Ricardo Mendes André

Gisela Mendes

Tuukka Rautiainen

Eduardo Jiménez

Carlos Varandas

Nuno Lopes

Andrea Michiorri
email: andrea.michiorri@mines-paristech.fr

Guido Pires
email: guido.pires@edp.ptpedro.matos@edp.pti.

Pedro Matos

V Va

A L Lu Ue

M A Ar

R K Ke

I R Ro On

N M Me

E N Nt

Customers' flexibility valued in market and regulated environment

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

The increase of renewable generation in distribution grids combined with increasingly volatile load diagrams raises the necessity for a more flexible grid. This flexibility can be provided by the DSO in a Business as Usual (BaU), approach or by the grid users themselves, through innovative schemes. The SENSIBLE project -Storage-Enabled Sustainable Energy for Buildings and Communities is an H2020 funded project focused on energy storage and energy management technologies developments applied both for grid and end user applications, with three complementary demonstrators, Portugal-Évora, Germany-Nuremberg and United Kingdom-Nottingham. The Portuguese demonstrator adopts a wide focus with several use cases focused in grid applications and end customers' energy services development. This paper describes a use case developed under SENSIBLE Project currently in development in the Portuguese demonstrator, where clients provide flexibility through the use of energy storage and energy management technologies, both in regulated and market environment, optimizing customers' energy consumption and minimizing its cost, providing at same time, grid services in case of grid technical constraints.

III. PORTUGUESE FRAMEWORK

Figure 1 outlines a general outlook about the energy cost structure in Portugal, where it can be seen that in LV grid about 40% of the cost is due energy cost, due to generation, retail and trading. Here are included the costs from the market in day-ahead and intraday timeframes, where some deviations from forecasts are corrected. Moreover about 60% of energy structure cost in LV is due to grid accesses, that includes distribution grid, transmission grid as well as other system costs. This leads to the conclusion that acting on grid access and energy price would have a considerable impact in energy cost to final LV client. Despite the good quality of service and the high level of reliability, the current grid infrastructure is ancient and needs to undergo significant adjustments to handle the future challenges, namely higher peak demand, greater control over energy costs, losses reduction and lower O&M cost. Despite these upcoming challenges for the reliability of 2015) [START_REF]EDP Distribuição[END_REF] the grid and its quality of service, the optimization of sustainable drivers like energy efficiency, environmental aspects and energy costs for clients or electrical sector costs, are classical drivers that cannot be discarded. Considering the distribution grid investment plan there are four main items that make up the investment: Continuity of Service, Technical Quality of Service, Grid Efficiency, and Operational Efficiency. As it shown in figure 2, the first two items sum up 60% of investment. Grid peak power is one of the key indicators that is strongly correlated with grid investment. Moreover, analyzing grid efficiency, and since technical losses are proportional to the square of current (Plosses ≈ I 2 ), the minimization of peak demand is a key factor to lower their value and strongly contributes to a more sustainable electrical system. Moreover, renewable energy sources (RES) integration is one of the DSO responsibilities according to European and Portuguese directives. Considering RES integration, Portugal is one of leading countries in Europe, according to national policies [START_REF][END_REF]. A quick overview on figure 3 clearly shows the strong growth of the renewable generation connected to the distribution grid (80% of overall Portuguese renewable capacity) which have been increasing year after year, even despite the Portuguese economic crisis the country is undergoing since 2010. This increase in RES connected to the distribution grid implies that the DSO faces new challenges since grids are beginning to be explored with a different strategy. They were deployed so that the power flowed from upstream to downstream, but they are now facing a new reality. One well known problem is the increase of voltage profiles, mainly in low short-circuit LV grids. Another considerable change is the clients' behaviour profiles that are getting a more active role than passive. New technologies and new energy management techniques are emerging. Since clients are not so aware of these techniques, innovative and real demonstrator projects like SENSIBLE should promote the first from clients to these new reality.

The aforementioned challenges and the demand for new energy services (like energy flexibility services) to distribution grids stakeholders, from retailers to customers or producers, can only be achieved within a smart grid concept. The key word to respond to a more volatile grid operation is flexibility, to be provided mainly to DSO.

The previous figures and facts outline three main conclusions of the Portuguese framework. i) the energy cost for LV costumer highly depends on two main items grid access costs and energy costs; ii) Quality-of-Service, Continuity of Supply and Grid efficiency are three of the main investment vectors, and this clearly shows its importance for the DSO mission; iii) Renewable generation integration is one of the DSO main challenges and responsibilities. This leads to new grid management techniques, where new use cases and tools developments should support new business models to be erected. This leads to four of the objectives of the use case studied in this paper, namely Continuity of Service, Quality of Service, Energy Efficiency and RES integration. Figure 4 outlines a daily load diagram and energy market daily price where it can be shown that market energy price peak and peak power consumption are not completely coupled.

S Some often the energy price can be decreasing while the peak power still remains high. This reinforce the idea that energy and power must be managed integrated concerning the two main energy cost components, rather than separated. The last objective is to minimize energy costs paid by the client and it's considered that this must be done through an integrated management between grid access costs and energy cost price since they are not decoupled variables.

