Miracle-dz/UniFAR-FTUs huggingface dataset:
The Random Walk of High Frequency Trading

This paper builds a model of high-frequency equity returns by separately modeling the dynamics of trade-time returns and trade arrivals. Our main contributions are threefold. First, we characterize the distributional behavior of high-frequency asset returns both in ordinary clock time and in trade time. We show that when controlling for pre-scheduled market news events, trade-time returns of the highly liquid near-month E-mini S&P 500 futures contract are well characterized by a Gaussian distribution at very fine time scales. Second, we develop a structured and parsimonious model of clock-time returns by subordinating a trade-time Gaussian distribution with a trade arrival process that is associated with a modified Markov-Switching Multifractal Duration (MSMD) model. This model provides an excellent characterization of high-frequency inter-trade durations. Over-dispersion in this distribution of inter-trade durations leads to leptokurtosis and volatility clustering in clock-time returns, even when trade-time returns are Gaussian. Finally, we use our model to extrapolate the empirical relationship between trade rate and volatility in an effort to understand conditions of market failure. Our model suggests that the 1,200 km physical separation of financial markets in Chicago and New York/New Jersey provides a natural ceiling on systemic volatility and may contribute to market stability during periods of extremely heavy trading.
On Post-Generation Data Operations in Secure Distributed Storage Systems with Internal Padding

Secure distributed storage systems can achieve data security and fault resilience by providing encrypted and redundant data segments across multiple computing nodes. However, such systems might face severe performance bottlenecks when frequently tacking data with high consistency demand. This paper proposed a secure distributed storage system based on revised secret sharing scheme with internal padding. Data are saved in multiple coefficients of associated polynomials for high capacity. Shares generated from these polynomials are distributed and can be recollected to retrieve the original data. Post-generation data operations including data insertion, deletion, updating and appending do not require the complete share regeneration. Only affected data portions will be reprocessed and parallel processing is supported if they are interleaved. Performance analyses and experimental results have demonstrated the effectiveness and efficiency of the post-generation data operations.
Smooth Pursuit Eye Movements in Children with Strabismus and in Children with Vergence Deficits

Purpose The objective of our study was to examine horizontal smooth pursuit performance in strabismic children and in children with vergence deficits, and to compare these data with those recorded in a group of control age-matched children. Methods Binocular eye movements were recorded by video-oculography in ten strabismic children (mean age: 9.8±0.8) and seven children with vergence deficits (mean age: 10.8±0.6). Data were compared to that of age-matched control children (mean age: 9.8±0.8 years). Results Catch-up saccades amplitude in strabismic children and in children with vergence deficits were significantly higher than in control age-matched children. Moreover, in strabismic children the amplitude of catch-up saccades was significantly higher in rightward than in leftward direction. The number of catch-up saccades was also significantly higher in rightward than in leftward direction. The gain value of pursuits in rightward direction was significantly higher in the right eye than in the left one; for the right eye, the gain value was significantly higher in rightward than in leftward direction. Binocular coordination of pursuit was better in control age-matched children than in children with vergence deficits and than in strabismic children. Conclusions Binocular coordination of pursuit is abnormal in children with vergence deficits and worse in strabismic children. Binocular vision plays an important role in improving binocular coordination of pursuit.
Improved and isotropic resolution in tomographic diffractive microscopy combining sample and illumination rotation

Tomographic Diffractive Microscopy is a technique, which permits to image transparent living specimens in three dimensions without staining. It is commonly implemented in two configurations, by either rotating the sample illumination keeping the specimen fixed, or by rotating the sample using a fixed illumination. Under the first-order Born approximation, the volume of the frequency domain that can be mapped with the rotating illumination method has the shape of a “doughnut”, which exhibits a so-called “missing cone” of non-captured frequencies, responsible for the strong resolution anisotropy characteristic of transmission microscopes. When rotating the sample, the resolution is almost isotropic, but the set of captured frequencies still exhibits a missing part, the shape of which resembles that of an apple core. Furthermore, its maximal extension is reduced compared to tomography with rotating illumination. We propose various configurations for tomographic diffractive microscopy, which combine both approaches, and aim at obtaining a high and isotropic resolution. We illustrate with simulations the expected imaging performances of these configurations.
EFFECTS OF LOCUS OF CONTROL ORIENTATION, FINANCIAL STATUS AND MARITAL QUALITY ON LIFE SATISFACTION AMONG LOCAL GOVERNMENT RETIREES IN SOUTH-EAST NIGERIA

