Miracle-dz/UniFAR-FTUs huggingface dataset:
Iris Recognition System Using Combined Colour Statistics

This paper proposes a high performance iris recognition system based on the probability distribution functions (PDF) of pixels in different colour channels. The PDFs of the segmented iris images are used as statistical feature vectors for the recognition of irises by minimizing the Kullback-Leibler distance (KLD) between the PDF of a given iris and the PDFs of irises in the training set. Feature vector fusion (FVF) and majority voting (MV) methods have been employed to combine feature vectors obtained from different colour channels in YCbCr and RGB colour spaces to improve the recognition performance. The system has been tested on the segmented iris images from the UPOL iris database. The proposed system gives a 98.44% recognition rate on that iris database.
Examining radical position and function in Chinese character recognition using the repetition blindness paradigm

ABSTRACT Repetition blindness (RB) is the failure to report the second occurrence of repeated items in a rapid serial visual presentation stream. The two-stage model of RB by Bavelier (1994) states that more properties shared between the repeated items lead to a larger RB effect. We used RB paradigm to examine the position (left or right) and the function (semantic or phonetic) of radicals in Chinese character recognition. Compared to the repeated radicals with the same position and function, RB was reduced when they were in different positions (Experiment 1A), but not when they had different functions (Experiment 1B). Similar RB-effect was observed when only one, or both, of the repeated radicals provided valid semantic or phonetic cues to characters (Experiments 2A and 2B). These results suggest that radicals are encoded with position but not function information. The radical function is likely implemented in lateral connections between semantic and phonological representations of characters.
Suicide in the 12 months after discharge from psychiatric inpatient care, Scotland 1968-92.

STUDY OBJECTIVE: To investigate the rate of suicide in the 12 months after discharge from psychiatric hospital and to determine its relationship to age, diagnosis, and period. DESIGN: Cohort study of patients discharged from psychiatric hospital. SETTING: Scotland. PARTICIPANTS: Altogether 159,742 men and 178,271 women, aged 15-84, who were discharged from Scottish psychiatric hospitals during 1968-92. MAIN RESULTS: During the 25 year period, 1212 male patients committed suicide in 198,059 person years at risk (612 per 100,000; 95% confidence interval (CI) 578,647) and 1099 female patients committed suicide in 228,993 person years at risk (480 per 100,000; 95% CI 452, 509). The overall standardised mortality ratio (general population rate = 1) was 27 (95% CI 26, 29) in men and 40 (95% CI 38, 43) in women. There were variations in the suicide rates in relation to age, diagnosis, and period. The ratio of the 1-28 day rate to the rate between days 29 and 365 over the whole study period was 1.7 (95% CI 1.4, 1.9) in men and 1.6 (95% CI 1.3, 1.8) in women. CONCLUSIONS: The variations in the post discharge suicide rate by age, sex, diagnosis, geographical location, and period suggest that there are several risk factors which vary in their distribution. Further study of these may lead to the development of effective interventions.
p6Gag is required for particle production from full-length human immunodeficiency virus type 1 molecular clones expressing protease

The human immunodeficiency virus type 1 (HIV-1) Gag protein precursor, Pr55Gag, contains at its C-terminal end a proline-rich, 6-kDa domain designated p6. Two functions have been proposed for p6: incorporation of the HIV-1 accessory protein Vpr into virus particles and virus particle production. To characterize the role of p6 in the HIV-1 life cycle and to map functional domains within p6, we introduced a number of nonsense and single and multiple amino acid substitution mutations into p6. Following the introduction of the mutations into the full-length HIV-1 molecular clone pNL4-3, the effects on Gag protein expression and processing, virus particle production, and virus infectivity were analyzed. The production of mutant virus particles was also examined by transmission electron microscopy. The results indicate that (i) p6 is required for efficient virus particle production from a full-length HIV-1 molecular clone; (ii) a Pro-Thr-Ala-Pro sequence, located between residues 7 and 10 of p6, is critical for virus particle production; (iii) mutations outside the Pro-Thr-Ala-Pro motif have little or no effect on virus assembly and release; (iv) the p6 defect is manifested at a late stage in the budding process; and (v) mutations in p6 that severely reduce virion production in HeLa cells also block or significantly delay the establishment of a productive infection in the CEM (12D-7) T-cell line. We further demonstrate that mutational inactivation of the viral protease reverses the p6 defect, suggesting a functional linkage between p6 and the proteolytic processing of the Gag precursor protein during the budding of progeny virions.
Targeting the CCL2-CCR2 signaling axis in cancer metastasis

