Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytopathic bovine viral diarrhea viruses (BVDV): emerging pestiviruses doomed to extinction

Bovine viral diarrhea virus (BVDV), a Flaviviridae pestivirus, is arguably one of the most widespread cattle pathogens worldwide. Each of its two genotypes has two biotypes, non-cytopathic (ncp) and cytopathic (cp). Only the ncp biotype of BVDV may establish persistent infection in the fetus when infecting a dam early in gestation, a time point which predates maturity of the adaptive immune system. Such fetuses may develop and be born healthy but remain infected for life. Due to this early initiation of fetal infection and to the expression of interferon antagonistic proteins, persistently infected (PI) animals remain immunotolerant to the infecting viral strain. Although only accounting for some 1% of all animals in regions where BVDV is endemic, PI animals ensure the viral persistence in the host population. These animals may, however, develop the fatal mucosal disease, which is characterized by widespread lesions in the gastrointestinal tract. Cp BVD virus, in addition to the persisting ncp biotype, can be isolated from such animals. The cp viruses are characterized by unrestrained genome replication, and their emergence from the persisting ncp ones is due to mutations that are unique in each virus analyzed. They include recombinations with host cell mRNA, gene translocations and duplications, and point mutations. Cytopathic BVD viruses fail to establish chains of infection and are unable to cause persistent infection. Hence, these viruses illustrate a case of “viral emergence to extinction” – irrelevant for BVDV evolution, but fatal for the PI host.
Understanding The Influence Of Participants' Preferences On The Affiliation Network Of Churches Using Agent-based Modeling

As the affiliation network of churches may potentially benefit public health, the impact of participants’ preferences on the affiliation network bears further study. This paper attempts to use agentbased modeling techniques associated with geographic information to study the affiliation network between churches and participants. Using churches in ZIP Code 30318 in Atlanta in Georgia, this study specifies the preferences of participants as personal radii and choice patterns. Results suggest (1) personal radii of participants are positively related to the size of affiliation network and the centralities of churches; (2) the change of choice pattern of participants can lead to a sharp reduction in size of the affiliation network of churches; (3) The centralities of churches among the affiliation network are corresponding to population density of census tracts. Findings can be used to understand the formulation of affiliation network of churches and their relationship with participants’ preferences. INDEX WORDS: Agent-based model, Affiliation network, GIS UNDERSTANDING THE INFLUENCE OF PARTICIPANTS’ PREFERENCES ON THE AFFILIATION NETWORK OF CHURCHES USING AGENT BASED MODELING
Heating of the intergalactic medium as a result of structure formation

ABSTRA C T We estimate the heating of the intergalactic medium as a result of shocks arising from structure formation. The heating of the gas outside the collapsed regions, with small overdensitiesâOnb/ nbU ! 200a is considered here, with the aid of a Zel’dovich approximation. We estimate the equation of state of this gas, relating the density to its temperature and its evolution in time, considering the shock heating caused by 1s density peaks as being the most dominant. We also estimate the mass fraction of gas above a given temperature as a function of redshift. We find that the baryon fraction above 10 6 Ka tza 0i s,10 per cent. We estimate the integrated Sunyaev‐ Zel’dovich distortion from this gas at the present epoch to be of the order of 10 26 .
Maximum likelihood range estimation for 3D-imaging based on pseudo-noise optical modulation

Acquiring real-time 3D images poses many challenges. Many 3D-imaging systems are based on estimating the time-of-flight (TOF) of photons between an emitter and a receiver, which in turn is based on transmitting a pseudo-noise optical signal and correlation measurements. The precision of such measurements is limited by photon shot noise. In this paper, we develop a maximum-likelihood estimator for the TOF (and thus for the range) that takes into account the Poisson distribution of the detected photons. The proposed estimator is shown to give better range estimates than a standard estimator that is used in current systems. The improvement is particularly significant when the period of the pseudo-noise sequence-based modulation signal is short.
Subjective and Objective Quality Assessment for Noise Reduced Speech

Recent development in telecommunication services, such as VoIP in NGN and car communications has become increasingly necessary for use of hands-free communication system using separate microphones and loudspeakers. Hands-free system has been largely affected by noisy circumstances. This paper describes experimental results and perspectives for subjective and objective quality assessment of noise reduced speech. In this paper, noisy circumstances, such as subway, babble, car, and exhibition were considered, and as the noise reduced algorithms, spectral subtraction with smoothing of the time direction, temporal domain SVD-based speech enhancement, GMM-based speech estimation, and KLT-based comb-filtering were used. Noise reduced speech were subjectively assessed by word intelligibility and opinion rating methods. Objective quality assessment was studied from viewpoints of objective quality measure using perceptual evaluation of speech quality (PESQ) in the auditory domain. First, this paper describes subjective and objective quality assessment from viewpoints of the opinion rating methods, and then, word intelligibility.
Self-Organized Criticality in Asynchronously Tuned Elementary Cellular Automata

