Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiobjective evolution of temporal rules

This thesis considers the problem of mining patterns in strings. Informally, this is the problem of extracting information (patterns) that characterizes parts of, or even the complete, string. The thesis describes a high performance hardware for string searching, which together with genetic programming, forms the basis for the thesis’ pattern mining algorithms.This work considers two different pattern mining problems and develops several different algorithms to solve different variants of these problems. Common to all algorithms is that they use genetic programming to evolve patterns that can be evaluated by the special purpose search hardware.The first pattern mining problem considered is unsupervised mining of prediction rules in discretized time series. Such prediction rules describe relations between consecutive patterns in the discretized time series; that is, the prediction rules state that if the first pattern occurs, the second pattern will, with high probability, follow within a fixed number of symbols. The goal is to automatically extract prediction rules that are accurate, comprehensible, and interesting.The second pattern mining problem considered is supervised learning of classifiers that predict whether or not a given string belongs to a specific class of strings. This binary classification problem is very general, but this thesis focuses on two recent problems from molecular biology: i) predicting the efficacy of short interfering RNAs and antisense oligonucleotides; and ii) predicting whether or not a given DNA sequence is a non-coding RNA gene. The thesis describes a genetic programming based mining algorithm that produce state-of-the-art classifiers on both problems.
Critical Role of TCF-1 in Repression of the IL-17 Gene

Overwhelming activation of IL-17, a gene involved in inflammation, leads to exaggerated Th17 responses associated with numerous autoimmune conditions, such as experimental autoimmune encephalomyelitis (EAE). Here we show that TCF-1 is a critical factor to repress IL-17 gene locus by chromatin modifications during T cell development. Deletion of TCF-1 resulted in increased IL-17 gene expression both in thymus and peripheral T cells, which led to enhanced Th17 differentiation. As a result, TCF-1-/- mice were susceptible to Th17-dependent EAE induction. Rag1-/- mice reconstituted with TCF-1-/- T cells were also susceptible to EAE, indicating TCF-1 is intrinsically required to repress IL-17. However, expression of wild-type TCF-1 or dominant negative TCF-1 did not interfere with Th17 differentiation in mature T cells. Furthermore, expression of TCF-1 in TCF-1-/- T cells could not restore Th17 differentiation to wild-type levels, indicating that TCF-1 cannot affect IL-17 production at the mature T cell stage. This is also supported by the normal up-regulation or activation in mature TCF-1-/- T cells of factors known to regulate Th17 differentiation, including RORγt and Stat3. We observed hyperacetylation together with trimethylation of Lys-4 at the IL-17 locus in TCF-1-/- thymocytes, two epigenetic modifications indicating an open active state of the gene. Such epigenetic modifications were preserved even when TCF-1-/- T cells migrated out of thymus. Therefore, TCF-1 mediates an active process to repress IL-17 gene expression via epigenetic modifications during T cell development. This TCF-1-mediated repression of IL-17 is critical for peripheral T cells to generate balanced immune responses.
Integrating Utilization Control with Task Consolidation for Power Optimization in Multi-Core Real-Time Systems

Since multi-core processors have become a primary trend in processor development, new scheduling algorithms are needed to minimize power consumption while achieving the desired timeliness guarantees for multi-core (and many-core) real-time embedded systems. Although various power/energyefficient scheduling algorithms have recently been proposed, existing studies may have degraded runtime performance in terms of power/energy efficiency and real-time guarantees when applied to real-time embedded systems with uncertain execution times. In this paper, we propose a novel online solution that integrates core-level feedback control with processor-level optimization to minimize both the dynamic and leakage power consumption of a multi-core real-time embedded system. Our solution monitors the utilization of each CPU core in the system and dynamically responds to unpredictable execution time variations by conducting per-core voltage and frequency scaling. We then perform task consolidation on a longer timescale and shut down unused cores for maximized power savings. Both empirical results on a hardware multi-core testbed with well-known benchmarks and simulation results in many-core systems show that our solution provides the desired real-time guarantees while achieving more power savings than three state-of-the-art algorithms.
An automatic modeling of human bodies from sizing parameters

