Miracle-dz/UniFAR-FTUs huggingface dataset:
Applied Probability in Great Britain

T he subject of probability was, of course, motivated initially by its applications. However, there have been earnest attempts to convert it into a branch of pure mathematics, a development suggested by the axiomatic basis of the theory and reinforced by a preoccupation with possible measure-theoretic pathologies. Excesses in this direction led to a reaction, marked by the appearance of the journals Journal of Applied Probability (1963) and Advances in Applied Probability (1968) in Britain and Annals of Applied Probability (1991) in the United States, plus, of course, explicit mention of applications in the titles of the key Russian and German probability journals. Natural pragmatism had in fact kept the development of the subject fairly continuous in Britain-see the opening quotation, whose reference to England should, as often, be taken as meaning Britain (or even the Anglo-Celtic population of the entire British Isles). The journals JAP and AAP thus found a natural home there, although the foundation and operation of the Applied Probability Trust with which they are associated owes everything to Joe Gani's untiring energy. (See Gani 1988 for his own account.) This survey is largely restricted to the post-war (World War II) surge of development, which began with the activity of people such as Bartlett, Daniels, D. G. Kendall, and Moran. However, there is, of course, a considerable body of classic earlier work. Much of this has a clear biological slant, such as the studies by Galton and Watson of surname extinction and branching processes, Fisher's studies of genetic models (notably Fisher 1937, which still reverberates in the literature), and the treatments by Kermack and McKendrick (1927) of epidemic models. The war itself gave impetus to stochastic modelling of an operational research character, such as E. A. Milne's study of the optimal distribution of fragmentation of anti-aircraft shells. The view taken in this article is a personal one rather than an attempt at an exhaustive enumeration, although fairness has been a goal throughout. Coverage of some more recent applications has not been attempted, despite their interest and substance, e.g., finance and artificial neural nets. By its nature, the survey is concerned with models and not with inference. So, for instance, the statistical methods of time series analysis (to which British authors have contributed prolifically) are excluded. The stochastics of time series models are indeed interesting but have long been clarified in the familiar linear stationary case (the only distinctive British contribution being perhaps that of Yule 1927, with his suggestion of the linear autoregression). The author is aware that he is over-represented in the reference list. This is a consequence purely of a spread of interests-one of the few favourable to him, some would say.
Ricci solitons and Einstein-scalar field theory

B List has recently studied a geometric flow whose fixed points correspond to static Ricci flat spacetimes. It is now known that this flow is in fact Ricci flow modulo pullback by a certain diffeomorphism. We use this observation to associate with each static Ricci flat spacetime a local Ricci soliton in one higher dimension. Also, solutions of Euclidean-signature Einstein gravity coupled to a free massless scalar field with nonzero cosmological constant are associated with shrinking or expanding Ricci solitons. We exhibit examples, including an explicit family of complete expanding solitons. These solitons can also be thought of as a Ricci flow for a complete Lorentzian metric. The possible generalization to Ricci-flat stationary metrics leads us to consider an alternative to Ricci flow.
Poverty and Economic Inequality in Tanzania's Kagera Region

This study addresses poverty, economic inequality, determinants of consumption, determinants of poverty, and decomposition analyses using a dataset collected in Tanzania’s Kagera region from 1991 to 1994. In the entire Kagera region, the share of the betweengroup inequality had increased between Waves 2 and 4, although all three inequality indices had decreased between Waves 2 and 4. Our regression decomposition analyses confirm that the households in the rural area of the Kagera region are poorer than the households in the urban area of the Kagera region mainly due to the difference in the returns to their endowments.
Improving the accuracy of English-Arabic statistical sentence alignment

Multilingual natural language processing systems are increasingly relying on parallel corpus to ameliorate their output. Parallel corpora constitute the basic block for training a statistical natural language processing system and creating translation and language models. Several systems have been devised that automatically align words of a pair of sentences, each in a language. Such systems have been used successfully with European languages. In this paper, one such system is used to align sentences in an English-Arabic corpus. The system works poorly given raw unaligned sentence English-Arabic sentence pairs. This prompted the development of a preprocessing step to be applied to the Arabic sentences. The same corpus was then preprocessed and a significant improvement is reported when alignment is attempted using the preprocessed unaligned sentences.
Multi-agent based ocean-transport and traffic controlling system: A simulation

