Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Generalized Competitive Modes and Return Maps for Characterizing Different Types of Chaotic attractors in Chen System

The Chen system of equations exhibits Lorenz, Transition, Chen and Transverse 8 type of chaotic attractors depending on the system parameters. Some authors have proposed a generalized competitive mode (GCM) technique to explain the topological difference between the Lorenz attractor and the Chen attractor. In this paper, we show a range of parameter values for which the nature of the topological attractor for the Chen system is not in accordance with that expected from GCM analysis. Instead, we find that return maps can be used to characterize the transition between different types of attractors more reliably.
A Morphology Study of Nanofiller Networks in Polymer Nanocomposites: Improving Their Electrical Conductivity through Better Doping Strategies

A Morphology Study of Nanofiller Networks in Polymer Nanocomposites: Improving Their Electrical Conductivity through Better Doping Strategies Angel Mora Over the past years, research efforts have focused on adding highly conductive nanoparticles, such as carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs), into polymers to improve their electrical conductivity or to tailor their piezoresistive behavior. Resultant materials are typically described by the weight or volume fractions of their nanoparticles. The weight/volume fraction alone is a very global quantity, making it a poor evaluator of a doping configuration. Knowing which particles actually participate in improving electrical conductivity can optimize the doping strategy. Additionally, conductive particles are only capable of charge transfer over a very short range, thus most of them do not form part of the conduction path. Thus, understanding how these particles are arranged is necessary to increase their efficiency. First, this work focuses on polymers loaded with CNTs. A computational modeling strategy based on a full morphological analysis of the CNT network is presented to systematically analyze conductive networks and show how particles are arranged. A definition of loading efficiency is provided based on the results obtained from this morphology analysis. This study provides useful guidelines for designing these types of materials based on important features, such as representative volume element, nanotube tortuosity and length, tunneling cutoff distance, and efficiency. Second, a computational approach is followed to study the conductive network formed by hybrid particles in polymer nanocomposites. These hybrid particles are synthesized by 5 growing CNTs on the surfaces of GNPs. The objective of this study is to show that the higher electrical conductivity of these composites is due to the hybrids forming a segregated structure. Polymers loaded with hybrid particles have shown a higher electrical conductivity compared with classical carbon fillers: only CNTs, only GNPs or mixed CNTs and GNPs. This is done to understand and compare the doping efficiency of the different types of nanoparticles. Finally, some parameters of the hybrid particle are studied: CNT density on GNPs, and CNT and GNP geometries. Recommendations to further improve the composite’s conductivity based on these parameters are presented. It is noted that this work is the first time the hybrid particle is studied through a computational approach.
Study of Plasmon Resonance

Plasma resonance plays an important role in photonic devices, optoelectronic integration, optical sensing, waveguides and biomedicine. So plasmon resonance has become one of the hot spots. In this article, we describe the properties of plasmon resonance, theoretical methods of plasmon resonance in noble metal structures, and some important applications. According to the existing research, the trend of plasmon resonance is analyzed and predicted.
Improve Safety Performance of Un-Signalized Intersections in Oman

Abstract—The main objective of this paper is to provide a new methodology for road safety assessment in Oman through the development of suitable accident prediction models. GLM technique with Poisson or NBR using SAS package was carried out to develop these models. The paper utilized the accidents data of 31 unsignalized T-intersections during three years. Five goodness-of-fit measures were used to assess the overall quality of the developed models. Two types of models were developed separately; the flowbased models including only traffic exposure functions, and the full models containing both exposure functions and other significant geometry and traffic variables. The results show that, traffic exposure functions produced much better fit to the accident data. The most effective geometric variables were major-road mean speed, minor-road 85 percentile speed, major-road lane width, distance to the nearest junction, and right-turn curb radius. The developed models can be used for intersection treatment or upgrading and specify the appropriate design parameters of Tintersections. Finally, the models presented in this thesis reflect the intersection conditions in Oman and could represent the typical conditions in several countries in the middle east area, especially gulf countries.
Micro-EDM Pulse Energy Distribution Ratio Determination

