Data-Driven Shape Analysis and Processing

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis, through reviewing the literature and relating the existing works with both qualitative and numerical comparisons. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.Comment: 10 pages, 19 figure

Pump-to-signal transfer of low-frequency intensity modulation in fiber optical parametric amplifiers

This paper describes the theoretical and experimental investigation of the transfer of low-frequency intensity modulation (IM) from pump to signal in fiber optical parametric amplifiers (OPAs). It is first established that low-frequency IM of the pump remains unchanged over the length of the amplifier in spite of the presence of parametric gain. The pump-power dependence of the OPA gain is then used to calculate the instantaneous effect of pump IM on the signal and idler output powers. These calculations are performed for both one- and two-pump OPAs. The main predictions are that 1) the ratio ρ of the signal intensity modulation depth to that of the pump varies across the OPA gain spectrum and 2) for a 20-dB gain, ρ can exceed 10 at some wavelengths, which indicates that this effect can be detrimental. Experiments have been performed to verify these predictions. Using sinusoidal IM of the pump, the resulting amplified signal IM was measured, and the experimental results were found to be in good agreement with the theoretical predictions. © 2005 IEEE.published_or_final_versio

Transmission of optical communication signals by distributed parametric amplification

We have demonstrated, for the first time to our knowledge, distributed parametric amplification, i.e. amplification of 10-Gb/s communication signals along a 75-km transmission fiber by using a co-propagating pump with only 66.5 mW of power.published_or_final_versio

Recent advances in the design and implementation of practical fiber optical parametric amplifiers

Conference on Optoelectronic and Microelectronic Materials and Devices, Brisbane, Australia, 8-10 December 2004Fiber optical parametric amplifiers (OPAs) are based on the third-order nonlinear susceptibility of glass fibers. If two strong pumps and a weak signal are fed into a fiber, an idler is generated. Signal and idler can grow together if pump power is high enough, and phase matching occurs. In recent years, impressive performance has been demonstrated in several respects: 1) Gain in excess of 60 dB has been obtained; 2) fiber OPAs can exhibit a large variety of gain spectra: a gain bandwidth of 400 nm has been demonstrated; tunable narrowband gain regions can also be generated; 3) Noise figure of 3.7 dB, limited by other third-order nonlinear process; 4) Polarization-insensitive operation in both one-pump and two-pump configurations; 5) The presence of the idler can be used for wavelength conversion. Also, the spectrum of the idler is inverted with respect to that of the signal; thus by placing an OPA in the middle of a fiber span one can realize mid-span spectral inversion (MSSI) which counteracts the effect of fiber dispersion and some nonlinear effects. Besides using fiber OPA in continuous-wave regime as in typical systems, pulsed-pump has also been demonstrated to achieve larger bandwidth and higher peak gain by combining with optical filtering technique. Furthermore, by modulating the pump it is possible to modulate signal and/or idler at the output. This can be used to implement a variety of signal processing functions, including: fast signal switching; demultiplexing of time-division-multiplexed signals; retiming and reshaping of waveforms; optical sampling. A number of challenges must be overcome in order for fiber OPAs to be useful in communication applications. In multi-wavelength systems, these are: four-wave mixing, cross-phase modulation; and cross-gain modulation between signals. Furthermore, the pump-to-signal relative intensity noise (RIN) transfer and frequency/phase modulation (FM/PM) to signal intensity conversion are also potential challenges for practical fiber OPAs. © 2005 IEEE.published_or_final_versio

Learning Material-Aware Local Descriptors for 3D Shapes

Material understanding is critical for design, geometric modeling, and analysis of functional objects. We enable material-aware 3D shape analysis by employing a projective convolutional neural network architecture to learn material- aware descriptors from view-based representations of 3D points for point-wise material classification or material- aware retrieval. Unfortunately, only a small fraction of shapes in 3D repositories are labeled with physical mate- rials, posing a challenge for learning methods. To address this challenge, we crowdsource a dataset of 3080 3D shapes with part-wise material labels. We focus on furniture models which exhibit interesting structure and material variabil- ity. In addition, we also contribute a high-quality expert- labeled benchmark of 115 shapes from Herman-Miller and IKEA for evaluation. We further apply a mesh-aware con- ditional random field, which incorporates rotational and reflective symmetries, to smooth our local material predic- tions across neighboring surface patches. We demonstrate the effectiveness of our learned descriptors for automatic texturing, material-aware retrieval, and physical simulation. The dataset and code will be publicly available.Comment: 3DV 201

