Magnetic Structure Investigations at the Nuclear Center

The magnetic structure of the compounds UOS, ß-CoSO4, YCO5, and HoCO5 is briefly described. UOS is antiferromagnetic. The Néel temperature is Tn=55°K. The magnetic cell is doubled in the c direction with a ++ - - sequence of U moments along c. The apparent spin is S∼1. The negative interaction corresponds to U-O-U links. In ß-CoSO4 (high-temperature modification, space group Pbnm), Co atoms are in 000, 00½, ½½½, ½½0. Here three different antiferromagnetic spin modes, mutually perpendicular, Ax(+ - - +), Gy(+-+-), and Cz(++ - - ), in the Wollan-Koehler notation, are coupled. Direction cosines are 0.71, 0.50, and 0.50, respectively. The Co moment is about 3,84 µB at 4.2°K. A field-induced spin flip to the configuration Fx, Cy, Gz is predicted. YCO5 is ferromagnetic at room temperature with a moment value of Co practically equal to that of metallic Co and moment direction along c, which is conserved down to 4.2°K. In HoCO5 the moment of Ho is opposite to those of the Co atoms. When cooling from room to liquid helium temperature, the direction of easy magnetization changes from near c to a direction in the basal plane and the Ho moment increases from 4 to about 9 µB. The compensation temperature is 70°K

Contribution of autochthonous maize populations for adaptation to European conditions

Early vigor, earliness and cold tolerance are the main potential contributions of European maize (Zea mays L.) for breeding programs for adaptation to areas with short growing seasons and cold springs. The objective of this research was to determine the potential contributions of populations from different European regions to breeding for adaptation. Six Spanish and six French maize populations differing on variability for earliness, vigor and cold tolerance were crossed in a complete diallel without reciprocals. The populations and their crosses were evaluated in the field and in a cold chamber. Minimum temperatures were the main environmental trait affecting genotype × environment interaction, probably due to the cold sensitivity of the genotypes with the best performance in the field. The best population cross, based on specific heterosis for adaptation-related traits in the field, was Viana × Rastrojero, but this cross was cold sensitive. Tuy × Lazcano should be the best choice for a breeding program for adaptation, based on performance in the field and cold tolerance. As conclusions, there was variability for earliness, vigor and cold tolerance among the populations and crosses involved in this study, being tolerant to cold conditions the populations with medium growing cycle originated in areas with short growing seasons. The highest yielding crosses were cold sensitive.Research supported by the Ministry of Science and Technology (Ref. HF1999-0138), the Ministère de l’Education Nationale et de la Recherche, the Committee for Science and Technology of Spain (Project AGL2004-06776), the Autonomous government of Galicia (PGIDIT04RAG403006PR), the Excma. Diputación Provincial de Pontevedra, and the European Union (RESGEN 88 CT96).Peer reviewe

A hybrid method for accurate iris segmentation on at-a-distance visible-wavelength images

