Miracle-dz/UniFAR-FTUs huggingface dataset:
Fas and Fas‐L expression in Huntington's disease and Parkinson's disease

The Fas/Fas‐L signalling system plays a role in the control of cell death and the survival of lymphocytes, in the regulation of the immune system, and in the progression of autoimmune diseases. Studies in the nervous system have shown Fas/Fas‐L activation in multiple sclerosis and in various paradigms leading to neuronal death. Enhanced Fas and Fas‐L expression has also been documented in astrocytomas and glioma cell lines. However, little is known about the possible implication of Fas/Fas‐L signals in primary human neurodegenerative diseases. In an attempt to gain understanding of the mechanisms commanding cell death and neurone loss in Huntington's disease (HD) and Parkinson's disease (PD), Fas and Fas‐L expression has been examined in the brains of patients with HD and PD with Western blotting and immunohistochemistry. Fas and Fas‐L expression levels are reduced in the caudate and putamen, but not in the parietal cortex, in HD, as revealed in Western blots. Moreover, Fas and Fas‐L immunoreactivity is reduced in striatal neurones in HD. Fas and Fas‐L immunoreactivity is also decreased in neurones of the substantia nigra pars compacta in PD. Reduced Fas and Fas‐L expression is observed equally in Lewy body‐bearing and non‐Lewy body‐bearing neurones. Yet increased Fas and Fas‐L immunoreactivity occurs in normal astrocytes in control brains and in reactive astrocytes in diseased brains. The meaning of increased Fas and Fas‐L expression in astrocytes is still unclear. However, the present results suggest that Fas/Fas‐L signals are minimized in sensitive neurones in HD and PD.
Role theory in international relations : approaches and analyses

Section I. Role Theory in IR and social theory 1. Introduction and defining of key terms of analysis Sebastian Harnisch 2. Role Theory research in IR. State of the art and blind spots Marijke Breuning 3. George Herbert Mead, the pragmatist tradition and role theory Sebastian Harnisch 4. Habermas meets role theory - communicative action as role playing Harald Muller 5. Identity and role change in international politics Dirk Nabers Section II. Comparative Foreign Policy Analysis. Combining Role theory with complementary approaches 6. Role transformation of NATO and its new members. socialization as a two way street? Trine Flockhart 7. Reconsidering the EU's role in international relations - do role performances fit to role conceptions? Ole Elgstrom & Rikard Bengtsson 8. Civilian power meets transforming Euroatlanticist. Comparing Germany's and Poland's European Security and Defence Policies Cornelia Frank 9. Does membership in EU and NATO matter? Convergence of Sweden's and Norway's role concepts by interaction with International institutions Rachel Folz Section III. On Hegemony and Hierarchy in IR. Foreign policy roles in the United States and allied countries 10. Agency and role change. the Obama factor in the reconstitution of US hegemony Hanns W. Maull 11. Terrorized America? September 11 and its impact on US foreign policy Raimund Wolf 12. With or without consensus? US hegemony and France as a reluctant ally Ulrich Krotz & James Sperling 13. With or without consensus? US hegemony and China's role as a rival but responsible power Jorn-Carsten Gottwald Section IV. Conclusions 14. Hegemony and consent. the current state of role theory and the international social order Sebastian Harnisch, Cornelia Frank, Hanns W. Maull
Oxidative stress‐triggered unfolded protein response is upstream of intrinsic cell death evoked by parkinsonian mimetics

Oxidative stress is a key player in a variety of neurodegenerative disorders including Parkinson's disease. Widely used as a parkinsonian mimetic, 6‐hydroxydopamine (6‐OHDA) generates reactive oxygen species (ROS) as well as coordinated changes in gene transcription associated with the unfolded protein response (UPR) and apoptosis. Whether 6‐OHDA‐induced UPR activation is dependent on ROS has not yet been determined. The present study used molecular indicators of oxidative stress to place 6‐OHDA‐generated ROS upstream of the appearance of UPR markers such as activating transcription factor 3 (ATF3) and phosphorylated stress‐activated protein kinase (SAPK/JNK) signaling molecules. Antioxidants completely blocked 6‐OHDA‐mediated UPR activation and rescued cells from toxicity. Moreover, cytochrome c release from mitochondria was observed after the appearance of early UPR markers, suggesting that cellular stress pathways are responsible for its release. Mechanistically, the 6‐OHDA‐induced UPR was independent of intracellular calcium changes. Rather, evidence of protein oxidation was observed before the expression of UPR markers, suggesting that the rapid accumulation of damaged proteins triggered cell stress/UPR. Taken together, 6‐OHDA‐mediated cell death in dopaminergic cells proceeds via ROS‐dependent UPR up‐regulation which leads to an interaction with the intrinsic mitochondrial pathway and downstream caspase activation.
A Multi-sensory Gesture-Based Login Environment

