Miracle-dz/UniFAR-FTUs huggingface dataset:
Proteomic Analysis of Glycosylphosphatidylinositol-anchored Membrane Proteins*

Glycosylphosphatidylinositol-anchored proteins (GPI-APs) are a functionally and structurally diverse family of post-translationally modified membrane proteins found mostly in the outer leaflet of the plasma membrane in a variety of eukaryotic cells. Although the general role of GPI-APs remains unclear, they have attracted attention because they act as enzymes and receptors in cell adhesion, differentiation, and host-pathogen interactions. GPI-APs may represent potential diagnostic and therapeutic targets in humans and are interesting in plant biotechnology because of their key role in root development. We here present a general mass spectrometry-based proteomic “shave-and-conquer” strategy that specifically targets GPI-APs. Using a combination of biochemical methods, mass spectrometry, and computational sequence analysis we identified six GPI-APs in a Homo sapiens lipid raft-enriched fraction and 44 GPI-APs in an Arabidopsis thaliana membrane preparation, representing the largest experimental dataset of GPI-anchored proteins to date.
A Model of Two-Thumb Text Entry

Although text entry has been extensively studied for touch typing on standard keyboards and finger and stylus input on soft keyboards, no such work exists for two-thumb text entry on miniature Qwerty keyboards. In this paper, we propose a model for this mode of text entry. The model provides a behavioural description of the interaction as well as a predicted text entry rate in words per minute. The prediction obtained is 60.74 words per minute. The prediction is based solely on the linguistic and motor components of the task; thus, it is a peak rate for expert text entry. A detailed sensitivity analysis is included to examine the effect of changing the model’s components and parameters over a broad range (+/-50% for the parameters). The model demonstrates reasonable stability — predictions remain within about 10% of the value just cited.
Optimized Error Diffusion for High Quality Image Display

Displaying natural images on an 8 bit computer monitor requires a substantial reduction of physically distinct colors. Simple minimum mean squared error (MMSE) quantization with 8 levels of red and green and 4 levels of blue yields poor image quality. A powerful means to improve the subjective quality of a quantized image is error diffusion. Error diffusion works by shaping the spectrum of the display error. Considering an image in raster ordering, this is done by adding a weighted sum of previous quantization errors to the current pixel before quantization. These weights form an error diffusion filter. We propose a method to find visually optimized error diffusion filters for monochrome and color image display applications. The design is based on the lowpass characteristic of the contrast sensitivity of the human visual system. The filter is chosen so that a cascade of the quantization system and the observer’s visual modulation transfer function yields a whitened error spectrum. The resulting images contain mostly high frequency components of the display error, which are less noticeable to the viewer. This corresponds well with previously This work was supported by an NEC Faculty Fellowship. Journal of Electronic Imaging, vol. 1, no. 3, pp. 277-292, July 1992. 1 published results about the visibility of halftoning patterns. An informal comparison with other error diffusion algorithms shows less artificial contouring and increased image quality.
Improving 3D indoor mapping with motion data

Using both RGB and depth information obtained from low-cost RGB-D cameras, 3D models of indoor environment can be reconstructed, which provide extensive knowledge for mobile robots to accomplish tasks such as localization, mapping, interaction with human, etc. Due to the limited views of RGB-D cameras, additional information about the camera pose is needed. In this paper, an enhanced 3D mapping algorithm is proposed to overcome the limitations. The motion of the RGB-D camera is estimated by a motion capture system after a calibration process. Based on the estimated pose, a multi-level ICP (Iterative Closest Point) algorithm is used to improve the alignment. The result shows that the 3D map can be generated in real-time. We compare our results with other approaches to show the robustness of our algorithm.
Annotation Guidelines for Machine Learning-Based Named Entity Recognition in Microbiology

Recent challenges on machine learning application to named-entity recognition in biology trigger discussions on the manual annotation guidelines for annotating the learning corpora. Some sources of potential inconsistency have been identified by corpus annotators and challenge participants. We go one step further by proposing specific annotation guidelines for biology and evaluating their effect on performances of machine learning methods. We show that a significant improvement can be achieved by this way that is not due to the feature set neither to the ML methods.
Ontology-Based Semantic Image Segmentation Using Mixture Models and Multiple CRFs

