Miracle-dz/UniFAR-FTUs huggingface dataset:
Deforming mandibular osteomyelitis in a cow caused by Trueperella pyogenes

This study reports an unusual case of deforming mandibular osteomyelitis in a cow caused by Trueperella (Arcanobacterium) pyogenes, on the face of the ventrolateral caudal portion of the right branch of the mandible. Fragment aspired of lesion by fine needle allowed cytological characterization, isolation and identification of T. pyogenes. Radiographic examination showed marked periosteal reaction in the right mandible, numerous lytic areas and cortical bone destruction. Despite of treatment based on in vitro antimicrobial sensitivity test, it was recommended the euthanasia due to progressive worsening of the cow's condition. Multiple abscesses were observed in the mandibular region at necropsy. Pyogranuloma was characterized in histological exam. Sampled material collected from the lesion after necropsy resulted in microbiological reisolation of T. pyogenes
Parametrización alternativa de Youla

En este articulo se propone una version especial de la parametrizacion de Youla para plantas inestables. El tema es articulado en la parametrizacion de todas las sensibilidades de todos aquellos lazos de control internamente estables para una planta dada. La propuesta incluye el caso de plantas de tiempo discreto estables e inestable, escalares (SISO) y multivariadas (MIMO).
ORGANIZATIONAL LEARNING IN RESEARCH AND DEVELOPMENT CENTERS IN DEVELOPING ECONOMIES: THE INFLUENCE OF INSTITUTIONAL CONTEXTS

The evolving role of public research institutes in the world in the recent decades has placed significant challenges for them. Governments and stakeholders continue to question their relevance and their ability to adapt to the changing circumstances and demands from society. Attempts to develop new organizational models and management strategies are common in both developed and emerging economies. Public R&D laboratories are thus faced with the need to undertake rapid organizational learning processes in order to adapt and to maintain legitimacy. However, these learning processes may be more complex and difficult when the institutional arrangements in which these organizations are nested are themselves immature. We present an analysis of those learning processes on the basis organizational case studies in Mexico and abroad. Theoretical and policy issues are discussed.
Horizontal and Vertical Intra-Industry Trade between the Former CEFTA Countries and the European Union

This paper analyses the production structure or intra-industry trade specialization (IIT) of the Czech Republic, Hungary, Poland, Slovenia and Slovakia in foreign trade with EU member states from 1995 to 2001 at the five-digit level of the SITC. The results confirmed that former CEFTA countries in general showed IIT specialization in the production of vertically differentiated products of lower quality either at the aggregate level of the manufacturing sectors (i.e. SITC 5–8) or at the level of the twenty chosen manufacturing activities (i.e. divisions 17–36 of the ISIC) and that differences also exist between IIT specializations of these countries.
On the nature of chaos

Based on newly discovered properties of the shift map (Theorem 1), we believe that chaos should involve not only nearby points can diverge apart but also faraway points can get close to each other. Therefore, we propose to call a continuous map $f$ from an infinite compact metric space $(X, d)$ to itself chaotic if there exists a positive number $\delta$ such that for any point $x$ and any nonempty open set $V$ (not necessarily an open neighborhood of $x$) in $X$ there is a point $y$ in $V$ such that $\limsup_{n \to \infty} d(f^n(x), f^n(y)) \ge \delta$ and $\liminf_{n \to \infty} d(f^n(x), f^n(y)) = 0$.
Patients' perception of doctor-patient health communication in a rural community

Effective communication between healthcare provider and patient is crucial, yet research indicates that this communication relationship is often unsatisfactory in both developed and developing countries. Several studies exist on provider-patient communication, but a synthesis of findings on ideal communication appears to be lacking. Thus, this study argues that health literacy and effective communication are important catalysts to enhance the coordinated management of meaning in health communication. For this study, in-depth interviews were conducted in the Mafikeng community in South Africa’s North-West province to collate a variety of patients’ perspectives on the challenges they face when communicating with doctors. Recurrent among the findings were semantic, psychological, physiological, institutional and structural barriers that could hinder effective communication. Practical implications are that all stakeholders should be proactive in promoting effective health communication. Theoretical implications have a bearing on policy formulation, implementation and revision, particularly the indigenous language policy to promote research on the development of medical terminology in indigenous languages.
A state-of-the-art review on magnetorheological elastomer devices

