Miracle-dz/UniFAR-FTUs huggingface dataset:
Matched Detector and Estimator with Signature Uncertainty

We consider the detection and estimation of a signal, whose associated spatial signature is imperfectly known, in the presence of broad-band noise. While in most cases, the spatial signature (or steering vector) is assumed to be known, i.e., lies along a known direction, we consider the case where the signature is known up to additive white Gaussian noise. This amounts to assuming that it somehow lies in a cone, the aperture of which depends upon the level of uncertainty. We consider the multiple snapshots case and assume the unknown signature to remain constant over the whole set of snapshots. We develop the maximum likelihood estimator of the different unknowns, build the generalized likelihood ratio (GLR). We then evaluate the statistical properties of the associated test under both hypotheses and check the validity of the asymptotic analysis on simulations.
Validation of Potential Reference Genes for qPCR in Maize across Abiotic Stresses, Hormone Treatments, and Tissue Types

The reverse transcription quantitative polymerase chain reaction (RT-qPCR) is a powerful and widely used technique for the measurement of gene expression. Reference genes, which serve as endogenous controls ensure that the results are accurate and reproducible, are vital for data normalization. To bolster the literature on reference gene selection in maize, ten candidate reference genes, including eight traditionally used internal control genes and two potential candidate genes from our microarray datasets, were evaluated for expression level in maize across abiotic stresses (cold, heat, salinity, and PEG), phytohormone treatments (abscisic acid, salicylic acid, jasmonic acid, ethylene, and gibberellins), and different tissue types. Three analytical software packages, geNorm, NormFinder, and Bestkeeper, were used to assess the stability of reference gene expression. The results revealed that elongation factor 1 alpha (EF1α), tubulin beta (β-TUB), cyclophilin (CYP), and eukaryotic initiation factor 4A (EIF4A) were the most reliable reference genes for overall gene expression normalization in maize, while GRP (Glycine-rich RNA-binding protein), GLU1(beta-glucosidase), and UBQ9 (ubiquitin 9) were the least stable and most unsuitable genes. In addition, the suitability of EF1α, β-TUB, and their combination as reference genes was confirmed by validating the expression of WRKY50 in various samples. The current study indicates the appropriate reference genes for the urgent requirement of gene expression normalization in maize across certain abiotic stresses, hormones, and tissue types.
The Protestant Work Ethic and Attitudes Towards Work

Abstract In this paper we will present the concept of Protestant Work Ethics as conceptualized and measured by several authors, starting with its initiator, Max Weber, in order to emphasize the importance of work ethic on attitudes towards work. We will also analyze the four dimensions of work ethic - hard work, nonleisure, independence and asceticism, identified by Blau and Ryan (1997) among military students, trying to identify how they vary according to a series of socio- demographic data of military students.
VAMNET: the functional approach to distributed programming

This article gives a design overview of a new reliable distributed operating system environment, combining the world of functional and distributed programming using a virtual machine approach for hiding system dependencies, offering rapid prototyping facilities. The basic operating system concepts used are derived from the Amoeba operating system by Andrew Tanenbaum and his work group, developed 20 years ago. VAMNET is not only a native operating system. It is a hybrid solution for expanding widely used operating systems like UNIX with a distributed execution environment.
A Reconfigurable Framework for Performance Enhancement With Dynamic FPGA Configuration Prefetching

Many modern applications exhibit a dynamic and nonstationary behavior, with certain characteristics in one phase of their execution, which change as the application enters new phases, in a manner unpredictable at design-time. In order to meet the demands of such applications, it is important to have adaptive and self-reconfiguring hardware platforms, coupled with intelligent on-line optimization algorithms, that together can adjust to the run-time requirements. Partially dynamically reconfigurable field programmable gate array architectures offer both high performance and flexibility. Despite these potential advantages, the challenges faced by designers trying to set-up a functioning system are still significant, mainly because of the still immature design tools and limited device drivers. We propose a complete framework, based on Xilinx's commercial design suite, that enables an application designer to leverage the advantages of partial dynamic reconfiguration with minimal effort. Our IP-based architecture, together with the comprehensive application programming interface, can be employed to accelerate an application by dynamically scheduling hardware prefetches. Moreover, a piecewise linear predictor is used to capture correlations and predict the hardware modules that will generate the highest performance improvement. Our evaluation comprises of extensive simulations, as well as a complete implementation of the smallest univalue segment assimilating nucleus image processing application on the ML605 board from Xilinx. The measurements show a significant reduction of the expected execution time compared to previous state-of-the-art prefetching algorithms, with only a minor energy overhead.
C O ] 2 5 Ju n 20 09 MOND effects in the inner solar system

