text:
, Yaakov and Barnes, Carol A and Rapp, Peter R},
doi = {10.1093/cercor/bhq210},
journal = {Cereb Cortex},
month = {jul},
number = {7},
pages = {1559--1573},
pmid = {21127015},
title = {{Volumetric correlates of spatiotemporal working and recognition memory impairment in aged rhesus monkeys}},
volume = {21},
year = {2011}
}
@book{Avants2012,
abstract = {Publicly available scientific resources help establish evaluation standards, provide a platform for teaching and may improve reproducibility. Version 4 of the Insight ToolKit ( ITK ) seeks to establish new standards in publicly available image registration methodology. In this work, we provide an overview and preliminary evaluation of the revised toolkit against registration based on the previous major ITK version (3.20). Furthermore, we propose a nomenclature that may be used to discuss registration frameworks via schematic representations. In total, the ITK contribution is intended as a structure to support reproducible research practices, will provide a more extensive foundation against which to evaluate new work in image registration and also enable application level programmers a broad suite of tools on which to build. {\textcopyright} 2012 Springer-Verlag.},
author = {Avants, B.B. and Tustison, N.J. and Song, G. and Wu, B. and Stauffer, M. and McCormick, M.M. and Johnson, H.J. and Gee, J.C.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-642-31340-0_28},
isbn = {9783642313394},
issn = {03029743},
title = {{A unified image registration framework for ITK}},
volume = {7359 LNCS},
year = {2012}
}
@article{Tustison2013c,
abstract = {Diffeomorphic mappings are central to image registration due largely to their topological properties and success in providing biologically plausible solutions to deformation and morphological estimation problems. Popular diffeomorphic image registration algorithms include those characterized by time-varying and constant velocity fields, and symmetrical considerations. Prior information in the form of regularization is used to enforce transform plausibility taking the form of physics-based constraints or through some approximation thereof, e.g., Gaussian smoothing of the vector fields [a la Thirion's Demons (Thirion, 1998)]. In the context of the original Demons' framework, the so-called directly manipulated free-form deformation (DMFFD) (Tustison et al., 2009) can be viewed as a smoothing alternative in which explicit regularization is achieved through fast B-spline approximation. This characterization can be used to provide B-spline "flavored" diffeomorphic image registration solutions with several advantages. Implementation is open source and available through the Insight Toolkit and our Advanced Normalization Tools (ANTs) repository. A thorough comparative evaluation with the well-known SyN algorithm (Avants et al., 2008), implemented within the same framework, and its B-spline analog is performed using open labeled brain data and open source evaluation tools. {\textcopyright} 2013 Tustison and Avants.},
author = {Tustison, N.J. and Avants, B.B.},
doi = {10.3389/fninf.2013.00039},
issn = {16625196},
journal = {Frontiers in Neuroinformatics},
keywords = {Advanced normalization tools,Diffeomorphisms,Directly manipulated free-form deformation,Insight toolkit,Spatial normalization},
number = {DEC},
title = {{Explicit B-spline regularization in diffeomorphic image registration}},
volume = {7},
year = {2013}
}
@article{Tustison:2011ab,
abstract = {The effects of certain lung pathologies include alterations in lung physiology negatively affecting pulmonary compliance. Current approaches to diagnosis and treatment assessment of lung disease commonly rely on pulmonary function testing. Such testing is limited to global measures of lung function, neglecting regional measurements, which are critical for early diagnosis and localization of disease. Increased accessibility to medical image acquisition strategies with high spatiotemporal resolution coupled with the development of sophisticated intensity-based and geometric registration techniques has resulted in the recent exploration of modeling pulmonary motion for calculating local measures of deformation. In this review, the authors provide a broad overview of such research efforts for the estimation of pulmonary deformation. This includes discussion of various techniques, current trends in validation approaches, and the public availability of software and data resources.},