The CCL2-CCR2 signaling axis has generated increasing interest in recent years due to its association with the progression of cancer. Although first described as a chemotactic molecule with physiological roles in regulating inflammation, recent studies have revealed a pro-tumorigenic function for CCL2 in favoring cancer development and subsequent metastasis. CCL2 binds the cognate receptor CCR2, and together this signaling pair has been shown to have multiple pro-tumorigenic roles, from mediating tumor growth and angiogenesis to recruiting and usurping host stromal cells to support tumor progression. The importance of CCL2-CCR2 signaling has been further championed by the establishment of clinical trials targeting this signaling pair in solid and metastatic cancers. Here we review the roles of CCL2-CCR2 signaling in the development and progression of cancer metastasis. We further evaluate the outcome of several clinical trials targeting either CCL2 or CCR2, and discuss the prospects and challenges of manipulating CCL2-CCR2 interaction as a potential approach for combating metastatic disease.
Exploring organisational learning in virtual forms of organisation

Reports on an ongoing research project into organisational learning in virtual organisations using the Organisational Learning Evaluation Cycle developed by J. Gasston and P. Halloran (1999). A review of the literature shows that considerable research has been done in the area of organisational learning; however, the concepts are mainly focused on traditional organisational forms and are difficult to apply to virtual organisations due to their unique characteristics. The characteristics relate to competitive relationships between organisational entities within the virtual organisation, the nature of which has an effect upon the level of organisational learning. This paper discusses factors that influence learning in the virtual organisation, including the type of alliance formed; the level of cooperation between organisations; the use of information and communication technologies; the ability to capture and codify tacit expert knowledge in constantly changing environments; the extent to which shared knowledge is applied; the level of individual contributions or the adoption of organisational memory; and the presence of a strong learning culture.
Typen des Individualismus, sozialer Wandel und Gewaltkriminalität

Empfohlene Zitierung / Suggested Citation: Birkel, C. (2006). Typen des Individualismus, sozialer Wandel und Gewaltkriminalität. In K. -S. Rehberg (Hrsg.), Soziale Ungleichheit, kulturelle Unterschiede: Verhandlungen des 32. Kongresses der Deutschen Gesellschaft für Soziologie in München. Teilbd. 1 und 2 (S. 3971-3989). Frankfurt am Main: Campus Verl. https://nbn-resolving.org/urn:nbn:de:0168ssoar-142375
The Role of Adherence in the Effects of a Mindfulness Intervention for Competitive Athletes: Changes in Mindfulness, Flow, Pessimism, and Anxiety

This study examined the role of degree of adherence in a mindfulness-based intervention on mindfulness, flow, sport anxiety, and sport-related pessimistic attributions in athletes. Twelve athletes participated in an 8-week mindfulness intervention which incorporated a mindfulness focus on movement training component. Participants completed baseline and posttest measures of mindfulness, flow, sport anxiety, and sport-related pessimistic attributions, and they filled out daily mindfulness-training logbooks documenting their frequency and duration of mindfulness practice. Participants were identified as either high adherence or low adherence with mindfulness-training based on a composite score of logbook practice records and workshop attendance. Athletes high in adherence, operationalized as following recommended practice of mindfulness exercises, showed significantly greater increases in mindfulness and aspects of flow, and significantly greater decreases in pessimism and anxiety than low adherence athletes.
Role of Salt-Inducible Kinase 1 in the Activation of MEF2-Dependent Transcription by BDNF

