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@STRING{ams = {American Mathematical Society}}

@STRING{ap = {Academic Press}}

@STRING{cgip = {Computer Graphics and Image Processing}}

@STRING{cs-unc = {Department of Computer Science, University of North Carolina at Chapel
	Hill}}

@STRING{cvgip = {Computer Vision, Graphics, and Image Processing}}

@STRING{cvgip-iu = {Computer Vision, Graphics, and Image Processing: Image Understanding}}

@STRING{ieeetranscom = {{IEEE} Transactions on Communications}}

@STRING{josa = {Journal of the Optical Society of {A}merica}}

@STRING{josa-a = {Journal of the Optical Society of {A}merica {A}}}

@STRING{lea = {Lawrence Erlbaum Associates}}

@STRING{lea-addr = {Hillsdale, New Jersey}}

@STRING{mit = {The MIT Press}}

@STRING{mit-addr = {Cambridge, MA}}

@STRING{pami = {{IEEE} Transactions on Pattern Analysis and Machine Intelligence}}

@STRING{ph = {Prentice Hall}}

@STRING{prletters = {Pattern Recognition Letters}}

@STRING{procnas = {Proc. Natl. Acad. Sci. USA}}

@STRING{psychrev = {Psychological Review}}

@STRING{sciam = {Scientific American}}

@STRING{spatialvis = {Spatial Vision}}

@STRING{springer = {Springer-Verlag}}

@STRING{tins = {Trends in Neuroscience ({TINS})}}

@STRING{unc-ch = {University of North Carolina at Chapel Hill}}

@STRING{vr = {Vision Research}}

@INPROCEEDINGS{Bauer2011c,
  author = {Bauer, Stefan and Nolte, Lutz-Peter and Reyes, Mauricio},
  title = {{Skull-stripping for Tumor-bearing Brain Images}},
  booktitle = {Annual Meeting of the Swiss Society for Biomedical Engineering},
  year = {2011},
  editor = {B\"{u}chler, Philippe and Ferguson, Stephen},
  pages = {2},
  address = {Bern},
  month = apr,
  publisher = {SSBE},
  note = {arXiv:1204.0357},
  abstract = {Skull-stripping separates the skull region of the head from the soft
	brain tissues. In many cases of brain image analysis, this is an
	essential preprocessing step in order to improve the final result.
	This is true for both registration and segmentation tasks. In fact,
	skull-stripping of magnetic resonance images (MRI) is a well-studied
	problem with numerous publications in recent years. Many different
	algorithms have been proposed, a summary and comparison of which
	can be found in [Fennema-Notestine, 2006]. Despite the abundance
	of approaches, we discovered that the algorithms which had been suggested
	so far, perform poorly when dealing with tumor-bearing brain images.
	This is mostly due to additional difficulties in separating the brain
	from the skull in this case, especially when the lesion is located
	very close to the skull border. Additionally, images acquired according
	to standard clinical protocols, often exhibit anisotropic resolution
	and only partial coverage, which further complicates the task. Therefore,
	we developed a method which is dedicated to skull-stripping for clinically
	acquired tumor-bearing brain images.},
  archiveprefix = {arXiv},
  arxivid = {1204.0357},
  eprint = {1204.0357},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Publications/conferences/SSBE2011/skullStripping/bauer-reyes-SSBE2011.pdf:pdf},
  keywords = {Brain tumor,MRI,Segmentation,Skull-stripping},
  owner = {Stefan},
  timestamp = {2012.04.18},
  url = {https://www.istb.unibe.ch/content/ssbe\_2011/ https://arxiv.org/abs/1204.0357}
}

@ARTICLE{Carass2011,
  author = {Carass, Aaron and Cuzzocreo, Jennifer and Wheeler, M Bryan and Bazin,
	Pierre-Louis and Resnick, Susan M and Prince, Jerry L},
  title = {{Simple paradigm for extra-cerebral tissue removal: Algorithm and
	analysis.}},
  journal = {NeuroImage},
  year = {2011},
  volume = {56},
  pages = {1982--1992},
  number = {4},
  month = mar,
  abstract = {Extraction of the brain-i.e. cerebrum, cerebellum, and brain stem-from
	T1-weighted structural magnetic resonance images is an important
	initial step in neuroimage analysis. Although automatic algorithms
	are available, their inconsistent handling of the cortical mantle
	often requires manual interaction, thereby reducing their effectiveness.
	This paper presents a fully automated brain extraction algorithm
	that incorporates elastic registration, tissue segmentation, and
	morphological techniques which are combined by a watershed principle,
	while paying special attention to the preservation of the boundary
	between the gray matter and the cerebrospinal fluid. The approach
	was evaluated by comparison to a manual rater, and compared to several
	other leading algorithms on a publically available data set of brain
	images using the Dice coefficient and containment index as performance
	metrics. The qualitative and quantitative impact of this initial
	step on subsequent cortical surface generation is also presented.
	Our experiments demonstrate that our approach is quantitatively better
	than six other leading algorithms (with statistical significance
	on modern T1-weighted MR data). We also validated the robustness
	of the algorithm on a very large data set of over one thousand subjects,
	and showed that it can replace an experienced manual rater as preprocessing
	for a cortical surface extraction algorithm with statistically insignificant
	differences in cortical surface position.},
  doi = {10.1016/j.neuroimage.2011.03.045},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/brain\_segmentation/carass2011.pdf:pdf},
  issn = {1095-9572},
  keywords = {Brain extraction,Medical image processing,Segmentation,Skull stripping,Watershed
	principle},
  owner = {Stefan},
  pmid = {21458576},
  publisher = {Elsevier Inc.},
  timestamp = {2012.04.18},
  url = {https://www.ncbi.nlm.nih.gov/pubmed/21458576}
}

@ARTICLE{Cocosco1997,
  author = {Cocosco, C.A. and Kollokian, V. and Kwan, R.S. and Evans, A.C.},
  title = {{BrainWeb: Online interface to a 3D MRI simulated brain database}},
  journal = {Neuroimage},
  year = {1997},
  volume = {5},
  number = {4},
  owner = {Stefan},
  timestamp = {2012.04.19}
}

@ARTICLE{Eskildsen2011,
  author = {Eskildsen, Simon F and Coup\'{e}, Pierrick and Fonov, Vladimir and
	Manj\'{o}n, Jos\'{e} V and Leung, Kelvin K and Guizard, Nicolas and
	Wassef, Shafik N and Ostergaard, Lasse Riis and Collins, D Louis},
  title = {{BEaST: Brain extraction based on nonlocal segmentation technique.}},
  journal = {NeuroImage},
  year = {2011},
  volume = {59},
  pages = {2362--2373},
  number = {3},
  month = sep,
  abstract = {Brain extraction is an important step in the analysis of brain images.
	The variability in brain morphology and the difference in intensity
	characteristics due to imaging sequences make the development of
	a general purpose brain extraction algorithm challenging. To address
	this issue, we propose a new robust method (BEaST) dedicated to produce
	consistent and accurate brain extraction. This method is based on
	nonlocal segmentation embedded in a multi-resolution framework. A
	library of 80 priors is semi-automatically constructed from the NIH-sponsored
	MRI study of normal brain development, the International Consortium
	for Brain Mapping, and the Alzheimer's Disease Neuroimaging Initiative
	databases. In testing, a mean Dice similarity coefficient of 0.9834±0.0053
	was obtained when performing leave-one-out cross validation selecting
	only 20 priors from the library. Validation using the online Segmentation
	Validation Engine resulted in a top ranking position with a mean
	Dice coefficient of 0.9781±0.0047. Robustness of BEaST is demonstrated
	on all baseline ADNI data, resulting in a very low failure rate.
	The segmentation accuracy of the method is better than two widely
	used publicly available methods and recent state-of-the-art hybrid
	approaches. BEaST provides results comparable to a recent label fusion
	approach, while being 40 times faster and requiring a much smaller
	library of priors.},
  doi = {10.1016/j.neuroimage.2011.09.012},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/brain\_segmentation/eskildsen2011.pdf:pdf},
  issn = {1095-9572},
  keywords = {BET,Brain extraction,MRI,Multi-resolution,Patch-based segmentation,Skull
	stripping},
  owner = {Stefan},
  pmid = {21945694},
  publisher = {Elsevier Inc.},
  timestamp = {2012.04.18},
  url = {https://www.ncbi.nlm.nih.gov/pubmed/21945694}
}

@ARTICLE{Fennema-Notestine2006,
  author = {Fennema-Notestine, Christine and Ozyurt, I Burak and Clark, Camellia
	P and Morris, Shaunna and Bischoff-Grethe, Amanda and Bondi, Mark
	W and Jernigan, Terry L and Fischl, Bruce and Segonne, Florent and
	Shattuck, David W and Leahy, Richard M and Rex, David E and Toga,
	Arthur W and Zou, Kelly H and Brown, Gregory G},
  title = {{Quantitative evaluation of automated skull-stripping methods applied
	to contemporary and legacy images: effects of diagnosis, bias correction,
	and slice location.}},
  journal = {Human brain mapping},
  year = {2006},
  volume = {27},
  pages = {99--113},
  number = {2},
  month = feb,
  abstract = {Performance of automated methods to isolate brain from nonbrain tissues
	in magnetic resonance (MR) structural images may be influenced by
	MR signal inhomogeneities, type of MR image set, regional anatomy,
	and age and diagnosis of subjects studied. The present study compared
	the performance of four methods: Brain Extraction Tool (BET; Smith
	[2002]: Hum Brain Mapp 17:143-155); 3dIntracranial (Ward [1999] Milwaukee:
	Biophysics Research Institute, Medical College of Wisconsin; in AFNI);
	a Hybrid Watershed algorithm (HWA, Segonne et al. [2004] Neuroimage
	22:1060-1075; in FreeSurfer); and Brain Surface Extractor (BSE, Sandor
	and Leahy [1997] IEEE Trans Med Imag 16:41-54; Shattuck et al. [2001]
	Neuroimage 13:856-876) to manually stripped images. The methods were
	applied to uncorrected and bias-corrected datasets; Legacy and Contemporary
	T1-weighted image sets; and four diagnostic groups (depressed, Alzheimer's,
	young and elderly control). To provide a criterion for outcome assessment,
	two experts manually stripped six sagittal sections for each dataset
	in locations where brain and nonbrain tissue are difficult to distinguish.
	Methods were compared on Jaccard similarity coefficients, Hausdorff
	distances, and an Expectation-Maximization algorithm. Methods tended
	to perform better on contemporary datasets; bias correction did not
	significantly improve method performance. Mesial sections were most
	difficult for all methods. Although AD image sets were most difficult
	to strip, HWA and BSE were more robust across diagnostic groups compared
	with 3dIntracranial and BET. With respect to specificity, BSE tended
	to perform best across all groups, whereas HWA was more sensitive
	than other methods. The results of this study may direct users towards
	a method appropriate to their T1-weighted datasets and improve the
	efficiency of processing for large, multisite neuroimaging studies.},
  doi = {10.1002/hbm.20161},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/notestine06.pdf:pdf},
  issn = {1065-9471},
  keywords = {Adult,Age Factors,Aged,Algorithms,Brain,Brain Diseases,Brain Diseases:
	radiography,Brain: radiography,Computer-Assisted,Computer-Assisted:
	methods,Humans,Image Processing,Magnetic Resonance Imaging,Middle
	Aged,Sensitivity and Specificity,Software},
  owner = {Stefan},
  pmid = {15986433},
  publisher = {John Wiley \& Sons},
  timestamp = {2012.04.18},
  url = {https://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2408865\&tool=pmcentrez\&rendertype=abstract}
}