Semantic image segmentation is a fundamental yet challenging problem, which can be viewed as an extension of the conventional object detection with close relation to image segmentation and classification. It aims to partition images into non-overlapping regions that are assigned predefined semantic labels. Most of the existing approaches utilize and integrate low-level local features and high-level contextual cues, which are fed into an inference framework such as, the conditional random field (CRF). However, the lack of meaning in the primitives (i.e., pixels or superpixels) and the cues provides low discriminatory capabilities, since they are rarely object-consistent. Moreover, blind combinations of heterogeneous features and contextual cues exploitation through limited neighborhood relations in the CRFs tend to degrade the labeling performance. This paper proposes an ontology-based semantic image segmentation (OBSIS) approach that jointly models image segmentation and object detection. In particular, a Dirichlet process mixture model transforms the low-level visual space into an intermediate semantic space, which drastically reduces the feature dimensionality. These features are then individually weighed and independently learned within the context, using multiple CRFs. The segmentation of images into object parts is hence reduced to a classification task, where object inference is passed to an ontology model. This model resembles the way by which humans understand the images through the combination of different cues, context models, and rule-based learning of the ontologies. Experimental evaluations using the MSRC-21 and PASCAL VOC'2010 data sets show promising results.
Graph grammar approach for transforming DATA

In this paper we propose an approach for translating DATA* structure to aggregate regions automaton using graph transformation. However, our approach allows to generate automatically a visual modeling tool for DATA* and the aggregate regions automaton. The cost of building a visual modeling tool from scratch is prohibitive. Meta-modeling approach is useful to deal with this problem since it allows the modeling of the formalisms themselves, by means of graph grammars. The meta-modeling tool AToM3 is used.
Stable Recovery of Sparse Signals Via Regularized Minimization

Suppose we want to recover a vector x<sub>0</sub>isinR<sup>m</sup> from incomplete and contaminated measurements y=Ax<sub>0</sub>+e, where A is a p by m matrix, p<m and e is an error term, parepar<sub>2</sub>=epsiv. In previous work, Donoho et al. (1998), Candes et al. (Commun. Pure Appl.) have shown that if the signal x<sub>0</sub> is sufficiently sparse, it can be recovered stably by lscr<sub>1</sub>-minimization. More precisely, the vector x<sup>#</sup> with minimal lscr<sub>1</sub> norm, constrained by parAx<sup>#</sup>-ypar<sub>2</sub>lesepsiv, satisfies parx<sup>#</sup>-x<sub>0</sub>par<sub>2</sub>lesCepsiv. In the present correspondence it is shown that one can also choose a regularization approach, in which one minimizes the functional parAx-ypar<sub>2</sub> <sup>2</sup>+muparxpar<sub>1</sub>, without additional constraints; its minimizer x* is likewise a good estimate for x<sub>0</sub>, with a bound on parx*-x<sub>0</sub>par<sub>2</sub> proportional to epsiv.
Using Term Location Information to Enhance Probabilistic Information Retrieval

Nouns are more important than other parts of speech in information retrieval and are more often found near the beginning or the end of sentences. In this paper, we investigate the effects of rewarding terms based on their location in sentences on information retrieval. Particularly, we propose a novel Term Location (TEL) retrieval model based on BM25 to enhance probabilistic information retrieval, where a kernel-based method is used to capture term placement patterns. Experiments on five TREC datasets of varied size and content indicate the proposed model significantly outperforms the optimized BM25 and DirichletLM in MAP over all datasets with all kernel functions, and excels the optimized BM25 and DirichletLM over most of the datasets in P@5 and P@20 with different kernel functions.
Proposal of Real Time Predictive Maintenance Platform with 3D Printer for Business Vehicles

This paper proposes a maintenance platform for business vehicles which detects failure sign using IoT data on the move, orders to create repair parts by 3D printers and to deliver them to the destination. Recently, IoT and 3D printer technologies have been progressed and application cases to manufacturing and maintenance have been increased. Especially in air flight industry, various sensing data are collected during flight by IoT technologies and parts are created by 3D printers. And IoT platforms which improve development/operation of IoT applications also have been appeared. However, existing IoT platforms mainly targets to visualize "things" statuses by batch processing of collected sensing data, and 3 factors of real-time, automatic orders of repair parts and parts stock cost are insufficient to accelerate businesses. This paper targets maintenance of business vehicles such as airplane or high-speed bus. We propose a maintenance platform with real-time analysis, automatic orders of repair parts and minimum stock cost of parts. The proposed platform collects data via closed VPN, analyzes stream data and predicts failures in real-time by online machine learning framework Jubatus, coordinates ERP or SCM via in memory DB to order repair parts and also distributes repair parts data to 3D printers to create repair parts near the destination.
The obstetrical and neonatal outcome of babies born after single-embryo transfer in IVF/ICSI compares favourably to spontaneously conceived babies.

