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1. Evolution and differentiation of the cybersecurity communities in three social question and answer sites: A mixed-methods analysis

   https://doi.org/10.1371/journal.pone.0261954  

   Wu, Muting ; Aranovich, Raul ; Filkov, Vladimir ( December 2021 , PLOS ONE)

   Haldorai, Anandakumar (Ed.)

   Cybersecurity affects us all in our daily lives. New knowledge on best practices, new vulnerabilities, and timely fixes for cybersecurity issues is growing super-linearly, and is spread across numerous, heterogeneous sources. Because of that, community contribution-based, question and answer sites have become clearinghouses for cybersecurity-related inquiries, as they have for many other topics. Historically, Stack Overflow has been the most popular platform for different kinds of technical questions, including for cybersecurity. That has been changing, however, with the advent of Security Stack Exchange, a site specifically designed for cybersecurity-related questions and answers. More recently, some cybersecurity-related subreddits of Reddit, have become hubs for cybersecurity-related questions and discussions. The availability of multiple overlapping communities has created a complex terrain to navigate for someone looking for an answer to a cybersecurity question. In this paper, we investigate how and why people choose among three prominent, overlapping, question and answer communities, for their cybersecurity knowledge needs. We aggregated data of several consecutive years of cybersecurity-related questions from Stack Overflow, Security Stack Exchange, and Reddit, and performed statistical, linguistic, and longitudinal analysis. To triangulate the results, we also conducted user surveys. We found that the user behavior across those three communities is different, in most cases. Likewise, cybersecurity-related questions asked on the three sites are different, more technical on Security Stack Exchange and Stack Overflow, and more subjective and personal on Reddit. Moreover, there appears to have been a differentiation of the communities along the same lines, accompanied by overall popularity trends suggestive of Stack Overflow’s decline and Security Stack Exchange’s rise within the cybersecurity community. Reddit is addressing the more subjective, discussion type needs of the lay community, and is growing rapidly. 

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2. HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

   https://doi.org/10.5194/hess-22-5639-2018  

   Shen, Chaopeng ; Laloy, Eric ; Elshorbagy, Amin ; Albert, Adrian ; Bales, Jerad ; Chang, Fi-John ; Ganguly, Sangram ; Hsu, Kuo-Lin ; Kifer, Daniel ; Fang, Zheng ; et al ( January 2018 , Hydrology and Earth System Sciences)

   Abstract. Recently, deep learning (DL) has emerged as a revolutionary andversatile tool transforming industry applications and generating new andimproved capabilities for scientific discovery and model building. Theadoption of DL in hydrology has so far been gradual, but the field is nowripe for breakthroughs. This paper suggests that DL-based methods can open up acomplementary avenue toward knowledge discovery in hydrologic sciences. Inthe new avenue, machine-learning algorithms present competing hypotheses thatare consistent with data. Interrogative methods are then invoked to interpretDL models for scientists to further evaluate. However, hydrology presentsmany challenges for DL methods, such as data limitations, heterogeneityand co-evolution, and the general inexperience of the hydrologic field withDL. The roadmap toward DL-powered scientific advances will require thecoordinated effort from a large community involving scientists and citizens.Integrating process-based models with DL models will help alleviate datalimitations. The sharing of data and baseline models will improve theefficiency of the community as a whole. Open competitions could serve as theorganizing events to greatly propel growth and nurture data science educationin hydrology, which demands a grassroots collaboration. The area ofhydrologic DL presents numerous research opportunities that could, in turn,stimulate advances in machine learning as well.

    

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3. Optimal eventual Byzantine agreement protocols with omission failures

   K. Alpturer ; J. Y. Halpern ; R. van der Meyden ( June 2023 , Proceedings of the 42nd Annual ACM Symposium on Principles of Distributed Computing (PODC))

   Work on optimal protocols for \emph{Eventual Byzantine Agreement} (EBA)---protocols that, in a precise sense, decide as soon as possible in every run and guarantee that all nonfaulty agents decide on the same value---has focused on full-information protocols} (FIPs), where agents repeatedly send messages that completely describe their past observations to every other agent. While it can be shown that, without loss of generality, we can take an optimal protocol to be an FIP, full information exchange is impractical to implement for many applications due to the required message size. We separate protocols into two parts, the information-exchange protocol and the action protocol, so as to be able to examine the effects of more limited information exchange. We then define a notion of optimality with respect to an information-exchange protocol. Roughly speaking, an action protocol P is optimal with respect to an information-exchange protocol E if, with P, agents decide as soon as possible among action protocols that exchange information according to E. We present a knowledge-based EBA program for omission failures all of whose implementations are guaranteed to be correct and are optimal if the information exchange satisfies a certain safety condition. We then construct concrete programs that implement this knowledge-based program in two settings of interest that are shown to satisfy the safety condition. Finally, we show that a small modification of our program results in an FIP that s both optimal and efficiently implementable, settling an open problem posed by Halpern, Moses, and Waarts (SIAM J. Comput., 2001). 

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4. Examining how prior knowledge impacts students’ discussions and knowledge construction during computational model building

   https://doi.org/10.3102/IP.22.1891766  

   Snyder, C. ( April 2022 , Proceedings of the American Educational Research Association Annual Meeting)

   Student discussions have been shown to be beneficial to student learning (Chi & Wylie, 2014), however, the impact of prior knowledge on these discussions is not fully understood. In this research, we analyze students’ synchronous spoken discussions to study how prior knowledge impacted group discussions and knowledge construction while constructing computational models of 1D and 2D motion. We present a method for evaluating the impact of prior knowledge on student discussions and individual work. We illustrate this method through a case study analysis of two groups with students across a spectrum of prior knowledge. Our exploratory findings suggest that students with low prior knowledge greatly benefit from group discussions followed by individual model construction. 

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5. Observation of Strong Bulk Damping‐Like Spin‐Orbit Torque in Chemically Disordered Ferromagnetic Single Layers

   https://doi.org/10.1002/adfm.202005201  

   Zhu, Lijun ; Zhang, Xiyue S. ; Muller, David A. ; Ralph, Daniel C. ; Buhrman, Robert A. ( September 2020 , Advanced Functional Materials)

   Strong damping‐like spin‐orbit torque (τ_DL) has great potential for enabling ultrafast energy‐efficient magnetic memories, oscillators, and logic. So far, the reported τ_DLexerted on a thin‐film magnet must result from an externally generated spin current or from an internal non‐equilibrium spin polarization in non‐centrosymmetric GaMnAs single crystals. Here, for the first time a very strong, unexpected τ_DLis demonstrated from current flow within ferromagnetic single layers of chemically disordered, face‐centered‐cubic CoPt. It is established here that the novel τ_DLis a bulk effect, with the strength per unit current density increasing monotonically with the CoPt thickness, and is insensitive to the presence or absence of spin sinks at the CoPt surfaces. This τ_DLmost likely arises from a net transverse spin polarization associated with a strong spin Hall effect, while there is no detectable long‐range asymmetry in the material. These results broaden the scope of spin‐orbitronics and provide a novel avenue for developing single‐layer‐based spin‐torque memory, oscillator, and logic technologies.

    

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