Miracle-dz/UniFAR-FTUs huggingface dataset:
A single predator charging a herd of prey: effects of self volume and predator–prey decision-making

We study the degree of success of a single predator hunting a herd of prey on a two-dimensional square lattice landscape. We explicitly consider the self volume of the prey restraining their dynamics on the lattice. The movement of both predator and prey is chosen to include an intelligent, decision making step based on their respective sighting ranges, the radius in which they can detect the other species (prey cannot recognise each other besides the self volume interaction): after spotting each other the motion of prey and predator turns from a nearest neighbour random walk into directed escape or chase, respectively. We consider a large range of prey densities and sighting ranges and compute the mean first passage time for a predator to catch a prey as well as characterise the effective dynamics of the hunted prey. We find that the prey's sighting range dominates their life expectancy and the predator profits more from a bad eyesight of the prey than from his own good eye sight. We characterise the dynamics in terms of the mean distance between the predator and the nearest prey. It turns out that effectively the dynamics of this distance coordinate can be captured in terms of a simple Ornstein–Uhlenbeck picture. Reducing the many-body problem to a simple two-body problem by imagining predator and nearest prey to be connected by an effective Hookean bond, all features of the model such as prey density and sighting ranges merge into the effective binding constant.
A PSO-Based Ball-Plate Calibration for Laser Scanner

Three coordinate laser scanner is one of the important equipments in geometric measurement and reverse engineering fields. The rapid development of manufacture precision towards precise or ultra-precise direction requires higher scanning precision. Calibration is the most direct, simplest method to check the measuring uncertainty of the scanner. This paper put forward a ball-plate based calibration method and proposed to use particle swarm optimization (PSO) algorithm to solve the critical point-cloud sphere center fitting problem in the calibration. A practical calibration is completed on a laser scanner and the calibration results show that PSO algorithm enables to present an adequately accurate fitting centers and the proposed method is practical and effective.
Eurographics Symposium on Geometry Processing (2007) Shape Optimization Using Reflection Lines

Many common objects have highly reflective metallic or painted finishes. Their appearance is primarily defined by the distortion the curved shape of the surface introduces in the reflections of surrounding objects. Reflection lines are commonly used for surface interrogation, as they capture many essential aspects of reflection distortion directly, and clearly show surface imperfections that may be hard to see with conventional lighting. In this paper, we propose the use of functionals based on reflection lines for mesh optimization and editing. We describe a simple and efficient discretization of such functionals based on screen-space surface parameterization, and we demonstrate how such discrete functionals can be used for several types of surface editing operations.
Utilizing Social Network Analysis in Support of Nation Building

Abstract : Social network analysis is a powerful set of techniques used by social scientists to study the formal and informal interrelat ions in a community. Since 9/11 these techniques have been increasingly utilized by the defense and intelligence communities to analyze terrorist networks to aid in thwarting our foes. This study investigates the use of social networks and structural holes to facilitate nation building in failed and failing states. Investigation of the underlying social structure of a community, identifying st ructural holes and gaps within the government, Security Stabilization Transition and Reconstruction Operations (SSTRO) efforts can be focused to strengthen the host nation government to provide security and unity for its citizens. This investigation focused on exploring techniques that link individuals in the professional and governmental community. It was found that Burt's technique of structural holes can be applied to a national level in order to identify structural gaps within an ethnically fractured failing state. This technique can highlight national, regional, or local holes that can be filled to facilitate nation building.
Relative Margin Support Tensor Machines for gait and action recognition

In this paper, we formulate the Relative Margin Support Tensor Machines (RMSTMs) problem as an extension of the Relative Margin Machines (RMMs). While the typical Support Tensor Machines (STMs) find a solution that is greatly influenced by the data spread, the proposed RMSTMs maximize the margin in a way relative to the spread of the data. The difference in the obtained solutions can be significant in the cases of badly scaled data, especially in the case of various spreads across different data dimensions. The efficiency of the proposed method is illustrated on the problems of gait and action recognition, where the results acquired verify the superiority of the method in terms of classification performance.
Speech-laughs: An HMM-based approach for amused speech synthesis

This paper presents an HMM-based synthesis approach for speechlaughs. The building stone of this project was the idea of the co-occurrence of smile and laughter bursts in varying proportions within amused speech utterances. A corpus with three complementary speaking styles was used to train the underlying HMM models: neutral speech, speech-smile, and finally laughter in different articulatory configurations. Two types of speech-laughs were then synthesized: one made by combining neutral speech and laughter bursts, and the other made by combining speech-smile and laughter bursts. Synthesized stimuli were then rated in terms of perceived amusement and naturalness levels. Results show the compound effect of both laughter bursts and smile on both amusement and naturalness and inspire interesting perspectives.
Algorithm for redundancy elimination in network traffic

