Publications - 'P'

Publications 1401 - 1425 de 2458
| % | ( | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | < | ? | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | [ | ` | {
Titre DOI
Predator-prey mass ratio drives microbial activity under dry conditions in Sphagnum peatlands
M.K. Reczuga; M. Lamentowicz; M. Mulot; E.A.D. Mitchell; A. Buttler; B. Chojnicki; M. Slowinski; P. Binet; G. Chiapusio; D. Gilbert; S. Slowinska; V.E.J. Jassey
2018
10.1002/ece3.4114
Predict and prevent from misbehaving intruders in heterogeneous vehicular networks
H. Sedjelmaci; S.Mohammed Senouci; T. Bouali
2017
10.1016/j.vehcom.2016.12.005
Predictability of drug encapsulation and release from propylene carbonate/PLGA microparticles
D. Grizic; A. Lamprecht
2020
10.1016/j.ijpharm.2020.119601
Predicted Drosophila Interactome Resource and web tool for functional interpretation of differentially expressed genes
X.B. Ding; J. Jin; Y.T. Tao; W.P. Guo; L. Ruan; Qlei Yang; P.C. Chen; H. Yao; Hbo Zhang; X. Chen
2020
10.1093/database/baaa005
Predicting antidepressant treatment without controlling for depression is ill-advised
R. Bianchi; I.Sam Schonfeld; E. Laurent
2015
10.1016/j.jpsychires.2015.07.007
Predicting As, Cd, Cu, Pb and Zn levels in grasses (Agrostis sp and Poa sp.) and stinging nettle (Urtica dioica) applying soil-plant transfer models
M. Boshoff; M. De Jonge; R. Scheifler; L. Bervoets
2014
10.1016/j.scitotenv.2014.06.076
Predicting bloom dates by temperature mediated kinetics of carbohydrate metabolism in deciduous trees
O. Sperling; T. Kamai; A. Tixier; A. Davidson; K. Jarvis-Shean; E. Raveh; T.M. DeJong; M.A. Zwieniecki
2019
10.1016/j.agrformet.2019.107643
Predicting Climate Impacts on Health at Sub-seasonal to Seasonal Timescales
A.M. Tompkins; R. Lowe; H. Nissan; N. Martiny; P. Roucou; M.C. Thomson; T. Nakazawa
2019
10.1016/B978-0-12-811714-9.00022-X
Predicting Dengue Fever Outbreaks in French Guiana Using Climate Indicators
A. Adde; P. Roucou; M. Mangeas; V. Ardillon; J.C. Desenclos; D. Rousset; R. Girod; S. Briolant; P. Quenel; C. Flamand
2016
10.1371/journal.pntd.0004681
Predicting disease risk areas through co-production of spatial models: The example of Kyasanur Forest Disease in India's forest landscapes
B.V. Purse; N. Darshan; G.S. Kasabi; F. Gerard; A. Samrat; C. George; A.T. Vanak; M. Oommen; M. Rahman; S.J. Burthe; J.C. Young; P.N. Srinivas; S.M. Schafer; P.A. Henrys; V.K. Sandhya; M. Chanda; M.V. Murhekar; S.L. Hoti; S.K. Kiran
2020
10.1371/journal.pntd.0008179
Predicting Fire Brigades Operational Breakdowns: A Real Case Study
S. Cerna; C. Guyeux; G. Royer; C. Chevallier; G. Plumerel
2020
10.3390/math8081383
Predicting heart failure class using a sequence prediction algorithm
C.Bou Rjeily; G. Badr; A.Hajjam Al Hassani; E. Andres
2017
Predicting in-hospital major bleeding in pulmonary embolism patients treated with systemic thrombolytic therapy
K.P. Kresoja; N. Meneveau; D. Jimenez; O. Sanchez; C. Becattini; F. Spillmann; B. Sobkowicz; S. Vanni; S. Konstantinides; M. Kurzyna; P. Pruszczyk; H. Wilkens; C. Bova; G. Meyer; M. Lankeit
2018