Taking into account the above framework, this paper to detail a use case where new energy services will be available to clients, which intends to reduce their energy costs (access and energy) through providing flexibility both to DSO and Retailer, as the following sections explain. IV.

SENSIBLE USE CASE -FLEXIBILITY AND DSM IN THE MARKET PARTICIPATION

The implementation of this use case is outlined in figure 4 where it is assumed that customer participation will occur through a Retailer or other Energy Service Company that acts in two timeframes (day-ahead and intraday) with complementary approaches, articulating regulated activities (grid management) and market activities (energy market).

Grid access cost will be managed by a dynamic tariff applied by the DSO under regulated rules which shall represent an incentive for customers to adapt their peak consumption in case of technical constraints. This tariff should reward customers that contribute to grid management, rather than clients that lead to grid expansion costs. The tariff should also be related to the avoidable costs (i.e. in grid investment, operation and maintenance) by DSO when clients contribute with flexibility in benefit of the grid operation. We can say that a dynamic tariff exists when they vary according to a certain purpose trying to incentive some type of behaviour. The aim of dynamic tariffs is to better reflect costs, either in terms of generation or distribution network. For the DSO, we can list some advantages dynamic tariff schemes can bring. First, they have some potential to lower the pace of growth of peak consumption. Networks are designed to accommodate maximum consumption. If peak consumption grows less, it means some investment can be deferred. Second, technical losses can decrease, if consumption has a flatter curve. Third, there will be a higher potential to integrate RES in the grid without compromising its reliability. Another important consequence has to do with the more efficient allocation of costs across customers, because dynamic schemes will tend to charge higher prices to the customers that actually cause the rise in the grid's peak consumption costs. Energy market benefits will come from market participation, where it's assumed that clients are equipped with flexibility management tools and flexible loads (as explained in Developments section) as well as that their flexibility will be used by an Energy Service Provider Company in an aggregated way.

Day-ahead timeframe

The client's final energy price combines the energy price resulting from wholesale market and the grid access regulated dynamic tariff. In case a technical constraint is foreseen, the dynamic tariff will charge more for grid's access, with the customer being warned in advance. If are forecasted such as excess of PV generation in a feeder, the DSO will apply a dynamic tariff to grid access cost item in order to promote energy consumption.

On the other hand an Energy Service Company (ESC) could optimize its market participation by managing the flexibility available in its clients' portfolio, optimizing the bids to the market and offers to the customers. This is done considering both the day-ahead wholesale electricity market and the optimal participation in the intraday market.

Intraday timeframe

In the intraday timeframe, considering a BaU scenario, any unbalance between day-ahead offers and intraday real consumption would be compensated in intraday market with higher costs to retailers that fails their previous offers and predictions. Moreover any deviations would be compensated by the TSO in secondary reserve market and this associated cost (System Adjusting Factor) would be paid by retailers whose clients failed their load prediction. These costs could be minimized using better predictions of the consumption and the flexibility of each within a retailer's client portfolio of clients in wide flexible market participation. This will result in a cost reduction to the retailers and these benefits will be shared also with customers Considering regulated activity, in the intraday timeframe the dynamic grid access tariff will not change due to strict regulated rules and grid access limitations will only be allowed under severe technical constraints. In such case client's load curtailment will be requested by DSO through a Demand Side Management (DSM) signal to each client's smart meter and simultaneously to the Retailer which will take advantage of its Energy Market Service Platform (ESMP) to optimize their clients load profile, through the HEMS according to grid limitation, as will be explained afterwards. A quick example of application is here described: a LV grid, because of any technical reason is forced to reduce its peak power to avoid a grid blackout. This amount of power should be reduced by this grid's clients according to fair and regulated rules, so that Continuity of Service can be assured. Under this technical constraint, those clients who could adapt their consumption would be disconnected by a DSM signal, while the technical constraint is active. These would be a clear situation where customers are invited to participate in grid management collecting benefits of the smartgrid infrastructure contributing to a more efficient grid.

V. DEMONSTRATION AND ARCHITECTURE

SENSIBLE' Évora demonstrator will be located in Valverde, a small village in Évora district, where 40 of 238 LV consumers are equipped with a Home Energy Management System (HEMS), which will manage Residential Energy Storage System, PV System, and Flexible Loads like Electrical Water Heaters (WH) among others, as outline in figure 8. The HEMS will be managed by high level tools. The HEMS will have two drivers both from market where market contribution will be calculated (EMSP) and from regulated activity where grid access costs will be managed (Grid Service Platform). A Demand Forecast tool and Production forecast tool will forecast generation and load profiles as an input to both grid access costs and available flexibility from customer's estimation. Afterwards, the EMSP will calculate the market and regulated items and optimize the best aggregated load profiles according to available flexibility from customers. The result of this aggregated flexibility, as a result of market participation and DSO requirements, will be breakdown through set points to HEMS among individual households according to the customers' flexibility usage.

VI. CONCLUSIONS AND FUTURE WORK

The Use Case of flexibility and DSM in market participation developed under the scope of SENSIBLE project aims to bring benefits to customers and to the grid. It will be test in a real environment, including 16% of Évora demonstrator LV customers. The use case results and conclusions are to be shared in next steps. Moreover, the regulatory framework will be tested so that new technics and business models can be ratified and true value materialized.

