Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Implementation of Health Information Systems

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Book review. Symmetry: a Journey into the Patterns of Nature

In January 1975, Jacques Tits gave a lecture during which he wrote down the order, 246 · 320 · 59 ·76 ·112 ·133 ·17·19·23·29·31·41·47·59·71, or about 8 · 1053, of a sporadic simple group M that Bernd Fischer and, independently, Robert Griess had predicted in 1973. Andrew Ogg, an expert in modular functions who happened to be in the audience, was uniquely qualified to recognize something peculiar about this order: he had recently determined the primes that give rise to a certain family of genus 0 modular curves, and the primes he had discovered were precisely the fifteen prime divisors on the blackboard. It was an astonishing coincidence. At the time, to suggest anything more than that would have been moonshine. Three years later, in 1978, Fischer, Donald Livingstone, and Michael Thorne calculated the character table of the Monster, as John Horton Conway had christened M , by assuming an additional prediction of Griess, the existence of an irreducible character of degree χ1 = 196883. Shortly thereafter, John McKay noticed that the
Self-* and Predictability: are these conflicting System Capabilities?

In principle, it would have been desirable for any system to have self-* capabilities when faced with changes that might occur either in the system or its environment. However, these capabilities are difficult to incorporate in certain classes of systems, mainly those in which uncertainties in their behaviours are not desirable. In this position paper, we discuss how the expected degree of autonomy of a system is related to the way in which a system can be described. The discussion is presented in the context of predictability and the assurances associated with the accuracy of that predictability. The subject of this paper are those systems known to be critical in the services they deliver, and which cannot incorporate high degree of uncertainty.
Nonlinear transformer simulation for real-time digital audio signal processing

Digital simulation of audio transformers is discussed in this paper. A simplified model of the audio transformer is designed. The model is described using nonlinear differential equations. The transformer core is modeled by Jiles-Atherton and Frohlich models. The whole system is approximated in order to reduce computational complexity. Finally, the proposed algorithm is tested in real-time and the computational complexity is determined.
A Complete 256-Electrode Retinal Prosthesis Chip

This paper presents a complete 256-electrode retinal prosthesis chip, which is small and ready for packaging and implantation. It contains 256 separate programmable drivers dedicated to 256 electrodes for flexible stimulation. A 4-wire interface is employed for power and data transmission between the chip and a driving unit. Power and forward data are recovered from a 600 kHz differential signal, while backward data are sent at 100 kbps rate simultaneously. The stimulator possesses many stimulation features, supporting various stimulation strategies. Many safety features are included such as real-time monitoring of voltage compliance and temperature, electrode self-locking in the event of out-of-compliance, and ESD protection circuit at every electrode. The chip is fabricated in a 65 nm CMOS process. The electrode driver pitch is 150 μm, and total chip area is 8 mm 2 . The chip has been extensively tested and all the requirements have been successfully verified. The measured DC current error for single driver stimulation without electrode shorting is 20 nA. The average power consumption per electrode with typical stimulus pulse parameters and full-scale output current is 129 μW, inclusive of all standby power. The chip overall power efficiency is 70% with 23 mW of power delivered to load.
Quality Connector An Architectural Pattern to Enhance QoS and Alleviate Dependencies in Distributed Real-time and Embedded Middleware

Commercial off-the-shelf (COTS) middleware increasingly offers distributed real-time and embedded (DRE) applications functional support for standard interfaces, along with the abilit y to optimize application resource utili zation. For example, a Real-time CORBA object request broker (ORB) permits DRE application developers to configure server thread pooling policies. This flexibility makes it possible to use standard functional interfaces in applications where they were not applicable previously. However, the nonstandard nature of the optimization mechanisms – i.e., the "knobs and dials" – acts against the very product-independence that standardized COTS interfaces are intended to provide. This paper presents an architectural pattern called Quality Connector, which is a meta-programming technique that enables applications to specify the QoS they require from their infrastructure, and then manages the operations that optimize the middleware to implement those QoS requirements. The Quality Connector architectural pattern decouples application components from the QoS configuration mechanisms provided by infrastructure components to permit the infrastructure to evolve without requiring manual changes to application component functionality. The Quality Connector mediates between the application and non-standard middleware configuration and control interfaces.
Author ' s personal copy Grammatical aspect and mental simulation