This study investigated the effects of locus of control orientation, financial status, and marital quality on life satisfaction among retirees. Participants for the study consisted of 217 Local Government retirees from Anambra State, South-East of Nigeria. These comprised of 148 males (68%) and 69 females (32%) and their ages ranged from 56 to 70 years with a mean age of 62.75 years (SD = 4.88). The study design was cross-sectional. Three hypotheses were stated. Correlation analysis was employed. Results of analysis showed that external locus of control orientation; low levels or inadequate financial status; as well as low levels of marital quality were each negatively related to life satisfaction among retirees. These results confirmed the three study hypotheses. Conclusions, recommendations and study limitations were highlighted.
Projective Networks: Topologies for Large Parallel Computer Systems

The interconnection network comprises a significant portion of the cost of large parallel computers, both in economic terms and power consumption. Several previous proposals exploit large-radix routers to build scalable low-distance topologies with the aim of minimizing these costs. However, they fail to consider potential unbalance in the network utilization, which in some cases results in suboptimal designs. Based on an appropriate cost model, this paper advocates the use of networks based on incidence graphs of projective planes, broadly denoted as Projective Networks. Projective Networks rely on generalized Moore graphs with uniform link utilization and encompass several proposed direct (PN and demi-PN) and indirect (OFT) topologies under a common mathematical framework. Compared to other proposals with average distance between 2 and 3 hops, these networks provide very high scalability while preserving a balanced network utilization, resulting in low network costs.
A Novel Single-Stage High-Power-Factor Electronic Ballast with Boost Topology for Multiple Fluorescent Lamps

A novel single-stage high-power-factor electronic ballast with boost topology for multiple fluorescent lamps is presented in this paper. A high power factor at the input terminal is achieved by operating the boost converter in discontinuous conduction mode. With carefully designed circuit parameters, soft switching on the power switches of the resonant inverter can be retained to attain high circuit efficiency. A prototype electronic ballast designed for four 20 W fluorescent lamps is built and tested to verify the analytical predictions. Satisfactory performance is obtained from the experimental results.
Resource Logics, Grammars, and Processing

The paper discusses work in progress on developing a tabular deduction method for multimodal logical grammar. The method is based on a compilation procedure, a single elimination rule for multiplicativeand additive(t) binary operators, and two rules defining residuation for the unary modals i/ #i . The method aims to achieve for multimodal logical grammar what chart-based parsing does for CFGs, namely a memoetic way of processing. The method is illustrated through a few examples and is compared to other available meth ods.
A standardisation proof for algebraic pattern calculi

This work gives some insights and results on standardisation for call-by-name pattern calculi. More precisely, we define standard reductions for a pattern calculus with constructor-based data terms and patterns. This notion is based on reduction steps that are needed to match an argument with respect to a given pattern. We prove the Standardisation Theorem by using the technique developed by Takahashi and Crary for lambda-calculus. The proof is based on the fact that any development can be specified as a sequence of head steps followed by internal reductions, i.e. reductions in which no head steps are involved.
Localisation of mobile underground mining equipment using wireless Ethernet

This review paper explores the use of IEEE 802.11b wireless Ethernet for the localisation of mobile equipment operating in an underground coal mining environment wireless communication networks have recently been introduced with some success in underground operations such as longwall mining to provide reliable high-speed communications for monitoring and control. We investigate the feasibility of this wireless paradigm for providing a new machine localisation capability underground, as has been recently considered in other non-mining domains. We overview two popular location estimation techniques, namely nearest-neighbour and Monte-Carlo Localisation, which use only the signal strength as received from several wireless access points to estimate location. Because the received signal strength is a highly variable parameter in underground environments, real data experiments are conducted using an in-house test facility to investigate signal properties and to evaluate the potential of the concept for underground mining.
Therapeutic Use of Native and Recombinant Enteroviruses

Research on human enteroviruses has resulted in the identification of more than 100 enterovirus types, which use more than 10 protein receptors and/or attachment factors required in cell binding and initiation of the replication cycle. Many of these “viral” receptors are overexpressed in cancer cells. Receptor binding and the ability to replicate in specific target cells define the tropism and pathogenesis of enterovirus types, because cellular infection often results in cytolytic response, i.e., disruption of the cells. Viral tropism and cytolytic properties thus make native enteroviruses prime candidates for oncolytic virotherapy. Copy DNA cloning and modification of enterovirus genomes have resulted in the generation of enterovirus vectors with properties that are useful in therapy or in vaccine trials where foreign antigenic epitopes are expressed from or on the surface of the vector virus. The small genome size and compact particle structure, however, set limits to enterovirus genome modifications. This review focuses on the therapeutic use of native and recombinant enteroviruses and the methods that have been applied to modify enterovirus genomes for therapy.
CHARACTERISTICS OF ROBUST COMPLEX NETWORKS