In this paper, we present an automatic, runtime modeler for modeling realistic, animatable human bodies. A user can generate a new model or modify an existing one simply by inputting a number of sizing parameters.We approach the problem by forming deformation functions that are devoted to the generation of appropriate shape and proportion of the body geometry by taking the parameters as input. Starting from a number of 3D scanned data of human body models as examples, we derive these functions by using radial basis interpolation. A prerequisite of such formulation is to have correspondence among example models in the database. We obtain the correspondence by fitting a template onto each scanned data. Throughout the paper, body geometry is considered to have two distinct entities, namely rigid and elastic component of the deformation. The rigid deformation is represented by the corresponding joint parameters, which will determine the linear approximation of the physique. The elastic deformation is essentially vertex displacements, which, when added to the rigid deformation, depicts the detail shape of the body.Having these interpolators formulated, the runtime modeling can be reduced to the function evaluation and application of the evaluated results to the template model. We demonstrate our method by applying different parameters to generate a wide range of different body models.
Function Clone Detection in Web Applications: A Semiautomated Approach

Many web applications use a mixture of HTML and scripting language code as the front-end to business services, where scripts can run on both the client and server side. Analogously to traditional applications, code duplication occurs frequently during the development and evolution of web applications. This ad-hoc but pathological form of reuse consists in copying, and eventually modifying, a block of existing code that implements a piece of required functionality. Duplicated blocks are named clones and the act of copying, including slight modifications, is called cloning. When entire functions are copied rather than fragments, duplicated functions are called function clones. This paper describes how a semiautomated approach can be used to identify cloned functions within scripting code of web applications. The approach is based on the automatic selection of potential function clones and the visual inspection of selected script functions. The results obtained from the clone analysis of four web applications show that the semiautomated approach is both effective and efficient at identifying function clones in web applications, and can be applied to prevent clone from spreading or to remove redundant scripting code.
DC motor identification based on Recurrent Neural Networks

The paper describes system identification by using Artificial Neural Networks that is applied to a permanent magnet DC motor. To identify its dynamic behavior an experimental setup has been developed that enables to measure data of the system input (armature voltage) and output (current and rotor speed). Generally, the identification methods can be classified as parametric and non-parametric. We use a non-parametric method (black box). A recurrent neural network was used and the Nonlinear AutoRegressive network with eXogenous inputs network (NARX) has been selected. Parallel architectures have been used in training the NARX network. The scaled conjugate gradient training algorithm, using the first and second derivatives of error to train the network to minimize the error function, has been selected. The network architecture which has been used to create the dynamic model of the motor consists of three hidden layers, a single input neuron, and two output neurons. The modeled and measured normalized data were compared with good conformity.
ADAM and ADAMTS gene expression in native and wound healing human lens epithelial cells

Purpose The ADAMs (a disintegrin and metalloproteinase) and the ADAMTSs (a disintegrin and metalloproteinase with thrombospondin-like motifs) are extracellular proteases that mediate cellular interactions and cell signaling via the modulation of adhesion and the cleavage of cell surface protein ectodomains and extracellular matrix molecules. Gene expression profiling was undertaken to better understand the role of the ADAM and ADAMTS families in the clear native human lenses and following surgical injury with particular relevance to posterior capsule opacification. Methods To carry out profile analysis, the lens (t=0d) was dissected into three regions; anterior epithelia, equatorial region, and fiber cells. Capsular bag culture was undertaken as a means of assessing short-term changes (t=6d) and post-cataractous lens capsular bags (ex vivo) were used to predict long-term changes in ADAM/ADAMTS gene expression. RNA was isolated and quantitative real-time (TaqMan) reverse transcription-PCR (RT–PCR) performed. Data were analyzed in terms of cycle threshold number (CT) and also normalized relative to endogenous 18S rRNA. Results High expression of ADAM-9, -10, -15, and -17 was detected in all native lens regions. ADAM-15 expression was a characteristic of the native lens epithelia more than the fibers. Post-surgical injury, lens capsular bags showed a positive shift in ADAM/ADAMTS expression that was significant for ADAM-9, -15, and ADAMTS-3. Ex vivo capsular bags, with a long-term post surgical injury period, maintained high expression of ADAM-9 and -10 genes. Conclusions The native human lens expresses ADAM and ADAMTS genes that are differentially regulated following surgical injury. Roles in maintaining cellular adhesion may be of particular importance to native lens tissue integrity and may be lost in the lens wound healing response following cataract surgery.
Is Zolpidem Associated with Increased Risk of Fractures in the Elderly with Sleep Disorders? A Nationwide Case Cross-Over Study in Taiwan

