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Density measurement of OH radicals in non-thermal plasmas by laser induced fluorescence and time-resolved absorption spectroscopy
No full textIn the present thesis work, we have developed two different experimental setups for the optical detection of the OH radical in discharges at atmospheric pressure. The first one allows us to improve the time-resolved broad-band absorption spectroscopy. The main advances of the new set up are a better collimation of the UV light and a novel gating scheme. They both significantly reduce the interference of the plasma-induced emission on the absorption measurement. The second setup is dedicated to an improved laser induced fluorescence experiment, which takes advantage of a novel multi-transition excitation scheme. This permits the simultaneous measurements of both the OH density and its ground state rotational temperature. In addition, we have developed a new rate-equation model to rationalize LIF spectra, by taking into account the electronic quenching, the vibrational and rotational energy transfers, and the spatial profile of the laser beam. Finally, the electrical power dissipated in the discharge was accurately measured
L'uomo al muro
No full textLa visione e la rappresentazione della guerra nei racconti compresi nel volume "I ventitré giorni della città di Alba" di Beppe Fenoglio
Il fatto colposo: la crisi del modello nomologico, l'aspettativa di diligenza e la condotta penalmente rilevante. Uno studio di diritto comparato sulla definizione della colpa punibile
No full textA quali condizioni é o in base a quali criteri di valutazione é una condotta che offende o che non impedisce la lesione di beni giuridici fondamentali quali la vita e l'integrità fisica della persona può dirsi non soltanto dannosa ma altresì colposa per il diritto penale?
Il lavoro che si presenta prende le mosse da una questione, come si vede, di enorme portata. Essa, in termini dogmatici, porta ad interrogarsi sui caratteri delle categorie concettuali afferenti all'elemento oggettivo del reato colposo (il relativo fatto tipico), sul metodo di concretizzazione del dovere di diligenza (che di tale elemento costituisce il cuore normativo) e sui criteri di giudizio in base ai quali esso può ritenersi inosservato.
Il metodo di indagine prescelto consiste nella comparazione di due esperienze, quella italiana e quella spagnola, omogenee sul piano teorico e cioé accomunate dall'utilizzo del medesimo linguaggio é ma attualmente caratterizzate e quantomeno nella materia in esame é da tendenze evolutive notevolmente differenti anche in ragione della diversa influenza esercitata nei loro confronti dalla dogmatica tedesca. Oltre che sul dibattito teorico sviluppatosi in questa due aree culturali, lo studio si occupa dell'esperienza applicativa maturata in entrambi i Paesi nei settori della responsabilità medica e della prevenzione dei rischi professionali (della salute e della sicurezza nei luoghi di lavoro), contesti nei quali si fa particolarmente evidente l'attuale crisi del cd. modello nomologico, cioé del metodo di spiegazione causale dâ'impronta neopositivista e del criterio ricostruttivo delle norme cautelari fondati su leggi scientifiche. In entrambi i casi, in entrambe le dimensioni del giudizio sulla tipicità del fatto, l'offuscamento dell'immagine di scienza su cui venne edificata la teoria del reato colposo nel corso del Novecento ha già indotto il diritto penale contemporaneo a rivalutare il proprio peculiare approccio argomentativo e valutativo abbandonando lo schema inferenziale dimostrativo nomologico-deduttivo ed interrogandosi sul metodo attraverso cui definire i concreti margini del rischio consentito.
