Miracle-dz/UniFAR-FTUs huggingface dataset:
A study on the relationship between airport privatisation and airport efficiency: An application of using AHP/DEA methods

In order to deal with the competitive environment surrounding the air transport industry, civil aviation authorities have undertaken several approaches to improve airport efficiency, such as investing in the infrastructure and privatising airport ownership or governance. Among these methods, airport privatisation policy has been implemented for around 25 years in the U.K., closely followed by other European countries. By contrast, decision makers elsewhere, such as in the Asia-Pacific region, are now interested in privatisation and in doing so evaluate the impact of this process elsewhere. Focussing on the most popular method for assessing airport efficiency, with Data Envelopment Analysis (DEA) a unit can appear efficient simply because of its pattern of inputs and outputs rather than any inherent efficiency. But only using DEA may not provide useful results about the efficiency of airports as different decision makers may weight the relative importance of inputs and outputs differently (for example, airport managers, and airline companies). In this research, another aim is to develop and demonstrate the applicability of different analysis techniques within the AEES. For this reason, Analytic Hierarchy Process (AHP) analysis is adopted to calculate the importance of each variable. These results are then integrated into both DEA and DEA, Assurance Region (AR) models, to reflect the different importance of the metrics. In the context of air transportation, an integrated AHP/DEA and AHP/DEA-AR model are applied for the first time to evaluate airport efficiency. A sensitivity analysis with different variable sets is carried out. In conclusion, an AEES is established and the result shows that the approach by adopting AHP/DEA-AR model in particular can provide more accurate values of relative efficiency than using the traditional DEA approach. There are also different priorities between stakeholder groups and these can affect the efficiency scores of airports. However, the results for each of the different analysis techniques show that there is no statistically significant relationship between airport ownership and efficiency. Therefore, the primary aim of this research is to examine the relationship between airport privatisation and efficiency, through an Airport Efficiency Evaluation System (AEES). The study covers Europe and the Asia-Pacific region, reflecting different attitudes towards the role of government within airport management. Focussing on the most popular method for assessing airport efficiency, with
Entry Threat in Duopoly

An oligopolistic market with vertical product differentiation is parametrized in cost parameters. This allows me to study the impact of the technology of the firms (cost parameters) on market structure, conduct, and performance. Firms which differ only by the order of the sequential move to choose a quality use sophisticated entry deterring or entry accomodating strategies. I show that infinitesimal changes in the cost parameters can generate discontinuities in market profits. In particular, higher entry costs can lead to a more competitive outcome.
Investigation of Mycoplasma agalactiae by molecular methods in goat bucks in West of Iran

The presence of asymptomatic carriers of Mycoplasma agalactiae in goat buck populations, and the internal presence of this microorganism in some of these animals, indicated that the ability of this micro-organism captive in contagious agalactiae to colonize in other locations such as the respiratory system or genitalia. This study was designed to detect the excretion Mycoplasma agalactiae in goat bucks reared in Iran, where the disease is considered endemic. A total of 196 samples which included semen (n=49), conjunctiva (n=49), nasal (n=49) and ear (n=49) of goat bucks were collected from July to September 2013. To avoid the introduction of goat bucks carrying Mycoplasma organisms sub clinically in samples were obtained from all candidate goat bucks for PCR, to detect the presence of Mycoplasma agalactiae. Of the samples tested, 31.12% were scored positive for Mycoplasma spp. and Mycoplasma agalactiae was detected in seventeen samples, conjunctival (6 positive sample), nasal (1 positive sample), ear (5 positive sample) and semen (5 positive sample). The results obtained in the present study confirm of Mycoplasma agalactiae in the semen, conjunctival, nasal and ear in goat bucks without clinical symptoms of contagious agalactiae infection. The presence of this agent in male goat is considered very risky in terms of reproductive disorders and contagious agalactiae outbreaks in endemic areas in Iran. This is the first report of Mycoplasma agalactiae in goat bucks without contagious agalactiae signs in Iran.
Real-time synchronous multi-view video transport system over IP networks

This paper proposes a prototype realization of real-time synchronous multi-view video transport system which can extend the software-based multi-view video transport system over IP networks. This system supports H.264/MPEG-2 system based real-time multi-view video transport and considers the synchronization during acquisition and transport for the interactive view-selection during transport. For the synchronized acquisition from multiple multi-view cameras through IEEE 1394 interface, this system estimates the timeline differences among H.264 compressed video streams by using global time of network between the cameras and a server and corrects timelines of video streams by changing the timestamp of the MPEG-2 system stream. Then, it multiplexes a selected number of acquired views at the MPEG-2 TS (transport stream) level for the interactive view-selection during transport. Thus, with the proposed synchronized multiplexing scheme, this system can display synchronized view.
Ectrodactyly and Lethal Pulmonary Acinar Dysplasia Associated with Homozygous FGFR2 Mutations Identified by Exome Sequencing