@INPROCEEDINGS{Hahn2000,
  author = {Hahn, H. and Peitgen, H.O.},
  title = {{The skull stripping problem in MRI solved by a single 3D watershed
	transform}},
  booktitle = {Medical Image Computing and Computer-Assisted Intervention–MICCAI
	2000},
  year = {2000},
  pages = {129--145},
  publisher = {Springer},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/hahn00.pdf:pdf},
  keywords = {3d watershed transform,neurological image processing,pre-flooding,skull
	stripping,whole brain segmentation},
  owner = {Stefan},
  timestamp = {2012.04.18},
  url = {http://www.springerlink.com/index/DEM79E6JGDKW3CW9.pdf}
}

@ARTICLE{Hartley2006,
  author = {Hartley, SW and Scher, AI and Korf, ESC and White, LR and Launer,
	LJ},
  title = {{Analysis and validation of automated skull stripping tools: a validation
	study based on 296 MR images from the Honolulu Asia aging study}},
  journal = {Neuroimage},
  year = {2006},
  volume = {30},
  pages = {1179--1186},
  number = {4},
  doi = {10.1016/j.neuroimage.2005.10.043},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/hartley06.pdf:pdf},
  issn = {1053-8119},
  owner = {Stefan},
  publisher = {Elsevier},
  timestamp = {2012.04.18},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S1053811905024407}
}

@BOOK{Ibanez2003,
  title = {{The ITK software guide}},
  publisher = {Citeseer},
  year = {2003},
  author = {Ibanez, L. and Schroeder, Will and Ng, L. and Cates, J. and Others},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/manuals/ItkSoftwareGuide-2.4.0.pdf:pdf},
  owner = {Stefan},
  timestamp = {2012.04.18},
  url = {https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.3166}
}

@ARTICLE{Iglesias2011,
  author = {Iglesias, Juan Eugenio and Liu, Cheng-Yi and Thompson, Paul M and
	Tu, Zhuowen},
  title = {{Robust brain extraction across datasets and comparison with publicly
	available methods.}},
  journal = {IEEE transactions on medical imaging},
  year = {2011},
  volume = {30},
  pages = {1617--34},
  number = {9},
  month = sep,
  abstract = {Automatic whole-brain extraction from magnetic resonance images (MRI),
	also known as skull stripping, is a key component in most neuroimage
	pipelines. As the first element in the chain, its robustness is critical
	for the overall performance of the system. Many skull stripping methods
	have been proposed, but the problem is not considered to be completely
	solved yet. Many systems in the literature have good performance
	on certain datasets (mostly the datasets they were trained/tuned
	on), but fail to produce satisfactory results when the acquisition
	conditions or study populations are different. In this paper we introduce
	a robust, learning-based brain extraction system (ROBEX). The method
	combines a discriminative and a generative model to achieve the final
	result. The discriminative model is a Random Forest classifier trained
	to detect the brain boundary; the generative model is a point distribution
	model that ensures that the result is plausible. When a new image
	is presented to the system, the generative model is explored to find
	the contour with highest likelihood according to the discriminative
	model. Because the target shape is in general not perfectly represented
	by the generative model, the contour is refined using graph cuts
	to obtain the final segmentation. Both models were trained using
	92 scans from a proprietary dataset but they achieve a high degree
	of robustness on a variety of other datasets. ROBEX was compared
	with six other popular, publicly available methods (BET, BSE, FreeSurfer,
	AFNI, BridgeBurner, and GCUT) on three publicly available datasets
	(IBSR, LPBA40, and OASIS, 137 scans in total) that include a wide
	range of acquisition hardware and a highly variable population (different
	age groups, healthy/diseased). The results show that ROBEX provides
	significantly improved performance measures for almost every method/dataset
	combination.},
  doi = {10.1109/TMI.2011.2138152},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/iglesias2011.pdf:pdf},
  issn = {1558-0062},
  owner = {Stefan},
  pmid = {21880566},
  timestamp = {2012.04.18},
  url = {https://www.ncbi.nlm.nih.gov/pubmed/21880566}
}

@ARTICLE{Lee2003,
  author = {Lee, J},
  title = {{Evaluation of automated and semi-automated skull-stripping algorithms
	using similarity index and segmentation error}},
  journal = {Computers in Biology and Medicine},
  year = {2003},
  volume = {33},
  pages = {495--507},
  number = {6},
  month = nov,
  doi = {10.1016/S0010-4825(03)00022-2},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/lee03.pdf:pdf},
  issn = {00104825},
  keywords = {false negative rate,false positive rate,inter-rater reliability,similarity
	index,simulated t1-weighted mri,skull-stripping},
  owner = {Stefan},
  timestamp = {2012.04.18},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0010482503000222}
}

@ARTICLE{Segonne2004,
  author = {S\'{e}gonne, F. and Dale, A.M. and Busa, E and Glessner, M and Salat,
	D and Hahn, H.K. and Fischl, B},
  title = {{A hybrid approach to the skull stripping problem in MRI}},
  journal = {Neuroimage},
  year = {2004},
  volume = {22},
  pages = {1060--1075},
  number = {3},
  doi = {10.1016/j.neuroimage.2004.03.032},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/segonne04.pdf:pdf},
  issn = {1053-8119},
  keywords = {atlas-based segmentation,brain segmentation,construction of detailed
	head,data with eeg and,generate spatiotem-,meg sensor information
	to,models that can be,skull stripping,template deformation,used to
	fuse mri,watershed transformation},
  owner = {Stefan},
  publisher = {Elsevier},
  timestamp = {2012.04.18},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S1053811904001880}
}

@ARTICLE{Sadananthan2010,
  author = {Sadananthan, S.A. and Zheng, Weili and Chee, M.W.L. and Zagorodnov,
	Vitali},
  title = {{Skull stripping using graph cuts}},
  journal = {NeuroImage},
  year = {2010},
  volume = {49},
  pages = {225--239},
  number = {1},
  doi = {10.1016/j.neuroimage.2009.08.050},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/sadananthan10.pdf:pdf},
  issn = {1053-8119},
  owner = {Stefan},
  publisher = {Elsevier},
  timestamp = {2012.04.18},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S1053811909009604}
}

@ARTICLE{Sandor1997,
  author = {Sandor, S and Leahy, R},
  title = {{Surface-based labeling of cortical anatomy using a deformable atlas.}},
  journal = {IEEE transactions on medical imaging},
  year = {1997},
  volume = {16},
  pages = {41--54},
  number = {1},
  month = feb,
  abstract = {We describe a computerized method to automatically find and label
	the cortical surface in three-dimensional (3-D) magnetic resonance
	(MR) brain images. The approach we take is to model a prelabeled
	brain atlas as a physical object and give it elastic properties,
	allowing it to warp itself onto regions in a preprocessed image.
	Preprocessing consists of boundary-finding and a morphological procedure
	which automatically extracts the brain and sulci from an MR image
	and provides a smoothed representation of the brain surface to which
	the deformable model can rapidly converge. Our deformable models
	are energy-minimizing elastic surfaces that can accurately locate
	image features. The models are parameterized with 3-D bicubic B-spline
	surfaces. We design the energy function such that cortical fissure
	(sulci) points on the model are attracted to fissure points on the
	image and the remaining model points are attracted to the brain surface.
	A conjugate gradient method minimizes the energy function, allowing
	the model to automatically converge to the smoothed brain surface.
	Finally, labels are propagated from the deformed atlas onto the high-resolution
	brain surface.},
  doi = {10.1109/42.552054},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/brain\_segmentation/sandor1997.pdf:pdf},
  issn = {0278-0062},
  keywords = {Algorithms,Anatomy, Artistic,Brain,Brain: anatomy \& histology,Cerebral
	Cortex,Cerebral Cortex: anatomy \& histology,Computer Simulation,Elasticity,Frontal
	Lobe,Frontal Lobe: anatomy \& histology,Humans,Image Enhancement,Image
	Interpretation, Computer-Assisted,Image Interpretation, Computer-Assisted:
	methods,Image Processing, Computer-Assisted,Image Processing, Computer-Assisted:
	methods,Magnetic Resonance Imaging,Magnetic Resonance Imaging: methods,Male,Medical
	Illustration,Occipital Lobe,Occipital Lobe: anatomy \& histology,Parietal
	Lobe,Parietal Lobe: anatomy \& histology,Software,Temporal Lobe,Temporal
	Lobe: anatomy \& histology},
  owner = {Stefan},
  pmid = {9050407},
  timestamp = {2012.04.18},
  url = {https://www.ncbi.nlm.nih.gov/pubmed/9050407}
}

@ARTICLE{Shattuck2009,
  author = {Shattuck, David W and Prasad, Gautam and Mirza, Mubeena and Narr,
	Katherine L and Toga, Arthur W},
  title = {{Online resource for validation of brain segmentation methods.}},
  journal = {NeuroImage},
  year = {2009},
  volume = {45},
  pages = {431--9},
  number = {2},
  month = apr,
  abstract = {One key issue that must be addressed during the development of image
	segmentation algorithms is the accuracy of the results they produce.
	Algorithm developers require this so they can see where methods need
	to be improved and see how new developments compare with existing
	ones. Users of algorithms also need to understand the characteristics
	of algorithms when they select and apply them to their neuroimaging
	analysis applications. Many metrics have been proposed to characterize
	error and success rates in segmentation, and several datasets have
	also been made public for evaluation. Still, the methodologies used
	in analyzing and reporting these results vary from study to study,
	so even when studies use the same metrics their numerical results
	may not necessarily be directly comparable. To address this problem,
	we developed a web-based resource for evaluating the performance
	of skull-stripping in T1-weighted MRI. The resource provides both
	the data to be segmented and an online application that performs
	a validation study on the data. Users may download the test dataset,
	segment it using whichever method they wish to assess, and upload
	their segmentation results to the server. The server computes a series
	of metrics, displays a detailed report of the validation results,
	and archives these for future browsing and analysis. We applied this
	framework to the evaluation of 3 popular skull-stripping algorithms--the
	Brain Extraction Tool [Smith, S.M., 2002. Fast robust automated brain
	extraction. Hum. Brain Mapp. 17 (3),143-155 (Nov)], the Hybrid Watershed
	Algorithm [S\'{e}gonne, F., Dale, A.M., Busa, E., Glessner, M., Salat,
	D., Hahn, H.K., Fischl, B., 2004. A hybrid approach to the skull
	stripping problem in MRI. NeuroImage 22 (3), 1060-1075 (Jul)], and
	the Brain Surface Extractor [Shattuck, D.W., Sandor-Leahy, S.R.,
	Schaper, K.A., Rottenberg, D.A., Leahy, R.M., 2001. Magnetic resonance
	image tissue classification using a partial volume model. NeuroImage
	13 (5), 856-876 (May) under several different program settings. Our
	results show that with proper parameter selection, all 3 algorithms
	can achieve satisfactory skull-stripping on the test data.},
  doi = {10.1016/j.neuroimage.2008.10.066},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/brain\_segmentation/shattuck08.pdf:pdf},
  issn = {1095-9572},
  keywords = {Adult,Algorithms,Computer Simulation,Database Management Systems,Databases,
	Factual,Female,Humans,Image Enhancement,Image Enhancement: methods,Image
	Interpretation, Computer-Assisted,Image Interpretation, Computer-Assisted:
	methods,Information Dissemination,Information Dissemination: methods,Internet,Magnetic
	Resonance Imaging,Magnetic Resonance Imaging: methods,Male,Models,
	Anatomic,Pattern Recognition, Automated,Pattern Recognition, Automated:
	methods,Reproducibility of Results,Sensitivity and Specificity},
  owner = {Stefan},
  pmid = {19073267},
  publisher = {Elsevier Inc.},
  timestamp = {2012.04.18},
  url = {https://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2757629\&tool=pmcentrez\&rendertype=abstract}
}

