“Driving While Black”: A Theory for Interethnic Integration and Evolution of Prejudice

This paper studies the evolution of interethnic attitudes, the integration or segregation dynamics of ethnic minorities and the conditions for the rising of ethnic-based social hierarchies. By means of a cultural evolution framework, a dynamics of interethnic attitudes is provided and conditions for their convergence derived. Steady states implying a constant role of racism and no role for racism are identified. Deriving sufficient conditions for convergence, we find that the way in which Oblique Socialization Schemes (the way children react to out-of-family stimuli when forming their cultural values) are defined and modelled becomes crucial for the structure of the derived long run equilibria. In particular, we find that Steady States implying an Ethnic-based social ranking or full integration of ethnicities may be reached depending on whether or not agents use Reciprocity and/or Ethnocentrism in their interethnic attitudes formation schemes. Allowing different groups for asymmetric use of reciprocity and Ethnocentrism, we explain why different ethnic minorities may show different integration patterns, and what are the different roles (Cultural bridge, cultural hub) an ethnic group may play in the integration process. Moreover, in this way, we explain why attitudes of some groups towards others converge to the same values, while other groups seems to be excluded from this process. At last, we provide the first steps for the endogeneization of socialization structures.Cultural transmission, Minority integration, Evolution of preferences

The urban-rural employment shift in Western Europe - an empirical analysis of the employment and population development in Britain, Germany and Italy

The aim of this paper is to investigate the continuity and the driving forces of the urban-rural employment shift in Western Europe. Based on a comparable area typology for the three case study states Britain, Germany and Italy, the study finds out that since the 1970s rural areas have overall been performing much better than urban areas. In contrast, for the 1990s the thesis of an urban-rural shift of jobs and population cannot be verified without qualifications. Even though there are rural regions that are outperforming the conurbations in terms of employment and population growth, the overriding trend has been a polarisation within the rural areas as well as within the conurbations. Concerning the determinants of rural growth, the study identifies two possible explanations: First, the above-average development of the manufacturing industries in rural areas, and second, the existence of specific "rural location factors" such as land availability, a loyal labour force and a high quality of life.

A stochastic interspecific competition model to predict the behaviour of Listeria monocytogenes in the fermentation process of a traditional Sicilian salami

The present paper discusses the use of modified Lotka-Volterra equations in order to stochastically simulate the behaviour of Listeria monocytogenes and Lactic Acid Bacteria (LAB) during the fermentation period (168 h) of a typical Sicilian salami. For this purpose, the differential equation system is set considering T, pH and aw as stochastic variables. Each of them is governed by dynamics that involve a deterministic linear decrease as a function of the time t and an "additive noise" term which instantaneously mimics the fluctuations of T, pH and aw. The choice of a suitable parameter accounting for the interaction of LAB on L. monocytogenes as well as the introduction of appropriate noise levels allows to match the observed data, both for the mean growth curves and for the probability distribution of L. monocytogenes concentration at 168 h.Comment: 19 pages, 2 figures, 2 tables. To be published in Eur. Food Res. Techno

A formula for the relative entropy in chiral CFT

We prove the QNEC on the Virasoro nets for a class of unitary states extending the coherent states, that is states obtained by applying an exponentiated stress energy tensor to the vacuum. We also verify the Bekenstein Bound by computing the relative entropy on a bounded interval

Fluid injections in the subsurface: a multidisciplinary approach for better understanding their implications on induced seismicity and the environment.

