Aleksandr I Egunov

Ayano Inaba

Simon Gree

Jean-Pierre Malval

Katsuhiro Tamura

Yukie Saito

Valeriy A Luchnikov
email: valeriy.luchnikov@uha.fr

Time-Programmed Release of Fluoroscein Isocyanate Dextran From Micro-Pattern-Designed Polymer Scrolls

Keywords: macromolecule, controlled release, model drug, chronopharmacology, chitosan, fluoroscein isocyanate dextran, ATR FTIR spectroscopy

In this article we present a relevant strategy for a non-trivial time-programmed release of water-soluble macromolecules from biocompatible -containers. The system is based on self-scrolled chitosan acetate (CA) fibers, encapsulated in a poly(dimethylsiloxane) matrix.

Mass transfer between a fiber and the external environment takes place via the only opened extremity of the fiber. Fluoroscein isocyanate dextran (FID) is initially deposited at the inner

Introduction.

Ever growing knowledge about the molecular mechanisms of disease processes has given rise to a new tendency in the pharmacological science, that is, the design of macromolecular drugs (MDs), which interact precisely via the molecular recognition processes with the required targets and perform in this way the therapeutic intervention. Such peculiarities of the MDs provide them high efficiency and specificity of the therapeutic action. Another modern tendency of the pharmacological research is time-controlled drug administration, recently termed chronopharmaceutics [START_REF] Youan | Chronopharmaceutics: gimmick or clinically relevant approach to drug delivery?[END_REF][2][START_REF] Singh | Chronopharmaceutical drug delivery system -a guided therapy[END_REF]. Since human physiology and biochemistry vary during a 24 hour

The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 3 period according to the so called circadian cycle, some medical conditions are more prevalent at certain periods of the day. For instance, the peak in serum cortisol, aldosterone, testosterone, platelet adhesiveness, or blood viscosity, is observed during the initial hours of daytime. In contrast, insulin, cholesterol, triglycerides, platelet numbers, and uric acid levels, peak later during the day and evening, etc. Therefore, multiple sequences for the administration of a drug, or a combination of two different drugs, at distinctive times, may be beneficial in situations in which not only the amount but also the timing of a dose of drug is important. Time-controlled administration of the macromolecular drugs is associated with specific problems related to their high molecular weight. The release from polymer matrices, explored with success for low-weight molecular substances, is not optimal in the case of the MDs because of very low diffusion rates the macromolecules in the material. In addition, complete release of macromolecules is limited due to their entanglement within the polymer matrix. In order to optimize the release of the MDs, the drug reservoirs are organized often as hierarchical porous materials, in which the transport of the drug molecules outside the matrix pursues via diffusion along the macropores with diameters of 50 nm and higher. An original approach to produce polymer particles with well-defined micro-and nanochannels was suggested by Liu et al. [START_REF] Sharma | Liu Formation of Polymeric Toroidal-Spiral Particles[END_REF]. The particles are formed by dropping a polymer solution in a less-dense liquid, leading to hydrodynamics formation of toroidal-spiral structure, which is flash-solidified by photo-triggered crosslinking. A macromolecular model drug, polyphosphate, was released by diffusion along the spiral channel in course of a few hours. In another approach, macroporous polymer matrices with the pore sizes of the order of 10-100m were explored as the macromolecular drug release media, with the release rates determined by the topology of the porous space [START_REF] Saltzman | Transport rates of proteins in porous materials with known microgeometry[END_REF][START_REF] Siegel | Mechanistic studies of macromolecular drug release from macromorous polymers. II Models for the slow kinetics of drug release[END_REF].

The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 4

In the present article, we propose a new macromolecular delivery strategy based on elaboration of chitosan-based micro-encapsulation media, which promote the release of the molecules according to a time-programmable kinetics. In our approach, the water-soluble macromolecules are initially encapsulated in biocompatible chitosan acetate (CA) microfibres, which are produced by selfscrolling of differentially strained CA films in aqueous solutions. Arbitrarily complex distributions of the macromolecules concentration along the fiber axis can be realized via 2Dpatterning of the films prior to the scrolling step. The fiber is embedded into a water-impermeable matrix in such a way that only one extremity is accessible to the external environment. The kinetics of the release can be controlled by i) the rate of the fiber swelling front propagation starting from the extremity, ii) the distribution of the macromolecules along the fibre's axis, and iii) the mass transport of the macromolecules along the swollen part of the fibre to the extremity. A broad range of the release kinetics can be programmed by taking into account these three factors. In the present paper, we demonstrate the realisation of a pulsatile release profile using fluorescein isocyanate dextran (FID), which is often explored as a macromolecular model drug [START_REF] Horita | Analysis of hair follicle penetration of lidocaine and fluorescein isothiocyanate-dextran 4 kDa using hair follicle-plugging method[END_REF][START_REF] Li | Self-assembled supramolecular hydrogels formed by biodegradable PEO-PHB-PEO triblock copolymers and acyclodextrin for controlled drug delivery[END_REF].

Materials and Methods.

2.1 Preparation of scrollable CA films. The 1% w.t. solution of chitosan (Sigma-Aldrich, 448877-50g, lot #MKBJ9698V, acetylation degree 20%) was prepared using aqueous solution of acetic acid (1% w.t.) as the solvent. One milliliter of the solution was cast on clean glass slides (7.5 cm × 2.5 cm) and gently dried at 70C until the formation of the solid film. The average thickness of the films was h=16 m. The films of the same thickness were obtained also by dip-coating of the glass slides from the 2.5% w.t. solution of CA in the 2.5% w.t. acetic acid, followed by drying at the same conditions. The 63m water. Acidity of the solutions was adjusted to pH3 by adding hydrochloric acid dropwise.

Gradient ionic crosslinking of the CA films was achieved by immersing the films for different times in the TPP solution, followed by immediate washing of the samples in DI water and drying with nitrogen stream. The films were rolled by detaching the stripes of the CA film mechanically from the substrate with a doctor blade and then transferring them onto the surface of DI water where the stripes rolled up within a few seconds of contact with water. Rolling experiments should be performed no later than a few hours after the films are prepared, in order to avoid aging effects.

Loading the CA fibres by FID.

The encapsulation and release experiments were conducted with fluorescein isothiocyanate dextran 500000-conjugate (Sigma Aldrich, 46947, Lot #BCBK4152V). Narrow (0.5mm wide , approx.) stripes of the FID solution were formed on the CA films manually with use of a glass capillary, connected to a syringe. After drying the drug solution, and forming the fibres by selfrolling on the water surface, the dried fibres were encapsulated in polydimetylsiloxane (PDMS) matrix (Sylgard 184 Kit). The ratio of PDMS to the curing agent was 30:1 (instead of the common 10:1 ratio), in order to reduce the stiffness of the matrix and facilitate the opening of pores after the fibers swelling.

Instrumentation and physical measurements.

Attenuated total reflection Fourier transform infra-red (ATR-FTIR) spectra of the face and the back sides of the films were measured on a Bruker IFS 66/S spectrometer (a diamond ATR cell). Time-dependent experiments for the release of fluorescent dextran have been performed using a FluoroMax-4 spectrofluorometer. The FID-loaded fibres, encapsulated in PDMS matrix, and open

The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 6 at one end by cutting, were introduced into a quartz cuvette that contained 3 ml of water at pH9. In this solution, the fibres were positioned on a grid at the upper side of the cuvette to maintain the optical detection window. The cell that was maintained at 25 °C was stirred continuously during the experiment.

Computer simulation.

The random walk model and the analytical solutions were implemented in the MATLAB R2015a programming environment.

Results

Chitosan acetate self-scrollable films.