Logging on to a system using a conventional keyboard may not be feasible in certain environments, such as, in a surgical operation theatre or in an industrial manufacturing facility. We have developed a multi-sensory gesture based login system that allows a user to access secure information using body gestures. The system can be configured to use different types of gestures according to the type of sensors available to the user. We have proposed a simple scheme to represent all alphanumeric characters required for password entry as gestures within the multi-sensory environment. Our scheme is scalable enough to support sensors that detect a large number of gestures to those that can only accept a few. This allows the system to be used in a variety of situations such as usage by disabled persons with limited ability to perform gestures. We are in the midst of deploying our developed system in a clinical environment.
Effect of artificial acid rain and SO2 on characteristics of delayed light emission.

The structure and function of chloroplast in plant leaves can be affected by acid rain and air pollution. The photosystem II in a plant is considered the primary site where light-induced delayed light emission (DLE) is produced. With the lamina of zijinghua (Bauhinia variegata L.) and soybean (Glycine max (L.) Merr. ) as testing models, we studied the effects of artificial acid rain and SO2 on characteristics of DLE by using a home-made weak luminescence detection system. The results show that the changes in DLE intensity of green plants can reflect the changes in chloroplast intactness and function. With proper calibration, DLE may provide an alternative means of evaluating environmental acid stress on plants. The changes in DLE intensity may provide a new approach for the detection of environmental pollution and its impact on the ecosystem.
Shift-invariant, DWT-based "projection" method for estimation of ultrasound pulse power spectrum

An approach to computing estimates of the ultrasound pulse spectrum from echo-ultrasound RF sequences measured from biological tissues, is proposed. It is computed by a "projection" algorithm based on the Discrete Wavelet Transform (DWT) using averaging over a range of linear shifts. It is shown that the robust, shift invariant estimate of the ultrasound pulse power spectrum can be obtained by the projection of RF line log spectrum on an appropriately chosen subspace of L/sup 2/(R) (i.e., the space of square-integrable functions) that is spanned by a redundant collection of compactly supported, scaling functions. This redundant set is formed from the traditional (in Wavelet analysis) orthogonal set of scaling functions and also by all its linear (discrete) shifts. A proof is given that the estimate, so obtained, could be viewed as the average of the orthogonal projections of the RF line log spectrum, computed for all significant linear shifts of the RIP line log spectrum in frequency domain. It implies that the estimate is shift-invariant. A computationally efficient scheme is presented for calculating the estimate. Proof is given that the averaged, shift-invariant estimate can be obtained simply by a convolution with a kernel, which can be viewed as the discretized auto-correlation function of the scaling function, appropriate to the particular subspace being considered. It implies that the computational burden is at most O(n log/sub 2/ n), where n is the problem size, making the estimate quite suitable for real-time processing. Because of the property of the wavelet transform to suppress polynomials of orders lower than the number of the vanishing moments of the wavelet used, the presented approach can be considered as a local polynomial fitting. This locality plays a crucial role in the performance of the algorithm, improving the robustness of the estimation. Moreover, it is shown that the "averaging" nature of the proposed estimation allows using (relatively) poorly regular wavelets (i.e., short filters), without affecting the estimation quality. The latter is of importance whenever the number of calculations is crucial.
Unsupervised Discriminative Induction of Synchronous Grammar for Machine Translation

We present a global log-linear model for synchronous grammar induction, which is capable of incorporating arbitrary features. The parameters in the model are trained in an unsuper- vised fashion from parallel sentences without word alignments. To make parameter training tractable, we also propose a novel and efficient cube pruning based synchronous parsing algo- rithm. Using learned synchronous grammar rules with millions of features that contain rule level, word level and translation boundary information, we significantly outperform a compet- itive hierarchical phrased-based baseline system by +1.4 BLEU on average on three NIST test
A R EVIEW ON : D YNAMIC L INK B ASED R ANKING

Dynamic authority-based ranking methods such as personalized PageRank and ObjectRank. Since they dynamically rank nodes in a data graph using an expensive matrix-multiplication method, the online execution time rapidly increases as the size of data graph grows. ObjectRank spends 20-40 seconds to compute query-specific relevance scores, which is unacceptable. We introduce a novel approach, BinRank, that approximates dynamic link-based ranking scores efficiently. BinRank partitions a dictionary into bins of relevant keywords and then constructs materialized subgraphs (MSGs) per bin in preprocessing stage. In query time, to produce highly accurate top-K results efficiently, BinRank uses the MSG corresponding to the given keyword, instead of the original data graph. In this project, a BinRank system that employs a hybrid approach where query time can be traded off for preprocessing time and storage. BinRank closely approximates ObjectRank scores by running the same ObjectRank algorithm on a small subgraph, instead of the full data graph.
Design for recurrent fuzzy neural networks using MSC-MFS and PSO-MBP

