Miracle-dz/UniFAR-FTUs huggingface dataset:
Sex differences in the working memory of students in Ahmadu Bello University, Zaria, Nigeria using the N-b

The study of sex differences in cognition has been shrouded with much controversy. Working memory is a central construct in cognitive neuroscience. This study examined sex differences in working memory of students in Ahmadu Bello University, Zaria using the N-back task. To achieve this aim, fifty four (54) students of Ahmadu Bello University in the age range of 18-35 years consisting of 31 females and 23 males were used for the study. The subjects were screened for some confounding variables such as blood pressure profiles, body mass index that affect cognition. Cognitive functions were assessed with the Mini Mental State Examination Test, while working memory was tested with the N-back task. Results obtained from the N-back scores showed that there was no statistically significant difference (p>0.05) in working memory sexes, with mean values of 75.09 ±0.63 for males and 73.81 ± 0.58 for females. The mini-mental state examination also revealed no statistically significant difference (p>0.05) between the both sexes with a mean values of 29.52±0.12 for males and 29.07±0.20 for females. The mean BMI of the male and female population was 22.24±0.47 kg/m and 22.36±0.88 kg/m respectively and was within the range accepted as normal. The present work revealed no sex differences in working memory using n-back task between males and females in the studied population.
Forecasting the Swiss economy using VECX models: An exercise in forecast combination across models and observation windows

This paper uses vector error correction models of Switzerland for forecasting output, inflation and the short-term interest rate. It considers three different ways of dealing with forecast uncertainties. First, it investigates the effect on forecasting performance of averaging over forecasts from different models. Second, it considers averaging forecasts from different estimation windows. It is found that averaging over estimation windows is at least as effective as averaging over different models and both complement each other. Third, it examines whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights the effect of alternative weighting schemes on forecast accuracy is small in the present application.
A SIMPLE PATTERN RECOGNITION APPROACH FOR MONITORING INCIPIENT STATOR FAULTS IN SALIENT-POLE SYNCHRONOUS GENERATORS

This paper studies the efiect of incipient stator faults in salient-pole synchronous generators and its detection using a simple pattern recognition methodology. A theoretical linear model for the synchronous generator is flrst developed to provide the relationships between stator and rotor harmonic currents and possible incipient faults on stator electric circuits. All theoretical flndings were verifled by experimental results. The stator currents and its fifl and dq representations have been used to detect incipient faults on salient-pole synchronous generators using a similar pattern recognition technique which have been proposed for induction machines. From our test results, it became clear that the proposed methodology is capable of correctly monitoring incipient stator faults in salient-pole synchronous generators.
Detecting New Stable Objects In Surveillance Video

We describe a novel method to detect new stable objects in video. This includes detecting new objects that appear in a scene and remain stationary for a period of time. Examples include detecting a dropped bag or a parked car. Our method utilizes the state transition history (or a record of the "life cycle") of individual Gaussian distributions in a Gaussian Mixture Model (GMM) used to model the background. In typical implementations of the GMM, this state transition information is ignored however we show that by observing and retaining the history of state transitions of individual distributions, it is possible to detect long term changes in a scene. In particular we identify changes to the most probable background distribution and impose certain conditions on the characteristics and temporal behavior of this distribution. Results presented in this paper illustrate the success of the proposed method and its relevance to surveillance applications
A limit theorem for recursively defined processes in L

In this paper we derive a limit theorem for recursively defined processes. For several instances of recursive processes like for depth first search processes in random trees with logarithmic height or for fractal processes it turns out that convergence can not be expected in the space of continuous functions or in the Skorohod space D. We therefore weaken the Skorohod topology and establish a convergence result in Lp spaces in which D is continuously imbedded. The proof of our convergence result is based on an extension of the contraction method. An application of the limit theorem is given to the FIND process. The paper extends in particular results in [HR00] on the existence and uniqueness of random fractal measures and processes. The depth first search processes of Catalan and of logarithmically growing trees do however not fit the assumptions of our limit theorem and lead to the so far unsolved problem of degenerate limits.
The Age of Insecurity

