Challenging the Constitutive Rules Inviolability Dogma

According to Searle (1969) a constitutive rule creates the very possibility of the entity it rules. Later on, other scholars - such as Benoist (2003), Conte (1983), Guastini (1983) - pointed out the inviolability of constitutive rules. In this paper we want to challenge the inviolability dogma by asking the following question: is it possible to have violations of constitutive rules? We will argue that a parametrical approach to constitutive rules can do away with the inviolability dogma. As a result, our approach allows for violations and introduces two different ways of exiting a game (semantic exit vs. practical exit)

Technical note: Functional sliced inverse regression to infer temperature, water vapour and ozone from IASI data.

A retrieval algorithm that uses a statistical strategy based on dimension reduction is proposed. The methodology and details of the implementation of the new algorithm are presented and discussed. The algorithm has been applied to high resolution spectra measured by the Infrared Atmospheric Sounding Interferometer instrument to retrieve atmospheric profiles of temperature, water vapour and ozone. The performance of the inversion strategy has been assessed by comparing the retrieved profiles to the ones obtained by co-locating in space and time profiles from the European Centre for Medium-Range Weather Forecasts analysi

Spatio-temporal constraints for emissivity and surface temperature retrieval: Preliminary results and comparisons for SEVIRI and IASI observation

Infrared instrumentation on geostationary satellites is now rapidly approaching the spectral quality and accuracy of modern sensors flying on polar platforms. Currently, the core of EUMETSAT geostationary meteorological programme is the Meteosat Second Generation (MSG). However, EUMETSAT is preparing for the Meteosat Third Generation (MTG). The capability of geostationary satellites to resolve the diurnal cycle and hence to provide time-resolved sequences or times series of observations is a source of information which could suitably constrain the derivation of geophysical parameters. Nowadays, also because of lack of time continuity, when dealing with observations from polar platforms, the problem of deriving geophysical parameters is normally solved by considering each single observation as independent of past and future events. For historical reason, the same approach is currently pursued with geostationary observations, which are still being dealt with as they were with polar observations. In this study we show some preliminary results on emissivity and surface temperature retrieval for SEVIRI observations, using the Kalman filter methodology (KF) and compare the retrievals with those obtained using IASI observations co-localized with SEVIRI ones using the times accumulation approach (Optimal Estimation OE). The Sahara desert was chosen as target area, and both SEVIRI and IASI data (infrared radiances and cloud mask) were acquired. The time period considered is that of July 2010 (the whole month). ECMWF analyses for the same date and target area have also been acquired, which comprise Ts, T(p), O(p), Q(p) for the canonical hours 0:00, 6:00, 12:00 and 18:00. Moreover, for the purpose of developing a suitable background for emissivity, the Global Infrared Land Surface Emissivity database developed at CIMSS, University of Wisconsin, derived by MODIS observations was used and was available from the year 2003 till 2011. Concerning the performance of the two methodologies, the retrieval of skin temperature is almost equivalent. The agreement between OE and KF is fairly good if compared with ECMWF analysis for sea surface, while for land surface, OE and KF agree fairly well with ECMWF during the night, but at midday ECMWF shows a cold bias of 10 K and more. For emissivity the comparison with the UW/BFEMIS database for the same date and location is fairly good for both methods

Biological invasions and host–parasite coevolution: different coevolutionary trajectories along separate parasite invasion fronts

Host–parasite coevolution has rarely been observed in natural systems. Its study often relies on microparasitic infections introducing a potential bias in the estimation of the evolutionary change of host and parasite traits. Using biological invasions as a tool to study host–parasite coevolution in nature can overcome these biases. We demonstrate this with a cross-infection experiment in the invasive macroparasite <i>Mytilicola intestinalis</i> and its bivalve host, the blue mussel <i>Mytilus edulis</i>. The invasion history of the parasite is well known for the southeastern North Sea and is characterised by two separate invasion fronts that reached opposite ends of the Wadden Sea (i.e. Texel, The Netherlands and Sylt, Germany) in a similar time frame. The species’ natural history thus makes this invasion an ideal natural experiment to study host–parasite coevolution in nature. We infected hosts from Texel, Sylt and Kiel (Baltic Sea, where the parasite is absent) with parasites from Texel and Sylt, to form sympatric, allopatric and naïve infestation combinations, respectively. We measured infection rate, host condition and parasite growth to show that sympatric host–parasite combinations diverged in terms of pre- and post-infection traits within <100 generations since their introduction. Texel parasites were more infective and more efficient at exploiting the host’s resources. Hosts on Texel, on the other hand, evolved resistance to infection, whereas hosts on Sylt may have evolved tolerance. This illustrates that different coevolutionary trajectories can evolve along separate invasion fronts of the parasite, highlighting the use of biological invasions in studies of host–parasite coevolution in nature

Kalman filter physical retrieval of surface emissivity and temperature from geostationary infrared radiances

The high temporal resolution of data acquisition by geostationary satellites and their capability to resolve the diurnal cycle allows for the retrieval of a valuable source of information about geophysical parameters. In this paper, we implement a Kalman filter approach to applying tempo-ral constraints on the retrieval of surface emissivity and temperature from radiance measurements made from geostationary platforms. Although we consider a case study in which we apply a strictly temporal constraint alone, the methodology will be presented in its general four-dimensional, i.e., space-time, setting. The case study we consider is the retrieval of emissivity and surface temperature from SEVIRI (Spinning Enhanced Visible and Infrared Imager) observations over a target area encompassing the Iberian Peninsula and northwestern Africa. The retrievals are then compared with in situ data and other similar satellite products. Our findings show that the Kalman filter strategy can simultaneously retrieve surface emissivity and temperature with an accuracy of ± 0.005 and ±0.2 K, respectively

