Public Articles
8,249 more reasons to use Authorea
Relatório 2 Detetive Ecológico
and 5 collaborators
Ferramentas do Detetive Ecológico: uso e avaliação de modelos com detecção imperfeita
Paulo Inácio de Knegt López de Prado
Instituto de Biociências, Universidade de São Paulo
Carlos Ernesto Candia-Gallardo, Pós-graduação em Ecologia IB–USP
Cristiane Honoran Millán, mestre em Ecologia
Gregório Menezes, consultor autônomo
Gustavo Mattos Accacio, consultor autônomo
Gustavo Requena, Pós-doutorado IB–USP
Leonardo Liberali Wedekin, Pós-doutorado IB–USP
Rodolpho Credo Rodrigues, Pós-graduação em Ecologia IB–USP
Melina de Souza Leite, Especialista em Laboratório, IB–USP
2013/19250-7 Auxílio Pesquisa - Regular
01/02/2014 a 31/01/2016
01/02/2015 a 31/10/2015
Radiative properties of ordered and disordered porous ceria particle clouds under solar irradiation
and 1 collaborator
We study the radiative behavior of particle clouds consisting of two types of highly porous spherical ceria particles under direct solar irradiation—one with a templated three-dimensionally ordered macroporous (3DOM) structure and the other with pores randomly located within the structure. Individual radiative properties—the scattering efficiency factor, absorption efficiency factor, and the scattering phase function—of the randomly porous particles are numerically predicted in this work for comparison against existing 3DOM data. Clouds of monodisperse particles with a spatially uniform particle density are studied for each case. Solutions are compared to results based on individual particle scattering properties obtained from an effective medium theory combined with Mie theory results. It is found that the high degree of order in 3DOM particles does not significantly change the radiative properties of the cloud. However *something interesting*.
Thesis: Machine Learning-based Indoor Localization for Micro Aerial Vehicles
\label{chap:introduction}
In the world of automation, micro aerial vehicles (MAVs) provide unprecedented perspectives for domestic and industrial applications. They can serve as mobile surveillance cameras, flexible transport platforms, or even as waiters in restaurants. However, indoor employment of these vehicles is still hindered by the lack of real-time positions estimates. The focus of this thesis is, thus, the development of accurate and fast indoor localization for MAVs combining computer vision and machine learning techniques.
How to Bring Science Publishing into the 21st Century
A new collaborative tool could revolutionize scientific authorship. Originally published by Scientific American
Welcome to Authorea!
Citing other papers is easy. Voilà: \cite{2012} or \cite{Holstein_2009}. Click on the cite
button in the toolbar to search articles and cite them. Authorea also comes with a powerful commenting system. Don’t agree that E = mc3?!? Highlight the text you want to discuss or click the comment button. Find out more about using Authorea on our help page.
The Night of the Shooting Stars
During the night of August 11th, a meteor shower called ’Perseids’ might put up a memorable show. After the moon sets, which occurs around 1:00 AM local time, it might be possible to see up to 200 ’shooting stars’ per hour. Below, what you need to know about this astronomical event.
Despite their name, shooting stars are actually small rocks (meteoroids) falling towards the Earth due to our planet’s gravitational attraction. As they move rapidly through the atmosphere, they reach very high temperatures due to friction with air particles. This makes them burn and become visible to the human eye. The trail they leave is called ’Meteor’. Due to their tiny size, they usually almost completely burn in a fraction of a second. In some very exceptional cases, large meteors can continue the hot descent and hit the ground. If they also survive the crash, they get promoted immediately to the ’meteorites’ class. Generally speaking a meteoroid producing a meteor needs to be at least as large as a marble to reach the Earth and eventually become a meteorite. Some Burning facts:
Average meteorite velocity: 30000 miles/hour (48000 km/h)
Max temperature: 3000 F (1650 C)
The Meteor Crater in Arizona was formed 50000 years ago by an object 160 feet (50 meters) across
... yes, impacts like the one that produced the Meteor Crater are extremely rare
Journal Of Structural Engineering Template
Tokenizing an arXiv.org article with LLaMaPUn
The Cornell preprint contains roughly a million scientific papers, making it a treasure trove for natural language processing (NLP) experiments.
However, a big difference from mainstream NLP corpora is the presence of mathematical formulas, citations and other language modalities specific to scientific discourse. A second, and in practice just as significant challenge is that the majority of documents are authored in LaTeX, making them very irregular for naive automated mining.