The network redundant traffic, not only consuming network bandwidth, but also reducing the efficiency of the Internet, exists abundantly in the course of exchanging Internet data. In the context, protocol-independent redundancy elimination, which can remove duplicate strings from within arbitrary network flows, has emerged as a powerful technique to improve the efficiency of network links in the face of repeated data and has been widely used. Redundancy elimination middle-boxes are being widely deployed to improve the effective bandwidth of network access links of enterprises and data centers alike, and for improving link loads in small ISP networks.
The Role of Incoherent MicroRNA-Mediated Feedforward Loops in Noise Buffering

MicroRNAs are endogenous non-coding RNAs which negatively regulate the expression of protein-coding genes in plants and animals. They are known to play an important role in several biological processes and, together with transcription factors, form a complex and highly interconnected regulatory network. Looking at the structure of this network, it is possible to recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions. Among them, a special role is played by the microRNA-mediated feedforward loop in which a master transcription factor regulates a microRNA and, together with it, a set of target genes. In this paper we show analytically and through simulations that the incoherent version of this motif can couple the fine-tuning of a target protein level with an efficient noise control, thus conferring precision and stability to the overall gene expression program, especially in the presence of fluctuations in upstream regulators. Among the other results, a nontrivial prediction of our model is that the optimal attenuation of fluctuations coincides with a modest repression of the target expression. This feature is coherent with the expected fine-tuning function and in agreement with experimental observations of the actual impact of a wide class of microRNAs on the protein output of their targets. Finally, we describe the impact on noise-buffering efficiency of the cross-talk between microRNA targets that can naturally arise if the microRNA-mediated circuit is not considered as isolated, but embedded in a larger network of regulations.
Learning Sparse Markov Network Structure via Ensemble-of-Trees Models

Learning the sparse structure of a general Markov network is a hard computational problem. One of the main difficulties is the computation of the generally intractable partition function. To circumvent this difficulty, we propose to learn the network structure using an ensemble-oftrees (ET) model. The ET model was first introduced by Meilă and Jaakkola (2006), and it represents a multivariate distribution using a mixture of all possible spanning trees. The advantage of the ET model is that, although it needs to sum over super-exponentially many trees, its partition function as well as data likelihood can be computed in a closed form. Furthermore, because the ET model tends to represent a Markov network using as small number of trees as possible, it provides a natural regularization for finding a sparse network structure. Our simulation results show that the proposed ET approach is able to accurately recover the true Markov network connectivity and outperform the state-of-art approaches for both discrete and continuous random variable networks when a small number of data samples is available. Furthermore, we also demonstrate the usage of the ET model for discovering the network of words from blog posts.
Lessons from The Lorax

In the late 1960s, Theodore Geisel (Dr. Seuss) fretted that he had read too many Adull things on conservation, full of statistics and preachy. @ He began work on what has become a classic of children=s literature and a standard text for Earth Day ceremonies. The Lorax, published in 1971, received immediate attention. Its original drawings joined moon rocks as focal points at the opening of the Lyndon B. Johnson Presidential Library. Since that auspicious beginning, The Lorax has sold around 600,000 copies. Moreover, it has been adapted to video. A cartoon version, complete with catchy tunes, has Afar exceeded expectations@ of its distributor. Despite its continuing success, no one teaching about the environment should use this book as a text without some trepidation. It does raise important questions, but it suggests answers that, despite good intentions, are misleading, perhaps dangerously so. The central truth of this wonderfully written story, that no society can prosper by depleting its stock of renewable resources, is undeniable: The difficulties with the story are twofold: It contains internal contradictions and its prescriptions direct attention away from alternatives that can actually achieve the stated goals. The latter failure is due to a common view that people, not incentives, must be changed if we are to avoid the fate depicted in the tale. Before addressing the content of each of our assertions we review the story and follow up with an interpretation that calls into
Does Image Segmentation Improve Object Categorization ?

