dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusion and future work This paper addressed the problem of MAC Layer mobility support in wireless and body sensor networks. This feature provides remote access to nodes moving across several access points' coverage range. In healthcare scenarios like hospital infirmaries it is possible to provide remote access (over a network backbone) to body sensor nodes carried by patients when they move around an infirmary. These nodes collect physiological parameters to monitor their health condition and send this data to remote repositories. A new handover approach to support continuous communication to nodes in a mobile WSN was proposed. This mechanism, called Handover Mechanism for MAC Layer supporting Continuous Communication in Mobile Wireless Sensor Networks (Hand4MAC), offers overall best performance in comparison with RSSI threshold-based handover method (RTHM).
Acknowledgments This work was partially supported by the  Instituto de Telcomunicações, Next Generation Networks and Applications Group (NetGNA) , Portugal, by Luso- French Program of Integrated University Actions  (PAUILF 2010)-Action No. F-CT-10/10 , by  Government of Russian Federation , Grant  074-U01 , by National Funding from the  FCT-Fundação para a Ciência e a Tecnologia  through the  Pest-OE/EEI/LA0008/2013  Project, and by the  AAL4ALL  (Ambient Assisted Living for All), Project co-financed by  COMPETE  under  FEDER  via  QREN Programme.
Number of iterations The number of iterations needed to converge is different for the algorithms. The convergence is shown in figure  7. The best reconstruction quality that can be obtained in these data is 92% for SMART, 94. 5% for BIMART and 95. 5% for MART. The number of iterations needed to reach this maximum is 8 for MART and BIMART and 20 for SMART. Five MART iterations are equivalent to eight BIMART iterations. The reprojection quality is around 98. 5% for MART and BIMART and 98% for SMART, showing that the convergence is equivalent. The maximum correlation quality is 95% for SMART after nine iterations and 97. 5% for BIMART after two iterations. The MART correlation quality is still increasing after 11 iterations where it reaches 98%. Hence MART in general converges toward a better solution, but it is closely followed by BIMART.
Conclusion The MART algorithm family was studied and optimized. The generalization to BIMART is interesting, as the reconstruction time is comparable to the SMART reconstruction time, but with a better accuracy. The most favorable algorithm using the synthetic data presented herein was BIMART with block size equal to four, using eight iterations and with a discintersect or the Gaussian functions as the weighting functions. An initialization with minLOS is necessary to reduce the computation time. By adding a few iterations of a fast version of SMART (four typically), the computation time can be decreased slightly. It was found that the relaxation parameter should be carefully selected based on the number of iterations to ensure the most rapid convergence and to avoid divergence. During the reconstruction, a filter (during the five first iterations) combined with a threshold (given by equation (  16 ) as a function of Ns) should be applied to improve the reconstruction and correlation qualities.
A particle size of around 3 voxels in diameter is ideal to improve the correlation quality. The image signal ratio should not exceed 70% for 1% error on the velocity field and 80% for 5% error. Camera configurations should be carefully planned before undertaking experiments, with a viewing angle of 27 • ±7 • for four cameras in cross configuration and an angle of 21 • ±3 • for the planar configuration. The volume should also be reconstructed wider by 10% on each side than the laser sheet, especially for noisy data. A misalignment correction procedure must be applied systematically. The BIMART algorithm can be parallelized easily because of its block architecture. This algorithm includes some a priori knowledge about the data to reconstruct (maximum of entropy, particles elongated in Z direction) but it would also be beneficial to add some stronger a priori, specifying that we want to reconstruct spherical particles.
Data regarding the age at which ambulation was lost, if this event occurred, were also collected. The ROC curves of the ten parameters tested for their ability to predict severe forms are schematized on this graph. Each marker is represented by a specific color, indicated in the key on the right. Note that the curves with the highest areas under the curve (AUC) are those obtained using the speed (AUC=0. 881) and the stride frequency (AUC=0. 862). Another interesting point is that the percentage of CD4 + CD49d hi (AUC=0. 853) remains highly specific (100%) until relatively high levels of sensitivity (44%). HW, height at withers; GQI, gait quality index; CK, creatine kinase.