Chitosan is a linear polysaccharide, derived by deacetylation reaction from chitin, a naturally abundant biopolymer, which is a characteristic component of cell walls of fungi, and of the exoskeletons of crustaceans and insects. In the chemical nomenclature, chitosan is designated as the random β-(1-4) linked copolymer of D-glucosamine (deacetylated unit) and N-acetyl-Dglucosamine (acetylated unit). Due to their remarkable biocompatibility, antibacterial, antifungal, and hemostatic properties, chitosan and its derivatives are broadly used in medicine and cosmetics [START_REF] Dutta | Chitin and chitosan: Chemistry, properties and applications[END_REF]. In particular, it is extensively used as the scaffold material of hydrogel drug delivery vessels [START_REF] Bhattarai | Chitosan-based hydrogels for controlled, localized drug delivery[END_REF][11][START_REF] Giri | Modified chitosan hydrogels as drug delivery and tissue engineering systems: present status and applications[END_REF]. Chitosan is not soluble in neutral water, but became such in acidic aqueous solutions for pH below 6, due to electrostatic charging of the chains via protonation of the amine groups. An aqueous solution of chitosan with acetic acid was used in our research and exhibits good film forming properties. The CA films were produced either by casting, or dip-coating of the CA solutions, as described in the Section 2.1.

As shown in our previous works, in order to impart a homopolymer films the self-scrolling ability in a suitable solvent, one should create the vertical gradient of swelling capacity, with one of the film sides being more swellable than the opposite one [START_REF] Luchnikov | Self-Rolled Polymer and Composite Polymer/Metal Micro-and Nanotubes with Patterned Inner Walls[END_REF][START_REF] Luchnikov | Self-Rolled Polymer Tubes: Novel Tools for Microfluidics, Microbiology, and Drug-Delivery Systems[END_REF][START_REF] Luchnikov | Novel Fibrous Material Created by Self-Rolling of a Patterned Polymer Thin Film[END_REF][START_REF] Gómez | Vapour processed self-rolled poly(dimethylsiloxane) microcapillaries form microfluidic devices with engineered inner surface[END_REF][START_REF] Saito | Self-scrolling ability of differentially acetylated chitosan film[END_REF]. For instance, the self-scrolling was observed in the films in which the gradient of the cross-linking density was created [START_REF] Luchnikov | Novel Fibrous Material Created by Self-Rolling of a Patterned Polymer Thin Film[END_REF]. According to the Flory-Renner theory [START_REF] Flory | Statistical Mechanics of Cross-Linked Polymer Networks II[END_REF]19], the degree of swelling of a polymer network decreases as the crosslinking density increases. The differential swelling generates the gradient of the in-plane stress and the bending moment. If the bending moment is sufficiently strong to overcome adhesion to the surface, or the film is free-standing, the film curls up and forms a tube or a scroll. Chitosan can be covalently crosslinked by glutaraldehyde [START_REF] Monteiro | Some studies of crosslinking chitosan-glutaraldehyde interaction in a homogeneous system[END_REF][START_REF] Wang | Preparation and characterization of uniform-sized chitosan microspheres containing insulin by membrane emulsification and a two-step solidification process[END_REF], or ionically crosslinked by sodium tripolyphosphate (TPP) [START_REF] Wang | Preparation and characterization of uniform-sized chitosan microspheres containing insulin by membrane emulsification and a two-step solidification process[END_REF]. The latter approach is attractive due to nontoxicity of TPP. The TPP-crosslinked chitosan-based hydrogels are stable in basic and slightly acidic (pH>3) water solutions, that makes the TPP ionic crosslinking suitable for our research.

Fabrication of ionically crosslinked CA films is schematically shown on the Fig. 1. The TPP bianion forms the electrovalent bonds with the -NH3 + groups of CA, realizing in this way the interor intra-chain links. The gradient of the crosslinking density is achieved due to brief (from few seconds to few dozens of seconds, depending on the thickness of the films) immersion of the slides with the CA films into the TPP solution. The gradient of the crosslinking density was confirmed by the attenuated total reflection Fourier transform infra-red (ATR-FTIR) spectra of the face and back sides of the dipped film and the reference spectrum of the fresh untreated film (Fig. 2). The spectrum of the bottom side resembles that of the untreated reference film. The spectrum of the face side differs significantly from these two spectra due to the clear presence of the P=O and P-O peaks. The brief exposure of the film to the TPP acidic solution therefore forms a vertical structural gradient in the CA films. The time of the film exposure to the TPP solution is important, since the structural gradient can be erased by overexposing the films to the crosslinking solution. The spectra of the face and bottom sides of the film kept in the TPP acidic solution for 1 h approach each other and are characterized by the strong peak that can be attributed to the P=O and P-O groups (Fig. S1, Supplementary Material).

The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 10

Fabrication of drug patterned µ-fibers.

Fig. 3 depicts the successive processing steps for the fabrication CA µ-fibers which are patterned with FID. Using a syringe filled with an aqueous solution of FID and caped with a very thin glass capillary, the drug patterns are manually drawn at the surface of CA films and consist in one or two parallel FID stripes. The dried CA film is then cut in small pieces, detached from the glass substrate and deposited at the surface of deionized water in such a way that the patterned side does not get in direct contact with water. The tubes which are generated by self-rolling effects after 2-3 seconds in aqueous medium are then extracted and dried at 30°C for a few hours. The tubes drying step induces the complete inner and outer shell collapsing of the structure leading to µfibers. Finally, the fiber is embedded in a polydimethylsiloxane (PDMS) matrix in such a manner that only one extremity of the fiber is accessible to the external environment.

The dimensions of the fibers are very sensitive to the experimental conditions. Fig. 4 presents the dependence of the fiber diameter as function of the exposure time of the CA film to the TPP solution (Fig. 4a) and as function of the concentration of the solution (Fig. 4b). Two thicknesses have been used for the films, h1≈16m and h2≈63m. For thicker films, the plot of the fibers diameter vs the exposure time to the TPP solution exhibits a minimum at 1min, approximately.

The existence of this minimum can be explained qualitatively. For a short exposure time, the depth for the penetration of TPP crosslinker within the chitosan film is relatively weak with respect to the film thickness. As a consequence, the superficial crosslinked part of the film hardly counterbalances the overall swelling of the major part of the film which results in a large diameter for the fiber. Increasing the exposure time should lead to the homogenization of the crosslinking density over the film thickness, as pointed above, suppression of the bending moment and, as a consequence, large fiber diameters. This observation is in line with the Timoshenko bilayer beam theory [START_REF] Timoshenko | Analysis of bi-metal thermostats[END_REF], which predicts zero curvature of the beam, either in the case when the thickness of one of the layers aspires to zero with respect to the thickness of the other layer, or in the case of almost identical volumetric response of the layers to an external factor [23]. The minimum of the fiber diameter would exist also for the thinner of the explored films, but it was technically impossible to put the films in contact with the TPP solution for the time shorter than approximately 3 sec. The fiber diameter diminishes monotonously with the TPP concentration for the both film thicknesses (Fig. 4b). The time of exposure of the films to the TPP solutions was 10 sec for the thinner films, and 1 min for the thicker ones.

The dependences shown on the Fig. 4 were obtained for the outer diameters of the fibers after the self-scrolling step in water (Fig. 5). One can distinguish on the optical microscopy images the diameter of the fiber. In these present experiments (Fig. 4 and Fig. 5), the 16m thick films were typically cut in the 1mm-wide stripes, and the 63m thick films were prepared as the 2mm-wide stripes. The resulted swelling was by about 210 % and 270 % for thin and thick films, respectively.

In this condition, 2 and 1.3 windings were typically observed for the corresponding fibers. It should be noted that larger stripes (approximately 5mm wide) of the 16m-thick films were used in the macromolecules release experiments presented in the following section. The scrolls formed from these stripes exhibit multiple windings, whose cross-section follows the shape similar to an Archimedean spiral, which reads in polar coordinates 𝑟(𝜃) = It was noted that the inner diameter 𝑑 diminishes with the number of windings, because the inner windings became squeezed by the outer ones. The comprensive analysis of the shape of the multishells fibers requires the energy minimization of the system with respect to the number of winding (or the inner diameter), and will be considered in a special study.

Programmed FID release from the patterned fibers.

