What is the relationship between interpretive methods and decolonizing projects? Decolonial thinkers often invoke pre-colonial traditions in their efforts to fashion “national cultures”— modes of being, understanding, and self-expression specific to a de-colonizing collectivity’s experience. While the substantive contributions of precolonial traditions to decolonial thought have received well-deserved attention in postcolonial and comparative political theory, this paper focuses on the role that interpretive methods play in generating the emancipatory sensibilities envisioned by decolonial thinkers. It draws on the contemporary Moroccan philosopher Mohammed ‘Abed Al-Jabri’s interpretive method to show that its decolonial potential lies in its “reader-centric” approach. This approach is concerned with transforming its postcolonial reader’s relationship to precolonial traditions, and not only with establishing the truth of historical texts or making use of their insights in the present as is more common in political-theoretical modes of interpretation. It does so through a tripartite process of disconnection, reconnection, and praxis.

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In Romania, as in the rest of the world, the flood frequency has increased considerably. Prahova river basin is among the most exposed catchments of the country to flood risk. It also represents the area of the present study for which the identification of surfaces with high susceptibility to flood phenomena was attempted by applying 2 hybrid models (adaptive neuro-fuzzy inference system and fuzzy support vector machine hybrid) and 2 bivariate statistical models (certainty factor and statistical index). The computation of Flood Potential Index (FPI) was possible by considering a number of 10 flood conditioning factors together with a number of 158 flood pixels and 158 non-flood pixels. Generally, the high and very high flood potential appears on around 25% of the upper and middle basin of Prahova river. The validation of the results was made through the ROC Curve model. One of the novelties of this research is related to the application of Fuzzy Support Vector Machine ensemble for the first time in a study concerning the evaluation of the susceptibility to a certain natural hazard.

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This paper tests whether the communication of the People's Bank of China affects market expectations and matters as a monetary policy tool. For that purpose, we first rely on a computational linguistic tool to measure the tone of PBC speeches and second, we use a high frequency methodology to estimate the effect of tone on stock price. Our results show that positive changes of the tone affect positively stock price in the Shanghai and the Shenzhen stocks markets. Additional extensions show that PBC communication still has a positive and significant impact on stock price even when controlling for all the monetary policy instruments implemented by the central bank, but that this impact is not persistent over time. One potential channel through which PBC tone affects stock prices is the risk-based channel of monetary policy.

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The livelihoods of the majority of the world's poor depend on agriculture. They face substantial risk from fluctuations in weather conditions. Better risk, credit and savings markets can improve productivity and welfare in rural areas but entail high administrative costs. We consider a classic public good with benefits that theoretically exceed those of perfect insurance contracts – improving the skill of long-run weather forecasts. We use an equilibrium model of agricultural production and labor migration, and a variety of Indian panel datasets to assess quantitatively the effects of improvements in seasonal forecasts of monsoon weather. We find that in areas where the forecast is accurate (has “skill”) that investment, migration and rural wages respond to forecasts. We calculate that if such skill were pervasive across India, the total value of an accurate forecast for farmers and wage workers is in the tens of billions of rupees.

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Nature uses 64 codons to encode the synthesis of proteins from the genome, and chooses 1 sense codon—out of up to 6 synonyms—to encode each amino acid. Synonymous codon choice has diverse and important roles, and many synonymous substitutions are detrimental. Here we demonstrate that the number of codons used to encode the canonical amino acids can be reduced, through the genome-wide substitution of target codons by defined synonyms. We create a variant of Escherichia coli with a four-megabase synthetic genome through a high-fidelity convergent total synthesis. Our synthetic genome implements a defined recoding and refactoring scheme—with simple corrections at just seven positions—to replace every known occurrence of two sense codons and a stop codon in the genome. Thus, we recode 18,214 codons to create an organism with a 61-codon genome; this organism uses 59 codons to encode the 20 amino acids, and enables the deletion of a previously essential transfer RNA.

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With efforts in tobacco control plateauing throughout much of Asia-Pacific and in parts of eastern Europe and Latin America over the past decade, cigarette smoking remains a defining health challenge globally. By far the number one killer of men worldwide, it is also a top cause of morbidity and mortality in women, while exposure to second-hand smoke is a concern in megacities across the southern hemisphere.

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The long season of unconventional monetary policies in advanced economies seems to be coming to an end. How can quantitative easing (QE) be effective where conventional monetary policy fails? How does it work in the peculiar environment of a monetary union? We study this latter case modelling a monetary union as the aggregate of two countries characterized by New Keynesian output and inflation relationships, with a Tobinian money market equation. QE is operated by the single central bank by expanding money supply in exchange for risky assets throughout the union. We assess the stabilization capacity of QE under different types of symmetric and asymmetric shocks, in which case fiscal accommodation at the country level should also intervene.

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In the electricity sector, innovation in large-scale storage is anticipated to reduce costs and improve performance. The effect on greenhouse gas emissions of lower storage costs depends on the interactions between storage and the entire grid. The literature has disagreed on the role of storage in reducing emissions. In this paper we present a stylized model, which suggests that the effect of storage costs on emissions depends on the supply responsiveness of both fossil and renewable generators. Under common conditions in the United States, lower storage costs are more likely to reduce emissions when wind investment responds to equilibrium electricity prices and when solar investment does not. Simulations of a computational model of grid investment and operation confirm these intuitions. Moreover, because of its effect on coal and natural gas–fired supply responsiveness, introducing a carbon dioxide emissions price may increase the likelihood that lower storage costs reduce emissions.

