Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning by Exploration and Cooperation in Dynamic Agencies

The building of cooperative multi-agent systems is an issue of growing importance in the field of Distributed Artificial Intelligence. We introduce a type of agency, called dynamic agency, that overcomes the critical problem of having agents that have both several specific operation functions, and one uniform cooperation ability. A dynamic agency is also suited to give flexibility with respect to classes of problems that can be addressed by the agency. Dynamic agencies are built from intelligent agents only providing operations (Fixed Intelligent Agents) that are visited by an intelligent agent carrying cooperation (Mobile Intelligent Agent), which replicates itself together with each fixed agent, in order to complete the agency based on a biagent fixed-mobile structure. The aim of the paper is to illustrate two relevant learning aspects that are of basic importance in constructing dynamic agencies. The first one is the exploration of fixed intelligent agents performed by a visiting mobile agent, namely the sequence of extraction of knowledge from fixed intelligent agents and organization of cooperation. The second learning aspect is related to the construction, called cooperation, of the strategic planner of the dynamic agency, that is devoted to decompose an agency problem in simpler agent sub-problems tackled by tactical planners.
Research of Communication Signal Modulation Scheme Recognition Based on One-Class SVM Bayesian Algorithm

This paper proposed a digital signal modulation scheme recognition method using a novel one-class SVM based multi-class Bayesian classification algorithm. It is proven that the solution of one-class SVM using the Gaussian kernel can be normalized as an estimate of probability density, and the probability density is used to construct the two-class and multi-class Bayesian classifier. The statistical characterization parameters of the multi communication signals are extracted as the input feature vectors of the one-class SVM. Experimental result showed that the correct mod scheme classification probability of the proposed classifier is comparable to traditional multi-class SVM classifier. In the condition of SNR=5dB, the recognition probability is 98.13%. However, in the case of multi-class signal recognition and large amount of training samples of each communication signal class, the calculation amount of training and storage is only 0.5 percent of the traditional SVM classifier, which leads to less training time for the proposed classifier, and can be widely used in on-line recognition software radio system.
Match outcome vs match status and frequency of selected technical activities of soccer players during UEFA Euro 2016

ABSTRACT The study aimed to examine the performance frequency of selected technical activities by soccer teams playing in the UEFA EURO 2016 in relation to match outcome and match status. Thirty-six matches of the group stage were analysed. The data were retrieved using an OPTA Sportsdata Company system. The notated technical activities: shots, passes, were expressed as frequency of performance (playing time/number of activities); while ball possession was expressed in percentage terms. There was a large effect size in frequency of shots on target (η2 = 0.201), of shots from inside the penalty area (η2 = 0.163) in relation to match outcome. A medium effect size was then found in frequency of passes (η2 = 0.102), short passes (η2 = 0.060) and ball possession (η2 = 0.113) in relation to match status. A team’s playing effectiveness requires a concurrent scrutiny of players’ technical activities in relation to match outcome and match status. Key technical activities affecting a successful match outcome are frequencies of different types of shots. However, when the team is playing to change an unfavourable score (losing and drawing in match status), the most important are frequencies of different types of passes and higher percent of ball possession.
Crystal image segmentation based on gray distribution steepest descent method

In the image-based monitoring and control of crystallization process, effective crystal image segmentation is a basis for crystal object recognition and measurement. In this paper, a new threshold segmentation algorithm based on gray distribution steepest descent method is presented according to the unimodal characteristics of the black background crystal images. The image segmentation threshold is selected to be the fastest decline point on the probability density function of the crystal image's gray distribution. The experimental results demonstrate the effectiveness and superiority of the proposed approach compared with the current image segmentation algorithms.
Comparison of secretory protein profiles in developing rat pancreatic rudiments and rat acinar tumor cells

We have previously established that secretory proteins from a rat acinar cell tumor lack two forms of procarboxypeptidase B, are deficient in a major lipase species, and possess markedly reduced amounts of the basic proteins proelastase, basic chymotrypsinogen, basic trypsinogen and ribonuclease (Iwanij, V., and J.D. Jamieson, J. Cell Biol., 95:734-741). Because secretory proteins are markers for acinar cell differentiation, we sought to establish whether the secretory protein profile of the acinar cell tumor is unique to the transformed cell or whether it resembles that of a stage of normal pancreatic development. To this end, we compared the secretory protein pattern from acinar tumor cells with that of rat pancreatic rudiments at days 19-22 of gestation and through day 21 of the postnatal period. Two-dimensional IEF-SDS gel electrophoresis coupled with biosynthetic labeling and fluorography indicates a time-dependent appearance of individual secretory proteins with basic polypeptides, except for amylase, appearing in the terminal stages of differentiation. In comparison, the secretory protein pattern of the acinar tumor cells most closely resembles that of day-19 embryonic pancreatic rudiments. We propose that the cells of the acinar cell tumor may, in part, mirror a stage of normal pancreatic development.
DISSIPATION AND EXTRA LIGHT IN GALACTIC NUCLEI. II. “CUSP” ELLIPTICALS