[EN] This work describes a new hybrid method for accurate iris segmentation from full-face images independently of the ethnicity of the subject. It is based on a combination of three methods: facial key-point detection, integro-differential operator (IDO) and mathematical morphology. First, facial landmarks are extracted by means of the Chehra algorithm in order to obtain the eye location. Then, the IDO is applied to the extracted sub-image containing only the eye in order to locate the iris. Once the iris is located, a series of mathematical morphological operations is performed in order to accurately segment it. Results are obtained and compared among four different ethnicities (Asian, Black, Latino and White) as well as with two other iris segmentation algorithms. In addition, robustness against rotation, blurring and noise is also assessed. Our method obtains state-of-the-art performance and shows itself robust with small amounts of blur, noise and/or rotation. Furthermore, it is fast, accurate, and its code is publicly available.Fuentes-Hurtado, FJ.; Naranjo Ornedo, V.; Diego-Mas, JA.; Alcañiz Raya, ML. (2019). A hybrid method for accurate iris segmentation on at-a-distance visible-wavelength images. EURASIP Journal on Image and Video Processing (Online). 2019(1):1-14. https://doi.org/10.1186/s13640-019-0473-0S11420191A. Radman, K. Jumari, N. Zainal, Fast and reliable iris segmentation algorithm. IET Image Process.7(1), 42–49 (2013).M. Erbilek, M. Fairhurst, M. C. D. C Abreu, in 5th International Conference on Imaging for Crime Detection and Prevention (ICDP 2013). Age prediction from iris biometrics (London, 2013), pp. 1–5. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6913712&isnumber=6867223 .A. Abbasi, M. Khan, Iris-pupil thickness based method for determining age group of a person. Int. Arab J. Inf. Technol. (IAJIT). 13(6) (2016).G. Mabuza-Hocquet, F. Nelwamondo, T. Marwala, in Intelligent Information and Database Systems. ed. by N. Nguyen, S. Tojo, L. Nguyen, B. Trawiński. Ethnicity Distinctiveness Through Iris Texture Features Using Gabor Filters. ACIIDS 2017. Lecture Notes in Computer Science, vol. 10192 (Springer, Cham, 2017).S. Lagree, K. W. Bowyer, in 2011 IEEE International Conference on Technologies for Homeland Security (HST). Predicting ethnicity and gender from iris texture (IEEEWaltham, 2011). p. 440–445. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6107909&isnumber=6107829 .J. G. Daugman, High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Anal. Mach. Intell.15(11), 1148–1161 (1993).N. Kourkoumelis, M. Tzaphlidou. Medical Safety Issues Concerning the Use of Incoherent Infrared Light in Biometrics, eds. A. Kumar, D. Zhang. Ethics and Policy of Biometrics. ICEB 2010. Lecture Notes in Computer Science, vol 6005 (Springer, Berlin, Heidelberg, 2010).R. P. Wildes, Iris recognition: an emerging biometric technology. Proc. IEEE. 85(9), 1348–1363 (1997).M. Kass, A. Witkin, D. Terzopoulos, Snakes: Active contour models. Int. J. Comput. Vision. 1(4), 321–331 (1988).S. J. Pundlik, D. L. Woodard, S. T. Birchfield, in 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. Non-ideal iris segmentation using graph cuts (IEEEAnchorage, 2008). p. 1–6. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4563108&isnumber=4562948 .H. Proença, Iris recognition: On the segmentation of degraded images acquired in the visible wavelength. IEEE Trans. Pattern Anal. Mach. Intell.32(8), 1502–1516 (2010). http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5156505&isnumber=5487331 .T. Tan, Z. He, Z. Sun, Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition. Image Vision Comput.28(2), 223–230 (2010).C. -W. Tan, A. Kumar, in CVPR 2011 WORKSHOPS. Automated segmentation of iris images using visible wavelength face images (Colorado Springs, 2011). p. 9–14. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5981682&isnumber=5981671 .Y. -H. Li, M. Savvides, An automatic iris occlusion estimation method based on high-dimensional density estimation. IEEE Trans. Pattern Anal. Mach. Intell.35(4), 784–796 (2013).M. Yahiaoui, E. Monfrini, B. Dorizzi, Markov chains for unsupervised segmentation of degraded nir iris images for person recognition. Pattern Recogn. Lett.82:, 116–123 (2016).A. Radman, N. Zainal, S. A. Suandi, Automated segmentation of iris images acquired in an unconstrained environment using hog-svm and growcut. Digit. Signal Proc.64:, 60–70 (2017).N. Liu, H. Li, M. Zhang, J. Liu, Z. Sun, T. Tan, in 2016 International Conference on Biometrics (ICB). Accurate iris segmentation in non-cooperative environments using fully convolutional networks (Halmstad, 2016). p. 1–8. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7550055&isnumber=7550036 .Z. Zhao, A. Kumar, in 2017 IEEE International Conference on Computer Vision (ICCV). Towards more accurate iris recognition using deeply learned spatially corresponding features (Venice, 2017). p. 3829–3838. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8237673&isnumber=8237262 .P. Li, X. Liu, L. Xiao, Q. Song, Robust and accurate iris segmentation in very noisy iris images. Image Vision Comput.28(2), 246–253 (2010).D. S. Jeong, J. W. Hwang, B. J. Kang, K. R. Park, C. S. Won, D. -K. Park, J. Kim, A new iris segmentation method for non-ideal iris images. Image Vision Comput.28(2), 254–260 (2010).Y. Chen, M. Adjouadi, C. Han, J. Wang, A. Barreto, N. Rishe, J. Andrian, A highly accurate and computationally efficient approach for unconstrained iris segmentation. Image Vision Comput. 