The µ-fibers were immersed in deionized water and the resulting time-dependent structural changes have been monitored by fluorescence microscopy. Fig. 6a and6c show two distinctive The flux of FID from the fibers extremity.

Figure 8

The same as for the Fig. 7, for a fiber patterned with one stripe, located at 2.5 mm from the fiber extremity exposed to water. The macromolecules release is retarded by approximately 3.5 hours.

epifluorescence images which has been respectively recorded at initial and final swelling steps of the CA fiber. As shown in Figures 6a and6b, a swelling front clearly propagates along the fiber The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 15 axis from the external extremity to inner part of the device. Importantly, encapsuation in the PDMS allows the expansion of the fiber in the direction perpendicular to its axis, due to the low stiffness of the matrix, but inhibits its expansion in the axial direction, so that only a small fraction of the fiber expands out of the PDMS block. The swelling front propagates inside the PDMS block (Fig. 6a,b) with the rate of the order of 𝑉 = 0.09 mm/min, decreasing to 𝑉 = 0.05 mm/min in course of 20min of observation. The swelling front becames poorly identifiable as it propagates sufficiently far along the fiber axis. The FID mass transport starts when the swelling front reaches the patterned zone (Fig. 6c) allowing the progressive drug dissolution and the subsequent diffusion of FID all along the fiber as illustrated in Fig. 6d. Moreover, embedding of the fiber into PDMS matrix implies a one-dimensional mass transport so that the release time-dependent profile of the drug in the external environment should be mainly influenced and modulated by the distance separating the fiber extremity to the FID stripes as well as the distance between the stripes. This provides interesting possibilities for programming the drug release kinetics. Two scenarios have been developed and illustrated by the distinctive kinetics time-profiles displayed in Fig. 7 and8. Fig. 7 displays the release time-profile and the FID flux from a µ-fiber in which the first FID stripe is made at X = 1mm, and the second stripe is positioned at X = 4 mm. The macromolecules release starts approximately 40 minutes after immersion of the µ-fiber in the aqueous medium. A second delivery step is clearly detected at t  8 hours. The amplitude of the second pulse is several times smaller than the amplitude of the first one. This might be due to diffusional broadening of the pulse, as discussed in the following Section.

The flux curve from the fiber orifice, derived from the concentration time-profile and the known volume of the cuvette, clearly demonstrates the occurrence of two distinctive drug-delivery pulses separated by 7 hours. Fig. 8 shows the release kinetics from a µ-fiber with a FID patterning that consists in a single stripe located at X = 2.5mm from the fiber extremity. The release starts approximately 3.5 hours after immersion of the µ-fiber in the aqueous medium. After this delay, the release time-profile gradually slows down during the 8 hours of observation.

Theoretically, the timing of the pulses is determined by a) the position of the FID stripes in the patterned fiber, b) the rate of swelling front propagation, and c) the rate for the mass transport in the swollen part of the fiber due to convection and diffusion processes. In the absence of any convection phenomena, the characteristic diffusion time from the i-th drug spot is estimated as

𝑖 = 𝑋 𝑖 2 𝐷 ⁄
, where 𝑋 𝑖 is the distance from the spot to the fiber extremity, and 𝐷 is the diffusion coefficient. The diffusion coefficient of high molecular weight (~500kDalton) dextran in water was estimated as ≈ 8 • 10 -5 𝑚𝑚 2 𝑠 -1 = 8 • 10 -11 𝑚 2 𝑠 -1 [START_REF] Seksek | Translational Diffusion of Macromolecule-sized Solutes in Cytoplasm and Nucleus[END_REF]. For two FID stripes respectively positioned at X1 = 1 mm and X2 = 4 mm, the characteristic diffusion times are about 3.5 hours and 56 hours which are much longer than those measured. Moreover, the experimental times for the macromolecules release do neither correspond to a simple convective time associated to the rate of the swelling front. This means that a non-diffusional mechanism of the mass transfer should play a role in the macromolecules release process from the pore. Possibly, it is related to the flow of water inside the swelling and opening pore. Although the rate of this flow is extremely low, it may provoke local convectional action, due to the imperfections on the walls of the capillary. Air microbubbles entrapped in the dry fiber may be also relevant to the relatively fast escape of the macromolecules from the fiber. More detailed research of the swelling and the mass transfer processes in the fibers is needed for the better understanding of the release mechanisms in the system.

Modeling of the FID release kinetics.

The Programming of a diffusion-controlled drug release kinetics via the nonuniform distribution of the drug in a hygrogel matrix was proposed for the first time in the pioneering works of P.I. Lee [START_REF] Lee | Effect of non-uniform initial drug concentration distribution on the kinetics of drug release from glassy hydrogel matrices[END_REF][START_REF] Lee | Initial concentration distribution as a mechanism for regulating drug release from diffusion controlled and surface controlled matrix systems[END_REF]. In our system, the macromolecules diffuse not through the swollen matrix, but along the tubular marcopore. The comprehensive theoretical description of the drug release from the gradually opening pores should take into account a multitude of the materials characteristics, such as the drug interaction with the pore's walls, possible hydrodynamics effects, mentioned above, and the dependence of the diffusion coefficient on the drug concentration in the solution. In general, the process is highly nonlinear and its predicting would require an elaborated numerical model. Nevertheless, some essential features of the process can be illustrated in frames of a simple theoretical approach and a random-walk model which we propose in this Section. We suppose that drug transport inside the swollen part of the fiber can be represented by the Fick's law, 𝑗 ⃗ = -𝐷∇𝐶, where 𝑗 ⃗ is the flux, 𝐶 is concentration, and 𝐷 is an effective diffusion coefficient.

Assuming that the diffusion takes place essentially along the fibers axis and that the concentration is homogeneous over any cross-section of the fiber, the evolution of the drug concentration in the swollen part of the fiber is described by the linear one-dimensional diffusion equation,

𝜕𝐶(𝑥,𝑡) 𝜕𝑡 = 𝐷 𝜕 2 𝐶(𝑥,𝑡) 𝜕𝑥 2 (1)
with the boundary conditions

𝐶(0, 𝑡) = 0; 𝜕𝐶(𝑥,𝑡) 𝜕𝑥 | 𝑋 𝑆 (𝑡) = 0 (2)
The conditions (2) signify the instant dispersion of the drug into the environment from the fiber extremity at 𝑥 = 0, and the absence of the drug transport through the swelling front, situated in the moment 𝑡 at the coordinate 𝑋 𝑆 (𝑡). The flux 𝐹(𝑡) from the orifice is calculated as

The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022

In general case, the solution (1) with the nonstationary conditions (2) is not possible in analytical form. In order to address the problem, we consider a random walk model [START_REF] Weiss | Aspects and Applications of the Random Walk, Random Materials and Processes[END_REF]. A fiber is represented by a finite 1-dimensional chain of 𝑀 sites, with the distance between the sites being ∆𝑥. The macromolecules are represented by 𝑁 "walkers", distributed over the sites. Each walker can jump to a neighboring site (left or right to its current site) with the probability 𝑝 within the time interval ∆𝑡. In the limit ∆𝑥 → 0 , ∆𝑡 → 0, 𝑁 → ∞, 𝑀 → ∞, the diffusion coefficient in the random walk model (RWM) is 𝐷 = of (1) for the static boundary conditions 𝑋 𝑆 = 𝑋 = 𝑐𝑜𝑛𝑠𝑡 (see the Fig. S3, the associated text in the Supplementary Material, and the Ref.

