Miracle-dz/UniFAR-FTUs huggingface dataset:
The ecology of football-related crime and disorder

Numerous studies have been conducted on football ‘hooliganism’ with the majority of this work ignoring the immediate, environmental conditions that facilitate opportunities for crime in the football match day context. Consequently, the existing theoretical framework for explaining why crime emerges during football matches remains incomplete. This thesis aims to fill this gap for understanding modern football-related crime and disorder. The thesis uses a predominantly environmental criminology framework to explore whether crime opportunity theories can make sense of crime patterns observed around previously unexplored English domestic football stadia. It is crime event-oriented, focussing on how variation in the ecology of the area around stadia on match days and a set of counterfactual days when the stadium is not used facilitates different criminal opportunities. This is achieved primarily through the analysis of police-recorded crime data for three kilometre areas surrounding a sample of five stadia for the period 2005- 2010. The thesis focuses on three components of crime events - where they occur, when they occur, and why a disproportionate amount of it clusters in some neighbourhoods and not others. Despite the contrasting physical environment around the five stadia, the findings suggest very similar spatial and temporal crime patterns in the area surrounding stadia when they are used relative to when they are not and thus lend support to environmental theories of crime in the football context. The findings also help draw attention to where and when crime is elevated on football match days. The implications of the research for reducing the unintended and unwanted side-effect of football that is desired for the positive utilities it brings, in particular the practicality of employing situational crime prevention in the context of English domestic football are discussed.
GEWEX Continental-scale International Project (GCIP)

The Global Energy and Water Cycle Experiment (GEWEX) represents the World Climate Research Program activities on clouds, radiation, and land-surface processes. The goal of the program is to reproduce and predict, by means of suitable models, the variations of the global hydrological regime and its impact on atmospheric and oceanic dynamics. However, GEWEX is also concerned with variations in regional hydrological processes and water resources and their response to changes in the environment such as increasing greenhouse gases. In fact, GEWEX contains a major new international project called the GEWEX Continental-scale International Project (GCIP), which is designed to bridge the gap between the small scales represented by hydrological models and those scales that are practical for predicting the regional impacts of climate change. The development and use of coupled mesoscale-hydrological models for this purpose is a high priority in GCIP. The objectives of GCIP are presented.
Parallel Neurodegenerative Phenotypes in Sporadic Parkinson’s Disease Fibroblasts and Midbrain Dopamine Neurons

Understanding the mechanisms causing Parkinson’s disease (PD) is vital to the development of much needed early diagnostics and therapeutics for this debilitating condition. Here, we report cellular and molecular alterations in skin fibroblasts of late-onset sporadic PD subjects, that were recapitulated in matched induced pluripotent stem cell (iPSC)-derived midbrain dopamine (DA) neurons, reprogrammed from the same fibroblasts. Specific changes in growth, morphology, reactive oxygen species levels, mitochondrial function, and autophagy, were seen in both the PD fibroblasts and DA neurons, as compared to their respective controls. Additionally, significant alterations in alpha synuclein expression and electrical activity were also noted in the PD DA neurons. Interestingly, although the fibroblast and neuronal phenotypes were similar to each other, they also differed in their nature and scale. Furthermore, statistical analysis revealed novel associations between various clinical measures of the PD subjects and the different fibroblast and neuronal data. In essence, these findings encapsulate spontaneous, in-tandem, disease-related phenotypes in both sporadic PD fibroblasts and iPSC-based DA neurons, from the same patient, and generates an innovative model to investigate PD mechanisms with a view towards rational disease stratification and precision treatments.
Cloud Computing A Social Relations Perspective

The second half of the 20th century has been characterized by an explosive development in information technology (Maney et al 2011). Processing power, storage capacity and network bandwidth have increased exponentially, resulting in new possibilities and shifting IT paradigms. In step with technological changes, the paradigmatic pendulum has swung between increased centralization on one side and a focus on distributed computing that pushes IT power out to end users on the other. With the introduction of outsourcing and cloud computing, centralization in large data centers is again dominating the IT scene. In line with the views presented by Nicolas Carr in 2003 (Carr 2003), it is a popular assumption that cloud computing will be the next utility (like water, electricity and gas) (Buyya et al 2009). However, this assumption disregards the fact that most IT production environments, unlike water and power supply, are in a constant state of change driven by new demands from users and the desire to utilize advances in technology. Research in IT outsourcing (ITO) has documented that social relations play a key role in successful ITO (Lacity et al 2009), for instance, in establishing and maintaining trust between the involved parties (Sabherwal 1999). So far, research in cloud computing has neglected this perspective and focused entirely on aspects relating to technology, economy, security and legal questions. While the core technologies of cloud computing (e.g. virtualization and workload balancing) are tried and tested, the consequences for IT professionals in the affected IT departments have not been studied in detail. Similar to Marston et al. (Marston et al 2011), this paper points to the need for studying the social, relational and inter-organizational challenges associated with the widespread introduction of cloud computing. Based on previous studies in ITO and a review of existing articles on cloud computing, the purpose of this paper is to document a gap in the cloud computing research and identify relevant perspectives to be adopted in future studies of cloud computing.
General Sequential Episodic Memory Model