Image segmentation and object recognition are among the most fundamental problems in computer vision, and the potential interaction between these tasks has been discussed for many years. The usefulness of recognition for segmentation has been demonstrated with various top-down segmentation algorithms, however, the impact of bottom-up image segmentation as pre-processing for object recognition is not well understood. One factor impeding the utility of segmentation for recognition is the unsatisfactory quality of image segmentation algorithms. In this work we take advantage of a recently proposed method for computing multiple stable segmentations and illustrate the application of bottom-up image segmentation as a preprocessing step for object recognition and categorization. We extend a popular bag-of-features recognition model to provide multiple class categorization and localization of objects in images. We compare our categorization results to that of a conventional bag-of-features recognition model on the Caltech and PASCAL image databases.
A Flexible and Scalable Affinity Lock for the Kernel

A number of NUMA-aware synchronization algorithms have been proposed lately to stress the scalability inefficiencies of existing locks. However their presupposed local lock granularity, a physical processor, is often not the optimum configuration for various workloads. This paper further explores the design space by taking into consideration the physical affinity between the cores within a single processor, and presents FSL to support variable and finely tuned group size for different lock contexts and instances. The new design provides a uniform model for the discussion of affinity locks and can completely subsume the previous NUMA-aware designs because they have only discussed one special case of the model. The interfaces of the new scheme are kernel-compatible and thus largely facilitate kernel incorporation. The investigation with the lock shows that an affinity lock with optimal local lock granularity can outperform its NUMA-aware counterpart by 29.40% and 58.28% at 80 cores with different workloads.
Efficiency and Profitability Test of Investment Firms: A Comparison between the UK and Italian Industries

This paper investigates the influence of environmental variables on the cost efficiency of the UK and Italian investment firms over the period 1995-1998, by employing four different specifications of the stochastic frontier methodology using a translog cost function in order to measure X-efficiency. The empirical findings show the importance of integrating environmental variables into the definition of the cross-country common frontier. The traditional common frontier reveals that Italian investment firms are nearly as efficient as the UK firms. Nevertheless, when institutional and interpretational variables are included in the model, differences between the two industries emerge. Finally, to identify investment firms that are both cost and profit efficient, we undertake a profitability test.
Hepatitis C Viral Heterogeneity Based on Core Gene and an Attempt to Design Small Interfering RNA Against Strains Resistant to Interferon in Rawalpindi, Pakistan

Background Global prevalence of Hepatitis C Virus (HCV) infection corresponds to about 130 million HCV positive patients worldwide. The only drug that effectively reduces viral load is interferon-α (IFN-α) and currently combination of IFN and ribavirin is the choice for treatment. Objectives The present study is aimed to resolve the genotypes based on core gene that might affect the response to interferon therapy. Furthermore an attempt was made to propose a powerful therapeutic approach by designing the siRNA from sequences of the same patients who remain resistant to IFN in this study. Patients and Methods To achieve the objectives, a sequence analysis was performed in five HCV ELISA positive subjects who have completed IFN treatment. Neighbor Joining (NJ) method was used to study the evolutionary relationship. Atomic models were predicted using online software PROCHECK and i- TASSER. Results Two new genotypes were reported for the first time namely 4a from suburban region of Rawalpindi and 6e from all over the Pakistan. According to Ramachandran plot, satisfactory atomic model was considered useful for further studies, i.e. to calculate HCV genotypes conservation at structural level, to find out critical binding sites for drug designing, or to silence those binding sites by using appropriate siRNA. Single siRNA can be used to inhibit HCV RNA synthesis against genotype 3 and 4, as the predicted siRNA were originated from the same domain in studied HCV core region in both genotypes. Conclusions We can conclude that any change or mutation in core region might be the cause of HCV strains to resist against IFN therapy. Therefore, further understanding of the complex mechanism involved in disrupting viral response to therapy would facilitate the development of more effective therapeutic regimens. Additionally, a single designed siRNA can be used as an alternative for current therapy against more than one resistant HCV genotypes.
capture and single molecule bisulfite sequencing High definition profiling of mammalian DNA methylation by array Material Supplemental

Material Supplemental http://genome.cshlp. org/content/suppl/2009/08/06/gr.095190. 109.DC1. html References http://genome.cshlp. org/content/19/9/1593.full. html#ref-list-1 This article cites 60 articles, 23 of which can be accessed free at: Open Access Freely available online through the Genome Research Open Access option. service Email alerting click here top right corner of the article or Receive free email alerts when new articles cite this article sign up in the box at the
Heart Rate Variability – A Historical Perspective