VII.

Figure 1 -

 1 Figure 1 -Energy tariff cost structure in Portugal, excluding taxes (2015)[START_REF]EDP Distribuição[END_REF]

Figure 4 -Figure 3 -

 43 Figure 4 -Daily peak consumption and energy price in wholesale market[4]

Figure 5 -

 5 Figure 5 -Use case framework

Figure 8 -

 8 Figure 8 -Residential energy management equipment in SENSIBLE's Évora demonstratorThis HEMS will be managed through an ICT (information and communications technologies) architecture where two main routes interact to the client: i) market route (red) for market based services and ii) regulated route (green) for DSO application services to grid management. The elements

Figure 9 -

 9 Figure 9 -Évora demonstrator architecture.


Mireille Fouillaud
email: mireille.fouillaud@univ-reunion.fr

Mekala Venkatachalam

Emmanuelle Girard-Valenciennes

Yanis Caro

Laurent Dufossé

Doru Abrudan

Samuil Micu

Carmen Socaciu

Adela Pintea

Andrea Bunea

Sanda Andrei Loredana

Florina Leopold

Cristina Coman

Dan Cristian Vodnar

Olivia Dumitrița

Rugină Zorița

Diaconeasa Oana

Lelia Pop

Francisc Dulf

Andreea Elena Pop

Lucian Cuibus

Dorottya Domokos

Andrei Lazar

Beatrice Dan

Norway Øyvind M Andersen

Marco Arlorio

Vincenzo Fogliano

United Kingdom Paul Fraser

Adriana Mercadante

Antonio Melendez Martinez

Jozsef Deli

Damaso Hornero-Mendez

Monica Monica Giusti

Gerhard Sandmann

George Britton

Neal E Craft

Antonio J Meléndez-Martínez

József Deli

Erika Turcsi

Attila Agócs

Veronika Nagy

Gergely Gulyás- Fekete

Enrique Murillo

Kristian Fog Nielsen

Daniele Giuffrida

Emmanuelle Girardvalenciennes

Antonia Melendez

Martinez -József Deli

Dámaso Hornero-Méndez

Judith Mueller-Maatsch

Florence Kreiser

Judith Hempel

Oliver Paquet-Durand

Reinhold Carle

Ralf Schweiggert

Saniye Işıl İlter

Mehmet Akyıl

Zeliha Koç

Meltem Demirel

Figen Conk- Dalay

Kaymak-Ertekin

Francesco Cacciola

Margita Utczas

Domenica Mangraviti

Ivana Bonaccorsi

Veronica Inferrera

Paola Donato

Paola Dugo

Luigi Mondello

A Ligia Focsan

Lowell D Kispert

Luis E Rodriguez-Saona

Manman Lu

Jianxiong Cai

Wei Xu

Jing Chen

Shujuan Zhao

Pu Jing

R M Arlorio

G Negri

J D Del Favero

V Coïsson

F Papillo

V Travaglia

D Gokmen

G B Marko

Giovenzana

Øyvind Andresen

Kewei Chen

María Roca

Myriam Benarroch

Justine Lallement

Larbi Rhazi

Camille Boroch

Cindy Hugot

Claude-Narcisse Niamba

Hassan Younes

Flore Depeint

Antonio Pérez-Gálvez

Juan Garrido-Fernández

José J Ríos

Ana A O Xavier

Josefa Aguayo Maldonado

Andreina Bruno

Mirana Durante

Pier Elisabetta Pace

Paolo Marrese

Giovanni Mita

Gabriella Piro

Marcello S Lenucci

Eszter Gábor Palotás

Sarkadi Nagy

Hussein Daood

Éva Martos

Lajos Helyes

Andrea Lugasi

Philippe Thonart

Manfred Eggersdorfer

Ulrich Killeit

Dirk Cremer

Michael Murkovic

Alam Zeb

Marini Damanik

Antoanela Patras

Razvan Filimon

Szabolcs Béni

András Darcsi

József Deli

olives. Miriana Maria Durante

Luca Tufariello

Gianluca Tommasi

Giovanni Bleve

Mita

Anna Rafaela Braga

Katia Biazotto

Veridiana Vera De Rosso

Cerrado Kátia

Regina Biazotto

Anna Rafaela

Cavalcante Braga

MARINE-DERIVED FUNGI PRODUCING RED ANTHRAQUINONES: NEW RESOURCES FOR NATURAL COLORS?