The state-of-the-art memory model is the General Associative Memory Model, a generalization of the classical Hopfield network. Like its ancestor, the general associative memory has a well-defined state-dependant energy surface, and its memories correlate with its fixed points. This is unlike human memories, which are commonly sequential rather than separated fixed points. In this paper, we introduce a class of General Sequential Episodic Memory Models (GSEMM) that, in the adiabatic limit, exhibit a dynamic energy surface, leading to a series of meta-stable states capable of encoding memory sequences. A multiple-timescale architecture enables the dynamic nature of the energy surface with newly introduced asymmetric synapses and signal propagation delays. We demonstrate its dense capacity under polynomial activation functions. GSEMM combines separate memories, short and long sequential episodic memories, under a unified theoretical framework, demonstrating how energy-based memory modeling can provide robust and scalable memory systems in static and dynamic memory cases.
Historical Border Changes, State Building, and Contemporary Trust in Europe

P olitical borders profoundly influence outcomes central to international politics. Accordingly, a growing literature shows that historical boundaries affect important macro-outcomes such as patterns of interstate disputes and trade. To explain these findings, existing theories posit that borders have persistent effects on individual-level behavior, but the literature lacks empirical evidence of such effects. Combining spatial data on centuries of border changes in Europe with a wide range of contemporary survey evidence, we show that historical border changes have persistent effects on two of the most politically significant aspects of behavior: individuals ’ political and social trust. We demonstrate that in areas where borders frequently changed, individuals are, on average, less trusting of others as well as their governments. We argue that this occurs because border changes disrupt historical state-building processes and limit the formation of interpersonal social networks, which leads to lower levels of trust.
Pigeonpea Baseline and Early Adoption Surveys in South Asia, Insights from TL-II (Phase 1) Project in India.

Pigeonpea is an important pulse crop particularly in the semi-arid tropics of India contributing towards the nutritional security and also generates significant income to small and marginal farmers. Its share in India’s pulse production is around 16%. India is the largest pigeonpea producing country in the world accounting for nearly 67% of the total production. Being a major pigeonpea consumer in the world, India imports around 0.6 million tons of pigeonpea per year to meet the domestic needs from Africa, Nepal and Myanmar. Area and production of pigeonpea in India showed a steady growth until recently. However, the productivity in the country has stagnated between 700 and 800 kg ha-1. Recent initiatives like National Food Security Mission (NFSM), Accelerated Pulse Production Programme (A3P) and enhancement of minimum support price created more interest in pigeonpea growers in the country. Pigeonpea is one of the mandate crops of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and this premier international institute has been contributing significantly to the genetic improvement and crop management in India and Africa during the last four decades. The generous support received from the Bill and Melinda Gates Foundation (BMGF) has provided ICRISAT an opportunity to work more intensively with its research and development partners to demonstrate the potential of new technologies to enhance the yields, raise the profitability and revive the interest of the farmers in pigeonpea crop in India and the strategy chosen is farmer participatory varietal selection (FPVS). This report synthesizes the efforts made under the Tropical Legumes-II Project during the short period of three years (2007-10) in the states of Andhra Pradesh and Maharashtra for pigeonpea crop improvement in India. Overall, the FPVS results established that the new improved varieties outyielded the respective check varieties in the two states. The diffusion and adoption of these varieties increased significantly in the targeted districts. From the past lessons learnt, the report re-focuses on further efforts needed during the second phase of the project to achieve greater success and impact.
Debiased Inference on Treatment Effect in a High-Dimensional Model

Abstract This article concerns the potential bias in statistical inference on treatment effects when a large number of covariates are present in a linear or partially linear model. While the estimation bias in an under-fitted model is well understood, we address a lesser-known bias that arises from an over-fitted model. The over-fitting bias can be eliminated through data splitting at the cost of statistical efficiency, and we show that smoothing over random data splits can be pursued to mitigate the efficiency loss. We also discuss some of the existing methods for debiased inference and provide insights into their intrinsic bias-variance trade-off, which leads to an improvement in bias controls. Under appropriate conditions, we show that the proposed estimators for the treatment effects are asymptotically normal and their variances can be well estimated. We discuss the pros and cons of various methods both theoretically and empirically, and show that the proposed methods are valuable options in post-selection inference. Supplementary materials for this article are available online.
Characterization and Control of Occupational Exposure to Nanoparticles and Ultrafine Particles