author = {Tustison, Nicholas J and Cook, Tessa S and Song, Gang and Gee, James C},
doi = {10.1016/j.acra.2010.10.019},
journal = {Acad Radiol},
month = {apr},
number = {4},
pages = {402--417},
pmid = {21377592},
title = {{Pulmonary kinematics from image data: a review}},
volume = {18},
year = {2011}
}
@article{Pustina2016,
abstract = {{\textcopyright} 2016 Wiley Periodicals, Inc. The gold standard for identifying stroke lesions is manual tracing, a method that is known to be observer dependent and time consuming, thus impractical for big data studies. We propose LINDA (Lesion Identification with Neighborhood Data Analysis), an automated segmentation algorithm capable of learning the relationship between existing manual segmentations and a single T1-weighted MRI. A dataset of 60 left hemispheric chronic stroke patients is used to build the method and test it with k-fold and leave-one-out procedures. With respect to manual tracings, predicted lesion maps showed a mean dice overlap of 0.696±0.16, Hausdorff distance of 17.9±9.8 mm, and average displacement of 2.54±1.38 mm. The manual and predicted lesion volumes correlated at r=0.961. An additional dataset of 45 patients was utilized to test LINDA with independent data, achieving high accuracy rates and confirming its cross-institutional applicability. To investigate the cost of moving from manual tracings to automated segmentation, we performed comparative lesion-to-symptom mapping (LSM) on five behavioral scores. Predicted and manual lesions produced similar neuro-cognitive maps, albeit with some discussed discrepancies. Of note, region-wise LSM was more robust to the prediction error than voxel-wise LSM. Our results show that, while several limitations exist, our current results compete with or exceed the state-of-the-art, producing consistent predictions, very low failure rates, and transferable knowledge between labs. This work also establishes a new viewpoint on evaluating automated methods not only with segmentation accuracy but also with brain-behavior relationships. LINDA is made available online with trained models from over 100 patients.},
author = {Pustina, D. and Coslett, H.B. and Turkeltaub, P.E. and Tustison, N. and Schwartz, M.F. and Avants, B.},
doi = {10.1002/hbm.23110},
issn = {10970193},
journal = {Human Brain Mapping},
keywords = {Automatic,Hierarchical,Machine learning,Random forests,Subacute,VLSM},
number = {4},
title = {{Automated segmentation of chronic stroke lesions using LINDA: Lesion identification with neighborhood data analysis}},
volume = {37},
year = {2016}
}
@inproceedings{Dhillon2013,
abstract = {Traditionally clinicians and medical researchers have been using either totally data driven approaches like PCA/CCA/ICA or ROI based analysis for exploratory analysis of brain images. However, PCA/CCA/ICA based approaches suffer from lack of interpretability of results and on the other hand ROI based approaches are too rigid and wrongly assume that the signal lies totally within a predefined region. In this paper, we propose a novel approach which stands in stark contrast with both these approaches as it borrows strength from both these paradigms and leads to statistically refined definitions of ROIs based on information from data. Our approach, called Anatomically Constrained PCA (AC-PCA) provides a principled way of incorporating prior information in the form of probabilistic or binary ROIs while still allowing the data to softly modify the original ROI definitions. Experimental results on cortical thickness images show the superiority of AC-PCA for MCI classification compared to ROI and unconstrained PCA (a totally data based approach). {\textcopyright} 2013 IEEE.},
author = {Dhillon, P.S. and Gee, J.C. and Ungar, L. and Avants, B.},
booktitle = {Proceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013},
doi = {10.1109/PRNI.2013.16},
isbn = {9780769550619},
keywords = {PCA,Prior,ROI},
title = {{Anatomically-constrained PCA for image parcellation}},
year = {2013}
}
@misc{ANTsR,
author = {PICSL},
title = {{ANTsR: ANTs with R}},
url = {https://github.com/stnava/ANTsR},
year = {2014}
}
@article{Purcell2007,
abstract = {Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.},
archivePrefix = {arXiv},
arxivId = {arXiv:1011.1669v3},