In this paper, a method for determining pulse energy distribution ratio in micro-EDM is presented. The pulse energy distribution ratio is a critical parameter in the EDM process. It determines how much of the total energy of a pulse has been distributed into each electrode and the inter-electrode gap. Instead of measuring the electrode temperature variation (which is very difficult), the method in this paper uses the dimensions of the generated craters to determine the pulse energy distribution ratio. The semi-infinite body with uniform disk heat source conduction model has been applied to simulate the EDM erosion process. By solving the thermal model, the radius of the plasma and the pulse energy distribution ratio can be got. Experiments with the pulse energy from 0.09 μJ to 1.02 μJ show that, the average pulse energy distribution ratio is 9.4% to the anode and is 3.6% to the cathode, respectively. These results agree with other reported EDM literature. Additionally the relationship of the anode crater volume to pulse energy is found to be linear.
Iterative Synchronization of Multiuser Ultra-Wideband Signals

In this paper, two novel iterative chip-level synchronization methods, one blind and the other data-aided, are proposed for chip-interleaved time-hopping (TH) ultra-wideband signals that are subject to intersymbol interference (ISI) and multiple access interference (MAI). Both algorithms are soft-input, soft-output devices which receive the a posteriori probability of each chip from the minimum mean-square error (MMSE) filter that suppresses both ISI and MAI. Using this soft information and the structure of TH codes, the blind synchronizer produces the probabilities of time delays which are fed into the channel decoder. In addition to the knowledge of TH codes and the soft information coming from the MMSE filter, the data-aided synchronizer uses a training sequence in the generation of the probabilities of time delays. Although the channel decoder for chip-interleaved systems is rather simple, here it is redesigned to incorporate the soft information. The resulting receivers perform as well as iterative equalization with perfect timing information, and catch the single-user performance at moderate signal-to-noise ratios.
Epigenetic Inactivation of the BRCA1 Interactor SRBC and Resistance to Oxaliplatin in Colorectal Cancer

Background A major problem in cancer chemotherapy is the existence of primary resistance and/or the acquisition of secondary resistance. Many cellular defects contribute to chemoresistance, but epigenetic changes can also be a cause. Methods A DNA methylation microarray was used to identify epigenetic differences in oxaliplatin-sensitive and -resistant colorectal cancer cells. The candidate gene SRBC was validated by single-locus DNA methylation and expression techniques. Transfection and short hairpin experiments were used to assess oxaliplatin sensitivity. Progression-free survival (PFS) and overall survival (OS) in metastasic colorectal cancer patients were explored with Kaplan–Meier and Cox regression analyses. All statistical tests were two-sided. Results We found that oxaliplatin resistance in colorectal cancer cells depends on the DNA methylation–associated inactivation of the BRCA1 interactor SRBC gene. SRBC overexpression or depletion gives rise to sensitivity or resistance to oxaliplatin, respectively. SRBC epigenetic inactivation occurred in primary tumors from a discovery cohort of colorectal cancer patients (29.8%; n = 39 of 131), where it predicted shorter PFS (hazard ratio [HR] = 1.83; 95% confidence interval [CI] = 1.15 to 2.92; log-rank P = .01), particularly in oxaliplatin-treated case subjects for which metastasis surgery was not indicated (HR = 1.96; 95% CI = 1.13 to 3.40; log-rank P = .01). In a validation cohort of unresectable colorectal tumors treated with oxaliplatin (n = 58), SRBC hypermethylation was also associated with shorter PFS (HR = 1.90; 95% CI = 1.01 to 3.60; log-rank P = .045). Conclusions These results provide a basis for future clinical studies to validate SRBC hypermethylation as a predictive marker for oxaliplatin resistance in colorectal cancer.
Microfluidics co-culture systems for studying tooth innervation

