Miracle-dz/UniFAR-FTUs huggingface dataset:
Opportunistic dynamic subchannel allocation in multiuser OFDM networks with limited feedback

In this paper we present a simple scheme for subchannel allocation in OFDM multiuser networks in the presence of limited feedback, in particular, when only one bit of information per subchannel is available at the base station. Our objective is to maximize the sum rate capacity of the network in the downlink transmission. We show that even with very limited feedback the sum rate capacity growth is the same as the fully informed transmission. We also extend this result to the case when subchannels are correlated.
FAST AND ROBUST GAUSSIAN MIXTURE MODEL FOR MRI BRAIN IMAGE SEGMENTATION

Image segmentation is crucial and preliminary stage of almost all medical imaging diagnosis tools. Gaussian Mixture Model (GMM) is one of common methods for image segmentation and usually, Expectation Maximizing (EM) is used to estimate the parameters of this model. In order to improve EM performance in presence of noise, an extension for EM is proposed which incorporates mean-filtered image as neighborhood information in clustering. In addition, the histogram of image is used as input for clustering to speed up the process. Proposed algorithm quantitatively evaluated in compare to current extensions for EM.
Can China’s Industrial SO 2 Emissions Trading Pilot Scheme Reduce Pollution Abatement Costs?

This paper evaluates the effects of China’s industrial SO 2 emissions trading pilot scheme (SETPS) on the pollution abatement costs (PAC) from the past and future perspective. We apply the kernel-based propensity score difference-in-difference method to examine the effects of SETPS on the average pollution abatement costs (APAC) and the marginal pollution abatement costs (MPAC) based on the environment data from the industrial sector of 29 provinces in China over the period of 1998 to 2011. Our findings are that SETPS failed to reduce PAC as a whole. During 2002 to 2011, SETPS increased APAC by 1310 RMB per ton on average and had an insignificant negative effect on MPAC. Nevertheless, the conclusions would be markedly different if we separately investigated the effects of SETPS each year of the pilot period. The positive effects of SETPS on PAC started to appear since 2009, and SETPS significantly reduced both APAC and MPAC, especially in 2009 and 2011.
Constraint-based Debugging of Spreadsheets

Despite being staggeringly error prone, spreadsheets can be viewed as a highly flexible end-users programming environment. As a consequence, spreadsheets are widely adopted for decision making by end-users, and may have a serious economical impact for the business. Hence, approaches for aiding the process of pinpointing the faulty cells in a spreadsheet are of great value. In this paper we present a constrainbased approach for debugging spreadsheets. We coin the approach ConBug. Essentially, the approach takes as input a (faulty) spreadsheet and a test case that reveals the fault (a test case specifies values for the input cells as well as the expected values for the output cells) and computes a set of diagnosis candidates for the debugging problem we are trying to solve. To compute the set of diagnosis candidates we convert the spreadsheet and test case to a constraint satisfaction problem (CSP), modeled using the state-of-the-art constraint solver MINION. We use a case study, in particular using a spreadsheet taken from the well-known EUSES Spreadsheet Corpus, to better explain the different phases of the approach as well as to measure the efficiency of ConBug. We conclude that ConBug can be of added value for the end user in order to pinpoint faulty cells.
A New Triterpenoid Saponin from Abrus precatorius Linn

A new triterpenoid saponin, 3-O-β-D-glucopyranosyl-(1→2)-β-D-glucopyranosyl subprogenin D (1), together with six known triterpenoids: subprogenin D (2), abrusgenic acid (3), triptotriterpenic acid B (4), abruslactone A (5), abrusogenin (6) and abrusoside C (7) were isolated from the leaves and stems of Abrus precatorius. Their structures were elucidated on the basis of physical and NMR analysis, respectively. Compounds 5 and 6 showed moderate cytotoxicity against MCF-7, SW1990, Hela, and Du-145 cell lines. Compounds 1, 2 and 4 were isolated from this plant for the first time.
Ancestry Informative Markers Clarify the Regional Admixture Variation in the Costa Rican Population