Cytometry For cytometry, we used fluorochrome-labeled monoclonal antibodies with specificities for CD3, CD4, CD8 (Serotec, Kidlington, UK) and CD49d (Pharmingen/Becton Dickinson, San Diego, CA, USA). Isotype/ fluorochrome-matched unrelated antibodies were obtained from Pharmingen/Becton Dickinson. Peripheral blood mononuclear cells (PBMCs) from GRMD and healthy controls were isolated through ficollhistopaque (Sigma-Aldrich, St Louis, MO, USA) sedimentation, using freshly obtained samples. PBMCs were first incubated in 96-well plateswith 5% fetal calf serum for 20 minutes at 4°C -and then subjected to fluorochrome-labeled primary monoclonal antibodies for 30 minutes. After washing, cells were fixed and acquisition for flow cytometry was carried out using a LSR II ® flow cytometer (Becton Dickinson, San Jose, CA, USA) equipped with FacsDiva software.
, 2009). Ten previously described variables were calculated from the acceleration curves in the software Equimetrix ® and are as follows: the speed (m/s), the stride frequency (cycles/s), the stride length (m), the regularity, the dorso-ventral, craniocaudal and medio-lateral powers (W/kg), the total power (W/kg), the force index [expressed in N/kg body weight, and calculated by normalizing the total power (W/kg) by the speed (m/s)], and a gait quality index recapitulating the association of seven variables. The speed and stride length, because directly influenced by the dog size, were normalized by the height at the withers (HW, m), and the axial powers were expressed as a proportion of the total power (%).
Acknowledgements We are very grateful to  Jean-Yves Hogrel  and  Eric Barrey  for their contribution to the accelerometry experiments. We thank  Mireille Dubord ,  Bodovoahangy Andriatiana  and  Priscille Hertault , of the CAAST of ENVA, for the biochemical analyses. We also thank the  Centre d'Elevage du Domaine des Souches  for breeding the GRMD dogs for this study, and  Dr Pablo Aguilar ,  Xavier Cauchois  and the whole team of the  UPR de Neurobiologie of ENVA  for their very good daily care to the dogs. We thank  Isabelle Valchera  for professional administrative assistance. We thank  PAPES/Fiocruz ,  CAPES ,  FAPERJ ,  CNPq (Brazil) ,  United Parent's Project for Muscular Dystrophies (UPPMD) ,  Inserm ,  UPMC ,  CNRS ,  Association Française contre les Myopathies (AFM) ,  Inserm/Fiocruz  and  CNPq/Inserm Conjoint Programs  for the financial support.
For these reasons, using central storage of biometric data is problematic. • The matching process could make errors for genuine users but also impostors could be falsely accepted. This is not the case for password verification as long as the correct password is typed (but there is no proof that it has been typed by the genuine user). • Biometric data could be intercepted during its transmission. This could lead to security problems, such as replay attacks and privacy attacks based on linkability. For these reasons, the biometric data should be cancelable and dynamic (changing at each transaction). In this paper, we propose a new solution that solves these problems. To achieve a security and privacy compliant solution, we combine two elements: the first one is a specific device owned by the user called OffPAD, and the second is a protocol using biometrics and cancelable algorithms.
III. SECURITY AND PRIVACY REQUIREMENTS In electronic payments, four main actors are present: The user C, who has an OffPAD, wants to purchase an online service with a credit card, through the website of a service provider SP. The user has an issuer bank and the SP has an acquirer bank. In this paper, we also call these payment providers: user's bank and SP bank. A fifth actor is often involved. It is the trusted party as a third-party cashier or the Directory used in 3D-Secure. The role of this fifth actor is various but generally allows to authenticate the banks. The proposed protocol is concentrated on user authentication and the user's registration with the SP. During an online payment, numerous personal data are involved and must be protected against several threats,  [4]. In order to preserve privacy and security properties, a list of ten requirements R i is defined.