When processing sentences about perceptible scenes and performable actions, language understanders activate perceptual and motor systems to perform mental simulations of those events. But little is known about exactly what linguistic elements activate modality-specific systems during language processing. While it is known that content words, like nouns and verbs, influence the content of a mental simulation, the role of grammar is less well understood. We investigate the role of grammatical markers in mental simulation through two experiments in which we manipulate the meanings of sentences by modifying the grammatical aspect they use. Using the Action-sentence Compatibility Effect (ACE) methodology [Glenberg, A. , Kaschak, M. (2002). Grounding language in action. Psychonomic Bulletin and Review, 9, 558–565], we show that progressive sentences about hand motion facilitate manual action in the same direction, while perfect sentences that are identical in every way except their aspect do not. The broader implication of this finding for language processing is that while content words tell understanders what to mentally simulate and what brain regions to use in performing these simulations, grammatical constructions such as aspect modulate how those simulations are performed. 2009 Elsevier Inc. All rights reserved.
Adaptive Class Association Rule Mining for Human Activity Recognition

The analysis of human activity data is an important research area in the context of ubiquitous and social environments. Using sensor data obtained by mobile devices, e. g. , utilizing accelerometer sensors contained in mobile phones, behavioral patterns and models can then be obtained. However, the utilized models are often not simple to interpret by humans in order to facilitate assessment, evaluation and validation, e. g. , in computational social science or in medical contexts. In this paper, we propose a novel approach for generating interpretable rule sets for classification: We present an adaptive framework for mining class association rules using subgroup discovery, and analyze different techniques for obtaining the final classifier. The approach is investigated in the context of human activity recognition. For our evaluation, we apply real-world activity data collected using mobile phone sensors.
Children’s Evaluations of Tattles, Confessions, Prosocial and Antisocial Lies

Lie-telling is a false verbal statement made with the intention to deceive another. Lies may be told for selfish reasons or due to prosocial motivations. As a result, the veracity of a statement holds more than just communicative intent but rather represents social intentions. In the current experiment children (6- to 12-years old) viewed 12 vignettes which depicted a protagonist either telling a truth or a lie. The protagonist’s statements either hurt another or themselves (other versus self). Following viewing of each vignette participants provided a moral evaluation of the protagonist’s statement (five-point Likert) and a classification of the statements; as either a truth or lie. Additionally, a novel method of evaluating statements was introduced, whereby children evaluated communicative intent as an act, to be rewarded or punished. Results revealed that both lies and truths were accurately identified, with the exception of altruistic lies (benefits to another) and tattling truths (harms another). Younger children rewarded truthful statements, which harmed or hurt another, significantly more often than older children. Older children ranked lies to help another significantly more favorably than lies to protect the self. Children also rewarded confessions and punished antisocial lies most frequently. Results highlight the notable differences in children’s perceptions of varying forms of honesty and lying.
Human Activity Recognition Based on Transform and Fourier Mellin Transform

Human activity recognition is attracting a lot of attention in the computer vision domain. In this paper we present a novel human activity recognition method based on transform and Fourier Mellin Transform (FMT). Firstly, we convert the original image sequence to the Radon domain, get the transform curves by transform. Then we extract the Rotation-Scaling-Translation (RST) invariant features by FMT and use to have dimension reduction by PCA method. At the recognition stage, the Earth Mover’s Distance (EMD) is used here. In the experiment, we compare our method to other methods. The experimental results show the effectiveness of our method.
Equivalences between Ranked and Unranked Weighted Tree Automata via Binarization

Encoding unranked trees to binary trees, henceforth called binarization, is an important method to deal with unranked trees. For each of three binarizations we show that weighted (ranked) tree automata together with the binarization are equivalent to weighted unranked tree automata; even in the probabilistic case. This allows to easily adapt training methods for weighted (ranked) tree automata to weighted unranked tree automata.
A new geometrical inverse kinematics method for planar hyper redundant manipulators

