548 results on '"P. Achard"'
Search Results
2. Large-Scale Correlation Screening under Dependence for Brain Functional Connectivity Network Inference
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Lbath, Hanâ, Petersen, Alexander, and Achard, Sophie
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Statistics - Methodology - Abstract
Data produced by resting-state functional Magnetic Resonance Imaging are widely used to infer brain functional connectivity networks. Such networks correlate neural signals to connect brain regions, which consist in groups of dependent voxels. Previous work has focused on aggregating data across voxels within predefined regions. However, the presence of within-region correlations has noticeable impacts on inter-regional correlation detection, and thus edge identification. To alleviate them, we propose to leverage techniques from the large-scale correlation screening literature, and derive simple and practical characterizations of the mean number of correlation discoveries that flexibly incorporate intra-regional dependence structures. A connectivity network inference framework is then presented. First, inter-regional correlation distributions are estimated. Then, correlation thresholds that can be tailored to one's application are constructed for each edge. Finally, the proposed framework is implemented on synthetic and real-world datasets. This novel approach for handling arbitrary intra-regional correlation is shown to limit false positives while improving true positive rates.
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- 2023
3. Toulouse Hyperspectral Data Set: a benchmark data set to assess semi-supervised spectral representation learning and pixel-wise classification techniques
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Thoreau, Romain, Risser, Laurent, Achard, Véronique, Berthelot, Béatrice, and Briottet, Xavier
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Airborne hyperspectral images can be used to map the land cover in large urban areas, thanks to their very high spatial and spectral resolutions on a wide spectral domain. While the spectral dimension of hyperspectral images is highly informative of the chemical composition of the land surface, the use of state-of-the-art machine learning algorithms to map the land cover has been dramatically limited by the availability of training data. To cope with the scarcity of annotations, semi-supervised and self-supervised techniques have lately raised a lot of interest in the community. Yet, the publicly available hyperspectral data sets commonly used to benchmark machine learning models are not totally suited to evaluate their generalization performances due to one or several of the following properties: a limited geographical coverage (which does not reflect the spectral diversity in metropolitan areas), a small number of land cover classes and a lack of appropriate standard train / test splits for semi-supervised and self-supervised learning. Therefore, we release in this paper the Toulouse Hyperspectral Data Set that stands out from other data sets in the above-mentioned respects in order to meet key issues in spectral representation learning and classification over large-scale hyperspectral images with very few labeled pixels. Besides, we discuss and experiment self-supervised techniques for spectral representation learning, including the Masked Autoencoder, and establish a baseline for pixel-wise classification achieving 85% overall accuracy and 77% F1 score. The Toulouse Hyperspectral Data Set and our code are publicly available at https://www.toulouse-hyperspectral-data-set.com and https://www.github.com/Romain3Ch216/tlse-experiments, respectively., Comment: 17 pages, 13 figures
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- 2023
4. Hot ion implantation to create dense NV centre ensembles in diamond
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Ngambou, Midrel Wilfried Ngandeu, Perrin, Pauline, Balasa, Ionut, Tiranov, Alexey, Brinza, Ovidiu, Benedic, Fabien, Renaud, Justine, Reveillard, Morgan, Silvent, Jeremie, Goldner, Philippe, Achard, Jocelyn, and Tallaire, Alexandre
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Physics - Applied Physics ,Quantum Physics - Abstract
Creating dense and shallow nitrogen vacancy (NV) ensembles with good spin properties, is a prerequisite for developing diamond-based quantum sensors exhibiting better performance. Ion implantation is a key enabling tool for precisely controlling spatial localisation and density of NV colour centres in diamond. However, it suffers from a low creation yield, while higher ion fluences significantly damage the crystal lattice. In this work, we realize N2 ion implantation in the 30 to 40 keV range at high temperatures. At 800 C, NV ensemble photoluminescence emission is three to four times higher than room temperature implanted films, while narrow electron spin resonance linewidths of 1.5 MHz, comparable to well established implantation techniques are obtained. In addition, we found that ion fluences above 2E14 ions per cm2 can be used without graphitization of the diamond film, in contrast to room temperature implantation. This study opens promising perspectives in optimizing diamond films with implanted NV ensembles that could be integrated into quantum sensing devices., Comment: 10 pages, 1 table, 4 figures
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- 2023
5. Exchanging... Watch out!
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Yang, Liu, Woo, Jieyeon, Achard, Catherine, and Pelachaud, Catherine
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Computer Science - Human-Computer Interaction - Abstract
During a conversation, individuals take turns speaking and engage in exchanges, which can occur smoothly or involve interruptions. Listeners have various ways of participating, such as displaying backchannels, signalling the aim to take a turn, waiting for the speaker to yield the floor, or even interrupting and taking over the conversation. These exchanges are commonplace in natural interactions. To create realistic and engaging interactions between human participants and embodied conversational agents (ECAs), it is crucial to equip virtual agents with the ability to manage these exchanges. This includes being able to initiate or respond to signals from the human user. In order to achieve this, we annotate, analyze and characterize these exchanges in human-human conversations. In this paper, we present an analysis of multimodal features, with a focus on prosodic features such as pitch (F0) and loudness, as well as facial expressions, to describe different types of exchanges.
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- 2023
6. A quantitative gibberellin signaling biosensor reveals a role for gibberellins in internode specification at the shoot apical meristem
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Shi, Bihai, Felipo-Benavent, Amelia, Cerutti, Guillaume, Galvan-Ampudia, Carlos, Jilli, Lucas, Brunoud, Geraldine, Mutterer, Jérome, Vallet, Elody, Sakvarelidze-Achard, Lali, Davière, Jean-Michel, Navarro-Galiano, Alejandro, Walia, Ankit, Lazary, Shani, Legrand, Jonathan, Weinstain, Roy, Jones, Alexander M., Prat, Salomé, Achard, Patrick, and Vernoux, Teva
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- 2024
- Full Text
- View/download PDF
7. A quantitative gibberellin signaling biosensor reveals a role for gibberellins in internode specification at the shoot apical meristem
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Bihai Shi, Amelia Felipo-Benavent, Guillaume Cerutti, Carlos Galvan-Ampudia, Lucas Jilli, Geraldine Brunoud, Jérome Mutterer, Elody Vallet, Lali Sakvarelidze-Achard, Jean-Michel Davière, Alejandro Navarro-Galiano, Ankit Walia, Shani Lazary, Jonathan Legrand, Roy Weinstain, Alexander M. Jones, Salomé Prat, Patrick Achard, and Teva Vernoux
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Science - Abstract
Abstract Growth at the shoot apical meristem (SAM) is essential for shoot architecture construction. The phytohormones gibberellins (GA) play a pivotal role in coordinating plant growth, but their role in the SAM remains mostly unknown. Here, we developed a ratiometric GA signaling biosensor by engineering one of the DELLA proteins, to suppress its master regulatory function in GA transcriptional responses while preserving its degradation upon GA sensing. We demonstrate that this degradation-based biosensor accurately reports on cellular changes in GA levels and perception during development. We used this biosensor to map GA signaling activity in the SAM. We show that high GA signaling is found primarily in cells located between organ primordia that are the precursors of internodes. By gain- and loss-of-function approaches, we further demonstrate that GAs regulate cell division plane orientation to establish the typical cellular organization of internodes, thus contributing to internode specification in the SAM.
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- 2024
- Full Text
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8. Gibberellin and abscisic acid transporters facilitate endodermal suberin formation in Arabidopsis.
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Binenbaum, Jenia, Wulff, Nikolai, Camut, Lucie, Kiradjiev, Kristian, Anfang, Moran, Tal, Iris, Vasuki, Himabindu, Zhang, Yuqin, Sakvarelidze-Achard, Lali, Davière, Jean-Michel, Ripper, Dagmar, Carrera, Esther, Crocoll, Christoph, Weinstain, Roy, Cohen, Hagai, Ragni, Laura, Aharoni, Asaph, Band, Leah, Achard, Patrick, Nour-Eldin, Hussam, Shani, Eilon, Manasherova, Ekaterina, Ben Yaakov, Shir, Lazary, Shani, Hua, Chengyao, and Novak, Vlastimil
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Arabidopsis ,Abscisic Acid ,Gibberellins ,Membrane Transport Proteins ,Arabidopsis Proteins ,Nitrate Transporters ,Hormones ,Gene Expression Regulation ,Plant - Abstract
The plant hormone gibberellin (GA) regulates multiple developmental processes. It accumulates in the root elongating endodermis, but how it moves into this cell file and the significance of this accumulation are unclear. Here we identify three NITRATE TRANSPORTER1/PEPTIDE TRANSPORTER (NPF) transporters required for GA and abscisic acid (ABA) translocation. We demonstrate that NPF2.14 is a subcellular GA/ABA transporter, presumably the first to be identified in plants, facilitating GA and ABA accumulation in the root endodermis to regulate suberization. Further, NPF2.12 and NPF2.13, closely related proteins, are plasma membrane-localized GA and ABA importers that facilitate shoot-to-root GA12 translocation, regulating endodermal hormone accumulation. This work reveals that GA is required for root suberization and that GA and ABA can act non-antagonistically. We demonstrate how the clade of transporters mediates hormone flow with cell-file-specific vacuolar storage at the phloem unloading zone, and slow release of hormone to induce suberin formation in the maturation zone.
