Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Development of a Distributed Tabletop System Using EBITA Framework

Over the past decade, tabletop systems are becoming more popular. However, prior works on tabletop system have mostly focused on supporting user interactions with digital contents on one single tabletop display, which are not easily extendable. In this paper we present a new scalable distributed tabletop system consisted of master/slave computer and tangible interfaces to provide high-resolution interactive tabletop display surfaces. Our work is to develop a tabletop system constructed with LCD panels and a cluster of low-cost commodity PCs to support a large highresolution scalable tiled display. It also employs the tangible user interface using the infrared camera tracking and tangible blocks to support intuitive user interaction on the tabletop surface. In this research, EBITA (Environment for Building Interactive Tangible Applications) framework is developed to support various modules necessary for easy construction of any interactive high-resolution applications that run on the distributed tabletop system. This paper briefly describes the design of EBITA framework and detail implementations of the current prototype of distributed tabletop system. Then it demonstrates two applications developed using EBITA framework: 2D high-resolution image viewer and 3D block crash game.
Bayesian Networks for Structured Information Retrieval

We present a bayesian framework for XML document retrieval. This framework allows us to consider content only. We perform the retrieval task using inference in our network. Our model can adapt to a specific corpus through parameter learning and uses a grammar to speed up the retrieval process in big or distributed databases. We also experimented list filtering to avoid element overlap in the retrieved element list.
RoCeT: Rough Clustering for web Transactions

Grouping web transactions into clusters is important in order to obtain better understanding of user's behavior. Currently, the rough approximation-based clustering technique has been used to group web transactions into clusters. However, the processing time is still an issue due to the high complexity for nding the similarity of upper approximations of a transaction which used to merge between two or more clusters. On the other hand, the problem of more than one transaction under given threshold is not addressed. In this paper, we propose RoCeT model for grouping web transactions using rough set theory. It is based on the two similarity classes which are nonvoid intersection. Keywords: Clustering, Web transactions, Rough set theory.
Temporal-Spatial Visualization of Interaction Data for Visual Debugging

The design of novel input devices and interaction techniques is a highly demanding task. The interaction designers need programming environments which provide high flexibility and complex functionalities. But above all, such tools have to be easy to learn and should support the analysis and interpretation of the interaction data even for interaction designers with little or no programming experience. Squidy is a Zoomable Design Environment which eases the design, integration and combination of novel input devices as well as appropriate interaction techniques. By providing a simple yet powerful visual programming language based on the pipe-and-filter metaphor combined with details-on-demand techniques, Squidy facilitates rapid prototyping and a fast iteration cycle [Konig et al. 2009]. Therefore, Squidy offers a versatile collection of ready-touse nodes such as devices, filters and interaction techniques which can be visually arranged and connected and thereby define the desired interaction technique. This can be for example an optical tracking of a laser pointer’s spot to interact with a distant display wall, as can be seen in [Figure 1]. Here, the 2-dimensional position data passes through several filters and finally controls a mouse cursor and a TUIO-based application. However, currently such a visual design of an interaction technique with Squidy requires a deep understanding of the data flow and the semantics of the designed pipeline. Current debugging techniques are based on textual output mostly combined with table-based representations that allow hierarchical navigation. However, they neither provide information about spatial location of data nor follow a chronological sequence. We introduce an approach to visually analyze and interpret the data flow inside the design environment.
Prion Strain Interactions Are Highly Selective

Various misfolded and aggregated neuronal proteins commonly coexist in neurodegenerative disease, but whether the proteins coaggregate and alter the disease pathogenesis is unclear. Here, we used mixtures of distinct prion strains, which are believed to differ in conformation, to test the hypothesis that two different aggregates interact and change the disease in vivo. We tracked two prion strains in mice histopathologically and biochemically, as well as by spectral analysis of plaque-bound PTAA (polythiophene acetic acid), a conformation-sensitive fluorescent amyloid ligand. We found that prion strains interacted in a highly selective and strain-specific manner, with (1) no interaction, (2) hybrid plaque formation, or (3) blockage of one strain by a second (interference). The hybrid plaques were maintained on additional passage in vivo and each strain seemed to maintain its original conformational properties, suggesting that one strain served only as a scaffold for aggregation of the second strain. These findings not only further our understanding of prion strain interactions but also directly demonstrate interactions that may occur in other protein aggregate mixtures.
Xanthene Derivatives Increase Glucose Utilization through Activation of LKB1-Dependent AMP-Activated Protein Kinase

