Wu, C. M., Dale, R., & Hawkins, R. D. (submitted). Group coordination catalyzes individual and cultural intelligence. PsyArXiv. https://doi.org/10.31234/osf.io/gscy6
@article{wu2023group,
title = {Group coordination catalyzes individual and cultural intelligence},
journal = {PsyArXiv},
year = {submitted},
keywords = {prep},
author = {Wu, Charley M and Dale, Rick and Hawkins, Robert D},
doi = {10.31234/osf.io/gscy6},
pdf = {https://charleywu.github.io/downloads/wu2023group.pdf}
}
Wu, C. M., Deffner, D., Kahl, B., Meder, B., Ho, M. H., & Kurvers, R. H. J. M. (submitted). Visual-spatial dynamics drive adaptive social learning in immersive environments. BioRxiv. https://doi.org/10.1101/2<IP_ADDRESS>6887
@article{wu2023visual,
title = {Visual-spatial dynamics drive adaptive social learning in immersive environments},
author = {Wu, Charley M and Deffner, Dominik and Kahl, Benjamin and Meder, Bj{\"o}rn and Ho, Mark H and Kurvers, Ralf HJM},
journal = {bioRxiv},
year = {submitted},
keywords = {prep},
doi = {10.1101/2<IP_ADDRESS>6887},
pdf = {https://charleywu.github.io/downloads/wu2023visual.pdf}
}
Deffner, D., Mezey, D., Kahl, B., Schakowski, A., Romanczuk, P., Wu, C. M., & Kurvers, R. (submitted). Collective incentives reduce over-exploitation of social information in unconstrained human groups. https://doi.org/10.31234/osf.io/p3bj7
@article{deffner2023collective,
title = {Collective incentives reduce over-exploitation of social information in unconstrained human groups},
url = {psyarxiv.com/p3bj7},
doi = {10.31234/osf.io/p3bj7},
publisher = {PsyArXiv},
author = {Deffner, Dominik and Mezey, David and Kahl, Benjamin and Schakowski, Alexander and Romanczuk, Pawel and Wu, Charley M and Kurvers, Ralf},
year = {submitted},
keywords = {prep},
pdf = {https://charleywu.github.io/downloads/deffner2023collective.pdf}
}
In Press
Haridi, S., Wu, C. M., Dasgupta, I., & Schulz, E. (in press). The scaling of mental computation in a sorting task. Cognition. https://doi.org/10.31234/osf.io/8hqtv
@article{haridi2022scaling,
title = {The scaling of mental computation in a sorting task},
journal = {Cognition},
author = {Haridi, Susanne and Wu, Charley M and Dasgupta, Ishita and Schulz, Eric},
doi = {10.31234/osf.io/8hqtv},
keywords = {prep},
preprint = {https://psyarxiv.com/8hqtv},
year = {in press},
code = {https://github.com/susanneharidi/mental-sorting},
pdf = {https://charleywu.github.io/downloads/haridi2022scaling.pdf}
}
2023
Rubino, V., Hamidi, M., Dayan, P., & Wu, C. M. (2023). Compositionality under time pressure. In M. Goldwater, F. Anggoro, B. Hayes, & D. Ong (Eds.), Proceedings of the 45th Annual Conference of the Cognitive Science Society. Sydney, Australia: Cognitive Science Society. https://doi.org/10.31234/osf.io/z2648
@inproceedings{rubino2023compositionality,
title = {Compositionality under time pressure},
author = {Rubino, Valerio and Hamidi, Mani and Dayan, Peter and Wu, Charley M},
year = {2023},
keywords = {published},
doi = {10.31234/osf.io/z2648},
booktitle = {{Proceedings of the 45th Annual Conference of the Cognitive Science Society}},
publisher = {{Cognitive Science Society}},
preprint = {https://psyarxiv.com/z2648/},
editor = {Goldwater, M. and Anggoro, F. and Hayes, B. and Ong, D.},
address = {{Sydney, Australia}},
pdf = {https://charleywu.github.io/downloads/rubino2023compositionality.pdf}
}
Uchiyama, R., Tennie, C., & Wu, C. M. (2023). Model-Based Assimilation Transmits and Recombines World Models. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK. https://doi.org/10.31234/osf.io/v69jy
@inproceedings{uchiyama2023model,
title = {Model-Based Assimilation Transmits and Recombines World Models},
url = {psyarxiv.com/v69jy},
doi = {10.31234/osf.io/v69jy},
author = {Uchiyama, Ryutaro and Tennie, Claudio and Wu, Charley M},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/uchiyama2023model.pdf}
}
Smith, A. L., Heuschkel, S., Keplinger, K., & Wu, C. M. (2023). Constructing and deconstructing bias: modeling privilege and mentorship in agent-based simulations. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK. https://doi.org/10.48550/arXiv.2304.02351
@inproceedings{smith2023constructing,
title = {Constructing and deconstructing bias: modeling privilege and mentorship in agent-based simulations},
author = {Smith, Andria L and Heuschkel, Simon and Keplinger, Ksenia and Wu, Charley M},
doi = {10.48550/arXiv.2304.02351},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/smith2023constructing.pdf}
}
Zhou, H., Tejero-Cantero, Á., & Wu, C. M. (2023). The Dynamic and Structured Nature of Learning and Memory. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK.
@inproceedings{zhou2023dynamic,
title = {The Dynamic and Structured Nature of Learning and Memory},
author = {Zhou, Hanqi and Tejero-Cantero, Álvaro and Wu, Charley M},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/zhou2023dynamic.pdf}
}
Rubino, V., Dayan, P., & Wu, C. M. (2023). Biases towards compositionally simpler hypotheses are robust and unaffected by learning. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK.
@inproceedings{rubino2023biases,
title = {Biases towards compositionally simpler hypotheses are robust and unaffected by learning},
author = {Rubino, Valerio and Dayan, Peter and Wu, Charley M},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/rubino2023biases.pdf}
}
Moneta, N., Wu, C. M., Doeller, C. F., & Schuck, N. W. (2023). Reward morphs non-spatial cognitive maps in humans. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK.
@inproceedings{moneta2023reward,
title = {Reward morphs non-spatial cognitive maps in humans},
author = {Moneta, Nir and Wu, Charley M and Doeller, Christian F and Schuck, Nicolas W},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/moneta2023reward.pdf}
}
Xiong, Y., Moneta, N., Bányai, M., & Wu, C. M. (2023). Selective memory for reward-relevant features is modulated by expertise during reward learning. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK.
@inproceedings{xiong2023selective,
title = {Selective memory for reward-relevant features is modulated by expertise during reward learning},
author = {Xiong, Yirong and Moneta, Nir and Bányai, Mihály and Wu, Charley M},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/xiong2023selective.pdf}
}
Brändle, F., Wu, C. M., & Schulz, E. (2023). Learning progress and uncompensated rewards as motivational drivers of engagement. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK.
@inproceedings{braendle2023learning,
title = {Learning progress and uncompensated rewards as motivational drivers of engagement},
author = {Brändle, Franziska and Wu, Charley M and Schulz, Eric},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/braendle2023learning.pdf}
}
Witt, A., Vasama, J., Vélez, N., & Wu, C. M. (2023). Playing to win or playing to learn? Human performance in a social card game task. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK.
@inproceedings{witt2023playing,
title = {Playing to win or playing to learn? Human performance in a social card game task},
author = {Witt, Alexandra and Vasama, Joel and Vélez, Natalia and Wu, Charley M},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/witt2023playing.pdf}
}
Hamidi, M., Bányai, M., & Wu, C. M. (2023). One bottleneck is not enough. In L. Hunt, C. Summerfield, T. Konkle, E. Fedorenko, & T. Naselaris (Eds.), Proceedings of the 2023 Conference on Cognitive Computational Neuroscience. Oxford, UK.
@inproceedings{hamidi2023one,
title = {One bottleneck is not enough},
author = {Hamidi, Mani and Bányai, Mihály and Wu, Charley M},
year = {2023},
keywords = {published},
booktitle = {{Proceedings of the 2023 Conference on Cognitive Computational Neuroscience}},
editor = {Hunt, L. and Summerfield, C and Konkle, T. and Fedorenko, E. and Naselaris, T},
address = {{Oxford, UK}},
pdf = {https://charleywu.github.io/downloads/hamidi2023one.pdf}
}
Collins, R. N., Mandel, D. R., Karvetski, C. W., Wu, C. M., & Nelson, J. D. (2023). The Wisdom of the Coherent: Improving Correspondence with Coherence-Weighted Aggregation. Decision. https://doi.org/10.1037/dec0000211
@article{collins2023wisdom,
title = {The Wisdom of the Coherent: Improving Correspondence with Coherence-Weighted Aggregation},
journal = {Decision},
doi = {10.1037/dec0000211},
keywords = {published},
preprint = {https://psyarxiv.com/fmnty/},
author = {Collins, Robert N and Mandel, David R and Karvetski, Christopher W and Wu, Charley M and Nelson, Jonathan D},
year = {2023},
code = {https://osf.io/46fdm/},
pdf = {https://charleywu.github.io/downloads/collins2023wisdom.pdf}
}
Witt, A., Toyokawa, W., Lala, K., Gaissmaier, W., & Wu, C. M. (2023). Social learning with a grain of salt. In M. Goldwater, F. Anggoro, B. Hayes, & D. Ong (Eds.), Proceedings of the 45th Annual Conference of the Cognitive Science Society. Sydney, Australia: Cognitive Science Society. https://doi.org/10.31234/osf.io/c3fuq
@inproceedings{witt2023social,
title = {Social learning with a grain of salt},
author = {Witt, Alexandra and Toyokawa, Wataru and Lala, Kevin and Gaissmaier, Wolfgang and Wu, Charley M},
year = {2023},
keywords = {published},
doi = {10.31234/osf.io/c3fuq},
booktitle = {{Proceedings of the 45th Annual Conference of the Cognitive Science Society}},
publisher = {{Cognitive Science Society}},
preprint = {https://psyarxiv.com/c3fuq/},
editor = {Goldwater, M. and Anggoro, F. and Hayes, B. and Ong, D.},
address = {{Sydney, Australia}},
pdf = {https://charleywu.github.io/downloads/witt2023social.pdf}
}
Giron, A. P., Ciranka, S., Schulz, E., van den Bos, W., Ruggeri, A., Meder, B., & Wu, C. M. (2023). Developmental changes in exploration resemble stochastic optimization. Nature Human Behaviour. https://doi.org/10.1038/s41562-023-01662-1
@article{giron2023developmental,
title = {Developmental changes in exploration resemble stochastic optimization},
preprint = {psyarxiv.com/9f4k3},
journal = {Nature Human Behaviour},
author = {Giron, Anna P and Ciranka, Simon and Schulz, Eric and van den Bos, Wouter and Ruggeri, Azzurra and Meder, Björn and Wu, Charley M},
year = {2023},
keywords = {published},
code = {https://github.com/AnnaGiron/developmental_trajectory},
pdf = {https://charleywu.github.io/downloads/giron2023developmental.pdf},
doi = {10.1038/s41562-023-01662-1},
supp = {https://charleywu.github.io/downloads/giron2023developmentalSI.pdf}
}
2022
Vélez, N., Wu, C. M., & Cushman, F. A. (2022). Representational exchange in social learning: Blurring the lines between the ritual and instrumental. Behavioral and Brain Sciences, 45, e271. https://doi.org/10.1017/S0140525X22001339
@article{velez2022representational,
title = {Representational exchange in social learning: Blurring the lines between the ritual and instrumental},
volume = {45},
doi = {10.1017/S0140525X22001339},
journal = {Behavioral and Brain Sciences},
publisher = {Cambridge University Press},
keywords = {published},
author = {Vélez, Natalia and Wu, Charley M. and Cushman, Fiery A.},
year = {2022},
pdf = {https://charleywu.github.io/downloads/velez2022representational.pdf},
pages = {e271}
}
Ludwig, T., Wu, C. M., & Schulz, E. (2022). Connecting Exploration, Generalization, and Planning in Correlated Trees. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society. Toronto, Canada: Cognitive Science Society. https://doi.org/10.31234/osf.io/72wda
@inproceedings{ludwig2022connecting,
author = {Ludwig, Tobias and Wu, Charley M and Schulz, Eric},
title = {Connecting Exploration, Generalization, and Planning in Correlated Trees},
editor = {Culbertson, J. and Perfors, A. and Rabagliati, H. and Ramenzoni, V.},
booktitle = {{Proceedings of the 44th Annual Conference of the Cognitive Science Society}},
year = {2022},
publisher = {{Cognitive Science Society}},
address = {{Toronto, Canada}},
keywords = {published},
pdf = {https://charleywu.github.io/downloads/ludwig2022connecting.pdf},
code = {https://github.com/cpilab/correlated-trees},
doi = {10.31234/osf.io/72wda}
}
Wu, C. M., Vélez, N., & Cushman, F. A. (2022). Representational exchange in human social learning: Balancing efficiency and flexibility. In I. C. Dezza, E. Schulz, & C. M. Wu (Eds.), The Drive for Knowledge: The Science of Human Information-Seeking. Cambridge: Cambridge University Press.
@incollection{wu2022representational,
author = {Wu, Charley M and V{\'e}lez, Natalia and Cushman, Fiery A},
title = {{Representational exchange in human social learning: Balancing efficiency and flexibility}},
year = {2022},
keywords = {published},
preprint = {https://psyarxiv.com/rm52c},
pdf = {https://charleywu.github.io/downloads/wu2022representational.pdf},
editor = {Dezza, Irene Cogliati and Schulz, Eric and Wu, Charley M},
booktitle = {{The Drive for Knowledge: The Science of Human Information-Seeking}},
publisher = {{Cambridge University Press}},
address = {Cambridge}
}
Cogliati Dezza, I., Schulz, E., & Wu, C. M. (Eds.). (2022). The Drive for Knowledge: The Science of Human Information-Seeking. Cambridge University Press. https://doi.org/10.1017/9781009026949
@book{driveforknowledge,
title = {The Drive for Knowledge: The Science of Human Information-Seeking},
editor = {Cogliati Dezza, Irene and Schulz, Eric and Wu, Charley M},
year = {2022},
keywords = {published},
location = {Cambridge},
doi = {10.1017/9781009026949},
publisher = {Cambridge University Press},
pdf = {https://charleywu.github.io/downloads/driveforknowledge.pdf},
password = {knowledge},
website = {https://www.cambridge.org/core/books/drive-for-knowledge/B7D7B75B7C1021D2F90089CC1B4C1DBF}
}
Wu, C. M., Schulz, E., Pleskac, T. J., & Speekenbrink, M. (2022). Time pressure changes how people explore and respond to uncertainty. Scientific Reports, 12, 1–14. https://doi.org/10.1038/s41598-022-07901-1
@article{wu2022time,
title = {Time pressure changes how people explore and respond to uncertainty},
author = {Wu, Charley M and Schulz, Eric and Pleskac, Timothy J and Speekenbrink, Maarten},
year = {2022},
keywords = {published},
preprint = {https://psyarxiv.com/dsw7q},
doi = {10.1038/s41598-022-07901-1},
journal = {{Scientific Reports}},
volume = {12},
paper = {4122},
pages = {1--14},
pdf = {https://charleywu.github.io/downloads/wu2022time.pdf},
code = {https://osf.io/v4dua/},
supp = {https://charleywu.github.io/downloads/wu2022timeSI.pdf}
}
Ciranka, S., Linde-Domingo, J., Padezhki, I., Wicharz, C., Wu, C. M., & Spitzer, B. (2022). Asymmetric learning facilitates human inference of transitive relations. Nature Human Behaviour. https://doi.org/10.1038/s41562-021-01263-w
@article{ciranka2022asymmetric,
author = {Ciranka, Simon and Linde-Domingo, Juan and Padezhki, Ivan and Wicharz, Clara and Wu, Charley M and Spitzer, Bernhard},
title = {Asymmetric learning facilitates human inference of transitive relations},
year = {2022},
doi = {10.1038/s41562-021-01263-w},
keywords = {published},
preprint = {https://www.biorxiv.org/content/10.1101/2<IP_ADDRESS>7766v2.full.pdf+html},
journal = {Nature Human Behaviour},
code = {https://arc-git.mpib-berlin.mpg.de/ti/asymm},
pdf = {https://charleywu.github.io/downloads/ciranka2022asymmetric.pdf},
supp = {https://charleywu.github.io/downloads/ciranka2022asymmetricSI.pdf}
}
2021
Wu, C. M., Ho, M. K., Kahl, B., Leuker, C., Meder, B., & Kurvers, R. H. J. M. (2021). Specialization and selective social attention establishes the balance between individual and social learning. In T. Fitch, C. Lamm, H. Leder, & K. Teßmar-Raible (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society (pp. 1921–1927). Vienna, Austria: Cognitive Science Society. https://doi.org/10.1101/2<IP_ADDRESS>9553
@inproceedings{wu2021specialization,
author = {Wu, Charley M and Ho, Mark K and Kahl, Benjamin and Leuker, Christina and Meder, Bj{\"o}rn and Kurvers, Ralf HJM},
title = {Specialization and selective social attention establishes the balance between individual and social learning},
editor = {Fitch, T. and Lamm, C. and Leder, H. and Teßmar-Raible, K.},
booktitle = {{Proceedings of the 43rd Annual Conference of the Cognitive Science Society}},
year = {2021},
keywords = {published},
pages = {1921-1927},
publisher = {{Cognitive Science Society}},
address = {{Vienna, Austria}},
pdf = {https://charleywu.github.io/downloads/wu2021specialization.pdf},
preprint = {https://www.biorxiv.org/content/10.1101/2<IP_ADDRESS>9553v2.full.pdf+html},
doi = {10.1101/2<IP_ADDRESS>9553}
}
Humaidan, D., Otte, S., Gumbsch, C., Wu, C. M., & Butz, M. V. (2021). Latent Event-Predictive Encodings through Counterfactual Regularization. In T. Fitch, C. Lamm, H. Leder, & K. Teßmar-Raible (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society (pp. 1726–1731). Vienna, Austria: Cognitive Science Society.
@inproceedings{humaidan2021latent,
author = {Humaidan, Dania and Otte, Sebastian and Gumbsch, Christian and Wu, Charley M and Butz, Martin V},
title = {Latent Event-Predictive Encodings through Counterfactual Regularization},
editor = {Fitch, T. and Lamm, C. and Leder, H. and Teßmar-Raible, K.},
booktitle = {{Proceedings of the 43rd Annual Conference of the Cognitive Science Society}},