author = {Purcell, Shaun and Neale, Benjamin and Todd-Brown, Kathe and Thomas, Lori and Ferreira, Manuel A.R. and Bender, David and Maller, Julian and Sklar, Pamela and de Bakker, Paul I.W. and Daly, Mark J. and Sham, Pak C.},
doi = {10.1086/519795},
eprint = {arXiv:1011.1669v3},
isbn = {00029297},
issn = {00029297},
journal = {The American Journal of Human Genetics},
pmid = {17701901},
title = {{PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses}},
year = {2007}
}
@book{Avants2006a,
abstract = {One of the most challenging problems in modern neuroimaging is detailed characterization of neurodegeneration. Quantifying spatial and longitudinal atrophy patterns is an important component of this process. These spatiotemporal signals will aid in discriminating between related diseases, such as frontotemporal dementia (FTD) and Alzheimer's disease (AD), which manifest themselves in the same at-risk population. We evaluate a novel symmetric diffeomorphic image registration method for automatically providing detailed anatomical measurement over the aged and neurodegenerative brain. Our evaluation will compare gold standard, human segmentation with our method's atlas-based segmentation of the cerebral cortex, cerebellum and the frontal lobe. The new method compares favorably to an open-source, previously evaluated implementation of Thirion's Demons algorithm. {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.},
author = {Avants, B.B. and Grossman, M. and Gee, J.C.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/11784012_7},
isbn = {3540356487},
issn = {16113349},
title = {{Symmetric diffeomorphic image registration: Evaluating automated labeling of elderly and neurodegenerative cortex and frontal lobe}},
volume = {4057 LNCS},
year = {2006}
}
@article{Hanson2010,
abstract = {Individuals who experience early adversity, such as child maltreatment, are at heightened risk for a broad array of social and health difficulties. However, little is known abou t how this behavioral risk is instantiated in the brain. Here we examine a neurobiological contribution to individual differences in human behavior using methodology appropriate for use with pediatric populations paired with an in-depth measure of social behavior.Weshow that alterations in the orbitofrontal cortex among individuals who experienced physical abuse are related to social difficulties. These data suggest a biological mechanism linking early social learning to later behavioral outcomes. Copyright {\textcopyright} 2010 the authors.},
author = {Hanson, J.L. and Chung, M.K. and Avants, B.B. and Shirtcliff, E.A. and Gee, J.C. and Davidson, R.J. and Pollak, S.D.},
doi = {10.1523/JNEUROSCI.0859-10.2010},
issn = {02706474},
journal = {Journal of Neuroscience},
number = {22},
title = {{Early stress is associated with alterations in the orbitofrontal cortex: A tensor-based morphometry investigation of brain structure and behavioral risk}},
volume = {30},
year = {2010}
}
@article{Lawson2013,
abstract = {Childhood socioeconomic status (SES) predicts executive function performance and measures of prefrontal cortical function, but little is known about its anatomical correlates. Structural MRI and demographic data from a sample of 283 healthy children from the NIH MRI Study of Normal Brain Development were used to investigate the relationship between SES and prefrontal cortical thickness. Specifically, we assessed the association between two principal measures of childhood SES, family income and parental education, and gray matter thickness in specific subregions of prefrontal cortex and on the asymmetry of these areas. After correcting for multiple comparisons and controlling for potentially confounding variables, parental education significantly predicted cortical thickness in the right anterior cingulate gyrus and left superior frontal gyrus. These results suggest that brain structure in frontal regions may provide a meaningful link between SES and cognitive function among healthy, typically developing children. {\textcopyright} 2013 John Wiley  {\&}  Sons Ltd.},
author = {Lawson, G.M. and Duda, J.T. and Avants, B.B. and Wu, J. and Farah, M.J.},
doi = {10.1111/desc.12096},
issn = {1363755X},
journal = {Developmental Science},
number = {5},
title = {{Associations between children's socioeconomic status and prefrontal cortical thickness}},
volume = {16},
year = {2013}
