Guiding-center dynamics of vortex dipoles in Bose-Einstein condensates

A quantized vortex dipole is the simplest vortex molecule, comprising two counter-circulating vortex lines in a superfluid. Although vortex dipoles are endemic in two-dimensional superfluids, the precise details of their dynamics have remained largely unexplored. We present here several striking observations of vortex dipoles in dilute-gas Bose-Einstein condensates, and develop a vortex-particle model that generates vortex line trajectories that are in good agreement with the experimental data. Interestingly, these diverse trajectories exhibit essentially identical quasi-periodic behavior, in which the vortex lines undergo stable epicyclic orbits.Comment: 4 pages, 2 figure

A Mixed-Method Analysis of Fatal Attacks on Police by Far-Right Extremists

Several recent high-profile homicides of police officers have brought increased attention to issues of far-right extremist violence in the United States. We still, however, know very little about why (and how) certain encounters between far-right extremists and police result in violence. To fill this research gap, we conduct a mixed-method analysis of far-right antipolice homicides based on quantitative and qualitative data from the U.S. Extremist Crime Database. We begin by categorizing cases based on key aspects of homicide storylines. We then comparatively analyze attributes of event precursor, transaction, and aftermath stages across four storyline categories. Finally, a case study is purposively selected to follow-up on each storyline category to better capture the nuances of fluid homicide processes. Our findings have important implications for identifying triggering events, escalation factors, and other situated sets of conditions and circumstances that contribute to deadly outcomes for police officers

EcoCTD for profiling oceanic physical-biological properties from an underway ship

Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of the Atmospheric and Oceanic Technology 37(5), (2020): 825-840, doi:10.1175/JTECH-D-19-0145.1.The study of ocean dynamics and biophysical variability at submesoscales of O(1) km and O(1) h raises several observational challenges. To address these by underway sampling, we recently developed a towed profiler called the EcoCTD, capable of concurrently measuring both hydrographic and bio-optical properties such as oxygen, chlorophyll fluorescence, and optical backscatter. The EcoCTD presents an attractive alternative to currently used towed platforms due to its light footprint, versatility in the field, and ease of deployment and recovery without cranes or heavy-duty winches. We demonstrate its use for gathering high-quality data at submesoscale spatiotemporal resolution. A dataset of bio-optical and hydrographic properties, collected with the EcoCTD during field trials in 2018, highlights its scientific potential for the study of physical–biological interactions at submesoscales.Authors would like to acknowledge Melissa Omand, Ben Pietro, and Jing He for their valuable input during the design phase of the EcoCTD, as well as for their support for deploying the EcoCTD in the field. We are grateful to Eva Alou, Andrea Carbonero, and John Allen for providing calibrated data from the shipboard CTD. Authors would also like to thank Don Peters along with Dynamics System Analysis Ltd. for facilitating access to ProteusDS and providing support in using the software. We are grateful to the crew of the RV Armstrong and NRV Alliance for their support in the field. Development of the EcoCTD is supported by the Office of Naval Research (ONR) through the CALYPSO Departmental Research Initiative (Grant N000141613130). Advanced field testing was supported by Woods Hole Oceanographic Institution internal funding. MATLAB routines for data processing are publicly available at https://github.com/mfreilich1/ecoctd_processing.2020-11-0

Denoising inferred functional association networks obtained by gene fusion analysis.

BACKGROUND: Gene fusion detection - also known as the 'Rosetta Stone' method - involves the identification of fused composite genes in a set of reference genomes, which indicates potential interactions between its un-fused counterpart genes in query genomes. The precision of this method typically improves with an ever-increasing number of reference genomes. RESULTS: In order to explore the usefulness and scope of this approach for protein interaction prediction and generate a high-quality, non-redundant set of interacting pairs of proteins across a wide taxonomic range, we have exhaustively performed gene fusion analysis for 184 genomes using an efficient variant of a previously developed protocol. By analyzing interaction graphs and applying a threshold that limits the maximum number of possible interactions within the largest graph components, we show that we can reduce the number of implausible interactions due to the detection of promiscuous domains. With this generally applicable approach, we generate a robust set of over 2 million distinct and testable interactions encompassing 696,894 proteins in 184 species or strains, most of which have never been the subject of high-throughput experimental proteomics. We investigate the cumulative effect of increasing numbers of genomes on the fidelity and quantity of predictions, and show that, for large numbers of genomes, predictions do not become saturated but continue to grow linearly, for the majority of the species. We also examine the percentage of component (and composite) proteins with relation to the number of genes and further validate the functional categories that are highly represented in this robust set of detected genome-wide interactions. CONCLUSION: We illustrate the phylogenetic and functional diversity of gene fusion events across genomes, and their usefulness for accurate prediction of protein interaction and function