year = {2021},
keywords = {published},
pages = {1726-1731},
publisher = {{Cognitive Science Society}},
address = {{Vienna, Austria}},
eprint = {2105.05894},
preprint = {https://arxiv.org/abs/2105.05894},
pdf = {https://charleywu.github.io/downloads/humaidan2021latent.pdf}
}
Wu, C. M., Schulz, E., & Gershman, S. J. (2021). Inference and search on graph-structured spaces. Computational Brain & Behavior, 4, 125–147. https://doi.org/10.1007/s42113-020-00091-x
@article{wu2021inference,
author = {Wu, Charley M and Schulz, Eric and Gershman, Samuel J},
title = {Inference and search on graph-structured spaces},
year = {2021},
volume = {4},
keywords = {published},
pages = {125--147},
doi = {10.1007/s42113-020-00091-x},
preprint = {https://www.biorxiv.org/content/10.1101/2<IP_ADDRESS>1399v2.full.pdf},
code = {https://github.com/charleywu/graphInference},
journal = {Computational Brain \& Behavior},
pdf = {https://charleywu.github.io/downloads/wu2021inference.pdf}
}
Meder, B., Wu, C. M., Schulz, E., & Ruggeri, A. (2021). Development of directed and random exploration in children. Developmental Science, 24(4), e13095. https://doi.org/10.1111/desc.13095
@article{meder2021development,
title = {Development of directed and random exploration in children},
author = {Meder, Bj{\"o}rn and Wu, Charley M and Schulz, Eric and Ruggeri, Azzurra},
year = {2021},
volume = {24},
number = {4},
pages = {e13095},
keywords = {published},
journal = {Developmental Science},
preprint = {https://psyarxiv.com/7zhxv/},
code = {https://osf.io/eq2bk/?view_only=fed4735fa15a4f3d8dd56db385b845b1},
pdf = {https://charleywu.github.io/downloads/meder2021development.pdf},
doi = {10.1111/desc.13095},
supp = {https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2Fdesc.13095&file=desc13095-sup-0001-DataS1-S2.pdf}
}
Zuberer, A., Kucyi, A., Yamashita, A., Wu, C. M., Walter, M., Valera, E. M., & Esterman, M. (2021). Integration and segregation across large-scale intrinsic brain networks as a marker of sustained attention and task-unrelated thought. NeuroImage, 229, 117610. https://doi.org/10.1016/j.neuroimage.2020.117610
@article{zuberer2021integration,
title = {Integration and segregation across large-scale intrinsic brain networks as a marker of sustained attention and task-unrelated thought},
author = {Zuberer, Agnieszka and Kucyi, Aaron and Yamashita, Ayumu and Wu, Charley M and Walter, Martin and Valera, Eve M and Esterman, Michael},
journal = {NeuroImage},
year = {2021},
code = {https://osf.io/6b83r/},
volume = {229},
pages = {117610},
doi = {10.1016/j.neuroimage.2020.117610},
pdf = {https://charleywu.github.io/downloads/zuberer2021integration.pdf},
keywords = {published}
}
2020
Wu, C. M., Schulz, E., Garvert, M. M., Meder, B., & Schuck, N. W. (2020). Similarities and differences in spatial and non-spatial cognitive maps. PLOS Computational Biology, 16, 1–28. https://doi.org/10.1371/journal.pcbi.1008149
@article{wu2020similarities,
author = {Wu, Charley M and Schulz, Eric and Garvert, Mona M and Meder, Bj{\"o}rn and Schuck, Nicolas W},
title = {Similarities and differences in spatial and non-spatial cognitive maps},
elocation-id = {2<IP_ADDRESS>4556},
year = {2020},
keywords = {published},
month = sep,
volume = {16},
pages = {1--28},
publisher = {Cold Spring Harbor Laboratory},
preprint = {https://www.biorxiv.org/content/10.1101/2<IP_ADDRESS>4556v3.full.pdf},
code = {https://github.com/charleywu/cognitivemaps},
journal = {PLOS Computational Biology},
pdf = {https://charleywu.github.io/downloads/wu2020similarities.pdf},
doi = {10.1371/journal.pcbi.1008149},
supp = {https://charleywu.github.io/downloads/wu2020similaritiesSI.pdf}
}
Wu, C. M., Vélez, N., Ho, M. K., & Goldstone, R. L. (2020). Cognition, Collectives, and Human Culture. In S. Denison, M. Mack, Y. Xu, & B. C. Armstrong (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 3–4). Austin, TX: Cognitive Science Society.
@inproceedings{wu2020cognition,
author = {Wu, Charley M and V{\'e}lez, Natalia and Ho, Mark K and Goldstone, Robert L},
title = {Cognition, Collectives, and Human Culture},
year = {2020},
editor = {Denison, Stephanie and Mack, Michael and Xu, Yang and Armstrong, Blair C.},
keywords = {published},
website = {https://cognitioncollectivesandculture.github.io/},
booktitle = {{Proceedings of the 42nd Annual Conference of the Cognitive Science Society}},
publisher = {{Cognitive Science Society}},
address = {{Austin, TX}},
pages = {3--4},
pdf = {https://charleywu.github.io/downloads/wu2020cognition.pdf},
link = {https://cognitivesciencesociety.org/cogsci20/papers/0002/0002.pdf}
}
Brändle, F., Wu, C. M., & Schulz, E. (2020). What are we curious about? Trends in Cognitive Science. https://doi.org/10.1016/j.tics.2020.05.010
@article{braendle2020curiosity,
author = {Br{\"a}ndle, Franziska and Wu, Charley M and Schulz, Eric},
title = {What are we curious about?},
year = {2020},
journal = {Trends in Cognitive Science},
keywords = {published},
preprint = {https://psyarxiv.com/y2835/},
doi = {10.1016/j.tics.2020.05.010},
code = {https://github.com/ericschulz/curiositysim},
pdf = {https://charleywu.github.io/downloads/braendle2020curiosity.pdf}
}
2019
Schulz, E., Wu, C. M., Ruggeri, A., & Meder, B. (2019). Searching for rewards like a child means less generalization and more directed exploration. Psychological Science, 30(11), 1561–1572. https://doi.org/10.1177/0956797619863663
@article{schulz2019searching,
title = {Searching for rewards like a child means less generalization and more directed exploration},
author = {Schulz, Eric and Wu, Charley M and Ruggeri, Azzurra and Meder, Bj{\"o}rn},
journal = {Psychological Science},
year = {2019},
volume = {30},
number = {11},
pages = {1561-1572},
keywords = {published},
preprint = {https://www.biorxiv.org/content/early/2018/09/13/327593},
code = {https://github.com/ericschulz/kwg},
pdf = {https://charleywu.github.io/downloads/schulz2018searching.pdf},
doi = {10.1177/0956797619863663},
supp = {https://charleywu.github.io/downloads/schulz2018searchingSI.pdf}
}
Wu, C. M., Schulz, E., & Gershman, S. J. (2019). Searching for rewards in graph-structured spaces. In Proceedings of the 2019 Conference on Cognitive Computational Neuroscience. https://doi.org/10.32470/CCN.2019.1041-0
@inproceedings{wu2019searching,
author = {Wu, Charley M and Schulz, Eric and Gershman, Samuel J},
title = {Searching for rewards in graph-structured spaces},
keywords = {published},
year = {2019},
booktitle = {{Proceedings of the 2019 Conference on Cognitive Computational Neuroscience}},
pdf = {https://charleywu.github.io/downloads/wu2019searching.pdf},
code = {https://github.com/charleywu/graphInference},
doi = {10.32470/CCN.2019.1041-0}
}
Wu, C. M. (2019). Guided by generalization and uncertainty: A theory of human learning and exploration (PhD thesis). Humboldt-Universität zu Berlin, Berlin, Germany. https://doi.org/10.18452/20383
@phdthesis{wu2019PhDThesis,
author = {Wu, Charley M},
title = {Guided by generalization and uncertainty: A theory of human learning and exploration},
school = {Humboldt-Universität zu Berlin},
year = {2019},
doi = {10.18452/20383},
address = {Berlin, Germany},
pdf = {https://charleywu.github.io/downloads/wu2019PhDThesis.pdf}
}
Analytis, P. P., Wu, C. M., & Gelastopoulos, A. (2019). Make-or-break: chasing risky goals or settling for safe rewards? Cognitive Science, 43, e12743. https://doi.org/10.1111/cogs.12743
@article{analytis2019make,
title = {Make-or-break: chasing risky goals or settling for safe rewards?},
author = {Analytis, Pantelis P and Wu, Charley M and Gelastopoulos, Alexandros},
year = {2019},
volume = {43},
pages = {e12743},
doi = {10.1111/cogs.12743},
journal = {Cognitive Science},
keywords = {published},
code = {https://osf.io/p2vur/},
preprint = {https://psyarxiv.com/4gzfd/},
pdf = {https://charleywu.github.io/downloads/analytis2019make.pdf},
supp = {https://charleywu.github.io/downloads/analytis2019makeSI.pdf}
}
Wu, C. M., Schulz, E., Gerbaulet, K., Pleskac, T. J., & Speekenbrink, M. (2019). Under pressure: The influence of time limits on human exploration. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 1219–1225). Montreal, QB: Cognitive Science Society.
@inproceedings{wu2019under,
title = {{Under pressure: The influence of time limits on human exploration}},
author = {Wu, Charley M and Schulz, Eric and Gerbaulet, Kimberly and Pleskac, Timothy J and Speekenbrink, Maarten},
editor = {Goel, A.K. and Seifert, C.M. and Freksa, C.},
booktitle = {{Proceedings of the 41st Annual Conference of the Cognitive Science Society}},
keywords = {published},
year = {2019},
pages = {1219–-1225},
publisher = {{Cognitive Science Society}},
address = {{Montreal, QB}},
link = {https://mindmodeling.org/cogsci2019/papers/0222/0222.pdf},
preprint = {https://doi.org/10.31234/osf.io/tsxq9},
pdf = {https://charleywu.github.io/downloads/wu2019under.pdf}
}
Wu, C. M., Schulz, E., & Gershman, S. J. (2019). Generalization as diffusion: human function learning on graphs. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 3122–3128). Montreal, QB: Cognitive Science Society.
@inproceedings{wu2019generalization,
author = {Wu, Charley M and Schulz, Eric and Gershman, Samuel J},
editor = {Goel, A.K. and Seifert, C.M. and Freksa, C.},
title = {Generalization as diffusion: human function learning on graphs},
keywords = {published},
year = {2019},
publisher = {{Cognitive Science Society}},
address = {{Montreal, QB}},
pages = {3122–-3128},
link = {https://mindmodeling.org/cogsci2019/papers/0525/0525.pdf},
booktitle = {{Proceedings of the 41st Annual Conference of the Cognitive Science Society}},
preprint = {https://www.biorxiv.org/content/early/2019/02/03/538934},
code = {https://github.com/charleywu/graphInference},
pdf = {https://charleywu.github.io/downloads/wu2019generalization.pdf}
}
Tump, A. N., Wu, C. M., Bouhlel, I., & Goldstone, R. L. (2019). The Evolutionary Dynamics of Cooperation in Collective Search. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 883–889). Montreal, QB: Cognitive Science Society.
@inproceedings{tump2019evolutionary,
author = {Tump, Alan Novaes and Wu, Charley M and Bouhlel, Imen and Goldstone, Robert L},
editor = {Goel, A.K. and Seifert, C.M. and Freksa, C.},
title = {The Evolutionary Dynamics of Cooperation in Collective Search},
keywords = {published},
year = {2019},
pages = {883–-889},
publisher = {{Cognitive Science Society}},
address = {{Montreal, QB}},
booktitle = {{Proceedings of the 41st Annual Conference of the Cognitive Science Society}},
preprint = {https://www.biorxiv.org/content/early/2019/02/01/538447},
link = {https://mindmodeling.org/cogsci2019/papers/0166/0166.pdf},
pdf = {https://charleywu.github.io/downloads/tump2019evolutionary.pdf},
code = {https://github.com/alantump/adaptiveSharingEvolution}
}
2018
Wu, C. M., Schulz, E., Speekenbrink, M., Nelson, J. D., & Meder, B. (2018). Generalization guides human exploration in vast decision spaces. Nature Human Behaviour, 2, 915–924. https://doi.org/10.1038/s41562-018-0467-4
@article{wu2018exploration,
title = {Generalization guides human exploration in vast decision spaces},
author = {Wu, Charley M and Schulz, Eric and Speekenbrink, Maarten and Nelson, Jonathan D and Meder, Bj{\"o}rn},
journal = {Nature Human Behaviour},
year = {2018},
keywords = {published},
doi = {10.1038/s41562-018-0467-4},
volume = {2},
pages = {915–-924},
preprint = {https://www.biorxiv.org/content/early/2018/09/25/171371},
code = {https://github.com/charleywu/gridsearch},
pdf = {https://charleywu.github.io/downloads/wu2018exploration.pdf},
supp = {https://charleywu.github.io/downloads/wu2018explorationSI.pdf}
}
Schulz, E., Wu, C. M., Huys, Q. J. M., Krause, A., & Speekenbrink, M. (2018). Generalization and search in risky environments. Cognitive Science, 42, 2592–2620. https://doi.org/10.1111/cogs.12695
@article{schulz2018generalization,
title = {Generalization and search in risky environments},
author = {Schulz, Eric and Wu, Charley M and Huys, Quentin JM and Krause, Andreas and Speekenbrink, Maarten},
journal = {Cognitive Science},
year = {2018},
volume = {42},
pages = {2592--2620},
doi = {10.1111/cogs.12695},
keywords = {published},
preprint = {https://www.biorxiv.org/content/early/2018/05/14/227322},
pdf = {https://charleywu.github.io/downloads/schulz2018generalization.pdf}
}
Bouhlel, I., Wu, C. M., Hanaki, N., & Goldstone, R. L. (2018). Sharing is not erring: Pseudo-reciprocity in collective search. In T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 156–161). Austin, TX: Cognitive Science Society.
@inproceedings{bouhlel2018sharing,
title = {Sharing is not erring: Pseudo-reciprocity in collective search},
author = {Bouhlel, Imen and Wu, Charley M and Hanaki, Nobuyuki and Goldstone, Robert L},
booktitle = {{Proceedings of the 40th Annual Conference of the Cognitive Science Society}},
editor = {Rogers, T. T. and Rau, M. and Zhu, X. and Kalish, C. W.},
shorttitle = {{CogSci}},
publisher = {{Cognitive Science Society}},
address = {{Austin, TX}},
pages = {156--161},
year = {2018},
keywords = {published},
link = {https://www.mindmodeling.org/cogsci2018/papers/0050/0050.pdf},
code = {https://github.com/charleywu/adaptiveSharingSimulations},
pdf = {https://charleywu.github.io/downloads/bouhlel2018sharing.pdf}
}
Wu, C. M., Schulz, E., Garvert, M. M., Meder, B., & Schuck, N. W. (2018). Connecting conceptual and spatial search via a model of generalization. In T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 1183–1188). Austin, TX: Cognitive Science Society.
@inproceedings{wu2018connecting,
title = {Connecting conceptual and spatial search via a model of generalization},
author = {Wu, Charley M and Schulz, Eric and Garvert, Mona M and Meder, Bj{\"o}rn and Schuck, Nicolas W},
booktitle = {{Proceedings of the 40th Annual Conference of the Cognitive Science Society}},
editor = {Rogers, T. T. and Rau, M. and Zhu, X. and Kalish, C. W.},
shorttitle = {{CogSci}},
publisher = {{Cognitive Science Society}},
address = {{Austin, TX}},
pages = {1183--1188},
year = {2018},
keywords = {published},
link = {https://www.mindmodeling.org/cogsci2018/papers/0232/0232.pdf},
pdf = {https://charleywu.github.io/downloads/wu2018connecting.pdf}
}
2017
Wu, C. M., Schulz, E., Speekenbrink, M., Nelson, J. D., & Meder, B. (2017). Mapping the unknown: The spatially correlated multi-armed bandit. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.), Proceedings of the 39th Annual Meeting of the Cognitive Science Society (pp. 1357–1362). Austin, TX: Cognitive Science Society.
@inproceedings{wu2017mapping,
title = {Mapping the unknown: The spatially correlated multi-armed bandit},
author = {Wu, Charley M and Schulz, Eric and Speekenbrink, Maarten and Nelson, Jonathan D and Meder, Bj{\"o}rn},
editor = {Gunzelmann, Glenn and Howes, Andrew and Tenbrink, Thora and Davelaar, Eddy J.},
booktitle = {{Proceedings of the 39th Annual Meeting of the Cognitive Science Society}},
shorttitle = {{CogSci}},
publisher = {{Cognitive Science Society}},
address = {{Austin, TX}},
pages = {1357--1362},
year = {2017},
keywords = {published},
link = {https://mindmodeling.org/cogsci2017/papers/0260/paper0260.pdf},
code = {https://github.com/charleywu/gridsearch},
pdf = {https://charleywu.github.io/downloads/wu2017mapping.pdf}
}
Wu, C. M., Meder, B., Filimon, F., & Nelson, J. D. (2017). Asking better questions: How presentation formats influence information search. Journal of Experimental Psychology: Learning, Memory, and Cognition, 8, 1274–1297. https://doi.org/10.1037/xlm0000374
@article{wu2017asking,
title = {Asking better questions: How presentation formats influence information search},
author = {Wu, Charley M and Meder, Bj{\"o}rn and Filimon, Flavia and Nelson, Jonathan D.},
journal = {Journal of Experimental Psychology: Learning, Memory, and Cognition},
volume = {8},
pages = {1274--1297},
year = {2017},
keywords = {published},
doi = {10.1037/xlm0000374},
code = {https://github.com/charleywu/AskingBetterQuestions},
pdf = {https://charleywu.github.io/downloads/wu2017asking.pdf}
}
2016
Barkoczi, D., Analytis, P. P., & Wu, C. M. (2016). Collective search on rugged landscapes: a crossenvironmental analysis. In A. Papafragou, D. Grodner, D. Mirman, & J. C. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society (pp. 918–923). Austin, TX: Cognitive Science Society.
@inproceedings{barkoczi2016collective,
title = {Collective search on rugged landscapes: a crossenvironmental analysis},
author = {Barkoczi, Daniel and Analytis, Pantelis P and Wu, Charley M},
booktitle = {{Proceedings of the 38th Annual Conference of the Cognitive Science Society}},
shorttitle = {{CogSci}},
publisher = {{Cognitive Science Society}},
address = {{Austin, TX}},
year = {2016},
editor = {Papafragou, A and Grodner, D and Mirman, D and Trueswell, J.C},
pages = {918--923},
keywords = {published},
link = {https://www.mindmodeling.org/cogsci2016/papers/0168/paper0168.pdf},
pdf = {https://charleywu.github.io/downloads/barkoczi2016collective.pdf},
code = {https://github.com/dnlbrkc/collective_search}
}