5′ AMP-activated protein kinase (AMPK) is a highly conserved serine-threonine kinase that regulates energy expenditure by activating catabolic metabolism and suppressing anabolic pathways to increase cellular energy levels. Therefore AMPK activators are considered to be drug targets for treatment of metabolic diseases such as diabetes mellitus. To identify novel AMPK activators, we screened xanthene derivatives. We determined that the AMPK activators 9H-xanthene-9-carboxylic acid {2,2,2-trichloro-1-[3-(3-nitro-phenyl)-thioureido]-ethyl}-amide (Xn) and 9H-xanthene-9-carboxylic acid {2,2,2-trichloro-1-[3-(3-cyano-phenyl)-thioureido]-ethyl}-amide (Xc) elevated glucose uptake in L6 myotubes by stimulating translocation of glucose transporter type 4 (GLUT4). Treatment with the chemical AMPK inhibitor compound C and infection with dominant-negative AMPKa2-virus inhibited AMPK phosphorylation and glucose uptake in myotubes induced by either Xn or Xc. Of the two major upstream kinases of AMPK, we found that Xn and Xc showed LKB1 dependency by knockdown of STK11, an ortholog of human LKB1. Single intravenous administration of Xn and Xc to high-fat diet-induced diabetic mice stimulated AMPK phosphorylation of skeletal muscle and improved glucose tolerance. Taken together, these results suggest that Xn and Xc regulate glucose homeostasis through LKB1-dependent AMPK activation and that the compounds are potential candidate drugs for the treatment of type 2 diabetes mellitus.
Automatic detection of interaction groups

This paper addresses the problem of detecting interaction groups in an intelligent environment. To understand human activity, we need to identify human actors and their interpersonal links. An interaction group can be seen as basic entity, within which individuals collaborate in order to achieve a common goal. In this regard, the dynamic change of interaction group configuration, i.e. the split and merge of interaction groups, can be seen as indicator of new activities. Our approach takes speech activity detection of individuals forming interaction groups as input. A classical HMM-based approach learning different HMM for the different group configurations did not produce promising results. We propose an approach for detecting interaction group configurations based on the assumption that conversational turn taking is synchronized inside groups. The proposed detector is based on one HMM constructed upon conversational hypotheses. The approach shows good results and thus confirms our conversational hypotheses.
A 60µW LNA for 2.4 GHz wireless sensors network applications

This work reports on the implementation of a 2.4 GHz ultra low power (ULP) low noise amplifier (LNA) in a standard CMOS 0.13 µm process. The proposed design methodology consists in optimizing the tradeoff between RF performances and current consumption of the MOS transistor. The supply of the circuit controlled by a 3bits DAC varies from 0.4 to 0.6 V. This digital tuning allows maximizing the figure of merit of the LNA. The approach yields the operating point within the sweet spot region of the amplifying transistors. Experimental results of the circuit indicate a power dissipation of 60 µW@0.4V, a noise figure of 5.3 dB, and a forward gain of 13.1 dB. The IIP3 and ICP1 are −12 dBm and −19 dBm, respectively. This works aims the development of a complete RF front end for micro-watt radio.
Retinal ganglion cell inputs to the koniocellular pathway

To understand the transmission of sensory signals in visual pathways we studied the morphology and central projection of ganglion cell populations in marmoset monkeys. Retinal ganglion cells were labeled by photofilling following injections of retrograde tracer in the lateral geniculate nucleus (LGN), or by intracellular injection with neurobiotin. Ganglion cell morphology was analyzed using hierarchical cluster analysis. In addition to midget and parasol ganglion cells, this method distinguished three main clusters of wide‐field cells that correspond to small bistratified, sparse, and broad thorny cells identified previously. The small bistratified and sparse cells occupy neighboring positions on the hierarchical (linkage distance) tree. These cell types are presumed to carry signals originating in short‐wavelength sensitive (S or “blue”) cones in the retina. The linkage distance from these putative S‐cone pathway ganglion cells to other wide‐field cells is similar to the linkage distance from midget cells to parasol cells, suggesting that S‐cone cells form a distinct functional subgroup of ganglion cells. Small bistratified cells and large sparse cells were the most commonly labeled wide‐field cells following LGN injections in koniocellular layer K3. This is consistent with physiological evidence that the role of this layer includes transmission of S‐cone signals to the visual cortex. Other wide‐field cell types were also labeled following injections including K3, and other koniocellular LGN layers; these cell types may correspond to “non‐blue koniocellular” receptive fields recorded in physiological studies. J. Comp. Neurol. 510:251–268, 2008. © 2008 Wiley‐Liss, Inc.
Regulation of Cell Transformation by Rb-Controlled Redox Homeostasis