@INPROCEEDINGS{Shi2011,
  author = {Shi, Feng and Wang, Li and Gilmore, J and Lin, Weili and Shen, Dinggang},
  title = {{Learning-Based Meta-Algorithm for MRI Brain Extraction}},
  booktitle = {MICCAI - Medical Image Computing and Computer Assisted Interventions},
  year = {2011},
  editor = {Fichtinger, Gabor and Martel, Anne and Peters, Terry},
  pages = {313--321},
  address = {Toronto},
  doi = {10.1007/978-3-642-23626-6\_39},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/shi2011.pdf:pdf},
  owner = {Stefan},
  timestamp = {2012.04.18},
  url = {http://www.springerlink.com/index/5U91163835492036.pdf}
}

@ARTICLE{Smith2002a,
  author = {Smith, Stephen M},
  title = {{Fast robust automated brain extraction.}},
  journal = {Human brain mapping},
  year = {2002a},
  volume = {17},
  pages = {143--55},
  number = {3},
  month = nov,
  abstract = {An automated method for segmenting magnetic resonance head images
	into brain and non-brain has been developed. It is very robust and
	accurate and has been tested on thousands of data sets from a wide
	variety of scanners and taken with a wide variety of MR sequences.
	The method, Brain Extraction Tool (BET), uses a deformable model
	that evolves to fit the brain's surface by the application of a set
	of locally adaptive model forces. The method is very fast and requires
	no preregistration or other pre-processing before being applied.
	We describe the new method and give examples of results and the results
	of extensive quantitative testing against "gold-standard" hand segmentations,
	and two other popular automated methods.},
  doi = {10.1002/hbm.10062},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/brain\_segmentation/smith2002.pdf:pdf},
  issn = {1065-9471},
  keywords = {Algorithms,Animals,Brain,Brain: anatomy \& histology,Brain: physiology,Humans,Magnetic
	Resonance Imaging,Magnetic Resonance Imaging: instrumentation,Magnetic
	Resonance Imaging: methods},
  owner = {Stefan},
  pmid = {12391568},
  timestamp = {2012.04.18},
  url = {https://www.ncbi.nlm.nih.gov/pubmed/12391568}
}

@INPROCEEDINGS{Speier2011,
  author = {Speier, William and Iglesias, J and El-Kara, L and Tu, Zhuowen and
	Arnold, Corey},
  title = {{Robust Skull Stripping of Clinical Glioblastoma Multiforme Data}},
  booktitle = {MICCAI - Medical Image Computing and Computer Assisted Interventions},
  year = {2011},
  editor = {Fichtinger, Gabor and Martel, Anne and Peters},
  pages = {659--666},
  address = {Toronto},
  publisher = {Springer LNCS},
  doi = {10.1007/978-3-642-23626-6\_81},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/speier2011.pdf:pdf},
  owner = {Stefan},
  timestamp = {2012.04.18},
  url = {http://www.springerlink.com/index/UL3V89802631X4P1.pdf}
}

@ARTICLE{Tsai2003,
  author = {Tsai, Richard and Osher, Stanley},
  title = {{Level Set Methods and their Applications in Image Science}},
  journal = {Communications in Mathematical Sciences},
  year = {2003},
  volume = {1},
  pages = {623--656},
  number = {4},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/segmentation/tsai2003.pdf:pdf},
  owner = {Stefan},
  timestamp = {2012.04.24},
  url = {https://projecteuclid.org/euclid.cms/1119655349}
}

@INPROCEEDINGS{Wang2011,
  author = {Wang, Yaping and Nie, Jingxin and Yap, PT and Shi, Feng and Guo,
	Lei and Shen, Dinggang},
  title = {{Robust Deformable-Surface-Based Skull-Stripping for Large-Scale
	Studies}},
  booktitle = {MICCAI - Medical Image Computing and Computer Assisted Interventions},
  year = {2011},
  editor = {Fichtinger, Gabor and Martel, Anne and Peters},
  pages = {635--642},
  address = {Toronto},
  publisher = {Springer LNCS},
  doi = {10.1007/978-3-642-23626-6\_78},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/wang2011.pdf:pdf},
  owner = {Stefan},
  timestamp = {2012.04.18},
  url = {http://www.springerlink.com/index/R772156766733370.pdf}
}

@ARTICLE{Zhuang2006,
  author = {Zhuang, A.H. and Valentino, D.J. and Toga, A.W.},
  title = {{Skull-stripping magnetic resonance brain images using a model-based
	level set}},
  journal = {NeuroImage},
  year = {2006},
  volume = {32},
  pages = {79--92},
  number = {1},
  doi = {10.1016/j.neuroimage.2006.03.019},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/skullStripping/zhuang06.pdf:pdf},
  issn = {1053-8119},
  owner = {Stefan},
  publisher = {Elsevier},
  timestamp = {2012.04.18},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S1053811906002126}
}

@ARTICLE{Zitova2003,
  author = {Zitova, Barbara and Flusser, Jan},
  title = {{Image registration methods: a survey}},
  journal = {Image and Vision Computing},
  year = {2003},
  volume = {21},
  pages = {977--1000},
  number = {11},
  month = oct,
  doi = {10.1016/S0262-8856(03)00137-9},
  file = {:C$\backslash$:/Documents and Settings/Stefan/My Documents/Files/Literature/registration/zitova03.pdf:pdf},
  issn = {02628856},
  keywords = {feature detection,feature matching,image registration,mapping function,resampling},
  owner = {Stefan},
  timestamp = {2012.04.24},
  url = {https://linkinghub.elsevier.com/retrieve/pii/S0262885603001379}
}

repository: InsightSoftwareConsortium/ITKSkullStrip

repo_name: InsightSoftwareConsortium/ITKSkullStrip


text:
@article{HierarchicalStochasticSimulation_watanabe_2014,
 abstract = {This paper describes a hierarchical stochastic simulation algorithm which has been implemented within iBioSim, a tool used to model, analyze, and visualize genetic circuits. Many biological analysis tools flatten out hierarchy before simulation, but there are many disadvantages associated with this approach. First, the memory required to represent the model can quickly expand in the process. Second, the flattening process is computationally expensive. Finally, when modeling a dynamic cellular population within iBioSim, inlining the hierarchy of the model is inefficient since models must grow dynamically over time. This paper discusses a new approach to handle hierarchy on the fly to make the tool faster and more memory-efficient. This approach yields significant performance improvements as compared to the former flat analysis method.},
 annotation = {00000},
 author = {Watanabe, Leandro H. and Myers, Chris J.},
 doi = {10.3389/fbioe.2014.00055},
 issn = {2296-4185},
 journal = {Frontiers in Bioengineering and Biotechnology},
 keywords = {Discrete-event simulation,Genetic circuits,Hierarchical Simulation,population modeling,SBML,Stochastic simulation},
 language = {English},
 title = {Hierarchical Stochastic Simulation Algorithm for SBML Models of Genetic Circuits},
 volume = {2},
 year = {2014}
}

license: MIT

license_type: permissive

branch_name: refs/heads/master

extension: bib


text:
LICENSE = "CLOSED"

SRC_URI = "file://CMakeLists.txt file://main.cpp"

PR = "r0"

S = "${WORKDIR}"

DEPENDS = "dragonet"

inherit cmake

# Specify any options you want to pass to cmake using EXTRA_OECMAKE:
EXTRA_OECMAKE += ""

repository: raphaelchang/meta-dragonflyte

repo_name: raphaelchang/meta-dragonflyte

extension: bb


text:
SUMMARY = "Python UPnP framework"
HOMEPAGE = "http://coherence.beebits.net/"
SECTION = "devel/python"
LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://LICENCE;md5=3f7c147addd67ce1d53239c68a6b7022"
DEPENDS = "libxml2"
SRCREV = "${@opendreambox_srcrev('25169a57519759a916b0f21a13ccb28791fd29a2', d)}"
PV = "0.8.1"
GITHUB_BRANCH = "develop"

inherit setuptools opendreambox-github

do_configure_prepend() {
        sed -e 's,from coherence import __version__$,__version__ = "${RECIPE_PV}",' -i setup.py
}
do_install_append() {
        rm ${D}${bindir}/applet-coherence
        rm -r ${D}${PYTHON_SITEPACKAGES_DIR}/Coherence-${RECIPE_PV}-*.egg-info
        rm -r ${D}${PYTHON_SITEPACKAGES_DIR}/coherence/test
}

PACKAGES =+ "${PN}-bin"

RDEPENDS_${PN} = "python-xmlrpc python-twisted-web"
RDEPENDS_${PN}-bin = "${PN} python-zopeinterface"

FILES_${PN}-bin = "${bindir} ${PYTHON_SITEPACKAGES_DIR}/misc/*.py"

repository: opendreambox/opendreambox

repo_name: opendreambox/opendreambox

branch_name: refs/heads/pyro

gha_license_id: NOASSERTION

gha_language: BitBake


text:
if (WIN32)
  # 4365 - signed/unsigned mismatch
  add_compile_options(/wd4365)

  # IJW
  add_compile_options(/clr)

  # IJW requires the CRT as a dll, not linked in
  add_compile_options(/MD$<$<OR:$<CONFIG:Debug>,$<CONFIG:Checked>>:d>)

  # CMake enables /RTC1 and /EHsc by default, but they're not compatible with /clr, so remove them
  if(CMAKE_CXX_FLAGS_DEBUG MATCHES "/RTC1")
    string(REPLACE "/RTC1" " " CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}")
  endif()

  if(CMAKE_CXX_FLAGS MATCHES "/EHsc")
    string(REPLACE "/EHsc" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
  endif()

  # IJW isn't compatible with CFG
  if(CMAKE_CXX_FLAGS MATCHES "/guard:cf")
    string(REPLACE "/guard:cf" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
  endif()

  # IJW isn't compatible with GR-
  if(CMAKE_CXX_FLAGS MATCHES "/GR-")
    string(REPLACE "/GR-" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
  endif()

endif()

gha_license_id: MIT

extension: cmake


text:
# Copyright (C) 2017 Afero, Inc. All rights reserved

DESCRIPTION = "Afero binary files"
SECTION = "examples"
DEPENDS = "libevent json-c zlib openssl curl af-ipc af-util attrd otamgr"
LICENSE = "CLOSED"
LIC_FILES_CHKSUM = ""

FILESEXTRAPATHS_prepend := "${THISDIR}/${PN}-${PV}:"

SRC_URI = "git://git@github.com/AferoCE/am335x-binaries;protocol=ssh"
SRCREV = "1eeebb94bd26b9cb2921699947d31bd784b76ef8"

INHIBIT_DEFAULT_DEFS = "1"
INHIBIT_PACKAGE_DEBUG_SPLIT = "1"
INHIBIT_PACKAGE_STRIP = "1"

S = "${WORKDIR}/git"

do_install() {
    install -d ${D}${bindir}
    install -d ${D}${sysconfdir}
    install -d ${D}${libdir}
    install -d ${D}${includedir}
    install -Dm 755 ${S}/${BUILD_TARGET}${bindir}/afsecd ${D}${bindir}
    install -Dm 755 ${S}/${BUILD_TARGET}${bindir}/hubby ${D}${bindir}
    install -Dm 755 ${S}/${BUILD_TARGET}${bindir}/provision ${D}${bindir}
    install -Dm 644 ${S}/${BUILD_TARGET}${sysconfdir}/hub.profile ${D}${sysconfdir}
    install -Dm 644 ${S}/${BUILD_TARGET}${sysconfdir}/app_ota_record.json ${D}${sysconfdir}
    install -Dm 644 ${S}/${BUILD_TARGET}${libdir}/libaf_edge.so.0.0.0 ${D}${libdir}
    ln -s libaf_edge.so.0.0.0 ${D}${libdir}/libaf_edge.so
    ln -s libaf_edge.so.0.0.0 ${D}${libdir}/libaf_edge.so.0
    install -Dm 644 ${S}/${BUILD_TARGET}${includedir}/aflib.h ${D}${includedir}
    install -Dm 644 ${S}/${BUILD_TARGET}${includedir}/aflib_mcu.h ${D}${includedir}
    install -Dm 644 ${S}/${BUILD_TARGET}${includedir}/af_transport.h ${D}${includedir}
    install -Dm 644 ${S}/${BUILD_TARGET}${libdir}/libafwp.a ${D}${libdir}
    install -Dm 644 ${S}/${BUILD_TARGET}${includedir}/afwp.h ${D}${includedir}
}