Abstract The genetic structure of Costa Rica's population is complex, both by region and by individual, due to the admixture process that started during the 15th century and historical events thereafter Previous studies have been done mostly on Amerindian populations and the Central Valley inhabitants using various microsatellites and mitochondrial DNA markers. Here, we study for the first time a random sample from all regions of the country with ancestry informative markers (AIMs) to address the individual and regional admixture proportions. A sample of 160 male individuals was screened for 78 AIMs customized in a GoldenGate platform from Illumina. We observed that this small set of AIMs has the same power of hundreds of microsatellites and thousands of single-nucleotide polymorphisms to evaluate admixture, with the benefit of reducing genotyping costs. This type of investigation is necessary to explore new genetic markers useful for forensic and genetic investigation. Our data showed a mean admixture proportion of 49.2% European (EUR), 37.8% Native American (NAM), and 12.9% African (AFR), with a disproportionate admixture composition by region. In addition, when Chinese (CHB) was included as a fourth component, the proportions changed to 45.6% EUR, 33.5% NAM, 11.7% AFR, and 9.2% CHB. The admixture trend is consistent among all regions (EUR > NAM > AFR), and individual admixture estimates vary broadly in each region. Though we did not find stratification in Costa Rica's population, gene admixture should be evaluated in future genetic studies of Costa Rica, especially for the Caribbean region, as it contains the largest proportion of African ancestry (30.9%).
Algorithms for Better Representation and Faster Learning in Radial Basis Function Networks

In this paper we present upper bounds for the learning rates for hybrid models that employ a combination of both self-organized and supervised learning, using radial basis functions to build receptive field representations in the hidden units. The learning performance in such networks with nearest neighbor heuristic can be improved upon by multiplying the individual receptive field widths by a suitable overlap factor. We present results indicating optimal values for such overlap factors. We also present a new algorithm for determining receptive field centers. This method negotiates more hidden units in the regions of the input space as a function of the output and is conducive to better learning when the number of patterns (hidden units) is small.
Toward improving the visual stimulus meaning for increasing the P300 detection

The P300 speller is a well known Brain-Computer Interface paradigm that has been used for over two decades. A new P300 speller paradigm (XP300) is proposed. It includes several characteristics: (i) the items are not intensified by using rows and columns, (ii) the order of the visual stimuli is pseudo-random, (iii) a visual feedback is added on each item to increase the stimulus meaning, which is the main novelty. XP300 has been tested on ten healthy subjects on copy spelling mode, with only eight sensors. It has been compared with the classical P300 paradigm (CP300). With five repetitions, the average recognition rate across subjects is 85.25% for XP300 and 77.25% for CP300. Single-trial detection is significantly higher with XP300 by comparing the AUC (Area Under Curve) of the ROC (Receiver Operating Characteristic) curve. The mean AUC is 0.86 for XP300, 0.80 for CP300. More importantly, XP300 has also been judged as more convenient and user-friendly than CP300, hence being able to allow longer sessions.
So how big is big? Investigating the impact of class size on ratings in student evaluation

Abstract Australian universities have a long history of use of student satisfaction surveys. Their use has expanded and purpose changed over time. The surveys are often viewed as distorted by external influences such as discipline context, class size and year level of participants. This paper reports on the results of a large-scale investigation interrogating the influence of class size on student satisfaction ratings. The investigation was conducted at a large, comprehensive, research-intensive Australian university. It drew on the data from a survey administered to all students in all units of undergraduate and postgraduate study conducted across the university over four semesters. Data were collated into four class size categories. This categorised data were subjected to statistical analyses. This paper discusses the approach taken, the results of the analysis and their implications for student evaluation of teaching and learning.
OPTIMAL PEDALING TECHNIQUE FOR SPRINT CYCLING : A COMPUTER SIMULATION STUDY