The recent impressive technological advancement in information technology (IT) and as well as in Communication have resulted the drastically improved developments in present systems. Most routine tasks have been automated with the support of advanced technologies. Multi-agent systems (MAS) play a major role in automating the tasks in wide range. In this sense current Ocean-Transportation and Traffic Management (OTTM) requires the support of artificial intelligence through MAS, transformation and evolution of ocean-transportation leads to a well-organized automated coordination. Currently the system has a limited capacity and cannot handle the increasing future ocean traffic demands. The proposed Agent based Ocean-Transport and Traffic Management (A-OTTM) concepts are deployed and thoroughly evaluated under realistic conditions with certain circumstances. Through this paper we present an agent based management system which is an emerging Multiagent A-OTTM simulator. It is developed with fairly accurate emulation of A-OTTM which is based on the human-controller-operation (HCO) workload model and human-computer interaction. We present preliminary as well as intermediary results of A-OTTM focusing on the efficiency and accuracy of the simulated controllers.
Trade reform and efficiency in Cameroon's manufacturing industries

Does trade reform generate gains in manufacturing firm-level technical efficiency? Pooling of pre and post trade reform data for Cameroon, and estimating a single stochastic production frontier for each industrial sector, yielded empirical results showing that the average technical efficiency increased in six of eight sectors following trade reform. The post trade reform firm-level technical efficiencies increased on average at an annual rate of 1.39%, while prior to trade reform they decreased on average at the annual rate of 0.76%. Before trade reform, the restricted trade regime coupled with macroeconomic and political instability negatively affected firm-level technical efficiency. Post trade reform potential determinants of firms’ technical efficiency include export share and import penetration rate.
Hood: A user-level threads library for multiprogrammed multiprocessors

TheHood user-level threads library delivers efficient performance under multiprogramming without any need for kernel-level resource management, such as cosc heduling or process control. It does so by scheduling threads with a non-blocking implementation o f the work-stealing algorithm. With this implementation, the execution time of a program running wit h arbitrarily many processes on arbitrarily many processors can be modeled as a simple function of work an d critical-path length. This model holds even when the program runs on a set of processors that arbitra rily grows and shrinks over time. In all cases, we observe linear speedup whenever the number of proc esses is small relative to the parallelism.
Compressive Sensing and Information Theory

In a series of recent work [5, 4], the theory of compressive sensing has been examined from an information theory perspective. Novel results regarding noisy compressive sensing have been found while viewing the compressive sensing problem as a communication channel. This perspective led to a new approach of solving the compressive sensing problem through a Bayesian approach. Belief propagation, a widely applied iterative decoding approach from coding theory, has been employed to solve the compressive sensing problem. Empirical results show superior performance of this approach.
Multilevel and Urban Health Modeling of Risk Factors for Diabetes Mellitus: A New Insight into Public Health and Preventive Medicine

This study aimed to apply multidisciplinary analysis approaches and test two hypotheses that (1) there was a significant increase in the prevalence of diabetes mellitus (DM) from 2002 to 2010 in the city of Philadelphia and that (2) there were significant variations in the prevalence of DM across neighborhoods, and these variations were significantly related to the variations in the neighborhood physical and social environment (PSE). Data from the Southeastern Pennsylvania Household Health Surveys in 2002–2004 (period 1, n = 8,567) and in 2008–2010 (period 2, n = 8,747) were analyzed using a cross-sectional comparison approach. An index of neighborhood PSE was constructed from 8 specific measures. The results show that age-adjusted prevalence of DM increased from period 1 (10.20%) to period 2 (11.91%) (P < 0.001). After adjusting age, sex, and survey years, an estimate of 12.14%, 18.33%, and 11.89% of the odds ratios for DM was related to the differences in the neighborhood PSE disadvantage, the prevalence of overweight/obesity, and those with lower education attendance, respectively. In conclusion, prevalence of DM significantly increased from 2002 to 2010 in the city of Philadelphia. In addition to risk factors for DM at personal level, neighborhood PSE disadvantage may play a critical role in the risk of DM.
Collaborative evaluation of a haptic-based medical virtual environment.

There is increasing use of virtual environments for medical training applications. Simulated medical environments allow clinical staff to practise medical procedures without endangering patients. Haptic devices are a key technology in many such systems adding a sense of touch to virtual interactions allowing healthcare practitioners to practise and test their clinical skills in life-like simulators. However, evaluating haptic-based virtual environments can be difficult as gathering user feedback on haptic interaction by traditional methods, such as post-session interviews and questionnaires, can be error-prone if users misremember their experiences. This paper describes the use of cooperative evaluation, a modified think aloud protocol, to evaluate the usability of a commercial haptic-based medical virtual environment called Virtual Veins. An evaluation was performed with 3rd year medical students using cooperative evaluation to evaluate Virtual Veins in a target deployment environment. Although the cooperative evaluation was successful in eliciting a number of usability issues, there were few haptic related verbalisations from participants. In haptic-based systems the evaluator does not share the sensory feedback with the participant. This can be problematic in questioning the participants about their haptic experience and encouraging haptic-specific comments.
EPA's Use of Benefit-cost Analysis: 1981-1986

