Miracle-dz/UniFAR-FTUs huggingface dataset:
The Crimes and Punishments of the ‘Enemies of the Church’ and the Nature of Russia’s Desecularising Regime1

Following a longstanding sociological tradition, this paper looks at reactions to nonconformity in order to understand the nature of social norms. In particular, it explores the patterns and scope of intolerance towards the perceived ‘enemies of the Church’ in order to understand social norms emerging in post-atheist Russia. Utilising the ‘social drama’ approach, the paper offers a comparative case study of increasingly repressive reactions by the Russian Orthodox Church (ROC) and state to two art exhibitions at the Sakharov Museum and anti-clerical publications by a blogger in Karelia, along with an in-depth analysis of the recent (2012) Pussy Riot action at Christ the Saviour Cathedral in Moscow and the resulting trial and punishment of three of the band’s members, as well as of a variety of events that have followed this initial action. We then utilise national and cross-national representative survey data to suggest that these repressive reactions were congruent with an intolerant public sentiment towards opponents of the ROC. Ultimately, we draw on Durkheim’s dialectic of norm and deviance, work on disciplinary modalities of power by Foucault and Agamben, desecularisation analysis and social identity theory to argue that the severe punishment of the perceived ‘enemies of the Church’ and the popular support for it reflect the crystallisation of a new normative system brought about by the desecularising regime in Russia, a regime which is characterised by a symbiosis of the ROC and the state.
Saving Saba Bank: Policy Implications of Biodiversity Studies

Saba Bank has always been an area of special importance to the neighboring island of Saba in the Netherlands Antilles. Sabans traditionally fished on the Bank as far back as 1907, but increasing foreign fishing pressures on the Bank in the 1970s and 1980s forced many Saban fishermen out. Concerns were compounded by the suspicion that shipping was also damaging the benthic habitat of the bank. Fishery legislation, enacted in 1996, brought an end to unlicensed fishing and established Coast Guard enforcement on the Bank, but also led to protests from neighboring countries that previously fished on the Bank. Research was necessary to support the need for protection. Review of available research of Saba Bank and rapid biological assessments and fisheries surveys since 1996 emphasized the richness of Saba Bank's biodiversity and the need for protection of fisheries stocks. The national nature policy plan recognized this and encouraged further research to base conservation measures on. Recent biological surveys of corals, fishes, and algae presented in this collection of articles emphasized habitat heterogeneity and the relative richness of the marine flora and fauna. These assessments formed the basis for a management plan to protect Saba Bank's biodiversity and a draft proposal to the International Maritime Organization (IMO) seeking Particularly Sensitive Sea Area (PSSA) status for the Bank. The intention of the PSSA proposal is to protect the benthic habitat on Saba Bank from anchor damage. This paper serves to provide the context for the results of the recent biodiversity surveys of Saba Bank. It is hoped that this collection will serve as a knowledge baseline and engender further research in the area.
A Transfer Learning Based Feature Extractor for Polyphonic Sound Event Detection Using Connectionist Temporal Classification

Sound event detection is the task of detecting the type, on-set time, and offset time of sound events in audio streams. The mainstream solution is recurrent neural networks (RNNs), which usually predict the probability of each sound event at every time step. Connectionist temporal classiﬁcation (CTC) has been applied in order to relax the need for exact annotations of onset and offset times; the CTC output layer is expected to generate a peak for each event boundary where the acoustic signal is most salient. However, with limited training data, the CTC network has been found to train slowly, and generalize poorly to new data. In this paper, we try to introduce knowledge learned from a much larger corpus into the CTC network. We train two variants of SoundNet, a deep convolutional network that takes the audio tracks of videos as input, and tries to approximate the visual information extracted by an image recognition network. A lower part of SoundNet or its variants is then used as a feature extractor for the CTC network to perform sound event detection. We show that the new feature extractor greatly accelerates the convergence of the CTC network, and slightly improves the generalization.
A Model of Rapid Memory Formation in the Hippocampal System

Our ability to remember events and situations in our daily life demonstrates our ability to rapidly acquire new memories. There is a broad consensus that the hippocampal system (HS) plays a critical role in the formation and retrieval of such memories. A computational model is described that demonstrates how the HS may rapidly transform a transient pattern of activity representing an event or a situation into a persistent structural encoding via long-term potentiation and long-term depression.
Event composition model: achieving naturalness in runtime enforcement