Background We conducted a study using a case-crossover design to clarify the risk of acute effects of zolpidem and benzodiazepine on all-sites of fractures in the elderly. Design of study Case-crossover design. Methods and Materials Elderly enrollees (n = 6010) in Taiwan’s National Health Insurance Research Database with zolpidem or benzodiazepine use were analyzed for the risk of developing fractures. Results After adjusting for medications such as antipsychotics, antidepressants, and diuretics, or comorbidities such as hypertension, osteoarthritis, osteoporosis, rheumatoid arthritis and depression, neither zolpidem nor benzodiazepine was found to be associated with increased risk in all-sites fractures. Subjects without depression were found to have an increased risk of fractures. Diazepam is the only benzodiazepine with increased risk of fractures after adjusting for medications and comorbidities. Hip and spine were particular sites for increased fracture risk, but following adjustment for comorbidities, the associations were found to be insignificant. Conclusion Neither zolpidem nor benzodiazepine was associated with increased risk of all-site fractures in this case cross-over study after adjusting for medications or comorbidities in elderly individuals with insomnia. Clinicians should balance the benefits and risks for prescribing zolpidem or benzodiazepine in the elderly accordingly.
Learning to Collaborate from Delayed Rewards in Foraging Like Environments ∗

Machine learning techniques are usually used in coordination problems and in competitive games but not in collaborative ones. Collaboration and coordination are different, while in coordination the task can not be concluded by a unique agent, in collaboration it can be solved by one agent or by a team, but the use of several agents has to be re ected in the performance of the system. In this work, authors propose the use of in uence value reinforcement learning (IVRL) in collaborative problems and test it into a foraging game. In early work authors show experimentally that, in coordination problems, the IVRL paradigm performs better than the traditional paradigms (independent learning and joint action learning). Thus, in this paper, authors compare their new paradigm (IVRL) with the traditional ones in order to establish if reinforcement learning is well suited to be used in collaboration problems, and shows that the proposed paradigm performs better than the traditional ones.
Non-Shift Edge Based Ratio (NSER): An Image Quality Assessment Metric Based on Early Vision Features

How to evaluate the image perceptual quality is a fundamental problem in image and video processing, and various methods have been proposed for image quality assessment (IQA). This letter presents a novel IQA metric, which is based on the image primitive features produced in the earliest processing stage of human visual system. The procedures involved in the proposed method include computing the response of classical receptive fields, zero-crossing detection, and non-shift edge based ratio (NSER) calculation. The proposed IQA metric is very simple but very effective. The experimental results on benchmark databases show that the NSER index has very high consistency with the psychological evaluation, performing much better than most state-of-the-art IQA metrics.
Harmonicity based blind dereverberation with time warping

Speech dereverberation is desirable in applications such as robust automatic speech recognition (ASR) in the real world. Although a number of dereverberation methods have been exploited, dereverberation is still a challenging problem especially when using a single microphone. To overcome this problem, a harmonicity based dereverberation method (HERB) has recently been proposed. HERB can blindly estimate the inverse filter of a room impulse response based on harmonicity of speech signals and dereverberate the signals. However, HERB uses an imprecise assumption that hinders the dereverberation performance, that is, the fundamental frequency ( ) of a speech signal is assumed to be constant within a short time frame when extracting the features of harmonic components. In this paper, we introduce time warping analysis into HERB to remove this bottleneck. Time warping analysis expands and contracts the time axis of a signal in order to make the of the signal constant, and makes it possible to estimate harmonic components precisely even when their frequencies change rapidly. We show that time warping analysis can effectively improve the dereverberation effect of HERB when the reverberation time is longer than 0.1 sec.
Relation Alignment for Textual Entailment Recognition

We present an approach to textual entailment recognition, in which inference is based on a shallow semantic representation of relations (predicates and their arguments) in the text and hypothesis of the entailment pair, and in which specialized knowledge is encapsulated in modular components with very simple interfaces. We propose an architecture designed to integrate different, unscaled Natural Language Processing resources, and demonstrate an alignment-based method for combining them. We clarify the purpose of alignment in the RTE task, identifying two distinct alignment models, each of which leads to a different type of entailment system. We identify desirable properties of alignment, and use this to inform our implementation of an alignment component. We evaluate the resulting system on the RTE5 data set, and use an ablation study to assess the conformance of our alignment approach with these desired characteristics.
Periischemic Cerebral Blood Flow (CBF) Does Not Explain Beneficial Effects of Isoflurane on Outcome from Near-complete Forebrain Ischemia in Rats