Ectrodactyly/split hand‐foot malformation is genetically heterogeneous with more than 100 syndromic associations. Acinar dysplasia is a rare congenital lung lesion of unknown etiology, which is frequently lethal postnatally. To date, there have been no reports of combinations of these two phenotypes. Here, we present an infant from a consanguineous union with both ectrodactyly and autopsy confirmed acinar dysplasia. SNP array and whole‐exome sequencing analyses of the affected infant identified a novel homozygous Fibroblast Growth Factor Receptor 2 (FGFR2) missense mutation (p.R255Q) in the IgIII domain (D3). Expression studies of Fgfr2 in development show localization to the affected limbs and organs. Molecular modeling and genetic and functional assays support that this mutation is at least a partial loss‐of‐function mutation, and contributes to ectrodactyly and acinar dysplasia only in homozygosity, unlike previously reported heterozygous activating FGFR2 mutations that cause Crouzon, Apert, and Pfeiffer syndromes. This is the first report of mutations in a human disease with ectrodactyly with pulmonary acinar dysplasia and, as such, homozygous loss‐of‐function FGFR2 mutations represent a unique syndrome.
The Financial Performance and Investment Style of French Ethical Funds

Following the literature about Socially Responsible Investment performance, the purpose of this paper is to study the investment style and the performance of French ethical funds from January 1994 to January 2007. The performance measurement aims to verify if an active management based on specific research of sustainability can add value with regard to the market from a retail investor perspective. The comparison of the ethical funds with their relevant Benchmark is performed through Jensen’s alpha. Results show a general but non- significant underperformance of the ethical funds. A common conservative attitude towards the market risk was also observed. The style analysis a la Fama and French confirms the existence of a small cap bias, already found in previous studies. However, no clear investment strategy, with regard to growth or value stocks, was observed. Finally, using Carhart model, we found that French equity ethical funds don’t have any particular Momentum strategy.
New multirate bandpass sigma-delta modulators

A new architecture for fourth- and sixth-order bandpass sigma-delta (BP-SD) modulators is proposed here. The basic BP-SD modulator is obtained from its low-pass (LP) counterpart by means of the standard transformation z/sup -1/ /spl rarr/ -z/sup -2/, which transforms the integrators in the LP modulator into resonators in the BP modulator, and places the input signal band at the frequency f/sub s//4, where f/sub s/ is the sampling rate. In the proposed architecture, the second resonator (and the third one for the sixth-order case) is implemented using a two-path strategy, by means of two high-pass filters (whose poles are located at f/sub s//2) operating in a time-interleaved mode. However, unlike other BP-SD modulators using the two-path strategy, in our approach, the effective sampling frequency in the second resonator (and in the third one for the sixth-order case) is increased to 2/spl middot/f/sub s/ by maintaining the clock rate of the high-pass filters to f/sub s/ which, in turn, places their poles at f/sub s//2. The signal band in the input of the second resonator is moved from the center frequency f/sub s//4 to f/sub s//2 by a modulation process that separates the signal into their in-phase and quadrature components. Another demodulation process in the digital domain reverses this frequency translation of the signal band before the output signal is converted to the analog domain and fed back to the modulator input. A detailed theoretical analysis of the architecture is done in the paper. Owing to the multirate nature of the proposed modulators, simulation results show an improvement of approximately 12 dB in the input dynamic range (fourth-order case) when compared to conventional modulators of the same order clocked at the same frequency rate (in the first resonator).
Improvement of child activity recognition algorithm for accurate calculation of consumption calorie

Childhood obesity is considered as a risk of likely adulthood obesity. Health management system for children to prevent it is, however, not sufficient. The authors' research group has been studying a monitoring system of child growth named Kinder-Guardian system for it. In this system, activity recognition algorithm for children was used as a method for watching over their activity. In this algorithm, child's activities are classified and verified using several clustering algorithms (J48, Naive Bayes, Random Forest, Random Tree, and REPtree) based on the feature amount computed from acceleration data. In our previous activity recognition, eleven kinds of activities were assumed, and calculation of calorie consumption based on the recognition accuracy did not work well sufficiently. Therefore, in order to improve the AR, a horizontal-vertical decomposition of acceleration signal was used and nine activities were assumed. As a result, accuracy of “Sitting” and “Running” were improved in 61.4% and 31.9%, respectively. Based on this result of activity recognition, precisions of computed calorie consumption for each activity became to be higher than in case of previous AR. Moreover, a field test using the prototype system was performed in a kindergarten. It was confirmed that the prototype system worked well automatically under daily kindergarten operation.
NAD-Glycohydrolase Production and speA and speC Distribution in Group A Streptococcus (GAS) Isolates Do Not Correlate with Severe GAS Diseases in the Australian Population