EPA's central mission is to carry out its various statutory directives to protect the nation's health, welfare, and environment from the risks posed by pollution. Because the nation's resources are limited, EPA seeks to the extent legally permitted to direct those resources towards the actions that will produce the greatest reductions in environmental risk. Benefit-cost analysis is one of the analytic tools that the Agency uses to help make these environmental decisions. This 1987 report examines the contributions made by and limitations of EPA's use of benefit-cost analysis. It analyses the statutory provisions that affect EPA's use of benefit-cost analysis in regulatory decision making and describes how EPA is working to improve future benefit-cost analyses. Includes executive summaries of 15 benefit-cost analyses discussed in the report.
The Genetic Origins of the Relationship between Psychological Traits and Social Trust

Recent studies have shown that trusting attitudes and behavior are biologically influenced. Focusing on the classic trust game, it has been demonstrated that oxytocin increases trust and that humans are endowed with genetic variation that influences their behavior in the game. Moreover, several studies have shown that a large share of the variation in survey responses to trust items is accounted for by an additive genetic component. Against this backdrop, this article makes two important contributions. First, utilizing a unique sample of more than 2,000 complete Swedish twin pairs, we provide further evidence of the heritability of social trust. Our estimates of the additive genetic component in social trust were consistent across the sexes – . 33 for males and . 39 for females – and are similar to the results reported in earlier studies. Secondly, we show that social trust is phenotypically related to three psychological traits – extraversion, personal control, and intelligence – and that genetic factors account for most of these correlations. Jointly, these psychological factors share around 30% of the genetic influence on social trust both for males and females. Future studies should further explore the possible causal pathways between genes and trust using panel data on both psychological traits and social trust.
Radio Access Network traffic generation for Mobile Switching Center

One of the challenges faced by telecom companies is to provide robust and powerful servers that are capable to handle the great increase of the number of subscribers and to accomplish the heavy Internet-based applications that generate a tremendous traffic load. Companies evaluate their products' performance before releasing them to the market by applying a large amount of generated traffic to the telecom servers in order to measure their capability under traffic load; powerful solutions are hence needed for generating traffic and modeling various telecom protocols. In this paper, we propose a new traffic generator solution to load the Mobile Switching Center (MSC) for the Universal Mobile Telecommunications System (UMTS). This traffic generator loads the MSC through various mobile call scenarios such as location update, mobile call originating, mobile call terminating, and call clearing. We utilize the UML Use Case Model to describe the functional behaviors of the traffic generator, and present the UML Analysis Model that provides the logical implementation of the functional behaviors of the proposed traffic generator.
Learn Sparse Dictionaries for Edit Propagation

With the increasing availability of high-resolution images, videos, and 3D models, the demand for scalable large data processing techniques increases. We introduce a method of sparse dictionary learning for edit propagation of large input data. Previous approaches for edit propagation typically employ a global optimization over the whole set of pixels (or vertexes), incurring a prohibitively high memory and time-consumption for large input data. Rather than propagating an edit pixel by pixel, we follow the principle of sparse representation to obtain a representative and compact dictionary and perform edit propagation on the dictionary instead. The sparse dictionary provides an intrinsic basis for input data, and the coding coefficients capture the linear relationship between all pixels and the dictionary atoms. The learned dictionary is then optimized by a novel scheme, which maximizes the Kullback-Leibler divergence between each atom pair to remove redundant atoms. To enable local edit propagation for images or videos with similar appearance, a dictionary learning strategy is proposed by considering range constraint to better account for the global distribution of pixels in their feature space. We show several applications of the sparsity-based edit propagation, including video recoloring, theme editing, and seamless cloning, operating on both color and texture features. Our approach can also be applied to computer graphics tasks, such as 3D surface deformation. We demonstrate that with an atom-to-pixel ratio in the order of 0.01% signifying a significant reduction on memory consumption, our method still maintains a high degree of visual fidelity.
Neuro-Fuzzy integrated system and its VLSI design for generating membership function

In this paper, a Neuro-Fuzzy integrated system, which is based on fuzzy inference system using on-line learning ability of neural network is presented. By using on-line learning procedure, the proposed neuro-fuzzy integrated system (NFIS) can be used to construct an input-output mapping based on fuzzy if-then rules and the tuning of the parameters of membership function. The membership functions for NFIS have been realized using operational transconductance amplifier (OTA). Attention is given to design the circuits with low power consumption 2.91mW and size less than 0.65 mm2 within the neuro-fuzzy chip. SPICE simulations showed that they are suitable to real time application.
Utilization of Home Healthcare Service by Medicare-Medicaid Dual Eligibles