}
@article{Pustina2015,
abstract = {{\textcopyright} 2015 The Authors. Published by Elsevier Inc. Pre-surgical evaluation of patients with temporal lobe epilepsy (TLE) relies on information obtained from multiple neuroimaging modalities. The relationship between modalities and their combined power in predicting the seizure focus is currently unknown. We investigated asymmetries from three different modalities, PET (glucose metabolism), MRI (cortical thickness), and diffusion tensor imaging (DTI; white matter anisotropy) in 28 left and 30 right TLE patients (LTLE and RTLE). Stepwise logistic regression models were built from each modality separately and from all three combined, while bootstrapped methods and split-sample validation verified the robustness of predictions. Among all multimodal asymmetries, three PET asymmetries formed the best predictive model (100{\%} success in full sample,  {\textgreater} 95{\%} success in split-sample validation). The combinations of PET with other modalities did not perform better than PET alone. Probabilistic classifications were obtained for new clinical cases, which showed correct lateralization for 7/7 new TLE patients (100{\%}) and for 4/5 operated patients with discordant or non-informative PET reports (80{\%}). Metabolism showed closer relationship with white matter in LTLE and closer relationship with gray matter in RTLE. Our data suggest that metabolism is a powerful modality that can predict seizure laterality with high accuracy, and offers high value for automated predictive models. The side of epileptogenic focus can affect the relationship of metabolism with brain structure. The data and tools necessary to obtain classifications for new TLE patients are made publicly available.},
author = {Pustina, D. and Avants, B. and Sperling, M. and Gorniak, R. and He, X. and Doucet, G. and Barnett, P. and Mintzer, S. and Sharan, A. and Tracy, J.},
doi = {10.1016/j.nicl.2015.07.010},
issn = {22131582},
journal = {NeuroImage: Clinical},
keywords = {Asymmetry,Classification,Machine learning,Metabolism,Resection},
title = {{Predicting the laterality of temporal lobe epilepsy from PET, MRI, and DTI: A multimodal study: Predicting temporal lobe epilepsy laterality}},
volume = {9},
year = {2015}
}
@book{Dubb2002,
abstract = {{\textcopyright} Springer-Verlag Berlin Heidelberg 2002. The presence of morphologic differences in the corpus callosum in people with schizophrenia has been the subject of intense investigation for a number of years. Researchers, however, have been unable to produce consistent results through comparison of total and partitioned areas. As an alternative to these indices, we use template deformations to find regional size variations in a population of 100 patients.We generated a set of Jacobian determinant maps using k-cluster segmentation followed by a curve registration algorithm. We performed several comparisons including control versus schizophrenia, control versus schizophrenia within gender and age-related effects of control versus schizophrenia. Statistical plots revealed a substantial area of contraction in the anterior callosum associated with schizophrenia. Gender stratification showed a large contribution of this effect was from females. In addition, patients failed to demonstrate an age-related expansion of the splenium that was present among controls. Our results show that template deformation morphometry can be used to show morphologic differences in the callosa of people with schizophrenia.},
author = {Dubb, A. and Avants, B. and Gur, R. and Gee, J.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
isbn = {3540442251},
issn = {16113349},
title = {{Shape characterization of the corpus callosum in schizophrenia using template deformation}},
volume = {2489},
year = {2002}
}
@article{Avants2007,