At the research group at Jacobs University we have invested a lot of work in trying to regularize the dataset and make it available for NLP research, which is a large topic in its own right. I wrote an entry-level blog post about that effort here.
In this blog post, I want to briefly introduce the newest incarnation of the NLP library for scientific documents, backed up by a running example of word tokenization on an average preprint from the dataset.
Have there been aliens? Will there be aliens?
The fact we are alive and pondering a vast Universe from spaceship Earth raises a number of fascinating questions. Astrophysicist are now asking why “here” and why “now”. What is the chance of life emerging around a star like the Sun, about 12-13 billion years after our Universe was born?
The SKV Algorithm as a Tool in Image Processing
The skv algorithm was introduced as a method of identifying onsets and offsets in a model of auditory signal processing \cite{Coath_2005} and it is also an integral part of a model of auditory feature extraction \cite{Denham_2005} \cite{Coath_2007}. It has been found to exhibit a range of desirable properties, as well as some features that make it biophysically plausible. The method has subsequently been used in a range of contexts including auditory salience detection \cite{Kovacs_2015}, beat tracking \cite{Coath_2009}, and studies of infant speech production \cite{Warlaumont_2016}.
It has also been shown that the important features of the skv response can be captured in the output of an artificial neural network \cite{Kovacs_2013}. These results demonstrate that the approach is suitable for parallel distributed programming and, possibly, other ’neuromorphic’ implementations.
The abbreviation skv when applied to auditory signals was derived from skewness over variable time, reflecting the measure of asymmetry (the skewness or third normalized moment) and the technique of varying the time window over which this value was calculated \cite{Coath_2005}. For image processing the v will stand instead for ’variable spatial frequency’, which also relates to the size of the window used.
VLASS Pilot Survey Design
and 5 collaborators
This document describes the design for the VLA Sky Survey (VLASS) Pilot Survey which will be carried out in the 27 May – 5 Sep 2016 time-frame.
Dear Social Media, Get DNA Chirality *Right*
and 1 collaborator
Welcome to Authorea!
Hey, welcome. Double click anywhere on the text to start writing. In addition to simple text you can also add text formatted in boldface, italic, and yes, math too: \(E = mc^{2}\)!
Add images by drag'n'drop or click on the "Insert Figure" button.
Linking Visualization and Understanding in Astronomy
This post accompanies a talk by the same name and author, presented at the 223rd Meeting of the American Astronomical Society, at 11:40 AM on January 6, 2014. Talk slides will be online after noon on January 6 at http://projects.iq.harvard.edu/seamlessastronomy/presentations.
In 1610, when Galileo pointed his small telescope at Jupiter, he drew sketches to record what he saw. After just a few nights of observing, he understood his sketches to be showing moons orbiting Jupiter. It was the visualization of Galileo's observations that led to his understanding of a clearly Sun-centered solar system, and to the revolution this understanding then caused. Similar stories can be found throughout the history of Astronomy, but visualization has never been so essential as it is today, when we find ourselves blessed with a larger wealth and diversity of data, per astronomer, than ever in the past.
In this talk, I will focus on how modern tools for interactive “linked-view” visualization can be used to gain insight. Linked views, which dynamically update all open graphical displays of a data set (e.g. multiple graphs, tables and/or images) in response to user selection, are particularly important in dealing with so-called “high-dimensional data.” These dimensions need not be spatial, even though, e.g. in the case of radio spectral-line cubes or optical IFU data), they often are. Instead, “dimensions” should be thought of as any measured attribute of an observation or a simulation (e.g. time, intensity, velocity, temperature, etc.). The best linked-view visualization tools allow users to explore relationships amongst all the dimensions of their data, and to weave statistical and algorithmic approaches into the visualization process in real time.
Particular tools and services will be highlighted in this talk, including: Glue (glueviz.org), the ADS All Sky Survey (adsass.org), WorldWide Telescope (worldwidetelescope.org), yt (yt-project.org), d3po (d3po.org), and a host of tools that can be interconnected via the SAMP message-passing architecture.
The talk will conclude with a discussion of future challenges, including the need to educate astronomers about the value of visualization and its relationship to astrostatistics, and the need for new technologies to enable humans to interact more effectively with large, high-dimensional data sets.