E' in questa direzione, quella di una rinnovata riflessione sui limiti della libertà di azione di ciascuno nella vita di relazione di fronte alla minaccia della sanzione penale, che ci si muove nelle pagine del presente lavor
Synthesis and Characterization of Multifunctional Polymer-Derived SiOCN
No full textThis PhD thesis focuses on the synthesis and characterization of multifunctional polymer-derived SiOCN ceramics. The main objective is to synthesize N-doped silicon oxycarbides (SiOCs), to characterize their structure and their properties (mainly electrical conductivity) and correlate them with the presence of N in the structure. We also aim to understand how the architecture of the starting polymer can influence the retention of N into the SiOC structure. First, N-doped SiOC polymer precursors were synthesized via hydrosilylation reaction between Si-H groups present in a commercial polysiloxane (PHMS) and –CH=CH2 groups of three different commercial N-containing compounds. The structural characterization of as-synthesized preceramic polymer precursor was investigated by FT-IR and NMR. Thermal degradation was studied by TGA. The results show that the architecture of the polymer precursors plays an important role on the pyrolythic transformation. Then, SiOCN ceramics were obtained by pyrolysis of the as-synthesized polymer precursors in nitrogen atmosphere at various temperatures for 1h using a tubular furnace. Subsequently, high temperature structural evolution was studied using combined techniques such as XRD, FT-IR, NMR, Elemental analysis, and XPS. The obtained results show that the type of N-containing compounds impacts on the crystallization behavior of the final ceramics. Elemental analysis clearly indicates that N is present in the SiOC matrix and the degree of N retention after pyrolysis is related to the type of N-containing starting compounds. XPS data indicate that N-C bonds are present in the SiOC ceramic samples even if only N-Si bonds exist in the starting N-containing precursor. However, a larger fraction of N-C bonds is present in the final SiOCN ceramic when N atoms form bonds with sp2 carbon atoms in the pre-ceramic polymer. We have also studied electrical and optical properties of the SiOCNs. Electrical conductivity of the powdered ceramic samples was determined using powder-solution-composite technique. The results show an increase in room temperature AC conductivity of three orders of magnitude, from ≈10-5 (S/cm) to ≈10-2 (S/cm), with increasing pyrolysis temperature from 1000 to 1400 °C. Furthermore, the electrical conductivity of the SiOCN ceramic derived from N-C bond bearing precursor is three to five times higher than that of the sample derived from N-Si containing precursor at each pyrolysis temperature. The combined structural study by Raman spectroscopy and chemical analysis suggests that the increase of electrical conductivity with the pyrolysis temperature is due to the sp3-to-sp2 transition of the amorphous carbon phase. The higher conductivity of the amine-derived SiOCN is also discussed considering features like the volume % of the free-carbon phase and its possible N-doping. Fluorescence of the SiOCN samples treated at low temperatures, 400 and 600 °C, has been studied. The spectra show that the heated precursors fluoresce in the visible range with a dominant blue emission. Since the non-heated polymer precursors do not fluoresce, emitting centers must be formed during the polymer-to-ceramic transformation and associated with the structural changes. The origin of the luminescence could be originated from defects related to C, O and/or Si.
Finally, we investigated the gas sensing behavior of the SiOCNs pyrolyzed at low and high temperatures. Regarding the electrical gas sensing of the SiOCN ceramics pyrolyzed at 1400 °C, the response to two target gases NO2 and H2 was tested by in situ DC conductance measurements at operating temperatures from 200 to 550 °C. The SiOCN ceramics are sensitive to NO2 at temperatures below 400 °C and to H2 at temperatures above 400 °C. In addition, the response observed for the studied SiOCN ceramics is higher than that reported in the previous studies for SiOC ceramic aerogels. With regard to the optical gas sensing of the SiOCNs obtained from the heat treatment of the polymer precursors at 400 and 600 °C, fluorescence spectra in the presence of organic vapors such as acetone and hexane were recorded. The results show that these tested vapors quench the fluorescence of the studied SiOCN. In conclusion, the SiOCN ceramics can be promising materials for the gas sensing application
Comprehensive Mapping of Volatile Organic Compounds in Fruits
No full textVolatile organic compounds (VOCs) are the key aroma producers in fruits and sensory quality of fruits is widely determined by qualitative and quantitative composition of VOCs. The aroma of grape is a complex of hundreds of VOCs belonging to different chemical classes like alcohols, esters, acids, terpenes, aldehydes, furanones, pyrazines, isoprenoids and many more. VOCs play important role as they determine the flavor of grapes and wine made from it. The objective of this thesis is to study of VOCs through development of different mass spectrometry based analytical methodologies and its applications for the comprehensive investigation and construction of database of the VOCs in grapes. First part of the study was dedicated to generation of the comprehensive database of grape VOCs through the screening of multiple grape varieties (n=124) representing different species, color and origin. The experiment was carried out using headspace solid-phase microextraction (HS-SPME) and gas chromatography mass spectrometry (GC-MS) based approach and according to metabolomics protocols. A customized dataset of reference standards (>350) was generated and, an automated pipeline for data analysis was created in collaboration with data management group of the institute. The results showed annotation of “level 1”of 117 VOCs in grape. The established database in this experiment will represent the significant portion of the future Grape Metabolome database. The second part of the study was dedicated to study the differential behavior of volatile organic compounds and their glycosylated precursors qualitatively and semi quantitatively. Volatile secondary metabolites also exist in the form of nonvolatile and odorless glycosylated precursors in grape and studies have confirmed that concentration of these precursors can be much higher than its free counterparts. The elevated concentrations of volatiles in glycosylated forms can significantly affect the wine aroma because of possible chemical modifications throughout the process of fermentation and wine ageing. In addition, the investigation of the biosynthesis and accumulation of VOCs in the fruit tissues requires the consideration of both the free and bound forms. To study the phenomenon an experiment was carried using solid phase extraction (SPE) of the free and glycosylated precursors; with enzymatic hydrolysis aglycone part of the precursors was released followed by subsequent GC-MS analysis. Over 10 different selected grape varieties were analyzed. Sixty-six significant different aroma compounds in grapes (pre and post hydrolysis) were identified. Identification was done based on several parameters like retention time, retention index and MS spectral database. The multivariate statistical analysis by two-way hierarchical clustering with heat map visualization showed distribution of the compounds within different varieties before and after hydrolysis. In the third part of the study, we performed experiments dedicated to training and applications of atmospheric pressure gas chromatography mass spectrometry (APGC-MS). The experiment was carried out at the Department of Biological Sciences, University of North Texas, under the supervision of Prof. Vladimir Shulaev. We have established the metabolomics protocol for the analysis of fruit volatiles using APGC-MS with an optimized GC and MS conditions and created novel library of the fruit volatile compounds using APGC-MS system. Six different grape varieties were analyzed as a case study and experimental results showed APGC-MS as a valuable solution for metabolomics analysis. The data processing and statistical evaluation was done using XCMS and progenesis QI© software. Moreover, observations based on injections of pure reference standards showed high abundance of molecular ions with minimal fragmentation at low collision energy that is typically missing in traditional vacuum source GC-MS. Moreover, the use of elevated collision energy data resulted in a spectrum similar to the traditional EI data
Query Answering over Contextualized RDF/OWL Knowledge with Expressive Bridge Rules: Decidable classes
No full textIn this thesis, we study the problem of reasoning and query answering over contextualized knowledge in quad format augmented with expressive forall-existential bridge rules. Such bridge rules contain conjunctions, existentially
quantified variables in the head, and are strictly more expressive than the bridge rules considered so far in similar setting. A set of quads together with forall-existential bridge rules is called a quad-system. We show that query answering over quad-systems in their unrestricted form is undecidable, in general. We propose various subclasses of quad-systems, for which query answering is decidable. Context-acyclic quad-systems do not allow the context dependency graph of the bridge rules to have cycles passing through triple-generating (value-generating) contexts, and hence guarantees the chase (deductive closure) to be finite. Csafe, msafe and safe classes of quad-systems restricts the structure of descendance graph of Skolem blank nodes generated during chase process to be directed acyclic graphs (DAGs) of bounded depth, and hence has finite chases. RR and restricted RR quad-systems do not allow for the creation of Skolem blank nodes, and hence restrict the chase to be of polynomial size. Besides the undecidability result of unrestricted quad-systems, tight complexity bounds has been established for each of the classes we have introduced. We then compare the problems, (resp. classes,) we address (resp. derive) in this thesis, for quad-systems with analogous problems (resp. classes) in the realm of forall-existential rules. We show that the query answering problem over quad-systems is polynomially equivalent to the query answering problem over ternary forall-existential rules, and
the technique of safety, we propose, is strictly more expressive than existing well known techniques such joint acyclicity and model maithful acyclicity, used for decidability guarantees, in the realm of forall-existential rules
Alginate-based Hydrogels for Central Nervous System Tissue Regeneration