• R 6 : SP authentication by the user or by a trusted party ensures the identity of the SP. • R 7 : Bank authentication by a trusted party ensures the identity of SP bank and customer's bank. • R 8 : Unlinkability of realized transactions prevents linking different transactions of the same customer. • R 9 : Confidentiality of customer information CI (data minimization principle) ensures only authorized persons access to this information. This requires the user's biometric data are unknown to the banks and SP. • R 10 : Data sovereignty means that personal data associated with the customer can only be processed with his/her control and consent. In the next section, we present the OffPAD concept as secure device for ensuring the security of sensitive operations.
IV. OFFPAD CONCEPT The PAD (Personal Authentication Device) is described by Jøsang and Pope  [13]  as a secure device external to the client computer platform. The PAD is the conceptual predecessor to the OffPAD. The OffPAD (Offline Personal Authentication Device) described by Klevjer et al. [16]  and Varmedal et al. [26]  is an enhanced version of the PAD, where an essential characteristic is to guarantee offline security (Machine to Machine communications). The OffPAD represents local user-centric identity management because it enables secure and user friendly management of digital identities and credentials locally on the user side. The OffPAD supports authentication of both user and service provider identities (i. e. mutual authentication) and can in addition support data authentication.
VI. PROPOSED AUTHENTICATION PROTOCOL The proposed authentication protocol uses biometric data that must be protected through the capture with the OffPAD device and template protection algorithms. Biometric template protection schemes are a group of technologies, included in privacy enhancing technologies, used to enhance both privacy and security of biometric data. Therefore, any template protection approach should allow to revoke a biometric data in case of interception, and should be carefully designed, with a strong security analysis. Among the different solutions in the literature, template protection can be achieved using biometric cryptosystems  [15] ,  [14] ,  [9] ,  [20]  or by transforming the biometric feature data  [22] ,  [5] ,  [25] ,  [23]. As detailed in the next section, BioHashing is one popular scheme that belongs to this second category and allows to revoke a biometric template.
A. Performance analysis In this section, we analyze the performance of the protocol to avoid false rejection and false impostor. We start by defining the experimental protocol. 1) Experimental protocol: In this study, we used three fingerprint databases, each one is composed of 800 images from 100 individuals with 8 samples from each user: • FVC2002 benchmark database DB2: the image resolution is 296×560 pixels with an optical sensor "FX2000" by Biometrika ; • FVC2004 benchmark database DB1: the image resolution is 640 × 480 pixels with an optical Sensor "V300" by CrossMatch ; • FVC2004 benchmark database DB3: the image resolution is 300×480 pixels with a thermal sweeping Sensor "FingerChip FCD4B14CB" by Atmel. Figure  6  presents one image from each database. We can see that fingerprints are quite different and representative of the different types of fingerprint (acquired with sensors using different technologies).
These databases have been used for competitions (Fingerprint Verification competition) in 2002 and 2004. Table  1  presents the performance of the best algorithms on these databases 1. The Equal Error Rate (EER) computes the compromise error rate when genuine users have been falsely rejected and impostor falsely accepted. ZeroFMR is the value of False Non Match Rate (FNMR) when no impostor is falsely accepted. These values define the complexity of each database and give some elements of the performance what we can expect on these databases. As FingerCode, we used Gabor features (GABOR)  [18]  of size n=512 (16 scales and 16 orientations) as template. These feature are very well known and permit a good texture analysis of a fingerprint. For each user, we used the first FingerCode sample as reference template.
Others are used for testing the proposed scheme. BioCodes are of size m=256 bits. In order to quantify the performance of the One Time Biometrics approach, we computed 1000 comparisons (with the Hamming distance) between the challenge Reference BioCode and challenge Capture BioCode for each user. We obtained 100. 000 intraclass and interclass scores for the performance analysis of the proposed scheme. Databases EER ZeroF M R F V C2002 DB2 0. 14% 0. 29% F V C2004 DB1 0. 61% 1. 93% F V C2004 DB3 1. 18% 4. 89% 2) Experimental results: We applied the previous protocol to the proposed authentication solution. On the three databases, we reach an EER value very close to 0%. In order to illustrate this efficiency, we show in Figure  7  the distribution of intraclass and interclass scores for each database.