We study the origin and properties of “extra” or “excess” central light in the surface brightness profiles of cusp or power-law elliptical galaxies. Dissipational mergers give rise to two-component profiles: an outer profile established by violent relaxation acting on stars already present in the progenitor galaxies prior to the final stages of the merger, and an inner stellar population comprising the extra light, formed in a compact central starburst. By combining a large set of hydrodynamical simulations with data that span a broad range of profiles at various masses, we show that observed cusp ellipticals appear consistent with the predicted “extra light” structure, and we use our simulations to motivate a two-component description of the observations that allows us to examine how the properties and mass of this component scale with, e.g., the mass, gas content, and other properties of the galaxies. We show how to robustly separate the physically meaningful extra light and outer, violently relaxed profile, and demonstrate that the observed cusps and “extra light” are reliable tracers of the degree of dissipation in the spheroid-forming merger. We show that the typical degree of dissipation is a strong function of stellar mass, roughly tracing the observed gas fractions of disks of the same mass over the redshift range z ∼ 0–2. We demonstrate a correlation between the strength of this component and effective radius at fixed mass, in the sense that systems with more dissipation are more compact, sufficient to explain the discrepancy in the maximum phase-space and mass densities of ellipticals and their progenitor spirals. We show that the outer shape of the light profile in simulated and observed systems (when fit to properly account for the central light) does not depend on mass, with a mean outer Sérsic index ∼2.5. We also explore how this relates to, e.g., the shapes, kinematic properties, and stellar population gradients of ellipticals. Extra light contributes to making remnants rounder and diskier, and imprints stellar population gradients. Simulations with the gas content needed to match observed surface brightness profiles reproduce the observed age, metallicity, and color gradients of cusp ellipticals, and we make predictions for how these can be used as tracers of the degree of dissipation in spheroid formation.
Sparse Neural Networks With Large Learning Diversity

Coded recurrent neural networks with three levels of sparsity are introduced. The first level is related to the size of messages that are much smaller than the number of available neurons. The second one is provided by a particular coding rule, acting as a local constraint in the neural activity. The third one is a characteristic of the low final connection density of the network after the learning phase. Though the proposed network is very simple since it is based on binary neurons and binary connections, it is able to learn a large number of messages and recall them, even in presence of strong erasures. The performance of the network is assessed as a classifier and as an associative memory.
3D facial model synthesis using coupled dictionaries

In this work, we propose a generative way of modeling faces, where the 3D shape of a face is generated by a supervised learning procedure involving coupled sparse feature learning. To learn dictionaries using the proposed method, we use the USF-HUMAN ID database [1]. We provide as input to our training system, paired correspondences of 2D and 3D images of individuals and aim to learn the low-level patches both in 2D and 3D domains that describe the corresponding subspaces in a sparse manner. We demonstrate the efficacy of our method by quantitative results on the 3D database and qualitative results on images drawn from the internet.
Usability studies on a visualisation for parallel display and control of alternative scenarios

Many applications require comparison between alternative scenarios; most support it poorly. A subjunctive interface supports comparison through its facilities for parallel setup, viewing and control of scenarios. To evaluate the usability and benefits of these facilities, we ran experiments in which subjects used both a simple and a subjunctive interface to make comparisons in a census data set. In the first experiment, subjects reported higher satisfaction and lower workload with the subjunctive interface, and relied less on interim marks on paper. Subjects also used fewer interface actions. However, we found no reduction in task completion time, mainly because some subjects encountered problems in using the facilities for setting up and controlling scenarios. Based on a detailed analysis of subjects' actions we redesigned the subjunctive interface to alleviate frequent problems, such as accidentally adjusting only one scenario when the intention was to adjust them all. At the end of a second, five-session experiment, users of this redesigned interface completed tasks 27% more quickly than with the simple interface.
Soft-Decision List Decoding with Linear Complexity for the First-Order Reed-Muller Codes

