Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Spatial Concepts Using a Partially-structured Connectionist Architecture \above" Lm Tr Figure 1: Learning to Associate Scenes with Spatial Terms

This paper reports on the learning of spatial concepts in the L 0 project. The challenge of designing an architecture capable of learning spatial concepts from any of the world's languages is rst highlighted by reviewing the spatial systems of a number of languages which diier strikingly from English in this regard. A partially structured connectionist architecture is presented which has successfully learned concepts from the languages outlined. In this architecture, highly structured subnetworks, specialized for the spatial concept learning task, feed into an unstructured, fully-connected upper subnetwork. The system's success at the learning task is attributed on the one hand to the constrained search space which results from structuring, and on the other hand to the exibility aaorded by the unstructured upper subnetwork.
Middle managers : managing change in a Lao higher education institution

ii ACKNOWLEDGEMENTS iii LIST OF TABLES AND FIGURES ix LIST OF ABBREVIATIONS x CHAPTER ONE: INTRODUCTION 1 BACKGROUND 3 RATIONALE 3 RESEARCH AIMS AND QUESTIONS 6 Research aims 6 Research questions 6 THESIS OUTLINE 7 CHAPTER TWO: LITERATURE REVIEW 9 INTRODUCTION 9 CONCEPT OF MIDDLE MANAGEMENT 9 Academic middle manager’s role in higher education 11 The challenges for academic middle managers in managing change 14 LEADERSHIP FOR CHANGE MANAGEMENT 17 Definition of leadership 17 The role of leadership in change management 18 ORGANISATIONAL CULTURE IN TIMES OF CHANGE 20 Understanding organisational culture 20 The importance of culture in change management 21 ORGANISATIONAL CHANGE 23 Perspectives of change management 23 Capabilities for change management 25 Change models 26
Feature oriented refactoring of legacy applications

Feature oriented refactoring (FOR) is the process of decomposinga program into features, where a feature is an increment in programfunctionality. We develop a theory of FOR that relates code refac-toring to algebraic factoring. Our theory explains relationshipsbetween features and their implementing modules, and why fea-tures in different programs of a product-line can have differentimplementations. We describe a tool and refactoring methodologybased on our theory, and present a validating case study.
On the Inexplicability of the Implicit: Differences in the Information Provided by Implicit and Explicit Tests

Abstract Implicit measures are often preferred to overt questioning in many areas of psychology. Their covert nature allows them to circumvent conscious expectations and biases, theoretically providing more objective indicators of people's true attitudes and beliefs. However, we argue that implicit and explicit measures tap into different memory systems, so that the interpretation of implicit measures is not as straightforward as the interpretation of explicit measures. We conducted an experiment investigating the relation between implicit and explicit measures of person impressions. The results demonstrate that a single stimulus can have opposite effects on implicit and explicit measures, supporting the theory that the measures reflect the contents of different memory systems. We suggest that implicit measures reflect simple associations stored in a “slow–learning” memory system, while explicit measures reflect a combination of these associations with contextually dependent memories stored in a “fast–bin.
Gravitomagnetic Moments of the Fundamental Fields

The quadratic form of the Dirac equation in a Riemann space–time yields a gravitational gyromagnetic ratio κS=2 for the interaction of a Dirac spinor with curvature. A gravitational gyromagnetic ratio κS=1 is also found for the interaction of a vector field with curvature. It is shown that the Dirac equation in a curved background can be obtained as the square-root of the corresponding vector field equation only if the gravitational gyromagnetic ratios are properly taken into account.
Information, Matching and Outcome Selection

We consider a finite population of agents who exchange information and are paired every period to play a game with tension between risk dominance and Pareto efficiency. Agents sample past plays and corresponding payoffs from their information neighborhood, and choose one of two possible actions using either best response or imitation. Information exchanges and possible matchings each constitutes a network. We first provide a complete description of the medium run outcomes and show that in the medium run only information matters. We then identify the conditions whereby either the risk dominant or the Pareto efficient convention is stochastically stable, and show how efficiency in the long run depends on the matching network.
A QoS-Oriented Reconfigurable Middleware for Self-Healing Web Services

Maintaining the Quality of Service (QoS) is important for self-healing web service-based distributed interactive applications. It requires the ability to deal with permanently changing constraints both at the communication and the execution levels. Preventing or repairing QoS degradation also requires the capacity of identifying its possible or actual sources and the capacity of reconfiguration decision and enforcement. Dealing with these issues is especially challenging for web services since the self-healing solution has to preserve the dynamic composition property and to be seamless for the service requesters, while being always usable under the different deployment constraints. In this paper, we present a self-healing middleware framework able to provide the self-healing properties for QoS management in web service-based distributed interactive applications. The framework implementation has been achieved in the context of the WS-DIAMOND project. It covers the whole cycle of adaptation management including monitoring and analysis of QoS values, and substitution-based reconfiguration.
Active envelope load pull system suitable for high modulation rate multi-tone applications

