Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards smart user models in open environments

Acknowledges The author would like to thank Beatriz López for all her remarks and early orientation and cooperation on this paper. Also, Josep Lluís de la Rosa for always having explanations on hand and for being able to link up the needs of industry and our research area. The opinions expressed in this paper are those of the authors.
Reconstructed imagery for equatorial monitoring combining AVHRR with reconstructed NSCAT

The availability of reconstructed imagery raises several questions. First, does reconstructed imagery provide any advantage over the ubiquitous Advanced Resolution Radiometer (AVHRR) imagery monitoring? What are the advantages and disadvantages of each reconstructed image type? What kind of geophysical information does each provide? Only continuing research will answer these complex questions. In this paper, emphasis is placed on comparisons between contemporary AVHRR and the latest reconstructed NASA Scatterometer (NSCAT) data sets for monitoring vegetation in equatorial areas. The authors demonstrate that AVHRR data combined with NSCAT provides better equatorial forest differentiation than AVHRR data used alone.
Novel control channel quality improvement in satellite communication systems employing high coding gain FEC

The authors propose a novel control channel quality improvement scheme for satellite communication systems using a majority decision method over convolutional coding and Viterbi decoding channels. To improve majority decision performance, which is degraded by burst errors due to Viterbi decoding in conventional serial transmission methods, a parallel transmission method is proposed. The performance of the parallel and serial transmission methods has been analyzed, and experimenta have been carried out using rate 1/2 convolutional encoding and Viterbi decoding (constraint length 4 and 7). It is shown that the parallel transmission method has about 10/sup 10/ times lower block error performance at P/sub e/=1*10/sup -4/ than the conventional method. <<ETX>>
Induction of immunoglobulin A as a therapeutic intervention in allergic asthma

textabstractAllergic asthma is a chronic inflammatory disorder of the airways in response to inhaled allergens and is characterized by airway inflammation, bronchial hyperresponsiveness and a variable degree of airflow obstruction, leading to episodes of wheezing, coughing and breathlessness. In addition, structural changes (‘airway remodeling’) in the airway including subepithelial and airway wall fibrosis, goblet cell hyperplasia/metaplasia, smooth muscle thickening and increased vascularity are observed. In susceptible individuals, repeated exposure to harmless environmental allergens like house-dust mites (HDMs), molds, plant pollen and animal dander can lead to sensitization and development of a chronic immune response consisting of an effector cascade leading to immediate and late-phase reactions to allergens and subsequent characteristic clinical symptoms.
Arrangements of Resting State Electroencephalography as the Input to Convolutional Neural Network for Biometric Identification

Biometric is an important field that enables identification of an individual to access their sensitive information and asset. In recent years, electroencephalography- (EEG-) based biometrics have been popularly explored by researchers because EEG is able to distinct between two individuals. The literature reviews have shown that convolutional neural network (CNN) is one of the classification approaches that can avoid the complex stages of preprocessing, feature extraction, and feature selection. Therefore, CNN is suggested to be one of the efficient classifiers for biometric identification. Conventionally, input to CNN can be in image or matrix form. The objective of this paper is to explore the arrangement of EEG for CNN input to investigate the most suitable input arrangement of EEG towards the performance of EEG-based identification. EEG datasets that are used in this paper are resting state eyes open (REO) and resting state eyes close (REC) EEG. Six types of data arrangement are compared in this paper. They are matrix of amplitude versus time, matrix of energy versus time, matrix of amplitude versus time for rearranged channels, image of amplitude versus time, image of energy versus time, and image of amplitude versus time for rearranged channels. It was found that the matrix of amplitude versus time for each rearranged channels using the combination of REC and REO performed the best for biometric identification, achieving validation accuracy and test accuracy of 83.21% and 79.08%, respectively.
Order Sensitive Scoring for Objective Evaluation of Remote Sensing - Image Retrieval System

In order to make the evaluation result become fair and consistent without relying on user judgement, we proposed a new mechanism of objective evaluation for remote sensing image retrieval system. This mechanism is performed by dividing the image database into some subjects and select one subject as a ground truth. Subsequently, we take an image of the ground truth as a query Q. Retrieval accurate ratio (pAR) for query Q will be computed as a comparison between utility value and maximum possible utility. This pAR value can provide the non-degeneracy score. We repeat the retrieval process for all the images in the ground truth as the query and take averaged accurate ratio (pAAR) for a subject as the average value of all the accurate ratio for all queries in a subject. These process is performed for all subjects in the database, thus we can obtain the mean averaged accurate ratio (pmAAR) as mean value of all averaged accurate ratio for all subjects.
De ecologische meerwaarde van het aanbrengen van grindbedden in de Tongelreep