[28]), which reads

𝐹 𝑋 (𝑡) = ∑ (-1) 𝑛 2𝐴𝐷  𝑛 𝑋 ∞ 𝑛=0 𝑒𝑥𝑝(-𝐷 𝑛 2 𝑡) ( 5
)
Here 𝐴 is the integral amount of the walkers,  𝑛 = (2𝑛+1)𝜋

2𝑋

, and all the walkers are supposed to be concentrated initially at 𝑥 = 𝑋. It is assumed that 𝐹(𝑡) ≡ 0 for 𝑡 ≤ 0. The total amount of the released walkers is

𝛷 𝑋 (𝑡) = ∫ 𝐹 𝑋 (𝜏) 𝑡 0 𝑑𝜏 = ∑ (-1) 𝑛 2𝐴 𝑋 𝑛 ∞ 𝑛=0 [1 -𝑒𝑥𝑝(-𝐷 𝑛 2 𝑡)] (6)
The moving boundary between the swollen and dry parts of the fibers is taken then into account by assuming that the walkers become mobile (can jump to the neighboring sites) if they are positioned left to the current coordinate of the swelling front. Also, the walkers cannot pass from

where 𝑣 0 is the initial swelling front propagation rate, and 𝑋 0 is a characteristic length, at which the propagation rate slows down by 𝑒 = 2.718 … times. Unfortunately, it was not possible instrumentally to measure the swelling front propagation parameters directly during the fluorometry acquisition. Moreover, the position of the swelling front became poorly identifiable as it penetrates into the PDMS matrix to the depth of 1.5-2mm. Finally, the swelling front propagation may vary from one fiber to another, due to imperfections of their structure. For these reasons, the functional form of the swelling front coordinate (6) only reflects the progressive decrease of the propagation rate, while 𝑣 0 and 𝑋 0 are the fitting parameters of the model, as well as the diffusion coefficient, and the scaling factor 𝑓 which relates the number of the released walkers to the concentration of macromolecules.

Fig. 9 depicts the the experimental data, obtained for the fiber patterned by 2 FID stripes at 𝑋 1 = 1𝑚𝑚 and at 𝑋 1 = 4𝑚𝑚 from the orifice exposed to water basic solution (Fig. 7) fitted by the RWM and by the analytical solutions

𝛷(𝑡) = 𝛷 𝑋 1 (𝑡 -𝜏 1 ) + 𝛷 𝑋 2 (𝑡 -𝜏 2 ) (8)
𝐹(𝑡) = 𝐹 𝑋 1 (𝑡 -𝜏 1 ) + 𝐹 𝑋 2 (𝑡 -𝜏 2 ) (9)
where

𝜏 𝑖 = 𝑋 𝑖 𝑣 0 [𝑒𝑥𝑝(𝑋 𝑖 𝑋 0 ⁄ ) -1]
is the time lag corresponding to the time when the swelling front reaches the position of the 𝑖-th FID stripe. The diffusion coefficient, and the parameters 𝑣 0 , 𝑋 0 , and 𝑓 of the RWM were defined by iterative process, the least square method being not applicable in this case. The diffusion coefficient of the analytical model is equal to that obtained via the fitting of the experimental data by the RWM. The equations ( 8), ( 9) are the superpositions of the solutions They describe the flux from the fiber without taking into account the finite rate of the swelling front propagation. The experimental data are fitted much better by the solution of the RWM, which incorporates the swelling front propagation rate. It means that the diffusion of the macromolecules in the direction of the swelling propagation (that is, opposite to the fiber orifice) leads to nonnegligible effects. Diffusion of the macromolecules over all the swollen part of the fiber seems to be responsible for the slow, but distinctive release between the 2 nd and the 7 th hours of the experiment, after the first release burst.

Surprisingly, the experimental release rate from the second FID stripe is significantly more intense than the release predicted by the analytical and by the random walk models. Further experiments are needed to elucidate the origin of this discrepancy.

The RWM matches reasonably well the experimental data also for the fiber with the single FID stripe situated at 𝑋 = 2.5𝑚𝑚 from the orifice. As expected, the retarded release is less intense than the kinetic from the spot at 𝑋 = 1𝑚𝑚, observed for the previous experimental system, due to diffusional broadening (see Fig. S4, Supplementary Material). Here again, the finite rate of the swelling front propagation should be taken into account in order to attain the satisfactory fitting of the experimental data by the model. diffuse out of the media. Programming of the release kinetics is feasible due to the possibility to create complex distributions of the drug along the fiber axis, via patterning of the polymer films prior to scrolling. Slow rate of swelling front propagation along the axis of the fibers enables good resolution of the release pulses originating from the neighboring spots in the patterned fiber.

The kinetics of the release can be fitted over the period of several hours in frames of the random walk model, which allows to take into account the finite rate of the swelling front propagation from the orifice of the fiber into the depth of the PDMS matrix encapsulating the fiber. Less precisely, the release can be represented by analytical solution of the diffusion equation with the quasi-stationary boundary conditions. The release pulses experience diffusional broadening which is as larger as the the initial materil location is further from the orifice of the fiber. This underlines the difficulty of programming short and intense drug release impulses on large time intervals. The future model should take into account the adsorbtion-desorbtion interaction of the molecules with the inner surface of the fibers. This factor is especially important for the submicron and few micron wide pores because of the high surface to volume ratio for these pores.

The material of the fibers is not limited to chitosan acetate. It can be any biocompatible polymer, to which one can impart the self-scrolling ability. In particular, collagen UV-crosslinked in the presence of riboflavin [START_REF] Tirella | Riboflavin and collagen: New crosslinking methods to tailor the stiffness of hydrogels[END_REF] might be also interesting as a potential material for the preparation of the self-scrollable films for the macromolecular drug encapsulation and controlled release.

The effective diffusion coefficients of FID, found in our fitting study, are approximately twoand sixfold larger than the diffusion coefficient of dextran of comparable molecular mass reported in the Ref. [START_REF] Seksek | Translational Diffusion of Macromolecule-sized Solutes in Cytoplasm and Nucleus[END_REF]. This is a reasonable difference, taking into account the presumed existence of the convectional flows in the fibers which undergo significant increase of their diameters due to swelling. Yet, the large variation of the diffusion coefficients for the FID release in our system, and the large discrepancy of the fiber swelling parameters point out on the imperfection of the fibers structure. Further efforts are needed for the unification of the CA fibers characteristics for the truly reliable programming of the therapeutic macromolecules.

Conclusion.

In summary, we have developed a new macromolecules release system, capable of the time programming of the release kinetics. In this way, it might be possible to combine two modern trends of the pharmacological research, that is, the chronopharmacology and the use of the macromolecular theurapeutics agents. Our release system consists of the macromolecules-loaded

Figure 1 .

 1 Figure 1. Fabrication of the CA films (scheme). The ionic crosslinking gradient is imparted to the films by their exposure to the TPP solution for a few seconds. The face side of the film, cased on a glass slide, became more densely cross-linked, than the back side, which is adjacent to the slide.

Figure 2 .

 2 Figure 2. ATR-FTIR spectra of m-thick films treated with TPP acidic solution for 3 sec.

Figure 3 .

 3 Figure 3. Formation of the fibers, loaded by the model drug, and the drug release experiment (scheme).

  The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 11

Figure 4 .

 4 Figure 4. Diameter of the rolled fibres as the function of (a) the time of films treatment in the TPP solution (TPP concentration is w.t. 4%), and (b) the concentration of the TPP solution. Filled squares: the film thickness ℎ 1 =16m. Open squares: the film thickness ℎ 2 =63m. For the (b), the treatment time is 10 sec for ℎ 1 and 60 sec for ℎ 2 .

12 Figure 5 .

 125 Figure 5. Optical microscopy images of CA fibers, right after the formation in water. (a) A fiber formed by the self-rolling a 16m thick film, after the treatment of the film in TPP solution (w.t. 4%, pH≈3) for 10 sec. The

13 Figure 6 .

 136 Figure 6. Drug release from the patterned fiber (epifluorescence microscopy). (a) Propagation of the swelling front from the extremity to the inner part of the fiber. (b) Magnified image of the swelling front. (c) Diffusion of FID along the fiber (d) The side view scheme of a patterned fiber, embedded in PDMS matrix, before (top) and after (bottom) insertion in water solution. The open horizontal arrows symbolize the swelling front propagation. The curved narrow arrows indicate the drug escape from the fiber.

