122 research outputs found
Sexual variation in the inter-triradial distance of the palm among Bengali Hindu population of Kolkata, India
No full textPalm prints are one of the most important forensic tools for human identification in medico-legal investigation. Palm prints are often used for forensic sex estimation to narrow down the pool of suspects through a process of elimination. The aim of this study was to test whether a novel approach of sex estimation from palmar inter-triradial distances previously posited by Badiye and colleagues [Journal of Forensic and Legal Medicine, 2019; 65(March):22–26] can be used as a primary tool for forensic sexing. For this study the bilateral palm prints from 200 Bengali Hindu adults (100 male, 100 female) were collected using traditional ink printing method and were analysed. Descriptive statistics were presented in tables and linear discriminant analysis was conducted to estimate the extent of sexual dimorphism in the inter-triradial distances and to find out variables with the strongest sex discriminating potential. Binary logistic regression analysis (BLR) was performed to derive sex estimation equations. Sexual dimorphism has been found to be statistically significant (p< 0.001) using linear discriminant analysis with a sexing accuracy of 79.0 percent for the left and 79.5 percent for the right palm. Distance between a and t triradius has been found to be the most influential on this model followed by the combined abcd-t distance. For the BLR analysis, the correct classification percentage was found to be the highest on the a-t distance of the right palm with a success rate of 80.5 percent which is closely followed by the combined abcd-t distance which has a classification success rate of 80.0 percent for the right palm. The present study has concluded that, inter-triradial distance of the palm is fairly dimorphic sexually but can only be used as a supplementary tool in inference of sex for medico-legal investigation. Due to a higher accuracy, the distance between a and t triradius has been proposed to be used instead of combined abcd-t distance which was suggested in the original study conducted by Badiye and colleagues (2019)
Do workers discriminate against their out-group employers? Evidence from an online platform economy
No full textWe study possible worker-to-employer discrimination manifested via social preferences. We run a well-powered, model-based experiment, wherein we recruit 6,000 white American workers from Amazon’s M-Turk platform for a real-effort task. We randomly (and unobtrusively) reveal the racial identity of their non-fictitious employer, who may either be white or black. We find evidence of race-based altruism towards black employers. However, the workers display significant racial discrimination in reciprocity – a small gift induces workers to put higher effort for white employers relative to black. While we detect evidence of altruism in favor of black employers that effect is entirely crowded out by the discrimination in reciprocity they face from white employees. Our results suggest that taste-based discrimination favoring the in-group can have significant adverse effects on outgroup employers.JEL Codes: J71, D91, C93This is a manuscript of an article published as Asad, Sher Afghan, Ritwik Banerjee, and Joydeep Bhattacharya. "Do workers discriminate against their out-group employers? Evidence from an online platform economy." Journal of Economic Behavior & Organization 216 (2023): 221-242. doi:10.1016/j.jebo.2023.10.002
. Quantifying Sexual Dimorphism in the Human Cranium: A Preliminary Analysis of a Novel Method. J Forensic Sci 2017;62(5):1259–65.
No full textOn the interpretation of World Values Survey trust question - Global expectations vs. local beliefs
No full textCorruption, Norm Violation and Decay in Social Capital
No full textThe paper studies the link between corruption and social capital (measured as trust), using data from a lab experiment. Subjects play either a harassment bribery game or a strategically identical but differently framed ultimatum game, followed by a trust game. In a second experiment, we elicit social appropriateness norm of actions in the bribery game and the ultimatum game treatments. Our experimental design allows us to examine whether subjects, who have been asked to pay a bribe, are less likely to trust than those in an isomorphic role in the ultimatum game. We also uncover the underlying mechanism behind any such behavioral spillover. Results suggest that a) there is a negative spillover effect of corruption on trust and the effect increases with decrease in social appropriateness norm of the bribe demand; b) lower trust in the bribery game treatment is explained by lower expected return on trust; c) surprisingly, for both the bribery and the ultimatum game treatments, social appropriateness norm violation engenders the decay in trust through its adverse effect on belief about trustworthiness
Activity and decrease in weight and its impact on parameters (metabolic and haemostatic) in the obese : ADIPOSE study
No full textEThOS - Electronic Theses Online ServiceGBUnited Kingdo
An Evaluation of the Revenue side as a source of fiscal consolidation in high debt economies
No full textUnsustainable levels of debt for some European economies is causing enormous strain in the Euro area. How to tide over the debt crisis seems to be the most important objective the European policy makers are currently facing. We use a dynamic general equilibrium closed economy model to compute the dynamic Laffer Curves for Portugal, Ireland, Greece and Spain for different class of taxes. We conclude that there exists scope for considerable revenue generation by raising certain class of taxes. Thus revenue generation, along with fiscal consolidation holds key for debt reduction
On the Interpretation of World Values Survey Trust Question: Global Expectations vs. Local Beliefs
No full textHow should we interpret the World Values Survey (WVS) trust question? We conduct an experiment in India, a low trust country, to correlate the WVS trust question with trust decisions in an incentivized Trust Game. Evidence supports findings from one strand of the fractured literature – the WVS trust question captures expectations about others' trustworthiness, though not always. We show that WVS trust question correlates with globally determined stable expectations but does not correlate with short term locally determined fluctuations in beliefs about trustworthiness. One implication of our study is that survey based methods may not be used to measure contextualized beliefs
Knowledge Extraction from Diverse Biomedical Corpora with Applications in Healthcare: Bridging the Translational Gap
No full textA wealth of knowledge in the biomedical domain is available in unstructured or semi-structured data repositories as natural language narratives. Much of this knowledge can provide immediate and tangible benefits in patient welfare and the healthcare industry. Extracting relevant knowledge from these natural language sources and providing them as structured information suitable for immediate real-time consumption in clinical settings is, however, a manual process restricted to human domain experts. As a result, it is expensive and time-consuming. A very real consequence of this is that the journey made by medical knowledge nuggets from research publications to patient care settings like hospitals often take several years. Even so, the knowledge still gets presented to clinicians in natural language -- unsuitable for machine consumption, and an impediment to the pace of work often demanded of clinicians (e.g. | in emergency rooms). Automatic extraction of this knowledge is a challenging task. Biomedical research literature is replete with language constructs that are highly specific to not just the domain, but internal sub-domains. The linguistic semantics used in discussions of, say, diabetes, are very different from the semantics used to discuss diseases like malaria that are caused by external agents. Moreover, being research literature, authors typically write for readers with a fair amount of encyclopaedic domain knowledge. Consequently, important information can often only be gleaned by identifying causal relations that are implicit. Standard information extraction methods that depend on identifying causality in text usually require explicit discourse connectives like because , since , etc. Additionally, they manage to extract only those relations that are expressed within the span of a single sentence. This proposal presents a novel relation learning methodology for biomedical natural language that is able to infer relations where (a) the relation is implicit, and (b) the related entities do not co-occur within the span of a single sentence. We show that our technique outperforms a sentence-level supervised classification approach. Further, as a human-in-the-loop (HITL) model, it is capable of augmenting biomedical knowledge bases quickly and accurately. Finally, we contribute two novel applications that demonstrate the use of such relational knowledge in providing real-time clinical decision support. | 75 page
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