Power amplifiers used in modern wireless systems need to efficiently transmit signals, without distortion, that have complex envelopes with variable phase and amplitude. The design of these power amplifiers require that transistors are characterized under complex excitations into variable load impedances, so that determination of perfect matching conditions for optimum performance is achieved. This paper presents a new active load pull system design, based on the envelope load-pull concept, which can provide for the required load-pull capability under high modulation rate multi-tone excitations. This performance is realized by incorporating analogue controlled delay elements into the envelope feedback loop to compensate for the inherent group delay encountered in the feedback loop. Measurements on a ldquoThrurdquo using this active load-pull system have demonstrated that it can provide constant, drive independent control of load impedances for multi-tone characterization of transistors and power amplifiers used in wireless communication systems such as GSM-EDGE.
Improving SAMC using smoothing methods: Theory and applications to Bayesian model selection problems

Stochastic approximation Monte Carlo (SAMC) has recently been proposed by Liang, Liu and Carroll [J. Amer. Statist. Assoc. 102 (2007) 305-320] as a general simulation and optimization algorithm. In this paper, we propose to improve its convergence using smoothing methods and discuss the application of the new algorithm to Bayesian model selection problems. The new algorithm is tested through a change-point identification example. The numerical results indicate that the new algorithm can outperform SAMC and reversible jump MCMC significantly for the model selection problems. The new algorithm represents a general form of the stochastic approximation Markov chain Monte Carlo algorithm. It allows multiple samples to be generated at each iteration, and a bias term to be included in the parameter updating step. A rigorous proof for the convergence of the general algorithm is established under verifiable conditions. This paper also provides a framework on how to improve efficiency of Monte Carlo simulations by incorporating some nonparametric techniques.
Genital Herpes Has Played a More Important Role than Any Other Sexually Transmitted Infection in Driving HIV Prevalence in Africa

Background Extensive evidence from observational studies suggests a role for genital herpes in the HIV epidemic. A number of herpes vaccines are under development and several trials of the efficacy of HSV-2 treatment with acyclovir in reducing HIV acquisition, transmission, and disease progression have just reported their results or will report their results in the next year. The potential impact of these interventions requires a quantitative assessment of the magnitude of the synergy between HIV and HSV-2 at the population level. Methods and Findings A deterministic compartmental model of HIV and HSV-2 dynamics and interactions was constructed. The nature of the epidemiologic synergy was explored qualitatively and quantitatively and compared to other sexually transmitted infections (STIs). The results suggest a more substantial role for HSV-2 in fueling HIV spread in sub-Saharan Africa than other STIs. We estimate that in settings of high HSV-2 prevalence, such as Kisumu, Kenya, more than a quarter of incident HIV infections may have been attributed directly to HSV-2. HSV-2 has also contributed considerably to the onward transmission of HIV by increasing the pool of HIV positive persons in the population and may explain one-third of the differential HIV prevalence among the cities of the Four City study. Conversely, we estimate that HIV had only a small net impact on HSV-2 prevalence. Conclusions HSV-2 role as a biological cofactor in HIV acquisition and transmission may have contributed substantially to HIV particularly by facilitating HIV spread among the low-risk population with stable long-term sexual partnerships. This finding suggests that prevention of HSV-2 infection through a prophylactic vaccine may be an effective intervention both in nascent epidemics with high HIV incidence in the high risk groups, and in established epidemics where a large portion of HIV transmission occurs in stable partnerships.
Adaptive responses of androgen receptor signaling in castration-resistant prostate cancer

Prostate Cancer (PCa) is an important age-related disease being the most common cancer malignancy and the second leading cause of cancer mortality in men in Western countries. Initially, PCa progression is androgen receptor (AR)- and androgen-dependent. Eventually advanced PCa reaches the stage of Castration-Resistant Prostate Cancer (CRPC), but remains dependent on AR, which indicates the importance of AR activity also for CRPC. Here, we discuss various pathways that influence the AR activity in CRPC, which indicates an adaptation of the AR signaling in PCa to overcome the treatment of PCa. The adaptation pathways include interferences of the normal regulation of the AR protein level, the expression of AR variants, the crosstalk of the AR with cytokine tyrosine kinases, the Src-Akt-, the MAPK-signaling pathways and AR corepressors. Furthermore, we summarize the current treatment options with regard to the underlying molecular basis of the common adaptation processes of AR signaling that may arise after the treatment with AR antagonists, androgen deprivation therapy (ADT) as well as for CRPC, and point towards novel therapeutic strategies. The understanding of individualized adaptation processes in PCa will lead to individualized treatment options in the future.
Formalization and validation of a subset of the European Train Control System