This study explores the characteristics of Medicare-only beneficiaries and Medicare-Medicaid dual eligibles in comparison, assess what factors determine the dual eligibility status, and examine the association between dual eligibility status and home healthcare service use. Using retrospective observational study of the U.S. 1996-2000 Medical Expenditure Panel Survey, we find that dual eligibles are disadvantaged in various personal characteristics compared to Medicare-only beneficiaries. The major predictors of dual eligibility status are race/ethnicity, family income and health conditions. Dual eligibles are likely to use more of both paid and unpaid home healthcare service, and subsequently induce higher total expenditures on home healthcare. As dual eligible population may be one contributor to the rapid growth in utilization and spending on home healthcare service in Medicare and Medicaid programs, policy makers need to precisely assess the medical need among the beneficiaries to efficiently coordinate Medicare and Medicaid programs.
SYNERGY : Detecting and Diagnosing Correlated Network Anomalies

Network anomalies occur in operational networks and may be logged by a number of network measurement tools such as SNMP and NetFlow. However, accurate and efficient detection of these anomalies in the logged data is very challenging due to the huge data volume and complex characteristics of anomalies. The existing approaches are limite d by the nature of underlying mathematical models and might be incapable of capturing some abnormal patterns. More importantly, existing approaches do not provide insights o n the root causes or impact of the detected anomalies, which makes it hard for a network operator to troubleshoot network performance issues. In this paper, we design and prototype a novel system, SYNERGY, that can detect network anomalies with high confidence by correlating across multiple data sources. It can report the root causes/impact assoc iated with the detected anomalies, which significantly facil itates the work of network operators. In addition, SYNERGY provides a great facility for the area of anomaly detection research – it can serve as a general framework to evaluate the performance of different anomaly detection methods . We evaluate SYNERGY using data collected at a tier-1 ISP network and show that it performs very well compared to the manually identified anomalies found in the operational practice. The methodology and algorithms in SYNERGY promise to be of immense use to network operations.
WHY DOES UNEMPLOYMENT PERSIST

The main movements of unemployment correspond to fluctuations in the short-run non-accelerating-inflation rate of unemployment (around a stable long-term non-accelerating-inflation rate of unemployment). These supply-side fluctuations have two main origins: (1) variations in the number of "insiders" involved in wage-setting; and (2) variations in the effectiveness of the unemployed "outsiders" as potential job-seekers. The evidence of micro studies suggests that (2) is more important than (1), and this also helps to explain the widespread shift outwards in the u/v curve. To derive these arguments rigorously, the paper presents a simple model of efficiency wages, another of collective bargaining, and finally a fully dynamic model with labor market flows. Copyright 1989 by The editors of the Scandinavian Journal of Economics.
Ventricular response during atrial fibrillation: Evaluation of exercise and flecainide effects

Ventricular response (VR) during atrial fibrillation (AF) is a complex process, which is modulated by the autonomic nervous system (ANS). The purpose of this study was to characterize VR to both exercise as ANS stimulus and flecainide which is also supposed to have effects on the ANS. RR series were analyzed by means of time domain parameters and non-linear methods. In 15 patients (10 male, aged 55 plusmn 13 years) with persistent AF (mean AF duration 13 plusmn24 months), time domain parameters and indexes assessing the predictability of the time series, (regularity index, approximate entropy and an index for linear predictability) were evaluated. VR during exercise resulted modulated by adrenergic stimulation. Flecainide exhibited vagolytic activity especially during exercise. Thus, monitoring of exercise- induced and antiarrhythmic drug effects on ANS is possible with parameters derived from time domain and non-linear analysis.
Mapsnp: An R Package to Plot a Genomic Map for Single Nucleotide Polymorphisms

Single-nucleotide polymorphism (SNP) is one of the most common sources of genetic variations of the genome. Currently, SNPs are a main target for most genetic association studies. Visualizing genomic coordinates of SNPs, including their physical location relative to their host gene, and the structure of the relevant transcripts, may provide intuitive supplements to the understanding of their functions. Nevertheless, to date, no such easy-to-use programming tools exist. Therefore, we developed an R package, “mapsnp”, to plot genomic map for a panel of SNPs within a genome region of interest, including the relative chromosome location and the transcripts in the region. mapsnp is a simple and flexible software package which can be used to visualize a genomic map for SNPs, integrating a chromosome ideogram, genomic coordinates, SNP locations and SNP labels.