Self-organized criticality (SOC) reveals a mechanism by which a system is autonomously evolved to be in a critical state without needing parameter tuning. Whereas various biological systems are found to be in critical states and the significance of SOC is being re-estimated, a simple model in a general platform has not been established. Here, we present SOC in asynchronously tuned elementary cellular automata (ECA), which was based on asynchronously updating and tuning the consistency between local dual modes of transitions. This duality was defined by adjunction, which can be ignored during synchronous updates. Duality coupled with asynchronous updating can demonstrate that SOC coincides with the criticality in a phase transition of asynchronous ECA with respect to density decay.
Effect of corn distiller's dried grains with solubles at various levels on performance of laying hens and egg yolk color.

Distiller's dried grains with solubles produced from corn as a co-product from ethanol production was fed at 0, 5, 10, or 15% of a corn-soybean meal diet to laying hens to determine if egg production parameters or yolk color would be affected. In experiment 1, diets were fed from 48 to 56 wk of age and DDGS had a goldenrod color. Egg production, weight, mass, specific gravity and yolk color were determined biweekly. Brown colored DDGS was included in diets fed from 58 to 67 wk of age. Egg production parameters and yolk color were measured tri-weekly. Egg production parameters were not different at most ages. However, there were occasional treatment effects. As DDGS increased, there were linear decreases in egg production (52-53 wk of age), egg weight (63 wk of age), egg mass (51 and 53 wk of age), and specific gravity (51 wk of age). Yolk color was increased linearly (p<0.01) as DDGS was increased in the diet throughout experiment 1. In experiment 2, yolk redness (a*) was increased linearly (p<0.001) by increasing levels of DDGS at all ages sampled. The results show that egg yolk is visually changed within one month when 10% or higher of a lightly colored DDGS is fed and by two months with 5% DDGS. In general, corn DDGS up to 15% of the diet did not affect egg production. However, variable results of experiment 1 suggest that a lower level of DDGS should be fed when the feedstuff is introduced in the diet.
Stochastic Queuing Simulation for Data Center Workloads

Data center systems and workloads are increasing in importance, yet there are few methods for evaluating potential changes to these systems. We introduce a new methodology for exascale evaluation, called Statistical Queuing Simulation (SQS). At its heart, SQS is a parallel, large-scale stochastic discrete time simulation of generalized queueing models that are driven by empirically-observed arrival and service distributions. SQS provides numerous practical advantages over alternative large-scale simulation techniques (e.g., trace-driven simulation), including statistical rigor and reduced turnaround time. We detail our methodology, workload suite, and practical concerns associated with them. To demonstrate our technique, we carry out a casestudy of data center power capping for 1000 servers. Finally, we discuss open research challenges for making SQS more robust.
The diversification benefits of Australian equities to international investors

We examine whether Australia offers any unique diversification benefits to an international investor. Our motivation arises from the implications such diversification benefits may have upon the trading strategies of offshore fund managers. Our research indicates that the Australian equities market, as a whole, does not provide a global investor with any unique diversification benefits that are not available elsewhere.
Denoising of 3 D Magnetic Resonance Images by Using 1 Higher-Order Singular Value Decomposition 2

The denoising of magnetic resonance (MR) images is important to improve the inspection quality and reliability of quantitative image analysis. Nonlocal filters by exploiting similarity and/or sparseness among patches or cubes achieve excellent performance in denoising MR images. Recently, higher-order singular value decomposition (HOSVD) has been demonstrated to be a simple and effective method for exploiting redundancy in the 3D stack of similar patches during denoising 2D natural image. This work aims to investigate the application and improvement of HOSVD to denoising MR volume data. The wiener-augmented HOSVD method achieves comparable performance to that of BM4D. For further improvement, we propose to augment the standard HOSVD stage by a second recursive stage, which is a repeated HOSVD filtering of the weighted summation of the residual and denoised image in the first stage. The appropriate weights have been investigated by experiments with different image types and noise levels. Experimental results over synthetic and real 3D MR data demonstrate that the proposed method outperforms current state-of-the-art denoising methods. Abstract 1 The denoising of magnetic resonance (MR) images is important to improve the 2 inspection quality and reliability of quantitative image analysis. Nonlocal filters by 3 exploiting similarity and/or sparseness among patches or cubes achieve excellent 4 performance in denoising MR images. Recently, higher-order singular value 5 decomposition (HOSVD) has been demonstrated to be a simple and effective method 6 for exploiting redundancy in the 3D stack of similar patches during denoising 2D 7 natural image. This work aims to investigate the application and improvement of 8 HOSVD to denoising MR volume data. The wiener-augmented HOSVD method 9 achieves comparable performance to that of BM4D. For further improvement, we 10 propose to augment the standard HOSVD stage by a second recursive stage, which is 11 a repeated HOSVD filtering of the weighted summation of the residual and denoised 12 image in the first stage. The appropriate weights have been investigated by 13 experiments with different image types and noise levels. Experimental results over 14 synthetic and real 3D MR data demonstrate that the proposed method outperforms 15 current state-of-the-art denoising methods.
The Mantis parallel debugger