I pinpoint a previously unrecognized MOND effect that may act in the inner solar system, and is due to the galactic acceleration, g g = ηa 0 : a byproduct of the MOND external-field effect. Predictions of the effect are not generic to the MOND paradigm, but depend on the particular MOND formulation at hand. However, the modified-Poisson formulation, on which I concentrate, uniquely predicts a subtle anomaly that may be detected in planetary and spacecraft motions (and perhaps in other precision systems, such as binary pulsars), despite their very high accelerations, and even if the MOND interpolating function is arbitrarily close to unity at high accelerations. Near the sun, this anomaly appears as a quadrupole field, with the acceleration at position u from the sun being g a i (u) = −q a ij u j , with q a ij diagonal, axisymmetric, and traceless: −2q a xx = −2q a yy = q a zz = q(η)(a 0 /r t), where r t = (M ⊙ G/a 0) 1/2 ≈ 8·10 3 a.u. is the MOND transition radius of the sun. The anomaly is described and analyzed as the Newtonian field of the fictitious cloud of " phantom matter " that hovers around the sun. I find, for the relevant range of η values, and for a range of interpolating functions, µ(x), values of 10 −2 −q 0.3, which turn out to be sensitive to the form of µ(x) around the MOND-to-Newtonian transition. This range verges on the present bounds from solar system measurements. There might thus exist favorable prospects for either measuring the effect, or constraining the theory and relevant parameters. Probing this anomaly may also help distinguish between modified inertia and modified gravity formulations of MOND. I also discuss briefly an anomaly that is generic to MOND in all its formulations, and competes with the quadrupole anomaly in the special case that 1 − µ(x) vanishes as x −3/2 as x → ∞.
Dynamic Analysis of Trade Balance and Real Exchange Rate: A Stationary VAR Form of Error Correction Model Approach

This paper analyzes the dynamics of trade balance and real exchange rate based on the elasticity and purchasing power parity (PPP) approaches. Here, a stationary vector autoregressive model with cointegration error, transformed from the error correction model in Kim (2012), is employed. Trade balance and PPP are jointly considered as the two long-run cointegration relationships that represent external economy equilibria. The model was applied to the dynamic analyses of Korea’s trade balance using monthly data from 1990, where model variables from the elasticity and PPP approaches were selected. Based on the estimation, we first confirmed the finding of Cheung et al. (2004), whereas trade balance is additionally considered. The nominal exchange rate adjustment, not the price adjustment, is the key engine that governs the speed of PPP convergence, and the nominal exchange rates were found to converge much more slowly than the prices. The nominal exchange shock did not significantly affect trade balance, whereas the price shocks did. Therefore, manipulation of the nominal exchange rate through intervention to improve trade balance might not be an effective policy tool.
ANALISIS RANTAI NILAI (VALUE CHAIN) KOMODITAS IKAN BANDENG DI KECAMATAN JUWANA, KABUPATEN PATI

Juwana district is the largest producer of Milkfish production in Pati Regency. The high potential of Milkfish production in Juwana District had not been registered along with the number of milkfish processors, so that it causes an actual occurrence of value chain at a complete standstill. This research aims to analyse the commodity value chain so therefore will increase the productivity of Milkfish commodity in Juwana District, Pati Regency, Central Java. An analysis of the Value Chains Analysis is used as a method. The sample that used was quota sampling by the number 100 farmers as respondents and Snowballing method was applying for respondents, Milkfish processors, wholesale, and retail fishmongers in Porda market. The method for interview is about to ask the key person from academia, business, government, and community (A-B-G-C). The results showed that in the Commodity Value Chain of Milkfish refers to margin’ the fish farmers and wholesale fishmongers were 0 in Porda market. It was caused by the wholesale fishmongers acted as commissioners. Margin’ for fishmongers and the retailers were 1.000, meanwhile margin for Milkfish processors and retail of fishmongers are 20.000, therefore the significant number of increasing margin was caused by value added in the processing of Milkfish
Local binary patterns and its variants for face recognition

Face recognition is one of the most important tasks in computer vision and Biometrics. Texture is an important spatial feature useful for identifying objects or regions of interest in an image. Texture based face recognition is widely used in many applications. LBP method is most successful for face recognition. It is based on characterizing the local image texture by local texture patterns. In this paper performance evaluation of Local Binary Pattern (LBP) and its modified models Multivariate Local Binary Pattern (MLBP), Center Symmetric Local Binary Pattern (CS-LBP) and Local Binary Pattern Variance (LBPV) are investigated. Facial features are extracted and compared using K nearest neighbour classification algorithm. G-statistics distance measure is used for classification. Experiments were conducted on JAFFE female, CMU-PIE and FRGC version 2 databases. The results shows that CS-LBP consistently performs much better than the remaining other models.
OSCAR KEMPTHORNE AND THE DISTRIBUTION OF QUADRATIC FORMS