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- 2023
9. Graph-based methods coupled with specific distributional distances for adversarial attack detection
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Nwaigwe, Dwight, Carboni, Lucrezia, Mermillod, Martial, Achard, Sophie, and Dojat, Michel
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Computer Science - Machine Learning ,Computer Science - Cryptography and Security ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Artificial neural networks are prone to being fooled by carefully perturbed inputs which cause an egregious misclassification. These \textit{adversarial} attacks have been the focus of extensive research. Likewise, there has been an abundance of research in ways to detect and defend against them. We introduce a novel approach of detection and interpretation of adversarial attacks from a graph perspective. For an input image, we compute an associated sparse graph using the layer-wise relevance propagation algorithm \cite{bach15}. Specifically, we only keep edges of the neural network with the highest relevance values. Three quantities are then computed from the graph which are then compared against those computed from the training set. The result of the comparison is a classification of the image as benign or adversarial. To make the comparison, two classification methods are introduced: 1) an explicit formula based on Wasserstein distance applied to the degree of node and 2) a logistic regression. Both classification methods produce strong results which lead us to believe that a graph-based interpretation of adversarial attacks is valuable., Comment: published in Neural Networks
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- 2023
10. AMII: Adaptive Multimodal Inter-personal and Intra-personal Model for Adapted Behavior Synthesis
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Woo, Jieyeon, Fares, Mireille, Pelachaud, Catherine, and Achard, Catherine
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Computer Science - Human-Computer Interaction ,Computer Science - Machine Learning ,Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing ,68T07 ,I.2.11 - Abstract
Socially Interactive Agents (SIAs) are physical or virtual embodied agents that display similar behavior as human multimodal behavior. Modeling SIAs' non-verbal behavior, such as speech and facial gestures, has always been a challenging task, given that a SIA can take the role of a speaker or a listener. A SIA must emit appropriate behavior adapted to its own speech, its previous behaviors (intra-personal), and the User's behaviors (inter-personal) for both roles. We propose AMII, a novel approach to synthesize adaptive facial gestures for SIAs while interacting with Users and acting interchangeably as a speaker or as a listener. AMII is characterized by modality memory encoding schema - where modality corresponds to either speech or facial gestures - and makes use of attention mechanisms to capture the intra-personal and inter-personal relationships. We validate our approach by conducting objective evaluations and comparing it with the state-of-the-art approaches., Comment: 8 pages, 1 figure
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- 2023
11. The LHCb upgrade I
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LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Achard, C., Ackernley, T., Adeva, B., Adinolfi, M., Adlarson, P., Afsharnia, H., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Albero, A. Alfonso, Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreani, A., Andreianov, A., Andreotti, M., Andreou, D., Andrews, J. E., Anelli, M., Anjam, A., Ao, D., Archilli, F., Arnaud, K., Artamonov, A., Artuso, M., Ashby, J., Aslanides, E., Atzeni, M., Audurier, B., Rocha, D. Ayres, Perea, I. B Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Bailly-reyre, A., Rodriguez, P. Baladron, Balagura, V., Balbi, G., Baldini, W., Balla, A., Baltazar, M., Band, H., Leite, J. Baptista de Souza, Barbetti, M., Barclay, P., Barlow, R. J., Barsuk, S., Barter, W., Bartolini, M., Baryshnikov, F., Basels, J. M., Bassi, G., Baszczyk, M., Lopes, J. C. Batista, Batsukh, B., Battig, A., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Beigbeder-Beau, C., Beiter, A., Belin, S., Bellee, V., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Benettoni, M., Ben-Haim, E., Berezhnoy, A., Bernard, F., Bernet, R., Andres, S. Bernet, Berninghoff, D., Bernstein, H. C., Bertella, C., Bertolin, A., Betancourt, C., Betti, F., Bezshyiko, Ia., Bezshyyko, O., Bhasin, S., Bhom, J., Bian, L., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blago, M. P., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bobulska, D., Bochin, B., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bogdanova, G., Boiaryntseva, I., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bondar, N., Booth, M. J., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Boterenbrood, H., Bouchiba, S. A., Bowcock, T. J. V., Boyaryntsev, A., Boyer, A., Bozzi, C., Bradley, M. J., Braun, S., Rodriguez, A. Brea, Bregliozzi, G., Bridges, K., Briere, M. M. J., Brock, M., Brodski, M., Brodzicka, J., Gonzalo, A. Brossa, Brown, C., Brown, J., Brummitt, A. J., Brundu, D., Brunetti, L., Buda, L., Buonaura, A., Buonincontri, L., Burke, A. T., Burmistrov, L., Burr, C., Bursche, A., Butkevich, A., Butter, J. S., Buytaert, J., Byczynski, W., Cachemiche, J. P., Cadeddu, S., Cai, H., Caillet, A., Calabrese, R., Calefice, L., Calegari, D., Cali, S., Calvi, M., Gomez, M. Calvo, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Canfer, S., Capelli, S., Capriotti, L., Carassiti, V., Carbone, A., Cardinale, R., Cardini, A., Carletti, M., Carniti, P., Carroll, J., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Cattaneo, M., Cavallero, G., Cavallini, V., Ceelie, L., Celani, S., Cerasoli, J., Cervenkov, D., Cesare, S., Chadaj, B., Chadwick, A. J., Chahrour, I., Chanal, H., Chapman, M. G., Charles, M., Charpentier, Ph., Chaumat, V. J., Barajas, C. A. Chavez, Chefdeville, M., Chen, C., Chen, S., Chernov, A., Chernov, E., Chernyshenko, S., Chiozzi, S., Chobanova, V., Cholak, S., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Cicala, M. F., Vidal, X. Cid, Ciezarek, G., Cifra, P., Citterio, M., Ciullo, G., Clark, K., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Cobbledick, J. L., Coco, V., Coelli, S., Cogan, J., Cogneras, E., Cojocariu, L., Collins, P., Colombo, T., Congedo, L., Conti, N., Contu, A., Cooke, N., Corredoira, I., Corti, G., Ramusino, A. Cotta, Couturier, B., Cowan, G. A., Craik, D. C., Torres, M. Cruz, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Damen, A., Daniel, J., Danilina, A., d'Argent, P., Daudon, F., Davies, J. E., Davis, A., Davis, J., Francisco, O. De Aguiar, De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., de Oliveira, R., De Paula, L., De Roo, K., De Serio, M., De Simone, D., De Simone, P., De Vellis, F., de Vries, J. A., De Wit, E., Dean, C. T., Debernardis, F., Decamp, D., Deckenhoff, M., Dedu, V., Del Buono, L., Delaney, B., Dembinski, H. -P., Denis, C., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Bari, D., Di Nezza, P., Diachkov, I., Didenko, S., Maronas, L. Dieste, Dijkstra, H., Ding, S., Dobishuk, V., Doets, M., Doherty, F., Dolmatov, A., Domke, M., Dong, C., Donohoe, A. M., Dordei, F., Dorosz, P., Reis, A. C. dos, Douglas, L., Downes, A. G., Duarte, O., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Dumps, R., Durante, P., Duras, M. M., Durham, J. M., Dutta, D., Duval, P. Y., Dziewiecki, M., Dziurda, A., Dzyuba, A., Easo, S., Egede, U., Egorychev, V., Orro, C. Eirea, Eisenhardt, S., Ejopu, E., Ekelhof, R., Ek-In, S., Eklund, L., Elashri, M. E, Ellbracht, J., Elvin, A., Ely, S., Ene, A., Epple, E., Escher, S., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farry, S., Fazzini, D., Felkowski, L. F, Feo, M., Declara, P. Fernandez, Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Ferreira, R., Lopes, L. Ferreira, Rodrigues, F. Ferreira, Sole, S. Ferreres, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Firlej, M., Fischer, K. M., Fitzgerald, D. S., Fitzpatrick, C., Fiutowski, T., Fleuret, F., Flores, L., Fontana, M., Fontanelli, F., Forty, R., Foulds-Holt, D., Fournier, C., Lima, V. Franco, Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Freestone, J., Frei, C., Frei, R., Frelier, J., Friday, D. A., Frontini, L. F, Fu, J., Fuehring, Q., Fulghesu, T., Fuzipeg, C., Gabriel, E., Galati, G., Galati, M. D., Galka, M., Torreira, A. Gallas, Galli, D., Gallorini, S., Gambetta, S., Gan, Y., Gandelman, M., Gandini, P., Gao, R., Gao, Y., Garau, M., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Plana, B. Garcia, Rosales, F. A. Garcia, Garrido, L., Garroum, N., Garsed, P. J., Gascon, D., Gaspar, C., Gasq, C., Gatta, M., Gavardi, L., Gebolis, P. M., Geertsema, R. E., Gerick, D., Gerken, L. L., Germann, D., Gersabeck, E., Gersabeck, M., Gershon, T., Getz, S. A., Giambastiani, L., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Girard, O. G., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gizdov, K., Gkougkousis, E. L., Gligorov, V. V., Göbel, C., Golinka-Bezshyyko, L., Golobardes, E., Golubkov, D., Golutvin, A., Gomes, A., Fernandez, S. Gomez, Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gorelov, I. V., Gotti, C., Grabowski, J. P., Grammatico, T., Cardoso, L. A. Granado, Grant, F., Graugés, E., Graverini, E., Graziani, G., Grecu, A. T., Greeven, L. M., Greim, R., Grieser, N. A., Grillo, L., Gromov, S., Gromov, V., Grub, N., Cazon, B. R. Gruberg, Grynyov, B., Gu, C., Guarise, M., Guerin, S., Guittiere, M., Günther, P. A., Gushchin, E., Guth, A., Guz, Y., Gys, T., Hachon, F., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Haimberger, J., Haines, S. C., Halewood-leagas, T., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Hamrat, S., Han, Q., Han, X., Hansen, E. B., Hansmann-Menzemer, S., Hao, L., Harnew, N., Harrison, T., Hasse, C., Hatch, M., He, J., Heijhoff, K., Hemmer, F. H, Henderson, C., Henderson, R. D. L., Hennequin, A. M., Hennessy, K., Henry, L., Herd, J., Herold, T., Heuel, J., Hicheur, A., Hill, D., Hilton, M., Hoft, G. T., Hollitt, S. E., Hopchev, P. H., Hornberger, O., Horswill, J., Hou, R., Hou, Y., Hu, J., Hu, W., Hu, X., Huang, W., Huang, X., Hulsbergen, W., Hummel, S., Hunter, R. J., Hushchyn, M., Hutanu, O. E., Hutchcroft, D., Hynds, D., Ibis, P., Idzik, M., Ilin, D., Ilten, P., Inglessi, A., Iniukhin, A., Insa, C., Ishteev, A., Ivshin, K., Jacobsson, R., Jage, H., Elles, S. J. Jaimes, Jakobsen, S., Jamet, O., Jans, E., Jashal, B. K., Jaspers, M., Jawahery, A., Jevaud, M., Jevtic, V., Jiang, E., Jiang, X., Jiang, Y., John, D., John, M., Johnson, D., Jones, C. R., Jones, T. P., Jost, B., Jurik, N., Juszczak, I., Kandybei, S., Kang, Y., Karacson, M., Kariuki, J. M., Karpenkov, D., Karpinski, W., Karpov, M., Kaufmann, K., Kautz, J. W., Kayzel, F., Keizer, F., Keller, D. M., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Kok, H., Koliiev, S., Kolk, L., Kondybayeva, A., Konoplyannikov, A., Kopciewicz, P., Kopecna, R., Koppenburg, P., Korolev, M., Kos, J., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kozlov, V. S., Kraan, M., Kravchenko, P., Kravchuk, L., Krawczyk, R. D., Kreps, M., Kretzschmar, S., Krokovny, P., Krupa, W., Krzemien, W., Kubat, J., Kubis, S., Kucewicz, W., Kucharczyk, M., Kudryavtsev, V., Kuhlman, A., Kuilman, W. C., Kulikova, E. K, Kuonen, A. K., Kupfer, N., Kupsc, A., Kvaratskheliya, T., Lacarrere, D., Lafferty, G., Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Langenbruch, C., Langer, J., Langstaff, M., Lantwin, O., Latham, T., Lazzari, F., Lazzaroni, M., Dortz, O. Le, Gac, R. Le, Lee, S. H., Lefèvre, R., Leflat, A., Legotin, S., Lemaitre, F., Lenisa, P., Leroy, O., Lesiak, T., Leverington, B., Li, A., Li, H., Li, K., Li, P., Li, P. -R., Li, S., Li, T., Li, Y., Li, Z., Liang, X., Lieunard, B., Lin, C., Lin, T., Lindner, R., Lisovskyi, V., Litvinov, R., Liu, G., Liu, H., Liu, Q., Liu, S., Salvia, A. Lobo, Loi, A., Lollini, R., Castro, J. Lomba, Longstaff, I., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Louis, D., Lovell, G. H., Loveridge, P., Lowe, A. D., Lu, Y., Lucarelli, C., Lucchesi, D., Luchuk, S., Martinez, M. Lucio, Lukashenko, V., Lukianov, A., Luo, H., Luo, Y., Lupato, A., Luppi, E., Lupton, O., Lusiani, A., Lutz, L. F., Lynch, K., Lyu, X. -R., Ma, R., Maccolini, S., Machefert, F., Maciuc, F., Mackay, I., Macko, V., Mackowiak, P., Maddrell-Mander, S., Mohan, L. R. Madhan, Maevskiy, A., Magne, M., Maisuzenko, D., Majewski, M. W., Malaguti, R., Malczewski, J. J., Malde, S., Malecki, B., Malinin, A., Malkinski, K., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manuzzi, D., Manzari, C. A., Marangotto, D., Marchand, J. F., Marconi, U., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Marshall, P. J., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Santos, D. Martinez, Vidal, F. Martinez, Masic, B., Massafferri, A., Materok, M., Matev, R., Mathad, A., Mathe, Z., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., de Cos, J. Mazorra, Mazurek, M., McCann, M., Mcconnell, L., McGrath, T. H., McHugh, N. T., McNab, A., McNulty, R., Mead, J. V., Meadows, B., Meier, G., Meier-villardita, L., Melnychuk, D., Meloni, S., Merk, M., Merli, A., Meunier, J. L., Garcia, L. Meyer, Miao, D., Mikhasenko, M., Milanes, D. A., Millard, E., Miller, G., Milovanovic, M., Minard, M. -N., Minotti, A., Minutoli, S., Miralles, T., Mitchell, S. E., Mitreska, B., Mittelstaedt, T., Mitzel, D. S., Mödden, A., Modenese, L., Mogini, A., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Mombächer, T., Monk, M., Monroy, I. A., Monteil, S., Monti, M., Morandin, M., Morello, G., Morello, M. J., Morgenthaler, M. P., Moron, J., Morris, A. B., Morris, A. G., Mountain, R., Mu, H., Muhammad, E., Muheim, F., Mulder, M., Muley, S., Müller, D., Müller, K., Munneke, B., Murphy, C. H., Murray, D., Murta, R., Muzzetto, P., Naik, P., Naik, S. A., Nakada, T., Nandakumar, R., Nanut, T., Nasteva, I., Nazarov, E., Needham, M., Neri, I., Neri, N., Neubert, S., Neufeld, N., Neustroev, P., Newcombe, R., Trung, T. Nguyen, Nicolini, J., Nicotra, D., Niel, E. M., Nieswand, S., Nikitin, N., Nolte, N. S., Normand, C., Fernandez, J. Novoa, Nowak, G. N, Nunez, C., O'Bannon, T., Oblakowska-Mucha, A., Obraztsov, V., O'Dell, J., Oeser, T., Okamura, S., Oldeman, R., Oliva, F., Olive, P., Onderwater, C. J. G., O'Neil, R. H., Orlov, V., Goicochea, J. M. Otalora, Ovsiannikova, T., Owen, P., Oyanguren, A., Ozcelik, O., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Pan, Y., Panshin, G., Paoletti, E., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parker, W., Parkes, C., Pasquali, L., Passalacqua, B., Passaleva, G., Pastore, A., Patel, M., Patrignani, C., Pavlenko, D., Pawley, C. J., Pearce, A., Regales, M. D. P. Peco, Pellegrino, A., Peltier, F., Altarelli, M. Pepe, Perazzini, S., Pereima, D., Castro, A. Pereiro, Perret, P., Perro, A., Perry, M., Pessina, G., Petridis, K., Petrolini, A., Petrucci, S., Petruzzo, M., Pham, H., Philippov, A., Piandani, R., Pica, L., Olloqui, E. Picatoste, Piccini, M., Piedigrossi, D., Pietrzyk, B., Pietrzyk, G., Pili, M., Pillet, N., Pilorz, E. M., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Plews, J., Casasus, M. Plo, Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polyakov, V., Polycarpo, E., Pomery, G. J., Ponce, S., Pons, X., Poplawski, K., Popov, D., Poslavskii, S., Prasanth, K., Pratt, D., Promberger, L., Prouve, C., Pugatch, V., Puill, V., Punzi, G., Qi, H. R., Qian, W., Qin, N., Qu, S., Quagliani, R., Raab, N. V., Rachwal, B., Rademacker, J. H., Rajagopalan, R., Rama, M., Ramaherison, J. J., Pernas, M. Ramos, Rangel, M. S., Ratnikov, F., Raven, G., De Miguel, M. Rebollo, Redi, F., Reich, J., Reiss, F., Alepuz, C. Remon, Ren, Z., Resmi, P. K., Rethore, F., Reynet, D., Ribatti, R., Ricci, A. M., Ricciardi, S., Richards, D. S., Richardson, K., Richardson-Slipper, M., Riedinger, J., Rinnert, K., Robbe, P., Robertson, G., Rochet, J., Rodrigues, A. B., Rodrigues, E., Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Perez, P. Rodriguez, Rodriguez, E. Rodriguez, Roeland, E., Rolf, D. L., Rollings, A., Roloff, P., Romanovskiy, V., Lamas, M. Romero, Vidal, A. Romero, Rosier, P., Roth, J. D., Rotondo, M., Rovekamp, J., Roy, L., Rudnyckyj, F., Rudolph, M. S., Ruf, T., Fernandez, R. A. Ruiz, Vidal, J. Ruiz, Ryzhikov, A., Ryzka, J., Silva, J. J. Saborido, Sagidova, N., Sahoo, N., Saitta, B., Salomoni, M., Gras, C. Sanchez, Sanders, F., Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santovetti, E., Saputi, A., Saranin, D., Sarpis, G., Sarpis, M., Sarti, A., Satriano, C., Satta, A., Saur, M., Saussac, A., Savrina, D., Sazak, H., Sborzacchi, F., Smead, L. G. Scantlebury, Scarabotto, A., Schael, S., Scherl, S., Schiller, M., Schimmel, A., Schindler, H., Schipper, J. D., Schmeitz, R., Schmelling, M., Schmidt, B., Schmitt, S., Schneider, O., Schneider, T., Schopper, A., Schubiger, M., Schulte, S., Schune, M. H., Schwemmer, R., Sciascia, B., Sciuccati, A., Sellam, S., Semennikov, A., Soares, M. Senghi, Sergi, A., Serra, N., Sestak, J., Sestini, L., Seuthe, A., Seyfert, P., Shang, Y., Shangase, D. M., Shapkin, M., Shchemerov, I., Shchutska, L., Shears, T., Shekhtman, L., Shen, Z., Sheng, S., Sherman, M. s, Shevchenko, V., Shi, B., Shields, E. B., Shimizu, Y., Shmanin, E., Shorkin, R., Shupperd, J. D., Siddi, B. G., Siebig, S., Sigmund, D., Sigurdsson, S., Coutinho, R. Silva, Simi, G., Simone, S., Singla, M., Skidmore, N., Skuza, R., Skwarnicki, T., Slater, M. W., Slattery, K., Slazyk, I., Smallwood, J. C., Smeaton, J. G., Smith, E., Smith, K., Smith, M., Smith, N. A., Snoch, A., Lavra, L. Soares, Socha, J-L., Sokoloff, M. D., Soler, F. J. P., Solomin, A., Solovev, A., Solovyev, I., Song, R., De Almeida, F. L. Souza, De Paula, B. Souza, Spaan, B., Norella, E. Spadaro, Spedicato, E., Spiridenkov, E., Spradlin, P., Squerzanti, S., Sriskaran, V., Stagni, F., Stahl, M., Stahl, S., Stanislaus, S., Steffens, E., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Stone, S., Stramaglia, M. E., Strekalina, D., Su, Y. S, Suljik, F., Sun, J., Sun, L., Sun, Y., Svihra, P., Swallow, P. N., Swientek, K., Swientek, S., Szabelski, A., Szumlak, T., Szymanski, M., Tagliente, G, Tan, Y., Taneja, S., Tat, M. D., Quere, M. Taurigna, Terentev, A., Terront, D. F., Teubert, F., Thomas, E., Thompson, D. J. D., Thomson, K. A., Tilquin, H., Tisserand, V., T'Jampens, S., Tobin, M., Tomassetti, L., Tonani, G., Tong, X., Topp-Joergensen, S., Machado, D. Torres, Tou, D. Y., Trilov, S. M., Trippl, C., Tuci, G., Tuning, N., Ukleja, A., Unverzagt, D. J., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagner, A., Vagnoni, V., Valassi, A., Valat, S., Valenti, G., Canudas, N. Valls, van Beuzekom, M., Van De Kraats, P. W., van der Heijden, B., Van Dijk, M., van Dongen, J., Van Hecke, H., van Herwijnen, E., Van Hulse, C. B., Van Nieuwland, L., van Overbeek, M., Van Stenis, M., van Veghel, M., Vandaele, R., Gomez, R. Vazquez, Regueiro, P. Vazquez, Sierra, C. Vázquez, Vecchi, S., Veldt, L., Velthuis, J. J., Veltri, M., Venkateswaran, A., Verkooijnen, H., Veronesi, M., Vesterinen, M., Barbosa, J. V. Viana, Vieira, D., Diaz, M. Vieites, Viel, K. J., Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Vink, W., Vitkovskiy, A., Volkov, V., Volle, F. C., Bruch, D. vom, Voneki, B., Vorbach, O., Vorobyev, A., Vorobyev, V., Voropaev, N., Vos, K., Vouters, G., Vrahas, C., Walet, W., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, J., Wang, M., Wang, R., Wang, X., Wang, Y., Wang, Z., Ward, J. A., Warda, K., Watson, N. K., Websdale, D., Webster, J., Wei, Y., Westhenry, B. D. C., White, D. J., Whitehead, M., Wieczorek, D., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, I., Williams, M., Williams, M. R. J., Williams, R., Wilson, F. F., Wimberley, J., Windelband, B., Wislicki, W., Witek, M., Witola, L., Wlochal, M., Wong, C. P., Wormald, M., Wormser, G., Wotton, S. A., Wraight, K., Wu, H., Wu, J., Wyllie, K., Xiang, Z., Xie, Y., Xu, A., Xu, J., Xu, L., Xu, M., Xu, Q., Xu, Z., Yang, D., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeomans, L. E., Yeroshenko, V., Yeung, H., Yin, H., Yu, J., Yuan, X., Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zenaiev, O., Zeng, M., Zhang, C., Zhang, D., Zhang, L., Zhang, S., Zhang, Y., Zhao, Y., Zharkova, A., Zhelezov, A., Zheng, Y., Zhou, T., Zhou, X., Zhou, Y., Zhovkovska, V., Zhu, X., Zhu, Z., Zhukov, V., Zivkovic, V., Zou, Q., Zucchelli, S., Zuliani, D., Zunica, G., and Zvyagintsev, S.