Construction, visualisation, and clustering of transcription networks from microarray expression data.

Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express(3D)

Understanding and Applying SAR to Ideological and Nation- State-Sponsored Cybercrimes

The use of computer hacking, malicious software, and other forms of cyberattacks against U.S. infrastructure has increased dramatically since the 1990s. Many of these attacks target corporations and individuals for instrumental economic gain, such as the theft of personal information for use in fraud. Ideologically motivated attacks also occur, though the degree to which they are understood or documented is generally limited. For instance, jihadi groups have expressed an interest in cyberattacks since the early 2000s (see Holt et al., 2022). Similarly, DHS (2009) noted in the late 2000s that they expected cyberattacks from environmental or animal liberation-focused groups to increase. Attacks not only originate from individual actors, but also from nation-state-sponsored actors who seek to further the political and economic interests of their governments

A New Approach to Patent Reform

Scholars and policy makers have tried for years to solve the tenacious and harmful crisis of low quality, erroneously granted patents. Far from resolving the problem, these determined efforts have resulted in hundreds of conflicting policy proposals, failed Congressional bills, and no way to evaluate the policies’ value or impact or to decide between the overwhelming multiplicity of policies. This Article provides not only new solutions, but a new approach for designing and assessing policies both in patent law and legal systems more generally. We introduce a formal economic model of the patent system that differs from existing scholarship because it permits us to (1) determine how a policy change to one part of the patent system affects the system as a whole; and (2) quantify the impact of policy changes. Existing scholarship typically analyses a policy by assessing its effect on just the targeted element of the patent system, but legal systems are complex with interrelated components and players react along multiple margins, so these analyses are incomplete and sometimes incorrect. Our approach fixes this problem, providing a comprehensive understanding of how a policy change affects the patent system from beginning-to-end. It also permits us to conduct complex analyses such as varying multiple policies at once. Further, much existing scholarship fails to quantify the magnitude of a policy’s effect, and even empirical scholarship can only measure the effect of an already-implemented policy, not predict the effect of a proposed change. Quantification is critical because policies generally have multiple effects, often in countervailing directions. Quantification—as shown using our model—permits scholars to determine the overall direction and size of a theoretically ambiguous effect. Quantification also allows us to compare the social welfare effects of different reforms so that policy-makers know where to focus their efforts. We apply our model to several of the most prominent policy debates in patent law. We conclude that certain reforms such as regulation of settlement licenses and increased examination intensity yield large gains in social welfare and should be prioritized. Other reforms that are popular with scholars, including decreasing the availability of injunctions and reducing litigation costs produce surprisingly small gains in social welfare. Often existing scholarship operates too much on intuition, which, we show, can be wrong. Our new approach to patent reform provides an approach that offers deeper understanding and a more effective evaluation framework

Dispensability of Escherichia coli's latent pathways

Gene-knockout experiments on single-cell organisms have established that expression of a substantial fraction of genes is not needed for optimal growth. This problem acquired a new dimension with the recent discovery that environmental and genetic perturbations of the bacterium Escherichia coli are followed by the temporary activation of a large number of latent metabolic pathways, which suggests the hypothesis that temporarily activated reactions impact growth and hence facilitate adaptation in the presence of perturbations. Here we test this hypothesis computationally and find, surprisingly, that the availability of latent pathways consistently offers no growth advantage, and tends in fact to inhibit growth after genetic perturbations. This is shown to be true even for latent pathways with a known function in alternate conditions, thus extending the significance of this adverse effect beyond apparently nonessential genes. These findings raise the possibility that latent pathway activation is in fact derivative of another, potentially suboptimal, adaptive response