Many workers are exposed to a range of particles present on a nanometric scale. In occupational hygiene, it is common to differentiate manufactured nanoparticles (NP) from ultrafine particles (UFP) coming from natural, human or industrial sources. Given that major deficiencies exist in the usual risk assessment approaches for these particles, the objective of this research was to assess occupational UFP and NP exposures. The secondary objective was comprehensive testing of the assessment capabilities regarding occupational NP and UFP exposures in an industrial and laboratory context. Two main types of assessment were performed during this research. The first concerns the assessment of the fine and ultrafine particle concentrations with a particle counter (P-Trak, model 8525), and the second pertains to the assessment of fine and ultrafine particle size distribution with an electrical low pressure impactor (ELPI). The measurements were taken in two welding schools, an aluminium smelter, the research centre of a thermoplastics processing company, and three university laboratories producing and/or using nanoparticles. The results revealed that aluminium smelter workers, people who perform welding tasks, and workers in the thermoplastic processing industry are exposed to UFPs. However, the assessments performed under this study do not reveal high NP concentrations in research laboratories. Only NP production by milling generated detectable NP concentrations. NP handling in glove boxes of two other laboratories seems to prevent worker exposure adequately. There is currently no consensus concerning UFP and NP exposure evaluation measures. However, our findings suggest that the P-Trak is suitable for occupational assessment of UFP concentrations, whereas several uncertainties remain to assess NP exposure, particularly in their agglomerated form. In view of this research, it appears that a characterization and control study of occupational NP and UFP exposure should include assessment of the mass and particle number concentrations, measurement of granulometric distribution and electron microscopic characterization of nanoscale particles. IRSST Characterization and Control of Occupational Exposure to Nanoparticles and Ultrafine Particles v
Acute Hand and Wrist Trauma

Procedure Appropriateness Category Relative Radiation Level Radiography area of interest Usually Appropriate Varies CT area of interest with IV contrast Usually Not Appropriate Varies CT area of interest without and with IV contrast Usually Not Appropriate Varies CT area of interest without IV contrast Usually Not Appropriate Varies MRI area of interest without and with IV contrast Usually Not Appropriate O MRI area of interest without IV contrast Usually Not Appropriate O Bone scan area of interest Usually Not Appropriate ☢☢☢ US area of interest Usually Not Appropriate O
European Journal of Operational Research a Discontinuous Mispricing Model under Asymmetric Information

We study a discontinuous mispricing model of a risky asset under asymmetric information where jumps in the asset price and mispricing are modelled by Lévy processes. By contracting the filtration of the informed investor, we obtain optimal portfolios and maximum expected utilities for the informed and uninformed investors. We also discuss their asymptotic properties, which can be estimated using the instantaneous centralized moments of return. We find that optimal and asymptotic utilities are increased due to jumps in mispricing for the uninformed investor but the informed investor still has excess utility, provided there is not too little or too much mispricing.
Classification using semiparametric mixtures

ABSTRACT A new density-based classification method that uses semiparametric mixtures is proposed. Like other density-based classifiers, it first estimates the probability density function for the observations in each class, with a semiparametric mixture, and then classifies a new observation by the highest posterior probability. By making a proper use of a multivariate nonparametric density estimator that has been developed recently, it is able to produce adaptively smooth and complicated decision boundaries in a high-dimensional space and can thus work well in such cases. Issues specific to classification are studied and discussed. Numerical studies using simulated and real-world data show that the new classifier performs very well as compared with other commonly used classification methods.
International Journal of Information Management Lean Tools and Methods to Support Efficient Knowledge Creation

Article history: Keywords: Dynamic knowledge SECI mode 'ba' Knowledge asset Lean thinking a b s t r a c t Continuous innovation is a key ingredient in maintaining a competitive advantage in the current dynamic and demanding marketplace. It requires an organization to regularly update and create knowledge for the current generation, and reuse it later for the next generation of a product. In this regard, an integrated dynamic knowledge model is targeted to structurally define a practical knowledge creation process in the product development domain. This model primarily consists of three distinct elements; SECI
The Advanced Computing Systems Association Proceedings of the Workshop on Intrusion Detection and Network Monitoring an Eye on Network Intruder-administrator Shootouts an Eye on Network Intruder-administrator Shootouts