| 007:007 Khan | : |
Then surely, We shall narrate unto them (their whole story) with knowledge, and indeed We were not absent. |
| 007:007 Maulana | : |
Then surely We shall relate to them with knowledge, and We are never absent. |
| 007:007 Pickthal | : |
Then verily We shall narrate unto them (the event) with knowledge, for We were not absent (when it came to pass). |
| 007:007 Rashad | : |
We will inform them authoritatively, for we were never absent. |
| 007:007 Sarwar | : |
We will tell them with absolute certainty (what they had done) for We had never been absent from them (during their lifetime). |
| 007:007 Shakir | : |
Then most certainly We will relate to them with knowledge, and We were not absent. |
| 007:007 Sherali | : |
The will WE certainly relate to them their deeds with knowledge, for WE were never absent. |
| 007:007 Yusufali | : |
And verily, We shall recount their whole story with knowledge, for We were never absent (at any time or place). |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > علمه جلّ شأنه Pillars of Islam> Islamic> Oneness of Allah> His Glory's Knowledge الإيمان > اليوم الآخر > العرض على الميزان واستلام الكتاب Faith> The Hereafter> The Exposure on the Balance (of Justice) and the Reception of the Record
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


fun addComponent(possibleComponent: PossibleComponent): Job
Get configuration and templates needed for the creation of a Component based on the given PossibleComponent.
Return Job related to this process.