A musculoskeletal model was developed to determine the theoretically optimal pedaling technique (quantified as pedal forces and kinematics) for sprint cycling. Input was a set of stimulation patterns for the eight major muscle groups in the lower extremity, output are the kinematics and forces predicted by a direct dynamics simulation. Stimulation patterns were optimized until maximal average power output was reached. The optimal technique produced 529.1 W in a single limb and was sufficiently similar to typical EMG, pedal force, and kinematic data to conclude that the model is a suitably realistic representation of a cyclist. The optimal pedaling technique was characterized by a raised heel at top dead centre and a large force along the crank at bottom dead centre. In addition, negative torque was produced during the upstroke. These features, traditionally regarded as undesirable, can be explained using properties of the system and the requirement of maximal power output. In a second set of optimizations, weighted combinations of power and technique variables (pedal force and pedal kinematics) were optimized in order to determine the sensitivity of performance to technique. This showed that sprint performance is not very sensitive to pedal kinematics, within a certain range. However, performance decreased by about 7% when an exaggerated 'ankling' technique was used, and by the same amount when the normal component of pedal force was reduced by 37%.
Clinico-microbiological study of candidemia in a tertiary care hospital of southern part of India

Background and Objectives: Over the last two decades, both the incidence of nosocomial candidaemia and the proportion of blood stream infection due to Candida spp. other than Candida albicans have increased. The aims of this study was to identify different species of Candida and risk factors associated with bloodstream infection and detection of biofilm production. Materials and Methods: This study was conducted in an 840 bedded tertiary care hospital, over a period of one year. All blood isolates received from patients during this period were screened for candidemia prospectively. Speciation was carried out by standard microbiological method. Biofilm production detection was done by Brachini et al method. Result: A total of 80 cases of candidemia were identified. Most important risk factor was placement of vascular access devices in all the age groups. Candida albicans accounted for 22 isolates (27.5%) whereas non-albicans Candida spp. accounted for 58 isolates (72.5%). Biofilm production was found in 31 strains (38.75%). Biofilm production was seen more in non-albicans Candidaspp. (83.87%) especially in C. tropicalis (66.67%, 8 of 12). Conclusions: Non-albicansspecies of Candida were most frequently recovered in our study. So, the epidemiology of Candida infection is changing. Non–albicans Candida spp have the capacity to produce significant amount of biofilm which may be the cause of their reduced susceptibility to antifungal agents.
Examination of a Culturable Microbial Population from the Gastrointestinal Tract of the Wood-Eating Loricariid Catfish Panaque nigrolineatus

Fish play a critical role in nutrient cycling and organic matter flow in aquatic environments. However, little is known about the microbial diversity within the gastrointestinal tracts that may be essential in these degradation activities. Panaque nigrolineatus is a loricariid catfish found in the Neotropics that have a rare dietary strategy of consuming large amounts of woody material in its natural environment. As a consequence, the gastrointestinal (GI) tract of P. nigrolineatus is continually exposed to high levels of cellulose and other recalcitrant wood compounds and is, therefore, an attractive, uncharacterized system to study microbial community diversity. Our previous 16S rRNA gene surveys demonstrated that the GI tract microbial community includes phylotypes having the capacity to degrade cellulose and fix molecular nitrogen. In the present study we verify the presence of a resident microbial community by fluorescence microscopy and focus on the cellulose-degrading members by culture-based and 13 C-labeled cellulose DNA stable-isotope probing (SIP) approaches. Analysis of GI tract communities generated from anaerobic microcrystalline cellulose enrichment cultures by 16S rRNA gene analysis revealed phylotypes sharing high sequence similarity to known cellulolytic bacteria including Clostridium, Cellulomonas, Bacteroides, Eubacterium and Aeromonas spp. Related bacteria were identified in the SIP community, which also
OS-level virtualization for industrial automation systems: are we there yet?