FILES_${PN} += " ${libdir}/libaf_edge.so ${libdir}/libaf_edge.so.0"


text:
footer div.footer-ribbon:before {
    border-right-color: #005580;
}
footer div.footer-ribbon:before {
    border-right: 10px solid #005580;
    border-top: 16px solid rgba(0, 0, 0, 0);
    content: "";
    display: block;
    height: 0;
    left: -10px;
    position: absolute;
    top: 0;
    width: 7px;
}
footer div.container div.row > div {
    margin-bottom: 10px;
}

footer div.footer-ribbon {
    background: #0088CC;
    margin: -100px 0 0 30px;
    padding: 10px 20px 6px;
    position: absolute;
    color: #ffffff;
    font-weight: 700;
}

footer div.footer-ribbon span{
    color: #ffffff;
    font-weight: 700;
}

footer {
    background: #121214;
    border-top: 4px solid #1F1F1F;
    font-size: 0.9em;
    padding: 80px 0 0;
    position: relative;
}

img{
    max-width: 100%;
}

section.contact{
    background: #f5f5f5 url(images/map-bottom.png);
    min-height: 400px;
    background-size:auto 100%;
    padding-top: 30px;
}

section.contact ul{
    list-style: none;
    margin: 0;
    padding: 0;
}

section.contact li{
    line-height: 2;
}

footer *{
    color: #ffffff;
}

.footer-copyright{
    margin-top: -70px;
}
#footer-menu{
	margin-top: 20px;
}
#footer-menu li{
    display: inline;
    list-style: none;
}
.title span{
    font-weight: 900;
}

extension: css


text:
# Imported from meta-iot-cloud as in:
# https://github.com/intel-iot-devkit/meta-iot-cloud/blob/fa0c6d50a517309dd6164bde3a67aa2bd789b046/recipes-devtools/python/python3-argcomplete_1.9.4.bb
inherit pypi setuptools3 update-alternatives
require python-argcomplete.inc

ALTERNATIVE_${PN} = "\
    activate-global-python-argcomplete \
    python-argcomplete-check-easy-install-script \
    register-python-argcomplete \
"

ALTERNATIVE_LINK_NAME[activate-global-python-argcomplete] = "${bindir}/activate-global-python-argcomplete"
ALTERNATIVE_LINK_NAME[python-argcomplete-check-easy-install-script] = "${bindir}/python-argcomplete-check-easy-install-script"
ALTERNATIVE_LINK_NAME[register-python-argcomplete] = "${bindir}/register-python-argcomplete"

ALTERNATIVE_PRIORITY = "30"

repository: jianchangfeng/meta-ros

repo_name: jianchangfeng/meta-ros


text:
DESCRIPTION = "The linux-fusion modules"
LICENSE = "GPLv2"
# dummy
LIC_FILES_CHKSUM = "file://README;md5=54be18c46d265cc8ea0aafee3034a26d"

DEPENDS = "virtual/kernel"

inherit module

PV = "9.0.2"
PR = "r0"

S = "${WORKDIR}/git"
SRCREV = "52f7ad63b4f98929fb15c2b73b9d40d39089f83e"
SRC_URI = "git://git.directfb.org/git/directfb/core/linux-fusion.git;protocol=git \
	   file://linux-fusion-modules-replace-KERNELDIR-with-KERNEL_SRC.patch"

# inherit autotools pkgconfig

export INSTALL_MOD_DIR="kernel/linux-fusion-modules"
export KERNEL_SRC="${STAGING_KERNEL_DIR}"

do_install_append() {
	install -d ${D}/usr/include/linux
	install -m 0644 ${S}/linux/include/linux/fusion.h ${D}/usr/include/linux
}

FILES_${PN}-headers = "/usr/include/linux"

gha_language: Python


text:
@article{2020arXiv201101243Z,
 adsnote = {Provided by the SAO/NASA Astrophysics Data System},
 adsurl = {https://ui.adsabs.harvard.edu/abs/2020arXiv201101243Z},
 archiveprefix = {arXiv},
 author = {Zhang, Keming and Bloom, Joshua S.},
 eid = {arXiv:2011.01243},
 eprint = {2011.01243},
 journal = {arXiv e-prints},
 keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Computer Science - Machine Learning, Physics - Data Analysis, Statistics and Probability},
 month = {November},
 pages = {arXiv:2011.01243},
 primaryclass = {astro-ph.IM},
 title = {Classification of Periodic Variable Stars with Novel Cyclic-Permutation Invariant Neural Networks},
 year = {2020}
}

repository: profjsb/my-content

repo_name: profjsb/my-content

gha_language: TeX


text:
SUMMARY = "recipe to add an user to the payload container"
LICENSE = "MIT"

EXCLUDE_FROM_WORLD = "1"

inherit useradd

# You must set USERADD_PACKAGES when you inherit useradd. This
# lists which output packages will include the user/group
# creation code.
USERADD_PACKAGES = "${PN}"

# You must also set USERADD_PARAM and/or GROUPADD_PARAM when
# you inherit useradd.
PAYLOAD_USER ?= "user"
PAYLOAD_UID ?= "1000"
PAYLOAD_GROUP ?= "group"
PAYLOAD_GID ?= "1000"

USERADD_PARAM:${PN} = "-u ${PAYLOAD_UID} -M ${PAYLOAD_USER}"
GROUPADD_PARAM:${PN} = "-g ${PAYLOAD_GID} ${PAYLOAD_GROUP}"

FILES:${PN} = "dummy"

do_install () {
	touch ${D}/dummy
}

repository: TheYoctoJester/meta-containerization

repo_name: TheYoctoJester/meta-containerization


text:
SECTION = "console/utils"
DESCRIPTION = "A tool for retrieving kernel spinlock metering information."
DEPENDS = "virtual/kernel"

SRC_URI = "ftp://oss.sgi.com/projects/lockmeter/download/old/lockstat-${PV}.tar.gz"
S = "${WORKDIR}/lockstat"

SRC_URI[md5sum] = "924779ede0615f41d033dc8eb49361fd"
SRC_URI[sha256sum] = "43125a2f26db5254bef8063bd85cfda60f32cbbc8ddb4d4141294d5d3627bf61"

export KERNEL_VERSION = "${@base_read_file('${STAGING_KERNEL_DIR}/kernel-abiversion')}"
export KERNEL_SOURCE = "${@base_read_file('${STAGING_KERNEL_DIR}/kernel-source')}"
CFLAGS += " -I${KERNEL_SOURCE}/include"

python () {
    # NOTE: any target machines with kernels supporting spinlock metering should
    # check the MACHINE variable here to prevent the SkipPackage.
    raise bb.parse.SkipPackage("The target machine's kernel does not appear able to use spinlock metering.")
}

do_compile () {
	oe_runmake
}

do_install () {
	install -d ${D}${sbindir}
	install -m 0755 lockstat ${D}${sbindir}/
}

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD


text:
# Recipe created by recipetool
# This is the basis of a recipe and may need further editing in order to be fully functional.
# (Feel free to remove these comments when editing.)

SUMMARY = "A module to control Raspberry Pi GPIO channels"
HOMEPAGE = "http://sourceforge.net/projects/raspberry-gpio-python/"
# WARNING: the following LICENSE and LIC_FILES_CHKSUM values are best guesses - it is
# your responsibility to verify that the values are complete and correct.
LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://LICENCE.txt;md5=9b95630a648966b142f1a0dcea001cb7"

SRC_URI = "https://files.pythonhosted.org/packages/cb/88/d3817eb11fc77a8d9a63abeab8fe303266b1e3b85e2952238f0da43fed4e/RPi.GPIO-${PV}.tar.gz"
SRC_URI[md5sum] = "777617f9dea9a1680f9af43db0cf150e"
SRC_URI[sha256sum] = "7424bc6c205466764f30f666c18187a0824077daf20b295c42f08aea2cb87d3f"

S = "${WORKDIR}/RPi.GPIO-${PV}"

inherit distutils3

# WARNING: the following rdepends are determined through basic analysis of the
# python sources, and might not be 100% accurate.
RDEPENDS_${PN} += "python3-core"


text:
@incollection{mcdonald-1982a,
author = "McDonald, John Alan",
year = "1988",
title = "Interactive Graphics for Data Analysis",
note = "Ph.D. thesis, Dept. of Statistics, Stanford, June 1982",
annote = "Dept. of Statistics, Stanford, Tech Rept Orion 11",
editor = "Cleveland, W.S. and McGill, M.E.",
booktitle = "Dynamic Graphics for Statistics",
publisher = "Wadsworth and Brooks/Cole",
address = "Belmont, CA",
pages = "247-275"}

@misc{McDonald:1982:OrionExploring,
author = "McDonald, John Alan",
year = "1982",
title = "Exploring Data with the {Orion I} Workstation",
note = "A 25 minute, 16mm sound film,
which demonstrates programs described in McDonald (1982)
It is available for loan from:
Jerome H. Friedman, Computation Research Group,
Bin \# 88, SLAC, P.O. Box 4349, Stanford, California 94305"}

@misc{McDonald:1982:OrionProjectionPursuit,
author = "McDonald, John Alan",
year = "1982",
title = "Projection Pursuit Regression with the {Orion I} Workstation",
note = "a 20 minute, 16mm color sound film,
which demonstrates programs described in McDonald (1982)
It is available for loan from:
Jerome H. Friedman, Computation Research Group,
Bin \# 88, SLAC, P.O. Box 4349, Stanford, California 94305"}

@article{McDonaldPedersen:1985:CompEnv1,
author = "McDonald, John Alan and Pedersen, Jan O.",
year = "1985",
title = "Computing Environments for Data Analysis {I}: Introduction",
journal = "{SIAM} J. Scientific and Statistical Computing",
volume = "6",
number = "4",
pages = "1004-1012"}

@article{McDonaldPedersen:1985:CompEnv2,
author = "McDonald, John Alan and Pedersen, Jan O.",
year = "1985",
title = "Computing Environments for Data Analysis {II}: Hardware",
journal = "{SIAM} J. Scientific and Statistical Computing",
volume = "6",
number = "4",
pages = "1013-1021"}

@article{McDonald:1986:PeriodicSmoothing,
author = "McDonald, John Alan",
year = "1986",
title = "Periodic Smoothing of Time Series",
journal = "{SIAM} J. Scientific and Statistical Computing",
volume = 7,
number = 2,
pages = "665-688"}

@inproceedings{McDonald:1986:Antelope,
author = "McDonald, John Alan",
year = "1986",
title = "Antelope: data analysis with object-oriented programming
        and constraints",
booktitle = "Proc. of the 1986 Joint Statistical Meetings, Stat. Comp. Sect.",
annote = "Also Tech Rept 89, Dept. of Statistics, U. of Washington"}

@article{McDonaldOwen:1986:SplitLinearFits,
author = "John Alan McDonald and Art B. Owen",
year = "1986",
title = "Smoothing with Split Linear Fits",
journal = "Technometrics",
volume = 28,
number = 3,
pages = "195-208"}

@techreport{McDonald:1987:OOLinearAlgebra,
author = "McDonald, John Alan",
year = "1987",
title = "Object-oriented design in numerical linear algebra",
institution = "Dept. of Statistics, U. of Washington",
number = "109"}

@articleMcDonaldPedersen:1988:CompEnv3,
author = "McDonald, John Alan and Pedersen, Jan O.",
year = "1988",
title = "Computing Environments for Data Analysis {III}:
        Programming Environments",
journal = "{SIAM} J. Scientific and Statistical Computing",
volume = "9",
number = "2",
pages = "380-400"}