UK investment trust portfolio strategies before the First World War

UK investment trust companies were at the forefront of financial innovation during the so-called first globalization era before the First World War. This study examines in detail their portfolio strategies using a unique dataset of 115 portfolio observations for 30 different investment trust companies, comprising a total of 32,708 portfolio holdings. Our results reveal strong performance and relatively sophisticated asset management, which was based on a mixture of a buy-and-hold investment strategy and active portfolio management. Investment trusts employed global rather than domestic diversification. The early predominant investment in bonds in the 1880s gradually declined in favour of ordinary and preferred shares. North and Latin American markets were the main geographical target of UK investment trusts, with less appetite for domestic investments and negligible interest in continental European financial securities. There is significant cross-sectional variation in asset allocation between investment trusts; they thus avoided herding behaviour in portfolio choice and developed a wide range of different portfolio strategies

Violent and non-violent crimes against sex workers : the influence of the sex market on reporting practices in the United Kingdom

Previous research has shown that sex workers experience extremely high rates of victimization but are often reluctant to report their experiences to the police. This paper explores how the markets in which sex workers operate in the United Kingdom impact upon the violent and non-violent crimes they report to a national support organization and their willingness to report victimization to the police. We use a secondary quantitative data analysis of 2,056 crime reports submitted to the UK National Ugly Mugs (NUM) scheme between 2012 and 2016. The findings indicate that although violence is the most common crime type reported to NUM, sex workers operating in different markets report varying relative proportions of different types of victimization. We also argue that there is some variation in the level of willingness to share reports with the police across the different sex markets, even when the type crime, presence of violence, and other variables are taken into account. Our finding that street sex workers are most likely to report victimization directly to the police challenges previously held assumptions that criminalization is the key factor preventing sex workers from engaging with the police. Key words: sex work; violence; policing; reported victimizatio

Risking safety and rights : online sex work, crimes and ‘blended safety repertories'

It has been well established that those working in the sex industry are at various risks of violence and crime depending on where they sell sex and the environments in which they work. What sociological research has failed to address is how crime and safety have been affected by the dynamic changing nature of sex work given the dominance of the internet and digital technologies, including the development of new markets such as webcamming. This paper reports the most comprehensive findings on the internet‐based sex market in the UK demonstrating types of crimes experienced by internet‐based sex workers and the strategies of risk management that sex workers adopt, building on our article in the British Journal of Sociology in 2007. We present the concept of ‘blended safety repertoires’ to explain how sex workers, particularly independent escorts, are using a range of traditional techniques alongside digitally enabled strategies to keep themselves safe. We contribute a deeper understanding of why sex workers who work indoors rarely report crimes to the police, reflecting the dilemmas experienced. Our findings highlight how legal and policy changes which seek to ban online adult services advertising and sex work related content within online spaces would have direct impact on the safety strategies online sex workers employ and would further undermine their safety. These findings occur in a context where aspects of sex work are quasi‐criminalized through the brothel keeping legislation. We conclude that the legal and policy failure to recognize sex work as a form of employment, contributes to the stigmatization of sex work and prevents individuals working together. Current UK policy disallows a framework for employment laws and health and safety standards to regulate sex work, leaving sex workers in the shadow economy, their safety at risk in a quasi‐legal system. In light of the strong evidence that the internet makes sex work safer, we argue that decriminalisation as a rights based model of regulation is most appropriate

Reliability of an automatic classifier for brain enlarged perivascular spaces burden and comparison with human performance

In the brain, enlarged perivascular spaces (PVS) relate to cerebral small vessel disease (SVD), poor cognition, inflammation and hypertension. We propose a fully automatic scheme that uses a support vector machine (SVM) to classify the burden of PVS in the basal ganglia (BG) region as low or high. We assess the performance of three different types of descriptors extracted from the BG region in T2-weighted MRI images: (i) statistics obtained from Wavelet transform’s coefficients, (ii) local binary patterns and (iii) bag of visual words (BoW) based descriptors characterizing local keypoints obtained from a dense grid with the scale-invariant feature transform (SIFT) characteristics. When the latter were used, the SVM classifier achieved the best accuracy (81.16%). The output from the classifier using the BoW descriptors was compared with visual ratings done by an experienced neuroradiologist (Observer 1) and by a trained image analyst (Observer 2). The agreement and cross-correlation between the classifier and Observer 2 (κ = 0.67 (0.58–0.76)) were slightly higher than between the classifier and Observer 1 (κ = 0.62 (0.53–0.72)) and comparable between both the observers (κ = 0.68 (0.61–0.75)). Finally, three logistic regression models using clinical variables as independent variable and each of the PVS ratings as dependent variable were built to assess how clinically meaningful were the predictions of the classifier. The goodness-of-fit of the model for the classifier was good (area under the curve (AUC) values: 0.93 (model 1), 0.90 (model 2) and 0.92 (model 3)) and slightly better (i.e. AUC values: 0.02 units higher) than that of the model for Observer 2. These results suggest that, although it can be improved, an automatic classifier to assess PVS burden from brain MRI can provide clinically meaningful results close to those from a trained observer

Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification

Multivariate analysis of psychological dat