Beekfauna kan profiteren van het aanbrengen van grindbedden in beken. Een van de weinige beken in Nederland waarin grind is aangebracht is de Tongelreep in Noord-Brabant. Dit artikel beschrijft de ervaringen met deze maatregel, waarbij is gekeken naar de stabiliteit van de grindbedden en de aanwezigheid van macrofauna. De grindbedden bleken zich niet te verplaatsen, maar varieerden wel in grootte door tijdelijke sedimentbedekking. Het aantal op het ingebrachte grind aanwezige kenmerkende taxa was opvallend hoog. Het stimuleren van het ontstaan van grindbedden verdient daarom meer aandacht bij het ontwerp van beekherstelmaatregelen.
Review on Corner Detection Algorithms

Corner detection algorithms are widely used in image recognition, image matching and edge detection. Accurately finding a corner in a image can greatly improves the algorithms accuracy of the above research areas. So many scientists and researchers have begun to the hot research field and have made much remarkable achievements. The paper introduced the theory of classic corner detection algorithm, including Harris algorithm, surf and sift algorithm, ORB algorithm, Susan algorithm and so on, And compared the difference of classic algorithms. Then, the recently outstanding algorithm and its application are introduced. Finally, the paper summarizes the research trends about corner detection
A Hidden Markov Factor Analysis Framework for Seizure Detection in Epilepsy Patients

Approximately 1% of the world population su↵ers from epilepsy. Continuous long-term electroencephalographic (EEG) monitoring is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. Detection of seizure from the recorded EEG is a laborious, time consuming and expensive task. In this study, we propose an automated seizure detection framework to assist electroencephalographers and physicins with identification of seizures in recorded EEG signals. In addition, an automated seizure detection algorithm can be used for treatment through automatic intervention during the seizure activity and on time triggering of the injection of a radiotracer to localize the seizure activity. In this study, we developed and tested a hidden Markov factor analysis (HMFA) framework for automated seizure detection based on di↵erent features such as total e↵ective inflow which is calculated based on connectivity measures between di↵erent sites of the brain. The algorithm was tested on long-term (2.4-7.66 days) continuous sEEG recordings from three patients and a total of 16 seizures, producing a mean sensitivity of 96.3% across all seizures, a mean specificity of 3.47 false positives per hour, and a mean latency of 3.7 seconds form the actual seizure onset. The latency was negative for a few of the seizures which implies the proposed method detects the seizure prior to its onset. This is an indication that with some extension the proposed method is capable of seizure prediction.
An Integrated Developmental Connectionist Model of Orthography to Phonology and Orthography to Seman

An important debate between theorists of dual-route models of word recognition and naming concerns the contribution which semantics makes to the generation of phonological codes from orthography. A recent paper by Plaut et al. [18] suggested that words are initially named through an orthography to phonology route, but redistribute and become named via an orthography to semantics to phonology route over time as reading skills are acquired based on the orthographic regularity of each word. This contradicted more traditional dual-route theories which suggest that words which have exceptional sound-spelling correspondences can only be correctly named through a lexical lookup process. A model which integrated connectionist networks for orthography to phonology and orthography to semantics translation was implemented to investigate this claim. Results were consistent with recent literature, and also provided an explanation for error scores which are typically found in naming tasks.
Distributed Computation In Neural Networks And Their Optical Analogs

A continuum model for a neural network with lateral inhibition biased near threshold behaves like a dispersive optical medium with convective gain in a narrow band of wave numbers. A quadratic memory nonlinearity causes a long-lived change in an excitability parameter with continued excitation, imprinting multiplexed volume holographic gratings in the medium. Pairs, Chains, and Cycles of associated images may then be reconstructed by multiple Bragg scattering, corresponding to the recognition of patterns of images invariant under groups of transformations. An optical analog of the neural medium is suggested which could implement pattern recognition tasks on noncoherent inputs within a single crystal.
Cardiovascular disease in patients with HIV