@inproceedings{McDonald:1988:Arizona,
author = "McDonald, John Alan",
year = "1988",
title = "{An outline of Arizona}",
booktitle = "Computer Science and Statistics:
        Proc. 20th Symp. on the Interface",
publisher = "ASA",
address = "Washington, D.C.",
pages = "282-291",
annote = "Also Tech. Rept. 131, Dept of Statistics, U. of Washington"}

@inproceedings{McDonaldPedersen:1989:Layout,
author = "McDonald, John Alan and Pedersen Jan O.",
year = "1989",
title = "A case study in statistical computing in a Lisp environment:
        Geometric Abstractions for Constrained Optimization
        of Layouts",
booktitle = "Proc. of the 1989 Joint Statistical Meetings, Stat. Comp. Sect."}

@article{McDonald:1989:OOPSLA,
author = "McDonald, John Alan",
year = "1989",
title = "Object-oriented programming for linear algebra",
journal = "{{SIGPLAN} Notices (Proceedings OOPSLA'89)}",
volume = "24",
number = "10",
pages = "175-184",
annote = "{also Tech. Rept. 175,
        Dept. of Statistics, GN-22,
        U. of Washington,
        Seattle, WA 98195}"}

@techreport{McDonaldStuetzleBuja:1989:PaintingTR174,
author = "McDonald, John Alan and Stuetzle, Werner and Buja, Andreas",
year = "1989",
title = "{Viewing high dimensional data by painting multiple views.}",
institution = "Dept. of Statistics, U. of Washington",
number = "174"}

@techreport{McDonaldStuetzleBuja:1989:PaintingTR178,
author = "McDonald, John Alan and Stuetzle, Werner and Buja, Andreas",
year = "1989",
title = "{Painting multiple views:
an interactive technique for ``feeling'' the shape
of complex, multi-dimensional data.}",
institution = "Dept. of Statistics, U. of Washington",
number = "178"}

@article{McDonaldStuetzleBuja:1990:PaintingOOPSLA,
author = "John Alan McDonald and Werner Stuetzle and Andreas Buja",
year = "1990",
title = "Painting multiple views of complex objects",
journal = "{{SIGPLAN} Notices}",
volume = 25,
number = 10,
pages = "245-257",
note = "(Proceedings OOPSLA/ECOOP'90)"}

@techreport{McDonaldSanella:1991:Arizona,
author = "John Alan McDonald and Michael Sannella",
year = "1991",
month = "February",
title = "Arizona overview and notes for release 0.0",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonaldSanella:1991:Geometry0,
author = "John Alan McDonald and Michael Sannella",
year = "1991",
month = "February",
title = "Geometry: a package for basic geometric calculation in {Common Lisp},
release 0.0",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonaldSanella:1992:Slate,
author = "John Alan McDonald and Michael Sannella",
year = "1991",
month = "February",
title = "Slate: a portable bitmap graphics package for {Common Lisp},
release 0.0",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonaldSanella:1992:Chart,
author = "John Alan McDonald and Michael Sannella",
year = "1991",
month = "February",
title = "Chart: a simple {Common Lisp}
package for plotting data and functions,
release 0.0",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonaldSanella:1991:Arizona,
author = "John Alan McDonald and Michael Sannella",
year = "1991",
month = "October",
title = "Arizona overview and notes for release 1.0",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonald:1991:Definitions,
author = "John Alan McDonald",
year = "1991",
month = "October",
title = {Definitions: a simple database for typesetting documentation},
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonald:1991:CLNPSOL,
author = "John Alan McDonald",
year = "1991",
month = "October",
title = "Calling {NPSOL} from {Common Lisp}",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonaldSanella:1991:Geometry,
author = "John Alan McDonald and Michael Sannella",
year = "1991",
month = "October",
title = "A package for basic geometric calculation in {Common Lisp}",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonaldSanella:1992:Slate,
author = "John Alan McDonald and Michael Sannella",
year = "1992",
title = "Slate: a portable bitmap graphics package for {Common Lisp},
release 1.0",
note = "in preparation",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonaldSanella:1992:Chart,
author = "John Alan McDonald and Michael Sannella",
year = "1992",
title = "Chart: a simple {Common Lisp}
package for plotting data and functions,
release 1.0",
note = "in preparation",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonaldNiehaus:1991:Announcements,
author = "John Alan McDonald and Mark Niehaus",
month = "October",
year = "1991",
title = "Announcements: an implementation of implicit invocation",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonald:1991:GraphBrowser,
author = "John Alan McDonald",
year = "1991",
month = "October",
title = "A simple graph browser",
institution = "Dept. of Statistics, U. of Washington"}

@inproceedings{BujaMcDonaldMIchalakStuetzle:1991,
year = "1991",
author = "Andreas Buja and John Alan McDonald and John Michalak and
Werner Stuetzle",
title = "Interactive Data Visualization using Focusing and Linking",
booktitle = "Proceedings of the Second {IEEE} Conference on
                Visualization, San Diego, 22-25 October 1991",
editor = "Gregory M. Nielson and Larry Rosenblum",
publisher = "{IEEE} Computer Society Press"}

@inproceedings{BujaMcDonaldMichalakStuetzleWillis:1991,
year = 1991,
author = "Andreas Buja and John Alan McDonald and John Michalak and
Werner Stuetzle and Steve Willis",
title = "Visualization of Complex Data",
booktitle = "Video Proceedings of Visualization1991",
note = "17 minute video tape",
annote= "in refereed video proceedings
of Visualization1991, Oct 21-25, 1991, San Diego, CA."}

@techreport{DeRoseEtal:1991:Reconstruction,
author = "Tony DeRose and Tom Duchamp and Hugues Hoppe and Werner Stuetzle
and John Alan McDonald",
year = "1991",
title = "Reconstructing Two-dimensional Manifolds from Scattered Data:
Motivation and Background",
number = 215,
institution = "Dept. of Statistics, U. of Washington"}

@incollection{McDonaldPedersen:1991:Layout,
author = "John Alan McDonald and Jan O. Pedersen",
year = "1991",
title = "Geometric abstractions for constrained optimization of layouts",
booktitle = "Computing and Graphics in Statistics",
editor = "Andreas Buja and Paul Tukey",
volume = "{IMA 36}",
publisher = "Springer-Verlag",
address = "{NY NY}"}

@techreport{McDonald:1992:Clay,
author = "John Alan McDonald",
year = "1992",
note = "in preparation",
title = "Clay: a high performance user interface toolkit",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonald:1992:ProbMeasureObjects,
author = "John Alan McDonald",
year = "1992",
note = "in preparation",
title = "{Probability Measure Objects} in {CLOS}",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonald:1992:BasicMath,
author = "John Alan McDonald",
year = "1992",
title = "{Basic Math}: a package of assorted numerical analysis functions
in {Common Lisp}",
note = "in preparation",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonald:1992:Cactus,
author = "John Alan McDonald",
year = "1992",
title = "{Cactus}: a object-oriented system for computational linear
algebra and optimization",
note = "in preparation",
institution = "Dept. of Statistics, U. of Washington"}

@misc{McDonaldStuetzleBuja:1992:PaintingVideo,
author = "John Alan McDonald and Werner Stuetzle and Andreas Buja",
year = "1992",
title = "Image Painting",
note = "A 5 minute video tape; Dept of Statistics, U. of Washington"}

@techreport{McDonald:1993:ImagePainting,
author = "John Alan McDonald",
year = "1993",
title = "Fast rotation and painting of large data sets",
note = "In preparation",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{McDonald:1993:Actors,
author = "John Alan McDonald",
year = "1993",
note = "In preparation",
title = "Actors, Interactors, Mediators and Their Roles",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{BillLundellMcDonald:1992:Brick,
author = "Thomas Bill and Bertil Lundell and John Alan McDonald",
year = "1992",
month = "April",
title = "Window layout using linear programming",
institution = "Dept. of Statistics, U. of Washington"}

@techreport{ChambersMcDonald:1994:ParrotOverview,
author = "John M. Chambers and John A. McDonald",
title = "Coordinating data analysis tools with {Parrot}",
year = 1994,
institution = "Dept. of Statistics, {GN-22}, U. of Washington",
address = "Seattle {WA} 98195",
note = "In preparation"
}

@techreport{ChambersMcDonald:1994:ParrotProtocol,
author = "John M. Chambers and John A. McDonald",
title = "{Parrot} Dispatcher and Protocol",
year = 1994,
institution = "Dept. of Statistics, {GN-22}, U. of Washington",
address = "Seattle {WA} 98195",
note = "In preparation"
}

@techreport{ChambersMcDonald:1994:ParrotLibraries,
author = "John M. Chambers and John A. McDonald",
title = "{Parrot} Interface Libraries",
year = 1994,
institution = "Dept. of Statistics, {GN-22}, U. of Washington",
address = "Seattle {WA} 98195",
note = "In preparation"
}

repository: palisades-lakes/xfp

repo_name: palisades-lakes/xfp


text:
@article{Weber-2022-Effects,
    title = "Effects of aqueous fluoxetine exposure on gut microbiome of adult Pimephales promelas",
    author = "Weber, Alana  and
      Xie, Yuwei  and
      Challis, Jonathan K.  and
      DeBofsky, Abigail  and
      Ankley, Phillip J.  and
      Hecker, Markus  and
      Jones, Paul  and
      Giesy, John P.",
    journal = "Science of The Total Environment, Volume 813",
    volume = "813",
    year = "2022",
    publisher = "Elsevier BV",
    url = "https://aclanthology.org/G22-20001",
    doi = "10.1016/j.scitotenv.2021.152422",
    pages = "152422",
}

repository: gwf-uwaterloo/gwf-publications

repo_name: gwf-uwaterloo/gwf-publications

branch_name: refs/heads/main


text:
set(OPTION_DEFAULT ON)

if(WIN32)
	set(OPTION_DEFAULT ON)
elseif(WITH_CUPS)
	set(OPTION_DEFAULT ON)
else()
	set(OPTION_DEFAULT OFF)
endif()

define_channel_options(NAME "printer" TYPE "device"
	DESCRIPTION "Print Virtual Channel Extension"
	SPECIFICATIONS "[MS-RDPEPC]"
	DEFAULT ${OPTION_DEFAULT})


text:
require ti-dmai.inc

DEFAULT_PREFERENCE = "-1"

PV = "2_10_00_01+svnr${SRCPV}"

# This package has high dependence on kernel, use kernel PR as base and append a local version
PR = "${MACHINE_KERNEL_PR}"
PR_append = "l"

DMAIBRANCH_dm6446     = "trunk"
DMAIBRANCH_dm6467     = "branches/GITPSP_INT_101009"
DMAIBRANCH_omap3      = "trunk"
DMAIBRANCH_dm355      = "branches/GITPSP_INT_101009"
DMAIBRANCH_dm365      = "branches/GITPSP_INT_101009"
DMAIBRANCH_omapl137   = "trunk"
DMAIBRANCH_omapl138   = "trunk"
DMAIBRANCH           ?= "<UNDEFINED_DMAIBRANCH>"

SRCREV_dm6446         = "423"
SRCREV_dm6467         = "441"
SRCREV_omap3          = "423"
SRCREV_dm355          = "424"
SRCREV_dm365          = "441"
SRCREV_omapl137       = "423"
SRCREV_omapl138       = "423"
SRCREV               ?= "<UNDEFINED_SRCREV>"

repository: libo/openembedded

repo_name: libo/openembedded


text:
@article{Bailis:2014:CAD:2735508.2735509,
 author = {Bailis, Peter and Fekete, Alan and Franklin, Michael J. and Ghodsi, Ali and Hellerstein, Joseph M. and Stoica, Ion},
 title = {Coordination Avoidance in Database Systems},
 journal = {Proc. VLDB Endow.},
 issue_date = {November 2014},
 volume = {8},
 number = {3},
 month = nov,
 year = {2014},
 issn = {2150-8097},
 pages = {185--196},
 numpages = {12},
 url = {http://dx.doi.org/10.14778/2735508.2735509},
 doi = {10.14778/2735508.2735509},
 acmid = {2735509},
 publisher = {VLDB Endowment},
}