Runtime enforcement techniques are introduced in the literature to cope with the failures that occur while software is being executed in its target environment. Runtime enforcement techniques contain various concepts that are composed with each other so that the overall functionality of the techniques is achieved. By the term concept we mean a fundamental abstraction or definition that exists in most runtime enforcement techniques. Since the development of runtime enforcement techniques can be complex, runtime enforcement frameworks are proposed to ease the development process. These frameworks offer specification languages to represent the concepts of interest. To facilitate a natural representation of the concepts, this thesis introduces a computation model termed as Event Composition Model, which offers a set of novel linguistic abstractions, called events, event modules, reactors, reactor chains, event composition language and event constraint language. Events represent changes in the states of interest. Event modules are means to group events, have input-output interfaces, and implementations. Reactors are the implementations of event modules. Reactor chains are groups of related reactors that process events in a sequence. The event composition language facilitates selecting the events of interest; and the event constraint language facilitates defining constraints among reactors or event modules. The thesis introduces the EventReactor language as an implementation of Event Composition Model. The language is open-ended for new sorts of events and reactor types. This helps to specify new sorts of concepts. It makes use of the Prolog language as its event composition language. Reactors and reactor chains are parameterizable, and are defined separately from event modules. This increases the reusability of event modules and their implementations. In the EventReactor language, the concepts of interest are represented independently from any programming language, and the compiler of EventReactor supports software developed in Java, C and . Net languages. For distributed software that makes use of Java-RMI as the middleware, the EventReactor language supports distribution-transparent representations of the concepts. There are two basic ways in utilizing the EventReactor language: a) as an underlying language for the specification languages of runtime enforcement frameworks; b) as an implementation language for runtime enforcement techniques.
Energy minimization-based mixture model for image segmentation

A novel mixture model with spatial constraint is proposed for image segmentation. This model assumes that the pixel label prior probabilities are similar if the pixels are geometric close. An energy function is defined on the spatial space for measuring the spatial information. We also derive an energy function on the observed data space from the log-likelihood function of the standard mixture model. We estimate the model parameters and posterior probability by minimizing the combination of the two energy functions, using the gradient descent algorithm. Numerical experiments are presented where the proposed method is tested on synthetic and real world images. These experimental results demonstrate that the proposed method achieves competitive performance compared to spatially variant finite mixture model.
Revealing Graph Bandits for Maximizing Local Influence

We study a graph bandit setting where the objective of the learner is to detect the most influential node of a graph by requesting as little information from the graph as possible. One of the relevant applications for this setting is marketing in social networks, where the marketer aims at finding and taking advantage of the most influential customers. The existing approaches for bandit problems on graphs require either partial or complete knowledge of the graph. In this paper, we do not assume any knowledge of the graph, but we consider a setting where it can be gradually discovered in a sequential and active way. At each round, the learner chooses a node of the graph and the only information it receives is a stochastic set of the nodes that the chosen node is currently influencing. To address this setting, we propose BARE, a bandit strategy for which we prove a regret guarantee that scales with the detectable dimension, a problem dependent quantity that is often much smaller than the number of nodes.
Assessing Capacity to Promote Science-Based Programs: A Key Informant Study of State Teen Pregnancy Prevention Organizations

The purpose of this qualitative study was to identify significant external and internal challenges that state organization leaders face in promoting science-based teen pregnancy prevention programs within their states. The state organization administrators were chosen because their organizations were funded by the U.S. Centers for Disease Control and Prevention (CDC) to promote science-based prevention programs between 2005 and 2010. Given a recent federal infusion of $155 million to replicate science-based programs nationwide, this study is timely. Data reported in this article were collected annually over three years (2006–2009) using semi-structured interviews. External factors influencing success include the states’ socio-political climate, including the impact of abstinence-only programs; internal factors include infrastructure, recruitment, and retention of key partners, organization, board, and staff management and financial sustainability.
REQUIRED READING : THE CANON IN SPANISH AND SPANISH AMERICAN LITERATURE

The required graduate reading lists of 56 leading Ph.D.-granting Spanish faculties in the United States were analyzed to characterize the current canon for Spanish and Spanish American literature. The database consisted of 14,686 items. Little consensus was found regarding authors, and even less for specific works of literature. Only two authors and two works from Spain achieved 100 percent representation on the lists. Thirty-nine authors (one female) and 22 male-authored works from Spain, and 24 authors (two female) and ten male-authored works from Spanish America were present on 75 percent or more of the lists. At the other end of the spectrum, nearly 1,000 different titles appeared just once in the database, demonstrating presence on only a single reading list. The findings show little agreement about what constitutes literary value in this field. This has important implications for graduate education.
Stocator: a high performance object store connector for spark