No full textAs the central nervous system shows very little capability for self-repair following injury, regenerative medicine approaches are increasingly interested in the use of stem cells for cell replacement strategies. Biomaterials are an interesting tool to carry out this type of therapies. They allow three-dimensional cultures for stem cells differentiation and are helpful in order to obtain cells at the right developmental stage for transplantation. Moreover, they could help to enhance and control cell survival after transplantation, minimizing cell death. Stroke is a very severe form of brain injury and one of the leading causes of death worldwide, as no effective cures are available. Several studies show that neural stem cells (NSCs) are able to integrate and improve functional recovery once transplanted in stroke animal models. However, the majority of the grafted NSCs die within weeks after transplantation, limiting treatment efficacy. Tissue engineering approaches aim to restore tissue functions combining principles of cell biology and engineering, using designed and tailored three-dimensional biomaterial scaffolds. In this study we tested alginate as candidate biomaterial for neural tissue repair. We studied its ability to support mouse embryonic stem cells (mESCs) neural differentiation in vitro. We evaluated whether changes in its concentration or modifications with extracellular matrix components could influence cell differentiation, analysing the mechanical and physical properties of the generated scaffolds. In the first part, we evaluated the suitability of alginate as a scaffold for three-dimensional cultures able to enhance differentiation of mESCs towards neural lineages. We tested whether encapsulation of mESCs within alginate beads could support and/or enhance neural differentiation with respect to two-dimensional cultures. We encapsulated cells in beads of alginate at two different concentrations, with or without modification by fibronectin, RGD peptide or hyaluronic acid. Cells survive and differentiate inside our scaffolds, forming clusters. Gene expression analyses showed that cells grown in alginate scaffolds increase differentiation toward neural lineages with respect to the two dimensional controls. Immunocytochemistry analyses confirmed these results, further showing terminal differentiation of neurons by the expression of synaptic markers. Cells showed also the capability to form networks among themselves and with cells of other clusters. All the scaffolds we prepared resembled brain tissue characteristics, thus we decided to test alginate as potential support for tissue engineering approaches in the injured brain. In the second part of the work we tested alginate as support for NSCs injection in the brain. We evaluated in vivo crosslinking of alginate after injection, and verified inflammation levels due to its presence in mouse brain tissue. Our preliminary studies suggest that alginate polymerizes in vivo, forming a hydrogel, and that it does not elicit any inflammatory response following injection. Our data show that alginate, alone or modified, is a suitable biomaterial to promote in vitro differentiation of pluripotent cells toward neural fates. Moreover, it could be used as injectable hydrogel for brain tissue regeneration. We plan to co-inject alginate with NSCs in stroke mouse models in order to enhance viability and integration of the engrafted cells in the damaged tissue. We plan to study alginate permanence in the brain and NSCs viability, integration and capability to stimulate regeneration after ischemic injury
Essays on Firm Heterogeneity and Export: Productivity, Quality and Access to Finance
No full textThe thesis investigates the relationship between firm heterogeneity and international trade from the perspective of a developing country. The standard heterogeneous firm trade models (Melitz, 2003; Bernard et. al, 2003) have largely focused on differences among firms in terms of an exogenously given productivity which would explain why only some firms self-select into international markets while the others serve the domestic market. Empirical evidences, especially from developing countries, note that firms’ selection into export is also the result of conscious investment decisions by firms that aim to improve their productivity and product attributes with explicit purpose of becoming exporters (Lòpez, 2004). In order to further understand the selection mechanism of developing countries’ firms into international markets, this thesis explores the roles of prices, quality and access to finance differences across firms as additional sources of heterogeneity, as well as their interaction. The thesis is composed of three self-standing but related empirical papers that exploit a unique panel data set that come from the annual Ethiopian Large and Medium Scale Manufacturing Enterprise census, and one concluding chapter with policy implications. The census is run by the Central Statistical Agency of Ethiopia (CSA). Unusual in many firm-level surveys, this data set provides plant-product level information on quantity and value of production and sales in both the domestic and foreign markets. Among other information, the census also collects data on the obstacles that firms face in their activities including financial resources. The richness of the data set allows constructing plant-product-level price and quality index, and firm-level access to finance indicators.
The first chapter investigates the role of price heterogeneity and demand factors in examining the link between export and productivity. One of the well-known empirical regularities in the literature is that, on average, exporters are more “productive” than non-exporters (ISGEP, 2008; Wagner, 2012). Despite this consensus, what the referred productivity really captures remains blurred: since quantity information is rarely available in most data sets, the standard approach is to proxy quantity by firm-level revenues deflated by industry-level price indices. However, this approach ignores within-sector price heterogeneity and, as a result, it confounds physical efficiency (output per unit input) and demand components into the revenue-based productivity estimates (De Loecker, 2011). This bias would be further exacerbated when firms operate in different markets, and thus have different pricing strategies. To the extent that the demand structure is different in domestic and foreign markets, it is reasonable to expect price differences between exporters and non-exporters, not to mention within-sector variations.