Keywords: Penicillium dravuni endophyte from algae, Fidji An1cancer ac1vity inducing apostosis in tumor cell lines (human glioma, hepatoma, prostate cancer, MCF- Halorosellinia sp sediments collected in Jilantai salt field, Alashan, Inner Mongolia, China Inhibitory effects against clinical mulJdrug-resistant Mycobacterium tuberculosis strains endophyte from mangrove plant, South China Sea

Natural Colors make

Presenting author: mireille.fouillaud@univ-reunion.fr

Keywords: red, pigment, anthraquinone, marine, fungi

In industries, authorized red pigments are mainly issued from plants (as lycopene from tomato or betalains from beetroot), cochineal insects (carmine red) or from chemical synthesis. Their uses are more and more questioned with regard to the culture constraints or health problems. New resources for the production of natural red colorants are therefore under focus [1,2]. Marine-derived fungi are at the forefront in the search of new compounds of interest that could be produced through biotechnology [3]. In the field of colors, the marine-derived microfungi are able to synthesize a wide diversity of pigments/ hues, amongst which red anthraquinones are well represented. Some of their main advantages are they are considered as natural, and their productions are « upscalable » in an industrial point of view. This work highlights the anthraquinoid red pigments known, up to date, from marine-derived fungi. We summarize about thirty compounds produced from about 25 strains that have been discovered in the former years. Beside the widespread Aspergillus, Alternaria, Eurotium, Fusarium or Penicillium, some original genera as Halorosellinia, Nigrospora, Stemphylium or Xylaria were identified as red anthraquinoid molecules's producers. Well known substances such as austrocortinin, catenarin, erythroglaucin or bostrycin were characterized in the fungal productions, as well as several new compounds, never mentioned, up to now, from other organisms. They could interestingly be further studied as potential sources of red colors to be operated in food, cosmetic or dyeing industries. Beside their coloring properties, these compounds sometimes exhibit diverse biological activities such as antimicrobial or anticancer effects, sparsely mentioned in the literature. This aspect, when available, is also documented, in order to examine the potential use of these compounds and to help broadening the horizon of colors with innovative natural substances.

BOOK of ABSTRACTS

Fig. 2 : 1 :

 21 Fig. 2 : 1.5 L fermentor allowing fungal growth and pigments producJon Fig. 3 : Red powder acer liquid/liquid extracJon Fig. 1: Penicillium sp. strain (a) on solid medium / (b) Microscopic observaJon with lactophenol blue stain

PIF2016 a great opportunity

  to visit the old academic city Cluj-Napoca, to enjoy the traditional food and life in the beautiful Transylvanian landscape and to discover its cultural heritage!

1,2

1 Laboratoire de Chimie des Substances Naturelles et des Sciences des Aliments -LCSNSA EA2212, Université de la Réunion, Saint-Denis, Ile de la Réunion, France 2 Ecole Supérieure d'Ingénieurs Réunion Océan Indien-ESIROI, Université de la Réunion, Sainte-Clotilde, Ile de la Réunion, France

in Food-VIII (2016) in Cluj-Napoca, Romania are dedicated to health benefits! PREFACE On

  behalf of the Organizers of the Eight International Congress PIGMENTS IN FOOD, it is our pleasure to welcome you, at the Department of Chemistry and Biochemistry at the University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Romania.We are delighted to offer you, meanwhile, the opportunity to visit the historical city of Cluj-Napoca, to enjoy the traditional food and life in the beautiful Transylvanian landscape and to discover our cultural and academic heritage!

	Cluj-Napoca ROMANIA a n l o C i t a n F r e t n I d o o g o n g r e s s o n P i n i m s i n F o o s t en I n t e r n a t i o n a l C o i m ent g n g r e ss o P n d
	8th International Congress
	"Pigments in Food"
	Colored Food for Health Benefits After seven successful Congresses "Pigments in Food", starting in Sevilla, Spain (1999)
	and passing through Lisbon, Portugal (2002), Quimper, France (2004), Stuttgart-
	Hohenheim, Germany (2006), Helsinki, Finland (2008), Budapest, Hungary (2010), and
	Novara, Italy (2013), we are honored to host this edition, PIF2016 in the capital or
	Transylvania region, Romania.
	BOOK of ABSTRACTS
	SCIENTIFIC PROGRAM -
	On behalf of the Organizing Committee,
		Carmen Socaciu -chair
	28th of June -1st of July 2016	Adela Pintea -co-chair
	Cluj-Napoca, Romania

Editors: Prof. dr. Carmen Socaciu Prof. dr. Adela Pintea

The publication include abstracts of oral and poster presentations.The editors does not assume any responsibility regarding the content of the abstracts, the authors are responsible for the content originality. Author(s) have the copyright ownership of the data presented in the abstracts book.

IV Pigments It was the best opportunity for scientists from all over the world (17countries: UK, USA, Germany, France, Reunion Island, Spain, Italy, Denmark, Hungary, Poland,Turkey, Brazil, Uruguay, Panama, Mexico, Chinaand Romania) to show their advances in scientific and technological topics,related to plant pigments and food colorants. The 6 sessions were well adapted to cover the most important and outstanding directions of research and technology development in this research e.g. chemical characterization and bioprospecting, to advanced bioanalytical methods, (bio)technological production and formulation, pigment processing and stability, bioactivity, functionality and health effects, as well quality and safety aspects. The program includes 5 plenary lectures and 7 keynote lectures by best international experts in the field, as well as 20 oral presentations and more than 65 poster contributions. An important aim of PIF2016 is also represented by the opportunity of meeting and discussion for scientists dealing with different aspects of pigments, such as chemists, food chemists, food technologists, biotechnologists, nutritionists, but also industry representatives. A comprehensive scientific program, adapted to the new approaches and trends in this scientific area was designed and realized -such approach had a particularly strategic aim, to demonstrate that and how pigments and colored food bringhealth benefits.