In network theory, a complex network represents a system whose evolving structure and dynamic behavior contribute to its robustness. The study of complex networks, though young, spans diverse domains including engineering, science, biology, sociology, psychology, and business, to name a few. Regardless of the field of interest, robustness defines a network’s survivability in the advent of classical component failures and at the onset of cryptic malicious attacks. With increasingly ambitious initiatives such as GENI and FIND that seek to design future internets, it becomes imperative to define the characteristics of robust topologies, and to build future networks optimized for robustness. This thesis investigates the characteristics of network topologies that maintain a high level of throughput in spite of multiple attacks. To this end, we select network topologies belonging to the main network models and some real world networks. We consider three types of attacks: removal of random nodes, high degree nodes, and high betweenness nodes. We use elasticity as our robustness measure and, through our analysis, illustrate that different topologies can have different degrees of robustness. In particular, elasticity can fall as low as 0.8% of the upper bound based on the attack employed. This result substantiates the need for optimized network topology design. Furthermore, we implement a tradeoff function that combines elasticity under the three attack strategies and considers the cost of the network. Our extensive simulations show that, for a given network density, regular and semi-regular topologies can have higher degrees of robustness than heterogeneous topologies, and that link redundancy is a sufficient but not necessary condition for robustness.
Boosting with incomplete information

In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we present a boosting approach that integrates features with incomplete information and those with complete information to form a strong classifier. By introducing hidden variables to model missing information, we form loss functions that combine fully labeled data with partially labeled data to effectively learn normalized and unnormalized models. The primal problems of the proposed optimization problems with these loss functions are provided to show their close relationship and the motivations behind them. We use auxiliary functions to bound the change of the loss functions and derive explicit parameter update rules for the learning algorithms. We demonstrate encouraging results on two real-world problems --- visual object recognition in computer vision and named entity recognition in natural language processing --- to show the effectiveness of the proposed boosting approach.
Politique structurelle européenne et développement local

Ce papier analyse l'effet des politiques regionales europeennes successives en estimant un modele econometrique de convergence conditionnelle. Selon ce modele, la convergence conditionnelle est affectee a la fois par les politiques appliquees et par la structure economique regionale, que nous apprehendons au travers des quotients d'emploi sectoriel. Le modele de convergence est specifie sur un panel dynamique couvrant la periode 1980-2005 pour 198 regions (NUTS2) de l'Europe des 15. Les estimateurs de beta-convergence et ceux decrivant la structure economique regionale, sont obtenus par moments generalises.
$V_rm DD$-Hopping Accelerators for On-Chip Power Supply Circuit to Achieve Nanosecond-Order Transient Time

A VDD-hopping accelerator for on-chip power supply circuits is proposed and the effectiveness of the accelerator circuit is experimentally verified. The quick dropper with the linear regulator enables nanosecond-order transient time in on-chip distributed power supply systems. The measured transition time is less than 5 ns with a load circuit equivalent to 25-k logic gates in 0.18-mum CMOS. This is to be compared with the case without the accelerator of the order of mus and thus the acceleration by two orders of magnitude is achieved. Extensions of the basic approach are also discussed including implementation of the quick dropper for a switching DC-DC converter, the control stability improvement, automatic timing generation, and the parasitic element effects of the power lines
Towards robust online inverse dynamics learning

Learning of inverse dynamics modeling errors is key for compliant or force control when analytical models are only rough approximations. Thus, designing real time capable function approximation algorithms has been a necessary focus towards the goal of online model learning. However, because these approaches learn a mapping from actual state and acceleration to torque, good tracking is required to observe data points on the desired path. Recently it has been shown how online gradient descent on a simple modeling error offset term to minimize tracking at acceleration level can address this issue. However, to adapt to larger errors a high learning rate of the online learner is required, resulting in reduced compliancy. Thus, here we propose to combine both approaches: The online adapted offset term ensures good tracking such that a nonlinear function approximator is able to learn an error model on the desired trajectory. This, in turn, reduces the load on the adaptive feedback, enabling it to use a lower learning rate. Combined this creates a controller with variable feedback and low gains, and a feedforward model that can account for larger modeling errors. We demonstrate the effectiveness of this framework, in simulation and on a real system.
A new deterministic source coding method in peer-to-peer systems

We propose a novel deterministic method for source coding in peer-to-peer networks. The main advantage of our method compared to randomized methods is that the coding will be invertible with probability one. A further advantage is a much lower communication overhead due to special coding vectors. We apply the coding algorithm in a scalable and robust peer-to-peer system. We analyze the deterministic method theoretically and prove upper and lower bounds for the number coded pieces. The theoretical results are backed up by simulations.
An Optimized Reduction Design to Minimize Atomic Operations in Shared Memory Multiprocessors

