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What makes Tony Soprano so likeable? Why would we rather leave the cannoli and take the gun? Do we truly want Scarface's Tony Montana to succeed? Is Michael Corleone a misunderstood hero or a despicable villain? Roberto Dainotto traces the complex and fascinating development of the Mafia: its rural beginnings in Western Sicily; its growth into what has been aptly described as a global multinational of crime; and its parallel evolution in music, print and on the big screen. The book probes the tension between the real Mafia - its brutal and often violent reality - and how we imagine it to be: a mythical assembly of codes of honour, family values and chivalric masochism. Rather than dismissing such Mafia stereotypes as untrue, Dainotto sets out to understand what needs and desires, material and psychic longings, are satisfied by our Mafia fantasies. Exploring the rich array of films, books, television, music and even video games portraying and inspired by the Mafia, this book offers not only a social, economic and political history of the Mafia but a new way of understanding our enduring fascination with what lurks behind the sinister omerta of the family business.

The capability of image deraining is a highly desirable component of intelligent decision-making in autonomous driving and outdoor surveillance systems. Image deraining aims to restore the clean scene from the degraded image captured in a rainy day. Although numerous single image deraining algorithms have been recently proposed, these algorithms are mainly evaluated using certain type of synthetic images, assuming a specific rain model, plus a few real images. It remains unclear how these algorithms would perform on rainy images acquired “in the wild” and how we could gauge the progress in the field. This paper aims to bridge this gap. We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy images of various rain types. This dataset highlights diverse rain models (rain streak, rain drop, rain and mist), as well as a rich variety of evaluation criteria (full- and no-reference objective, subjective, and task-specific). We further provide a comprehensive suite of criteria for deraining algorithm evaluation, including full- and no-reference metrics, subjective evaluation, and the novel task-driven evaluation. The proposed benchmark is accompanied with extensive experimental results that facilitate the assessment of the state-of-the-arts on a quantitative basis. Our evaluation and analysis indicate the gap between the achievable performance on synthetic rainy images and the practical demand on real-world images. We show that, despite many advances, image deraining is still a largely open problem. The paper is concluded by summarizing our general observations, identifying open research challenges and pointing out future directions. Our code and dataset is publicly available at http://uee.me/ddQsw.

يناقش كتاب المافيا، الإرث الثقافي والتطور المذهل والرائع للمافيا : بداياتها الريفية في غرب صقلية، نموها إلى ما تم وصفه على نحو مناسب باعتبارها جريمة متعددة الجنسيات وتطورها الموازي في الموسيقى والطباعة والأفلام وهو يحقق التوتر بين المافيا الحقيقية وواقعها الوحشي والعنيف في كثير من الأحيان وهذا الكتاب لا يقدم تاريخا اجتماعيا واقتصاديا وسياسيا للمافيا وحسب، بل طريقة جديدة لفهم سحرنا الدائم مع ما يتربص بها وراء ما يسمى بالمافيا.

Heat spontaneously flows from hot to cold in standard thermodynamics. However, the latter theory presupposes the absence of initial correlations between interacting systems. We here experimentally demonstrate the reversal of heat flow for two quantum correlated spins-1/2, initially prepared in local thermal states at different effective temperatures, employing a Nuclear Magnetic Resonance setup. We observe a spontaneous energy flow from the cold to the hot system. This process is enabled by a trade off between correlations and entropy that we quantify with information-theoretical quantities. These results highlight the subtle interplay of quantum mechanics, thermodynamics and information theory. They further provide a mechanism to control heat on the microscale. The presence of correlations can strongly affect the evolution of a quantum system. Here, the authors directly observe differences in the dynamics of two spins-1/2 systems in an NMR setup depending on the correlations of the initial state, including differences in energy flow and mutual information.

\"A consistent problem that confronts disaster reduction is the disjunction between academic and expert knowledge and policies and practices of agencies mandated to deal with the concern. Although a great deal of knowledge has been acquired regarding many aspects of the gap, such as driving factors, risk construction, complexity of resettlement, and importance of peoples' culture, very little has gotten into protocol and procedure. Disaster Upon Disaster illuminates the numerous disjunctions between the suppositions, realities, agendas, and executions in the field, goes on to detail contingencies, predicaments, old and new plights, and finally advances solutions and the matter of outcomes\"-- Provided by publisher.