During the last few decades, magnetorheological (MR) elastomers have attracted a significant amount of attention for their enormous potential in engineering applications. Because they are a solid counterpart to MR fluids, MR elastomers exhibit a unique field-dependent material property when exposed to a magnetic field, and they overcome major issues faced in magnetorheological fluids, e.g. the deposition of iron particles, sealing problems and environmental contamination. Such advantages offer great potential for designing intelligent devices to be used in various engineering fields, especially in fields that involve vibration reduction and isolation. This paper presents a state of the art review on the recent progress of MR elastomer technology, with special emphasis on the research and development of MR elastomer devices and their applications. To keep the integrity of the knowledge, this review includes a brief introduction of MR elastomer materials and follows with a discussion of critical issues involved in designing magnetorheological elastomer devices, i.e. operation modes, coil placements and principle fundamentals. A comprehensive review has been presented on the research and development of MR elastomer devices, including vibration absorbers, vibration isolators, base isolators, sensing devices, and so on. A summary of the research on the modeling mechanical behavior for both the material and the devices is presented. Finally, the challenges and the potential facing magnetorheological elastomer technology are discussed, and suggestions have been made based on the authors’ knowledge and experience.
EFFECTS OF A SEVERE COLD EVENT ON THE SUBTROPICAL, ESTUARINE— DEPENDENT COMMON SNOOK, CENTROPOMUS UNDECIMALIS

The effects of infrequent disturbance events on marine fishes are often difficult to determine, due largely to lack of sufficient pre— and post—disturbance event data. In January 2010, subtropical southwestern Florida (USA) experienced extreme cold for 13 days, which caused extensive mortality of many fish species. The effect of this severe cold event on common snook ( Centropomus undecimalis), an economically important gamefish, was assessed using three years (2007—2009) of pre—event and one year (2010) of post—event data from a tag—recapture program conducted over 28 km of Gulf of Mexico barrier islands of Florida. All metrics pointed to a significant effect of the severe cold event: post—disturbance apparent survival of marked fish was 96—97% lower than pre—disturbance, and post—disturbance common snook abundance was 75.57% and 41.88% less than in 2008 and 2009, the two years immediately pre—event. Although severe cold events have impacted subtropical Florida in the past, these events are infrequent (the previous recorded event was >30 years prior), and documentation of the impacts on common snook have not previously been published.
Deep Learning for Actor-Critic Reinforcement Learning

Reinforcement Learning (RL) is a framework to deal with decision-making problems with the goal of finding optimal control policies. Robotics decision-making problems are of importance and provide interesting applications for reinforcement learning; however, since real-world robots have many degrees of freedom, high-dimensionality arises when applying reinforcement learning algorithms. Deep Neural Networks (DNNs) have the potential to reduce the high-dimensional state spaces without losing information. A low-dimensional representation is generated by training a multilayer neural network with a small central layer to reconstruct high-dimensional input vectors. Backpropagation algorithms can be used to tune the weightings in this neural network with the help of the gradient descent method. The objective of this project is to develop approaches of applying deep neural networks with reinforcement learning, hereby, efficiently generating dynamic policies in robot motion-control applications. More specifically, the objective of this project is to overcome the high-dimensionality challenge in reinforcement learning with the help of deep neural networks, a stacked auto-encoder, and using various types of sensory inputs like angles and angular velocities in the manipulator. Experimentally, a simple segway system, which consists of a link and a wheel, is used to test performance. The main approach to improve the learning performance is to develop a low-dimensional representation replacing the original inputs that describe the current states of the segway system in the learning process and using a stacked auto-encoder instead. Xueli Jia Delft, July 2015
Fatty acid profiles in different fish species in Lake Baikal

The fatty acid (FA) composition in the heart tissue and white muscle of 13 species/ecoforms of Lake Baikal fish was determined. All the FAs usually found in freshwater or marine fish were detected in both tissues of all species studied. White muscle con- tained lower levels of saturated and monounsatu- rated FAs (SAFAs and MUFAs), and higher levels of poly unsaturated FAs (PUFAs) than heart tissue. The n3/n6 PUFA ratio ranged between 1.3 and 3.2 in heart tissue and 1.4 and 6.6 in white muscle, typical for fresh- water fish. The most prominent n3 PUFAs, 20:5n3 and 22:6n3, occurred at levels comparable to those found in corresponding species in other freshwater lakes and rivers and also in marine fish. The FA compositions were species specific, following the taxonomic distinc- tion between the species. Apparently, dietary FAs are modified significantly through the metabolism of the fish to produce the species-specific FA composition necessary for the structural lipids of heart tissue and white muscle.
Indirect estimation of GARCH models with alpha-stable innovations