Parallel tools often fad to integrate effectively with other parallel systems, exacerbating the inherent difficulty of programming a massively parallel machine. Successful parallel debugging requires the rethinking of traditional debugging goals in the context of parallelism. The following four objectives: rapid focus, scalability, economy of presentation, and portability, represent the more dificult aspects of parallel debugging. In light of these specific goals, this paper presents Mantis, a graphical debugger for paraliei programs. Mantis targets the lwoad class of paralle[ programs known as bulk synchronous SPMD programs and provides support for Split-C, a paraliel extension of C. Although designed for parallel debugging, the Mantis interface also supports sequential debugging, aIlowing a single environment for both sequential and parallel debugging. Mantis currently runs on the Thinking Machines Corp. CM-5 and on networks of workstations and is built using a Tcl/Tk graphica! user interface tinked to a modified version of the Free Software Foundation’s gdb debugger. Through the application of a clear set of general principles, Mantis haa become a practical parallel tool. Mantis made its debut at U. C. Berkeley during the Spring 199J semester and has been used heavily by the parallel computation course for two years.
Automation spectrum, inner / outer compatibility and other potentially useful human factors concepts for assistance and automation

Enabled by scientific, technological and societal progress, and pulled by human demands, more and more aspects of our life can be assisted or automated. One example is the transportation domain, where in the sky commercial aircraft are highly automated, and on the roads a gradual revolution takes place towards assisted, highly automated or fully automated cars and trucks. Assistance and automation can have benefits such as higher safety, lower workload, or a fascination of use. Assistance and automation can also come with downsides, especially regarding the interplay between human and technology (e.g., Bainbridge, 1983; Billings, 1997; Norman, 1990; Sarter and Woods, 1995a). In parallel to the technological progress, the science of human factors has to be continuously developed such that it can help to handle the technological complexity without adding new complexity (e.g., Hollnagel, 2007). In this overview article, some fundamental human factors issues for assistance and automation that the authors found useful in their daily work are briefly sketched. Some examples are described how those concepts could be used in the development of assistance and automation systems. While the article deals especially with assistance and automation in vehicles, the underlying concepts might also be useful in other domains.
Finite-time stabilization of switching linear systems with uncertain resetting times

In this paper we deal with the finite-time stability analysis and control of switching linear systems, which are linear continuous-time systems with isolated discrete switching events, and whose state can undergo finite jump discontinuities. Moreover, the case in which the time occurrence of the switching events is unknown is considered. Sufficient conditions for finite-time stability and stabilization are provided in terms of feasibility problems involving differential LMIs. Numerical examples are provided to better illustrate the proposed approach.
The Structure of Wages and Investment in General Training

In the human capital model with perfect labor markets, firms never invest in general skills and all cost of general training are borne by workers. When lobor market frictions compress the structure of wages, firms may pay for these investments. The distortion in the wage structure turns “technologically” general skills into de facto “specific ” skills. Credit market imperfections are neither neccessary nor sufficient for firm‐sponsored training. Since labor market frictions and insititutions shape the wage structure, they may have an important impact on the financing and amount of human capital investments and account for some international differences in training practices.
Passing the burden: corporate tax incidence in open economies

High rates of corporate taxation reduce corporate investment and thereby depress local wages. Using cross-country data from the Luxembourg Income Study, I estimate that a ten percentage point increase in the corporate tax rate of high-income countries reduces mean annual gross wages by seven percent. The results do not support the common belief that the burden of corporate taxes falls most heavily on skilled labor; corporate taxation appears to reduce the wages of low-skill workers to the same degree that it reduces the wages of high-skill workers. Interactions between corporate tax rates and measures of economic openness suggest that firms more effectively avoid corporate taxes as the economy becomes more open. The inefficiency of taxing corporate income, together with the incidence of the tax in the form of reduced wages, suggests that taxing labor instead of taxing corporations could be Pareto-improving.
What a Rational Interpreter Would Do : Building , Ranking , and Updating Quantifier Scope Representations in Discourse

We frame the general problem of ‘rationally’ (in the sense of Anderson et al’s ACT-R framework) integrating semantic theories and processing, and indicate how this integrated theory could be explicitly formalized; an explicit formalization enables us to empirically evaluate semantic and processing theories both qualitatively and quantitatively. We then introduce the problem of quantifier scope, the processing difficulty of inverse scope, and two types of theories of scope, and discuss the results of a self-paced reading experiment and its consequences for these two types of theories. Finally, we outline how probabilities for LF construction rules could be computed based on the experimental results.
Non-Abelian statistics from an Abelian model