Figure 7

 7 Figure 7 Kinetics of the macromolecules release from a fiber patterned with two FID stripes, positioned at 1mm and 4mm from the fiber extremity, which is in contact with water. (a) FID concentration in water as the function of time. Concentration of FID released from the tube to the aqueous environment has been determined according to a linear calibration curve between the fluorescence intensity of dextran at 511 nm as function of concentration the polymer introduced in the probing aqueous medium as depicted in Fig. S2 of the Supplementary Material. (b)

Figure 9 .

 9 Figure 9. Fitting of the FID release experimental data (solid red lines) presented on the Fig.7 by the random walk model with the moving swelling front (dashed blue line), and by the analytical solution for the quasistationary boundary conditions (dash-dotted green line). The parameters of the RWM: ∆𝑡 = 0.00014 ℎ𝑜𝑢𝑟𝑠; ∆𝑥 = 0.05𝑚𝑚; 𝑝 = 0.067; 𝑣 0 = 2.1𝑚𝑚ℎ𝑜𝑢𝑟 -1 ; 𝑋 0 = 2.2𝑚𝑚; the initial numbers of walkers at 𝑋 1 and 𝑋 2 is 𝑁 1 = 𝑁 2 = 10000, respectively; 𝑓 = 5.29 • 10 -5 ; 𝑋 1 = 1𝑚𝑚; 𝑋 2 = 4𝑚𝑚; 𝐷 = 0.6𝑚𝑚 2 ℎ𝑜𝑢𝑟 -1 ≈ 1.6 • 10 -10 𝑚 2 𝑠 -1 . The lag times of the analytical model are 𝜏 1 = 0.60 ℎ𝑜𝑢𝑟, 𝜏 2 = 5.40 ℎ𝑜𝑢𝑟𝑠. (a) The total amount of the released walkers vs FID concentration in the cuvette. (b) The FID flux from the fiber orifice vs the normalized flux of the walkers.

Figure 10 .

 10 Figure10. The same as for the Fig.9, for the fiber patterned by a single FID stripe positioned at 𝑋 = 2.5𝑚𝑚 from the orifice (see Fig.8). The parameters of the RWM: ∆𝑡 = 0.00014 ℎ𝑜𝑢𝑟; ∆𝑥 = 0.05𝑚𝑚; 𝑝 = 0.15; 𝑣 0 = 1.1𝑚𝑚ℎ𝑜𝑢𝑟 -1 ; 𝑋 0 = 5.0𝑚𝑚; 𝑁 = 10000; 𝑓 = 2.56 • 10 -5 ; 𝑋 = 2.5𝑚𝑚; 𝐷 = 1.34𝑚𝑚 2 ℎ𝑜𝑢𝑟 -1 ≈ 3.6 • 10 -10 𝑚 2 𝑠 -1 . The lag time of the analytical model is 𝜏 1 = 2.94 ℎ𝑜𝑢𝑟𝑠.

  self-rolled chitosan acetate microfibers, embedded in a hydrophobic matrix. Transforming the fibers into tubular macropores upon the swelling step enables the transport of the macromolecules into the environment. Non-trivial time-programmed release kinetics can be achieved via discrete distribution of drug along the fiber axis. Here we demonstrated an original pulsatile time-profile for the drug delivery kinetics. The experimental data are fitted by the random walk model and the analytical solution of the diffusion equation.

  The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 5 thick films were produced by dip coating from the 5% w.t. solution of CA in the 5% w.t. acetic acid. A set of TPP solutions (1%, 2%, 3%, 4%, 6%, and 8% w.t.) was prepared in deionized (DI)

  manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 17

  The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 20 the swollen region to the not swollen one. The coordinate of the swelling front is assumed to be

	in the form
	𝑋 𝑆 (𝑡) = 𝑋 0 𝑙𝑛 (1 +	𝑣 0 𝑡 𝑋 0	)

  The manuscript published in Journal of Controlled Release, 2016, 233, 39-47. https://doi.org/10.1016/j.jconrel.2016.05.022 22

	6. Discussion.
	Self-rolled polymer fibers used as water-soluble macromolecules carriers allow achieving time-
	controlled release kinetics. The release of the macromolecules is enabled by the open geometry

of the swollen parts of the fibers, which acquire open tubular geometry after the swelling step. The macromolecules, immobilized initially in a collapsed dry fiber, became then mobile and can freely

Acknowledgements

V.A.L. thanks the financial support by the French National Research Agency, award no. ANR-13-IS09-0002-01.

Supplementary Material

Time-Programmed Release of Fluoroscein Isocyanate Dextran From Micro-Pattern-Designed Polymer Scrolls.

Aleksandr I. Egunov, 1 Ayano Inaba, 2 Simon Gree, 1 Jean-Pierre Malval, 1 Katsuhiro Tamura, 2 Yukie Saito, 3 For the sake of simplicity, we assumed the initial distribution 𝐶 0 (𝑥) to be pointlike,

where 𝛿(𝑥 -𝑋) is the Diracs delta-function, and 𝐴 is the integral amount of the drug in the stripe.

The solution of (1) with the boundary conditions (4) and initial distribution (5) reads [START_REF] Lee | Effect of non-uniform initial drug concentration distribution on the kinetics of drug release from glassy hydrogel matrices[END_REF]:

where

. Taking the derivative (3) gives the solution for the drug release kinetics from the spot:

The total amount of the released walkers is


Viet-Phi Huynh

Jixiong Liu

Yoan Chabot

Frédéric Deuzé

Thomas Labbé

Pierre Monnin

Raphaël Troncy

Dagobah

DAGOBAH: Annotation sémantique de données tabulaires par comparaison du contexte des tables et d'un graphe de connaissances

Keywords: Interpretation sémantique de tables, DAGOBAH, SemTab Semantic Table Interpretation, DAGOBAH, SemTab 1. Semantic Web Challenge on Tabular Data to Knowledge Graph

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

Introduction

Les données tabulaires constituent une source importante de connaissances, une grande partie des gisements internes des entreprises et du Web étant représentée sous cette forme. Par conséquent, il existe un vif interêt pour le domaine de l'interprétation automatique de données tabulaires (en anglais Semantic Table Interpretation ou STI). Ce domaine est caractérisé par le développement de méthodes d'interprétation automatique de tables à l'aide d'un graphe de connaissances via trois tâches principales. La tâche Cell-Entity Annotation (CEA) consiste à associer chaque cellule de la table avec une entité du graphe de connaissances. Par exemple, la mention "Belfort" de la Figure 1 sera annotée avec l'entité Q171545 (Belfort) du graphe de connaissances Wikidata. La tâche Column-Type Annotation (CTA) vise à annoter chaque colonne avec une classe. Par exemple, la première colonne "City" de la Figure 1 sera annotée avec l'entité Q484170 (commune française). Enfin, la tâche Columns-Property Annotation (CPA) vise à associer chaque paire de colonnes à une propriété. Par exemple, la relation entre les colonnes "City" et "Region" dans la Figure 1 serait la propriété P361 (fait partie de). Les annotations ainsi générées peuvent être utilisées dans de nombreux cas d'utilisation, de l'indexation des jeux de données et leur recommandation jusqu'à l'enrichissement de graphes de connaissances. Les algorithmes de STI DAGOBAH, développés conjointement par Orange et EURECOM, ont été évalués lors des différentes éditions du challenge international Sem-Tab 1 [START_REF] Cutrona | Results of SemTab[END_REF][START_REF] Jiménez-Ruiz | Sem-Tab 2019 : Resources to Benchmark Tabular Data to Knowledge Graph Matching Systems[END_REF][START_REF] Jiménez-Ruiz | Results of SemTab 2020[END_REF], colocalisé avec la conférence ISWC. Cet évènement centré sur les problématiques d'annotations de données tabulaires a attiré près de 50 équipes participantes au cours des trois dernières éditions. Comme démontré lors de ce challenge, nos outils ont atteint un niveau de maturité permettant de répondre à des problématiques industrielles dans le groupe. En effet, Orange est une multinationale opérant dans un grand nombre de domaines métiers (e.g. télécommunications, contenu multimédia, cybersécurité, etc.). Par conséquent, Orange produit de grands volumes de données tabulaires hétérogènes. A l'aide des techniques de STI, ces données peuvent être exploitées stratégiquement, par exemple, en structurant les connaissances dormantes dans ces données et en les rendant exploitables par le biais de moteurs de type questions-réponses [START_REF] Chabot | A Framework for Automatically Interpreting Tabular Data at Orange[END_REF]. Le challenge SemTab2021 et les besoins industriels mentionnés ci-dessus ont motivé des travaux de recherche qui constituent le coeur des algorithmes utilisés par le système DAGOBAH SL présenté en 2020 [START_REF] Huynh | DAGO-BAH : enhanced scoring algorithms for scalable annotations of tabular data[END_REF] et amélioré en 2021 [START_REF] Huynh | DAGOBAH : Table and Graph Contexts For Efficient Semantic Annotation Of Tabular Data[END_REF]. En particulier, le calcul de scores et le classement des entités ont été optimisés grâce à :