Virtualization is entering the world of real-time embedded systems. Industrial automation systems, in particular, can benefit from what virtualization has to offer: flexible consolidation of applications on different hardware types and scales, extending the life-time of legacy code or decoupling software and hardware lifecycles. However, such systems require a light-weight virtualization technology in order to be able to maintain real-time behavior while dealing with real-time data. This paper sets out to investigate the applicability of container-based OS-level virtualization technology to industrial automation systems. To this end, we provide insights into the capabilities of containers to achieve flexible consolidation and easy migration of industrial automation applications as well as into the container technology readiness with respect to the fundamental requirement of industrial automation systems, namely performing timely control actions based on real-time data. Moreover, we provide an empirical study of the performance overhead introduced by containers based on micro-benchmarks that capture the characteristics of targeted industrial automation applications.
Communication in Medical Care: Explaining illness: patients' proposals and physicians' responses

Patients visit doctors for a variety of reasons, and a prominent one is to find out what is causing some health problem or symptom they are experiencing (Korsch et al. 1968; Novack 1995). However, during the course of medical interviews, patients often offer their own “lay” or “folk” explanations for what is causing their health difficulties. In the view of many researchers, doctors routinely ignore or dismiss patients’ theories (Cicourel 1983; Fisher and Groce 1990; Kleinman et al. 1978; Mehan 1990; Mishler 1984; Stoeckle and Barsky 1981; Waitzkin 1979, 1991). Doctors, because of their power and authority, are said to impose a biomedical perspective upon patients.1 They maintain an exclusive focus on only those symptoms and disease processes that are under the purview of the medical model, rather than considering or appreciating patients’ social experiences and perspectives regarding their illnesses. Thus, the “voice of medicine” regularly silences the “voice of the life world” (Fisher and Groce 1990; Mishler 1984). Despite such pronouncements, investigators have not described or analyzed, in any detail, the interactional structure of patients’ explanations and doctors’ responses (explanation– response sequences) as they occur within the context of clinic visits. Nor has enough attention been given to how explanation–response sequences relate to ongoing courses of activity, such as the different
Auditory Modeling in Automatic Recognition of Speech

The paper argues against blind implementing of scattered accidental knowledge which may be irrelevant to a speech recognition task and advance the notion that the reason for applying knowledge of human auditory perception in engineering applications should be the ability of perception to suppress some parts of information in the speech message. In general, it advocates selective use of auditory knowledge, optimized on real speech data. 1 Ignorance and Knowledge in Handling The Nonlinguistic Variability in ASR With an advent of powerful stochastic classiication techniques , many believe that the task of alleviating the irrelevant variability should be left on the classiier. In the training stage the recognizer would be presented with all the information that is available (i.e., both \signal" and \noise"). Such exhaustive training should allow (during recognition) for a separation of the desired signal from the noise. However, for this to be true, the classiier would have to be a model-free classiier (so that no prior knowledge constrains its capabilities) and it would have to be presented with all possible past and future speech data. Therefore, weakly-structured data-driven ASR systems require large amounts of training data. Further, the knowledge acquired by the training is typically speciic to a given application and may not be easily reusable in another system. Some speculate that more structured designs with some build-in knowledge of human speech communication processes could provide desirable constraints for the ASR problem. As will become more obvious after reading through this paper, we are currently advocating selective use of auditory knowledge optimized on real speech data. 2 Analysis in ASR The information rate in speech signal is by some estimates 1] of the order of 36 kbits/s. The written equivalent of the linguistic message in the signal is less that 50 bits/s 1]. The general task of ASR is to identify and reduce information in the signal. The analysis should support this goal by alleviating as much as possible non-linguistic factors in the signal. Additional practical requirements for current ASR techniques are that speech features derived from speech analysis should be low-dimensional and their statistics should be well described by gaussian distributions. Automatic speech recognition (ASR) typically uses features based on a short-term spectrum of speech which describes time-varying speech signal as a sequence of short-term feature vectors. Each vector reeects properties of a relatively short (10-20 ms) segment of the signal. Each individual feature vector is …
From instrumental use to institutional routine: A longitudinal study of sports journalists live-tweeting the Daytona 500