BackgroundIsoflurane improves outcome from near-complete forebrain ischemia in rats compared with fentanyl–nitrous oxide (N2O). Sympathetic ganglionic blockade with trimethaphan abolishes this beneficial effect. To evaluate whether anesthesia-related differences in cerebral blood flow (CBF) may explain these findings, this study compared regional CBF before, during, and after near-complete forebrain ischemia in rats anesthetized with either isoflurane (with and without trimethaphan) or fentanyl–nitrous oxide. MethodsFasted, normothermic isoflurane anesthetized Sprague-Dawley rats were prepared for near-complete forebrain ischemia (10 min of bilateral carotid occlusion and mean arterial pressure = 30 mmHg). After surgery, rats were anesthetized with either 1.4% isoflurane (with or without 2.5 mg of trimethaphan intravenously at onset of ischemia) or fentanyl–nitrous oxide (25&mgr;g · kg−1 · h−1 · 70% N2O−1). Regional CBF was determined (14C-iodoantipyrine autoradiography) before ischemia, 8 min after onset of ischemia, and 30 min after onset of reperfusion. ResultsRegional CBF did not differ significantly among groups at any measurement interval. Ischemia caused a marked flow reduction to 5% or less of baseline (P < 0.001) in selectively vulnerable regions, such as the cortex, caudoputamen and hippocampus, whereas flow in the brain stem and cerebellum was preserved. Reperfusion at 30 min was associated with partial restoration of flow to 35–50% of baseline values in ischemic structures. ConclusionsThe results indicate that improved histologic–behavioral outcome provided by isoflurane anesthesia cannot be explained by differential vasodilative effects of the anesthetic states before, during, or after severe forebrain ischemia. This study also shows severe postischemic delayed hypoperfusion that was not affected by choice of anesthetic or the presence of trimethaphan. Mechanisms other than effects on periischemic CBF must be responsible for beneficial effects of isoflurane in this model.
Cover Sheet Individual and Population Differences in Focal Colors Contributor ( 1 )

Introduction Perhaps the central problem in understanding color appearance is that the only available measures are subjective. Much is now known about the neural mechanisms underlying the early encoding of color information in the human visual system, yet few clear links have been identified between these mechanisms and the perceptual organization of color experience. [For recent an objective test for " red " , studies of color appearance have instead had to rely on characterizing how observers describe the stimulus, and this has left open the debate of whether these descriptions reflect the characteristics of perceptual or linguistic processes. Arguments in this debate have hinged largely on the question of whether different individuals label spectral stimuli in similar or different ways. Comparisons of color naming across languages point to a remarkably consistent structure of color categories (Berlin & Kay, 1969; Kay & Regier, 2003). Though exceptions and counter-arguments have been noted by a & van Brakel, 1997), the observed similarities have been taken by many as strong evidence for universal tendencies in color experience that are shaped by Yet within-language studies of color naming, and in particular of the loci of perceptually pure or unique hues, have also shown that these can vary widely from one individual to another within a given population (Kuehni, 2004), and this suggests that something about the underlying processes is highly labile. In this chapter we examine the potential sources and nature of inter-individual and inter-language variability and what these mean for the notion of universal color categories. While individual differences have been taken by some as evidence for linguistic relativity (Saunders & van Brakel, 1997), we argue that they instead suggest that the vagaries of particular languages may often place only a weak constraint on color categories, and that the factors that underlie inter-language differences may themselves show strong universal tendencies. Berlin and Kay (1969) advanced a hypothesis of universals in cross-language color naming in a study that compared color naming across 20 languages. Naming was assessed by asking individuals to label the colors they saw in a palette of Munsell chips that varied in hue and lightness (Munsell Value) at a high saturation (Munsell Chroma; see Figure 1A). The chips chosen as the best examples of color terms by speakers of these languages were also Individual and Population Differences in Focal Colors 4 elicited; these clustered in small regions of the palette, leading …
Techniques for Identifying the Country Origin of Mailing List Participants

Developer mailing lists play a central role in facilitating communication in open source projects. Participants from different countries and across diverse time zones discuss and resolve important design decisions or conflicts. A good understanding of the social structure of these mailing lists helps in managing these projects and in shaping their implementation structure (i.e., design and architecture). In this paper, we present a technique to determine the country of a mailing list participant. A case study on the developer mailing list for two large open source projects (i.e., PostgreSQL and GTK+) shows that our technique outperforms prior technique.
Co-optimization of Streaming Multimedia QOS and Backlight Power Consumption for Mobile Handheld Devices

Mobile handheld devices have stringent constraints on power consumption because they run on batteries that have a limited lifetime. Conserving power to prolong battery life is of primary importance for these devices. Several factors such as backlight intensity, the hard disk, the CPU, the network interface and the nature of the application contribute significantly towards power consumption for a mobile device. While significant research effort has been made to optimize power consumption at the application, network and processor levels, comparatively little work has been done to reduce or adapt to the power consumed by the backlight. We propose an adaptive middleware based approach to optimize backlight power consumption for mobile handheld devices when playing streaming MPEG-1 video, without significantly compromising on video quality. Our performance results indicate that up to 60% of the power consumed by the backlight can be saved by using the proposed approach.