-Une amélioration des stratégies d'indexation et de mise en correspondance des entités pour améliorer la qualité et la couverture de la recherche de candidats (i.e. lookup) ; -Une meilleure représentation et désambiguïsation des entités en exploitant plus efficacement leurs contextes (i.e. voisinage) dans le graphe de connaissances ; -Un algorithme de notation (i.e. scoring) des entités amélioré et plus flexible exploitant à la fois des informations locales et des informations globales à la table étudiée. Ces nouvelles contributions ont donné naissance au système DAGOBAH SL 2021 décrit dans la Section 3. Nous présentons les résultats de l'évaluation menée dans le cadre du challenge dans la Section 4. La Section 5 introduit les efforts autour de l'utilisabilité des systèmes d'annotation avec en particulier la mise à disposition d'une API REST TableAnnotation ainsi qu'une interface utilisateur nommée DAGOBAH UI. Enfin, la Section 6 offre des éléments de réflexions autour du challenge SemTab et de l'adoption des outils de STI au sein des entreprises.

Etat de l'art

L'approche courante pour réaliser la tâche de CEA consiste à effectuer des opérations de recherche syntaxique (e.g. Levenshtein), d'alignement d'ontologies ou d'exploitation de plongements [START_REF] Limaye | Annotating and searching web tables using entities, types and relationships[END_REF]. La désambiguïsation des entités candidates est ensuite traitée comme une tâche de classement des candidats, en utilisant des heuristiques, des algorithmes tels que PageRank [START_REF] Efthymiou | Matching web tables with knowledge base entities : From entity lookups to entity embeddings[END_REF] ou des modèles basés sur les graphes [START_REF] Ibrahim | Making sense of entities and quantities in Web tables[END_REF]. Les principales approches sur le typage de colonnes (CTA) infèrent des classes à partir des entités produites par la tâche CEA. Des heuristiques plus ou moins complexes construites autour du vote majoritaire sont utilisées [START_REF] Mulwad | Using linked data to interpret tables[END_REF]. Enfin, l'extraction de relations (CPA) est généralement réalisée par la recherche de paires d'éléments en colonnes, i.e. types et entités préalablement choisis [START_REF] Ran | Domain-specific knowledge base enrichment using wikipedia tables[END_REF]. Récemment, le challenge SemTab a permis d'accélérer le développement des approches de STI. Une majorité d'entre elles prennent la forme de systèmes basés sur la recherche de candidats dans DBpedia et Wikidata, le calcul d'une similarité syntaxique et des votes majoritaires [START_REF] Abdelmageed | JenTab Meets SemTab 2021's New Challenges[END_REF][START_REF] Chen | Linkingpark : An integrated approach for semantic table interpretation[END_REF][START_REF] Cremaschi | MantisTable SE : an Efficient Approach for the Semantic Table Interpretation[END_REF]. MTab4Wikidata [START_REF] Nguyen | SemTab 2021 : Tabular Data Annotation with MTab Tool[END_REF] adopte la correspondance floue et la "recherche à deux cellules" pour améliorer la prise en charge des fautes d'orthographe et des ambiguïtés dans le contenu des tableaux. Ce système a remporté le premier prix des défis SemTab 2019 et SemTab 2020.

Système DAGOBAH SL 2021

DAGOBAH est un processus de bout en bout annotant des tables relationnelles avec des éléments d'un graphe de connaissances tel que Wikidata. Ce processus se compose de quatre étapes exécutées en séquence tel qu'illustré dans la Figure 1. Etant donné une table relationnelle en entrée, l'étape de pré-traitement détermine un ensemble de métadonnées de la table ainsi que les cibles de l'annotation (Section 3.1). Le module de recherche de candidats collecte ensuite des entités candidates dans le graphe de connaissances pour chaque cellule cible de la table (Section 3.2). Le module de notation préliminaire évalue chacun de ces candidats afin de déterminer un score de confiance (Section 3.3). Les étapes suivantes visent à générer les annotations CTA ainsi que les annotations CPA (Section 3.4). Enfin, les annotations précédentes sont mises à contribution pour générer les annotations CEA (Section 3.4). une mention contenue dans une cellule et l'ensemble des labels de chaque entité candidate. Ce mode de fonctionnement permet de traiter au mieux les chaines de caractère présentant des ordonancements des sous-chaînes différents (e.g. "Elon Musk" et "Musk Elon"). × e γ(Scsim(ec,em)- -----→ Bourgogne Franche Comté. Seuls les sous-graphes à un saut étant pris en compte, les chemins de prédicats résultant ont une longueur maximum de deux. Cette approche permet d'enrichir les informations sur une entité en incluant non seulement les voisins directs mais également les voisins indirects à une distance de deux sauts. Ces contextes enrichis du graphe permettent d'augmenter les chances de correspondance avec une cellule voisine n i ∈ N table (e m ) et rendent ainsi le score de contexte plus précis. Après des tests, nous faisons l'hypothèse que pour l'interprétation de tables avec Wikidata, des chemins de taille supérieure à deux sont peu significatifs et apportent du bruit pouvant impacter négativement la pertinence du score de contexte.

Pré-traitement des données tabulaires

Notation préliminaire des candidats

Sc context (N graph (e c ), N table (e m )) = i w i × sn i i w i (2)

Notation souple du contexte

Dans l'Equation (2), les scores de correspondances du voisinage sn i sont pondérés pour calculer le score final d'une entité. En effet, chaque cellule voisine n i ∈ N table (e m ) contribue à un niveau différent à l'annotation de la cellule cible e m avec un poids w i défini par l'Equation (3) :

w i = (3a) se i d(col i ) + 1 (3b) × (3c) cnt(col i ) × (3d)
τ (e i ) .

(

τ (e i ) = τ (e c p1 -→ v p2 -→ e i ) = 1 1 + log(g(v)) (4)
où g(v) est la généricité du noeud intermédiaire v, i.e. le nombre de ses relations entrantes et sortantes dans le graphe de connaissances. Il est à noter que les voisins directs (i.e. les chemins de longueur 1) obtiennent toujours une valeur de vérité de 1.0.

Tâches d'annotation 3.4.1 Annotation des propriétés de colonnes (CPA)

La tâche de CPA identifie la relation sémantique r la plus adaptée pour une paire ordonnée de colonnes. Nous adoptons une stratégie de vote majoritaire reposant sur les occurrences et les scores de confiances cumulés des lignes pour r (pour plus de détails, voir [START_REF] Huynh | DAGO-BAH : enhanced scoring algorithms for scalable annotations of tabular data[END_REF]). Il est à noter que, conformément à la Section 3.3, r peut être un chemin de prédicats de longueur 1 (i.e., tion du contexte de graphe à deux sauts semble donc être un ajout bénéfique permettant de récupérer des informations pertinentes. Les meilleures performances des configurations 3 et 4 vis à vis de la configuration 2 montre l'efficacité de la notation de contexte souple. Nous notons que la configuration 3 atteint des performances proches de la configuration 4. Ainsi, les chemins unidirectionnels (i.e. ---------United States of America) est limitée par le calcul de score de contexte souple qui évite une dégradation de la qualité de l'annotation. Cela permet aux chemins bidirectionnels pertinents de contribuer positivement au score de l'entité. On peut observer que les performances du CTA et du CPA ne sont pas aussi élevées qu'envisagé sur la plupart des corpus, et ce, malgré de bonnes performances de CEA. Le développement de stratégies plus performantes pour la sélection du type et des relations fera l'objet de travaux futurs.