Chapter 2 Organize
If you are using R to write for larger projects, including research for academic papers and theses, you should start putting some thought into how you organize your research files, including raw data, cleaned data, coding scripts for analysis, and output like paper drafts and figures. So far, you may have run much of your analysis within a single R script or R Markdown file. Often, any associated data are within the same working directory as your script or R Markdown file, but the files for one project are not separated from files for other projects. As you move to larger projects, this kind of set-up won’t work as well. Instead, you’ll want to start keeping all materials for a project in a single and exclusive directory.
2.1 R Projects
RStudio allows you to create “Projects”, which help with this
organization. An R Project is very simple—it’s just a file directory, with an
extra subdirectory added to the directory with settings to remind RStudio about for the project. This directory is
saved as a dot file, so you probably won’t be able to see it
listed if you look at the directory contents using your computer’s file finder. If you’d like
to see the listing (or delete it by hand, although you likely won’t ever need to
do this), check the settings for your file finder, and see if you have the option
to show all files. Alternatively, you can use the “list” command with the “all” option
(ls -a
) at a Bash shell to view all files and subdirectories in a directory.
Advantages of setting a directory to be an R Project are:
- Automatically uses the directory as your current working directory when you open the project.
- Coordinates well with git version control and GitHub repository system.
- Opens a “Files” window for navigating project files in an RStudio pane when you open the project.
You can either create an R Project as a new directory or convert an existing directory into an R Project. To do either, in RStudio go to the “File” menu and select “New Project”. You’ll then have the option to either create a new directory that’s an R Project or to search through your computer’s files to find an existing directory to make into an R Project.
Once you’ve created an R Project, you can open it in RStudio; opening an R Project will set the project’s directory as your working directory, opening a “Files” window with all the subdirectories and files in the project directory and allowing you to run code with relative filenames from the project’s directory. If you share the R Project with someone else,2 he or she will also be able to open the R project using RStudio.
One benefit of R Projects is that it is very easy to initialize them as git repositories.
A later section (“Track”) will go over how to initialize and use git version control for
R Projects. You will also definitely want to use an R Project for any R package you write,
as this will introduce a lot of functionality that “plays well” with the devtools
package
to make it easier to write, build, and publish an R package.
2.2 Directory organization
My desk at work is very messy, with lots of paper printouts piled up. But I do keep my project directories very tidy, and I strongly recommend the practice.
This goes beyond “well-organized”, which we just covered (putting all project files in one directory, using subdirectories to divide up files in a project, using consistent names for project file directories, etc.). Keeping a project directory “tidy” means having only one version of each file. Often, as you develop a project, especially when collaborators are involved, you can end up with many versions of a file. For example, you may have the draft of a journal article’s text saved in some versions with the file name reflecting the date of the draft (“draft_may_12.docx”), some versions that include the initials of people who reviewed it (“paper_draft_ba_rp_mb2.docx”), and so on.
This type of organization—having multiple versions of project files, with the
file names meant to help you keep track of them—results in very cluttered and
hard-to-manage project directories. Instead, at any given moment, each of your
project directories should have only one version of each project file. You
certainly won’t want to lose information from edits and changes to the files
along the way, so it’s smart to use some type of version control
system[version control system. Software for tracking changes to software
projects. Some researchers who use a lot of coding also use this software to
track their projects One well-known example is git, but there are other
version control systems as well.] on each project directory. This will allow you
to track the changes you’ve made to each file and to go back and revisit the
file at any moment in the project’s history. A later section of this booklet
(“Track”) will describe how you can use git
for version control for R
projects.
2.2.1 Avoiding repetition
One key to efficient organization is to avoid repetition.3 In practice, it often happens that you’re using the same code across several projects. For example, say you have some code that calculates the apparent temperature from air temperature and some measure of dewpoint temperature. If you have organized your project files to have one directory per paper, with all the associated code for a paper within the project’s directory, then you may find you’re often copying and pasting the code to calculate apparent temperature into different directories.
This situation makes for a tricky balance—you want to organize your files and have a separate directory for each project, but cutting and pasting code can be a recide for disaster. Each time you move the code, there’s a chance for an error to slip in. Also, what if you want to make a change in the code? Say you hear about a better algorithm for calculating apparent temperature? You will either need to go through all of your projects that use that code and change the code everywhere, or you will have to settle for different projects using different algorithms.
This means it’s time to start thinking about writing your own R package. You do not have to publish every R package you write—it’s fine to just use it yourself and not share it more widely. Regardless, a package is the right place to store related code that you use often, as well as documentation (and possibly tests) to go with that code. A later section of this booklet (“Package”) will go over a bit about how to write your own R packages, as well as references for learning more about package development.
2.3 Learn more
Reproducible Research with R and R Studio is an excellent book with advice on improving the reproducibility of projects using R, including academic research projects.
A few good articles have come out recently that describe project organization within different scientific fields (e.g., biology, archaeology, ecology). It’s worth searching Google Scholar for “reproducible research in R” and your own or a closely related research field.