Reduction operations play a key role in modern massively data parallel computation. However, current implementations in shared memory programming APIs such as OpenMP are often computation bottlenecks due to the high number of atomic operations involved. We propose a reduction design that exploits the coupling with a barrier synchronization to optimize the execution of the reduction. Experimental results show how the number of atomic operations involved is dramatically reduced, which can lead to significant improvement in scaling properties on large numbers of processing elements. We report a speedup of 1.53x on the emph{312.swim m} SPEC OMP2001 benchmark and a speedup of 4.02x on the emph{stream cluster} benchmark from the PARSEC suite over the baseline.
Improved ON/OFF temporally differentiating address-event imager

We have fabricated an improved version of an imager reported earlier (Kramer, J., Int. Symp. Circuits and Systems, vol.II, p.165-8, 2002), primarily by using a better pixel circuit and better layout principles. The new imager functions over 5 decades of background illumination and has much more symmetrical ON and OFF responses. This imager achieves massive redundancy reduction by temporally differentiating the image contrast. The ideal functions of the pixels are to compute the rectified derivatives /sup d///sub dt/(log I) = (dI/dt)/I, where I is the photocurrent in the pixel. The values of these derivatives are rectified and output as rate-coded events on the AER (address-event representation) bus. The 2.2 mm by 2.2 mm, chip was built in a 0.35 /spl mu/m 4M 2P CMOS process. The pixels are 40 /spl mu/m by 40 /spl mu/m and the array has 32 by 32 pixels, each with ON and OFF outputs. System power consumption is about 30 mA at 3.3 V.
Reasoning about Global Clones: Scalable Semantic Clone Detection

The Semantic Web is slowly transforming the Web as we know it into a machine understandable pool of information that can be consumed and reasoned about by various clients. Source code is no exception to this trend and various communities have proposed standards to share code as linked data. With the availability of large amounts of open source code published in publicly accessible repositories, the introduction of massive horizontal scaling frameworks, and cloud computing infrastructures, a new era of software mining across information silos is reshaping the software engineering landscape. Given these technological advances, analyzing code at a global scale, across systems, projects and organizational boundaries, becomes feasible. In this paper, we introduce a clone detection algorithm and its implementation that can scale to such large global datasets, by modeling clones using description logic and applying a horizontal scaling Semantic Web reasoner. We demonstrate how our simple feature vector that only uses control statements, data types and method calls, can yield results similar to other popular clone detection tools. Our approach does not only allow us to reliably identify clones in a global context. By using a semantic reasoner, it also allows us to expand clone detection to a new class of semantic clones. We have compared our algorithm to some of the leading clone detection tools (DECKARD, CCFinder, JCD, and Simian) in order to validate our approach and show the differences in detected clones and performance.
Development of a Fluorescence Polarization Based High-Throughput Assay to Identify Casitas B-Lineage Lymphoma RING Domain Regulators

The E3 ubiquitin protein ligase Casitas B-lineage Lymphoma (Cbl) proteins and their binding partners play an important role in regulating signal transduction pathways. It is important to utilize regulators to study the protein-protein interactions (PPIs) between these proteins. However, finding specific small-molecule regulators of PPIs remains a significant challenge due to the fact that the interfaces involved in PPIs are not well suited for effective small molecule binding. We report the development of a competitive, homogeneous, high-throughput fluorescence polarization (FP) assay to identify small molecule regulators of Cbl (RING) domain. The FP assay was used to measure binding affinities and inhibition constants of UbCH7 peptides and small molecule regulators of Cbl (RING) domains, respectively. In order to rule out promiscuous, aggregation-based inhibition, two assay conditions were developed and compared side by side. Under optimized conditions, we screened a 10,000 natural compound library in detergent-free and detergent-present (0.01% Triton X-100) systems. The results indicate that the detergent-present system is more suitable for high-throughput screens. Three potential compounds, methylprotodioscin, leonuride and catalpol, have been identified that bind to Cbl (RING) domain and interfere with the Cbl (RING)-UbCH7 protein-protein interaction.
Online feature extraction for the incremental learning of gestures in human-swarm interaction

We present a novel approach for the online learning of hand gestures in swarm robotic (multi-robot) systems. We address the problem of online feature learning by proposing Convolutional Max-Pooling (CMP), a simple feed-forward two-layer network derived from the deep hierarchical Max-Pooling Convolutional Neural Network (MPCNN). To learn and classify gestures in an online and incremental fashion, we employ a 2nd order online learning method, namely the Soft-Confidence Weighted (SCW) learning scheme. In order for all robots to collectively take part in the learning and recognition task and obtain a swarm-level classification, we build a distributed consensus by fusing the individual decision opinions of robots together with the individual weights generated from multiple classifiers. Accuracy, robustness, and scalability of obtained solutions have been verified through emulation experiments performed on a large data set of real data acquired by a networked swarm of robots.