Corpus BioDivTab et GitTables

Il est à noter que pour les corpus BioDivTab et GitTables, nous avons adapté les algorithmes DAGOBAH présentés dans cet article. En effet, pour le corpus BioDivTab, les types primitifs générés par le pré-traitement ont été utilisés pour discriminer les colonnes "entités" et les colonnes contenant des littéraux. Une colonne contient des littéraux si elle contient des valeurs numériques, des dates, des unités ou des valeurs diverses. Sinon, la colonne est considérée comme une colonne d'entités et ses mentions peuvent donc être utilisées par le module de recherche de candidats. Pour le corpus GitTables, des règles de correspondance ont été définies entre les types primitifs et des classes de Schema.org et de l'ontologie DBpedia.

L'interprétation de données tabulaires à Orange

Pour améliorer la pertinence de DAGOBAH sur des cas d'utilisation industriels réels, nous avons adopté une approche Test & Learn. Dans cette optique, les algorithmes de DAGOBAH sont mis à disposition au sein de l'entreprise pour permettre aux collaborateurs internes de tester les outils d'annotation. Cette mise à disposition s'effectue via deux vecteurs : une API REST nommée TableAnnotation et une interface graphique nommée DAGOBAH UI.

API TableAnnotation

Cette API REST est déployée sur le portail Orange Developer. 6 Elle fournit des services de pré-traitement de données tabulaires, d'annotation sémantique et également de recherche d'entités candidates permettant, à partir d'une Nous avons récemment proposé une classification reflétant l'hétérogénéité des tables que l'on peut rencontrer ainsi qu'un inventaire exhaustif des méthodes, à base de règles et d'heuristiques, ou à base d'apprentissage profond pour l'interprétation sémantique de données tabulaires [START_REF] Liu | From Tabular Data to Knowledge Graphs : A Survey of Semantic Table Interpretation Tasks and Methods[END_REF]. Nos travaux en cours se concentrent sur l'interprétation de tables où une grande part des mentions d'une colonne ne trouve pas de correspondance, ou avec peu de lignes et donc peu de contexte. Dans ces cas difficiles, nous cherchons à tirer profit des modèles de langage et des méthodes de plongement de graphes qui pourraient apporter un complément intéressant aux stratégies de calcul de score de contexte.

Conclusion

Dans cet article, nous avons présenté les améliorations apportées au système DAGOBAH [START_REF] Chabot | DAGOBAH : Un système d'annotation sémantique de données tabulaires indépendant du contexte[END_REF]. Grace à un mécanisme de recherche de candidats optimisé, l'enrichissement des contextes du graphe et la notation souple, DAGOBAH a obtenu la meilleure performance lors du challenge Sem-Tab2021. 7 Les travaux futurs auront pour objectif d'augmenter la précision de l'annotation sur des tables présentant des mentions très ambiguës. Nous avons notamment l'ambition d'exploiter des dictionnaires fournissant des abréviations ou des acronymes. Pour assurer la généricité de notre approche, de tels dictionnaires devraient être construits à partir de grandes quantités de documents et être applicables à divers ensembles de données.

L

  'étape de notation préliminaire évalue la pertinence des entités candidates e c ∈ E c (e m ) d'une cellule e m à l'aide d'un score : P Sc(e c , e m ) = Sc context (N graph (e c ), N table (e m ))

  DAGOBAH SL 2021 résout deux problèmes de DAGO-BAH SL 2020 inhérents au calcul du score de contexte : Evaluation coûteuse. Chaque sn i était évalué en itérant sur l'ensemble des noeuds dans N graph (e c ) pour trouver la meilleure correspondance. Par conséquent, un problème de performance survient lorsque l'algorithme doit noter une entité très générique du graphe de connaissances présentant des centaines voire des milliers de propriétés. Par exemple, considérons la cellule "Belfort" dans la Figure 1 et l'entité Wikidata candidate Q171545. Pour vérifier si la cellule "Bourgogne Franche Comté" est dans le contexte de Q171545, nous devons effectuer une comparaison avec chacun des ∼ 1000 noeuds de N graph (Q171545) ce qui inclus Q142 (France), Q3371185 (Paul Faivre), etc. (Figure 2a).

FIGURE 2 -

 2 FIGURE 2 -Contexte (i.e. voisinage) de l'entité Q171545 (Belfort) dans le graphe Wikidata. (a) Contexte à un saut de Q171545. (b) Le contexte est étendu via l'intersection de sous-graphe.

( 3d )FIGURE 3 -

 3d3 FIGURE 3 -Les noeuds voisins de Belfort (Q171545) contribuent de manière différente à son contenu informationnel.

  apportent suffisamment d'informations et permettent d'obtenir des résultats équivalents par rapport à la configuration considérant à la fois les chemins unidirectionnels et bidirectionnels. De plus, l'influence négative du bruit apporté par les chemins bidirectionnels (e.g. Belfort country ----→ France diplomaticRelation ← -

  Les cellules n i appartenant à une colonne voisine très connectée à la colonne cible devrait avoir un plus grand poids dans le contexte. Par conséquent, nous prenons en compte la connectivité cnt(col i ) d'une cellule voisine par rapport à la colonne cible. La connectivité est définie ici comme le nombre d'occurrence de la propriété la plus souvent observée entre les deux colonnes.

) (3a) Les cellules contenant des entités devraient avoir une plus grande importance que les cellules contenant des littéraux (e.g. date, mesure avec ou sans unités, nombre) compte tenu du manque de méthodes de désambiguïsation des littéraux (e.g. normalisation des dates, détection des unités/normalisation/conversion). C'est la raison pour laquelle nous fixons la valeur de se i à 1.0 dans le cas où la cellule voisine n i contient une entité et à 0.15 si n i contient un littéral. (3b) Une cellule voisine sur la partie gauche de la table a plus de chance d'être un contexte significatif pour la cellule cible. Par conséquent, d(col i ) est la distance entre la colonne col i et la première colonne de type "entité" de la table.

(3c)

  Il est à noter que le nombre d'occurrences du CTA/CPA est divisé par 2 pour accorder davantage d'importance au score préliminaire P Sc(e c , e m ).