Carefully logging network activity is essential to meet the requirements of high security and optimal resource availability. However, detecting break-in attempts within this activity is a difficult task. Making the distinction between misuse and normal use is hard, and identifying intrusions that use novel attacks is fundamentally difficult. In this paper, we introduce a visual approach for analyzing network activity. This approach differs from anomaly and misuse detection because it considers human factors to support the exploration of network traffic. Our prototype application is based on an unsuper-vised neural network and consequently does not rely on any prior knowledge of the data being analyzed. We use self-organizing maps to project the network events on a space appropriate for visualization, and achieve their exploration using a map metaphor. The approach we present can be used to analyze past and present activities , as well as to show trends in the events. To demonstrate the usability of our tools, we describe the investigation of a dataset containing common intrusion patterns. We also discuss some weaknesses of current intrusion detection systems and propose a new paradigm for monitoring network activity that enables the discovery of new, sophisticated, and structured attacks .
The Advanced Computing Systems Association Proceedings of the Workshop on Intrusion Detection and Network Monitoring a Statistical Method for Profiling Network Traffic a Statistical Method for Profiling Network Traffic

Two clustering methods are described and applied to network data. These allow the clustering of machines into " activity groups " , which consist of machines which tend to have similar activity profiles. In addition, these methods allow the user to determine whether current activity matches these profiles, and hence to determine when there is " abnormal " activity on the network. A method for visualizing the clusters is described, and the approaches are applied to a data set consisting of a months worth of data from 993 machines.
Forests and scrublands of northern Fiordland.

The composition and structure of the forests and scrublands of northern Fiordland were recorded at 1,053 sample points. The vegetation at each sample point was classified into one of 16 associations using a combination of Sorensen's 'k' index of similarity, and a multi-linkage cluster analysis. The associations were related to habitat and the distribution of each was determined. The influence of the introduced ungulates, red deer and wapiti, on the forests and scrublands was determined. Stand structure was analysed to provide information on the susceptibility of the vegetation to damage from browsing and on the history of ungulate utilisation of the vegetation. Browse indices were calculated to provide information on current ungulate utilisation of the vegetation. INTRODUCTION A reconnaissance of northern Fiordland was carried out during the summer of 1969-70 by staff of the Forest and Range Experiment Station. The purpose was to describe the composition, structure, and habitat of the forest and scrub associations, to determine both present and past influence of ungulates on them, and to establish a number of permanent reference points to permit measurement of future changes in the vegetation. The area studied lies between the western shores of Lake Te Anau and the Tasman Sea. The southern boundary is the South Fiord of Lake Te Anau, the Esk Burn and Windward River catchments, and Charles Sound; the northern boundary is the Worsley and Transit River catchments (Fig. 1). The total area is ca. 700,000 acres of which almost two-thirds supports a forest or scrub cover. The area is a deeply dissected upland rising to over 6,000ft altitude in places. The highest peaks are the Llawrenny peaks (6,440ft) and Castle Mountain (6,872ft) in the north, and Mt Irene (6,085ft) and Mt Lyall (6,097ft) in the south. The main mountain ranges are the result of considerable late Tertiary and Pleistocene movement on more or less north-trending faults. The main alpine fault follows along the western limits of the survey area and forms a fault-line coast. Successive ice advances in the Pleistocene have extensively modified the landscape to give deeply eroded glacial valleys, fiords, lake basins, cirques (which may be lake filled), sharpened mountain peaks, and aggraded N.Z. JI For . Sci. 1 (1): 80-115 No. 1 Wardle, Hayward, & Herbert —• Forests of Northern Fiordland 81
A history of U.S. Department of Agriculture Forest Service forest survey, 1830-2004

This article provides a summary of a new report on the history of the Forest Survey (Forest Inventory) in the United States as it evolved within the U.S. Department of Agriculture Forest Service over a period of more than 100 years. It draws on the writings of several authors who have published on various aspects of the Forest Survey program. It reviews nine ground-plot designs used in the Forest Survey and Forest Inventory and Analysis (FIA) programs since 1931. The report also highlights the major events contributing to the current FIA, beginning as far back as 1830.
Journal of Emerging Trends in Computing and Information Sciences Drivers' Reading Time Model on Variable Message Signs Using Korean Characters

Variable message sign (VMS) which is used for providing real-time information on traffic conditions and accident occurrences is an important component of intelligent transport systems (ITS). Proper consideration of drivers' message reading time is necessary for designing VMS message phase and duration. The drivers' message reading time depends on various factors, such as the number of information units, the number of lines, character height, drivers' travel speed, and driver characteristics. In this study, a portable VMS (PVMS) using Korean characters was specially manufactured for the study of VMS message reading time, which has three lines with eight characters per line. Various field experiments were conducted using this portable VMS to obtain drivers' message reading time with respect to the above causal factors. The relationships between the drivers' message reading time and various causal factors were statistically tested by ANOVA. Also, regression modeling techniques were applied to develop an estimation model for drivers' message reading time. By the final established model, it is shown that the message reading time is affected by the number of information units, drivers' travel speed, gender and age group.