28(2), 261–269 (2010).Z. Zhao, A. Kumar, in 2015 IEEE International Conference on Computer Vision (ICCV). An accurate iris segmentation framework under relaxed imaging constraints using total variation model (Santiago, 2015). p. 3828–3836. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7410793&isnumber=7410356 .Y. Hu, K. Sirlantzis, G. Howells, Improving colour iris segmentation using a model selection technique. Pattern Recogn. Lett.57:, 24–32 (2015).E. Ouabida, A. Essadique, A. Bouzid, Vander lugt correlator based active contours for iris segmentation and tracking. Expert Systems Appl.71:, 383–395 (2017).C. -W. Tan, A. Kumar, Unified framework for automated iris segmentation using distantly acquired face images. IEEE Trans. Image Proc.21(9), 4068–4079 (2012).C. -W. Tan, A. Kumar, in Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012). Human identification from at-a-distance images by simultaneously exploiting iris and periocular features (Tsukuba, 2012). p. 553–556. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6460194&isnumber=6460043 .C. -W. Tan, A. Kumar, Towards online iris and periocular recognition under relaxed imaging constraints. IEEE Trans. Image Proc.22(10), 3751–3765 (2013).K. Y. Shin, Y. G. Kim, K. R. Park, Enhanced iris recognition method based on multi-unit iris images. Opt. Eng.52(4), 047201–047201 (2013).CASIA iris databases. http://biometrics.idealtest.org/ . Accessed 06 Sept 2017.WVU iris databases. hhttp://biic.wvu.edu/data-sets/synthetic-iris-dataset . Accessed 06 Sept 2017.UBIRIS iris database. http://iris.di.ubi.pt . Accessed 06 Sept 2017.MICHE iris database. http://biplab.unisa.it/MICHE/ . Accessed 06 Sept 2017.P. J. Phillips, et al, in 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), 1. Overview of the face recognition grand challenge (San Diego, 2005). p. 947–954. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1467368&isnumber=31472 .D. S. Ma, J. Correll, B. Wittenbrink, The chicago face database: A free stimulus set of faces and norming data. Behav. Res. Methods. 47(4), 1122–1135 (2015).P. Soille, Morphological Image Analysis: Principles and Applications (Springer, 2013).A. K. Jain, Fundamentals of Digital Image Processing (Prentice-Hall, Inc., Englewood Cliffs, 1989).J. Daugman, How iris recognition works. IEEE Trans. Circ. Syst. Video Technol.14(1), 21–30 (2004).A. Asthana, S. Zafeiriou, S. Cheng, M. Pantic, in 2014 IEEE Conference on Computer Vision and Pattern Recognition. Incremental face alignment in the wild (Columbus, 2014). p. 1859–1866. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6909636&isnumber=6909393 .T. Baltrusaitis, P. Robinson, L. -P. Morency, in 2013 IEEE International Conference on Computer Vision Workshops. Constrained local neural fields for robust facial landmark detection in the wild (Sydney, 2013). p. 354–361. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6755919&isnumber=6755862 .X. Zhu, D. Ramanan, in Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference On. Face detection, pose estimation, and landmark localization in the wild (IEEEBerlin Heidelberg, 2012), pp. 2879–2886.G. Tzimiropoulos, in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Project-out cascaded regression with an application to face alignment (Boston, 2015). p. 3659–3667. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7298989&isnumber=7298593 .H. Hofbauer, F. Alonso-Fernandez, P. Wild, J. Bigun, A. Uhl, in 2014 22nd International Conference on Pattern Recognition. A ground truth for iris segmentation (Stockholm, 2014). p. 527–532. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6976811&isnumber=6976709 .H. Proença, L. A. Alexandre, in 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems. The NICE.I: Noisy Iris Challenge Evaluation - Part I (Crystal City, 2007). p. 1–4. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4401910&isnumber=4401902 .J. Daugman, in European Convention on Security and Detection. High confidence recognition of persons by rapid video analysis of iris texture, (1995). p. 244–251. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=491729&isnumber=10615 .Code of Matlab implementation of Daugman’s integro-differential operator (IDO). https://es.mathworks.com/matlabcentral/fileexchange/15652-iris-segmentation-using-daugman-s-integrodifferential-operator/ . Accessed 06 Sept 2017.Code of Matlab implementation of Zhao and Kumar’s iris segmentation framework under relaxed imaging constraints using total variation model. http://www4.comp.polyu.edu.hk/~csajaykr/tvmiris.htm/ . Accessed 06 Sept 2017.Code of Matlab implementation of presented work. https://gitlab.com/ffuentes/hybrid_iris_segmentation/ . Accessed 06 Sept 2017.Face and eye detection with OpenCV. https://docs.opencv.org/trunk/d7/d8b/tutorial_py_face_detection.html . Accessed 07 Sept 2018.A. K. Boyat, B. K. Joshi, 6. A review paper:noise models in digital image processing signal & image processing. An International Journal (SIPIJ), (2015), pp. 63–75. https://doi.org/10.5121/sipij.2015.6206 .A. Buades, Y. Lou, J. M. Morel, Z. Tang, Multi image noise estimation and denoising (2010). Available: https://hal.archives-ouvertes.fr/hal-00510866/