Innervation plays a key role in the development and homeostasis of organs and tissues of the orofacial complex. Among these structures, teeth are peculiar organs as they are not innervated until later stages of development. Furthermore, the implication of neurons in tooth initiation, morphogenesis and differentiation is still controversial. Co-cultures constitute a valuable method to investigate and manipulate the interactions of nerve fibers with their target organs in a controlled and isolated environment. Conventional co-cultures between neurons and their target tissues have already been performed, but these cultures do not offer optimal conditions that are closely mimicking the in vivo situation. Indeed, specific cell populations require different culture media in order to preserve their physiological properties. In this study we evaluate the usefulness of a microfluidics system for co-culturing mouse trigeminal ganglia and developing teeth. This device allows the application of specific media for the appropriate development of both neuronal and dental tissues. The results show that mouse trigeminal ganglia and teeth survive for long culture periods in this microfluidics system, and that teeth maintain the attractive or repulsive effect on trigeminal neurites that has been observed in vivo. Neurites are repealed when co-cultured with embryonic tooth germs, while postnatal teeth exert an attractive effect to trigeminal ganglia-derived neurons. In conclusion, microfluidics system devices provide a valuable tool for studying the behavior of neurons during the development of orofacial tissues and organs, faithfully imitating the in vivo situation.
Autism Spectrum Disorders

Abstract According to Healthy People 2020, one population confronted with health disparities is that of individuals living with disabilities. Among these individuals are children living with autism spectrum disorders (ASDs). Increasing numbers of children in the United States have been diagnosed with ASDs, a group of developmental disorders for which no specific cause or cure has been conclusively identified. Increasing media exposure as well as legislation addressing ASDs reflects the increasing awareness of ASDs as a significant public health issue. However, whereas ASDs have become an issue of great interest to the general public, the amount of health education literature addressing autism spectrum disorders is extremely limited. This paper provides health educators with a review of literature concerning autism spectrum disorders, specifically its background, prevalence, possible causes, symptoms and diagnostic methods. Furthermore, the potential roles played by health educators in serving individuals (e.g., parents, educators, medical providers) who support children with ASDs is suggested through the application of National Commission for Health Education Credentialing, Inc. responsibilities and competencies for health educators.
Impact of Interference in Coexisting Wireless Networks with Applications to Arbitrarily Varying Bidirectional Broadcast Channels

The paradigm shift from an exclusive allocation of frequency bands, one for each system, to a shared use of frequencies comes along with the need of new concepts since interference will be an ubiquitous phenomenon. In this paper, we use the concept of arbitrarily varying channels to model the impact of unknown interference caused by coexisting wireless systems which operate on the same frequencies. Within this framework, capacity can be zero if pre-specified encoders and decoders are used. This necessitates the use of more sophisticated coordination schemes where the choice of encoders and decoders is additionally coordinated based on common randomness. As an application we study the arbitrarily varying bidirectional broadcast channel and derive the capacity regions for different coordination strategies. This problem is motivated by decode-and-forward bidirectional or two-way relaying, where a relay establishes a bidirectional communication between two other nodes while sharing the resources with other coexisting wireless networks.
A Human Action Recognition System for Embedded Computer Vision Application

In this paper, we propose a human action recognition system suitable for embedded computer vision applications in security systems, human-computer interaction and intelligent environments. Our system is suitable for embedded computer vision application based on three reasons. Firstly, the system was based on a linear support vector machine (SVM) classifier where classification progress can be implemented easily and quickly in embedded hardware. Secondly, we use compacted motion features easily obtained from videos. We address the limitations of the well known motion history image (MHI) and propose a new hierarchical motion history histogram (HMHH) feature to represent the motion information. HMHH not only provides rich motion information, but also remains computationally inexpensive. Finally, we combine MHI and HMHH together and extract a low dimension feature vector to be used in the SVM classifiers. Experimental results show that our system achieves significant improvement on the recognition performance.
Processing Panorama Video in Real-time