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This teaching project describes the process of creating, implementing, and appraising the use of escape room concepts within a urosepsis high-fidelity simulation scenario.Instead of a locked room, Breakout EDU locked boxes were incorporated into a clinical simulation. Nursing students applied concepts learned in class and analyzed patient data to obtain clues. These clues helped determine the combination to four locks and progress through the simulation within 60 minutes. After completing the escape room simulation, each group had an opportunity to gather for a team photo, which they posted on social media.Students reported the escape game contributed to their learning and improved their ability to delegate tasks and work as a team. Preliminary observations reveal that “time” may be a significant factor associated with this teaching strategy.The concept of an escape room or serious game-based learning was found to be an engaging teaching strategy by faculty and students.

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Dr. Zheng and Dr. Li raised concerns about three methodological issues that they say may compromise the inferences of our study.First, they refer that the term “active smoking during pregnancy” was not defined in our study. In the second paragraph of the method section, we present the following definition: “Smoking is generally defined as both the addiction to smoking and the use of tobacco. Tobacco can be defined as cigarettes, cigars and pipes and smokeless tobacco products inhaled as powder or absorbed by the oral mucosa when they are chewed. We included studies that considered the active smoking of cigarettes...

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Touch-stroke dynamics is a relatively recent behavioral biometrics. It authenticates an individual by observing his behavior when swiping a “stroke” on a smartphone or tablet. Several studies have attempted to determine the optimum authentication accuracy of classifiers, but none of them has used time series or temporal machine learning techniques. We postulate that when a user performs a series of touch-strokes in a continuous manner, it can be perceived as a temporal behavior characteristic of the person. In this paper, we propose the use of a Temporal Regression Forest to unearth this hidden but vital temporal information. By incorporating this temporal information in the authentication process, the proposed model is able to achieve average equal error rates (EER) of ~4.0% and ~2.5% on the Serwadda dataset and Frank dataset, respectively.

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This article explores how Russian television news deconstructed the narrative embracing Ukrainians as ‘brothers’ through repositioning them within an imagined social reality wherein Ukrainians assume the guise of a threatening ‘Other’. The research material comprises extracts from Channel One, which is one of Russia’s most significant and popular television channels. The data was collected from the channel’s website over two years from 1 November 2012 to 31 October 2014. The sample of 480 news stories was selected on the basis of tag words and engagement with the stories on social media. Frames comprising visual, auditory and textual streams were analysed to explore the narratives about Ukrainians that were promulgated both before and during the Ukrainian crisis. The data revealed that, prior to the conflict, the media portrayed Ukraine as Russia’s ‘little brother’. Following Euromaidan, Channel One replaced this guise with that of an enemy in order to appeal directly to the cultural and spiritual values of its audience. Applying the conceptual framework of strategic narrative, the study illustrates the dynamics at play in the transformation of one image into another.

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Recent research has discovered links between patient satisfaction and waiting time perceptions. We examine factors associated with waiting time estimation behaviour and how it can be linked to patient flow modelling. Using data from more than 250 patients, we evaluate machine learning (ML) methods to understand waiting time estimation behaviour in two emergency department areas. Our attribute ranking and selection methods reveal that actual waiting time, clinical attributes, and the service environment are among the top ranked and selected attributes. The classification precision for the true outcome of overestimating waiting times reaches almost 70% and 78% in the waiting area and the treatment room, respectively. We linked the ML results with a discrete-event simulation model. Our scenario analysis reveals that changing staffing patterns can lead to a substantial drop-off in overestimation of waiting times. These insights can be employed to control waiting time perceptions and, potentially, increase patient satisfaction.

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California’s paid family leave (PFL) policy improved mothers’ labor market outcomes, however, the health impacts of this program are less studied. I compare child and parental health of likely eligible households to a series of control groups before and after California’s PFL program was implemented. I find improvements in parent-reported overall child health and suggestive improvements in maternal mental health status. Findings also suggest a reduction in asthma and a greater likelihood that parents feel they are coping well with the day-to-day demands of parenting. There are no significant effects on respiratory or food allergies, or father’s mental health status. The results are robust to multiple control groups and placebo tests.

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Social network sites may have contributed to the global electoral success of populism in important ways. Drawing on the technological affordances of social media, politicians are enabled to directly communicate populist discourse via Twitter by constructing a pervasive societal divide between the “good” people and “corrupt” elites. Such Tweets may resonate with the reality constructions of receivers—who are also enabled to communicate populist discourse online. To understand the intersections of the supply- and demand-sides of populist discourse in the U.S. and Europe, this paper draws on extensive comparative qualitative content analyses of Trump’s and Wilders’ Tweets (N = 2681) and the electorates’ discourse on Facebook (N = 657). The results provide important insights into the mechanisms of inclusion and exclusion at play in populist discourse and the affordances of social media in shaping populist and polarized discourse among politicians and the electorate at election times.

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Firms engage in competitive actions to gain market share and hence to grow their revenues. However, not all firms are equally able to use competitive actions to drive growth. We argue that the ability to translate competitive actions to revenue growth depends on the ownership of the firm. Drawing on principal-agent and principal-principal perspectives, we argue that: (1) private owners (both foreign and local) are better able to employ aggressive actions to grow their business than state owners; (2) firms with multiple owners (especially international joint ventures) are less able to implement actions that drive business growth than full ownership. We find support for these arguments in empirical tests on survey-based data of 106 firms in China. Results show that in an emerging market the principal-principal perspective can better explain governance and competition than the principal-agent perspective.

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