abstract = {We assess the effects of in utero cocaine and polysubstance exposure on the adolescent caudate nucleus through high-resolution magnetic resonance imaging. Cocaine exposure may compromise the developing brain through disruption of neural ontogeny in dopaminergic systems, effects secondary to fetal hypoxemia, or altered cerebrovascular reactivity. Cocaine exposure may also lead to neonatal lesions in the caudate. However, long-term or latent effects of intrauterine cocaine exposure are rarely found. We use T 1 -weighted magnetic resonance imaging to quantify caudate nucleus morphology in matched control and exposed groups. The literature suggests that in utero cocaine exposure consequences in adolescents may be subtle, or masked by other variables. Our comparison focuses on contrasting the control group with high-exposure subjects (mothers who reported 2 median of 117 days of cocaine use during pregnancy; 82{\%} tested positive for cocaine use at term). We use advanced image registration and segmentation tools to quantify left and right caudate morphology. Our results indicate that the caudate is significantly larger in controls versus subjects (P  {\textless}  0.0025), implying cocaine exposure-related detriments to the dopaminergic system. The right (P  {\textless}  0.025) and left (P  {\textless}  0.035) caudate, studied independently, show the same significant trend. Permutation testing and the false discovery rate were used to assess significance. {\textcopyright} 2007 Elsevier Inc. All rights reserved.},
author = {Avants, B.B. and Hurt, H. and Giannetta, J.M. and Epstein, C.L. and Shera, D.M. and Rao, H. and Wang, J. and Gee, J.C.},
doi = {10.1016/j.pediatrneurol.2007.06.012},
issn = {08878994},
journal = {Pediatric Neurology},
number = {4},
title = {{Effects of Heavy In Utero Cocaine Exposure on Adolescent Caudate Morphology}},
volume = {37},
year = {2007}
}
@inproceedings{Avants2006,
abstract = {Cocaine exposure (CE) may compromise the developing brain through disruption of neural ontogeny in dopaminergic systems, effects secondary to fetal hypoxemia, and, perhaps, via altered cerebrovascular reactivity. Although studies in adult cocaine addicts show decreases in gray matter, white matter, and functional connectivity, there are few investigations to date regarding intra-uterine cocaine exposure (IUCE) in young subjects. The existing literature suggests that long term CE consequences in adolescents may be subtle or masked by other variables. Therefore, sensitive methods of analysis are needed. Here, we describe our most recent methods for deriving an optimal pediatric atlas from the 49 subject IUCE population involved in this study. Our method, symmetric normalization (SyN), is entirely symmetric, in that both the pair wise registration and group wise registration methods do not depend on the ordering of the input data. The method eliminates atlas selection by deriving an optimal shape and intensity atlas from the data. Preliminary results using SyN indicate significant size differences in caudate nuclei and the splenium of the corpus callosum, suggesting CE-related detriment to the dopaminergic and visual systems. Furthermore, we have found that, in comparison, statistical parametric mapping (SPM) does not produce significant results. {\textcopyright} 2006 IEEE.},
author = {Avants, B.B. and Hurt, H. and Giannetta, J. and Epstein, C.L. and Shera, D. and Rao, H. and Wang, J. and Gee, J.C.},
booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
doi = {10.1109/CVPRW.2006.30},
isbn = {0769526462},
issn = {10636919},
title = {{Analyzing effects of intra-uterine cocaine exposure on adolescent brain structure with symmetric diffeomorphisms}},
volume = {2006},
year = {2006}
}
@book{Sundaram2005a,
abstract = {We approach the problem of temporal reparameterization of dynamic sequences of lung MR images. In earlier work, we employed capacity-based reparameterization to co-register temporal sequences of 2-D coronal images of the human lungs. Here, we extend that work to the evaluation of a ventilator-acquired 3-D dataset from a normal mouse. Reparameterization according to both deformation and lung volume is evaluated. Both measures provide results that closely approximate normal physiological behavior, as judged from the original data. Our ultimate goal is to be able to characterize normal parenchymal biomechanics over a population of healthy individuals, and to use this statistical model to evaluate lung deformation under various pathological states. {\textcopyright} Springer-Verlag Berlin Heidelberg 2005.},
author = {Sundaram, T.A. and Avants, B.B. and Gee, J.C.},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/11566489_41},
isbn = {3540293264},
issn = {03029743},
title = {{Towards a dynamic model of pulmonary parenchymal deformation: Evaluation of methods for temporal reparameterization of lung data}},
volume = {3750 LNCS},
year = {2005}
}