Predicting odor similarity of complex mixtures from molecular approach
A. Roche; T. Thomas-Danguin; J. Mainland
2019
Predicting odor similarity of complex mixtures from molecular approach
A. Roche; T. Thomas-Danguin; J. Mainland
2019
Predicting outcome in patients with sepsis: new biomarkers for old expectations
P.E. Charles; S. Gibot
2014
10.1186/cc13723
Predicting poor prognosis recurrence in women with endometrial cancer: a nomogram developed by the FRANCOGYN study group
L. Ouldamer; S. Bendifallah; G. Body; C. Touboul; O. Graesslin; E. Raimond; P. Collinet; C. Coutant; V. Lavoue; J. Leveque; E. Darai; M. Ballester; G.Recherche FRANCOGYN
2016
10.1038/bjc.2016.337
Predicting postoperative complications with the respiratory exchange ratio after high-risk noncardiac surgery A prospective cohort study
S. Bar; C. Grenez; M. Nguyen; B. de Broca; E. Bernard; O. Abou-Arab; B. Bouhemad; E. Lorne; P.G. Guinot
2020
10.1097/EJA.0000000000001111
Predicting Temporal Gait Kinematics: Anthropometric Characteristics and Global Running Pattern Matter
A. Patoz; T. Lussiana; C. Gindre; L. Mourot
2021
10.3389/fphys.2020.625557
Predicting the development of in-hospital cardiogenic shock in patients with ST-segment elevation myocardial infarction treated by primary percutaneous coronary intervention: the ORBI risk score
V. Auffret; Y. Cottin; G. Leurent; M. Gilard; J.C. Beer; A. Zabalawi; F. Chague; E. Filippi; D. Brunet; J.P. Hacot; P. Brunel; M. Mejri; L. Lorgis; G. Rouault; P. Druelles; J.C. Cornily; R. Didier; E. Bot; B. Boulanger; I. Coudert; A. Loirat; M. Bedossa; D. Boulmier; M. Maza; M. Le Guellec; R. Puri; M. Zeller; H. Le Breton; O.R.B.I.R.I.C.O.Worki Grp
2018
10.1093/eurheartj/ehy127
Predicting the invasion of the acoustic niche: Potential distribution and call transmission efficiency of a newly introduced frog in Cuba
S.L. del Cas Dominguez; C.A.Mancina Gonzalez; E.Bandera Fernandez; L.Perez Pelea; F. Cezilly; R.Alonso Bosch
2021
10.1016/j.pecon.2020.12.002
Predicting the Long-Term Efficacy of Ifna in JAK2(V617F) and Calr-Mutated MPN Patients
A. Tisserand; R. Noble; M. Mosca; C. Marzac; G. Vertenoeil; H. Campario; M. El-Khoury; C. Marty; P. Rameau; N. Casadevall; E. Solary; F. Pasquier; H. Raslova; B. Cassinat; S.N. Constantinescu; J.J. Kiladjian; F. Girodon; M. Hochberg; V. Jean-Luc; W. Vainchenker; I. Plo
2019
10.1182/blood-2019-127903
Predicting the retinal content in omega-3 fatty acids for age-related macular- degeneration
N. Acar; B.M.J. Merle; S. Ajana; Z. He; S. Gregoire; B.P. Hejblum; L. Martine; B. Buaud; A.M. Bron; C.P. Creuzot-Garcher; J.F. Korobelnik; O. Berdeaux; H. Jacqmin-Gadda; L. Bretillon; C. Delcourt; B.Lipid Status
2021
10.1002/ctm2.404
Predicting the seasonal evolution of southern African summer precipitation in the DePreSys3 prediction system
P.A. Monerie; J. Robson; B. Dong; B. Dieppois; B. Pohl; N. Dunstone
2019
10.1007/s00382-018-4526-3
Predicting ultrafast nonlinear dynamics in fibre optics with a recurrent neural network
L. Salmela; N. Tsipinakis; A. Foi; C. Billet; J.M. Dudley; G. Genty
2021
10.1038/s42256-021-00297-z

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