Soft-decision decoding on a memoryless channel is considered for the first-order Reed-Muller codes RM(1,m) of length 2m. We assume that different positions j of the received binary vector y can be corrupted by the errors of varying weight Wj. The generalized Hamming distance between vector y and any binary vector c is then defined as the sum of weighted differences Wj|yj - Cj| taken over all n positions. We obtain a tight upper bound Lt on the number of codewords located within generalized Hamming distance T from vector y, and design a decoding algorithm that outputs this list of codewords with complexity O(n In2 Lt)- In particular, all possible error weights wj equal 1 if this combinatorial model is applied to a binary symmetric channel. In this case, the well known Green algorithm performs full maximum likelihood decoding of RM(1,m) and requires O(n ln2 n) bit operations, whereas the Litsyn-Shekhovtsov algorithm operates within the bounded-distance decoding radius n/4 - 1 with linear complexity O(n). We close the performance-complexity gap between the two algorithms. Namely, for any fixed epsi isin (0, frac12), our algorithm outputs the complete list of codewords within the decoding radius n(frac12 - epsi) with linear complexity of order n ln2 epsi.
Shifting Gears: User Interfaces in the Age of Autonomous Driving

The field of automotive user interfaces has developed rapidly over the last several years. To date, the field has primarily focused on creating user interfaces that promote safe driving, including when the driver is engaged in a secondary task in addition to operating the vehicle. However, researchers now need to prepare for a major change in the automotive domain: the automated driving revolution. The authors argue for a new research agenda that focuses on four challenges for automotive user interfaces: assuring safety in the age of automation, transforming vehicles into places for productivity and play, taking advantage of new mobility options made possible by automated vehicles, while throughout all this preserving user privacy and data security. This article is part of a special issue on smart vehicle spaces.
An improved selective spatio-temporal interest point detector

In the recent years, human activity recognition is considered to be very important in video analysis researches due to the extensive requests from numerous users in different fields, such as public area surveillance, entertainment, human machine interaction and healthcare systems. In this work, we present a comparative study of two space-time interest points' detectors. These two detectors are evaluated using different noise attacks such as scale change, illumination change and rotation. The performance of our approach is justified by good matching results.
A Combined Molecular Docking/Dynamics Approach to Probe the Binding Mode of Cancer Drugs with Cytochrome P450 3A4

Cytarabine, daunorubicin, doxorubicin and vincristine are clinically used for combinatorial therapies of cancers in different combinations. However, the knowledge about the interaction of these drugs with the metabolizing enzyme cytochrome P450 is limited. Therefore, we utilized computational methods to predict and assess the drug-binding modes. In this study, we performed docking, MD simulations and free energy landscape analysis to understand the drug-enzyme interactions, protein domain motions and the most populated free energy minimum conformations of the docked protein-drug complexes, respectively. The outcome of docking and MD simulations predicted the productive, as well as the non-productive binding modes of the selected drugs. Based on these interaction studies, we observed that S119, R212 and R372 are the major drug-binding residues in CYP3A4. The molecular mechanics Poisson–Boltzmann surface area analysis revealed the dominance of hydrophobic forces in the CYP3A4-drug association. Further analyses predicted the residues that may contain favorable drug-specific interactions. The probable binding modes of the cancer drugs from this study may extend the knowledge of the protein-drug interaction and pave the way to design analogs with reduced toxicity. In addition, they also provide valuable insights into the metabolism of the cancer drugs.
The influence of femoral internal and external rotation on cartilage stresses within the patellofemoral joint

Internal and external rotation of the femur plays an important role in defining the orientation of the patellofemoral joint, influencing contact areas, pressures, and cartilage stress distributions. The purpose of this study was to determine the influence of femoral internal and external rotation on stresses in the patellofemoral cartilage. We constructed finite element models of the patellofemoral joint using magnetic resonance (MR) images from 16 volunteers (8 male and 8 female). Subjects performed an upright weight‐bearing squat with the knee at 60° of flexion inside an open‐MR scanner and in a gait laboratory. Quadriceps muscle forces were estimated for each subject using an electromyographic‐driven model and input to a finite element analysis. Hydrostatic and octahedral shear stresses within the cartilage were modeled with the tibiofemoral joint in a “neutral” position and also with the femur rotated internally or externally by 5° increments to ±15°. Cartilage stresses were more sensitive to external rotation of the femur, compared with internal rotation, with large variation across subjects. Peak patellar shear stresses increased more than 10% with 15° of external rotation in 75% of the subjects. Shear stresses were higher in the patellar cartilage compared to the femoral cartilage and patellar cartilage stresses were more sensitive to femoral rotation compared with femoral cartilage stress. Large variation in the cartilage stress response between individuals reflects the complex nature of the extensor mechanism and has clinical relevance when considering treatment strategies designed to reduce cartilage stresses by altering femoral internal and external rotation. © 2008 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res
S-Parameter Analysis of GaN Schottky Diodes for Microwave Power Rectification