A 300-bp plasmid fragment of the hemagglutinin gene was used as target DNA to develop a rapid real-time LightCycler (Roche Applied Science, Indianapolis, Ind.) PCR assay for laboratory detection of smallpox virus. PCR primers and probes were designed specifically for detection of smallpox virus DNA, but all viruses of the genus Orthopoxvirus tested could be detected by use of the hemagglutinin gene target sequence. Base pair mismatches in the 204-bp amplicon allowed discrimination of cowpox virus (melting temperature [T(m)], 56.40 degrees C), monkeypox virus (T(m), 56.24 degrees C), and vaccinia virus (T(m), 56.72 degrees C), including the Dryvax vaccine strain, from smallpox virus (T(m), 62.45 degrees C) by melting curve analysis. The analytical sensitivity was 5 to 10 copies of target DNA per sample. The assay was specific for members of the genus Orthopoxvirus; the DNAs of herpes simplex virus and varicella-zoster virus were not detected by the smallpox virus LightCycler PCR.
Time-domain techniques for the computation and reconstruction of one~dimensional profiles

This paper presents a time-domain technique to compute the electromagnetic fields and to reconstruct the permittivity profile within a one-dimensional medium of fi- nite length. The medium is characterized by a permittivity as well as conductivity profile which vary only with depth. The discussed scattering problem is thus one-dimensional. The modeling tool is divided into two different schemes which are named as the forward solver and the inverse solver. The task of the forward solver is to compute the internal fields of the specimen which is performed by Greens function ap- proach. When a known electromagnetic wave is incident nor- mally on the media, the resulting electromagnetic field within the media can be calculated by constructing a Greens oper- ator. This operator maps the incident field on either side of the medium to the field at an arbitrary observation point. It is nothing but a matrix of integral operators with kernels satis- fying known partial differential equations. The reflection and transmission behavior of the medium is also determined from the boundary values of the Green's operator. The inverse solver is responsible for solving an inverse scattering prob- lem by reconstructing the permittivity profile of the medium. Though it is possible to use several algorithms to solve this problem, the invariant embedding method, also known as the layer-stripping method, has been implemented here due to the advantage that it requires a finite time trace of reflection data. Here only one round trip of reflection data is used, where one round trip is defined by the time required by the pulse to propagate through the medium and back again. The inversion process begins by retrieving the reflection kernel from the reflected wave data by simply using a deconvolu- tion technique. The rest of the task can easily be performed by applying a numerical approach to determine different pro- file parameters. Both the solvers have been found to have the ability to deal with different types of slabs and incident elec- tromagnetic pulses. Slabs having continuous and discontin- uous relative permittivity have already been tested success- fully. The tested electromagnetic pulses are a Dirac, Gaus- sian and sinusoidal pulse. Due to sampling, the resolution of the system also plays a significant role in obtaining better outputs from this scheme.
Two approximations of solutions of Hamilton-Jacobi equations

Abstract : Equations of Hamilton-Jacobi type arise in many areas of application, including the calculus of variations, control theory and differential games. The associated initial-value problems almost never have global-time classical solutions, and one must deal with suitable generalized solutions. The correct class of generalized solutions has only recently been established by the authors. This article establishes the convergence of a class of difference approximations to these solutions by obtaining explicit error estimates. Analogous results are proved by similar means for the method of vanishing viscosity. (Author)
Supporting early contextualization of textual content in digital documents on the Web

The World Wide Web is arguably the most important source of digital documents nowadays. These documents mainly consist of unstructured and semi-structured data comprising a wealth of information at the disposal of the DAR (Document Analysis and Recognition) community. Contextualization plays an important role in understanding the content of those documents. In this paper, we present an approach to early contextualization of textual data in HTML documents. It combines automatic as well as semiautomatic annotation of named entities with user interaction to support contextualization of the content of digital documents as early as in the authoring stage of their life cycle. We also present the results of an online experimental evaluation involving 120 human test subjects. They show that our approach successfully managed to produce semantically annotated versions of unstructured textual content, which contain reliable contextual information, thus facilitating the task of later document analysis stages.
80 Common Errors in Company Valuation