PIF 2016 at USAMV, Cluj-Napoca Tuesday June 28 th Wednesday, June 29 th Thursday, June 30 th Friday, July 1 st

	Session 6	Quality and safety of food pigments	9.00-9.30 Key note lecture 7: Manfred	Eggersdorfer	9.30-10.00 Oral presentations (15min)	Michael Murkovic, Antoanela	Patras	10.00-10.35 Selected poster presentations (6	x 6 min)
	Session 4	Food processing, pigments stability and color	development	8.30-9.15 Plenary lecture 5: Monica Giusti	9.15-9.45 Key note lecture 5: Laurent Dufossé	9.45-11.00 Oral presentations (15 min)	Kewei Chen, Mihaela Turturică, Miriana	Durante,	Pu Jing, Marco Arlorio
	8.00-9.00 Registration		9.00-9.45 Plenary lecture 2: Neal Craft	9.45-10.00 Welcome EUCHEMS FCD -Marco Arlorio	Session 1A	Chemical characterization and Bioprospecting	10.00-10.30 Key note lecture 1: Antonio Meléndez Martinez	10.30-11.00 Oral presentations (15min):	Jozsef Deli, Mekala Venkatachalam	11.00-
										14.00-18.00 Registration	16.30-17.00	Opening Ceremony	17.00-17.45	Plenary lecture 1:	George Britton	17.45-19.00	Poster session	19.00	Welcome party

11.30: Coffee Break & Poster session 11.00-11.30 Coffee Break & Poster session 10.35-11.15 Coffee Break & Poster session

	Session 7	Round Table	11.15-12.15 Presentation of EU projects:	COST EUROCAROTEN	FP-7 DISCOvery	PROCAR	12.15-13.00 Poster
	Session 5	Bioactivity, functionality and health effects	11.30-12.00 Key note lecture 6: Begoña Olmedilla-	Alonso	12.00-13.15 Oral presentations (15 min)	María Roca, Flore Depeint,	Antonio Pérez-Gálvez, Marcello S.	Lenucci, Gábor Palotás
	Session 1B	Chemical characterization and Bioprospecting	11.30-12.00 Key note lecture 2: Dámaso H.Méndez	12.00-12.30 Oral presentations (15min)	Judith Müller-Maatsch, Işıl İlter

Awards and Closing ceremony 12.30-13.30 Lunch break 13.15-14.15 Lunch break and Poster session 13.00-14.00 Lunch 13.30-14.00 Poster session 14.30 Transylvanian Landscape Trip: from Salt Mine Turda to Coltesti, a typical Transylvania village (including Dinner) Optional social events:

	City Tour	and concerts at International Festival "Jazz in	the Park"
	14.00-14.45

Plenary lecture 3: Øyvind Andersen Session 2 Advanced bioanalytical methods

  14.45-15.15 Key note lecture 3: Daniele Giuffrida 15.15-15.45 Oral presentations (15min) A. Ligia Focsan, Luis E. Rodriguez-Saona 15.

45-16.15 Coffee Break & Poster session 16:45-17:30 Plenary lecture 4: Gerhard Sandmann Session 3 Emerging (bio)technologies of pigment production and formulation

  17.30-18.00 Key note lecture 4: Paul Fraser 18.00-18.30 Oral presentations Philippe Thonart, Stefan Martens 20.00 Gala

Dinner in Cluj-Napoca

ACKNOWLEDGEMENT: This work was financed by the University of Reunion Island and the Conseil Régional de La Réunion, COLORMAR project (DIRED / 20140704).


Pierrick Coupé

Charles-Alban Deledalle

Charles Dossal

Michèle Allard

Sparse-Based Morphometry: Principle and Application to Alzheimer's Disease

Keywords: voxel-based morphometry, Alzheimer's Disease, dictionary learning, abnormality detection, patch-based processing

The detection of brain alterations is crucial for understanding pathophysiological or neurodegenerative processes. The Voxel-Based Morphometry (VBM) is one of the most popular methods to achieve this task. Based on the comparison of local averages of tissue densities, VBM has been used in a large number of studies. Despite its numerous advantages, VBM is based on a highly reduced representation of the local brain anatomy since complex anatomical patterns are reduced to local averages of tissue probabilities. In this paper, we propose a new framework called Sparse-Based Morphometry (SBM) to better represent local brain anatomies. The presented patch-based approach uses dictionary learning to detect anatomical pattern modifications based on their shape and geometry. In our validation, the impact of the patch and group sizes is evaluated. Moreover, the sensitivity of SBM along Alzheimer's Disease (AD) progression is compared to VBM. Our results indicate that SBM is more sensitive than VBM on small groups and to detect early anatomical modifications caused by AD.