We clearly see that there is no overlap between the two distributions and a threshold near 60 (meaning maximal 60 different bits between the capture and Reference BioCodes is tolerated) could be used. In the last column of Table  2 , we present the EER value by considering an impostor has in his/her possession the OffPAD device and the user password (worst case). In this case, the impostor can apply the Zero effort attack by providing his/her biometric data to impersonate the genuine user. We tested 100. 000 attacks for each database and this attack is successful from 16% to 25% of the cases. In classical approaches (two-factor authentication), this attack is always successful.
The first component is a specific device called OffPAD that ensures many security and privacy issues. The second component is the use of a biometric template protection algorithm to make possible the storage of a biometric data in a centralized way by the Issuer Bank. A challenge-based protocol is then proposed to prevent replay attacks. The user authentication scheme is usable for users as they do not have to remember different passwords. The protocol demonstrates very good performances on three benchmark fingerprint databases and good properties considering security and privacy issues. Future perspectives of this study are numerous. We plan to use multiple biometric data in order to avoid the use of a password in the proposed protocol, and we also plan to design a biometric data authenticaiton protocol.
Background: The ESTRO Health Economics in Radiation Oncology (HERO) project has the overall aim to develop a knowledge base of the provision of radiotherapy in Europe and build a model for health economic evaluation of radiation treatments at the European level. The first milestone was to assess the availability of radiotherapy resources within Europe. This paper presents the personnel data collected in the ESTRO HERO database. Materials and methods: An 84-item questionnaire was sent out to European countries, through their national scientific and professional radiotherapy societies. The current report includes a detailed analysis of radiotherapy staffing (questionnaire items 47-60), analysed in relation to the annual number of treatment courses and the socio-economic status of the countries.
The partial or complete data sets regarding personnel resources in the remaining 24 ECO countries form the basis of the present analysis (Table  1 ). Data from the United Kingdom were calculated by pooling together the data from the four separate countries, when available. Personnel resources were reviewed for radiation oncologists (RO), medical physicists (MP or physicists), dosimetrists (DO), radiation therapists (RTT), radiotherapy nurses (RN or nurses) and radiobiologists, both for the public and private sector, excluding trainees. Actual numbers and full time equivalents (FTE) were collected. Guidelines being typically defined for personnel numbers and uncertainties being recognised in the FTE data, the actual numbers were used for the calculation of the key indicators, except for countries only providing FTE, where these were used as a proxy.
The number of delivered radiotherapy treatment coursesradical, palliative, or re-treatment -was recorded in the questionnaire. For the 8 countries where the information about retreatments was unavailable, the primary treatment figures were augmented with 25%  [9] [10] [11]. The economic status of the countries was expressed as gross national income per capita (GNI/n; in US$ according to World Bank standards) using the Atlas method  [2]. In order to identify relatively homogeneous groups of countries based on selected characteristics of personnel per million inhabitants (RO, MP + DO, RTT + RN) and of GNI/n, the k-means clustering via principal components analysis using the Hartigan and Wong method was applied  [12]. With this method, multidimensional data can be represented into two axes and cluster centroids defined (vector of mean values of each variable).
Discussion This paper presents the personnel data collected in the ESTRO HERO database, based on validated national data entry in collabo-ration with the National Societies. It demonstrates a large variability of all evaluated parameters. Weighing personnel availability to population figures disregards cancer incidence and differences by tumour site distribution, both critical in determining optimal radiotherapy utilisation and hence the level of radiotherapy resources required  [9, 14]. It is therefore more relevant to relate staffing to a certain productivity level, such as courses or fractions delivered on an annual basis. But many European countries use both approaches in their guidelines: requirements for RTTs are frequently defined in relation to equipment numbers, in turn often determined by population figures, whereas national recommendations regarding radiation oncologists more frequently refer to patient loads  [8, 14].