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High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
The LHCb upgrade represents a major change of the experiment. The detectors have been almost completely renewed to allow running at an instantaneous luminosity five times larger than that of the previous running periods. Readout of all detectors into an all-software trigger is central to the new design, facilitating the reconstruction of events at the maximum LHC interaction rate, and their selection in real time. The experiment's tracking system has been completely upgraded with a new pixel vertex detector, a silicon tracker upstream of the dipole magnet and three scintillating fibre tracking stations downstream of the magnet. The whole photon detection system of the RICH detectors has been renewed and the readout electronics of the calorimeter and muon systems have been fully overhauled. The first stage of the all-software trigger is implemented on a GPU farm. The output of the trigger provides a combination of totally reconstructed physics objects, such as tracks and vertices, ready for final analysis, and of entire events which need further offline reprocessing. This scheme required a complete revision of the computing model and rewriting of the experiment's software., Comment: All figures and tables, along with any supplementary material and additional information, are available at http://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-DP-2022-002.html (LHCb public pages)
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- 2023
12. A single subcutaneous dose of eprinomectin (Eprecis®) is effective against common gastrointestinal nematodes and lungworms in experimentally infected lactating goats
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Beck, Alexandra, Thomson, Sarah, Reddick, David, Brunner, Rike, Campbell-Wilson, Dana, Achard, Damien, Isaka, Naomi, Trotel, Anne, and Karembe, Hamadi
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- 2024
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13. A microfluidic platform integrating functional vascularized organoids-on-chip
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Quintard, Clément, Tubbs, Emily, Jonsson, Gustav, Jiao, Jie, Wang, Jun, Werschler, Nicolas, Laporte, Camille, Pitaval, Amandine, Bah, Thierno-Sidy, Pomeranz, Gideon, Bissardon, Caroline, Kaal, Joris, Leopoldi, Alexandra, Long, David A., Blandin, Pierre, Achard, Jean-Luc, Battail, Christophe, Hagelkruys, Astrid, Navarro, Fabrice, Fouillet, Yves, Penninger, Josef M., and Gidrol, Xavier
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- 2024
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14. RoCNet: 3D Robust Registration of Point-Clouds using Deep Learning
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Slimani, Karim, Tamadazte, Brahim, and Achard, Catherine
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Computer Science - Computer Vision and Pattern Recognition - Abstract
This paper introduces a new method for 3D point cloud registration based on deep learning. The architecture is composed of three distinct blocs: (i) an encoder composed of a convolutional graph-based descriptor that encodes the immediate neighbourhood of each point and an attention mechanism that encodes the variations of the surface normals. Such descriptors are refined by highlighting attention between the points of the same set and then between the points of the two sets. (ii) a matching process that estimates a matrix of correspondences using the Sinkhorn algorithm. (iii) Finally, the rigid transformation between the two point clouds is calculated by RANSAC using the Kc best scores from the correspondence matrix. We conduct experiments on the ModelNet40 dataset, and our proposed architecture shows very promising results, outperforming state-of-the-art methods in most of the simulated configurations, including partial overlap and data augmentation with Gaussian noise., Comment: 8 pages
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- 2023
15. Clustering-Based Inter-Regional Correlation Estimation
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Lbath, Hanâ, Petersen, Alexander, Meiring, Wendy, and Achard, Sophie
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Statistics - Methodology - Abstract
A novel non-parametric estimator of the correlation between grouped measurements of a quantity is proposed in the presence of noise. This work is primarily motivated by functional brain network construction from fMRI data, where brain regions correspond to groups of spatial units, and correlation between region pairs defines the network. The challenge resides in the fact that both noise and intra-regional correlation lead to inconsistent inter-regional correlation estimation using classical approaches. While some existing methods handle either one of these issues, no non-parametric approaches tackle both simultaneously. To address this problem, we propose a trade-off between two procedures: correlating regional averages, which is not robust to intra-regional correlation; and averaging pairwise inter-regional correlations, which is not robust to noise. To that end, we project the data onto a space where Euclidean distance is used as a proxy for sample correlation. We then propose to leverage hierarchical clustering to gather together highly correlated variables within each region prior to inter-regional correlation estimation. We provide consistency results, and empirically show our approach surpasses several other popular methods in terms of quality. We also provide illustrations on real-world datasets that further demonstrate its effectiveness.
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- 2023
16. A single subcutaneous dose of eprinomectin (Eprecis®) is effective against common gastrointestinal nematodes and lungworms in experimentally infected lactating goats
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Alexandra Beck, Sarah Thomson, David Reddick, Rike Brunner, Dana Campbell-Wilson, Damien Achard, Naomi Isaka, Anne Trotel, and Hamadi Karembe
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Gastrointestinal nematodes ,Lungworms ,Teladorsagia circumcincta ,Haemonchus contortus ,Trichostrongylus colubriformis ,Dictyocaulus filaria ,Infectious and parasitic diseases ,RC109-216 - Abstract
Abstract Background The health and productivity of dairy goats continue to be impacted by gastrointestinal nematodes (GIN) and lungworms (LW). Eprinomectin (EPN) is frequently selected for treatment because it is generally effective and does not require a milk withdrawal period. However, some factors, such as lactation, can have an impact on EPN pharmacokinetics and potentially its efficacy. To evaluate whether this can alter the efficacy of Eprecis® 2%, an eprinomectin injectable solution, a study was performed in lactating goats using the dose currently registered in cattle, sheep and goats (0.2 mg/kg). Methods This study was a blinded, randomized, controlled trial performed according to the VICH guidelines. Eighteen (18) worm-free lactating goats were included and experimentally challenged on day 28 with a mixed culture of infective gastrointestinal and lung nematode larvae (Haemonchus contortus, Trichostrongylus colubriformis, Teladorsagia circumcincta, Dictyocaulus filaria). At D-1, fecal samples were collected to confirm patent infection in all animals. On D0, the goats were randomly allocated into two groups of nine goats; group 1 was treated with Eprecis® 2% at 0.2 mg/kg BW by subcutaneous injection, while group 2 remained untreated. Fecal samples for egg counts were collected from all animals on days 3, 5, 7, 9, 11 and 14. On D14, all goats were killed, and the abomasum, small intestine and lungs were removed, processed and subsampled to record the number and species of worms. Results The treatment was well tolerated. After treatment, the arithmetic mean FEC decreased in the treated group and remained < 5 EPG until the end of the study, while the arithmetic mean FEC in the control group remained > 849.0 EPG. At D14, goats in the treated group had very limited or zero total worm counts, whereas all animals from the control group had a high worm burden. The measured efficacy was 100.0% against H. contortus and T. colubriformis, 99.9% against T. circumcincta and 98.0% against D. filaria. Conclusions Eprinomectin (Eprecis®, 20 mg/ml), administered at the label dose (0.2 mg/kg), is highly effective against gastrointestinal nematodes and lungworms in lactating goats. Graphical abstract
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- 2024
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17. All-Optical Nuclear Quantum Sensing using Nitrogen-Vacancy Centers in Diamond
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Bürgler, Beat, Sjolander, Tobias F., Brinza, Ovidiu, Tallaire, Alexandre, Achard, Jocelyn, and Maletinsky, Patrick
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Condensed Matter - Mesoscale and Nanoscale Physics ,Quantum Physics - Abstract
Solid state spins have demonstrated significant potential in quantum sensing with applications including fundamental science, medical diagnostics and navigation. The quantum sensing schemes showing best performance under ambient conditions all utilize microwave or radio-frequency driving, which poses a significant limitation for miniaturization, energy-efficiency and non-invasiveness of quantum sensors. We overcome this limitation by demonstrating a purely optical approach to coherent quantum sensing. Our scheme involves the $^{15}$N nuclear spin of the Nitrogen-Vacancy (NV) center in diamond as a sensing resource, and exploits NV spin dynamics in oblique magnetic fields near the NV's excited state level anti-crossing to optically pump the nuclear spin into a quantum superposition state. We demonstrate all-optical free-induction decay measurements - the key protocol for low-frequency quantum sensing - both on single spins and spin ensembles. Our results pave the way for highly compact quantum sensors to be employed for magnetometry or gyroscopy applications in challenging environments., Comment: 6 pages, 4 figures, plus supplementary material. Questions and comments are welcome
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- 2022
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18. A Mixed Model Approach for Estimating Regional Functional Connectivity from Voxel-level BOLD Signals
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Zhang, Chao, Tran, Chau, Achard, Sophie, Meiring, Wendy, and Petersen, Alexander
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Statistics - Methodology ,Statistics - Applications - Abstract
Resting state brain functional connectivity quantifies the similarity between brain regions, each of which consists of voxels at which dynamic signals are acquired via neuroimaging techniques such as blood-oxygen-level-dependent signals in functional magnetic resonance imaging. Pearson correlation and similar metrics have been adopted by neuroscientists to estimate inter-regional connectivity, usually after averaging of signals within regions. However, dependencies between signals within each region and the presence of noise could contaminate such inter-regional correlation estimates. We propose a mixed-effects model with a novel covariance structure that explicitly isolates the different sources of variability in the observed BOLD signals, including correlated regional signals, local spatiotemporal variability, and measurement error. Methods for tackling the computational challenges associated with restricted maximum likelihood estimation will be discussed. Large sample properties are discussed and used for uncertainty quantification. Simulation results demonstrate that the parameters of the proposed model parameters can be accurately estimated and is superior to the Pearson correlation of averages in the presence of spatiotemporal noise. The proposed model is also applied to a real data set of BOLD signals collected from rats to construct individual brain networks., Comment: 25 pages, 6 figures
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- 2022
19. p$^3$VAE: a physics-integrated generative model. Application to the pixel-wise classification of airborne hyperspectral images
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Thoreau, Romain, Risser, Laurent, Achard, Véronique, Berthelot, Béatrice, and Briottet, Xavier
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Computer Science - Computer Vision and Pattern Recognition ,Statistics - Machine Learning ,68T45 ,I.2.6 ,I.2.10 - Abstract