Data is the natural resource of the 21st century. It is being produced at dizzying rates, e.g., for genomics by sequencers, for Media and Entertainment with very high resolution formats, and for Internet of Things (IoT) by multitudes of sensors. Object Stores such as AWS S3, Azure Blob storage, and IBM Cloud Object Storage, are highly scalable distributed storage systems that offer high capacity, cost effective storage for this data. But it is not enough just to store data; we also need to derive value from it. Apache Spark is the leading big data analytics processing engine. It runs up to one hundred times faster than Hadoop MapReduce and combines SQL, streaming and complex analytics. In this poster we present Stocator, a high performance storage connector, that enables Spark to work directly on data stored in object storage systems.
Characterization of a Transition-Edge Bolometer Made of YBCO Thin Films Prepared by Nonfluorine Metal–Organic Deposition

We present the results of a bolometric transition-edge sensor made of a high-Tc superconductor YBCO thin film prepared by fluorine-free metal-organic deposition. The structure of the films was characterized by X-ray diffraction and scanning electron microscopy, and the superconducting properties were determined by R-T measurements. The applicability of the resulting film as an infrared sensor is reported here. The optical response in the range of near infrared and the noise characteristics of the patterned bolometer are measured and analyzed. The dependence of device sensitivity on the bias current and modulation frequency is also investigated. As it is presented in this paper, the results of the fabricated device are comparable to the devices made of high-quality pulsed laser deposition YBCO thin films.
A practical method for multi-domain clock skew optimization

Clock skew scheduling is an effective technique in performance optimization of sequential circuits. However, with process variations, it becomes more difficult to reliably implement a wide spectrum of clock delays at the registers. Multidomain clock skew scheduling is a good option to overcome this limitation. In this paper, we propose a practical method to efficiently and optimally solve this problem. A framework based on branch-and-bound is carefully designed to search for the optimal clocking domain assignment, and a greedy clustering algorithm is developed to quickly estimate the upper bound of cycle period for a given branch. Experiment results on ISCAS89 sequential benchmarks show both the optimality and efficiency of our method compared with previous works.
Network Working Group Label Switched Path Stitching with Generalized Multiprotocol Label Switching Traffic Engineering (gmpls Te)

Status of This Memo This document specifies an Internet standards track protocol for the Internet community, and requests discussion and suggestions for improvements. Please refer to the current edition of the "Internet Official Protocol Standards" (STD 1) for the standardization state and status of this protocol. Distribution of this memo is unlimited. Abstract In certain scenarios, there may be a need to combine several Generalized Multiprotocol Label Switching (GMPLS) Label Switched Paths (LSPs) such that a single end-to-end (e2e) LSP is realized and all traffic from one constituent LSP is switched onto the next LSP. We will refer to this as "LSP stitching", the key requirement being that a constituent LSP not be allocated to more than one e2e LSP. The constituent LSPs will be referred to as "LSP segments" (S-LSPs). This document describes extensions to the existing GMPLS signaling protocol (Resource Reservation Protocol-Traffic Engineering (RSVP-TE)) to establish e2e LSPs created from S-LSPs, and describes how the LSPs can be managed using the GMPLS signaling and routing protocols. It may be possible to configure a GMPLS node to switch the traffic from an LSP for which it is the egress, to another LSP for which it is the ingress, without requiring any signaling or routing extensions whatsoever and such that the operation is completely transparent to other nodes. This will also result in LSP stitching in the data plane. However, this document does not cover this scenario of LSP stitching.
A law of comparative judgment.

The object of this paper is to describe a new psychophysical law which may be called the law of comparative judgment and to show some of its special applications in the measurement of psychological values. The law of comparative judgment is implied in Weber's law and in Fechner's law. The law of comparative judgment is applicable not only to the comparison of physical stimulus intensities but also to qualitative comparative judgments such as those of excellence of specimens in an educational scale and it has been applied in the measurement of such psychological values as a series of opinions on disputed public issues. The latter application of the law will be illustrated in a forthcoming study. It should be possible also to verify it on comparative judgments which involve simultaneous and successive contrast.
Comparing Learning From Productive Failure and Vicarious Failure

A total of 136 eighth-grade math students from 2 Singapore schools learned from either productive failure (PF) or vicarious failure (VF). PF students generated solutions to a complex problem targeting the concept of variance that they had not learned yet before receiving instruction on the targeted concept. VF students evaluated the solutions generated by PF students before receiving the same instruction. Student-generated solutions were either suboptimal or incorrect, and in this sense can be conceived as failed problem-solving attempts. Although there was no difference on self-reported engagement, PF students reported significantly greater mental effort and interest in knowing the canonical solution to the problem than VF students. When preexisting differences in general ability, math ability, and prior knowledge were controlled, PF students outperformed VF students on conceptual understanding and transfer without compromising procedural fluency. These results suggest that when learning a new math concept, people learn better from their own failed solutions than those of others provided appropriate instruction on the targeted concept is given after the generation or evaluation activity.
Explicit and implicit attitudes of Scottish and Maltese children to national identity