Example Article: Geoscientific Visualization in Authorea with iPython Notebooks
Ok, I can’t stand to try it out and test Authorea with a visualization I made for a former lab report. Let’s go.
At first, we have to create a Notebook file. I took the data and Python script that I made for the lab report and put it in a local folder called ipython. Using the terminal, I switched into this folder and called ipython notebook %matplotlib inline
. The latter argument is used to have my plot show up in ipython itself underneath the code cell that runs the plot. I also splitted up the code in smaller chunks and converted some of my code comments into Markdown cells. That makes it nice to read the Notebook and structures the code.
Afterwards I ran every code cell from top to bottom using the Shift + Enter keys. The plot the plot appearing under the last cell was then saved to the folder containing the Notebook file.
Ok, now I have some files containing my code (the Notebook file), the rendered plot image, and the raw data in an Excel Sheet.
To use the image in Authorea, I just need to upload it and reference it inside my latex document. But as a scientist standing for open research, I also want my colleagues and readers to be able to access the raw data and algorithms used to produce the plot, so I upload them, too.
So I created a folder inside my document structure in Authorea called depth-plot and put all files in it. Inside my structure.md file I referenced the image with the relative path and now it shows up at the corresponding position of the document structure (below this text). Because the image and the Notebook file are in the same folder, hovering over the image shows a “launch ipython” button, that anybody can use to open the Notebook inside the browser and play around with it.
Nice, isn’t it?
(At the moment, Notebook sessions opened inside the browser get killed automatically after 5 minutes. I think that’s due to the fact that Authorea is still quite new and should be seen as Beta software. If you want to have a closer look at the Notebooks, you still can download it and play around locally.)
LaTeX was not built for the web
One of the questions we get more often from our users at Authorea is:
Why is my LaTeX command not working?
The short answer to that is:
Because that LaTeX command was not intended for a webpage; it was intended for the printer. :(
The longer answer.
Authorea understands and renders markup languages such as Markdown, and LaTeX. But it does not rely on a compiler which takes TeX and spits out PDF. All the content created on Authorea is web-native. As we create more and more content on the web, we think that scholarly articles, too, should live on the web.
That said, we do enjoy and use LaTeX frequently at Authorea. This post for example, was written in LaTeX! Want to see? Let’s grab a pre-baked equation, for example this Fourier transform and render it below:
a \Leftrightarrow 2\pi a\sum\limits_{k = - \infty }^\infty
{\delta (\omega + 2\pi k)} ,( - \infty < n < \infty )
\begin{equation} a \Leftrightarrow 2\pi a\sum\limits_{k = - \infty }^\infty {\delta (\omega + 2\pi k)} ,( - \infty < n < \infty ) \end{equation}
We decided to support LaTeX from the very beginning, as it is the document preparation toolkit of choice for many (most?) researchers in the hard sciences. We think LaTeX is still the best programming language to tell a computer how to place text on a page. But the TeX project started pre-web, in 1978, and its scope and function are tightly linked to the printed page, not the webpage. Take, as an example a table definiton that begins with \begin{table}[ht]
. This table command instructs TeX to put the table in the page, here, where the table is declared (h
) AND at the top of the page (t
). The list of examples could go on and on — think of minipage environments, page margins, text width parameters... all LaTeX notation that does really not make sense for a webpage.
Is CSS the next LaTeX?.
What does the future hold for academic writing? We like to think that a few years from now we will format our research papers with the web version in mind, rather than the printed PDF. And we are not alone! LaTeX will very likely be used many years from now, but, we think, in a much more stripped-down, web-friendly incarnation, like the subset that Authorea currently supports. (We use some amazing tools like Pandoc and MathJax to convert between formats and render equations). Or maybe someday we will just format papers using CSS stylesheets?