For a considerable number of years, Oscar Kempthorne and I were colleagues in the Iowa State University Department of Statistics and shared the responsibility for the teaching of two graduate-level courses on linear models. The first of these was an M.S.-level course in which most, but not all, of the students were statistics majors and for which an introductory course in linear or matrix algebra was a prerequisite. The second was a Ph.D.-level course with an enrollment consisting (aside from a very occasional exception) entirely of statistics majors. Both of these courses included some coverage of the distribution of quadratic forms, as do most courses on linear models. And, as do most instructors of such courses, Oscar and I wrestled with various questions about how this material should be taught. There are two results on the distribution of quadratic forms that are of great importance in linear-model theory. One of them gives a condition that is necessary and sufficient for a quadratic form (in normal variates) to have a (possibly noncentral) chi-square distribution. In some comments published (as a letter to the editor) in the American Statistician (Harville 2000), I offered some opinions on various issues related to how this result should be presented and proved. The second important result on the distribution of quadratic forms gives conditions that are necessary and sufficient for quadratic forms to be distributed independently of each other and of linear forms. It is this second result that is the subject in what follows. Let x represent an random vector whose distribution is MVN (multivariate normal) with mean vector and variance-covariance matrix V. And, let A and B represent symmetric matrices, and take a and b to be -dimensional column vectors. Further, define a x x Ax and b x x Bx (where and are scalars). In the important special case where V is nonsingular, a necessary and sufficient condition for two linear forms a x and b x to be statistically independent is that a Vb , a necessary and sufficient condition for a linear form b x and a quadratic form x Ax to be statistically independent is AVb 0 (or equivalently b VA 0 ), and a necessary and sufficient condition for two quadratic forms x Ax and x Bx to be statistically independent is AVB 0. For purposes of both proof and presentation, I find it convenient to regard all three of these results as special cases of the following theorem. Theorem 1. Suppose that V is nonsingular. Then, for and to be statistically independent, it is necessary and sufficient that
Detection and classification of painted road objects for intersection assistance applications

For a Driving Assistance System dedicated to intersection safety, knowledge about the structure and position of the intersection is essential, and detecting the painted road signs can greatly improve this knowledge. This paper describes a method for detection, measurement and classification of painted road objects that are typically found in European intersections. The features of the painted objects are first extracted using dark light dark transition detection on horizontal line regions, and then are refined using gray level segmentation based on Gaussian mixtures. The 3D bounding box of the objects is reconstructed using perspective geometry. The objects are classified based on a restricted set of features, using a decision tree and size constraints.
Monetary Shocks and Real Exchange Rates

Many explanations of the stylized facts concerning real exchange rate movements focus on monetary shocks, but it is often found empirically that monetary shocks are unimportant. I provide evidence that is contrary to this empirical finding. Using over 100 years of data, I estimate the contribution of various shocks to explaining variation in the real pound-dollar exchange rate. Monetary shocks consist of both monetary base and money multiplier shocks; real shocks include fiscal, productivity, and preference shocks. Estimates of several alternative VAR specifications provide a range for the contribution of the various shocks: from 19 to 60 percent in the short-run for monetary shocks and 4 to 26 percent for fiscal and productivity shocks combined. My modeling strategy and results are compared directly to related work. The results lend empirical support to the convention in recent quantitative general equilibrium modeling of focusing on monetary shocks.
Position Changes in Chinese Phrase : A fMRI Study

Position changes in Chinese phrase are explained with light verb assumption in Generative Grammar. With regards to the idea that light verb is a hypothetical element, this study attempted to find the brain neural correlates in positions changes of Chinese phrases and whether this processing is launched by light verb or not. The results show that these phrases which can change the positions activated more brain areas than those that can’t change positions. In particular, the activated left inferior frontal gyrus indicated that this activation involved a syntactic process. It is possible that light verb made this process occur.
A Distinct Class of Slow (∼0.2–2 Hz) Intrinsically Bursting Layer 5 Pyramidal Neurons Determines UP/DOWN State Dynamics in the Neocortex