A novel hybrid learning algorithm for designing a TSK-type recurrent fuzzy neural network (RFNN) is proposed in this paper. The whole designing process includes two stages, i.e., structure identification and parameter optimization. The structure identification includes mean shift clustering (MSC) and mean firing strength (MFS). The MSC is used to partition the input space and the mean firing strength (MFS) is employed to prune the redundant rule neurons. After the structure identification is performed, we adopt the PSO to adjust the free parameters of the RFNN and generate the near-optimal free parameters solution. Then, MBP is used to continue the learning process until the terminal condition is satisfied. The proposed hybrid learning algorithm achieves superior performance in learning accuracy.
Attentional control mediates the relationship between social anhedonia and social impairment

Social anhedonia (SA), a trait-like disinterest in social contact and diminished capacity to experience pleasure from social interactions, is consistently associated with social impairments in both healthy and clinical populations. However, the mechanisms underlying the relationship between SA and social impairment are poorly understood. Attentional control, selecting and focusing on relevant information and inhibiting irrelevant, may be one such mechanism. We examined individual differences in SA, attentional control, and social impairment in 108 healthy adults. High SA related to low attentional control and high social impairment. Moreover, attentional control mediated the relationship between SA and social impairment, establishing attentional control as one mechanism underlying aberrations in the fundamental human need for social contact. Although both attentional deficits and social impairment have been separately noted in SA, the relationship between SA, attentional control and social impairment in this non-clinical sample reflects a novel contribution.
Role of ADAM17 in invasion and migration of CD133-expressing liver cancer stem cells after irradiation

We investigated the biological role of CD133-expressing liver cancer stem cells (CSCs) enriched after irradiation of Huh7 cells in cell invasion and migration. We also explored whether a disintegrin and metalloproteinase-17 (ADAM17) influences the metastatic potential of CSC-enriched hepatocellular carcinoma (HCC) cells after irradiation. A CD133-expressing Huh7 cell subpopulation showed greater resistance to sublethal irradiation and specifically enhanced cell invasion and migration capabilities. We also demonstrated that the radiation-induced MMP-2 and MMP-9 enzyme activities as well as the secretion of vascular endothelial growth factor were increased more predominantly in Huh7CD133+ cell subpopulations than Huh7CD133− cell subpopulations. Furthermore, we showed that silencing ADAM17 significantly inhibited the migration and invasiveness of enriched Huh7CD133+ cells after irradiation; moreover, Notch signaling was significantly reduced in irradiated CD133-expressing liver CSCs following stable knockdown of the ADAM17 gene. In conclusion, our findings indicate that CD133-expressing liver CSCs have considerable metastatic capabilities after irradiation of HCC cells, and their metastatic capabilities might be maintained by ADAM17. Therefore, suppression of ADAM17 shows promise for improving the efficiency of current radiotherapies and reducing the metastatic potential of liver CSCs during HCC treatment.
The Graph Signature: A Scalable Query Optimization Index for RDF Graph Databases Using Bisimulation and Trace Equivalence Summarization

Querying large data graphs has brought the attention of the research community. Many solutions were proposed, such as Oracle Semantic Technologies, Virtuoso, RDF3X, and C-Store, among others. Although such approaches have shown good performance in queries with medium complexity, they perform poorly when the complexity of the queries increases. In this paper, the authors propose the Graph Signature Index, a novel and scalable approach to index and query large data graphs. The idea is that they summarize a graph and instead of executing the query on the original graph, they execute it on the summaries. The authors' experiments with Yago 16M triples have shown that e.g., a query with 4 levels costs 62 sec using Oracle but it only costs about 0.6 sec with their index. Their index can be implemented on top of any Graph database, but they chose to implement it as an extension to Oracle on top of the SEM_MATCH table function. The paper also introduces disk-based versions of the Trace Equivalence and Bisimilarity algorithms to summarize data graphs, and discusses their complexity and usability for RDF graphs.
AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract)

Algorithm selection (AS) techniques – which involve choosing from a set of algorithms the one expected to solve a given problem instance most efficiently – have substantially improved the state of the art in solving many prominent AI problems, such as SAT, CSP, ASP, MAXSAT and QBF. Although several AS procedures have been introduced, not too surprisingly, none of them dominates all others across all AS scenarios. Furthermore, these procedures have parameters whose optimal values vary across AS scenarios. In this extended abstract of our 2015 JAIR article of the same title, we summarize AUTOFOLIO, which uses an algorithm configuration procedure to automatically select an AS approach and optimize its parameters for a given AS scenario. AUTOFOLIO allows researchers and practitioners across a broad range of applications to exploit the combined power of many different AS methods and to automatically construct high-performance algorithm selectors. We demonstrate that AUTOFOLIO was able to produce new state-of-the-art algorithm selectors for 7 well-studied AS scenarios and matches state-ofthe-art performance statistically on all other scenarios. Compared to the best single algorithm for each AS scenario, AUTOFOLIO achieved average speedup factors between 1.3 and 15.4.
Boundary feedback stabilization of the two dimensional Navier-Stokes equations with finite dimensional controllers