We live in an era in which the culture and values of big business are dominant. The riptides of capital swirl around the globe ruining entire economies overnight. Directors and chief executives cash in stock options for unimaginable fortunes while whole workforces are "downsized" as companies relocate at a whim. Environmental degradation escalates as the earth's resources are looted. The dream of worldwide prosperity and peace is given the lie from Kosovo to the Congo, from the drug baronies of South America to the criminal empires of the former Soviet Union. Welcome to the Age of Insecurity. In the face of this slow-motion global coup d'etat by untrammelled finance, traditionally left leaning parties now in power have abandoned their concern with regulating business for a compulsive and self-righteous moralism; the Blair government stands as a perfect exemplar in this trend. In the coruscating argument the authors make a plea for government to turn strictures concerning ethics away from the citizen and on to a financial system that is making our society ever more precarious. Since the publication of the hardback of he Age of Insecurity in May 1998 events have conspired to validate the author's argument. In a new preface and afterword Elliott and Atkinson draw out the lessons to be learned from the hedge-fund crisis, the disintegration of the rouble and the spreading of economic turmoil in Latin America. The Age of Insecurity is, more than ever, a vital and radical tract for our times.
Efficient Compilation to Event-Driven Task Programs

As illustrated by the emergence of a class of new languages and runtimes, it is expected that a large portion of the programs to run on extreme scale computers will need to be written as graphs of event-driven tasks (EDTs). EDT runtime systems, which schedule such collections of tasks, enable more concurrency than traditional runtimes by reducing the amount of inter-task synchronization, improving dynamic load balancing and making more operations asynchronous. We present an efficient technique to generate such task graphs from a polyhedral representation of a program, both in terms of compilation time and asymptotic execution time. Task dependences become materialized in different forms, depending upon the synchronization model available with the targeted runtime. We explore the different ways of programming EDTs using each synchronization model, and identify important sources of overhead associated with them. We evaluate these programming schemes according to the cost they entail in terms of sequential start-up, in-flight task management, space used for synchronization objects, and garbage collection of these objects. While our implementation and evaluation take place in a polyhedral compiler, the presented overhead cost analysis is useful in the more general context of automatic code generation.
Analysing and Modelling Traffic of Systems with Highly Dynamic User Generated Content

As the web continues to evolve, its users have gone from only consuming content to actually producing it, resulting in systems with highly dynamic, user-generated content that cannot be easily modelled with existing tools. In this paper we investigate two such systems, digg and reddit, derive a general model for them, and show how this model can be used to improve their efficiency as well as that of other systems with similar characteristics. In order to achieve this, we have collected data on hundreds of thousands of posts and member profiles from both sites. digg and reddit are social news sites that allow users to post links to other websites as well as to vote for them. We analyse the data to get an understanding of how content is generated and how the popularity of a post evolves over time. We use the results of this analysis coupled with userlocation information to derive a general model that describes the user posting behaviour across different time zones. We further demonstrate how this model can be used to do efficient replication and caching, improving these systems’ performance. More importantly though, the periodic trends inherent in the model are not only applicable to these news sites, but also to applications as varied as chatting and online gaming servers, peer-to-peer content distribution and energy-efficient load balancing. We end by showing how the derived model can be used to improve some of these sys-
Promoting Safety through Well-Being: An Experience in Healthcare

Practitioners’ well-being and clinical risk management are two interrelated concepts in healthcare. Patient safety, workers’ safety and practitioners well-being have often been managed and measured with different methods, even though they are tightly linked. In this paper we propose a method that is suitable to increase organizational health. The action-research project aims to increase the commitment of healthcare managers and practitioners toward the development of an organizational culture which is oriented to patient and practitioner safety and well-being. These are crucial organizational resource for an effective process management. The project lasted 18 months and involved 60 nurses and physicians working in the operating room of six hospitals in the North of Italy. The project aimed to develop an inter-organizational methodology for noticing and monitoring critical threats to safety and well-being. The tool consisted of a report form in which practitioners could describe possible threats, solutions and personal contributions to the solutions. The participants designed it according to their practice and it was considered suitable and usable in their current work activities. Its added value is to overcome the habitual bottleneck between anomalies investigation and action planning, by identifying a specific role in the learning process to take care of the transition from data gathering to data use. The tool aims to enable individuals and teams to monitor and share ideas about critical aspects that affect their safety and well-being, collect contributions to solve them, sustain dissemination of good practices and frame health promotion as a crucial organizational resource.
How to Simulate the Universe in a Computer

Abstract In this contribution a broad overview of the methodologies of cosmological N-body simulations and a short introduction explaining the general idea behind such simulations is presented. After explaining how to set up the initial conditions using a set of N particles two (diverse) techniques are presented for evolving these particles forward in time under the influence of their self-gravity. One technique (tree codes) is solely based upon a sophistication of the direct particle–particle summation whereas the other method relies on the continuous (de-)construction of arbitrarily shaped grids and is realized in adaptive mesh refinement codes.
Stochastic Shortest Path MDPs with Dead Ends