Biotechnologies for Marine Oil Spill Cleanup : Indissoluble Ties with Microorganisms

The ubiquitous exploitation of petroleum hydrocarbons (HCs) has been accompanied by accidental spills and chronic pollution in marine ecosystems, including the deep ocean. Physicochemical technologies are available for oil spill cleanup, but HCs must ultimately be mineralized by microorganisms. How environmental factors drive the assembly and activity of HC-degrading microbial communities remains unknown, limiting our capacity to integrate microorganism-based cleanup strategies with current physicochemical remediation technologies. In this review, we summarize recent findings about microbial physiology, metabolism and ecology and describe how microbes can be exploited to create improved biotechnological solutions to clean up marine surface and deep waters, sediments and beaches. Cleaning up oil spills in marine environments ultimately relies on microbial metabolism of HC, which complements the current chemicophysical techniques used in emergency response.Consolidated biotechnologies include microbial communities biostimulation, biosurfactant supplementation and bioaugmentation HC-degrading microbial cells.The effectiveness of biotechnologies is limited by our understanding of the microbial ecology of polluted marine systems. We lack knowledge on how environmental factors, such as hydrostatic pressure, temperature and dispersant toxicity, affect microbial successions.The recent availability of meta-omics data and the improved understanding of microbial metabolism are leading to novel biotechnologies for marine oil spill cleanup, such as slow-release particles for efficient biostimulation and bioelectrochemical approaches for sediment cleanup

Comparative Chemical Profiling and Antimicrobial/Anticancer Evaluation of Extracts from Farmed versus Wild Agelas oroides and Sarcotragus foetidus Sponges

This study was implemented in the framework of the research project SPINAQUA (Grant No 239) funded by the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Technology (GSRT) under the “1st call for H.F.R.I. Research Projects for the support of Post-doctoral Researchers”. This publication is based upon work from COST Action CA18238 (Ocean4Biotech), supported by COST (European Cooperation in Science and Technology) program, which provided Short Term Scientific Mission (STSM) grant support to D.V.-M. to perform the experimental work at NOVA-FCT. C.M.P.R. is financially supported by La Caixa Foundation (Grant No LCF/PR/HR21/52410028). Publisher Copyright: © 2023 by the authors.Marine sponges are highly efficient in removing organic pollutants and their cultivation, adjacent to fish farms, is increasingly considered as a strategy for improving seawater quality. Moreover, these invertebrates produce a plethora of bioactive metabolites, which could translate into an extra profit for the aquaculture sector. Here, we investigated the chemical profile and bioactivity of two Mediterranean species (i.e., Agelas oroides and Sarcotragus foetidus) and we assessed whether cultivated sponges differed substantially from their wild counterparts. Metabolomic analysis of crude sponge extracts revealed species-specific chemical patterns, with A. oroides and S. foetidus dominated by alkaloids and lipids, respectively. More importantly, farmed and wild explants of each species demonstrated similar chemical fingerprints, with the majority of the metabolites showing modest differences on a sponge mass-normalized basis. Furthermore, farmed sponge extracts presented similar or slightly lower antibacterial activity against methicillin-resistant Staphylococcus aureus, compared to the extracts resulting from wild sponges. Anticancer assays against human colorectal carcinoma cells (HCT-116) revealed marginally active extracts from both wild and farmed S. foetidus populations. Our study highlights that, besides mitigating organic pollution in fish aquaculture, sponge farming can serve as a valuable resource of biomolecules, with promising potential in pharmaceutical and biomedical applications.publishersversionpublishe

3D visualization processes for recreating and studying organismal form

The study of biological form is a vital goal of evolutionary biology and functional morphology. We review an emerging set of methods that allow scientists to create and study accurate 3D models of living organisms and animate those models for biomechanical and fluid dynamic analyses. The methods for creating such models include 3D photogrammetry, laser and CT-scanning, and 3D software. New multi-camera devices can be used to create accurate 3D models of living animals in the wild and captivity. New websites and virtual reality/augmented reality devices now enable the visualization and sharing of these data. We provide examples of these approaches for animals ranging from large whales to lizards and show applications for several areas: Natural history collections; body condition/scaling, bioinspired robotics, computational fluids dynamics (CFD), machine learning, and education. We provide two data sets to demonstrate the efficacy of CFD and machine learning approaches and conclude with a prospectus