Our study encountered some limitations. Most nations do not have databases in which the requested data are readily available, and for many National Societies dedicated data collection was not possible within the constraints of their available resources. As a consequence, we were flexible in the year to which the data pertain, with the resulting mix in collection year as presented. In addition, evidence on courses delivered may have been obtained from different data sets, in turn translating into slightly different activity denominators. The aim of this work was to benchmark among European countries. National averages however disregard regional variations within countries due to population density, accessibility of care, regional health care and reimbursement systems. Although beyond the scope of this work, future refinements at the regional level may be pursued.
Finally we acknowledge that some of the pragmatic decisions taken to allow analysis of this highly heterogeneous data setthe use of personnel numbers instead of FTE, grouping different personnel categories, the omission of trainees in the analysesmay have resulted in a simplification of reality. In spite of these shortcomings, this is the most comprehensive data set on personnel resources in Europe available to date. We hope that the results of this experience will facilitate future updates of the HERO database and that the basis has been laid for an even stronger collegial network of National Societies. The next step in the HERO framework is to benchmark these data to the staffing needs in the individual countries, based on cancer incidence and stage mix and performed together with the Collaboration for Cancer Outcomes, Research and Evaluation (CCORE) in Australia  [9, 14].
The Cap-Ferret Canyon (CFC), a major morphologic feature of the eastern margin of the Bay of Biscay, occupies a deep structural depression that opens about 60 km southwest of the Gironde Estuary. Detailed depth profiles of the particle-reactive radionuclides 234 Th and 210 Pb in interface sediments were used to characterise the present sedimentation (bioturbation, sediment mass accumulation, and focusing) in the CFC region. Two bathymetric transects were sampled along the CFC axis and the southern adjacent margin. Particle fluxes were recorded from the nearby Landes Plateau by means of sediment traps in 2006 and 2007. This dataset provides a new and comprehensive view of particulate matter transfer in the Cap-Ferret Canyon region, through a direct comparison of the canyon with the adjacent southern margin.
Two bathymetric transects were sampled, along the canyon axis and the southern adjacent margin. We present also downward particulate mass fluxes recorded, by means of sediment traps, in the nearby Landes Plateau between 2006 and 2007. Results of a first investigation of the CFC conducted in 1990 (ECOFER-ECOsystème du canyon de cap-FERet;  Heussner et al. , 1999)  are also included. This dataset is discussed in order to compare the present sedimentation framework (bioturbation, sediment mass accumulation, and focusing) of the CFC and of the adjacent open slope and to define a conceptual framework of the sedimentary activity along the CFC. Based on a comparison with other canyons, we suggest the "Type II" canyon category, as defined by  Jobe et al. (2011) , to be subdivided into at least two classes.
Settling particles in the water column During the ANR-FORCLIM programme, a long-term mooring equipped with two sediment traps (PPS5 TECHNICAP; sampling area 1 m 2 ) was deployed at the deepest station 6′, on the Landes Plateau (southeast Aquitanian margin) (Fig. 1 , Table  1 ). Settling particles were sampled at two water depths, 800 m and 1700 m respectively, over a 17-month period, from  June 22, 2006 , to November 23, 2007. Details on moorings, sample processing and data are given by  Schmidt et al. (2009)  and  Kuhnt et al. (2013). Station 6′ (44133′N, 2145′W, 2000 m water depth) is also labelled WH in previous works on the Aquitanian margin; the label 6′ is preferred in this work for coherence with the notation of the other sites on the slope transect. During ECOFER, two trap moorings were also deployed, but in the canyon axis, at 2300 and 3000 m water depth, for 14 months from June 1990 to August 1991.
In the CFC, the amazing coherence between the two dataset (ECOFER and LEVIATHAN cruises), considering the time interval between the experiments, demonstrates also the rather regular and calm sedimentation. This does not exclude rarer and violent downslope sediment transport, as suggested by subsurface layers of old ( 210 Pb-depleted) sediments observed in cores 7 (water depth ¼2050 m), 8 (water depth¼ 2890 m) and 9 (water depth ¼3168 m) from the lower part of the CFC. "Quiescent" canyons can be exceptionally active during extreme and unpredictable events such as centennial storms or high-magnitude earthquakes.