Obtaining the joint variables that result in a desired position of the robot end-effector called as inverse kinematics is one of the most important problems in robot kinematics and control. As the complexity of robot increases, obtaining the inverse kinematics solution requires the solution of non linear equations having transcendental functions are difficult and computationally expensive. This paper proposed a new geometrical method to find the inverse kinematics of the planar redundant manipulators. Using the proposed method, singularity avoidance is achieved by setting the angles between the adjacent links to be equal, which makes it impossible for any two or more joint axes to line up. Two study cases are simulated in this paper to show the performance of the proposed method.
LIGHT enhances the bactericidal activity of human monocytes and neutrophils via HVEM

Human monocytes and neutrophils play major roles in clearing bacteria from human blood and tissues. We found that the herpes virus entry mediator (HVEM) was highly expressed in monocytes and neutrophils, and its interaction with “homologous to lymphotoxins, shows inducible expression, and competes with herpes simplex virus glycoprotein D for HVEM/tumor necrosis factor (TNF)‐related 2” (LIGHT) enhanced bactericidal activity against Listeria monocytogenes and Staphylococcus aureus. The LIGHT‐HVEM interaction increased levels of phagocytosis, interleukin (IL)‐8, TNF‐α, nitric oxide (NO), and reactive oxygen species (ROS) in monocytes and neutrophils. Anti‐HVEM monoclonal antibody was able to block LIGHT‐induced bactericidal activity, cytokine production (IL‐8 and TNF‐α), and ROS generation. Moreover, inhibition of ROS and NO production blocked LIGHT‐induced bactericidal activity. Our results indicate that the LIGHT/HVEM interaction in monocytes and neutrophils contributes to antibacterial activity.
D-Alanylation of Lipoteichoic Acids Confers Resistance to Cationic Peptides in Group B Streptococcus by Increasing the Cell Wall Density

Cationic antimicrobial peptides (CAMPs) serve as the first line of defense of the innate immune system against invading microbial pathogens. Gram-positive bacteria can resist CAMPs by modifying their anionic teichoic acids (TAs) with D-alanine, but the exact mechanism of resistance is not fully understood. Here, we utilized various functional and biophysical approaches to investigate the interactions of the human pathogen Group B Streptococcus (GBS) with a series of CAMPs having different properties. The data reveal that: (i) D-alanylation of lipoteichoic acids (LTAs) enhance GBS resistance only to a subset of CAMPs and there is a direct correlation between resistance and CAMPs length and charge density; (ii) resistance due to reduced anionic charge of LTAs is not attributed to decreased amounts of bound peptides to the bacteria; and (iii) D-alanylation most probably alters the conformation of LTAs which results in increasing the cell wall density, as seen by Transmission Electron Microscopy, and reduces the penetration of CAMPs through the cell wall. Furthermore, Atomic Force Microscopy reveals increased surface rigidity of the cell wall of the wild-type GBS strain to more than 20-fold that of the dltA mutant. We propose that D-alanylation of LTAs confers protection against linear CAMPs mainly by decreasing the flexibility and permeability of the cell wall, rather than by reducing the electrostatic interactions of the peptide with the cell surface. Overall, our findings uncover an important protective role of the cell wall against CAMPs and extend our understanding of mechanisms of bacterial resistance.
Parallel BCC with one common and two confidential messages and imperfect CSIT

We consider a broadcast communication system over parallel sub-channels where the transmitter sends three messages: a common message to two users, and two confidential messages to each user which need to be kept secret from the other user. We assume partial channel state information at the transmitter (CSIT), stemming from noisy channel estimation. The first contribution of this paper is the characterization of the secrecy capacity region boundary as the solution of weighted sum-rate problems, with suitable weights. Partial CSIT is addressed by adding a margin to the estimated channel gains. The second paper contribution is the solution of this problem in an almost closed-form, where only two single real parameters must be optimized, e.g., through dichotomic searches. On the one hand, the considered problem generalizes existing literature where only two out of the three messages are transmitted. On the other hand, the solution finds also practical applications into the resource allocation of orthogonal frequency division multiplexing (OFDM) systems with both secrecy and fairness constraints.
A Fast Bacterial Swarming Algorithm for high-dimensional function optimization