We study the boundary stabilization of the two-dimensional Navier-Stokes equations about an unstable stationary solution by controls of finite dimension in feedback form. The main novelty is that the linear feedback control law is determined by solving an optimal control problem of finite dimension. More precisely, we show that, to stabilize locally the Navier-Stokes equations, it is sufficient to look for a boundary feedback control of finite dimension, able to stabilize the projection of the linearized equation onto the unstable subspace of the linearized Navier-Stokes operator. The feedback operator is obtained by solving an algebraic Riccati equation in a space of finite dimension, that is to say a matrix Riccati equation.
Reciprocal Interactions of the SMA and Cingulate Cortex Sustain Premovement Activity for Voluntary Actions

Voluntary action is one of the core functions of the human brain, and is accompanied by the well known readiness potential or Bereitschaftspotential. A network of cortical areas is responsible for the motor preparation process, including the anterior mid-cingulate cortex (aMCC) and the SMA. However, the relationship between activity in these regions during movement preparation and the readiness potential is poorly understood. We examined this relationship by integrating simultaneously acquired EEG and fMRI through computational modeling. We first observed that global field power of premovement neural activity showed a specific correlation with BOLD responses in the aMCC. We then used dynamic causal modeling to infer premovement interactions between these regions and their relationship to the premovement neural activity underlying the readiness potential. These analyses suggest that SMA and aMCC have strong reciprocal connections that act to sustain each other's activity, and that this interaction is mediated during movement preparation according to the readiness potential amplitude, as reflected in global cortical field power. Our study suggests that the reciprocal connections between SMA and aMCC are important to maintain the sustained activity of the readiness potential before movement and lead to a weak system instability at movement onset. We suggest that the effective connectivity of this network underlies its functional role in the preparation of self-generated actions.
Real-Time Data Acquisition for Long-Distance Reflective Ghost Imaging Experiment

We present a real-time data acquisition (DAQ) system for the long-distance reflective ghost imaging experiment which has broad application prospects in remote sensing. In the experimental setup, the light from a pseudo thermal light source is separated into signal beam and reference beam. The signal beam illuminates the target, and then the reflected light is collected by a bucket detector. In the mean time, the reference beam is directly captured by an area detector. In order to obtain the target image, the experiment requires high-speed and high-precision correlated data acquisition to collect the light intensity fluctuation in the signal beam and the reference beam. Furthermore, to reduce imaging time, real-time data acquisition is also required. The DAQ system consists of a photon-multiplier tube (PMT), a charge-coupled device (CCD) camera, a DAQ module and DAQ software. The CCD camera as the area detector connects to computer via Gigabit Ethernet. The PMT and a telescope compose the bucket detector which outputs signals to the DAQ module. The DAQ module sends acquired data to computer through universal serial bus (USB). The DAQ software collects the data and reconstructs the target image. The results of electronic tests and experiments show that the DAQ system satisfies the requirements of the experiment.
Demographic and Socioeconomic Determinants of Self-Efficacy: An Empirical Study of Korean Older Adults

This study conceptualizes the dimensions of older adults' self-efficacy and identifies its determinants by using panel data collected by the National Pension Research Institute in Korea. The analysis supported the conceptualization of older people's self-efficacy as a multidimensional construct and found strong support for the three subscales. For older adults in Korea, general self-efficacy was condensed into a sense of competence. Older adults' social self-efficacy was delineated into two subscales: inward social self-efficacy and interactive social self-efficacy. Inward social self-efficacy could be characterized as a set of inward-looking social capabilities, whereas interactive self-efficacy could be considered as a set of relation-oriented capabilities with various groups of individuals. Of the three regression models representing dimensions of older people's self-efficacy, each model uncovered its own set of variables that played a decisive role in perceived self-efficacy. Demographic variables were more effective determinants of older adults' self-efficacy than socioeconomic factors.
Human identity verification based on Mel frequency analysis of digital heart sounds

This paper presents new results in human identity verification via frequency analysis of cardiac sounds. More specifically, the paper proposes a pattern recognition approach based on a feature set of 13 Mel Frequency Cepstral Coefficients (MFCCs) extracted from the first (S1) and second (S2) heart sounds and a metric based on the power ratio of S1 to S2. The new algorithm yields significantly better performances with respect to the previous method based on the Chirp z-transform, guaranteeing an equal error rate (EER) below 9 %.