Several studies have highlighted the fact that heavy-tailedness of asset returns can be the consequence of conditional heteroskedasticity. GARCH models have thus become very popular, given their ability to account for volatility clustering and, implicitly, heavy tails. However, these models encounter some difficulties in handling financial time series, as they respond equally to positive and negative shocks and their tail behavior remains too short even with Student-t error terms. To overcome these weaknesses we apply GARCH-type models with alpha-stable innovations. The stable family of distributions constitutes a generalization of the Gaussian distribution that has intriguing theoretical and practical properties. Indeed it is stable under addiction and, having four parameters, it allows for asymmetry and heavy tails. Unfortunately stable models do not have closed likelihood function, but since simulated values from α-stable distributions can be straightforwardly obtained, the indirect inference approach is particularly suited to the situation at hand. In this work we provide a description of how to estimate a GARCH(1,1) and a TGARCH(1,1) with symmetric stable shocks using as auxiliary model a GARCH(1,1) with skew-t innovations. Monte Carlo simulations, conducted using GAUSS, are presented and finally the proposed models are used to estimate the IBM weekly return series as an illustration of how they perform on real data.
Lifestyle factors, dietary quality and health: Econometric evidence from US micro data

Summary – The study applies household production theory to investigate how socioeconomic characteristics and behavioural choices affect health status of an individual (here related to cardiovascular diseases). Structural equation modelling (SEM) is used as an estimation approach, which allows to model health inputs as endogenous variables, to test the hypothesized linkages among them (e.g., between smoking and weight) and to investigate their contribution to a production of a particular health state. Moreover, direct effects of exogenous personal characteristics on health can be disentangled from their indirect impact via lifestyle choices. To improve its measurement properties, health status is modelled via SEM as a latent variable. The results indicate a multidimensionality of cardiovascular health, which is more adequately represented by a two-factor latent variable model rather than by a single-factor model. Moreover, the specified two health dimensions (hypertension and lipids) are (partly) differently explained by the model variables. While higher weight negatively and significantly impacts both health dimensions, a diet rich in F&V (Fruit & Vegetable) has stronger contribution to a lower hypertension risk. At the same time, higher educational level showed to be rather related to lower measurements of blood fat. A special focus in the model is given to the (in)direct impact of education and income. Both variables showed to be related to less frequent smoking and engaging in sedentary leisure time activities. However, their impact on diet was rather indirect through their positive contribution to nutrition knowledge.
Locating Distributed Leadership

This special issue addresses a number of the key themes that have been surfacing from the literature on distributed leadership (DL) for some time. Together with those papers selected to be included in this special issue, the authors set out both to explore and contribute to a number of the current academic debates in relation to DL, while at the same time examining the extent to which research on DL has permeated the management field. The paper examines a number of key concepts, ideas and themes in relation to DL and, in so doing, highlights the insights offered through new contributions and interpretations. The paper offers a means by which forms of DL might be conceptualized to be better incorporated into researchers' scholarship and research, and a framework is presented which considers a number of different dimensions of DL, how it may be planned, and how it may emerge, together with how it may or may not align with other organizational activities and aspects.
Community Detection Based on Local Information and Dynamic Expansion

Mining the community structure in the real-world networks has been a hot topic in the field of complex networks, and has emerged as a prominent research area and continues to grow with the introduction of requirements for personalized recommendation. However, most of the existing community detection algorithms are based on global information, fewer works are devoted to detecting the communities hidden in the network by using local information. To this end, in this paper, we propose two improved signed modularity functions to evaluate the community properties in complex network, and then we apply these indicators to identify the community structure by using the local information since it is difficult to obtain the global information in practice. During the dynamic expansion, each local community will absorb the neighboring node with the highest positive energy; in addition, a new local community is generated when all local communities cannot contain the neighboring node. Finally, the algorithm has been applied to unsigned networks and signed networks, respectively. The experimental results show that the division results given by our proposed algorithm are in line with the actual ones in artificial and real-life networks.
COMPARISON OF NON CHIRPED NRZ, CHIRPED NRZ AND ALTERNATE-CHIRPED NRZ MODULATION TECHNIQUES FOR FREE SPACE OPTIC (FSO) SYSTEMS

Free Space Optics (FSO) is the technology where transmission occurs through optical waveform that contains data transformed at the transmitter from electrical signal. Since the transmission medium of FSO is atmosphere, atmospheric scattering is the major cause for interruption of FSO link. Non return zero (NRZ) modulation is the dominant modulation scheme employed in commercial terrestrial Free Space Optic (FSO) communication systems. This research are required to investigate three viable modulation techniques; NRZ pulse formats, non-chirped NRZ, chirped NRZ, and alternatechirped NRZ at 10 Gb/s and 40 Gb/s data rate. The 1550 nm of continuous wave (CW) laser is modulated with three different modulation formats over 1 km of FSO channel. The signal is propogated at different attenuation value based on Malaysia weather conditions. In this paper we have successfully compared the three modulation techniques in FSO system due to the Malaysia weather and the performance is accessed at bit error rate (BER) of 1x10-9. The presented simulation of these three modulation shows that alternate-chirped NRZ has slightly better performance compared to the non-chirped NRZ and chirped NRZ modulation format at clear weather, haze, light rain, medium rain and heavy rain. We believe that, this system is an alternative for the future optical wireless network that has a potential to be installed in the urban and sub-urban area. Key words: Free Space Optic (FSO) Non Return Zero (NRZ) Chirping Modulation
On the validity of the ionospheric pierce point (IPP) altitude of 350 km in the Indian equatorial and low-latitude sector