The combination of machine learning models with physical models is a recent research path to learn robust data representations. In this paper, we introduce p$^3$VAE, a generative model that integrates a physical model which deterministically models some of the true underlying factors of variation in the data. To fully leverage our hybrid design, we enhance an existing semi-supervised optimization technique and introduce a new inference scheme that comes along meaningful uncertainty estimates. We apply p$^3$VAE to the pixel-wise classification of airborne hyperspectral images. Our experiments on simulated and real data demonstrate the benefits of our hybrid model against conventional machine learning models in terms of extrapolation capabilities and interpretability. In particular, we show that p$^3$VAE naturally has high disentanglement capabilities. Our code and data have been made publicly available at https://github.com/Romain3Ch216/p3VAE., Comment: 29 pages, 14 figures, submitted to Springer Machine Learning
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- 2022
20. Nodal statistics-based equivalence relation for graph collections
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Carboni, Lucrezia, Dojat, Michel, and Achard, Sophie
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Quantitative Biology - Neurons and Cognition - Abstract
Node role explainability in complex networks is very difficult, yet is crucial in different application domains such as social science, neurosciences or computer science. Many efforts have been made on the quantification of hubs revealing particular nodes in a network using a given structural property. Yet, in several applications, when multiple instances of networks are available and several structural properties appear to be relevant, the identification of node roles remains largely unexplored. Inspired by the node automorphically equivalence relation, we define an equivalence relation on graph nodes associated with any collection of nodal statistics (i.e. any functions on the node-set). This allows us to define new graph global measures: the power coefficient, and the orthogonality score to evaluate the parsimony and heterogeneity of a given nodal statistics collection. In addition, we introduce a new method based on structural patterns to compare graphs that have the same vertices set. This method assigns a value to a node to determine its role distinctiveness in a graph family. Extensive numerical results of our method are conducted on both generative graph models and real data concerning human brain functional connectivity. The differences in nodal statistics are shown to be dependent on the underlying graph structure. Comparisons between generative models and real networks combining two different nodal statistics reveal the complexity of human brain functional connectivity with differences at both global and nodal levels. Using a group of 200 healthy controls connectivity networks, our method computes high correspondence scores among the whole population, to detect homotopy, and finally quantify differences between comatose patients and healthy controls., Comment: 15 pages, 16 figures
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- 2022
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21. Optical properties of SiV and GeV color centers in nanodiamonds under hydrostatic pressures up to 180 GPa
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Vindolet, Baptiste, Adam, Marie-Pierre, Toraille, Loïc, Chipaux, Mayeul, Hilberer, Antoine, Dupuy, Géraud, Razinkovas, Lukas, Alkauskas, Audrius, Thiering, Gergő, Gali, Adam, De Feudis, Mary, Ngambou, Midrel Wilfried Ngandeu, Achard, Jocelyn, Tallaire, Alexandre, Schmidt, Martin, Becher, Christoph, and Roch, Jean-François
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Quantum Physics ,Condensed Matter - Materials Science - Abstract
We investigate the optical properties of silicon-vacancy (SiV) and germanium-vacancy (GeV) color centers in nanodiamonds under hydrostatic pressure up to 180 GPa. The nanodiamonds were synthetized by Si or Ge-doped plasma assisted chemical vapor deposition and, for our experiment, pressurized in a diamond anvil cell. Under hydrostatic pressure we observe blue-shifts of the SiV and GeV zero-phonon lines by 17 THz (70 meV) and 78 THz (320 meV), respectively. These measured pressure induced shifts are in good agreement with ab initio calculations that take into account the lattice compression based on the equation of state of diamond and that are extended to the case of the tin-vacancy (SnV) center. This work provides guidance on the use of group-IV-vacancy centers as quantum sensors under extreme pressures that will exploit their specific optical and spin properties induced by their intrinsic inversion-symmetric structure., Comment: 7 pages, 4 figures
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- 2022
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22. Microscopic-scale recording of brain neuronal electrical activity using a diamond quantum sensor
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Hansen, Nikolaj Winther, Webb, James Luke, Troise, Luca, Olsson, Christoffer, Tomasevic, Leo, Brinza, Ovidiu, Achard, Jocelyn, Staacke, Robert, Kieschnick, Michael, Meijer, Jan, Thielscher, Axel, Siebner, Hartwig Roman, Berg-Sørensen, Kirstine, Perrier, Jean-François, Huck, Alexander, and Andersen, Ulrik Lund
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Physics - Biological Physics ,Physics - Applied Physics ,Quantum Physics - Abstract
An important tool in the investigation of the early stages of neurodegenerative disease is the study of dissected living tissue from the brain of an animal model. Such investigations allow the physical structure of individual neurons and neural circuits to be probed alongside neuronal electrical activity, disruption of which can shed light on the mechanisms of emergence of disease. Existing techniques for recording activity rely on potentially damaging direct interaction with the sample, either mechanically as point electrical probes or via intense focused laser light combined with highly specific genetic modification and/or potentially toxic fluorescent dyes. In this work, we instead perform passive, microscopic-scale recording of electrical activity using a biocompatible quantum sensor based on colour centres in diamond. We record biomagnetic field induced by ionic currents in mouse corpus callosum axons without direct sample interaction, accurately recovering signals corresponding to action potential propagation while demonstrating in situ pharmacology during biomagnetic recording through tetrodotoxin inhibition of voltage gated sodium channels. Our results open a promising new avenue for the microscopic recording of neuronal signals, offering the prospect of high resolution imaging of electrical circuits in the living mammalian brain.
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- 2022
23. A microfluidic platform integrating functional vascularized organoids-on-chip
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Clément Quintard, Emily Tubbs, Gustav Jonsson, Jie Jiao, Jun Wang, Nicolas Werschler, Camille Laporte, Amandine Pitaval, Thierno-Sidy Bah, Gideon Pomeranz, Caroline Bissardon, Joris Kaal, Alexandra Leopoldi, David A. Long, Pierre Blandin, Jean-Luc Achard, Christophe Battail, Astrid Hagelkruys, Fabrice Navarro, Yves Fouillet, Josef M. Penninger, and Xavier Gidrol
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Science - Abstract
Abstract The development of vascular networks in microfluidic chips is crucial for the long-term culture of three-dimensional cell aggregates such as spheroids, organoids, tumoroids, or tissue explants. Despite rapid advancement in microvascular network systems and organoid technologies, vascularizing organoids-on-chips remains a challenge in tissue engineering. Most existing microfluidic devices poorly reflect the complexity of in vivo flows and require complex technical set-ups. Considering these constraints, we develop a platform to establish and monitor the formation of endothelial networks around mesenchymal and pancreatic islet spheroids, as well as blood vessel organoids generated from pluripotent stem cells, cultured for up to 30 days on-chip. We show that these networks establish functional connections with the endothelium-rich spheroids and vascular organoids, as they successfully provide intravascular perfusion to these structures. We find that organoid growth, maturation, and function are enhanced when cultured on-chip using our vascularization method. This microphysiological system represents a viable organ-on-chip model to vascularize diverse biological 3D tissues and sets the stage to establish organoid perfusions using advanced microfluidics.
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- 2024
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24. Conditioner application improves bedding quality and bacterial composition with potential beneficial impacts for dairy cow’s health
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Lysiane Duniere, Bastien Frayssinet, Caroline Achard, Eric Chevaux, and Julia Plateau
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RMS-bedding ,mastitis ,bacterial communities ,teat skin ,SCC ,Microbiology ,QR1-502 - Abstract
ABSTRACTRecycled manure solids (RMS) is used as bedding material in cow housing but can be at risk for pathogens development. Cows spend several hours per day lying down, contributing to the transfer of potential mastitis pathogens from the bedding to the udder. The effect of a bacterial conditioner (Manure Pro, MP) application was studied on RMS-bedding and milk qualities and on animal health. MP product was applied on bedding once a week for 3 months. Bedding and teat skin samples were collected from Control and MP groups at D01, D51, and D90 and analyzed through 16S rRNA amplicon sequencing. MP application modified bacterial profiles and diversity. Control bedding was significantly associated with potential mastitis pathogens, while no taxa of potential health risk were significantly detected in MP beddings. Functional prediction identified enrichment of metabolic pathways of agronomic interest in MP beddings. Significant associations with potential mastitis pathogens were mainly observed in Control teat skin samples. Finally, significantly better hygiene and lower Somatic Cell Counts in milk were observed for cows from MP group, while no group impact was observed on milk quality and microbiota. No dissemination of MP strains was observed from bedding to teats or milk.IMPORTANCEThe use of Manure Pro (MP) conditioner improved recycled manure solids-bedding quality and this higher sanitary condition had further impacts on dairy cows' health with less potential mastitis pathogens significantly associated with bedding and teat skin samples of animals from MP group. The animals also presented an improved inflammation status, while milk quality was not modified. The use of MP conditioner on bedding may be of interest in controlling the risk of mastitis onset for dairy cows and further associated costs.
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- 2024
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25. Laser stimulation of muscle activity with simultaneous detection using a diamond colour centre biosensor
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Troise, Luca, Hansen, Nikolaj Winther, Olsson, Christoffer, Webb, James Luke, Tomasevic, Leo, Achard, Jocelyn, Brinza, Ovidiu, Staacke, Robert, Kieschnick, Michael, Meijer, Jan, Thielscher, Axel, Siebner, Hartwig Roman, Berg-Sørensen, Kirstine, Perrier, Jean-François, Huck, Alexander, and Andersen, Ulrik Lund
- Subjects
Physics - Biological Physics ,Physics - Applied Physics ,Physics - Optics ,Quantum Physics - Abstract
The detection of physiological activity at the microscopic level is key for understanding the function of biosystems and relating this to physical structure. Current sensing methods often rely on invasive probes to stimulate and detect activity, bearing the risk of inducing damage in the target system. In recent years, a new type of biosensor based on color centers in diamond offers the possibility to passively, noninvasively sense and image living biological systems. Here, we use such a sensor for the \textit{in-vitro} recording of the local magnetic field generated by tightly focused, high intensity pulsed laser optogenetic neuromuscular stimulation of the extensor digitorum longus muscles. Recordings captured a compound action potential response and a slow signal component which we seek to explain using a detailed model of the biological system. We show that our sensor is capable of recording localized neuromuscular activity from the laser stimulation site without photovoltaic or fluorescence artifacts associated with alternative techniques. Our work represents an important step towards selective induction of localized neurobiological activity while performing passive sensing and imaging with diamond sensors, motivating further research into mapping of neural activity and intra-cellular processes.