It is well known that the Abelian ${Z}_{2}$ anyonic model (toric code) can be realized on a highly entangled two-dimensional spin lattice, where the anyons are quasiparticles located at the end points of stringlike concatenations of Pauli operators. Here we show that the same entangled states of the same lattice are capable of supporting the non-Abelian Ising model, where the concatenated operators are elements of the Clifford group. The Ising anyons are shown to be essentially superpositions of the Abelian toric code anyons, reproducing the required fusion, braiding, and statistical properties. We propose a string framing and ancillary qubits to implement the nontrivial chirality of this model.
Mining Sequences in Distributed Sensors Data for Energy Production

The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is concerned with sequence mining on power generation data and has the intent of modeling power generation. The data streams analyzed are average hourly power generation that is reported to the EPA. A global statistical model is proven impractical for the data streams, and local modeling via sequence mining is performed. The methodology presented, Uniform Sequence Discovery, implements the idea of uniform population coding, stream mining, and cross-stream mining. 1671 streams from years 2002 through 2004 are coded, mined for sequences, and cross-mined for matching sequences. 486 and 270 frequent sequences were extracted from the learning and testing data respectively. Association rules and the accompanying confidence and support values are used to create local models for power generation prediction. 159 local models were confirmed in the testing phase with a minimum confidence of 0.60. Power traders, concerned with predicting available generation, would then use the local models for prediction of natural gas-fired power generation.
An Action Language for Multi-Agent Domains: Foundations

In multi-agent domains (MADs), an agent's action may not just change the world and the agent's knowledge and beliefs about the world, but also may change other agents' knowledge and beliefs about the world and their knowledge and beliefs about other agents' knowledge and beliefs about the world. The goals of an agent in a multi-agent world may involve manipulating the knowledge and beliefs of other agents' and again, not just their knowledge/belief about the world, but also their knowledge about other agents' knowledge about the world. Our goal is to present an action language (mA+) that has the necessary features to address the above aspects in representing and RAC in MADs. mA+ allows the representation of and reasoning about different types of actions that an agent can perform in a domain where many other agents might be present -- such as world-altering actions, sensing actions, and announcement/communication actions. It also allows the specification of agents' dynamic awareness of action occurrences which has future implications on what agents' know about the world and other agents' knowledge about the world. mA+ considers three different types of awareness: full-, partial- awareness, and complete oblivion of an action occurrence and its effects. This keeps the language simple, yet powerful enough to address a large variety of knowledge manipulation scenarios in MADs. The semantics of mA+ relies on the notion of state, which is described by a pointed Kripke model and is used to encode the agent's knowledge and the real state of the world. It is defined by a transition function that maps pairs of actions and states into sets of states. We illustrate properties of the action theories, including properties that guarantee finiteness of the set of initial states and their practical implementability. Finally, we relate mA+ to other related formalisms that contribute to RAC in MADs.
Impact of Real Effective Exchange Rate on Inflation in Pakistan

The determination of inflation is widely debated all over the world. The macroeconomic variables namely: money supply, income velocity of circulation, real effective exchange rate and real income of the economy are the main affect of inflation. The objective of the study was to investigate the impact of real effective exchange rate on inflation in Pakistan. The time series data of real GDP, nominal GDP, real effective exchange rate, prices and money supply for the period of 1973 to 2007 was used in the study. It was concluded that the real effective exchange rate has impact upon inflation in Pakistan. The correlation matrix of the explanatory variables was calculated to establish the relationship among real effective exchange rate and with other variables. A positive and strong relationship between the real effective exchange rate and inflation was found.
Automatic heart rate detection from FBG sensors using sensor fusion and enhanced empirical mode decomposition

Cardiovascular diseases are the world's top leading causes of death. Real time monitoring of patients who have cardiovascular abnormalities can provide comprehensive and preventative health care. We investigate the role of the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and sensor fusion for automatic heart rate detection from a mat with embedded Fiber Bragg Grating (FBG) sensor arrays. The fusion process is performed in the time domain by averaging the readings of the sensors for each sensor array. Subsequently, the CEEMDAN is applied to obtain the interbeat intervals. Experiments are performed with 10 human subjects (males and females) lying on two different positions on a bed for a period of 20 minutes. The overall system performance is assessed against the reference ECG signals. The average and standard deviation of the mean relative absolute error are 0.049, 0.019 and 0.047, 0.038 for fused and best sensors respectively. Sensor fusion together with CEEMDAN proved to be robust against motion artifacts caused by body movements.