A data-driven computational model on the effects of immigration policies

Many scholars suggest that visa restrictions push individuals who would have otherwise migrated legally toward illegal channels. This expectation is difficult to test empirically for three reasons. First, unauthorized migration is clandestine and often unobservable. Second, interpersonal ties between migrants and would-be migrants form a self-perpetuating system, which adapts in ways that are difficult to observe or predict. Third, empirical evaluations of immigration policy are vulnerable to endogeneity and other issues of causal inference. In this paper, we pair tailor-made empirical designs with an agent-based computational model (ABM) to capture the dynamics of a migration system that often elude empirical analysis, while grounding agent rules and characteristics with primary data collected in Jamaica, an origin country. We find that some government-imposed restrictions on migrants can deter total migration, but others are ineffective. Relative to a system of free movement, the minimal eligibility conditions required to classify migrants into visa categories alone make migration inaccessible for many. Restrictive policies imposed on student and high-skilled visa categories have little added effect because eligible individuals are likely able to migrate through alternative legal categories. Meanwhile, restrictions on family-based visas result in significant reductions in total migration. However, they also produce the largest reorientation toward unauthorized channels—an unintended consequence that even the highest rates of apprehension do not effectively eliminate

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL

The influence of organizational culture and climate on entrepreneurial intentions among research scientists

Over the past decades, universities have increasingly become involved in entrepreneurial activities. Despite efforts to embrace their ‘third mission’, universities still demonstrate great heterogeneity in terms of their involvement in academic entrepreneurship. This papers adopts an institutional perspective to understand how organizational characteristics affect research scientists’ entrepreneurial intentions. Specifically, we study the impact of university culture and climate on entrepreneurial intentions, including intentions to spin off a company, to engage in patenting or licensing and to interact with industry through contract research or consulting. Using a sample of 437 research scientists from Swedish and German universities, our results reveal that the extent to which universities articulate entrepreneurship as a fundamental element of their mission fosters research scientists’ intentions to engage in spin-off creation and intellectual property rights, but not industry-science interaction. Furthermore, the presence of university role models positively affects research scientists’ propensity to engage in entrepreneurial activities, both directly and indirectly through entrepreneurial self-efficacy. Finally, research scientists working at universities which explicitly reward people for ‘third mission’ related output show higher levels of spin-off and patenting or licensing intentions. This study has implications for both academics and practitioners, including university managers and policy makers

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research

Innovation Practices in Emerging Economies: Do University Partnerships Matter?

Enterprises’ resources and capabilities determine their ability to achieve competitive advantage. In this regard, the key innovation challenges that enterprises face are liabilities associated with their age and size, and the entry barriers imposed on them. In this line, a growing number of enterprises are starting to implement innovation practices in which they employ both internal/external flows of knowledge in order to explore/exploit innovation in collaboration with commercial or scientific agents. Within this context, universities play a significant role providing fertile knowledge-intensive environments to support the exploration and exploitation of innovative and entrepreneurial ideas, especially in emerging economies, where governments have created subsidies to promote enterprise innovation through compulsory university partnerships. Based on these ideas, the purpose of this exploratory research is to provide a better understanding about the role of universities on enterprises’ innovation practices in emerging economies. More concretely, in the context of Mexico, we explored the enterprises’ motivations to collaborate with universities in terms of innovation purposes (exploration and exploitation) or alternatives to access to public funds (compulsory requirement of being involved in a university partnership). Using a sample of 10,167 Mexican enterprises in the 2012 Research and Technological Development Survey collected by the Mexican National Institute of Statistics and Geography, we tested a multinomial regression model. Our results provide insights about the relevant role of universities inside enterprises’ exploratory innovation practices, as well as, in the access of R&D research subsidies

The L 98-59 System: Three Transiting, Terrestrial-size Planets Orbiting a Nearby M Dwarf

We report the Transiting Exoplanet Survey Satellite (TESS) discovery of three terrestrial-size planets transiting L 98-59 (TOI-175, TIC 307210830)—a bright M dwarf at a distance of 10.6 pc. Using the Gaia-measured distance and broadband photometry, we find that the host star is an M3 dwarf. Combined with the TESS transits from three sectors, the corresponding stellar parameters yield planet radii ranging from 0.8 R ⊕ to 1.6 R ⊕. All three planets have short orbital periods, ranging from 2.25 to 7.45 days with the outer pair just wide of a 2:1 period resonance. Diagnostic tests produced by the TESS Data Validation Report and the vetting package DAVE rule out common false-positive sources. These analyses, along with dedicated follow-up and the multiplicity of the system, lend confidence that the observed signals are caused by planets transiting L 98-59 and are not associated with other sources in the field. The L 98-59 system is interesting for a number of reasons: the host star is bright (V = 11.7 mag, K = 7.1 mag) and the planets are prime targets for further follow-up observations including precision radial-velocity mass measurements and future transit spectroscopy with the James Webb Space Telescope; the near-resonant configuration makes the system a laboratory to study planetary system dynamical evolution; and three planets of relatively similar size in the same system present an opportunity to study terrestrial planets where other variables (age, metallicity, etc.) can be held constant. L 98-59 will be observed in four more TESS sectors, which will provide a wealth of information on the three currently known planets and have the potential to reveal additional planets in the system

Police performance measurement: an annotated bibliography

This study provides information to assist those involved in performance measurement in police organisations. The strategies used to identify the literature are described. Thematic sections cover; general overviews; methodological issues; performance management in other industries; national, international and cross-national studies; frameworks (e.g. Compstat; the Balanced Scorecard); criticisms (particularly unintended consequences); crime-specific measures; practitioner guides; performance evaluation of individual staff; police department plans and evaluations; annotated bibliographies in related areas, and; other literature. Our discussion offers two conclusions: the measures best aligned with performance are typically more expensive, while most operational data should only provide contextual information; the philosophy of open governance should be pursued to promote transparency, accountability and communication to improve police performance

Stress Processes: An Essential Ingredient in the Entrepreneurial Process

The entrepreneurial process is associated with high uncertainty. Uncertainty is also a major source of stress. Therefore, a core aim of entrepreneurs is to reduce uncertainty to an extent that allows the entrepreneurial process to unfold. However, entrepreneurship scholars have insufficiently addressed stress processes that may be associated with this uncertainty. We argue that uncertainty is the concept connecting both the entrepreneurial and stress processes. We discuss the link between the two processes regarding: (1) opportunity recognition, (2) opportunity exploitation, and (3) associated outcomes. We then illustrate how future research should incorporate the interaction between the two processes using a morphological box and discuss how such research would change the way we specify entrepreneurial process models and study entrepreneurial behavior