Miracle-dz/UniFAR-FTUs huggingface dataset:
Community variations in hoax calls and suspicious fires : Geographic , temporal and socio-economic dimensions and trajectories

This is a project supported by a grant from the Criminology Research Grants. The views expressed are the responsibility of the author and are not necessarily those of the Council. Descriptive mapping and analysis of malicious hoax calls 38 Descriptive mapping and analysis of suspicious fires 46 Summary of descriptive mapping and analysis 53 Understanding the dynamics of suspicious fires and malicious hoax calls The present project seeks to better understand the spatial dynamics of suspicious fires and malicious hoax calls across Queensland. Currently an extensive body of empirical research considers the psychological motivations and disorders related to fire setting behaviour. Not surprisingly policy and prevention initiatives also focus on individual behaviours or predispositions. While some studies are beginning to consider the spatial and environmental characteristics where fires occur, the current project is the first to examine fire incidents over such a large geographic area (State of Queensland) and time period (13 years). In so doing it makes central the spaces in which malicious hoax calls and suspicious fires occur and how these incidents in these spaces change over time. This research aims to examine and capture the spatial and temporal patterning of malicious hoax calls and suspicious fires across Queensland. It takes a longitudinal approach examining the geographical trajectories of malicious hoax calls and suspicious fires over time. This project aims to identify changing patterns of malicious hoax calls and suspicious fires over time by categorising changes into persistent, transient or emergent spatial concentrations. Further it identifies the most salient socioeconomic characteristics of spatial areas that predict the occurrence and spatial patterning of malicious hoax calls and suspicious fires. Methodology This project employed three analytic techniques to examine the spatial dynamics of malicious hoax calls and suspicious fires over time: (1) cluster mapping; (2) geographically weighted regression, and; (3) trajectory modelling. These techniques required an integrated data file which was a major undertaking of the project. The sources necessary to conduct this study included Queensland Fire and Rescue Service incident data across 13 years and key variables drawn from the 1996, 2001, and 2006 Australian Bureau of Statistics (ABS) Censuses that were concorded to 2006 Census boundaries. Our cluster mapping analyses employed spatial autocorrelation statistics across time to examine the correlations among spatial areas in relation to fire incidents and to identify clusters or 'hot spots' of fire incidents. The second approach utilised geographically weighted regression to analyse spatial …
Opportunities and Challenges of Peer-to-Peer Internet Video Broadcast

There have been tremendous efforts and many technical innovations in supporting real-time video streaming in the past two decades, but cost-effective large-scale video broadcast has remained an elusive goal. Internet protocol (IP) multicast represented an earlier attempt to tackle this problem but failed largely due to concerns regarding scalability, deployment, and support for higher level functionality. Recently, peer-to-peer based broadcast has emerged as a promising technique, which has been shown to be cost effective and easy to deploy. This new paradigm brings a number of unique advantages such as scalability, resilience, and effectiveness in coping with dynamics and heterogeneity. While peer-to-peer applications such as file download and voice-over-IP have gained tremendous popularity, video broadcast is still in its early stages, and its full potential remains to be seen. This paper reviews the state-of-the-art of peer-to-peer Internet video broadcast technologies. We describe the basic taxonomy of peer-to-peer broadcast and summarize the major issues associated with the design of broadcast overlays. We closely examine two approaches - tree-based and data-driven - and discuss their fundamental tradeoff and potential for large-scale deployment. Lastly, we outline the key challenges and open problems and highlight possible avenues for future directions.
Something in the way people move: the benefit of facial movements in face identification

While the dissociation between invariant aspects of a face and emotional expressions has been studied extensively, the role of non-emotional changeable aspects in face recognition has been considered in the literature rarely. The purpose of the present study was to understand whether information on changeable aspects (with and without emotional content) can help those individuals with poor face recognition abilities (when based on invariant features) in recognizing famous faces. From a population of 80 university students we selected two groups of participants, one with poor performance (experimental group, EG) and the other with good performance (control group, CG). By means of a preliminary experiment, we selected videos of 16 Italian celebrities that were presented in three different conditions: motionless, with non-emotional expressions, and with emotional expressions. While the CG did not differ in the three conditions, the EG showed a significantly better performance in the two conditions with facial movements, which did not differ between each other. These results suggest a role of changeable aspects in the identification of famous faces, rising only in the case invariant features are not analyzed properly.
Digital Education Platforms as Catalysts for Entrepreneurial Ventures