Fluid injections in the subsurface are common operations in underground industrial activities such as oil and gas exploitation, geothermal energy development, and carbon capture and storage (CCS). In recent years, it became a focal point as new drilling technologies (e.g., hydraulic fracturing) enable the extraction of oil and gas in unconventional reservoirs and the development of CCS injection techniques became a key research topic in the context of the low-carbon energy transition. Fluid injections have drawn the attention also in the general public because of their main potential implications such as the induced seismicity phenomenon (Rubinstein and Mahani, 2015) and the environmental pollution (Burton et al., 2016, Pitchel et al., 2016). Considering the strong socioeconomic impact of fluid injection operations (National Research Council, 2013; Ellsworth, 2013; Grigoli et al., 2017) the current research in this field needs the integration of multidisciplinary studies, involving knowledge on geology, seismology, source physics, hydrogeology, fluid geochemistry, rocks geomechanics for a complete understanding of the phenomenon and to set-up the most effective and “best practice” protocols for the monitoring of areas where injection operation are performed. On this basis, this work applied a multidisciplinary approach integrating seismological methods, geochemical studies, and machine learning techniques. Two key-study areas characterized by high fluid-rock interaction and fluid-injection in the subsurface were analyzed: i) the High Agri Valley (hereinafter HAV), hosting the largest onshore oil field in West Europe, in which wastewater disposal operations have been carried out since 2006 at the Costa Molina 2 injection well and where both natural and induced seismicity clusters were recognized; ii) the Mefite d’Ansanto, the largest natural emission of CO2-rich gases with mantle-derived fluids (from non‐volcanic environment) ever measured on the Earth (Carcausi et al., 2013; Caracausi and Paternoster, 2015; Chiodini et al, 2010). Regarding the HAV study area, we reconstructed the preliminary catalogue of seismicity through accurate absolute locations in a 3D-velocity model (Serlenga and Stabile, 2019) of earthquakes detected from the local seismic INSIEME network managed by the CNR-IMAA. A total of 852 between local tectonic and induced earthquakes occurred in the HAV between September 2016 and March 2019. We tested the potential of the unsupervised machine-learning approach as an automated tool to make faster dataset exploratory analysis, founding the density-based approach (DBSCAN algorithm-Density-Based Spatial Clustering of Applications with Noise, Ester et al., 1996) particularly suitable for the fast identification of clusters in the catalogue resulting from both injection-induced events and tectonic local earthquake swarms. Moreover, we proposed a semi-automated workflow for earthquake detection and location with the aim to improve the current standard procedures, quite time-consuming and strictly related to human operators. The workflow, integrating manual, semi-automatic and automatic detection and location methods enabled us to characterize a low magnitude natural seismic sequence occurred in August 2020 in the southwestern area of the HAV (Castelsaraceno sequence) in a relatively short time with respect to the application of standard techniques, thus representing a starting point for the improvement of the efficiency of seismic monitoring techniques of both anthropogenic and natural seismicity in the HAV. Our multidisciplinary approach involved the geochemical study of the HAV groundwaters with the aim to: (1) determine the geochemical processes controlling the chemical composition; (2) define a geochemical conceptual model regarding fluid origin (deep vs shallow) and mixing processes by means isotopic data; (3) establish a geochemical baseline for the long-term environmental monitoring of the area. A total of 39 water samples were collected from springs and wells located at the main hydro-structures bordering the valley to determine chemical (major, minor and trace elements) and isotopic composition (e.g., dD, d18O, d13C-TDIC and noble gas). All investigated water samples have a meteoric origin, although some springs show long and deep flow than the other ones, and a bicarbonate alkaline-earth composition, thus suggesting the carbonate hydrolysis as the main water-rock interaction process. Our results demonstrated that HAV groundwater is chemically suitable for drinking use showing no criticalities for potentially toxic metals reported by the Italian and European legislation guidelines. Particular attention was given on thermal water of Tramutola well, built by Agip S.p.a. for oil & gas exploration, with the occurrence of bubbling gases. The geochemical study highlighted a substantial difference of these CH4-dominated thermal fluids with the rest of the dataset. Helium isotope (3He/4He) indicate a prevalent radiogenic component with a contribution of mantle-derived helium (~20%) and the average δ13C-CO2 value is of – 4.6 ‰ VPDB, consistent with a mantle origin. Methane isotope composition indicates a likely microbial isotopic signature (δ13C-CH4 =−63.1‰, −62.4‰, δD-CH4=−196‰, −212‰), probably due to biodegradation processes of thermogenic hydrocarbons. The methane output at the well, evaluated by means of anemometric measurement of the volume flow (m3/h) is of ~156 t/y, that represent about 1.5% of total national anthropogenic sources related to fossil fuel industry (Etiope et al., 2007). Our work highlighted that Tramutola well may represent a key natural laboratory to better understand the complex coupling effects between mechanical and fluid-dynamic processes in earthquake generation. Moreover, the integration of seismic and geochemical data in this work allowed us to identify the most suitable locations for the future installation of multiparametric stations for the long-term monitoring of the area and development of integrated research in the HAV. Regarding the Mefite d’Ansanto, we analyzed the background seismicity in the emission area recorded by a dense temporary seismic network deployed at the site between 30-10-2019 and 02-11-2019. First, we implemented and tested an automated detection algorithm based on non-parametric statistics of the recorded amplitudes at each station, collecting a total dataset of 8561 events. Then, both unsupervised (DBSCAN) and supervised (KNN-k-nearest neighbors classification, Fix & Hodges, 1951) machine learning techniques were applied, based on specific parameters (duration, RMS-amplitude and arrival slope) of the detected events. DBSCAN algorithm allowed to determine characteristic bivariate correlations among tremors parameters: a high linear correlation (r~0.6-0.7) between duration and RMS-amplitude and a lower one (r~0.5-0.6) between amplitude and arrival slope (first arrival parametrization). These relationships let us to define training samples for the KNN algorithm, which allowed to classify tremor signals at each station and to automatically discriminate between tremors and accidentally detected anthropogenic noise. Results allowed to extract new information on seismic tremor at Mefite d’Ansanto, previously poorly quantitively analyzed, and its discrimination, thus providing a starting workflow for monitoring the non-volcanic emission. Isotopic geochemistry (3He/4He, 4 He/20Ne, δ13CCO2) indicated a mixing of mantle (30%-40%) and crust-derived fluids. The source location of the emission related tremor would represent a step forward in its characterization, and for setting up more advanced automated detection and machine learning classification techniques to exploit the information provided by seismic tremor for an improved automatic monitoring of non-volcanic, CO2 -gas emissions