Substantial evidence supports a role for myocyte enhancer factor 2 (MEF2)-mediated transcription in neuronal survival, differentiation and synaptic function. In developing neurons, it has been shown that MEF2-dependent transcription is regulated by neurotrophins. Despite these observations, little is known about the cellular mechanisms by which neurotrophins activate MEF2 transcriptional activity. In this study, we examined the role of salt-inducible kinase 1 (SIK1), a member of the AMP-activated protein kinase (AMPK) family, in the regulation of MEF2-mediated transcription by the neurotrophin brain-derived neurotrophic factor (BDNF). We show that BDNF increases the expression of SIK1 in primary cultures of rat cortical neurons through the extracellular signal-regulated kinase 1/2 (ERK1/2)-signaling pathway. In addition to inducing SIK1 expression, BDNF triggers the phosphorylation of SIK1 at Thr182 and its translocation from the cytoplasm to the nucleus of cortical neurons. The effects of BDNF on the expression, phosphorylation and, translocation of SIK1 are followed by the phosphorylation and nuclear export of histone deacetylase 5 (HDAC5). Blockade of SIK activity with a low concentration of staurosporine abolished BDNF-induced phosphorylation and nuclear export of HDAC5 in cortical neurons. Importantly, stimulation of HDAC5 phosphorylation and nuclear export by BDNF is accompanied by the activation of MEF2-mediated transcription, an effect that is suppressed by staurosporine. Consistent with these data, BDNF induces the expression of the MEF2 target genes Arc and Nur77, in a staurosporine-sensitive manner. In further support of the role of SIK1 in the regulation of MEF2-dependent transcription by BDNF, we found that expression of wild-type SIK1 or S577A SIK1, a mutated form of SIK1 which is retained in the nucleus of transfected cells, is sufficient to enhance MEF2 transcriptional activity in cortical neurons. Together, these data identify a previously unrecognized mechanism by which SIK1 mediates the activation of MEF2-dependent transcription by BDNF.
A real-world achievement system

We propose a system for the acquisition, maintenance, and communication of Real-World Achievements. The concept is based on online entertainment systems like Microsoft's XBox Live or virtual worlds like World of Warcraft. The system design is centered around a global database of achievement definitions and individual progress. Focus is put on flexibility to track achievement-related actions and instantaneous notification of obtained achievements. We have tested our system at a major international conference, and conclude that our approach is suitable for implementing a Real World Achievement System.
Microstrip Patch Antenna for GPS Application

The study and the design of rectangular microstrip patch antenna for multiband applications are presented in this paper. They can be simulated on antenna design software’s such as High Frequency Simulation Software (HFSS), Advanced Design System Momentum (ADS) and Agilent Vector Network Analyzer (E8361A) where different feeding techniques have been deployed to get the desired results. Two rectangular microstrip patch antennas of frequencies 1.5 GHz and 2.4 GHz are designed and simulated on HFSS.
Time-Multiplexed Compressed Test of SOC Designs

In this paper we observe that the necessary amount of compressed test data transferred from the tester to the embedded cores in a system-on-a-chip (SOC) varies significantly during the testing process. This motivates a novel approach to compressed system-on-a-chip testing based on time-multiplexing the tester channels. It is shown how the introduction of a few control channels will enable the sharing of data channels, on which compressed seeds are passed to every embedded core. Through the use of modular and scalable hardware for on-chip test control and test data decompression, we define a new algorithmic framework for test data compression that is applicable to system-on-a-chip devices comprising intellectual property-protected blocks.
A Botnet Detection System Based on Neural Networks