Le destin exceptionnel du maïs

The Exceptional Destiny of Corn. After reviewing the long controversy concerning the origin of corn, the author sums up for us the various hypotheses regarding the botanic and genetic origin of this American plant. It is to the Amerindian civilizations of Central America that we owe its domestication, the first stages of which go back to 10,000 B.C.. Brought to Europe by Christopher Columbus in 1493, corn spread rapidly throughout the Mediterranean region. Later, it launched an assault of Africa and Asia. The adaptation of the plant to different ecological sectors would increase its diversity and cause a change in the lives of the local populations under the influence of joint selection on the part of farmer and setting. The sole species to exist only in a farmed form, corn is one of the main food plants of the modern farmer.Après un rappel de la longue contreverse sur l'origine du maïs, l'auteur nous résume les hypothèses concernant l'origine botanique et génétique de cette plante américaine. C'est aux civilisations amérindiennes de la Méso-Amérique qu'on doit sa domestication dont les premières étapes remontent à 10 000 ans BP. Introduit en Europe par Christophe Colomb dès 1493, le maïs aura une diffusion rapide dans le bassin méditerranéen. Plus tard, il partira à la conquête de l'Afrique puis de l'Asie. L'adap¬ tation de la plante à des niches écologiques variées va amplifier sa diversité et provoque une évolution vers des populations typées sous la pression de sélection conjointe de l'agriculteur et du milieu. Seule espèce à n'exister que sous la forme cultivée, le maïs est l'une des principales plantes alimentaires de l'agriculteur moderne.Boyat A. Le destin exceptionnel du maïs. In: Cahiers d'outre-mer. N° 179-180 - 45e année, Juillet-décembre 1992. Les plantes américaines à la conquête du monde, sous la direction de Yves Monnier et Alain Huetz de Lemps. pp. 315-326

Evaluation of three grain maize composites developed from broad-base synthetics by divergent selection on three complementary testers

Three composites, FC(TC)C0, FC(TD)C0 and FC(TI)C0, were developed from S1 families with good general combining ability, derived from broad-base maize synthetics. These synthetics were developed by the INRA (Institut national de la recherche agronomique) maize laboratory of Montpellier from inbred lines belonging to different heterotic groups. The idea was to develop new heterotic groups. Composite development is the initial phase of a recurrent selection program. The grain productivity of the composites (yield, grain moisture and lodging resistance) and their genetic divergence were evaluated in both diallel and topcross designs. In crosses with testers, the yields of composites were on average 11-14 q/ha less than that of commercial checks with a comparable grain moisture, and they were more susceptible to lodging. Heterosis for yield between composites was low. This low divergence is consistent with the constitution procedure of the composite, based mainly on the general combining ability.Évaluation de trois composites de maïs grain constitués à partir de synthétiques à base large par sélection divergente sur trois testeurs complémentaires. Trois composites de maïs, FC(TC)C0, FC(TD)C0 et FC(TI)C0, ont été constitués à partir des familles S1 ayant une bonne aptitude à la combinaison sur trois testeurs complémentaires, et issues de synthétiques à base large. Ces synthétiques ont été constitués par le laboratoire maïs de l'Institut national de la recherche agronomique (Inra) de Montpellier (France) à partir de lignées appartenant à divers groupes hétérotiques. L'idée était de développer de nouveaux groupes hétérotiques. La constitution des composites est la phase initiale d'un programme de sélection récurrente réciproque. Le comportement agronomique des composites pour la production de grain (rendement, humidité à maturité, résistance à la verse) et leur divergence génétique ont été évalués dans un réseau multilocal dans un plan de croisement diallèle associé à un plan de croisement avec les testeurs utilisés pour la sélection des constituants des composites. En croisement avec les testeurs, les composites ont un rendement moyen de 11 à 14 q/ha moins élevé que les témoins commerciaux actuels à précocité égale et une plus grande sensibilité à la verse. L'hétérosis pour le rendement entre les composites est faible. Cette faible divergence est en accord avec la procédure de constitution des composites privilégiant l'aptitude générale à la combinaison

