A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction

Abstract. In this paper, we present a stochastic algorithm by effective Markov chain Monte Carlo (MCMC) for segmenting and reconstructing 3D scenes. The objective is to segment a range image and its associated reflectance map into a number of surfaces which fit to various 3D surface models and have homogeneous reflectance (material) properties. In comparison to previous work on range image segmentation, the paper makes the following contributions. Firstly, it is aimed at generic natural scenes, indoor and outdoor, which are often much complexer than most of the existing experiments in the “polyhedra world”. Natural scenes require the algorithm to automatically deal with multiple types (families) of surface models which compete to explain the data. Secondly, it integrates the range image with the reflectance map. The latter provides material properties and is especially useful for surface of high specularity, such as glass, metal, ceramics. Thirdly, the algorithm is designed by reversible jump and diffusion Markov chain dynamics and thus achieves globally optimal solutions under the Bayesian statistical framework. Thus it realizes the cue integration and multiple model switching. Fourthly, it adopts two techniques to improve the speed of the Markov chain search: One is a coarse-to-fine strategy and the other are data driven techniques such as edge detection and clustering. The data driven methods provide important information for narrowing the search spaces in a probabilistic fashion. We apply the algorithm to two data sets and the experiments demonstrate robust and satisfactory results on both. Based on the segmentation results, we extend the reconstruction of surfaces behind occlusions to fill in the occluded parts.

Review of recent experimental progresses in Foundations of Quantum Mechanics and Quantum Information obtained in Parametric Down Conversion Experiments at IENGF

We review some recent experimental progresses concerning Foundations of Quantum Mechanics and Quantum Information obtained in Quantum Optics Laboratory "Carlo Novero" at IENGF. More in details, after a short presentation of our polarization entangled photons source (based on precise superposition of two Type I PDC emission) and of the results obtained with it, we describe an innovative double slit experiment where two degenerate photons produced by PDC are sent each to a specific slit. Beyond representing an interesting example of relation between visibility of interference and "welcher weg" knowledge, this configuration has been suggested for testing de Broglie-Bohm theory against Standard Quantum Mechanics. Our results perfectly fit SQM results, but disagree with dBB predictions. Then, we discuss a recent experiment addressed to clarify the issue of which wave-particle observables are really to be considered when discussing wave particle duality. This experiments realises the Agarwal et al. theoretical proposal, overcoming limitations of a former experiment. Finally, we hint to the realization of a high-intensity high-spectral-selected PDC source to be used for quantum information studies

Ethnomedicinal plant knowledge and practice of the Oromo ethnic group in southwestern Ethiopia

An ethnomedicinal study was conducted to document the indigenous medicinal plant knowledge and use by traditional healers in southwestern Ethiopia from December 2005 to November 2006. Data were collected from 45 randomly selected traditional healers using semi-structured interviews and observations. Sixty-seven ethnomedicinal plant species used by traditional healers to manage 51 different human ailments were identified and documented. Healers' indigenous knowledge was positively correlated with their reported age but not with their educational level. High degree of consensus was observed among traditional healers in treating tumor (locally known as Tanacha), rabies (Dhukuba Seree) and insect bite (Hadhaa). The use of more than one species was significantly cited for remedy preparations. The reported abundance of the ethnomedicinal plant species varied significantly with respect to the presence of multiple uses of the reported species. Our results showed that ethnomedicinal plant species used by healers are under serious threat due to several factors, which indicates the need for urgent attention towards their conservation and sustainable utilization

A framework to assess forest-agricultural landscape management for socioecological well-being outcomes

