117,733 research outputs found
Typification and checklist of the names in Trichospermum (Malvaceae, Grewioideae)
No full textGerace, Samuele, Peruzzi, Lorenzo (2022): Typification and checklist of the names in Trichospermum (Malvaceae, Grewioideae). Phytotaxa 558 (3): 263-275, DOI: 10.11646/phytotaxa.558.3.
Typification of names in the neotropical genus Luehea (Malvaceae: Grewioideae)
No full textGerace, Samuele, Bovini, Massimo G., Peruzzi, Lorenzo, Baumgratz, José Fernando A. (2022): Typification of names in the neotropical genus Luehea (Malvaceae: Grewioideae). Phytotaxa 542 (2): 180-188, DOI: 10.11646/phytotaxa.542.2.5, URL: http://dx.doi.org/10.11646/phytotaxa.542.2.
François Luc de Bruges (1548/49-1619): un humaniste biblique à Saint-Omer
No full textIl saggio ripercorre la vita e le opere del biblista fiammingo François Luc di Bruge
QuantStudioTM 12K Flex OpenArray® System as a Tool for High-Throughput Genotyping and Gene Expression Analysis
No full textReal time technology provides great advancements over PCR-based methods for a broad range of applications. With the increased availability of sequencing information, there is a need for the development and application of high-throughput real time PCR genotyping and gene expression methods that significantly broaden the current screening capabilities. Thermo Fisher Scientific (USA) has released a platform (QuantStudioTM 12K Flex system coupled with OpenArray® technology) with key elements required for high-throughput SNP genotyping and gene expression analysis. This allows for a rapid screening of large numbers of TaqMan® assays (up to 256) in many samples (up to 480) per run. This advanced real-time method involves the use of an array composed of 3,000 through-holes running on the QuantStudioTM 12K with OpenArray® block. The aim of this chapter is to outline the OpenArray® approach while providing a comprehensive in-depth review of the scientific literature on this topic. In agreement with a large number of independent studies, we conclude that the use of OpenArray® technology is a rapid and accurate method for high-throughput and large-scale systems biology studies with high specificity and sensitivity
Slow light with interleaved p-n junction to enhance performance of integrated Mach-Zehnder silicon modulators
No full textSlow light is a very important concept in nanophotonics, especially in the context of photonic crystals. In this work, we apply our previous design of band-edge slow light in silicon waveguide gratings [M. Passoni et al, Opt. Express 26, 8470 (2018)] to Mach-Zehnder modulators based on the plasma dispersion effect. The key idea is to employ an interleaved p-n junction with the same periodicity as the grating, in order to achieve optimal matching between the electromagnetic field profile and the depletion regions of the p-n junction. The resulting modulation efficiency is strongly improved as compared to common modulators based on normal rib waveguides, even in a bandwidth of 20–30 nm near the band edge, while the total insertion loss due to free carriers is not increased. The present concept is promising in view of realizing slow-light modulators for silicon photonics with reduced energy dissipation
Realization of high-Q/V photonic crystal cavities defined by an effective Aubry-André-Harper bichromatic potential
No full textWe report on the realization of high-Q/V
photonic crystal
cavities in
thin silicon
membranes, with resonances around 1.55 μm wavelength. The cavity designs are based
on a recently proposed photonic
crystal implementation of the Aubry-André-Harper bichromatic potential,
defined from the superposition of two one-dimensional lattices with a non-integer ratio
between their periodicity constants. In photonic crystal nanocavities, this confinement mechanism
is such that optimized figures of merit can be straightforwardly achieved, in particular
an ultra-high-Q factor and diffraction-limited mode volume. Several silicon membrane photonic crystal nanocavities
have been realized with measured
Q-factors in the 1 × 106 range, as evidenced by resonant scattering. The
generality of the proposed designs and their easy implementation and scalability make
these results particularly interesting for realizing highly performing photonic nanocavities on
different material
platforms and operational wavelengths
Optimizing polarization-diversity couplers for Si-photonics: reaching the −1dB coupling efficiency threshold
No full textPolarization-diversity couplers are low-cost industrially-scalable passive devices that can couple light of unknown polarization from a telecom fiber-mode to a pair of TE-polarized wave-guided modes in the Silicon-on-Insulator platform. These couplers offer significantly more relaxed alignment tolerances than edge-coupling schemes, which is advantageous for commercial fiber-packaging of Si-photonic circuits. However, until now, polarization-diversity couplers have not offered sufficient coupling efficiency to motivate serious commercial consideration. Using 3D finite difference time domain calculations for device optimization, we identify Silicon-on-Insulator polarization-diversity couplers with 1,550 nm coupling efficiencies of -0.95 dB and -1.9 dB, for designs with and without bottom-reflector elements, respectively. These designs offer a significant improvement over state-of-the-art performance, and effectively bridge the "performance gap" between polarization-diversity couplers and 1D-grating couplers. Our best polarization-diversity coupler design goes beyond the -1dB efficiency limit that is typically accepted as the minimum needed for industrial adoption of coupler devices in the telecoms market
From statistical inference to a differential learning rule for stochastic neural networks
No full textStochastic neural networks are a prototypical computational device able to build a probabilistic representation of an ensemble of external stimuli. Building on the relationship between inference and learning, we derive a synaptic plasticity rule that relies only on delayed activity correlations, and that shows a number of remarkable features. Our delayed-correlations matching (DCM) rule satisfies some basic requirements for biological feasibility: finite and noisy afferent signals, Dale's principle and asymmetry of synaptic connections, locality of the weight update computations. Nevertheless, the DCM rule is capable of storing a large, extensive number of patterns as attractors in a stochastic recurrent neural network, under general scenarios without requiring any modification: it can deal with correlated patterns, a broad range of architectures (with or without hidden neuronal states), one-shot learning with the palimpsest property, all the while avoiding the proliferation of spurious attractors. When hidden units are present, our learning rule can be employed to construct Boltzmann machine-like generative models, exploiting the addition of hidden neurons in feature extraction and classification tasks
Optimal condition to probe strong coupling of two-dimensional excitons and zero-dimensional cavity modes
No full textThe light-matter interaction associated with a two-dimensional excitonic transition coupled to a zero-dimensional photonic cavity is fundamentally different from cavity-coupled localized excitations in quantum dots or color centers, which have negligible spatial extent compared to the cavity-confined mode profile. We provide a succinct expression for calculating the light-matter interaction of a two-dimensional optical transition coupled to a zero-dimensional confined cavity mode. From this expression, we found there is an optimal spatial extent of the excitonic transition that maximizes such an interaction strength due to the competition between minimizing the excitonic envelope function area and maximizing the total integrated field. We also found that at near zero exciton-cavity detuning, the direct transmission efficiency of a waveguide-integrated cavity can be severely suppressed, which suggests performing experiments using a side-coupled cavity
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