ii DEDICATION . iv LIST OF ABBREVIATIONS AND SYMBOLS . v ACKNOWLEDGMENTS . vi LIST OF TABLES . ix CHAPTER 1: INTRODUCTION . 1 Sports News Creation in the 21 Century – A Social Media Shift . 1 NASCAR’s Daytona 500 as Study Event . 3 Purpose of the Dissertation . 7 Significance of the Dissertation . 9 Overview of the Dissertation . 10 CHAPTER 2: REVIEW OF LITERATURE . 12 Changing Journalism Industry, Journalist Mimicry . 12 Journalist as Brand . 17 Bloggers . 20 Twitter and Second Screen . 21 Twitter . 21 Second Screen . 24 Research Questions and Hypotheses . 27
Modelling And Forecasting Small Haplochromine Species (Kambuzi) Production In Malawi - A Stochastic Model Approach

The study aimed at forecasting small Haplochromine species locally known as Kambuzi yield in Malaŵi, based on data on Lake Malombe fish catches during the years from 1976 to 2011. The study considered Autoregressive (AR), Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) processes to select the appropriate stochastic model for forecasting small Haplochromine species yield in Lake Malombe. Based on ARIMA (p, d, q) and its components Autocorrelation function (ACF), Partial autocorrelation (PACF), Normalized Bayesian Information Criterion (NBIC), Box – Ljung Q statistics and residuals estimated, ARIMA (0, 1, 1) was selected. Based on the chosen model, it could be predicted that the small Haplochromine species yield would increase to 4,224 tons in 2021 from 93 tons in 1976.
Impact of Pre-Procedure Interventions on No-Show Rate in Pediatric Endoscopy

Pediatric endoscopy has evolved into an indispensable tool in the diagnosis and management of gastrointestinal diseases in children. However, there is limited literature focusing on quality improvement initiatives in pediatric endoscopy. The primary goal of this project was to reduce the no-show rate in the pediatric endoscopy unit. Also, we aimed to improve patient and family satisfaction with the procedure by identifying opportunities for improvement. A checklist was designed based on the potential causes of no-show. The endoscopy nurse coordinator reviewed the checklist when scheduling the procedure to identify patients at high risk for non-compliance. Once a risk factor was identified, appropriate actions were taken. She also made a pre-procedure phone call as a reminder and to address any of these risks for non-compliance if present. A patient satisfaction survey was used to identify potential areas for improvement. The no-show rate decreased from an average of 7% in the pre-intervention phase to 2% in the post-intervention phase (p = 0.009). 91% of the patients/family recorded an overall satisfaction of 4 or 5 on a scale of 1–5 (5 being best). Quality improvement strategies decreased the no-show rate in the pediatric endoscopy unit. A patient satisfaction survey helped in identifying areas for improvement.
A study on LIWC categories for opinion mining in Spanish reviews

With the exponential growth of social media, that is, blogs and social networks, organizations and individual persons are increasingly using the number of reviews of these media for decision-making about a product or service. Opinion mining detects whether the emotions of an opinion expressed by a user on Web platforms in natural language are positive or negative. This paper presents extensive experiments to study the effectiveness of the classification of Spanish opinions in five categories: highly positive, highly negative, positive, negative and neutral, using the combination of the psychological and linguistic features of LIWC (Linguistic Inquiry and Word Count). LIWC is a text analysis software that enables the extraction of different psychological and linguistic features from natural language text. For this study, two corpora have been used, one about movies and one about technological products. Furthermore, we conducted a comparative assessment of the performance of various classification techniques, J48, SMO and BayesNet, using precision, recall and F-measure metrics. The findings revealed that the positive and negative categories provide better results than the other categories. Finally, experiments on both corpora indicated that SMO produces better results than BayesNet and J48 algorithms, obtaining an F-measure of 90.4 and 87.2% in each domain.