Global demand for agricultural products continues to grow. However, efforts to boost productivity exacerbate existing pressures on nature, both on farms and in the wider landscape. There is widespread appreciation of the critical need to achieve balance between biodiversity and human well-being in rural tropical crop production landscapes, that are essential for livelihoods and food security. There is limited empirical evidence of the interrelationships between natural capital, the benefits and costs of nature and its management, and food security in agricultural landscapes. Agroforestry practices are frequently framed as win-win solutions to reconcile the provision of ecosystem services important to farmers (i.e., maintaining soil quality, supporting pollinator, and pest control species) with nature conservation. Yet, underlying trade-offs (including ecosystem disservices linked to pest species or human-wildlife conflicts) and synergies (e.g., impact of ecosystem service provision on human well-being) are seldom analysed together at the landscape scale. Here, we propose a systems model framework to analyse the complex pathways, with which natural capital on and around farms interacts with human well-being, in a spatially explicit manner. To illustrate the potential application of the framework, we apply it to a biodiversity and well-being priority landscape in the Southern Agricultural Growth Corridor of Tanzania, a public-private partnership for increasing production of cash and food crops. Our framework integrates three main dimensions: biodiversity (using tree cover and wildlife as key indicators), food security through crop yield and crop health, and climate change adaptation through microclimate buffering of trees. The system model can be applied to analyse forest-agricultural landscapes as socio-ecological systems that retain the capacity to adapt in the face of change in ways that continue to support human well-being. It is based on metrics and pathways that can be quantified and parameterised, providing a tool for monitoring multiple outcomes from management of forest-agricultural landscapes. This bottom-up approach shifts emphasis from global prioritisation and optimisation modelling frameworks, based on biophysical properties, to local socio-economic contexts relevant in biodiversity-food production interactions across large parts of the rural tropics.Agrisys Tanzania project was funded through BBSRC Global Challenges Research Fund.https://www.frontiersin.org/journals/forests-and-global-changedm2022Zoology and Entomolog

Dark energy survey year 1 results: calibration of redMaGiC redshift distributions in DES and SDSS from cross-correlations

FINEP - FINANCIADORA DE ESTUDOS E PROJETOSFAPERJ - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIROCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMCTIC - MINISTÉRIO DA CIÊNCIA, TECNOLOGIA, INOVAÇÕES E COMUNICAÇÕESWe present calibrations of the redshift distributions of redMaGiC galaxies in the Dark Energy Survey Year 1 (DES Y1) and Sloan Digital Sky Survey (SDSS) DR8 data. These results determine the priors of the redshift distribution of redMaGiC galaxies, which were used for galaxy clustering measurements and as lenses for galaxy-galaxy lensing measurements in DES Y1 cosmological analyses. We empirically determine the bias in redMaGiC photometric redshift estimates using angular cross-correlations with Baryon Oscillation Spectroscopic Survey (BOSS) galaxies. For DES, we calibrate a single-parameter redshift bias in three photometric redshift bins: z is an element of [0.15, 0.3], [0.3,0.45], and [0.45,0.6]. Our best-fit results in each bin give photometric redshift biases of vertical bar Delta z vertical bar < 0.01. To further test the redMaGiC algorithm, we apply our calibration procedure to SDSS redMaGiC galaxies, where the statistical precision of the cross-correlation measurement is much higher due to a greater overlap with BOSS galaxies. For SDSS, we also find best-fit results of vertical bar Delta z vertical bar < 0.01. We compare our results to other analyses of redMaGiC photometric redshifts.481224272443FINEP - FINANCIADORA DE ESTUDOS E PROJETOSFAPERJ - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIROCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMCTIC - MINISTÉRIO DA CIÊNCIA, TECNOLOGIA, INOVAÇÕES E COMUNICAÇÕESFINEP - FINANCIADORA DE ESTUDOS E PROJETOSFAPERJ - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIROCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMCTIC - MINISTÉRIO DA CIÊNCIA, TECNOLOGIA, INOVAÇÕES E COMUNICAÇÕESSem informaçãoSem informaçãoSem informaçãoSem informaçãoAgências de fomento estrangeiras apoiaram essa pesquisa, mais informações acesse artig

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

Particularistic and system trust in family businesses: the role of family influence

Research on how trust develops and why it matters in family businesses is in development. Our study investigates the emergence and the evolution of trust in family business leaders. Drawing on the New Systems Theory, we also examine the impact of family influence on trust. Multiple semi‐structured interviews were performed in three Chinese family businesses. Results suggest that relationship‐based particularistic trust prevails at the start‐up stage because of the void of governance mechanisms. As businesses grow, particularistic trust gradually gives way to institution‐based system trust. Evidence further indicates high family influence catalyzes particularistic trust initially and restricts system trust subsequently