This study looks at the dynamic relationship between digital education platforms and entrepreneurial ventures, specifically the impact on skill development, global connectivity, and integration into entrepreneurial practices. This research investigates the experiences of business owners who have tried their hand at online education by employing a mixed-methods approach that includes qualitative in-depth interviews and thematic analysis. The findings show a symbiotic relationship, emphasizing the importance of digital education platforms in developing a diverse set of skills required for entrepreneurial success, fostering global networking opportunities, and facilitating real-time learning. The study also recognizes challenges, such as reliability issues and information overload, emphasizing the importance of addressing these limitations. This study adds to the evolving discussion about the transformative impact of digital learning on entrepreneurship, providing useful insights for individuals, educators, and policymakers navigating this dynamic intersection.
A Convergent Online Single Time Scale Actor Critic Algorithm

Actor-Critic based approaches were among the first to address reinforcement learning in a general setting. Recently, these algorithms have gained renewed interest due to their generality, good convergence properties, and possible biological relevance. In this paper, we introduce an online temporal difference based actor-critic algorithm which is proved to converge to a neighborhood of a local maximum of the average reward. Linear function approximation is used by the critic in order estimate the value function, and the temporal difference signal, which is passed from the critic to the actor. The main distinguishing feature of the present convergence proof is that both the actor and the critic operate on a similar time scale, while in most current convergence proofs they are required to have very different time scales in order to converge. Moreover, the same temporal difference signal is used to update the parameters of both the actor and the critic. A limitation of the proposed approach, compared to results available for two time scale convergence, is that convergence is guaranteed only to a neighborhood of an optimal value, rather to an optimal value itself. The single time scale and identical temporal difference signal used by the actor and the critic, may provide a step towards constructing more biologically realistic models of reinforcement learning in the brain.
A Clinical Prediction Rule for the Severity of Congenital Diaphragmatic Hernias in Newborns

BACKGROUND: Congenital diaphragmatic hernia (CDH) is a condition with a highly variable outcome. Some infants have a relatively mild disease process, whereas others have significant pulmonary hypoplasia and hypertension. Identifying high-risk infants postnatally may allow for targeted therapy. METHODS: Data were obtained on 2202 infants from the Congenital Diaphragmatic Hernia Study Group database from January 2007 to October 2011. Using binary baseline predictors generated from birth weight, 5-minute Apgar score, congenital heart anomalies, and chromosome anomalies, as well as echocardiographic evidence of pulmonary hypertension, a clinical prediction rule was developed on a randomly selected subset of the data by using a backward selection algorithm. An integer-based clinical prediction rule was created. The performance of the model was validated by using the remaining data in terms of calibration and discrimination. RESULTS: The final model included the following predictors: very low birth weight, absent or low 5-minute Apgar score, presence of chromosomal or major cardiac anomaly, and suprasystemic pulmonary hypertension. This model discriminated between a population at high risk of death (∼50%) intermediate risk (∼20%), or low risk (<10%). The model performed well, with a C statistic of 0.806 in the derivation set and 0.769 in the validation set and good calibration (Hosmer-Lemeshow test, P = .2). CONCLUSIONS: A simple, generalizable scoring system was developed for CDH that can be calculated rapidly at the bedside. Using this model, intermediate- and high-risk infants could be selected for transfer to high-volume centers while infants at highest risk could be considered for advanced medical therapies.
Isolation prevalence of pulmonary nontuberculous mycobacteria in Ontario in 2007.

BACKGROUND The reported prevalence of pulmonary nontuberculous mycobacteria (NTM) infections is increasing. OBJECTIVE To determine the 'isolation prevalence' of NTM in 2007 and compare it with previously published research that examined the increasing rates of isolation of NTM from clinical pulmonary specimens between 1997 and 2003. METHODS Isolation prevalence was investigated retrospectively by reviewing a cohort of all positive pulmonary NTM culture results from the Tuberculosis and Mycobacteriology Laboratory, Public Health Laboratory (Toronto, Ontario) in 2007, which identifies at least 95% of NTM isolates in Ontario. Isolation prevalence was calculated as the number of persons with a pulmonary isolate in a calendar year divided by the contemporary population and expressed per 100,000 population. Changes in isolation prevalence from previous years were assessed for statistical significance using generalized linear models with a negative binomial distribution. RESULTS In 2007, 4160 pulmonary isolates of NTM were collected from 2463 patients. The isolation prevalence of all species (excluding Mycobacterium gordonae) was 19 per 100,000 population in 2007 - an increase from previous observations reported for Ontario - corresponding to an average annual increase of 8.5% from 1997 to 2007 (P<0.0001). Average annual increases in isolation prevalence of Mycobacterium avium complex (8.8%, P<0.0001) and Mycobacterium xenopi (7.3%, P=0.0005) were largely responsible for the overall increase, while prevalence rates of rapidly growing mycobacteria remained relatively stable. CONCLUSION The isolation prevalence of pulmonary NTM continues to increase significantly in Ontario, supporting the belief that pulmonary NTM disease is increasingly common.
Flow dynamics over a foredune scarp