Rb is a tumor suppressor, and regulates various biological progresses, such as cell proliferation, development, metabolism and cell death. In the current study, we show that Rb knockout in 3T3 cells leads to oxidative redox state and low mitochondrial membrane potential by regulating mitochondrial activity. Our results indicate that Rb plays an important role in controlling redox homeostasis. More importantly, the functions of Rb in modulating cell proliferation, death and transformation are, at least in part, mediated by its controlling cellular redox state. In addition, our results also suggest that the cellular redox state possibly determines various biological activities, including cell survival, death and transformation, where Rb is functioning as a regulator of redox homeostasis.
Incremental satisfiability counting for real-time systems

Testing constraints for real-time systems are usually verified through the satisfiability of propositional formulae. In this paper, we propose an alternative where the verification of timing constraints can be done by counting the number of truth assignments instead of Boolean satisfiability. This number can also tell us how "far away" a given specification is from satisfying its safety assertion. Furthermore, specifications and safety assertions are often modified in an incremental fashion, where problematic bugs are fixed one at a time. To support this development, we propose an incremental algorithm for counting satisfiability. Our proposed incremental algorithm is optimal as no unnecessary nodes are created during each counting. This works for the class of expressions, known as path RTL ([F. Jahanian et al. (1987), F. Wang et al. (1994)]). To illustrate this application, we show how incremental satisfiability counting can be applied to a well-known rail-road crossing example, particularly when its specification is still being refined.
The role of motivational and volitional factors for self-regulated running training: associations on the between- and within- person level.

OBJECTIVES Most studies examine associations between social-cognitive variables and self-regulated behavioural change across two or three occasions only. This study adopts an innovative perspective by analysing associations across 11 occasions, which allows examining patterns of associations both on the between- and within-person levels. METHOD Thirty initially untrained participants of a running training programme completed 11 monthly questionnaires. All questionnaires assessed motivational and volitional variables and self-reported running. Additionally, net running time of marathon, or half-marathon distance at the end of programme, was available. RESULTS Self-efficacy turned out to be associated with intentions on the between- and within-person levels. Individual differences in change patterns and within-person fluctuations in volitional variables, intentions, and self-efficacy turned out to be consistently associated with change patterns and within-person fluctuations in self-regulated running training over time and with successfully running marathon or half-marathon distance. CONCLUSIONS In contrast to examining only one facet of change, this study is the first to differentiate two components of change in health behaviour self-regulation: a systematic trend component, and a component representing within-person unsystematic fluctuations. Thus, results of the present study provide a comprehensive picture of the dynamic relations between motivational, volitional, and behavioural characteristics which occur between and within persons.
Disk Shadowing

Disk shadowing is a technique for maintaining a set of two or more identical disk images on separate disk devices. Its primary purpose is to enhance reliability and availability of secondary storage by providing multiple paths to redundant data. However, shadowing can also boost UO performance. In this paper, we contend that intelligent device scheduling of shadowed disks increases the I/O rate, by allowing parallel reads and by substantially reducing the average seek time for random reads. In particular, we develop an analytic model which shows that the seek time for a random read in a shadow set is a monotonic decreasing function of the number of disks in the set.
LEARNING FROM EXAMPLES IN CRITICAL BANDS OF

We propose to mimic auditory strategies for recognizing noisy or distorted speech. Motivated by psychoacoustic data on human performance, we begin by studying how to detect the phonetic feature of voicing. We describe an automatic method for voicing detection starting from a cochlear lterbank. Our method has three stages: rst, speech is l-tered into critical bands and enhanced by nonlinearities; second, a degree of voicing is computed in each band based on its periodicity and signal-to-noise ratio; third, signals from diierent bands are combined to make a global decision. These stages are formulated as components of a probabilistic graphical model, represented by a multilayer Bayesian network. We train the model from a corpus of phonetically transcribed speech, then evaluate its robust-ness to noise and corrupting innuences. Implications for automatic speech recognition are discussed.
Prevalence and Correlates of Microalbuminuria in Children with Sickle Cell Anaemia: Experience in a Tertiary Health Facility in Enugu, Nigeria

