Gun Ownership and Firearm-related Deaths

BACKGROUND: A variety of claims about possible associations between gun ownership rates, mental illness burden, and the risk of fi rearm-related deaths have been put forward. However, systematic data on this issue among various countries remain scant. Our objective was to assess whether the popular notion "guns make a nation safer" has any merits.METHODS: Data on gun ownership were obtained from the Small Arms Survey, and for fi rearm-related deaths from a European detailed mortality database (World Health Organization), the National Center for Health Statistics, and others. Crime rate was used as an indicator of safety of the nation and was obtained from the United Nations Surveys of Crime Trends. Age-standardized disability-adjusted life- year rates due to major depressive disorder per 100,000 inhabitants with data obtained from the World Health Organization database were used as a putative indicator for mental illness burden in a given country.RESULTS: Among the 27 developed countries, there was a significant positive correlation between guns per capita per country and the rate of fi rearm-related deaths ( r ¼ 0.80; P < .0001). In addition, there was a positive correlation (r ¼ 0.52; P ¼ .005) between mental illness burden in a country and fi rearm-related deaths. However, there was no significant correlation (P ¼ .10) between guns per capita per country and crime rate ( r ¼ .33), or between mental illness and crime rate ( r ¼ 0.32; P ¼ .11). In a linear regression model with fi rearm-related deaths as the dependent variable with gun ownership and mental illness as independent covariates, gun ownership was a significant predictor ( P < .0001) of fi rearm-related deaths, whereas mental illness was of borderline significance ( P ¼ .05) only.CONCLUSION: The number of guns per capita per country was a strong and independent predictor of fi rearm-related death in a given country, whereas the predictive power of the mental illness burden was of borderline significance in a multivariable model. Regardless of exact cause and effect, however, the current study debunks the widely quoted hypothesis that guns make a nation safer

Bootstrapping Multilingual Intent Models via Machine Translation for Dialog Automation

With the resurgence of chat-based dialog systems in consumer and enterprise applications, there has been much success in developing data-driven and rule-based natural language models to understand human intent. Since these models require large amounts of data and in-domain knowledge, expanding an equivalent service into new markets is disrupted by language barriers that inhibit dialog automation. This paper presents a user study to evaluate the utility of out-of-the-box machine translation technology to (1) rapidly bootstrap multilingual spoken dialog systems and (2) enable existing human analysts to understand foreign language utterances. We additionally evaluate the utility of machine translation in human assisted environments, where a portion of the traffic is processed by analysts. In English->Spanish experiments, we observe a high potential for dialog automation, as well as the potential for human analysts to process foreign language utterances with high accuracy.Comment: 6 pages, 3 figures, accepted for publication at the 2018 European Association for Machine Translation Conference (EAMT 2018

Tracking of motor vehicles from aerial video imagery using the OT-MACH correlation filter

Accurately tracking moving targets in a complex scene involving moving cameras, occlusions and targets embedded in noise is a very active research area in computer vision. In this paper, an optimal trade-off maximum correlation height (OT-MACH) filter has been designed and implemented as a robust tracker. The algorithm allows selection of different objects as a target, based on the operator’s requirements. The user interface is designed so as to allow the selection of a different target for tracking at any time. The filter is updated, at a frequency selected by the user, which makes the filter more resistant to progressive changes in the object’s orientation and scale. The tracker has been tested on both colour visible band as well as infra-red band video sequences acquired from the air by the Sussex County police helicopter. Initial testing has demonstrated the ability of the filter to maintain a stable track on vehicles despite changes of scale, orientation and lighting and the ability to re-acquire the track after short losses due to the vehicle passing behind occlusions