A Repository of Cloud Services for Small and Micro Enterprises

According to the Association for Enterprise Opportunity (AEO), there are over 23 million microenterprises in the U.S and that number translates to 87% of all businesses in the United States. While the majority of businesses around the world are small and microenterprises, they are the most vulnerable and are often run by people with limited resources, and skills to be able to avail the benefits of Information and Communication Technologies. When they do adopt Information Technology their potential to survive and grow increases as they are then able to participate in the global economy. The challenge for global development lies in enabling these small and microenterprises to first become aware of the available technologies and then to adopt the appropriate technology solution that fits their needs. Cloud computing offers an opportunity to support the growth and development of small and microenterprises by enabling low cost IT solutions delivered over the Internet to be made available to them so that they may adopt with little effort or skill. The contribution of this study is in facilitating the first step towards this goal by developing an online repository of cloud services that are categorized by common business needs. This online repository serves as a “one-stop” location for small and micro enterprise entrepreneurs looking for cost-effective options to meet their business goals and bring about improved administrative efficiencies

Should we perform multiparametric magnetic resonance imaging of the bladder before transurethral resection of bladder? Time to reconsider the rules

We would like to congratulate Ueno and colleagues [1] on their paper on diagnostic accuracy and interobserver agreement for the new Vesical Imaging-Reporting and Data System (VI-RADS) [2] for muscle-invasive bladder cancer (MIBC) in this issue of European Urology. Their report on 74 patients who underwent multiparametric magnetic resonance imaging (mpMRI) before transurethral resection of bladder tumor (TURBT) raises great interest in the RADS (Reporting and Data Systems) era. They address the questions of reproducibility and diagnostic performance of mpMRI in the setting of bladder ca (BC), in which potential applications of this imaging technique have seen constant growth in the past decades without a definitive role having been identified

Evaluating Regional Governance - Methodological Concerns and Practical Experiences

Since the early 1990s, new forms of regional governance have spread over Western Europe: In many countries, the competencies and ressources of the subnational level have been reinforced (Jessop 1997). In parallel, there has been a shift from hyrarchical modes of government to more flexible, network-based types of governance. These are largely based on the cooperation of public and private actors as well as the civic sector (Benz 2003, Healey 2002 a.o.). Despite its popularity, the regional governance approach has so far only rarely been evaluated systematically. There might be several reasons for this shortcoming. First, the regional governance concept still lacks a clear definition; without knowing what regional governance is, it is hardly feasible to “test” for its outcomes. Moreover, regional governance systems and processes are marked by continuous and rapid transformations. Hence it is difficult to capture their impacts. Finally, the complexity of regional development processes render the assessment of the institutional background a methodological challenge. In the face of these considerations, this paper pursues a threefold objective. First, the authors explain the various needs of evaluating regional governance approaches. These include matters of efficiency as well as cohesion and accountability. Second, the paper discusses the methodological pitfalls and tasks that evaluators need to tackle in order to assess the benefits and weaknesses of regional governance processes . Third, the paper povides an insight into German evaluation experiences in the field, namely some first results from an evaluation of regional cooperation processes in Northrhine-Westfalia carried out at the ILS NRW in Dortmund. The paper concludes by deducing recommendations on how to evaluate regional governance.