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--- layout: post title: Tandy Hills Park date: 2014-10-26 16:19:06.000000000 -05:00 categories: - Personal tags: - fort worth - hiking - liswamírë - photo - tandy hills - texas - vanyánan status: publish type: post published: true author: image: /assets/images/img_0250.jpg ---
Hiking with Liswamírë in Tandy Hills Park with the dogs. You can see downtown Fort Worth in the distance, but other than that, it's just forested north Texas forest and grass land.


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Hello!I am Shobha Jain. I am an ordinary home maker who loves her work and her family. I also love cooking and serving food. I enjoy cooking vegetarian cuisines of different cultures and regions around the world.


Sanctuary California Gives Mexican Gang Member to ICE for Deportation
The State of California honored an immigration detainer placed on a previously deported violent Mexican national. The criminal alien returned to the U.S. after being deported in 1999 and received a conviction for voluntary manslaughter in 2003.
by Bob.Price.Texas, Bob PriceU.S. Immigration and Customs Enforcement (ICE) Enforcement and Removal Operations (ERO) officers lodged an immigration detainer on 44-year-old Luis Gonzalez-Valencia, a Mexican national and confirmed gang member. California authorities honored the detainer and turned the prisoner over to ERO officers at the Calipatria State Prison. ERO officers verified the criminal alien’s identity and placed him in custody for removal proceedings.
“We are grateful for the cooperation of the California State Department of Corrections honoring the lodged detainer for this violent felon; however, ICE continues to be challenged by California’s protection of the criminal alien populations within their correctional system, San Diego Deputy Field Office Director Jamison Matuszewski said in a written statement. “These challenges are further enhanced when California’s legislative body devalues criminal convictions specifically inhibiting federal immigration entities from using those convictions for removal or federal prosecution.”
A California court convicted Gonzalez-Valencia in 2003 for involuntary manslaughter. The court handed down an 11-year prison sentence which he served at the Calipatria State Prison. ICE records show the criminal alien had a prior deportation in 1999 after two burglary convictions in 1994 and 1996. He returned to the U.S. illegal sometime after his 1999 deportation and later killed someone resulting in the conviction for voluntary manslaughter.
ERO officers took Gonzalez-Valencia into custody on November 22 and immediately reinstated his order of removal at the ERO office in El Centro, California. Officers removed him to Mexico that same day.
Bob Price serves as associate editor and senior political news contributor for the Breitbart Border team. He is an original member of the Breitbart Texas team. Follow him on Twitter @BobPriceBBTX and Facebook .


{% extends "base/app-page-content.html" %} {% load staticfiles %} {% block title %}How to Get Involved{% endblock title %} {% block header %}{% include "base/header.html" with h1="How to Get Involved" %}{% endblock header %} {% block app-content %}
Your donation is tax-deductible and will be put towards many possible expenses including tools, food for volunteers, procuring plants, building materials, etc. Thank you so much, it helps as we are a volunteer-run organization.
This link will sign you up for our mailing list which provides notice of upcoming work parties, events, as well as the monthly newsletter.
Head over to Facebook and like our page. It helps further our reach and is a great way to become part of the community.
Come to a work party and engage in activities to help develop and maintain the Beacon Food Forest. ALL ages and skill levels are welcome. Lunch will be served. Bring your gloves and head over because we want to see you, rain or shine. Orientations for new volunteers are offered at every work party. Check the calendar for the next work party.
During summer we have sunset labs, maintenance and harvest of the Helix farm plot, wetland restoration and various other tasks as they come up. Come by a site development meeting (see calendar) or email the volunteer coordinator for more information.
The Beacon Food Forest is one giant P-Patch (garden). Sign up to tend your own plot. Volunteer hours as well as a small fee are required to maintain a P-Patch. Sign up is done through the city of Seattle.
Want to learn the workings of the Beacon Food Forest and help out the organization? Writing grants, holding classes, leading tasks, volunteer coordination, or simply just being a part of an amazing community of volunteers who do their best. ALL skill levels are welcome. Check the calendar for the next new volunteer orientation.
Our volunteer coordinators are here to help. Don't know where to start? Send an email and start asking questions.
Dream big, and bring your art proposal to our Community Outreach Coordinator. We relish art and that which brings harmony. Get yourself a grant and see that vision come to life at the Beacon Food Forest!
We invite organizations or large groups to come help on site. Email our group visits coordinator to get matched up with some volunteers that will help coordinate tasks and planning for the big day out of the office.
The Beacon Food Forest is global. People from Taiwan, Ukraine, France and many others have visited to understand just how the magic happened here. Free tours are offered during our monthly work parties. See the calendar for dates. If you are a big group and would like your own tour, email the group visits coordinator. Kindly consider making a donation to support our volunteer-run organization.


Storyboard StudyRightWithAssignmentsStoryboard
1. (start situation/pre-condition) Karli enters the Study-Right University in the math room. Karli has no credits yet and still a motivation of 214.
University university = new University() .withName("StudyRight"); Student karli = university.createStudents() .withId("4242") .withName("Karli"); Assignment matrixMult = new Assignment() .withContent("Matrix Multiplication") .withPoints(5); Assignment series = new Assignment() .withContent("Series") .withPoints(6); Assignment a3 = new Assignment() .withContent("Integrals") .withPoints(8); Room mathRoom = university.createRooms() .withName("senate") .withTopic("math") .withCredits(17) .withStudents(karli) .withAssignments(matrixMult, series, a3); Room artsRoom = university.createRooms() .withName("7522") .withTopic("arts") .withCredits(16) .withDoors(mathRoom); Room sportsRoom = university.createRooms() .withName("gymnasium") .withTopic("sports") .withCredits(25) .withDoors(mathRoom, artsRoom); Room examRoom = university.createRooms() .withName("The End") .withTopic("exam") .withCredits(0) .withDoors(sportsRoom, artsRoom); Room softwareEngineering = university.createRooms() .withName("7422") .withTopic("Software Engineering") .withCredits(42) .withDoors(artsRoom, examRoom);
2. Karli does assignment a1 on Matrix Multiplication and earns 5 points
(general rule: the student earns always full points for doing an assignment).
Karli's motivation is reduced by 5 points to now 209.
karli.setAssignmentPoints(karli.getAssignmentPoints() + matrixMult.getPoints()); karli.withDone(matrixMult);
3. Karli does assignment a2 on Series and earns another 6 points.
Thus Karli has 11 points now. Motivation is reduced to 203.
karli.setAssignmentPoints(karli.getAssignmentPoints() + series.getPoints()); karli.withDone(series);
4. Karli does the third assignment on Integrals, earns
another 8 points and thus Karli has now 19 points and a motivation of 195.
karli.setAssignmentPoints(karli.getAssignmentPoints() + a3.getPoints()); karli.withDone(a3);
5. Since 19 points are more than the 17 points required
for the 17 math credits, Karli hands the points in and earns the credits
and has his assignmnet points reset to 0.
(General rule: if the points earned by the assignments are higher or equal than
the credit points, the credit points will be awarded to the student.)
if (karli.getAssignmentPoints() >= mathRoom.getCredits()) { karli.setCredits(karli.getCredits() + mathRoom.getCredits()); karli.setAssignmentPoints(0); }
6. (end situation/post-condition) Karli has completed the math topic and moves to sports.
Check: Karli's credits: 17 actual 17
Check: Karli's assignment points: 0 actual 0
Check: Number of students: 1 actual 1


--- layout: page title: About header-img: "img/about-bg.png" ---
Got an econ degree and then realized I didn't like it.