Introduction

In neurological diseases such as Alzheimer's Disease (AD), numerous studies suggest that some structures are affected by atrophy whereas others are relatively preserved. These brain abnormalities reflect pathophysiological processes, and are correlated with cognitive impairments and clinical symptoms. Thus, the Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

analysis of the anatomical brain integrity in patients is an important challenge of current research in neurology. Automatic detection of such brain abnormalities enables us to link anatomical substratum to cognitive performance or clinical symptoms. One of the classical methods used for automatic analysis of brain structures is voxel-based morphometry (VBM) [START_REF] Ashburner | Voxel-based morphometry-the methods[END_REF]. VBM is an image processing framework enabling the identification of differences in the tissue density over the whole brain without a priori definition of a region of interest. Since its introduction, VBM has been successfully used in studies dedicated to a large variety of disorders. Despite its numerous advantages, VBM is based on a highly reduced representation of the local brain anatomy. Indeed, the complex local gray matter (GM) pattern is reduced to a local weighted average of GM probabilities through a Gaussian smoothing. While the importance of this smoothing step is well-known from a practical point of view [START_REF] Shen | VBM lesion detection depends on the normalization template: a study using simulated atrophy[END_REF], the use of a local average to represent complex anatomical patterns should be questioned. In this paper, we investigate the possibility of using a patch-based strategy to better represent the local brain anatomy. Recently, patch-based methods have demonstrated high performance in many neuroimaging applications such as anatomical structure segmentation [START_REF] Coupé | Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation[END_REF][START_REF] Tong | Segmentation of MR images via discriminative dictionary learning and sparse coding: application to hippocampus labeling[END_REF] or automatic diagnosis [START_REF] Coupé | Simultaneous segmentation and grading of anatomical structures for patient's classification: application to alzheimer's disease[END_REF][START_REF] Liu | Ensemble sparse classification of alzheimer's disease[END_REF]. As recently proposed for segmentation purposes [START_REF] Tong | Segmentation of MR images via discriminative dictionary learning and sparse coding: application to hippocampus labeling[END_REF], we use a dictionary learning process to construct a sparse representation of anatomical patterns. Unlike [START_REF] Tong | Segmentation of MR images via discriminative dictionary learning and sparse coding: application to hippocampus labeling[END_REF], this sparse modeling of the brain anatomy is used to detect abnormalities through a new framework called Sparse-Based Morphometry (SBM). As shown later, SBM is especially well-suited to detect local modifications in terms of their shape and geometry. However, the inherent patch normalization involved in sparse-coding approaches makes SBM insensitive to modifications of the mean GM density within a patch. Therefore, we propose to combine the capability of VBM to detect modifications of local average GM density with the high ability of SBM to capture subtle alterations of the local shape of GM patterns. As discussed in the following, VBM can be viewed as the comparison of the patch mean while SBM compares the patch geometry. The contribution of this paper is threefold: (i) we present the new concept of SBM susceptible to better represent the complexity of local anatomical patterns, (ii) we propose to combine VBM and SBM in order to simultaneously analyze modifications of the local mean GM density and alterations of the shape and geometry of local GM patterns, and (iii) we evaluate the proposed framework on the ADNI dataset.

Methods and Materials

Subjects selection and Preprocessing In this study we used a sample of the standardized ADNI1 collection [START_REF]Standardization of analysis sets for reporting results from ADNI MRI data[END_REF]. By using the 818 baseline MRI scan at 1.5T, we created three groups of cognitively normal subjects (CN), one group of patients with AD, one group of subjects with Mild Cognitive Impairment (MCI) who progressed to AD (progressive MCI or pMCI) and one group of subjects with MCI who remained stable during the follow-up period (sMCI). All the groups have the same number of subjects (N = 70). In addition, to remove potential

Sparse-based modeling of the brain anatomy

The proposed method estimates at each voxel the distribution of a scoring function measuring the degree of abnormality of a population at this location. The choice of the scoring function is the key to success for such an approach and thus it should be designed to be invariant to inter-subject variabilities inside the reference group while being discriminant to intra-group variabilities. In order to capture the local morphological structure of the brain, for each location in the MNI space, we use a 3D patch (i.e., a small rectangular windows) centered in a voxel v. The proposed scoring function measures the ability of this patch to be decomposed in a sparse way, i.e., as a linear combination of a small number of predefined patches. This family of predefined patches, called dictionary, is learned offline from the set of patches located at v in the training group. In this study, we then distinguish three groups G 1 , G 2 and G 3 . The first group G 1 composed of CN subjects is used to learn the dictionary (CN training). Distributions of the scoring functions are next computed independently on two other groups, a reference group G 2 composed of CN subjects (CN testing) and the group of interest G 3 (e.g., composed of AD patients). Since G 1 and G 2 are two groups composed of CN, the scoring function is expected to be statistically different for groups G 2 and G 3 where G 3 is abnormal compared to the control.