A concerted fight against botnets is needed in order to avoid them from becoming a serious threat to global security in the forthcoming years. Zombie detection is currently performed at the host and/or network levels, but these options have important drawbacks: antivirus, firewalls and anti-spyware are not effective against this threat because they are not able to detect hosts that are compromised via new or target specific malicious software and were not designed to protect the network from external attacks or vulnerabilities that are already present inside the local area network. To overcome these limitations, we propose a new botnet detection approach based on the identification of traffic patterns: since each network application, whether it is licit or illicit, has a characteristic traffic pattern that can uniquely identify it, the detection framework will rely on an Artificial Neural Network to identify the licit and illicit patterns. After the identification phase, the system will generate alarms to the system administrator, that can trigger the most appropriate security actions, like blocking the corresponding IP addresses, putting them under a deeper surveillance or acting over some suspicious network segment. A general detection framework was developed in order to incorporate the detection methodology itself, as well as the data collection and storage modules and all the necessary management functions. Some performance tests were already carried out on the proposed system and the results obtained show that the system is stable and fast and the detection approach is efficient, since it provides high detection rates with low computational overhead.
Theory of mind after mild TBI in preschool children : a longitudinal perspective

ly-represented experiences, independent of modality in which the information was acquired. Gender differences have been studied extensively in relation to discrepancies in performance on ToM tasks. Behavioural studies have provided evidence that women perform better on ToM tasks than do men, regardless of age, and these gender differences are apparent even in
MMPTCP: A multipath transport protocol for data centers

Modern data centres provide large aggregate network capacity and multiple paths among servers. Traffic is very diverse; most of the data is produced by long, bandwidth hungry flows but the large majority of flows, which commonly come with strict deadlines regarding their completion time, are short. It has been shown that TCP is not efficient for any of these types of traffic in modern data centres. More recent protocols such MultiPath TCP (MPTCP) are very efficient for long flows, but are ill-suited for short flows. In this paper, we present Maximum MultiPath TCP (MMPTCP), a novel transport protocol which, compared to TCP and MPTCP, reduces short flows' completion times, while providing excellent goodput to long flows. To do so, MMPTCP runs in two phases; initially, it randomly scatters packets in the network under a single congestion window exploiting all available paths. This is beneficial to latency-sensitive flows. After a specific amount of data is sent, MMPTCP switches to a regular MultiPath TCP mode. MMPTCP is incrementally deployable in existing data centres as it does not require any modifications outside the transport layer and behaves well when competing with legacy TCP and MPTCP flows. Our extensive experimental evaluation in simulated FatTree topologies shows that all design objectives for MMPTCP are met.
High-Rate Redundant Space-Time Coding

We present a new space-time encoder based on packet-level redundancy which can increase the space-time encoder rate beyond unity without compromising diversity gains. A complementary low-complexity decoding algorithm based on maximum ratio combining and successive interference cancelation is further proposed. A major merit of the decoding algorithm is that it allows to adaptively tradeoff between diversity and multiplexing gains based on the estimated channel parameters at the receiver without requiring any channel state information at the transmitter. System level simulation results give insight into the advantages of the proposed scheme when compared to its Alamouti and MIMO multiplexing based on single value decomposition counterparts.
DCT-based channel estimation for wireless OFDM systems with the hexagonal pilot pattern

When there are some virtual subcarriers and high Doppler frequency in practical orthogonal frequency division multiplexing (OFDM) system, we adopt discrete cosine transform (DCT)-based channel estimator instead of conventional DFT-based one to reduce the performance deterioration. And as hexagonal distribution of pilots is optimum in term of sampling efficiency, that is, it provides better performance than the rectangular one. So a two dimensional (2-D) DCT-based channel estimator with hexagonal pilot patterns is proposed, and detailed derivation is given. Simulation results show that the performance of the proposed method can well approach the 2-D Wiener filtering estimator
Adaptive Voltage-Controlled Oscillator for Improved Dynamic Performance in LLC Resonant Converter

This paper proposes an adaptive voltage-controlled oscillator (VCO) to improve the dynamic performance in LLC resonant converters. The proposed adaptive VCO is designed to have frequency-dependent small-signal gains, so that the variation of low-frequency magnitude in frequency response of LLC resonant converter is effectively adjusted. As a result, an enhanced dynamic performance is obtained over wide-operating ranges. Through approximated derivation, the proposed adaptive VCO has a simple formula and does not require any additional sensing circuits. Furthermore, it is robust to variation of circuit parameters. Dynamic performance enhancement was verified by experimental results with a 144-W laboratory prototype half-bridge LLC resonant converter.
Three-Dimensional MRI Atlas of the Human Cerebellum in Proportional Stereotaxic Space

