Miracle-dz/UniFAR-FTUs huggingface dataset:
Involvement of Interferon-γ in Microglial-Mediated Loss of Dopaminergic Neurons

Growing evidence implicates microglia in the loss of dopaminergic neurons in Parkinson's disease (PD). However, factors mediating microglial activation in PD are poorly understood. Proinflammatory cytokines, such as interferon-γ (IFN-γ), orchestrate the actions of microglia. We report here that PD patients express significantly elevated levels of IFN-γ in their blood plasma. After this initial finding, we found that IFN-γ-deficient mice displayed attenuated 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced substantia nigra pars compacta dopaminergic cell loss along with reduced loss of striatal tyrosine hydroxylase and dopamine transporter fiber density. MPTP-induced depletion of striatal dopamine and its metabolite DOPAC (3,4-dihydroxyphenylacetic acid), as well as ΔFosB, a marker of postsynaptic dysfunction, were also attenuated in these knock-out mice. Consistent with the role for IFN-γ in microglial activation, MPTP-induced morphological activation of microglia was abrogated compared with wild-type mice. To examine more mechanistically the role of IFN-γ in microglial activation, we evaluated the interactions between microglia and dopaminergic neurons in an in vitro mixed microglia/midbrain neuron rotenone-induced death paradigm. In this in vitro paradigm, dopaminergic neurons are selectively damaged by rotenone. Exogenous IFN-γ ligand alone and without rotenone resulted in dopaminergic cell loss, but only in the presence of microglia. The addition of an IFN-γ neutralizing antibody attenuated neuronal loss as a result of rotenone treatment. The presence of only wild-type microglia and not those deficient in IFN-γ receptor elicited significant dopaminergic cell loss when exposed to rotenone. Neurons deficient in IFN-γ receptor, however, did not display increased resistance to death. Finally, levels of IFN-γ message increased in microglia in response to rotenone. Together, these data suggest that IFN-γ participates in death of dopaminergic neurons by regulating microglial activity.
Activation of the IκB Kinase Complex and Nuclear Factor-κB Contributes to Mutant Huntingtin Neurotoxicity

Transcriptional dysregulation by mutant huntingtin (Htt) protein has been implicated in the pathogenesis of Huntington's disease (HD). We find that cultured cells expressing mutant Htt and striatal cells from HD transgenic mice have elevated nuclear factor-κB (NF-κB) activity. Furthermore, NF-κB is concentrated in the nucleus of neurons in the brains of HD transgenic mice. In inducible PC12 cells and in HD transgenic mice, mutant Htt activates the IκB kinase complex (IKK), a key regulator of NF-κB. Activation of IKK is likely mediated by direct interaction with mutant Htt, because the expanded polyglutamine stretch and adjacent proline-rich motifs in mutant Htt interact with IKKγ, a regulatory subunit of IKK. Activation of IKK may also influence the toxicity of mutant Htt, because expression of IKKγ promotes aggregation and nuclear localization of mutant Htt exon-1. Moreover, in acute striatal slice cultures, inhibition of IKK activity with an N-terminally truncated form of IKKγ blocks mutant Htt-induced toxicity in medium-sized spiny neurons (MSNs). In addition, blocking degradation of NF-κB inhibitors with a dominant-negative ubiquitin ligase β-transducin repeat-containing protein also reduces the toxicity of mutant Htt in MSNs. Therefore, aberrant NF-κB activation may contribute to the neurodegeneration induced by mutant Htt.
Attention, Consciousness, and the Damaged Brain: Insights From Parietal Neglect and Extinction

Milner and Goodale's (1995) model of the primate cortical visual system has been justly influential in shaping recent empirical and theoretical work on the neural basis of conscious vision. In this commentary I examine the extent to which their model accounts for recent neuropsychological findings from patients with visual neglect and extinction, two profound disorders of visual consciousness that arise after unilateral brain damage. I begin by outlining two key claims from their model: first, that the characteristic loss of awareness for contralesional sensory inputs in neglect reflects disruption of ventral, object-recognition processes, rather than dorsal processes as has commonly been thought; and second, that extinction of the more contralesional of two concurrent stimulus events is primarily a disorder of orienting and action-related attention arising from damage to the dorsal, visuomotor stream. I then present recent findings that cast some doubt on these claims. Visual neglect arising from damage to the inferior parietal lobe can involve a significant visuomotor impairment, independent of any perceptual deficit. Moreover, visual extinction can be modulated by perceptual factors that are likely to call upon the ventral object-recognition stream. These findings suggest
Configuration Management Stories from the Distributed Software Development Trenches