BACKGROUND Recently, concern has risen about poor obstetrical and neonatal outcome of singletons after IVF/ICSI. Because the population of patients receiving single-embryo transfer (SET) resulting in singleton pregnancies is different from the one that would have become pregnant (with a singleton) before SET was introduced, we wanted to investigate whether the outcome of singleton pregnancies after SET differed from spontaneously conceived singletons. METHODS The obstetrical and early neonatal outcome of all pregnancies originating from SET after IVF/ICSI procedures between 1 January 1998 and 31 December 2003, was prospectively collected and analyzed. RESULTS Data from 251 singleton pregnancies and births after SET were analyzed and compared to data from 59,535 spontaneously conceived singletons retrieved from the Centre for Perinatal Epidemiology. The mean birthweight of the singletons after SET was 3322 g (+/-538 SD) versus 3330 g (+/-531 SD) for the spontaneously conceived singletons (P = 0.82). The mean gestational age was 38.7 weeks (+/-1.9 SD) for SET and 38.9 weeks (+/-1.8 SD) for spontaneously conceived singletons (P = 0.06). The proportion of very preterm birth (<32 weeks) was 0.8% in each group, and the proportion of preterm birth (<37 weeks) was 10.0% for SET singletons and 6.24% for spontaneous singletons (P = 0.03). However, mean birthweight of very preterm, preterm and term SET singleton babies was similar to the mean birthweight in every category of gestational age in the spontaneous conceived control group. Stillbirth was 0.4% for both populations (P = 0.99). CONCLUSIONS Good prognosis patients, in whom SET is applied, do not only have a higher chance of conception but do not have an unfavourable outcome of their singleton baby when compared to spontaneous singletons.
EXPERIMENTAL AND NUMERICAL INVESTIGATIONS OF STABLY STATIFIED ATMOSPHERIC FLOWS

Statically stable atmospheric flows are characterized by weak and highly anisotropic turbulence, gravity waves, instabilities, and meandering motions that are not observed in neutral or unstable flows. These features complicate both modeling and measurements in stable boundary layers. Nevertheless, these flows remain of considerable importance for a variety of problems including nighttime flow and transport and polar boundary layers and climates. This paper presents experimental and numerical studies of turbulence under stable conditions in the atmospheric boundary layer.
Modulation noradrénergique de l’attention

La neuromodulation apporte une extraordinaire richesse a la dynamique des reseaux de neurones. Parmi les neuromodulateurs du systeme nerveux central, la noradrenaline permettrait de faciliter l'adaptation du comportement face aux variations des contraintes environnementales en modulant l'attention, cette fonction au coeur de la cognition qui nous permet de selectionner l'information la plus pertinente en fonction de notre but. Ce processus complexe qui opere a chaque instant a la fois dans l'espace et le temps, constitue une etape essentielle dans cette adaptation comportementale. Cependant, a ce jour, les mecanismes par lesquels ce neuromodulateur exerce ses effets sur le cerveau sain demeurent mal connus. Mon travail de these a pour objectif d'examiner les determinants comportementaux et les marqueurs neuronaux de l'effet stimulant des agonistes noradrenergiques. La question posee etait : "Comment la noradrenaline agit-elle pour optimiser l'attention? " Pour repondre a cette question, j'ai choisi de combiner la pharmacologie, l'analyse du comportement, et l'imagerie par resonnance magnetique fonctionnelle chez le singe. Un des principaux resultats de mes travaux est que l'administration d'agents noradrenergiques induit une large reorganisation des reseaux cerebraux, qui pourrait etre a l'origine de l'optimisation des reponses comportementales observees parallelement
Developing a New Model for availability Optimization Applied to a Series-Parallel System

Redundancy technique is known as a way to enhance the reliability and availability of non-reparable systems, but for repairable systems, another factor is getting prominent called as the number of maintenance resources. In this study, availability optimization of series-parallel systems is modelled by using Markovian process by which the number of maintenance resources is located into the objective model under constraints such as cost, weight, and volume. Due to complexity of the model as nonlinear programming , solving the model by commercial softwares is not possible, and a simple heuristic method called as simulated annealing is applied. Our main contribution in this study is related to the development of a new availability model considering a new decision variable called as the number of maintenance resources. A numerical simulation is solved and the results are shown to demonstrate the effecienct of the method.
Simulation of pollutant transport using a particle method

Abstract A Lagrangian scheme is presented for the two-dimensional simulation of pollutant transport in a porous medium. The anisotropic extension of the particle strength exchange method is implemented to describe the diffusive–dispersive process. By applying the scheme to a benchmark problem with an analytical solution, the method is shown to be accurate and stable even in the limiting cases of vanishing diffusion–dispersion coefficients and high anisotropy ratios. The scheme is shown to perform well with spatially variable velocity fields also.
Comment on Mariassunta Giannetti and Andrei Simonov: On the determinants of entrepreneurial activity: Social norms, economic environment and individual characteristics