 It includes a padded 17” laptop sleeve secured with a button closure. There are 8 interior pockets for organizing your wallet, phone, Metrocard, tablet, messy tech cables and lip balm. A detachable key leash lets you pull out your keys with ease. Travel comfortably and hands-free with an adjustable messenger shoulder strap. Or use the back sleeve for sliding your tote over luggage.
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JSC SDK Meeting Management Test App
Config and credentials
Host:Port
Organization alias
User name
Password
Upload config
Login
Logout
Fetch by period: date from
Fetch by period: date to
Fetch by date
Fetch by Id
Fetch starts in (minutes)
Fetch by status:
ABNORMAL_STOPPED
CANCELLED
FINISHED
IN_SESSION
NOT_START
SCHEDULE_FAILED
START_FAILED
STOP_FAILED
Fetch Past Meetings
Detailed
Fetch by period
Fetch by date
Fetch by Id
Fetch by status
Fetch ongoing meetings
Fetch starts in
Create meeting
Meeting List
Log
Create meeting
Subject
Start time
End time
Location Id
Access PIN
Moderator PIN
User Id
Member Id
Number
Service Template Id
Service prefix
ConferenceId
Description
Early time
Time zone Id
Duration
Allow Streaming:
ON
OFF
DISABLED
UNDEFINED
Streaming status:
ON
OFF
DISABLED
UNDEFINED
Priority:
DELAY
LOCAL
UNSPECIFIED
Status:
ABNORMAL_STOPPED
CANCELLED
FINISHED
IN_SESSION
NOT_START
SCHEDULE_FAILED
START_FAILED
STOP_FAILED
Block dial in
Auto extend
Waiting room
One time PIN required
Test only
Sending notification
Recording meeting when start
Attendees
add_circle_outline
Daily
Number Of Every Day
Every Week Day
Weekly
Number Of Every Week
Days Of Week
Monthly
Number Of Every Month
Day Of Month
Day Of Number Of Every Month
RecurrenceEnd
End Of Occurrences
By
Advanced properties
Duration After Left
Max Participants
Termination Condition:
NORMAL
AFTER_ALL_PARTIES_LEFT
AFTER_HOST_LEFT
Broadcast setting
Thumbnail
Public
Questions And Answers Enabled
Subject
Pin
Thumbnail Mime Type
Profile
Description
User Ids
Moderator PIN
Program Id
Access Mode:
PRIVATE
LIMITED_USERS
ALL_AUTHED_USERS
ALL_USERS
The meeting should have
Number
,
Start time
and
Duration
The meeting has minimum required fields.
Delete meeting
Save meeting
Close
Please wait...
Operation failed
Failure details
No results found
There are no meetings matching your search request
Time:
-
Subject:
Description:
expand_more
delete
First name
Last name
User Id
Email
Terminal Id
Terminal Name
Terminal Number
Protocol
maxBandwidth
maxISDNBandwidth
Area Code
Country Code
Telephone Number
Organizer
Host
Restricted mode
threeG
Voice only
needOnMaster
autoDialIn


Deploy an Intrusion Detection System (IDS) appliance in your cloud. The IDS may be installed within your Virtual Private Cloud (VPC), or at your premises' VPC end point. The preferred location is within the Amazon VPC.
An IDS monitors your cloud environment and alerts you about detected intrusions. The IDS logs give you important information about API access such as:
With this information you can update IDS settings and policies. The IDS is also important for monitoring and managing changes, and detecting AWS-specific environment changes.
Install IDS. Choose an IDS with the required features. Traditional rack-based and virtual IDS's are available. Deploy the IDS in your VPC using documentation supplied with the system.
Create Security Audit Role. Create a named security audit role (such as secaudit) with IAM. Make this a role with cross-account access. Enter the ID of the AWS account. Set the access permissions to Read Only for policies and configurations that will be monitored. Credentials are not required. Your policy establishes who or what can assume this role.
Create Security Role Policy.
Configure Write Once Storage. Configure versioning on a bucket with the console or AWS SDKs. Optionally, add MFA Delete for an additional security layer by requiring MFA on the bucket.
Turn On AWS CloudTrail. When you enable CloudTrail, create a new S3 bucket. Name the bucket. If you already have a centralized write-only store, that can be used.
Detect Unauthorized Credentials. Manual steps to investigate access and credentials for public, non-public, and cross-account users can be performed with the console. Go to the dashboard and select a user. View the user access keys, date and time for security.