Sparse brain anatomy representation using dictionary learning

For each subject i of group G 1 and at each voxel v in the MNI space, a 3D patch is extracted, centered (subtraction of its mean), normalized (divided by its norm) and vectorized into a vector x i . The dictionary D, that is a matrix whose columns are p patches, is next selected as the one minimizing the following quantity:

min D,αi |G1| i=1 1 2 x i -Dα i 2 2 + λ α i 1 ( 1
)
where λ is a positive parameter. The first term 1 2 x i -Dα i 2 2 ensures that each extracted patch x i is not too far from its approximation Dα i , while the second term α i 1 promotes that each extracted patch x i can be indeed efficiently decomposed in a sparse way into the resulting dictionary D (i.e., such that α i contains a large number of zero coefficients). At the end of the procedure, each column of D is a vectorization of a patch encoding one of the possible local morphological configurations of the brain in the training group G 1 .

Group comparison using sparse-based morphometry

As for the dictionary learning step, a patch is extracted at voxel v for each subjects of groups G 2 and G 3 . This patch is also centered, normalized and vectorized. The following scoring function

f (x) = min α∈R p 1 2 x -Dα 2 2 + λ α 1
is then applied on each patch where D is the learned dictionary associated to voxel v. The empirical distribution of the scoring function f (x) is next computed independently on each group. Thanks to the learning of an adapted dictionary on the CN training subjects of G 1 , the dictionary D is expected to be flexible enough to reconstruct sparsely most of the patches of the CN testing group G 2 used as reference, hence leading to statistically low scoring values f (x). On the contrary, at locations where the group of interest G 3 presents some abnormalities, a low approximation error 1 2 x -Dα 2 2 might not be reachable with low sparsity level, hence leading to statistically large values of α 1 and f (x). After applying a T-test on the distributions of f (x) estimated at each voxel, our sparse-based morphological technique provides a map of degree of difference between the groups G 2 and G 3 . Low values in this map can next be used to determine the voxels where G 3 seems to present some abnormalities.

Fusion of SBM and VBM As usually done in sparse-based approaches, the patches are centered and normalized during the proposed SBM procedure. Therefore, the mean of the patches (i.e., the local GM density used for VBM) is not taken into account in SBM. We propose to fuse the SBM and VBM features in order to capture jointly the local anatomical geometry and the local tissue density. To this end, we propose to fuse the T-maps produced by SBM and VBM. The simple approach that takes the minimal p-value at each voxel is known to not produce p-values [START_REF] Vovk | Combining p-values via averaging[END_REF]. We use Bonferroni's method that is guaranteed to produce p-values from K p-values p k using the fusion function F defined as:

F (p 1 , ..., p K ) := K min(p 1 , ..., p K ) .
(2) Implementation details and Quality metric In our experiments the value of λ is not crucial and set to 0.15. The optimization of Eq. ( 1) is computed by alternating minimization on the dictionary D and the sequence (α i ) using SPAMS' toolbox (http://spams-devel.gforge.inria.fr/index.htm) [START_REF] Mairal | Online dictionary learning for sparse coding[END_REF]. In the following, the half patch sizes (HPS) are reported in mm. The number of atoms in the dictionary is set to 8. This number does not have a drastic impact on results according to our experiments. All images are displayed using the same p-value range from 10 -2 to 10 -8 and at the same coordinates in the MNI space. The methods are evaluated with two metrics. First, the abnormality ratio metric estimates the percentage of GM detected as abnormal (i.e., with p-value inferior to 0.01). Second, a merged p-value (p) metric reflects the level of significance in the area detected as abnormal. The p-values inferior to 0.01 are aggregated using the merging function [START_REF] Vovk | Combining p-values via averaging[END_REF] that produces a p-value (unlike the standard average):

M (p 1 , ..., p K ) := 2 K (p 1 + ... + p K ) (3)
3 Results

Impact of the patch size and number of subjects

Table 2 presents the abnormality ratio and the merged p-value p obtained for the considered patch sizes. The abnormality ratio increases when using bigger patch sizes and the fusion of SBM and VBM lead to similar or higher ratios. In terms of significance, SBM and the fusion provides lower p than VBM. In addition, the fusion of VBM and SBM produces lower p than SBM alone. We can note that a plateau is reached at HP S = 15mm for VBM and that the p values are stable for SBM and the fusion. We therefore use this patch size in the following. Table 3 presents the abnormality ratio and the p obtained for the considered group sizes. As expected, more significant differences are found between both groups when using a larger number of samples. Moreover, VBM is more affected by the reduction of the group size than SBM.