	Configuration 4 Ce paramétrage restreint la configu-
	ration 3 au voisinage à un saut et aux voisins liés
	par un chemin unidirectionnel de longueur 2 dans le
	graphe. Cette configuration permet d'évaluer l'im-
	pact des chemins bidirectionnels qui semblent être
	moins informatifs (et amenant parfois du bruit) mais
	utiles dans certains cas bien ciblés.
	4.2 Résultats
	4.2.1 Evaluation expérimentale
	Les résultats pour les quatre configurations définies précé-
	demment sont donnés dans la Table 1. Il est à noter que les
	performances de DAGOBAH se sont continuellement amé-
	liorées tout au long du challenge SemTab2021. Ainsi, les
	résultats de l'évaluation sont basés sur la dernière version
	de DAGOBAH mais nous indiquons également les résul-
	tats soumis lors des différentes phases du challenge dans
	les cellules grisées ainsi que le meilleur score parmi les
	participants du challenge 5 , pour comparaison. Afin de vali-
	der la pertinence des modifications proposées dans les Sec-
	tions 3.2 et 3.3, nous incluons également les scores du sys-
	tème DAGOBAH 2020 pour les tables du Round 1 annotées
	à l'aide de Wikidata. Les configurations des soumissions
	{1,2,3,4}* sont similaires aux configurations {1,2,3,4} dé-
	finies précédemment avec quelques adaptations sur l'initia-
	lisation des scores et des poids. Cela n'impacte toutefois
	pas les scores de CEA mais a en revanche un impact sur les
	performances du CTA. En effet, le CTA est très sensible aux
	scores d'entités et aux poids attribués à la taxonomie pour
	la sélection du type le plus spécifique parmi l'ensemble des
	types possibles pour les entités (types directs, parents, etc.).
	DAGOBAH obtient d'excellents résultats sur les jeux de
	données synthétiques (Round 2) tandis que les jeux de don-nées générés manuellement et présentant des dispositions	4 Evaluation
	plus complexes semblent être traités de manière moins sa-	4.1 Configurations
	tisfaisante (Rounds 1 et 3). Sur le corpus HardTable, l'utili-	Afin d'évaluer l'apport des contextes de graphe à un et à
	sation de contextes plus riches et de la technique de notation	deux sauts ainsi que de la notation de contexte souple défi-
	souple ne semble pas amener de gain. Cela peut s'expliquer	nis dans la Section 3, nous définissons quatre configurations
	par le fait que les tableaux de ce corpus sont presque en-3.4.2 Annotation des types de colonnes (CTA) La tâche de CTA a pour but d'identifier le type le plus re-présentatif et le plus spécifique d'une colonne donnée. Pour cela, les types des entités candidates de la colonne sont col-lectés et une stratégie de vote majoritaire est appliquée pour déterminer le type le plus précis (voir [11] pour plus de dé-tièrement représentés dans le graphe de connaissances et que les colonnes peuvent donc être désambiguisées seule-ment à partir de leur contenu. A l'inverse, le corpus Bio-Table contient des ambiguités plus complexes avec des che-vauchements de contenu entre les colonnes empêchant leur désambiguisation (e.g. la colonne "Gene" peut être confon-tails sur les méthodes d'enrichissement de type et les cal-due avec la colonne "Protein", les valeurs étant souvent si-culs de scores). milaires). L'annotation semble donc bénéficier de contextes	pour les expériences : Configuration 1 Le score de contexte d'une entité est calculé en utilisant uniquement le voisinage à un saut du graphe de connaissances. Les poids w i ne sont pas calculés à l'aide de l'Equation (3) mais fixés à 1.0 pour les entités et 0.15 pour les littéraux. Configuration 2 Le score de contexte d'une entité est calculé en utilisant le voisinage à deux sauts du
	3.4.3 Annotation des entités de cellules (CEA) de graphes plus riches. Pour BioDivTable, la configuration	graphe de connaissances. Les poids w i ne sont pas
	4 est celle obtenant les scores les plus bas, tandis que la La tâche de CEA sélectionne pour une cellule e m l'entité la configuration 1 est comparable à la configuration 3. Nous plus pertinente parmi les entités candidates e c ∈ E c (e m ) collectées dans le graphe de connaissances. Cette étape supposons que les chemins unidirectionnels de longueur	calculés à l'aide de l'Equation (3) mais sont fixés à 1.0 pour les voisins à un saut, 0.25 pour les voisins à deux sauts et 0.15 pour les littéraux.
	s'appuie à la fois sur la notation préliminaire des entités et 2 apportent du bruit pouvant expliquer les faibles perfor-	Configuration 3 Le score de contexte d'une entité est
	sur les informations fournies par le CTA et le CPA pour cal-mances de la configuration 4.	calculé en utilisant le voisinage à deux sauts du

culer la note finale des entités candidates. En effet, la notation préliminaire d'une entité candidate e c tient uniquement compte des informations locales, i.e. les informations de la ligne à laquelle elle appartient. La prise en compte du type de colonne fourni par le CTA et de la propriété identifiée par le CPA permet de prendre en compte des informations globales. Par conséquent, le score final Sc(e c , e m ) d'une entité candidate e c est calculé comme suit :

Sc(e c , e m ) = (P Sc(e c , e m ) + α × score CT A + β × score CP A ) 1 + α + β

(5)

Si e c appartient au type généré par le CTA pour la colonne, alors score CT A est égal au score attribué à ce type et 0 dans le cas contraire. Via score CP A , nous calculons la moyenne des scores des relations identifiées par le CPA impliquant la colonne de e c . Pour chaque relation, si e c appartient au domaine ou au co-domaine (selon l'orientation de la relation), alors nous considérons le score de cette relation, sinon, le score est fixé à 0. Pour renforcer (resp. affaiblir) un CTA/CPA fréquent (resp. peu fréquent) lors de la mise à jour de Sc(e c , e m ), un coefficient α (resp. β) est utilisé et défini par occurrence(CT A) 2 (resp. occurrence(CP A) 2

). graphe de connaissances. Les poids w i sont calculés à l'aide de l'Equation

[START_REF] Chabot | DAGOBAH : Un système d'annotation sémantique de données tabulaires indépendant du contexte[END_REF]

. Cette configuration permet de tester si des contextes plus riches associés à une notation stricte permet de générer de meilleures annotations. En règle général, les configurations 2, 3 et 4 sont plus précises pour le CEA que la configuration 1. La récupéra-5. Les résultats complets sont disponibles en ligne : http: //www.cs.ox.ac.uk/isg/challenges/sem-tab/2021/ index.html#results

TABLE 1 -

 1 Comparaison des configurations expérimentales et des performances du système DAGOBAH sur les Rounds 1, 2, et 3 du challenge SemTab2021 (dans les cellules grisées). "F1" signifie F1-score, "P" signifie Precision. Les meilleurs résultats sont mis en valeur en gras. DAGOBAH avec notamment l'exploitation des types primitifs générés par le pré-traitement et l'utilisation de contextes de graphes enrichis. Néanmoins, de nouvelles directions de recherche peuvent encore être explorées pour faire face à l'hétérogénéité des types de tableaux publiés sur le Web. Ainsi, la structure des tableaux et les relations internes pourraient être prises en compte (e.g. orientation des tableaux, cellules imbriquées, concaténation pour mise en page, cellules à valeurs multiples, sujets répartis dans plusieurs colonnes comme les noms et prénoms d'une personne, etc). De plus, une problématique demeure dans le traitement des données hors graphe de connaissances, i.e. des entités non présentes dans un graphe cible donné, ce qui est souvent le cas pour des données spécifiques aux entreprises. Il convient de noter que les données hors graphe de connaissances ont commencé à être abordées avec le corpus GitTables. Ce dernier nécessitait en effet d'annoter des tables avec Schema.org et l'ontologie DBpedia uniquement. Cependant, cette tâche n'était pas entièrement conforme avec la définition du CTA utilisée par la communauté car les annotations recherchées mélangeaient des classes et des propriétés. Ces annotations hétérogènes peuvent conduire à des évaluations incohérentes. Au delà des données hors graphe, il serait intéressant d'évaluer la portabilité de l'approche à des graphes de domaines (e.g. biomédicaux, linguistiques) et leur apport pour l'annotation de jeux de données spécifiques.

	Corpus	Configuration	CTA		CEA		CPA
			F1	P	F1	P	F1	P
	Round 1 -WDTable

https://tinyurl.com/dagobah-ui. Les développements récents sur cette interface permettent (i) l'enrichissement de graphes de connaissances à partir d'éléments de la table non présents dans le graphe, (ii) l'enrichissement de la table à partir du graphe de connaissances afin de compléter des valeurs manquantes ou d'ajouter de nouvelles colonnes, et (iii) la visualisation interactive du graphe pedia) et l'annotation à l'aide de schémas uniquement (Schema.org et l'ontologie DBpedia). Ces challenges nous ont permis d'améliorer les stratégies d'annotation du sys-tème

Actuellement, seul l'identification d'une colonne clé unique est supportée par l'outil.

3. https://github.com/seatgeek/thefuzz

Les noeuds voisins sont connectés à ec via des chemins de prédicats dans le graphe de connaissances, quelque soit la direction des prédicats.

Remerciements

Les auteurs remercient Christophe Sarthou-Camy et Guillaume Jourdain pour leurs contributions importantes dans le développement de DAGOBAH UI.

.ox.ac.uk/isg/challenges/ sem-tab/