Open the modal!
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A Julia set explorer ( julia.m) version 01-Jan-17
Author: Paul Mennen
Email<EMAIL_ADDRESS>Introduction
Julia set images are traditionally generated by repeated application of the
equation z = z2 + c (z and c
are complex). The color of the image is determined by the number of iterations it
takes for the magnitude of z to grow larger than some fixed value (2.0 for this program).
The Mandelbrot set uses the same equation and the same color assignment method,
but differs in how the equation is initialized.
It's easy to find dozens of Julia set graphing
programs in nearly every language (including Matlab), so I wouldn't fault you if you were
skeptical of the need for yet another application with this purpose. However my goal
was to show how fun it is to explore Julia sets and to make this application more
compelling than any similar application out there.
I'll let you be the judge of how well I have met this challenge.
Program initialization
When julia.m starts, it creates two images which we refer to as the left and right images
(or sometimes the "opposite" image to refer to the right image when we are editing the left
and vice versa). Initially both images show the traditional Mandelbrot set (i.e.
with the exponent equal to two). The images will look identical (i.e. the same axis limits,
the same color map, the same color depth, and the same resolution), however after taking any
action, the two images will no longer be the same as in the screen capture shown here.
There is nothing special about the left or right image. Any action we can take on the right
image can also be taken on the left. However you will soon see the benefits of having two
images to play with.
(Click on this screen capture to view it in its full resolution.)
The Julia set exponent
There are two controls related to selecting the Julia set. The first control, labeled "exp",
is located near the lower left corner of each image and determines the exponent (e) used in
the recurrence relation z = ze + c
which determines the color of each point on the image.
Although 2 is the most common exponent used for Julia sets, other integer exponents are
also used (the generalized Julia set). The easiest way to change the exponent is to use
the edit object's "auto-increment" mode (i.e. click on the right side of the exponent to
increase its value by one and click on the left side to decrease its value). The image will
immediately update to reflect the new exponent. Non-integer values may also be used, which
often produce even wilder images. The easiest way to enter a non-integer value is to right
click on the exponent and then type in whatever value you want. Sometimes it is useful to
be able to change the auto-increment value from one to some other value. Suppose you want
to change this from 1 to 0.1. Simply right-click on the edit object and type in "0.1i".
After you press return, the auto-increment value will change to the entered value. (You
can think of the "i" at the end as referring to "increment".) This is especially useful
for creating animated Julia sets because holding down the mouse button continues to modify
the exponent, which often yields eye-popping animations. With the default settings the
display update rate will probably be too slow for this purpose, but below you will find
methods described to increase the update rate. This method of changing the auto-increment
value, and continuous incrementing can be used with any edit pseudo object and will also
be useful for creating animations by changing the Julia constant (described next).
The Julia set constant
The second control related to selecting the Julia set is a popup menu located near the upper
left corner of each image (which initially appears as the yellow label "Mandelbrot").
Assuming the exponent is at its default value (2), this is the popup that will appear when
you click on that label. For the first selection of the popup (Mandelbrot) z is initialized
to zero and c is chosen to correspond to the position we are determining the color for.
For the remaining selections (Julia sets), z is initialized to the value corresponding to the
pixel we are determining the color for, and then the recurrence relation is computed using
one of the 14 constants shown in this popup menu. These 14 constants were chosen somewhat
haphazardly although with the goal of creating interesting images. After one of the constants
is chosen, the real and complex components of the constant are placed in edit pseudo objects
so they may be modified easily. The default autoincrement amount is set to .01 but this may
be modified by entering an increment value as described above. And as before, Julia set
animations may be created by holding down the mouse to slide the real or imaginary components
of the constant around the Julia set landscape while looking for interesting territory.
If you change the Julia set exponent from 2 to any other value, the list of constants in
the popup menu shrink from 14 to 4. (This is to simplify the task of placing the constants
in interesting territory.) Notice that the four choices given continue to change as you
change the exponent. They change in an attempt to remain in interesting territory and this
generally is successful for relatively small (i.e. less than 10) whole number exponents.
This is also at least somewhat successful for small fractional exponents.
Instead of opening up the Julia set constant popup with a left click, you will probably
find it more convenient to use the right mouse button instead. This will scroll thru the
various Julia set constants (updating the image and the edit boxes for the real and imaginary
parts of the constant) without having to open up the pseudo popup menu. After the last constant
in the menu is selected, the next right click will cycle you back to the Mandelbrot set.
Zooming the image
To appreciate the beauty and complexity of Julia sets you need to zoom into ever smaller
regions of the set. The flexible and intuitive zoom features of this application are what
makes it fun to use and set it apart from the many dozens of Julia set graphing programs
you can find. There are many ways to zoom an image (see the
Zooming and panning
section), but the easiest method for this application is to double click the mouse while
holding the mouse button down after the 2nd click. Then drag the mouse while continuing to
hold down the mouse button. As you do this, a zoom box will be drawn - expanding in size
as you drag the mouse. Even during this zoom box drawing operation, the opposite image will
display the portion of the data inside the zoom box, behaving much like a magnifying glass.
The smaller the zoom box, the higher the magnification and the more pixilated the image
will appear. However once you let go of the mouse button, the magnified region is recomputed
to the currently specified resolution (1 bit per pixel by default) at which point you will
be able to see details in the image that were not visible before. If you find the double
click and drag method awkward, you might try clicking both mouse buttons at the same time
and holding them down while you drag. (My testing indicates that this works when you are
using Matlab version 2014a or any earlier version, but not in more recent versions.) If you
don't mind using the keyboard for this, another method requiring less dexterity is to hold
the keyboard shift button down while dragging the mouse from the first corner to the
opposite corner of the zoom box. (No double clicking required). This method works with all
versions of Matlab.
Moving the zoom box
You can change the zoom box using one or more of these methods:
- Reposition the zoom box (without changing its size) by grabbing the midpoint of
any one of the four zoom box edges and dragging it with the mouse. Note that as you
drag the image on the opposite side will again behave like a moving magnifying glass, with
a pixelated image. The magnified image will be recomputed (thus removing undesired pixelated
effects) as soon as you release the mouse button after the repositioning operation.
- Resize the zoom box by grabbing any one of the four zoom box corners. Again, as mentioned
above, the magnified area recomputes as soon as you release the mouse button after the resize
operation.
- If you want the any of the zoom box coordinates to be a particular exact value simply
type it into one of the edit boxes below the graph (xmin/xmax on the left and ymin/ymax
on the right). As soon as you hit "enter" after typing a new value, the position of the
corresponding edge of the zoom box will change to reflect the new entry and the opposite
image will update (with full resolution) to show the area associated with the new zoom
box region. If you want to enter all four zoom box coordinates, it is easiest to start
with the xmin value because after entering the xmin value you can use tab (instead of
enter) to enter the new value and proceed to the xmax value (then ymin, then ymax)
without having to interrupt your typing to select the next edit box.
Magnification
Usually after the zoom window is drawn and you see the full detail in the magnified region
you see something in the magnified region that you want to see in yet more detail. Use the
same method to draw a zoom box again. In this manner you can bounce back and forth between
the left and right images, getting higher and higher magnifications on smaller regions of
the Julia set. Notice that below the plot, the magnification is shown compared with the
original scaling (i.e. when the Julia set was first plotted). In the example shown here,
the magnification is 4.09e7 which means that the area being displayed is 40 million times
smaller than the original image. The edit boxes on the left show that the x values shown
in the displayed region are between .31787 and .31825 (approximately). More digits are
displayed than typical for these edit boxes because of the extreme magnification often used
for plotting Julia sets. Similarly the y axis limits are shown in the two right hand edit boxes.
Right below the plot, the number of times the recurrence relation was computed to generate the
image is shown (289 iterations in this example). You will notice that as you zoom in to higher
magnifications, more iterations are computed since this is necessary to achieve the same
detail level. The magnification readout can also be used as a zoom control. Simply left-click
on it to zoom out by a factor of 100 (in area), or zoom out all the way to the original axis
limits by right-clicking instead. You can also experiment with panning the image (just click
and drag the mouse inside the image) or do that with the right mouse button instead to Zoom
in or out (without using a zoom box). Left or right-clicking the Zout tag will zoom out or in
by a small amount (doubling or halving the area), although usually you will find you want the
large zoom factors available with the other methods.
The sync check box
The method described above for zooming to higher and higher magnifications (by alternating
between the left and right images) is probably the easiest way; however, you may want to zoom
into a region on one image without changing the image on the opposite side. For instance you
may be interested in comparing two different regions of a Julia set or comparing the same region of
two different Julia sets. In such situations you should uncheck the sync checkbox (just
to the left of the "Magnification: 4.09e7" indicator in the above screen capture). This changes
the plot from the "automatic sync" mode to the "manual sync" mode. To prevent automatic
synchronization in both directions, you must uncheck the sync checkbox under both image plots.
Once in manual sync mode, after drawing a zoom box you will see no changes to the image right
away except for the existence of the zoom box. You can follow the drawing of a zoom box with
one or more of these actions:
- Reposition or resize the zoom box by any of the three methods mentioned above.
- Left-click anywhere in the plot area (not near the zoom box) to expand the plot to
so that it shows just the region inside the zoom box. The Julia set will be recomputed
to match the requested resolution.
- Right-click anywhere in the plot area to cancel the zoom operation (and remove
the zoom box from the display).
Even in manual sync mode you sometimes may want to synchronize the two displays. This is done
by RIGHT-clicking on the sync checkbox (which will not toggle the checkmark like the left click
does). Right-clicking on the sync box of under the left hand image when a zoom box is visible
in the left hand image will copy the data inside the zoom box to the right hand image and then
recompute the right image so that it is displayed in the full requested resolution. If you do
the same thing when no zoom box is visible, then the entire left hand image is copied to the
right image. You might expect that the right and left images would look exactly the same after
such an operation, and in fact this is usually the case. However there are two display parameters
(the depth parameter and the pixels per bit parameter, both discussed below) that are not
transferred during the sync operations. This means that one side may show more or less detail
than the other side after a sync operation.
The pixels/bit parameter and the depth parameter
When you are using the edit box auto-increment feature to cycle thru small changes in the Julia
set exponent or the Julia set constant a fast update rate is essential to finding interesting
regions of the Julia sets. The update rate is probably going to be too slow for this purpose when
using the default settings, however there are three things you can do to speed this up. The first
is to make the figure window smaller. You may have already tried expanding the figure to full
screen mode, and indeed this does produce large images with great detail. However the update rate
will be slower since it increases proportionally with the number of pixels. Shrinking the figure
will conversely speed up the update rate, although if you shrink the figure too much, the controls
will become too small to use easily.
The second way you can speed up the update rate is to reduce the number of times the recursion
formula is executed. This is done using the depth parameter which can be changed using the edit
box just above the menubox near the lower left corner of each image. When you select a new Julia
set (by changing the Julia set exponent or constant) a default depth (usually 50) is chosen which
produces a pleasing image for that particular set. Try setting the depth to 5 and notice that the display updates 10 times faster. Then notice as you click the mouse on the different
colors of the image the Z value (which appears just above the sync checkbox) will range from zero
to five and the image will include no more than six colors. Z=0 indicates that the recurrence
relation never exceeded a magnitude of 2, and Z=5 indicates that the recurrence relation exceeded
a magnitude of 2 on the 5th iteration. The number of iterations only matches the depth setting
when the magnification is equal to one. As you zoom in, the iterations automatically increase.
(The number of iterations doubles every time the magnification is increased
by a factor of 1000.)
The last (and strongest) influence you can make on the update rate is the pixels/bit setting.
The default setting is "one" indicating that the color for each pixel of the image is determined
independently. Thus for a 500 by 500 pixel image the recurrence relation must be repeated
250 thousand times for each iteration. However if you change the pixels/bit setting (just above
the image) to 3 (for example) you reduce the computations by a factor of 9 since each 3x3 block
of pixels will be assigned the same color. The resulting blocky image is not as pleasing, but it
is still fine for finding the interesting regions where you want to focus your interest. You can
use higher settings (lower resolutions) as well, but 3 is probably as high as you will need to
go to get acceptable update rates. In fact a setting of 2 will often be sufficiently fast as well.
The color map selectors
If you click on one of the vertical color bars to the left of each image, a new mapping between
the Z values and the image colors will be selected. There are 10 different color maps and after
selecting the 10th one, clicking again will select the first one again. Also right-clicking will
cycle thru the color maps in the reverse order. Most of the color maps are designed to make it
easy for you to see the general shape of the surface contour (i.e. high vs low areas) based on
the image color. However two of the color maps (colorcube and lines) are designed to allow you
to see as many level transitions as possible, and the general shape of the contour is difficult
to discern (and in fact impossible with the lines color map). Clicking on the color bar next to
the left image only changes the color map for that image, so this makes it easy to compare two
identical Julia sets colored with different maps. However if you are using a version of Matlab
older than version 2014b you will find that changing the left color map automatically changes
the right color map (and vice versa). This is because those versions only allow one color map
at a time to be associated with any figure window.
Initial help text
When this application first starts, some very basic help text appears in the left image (white
characters). Although it can't really substitute for the full help information in this document,
it may be enough to get you started. As soon as you click in the plot area or make any changes
to the fractal parameters, the help text disappears so it doesn't interfere with viewing the fractals.
Copyright © 2017
Paul Mennen


We all think it whenever we see "Cloud", now you can update your webpages to have clown instead of cloud. Just enter the URL of your page to have it fixed.


Channel
Rxmq channel class
Constructor Summary
| Public Constructor | ||
| public |
constructor(plugins: Array): void Represents a new Rxmq channel. |
Member Summary
| Private Members | ||
| private |
[prop]: * Hide from esdoc |
|
| private |
Channel bus |
|
| private |
channelStream: Rx.Observable Permanent channel bus stream as Rx.Observable |
|
| private |
Instances of subjects |
|
| private |
Internal set of utilities |
Method Summary
| Public Methods | ||
| public |
Get an Rx.Observable for specific set of topics |
|
| public |
registerPlugin(plugin: Object): void Channel plugin registration |
|
| public |
Do a request that will be replied into returned Rx.AsyncSubject Alias for '.request()' that uses single object as params |
|
| public |
subject(name: String): EndlessSubject Returns EndlessSubject representing given topic |
Public Constructors
Private Members
Public Methods
public observe(name: String): Rx.Observable source
Get an Rx.Observable for specific set of topics
Params:
| Name | Type | Attribute | Description |
| name | String | Topic name / pattern |
Return:
| Rx.Observable | Rx.Observable for given set of topics |
Example:
const channel = rxmq.channel('test');
channel.observe('test.topic')
.subscribe((res) => { // default Rx.Observable subscription
// handle results
});
public registerPlugin(plugin: Object): void source
Channel plugin registration
Params:
| Name | Type | Attribute | Description |
| plugin | Object | Plugin object to apply |
Return:
| void |
public request(options: Object): Rx.AsyncSubject source
Do a request that will be replied into returned Rx.AsyncSubject Alias for '.request()' that uses single object as params
Return:
| Rx.AsyncSubject | AsyncSubject that will dispatch the response |
Example:
const channel = rxmq.channel('test');
channel.requestTo({
topic: 'test.topic',
data: 'test data',
}).subscribe((response) => { // default Rx.Observable subscription
// handle response
});
public subject(name: String): EndlessSubject source
Returns EndlessSubject representing given topic
Params:
| Name | Type | Attribute | Description |
| name | String | Topic name |
Example:
const channel = rxmq.channel('test');
const subject = channel.subject('test.topic');