During sleep and anesthesia, neocortical neurons exhibit rhythmic UP/DOWN membrane potential states. Although UP states are maintained by synaptic activity, the mechanisms that underlie the initiation and robust rhythmicity of UP states are unknown. Using a physiologically validated model of UP/DOWN state generation in mouse neocortical slices whereby the cholinergic tone present in vivo is reinstated, we show that the regular initiation of UP states is driven by an electrophysiologically distinct subset of morphologically identified layer 5 neurons, which exhibit intrinsic rhythmic low-frequency burst firing at ∼0.2–2 Hz. This low-frequency bursting is resistant to block of glutamatergic and GABAergic transmission but is absent when slices are maintained in a low Ca2+ medium (an alternative, widely used model of cortical UP/DOWN states), thus explaining the lack of rhythmic UP states and abnormally prolonged DOWN states in this condition. We also characterized the activity of various other pyramidal and nonpyramidal neurons during UP/DOWN states and found that an electrophysiologically distinct subset of layer 5 regular spiking pyramidal neurons fires earlier during the onset of network oscillations compared with all other types of neurons recorded. This study, therefore, identifies an important role for cell-type-specific neuronal activity in driving neocortical UP states.
An Efficient Similarity Search For Financial Multivariate Time Series

Multivariate time series (MTS) data sets are common in many multimedia, medical, process industry and financial applications such as gesture recognition, video sequence matching, EEG/ECG data analysis or prediction of abnormal situation or trend of stock price. In order to efficiently perform similarity search for financial MTS datasets, we present a distance-based index structure (Dbis) for range search and k nearest neighbor (kNN) search. The financial MTS database is parted by cluster, A MTS item is selected for each partition as reference point. The MTS items in each partition are transformed into a single dimensional space based on their similarity with respect to a reference MTS item. This allows the MTS items to be indexed by using a B+-tree structure. An extended Frobenius norm (Eros) is used to compare the similarity between MTS items. Several experiments on a financial MTS database are performed and the results show the effectiveness of Dbis.
The process of spatial knowledge acquisition in a square and a circular virtual environment

This study investigated the effect of the environmental structure (circular vs. square environment) on spatial knowledge acquisition in a desktop virtual situation in which self-determined movement was allowed with a total of 120 participants: 7-, 8-year-old children; 11, 12-year-old children, and adults. In all measurements of spatial knowledge acquisition an overall developmental performance increase from younger children to adults was found. In contrast to that, the exploration and learning behavior did not differ between adults and children. Furthermore, the environmental structure influencedthenumber of trials needed to learn the two routes used and the distance walked to the determined landmarks. All these tasks were easier in a circular than in a square environment. This influenceofthe environmental structure was absent in the direction estimations task. The advantage of spatial knowledge acquisition in a circular environment in three of four tasks is discussed.
Scaling Up Reinforcement Learning with a Relational Representation

Reinforcement learning has been repeatedly suggested as good candidate for learning in robotics. However, the large search spaces normally occurring robotics and expensive training experiences required by reinforcement learning algorithms has hampered its applicability. This paper introduces a new approach for reinforcement learning based on a relational representation which: (i) can be applied over large search spaces, (ii) can incorporate domain knowledge, and (iii) can use previously learned policies on different, although similar, problems. In the proposed framework states are represented as sets of first order relations, actions in terms of those relations, and policies are learned over such generalized representation. It is shown how this representation can capture large search spaces with a relatively small set of actions and states, and that policies learned over this generalized representation can be directly apply to other problems which can be characterized by the same set of
Towards Including Simple Emotions in a Cognitive Architecture in Order to Better Fit Children’s Behavior

Emotions are an important aspect of human behavior that should be included in cognitive models. Including them in a cognitive architecture is the safest way to ensure consistency, and to get reuse. We demonstrate here how interest, distress, and pleasure, three primary emotions shown by children when problem solving, can be implemented in a specific ACT-R (Anderson & Lebiere, 1998) model. These emotions can be initially implemented by modifying some of the ACT-R problem solving mechanisms and our reusable model of vision. While emotions can be a result of information and knowledge processing, they are not purely cognitive processes. They may result in bodily changes (hormones etc.) that influence behavior, perception and decision making. Our task is to implement a simple theory of emotions into the ACT-R cognitive architecture and test it on an existing model of human behavior.
Beyond Utterances: Distributed Cognition as a Framework for Studying Discourse in Adults with Acquired Brain Injury

Abstract Considerable effort has been directed at understanding the nature of the communicative deficits observed in individuals with acquired brain injuries. Yet several theoretical, methodological, and clinical challenges remain. In this article, we examine distributed cognition as a framework for understanding interaction among communication partners, interaction of communication and cognition, and interaction with the environments and contexts of everyday language use. We review the basic principles of distributed cognition and the implications for applying this approach to the study of discourse in individuals with cognitive-communication disorders. We also review a range of protocols and findings from our research that highlight how the distributed cognition approach might offer a deeper understanding of communicative mechanisms and deficits in individuals with cognitive communication impairments. The advantages and implications of distributed cognition as a framework for studying discourse in adults with acquired brain injury are discussed.