Microalbuminuria is a pre-clinical marker of renal damage in children with sickle cell anaemia and can predict renal failure. Reported prevalence rates increased with age. In Nigeria, burden of disease and prevailing poor health facilities necessitate its screening, determination of prevalence and associated risk factors. It is a cross-sectional as well as descriptive study. Screening microalbuminuria used subjects' early morning urine. Socio-demographic as well as clinical details were ascertained using semi-structured questionnaires and case files. Associations and statistical relationship of prevalence rates and clinical/epidemiological data were ascertained using chi-squared and multivariate analysis (P < 0.05). Two hundred children with sickle cell anaemia (4–17 years) in steady state and 200 age/gender-matched controls were enrolled. Prevalence of microalbuminuria was ,respectively, 18.5% and 2.5% for subjects and controls (P = 0.001). Microalbuminuria was commoner in females (19.8%) than males (17.4%) P = 0.70, increased with age (P = 0.016), significantly associated with haemoglobin level (P = 0.002) and hospitalizations (0.001). Subjects had normal renal function. Hospitalizations and haemoglobin levels showed statistical significance on multivariate analysis. Prevalence of microalbuminuria is 18.5%. Age, haemoglobin concentrations, and higher hospitalizations influenced microalbuminuria among subjects. Screening for microalbuminuria should be incorporated in the case management of subjects with identified risk factors.
Object Recognition and Localization: The Role of Tactile Sensors

Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF) is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC) algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments.
In Vivo Activity of Released Cell Wall Lipids of Mycobacterium bovis Bacillus Calmette-Guérin Is Due Principally to Trehalose Mycolates1

The hallmark of Mycobacterium-induced pathology is granulomatous inflammation at the site of infection. Mycobacterial lipids are potent immunomodulators that contribute to the granulomatous response and are released in appreciable quantities by intracellular bacilli. Previously we investigated the granulomagenic nature of the peripheral cell wall lipids of Mycobacterium bovis bacillus Calmette-Guérin (BCG) by coating the lipids onto 90-μm diameter microspheres that were mixed into Matrigel matrix with syngeneic bone marrow-derived macrophages and injected i.p. into mice. These studies demonstrated that BCG lipids elicit proinflammatory cytokines and recruit leukocytes. In the current study we determined the lipids responsible for this proinflammatory effect. BCG-derived cell wall lipids were fractionated and purified by liquid chromatography and preparative TLC. The isolated fractions including phosphatidylinositol dimannosides, cardiolipin, phosphatidylglycerol, phosphatidylethanolamine, trehalose monomycolate, trehalose dimycolate, and mycoside B. Trehalose dimycolate, when delivered to bone marrow-derived murine macrophages, induced the greatest secretion of IL-1β, IL-6, and TNF-α in vitro. Trehalose dimycolate similarly induced the greatest secretion of these proinflammatory cytokines in ex vivo matrices over the course of 12 days. Trehalose monomycolate and dimycolate also induced profound neutrophil recruitment in vivo. Experiments with TLR2 or TLR4 gene-deficient mice revealed no defects in responses to trehalose mycolates, although MyD88-deficient mice manifested significantly reduced cell recruitment and cytokine production. These results demonstrate that the trehalose mycolates, particularly trehalose dimycolate, are the most bioactive lipids in the BCG extract, inducing a proinflammatory cascade that influences granuloma formation.
Open user schema guided evaluation of streaming RDF queries

Performance and scalability are two issues that are becoming increasingly pressing as RDF data model is applied to real-world applications. Because neither vertical nor flat structures of RDF storage can handle frequent schema updates and meanwhile avoid possible long-chain joins, there is no clear winner between these two typical structures. In this paper, we propose an alternative storage schema called open user schema. The open user schema consists of flat tables automatically extracted from RDF query streams. A query is divided into two parts and conquered,respectively, on the flat tables in the open user schema and on the vertical table stored in a backend storage. At the core of this divide and conquer architecture with open user schema, an efficient isomorphism decision algorithm is given to guide a query to related flat tables in the open user schema. Our proposal in essence departs from existing methods in that it can accommodate schema updates without possible long-chain joins. We implement our approach and provide empirical evaluations to demonstrate both efficiency and effectiveness of our approach in evaluating complex RDF queries.
Robust Routing

In a network, traffic demands are known with a degree of uncertainty, traffic engineering should take into account the traffic variability. In this research work we focus on the robust routing under changing network conditions. Daily Internet traffic pattern shows that network is vulnerable to malicious attacks, denial of service attacks, worms and viruses. Oblivious routing has a substantially better performance than open shortest path first [OSPF] routing for different level of uncertainty. We propose a theoretical framework for Robust Routing aiming to improve online and offline traffic engineering approaches.
Interactive Multi-resolution Exploration of Million Node Graphs

We are working on a scalable, interactive graph visualization system to support multi-resolution exploration of million-node graphs in real time. By adapting a state-of-the-art graph algorithm, our prototype system generates a multi-resolution view of graphs with up to 68 million edges under a few seconds. We are experimenting with interaction techniques that help users interactively explore this overview and drill down into details. While many visualization systems for million-node graphs require dedicated servers to process the graphs, our prototype runs on a commodity laptop computer. We aim to handle graphs that are at least an order of magnitude (100M edges) larger than what current systems can support.