There are many scenarios where high resolution, wide field of view video is useful. Such panorama video may be generated using camera arrays where the feeds from multiple cameras pointing at different parts of the captured area are stitched together. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent timeliness requirements. In our research, we use panorama video in a sport analysis system called Bagadus. This system is deployed at Alfheim stadium in Tromso, and due to live usage, the video events must be generated in real-time. In this paper, we describe our real-time panorama system built using a low-cost CCD HD video camera array. We describe how we have implemented different components and evaluated alternatives. The performance results from experiments ran on commodity hardware with and without co-processors like graphics processing units (GPUs) show that the entire pipeline is able to run in real-time.
Orthogonal range searching on the RAM, revisited

We present a number of new results on one of the most extensively studied topics in computational geometry, orthogonal range searching. All our results are in the standard word RAM model: We present two data structures for 2-d orthogonal range emptiness. The first achieves O(n lg lg n) space and O(lg lg n) query time, assuming that the n given points are in rank space. This improves the previous results by Alstrup, Brodal, and Rauhe (FOCS'00), with O(n lgε n) space and O(lg lg n) query time, or with O(n lg lg n) space and O(lg2lg n) query time. Our second data structure uses O(n) space and answers queries in O(lgε n) time. The best previous O(n)-space data structure, due to Nekrich (WADS'07), answers queries in O(lg n/lg lg n) time. We give a data structure for 3-d orthogonal range reporting with O(n lg1+ε n) space and O(lg lg n + k) query time for points in rank space, for any constant ε>0. This improves the previous results by Afshani (ESA'08), Karpinski and Nekrich (COCOON'09), and Chan (SODA'11), with O(n lg3 n) space and O(lg lg n + k) query time, or with O(n lg1+εn) space and O(lg2lg n + k) query time. Consequently, we obtain improved upper bounds for orthogonal range reporting in all constant dimensions above 3. Our approach also leads to a new data structure for 2D orthogonal range minimum queries with O(n lgε n) space and O(lg lg n) query time for points in rank space. We give a randomized algorithm for 4-d offline dominance range reporting/emptiness with running time O(n log n) plus the output size. This resolves two open problems (both appeared in Preparata and Shamos' seminal book): given a set of n axis-aligned rectangles in the plane, we can report all k enclosure pairs (i.e., pairs (r1,r2) where rectangle r1 completely encloses rectangle r2) in O(n lg n + k) expected time; given a set of n points in 4-d, we can find all maximal points (points not dominated by any other points) in O(n lg n) expected time. The most recent previous development on (a) was reported back in SoCG'95 by Gupta, Janardan, Smid, and Dasgupta, whose main result was an O([n lg n + k] lg lg n) algorithm. The best previous result on (b) was an O(n lg n lg lg n) algorithm due to Gabow, Bentley, and Tarjan---from STOC'84! As a consequence, we also obtain the current-record time bound for the maxima problem in all constant dimensions above~4.
The Mold-Specific MS8 Gene Is Required for Normal Hypha Formation in the Dimorphic Pathogenic Fungus Histoplasma capsulatum

ABSTRACT The dimorphic fungus Histoplasma capsulatum is the etiologic agent of one of the most common systemic mycoses of humans, histoplasmosis. In the environment, H. capsulatum grows in a differentiated mold form and shifts to an undifferentiated yeast form after mold fragments or spores are inhaled. This mold-to-yeast shift is required for disease. Little is known about the molecular biology of dimorphism in Histoplasma, and most studies have been directed toward yeast-specific genes. While it is important to examine the role of genes upregulated in the yeast morphotype, genes which are silenced in the yeast (i.e., mold-specific genes) may also play a critical role in dimorphism. To begin to examine this hypothesis, we report here the first misexpression and knockout analysis of a mold-specific gene in Histoplasma. The strongly expressed MS8 gene encodes a predicted 21-kDa protein extremely rich in glycine and glutamine. Forced expression of MS8 driven by the TEF1 promoter in yeast did not alter the yeast morphology at 37°C or mold formation at 25°C. Yeast expressing MS8 did exhibit clumping in liquid medium and formed “sticky” colonies on agar plates. Allelic replacement of MS8 was accomplished by a positive-negative selection procedure. ms8 knockout mutants formed apparently normal yeast at 37°C but gave rise to aberrant mycelia at 25°C. The mold colonies of the knockouts were less than half as large as normal, had a granular surface, produced a dark-red pigment, and formed short hyphae which were 40% wider with a distinctive twisted “zig-zag” shape.
A roadmap of nature-inspired systems research and development