The nature of wind flow over a small, 0.6 m high foredune scarp is investigated on the Sir Richard Peninsula, South Australia during a variety of incident wind directions and speeds. The study provides additional supporting evidence that the presence of the scarp and the dune exerts a strong influence on a landwards trending reduction in wind velocity and an increase in turbulence, with the greatest area of turbulence occurring near and at the foredune scarp base. For an incident oblique wind, an alongshore helicoidal flow is formed within a separation region along the scarp basal region. In this region, the coefficient of variation (CV) of wind speed is high and displays significant fluctuations. The flow at the scarp crest is compressed, streamlined and accelerated, turbulence is suppressed, and local jets may occur depending on the incident wind approach angle. Jets are more likely where the incident flow is perpendicular or nearly so. A flow separation region does not develop downwind of the scarp crest where the morphology of the foredune stoss slope downwind of the scarp is more convex (as in this case) rather than relatively flat, and possibly due to the presence of vegetation at the scarp crest. A tentative model of the flow regions developed across a backshore–scarp–foredune region during oblique incident flow is provided. © 2018 John Wiley & Sons, Ltd.
Medium Voltage Smart Grid: Experimental Analysis of Secondary Substation Narrow Band Power Line Communication

This paper is focused on the possibility of employing narrow band power line communication (PLC) in medium voltage (MV) distribution networks. The topic is investigated by means of both simulations and experimental tests, which were carried out in the distribution network of Ustica Island. In detail, a two-way MV communication was tested between two secondary substations connected by an MV cable power line. Each substation has a by-pass connection at MV bus-bars and an MV/LV oil filled power transformer. In this paper, the MV and the PLC systems under test are described and the experimental tests are presented, which were carried out to evaluate the parameters of the simulation model. The aforesaid model is described and a comparison is shown between simulation and results of experiments, which were carried out in the presence of voltage net, i.e., 24 kV. Finally, the possibility is investigated of a reliable communication and the faster achievable bit-rate; the analysis is performed by means of further experimental results of several communication tests, which were carried out with different modulation techniques.
Gaze-touch: combining gaze with multi-touch for interaction on the same surface

Gaze has the potential to complement multi-touch for interaction on the same surface. We present gaze-touch, a technique that combines the two modalities based on the principle of 'gaze selects, touch manipulates'. Gaze is used to select a target, and coupled with multi-touch gestures that the user can perform anywhere on the surface. Gaze-touch enables users to manipulate any target from the same touch position, for whole-surface reachability and rapid context switching. Conversely, gaze-touch enables manipulation of the same target from any touch position on the surface, for example to avoid occlusion. Gaze-touch is designed to complement direct-touch as the default interaction on multi-touch surfaces. We provide a design space analysis of the properties of gaze-touch versus direct-touch, and present four applications that explore how gaze-touch can be used alongside direct-touch. The applications demonstrate use cases for interchangeable, complementary and alternative use of the two modes of interaction, and introduce novel techniques arising from the combination of gaze-touch and conventional multi-touch.
Affective attention under cognitive load: reduced emotional biases but emergent anxiety-related costs to inhibitory control

Trait anxiety is associated with deficits in attentional control, particularly in the ability to inhibit prepotent responses. Here, we investigated this effect while varying the level of cognitive load in a modified antisaccade task that employed emotional facial expressions (neutral, happy, and angry) as targets. Load was manipulated using a secondary auditory task requiring recognition of tones (low load), or recognition of specific tone pitch (high load). Results showed that load increased antisaccade latencies on trials where gaze toward face stimuli should be inhibited. This effect was exacerbated for high anxious individuals. Emotional expression also modulated task performance on antisaccade trials for both high and low anxious participants under low cognitive load, but did not influence performance under high load. Collectively, results (1) suggest that individuals reporting high levels of anxiety are particularly vulnerable to the effects of cognitive load on inhibition, and (2) support recent evidence that loading cognitive processes can reduce emotional influences on attention and cognition.
An Efficient Numerical Method for the Solution of the L2 Optimal Mass Transfer Problem

In this paper we present a new computationally efficient numerical scheme for the minimizing flow approach for the computation of the optimal L(2) mass transport mapping. In contrast to the integration of a time dependent partial differential equation proposed in [S. Angenent, S. Haker, and A. Tannenbaum, SIAM J. Math. Anal. , 35 (2003), pp. 61-97], we employ in the present work a direct variational method. The efficacy of the approach is demonstrated on both real and synthetic data.
Circadian and wake-dependent influences on subjective sleepiness, cognitive throughput, and reaction time performance in older and young adults.