Complexity of Lexical Descriptions and its Relevance to Partial Parsing

In this dissertation, we have proposed novel methods for robust parsing that integrate the flexibility of linguistically motivated lexical descriptions with the robustness of statistical techniques. Our thesis is that the computation of linguistic structure can be localized if lexical items are associated with rich descriptions (supertags) that impose complex constraints in a local context. However, increasing the complexity of descriptions makes the number of different descriptions for each lexical item much larger and hence increases the local ambiguity for a parser. This local ambiguity can be resolved by using supertag co-occurrence statistics collected from parsed corpora. We have explored these ideas in the context of Lexicalized Tree-Adjoining Grammar (LTAG) framework wherein supertag disambiguation provides a representation that is an almost parse. We have used the disambiguated supertag sequence in conjunction with a lightweight dependency analyzer to compute noun groups, verb groups, dependency linkages and even partial parses. We have shown that a trigram-based supertagger achieves an accuracy of 92.1‰ on Wall Street Journal (WSJ) texts. Furthermore, we have shown that the lightweight dependency analysis on the output of the supertagger identifies 83‰ of the dependency links accurately. We have exploited the representation of supertags with Explanation-Based Learning to improve parsing effciency. In this approach, parsing in limited domains can be modeled as a Finite-State Transduction. We have implemented such a system for the ATIS domain which improves parsing eciency by a factor of 15. We have used the supertagger in a variety of applications to provide lexical descriptions at an appropriate granularity. In an information retrieval application, we show that the supertag based system performs at higher levels of precision compared to a system based on part-of-speech tags. In an information extraction task, supertags are used in specifying extraction patterns. For language modeling applications, we view supertags as syntactically motivated class labels in a class-based language model. The distinction between recursive and non-recursive supertags is exploited in a sentence simplification application

Pi-Calculus: A Unifying Framework for Programming Paradigms

π-calculus is a calculus for modeling dynamically changing configurations of a network of communicating agents. This paper studies the suitability of π-calculus as a unifying framework to model the operational semantics of the three paradigms of programming: functional, logic and imperative paradigms. In doing so, the attempt is to demonstrate that π-calculus models a primitive that is pervasive in the three paradigms and to illustrate that the three forms of sequential computing are special instances of concurrent computing

Replication of barley yellow dwarf luteovirus-PAV RNA

Barley yellow dwarf luteovirus (BYDV)-PAV serotype, an economically important virus of small grain cereals, has a positive-sense RNA genome encoding at least six open reading frames (ORFs). The goal of the research was to determine the genes and sequences involved in the viral replication and to design efficient antiviral strategies to BYDV-PAV. Genetically engineered resistance is essential for BYDV as the natural resistance is inadequate. Antiviral constructs such as sense RNA, antisense RNA and viral polymerase gene were tested for their ability to reduce virus titre in oat protoplasts as monitored by enzyme-linked immunosorbent assay. All antiviral constructs yielded low levels of viral antigen. However, none of the above constructs showed decrease in viral RNA accumulation in Northern blot analysis. Deletion and mutation analyses were performed to determine genes and cis-acting signals involved in translation, replication and encapsidation of BYDV-PAV. ORFs 1 and 2, which encode the putative polymerase gene, were required for replication. Deletion of the coat protein (CP) gene reduced the accumulation of genomic RNA. The carboxy-terminally extended form of the CP was not necessary for replication or encapsidation. Cis-acting RNA signals in and around ORF6 were essential for viral replication. BYDV-PAV replication may be coupled to translation because defective RNAs containing various deletions were not replicated in trans by the co-inoculated wild-type helper genome. Site-directed mutagenesis was used to map the subgenomic RNA1 (sgRNA1) promoter because subgenomic promoters are putative hotspots of viral recombination and putative replication origin. Mutating the sgRNA1 transcription initiation base, G at 2670, or the nucleotides immediately flanking it, reduced sgRNA1 accumulation. Computer-predicted secondary structures in the putative sgRNA1 promoter regions of many members of subgroup I luteovirus has revealed a conserved stem-loop structure near the sgRNA1 start site. Altering the conserved ACAAA motif reduced both the genomic RNA and sgRNA1 accumulation. A premature stop codon introduced at base 2650, 90 bases from the 3\u27 end of the polymerase gene, abolished BYDV-PAV replication in oat protoplasts

Let\u27s get hairy : women, body hair and stigma in arts education

A woman who is visibly hairy might be viewed as masculine, dirty, unprofessional, or as a radical feminist. There are variations on what it means to be a woman; feminine does not have to be synonymous with “hairless”. Body hair is a stigma because it is a physical characteristic that is undesirable and shamed when exposed. Body hair as stigma can be explored in terms of creativity and pedagogy. How can creativity work to dismantle stigma? Talking about stigma gives one the chance to express themselves in a way that is exploratory, sparking new ways of understanding. Arts education already possesses qualities that are beneficial to stigma—how can educators and students take advantage of all that creativity has to offer? Creating artwork about women and body hair and analyzing existing works can deepen one’s knowledge of body hair; as a societal form of control and as a lens to look more closely at stigma in arts education. Creativity can be the outlet to find new ways to accept and appreciate the hair on women’s bodies. Creativity can be a valuable tool to address topics that are controversial or simply overlooked. Let’s get hairy