Classification of French maize populations based on morphological traits

The genetic variability of the whole collection of 262 maize populations originating from metropolitan France was evaluated in two locations for agro-morphological traits. The most important variables in the principal component (PC) axis were related to maturity traits, and ear and grain shapes. On the first plane of the PC analysis, the distribution of populations was continuous, and populations from some particular regions were found grouped together: Pyrenees (early material and conical ears), Alsace (cylindrical ears), Bresse (mostly small kernels), Vallée de la Garonne (late material with long ears or with small kernels). The two distance matrices among populations calculated on the first four PC and on the geographic coordinates were correlated. Based on the first four standardized PC axes, which accounted for 77% of the variability, hierarchical classifications were computed and dendrograms confirmed the magnitude of maturity traits, and ear and kernel shapes in the classification.Classification des populations françaises de maïs basée sur les caractères morphologiques. L'ensemble des 262 populations originaires de France métropolitaine conservées dans la collection Inra-Promais a été étudié. La variabilité génétique a été évaluée en deux lieux pour les caractères agromorphologiques (précocité, épi, grain, panicule). Les variables déterminant les axes sont, dans l'ordre : la précocité, les formes de l'épi et du grain. Sur le premier plan de l'analyse en composantes principales, la répartition des populations est continue et les populations de quelques régions se regroupent avec des caractéristiques particulières : Pyrénées (matériel précoce à épi conique), Alsace (épi cylindrique), Bresse (petit grain pour la majorité), Vallée de la Garonne (matériel tardif à épi long ou à petit grains). Les matrices de distance entre populations calculées sur les coordonnées des axes de l'analyse en composantes principales et sur les coordonnées géographiques sont corrélées. À partir des quatre premiers axes standardisés de l'analyse en composantes principales représentant 77 % de variabilité, des analyses ascendantes hiérarchiques ont été effectuées. Les dendrogrammes confirment l'importance de ces caractères dans la classification

Evaluation of three grain maize composites developed from broad-base synthetics by divergent selection on three complementary testers

Three composites, FC(TC)C0, FC(TD)C0 and FC(TI)C0, were developed from S1 families with good general combining ability, derived from broad-base maize synthetics. These synthetics were developed by the INRA (Institut national de la recherche agronomique) maize laboratory of Montpellier from inbred lines belonging to different heterotic groups. The idea was to develop new heterotic groups. Composite development is the initial phase of a recurrent selection program. The grain productivity of the composites (yield, grain moisture and lodging resistance) and their genetic divergence were evaluated in both diallel and topcross designs. In crosses with testers, the yields of composites were on average 11-14 q/ha less than that of commercial checks with a comparable grain moisture, and they were more susceptible to lodging. Heterosis for yield between composites was low. This low divergence is consistent with the constitution procedure of the composite, based mainly on the general combining ability.Évaluation de trois composites de maïs grain constitués à partir de synthétiques à base large par sélection divergente sur trois testeurs complémentaires. Trois composites de maïs, FC(TC)C0, FC(TD)C0 et FC(TI)C0, ont été constitués à partir des familles S1 ayant une bonne aptitude à la combinaison sur trois testeurs complémentaires, et issues de synthétiques à base large. Ces synthétiques ont été constitués par le laboratoire maïs de l'Institut national de la recherche agronomique (Inra) de Montpellier (France) à partir de lignées appartenant à divers groupes hétérotiques. L'idée était de développer de nouveaux groupes hétérotiques. La constitution des composites est la phase initiale d'un programme de sélection récurrente réciproque. Le comportement agronomique des composites pour la production de grain (rendement, humidité à maturité, résistance à la verse) et leur divergence génétique ont été évalués dans un réseau multilocal dans un plan de croisement diallèle associé à un plan de croisement avec les testeurs utilisés pour la sélection des constituants des composites. En croisement avec les testeurs, les composites ont un rendement moyen de 11 à 14 q/ha moins élevé que les témoins commerciaux actuels à précocité égale et une plus grande sensibilité à la verse. L'hétérosis pour le rendement entre les composites est faible. Cette faible divergence est en accord avec la procédure de constitution des composites privilégiant l'aptitude générale à la combinaison