We study the sources of women’s underrepresentation in hiring for top management jobs by focusing on the context of executive search. Using data that include proprietary information on 10,970 individuals considered by a search firm, we examine the sources of the low proportion of women placed in senior roles. Contrary to received wisdom, we find limited evidence that demand-side screeners strongly contribute to gender disadvantage in this setting. What gender differences exist tend to play out at the start of the hiring process and are driven both by supply-side and demand-side actors. Once considered for a position, women are no less likely than men to be hired—though they are slightly less likely to be interviewed by the search firm. Our findings highlight the theoretical importance of disentangling candidates’ “self-steering” behavior from the “pipeline bending” of hiring agents. We discuss the implications of our results for understanding gender inequality at upper echelons of the labor market. This paper was accepted by Olav Sorenson, organizations .

In this paper, we propose a novel multiclass classifier for the open-set recognition scenario. This scenario is the one in which there are no a priori training samples for some classes that might appear during testing. Usually, many applications are inherently open set. Consequently, successful closed-set solutions in the literature are not always suitable for real-world recognition problems. The proposed open-set classifier extends upon the Nearest-Neighbor (NN) classifier. Nearest neighbors are simple, parameter independent, multiclass, and widely used for closed-set problems. The proposed Open-Set NN (OSNN) method incorporates the ability of recognizing samples belonging to classes that are unknown at training time, being suitable for open-set recognition. In addition, we explore evaluation measures for open-set problems, properly measuring the resilience of methods to unknown classes during testing. For validation, we consider large freely-available benchmarks with different open-set recognition regimes and demonstrate that the proposed OSNN significantly outperforms their counterparts in the literature.

Non‐primary motor areas, including dorsal premotor cortex (PMd), ventral premotor cortex (PMv), and posterior parietal cortex (PPC), contribute to movement planning, but how these regions differentially shape kinematic features of goal‐directed movements, and how this specialization is associated with functional connectivity within the frontoparietal network, remains of interest, particularly in relation to recovery after stroke. We used functional magnetic resonance imaging (fMRI), transcranial magnetic stimulation (TMS), and kinematic assessments to explore how these areas influence reaching performance in neurologically intact adults. Participants performed a goal‐directed planar reaching task using the KINARM exoskeleton robot. Brief TMS pulse trains were initiated before movement onset to perturb cortical activity at subthreshold and suprathreshold intensities targeting bilateral PMd, PMv, and dorsomedial superior parietal lobule (SPL) within PPC. Resting‐state fMRI quantified functional connectivity among these regions to assess whether connectivity explains stimulation‐induced kinematic changes. Relative to the control target within the postcentral sulcus (PCS), subthreshold stimulation of contralateral PMd and PMv reduced reach efficiency and smoothness, while suprathreshold stimulation of contralateral PPC increased deviation error and reduced smoothness. Among ipsilateral targets, PMd showed consistent TMS‐induced effects, and was the only target where resting‐state connectivity predicted behavioral response. Stronger interhemispheric connectivity in the primary motor cortex and weaker interhemispheric PPC connectivity were associated with greater reductions in straightness and smoothness during subthreshold ipsilateral PMd stimulation. We found that perturbation of premotor and parietal targets led to distinct kinematic effects that varied by site, intensity, and laterality, with premotor stimulation showing the most consistent disruptions at subthreshold intensity and bilateral effects, whereas parietal effects were observed primarily for contralateral stimulation at suprathreshold intensity, and differences in network organization explain variability in behavioral response. Identifying contributions of cortical areas and connectivity patterns may help personalize interventions after stroke. Trial Registration: This study was registered at ClinicalTrials.gov under ID NCT04286516 Key Points Perturbing neural activity in contralateral PMd, PMv, or PPC shortly before movement onset reduced reach straightness and smoothness, supporting their role in the transition from early movement planning to execution. Among ipsilateral targets, only PMd consistently showed TMS‐induced behavioral changes, modulated by individual differences in resting‐state connectivity. Stronger bilateral M1 connectivity and weaker bilateral PPC connectivity were associated with greater sensitivity to ipsilateral PMd stimulation, suggesting that individual connectivity patterns influence responsiveness to stimulation. Transcranial magnetic stimulation (TMS) to the contralateral premotor and parietal cortex altered reaching performance, indicating their role in early movement planning. Among ipsilateral targets, only the dorsal premotor cortex showed consistent effects, which were predicted by resting‐state connectivity. Participants with stronger bilateral primary motor connectivity and weaker parietal connectivity showed greater behavioral sensitivity.