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| DOSE: |
1 hit |
oral |
LSD |
(blotter / tab) |
Prior to April 09. I had never done a hallucinogen, and like many people I feared LSD. I had heard way to many stories...'I knew this guy who no this kid whose brother killed himself on it' you know those kinds of stories, and honestly believed in the fairy tale horrible experience that occurred on TV would occur in me. I was quite judging of the 'those' people who had tried Acid before. Overall I thought it was a sketchy Drug.
The past couple of months I have gone in a separate direction with my life. I had been using more like abusing marijuana for 2 years now, and had barely gone a week without it.  So in about January I changed alot of things. My diet changed cut out soda...refined sugar...junk food basically I lived off of rice and vegetables. I ate some meat at least 3 times a weak though but very little. I also moved out of my house which was HELL on earth and in to a trailer filled with people who loved me and desperately wanted me to do well.
So Ive spent since January extremely happy probably the happiest Ive been in years and living life for myself again.
Ok so thatís just some background on my mental state.
So it's a normal high school art room setting, Iím chillin working on a painting I turn to my favorite DD and ask him whats new on the scene he says 'acidí. I immediately shudder don't know what to say then it occurs to me, I NEED TO TRY THIS.
So I buy my $10 TAB which I later find out is expensive for ACID and then take it around 2:15 pm. I decided that I wouldn't tell anyone because of the stigma attached to it. So I felt fairly secretive about it.
(I FEEL RIPPED OFF)
I was still a little scared/anxious about taking it but understood that I was about to embark on something that I couldn't change my mind on once I had started. I understood that it was extremely counterproductive to be worried about it so I just let go of that emotion and took the tab.
I decided to document the trip in the form of a letter to my friend who was debating whether or not he wanted to try it. So here is the letter....
Dear P.
Iím sorry I couldn't stick around long enough to wait for you to get out of Drivers Ed. I am writing you this because that seems to be what I feel like doing right now.  The past hour has been a euphoric roller coaster climb. I just keep getting happier and happier. Every time I talk to the parental unit I cant stop smiling, she probably knows somethingís up but thatís ok. Iím not sketched out about her presence at all, itís actually really comforting to know that she is there.
3:00pm The visuals haven't come yet but I suspect they are on there way.
5:30pm I have no idea why people make such a big deal out of this.  Similar to when you're stoned like the 1st 15min of youre mourn high thatís what I've been feeling I just started to shake a little not violently but more like the shivering you get when you are cold. Right after I noticed the stove and floor blend into each other. Literally like in a blinder. The freaking TV is flickering not intensely but its flickering.
6:15pm Watching this war on TV is crazy. Iraq is a beautiful country. Its people are finally being liberated!  NO MORE SADDAM! I know what I feel right now doesnít even compare to how happy those people are.   Trow was right about not watching T.V. as soon as I turned it off the visuals took a hold of me. This would definitely be better for me at least if I was smokin weed. I get intensely focused. Only when you are intensely focused does the acid start to take effect. Probably why for some this is not a good idea to do. Had I realized this hours ago my 'TRIP' I love saying that would be a lot different. So No Horror stories. This papers starting to move up and down like its breathing. It's not scary though because if I just look away it stops.  The words on the paper started to move its doing it again. They move when Iím writing and focused. guess you would say this is not a bad trip at all. Iím sad that I waited so long before I understood how to see things.
8:11pm J.R. just called me. My favorite hippie.  I miss that kid so much. Its not worth it for me to even fight it. THIS is not scary at all. Easily you can make yourself not 'tripped out' If I let my mind wander fore even a second things are back to norm again. Could this be A DANGEROUS side EFFECT?  I HAVE RULED OUT ALL THE POSSIBLE DISTRACTIONS they are nothing more than distractions.
It is really easy to continue on with everyday activity almost easier than with WEED. The hallucinations take patience. In this fast paced world we live in where we want every fuckin' instantaneously acid's hallucinations do NOT configure into that way of thinking. The more I look for them or rather don't look for them, depending on which way you would prefer to look at life. In the same instance I realize this I realize other things too. To much thinking.  Lights are flickering in the background my eyes seem to never catch it though its just background junk. Think I am going to go outside.
(I wrote little side notes to myself so on the letter there are little purple sticky notes attached to certain places where I was having thoughts on top of thoughts.)
8:40pm I was out outside gazing up at the clouds pass the moon. Just as the trees started to open up and magnify the moonlight.  I ask myself why I am sitting here writing this in the dark, there is just enough light now for me to see that that I am not writing on top of words. Words on top of words would look pretty messed up. Even worse illegible which would defeat the purpose of me writing this to you. The paper shifts, the pen is writing what I am thinking I am not. The rearrangement of the words on this paper is interesting. REAL or NOT REAL? TO BE OR NOT TO BE? THAT BY GEORGE IS THE QUESTION.
If I had some weed right now I would be experiencing things alot differently. Why is it that I continue to want more out of these things. If I have learned anything it's that trips are what you make of them. If you stop fighting it which I have been for fear that this might turn into something BAD. (a prejudgment I had in my mind about ACID) If I could just free my mind.
* Ones hallucinations are just reality shifts. Whatís real and what's not real are clearly balanced. The 2nd reality comes only when I stop fighting it.*

I know that while I am writing this I am missing out on some HALL. the ones I am experiencing now. For instance my skin has continuously blended into my kitchen table, but only when I allow it to, I just watched the lines in the wood creep up my arm I became the table I had to look away and when I stopped looking it stopped. Brown skin brown table. Blending trying to become one again, out of fear I kept fighting it.

A current has just taken over my floor and caused it to move like the ocean. I am desiring for it to consume me. I want it to in a sense CAPTURE ME.
*I will miss this when its over. I am the ultimate escapist. Not only do I want to escape my reality as I know it but I want to get lost in it TO BE KIDNAPPED but it.
I HAVE CONTROL seemingly not what I wanted but its what I have. Iím thankful and unthankful at the same time. MY GLASS IS LITERALLY HALF EMPTY AND HALF FULL.
My heart starts to pound I am clearly uncomfortable with this thought. Why? Am I yearning to be out of control ? I just had a scary thought while watching the floor move. Would I steal for this? Would I beg T? to let me take one more TAB in school tomorrow and promise to pay him back later, when I got the money? I HAVE FOUND MY CRACK. I have never heard of acid being highly addictive.  (More For me that way HHAH)No but seriously there are alot of people I would not recommend this too. preferably people like myself with OBCUMP personalities. This is like nothing I have ever experienced before. IT IS NOT SCARY. Now I just want to do more. I just donít want this experience to end. Which was basically me writing for hours. My pen keeps disappearing in and out of the paper its hard in the dark or in the little moonlight that I have to tell if I am even writing at all.
Taking one HIT of ACiD was a good idea for the 1st time. It's just enough to allow you to make a decision about it. It's not to much so that I can't differentiate between the real and not real UNWILLINGLY <<
>. Its just enough to go in and out of my trip as I please.
 *NO WONDER PEOPLE THINK THEMSELVES TO BE GOD ON THIS STUFF, All you can relate to the experience is god or something unhuman unearthly, never before have I been able to think the thoughts I have had tonight or see the things that I see now GOD is a perfect explanation for it all.  * ITS JUST ABOUT UNDERSTANDING* Whether or not your beliefs are the same as you thought them to be before you tried ACID, while you were on it and while youíre off it. Its just about trying to make sense out of life.
That is what I am afraid of, but at the same time is the reason for me to even be doing this. I want my mind to be freed and for life to make some sense but it still not willing to embrace the change. Good or bad tripping on not its life.
I NEED TO GO BACK OUTSIDE. NO MORE WRITING FOR NOW.
10:15pm Before I go out though I have to write down this thought. Will I believe the fairy tale acid stories of things jumping out at you and trying to eat you? I am not going to be impressed by them anymore. I have finally done what I SWORE TO GOD WHAT I SWORE TO MYSELF AND OTHERS I would never do.  Am I to do this again or any type of hallucinogen. AM I being seriously mislead? IS THIS REALLY AS DANGEROUS AS PEOPLE (mainstream America) made it out to be. All I know is that I wouldn't recommend this to everyone? Small dose this isn't unsafe? Hell I didnít even notice I was on it while watching TV but had I smoked the endless amounts of KB I want to or think I want to this might have turned out very differently.
Now I am going to venture outside just me my puffy down jacket and my hacky sack. Playing hackysack underneath the moon and stars.
9:51 It no longer feels natural to write so much now SO I will stop.
* THIS WAS A VERY GOOD THING FOR ME TO DO*
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Before Change
import re
import sys
STDIN = codecs.getreader("utf-8")(sys.stdin)
STDOUT = codecs.getwriter("utf-8")(sys.stdout)
STDERR = codecs.getwriter("utf-8")(sys.stderr)
EITHER = re.compile(r"""
( [-()]
| [\u1000-\u109F]
After Change
import sys
STDIN = io.open(0, mode="rt", encoding="utf-8", closefd=False)
STDOUT = io.open(1, mode="wt", encoding="utf-8", closefd=False)
EITHER = re.compile(r"""
( [-()]
| [\u1000-\u109F]


PILOT
EXP:
GLOBAL RANKING:
KILLS
DEATHS
RATIO
LEVEL
SHIP
SPEED
HEALTH BONUS
+
DAMAGE BONUS
AREA
LATENCY
WORLD TARGETS
WORLD BULLETS
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Creator
N. Taylor Mullen
Designer
Jonah Sterling
Developer
David Fowler
Damian Edwards
Stephen Halter
SHOOTr
SIGNALr
K: D:


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