Stochastic Shortest Path (SSP) MDPs is a problem class widely studied in AI, especially for probabilistic planning. To make value functions bounded, SSPs make the severe assumption of no dead-end states. Thus, they are unable to model various scenarios that may have catastrophic events (e.g., sending a rover on Mars). Even though MDP algorithms are used for solving problems with dead-ends, a principled theory of SSP extensions that would allow dead ends, including theoretically sound algorithms for solving them, has been lacking. In this paper, we propose three new MDP classes that admit dead ends with increasingly weaker assumptions. We present Value Iteration-based as well as the more efficient heuristic search algorithms for optimally solving each class, and explore theoretical relationships between these classes. We also conduct a preliminary empirical study comparing the performance of our algorithms on different MDP classes, especially on scenarios with unavoidable dead
Application of Neutralizing Antibodies against NI-35/250 Myelin-Associated Neurite Growth Inhibitory Proteins to the Adult Rat Cerebellum Induces Sprouting of Uninjured Purkinje Cell Axons

The myelin-associated proteins NI-35/250 exert a powerful inhibition on axon regeneration, but their function exerted on intact neurons is still unclear. In the adult CNS these proteins are thought to regulate axon growth processes to confine plasticity within restricted regions and to prevent the formation of aberrant connections. We have recently shown that application of neutralizing IN-1 antibody Fab fragment against NI-35/250 proteins to the adult cerebellum induces the expression of injury/growth-associated markers in intact Purkinje cells. Here, we asked whether these cellular modifications are accompanied by growth phenomena of Purkinje neurites. A single intraparenchymal application of IN-1 Fab fragment to the adult cerebellum induces a profuse sprouting of Purkinje axons along their intracortical course. The newly formed processes spread to cover most of the granular layer depth. A significant axon outgrowth is evident 2 d after injection; it tends to increase at 5 and 7 d, but it is almost completely reversed after 1 month. No axonal modifications occur in control Fab-treated cerebella. The IN-1 Fab fragment-induced cellular changes and axon remodeling are essentially reproduced by applying affinity-purified antibody 472 raised against a peptide sequence of the recombinant protein NI-220, thus confirming the specificity of the applied treatments on these myelin-associated molecules. Functional neutralization of NI-35/250 proteins induces outgrowth from uninjured Purkinje neurites in the adult cerebellum. Together with previous observations, this suggests that these molecules regulate axonal plasticity to maintain the proper targeting of terminal arbors within specific gray matter regions.
Pruning recurrent neural networks for improved generalization performance

The experimental results in this paper demonstrate that a simple pruning/retraining method effectively improves the generalization performance of recurrent neural networks trained to recognize regular languages. The technique also permits the extraction of symbolic knowledge in the form of deterministic finite-state automata (DFA) which are more consistent with the rules to be learned. Weight decay has also been shown to improve a network's generalization performance. Simulations with two small DFA (/spl les/10 states) and a large finite-memory machine (64 states) demonstrate that the performance improvement due to pruning/retraining is generally superior to the improvement due to training with weight decay. In addition, there is no need to guess a 'good' decay rate. <<ETX>>
Notice of RetractionGovernment expenditure and economic growth in China

When economists and politicians discuss the policies that could raise growth rates, usually fiscal policy takes centre stage. Using yearly data set from 1952 to 2008, this paper has proposed to use linear Granger causality to investigate the relationship between government expenditure and economic growth in China. The study finds that there is a strictly bidirectional Granger causality between the government expenditure and economic growth. The government expenditure drives economic growth and in turn is driven by economic growth. Furthermore, the bidirectional Granger causality is robust in eight years, after eight years the bidirectional Granger causality die out.
Constraints on the dense matter equation of state from the measurements of PSR J0737¿3039A moment of inertia and PSR J0751+1807 mass

The moment of inertia of the pulsar A in the neutron star binary J0737−3039 will soon be measurable through detailed measurements of the periastron advance. We present the calculation of the moment of inertia of neutron stars with the masses of the components of the binary J0737−3039 for a broad range of equations of state of dense matter, and we discuss the implications of such measurement for constraining the equation of state. An observational determination of the moment of inertia of the pulsar A in J0737−3039 with the accuracy of 10 per cent will narrow down considerably the range of viable equations of state. We also show that limits on the maximal mass of a neutron star provide a complementary set of constraints on the properties of dense nuclear matter.
A CPG-based locomotion control architecture for hexapod robot