Abstract. The GPS data provides an effective way to estimate the total electron content (TEC) from the differential time delay of L1 and L2 transmissions from the GPS. The spacing of the constellation of GPS satellites in orbits are such that a minimum of four GPS satellites are observed at any given point in time from any location on the ground. Since these satellites are in different parts of the sky and the electron content in the ionosphere varies both spatially and temporally, the ionospheric pierce point (IPP) altitude or the assumed altitude of the centroid of mass of the ionosphere plays an important role in converting the vertical TEC from the measured slant TEC and vice versa. In this paper efforts are made to examine the validity of the IPP altitude of 350 km in the Indian zone comprising of the ever-changing and dynamic ionosphere from the equator to the ionization anomaly crest region and beyond, using the simultaneous ionosonde data from four different locations in India. From this data it is found that the peak electron density height (hpF2) varies from about 275 to 575 km at the equatorial region, and varies marginally from 300 to 350 km at and beyond the anomaly crest regions. Determination of the effective altitude of the IPP employing the inverse method suggested by Birch et al. (2002) did not yield any consistent altitude in particular for low elevation angles, but varied from a few hundred to one thousand kilometers and beyond in the Indian region. However, the vertical TEC computed from the measured GPS slant TEC for different IPP altitudes ranging from 250 to 750 km in the Indian region has revealed that the TEC does not change significantly with the IPP altitude, as long as the elevation angle of the satellite is greater than 50 degrees. However, in the case of satellites with lower elevation angles (
Parametric study of unsteady-flow-induced volute casing vibro-acoustics in a centrifugal fan

A numerical parametric analysis of a vibro-acoustic coupling method that considered the influence of vibro-acoustic coupling was carried out to investigate the casing vibrations and feathers of vibrational noise induced by unsteady flow of the centrifugal fan at the best-efficiency point (BEP). There are three important aspects of this method. First, an unsteady flow-field with a whole impeller-volute configuration was solved based on three-dimensional incompressible Navier-Stokes equations and a standard k-e turbulence mode to obtain the source of the vibro-acoustics. Second, a one-way-flow structural acoustic coupling method was implemented to study the volute vibrations and behaviors of vibrational noise by adoption. The generation mechanism of vibrational noise of the volute casing was revealed. Third, the parametric analysis method was used to explore the parametric relationship between the panel thicknesses (such as front-panel thickness [FT], side-panel thickness [ST], and back-panel thickness [BT]) and the outlet acoustical power of the volute casing surface. The parametric analysis provides a reasonable range of values of three panel thicknesses that result in minimal vibrational sound radiation.
A Summarized Review on Web Usage Mining

Incremental growth in the use of web based services and systems have led to generation of such tremendous amounts of data which is beyond imagining. This data plays a vital role in determining the factors like user’s interests, priorities and product or services usage trends. This knowledge enables organizations to evaluate the effectiveness of their strategies and quality of services/products provided and leads them for further refinement. Solicitation of data mining approaches to process huge volume of data available on net is termed as web mining. Web usage is a further phase in web mining which discovers data about the use of internet. This paper aims at providing a review of phases and techniques involved in web usage mining.
Proses komunikasi antara penyandang tunarungu dan tunawicara dapat dipahami antara sesama dengan baik karena mereka sudah terbiasa sehari-harinya menggunakan bahasa isyarat. Namun sebagian orang normal akan kesulitan untuk memahami bahasa isyarat yang disampaikan oleh penyandang tunarungu dan tunawi

Process of communication between the deaf and dumb people can be well understood by each other because they are already familiar to sign language. However, most of normal people will find it hard to understand sign language conveyed by the deaf and dumb people, and vice versa. To overcome these problems, we will develop a sign language recognition system uses Leap Motion Controller (LMC). The recognition of sign language by using only static features can only recognize static sign language and can not well recognize dynamic sign language. In this study, we propose the SIBI sign language recognition which combining static and dynamic features of the LMC based on Logarithmic Learning for Generalized Classifier Neural Network (L-GCNN). The static features are used to recognize the static sign language, and the dynamic features are used to recognize the dynamic sign language. L-GCNN was used to improve the accuracy of recognition. From the results of test performed SIBI recognition using only static features can only recognize static sign language and can not well recognize dynamic sign language. While the SIBI recognition using combination of static features and dynamic features can recognize both static sign language and dynamic sign language well.