Caractéristiques cristallographiques, propriétés et structure magnétiques de TbPO4 dans la gamme 1,5 K-300 K

Magnetic susceptibility measurements, X-ray powder diffractometry in the 2.6-295 K temperature range, and neutron diffraction experiments at 1.5 K, 4.2 K and 300 K have been performed on TbPO4. This compound shows a paramagnetic behaviour for T > 2.2 K. An antiferromagnetic canted spin arrangement has been determined at 1.5 K. The Tb moments are oriented at about 20° from the tetragonal axis in the (110) plane; this value does not agree with the determination of Spooner, Lee and Moos. The magnetic structure is found to be monoclinic, the Shubnikov space group being C2'; the value of the magnetic moment extrapolated to U K is 7.9 μB. A very small crystal distortion, monoclinic or triclinic, occurs below 6 K ; the spin arrangement is compatible with a C centered face monoclinic cell ; the crystal space group is C2 and the Tb local symmetry is then lowered from tetragonal : 42 m(D2d) to monoclinic : 2(C2). The thermal expansion curves are given in the range 2.6 K-295 K : a very large negative thermal anomaly of the a parameter occurs progressively below 170 K, while the c parameter undergoes a usual Debye thermal expansion. Neutron diffraction data allow the interpretation of these latter crystallographic results : the crystal field anisotropy changes with decreasing temperature because oxygen ions surrounding the terbium move in a plane perpendicular to the c axis. The oxygen parameters are :[FORMULA] The lattice parameters' are :[FORMULA] .Le phosphate de terbium a été étudié par diffraction des rayons X entre 2,6 K et 295 K, par mesure de sa suscéptibilité magnétique et par diffraction neutronique à 1,5 K, 4,2 K et 300 K. Les paramètres du réseau quadratique sont : [FORMULE]. Les paramètres des oxygènes sont : [FORMULE](description non centro-symétrique du groupe I41/amd). TbPO4 a un comportement paramagnétique pour toute température supérieure à 2,2 K. L'arrangement des moments du terbium à 1,5 K est antiferromagnétique ; ces moments, colinéaires et situés dans les plans (110), font un angle de 20° avec l'axe c. La symétrie de la structure magnétique est monoclinique, le groupe de Shubnikov étant C2'. La valeur du moment magnétique extrapolée à 0 K est 7,9 μB. Une très faible distorsion du cristal, monoclinique ou triclinique, apparaît au-dessous de 6 K ; or, la maille de la structure magnétique est monoclinique à faces C centrées ; le groupe d'espace est C2(C32) et la symétrie du site de Tb est abaissée de 42 m(D2d) à 2(C2). Les courbes de dilatation thermique entre 2,6 K et 295 K font apparaître une très forte anomalie de dilatation du paramètre a (contraction de 0,04 % entre 6 K et 140 K) alors que le paramètre c suit une loi de Debye ordinaire. Cette anomalie a été interprétée par une variation de l'anisotropie du champ cristallin agissant sur l'ion terbium

Designing and Testing Basic Protocol for Medium Fast Bowler to Increase the Speed and Accuracy

Background: The skill of medium Fast bowlers to consistently maintain their pace and accuracy while bowling , help them to not allow batsman to settle in their inning, and benefit to bowlers to take their wickets. In field of cricket the various parameters like bowling speed and accuracy have been a major area of research. Aim. To study the effect of designed and tested basic protocol on medium Fast bowlers speed and  accuracy. To study the Kinematic measures in the first four overs of medium Fast bowling. To study the effect of a designed based training on, 6RM Squat Test , 6 RM Bench Press Test and Yo-Yo Intermittent Recovery Test Level 1 ( YYIRTL1). Material and Methods: 60 State Level  Male Medium Fast Cricket Bowlers  ( mean age under 19 boys ) were  divided into two  group one group will going to do subject specific protocol based training for 6 weeks and another  will be an control group.&nbsp