Blind spatial unmixing of multispectral images: New methods combining sparse component analysis,clustering and non-negativity constraints

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. Traditional classification techniques assign only one class (e.g., water, soil, grass) to each pixel of remote sensing images. However, the area covered by one pixel contains more than one surface component and results in the mixture of these surface components. In such situations, classical classification is not acceptable for many major applications, such as environmental monitoring, agriculture, mineral exploration and mining, etc. Most methods proposed for treating this problem have been developed for hyperspectral images. On the contrary, there are very few automatic techniques suited to multispectral images. In this paper, we propose new unsupervised spatial methods (called 2D-Corr-NLS and 2D-Corr-NMF) in order to unmix each pixel of a multispectral image for better recognizing the surface components constituting the observed scene. These methods are related to the blind source separation (BSS) problem, and are based on sparse component analysis (SCA), clustering and non-negativity constraints. Our approach consists in first identifying the mixing matrix involved in this BSS problem, by using the first stage of a spatial correlation-based SCA method with very limited source sparsity constraints, combined with clustering. Non-negative least squares (NLS) or non-negative matrix factorization (NMF) methods are then used to extract spatial sources. An important advantage of our proposed methods is their applicability to the possibly globally underdetermined, but locally (over)determined BSS model in multispectral remote sensing images. Experiments based on realistic synthetic mixtures and real multispectral images collected by the Landsat ETM+ and the Formosat-2 sensors are performed to evaluate the performance of the proposed approach. We also show that our methods significantly outperform the sequential maximum angle convex cone (SMACC) method.     

Growth of Yb-doped YLiF4 laser crystal by the Czochralski method. Attempt of Yb energy level assignment and estimation of the laser potentiality

YLiF₄ (YLF) single crystals undoped and Yb³⁺-doped with different concentrations were grown by the Czochralski technique under CF₄ atmosphere. Detailed analysis of Yb³⁺-doped YLF spectroscopy were made to contribute to the determination of energy levels in this host. We are dealing with temperature and concentration dependences of both π and σ polarizations of the infrared (IR) absorption and emission spectra. Raman spectra were also used to give an attempt of interpretation of electronic and vibronic levels. The radiative energy transfer (self-trapping) and strong phonon–electron coupling make the assignment of Yb³⁺ energy levels difficult. Evaluation of the laser potentiality of this fluoride host is also presented.     

Czochralski growth of Yb doped oxyapatite for high power laser application

Ca₈(La,Yb)₂(PO₄)₆O₂ (Yb:CLPA) single crystals with the apatite-type structure could be grown from the melt using the Czochralski method. Grown crystal was 18 mm in diameter and 110 mm in length. It is transparent with slightly blue color. Neither visible inclusion nor crack was observed. Thermal conductivity of Yb:CLPA was calculated from the values of thermal diffusivity, heat capacity measurement and density. Luminescent characterization was carried out from the results of emission, absorption and Raman spectrum.     

Cereal‐based fermented foods in developing countries: ancient foods for modern research

Cereal‐based fermented foods are major contributors to energy intake in developing countries (DC). Their microbiota is dominated by lactic acid bacteria and has been extensively investigated. Diversity studies have been facilitated by molecular methods enabling genotyping of isolates; the rapid development of ‘omics’ approaches should facilitate more comprehensive studies to describe the relation between microbial diversity, cell physiology and product characteristics. Also, the link between the food microbiota and health benefits, in particular in nutrition, should be investigated. There is a need to encourage researches in the field of DC cereal‐based foods in direction of more mechanistic approaches.     

Automatic speech recognition system for Tunisian dialect

Although Modern Standard Arabic is taught in schools and used in written communication and TV/radio broadcasts, all informal communication is typically carried out in dialectal Arabic. In this work, we focus on the design of speech tools and resources required for the development of an Automatic Speech Recognition system for the Tunisian dialect. The development of such a system faces the challenges of the lack of annotated resources and tools, apart from the lack of standardization at all linguistic levels (phonological, morphological, syntactic and lexical) together with the mispronunciation dictionary needed for ASR development. In this paper, we present a historical overview of the Tunisian dialect and its linguistic characteristics. We also describe and evaluate our rule-based phonetic tool. Next, we go deeper into the details of Tunisian dialect corpus creation. This corpus is finally approved and used to build the first ASR system for Tunisian dialect with a Word Error Rate of 22.6%.     

Discovery of Heterocyclic Nonacetamide Synaptic Vesicle Protein 2A (SV2A) Ligands with Single‐Digit Nanomolar Potency: Opening Avenues towards the First SV2A Positron Emission Tomography (PET) Ligands

The role of the synaptic vesicle protein 2A (SV2A) protein, target of the antiepileptic drug levetiracetam, is still mostly unknown. Considering its potential to provide in vivo functional insights into the role of SV2A in epileptic patients, the development of an SV2A positron emission tomography (PET) tracer has been undertaken. Using a 3D pharmacophore model based on close analogues of levetiracetam, we report the rationale design of three heterocyclic non‐acetamide lead compounds, UCB‐A, UCB‐H and UCB‐J, the first single‐digit nanomolar SV2A ligands with suitable properties for development as PET tracers.     

Production planning in automotive powertrain plants: a case study

Based on a real case study from the automotive industry, this paper deals with production planning in powertrain plants. We present an overview of the production planning process and propose a mixed integer linear programme to determine the production quantities of each product over a planning horizon of several days. Then, using real data of an engine assembly line, we simulate the performance obtained through the proposed model within a rolling horizon planning process. We perform multiple tests in order to evaluate the impact of two parameters involved in this process: planning frequency and frozen horizon length. Furthermore, in order to illustrate the value of improving coordination between engine plants and their customers, we evaluate the impact of the quality of demand information (orders and forecasts). We analyse the simulation results and provide insights and recommendations in order to achieve a good trade-off between service level, inventory, and planning stability.     

A GIS-based Land Cover Classification Approach Suitable for Fine‐scale Urban Water Management

Water Resources Management - In the context of climate stress, urbanisation and population growth, design and planning tools that assist in decentralised and environmental infrastructural planning...     

Silicene Nanoribbons on an Insulating Thin Film

Silicene, a new 2D material has attracted intense research because of the ubiquitous use of silicon in modern technology. However, producing free-standing silicene has proved to be a huge challenge. Until now, silicene could be synthesized only on metal surfaces where it naturally forms strong interactions with the metal substrate that modify its electronic properties. Here, the authors report the first experimental evidence of silicene nanoribbons on an insulating NaCl thin film. This work represents a major breakthrough, for the study of the intrinsic properties of silicene, and by extension to other 2D materials that have so far only been grown on metal surfaces.     

Decidability of Equivalence of Symbolic Derivations

We give in this paper an alternative, and we believe simpler, proof of a deep result by Mathieu Baudet, namely that the equivalence of symbolic constraints is decidable for deduction systems on a finite signature modulo a subterm convergent equational theory.