@inproceedings{Shapiro:2011:CRD:2050613.2050642,
 author = {Shapiro, Marc and Pregui\c{c}a, Nuno and Baquero, Carlos and Zawirski, Marek},
 title = {Conflict-free Replicated Data Types},
 booktitle = {Proceedings of the 13th International Conference on Stabilization, Safety, and Security of Distributed Systems},
 series = {SSS'11},
 year = {2011},
 isbn = {978-3-642-24549-7},
 location = {Grenoble, France},
 pages = {386--400},
 numpages = {15},
 url = {http://dl.acm.org/citation.cfm?id=2050613.2050642},
 acmid = {2050642},
 publisher = {Springer-Verlag},
 address = {Berlin, Heidelberg},
 keywords = {eventual consistency, large-scale distributed systems, replicated shared objects},
}

repository: RobbieMcKinstry/bibliographies

repo_name: RobbieMcKinstry/bibliographies


text:
@book{Criminisi2013,
  title={Decision forests for computer vision and medical image analysis},
  author={Criminisi, Antonio and Shotton, Jamie},
  year={2013},
  publisher={Springer Science \& Business Media}
}

repository: mrunibe/MIALab

repo_name: mrunibe/MIALab


text:
# TODO: port to sdl.bbclass?
DESCRIPTION = "3D arcade space shooter"
HOMEPAGE = "http://www.realtech-vr.com/nogravity/"
LICENSE = "GPL"
SECTION = "x11/games"
DEPENDS = "virtual/libsdl zlib libpng libsdl-mixer libogg libvorbis"
PR = "r1"

SRC_URI = "http://zaurus.vivaphp.net/nogravity.tar.bz2;name=archive \
	   ${SOURCEFORGE_MIRROR}/nogravity/rt-nogravity-data.zip;name=data"

S = "${WORKDIR}/${PN}/src/Linux/"
PACKAGES += "${PN}-data"

inherit autotools pkgconfig

EXTRA_OECONF = "--enable-sound=sdl_mixer  --disable-opengl"

FILES_${PN} += "/usr/games/nogravity/no*"
FILES_${PN}-data = "/usr/games/nogravity/*.RMX"
PACKAGE_ARCH_${PN}-data = "all"
RRECOMMENDS_${PN} = "${PN}-data"

do_install_prepend() {
	install -d  ${D}/usr/games/nogravity/
	install -m 644 ${WORKDIR}/*.RMX ${D}/usr/games/nogravity/
}

SRC_URI[archive.md5sum] = "42d9e4cfd86b15826426797a0fb6d499"
SRC_URI[archive.sha256sum] = "f9c86a163bd27dc4fd05abb958bb857109a556a4a58f8d06663d49ac0559ac92"
SRC_URI[data.md5sum] = "c7536e907363ea1da63430b49e42931d"
SRC_URI[data.sha256sum] = "d7d5a3d17f492049fceb2b9ea22c4c2af7243506219d83f7005b77ae410add29"


text:
@article{ahmadbeyond,
 author = {Ahmad, Ibrahim Said and Bakar, Azuraliza Abu and Yaakub, Mohd Ridzwan and Darwich, Mohammad},
 date-modified = {2020-11-06 15:50:30 +0000},
 journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
 title = {Beyond Sentiment Classification: A Novel Approach for Utilizing Social Media Data for Business Intelligence},
 volume = {3},
 year = {2020}
}

repository: buknlp/researchgroup

repo_name: buknlp/researchgroup


text:
@article{berger2008variation,
  title={{Variation in homeodomain DNA binding revealed by high-resolution analysis of sequence preferences}},
  author={Berger, Michael F and Badis, Gwenael and Gehrke, Andrew R and Talukder, Shaheynoor and Philippakis, Anthony A and Pena-Castillo, Lourdes and Alleyne, Trevis M and Mnaimneh, Sanie and Botvinnik, Olga B and Chan, Esther T and others},
  journal={Cell},
  volume={133},
  number={7},
  pages={1266--1276},
  year={2008},
  publisher={Elsevier}
}

@article{wood2012microscale,
  title={{MicroSCALE screening reveals genetic modifiers of therapeutic response in melanoma}},
  author={Wood, Kris C and Konieczkowski, David J and Johannessen, Cory M and Boehm, Jesse S and Tamayo, Pablo and Botvinnik, Olga B and Mesirov, Jill P and Hahn, William C and Root, David E and Garraway, Levi A and others},
  journal={Science Signaling},
  volume={5},
  number={224},
  pages={rs4},
  year={2012},
  publisher={NIH Public Access}
}

@article{galili2012prediction,
  title={Prediction of response to therapy with ezatiostat in lower risk myelodysplastic syndrome},
  author={Galili, Naomi and Tamayo, Pablo and Botvinnik, Olga B and Mesirov, Jill P and Brooks, Margarita R and Brown, Gail and Raza, Azra},
  journal={Journal of Hematology \& Oncology},
  volume={5},
  number={1},
  pages={1},
  year={2012},
  publisher={BioMed Central}
}

@article{galili2011gene,
  title={{Gene Expression Studies May Identify Lower Risk Myelodysplastic Syndrome Patients Likely to Respond to Therapy with Ezatiostat Hydrochloride (TLK199)}},
  author={Galili, Naomi and Tamayo, Pablo and Botvinnik, Olga B and Mesirov, Jill P and Zikria, Jennifer and Brown, Gail and Raza, Azra},
  journal={Blood},
  volume={118},
  number={21},
  pages={2779--2779},
  year={2011},
  publisher={American Society of Hematology}
}

@article{kim2016characterizing,
  title={Characterizing genomic alterations in cancer by complementary functional associations},
  author={Kim*, Jong Wook and Botvinnik*, Olga B and Abudayyeh, Omar and Birger, Chet and Rosenbluh, Joseph and Shrestha, Yashaswi and Abazeed, Mohamed E and Hammerman, Peter S and DiCara, Daniel and Konieczkowski, David J and others},
  journal={Nature Biotechnology},
  year={2016},
  publisher={Nature Publishing Group},
  note={* These authors contributed equally to this work}
}

@article{song2017,
  title={Single-Cell Alternative Splicing Analysis with Expedition Reveals Splicing Dynamics during Neuron Differentiation},
  author={Song*, Yan and Botvinnik*, Olga B and Lovci, Michael T and Kakaradov, Boyko and Liu, Patrick and Xu, Jia L and Yeo, Gene},
  journal={Molecular Cell},
  year={2017},
  publisher={Nature Publishing Group},
  note={* These authors contributed equally to this work}
}

%% Created using Papers on Mon, 26 Dec 2016.
%% http://papersapp.com/papers/

@article{Nutter:2016fd,
author = {Nutter, Curtis A and Jaworski, Elizabeth A and Verma, Sunil K and Deshmukh, Vaibhav and Wang, Qiongling and Botvinnik, Olga B and Lozano, Mario J and Abass, Ismail J and Ijaz, Talha and Brasier, Allan R and Garg, Nisha J and Wehrens, Xander H T and Yeo, Gene W and Kuyumcu-Martinez, Muge N},
title = {{Dysregulation of RBFOX2 Is an Early Event in Cardiac Pathogenesis of Diabetes}},
journal = {Cell Reports},
year = {2016},
volume = {15},
number = {10},
pages = {2200--2213},
doi = {10.1016/j.celrep.2016.05.002},
language = {English},
rating = {0},
date-added = {2016-12-26T22:41:36GMT},
date-modified = {2016-12-26T22:43:33GMT},
url = {http://linkinghub.elsevier.com/retrieve/pii/S2211124716305551},
local-url = {file://localhost/Users/olga/Documents/Library.papers3/Articles/2016/Nutter/Cell%20Reports%202016%20Nutter.pdf},
file = {{Cell Reports 2016 Nutter.pdf:/Users/olga/Documents/Library.papers3/Articles/2016/Nutter/Cell Reports 2016 Nutter.pdf:application/pdf;Cell Reports 2016 Nutter.pdf:/Users/olga/Documents/Library.papers3/Articles/2016/Nutter/Cell Reports 2016 Nutter.pdf:application/pdf}},
uri = {\url{papers3://publication/doi/10.1016/j.celrep.2016.05.002}}
}

@article{Goncearenco:2012eha,
author = {Goncearenco, A and Grynberg, P and Botvinnik, Olga B and Macintyre, Geoff and Abeel, Thomas},
title = {{Highlights from the Eighth International Society for Computational Biology (ISCB) Student Council Symposium 2012}},
journal = {BMC Bioinformatics},
year = {2012},
doi = {10.1186/1471-2105-13-S18-A1},
read = {Yes},
rating = {0},
date-added = {2016-12-26T22:41:19GMT},
date-modified = {2016-12-26T22:45:51GMT},
abstract = {... BMC Bioinformatics201213(Suppl 18):A1. DOI: 10.1186 / 1471 - 2105 - 13 - S18 - A1 . {\textcopyright} Goncearenco et al; licensee BioMed Central Ltd. 2012. Published: 14 December 2012. Abstract. The report summarizes the scientific content of ...
},
url = {http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-13-S18-A1},
local-url = {file://localhost/Users/olga/Documents/Library.papers3/Articles/2012/Goncearenco/2012%20Goncearenco.pdf},
file = {{2012 Goncearenco.pdf:/Users/olga/Documents/Library.papers3/Articles/2012/Goncearenco/2012 Goncearenco.pdf:application/pdf}},
uri = {\url{papers3://publication/doi/10.1186/1471-2105-13-S18-A1}}
}

@article{TabulaMuris:2018gj,
author = {{Tabula Muris Consortium}},
title = {{Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris}},
journal = {Nature},
year = {2018},
pages = {1--25},
month = oct,
URL = {https://www.nature.com/articles/s41586-018-0590-4},
eprint = {https://www.biorxiv.org/content/early/2017/12/20/237446.full.pdf}
}

@article{Botvinnik:2020,
author = {{Botvinnik, Olga B and Vemuri, Venkata Naga Pranathi and Logan, Phoenix Aja and Nafees, Saba and Brown, C. Titus and Karkanias, Jim}},
title = {{Sencha directly translates RNA-seq reads to enable functional prediction of transcriptomic `dark matter' across species}},
year = {2020},
journal = {In preparation},
URL = {https://czbiohub.github.io/de-novo-orthology-paper/},
}