The European Train Control System (ETCS) is a control system for the interoperability of the railways across Europe. In this paper, we report on the activities of the EuRailCheck project, promoted by the European Railway Agency, for the development of a methodology and tools for the formalization and validation of the ETCS specifications. Within the project, we achieved three main results. First, we developed a methodology for the formalization and validation of the ETCS specifications. The methodology is based on a three-phases approach that goes from the informal analysis of the requirements, to their formalization and validation. Second, we developed a set of support tools, covering the various phases of the methodology. Third, we formalized a realistic subset of the specification in an industrial setting. The results of the project were positively evaluated by domain experts from different manufacturing and railway companies.
On disclosure risk analysis of anonymized itemsets in the presence of prior knowledge

Decision makers of companies often face the dilemma of whether to release data for knowledge discovery, vis-a-vis the risk of disclosing proprietary or sensitive information. Among the various methods employed for “sanitizing” the data prior to disclosure, we focus in this article on anonymization, given its widespread use in practice. We do due diligence to the question “just how safe is the anonymized data? ” We consider both those scenarios when the hacker has no information and, more realistically, when the hacker may have partial information about items in the domain. We conduct our analyses in the context of frequent set mining and address the safety question at two different levels: (i) how likely of being cracked (i.e., re-identified by a hacker), are the identities of individual items and (ii) how likely are sets of items cracked? For capturing the prior knowledge of the hacker, we propose a belief function, which amounts to an educated guess of the frequency of each item. For various classes of belief functions which correspond to different degrees of prior knowledge, we derive formulas for computing the expected number of cracks of single items and for itemsets, the probability of cracking the itemsets. While obtaining, exact values for more general situations is computationally hard, we propose a series of heuristics called the O-estimates. They are easy to compute and are shown fairly accurate, justified by empirical results on real benchmark datasets. Based on the O-estimates, we propose a recipe for the decision makers to resolve their dilemma. Our recipe operates at two different levels, depending on whether the data owner wants to reason in terms of single items or sets of items (or both). Finally, we present techniques for ascertaining a hacker's knowledge of correlation in terms of co-occurrence of items likely. This information regarding the hacker's knowledge can be incorporated into our framework of disclosure risk analysis and we present experimental results demonstrating how this knowledge affects the heuristic estimates we have developed.
Large-scale Gaussian Process Regression via Doubly Stochastic Gradient Descent

Gaussian process regression (GPR) is a popular tool for nonlinear function approximation. Unfortunately , GPR can be difficult to use in practice due to the O(n 2) memory and O(n 3) processing requirements for n training data points. We propose a novel approach to scaling up GPR to handle large datasets using the recent concept of doubly stochastic functional gradients. Our approach relies on the fact that GPR can be expressed as a convex optimization problem that can be solved by making two unbiased stochas-tic approximations to the functional gradient, one using random training points and another using random features, and then descending using this noisy functional gradient. The effectiveness of the resulting algorithm is evaluated on the well-known problem of learning the inverse dynamics of a robot manipulator.
Unitary equivalence of the metric and holonomy formulations of (2+1)-dimensional quantum gravity on the torus.

Recent work on canonical transformations in quantum mechanics is applied to transform between the Moncrief metric formulation and the Witten-Carlip holonomy formulation of (2+1)-dimensional quantum gravity on the torus. A nonpolynomial factor ordering of the classical canonical transformation between the metric and holonomy variables is constructed which preserves their classical modular transformation properties. An extension of the definition of a unitary transformation is briefly discussed and is used to find the inner product in the holonomy variables which makes the canonical transformation unitary. This defines the Hilbert space in the Witten-Carlip formulation which is unitarily equivalent to the natural Hilbert space in the Moncrief formulation. In addition, gravitational $\ensuremath{\theta}$ states arising from "large" diffeomorphisms are found in the theory.
Exploiting workload dynamics to improve SSD read latency via differentiated error correction codes

This article presents a cross-layer codesign approach to reduce SSD read response latency. The key is to cohesively exploit the NAND flash memory device write speed vs. raw storage reliability trade-off at the physical layer and runtime data access workload dynamics at the system level. Leveraging runtime data access workload variation, we can opportunistically slow down NAND flash memory write speed and hence improve NAND flash memory raw storage reliability. This naturally enables an opportunistic use of weaker error correction schemes that can directly reduce SSD read access latency. We develop a disk-level scheduling scheme to effectively smooth the write workload in order to maximize the occurrence of runtime opportunistic NAND flash memory write slowdown. Using 2 bits/cell NAND flash memory with BCH-based error correction correction as a test vehicle, we carry out extensive simulations over various workloads and demonstrate that this developed cross-layer co-design solution can reduce the average SSD read latency by up to 59.4% without sacrificing the write throughput performance.
CENTERED FEATURES FROM INTEGRAL IMAGES