- Published
- 2021
26. Mapping of Clay Montmorillonite Abundance in Agricultural Fields Using Unmixing Methods at Centimeter Scale Hyperspectral Images
- Author
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Etienne Ducasse, Karine Adeline, Audrey Hohmann, Véronique Achard, Anne Bourguignon, Gilles Grandjean, and Xavier Briottet
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clay ,montmorillonite ,imaging spectroscopy ,unmixing ,spectral preprocessing ,agricultural ploughed fields ,Science - Abstract
The composition of clay minerals in soils, and more particularly the presence of montmorillonite (as part of the smectite family), is a key factor in soil swell–shrinking as well as off–road vehicle mobility. Detecting these topsoil clay minerals and quantifying the montmorillonite abundance are a challenge since they are usually intimately mixed with other minerals, soil organic carbon and soil moisture content. Imaging spectroscopy coupled with unmixing methods can address these issues, but the quality of the estimation degrades the coarser the spatial resolution is due to pixel heterogeneity. With the advent of UAV-borne and proximal hyperspectral acquisitions, it is now possible to acquire images at a centimeter scale. Thus, the objective of this paper is to evaluate the accuracy and limitations of unmixing methods to retrieve montmorillonite abundance from very-high-resolution hyperspectral images (1.5 cm) acquired from a camera installed on top of a bucket truck over three different agricultural fields, in Loiret department, France. Two automatic endmember detection methods based on the assumption that materials are linearly mixed, namely the Simplex Identification via Split Augmented Lagrangian (SISAL) and the Minimum Volume Constrained Non-negative Matrix Factorization (MVC-NMF), were tested prior to unmixing. Then, two linear unmixing methods, the fully constrained least square method (FCLS) and the multiple endmember spectral mixture analysis (MESMA), and two nonlinear unmixing ones, the generalized bilinear method (GBM) and the multi-linear model (MLM), were performed on the images. In addition, several spectral preprocessings coupled with these unmixing methods were applied in order to improve the performances. Results showed that our selected automatic endmember detection methods were not suitable in this context. However, unmixing methods with endmembers taken from available spectral libraries performed successfully. The nonlinear method, MLM, without prior spectral preprocessing or with the application of the first Savitzky–Golay derivative, gave the best accuracies for montmorillonite abundance estimation using the USGS library (RMSE between 2.2–13.3% and 1.4–19.7%). Furthermore, a significant impact on the abundance estimations at this scale was in majority due to (i) the high variability of the soil composition, (ii) the soil roughness inducing large variations of the illumination conditions and multiple surface scatterings and (iii) multiple volume scatterings coming from the intimate mixture. Finally, these results offer a new opportunity for mapping expansive soils from imaging spectroscopy at very high spatial resolution.
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- 2024
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27. Surface production of negative ions from pulse-biased nitrogen doped diamond within a low-pressure deuterium plasma
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Smith, Gregory J., Tahri, Lenny, Achard, Jocelyn, Issaoui, Riadh, Gans, Timo, Dedrick, James P., and Cartry, Gilles
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Physics - Plasma Physics - Abstract
The production of negative ions is of significant interest for applications including mass spectrometry, materials surface processing, and neutral beam injection for magnetic confined fusion. Neutral beam injection sources maximise negative ion production through the use of surface production processes and low work function metals, which introduce complex engineering. Investigating materials and techniques to avoid the use of low work function metals is of interest to broaden the application of negative ion sources and simplify future devices. In this study, we use pulsed sample biasing to investigate the surface production of negative ions from nitrogen doped diamond. The use of a pulsed bias allows for the study of insulating samples in a preserved surface state at temperatures between 150$^{\circ}$C and 700$^{\circ}$C in a 2 Pa, 130 W, (n$_e$ $\sim$ $10^9$ cm$^{-3}$, T$_e$ $\sim$ 0.6 eV) inductively coupled deuterium plasma. The negative ion yield during the application of a pulsed negative bias is measured using a mass spectrometer and found to be approximately 20% higher for nitrogen doped diamond compared to non-doped diamond. It is also shown that the pulsed sample bias has a lower peak negative ion yield compared to a continuous sample bias, which suggests that the formation of an optimum ratio of defects on its surface can be favourable for negative ion production., Comment: This is the Accepted Manuscript version of an article accepted for publication in Journal of Physics D: Applied physics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. This Accepted Manuscript is published under a CC BY licence. The Version of Record is available online at
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- 2021
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28. Higher levels of Pseudomonas aeruginosa LasB elastase expression are associated with early-stage infection in cystic fibrosis patients
- Author
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Llanos, Agustina, Achard, Pauline, Bousquet, Justine, Lozano, Clarisse, Zalacain, Magdalena, Sable, Carole, Revillet, Hélène, Murris, Marlène, Mittaine, Marie, Lemonnier, Marc, and Everett, Martin
- Published
- 2023
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29. Microscopic-scale magnetic recording of brain neuronal electrical activity using a diamond quantum sensor
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Hansen, Nikolaj Winther, Webb, James Luke, Troise, Luca, Olsson, Christoffer, Tomasevic, Leo, Brinza, Ovidiu, Achard, Jocelyn, Staacke, Robert, Kieschnick, Michael, Meijer, Jan, Thielscher, Axel, Siebner, Hartwig Roman, Berg-Sørensen, Kirstine, Perrier, Jean-François, Huck, Alexander, and Andersen, Ulrik Lund
- Published
- 2023
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30. A universal tool for stability predictions of biotherapeutics, vaccines and in vitro diagnostic products
- Author
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Huelsmeyer, M., Kuzman, D., Bončina, M., Martinez, J., Steinbrugger, C., Weusten, J., Calero-Rubio, C., Roche, W., Niederhaus, B., VanHaelst, Y., Hrynyk, M., Ballesta, P., Achard, H., Augusto, S., Guillois, M., Pszczolinski, C., Gerasimov, M., Neyra, C., Ponduri, D., Ramesh, S., and Clénet, D.
- Published
- 2023
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31. All-optical nuclear quantum sensing using nitrogen-vacancy centers in diamond
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Bürgler, B., Sjolander, T. F., Brinza, O., Tallaire, A., Achard, J., and Maletinsky, P.
- Published
- 2023
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32. Combined functional genomic and metabolomic approaches identify new genes required for growth in human urine by multidrug-resistant Escherichia coli ST131
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Minh-Duy Phan, Horst Joachim Schirra, Nguyen Thi Khanh Nhu, Kate M. Peters, Sohinee Sarkar, Luke P. Allsopp, Maud E. S. Achard, Ulrike Kappler, and Mark A. Schembri
- Subjects
uropathogenic Escherichia coli ,urinary tract infection ,bacterial pathogenesis ,Microbiology ,QR1-502 - Abstract
ABSTRACT Urinary tract infections (UTIs) are one of the most common bacterial infections in humans, with ~400 million cases across the globe each year. Uropathogenic Escherichia coli (UPEC) is the major cause of UTI and increasingly associated with antibiotic resistance. This scenario has been worsened by the emergence and spread of pandemic UPEC sequence type 131 (ST131), a multidrug-resistant clone associated with extraordinarily high rates of infection. Here, we employed transposon-directed insertion site sequencing in combination with metabolomic profiling to identify genes and biochemical pathways required for growth and survival of the UPEC ST131 reference strain EC958 in human urine (HU). We identified 24 genes required for growth in HU, which mapped to diverse pathways involving small peptide, amino acid and nucleotide metabolism, the stringent response pathway, and lipopolysaccharide biosynthesis. We also discovered a role for UPEC resistance to fluoride during growth in HU, most likely associated with fluoridation of drinking water. Complementary nuclear magnetic resonance (NMR)-based metabolomics identified changes in a range of HU metabolites following UPEC growth, the most pronounced being L-lactate, which was utilized as a carbon source via the L-lactate dehydrogenase LldD. Using a mouse UTI model with mixed competitive infection experiments, we demonstrated a role for nucleotide metabolism and the stringent response in UPEC colonization of the mouse bladder. Together, our application of two omics technologies combined with different infection-relevant settings has uncovered new factors required for UPEC growth in HU, thus enhancing our understanding of this pivotal step in the UPEC infection pathway.IMPORTANCEUropathogenic Escherichia coli (UPEC) cause ~80% of all urinary tract infections (UTIs), with increasing rates of antibiotic resistance presenting an urgent threat to effective treatment. To cause infection, UPEC must grow efficiently in human urine (HU), necessitating a need to understand mechanisms that promote its adaptation and survival in this nutrient-limited environment. Here, we used a combination of functional genomic and metabolomic techniques and identified roles for the metabolism of small peptides, amino acids, nucleotides, and L-lactate, as well as the stringent response pathway, lipopolysaccharide biosynthesis, and fluoride resistance, for UPEC growth in HU. We further demonstrated that pathways involving nucleotide metabolism and the stringent response are required for UPEC colonization of the mouse bladder. The UPEC genes and metabolic pathways identified in this study represent targets for the development of innovative therapeutics to prevent UPEC growth during human UTI, an urgent need given the rapidly rising rates of global antibiotic resistance.
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- 2024
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33. Stereotactic body radiation therapy for prostate cancer after surgical treatment of prostatic obstruction: Impact on urinary morbidity and mitigation strategies
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Constance Huck, Vérane Achard, Priyamvada Maitre, Vedang Murthy, and Thomas Zilli
- Subjects
Prostate cancer ,Radiotherapy ,Stereotactic body radiation therapy ,Transurethral resection ,Adenomectomy ,Toxicity ,Medical physics. Medical radiology. Nuclear medicine ,R895-920 ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
In the past decade, stereotactic body radiation therapy (SBRT) has emerged as a valid treatment option for patients with localized prostate cancer. Despite the promising results of ultra-hypofractionation in terms of tolerance and disease control, the toxicity profile of SBRT for prostate cancer patients with a history of surgical treatment of benign prostate hyperplasia is still underreported. Here we present an overview of the available data on urinary morbidity for prostate cancer patients treated with SBRT after prior surgical treatments for benign prostate hyperplasia. Technical improvements useful to minimize toxicity and possible treatments for radiation-induced urethritis are discussed.