Distributed projects are generally recognized as being more complex and adding a number of new challenges to project management. Configuration management (CM) can be considered the infrastructure of all types of project being they co-located or distributed and lack of CM or badly implemented CM will hurt any type of project. In this paper, we take a closer look at the role of CM in distributed projects -- where can standard CM techniques help, how can they be implemented, and what special challenges does distribution pose. We do that by looking at general and CM-specific challenges from literature on global software development and discuss those in the light of our experience as CM practitioners on different distributed industrial projects. Some challenges in distributed development can be solved or alleviated by CM techniques, for other challenges CM has to be implemented differently -- and some challenges are challenges to CM too.
STATISTICAL SOFTWARE PROPERTIES: DEFINITION, INFERENCE AND MONITORING

Software properties define how software systems should operate. Specifying correct properties, however, can be difficult and expensive as it requires deep knowledge of the system's expected behavior and the environment in which it operates. Automated analysis techniques to infer properties from code or code executions can mitigate that cost, but are still unable to go beyond state properties and the simplest patterns of temporal properties. This limitation renders properties that sacrifice fault detection power. To address this problem, we introduce a new type of software properties called statistical properties, which characterize significant statistical relationships among the values of variables across program states. We define an approach to infer these relationships automatically and support their monitoring while controlling the trade-offs between overhead and the precision and recall of the inferred properties. We perform several experiments to assess the approach in the context of distributed robotics applications. Our findings indicate that the inferred statistical properties can be use to generate precise and cost-effective models capable of detecting faults in software systems while keeping the number of false positives close to zero and previous knowledge of the software system design and behavior unnecessary. iii ACKNOWLEDGMENTS My sincerest thanks to all those who have participated in the completion of this thesis. I found support and encouragement from a large list of persons, which contributed in many different ways, and I am sorry it is not possible to list them all on just one page. To my family, friends and colleagues, thank you. It would not have been possible without you. I would like to specially thank the invaluable guidance of my advisor, Sebastian Elbaum. Any recognition to his support and dedication will fall short. I would also like to thank all the Computer Science faculty and staff, most specially those on my committee, Carrick Detweiler and Matthew Dwyer, for their feedback and suggestions. My deepest thanks to my father, mother, siblings and my beloved wife Ana, who makes me the happiest person every single day. I would also like to thank They made university felt like home.
An Artificial Market Analysis of Exchange Rate Dynamics

In this study, we propose an exchange market model with artificial adaptive agents (AGEDASI TOF) and conduct a computer simulation as a study on the artificial market. First, AGEDASI TOF is compared with a random walk model and a linear regression model in out-of-sample forecasts. The results indicate that AGEDASI TOF outperforms the other models over all forecast horizons. Next, we analyze an exchange rate bubble in the real world using AGEDASI TOF. From the results, we conclude that the bubble starts by support of fundamental factors, grows by bandwagon expectations, stops by coincidence of all agents’ expectations, and collapses by regressive expectations. This study shows that the artificial market approach is effective not only for qualitative analysis but also for quantitative analysis of economic systems in the real world.
Mild Induced Hypertension Improves Blood Flow and Oxygen Metabolism in Transient Focal Cerebral Ischemia

Background and Purpose— In focal ischemic cortex, cerebral blood flow autoregulation is impaired, and perfusion passively follows blood pressure variations. Although it is generally agreed that profound hypotension is harmful in acute stroke, the hemodynamic and metabolic impact of increased blood pressure on the ischemic core and penumbra are less well understood. We, therefore, tested whether pharmacologically induced hypertension improves cerebral blood flow and metabolism and tissue outcome in acute stroke using optical imaging with high spatiotemporal resolution. Methods— Cerebral blood flow, oxyhemoglobin, and cerebral metabolic rate of oxygen were measured noninvasively using simultaneous multispectral reflectance imaging and laser speckle flowmetry during distal middle cerebral artery occlusion in mice. Hypertension was induced by phenylephrine infusion starting 10 or 60 minutes after ischemia to raise blood pressure by 30% for the duration of ischemia; control groups received saline infusion. Results— Mild induced hypertension rapidly increased cerebral blood flow, oxyhemoglobin, and cerebral metabolic rate of oxygen in both the core and penumbra and prevented the expansion of cerebral blood flow deficit during 1 hour distal middle cerebral artery occlusion. Induced hypertension also diminished the deleterious effects of periinfarct depolarizations on cerebral blood flow, oxyhemoglobin, and cerebral metabolic rate of oxygen without altering their frequency. Consistent with this, mild induced hypertension reduced infarct volume by 48% without exacerbating tissue swelling when measured 2 days after 1 hour transient distal middle cerebral artery occlusion. Conclusions— Our data suggest that mild induced hypertension increases collateral cerebral blood flow and oxygenation and improves cerebral metabolic rate of oxygen in the core and penumbra, supporting its use as bridging therapy in acute ischemic stroke until arterial recanalization is achieved.
Discrete Fourier-Invariant Signals: Design and Application