An essential tool for fast image processing is the computation of image features. Integral Images are a popular approach to obtain this goal. A drawback of this technique is that it only allows for rectangular image features. In this paper, the goal is to investigate if circular image features outperform rectangular image features using integral image approach. Additionally, experimental work for the purpose of comparison between different and new descriptor methods has also been presented in this paper.
Decomposition Techniques with Subproblem Truncation

Typical decomposition techniques separate a monolithic optimization problem into master and subproblems. To obtain an optimal solution to the monolithic problem, the master and subproblems must be solved many times in an iterative fashion. Typical convergence proofs generally require that the subproblems are solved optimally or nearly so. For the latter, each subproblem in iteration k is solved, e.g., until an εk–optimal solution is obtained where εk converges to zero in the limit.
Use of Religious Doctrine and Symbolism in the Iran-Iraq War

The political and economic isolation of the Islamic Republic, brought on by its ideological rejection of Western and Soviet influences, gave greater weight to the use of religion in a pragmatic, compensatory fashion. In particular, political leaders of Iran used Islamic doctrines, symbolism, and language to legitimize their wartime policy. I argue that Iran’s political leaders specifically reconstructed certain Islamic tenets, both via the ahadith and juristic precedence, in order to justify military actions such as retaliation against non-combatants, human wave attacks, and economic warfare.
Video similarity search by using compact representations

The amount of applications using unstructured data, like videos, has been increased, and the researches concerning multimedia retrieval have attracted great attention. The need to efficiently index and retrieve this kind of data is of great concern, due to the fact that common searching approaches based on the use of keywords are not adequate for large video databases. Similarity search is a content based approach and it has been successfully used in retrieval systems. Accordingly, a major challenge is to provide an accurate and compact video representation that can achieve good performance with a fast answer in this type of searching. In this work, we proposed a compact video representation by using Min-Hash and the k-nearest GIST descriptors. Furthermore, we also present the first use of BossaNova Video Descriptor (BNVD) to video similarity search. Both compact video representations have shown more than 88% of mean average precision on similarity video search. The experimental results indicate high efficiency of our proposed representations in video retrieval task.
Returns to E/P Strategies, Higgledy-Piggledy Growth, Analysts' Forecast Errors, and Omitted Risk Factors

High E/P (low P/E) investing has been a popular investment strategy for many years. A n u mber of academic studies document that high E/P strategies have historically generated, on average, above-normal returns. Some examples are Basu [1983], Goodman and Peavey [1986], and Jaffe, Keim, and Westerfield [l989]. Fama and French [1992] also find positive abnormal returns associated with high E/P stocks, but they find an even stronger relationship between book value t o p rice ratios (B/P) and abnormal returns.
Reactive Maze Solving with a Biologically Inspired Wind Sensor

Tim Chapman Department of Psychology, University of Stirling, Scotland, FK9 4DN, UK t.p.chapman@stirling.ac. uk Adam T. Hayes MS136-93, California Institute of Technology, Pasadena, CA 91125, USA athayes@its.caltech. edu Mark W. Tilden MSA454, Los Alamos National Laboratory, Los Alamos, NM 87545, USA mwtilden@lanl.gov Abstract We describe the design and testing of a novel biologically-inspired wind sensor, based on the cricket's cercal liform hair cells. The sensor is mounted on a Khepera mobile robot, and competence at following a real wind plume is shown, even at low wind speeds. Further testing demonstrates the ability of the system to perform a dynamic maze solving task, and the exploitation of the hair sensors as tactile whiskers is discussed.
Origination, Expansion, Evolutionary Trajectory, and Expression Bias of AP2/ERF Superfamily in Brassica napus

The AP2/ERF superfamily, one of the most important transcription factor families, plays crucial roles in response to biotic and abiotic stresses. So far, a comprehensive evolutionary inference of its origination and expansion has not been available. Here, we identified 515 AP2/ERF genes in B. napus, a neo-tetraploid forming ~7500 years ago, and found that 82.14% of them were duplicated in the tetraploidization. A prominent subgenome bias was revealed in gene expression, tissue-specific, and gene conversion. Moreover, a large-scale analysis across plants and alga suggested that this superfamily could have been originated from AP2 family, expanding to form other families (ERF, and RAV). This process was accompanied by duplicating and/or alternative deleting AP2 domain, intragenic domain sequence conversion, and/or by acquiring other domains, resulting in copy number variations, alternatively contributing to functional innovation. We found that significant positive selection occurred at certain critical nodes during the evolution of land plants, possibly responding to changing environment. In conclusion, the present research revealed origination, functional innovation, and evolutionary trajectory of the AP2/ERF superfamily, contributing to understanding their roles in plant stress tolerance.