Quite a large body of academic economic research on selfemployment and entrepreneurship has emerged during the last 15 years, perhaps as a consequence of an increased political interest in the subject. Indeed, increased entrepreneurship is seen by many as a potential way of improving an economy’s GDP growth and employment growth. In terms of empirical economic research, the by far most popular research topic has been the determinants of self-employment, i.e. why some individuals are self-employed whereas others are not. In early research, researchers mostly used cross-section data in order to test hypotheses about why someone is self-employed at a given point in time. Owing to endogeneity problems, later research has, to a large extent, made use of longitudinal data. By doing so, it is possible to examine factors that affect the transition into self-employment, using past values of explanatory variables. This approach will mitigate the endogeneity problems (Meyer, 1990). This branch of research has focussed on a number of topics, for example the effect of personal wealth on the probability of becoming self-employed (e.g. Evans and Leighton, 1989; Evans and Jovanovic, 1989; Holtz-Eakin et al., 1994; Lindh and Ohlsson, 1996; Blanchflower and Oswald, 1998; Johansson, 2000; Taylor, 2001), the effect of taxes (Bruce, 2000; Schuetze, 2000), or the effect of family background (Lentz and Laband, 1990; Fairlie, 1999; Dunn and HoltzEakin, 2000; Hout and Rosen, 2000).
Reflections on complexity of ML type reconstruction

This is a collection of some more or less chaotic remarks on the ML type system, definitely not sufficient to fill a research paper of reasonable quality, but perhaps interesting enough to be written down as a note. At the beginning the idea was to investigate the complexity of type reconstruction and typability in bounded order fragments of ML. Unexpectedly the problem turned out to be hard, and finally I obtained only partial results. I do not feel like spending more time on this topic, so the text is not polished, the proofs — if included at all — are only sketched and of rather poor mathematical quality. I believe however, that some remarks, especially those of “philosophical” nature, shed some light on the ML type system and may be of some value to the reader interested especially in the interaction between theory and practice of ML type reconstruction.
Accelerating Symmetric and Asymmetric Ciphers with Register File Extension for Multi-word and Long-word Operation

In this paper, we propose a new register file architecture called the register file extension for multi-word and long-word operation (RFEMLO) to accelerate both symmetric and asymmetric cryptographic algorithms. Based on the idea that most of cryptographic algorithms heavily use multi-word or long-word operations, RFEMLO allows multiple contiguous registers to be specified as a single operand. RFEMLO can be applied to a general purpose processor by providing an instruction set extension and an additional functional unit. To evaluate the performance of RFEMLO, we use Simplescalar/ARM 3.0 (with gcc 2.95.2) and run detailed simulations on various cryptographic algorithms. The simulation results show that we could achieve 83% and 138% performance gain in both symmetric and asymmetric ciphers by applying RFEMLO to a conventional superscalar processor.
Development of a Spoken Dialogue System for accessing Agricultural Information in Telugu

In this paper we describe the development of Mandi Information System, a Telugu spoken dialogue system for obtaining price information of agricultural commodities like vegetables, fruits, pulses, spices, etc. The target users of MIS are primarily the farmers in rural and semiurban areas. Speech recognition is error prone and it is necessary for the dialogue system to make minimum number of errors while acquiring information from a user and also to detect errors (if not correctable) and adopt appropriate strategies. In this paper we suggest an approach to improve the performance and usability of the system by using multiple decoders and contextual information.
Pathogenic variation in isolates of Pseudomonas causing the brown blotch of cultivated mushroom, Agaricus bisporus

Twenty seven bacterial isolates were isolated from superficial brown discolorations on the caps of cultivated Agaricus bisporus. After White Line Assay (WLA) and the assist of Biolog computer-identification system, isolates were divided into groups: (I) comprised ninteen bacterial isolates that positively responded to a Pseudomonas “reactans” reference strain (NCPPB1311) in WLA and were identified as Pseudomonas tolaasii, (II) comprised two isolates which were WLA+ towards the reference strain (JCM21583) of P. tolaasii and were proposed to be P. “reactans”. The third group comprised six isolates, two of which weakly responded to the strain of P. tolaasii and were identified as P. gingeri whereas the other four were WLA-and identified as P. fluorescens (three isolates) and P. marginalis (one isolate). Isolates of P. tolaasii showed high aggressiveness compared with those of P. “reactans” in pathogenicity tests. Cubes of 1 cm3 of A. bisporus turned brown and decreased in size when were inoculated with 10 µl of P. tolaasii suspension containing 108 CFU ml-1, whereas a similar concentration of P. “reactans” caused only light browning. Fifty µl of the same concentration of P. tolaasii isolates gave typical brown blotch symptoms on fresh mushroom sporophores whereas the two P. “reactans” isolates caused superficial light discoloration only after inoculation with 100 µl of the same concentration. Mixture from both bacterial suspensions increased the brown areas formed on the pileus. This is the first pathogenicity report of P. tolasii and P. “reactans” isolated from cultivated A. bisporus in Egypt.