Using a rich panel data from Ethiopian manufacturing firms, the first chapter characterizes firms by three distinctive margins that are confounded in revenue productivity: physical productivity, output prices and demand shocks, and examines the relationship between these different sources of competencies of firms, and their separate role in shaping export participation. The main results show that exporters are more productive than non-exporters in both revenue and quantity based productivity measures. However, the productivity gap is larger in revenue productivity. Regarding the decision to export, revenue productivity and price significantly explain probability to export, but physical productivity hardly plays a role. Further evidence shows that price is increasing in revenue productivity and decreasing in physical productivity. On average, exporters charge higher prices than non-exporters. The overall results suggest that revenue productivity overstate the relationship between export and productivity because exporters have favourable demand condition that allows them to charge higher prices than non-exporters. This finding provides a new insight in understanding how export contributes to aggregate productivity growth. To the extent that exporters are more productive than non-exporters, the findings about prices are at odds with the standard firm heterogeneity model of Melitz (2003), where more productive firms have lower marginal costs and thus charge lower prices.
The second chapter addresses this puzzle, further investigating the determinants of firms’ decision to export. To this end, I refer to the analytical framework that extends the standard firm heterogeneity model by introducing quality (e.g., Hallak and Sivadsan, 2013). Recent empirical findings also confirm that exported products feature higher prices than domestic products, and this price difference is ascribed to quality differences (for example see, Iacovone and Javorcik, 2012). Nevertheless, even if prices do correlate with quality, a major limitation of using prices as a proxy for quality lies in the inability to distinguish between quality and cost factors. To address this issue, I follow the recent empirical strategy proposed by Khandelwal (2010) to estimate quality, thus relaxing the assumption product quality is fully captured by its price.
The results show that high-price products are more likely to be exported. However, once price is adjusted for quality difference, products with higher quality-adjusted price are less likely to enter into foreign markets. Jointly these results suggest that the observed price-export relationship reflects quality differences. Furthermore, I find that quality is the most important factor in determining firm export decision; and the effect of firm efficiency on export mainly operates through the quality channel. Based on an analysis of the dynamics of quality and product entry, I find that high-quality products self-select into export. Specifically, the trajectories of exported products show that quality upgrading took place three years prior to export entry. In the run-up phases of export entry, firms also change the composition of their production in favor of future exported varieties. The third chapter, is the result of a joint work with my supervisor Stefano Schiavo, and investigates the mechanisms through which access to bank credit affects firms export. In particular it examines the interplay between financial constraints and product quality in explaining firms’ export behavior using information on a panel of Ethiopian manufacturing firms. Similar to many recent studies, the previous chapter suggests that quality matters a lot for export and, moreover, that firms need to make conscious investment decisions aimed at upgrading their product quality before entering foreign markets. The implication is that, in addition to its direct effect on firms’ ability to pay upfront entry costs, access to finance may affect export decisions through its effect on investment. Since firms in developing countries have typically limited internal revenue and operate in underdeveloped financial markets, financial resources are especially important in shaping the decision to export.