A novel fast bacterial swarming algorithm (FBSA) for high-dimensional function optimization is presented in this paper. The proposed algorithm combines the foraging mechanism of E-coli bacterium introduced in bacterial foraging algorithm (BFA) with the swarming pattern of birds in block introduced in particle swarm optimization (PSO). It incorporates the merits of the two bio-inspired algorithms to improve the convergence for high-dimensional function optimization. A new parameter called attraction factor is introduced to adjust the bacterial trajectory according to the location of the best bacterium (bacterium with best fitness value). An adaptive step length is adopted to improve the local search ability. The algorithm has been evaluated on standard high-dimensional benchmark functions in comparison with BFA and PSO respectively. The simulation results have demonstrated the fast convergence ability and the improved optimization accuracy of FBSA.
Coupling dense and landmark-based approaches for nonrigid registration

We investigate the introduction of cortical constraints for non rigid intersubject brain registration. We extract sulcal patterns with the active ribbon method, presented by Le Goualher et al. (1997). An energy based registration method (Hellier et al., 2001), which will be called photometric registration method in this paper, makes it possible to incorporate the matching of cortical sulci. The local sparse similarity and the photometric similarity are, thus, expressed in a unified framework. We show the benefits of cortical constraints on a database of 18 subjects, with global and local assessment of the registration. This new registration scheme has also been evaluated on functional magnetoencephalography data. We show that the anatomically constrained registration leads to a substantial reduction of the intersubject functional variability.
An Intelligent Database Application for the Semantic Web

Semantic Web is one of the important research fields that came into light recently. Its major concern is to convert the World Wide Web from just a huge repository of unrelated text, into useful linked pieces of information. Linking the information is not only based on text similarity, but mainly on the meanings and realworld relations between items. In this research, we use the techniques of the semantic web, to create formal definition rules for some kind of unstructured data, and to query this data for information that might be not explicitly stated, and that would otherwise be very difficult to extract. For this purpose, we develop an integrated system that can extract data from both unstructured and structured documents, and then answer users' queries using the extracted data together with some inference rule that help to deduce more information from this data. As an example of this data, we take the social relationships found in death-ads in newspapers. These ads contain both implicit and explicit information about various relationships among people. These relationships, if arranged and organized in a proper way, can be used to extract and infer other hidden, not explicitly mentioned relationships.
Exploiting Parallelism in Geometry Processing with General Purpose Processors and Floating-Point SIMD Instructions

Three-dimensional (3D) graphics applications have become very important workloads running on today's computer systems. A cost-effective graphics solution is to perform geometry processing of 3D graphics on the host CPU and have specialized hardware handle the rendering task. In this paper, we analyze microarchitecture and SIMD instruction set enhancements to a RISC superscalar processor for exploiting parallelism in geometry processing for 3D computer graphics. Our results show that 3D geometry processing has inherent parallelism. Adding SIMD operations improves performance from 8 percent to 28 percent on a 4-issue dynamically scheduled processor that can issue at most two floating-point operations. In comparison, an 8-issue processor, ignoring cycle time effects, can achieve 20 to 60 percent performance improvement over a 4-issue. If processor cycle time scales with the number of ports to the register file, then doubling only the floating-point issue width of a 4-issue processor with SIMD instructions gives the best performance among the architectural configurations that we examine (the most aggressive configuration is an 8-issue processor with SIMD instructions).
Detection of Filamentous Structures in Low-Contrast Images Acquired in Defocus Pair by Cryo-Electron Microscopy

Since the foundation of the three-dimensional image reconstruction of helical objects from electron micrographs was laid more than 30 years ago, there have been sustained developments in specimen preparation, data acquisition, image analysis, and interpretation of results. However, the boxing of filaments in large number of images—one of the critical step toward the reconstruction in atomic resolution—is still restrained by manual processing even though interactive interfaces have been built to aid the tedious and less accurate manual boxing. This article describes an accurate approach for automatically detecting filamentous structures in lowcontrast images acquired in defocus pair using cryoelectron microscopy. The performance of the proposed approach has been evaluated across various magnifications and a series of defocus values using as a test driver specimens of tobacco mosaic virus (TMV) preserved in vitreous ice. By integrating the proposed approach into our automated data acquisition and reconstruction, we are able to get a 3D map of TMV at the resolution of 10A within hours in a fully automatic way.