@article {Shah2020.05.02.20082461,
	author = {Shah, Sachin J and Barish, Peter N and Prasad, Priya A and Kistler, Amy L and Neff, Norma and Kamm, Jack and Li, Lucy M and Chiu, Charles Y and Babick, Jennifer M and Fang, Margaret C and Abe-Jones, Yumiko and Alipanah, Narges and Alvarez, Francisco N and Botvinnik, Olga B and Davis, Jennifer M and Castenada, Gloria D and Consortium, CLIAHub and Dadasovich, Rand M and Deng, Xianding and DeRisi, Joseph L and Detweiler, Angela M and Federman, Scot and Haliburton, John R and Hao, Samantha L and Kerkhoff, Andrew D and Kumar, Renuka and Malcolm, Katherine and Mann, Sabrina A and Martinez, Sandra P and Marya, Rupa and Mick, Eran and Mwakibete, Lusajo L and Najafi, Nader and Peluso, Michael J and Phelps, Maira S and Pisco, Angela O and Ratnasiri, Kalani and Rubio, Luis A and Sellas, Anna B and Sherwood, Kyla D and Sheu, Jonathan and Spottiswoode, Natasha and Tan, Michelle and Yu, Guixa and Kangelaris, Kirsten N and Langelier, Charles},
	title = {Clinical features, diagnostics, and outcomes of patients presenting with acute respiratory illness: a comparison of patients with and without COVID-19},
	elocation-id = {2020.05.02.20082461},
	year = {2020},
	doi = {10.1101/2020.05.02.20082461},
	publisher = {Cold Spring Harbor Laboratory Press},
	abstract = {Background: Emerging data on the clinical presentation, diagnostics, and outcomes of patients with COVID-19 have largely been presented as case series. Few studies have compared these clinical features and outcomes of COVID-19 to other acute respiratory illnesses. Methods: We examined all patients presenting to an emergency department in San Francisco, California between February 3 and March 31, 2020 with an acute respiratory illness who were tested for SARS-CoV-2. We determined COVID-19 status by PCR and metagenomic next generation sequencing (mNGS). We compared demographics, comorbidities, symptoms, vital signs, and laboratory results including viral diagnostics using PCR and mNGS. Among those hospitalized, we determined differences in treatment (antibiotics, antivirals, respiratory support) and outcomes (ICU admission, ICU interventions, acute respiratory distress syndrome, cardiac injury). Findings: In a cohort of 316 patients, 33 (10\%) tested positive for SARS-CoV-2; 31 patients, all without COVID-19, tested positive for another respiratory virus (16\%). Among patients with additional viral testing, no co-infections with SARS-CoV-2 were identified by PCR or mNGS. Patients with COVID-19 reported longer symptoms duration (median 7 vs. 3 days), and were more likely to report fever (82\% vs. 44\%), fatigue (85\% vs. 50\%), and myalgias (61\% vs 27\%); p\<0.001 for all comparisons. Lymphopenia (55\% vs 34\%, p=0.018) and bilateral opacities on initial chest radiograph (55\% vs. 24\%, p=0.001) were more common in patients with COVID-19. Patients with COVID-19 were more often hospitalized (79\% vs. 56\%, p=0.014). Of 186 hospitalized patients, patients with COVID-19 had longer hospitalizations (median 10.7d vs. 4.7d, p\<0.001) and were more likely to develop ARDS (23\% vs. 3\%, p\<0.001). Most comorbidities, home medications, signs and symptoms, vital signs, laboratory results, treatment, and outcomes did not differ by COVID-19 status. Interpretation: While we found differences in clinical features of COVID-19 compared to other acute respiratory illnesses, there was significant overlap in presentation and comorbidities. Patients with COVID-19 were more likely to be admitted to the hospital, have longer hospitalizations and develop ARDS, and were unlikely to have co-existent viral infections. These findings enhance understanding of the clinical characteristics of COVID-19 in comparison to other acute respiratory illnesses.   Competing Interest StatementDr. Prasad reports personal fees from EpiExcellence, LLC, outside the submitted work. Dr. Chiu reports grants from National Institutes of Health/NHLBI, grants from National Institutes of Health/NIAID, during the conduct of the study. Dr. Peluso reports grants from Gilead Sciences, outside the submitted work. Dr. Deng has a patent 62/667344 pending.Funding StatementThis study was supported by the National Center for Advancing Translational Sciences (KL2TR001870), the National Heart Lung Blood Institute (1K23HL138461-01A1, R01-HL105704), National Institute of Allergy and Infectious Diseases (T32 AI060530, R33-AI120977), the Chan Zuckerberg Biohub, the Chan Zuckerberg Initiative. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  Author DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesViral genomic data is publicly accessible via gisaid.org (Global Initiative on Sharing All Influenza Data) 36 and Genbank (MT385414 - MT385497).},
	URL = {https://www.medrxiv.org/content/early/2020/05/06/2020.05.02.20082461},
	eprint = {https://www.medrxiv.org/content/early/2020/05/06/2020.05.02.20082461.full.pdf},
	journal = {medRxiv}
}

repository: burmist-git/latex-moderncv

repo_name: burmist-git/latex-moderncv


text:
@ARTICLE{Kuhne2009-tn,
  title   = "Improving the Traditional Information Management in Natural
  Sciences",
  author  = "K{\"u}hne, Martin and Liehr, Andreas W",
  journal = "Data Sci. J.",
  volume  =  8,
  pages   = "18--26",
  year    =  2009,
  issn    = "1683-1470, 0308-9541",
  doi     = "10.2481/dsj.8.18"
}

 @ARTICLE{Maxwell2018-ht,
   title     = "{Drying--Rewetting} Cycles Affect Nitrate Removal Rates in
                Woodchip Bioreactors",
   author    = "Maxwell, Bryan M and Birgand, Fran{\c c}ois and Schipper, Louis
                A and Christianson, Laura E and Tian, Shiying and Helmers,
                Matthew J and Williams, David J and Chescheir, George M and
                Youssef, Mohamed A",
   journal   = "J. Environ. Qual.",
   publisher = "The American Society of Agronomy, Crop Science Society of
                America, and Soil Science Society of America, Inc.",
   year      =  2018,
   url       = "http://dx.doi.org/10.2134/jeq2018.05.0199",
   file      = "All Papers/M/Maxwell et al. 2018 - Drying–Rewetting Cycles Affect Nitrate Removal Rates in Woodchip Bioreactors.pdf",
   address   = "Madison, WI",
   issn      = "0047-2425",
   doi       = "10.2134/jeq2018.05.0199"
 }

 @MISC{Wikipedia_contributors2018-ia,
   title        = "Denitrification",
   booktitle    = "Wikipedia, The Free Encyclopedia",
   author       = "{Wikipedia contributors}",
   month        =  dec,
   year         =  2018,
   url          = "https://en.wikipedia.org/w/index.php?title=Denitrification&oldid=872283218",
   howpublished = "\url{https://en.wikipedia.org/w/index.php?title=Denitrification&oldid=872283218}",
   note         = "Accessed: 2018-12-17"
 }

repository: francoisbirgand/BAEBookExample

repo_name: francoisbirgand/BAEBookExample


text:
@article{Hancock2015,
 abstract = {Full waveform lidar has a unique capability to characterise vegetation in more detail than any other practical method. The reflectance, calculated from the energy of lidar returns, is a key parameter for a wide range of applications and so it is vital to extract it accurately. Fifteen separate methods have been proposed to extract return energy (the amount of light backscattered from a target), ranging from simple to mathematically complex, but the relative accuracies have not yet been assessed. This paper uses a simulator to compare all methods over a wide range of targets and lidar system parameters. For hard targets the simplest methods (windowed sum, peak and quadratic) gave the most consistent estimates. They did not have high accuracies, but low standard deviations show that they could be calibrated to give accurate energy. This may be why some commercial lidar developers use them, where the primary interest is in surveying solid objects. However, simulations showed that these methods are not appropriate over vegetation. The widely used Gaussian fitting performed well over hard targets (0.24% root mean square error, RMSE), as did the sum and spline methods (0.30% RMSE). Over vegetation, for large footprint (15 m) systems, Gaussian fitting performed the best (12.2% RMSE) followed closely by the sum and spline (both 12.7% RMSE). For smaller footprints (33 cm and 1 cm) over vegetation, the relative accuracies were reversed (0.56% RMSE for the sum and spline and 1.37% for Gaussian fitting). Gaussian fitting required heavy smoothing (convolution with an 8 m Gaussian) whereas none was needed for the sum and spline. These simpler methods were also more robust to noise and far less computationally expensive than Gaussian fitting. Therefore it was concluded that the sum and spline were the most accurate for extracting return energy from waveform lidar over vegetation, except for large footprint (15 m), where Gaussian fitting was slightly more accurate. These results suggest that small footprint (≪ 15 m) lidar systems that use Gaussian fitting or proprietary algorithms may report inaccurate energies, and thus reflectances, over vegetation. In addition the effect of system pulse length, sampling interval and noise on accuracy for different targets was assessed, which has implications for sensor design.},
 author = {Hancock, Steven and Armston, John D. and Li, Zhan and Gaulton, Rachel and Lewis, Philip E. and Disney, Mathias I. and Mark Danson, F. and Strahler, Alan H. and Schaaf, Crystal and Anderson, Karen and Gaston, Kevin J},
 copyright = {All rights reserved},
 doi = {10.1016/j.rse.2015.04.013},
 issn = {00344257},
 journal = {Remote Sensing of Environment},
 keywords = {Forests, Full waveform, Lidar, Reflectance, Signal processing},
 month = {July},
 number = {0},
 pages = {208--224},
 title = {Waveform lidar over vegetation: An evaluation of inversion methods for estimating return energy},
 url = {http://www.sciencedirect.com/science/article/pii/S003442571500142X},
 volume = {164},
 year = {2015}
}


text:
require gimp.inc

PR = "r1"

DEPENDS += "webkit-gtk lcms gegl hal"

SRC_URI = "ftp://ftp.gimp.org/pub/gimp/v2.6/gimp-${PV}.tar.bz2 \
          "

SRC_URI[md5sum] = "a4d9462c9420954824a80c9b1963f9d9"
SRC_URI[sha256sum] = "d5d4218b742390157fca23a9d2cce436904546a2ea419ffeb44a5f43c99a3332"


text:
SECTION = "libs"
DESCRIPTION = "an ELF object file access library \
The elf library provides routines to access, and manipulate, Elf object \
files. It is still not complete, but is required for a number of programs, \
such as Eli (a state of the art compiler generation system), and Elk (the \
Extension Language Kit - an implementation of the Scheme programming \
language.)"
LICENSE = "LGPL"

SRC_URI = "http://www.mr511.de/software/libelf-${PV}.tar.gz"

inherit autotools

do_configure_prepend () {
	if test ! -e acinclude.m4; then
		cp aclocal.m4 acinclude.m4
	fi
}

do_install () {
	oe_runmake 'prefix=${D}${prefix}' 'exec_prefix=${D}${exec_prefix}' \
		   'libdir=${D}${libdir}' 'includedir=${D}${includedir}' \
		   install
}

do_stage () {
	oe_libinstall -so -C lib libelf ${STAGING_LIBDIR}/
	install -d ${STAGING_INCDIR}/libelf
	for i in libelf.h nlist.h gelf.h sys_elf.h; do
		install -m 0644 lib/$i ${STAGING_INCDIR}/libelf/
	done
	make includedir=${STAGING_INCDIR} install-compat
}

SRC_URI[md5sum] = "f85d6dc4b4ef1c126080d86cf0ce63fd"
SRC_URI[sha256sum] = "644262514d0f6c3572f66935921a5290383a15e804e9b085e293ab78102d3513"


text:
@article{jackson_vegetable_2019,
 abstract = {© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Nitric oxide (NO) facilitates anti-atherosclerotic effects. Vegetables are a major source of dietary nitrate. Experimental data indicates that dietary nitrate can significantly reduce major risk factors for atherosclerosis and subsequent cardiovascular disease (CVD), as nitrate can be metabolized to produce NO via the nitrate-nitrite-NO pathway. The purpose of this study was to prospectively investigate the association between habitual dietary nitrate intakes and the incidence of self-reported CVD-related complications within a representative sample of middle-aged Australian women (1946–1951 cohort of the Australian Longitudinal Study on Women’s Health). Women free from disease at baseline who had completed the food frequency questionnaire data were included. Generalized estimating equations were used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) across quartiles for nitrate intakes. Of the 5324 women included for analysis, there were 1951 new cases of CVD-related complications over 15-years of follow-up. Women reporting higher total dietary nitrate intakes (Q4 \textgreater 78.2 mg/day) and vegetable nitrate intakes (Q4 \textgreater 64.4 mg/day) were 25% and 27% reduced risk of developing CVD-related complications respectively, compared with women reporting low total (Q1 \textless 45.5 mg/day) and vegetable nitrate intakes (Q1 \textless 34.8 mg/day). Our findings were consistent with other observational data indicating that dietary nitrate may explain some of the cardiovascular benefits of vegetable consumption.},
 author = {Jackson, J.K. and Patterson, A.J. and Macdonald-Wicks, L.K. and Forder, P.M. and Blekkenhorst, L.C. and Bondonno, C.P. and Hodgson, J.M. and Ward, N.C. and Holder, C. and Oldmeadow, C. and Byles, J.E. and McEvoy, M.A.},
 doi = {10.3390/nu11020240},
 issn = {2072-6643},
 journal = {Nutrients},
 month = {February},
 number = {2},
 title = {Vegetable nitrate intakes are associated with reduced self-reported cardiovascular-related complications within a representative sample of middle-aged australian women, prospectively followed up for 15 years},
 volume = {11},
 year = {2019}
}

repository: ChrisOldmeadow/academic-kickstart

repo_name: ChrisOldmeadow/academic-kickstart


text:
DESCRIPTION = "Hubbub is an HTML5 compliant parsing library"
HOMEPAGE = "http://www.netsurf-browser.org/projects/hubbub/"
SECTION = "libs"
PRIORITY = "optional"
LICENSE = "MIT"
DEPENDS = "libparserutils"