The main results confirm the presence of substantial sunk costs associated with exporting. Despite this, bank finance does not appear to have a strong direct effect on export participation. On the other hand, both present and past product quality is robustly associated with export status, and quality upgrading requires substantial investment. Therefore, bank credit is relevant for export only insofar as it is channeled to the fixed investments required to enhance quality. An important implication of this chapter is that improving financial conditions and access to bank credit can help firms to move from low- to high-quality products, enhance their ability to access foreign markets and therefore improve the overall export performance of the economy. The common message of all the three chapters is that the success of Ethiopian firms in international market is mainly driven by demand factors in which only firms that able to attract demand for their products succeed in foreign markets. However, despite the presumed relevance of firm productivity efficiency to drive export, there is no strong evidence that this apply for Ethiopian firms. Further analyses of the demand factors unveil the crucial role of product quality upgrading in determining firms’ entry into export markets. These findings sheds some light on the sources of the productivity difference between exporters and non-exporters that have been found in the literature, including studies focusing on African firms (for example, Van Biesebroeck 2005, and Bigsten and Gebreeyesus 2009). Furthermore, it confirms the general importance of satisfying foreign market quality standards for firms in developing countries to succeed in international markets (Chen et.al., 2008). The evidence suggests that export promoting policies that exclusively focus on achieving quantitative targets, such as productivity, as a means to increase competitiveness in international markets should be revisited: especially for developing countries, a policy shift from quality to quantity is a right direction to go forward
Theoretical and numerical models on the diffusive and hereditary properties of biological structures
No full textThe main bulk of this Thesis is focused on the response of cell membranes due to chemical and mechanical stimuli. Henceforth, it is mainly devoted to deduce how the key aspect of the cell response activated by chemical signaling can be predicted by a simplified energetics, making use of both theoretical models and numerical simulations. The a ention is focused on cell membranes embedding G protein-coupled receptors (GPRCs). By analyzing the behavior of cell mem- branes, one can isolate three main contributions in order to model their respon- se: (1) diffusion of receptors and transporters embedded in the lipid membrane; (2) conformational changes of the receptors; (3) membrane elasticity. Moreover, the interplay between TM confomational changes and lateral pressure of the lipid membrane against such TMs is introduced. The chemical potential of the receptor-ligand compound, deduced as the variational derivative of such energy, is compared with the one calculated by accounting for the work done by the lateral pressure. The result yields a relationship between the conformational field, the mechanical field (interpreted as either the thickness change or the areal change) and the distribution of the compounds receptor-ligand. The analysis of such resulting constitutive equation among those three quantities shows that, essentially, the reason why ligand-GPRCs compounds prefer to live on lipid ra is a necessity involving the interplay between the work performed by the lateral pressure and the need of TMs to change their conformation during ligand binding. Henceforth, mechanobiology gives a justification to the experimental findings of Kobilka and Lei ovitz, Chemistry Nobel Prizes 2012
Advanced Techniques for Automatic Change Detection in Multitemporal Hyperspectral Images
Get PDFThe increasing availability of the new generation remote sensing satellite hyperspectral images provides an important data source for Earth Observation (EO). Hyperspectral images are characterized by a very detailed spectral sampling (i.e., very high spectral resolution) over a wide spectral wavelength range. This important property makes it possible the monitoring of the land-cover dynamic and environmental evolution at a fine spectral scale. This also allows one to potentially detect subtle spectral variations associated with the land-cover transitions that are usually not detectable in the traditional multispectral images due to their poor spectral signature representation (i.e., generally sufficient for representing only the major changes). To fully utilize the available multitemporal hyperspectral images and their rich information content, it is necessary to develop advanced techniques for robust change detection (CD) in multitemporal hyperspectral images, thus to automatically discover and identify the interesting and valuable change information. This is the main goal of this thesis.
In the literature, most of the CD approaches were designed for multispectral images. The effectiveness of these approaches, to the complex CD problems is reduced, when dealing with the hyperspectral images. Accordingly, the research activities carried out during this PhD study and presented in this thesis are devoted to the development of effective methods for multiple change detection in multitemporal hyperspectral images. These methods consider the intrinsic properties of the hyperspectral data and overcome the drawbacks of the existing CD techniques. In particular, the following specific novel contributions are introduced in this thesis:
1) A theoretical and empirical analysis of the multiple-change detection problem in multitemporal hyperspectral images. Definition and discussion of concepts as the changes and of the change endmembers, the hierarchical change structure and the multitemporal spectral mixture is given.
2) A novel semi-automatic sequential technique for iteratively discovering, visualizing, and detecting multiple changes. Reliable change variables are adaptively generated for the representation of each specific considered change. Thus multiple changes are discovered and discriminated according to an iterative re-projection of the spectral change vectors into new compressed change representation domains. Moreover, a simple yet effective tool is developed allowing user to have an interaction within the CD procedure.
3) A novel partially-unsupervised hierarchical clustering technique for the separation and identification of multiple changes. By considering spectral variations at different processing levels, multiple change information is adaptively modelled and clustered according to spectral homogeneity. A manual initialization is used to drive the whole hierarchical clustering procedure;
4) A novel automatic multitemporal spectral unmixing approach to detect multiple changes in hyperspectral images. A multitemporal spectral mixture model is proposed to analyse the spectral variations at sub-pixel level, thus investigating in details the spectral composition of change and no-change endmembers within a pixel. A patch-scheme is used in the endmembers extraction and unmixing, which better considers endmember variability.
Comprehensive qualitative and quantitative experimental results obtained on both simulated and real multitemporal hyperspectral images confirm the effectiveness of the proposed techniques