This paper proposes a novel CPG-based control architecture for hexapod walking robot. We investigate the CPG systems from the perspective of network synchronization. In this way the motion control of hexapod robot can be refined into the gait generation level and joints coordination level. On the first level, we develop a gait generator consists of CPG network in ring based on modified Van der Pol (VDP) oscillator to realize various stable gaits as well as gait transition for hexapod walking. The limit cycle behavior of VDP model is analytically studied by virtue of perturbation technique. On the second level, we address the problem of multi-DoF coordination of single leg via phase order modulation and amplitude adjustment of the neural oscillators. Consequently we propose a single-leg controller consists of a three-coupled CPG network and a linear coefficient converter to generator smooth and feasible trajectories in task space. The effectiveness of the proposed control architecture is demonstrated through simulation and real physical robot experiment.
Collaborative approach for inter-domain botnet detection in large-scale networks

The members of almost all botnets are distributed between several networks. Such distribution hardens their detection as the centralized approaches require to centralize network data for their analysis, which is indeed not possible in regard to the legacy and business constraints applied to network operators. In this paper, we propose a collaborative and inter-domain botnet detection system which conciliates the requirements of privacy and business preservation, while enabling realtime analysis for large scale networks. The different probes of our collaborative detection system exchange anonymised information in order to synchronize the network analysis of the members of botnets and to identify the malicious servers controlling them. We evaluated our system using anonymised traffic captured on an operator's network, and the results showed an improvement of 31% of malicious servers detected resulting from the collaboration, and this without significant performance impact and bandwidth overhead (respectively 4% and 11kb/s).
Panache: a parallel WAN cache for clustered filesystems

Panache is a scalable, high-performance, remote file data caching solution integrated with the GPFS cluster file system. It leverages the inherent scalability of GPFS to provide a multi-node, consistent cache of data exported by a remote file system cluster. Panache exploits the soon-to-be standard pNFS protocol to move data in parallel from the remote file cluster. Furthermore, it provides a POSIX compliant file system interface making the cache completely transparent to applications. Panache can mask the fluctuating wide-area-network latencies and outages by supporting asynchronous and disconnected-mode operations. It allows concurrent updates to be made at the cache and at the remote cluster and synchronizes them by using conflict detection techniques to flag and handle conflicts. To maintain commercial viability, Panache relies on open standards for high-performance file serving and does not require any proprietary hardware or software to be deployed at the remote cluster. In this paper we present the overall architecture of Panache and its key features.
Quantum E(2) groups and Lie bialgebra structures

Lie bialgebra structures on e(2) are classified. For two Lie bialgebra structures which are not coboundaries (i.e. those which are not determined by a classical r-matrix) we solve the cocycle condition, find the Lie - Poisson brackets and obtain quantum group relations. There is one to one correspondence between Lie bialgebra structures on e(2) and possible quantum deformations of U(e(2)) and E(2).
Lip synchronization using linear predictive analysis

Linear predictive analysis is a widely used technique for speech analysis and encoding. The authors discuss the issues involved in its application to phoneme extraction and lip synchronization. The LP analysis results in a set of reflection coefficients that are closely related to the vocal tract shape. Since the vocal tract shape can be correlated with the phoneme being spoken, LP analysis can be directly applied to phoneme extraction. We use neural networks to train and classify the reflection coefficients into a set of vowels. In addition, average energy is used to take care of vowel-vowel and vowel-consonant transitions, whereas the zero crossing information is used to detect the presence of fricatives. We directly apply the extracted phoneme information to our synthetic 3D face model. The proposed method is fast, easy to implement, and adequate for real time speech animation. As the method does not rely on language structure or speech recognition, it is language independent. Moreover, the method is speaker independent. It can be applied to lip synchronization for entertainment applications and avatar animation in virtual environments.
Encyclopedia of tariffs and trade in U.S. history

The tariff, central to the colonies' separation from Great Britain, has remained one of the most divisive and misunderstood issues in American history. This encyclopedia provides comprehensive coverage of tariffs and trade from pre-colonial times to the present, featuring more than 400 A-Z entries, selected primary documents, and texts of the tariffs. It overviews the people, events, and legislation that have affected tariffs and trade policy, while illustrating the issues with primary documents from the Federalist Papers to the Gore-Perot debate over NAFTA. Designed as a tool for students, scholars, and the general public, this book is the only encyclopedia on tariffs and trade from the 1600s to the present. The book's introduction offers a solid historical survey, while entries include overviews of each tariff from 1789 to the present, concise biographies of individuals-including both opponents of tariffs and advocates of protectionism-and coverage of the events that have shaped economic and trade policies. The encyclopedia's extensive information provides a broader, fuller understanding of tariffs, their role in U.S. history, and their impact on trade than any other reference.