A gallium nitride (GaN) Schottky diode on semi-insulating SiC has been developed for microwave power rectification. A 2 μm x 100 μm finger type diode shows ON resistance of 8.2 Ω and depletion capacitance of 0.36 pF at 0 V with breakdown voltage of 90 V. S-parameter analysis separated the ON resistance into the intrinsic part and the access region part, which will benefit device optimization. With a 10-finger diode, RF/DC conversion efficiency of 74.4% is obtained at input power of 5 W and frequency of 2.45 GHz.
Carbon Footprint versus Performance of Aluminum, Plastic, and Wood Window Frames from Cradle to Gate

Window frame material has significant impact on the thermal performance of the window. Moreover, with sustainable design becoming a necessity, window frame materials need to have higher levels of environmental performance to be considered sustainable. As a result, a holistic performance metric is needed to assess window frame material. Three similar frames were considered, manufactured from aluminum, polyvinyl chloride (PVC), and wood. First their thermal performance was evaluated and compared using a heat transfer model. Then, carbon footprints of the three materials were considered for 1m2 of window area with a similar thermal performance. It was found that the thermal, as well as the environmental, performance of the wooden window frame was superior to those of aluminum and PVC. On the other hand aluminum frames had high environmental impacts and comparatively lower thermal performance. This study provides a holistic viewpoint on window frames by considering both environmental and thermal performance.
Associations between urinary phthalate monoesters and thyroid hormones in pregnant women.

BACKGROUND Maternal hypothyroidism during pregnancy can cause adverse effects in the fetus. Scientific evidence has shown that probable thyroid-like function of some phthalates in vitro and in vivo, and phthalates exposure, can begin in utero. This study investigated the association between phthalate exposure and thyroid hormones in pregnant women. METHODS Serum and spot urine samples were collected from 76 Taiwanese pregnant women at second trimester. Thyroid hormones, including thyroid-stimulating hormone (TSH), triiodothyronine (T(3)), thyroxine (T(4)) and free T(4) (FT(4)) were analysed in serum samples, and five urinary phthalate monoesters, including mono butyl phthalate (MBP), monoethyl phthalate (MEP) and mono ethylhexyl phthalate (MEHP), were measured. RESULTS Urinary MBP, MEP and MEHP, the median levels of which were 81.8, 27.7 and 20.6 ng/ml, respectively, were the predominant substances in the urinary phthalate monoesters. Significant mild negative correlations were found between T(4) and urinary MBP (R = -0.248, P < 0.05), and between FT(4) and urinary MBP (R = -0.368, P < 0.05). After adjusting for age, BMI and gestation, urinary MBP levels showed negative associations with FT(4) and T(4) (FT(4): beta = -0.110, P < 0.001; T(4): beta=-0.112, P = 0.003). CONCLUSIONS Exposure to di-n-butyl phthalate (DBP) may affect thyroid activity in pregnant women, but how DBP affects thyroid function is unclear. Further studies are needed to elucidate the mechanism of action and to investigate whether any other factors related to DBP exposure alter the thyroid function.
An approach for solving multi-objective assignment problem with interval parameters

Article history: Received March 2 2014 Accepted 29 July 2014 Available online July 31 2014 This paper presents a multi-objective assignment problem (MAP) with interval parameters. Here, the model concentrates on three criteria: total cost, total profit and total operation time of assignment. The proposed model is classified as a nonlinear programming, in which it is difficult to solve. Hence, the model is converted into crisp linear programming problem by applying a substitution variables approach. In addition, a weighted min-max method is applied to transform the multi-objective problem into a single objective optimization problem. Finally, several numerical examples are provided to illustrate the implementation of the proposed approach. The results clearly provide some evidences that the proposed approach was easier to contrast compared with other approaches. The results also indicate that decision makers’ preferences over various objectives could influence on solutions. © 2014 Growing Science Ltd. All rights reserved.
Blind equalization of SIMO FIR channels driven by colored signals with unknown statistics

We consider the blind equalization of single-input multiple-output finite impulse response channel driven by colored signals. The statistics of the input colored signals are unknown a priori. By exploiting the inherent structural relationship between the source autocorrelation matrices of different delay lags, the closed-form zero-forcing and minimum mean-square-error equalizers of desired delays are estimated from the second-order statistics of the received data. The blind equalizability conditions of the proposed method are investigated. Numerical simulation results are presented to illustrate the performance of the proposed algorithm.