Early detection of AD signature

In this last experiment, we investigate the results provided by the methods on sMCI and pMCI groups. The pMCI group is expected to produce abnormalities close to the abnormalities detected in the AD group since the pMCI group is composed by patients converting to AD during the follow-up. The sMCI is expected to be closer to the CN group and can be viewed as an earlier stage of the AD compared to pMCI. Figure 1 shows the results of our abnormality detection approach on the considered groups (i.e., AD, pMCI, and sMCI). Table 4 presents the abnormality ratio and the p obtained for each group. As expected, for all the methods, more abnormalities were detected in the AD group, followed by pMCI and sMCI. In all cases, SBM produces a higher abnormality ratio than VBM. Moreover, VBM produces a very low abnormality ratio for the sMCI group. These results seem to indicate that VBM is not sensitive enough to detect to subtle anatomical alterations present in the sMCI group. Consequently, the low abnormality ratio produced by VBM for the sMCI group impacts the fusion. For pMCI and AD groups similar results are obtained for SBM and fusion in terms of the abnormality ratio. However, fusion provides lower p than SBM. In terms of anatomical difference, SBM finds significant differences for pMCI group in areas only detected for the AD group using VBM (e.g., medial frontal cortex and thalamus). VBM and SBM detect abnormalities in the posteriori cingulate cortex, while only SBM detects abnormality in the anterior cingulate cortex. Moreover, SBM found differences in the precuneus and the posterior cingulate cortex. Both structures have been shown to be impacted by AD in terms of anatomical atrophy [START_REF] Karas | Precuneus atrophy in early-onset alzheimer's disease: a morphometric structural mri study[END_REF], metabolism reduction [START_REF] Ikonomovic | Precuneus amyloid burden is associated with reduced cholinergic activity in alzheimer disease[END_REF] and functional alteration [START_REF] He | Regional coherence changes in the early stages of alzheimer's disease: a combined structural and resting-state functional mri study[END_REF]. In addition, SBM and VBM detect abnormalities in the left entorhinal and parahippocampal cortex for the sMCI group with a larger extentfor SBM. It is interesting to note that these structures are known to be affected at the first stage of the pathology [START_REF] Devanand | Hippocampal and entorhinal atrophy in mild cognitive impairment prediction of alzheimer disease[END_REF]. Finally, SBM is able to find subtle abnormalities in the medial frontal cortex in the sMCI group while such alterations are detected only in the AD group using VBM (see Fig. 1). This last result highlights the high sensitivity of SBM compared to VBM.

Conclusion

In this paper, we proposed a new method to detect anatomical abnormalities called sparse-based morphometry. Based on local modeling of the normal anatomy using dictionary learning, SBM enables us to efficiently capture brain alterations in terms of their geometry and shape. In our experiments, SBM was shown to be more sensitive than VBM when using small groups or when studying early anatomical modifications caused by AD at the first stage of the pathology. We also presented a fusion strategy to combine VBM and SBM in order to take into account modifications of the local average GM density and to capture alterations of the local shape of GM patterns.

Fig. 1 :

 1 Fig. 1: Detection of abnormality in AD, sMCI and pMCI groups using HP S = 15mm and 70 subjects per group. The p-values of the T-maps are thresholded at 0.01.

Table 1 :

 1 Demographic information about the considered groups bias during our experiments, we randomly selected subjects from each group with the constraint of similar age and similar gender proportion between groups. See Table1for details. As explained later, the CN (training) group is used to learn dictionaries (i.e., to create a sparse representation of the normal brain anatomy)

	Group	Size Gender (% Female) Age (SD) MMSE (SD)
	CN training 70	53%	76.3 (5.1) 29.0 (0.9)
	CN testing 70	47%	76.1 (4.8) 29.0 (0.9)
	sMCI	70	41%	76.3 (7.2) 27.2 (3.5)
	pMCI	70	42%	75.8 (6.6) 26.1 (2.1)
	AD	70	55%	76.6 (7.7) 23.0 (3.3)

while the testing CN group is used to model the inter-subject variability. All the data were preprocessed with the Statistical Parametric Mapping 8 software (SPM8; http://www.fil.ion.ucl.ac.uk/spm) and the VBM8-toolbox (http: //dbm.neuro.uni-jena.de/vbm.html) using default settings.

Table 2 :

 2 Abnormality ratios in % and merged p-values (p) in parentheses for each considered patch size. The presented results were obtained on 70 CN vs. 70 AD. The used threshold on the T-maps was set to 0.01.

	VBM	SBM	Fused
	HP S = 9mm 49.2% (0.0032) 53.1% (0.0027) 58.0% (0.0027)
	HP S = 12mm 54.4% (0.0028) 62.2% (0.0022) 64.8% (0.0021)
	HP S = 15mm 57.3% (0.0025) 69.4% (0.0019) 69.6% (0.0018)

Table 3 :

 3 Same as above but for each considered group size. The presented results were obtained on CN vs. AD using HP S = 15mm.

	VBM	SBM	Fused
	30 CN vs. 30 AD 29.8% (0.0048) 47.5% (0.0033) 46.4% (0.0035)
	50 CN vs. 50 AD 57.9% (0.0028) 65.4% (0.0023) 67.3% (0.0021)
	70 CN vs. 70 AD 57.3% (0.0025) 69.4% (0.0019) 69.6% (0.0018)

Table 4 :

 4 Same as above but for each considered testing group. The presented results were obtained with HP S = 15mm and 70 subjects per group.

	VBM	SBM	Fused
	sMCI 0.1% (0.0170) 1.3% (0.0132) 0.3% (0.0147)
	pMCI 34.5% (0.0045) 53.7% (0.0046) 51.2% (0.0043)
	AD 57.3% (0.0025) 69.4% (0.0019) 69.6% (0.0018)

Acknowledgments

This study has been carried out with financial support from the French State, managed by the French National Research Agency (ANR) in the frame of the Investments for the future Program IdEx Bordeaux (HL-MRI ANR-10-IDEX-03-02), Clusters of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57) and the CNRS multidisciplinary project "Défi imag'In".