In this paper, two methods for the design of discrete Fourier-invariant signals are proposed. The direct design method provides splitting between independent and dependent signal parts and calculation of the dependent part for any given independent part. The iterative design method generates a family of discrete Fourier-invariant signals by a successive approach. Further we show how the proposed direct design method can be combined with the Gabor uncertainty principle to generate discrete Fourier-invariant signals with the minimum product of their bandwidth (B) and their time-width (T). We show that these signals as well as signal families generated with the iterative design method achieve the theoretical lower BT bound. Also, it is shown that the BT product of discrete Hermite-Gauss signals converges to the theoretical lower bound. Finally, possible applications are illustrated in the case of time-frequency spectral analysis using the obtained discrete Fourier-invariant signals as the window that provides isoresolution.
JANUS 93: towards spontaneous speech translation

We present first results from our efforts toward translation of spontaneously spoken speech. Improvements include increasing coverage, robustness, generality and speed of JANUS, the speech-to-speech translation system of Carnegie Mellon and Karlsruhe University. The recognition and machine translation engine have been upgraded to deal with requirements introduced by spontaneous human to human dialogs. To allow for development and evaluation of our system on adequate data, a large database with spontaneous scheduling dialogs is being gathered for English, German and Spanish. <<ETX>>
Towards finding optimal features of perceived prominence.

In this paper we present acoustical as well as lexical features for classification purposes of perceived prominence in read aloud Dutch sentences. Via a perception experiment with 10 naive listeners we derived prominence labels at the word level for 500 sentences. Part of these sentences are used for lexical/syntactical analyses. It turns out that most of the function words are never perceived as prominent, and that specific content words namely adverbs, nouns and adjectives are almost always perceived with some degree of prominence, whereas verbs form a middle class. So we decided to concentrate on the lexically stressed syllables of content words, because these are the words whose prominence is not uniquely classified by their lexical class. In this paper we use F0 range per syllable, both ‘raw’ and corrected for the declination line, to distinguish between the most prominent and non-prominent content words, although intensity and duration features can be used as additional features to improve the classification. As an initial result we can conclude that F0 range is a very good feature to distinguish between prominent and non-prominent content words.
Notes on the Concept of the Social Unconscious in Group Analysis

Abstract:The concept of the social unconscious and the theory in which it is embedded have a long history, drawing on sociology and psychoanalysis. Although the words social unconscious have been used in various ways to emphasise aspects of the unconscious restraints and constraints of socio-cultural-political arrangements of which people are unconscious, including the arrangements themselves, the actual concept and theory form the cornerstone of contemporary group analysis, as founded by S. H. Foulkes, which has been called the tripartite matrix, involving several realms and dimensions of social psychological reality. These ideas have important clinical, ethical, and political implications.
GROUP DECISION SUPPORT SYSTEM BASED ON ENHANCED AHP FOR TENDER EVALUATION

Application of model base in group decision making that makes up a Group Decision Support System (GDSS) is of paramount importance. Analytic Hierarchy Process (AHP) is the multi-criteria decision making (MCDM) that has been applied in GDSS. In order to be effectively used in GDSS, AHP needs to be customized so that it is more user friendly with ease of used features. In this paper, we propose an enhanced AHP model for GDSS tendering. The enhanced AHP method used is the Guided Ranked AHP (GRAHP). It is a technique where decision matrix tables are automatically filled in based on ranked data. However, the generated values in the decision matrix tables can still be altered by following the guidelines which in turn serve the purpose of improving the consistency of the decision matrix table. This process is transparent to Decision Makers because the degree of data inconsistency is visible. A prototype system based on tendering process has been developed to test the GRAHP model in terms of its applicability and robustness.
Low Complexity Soft Decision Decoding Algorithms for Reed-Solomon Codes

We propose a method to represent non-binary error patterns for Reed-Solomon codes using a trellis. All error patterns are sorted according to their Euclidean distances from the received vector. The decoder searches through the trellis until it finds a codeword. This results in a soft-decision maximum likelihood algorithm with lower complexity compared to other known MLD methods. The proposed MLD algorithm is subsequently modified to further simplify complexity, reflecting in a slight reduction in the error performance. key words: Reed-Solomon code, soft decision decoding
Architectures for Realistic Volume Imaging