PR = "r1"

SRC_URI = "http://www.netsurf-browser.org/projects/releases/hubbub-${PV}-src.tar.gz"

inherit pkgconfig

EXTRA_OEMAKE = "CURDIR=${S} DESTDIR=${D} PREFIX=${prefix} BUILDDIR=build-OE"

# NOTE: we're using default buildmode here, which results in building only
# static libraries (.a) Not a problem as hubbub is only used by Netsurf
# at the moment

do_stage() {
        oe_libinstall -a -C build-OE/ libhubbub ${STAGING_LIBDIR}
        install -m 0644 build-OE/libhubbub.pc ${STAGING_LIBDIR}/pkgconfig
        install -d ${STAGING_INCDIR}/hubbub
        install -m 0644 include/hubbub/*.h ${STAGING_INCDIR}/hubbub
}

do_install() {
	oe_runmake install
}

SRC_URI[md5sum] = "dbdc6bb13a71ce72384d7ee5891a0382"
SRC_URI[sha256sum] = "fd195b91e80ef2ea1f558f94bd5bb5df89228b1af3e9b7c5c1039f65d506aa1d"


text:
@article{2012ApJ...755...98M,
 abstract = {We present the results of a machine-learning (ML)-based search for new R
Coronae Borealis (RCB) stars and DY Persei-like stars (DYPers)
in the Galaxy using cataloged light curves from the All-Sky
Automated Survey (ASAS) Catalog of Variable Stars (ACVS). RCB
stars—a rare class of hydrogen-deficient carbon-rich
supergiants—are of great interest owing to the
insights they can provide on the late stages of stellar
evolution. DYPers are possibly the low-temperature, low-
luminosity analogs to the RCB phenomenon, though additional
examples are needed to fully establish this connection. While
RCB stars and DYPers are traditionally identified by epochs of
extreme dimming that occur without regularity, the ML search
framework more fully captures the richness and diversity of
their photometric behavior. We demonstrate that our ML method
can use newly discovered RCB stars to identify additional
candidates within the same data set. Our search yields 15
candidates that we consider likely RCB stars/DYPers: new
spectroscopic observations confirm that four of these candidates
are RCB stars and four are DYPers. Our discovery of four new
DYPers increases the number of known Galactic DYPers from two to
six; noteworthy is that one of the new DYPers has a measured
parallax and is m \ensuremath≈ 7 mag, making it the
brightest known DYPer to date. Future observations of these new
DYPers should prove instrumental in establishing the RCB
connection. We consider these results, derived from a machine-
learned probabilistic classification catalog, as an important
proof-of-concept for the efficient discovery of rare sources
with time-domain surveys.},
 adsnote = {Provided by the SAO/NASA Astrophysics Data System},
 adsurl = {https://ui.adsabs.harvard.edu/abs/2012ApJ...755...98M},
 archiveprefix = {arXiv},
 author = {Miller, A.~A. and Richards, J.~W. and Bloom, J.~S. and
Cenko, S.~B. and Silverman, J.~M. and Starr, D.~L. and
Stassun, K.~G.},
 doi = {10.1088/0004-637X/755/2/98},
 eid = {98},
 eprint = {1204.4181},
 journal = {\apj},
 keywords = {circumstellar matter, methods: data analysis, stars: carbon, stars: evolution, stars: variables: general, techniques: photometric, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
 month = {Aug},
 number = {2},
 pages = {98},
 primaryclass = {astro-ph.SR},
 title = {Discovery of Bright Galactic R Coronae Borealis and DY Persei Variables: Rare Gems Mined from ACVS},
 volume = {755},
 year = {2012}
}


text:
%%% -*-BibTeX-*-
@inproceedings{ECCV12,
    author      = {Rui Yao and Qinfeng Shi and Chunhua Shen and Yanning Zhang and Anton {van den Hengel} },
    title       = {Robust Tracking with Weighted Online Structured Learning},
    year        = {2012},
    month       = {},
    booktitle   = {European Conference on Computer Vision (ECCV'12)},
    address     = {},
    venue       = {ECCV},
    pages       = {158--172},
    volume      = {7574},
    publisher   = {LNCS, Springer},
    note        = {},
    eprint      = {},
    url         = {},
    pdf         = {https://sites.google.com/site/chhshen/publication/weighted_tracking_eccv12.pdf?attredirects=1}
}


text:
@Article{bedo2016information,
  title = {Information theoretic alignment free variant calling},
  author = {Justin Bedo and Benjamin Goudey and Jeremy Wazny and Zeyu Zhou},
  journal = {PeerJ Computer Science},
  volume = {2},
  pages = {e71},
  year = {2016},
  publisher = {PeerJ Inc.},
  date = {2016-01-01},
}

repository: bwgoudey/starter-academic

repo_name: bwgoudey/starter-academic


text:
# Install script for directory: C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout

# Set the install prefix
if(NOT DEFINED CMAKE_INSTALL_PREFIX)
  set(CMAKE_INSTALL_PREFIX "C:/Program Files (x86)/VTK")
endif()
string(REGEX REPLACE "/$" "" CMAKE_INSTALL_PREFIX "${CMAKE_INSTALL_PREFIX}")

# Set the install configuration name.
if(NOT DEFINED CMAKE_INSTALL_CONFIG_NAME)
  if(BUILD_TYPE)
    string(REGEX REPLACE "^[^A-Za-z0-9_]+" ""
           CMAKE_INSTALL_CONFIG_NAME "${BUILD_TYPE}")
  else()
    set(CMAKE_INSTALL_CONFIG_NAME "Release")
  endif()
  message(STATUS "Install configuration: \"${CMAKE_INSTALL_CONFIG_NAME}\"")
endif()

# Set the component getting installed.
if(NOT CMAKE_INSTALL_COMPONENT)
  if(COMPONENT)
    message(STATUS "Install component: \"${COMPONENT}\"")
    set(CMAKE_INSTALL_COMPONENT "${COMPONENT}")
  else()
    set(CMAKE_INSTALL_COMPONENT)
  endif()
endif()

# Is this installation the result of a crosscompile?
if(NOT DEFINED CMAKE_CROSSCOMPILING)
  set(CMAKE_CROSSCOMPILING "FALSE")
endif()

if("x${CMAKE_INSTALL_COMPONENT}x" STREQUAL "xdevelopmentx" OR NOT CMAKE_INSTALL_COMPONENT)
  file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/include/vtk-9.0" TYPE FILE FILES
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkArcParallelEdgeStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkAreaLayout.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkAreaLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkAssignCoordinates.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkAssignCoordinatesLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkAttributeClustering2DLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkBoxLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkCirclePackFrontChainLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkCirclePackLayout.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkCirclePackLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkCirclePackToPolyData.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkCircularLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkClustering2DLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkCommunity2DLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkConeLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkConstrained2DLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkCosmicTreeLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkEdgeLayout.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkEdgeLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkFast2DLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkForceDirectedLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkGeoEdgeStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkGeoMath.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkGraphLayout.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkGraphLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkIncrementalForceLayout.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkKCoreLayout.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkPassThroughEdgeStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkPassThroughLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkPerturbCoincidentVertices.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkRandomLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkSimple2DLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkSimple3DCirclesStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkSliceAndDiceLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkSpanTreeLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkSplineGraphEdges.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkSquarifyLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkStackedTreeLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkTreeLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkTreeMapLayout.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkTreeMapLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkTreeMapToPolyData.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkTreeOrbitLayoutStrategy.h"
    "C:/Development/op3d_active/VTK-9.0.1/Infovis/Layout/vtkTreeRingToPolyData.h"
    "C:/Development/op3d_active/VTK-9.0.1/msvc/Infovis/Layout/vtkInfovisLayoutModule.h"
    )
endif()

if("x${CMAKE_INSTALL_COMPONENT}x" STREQUAL "xdevelopmentx" OR NOT CMAKE_INSTALL_COMPONENT)
  file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/lib/vtk/hierarchy/VTK" TYPE FILE RENAME "vtkInfovisLayout-hierarchy.txt" FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/lib/vtk/hierarchy/VTK/vtkInfovisLayout-hierarchy.txt")
endif()

if("x${CMAKE_INSTALL_COMPONENT}x" STREQUAL "xdevelopmentx" OR NOT CMAKE_INSTALL_COMPONENT)
  if("${CMAKE_INSTALL_CONFIG_NAME}" MATCHES "^([Dd][Ee][Bb][Uu][Gg])$")
    file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/lib" TYPE STATIC_LIBRARY OPTIONAL FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/lib/Debug/vtkInfovisLayout-9.0d.lib")
  elseif("${CMAKE_INSTALL_CONFIG_NAME}" MATCHES "^([Rr][Ee][Ll][Ee][Aa][Ss][Ee])$")
    file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/lib" TYPE STATIC_LIBRARY OPTIONAL FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/lib/Release/vtkInfovisLayout-9.0.lib")
  elseif("${CMAKE_INSTALL_CONFIG_NAME}" MATCHES "^([Mm][Ii][Nn][Ss][Ii][Zz][Ee][Rr][Ee][Ll])$")
    file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/lib" TYPE STATIC_LIBRARY OPTIONAL FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/lib/MinSizeRel/vtkInfovisLayout-9.0.lib")
  elseif("${CMAKE_INSTALL_CONFIG_NAME}" MATCHES "^([Rr][Ee][Ll][Ww][Ii][Tt][Hh][Dd][Ee][Bb][Ii][Nn][Ff][Oo])$")
    file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/lib" TYPE STATIC_LIBRARY OPTIONAL FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/lib/RelWithDebInfo/vtkInfovisLayout-9.0.lib")
  endif()
endif()

if("x${CMAKE_INSTALL_COMPONENT}x" STREQUAL "xruntimex" OR NOT CMAKE_INSTALL_COMPONENT)
  if("${CMAKE_INSTALL_CONFIG_NAME}" MATCHES "^([Dd][Ee][Bb][Uu][Gg])$")
    file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/bin" TYPE SHARED_LIBRARY FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/bin/Debug/vtkInfovisLayout-9.0d.dll")
  elseif("${CMAKE_INSTALL_CONFIG_NAME}" MATCHES "^([Rr][Ee][Ll][Ee][Aa][Ss][Ee])$")
    file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/bin" TYPE SHARED_LIBRARY FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/bin/Release/vtkInfovisLayout-9.0.dll")
  elseif("${CMAKE_INSTALL_CONFIG_NAME}" MATCHES "^([Mm][Ii][Nn][Ss][Ii][Zz][Ee][Rr][Ee][Ll])$")
    file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/bin" TYPE SHARED_LIBRARY FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/bin/MinSizeRel/vtkInfovisLayout-9.0.dll")
  elseif("${CMAKE_INSTALL_CONFIG_NAME}" MATCHES "^([Rr][Ee][Ll][Ww][Ii][Tt][Hh][Dd][Ee][Bb][Ii][Nn][Ff][Oo])$")
    file(INSTALL DESTINATION "${CMAKE_INSTALL_PREFIX}/bin" TYPE SHARED_LIBRARY FILES "C:/Development/op3d_active/VTK-9.0.1/msvc/bin/RelWithDebInfo/vtkInfovisLayout-9.0.dll")
  endif()
endif()