license_type: permissive

branch_name: refs/heads/master

extension: bib


text:
inherit externalsrc

SUMMARY = "Mellanox BlueField Boot Control tool"
HOMEPAGE = ""

LICENSE = "GPLv2+"
LIC_FILES_CHKSUM = "file://mlxbf-bootctl.c;beginline=1;endline=29;md5=b7861d57cc6f43fb2a002a17241b5160"
DEPENDS = ""

PV = "1.0"
PR = "r1"

SRC_URI = "file://mlxbf-bootctl-1.0.tar.xz"

do_compile() {
        oe_runmake -f ${S}/Makefile
}

do_install () {
        oe_runmake -f ${S}/Makefile install DESTDIR=${D} SBINDIR=${base_sbindir}
}

license: MIT

repository: Mellanox/meta-bluefield

repo_name: Mellanox/meta-bluefield

extension: bb


text:
@inproceedings{johal2015robots,
 author = {Johal, Wafa},
 booktitle = {Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts},
 organization = {ACM},
 pages = {191--192},
 title = {Robots Interacting with Style},
 year = {2015}
}

repository: estella-a/research-group-website-src

repo_name: estella-a/research-group-website-src

branch_name: refs/heads/main


text:
package funString

import (
	"testing"
	. "github.com/smartystreets/goconvey/convey"
	"github.com/yioio/fun/funString"
)

func Test_Rtrim(t *testing.T) {

	Convey("删除字符串末端的空白字符（或者其他字符）", t, func() {

		So(funString.Rtrim("abc "), ShouldEqual, "abc")
		So(funString.Rtrim("abc&", "&"), ShouldEqual, "abc")
	})
}

repository: yioio/fun

repo_name: yioio/fun

gha_license_id: MIT

gha_language: Go

extension: go


text:
PV = "0.0+cvs${SRCDATE}"
PR = "r1"
LICENSE= "MIT"
DESCRIPTION = "X Server Extension library"
SECTION = "x11/libs"
PRIORITY = "optional"
DEPENDS = "xproto x11 xextensions"

SRC_URI = "cvs://anoncvs:anoncvs@pdx.freedesktop.org/cvs/xlibs;module=Xext"
S = "${WORKDIR}/Xext"

inherit autotools pkgconfig
do_stage() {
	autotools_stage_all
}

repository: BackupTheBerlios/openslug-svn

repo_name: BackupTheBerlios/openslug-svn


text:
DESCRIPTION = "library to provide userspace access to USB devices"
HOMEPAGE = "http://libusb.sf.net"
SECTION = "libs"
LICENSE = "LGPLv2.1"

PR = "r1"

SRC_URI = " \
           ${SOURCEFORGE_MIRROR}/libusb/libusb-${PV}.tar.bz2 \
           file://libusb-shortok.patch \
          "
S = "${WORKDIR}/libusb-${PV}"

inherit autotools

EXTRA_OECONF = "--disable-build-docs"

SRC_URI[md5sum] = "a1f2206f1b4bd800e2461157faaa887f"
SRC_URI[sha256sum] = "6de182e93c946d432ed04362f0b93d889072438448dad20a21d4fcfa34cffa1d"

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD


text:
@inproceedings{simonnet-2018-SLUErrF,
TITLE = {{Simulation d'erreurs de reconnaissance automatique dans un cadre de compr{\'e}hension de la parole}},
AUTHOR = {Simonnet, Edwin and Ghannay, Sahar and Camelin, Nathalie and Est{\`e}ve, Yannick},
URL = {https://hal.archives-ouvertes.fr/hal-01757770},
BOOKTITLE = {{XXXIIe Journ{\'e}es d'Etudes sur la Parole (JEP 2018)}},
ADDRESS = {Aix-en-Provence, France},
YEAR = {2018},
MONTH = Jun,
HAL_ID = {hal-01757770},
HAL_VERSION = {v1},
}

repository: saharghannay/academic-kickstart

repo_name: saharghannay/academic-kickstart


text:
RDEPENDS = "enigma2"

PR = "r0"

SRC_URI = "file://skin_user.xml \
	file://vfd_icons \
"

do_install() {
	install -d ${D}/usr/share/enigma2/defaults/
	install -m 0644 ${WORKDIR}/skin_user.xml ${D}/usr/share/enigma2/defaults/
        install -d ${D}/usr/share/enigma2/vfd_icons/
        install -m 0644 ${WORKDIR}/vfd_icons/*.png ${D}/usr/share/enigma2/vfd_icons/
}

FILES_${PN} = "/usr/share/enigma2/defaults"
FILES_${PN} += "/usr/share/enigma2/vfd_icons"

PACKAGE_ARCH = "${MACHINE_ARCH}"

gha_language: C


text:
require openssl.inc

PR = "r6"

SRC_URI += "file://debian.patch;patch=1 \
            file://armeb.patch;patch=1 \
            file://gnueabi-arm.patch;patch=1"