This paper utilised a combination of explicit and implicit techniques to investigate the ways in which children aged 5–16 from two small European nation-states develop in-group favouritism, and positive and/or negative attitudes towards other nation-states. The study adopted a combination of data collection approaches to gain greater evaluation of variability in the responses obtained. Data were analysed statistically for both quantitative and qualitative data. The findings show self-regulation of overt negativity and clearly demonstrate some disquieting outcomes. It poses questions of the extent to which social norms of xenophobia and racism disseminated to children through access to an adult directed media; and what interventions might diminish out-group negativity and prejudice whilst maintaining a level of in-group favouritism that delivers personal self-esteem, and provides the basis for national regard that does not compromise the rights of others.
Trust in B-to-B: Toward a Dynamic and Integrative Approach

The concept of trust in B-to-B has evolved in many directions. This split has created a rich diversity of research development but has also hampered the construction of a coherent theory. The purpose of this article is to present a clear and critical synthesis based upon empirical work on this concept over the last twenty years. While explaining agreements on various definitions, models and measures of the concept, we highlight their main weaknesses. New opportunities to clarify the status of trust are also proposed.
Eight Teachers' Reported Pedagogical Dependency on Basal Readers

This article reports on a qualitative study based on interviews of 8 elementary teachers concerning their beliefs, perceptions, and feelings about reading instruction and the role of basal readers in reading instruction, and their beliefs about the needs fulfilled for students, teachers, parents, and school administrators through classroom reading instruction. Results indicated a conflict between teachers' beliefs and their reported methods of teaching reading. Although teachers believed that basal instruction was not the best way to teach reading, they continued to rely heavily on the basal. The results also indicated that teachers felt that basal reading instruction fulfilled primarily lower-level security needs of students and teachers. Lower-level needs of students were addressed through, for example, skills instruction, grouping, and pacing. Higher-level needs such as self-actualization, knowing and understanding the world, obtaining pleasure from learning, and creativity were rarely met by basal instruction. Basal instruction met only lower-level needs of parents and administrators. Teachers reported that nonbasal instruction satisfied needs associated with enjoyment, creativity, and alleviating pressure to cover a certain amount of material. These results are discussed in terms of critical theory, cognitive dissonance, exchange theory, pressures on teachers related to accountability, professional uncertainty, and contextual aspects of the study. We conclude with a discussion of the need for teacher empowerment in the delivery of reading instruction and implications for further research.
catena-Poly[[(2,2′:6′,2′′-terpyridine-κ3 N,N′,N′′)(tricyanomethanido-κN)nickel(II)]-μ-tricyanomethanido]

In the title complex, [Ni(C4N3)2(C15H11N3)]n, each of the two different NiII atoms is coordinated by one 2,2′:6′2′′-terpyridine (terpy) and three tricyanomethanide ligands in a distorted octahedral geometry. The NiII atoms are linked to each other, forming an infinite chain parallel to (10). π–π Stacking interactions of terpy molecules between adjacent chains (centroid–centroid distance = 3.785 Å), along with weak intermolecular C—H⋯N hydrogen bonds involving the uncoordinated terminal N atoms of the tricyanomethanide ions and the terpyridine H atoms, result in the formation of a three-dimensional network structure.
Structure of Domestic Energy Saving

The purpose of this study is to examine whether we can find, behind the richness of energy-saving behavior, more general behavioral patterns. Specifically, this study compares the one-factor confirmatory model, the two-factor confirmatory model, and the Rasch model, which embody alternative assumptions about the dimensionality of energy-saving behavior. Unlike previous studies, this study uses a confirmatory approach to the testing of alternative models, and covers 10 Organisation for Economic Co-operation and Development (OECD) countries (N = 10,251). This makes our tests rigorous and generalizable beyond a country-specific context. Our results indicate that energy saving is a one-dimensional class of behavior that is a function of individual’s propensity to engage in energy saving and the difficulty of energy-saving behavior. The Rasch model provides a valid and parsimonious representation of energy-saving behavior that outperforms the one- and two-factor models. We also show that the curtailment–efficiency dichotomy is not empirically valid.
Destination loyalty and repeat behaviour: an application of optimum stimulation measurement.

This paper reports on a study of consumer loyalty in the holiday destination selection process. The study does not define loyalty, but attempts to contribute to an understanding of the concept by applying a psychological measure of variety seeking directly to patterns of holiday destination choice. The measure used is based on the optimum stimulation level (OSL) concept. The guiding proposition in this study was that tourists with a high need for variety would display a varied pattern in their vacation destination selection and this assumption is modestly supported by the empirical findings. The results suggest that further experimentation with the OSL would be fruitful when combined with attitudinal measures and with precisely defined sets of tourist behaviours. Copyright © 2004 John Wiley & Sons, Ltd.