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martedì 28 maggio 2019

# gst: to create standing waves induced by mismatches

<< In work recently published (..), the mismatch of electronic momentum across domain walls (i.e., regions with a different orientation of the intrinsic electric dipole) is shown to create standing waves, even though there is no potential buildup across the domain wall. >>

Researchers demonstrate new properties of atomically thin ferroelectrics. University of Arkansas.  May 28, 2019

https://m.phys.org/news/2019-05-properties-atomically-thin-ferroelectrics.html  

Kai Chang, Brandon J. Miller, et al. Standing Waves Induced by Valley-Mismatched Domains in Ferroelectric SnTe Monolayers. Phys. Rev. Lett. 122, 206402 May 24, 2019.

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.122.206402   

lunedì 27 maggio 2019

# game: a pulsating, sadistic search for "disinformation", by John.

<< What this shows is that disinformation, which is ignorance of the truth, is simple to impose, even if logic denies it. What is even simpler is discovering a person’s ignorance set without imparting knowledge, >> John McAfee

Scott Thompson. John McAfee discusses the value of ignorance in new essay. May 25, 2019.

https://finance.yahoo.com/news/john-mcafee-discusses-value-ignorance-110005220.html

https://twitter.com/officialmcafee/status/1132321395243966464

Also

artists and machine intelligence interactions: the Ross' conjecture. Jun 13, 2016.

https://flashontrack.blogspot.com/2016/06/s-ai-artists-and-machine-intelligence.html

Charlie vs Donald (never boring with chaos and tit-for-tat theories). Jun 12, 2016.

https://flashontrack.blogspot.com/2016/06/s-gst-never-boring-with-chaos-and-tit.html

sabato 25 maggio 2019

# brain: negative emotional contagion and cognitive bias (in ravens, Corvus corax).

<< after witnessing a conspecific in a negative state, ravens perform in a negatively biased manner on a judgment task. >>

AA << findings thus suggest negative emotional contagion in ravens, and in turn advance our understanding of the evolution of empathy. >>

Jessie E. C. Adriaense, Jordan S. Martin, et al. Negative emotional contagion and cognitive bias in common ravens (Corvus corax). PNAS. first published  doi: 10.1073/pnas.1817066116 May 20, 2019.

https://www.pnas.org/content/early/2019/05/14/1817066116  

Bob Yirka. Researchers find evidence of negative emotional contagion in lab ravens. Phys.org. May 21, 2019.

https://phys.org/news/2019-05-evidence-negative-emotional-contagion-lab.amp

venerdì 24 maggio 2019

# phys: it could be used to completely remove all noise from a noisy channel

AA << have proposed a second level of quantization, in which both the information carriers and the channels can be in quantum superposition. In this new paradigm of communication, the information carriers can travel through multiple channels simultaneously. >>

AA << formulated a quantum communications model that can be used to compute the amount of information that can be reliably transmitted when using a given number of channels in a quantum superposition. (..) for certain types of noise, the superposition of channels, along with the ability to switch a channel with itself, could be used to completely remove all noise. This opens up the possibility of obtaining perfect quantum communication in a noisy channel. >>

Lisa Zyga. Physicists propose a second level of quantization for quantum Shannon theory. Phys.org  May 22, 2019.

https://m.phys.org/news/2019-05-physicists-quantization-quantum-shannon-theory.html  

Giulio Chiribella, Hler Kristjansson.
Quantum Shannon theory with superpositions of trajectories. Proceedings of the Royal Society A.   doi: 10.1098/rspa.2018.0903  May 8, 2019.

https://royalsocietypublishing.org/doi/full/10.1098/rspa.2018.0903  

giovedì 23 maggio 2019

# ai: apropos of black box approach in machine learning algorithms

<< A black box is a machine learning program that does not explain how it reaches its conclusions, either because it is too complicated for a human to understand or because its inner workings are proprietary. In response to concerns that these types of models may include unjust inner workings—such as racism—another growing trend is to create additional models to "explain" these black boxes. >>

<<  Even when so-called explanation models are created, (..) decision-makers should be opting for interpretable models, which are completely transparent and easily understood by its users. >>

Ken Kingery. Stop gambling with black box and explainable models on high-stakes decisions. Duke University.  May 14, 2019.

https://m.techxplore.com/news/2019-05-gambling-black-high-stakes-decisions.html  

Cynthia Rudin. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence. volume 1, pages 206–215 May 13, 2019

https://www.nature.com/articles/s42256-019-0048-x   

mercoledì 22 maggio 2019

# behav: intriguing wolves, prosociality among wolves (compared to dogs)

<<  Prosociality is important for initiating cooperation. (..) In a prosocial choice task, wolves acted prosocially to in-group partners; providing significantly more food to a pack-member compared to a control where the partner had no access to the food. Dogs did not. Additionally, wolves did not show a prosocial response to non-pack members, in line with previous research that social relationships are important for prosociality.  >>

Rachel Dale, Sylvain Palma-Jacinto, et al. Wolves, but not dogs, are prosocial in a touch screen task. PLoS ONE 14(5): e0215444. doi: 10.1371/journal.pone.0215444  May 1, 2019.

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0215444

Wolves more prosocial than pack dogs in touchscreen experiment. Findings support idea that dogs helping pack members is ancestral tendency, and not due to domestication. May 1, 2019.

https://www.eurekalert.org/pub_releases/2019-05/p-wmp042419.php

Also

'wolves'

https://flashontrack.blogspot.com/search?q=wolves

martedì 21 maggio 2019

# soc: computational socioeconomics, a brief manifesto.

AA << will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. >>

Jian Gao, Yi-Cheng Zhang, Tao Zhou.
Computational Socioeconomics. arXiv:1905.06166v1 [physics.soc-ph].  May 15, 2019.

https://arxiv.org/abs/1905.06166

download (free, ~11Mb):    https://arxiv.org/pdf/1905.06166