In this work, we propose architectures that enable increased realism in volume rendering. The real world is a complex environment with complex illumination. We feel that a volumetric representation is ideal for many applications and that compelling realism is possible using advanced rendering algorithms. This work attacks the problem of increasing realism on several fronts. We present algorithms for managing complexity in volumetric rendering algorithms. We present methods for modeling complexity in a volumetric scene. And finally, we present hardware architectures to support these modeling and rendering algorithms. First, we describe our efforts to increase the realism of volume rendering on general-purpose graphics hardware. We propose new algorithms for volumetric global illumination using bi-directional importance methods and novel depth-first, progressive illumination transport. We propose a hardware design capable of simulating general optical transport through volumes enabling direct perspective volume rendering with single scattering, volumetric global illumination, and both parallel and cone-beam tomographic reconstruction. Finally, we give other methods to increase the realism in a volumetric scene through improved modeling. The first improvement is a fast algorithm for accurate, multi-valued voxelization of geometric surf aces. This algorithm is suitable for hardware implementation, and such a design is given. The second improvement is a dynamic scenegraph structure useful for specifying dynamic volumetric scenes of multiple volumes that incorporate the methods described in this work with accurate.
Spring 5-17-2010 ISOLATED HYPERSURFACE SINGULARITIES AS NONCOMMUTATIVE SPACES

ISOLATED HYPERSURFACE SINGULARITIES AS NONCOMMUTATIVE SPACES Tobias Dyckerhoff Tony Pantev, Advisor We study the category of matrix factorizations associated to the germ of an isolated hypersurface singularity. This category is shown to admit a compact generator which is given by the stabilization of the residue field. We deduce a quasiequivalence between the category of matrix factorizations and the dg derived category of an explicitly computable dg algebra. Building on this result, we employ a variant of Toën’s derived Morita theory to identify continuous functors between matrix factorization categories as integral transforms. This enables us to calculate the Hochschild chain and cochain complexes of these categories. Finally, we give interpretations of the results of this thesis in terms of noncommutative geometry based on dg categories.
A Novel Hierarchical Overlay for Structured Peer-to-Peer Network

Large-scale P2P systems typically have hundreds of thousands of peers that involve frequent dynamic activities. Empirical studies have shown that participating nodes in P2P systems are not equivalent. Such heterogeneity has been taken into account in the design of P2P systems. In this paper, to achieve better scalability and improve the routing performance of REIK, we design a novel hierarchical REIK overlay network by exploiting super peers, HiREIK. REIK is an inverse Kautz based overlay network with Byzantine fault tolerance. In HiREIK, the peers are organized into clusters, and the clusters themselves are organized in a top-level overlay network. The results show that the hierarchical design can significantly reduce the expected number of hops in REIK system. We also propose a scalable design for managing the clusters and the super-peers.
Designing Adaptive Deception Strategies

Deception-based defense is the process by which actions are intentionally employed to cause misrepresentation and induce erroneous inferences on attackers. Deception can be employed in different levels of computation, from network to application-level, which demands careful planning and coordination between multiple strategies and tactics. Despite of advances on using deception in computer defenses, ad-hoc approaches are still used for their design. As a result, deception is realized essentially as single tools or as entire solutions repackaged as honeypot machines. In this paper, we propose a model to specify coordinated deception tactics based on adaptive architectures. Our contributions rely on a deception-based defense life-cycle approach integrated in a software design process, including a model to specify coordinated deception strategies. The feasibility of the proposed approach is shown via an example where a deception strategy is designed for a smartphone application that synchronizes data with a central database.
Iterative Distributed Amplitude Optimization for Distributed Detection in Wireless Sensor Networks

In this paper, an iterative distributed approach is studied for the signal amplitude optimization when the distributed detection is carried out with a symmetric signaling constraint in a wireless sensor network (WSN) consisting of a fusion center (FC) and multiple sensors. In the conventional distributed detection, if sensors'' characteristics change due to aging problems or varying operating conditions, they have to be available at the FC for a best combining result. On the other hand, in the proposed approach, each sensor can adjust its signal amplitude using a type-based multiple access (TBMA) technique to provide a best performance at the FC through an iterative approach without sending their individual characteristics.
Primary teachers’ experiences with weekly education outside the classroom during a year

ABSTRACT The aim of the present study was through semi-structured interviews to explore udeskole teacher’s perceptions of motivational factors and challenges while teaching regularly outside the classroom on a weekly basis during a year. Six females and two male udeskole teachers participated and answered an interview guide containing five themes about their motivations, student relations, teaching experiences, challenges and recognition. Udeskole was perceived to have substantial potentials to improve both academic learning and life skills and ‘the common third’, i.e. teacher–pupil relations, was mentioned as a value added to the indoor teaching. Health and safety issues were not perceived as barriers.