We have prepared an atlas of the human cerebellum using high-resolution magnetic resonance-derived images warped into the proportional stereotaxic space of Talairach and Tournoux. Software that permits simultaneous visualization of the three cardinal planes facilitated the identification of the cerebellar fissures and lobules. A revised version of the Larsell nomenclature facilitated a simple description of the cerebellum. This atlas derived from a single individual was instrumental in addressing longstanding debates about the gross morphologic organization of the cerebellum. It may serve as the template for more precise identification of cerebellar topography in functional imaging studies in normals, for investigating clinical-pathologic correlations in patients, and for the development of future probabilistic maps of the human cerebellum.
Simultaneous Multi-class Pixel Labeling over Coherent Image Sets

Multi-class pixel labeling is an important problem in computer vision that has many diverse applications, including interactive image segmentation, semantic and geometric scene understanding, and stereo reconstruction. Current state-of-the-art approaches learn a model on a set of training images and then apply the learned model to each image in a test set independently. The quality of the results, therefore, depends strongly on the quality of the learned models and the information available within each training image. Importantly, this approach cannot leverage information available in other images at test time which may help to label the image at hand. Instead of labeling each image independently, we propose a semi-supervised approach that exploits the similarity between regions across many images in coherent image subsets. Specifically, our model finds similar regions in related images and constrains the joint labeling of the images to agree on the labels within these regions. By considering the joint labeling, our model gets to leverage contextual information that is not available when considering images in isolation. We test our approach on the popular 21-class MSRC multi-class image segmentation dataset and show improvement in accuracy over a strong baseline model.
Effects of Venous Superdrainage and Arterial Supercharging on Dorsal Perforator Flap in a Rat Model

Objective To comparatively assess the effects of venous superdrainage and arterial supercharging on dorsal perforator flap survival. Materials and Methods Sixty male Sprague-Dawley rats (450–550g) were randomly divided into three groups (n = 20), including control group (Control) and experimental groups A (venous superdrainage, Exp. A) and B (arterial supercharging, Exp. B). At postoperative day 7, survival areas of the flaps were evaluated and all animals underwent angiography. Laser Doppler was used to evaluate flap perfusion from 0h to 7days after surgery. Histology with hematoxylin and eosin staining was used to count microvessels. Tissue of “Choke vessels”was excised for quantification of hypoxia inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) by western blot assay at 6h and 7days after surgery. Results In the Exp. A group, almost all flaps survived (98.2±1.6%); in the Exp. B and control group, survival areas accounted for 78.8±8.5% and 60.3±7.8%, respectively (P <0.001). In addition, Exp. A animals showed improved anastomosis of choke vessels 2 compared with the Exp. B and Control groups. Furthermore, flap blood flow and partial pressure of oxygen in the Exp. A group were significantly higher compared with values obtained for the Exp. B and Control groups, from 6 hours to 7 days after surgery. More microvessels were found in the Exp. A group (11.65±1.33) than in Exp. B (9.25±0.34) and control (7.25±0.91) animals on POD 7. The relative expression level of HIF-1α and VEGF were significant at 6h and 7days after surgery. Conclusions Venous superdrainage in rat dorsal perforator flap is more effective than arterial supercharging in promoting flap survival, and could effectively alter hemodynamics in the microcirculation and stimulate blood vessel formation.
A New Appearance-Based Facial Expression Recognition System with Expression Transition Matrices

In this study, we propose a novel image-based facial expression recognition method called "expression transition" to identify six kinds of facial expressions (anger, fear, happiness, neutral, sadness, and surprise) at low-resolution images. The boosted tree classifiers and template matching are used to locate and crop the effective face region that may characterize the facial expressions. Then, the expression transformed images via a set of expression transition matrices are matched with the real facial images to identify the facial expressions. The proposed system can recognize the facial expressions with the speed of 0.24 seconds per frame and accuracy. above 86%.