGE-M is a radio antenna array atop ∼ 2.7 km-high Mt. Melbourne in Antarctica for detecting ultra-high energy (UHE, E > 1017 eV) air showers in near-horizontal directions. Besides the detection of cosmic rays a...
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Because of their natural one-dimensional (1D) structure combined with intricate chiral variations, carbon nanotubes (CNTs) exhibit various exceptional physical properties, such as ultrahigh electrical and thermal cond...
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The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via sel...
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A polarization-insensitive plasmonic absorber is designed consisting of Au fishnet structures on a TiO2 spacer/Ag mirror. The fishnet structures excite localized surface plasmon and generate hot electrons from the abs...
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A polarization-insensitive plasmonic absorber is designed consisting of Au fishnet structures on a TiO2 spacer/Ag mirror. The fishnet structures excite localized surface plasmon and generate hot electrons from the absorbed photons, while the TiO2 layer induces Fabry–Perot resonance, and the Ag mirror acts as a back *** optimizing the TiO2 layer thickness, numerical simulation shows that 97% of the incident light is absorbed in the Au layer. The maximum responsivity and external quantum efficiency of the device can approach 5 mA/W and ~1%, respectively, at the wavelength of 700 nm.
Background Despite continuous improvement in long-term survival after esophagectomy, potential serious post-operative complications, such as anastomotic leaks (ALs), still occur. Several risk factors for ALs have been...
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Background Despite continuous improvement in long-term survival after esophagectomy, potential serious post-operative complications, such as anastomotic leaks (ALs), still occur. Several risk factors for ALs have been proposed, including environmental factors. Our main objective was to examine the correlation of esophageal tumor microbiome composition and functional profile with ALs. Additionally, we analyzed the microbiome of esophageal tumors and their potential correlation with clinical features of the patients. Materials and methods Surgical specimens of esophageal tumors and adjacent normal tissues were collected from consecutive patients who underwent an esophagectomy. Formalin-fixed paraffin-embedded (FFPE) tissue samples were processed using 16S ribosomal DNA multiple fragments amplicon sequencing to characterize bacterial microbiome composition. The tumor and normal tissue microbiome and bacterial functional profile were analyzed based on the clinical outcome of ALs. Results Out of 60 patients who met the inclusion criteria, 52 (86.7%) patients had both normal adjacent tissue (NAT) and tumor (T) FFPE samples included with sufficient bacterial DNA extracted for analysis. A total of 28% of participants had esophageal ALs. Proportion tests [ P < 0.05, false discovery rate (FDR) < 0.25] revealed operational taxonomic units (OTUs) significantly present in T samples as opposed to NAT samples, as well as significantly present OTUs in patients with AL as opposed to patients without AL complication. Conclusions In this study, we provide a profile of the understudied esophageal microbiome and its connection to ALs. Our results can provide potential clues on how to avoid ALs by considering a patient’s personal microbiome when providing perioperative care.
Magnetic kagome materials provide a fascinating playground for exploring the interplay of magnetism, correlation and topology. Many magnetic kagome systems have been reported including the binary FemXn (X=Sn, Ge;m:n =...
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Features such as photon rings, jets, or hot spots can leave particular topological signatures in a black hole image. As such, topological data analysis can be used to characterize images resulting from high-resolution...
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Features such as photon rings, jets, or hot spots can leave particular topological signatures in a black hole image. As such, topological data analysis can be used to characterize images resulting from high-resolution observations (synthetic or real) of black holes in the electromagnetic sector. We demonstrate that persistent homology allows for this characterization to be made automatically by counting the number of connected components and one-dimensional holes. Further, persistent homology also allows for the distance between connected components or the diameter of holes to be extracted from the image. In order to apply persistent homology on synthetic black hole images, we also introduce metronization, a new algorithm to prepare black hole images in a form that is suitable for topological analysis.
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