This paper contains a collection and classification of 80 errors seen in company valuations performed by financial analysts, investment banks and financial consultants. The author had access to most of the valuations referred to in this paper in his capacity as a consultant in company acquisitions, sales and mergers, and arbitrage processes. Some of the errors are taken from published reports by financial analysts. We classify the errors in six main categories: 1) Errors in the discount rate calculation and concerning the riskiness of the company; 2) Errors when calculating or forecasting the expected cash flows; 3) Errors in the calculation of the residual value; 4) Inconsistencies and conceptual errors; 5) Errors when interpreting the valuation; and 6) Organizational errors.
MODELLING THE DIRECTION-SPECIFIC BUILD-UP OF THE PRECEDENCE EFFECT

One of the remarkable properties of the auditory precedence effect is that it adapts to the listeners' acoustic environment. The “build-up” of the precedence effect has been investigated in a series of psycho-acoustic investigations to test the hypothesis of a “direction-specific“ build-up effect (Djelani and Blauert, 2001). A result of this work is a first model of the auditory precedence effect based on an inhibition model as proposed by Lindemann (1986a;1986b) and Zurek (1987).
Prediction of higher order functional networks from genomic data.

Post-genomics may be defined in different ways depending on how one views the challenges after the discovery of the genome. A traditional view is to follow the concept of the central dogma in molecular biology, namely from genome to transcriptome to proteome. Projects are ongoing to analyse gene expression profiles both at the mRNA and protein levels, and to catalogue protein 3D structure families, which will no doubt help the understanding of the information in the genome. However, once complete, such experimentally determined catalogues of genes, RNAs and proteins only tell us about the building blocks of life. They do not tell us much about how life operates as a system, such as higher order functional behaviours of the cell or the organism. Thus, an alternative view of post-genomics is to go up from the molecular level to the cellular level and eventually to still higher levels, i.e., the biological systems. Bioinformatics provides basic concepts as well as practical methods to integrate this view with the traditional view and to analyse complex interactions among building blocks and with dynamic environments.
Optimization of the extraction of polyphenols from grape seed meal by aqueous ethanol solution

The efficient methods for extracting phenolics from grape seeds have been of great interest to many investigators, due to the special health promoting and disease preventing effects of polyphenols. In this study, extractions were performed by using aqueous ethanol. The effects of single factors such as the concentration of ethanol, the ratio of liquid to solid (L/S), extraction temperature, extraction time, and number of extractions on the extraction efficiency were studied. Total phenol was measured by the Folin-Ciocalteu procedure to monitor the efficiency of the extraction under different experimental conditions. High pressure liquid chromatograph (HPLC) analysis was applied to identify and quantify some specific dimeric and trimeric phenolics in grape seeds. The concentration of ethanol and the extraction temperature showed the most significant impact on the yield of total phenolics. At room temperature, the extract with highest total phenolics was obtained with 50% ethanol. A higher extraction yield was obtained at higher temperature. When ethanol concentration and temperature were kept constant, 1.5 hr extraction time and liquid to solid ratio of 7.5:1 resulted in the best yield. In all cases, the phenolics extracted by first and second stage consisted of 90-97% of the total phenolics of the sum of the three stages. Therefore, two-stage extraction would be more cost efficient than three-stage extraction.
Applying Techniques in Supervised Deep Learning to Steering Angle Prediction in Autonomous Vehicles

The development of effective autonomous vehicles is, in today’s day and age, an undoubtedly popular application of research in machine learning and control. One of the most fundamental tasks in the design of algorithms to control autonomous vehicles is steering angle prediction based on realtime driving data. In this paper, we discuss the application of techniques in supervised learning to predict the vector of steering angles required to navigate a car through some specified trajectory. The attributes upon which we construct features and train supervised learning algorithms are provided in a dataset recently released by Udacity [1]. Each file in the dataset describes a trajectory (roughly a 15 to 45 minute drive), over the duration of which attributes are collected. For each point along the trajectory, the steering angle at that point is recorded along with [1] the GPS coordinates of the car, [2] the instantaneous speed at which the car is traveling, and [3] a set of 3 images {left,center,right} captured by onboard forward facing cameras in the vehicle. Our analysis of the problem can be split broadly into three phases, with primary emphasis on the last phase. The first phase concerns the prediction of steering angle from GPS coordinates and speed alone. The second phase of the analysis concerns the evaluation of conventional techniques in supervised learning (such as support vector regression) to predict steering angle from (1) pre-processed dataset images and (2) extracted features of these images. The third and final phase of the analysis concerns the evaluation of deep learning schemes to predict the steering angles (from both raw images and pre-processed ones). For this last phase in particular, we consider both a multi-layer convolutional neural network and a multilayer perceptron model.