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- 2024
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34. Point-Of-Care low-field MRI in acute Stroke (POCS): protocol for a multicentric prospective open-label study evaluating diagnostic accuracy
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Mauro Silvestrini, Simona Sacco, Massimo Caulo, Simona Marcheselli, Carmine Marini, Sergio Lucio Vinci, Angelo Galante, Marco Colasurdo, Raffaele Ornello, Matteo Foschi, Stefano Necozione, Mario Muselli, Paola Olimpia Achard, Luciano Fratocchi, Marco Cavallaro, Gabriele Polonara, Laura Straffi, Luca Sorrentino, Enrico Franconi, and Marcello Alecci
- Subjects
Medicine - Abstract
Introduction Fast and accurate diagnosis of acute stroke is crucial to timely initiate reperfusion therapies. Conventional high-field (HF) MRI yields the highest accuracy in discriminating early ischaemia from haemorrhages and mimics. Rapid access to HF-MRI is often limited by contraindications or unavailability. Low-field (LF) MRI (
- Published
- 2024
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35. Are Land‐Use Change Emissions in Southeast Asia Decreasing or Increasing?
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Kondo, Masayuki, Sitch, Stephen, Ciais, Philippe, Achard, Frédéric, Kato, Etsushi, Pongratz, Julia, Houghton, Richard A, Canadell, Josep G, Patra, Prabir K, Friedlingstein, Pierre, Li, Wei, Anthoni, Peter, Arneth, Almut, Chevallier, Frédéric, Ganzenmüller, Raphael, Harper, Anna, Jain, Atul K, Koven, Charles, Lienert, Sebastian, Lombardozzi, Danica, Maki, Takashi, Nabel, Julia EMS, Nakamura, Takashi, Niwa, Yosuke, Peylin, Philippe, Poulter, Benjamin, Pugh, Thomas AM, Rödenbeck, Christian, Saeki, Tazu, Stocker, Benjamin, Viovy, Nicolas, Wiltshire, Andy, and Zaehle, Sönke
- Subjects
Earth Sciences ,Atmospheric Sciences ,Aging ,Life on Land ,Southeast Asia ,land-use changes ,Dynamic Global Vegetation Models ,book-keeping models ,forest area ,atmospheric inversions ,Geochemistry ,Oceanography ,Meteorology & Atmospheric Sciences ,Geoinformatics ,Climate change impacts and adaptation - Abstract
Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision.
- Published
- 2022
36. Local Whittle estimation with (quasi-)analytic wavelets
- Author
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Achard, Sophie and Gannaz, Irène
- Subjects
Mathematics - Statistics Theory - Abstract
In the general setting of long-memory multivariate time series, the long-memory characteristics are defined by two components. The long-memory parameters describe the autocorrelation of each time series. And the long-run covariance measures the coupling between time series, with general phase parameters. It is of interest to estimate the long-memory, long-run covariance and general phase parameters of time series generated by this wide class of models although they are not necessarily Gaussian nor stationary. This estimation is thus not directly possible using real wavelets decomposition or Fourier analysis. Our purpose is to define an inference approach based on a representation using quasi-analytic wavelets. We first show that the covariance of the wavelet coefficients provides an adequate estimator of the covariance structure including the phase term. Consistent estimators based on a local Whittle approximation are then proposed. Simulations highlight a satisfactory behavior of the estimation on finite samples on linear time series and on multivariate fractional Brownian motions. An application on a real neuroscience dataset is presented, where long-memory and brain connectivity are inferred.
- Published
- 2021
37. Higher levels of Pseudomonas aeruginosa LasB elastase expression are associated with early-stage infection in cystic fibrosis patients
- Author
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Agustina Llanos, Pauline Achard, Justine Bousquet, Clarisse Lozano, Magdalena Zalacain, Carole Sable, Hélène Revillet, Marlène Murris, Marie Mittaine, Marc Lemonnier, and Martin Everett
- Subjects
Medicine ,Science - Abstract
Abstract Pseudomonas aeruginosa is a common pathogen in cystic fibrosis (CF) patients and a major contributor to progressive lung damage. P. aeruginosa elastase (LasB), a key virulence factor, has been identified as a potential target for anti-virulence therapy. Here, we sought to differentiate the P. aeruginosa isolates from early versus established stages of infection in CF patients and to determine if LasB was associated with either stage. The lasB gene was amplified from 255 P. aeruginosa clinical isolates from 70 CF patients from the Toulouse region (France). Nine LasB variants were identified and 69% of the isolates produced detectable levels of LasB activity. Hierarchical clustering using experimental and clinical data distinguished two classes of isolates, designated as ‘Early’ and ‘Established’ infection. Multivariate analysis revealed that the isolates from the Early infection class show higher LasB activity, fast growth, tobramycin susceptibility, non-mucoid, pigmented colonies and wild-type lasR genotype. These traits were associated with younger patients with polymicrobial infections and high pFEV1. Our findings show a correlation between elevated LasB activity in P. aeruginosa isolates and early-stage infection in CF patients. Hence, it is this patient group, prior to the onset of chronic disease, that may benefit most from novel therapies targeting LasB.
- Published
- 2023
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38. Microscopic-scale magnetic recording of brain neuronal electrical activity using a diamond quantum sensor
- Author
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Nikolaj Winther Hansen, James Luke Webb, Luca Troise, Christoffer Olsson, Leo Tomasevic, Ovidiu Brinza, Jocelyn Achard, Robert Staacke, Michael Kieschnick, Jan Meijer, Axel Thielscher, Hartwig Roman Siebner, Kirstine Berg-Sørensen, Jean-François Perrier, Alexander Huck, and Ulrik Lund Andersen
- Subjects
Medicine ,Science - Abstract
Abstract Quantum sensors using solid state qubits have demonstrated outstanding sensitivity, beyond that possible using classical devices. In particular, those based on colour centres in diamond have demonstrated high sensitivity to magnetic field through exploiting the field-dependent emission of fluorescence under coherent control using microwaves. Given the highly biocompatible nature of diamond, sensing from biological samples is a key interdisciplinary application. In particular, the microscopic-scale study of living systems can be possible through recording of temperature and biomagnetic field. In this work, we use such a quantum sensor to demonstrate such microscopic-scale recording of electrical activity from neurons in fragile living brain tissue. By recording weak magnetic field induced by ionic currents in mouse corpus callosum axons, we accurately recover signals from neuronal action potential propagation while demonstrating in situ pharmacology. Our sensor allows recording of the electrical activity in neural circuits, disruption of which can shed light on the mechanisms of disease emergence. Unlike existing techniques for recording activity, which can require potentially damaging direct interaction, our sensing is entirely passive and remote from the sample. Our results open a promising new avenue for the microscopic recording of neuronal signals, offering the eventual prospect of microscopic imaging of electrical activity in the living mammalian brain.
- Published
- 2023
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39. Inter-regional correlation estimators for functional magnetic resonance imaging
- Author
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Achard, Sophie, Coeurjolly, Jean-Francois, de Micheaux, Pierre Lafaye, and Richiardi, Jonas
- Subjects
Statistics - Methodology - Abstract
Functional magnetic resonance imaging (fMRI) functional connectivity between brain regions is often computed using parcellations defined by functional or structural atlases. Typically, some kind of voxel averaging is performed to obtain a single temporal correlation estimate per region pair. However, several estimators can be defined for this task, with various assumptions and degrees of robustness to local noise, global noise, and region size. In this paper, we systematically present and study the properties of 9 different functional connectivity estimators taking into account the spatial structure of fMRI data, based on a simple fMRI data spatial model. These include 3 existing estimators and 6 novel estimators. We demonstrate the empirical properties of the estimators using synthetic, animal, and human data, in terms of graph structure, repeatability and reproducibility, discriminability, dependence on region size, as well as local and global noise robustness. We prove analytically the link between regional intra-correlation and inter-region correlation, and show that the choice of estimator has a strong influence on inter-correlation values.
- Published
- 2020
40. SALAD: Self-Assessment Learning for Action Detection
- Author
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Vaudaux-Ruth, Guillaume, Chan-Hon-Tong, Adrien, and Achard, Catherine
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Literature on self-assessment in machine learning mainly focuses on the production of well-calibrated algorithms through consensus frameworks i.e. calibration is seen as a problem. Yet, we observe that learning to be properly confident could behave like a powerful regularization and thus, could be an opportunity to improve performance.Precisely, we show that used within a framework of action detection, the learning of a self-assessment score is able to improve the whole action localization process.Experimental results show that our approach outperforms the state-of-the-art on two action detection benchmarks. On THUMOS14 dataset, the mAP at tIoU@0.5 is improved from 42.8\% to 44.6\%, and from 50.4\% to 51.7\% on ActivityNet1.3 dataset. For lower tIoU values, we achieve even more significant improvements on both datasets.
- Published
- 2020
41. The carbon sink of secondary and degraded humid tropical forests
- Author
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Heinrich, Viola H. A., Vancutsem, Christelle, Dalagnol, Ricardo, Rosan, Thais M., Fawcett, Dominic, Silva-Junior, Celso H. L., Cassol, Henrique L. G., Achard, Frédéric, Jucker, Tommaso, Silva, Carlos A., House, Jo, Sitch, Stephen, Hales, Tristram C., and Aragão, Luiz E. O. C.
- Published
- 2023
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42. A universal tool for stability predictions of biotherapeutics, vaccines and in vitro diagnostic products
- Author
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M. Huelsmeyer, D. Kuzman, M. Bončina, J. Martinez, C. Steinbrugger, J. Weusten, C. Calero-Rubio, W. Roche, B. Niederhaus, Y. VanHaelst, M. Hrynyk, P. Ballesta, H. Achard, S. Augusto, M. Guillois, C. Pszczolinski, M. Gerasimov, C. Neyra, D. Ponduri, S. Ramesh, and D. Clénet
- Subjects
Medicine ,Science - Abstract
Abstract It is of particular interest for biopharmaceutical companies developing and distributing fragile biomolecules to warrant the stability and activity of their products during long-term storage and shipment. In accordance with quality by design principles, advanced kinetic modeling (AKM) has been successfully used to predict long-term product shelf-life and relies on data from short-term accelerated stability studies that are used to generate Arrhenius-based kinetic models that can, in turn, be exploited for stability forecasts. The AKM methodology was evaluated through a cross-company perspective on stability modeling for key stability indicating attributes of different types of biotherapeutics, vaccines and biomolecules combined in in vitro diagnostic kits. It is demonstrated that stability predictions up to 3 years for products maintained under recommended storage conditions (2–8 °C) or for products that have experienced temperature excursions outside the cold-chain show excellent agreement with experimental real-time data, thus confirming AKM as a universal and reliable tool for stability predictions for a wide range of product types.