STUDY OBJECTIVES To assess circadian and homeostatic influences on subjective sleepiness and cognitive performance in older adults when sleep and waking are scheduled at different times of day; to assess changes in subjective sleepiness and cognitive performance across several weeks of an inpatient study; and to compare these findings with results from younger adults. DESIGN Three 24-h baseline days consisting of 16 h of wakefulness and an 8-h sleep opportunity followed by 3-beat cycles of a 20-h forced desynchrony (FD) condition; 18 20-h "days," each consisting of 13.33 h of scheduled wakefulness and 6.67 h of scheduled sleep opportunity. SETTING Intensive Physiological Monitoring Unit of the Brigham and Women's Hospital General Clinical Research Center. PARTICIPANTS 10 healthy older adults (age 64.00 +/- 5.98 y, 5 females) and 10 healthy younger adults (age 24.50 +/- 3.54 y, 5 females). INTERVENTIONS Wake episodes during FD scheduled to begin 4 h earlier each day allowing for data collection at a full range of circadian phases. MEASUREMENTS AND RESULTS Subjective sleepiness, cognitive throughput, and psychomotor vigilance assessed every 2 h throughout the study. Core body temperature (CBT) data collected throughout to assess circadian phase. Older subjects were less sleepy and performed significantly better on reaction time (RT) measures than younger subjects. Decrements among younger subjects increased in magnitude further into the experiment, while the performance of older subjects remained stable. CONCLUSIONS Our findings demonstrate that the waking performance and alertness of healthy older subjects are less impacted by the cumulative effects of repeated exposure to adverse circadian phase than that of young adults. This suggests that there are age-related changes in the circadian promotion of alertness, in the wake-dependent decline of alertness, and/or in how these 2 regulatory systems interact in healthy aging.
Exceptionally high whole-rock δ18O values in intra-caldera rhyolites from Northeast Iceland

ABSTRACT The Icelandic crust is characterized by low δ18O values that originate from pervasive high-temperature hydrothermal alteration by 18O-depleted meteoric waters. Igneous rocks in Iceland with δ18O values significantly higher than unaltered oceanic crust (~5.7‰) are therefore rare. Here we report on rhyolitic intra-caldera samples from a cluster of Neogene central volcanoes in Borgarfjörður Eystri, Northeast Iceland, that show whole-rock δ18O values between +2.9 and +17.6‰ (n = 6), placing them among the highest δ18O values thus far recorded for Iceland. Extra-caldera rhyolite samples from the region, in turn, show δ18O whole-rock values between +3.7 and +7.8‰ (n = 6), consistent with the range of previously reported Icelandic rhyolites. Feldspar in the intra-caldera samples (n = 4) show δ18O values between +4.9 and +18.7‰, whereas pyroxene (n = 4) shows overall low δ18O values of +4.0 to +4.2‰, consistent with regional rhyolite values. In combination with the evidence from mineralogy and rock H2O contents, the high whole-rock δ18O values of the intra-caldera rhyolites appear to be the result of pervasive isotopic exchange during subsolidus hydrothermal alteration with 18O-enriched water. This alteration conceivably occurred in a near-surface hot spring environment at the distal end of an intra-caldera hydrothermal system, and was probably fed by waters that had already undergone significant isotope exchange with the country rock. Alternatively, 18O-enriched alteration fluids may have been produced during evaporation and boiling of standing water in former caldera lakes, which then interacted with the intra-caldera rock suites. Irrespective of the exact exchange processes involved, a previously unrecognized and highly localized δ18O-enriched rock composition exists on Iceland and thus probably within the Icelandic crust too.
Neural network-based model reference adaptive control system

In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.
Formalizing Randomized Matching Algorithms

Using Jerábek's framework for probabilistic reasoning, we formalize the correctness of two fundamental RNC^2 algorithms for bipartite perfect matching within the theory VPV for polytime reasoning. The first algorithm is for testing if a bipartite graph has a perfect matching, and is based on the Schwartz-Zippel Lemma for polynomial identity testing applied to the Edmonds polynomial of the graph. The second algorithm, due to Mulmuley, Vazirani and Vazirani, is for finding a perfect matching, where the key ingredient of this algorithm is the Isolating Lemma.