Nature-inspired algorithms such as genetic algorithms, particle swarm optimisation and ant colony algorithms have successfully solved computer science problems of search and optimisation. The initial implementations of these techniques focused on static problems solved on single machines. These have been extended by adding parallelisation capabilities in the vein of distributed computing with a centralised master/slave approach. However, the natural systems on which nature-inspired algorithms are based possess many additional characteristics that are of potential benefit within computing environments. In this paper, we discuss the benefits of nature-inspired techniques within modern and emerging computing environments. Software entities within these environments execute and interact in a fashion that is parallel, asynchronous, and decentralised. Given that the natural environment is in itself parallel, asynchronous and decentralised, nature-inspired techniques are an excellent fit for computing environments that exhibit these characteristics. Future research challenges for nature-inspired techniques within emerging computing environments are also discussed.
A real time classifier for emotion and stress recognition in a vehicle driver

Recently there is a great interest in artificial systems able to understand and recognize human emotions. In this paper an Emotion Recognition System based on classical neural networks and neuro-fuzzy classifiers is proposed. Emotion recognition is performed in real time starting from a video stream acquired by a common webcam monitoring the user's face. Neurofuzzy classifiers, in comparison with Multi Layer Perceptron trained by EBP algorithm, show very short training times, allowing applications with easy and automated set up procedures, to be used in a wide range of applications, from entertainment to safety. The algorithm yields very interesting performances and can be adopted to recognize emotions as well as possible pathological conditions of the individual to be monitored.
VOLATILITY PATTERNS OF THE LARGEST POLISH COMPANIES: SOME EVIDENCE FROM HIGH-FREQUENCY DATA

Purpose. The article is focused on the empirical properties of the high-frequency data of 20 selected stocks from the Warsaw Stock Exchange (in particular the ones listed on WIG 20). The intraday data from at least more than 1 year were analysed. In particular, correlation between returns and durations were checked. Methodology. Also, the heterogeneous autoregressive model for realized volatility (HAR) was analysed and an attempt to construct the UHF-GARCH model was taken. The HAR model is a linear model and the UHF-GARCH is based on a certain adjustment of physical durations. Then, the standard ARMA-GARCH approach can be considered. Moreover, the hypothesis of Diamond and Verrecchia predicting a negative correlation between price changes and the time passed between transactions was checked. The analysis was done in R statistical software. Findings. The presented research can serve as an introduction to some further (and more thorough and narrow) researches. Except a direct presentation of outcomes from the study of the selected stocks from the Warsaw Stock Exchange, the paper contains quite an extensive literature review on high-frequency data.
Variational Design with Parametric Meshes of Arbitrary Topology

Many mathematical problems in geometric modeling are merely due to the di culties of handling piecewise polynomial parameterizations of surfaces (e.g., smooth connection of patches, evaluation of geometric fairness measures). Dealing with polygonal meshes is mathematically much easier although in nitesimal smoothness can no longer be achieved. However, transferring the notion of fairness to the discrete setting of triangle meshes allows to develop very e cient algorithms for many speci c tasks within the design process of high quality surfaces. The use of discrete meshes instead of continuous spline surfaces is tolerable in all applications where (on an intermediate stage) explicit parameterizations are not necessary. We explain the basic technique of discrete fairing and give a survey of possible applications of this approach.