- Published
- 2023
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43. All-optical nuclear quantum sensing using nitrogen-vacancy centers in diamond
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B. Bürgler, T. F. Sjolander, O. Brinza, A. Tallaire, J. Achard, and P. Maletinsky
- Subjects
Physics ,QC1-999 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Abstract Solid state spins have demonstrated significant potential in quantum sensing with applications including fundamental science, medical diagnostics and navigation. The quantum sensing schemes showing best performance under ambient conditions all utilize microwave or radio-frequency driving, which poses a significant limitation for miniaturization, energy efficiency, and non-invasiveness of quantum sensors. We overcome this limitation by demonstrating a purely optical approach to coherent quantum sensing. Our scheme involves the 15N nuclear spin of the Nitrogen-Vacancy (NV) center in diamond as a sensing resource, and exploits NV spin dynamics in oblique magnetic fields near the NV’s excited state level anti-crossing to optically pump the nuclear spin into a quantum superposition state. We demonstrate all-optical free-induction decay measurements—the key protocol for low-frequency quantum sensing—both on single spins and spin ensembles. Our results pave the way for highly compact quantum sensors to be employed for magnetometry or gyroscopy applications in challenging environments.
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- 2023
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44. First report of eprinomectin-resistant isolates of Haemonchus contortus in 5 dairy sheep farms from the Pyrénées Atlantiques département in France
- Author
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S. Jouffroy, L. Bordes, C. Grisez, J. F. Sutra, T. Cazajous, J. Lafon, N. Dumont, M. Chastel, C. Vial-Novella, D. Achard, H. Karembe, M. Devaux, M. Abbadie, C. Delmas, A. Lespine, and P. Jacquiet
- Subjects
Dairy sheep ,eprinomectin ,Haemonchus contortus ,resistance ,Biochemistry ,QD415-436 ,Infectious and parasitic diseases ,RC109-216 ,Microbiology ,QR1-502 - Abstract
Infection of sheep by gastrointestinal nematodes (GIN) in pastoral systems such as those found in the South Western area of France, the Pyrénées Atlantiques, is one of the main reasons for economic loss and degradation of their welfare. In the present study, the efficacy of eprinomectin (EPN) was monitored on farms from this area following suspicion of lack of anthelmintic efficacy. Suspicions were raised by veterinarians, based on clinical signs ranging from milk and body condition loss, to anaemia, and mortality. Resistance was evaluated according to the World Association for the Advancement for Veterinary Parasitology (WAAVP) guidelines using fecal egg count reduction tests reinforced by individual analysis of drug concentration in the serum of all treated ewes by high-performance liquid chromatography (HPLC). EPN was administered by subcutaneous (SC) and topical (T) route according to manufacturer's requirements, as well as by the oral route (O) with the topical solution according to off-labelled practices in the field. For the first time in France, the presence of resistant isolates of Haemonchus contortus to EPN was observed in 5 dairy sheep farms. The HPLC dosages showed exposure of worms to concentrations compatible with anthelmintic activity for animals treated by the SC and O routes. By contrast, they showed under exposure to the drug of most individuals treated by the T route. EPN is the only null milk withdrawal anthelmintic molecule currently available. The presence of resistant isolates of the pathogenic H. contortus to EPN in this important dairy region requires an urgent change in grazing, and sometimes production, systems.
- Published
- 2023
- Full Text
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45. Detection of biological signals from a live mammalian muscle using a diamond quantum sensor
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Webb, James Luke, Troise, Luca, Hansen, Nikolaj Winther, Olsson, Christoffer, Wojciechowski, Adam, Achard, Jocelyn, Brinza, Ovidiu, Staacke, Robert, Kieschnick, Michael, Meijer, Jan, Thielscher, Axel, Perrier, Jean-Francois, Berg-Sorensen, Kirstine, Huck, Alexander, and Andersen, Ulrik Lund
- Subjects
Physics - Biological Physics ,Physics - Applied Physics ,Physics - Medical Physics ,Quantum Physics - Abstract
The ability to perform noninvasive, non-contact measurements of electric signals produced by action potentials is essential in biomedicine. A key method to do this is to remotely sense signals by the magnetic field they induce. Existing methods for magnetic field sensing of mammalian tissue, used in techniques such as magnetoencephalography of the brain, require cryogenically cooled superconducting detectors. These have many disadvantages in terms of high cost, flexibility and limited portability as well as poor spatial and temporal resolution. In this work we demonstrate an alternative technique for detecting magnetic fields generated by the current from action potentials in living tissue using nitrogen vacancy centres in diamond. With 50pT/$\sqrt{Hz}$ sensitivity, we show the first measurements of sensing from mammalian tissue with a diamond sensor using mouse muscle optogenetically activated with blue light. We show these measurements can be performed in an ordinary, unshielded lab environment and that the signal can be easily recovered by digital signal processing techniques.
- Published
- 2020
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46. Impact of positive ion energy on carbon-surface production of negative ions in deuterium plasmas
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Kogut, D., Moussaoui, R., Ning, Ning, Faure, J., Layet, J., Farley, T, Achard, J., Gicquel, A., and Cartry, G.
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Physics - Plasma Physics - Abstract
This work focuses on the production of negative-ions on graphite and diamond surfaces bombarded by positive ions in a low pressure (2 Pa) low power (20 W) capacitively coupled deuterium plasma. A sample is placed opposite a mass spectrometer and negatively biased so that surface produced negative ions can be self-extracted from the plasma and measured by the mass spectrometer. The ratio between negative-ion counts at mass spectrometer and positive ion current at sample surface defines a relative negative-ion yield. Changes in negative-ion production yields versus positive ion energy in the range 10-60 eV are analysed. While the negative-ion production yield is decreasing for diamond surfaces when increasing the positive ion impact energy, it is strongly increasing for graphite. This increase is attributed to the onset of the sputtering mechanisms between 20 and 40 eV which creates negative ions at rather low energy that are efficiently collected by the mass spectrometer. The same mechanism occurs for diamond but is mitigated by a strong decrease of the ionization probability due to defect creation and loss of diamond electronic properties.
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- 2020
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47. Asymptotic control of FWER under Gaussian assumption: application to correlation tests
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Achard, Sophie, Borgnat, Pierre, and Gannaz, Irène
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Mathematics - Statistics Theory - Abstract
In many applications, hypothesis testing is based on an asymptotic distribution of statistics. The aim of this paper is to clarify and extend multiple correction procedures when the statistics are asymptotically Gaussian. We propose a unified framework to prove their asymptotic behavior which is valid in the case of highly correlated tests. We focus on correlation tests where several test statistics are proposed. All these multiple testing procedures on correlations are shown to control FWER. An extensive simulation study on correlation-based graph estimation highlights finite sample behavior, independence on the sparsity of graphs and dependence on the values of correlations. Empirical evaluation of power provides comparisons of the proposed methods. Finally validation of our procedures is proposed on real dataset of rats brain connectivity measured by fMRI. We confirm our theoretical findings by applying our procedures on a full null hypotheses with data from dead rats. Data on alive rats show the performance of the proposed procedures to correctly identify brain connectivity graphs with controlled errors.
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- 2020
48. Enhancing surface production of negative ions using nitrogen doped diamond in a deuterium plasma
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Smith, Gregory J., Ellis, James, Moussaoui, Roba, Pardanaud, Cédric, Martin, Céline, Achard, Jocelyn, Issaoui, Riadh, Gans, Timo, Dedrick, James P., and Cartry, Gilles
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Physics - Plasma Physics - Abstract
The production of negative ions is of significant interest for applications including mass spectrometry, particle acceleration, material surface processing, and neutral beam injection for magnetic confinement fusion. Methods to improve the efficiency of the surface production of negative ions, without the use of low work function metals, are of interest for mitigating the complex engineering challenges these materials introduce. In this study we investigate the production of negative ions by doping diamond with nitrogen. Negatively biased ($-20$ V or $-130$ V), nitrogen doped micro-crystalline diamond films are introduced to a low pressure deuterium plasma (helicon source operated in capacitive mode, 2 Pa, 26 W) and negative ion energy distribution functions (NIEDFs) are measured via mass spectrometry with respect to the surface temperature (30$^{\circ}$C to 750$^{\circ}$C) and dopant concentration. The results suggest that nitrogen doping has little influence on the yield when the sample is biased at $-130$ V, but when a relatively small bias voltage of $-20$ V is applied the yield is increased by a factor of 2 above that of un-doped diamond when its temperature reaches 550$^{\circ}$C. The doping of diamond with nitrogen is a new method for controlling the surface production of negative ions, which continues to be of significant interest for a wide variety of practical applications.
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- 2020
49. Coherent Microwave Control of a Nuclear Spin Ensemble at Room Temperature
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Huillery, P., Leibold, J., Delord, T., Nicolas, L., Achard, J., Tallaire, A., and Hétet, G.
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Quantum Physics - Abstract
We use nominally forbidden electron-nuclear spin transitions in nitrogen-vacancy (NV) centers in diamond to demonstrate coherent manipulation of a nuclear spin ensemble using microwave fields at room temperature. We show that employing an off-axis magnetic field with a modest amplitude($\approx$ 0.01 T) at an angle with respect to the NV natural quantization axes is enough to tilt the direction of the electronic spins, and enable efficient spin exchange with the nitrogen nuclei of the NV center. We could then demonstrate fast Rabi oscillations on electron-nuclear spin exchanging transitions, coherent population trapping and polarization of nuclear spin ensembles in the microwave regime. Coupling many electronic spins of NV centers to their intrinsic nuclei offers full scalability with respect to the number of controllable spins and provides prospects for transduction. In particular, the technique could be applied to long-lived storage of microwave photons and to the coupling of nuclear spins to mechanical oscillators in the resolved sideband regime., Comment: 15 pages, 14 figures
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- 2020
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50. Manifold learning for brain connectivity
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Renard, Félix, Heinrich, Christian, Bouthillon, Marine, Schenck, Maleka, Schneider, Francis, Kremer, Stéphane, and Achard, Sophie
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Quantitative Biology - Neurons and Cognition ,Statistics - Applications - Abstract
Human brain connectome studies aim at extracting and analyzing relevant features associated to pathologies of interest. Usually this consists in modeling the brain connectome as a graph and in using graph metrics as features. A fine brain description requires graph metrics computation at the node level. Given the relatively reduced number of patients in standard cohorts, such data analysis problems fall in the high-dimension low sample size framework. In this context, our goal is to provide a machine learning technique that exhibits flexibility, gives the investigator grip on the features and covariates, allows visualization and exploration, and yields insight into the data and the biological phenomena at stake. The retained approach is dimension reduction in a manifold learning methodology, the originality lying in that one (or several) reduced variables be chosen by the investigator. The proposed method is illustrated on two studies, the first one addressing comatose patients, the second one addressing young versus elderly population comparison. The method sheds light on the graph metrics and underlying neurobiological phenomena., Comment: submitted
- Published
- 2020
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