The Fork Factor: an academic impact factor based on reuse.
and 1 collaborator
How is academic research evaluated? There are many different ways to determine the impact of scientific research. One of the oldest and best established measures is to look at the Impact Factor (IF) of the academic journal where the research has been published. The IF is simply the average number of citations to recent articles published in such an academic journal. The IF is important because the reputation of a journal is also used as a proxy to evaluate the relevance of past research performed by a scientist when s/he is applying to a new position or for funding. So, if you are a scientist who publishes in high-impact journals (the big names) you are more likely to get tenure or a research grant. Several criticisms have been made to the use and misuse of the IF. One of these is the policies that academic journal editors adopt to boost the IF of their journal (and get more ads), to the detriment of readers, writers and science at large. Unfortunately, these policies promote the publication of sensational claims by researchers who are in turn rewarded by funding agencies for publishing in high IF journals. This effect is broadly recognized by the scientific community and represents a conflict of interests, that in the long run increases public distrust in published data and slows down scientific discoveries. Scientific discoveries should instead foster new findings through the sharing of high quality scientific data, which feeds back into increasing the pace of scientific breakthroughs. It is apparent that the IF is a crucially deviated player in this situation. To resolve the conflict of interest, it is thus fundamental that funding agents (a major driving force in science) start complementing the IF with a better proxy for the relevance of publishing venues and, in turn, scientists’ work.
Research impact in the era of forking. A number of alternative metrics for evaluating academic impact are emerging. These include metrics to give scholars credit for sharing of raw science (like datasets and code), semantic publishing, and social media contribution, based not solely on citation but also on usage, social bookmarking, conversations. We, at Authorea, strongly believe that these alternative metrics should and will be a fundamental ingredient of how scholars are evaluated for funding in the future. In fact, Authorea already welcomes data, code, and raw science materials alongside its articles, and is built on an infrastructure (Git) that naturally poses as a framework for distributing, versioning, and tracking those materials. Git is a versioning control platform currently employed by developers for collaborating on source code, and its features perfectly fit the needs of most scientists as well. A versioning system, such as Authorea and GitHub, empowers forking of peer-reviewed research data, allowing a colleague of yours to further develop it in a new direction. Forking inherits the history of the work and preserves the value chain of science (i.e., who did what). In other words, forking in science means standing on the shoulder of giants (or soon to be giants) and is equivalent to citing someone else’s work but in a functional manner. Whether it is a “negative” result (we like to call it non-confirmatory result) or not, publishing your peer reviewed research in Authorea will promote forking of your data. (To learn how we plan to implement peer review in the system, please stay tuned for future posts on this blog.)
More forking, more impact, higher quality science. Obviously, the more of your research data are published, the higher are your chances that they will be forked and used as a basis for groundbreaking work, and in turn, the higher the interest in your work and your academic impact. Whether your projects are data-driven peer reviewed articles on Authorea discussing a new finding, raw datasets detailing some novel findings on Zenodo or Figshare, source code repositories hosted on Github presenting a new statistical package, every bit of your work that can be reused, will be forked and will give you credit. Do you want to do a favor to science? Publish also non-confirmatory results and help your scientific community to quickly spot bad science by publishing a dead end fork (Figure 1).
Authorea raises a seed round of investment.
We are very excited to announce that Authorea has recently raised its first round of funding for a total of $610k with a joint investment by ff Venture Capital and NY Angels!
ffVC is an institutional venture capital investor in seed-stage companies based in New York City. NY Angels is the largest and most active technology-focused angel investment organization on the East Coast.
This investment is important for Authorea on many levels.
First of all, we are solidifying and growing our team. We're hiring! If you are interested in making science better, you will enjoy working with us. Drop us a line.
A bigger team means that Authorea will get better faster.
We will keep working toward our mission to accelerate science, to improve dissemination and quality of research results and to promote Open Science. We look forward to making Authorea your platform of choice for scholarly writing, research collaboration, and data sharing.
We are also thrilled to announce that our brand new Board of Directors will welcome John Frankel, CEO of ff Venture Capital, and Brian Cohen, Chairman of NY Angels. Together with John and Brian, the board will also be composed of Matteo Cantiello (formerly Authorea's Scientific Advisor) and us, the two co-founders, Nathan and Alberto. We will be announcing our full team and advisory board in the next few weeks.
Happy writing!
---Nathan and Alberto
First evidence of Quantum Gravity? Ask the dust
Rise and fall of the biggest discovery of the century highlights the importance of open, collaborative science.
On 17 March 2014 BICEP2, a South Pole based experiment aimed at studying the very first moments of the universe, made a sensational announcement. They claimed to have detected for the first time the signature of an extremely rapid expansion of space that occurred right after the universe’s birth. This expansion, also called inflation, is believed to be responsible for the existence of large-scale structures like clusters of galaxies, as well as to explain why the properties of the universe appear to be the same for all observers. If confirmed, the existence of inflation would represent the first evidence of a fundamental connection between gravity (general relativity) and quantum physics.