Heart rate variability (HRV), the beat-to-beat variation in either heart rate or the duration of the R–R interval – the heart period, has become a popular clinical and investigational tool. The temporal fluctuations in heart rate exhibit a marked synchrony with respiration (increasing during inspiration and decreasing during expiration – the so called respiratory sinus arrhythmia, RSA) and are widely believed to reflect changes in cardiac autonomic regulation. Although the exact contributions of the parasympathetic and the sympathetic divisions of the autonomic nervous system to this variability are controversial and remain the subject of active investigation and debate, a number of time and frequency domain techniques have been developed to provide insight into cardiac autonomic regulation in both health and disease. It is the purpose of this essay to provide an historical overview of the evolution in the concept of HRV. Briefly, pulse rate was first measured by ancient Greek physicians and scientists. However, it was not until the invention of the “Physician’s Pulse Watch” (a watch with a second hand that could be stopped) in 1707 that changes in pulse rate could be accurately assessed. The Rev. Stephen Hales (1733) was the first to note that pulse varied with respiration and in 1847 Carl Ludwig was the first to record RSA. With the measurement of the ECG (1895) and advent of digital signal processing techniques in the 1960s, investigation of HRV and its relationship to health and disease has exploded. This essay will conclude with a brief description of time domain, frequency domain, and non-linear dynamic analysis techniques (and their limitations) that are commonly used to measure HRV.
An inductorless RC-based quadrature phase generator and its application to vector-sum phase shifter

An inductorless quadrature phase generator is designed and implemented in 0.18 μm CMOS technology. The proposed circuit is composed of two resistors, two capacitors, and four differential amplifiers. The performance of proposed circuit is verified by a single sideband (SSB) mixer and a vector-sum phase shifter. Measurement results show that the image rejection ratio is 42.38 dBc at 2.16 GHz. The measured RMS phase error and RMS magnitude error are below 3.5 degrees and 0.55 dB in 2-2.6 GHz, respectively.
Myrmic : Secure and Robust DHT Routing

A distributed hash table such as Chord attempts to build a persistent store from a network of (possibly unstable) peer nodes. There has been a great deal of work on making DHTs robust to environmental interference (such as membership churn, transient routing failures and high CPU load) but con siderably less work on implementing DHTs that are secure againstadversarialbehavior designed to cause DHT failure. In this paper, we introduceMyrmic, a novel DHT routing protocol designed to be robust against adversarial interfe rence. A key feature distinguishing Myrmic from other DHT implementationsis a root verification protocolthat allows anyone to verify that the node responding to a query for key k is indeed the “correct” holder of the key. We give analytical results showing that even when a large fraction of nodes, for example 30%, cooperate to adversarially interfere with query routing, Myrmic finds uncorrupted roots in expected logarithmic time, and confirm these results with simulation s of 1000 nodes. Finally, we implement the proposed protocol and evaluate it through experimentation with 120 nodes on PlanetLab in order to measure wide area network performance. All of these results suggest that Myrmic provides stronger robustness guarantees while incurring minimal ne twork and CPU overhead.
Risk financing for knowledge-based enterprises: Mechanisms and policy options

New knowledge-based enterprises have several characteristics that limit their options for obtaining financing from external sources: they have little or no collateral, their assets tend to be intangible, and the value of their innovations is hard to calculate. For these reasons, entrepreneurs in the more knowledge-intensive fields tend to rely largely on equity financing. This is a more ‘patient’ form of capital for early stage operations with returns linked directly to firm earnings. Using examples from various countries, this paper surveys the various mechanisms for risk financing and the complementary, yet constantly evolving, roles of business angels, venture capital firms, and government programs in such financing. Copyright , Beech Tree Publishing.
Overcoming far-end congestion in large-scale networks

Accurately estimating congestion for proper global adaptive routing decisions (i.e., determine whether a packet should be routed minimally or non-minimally) has a significant impact on overall performance for high-radix topologies, such as the Dragonfly topology. Prior work have focused on understanding near-end congestion - i.e., congestion that occurs at the current router - or downstream congestion - i.e., congestion that occurs in downstream routers. However, most prior work do not evaluate the impact of far-end congestion or the congestion from the high channel latency between the routers. In this work, we refer to far-end congestion as phantom congestion as the congestion is not "real" congestion. Because of the long inter-router latency, the in-flight packets (and credits) result in inaccurate congestion information and can lead to inaccurate adaptive routing decisions. In addition, we show how transient congestion occurs as the occupancy of network queues fluctuate due to random traffic variation, even in steady-state conditions. This also results in inaccurate adaptive routing decisions that degrade network performance with lower throughput and higher latency. To overcome these limitations, we propose a history-window based approach to remove the impact of phantom congestion. We also show how using the average of local queue occupancies and adding an offset significantly remove the impact of transient congestion. Our evaluations of the adaptive routing in a large-scale Dragonfly network show that the combination of these techniques results in an adaptive routing that nearly matches the performance of an ideal adaptive routing algorithm.