The introduction of combination antiretroviral therapy (cART) has substantially decreased mortality among the HIV-infected population. In this setting, cardiovascular disease (CVD) has become a leading cause of morbidity and mortality. Compared with the general population, higher rates of myocardial infarction as well as a high prevalence of subclinical coronary atherosclerosis have been found in the HIV-infected population. It has been suggested that in HIV-infected patients, the atherosclerotic burden is not based solely on traditional cardiovascular risk factors. The interplay of other mechanisms such as chronic inflammation, effects of cART or immune activation after initiation of cART may predispose to accelerated and increased risk of CVD. Effective treatment are available today to reduce CVD in at-risk patients, and therefore early detection of subclinical coronary atherosclerosis is important. However, the mechanisms behind the development of CVD in HIV-infected patients may limit the usefulness o.
Second surgical procedures for continuous ambulatory peritoneal dialysis patients: An analysis of 148 cases

Aim: Patients who undergo continuous ambulatory peritoneal dialysis (CAPD) frequently need second surgical procedures (SSP) for various reasons. After 18 years of practice and observation, we analysed the records of these patients and tried to determine what complications occurred most often and how to deal with them.
Practice Educator Perspectives of Multiple Mentoring in Diverse Clinical Settings

Introduction: In a climate of overloaded health systems and limited opportunities for practice education, there is a need to provide high quality placements that prepare students adequately for contemporary practice. Group models of supervision are one way to address this. This study trialled a multiple mentoring (group supervision) model across three different settings: a university clinic, an acute hospital and a community-based service. The perceptions of practice educators regarding its use and essential implementation features of the model were explored. Method: The model was trialled over an 18-month period. A total of 15 practice educators participated in three focus groups. Findings: Following inductive analysis, three main themes emerged: being clear in the chaos; qualities of the service and people; and challenges and benefits. Findings indicated a range of factors that influenced practice educators' experiences, including the structure of the placement, communication processes and the organisational context. Conclusion: A multiple mentoring model of student supervision can be implemented across a range of practice settings, providing that care is taken to tailor the practicum for each setting. Practice educators perceived that the benefits to themselves, the students, the service and the clients outweighed the challenges.
Effect of Normalization on Detection of Differentially-Expressed Genes with Moderate Effects

The current existing literature offers little guidance on how to decide which method to use to analyze one-channel microarray measurements when dealing with large, grouped samples. Most previous methods have focused on two-channel data;therefore they can not be easily applied to one-channel microarray data. Thus, a more reliable method is required to determine an appropriate combination of individual basic processing steps for a given dataset in order to improve the validity of one-channel expression data analysis. We address key issues in evaluating the effectiveness of basic statistical processing steps of microarray data that can affect the final outcome of gene expression analysis without focusingon the intrinsic data underlying biological interpretation.
AutoCAD 2006 Tutorial - Second Level: 3D Modeling

The primary goal of AutoCAD 2011 Tutorial - Second Level: 3D Modeling is to introduce the aspects of computer based three dimensional modeling. This text is intended to be used as a training guide for both students and professionals. The chapters in this book cover AutoCAD 2011 and proceed in a pedagogical fashion to guide you from constructing 3D wire frame models, 3D surface models, and 3D solid models to making multiview drawings and rendering images. The text takes a hands-on, exercise-intensive approach to all the important 3D modeling techniques and concepts. This book contains a series of twelve tutorial style chapters designed to introduce CAD users to 3D modeling with AutoCAD 2011. Users upgrading from a previous release of the AutoCAD software will also find this text helpful. The basic premise of this book is that the more 3D designs you create using AutoCAD 2011 the better you learn the software. With this in mind each tutorial introduces a new set of commands and concepts, building on previous chapters. By going through this book readers will establish a good basis for exploring and growing in the exciting field of Computer Aided Engineering. Table of Contents 1. Getting Started 2. User Coordinate System (UCS) and the Z-axis 3. 3D Wireframe Modeling 4. UCS, Viewports and Wireframe Modeling 5. 3D Surface Modeling 6. Solid Modeling - Constructive Solid Geometry 7. Regions, Extrude and Solid Modeling 8. Multiview Drawings from 3D Models 9. Symmetrical Features in Designs 10. Advanced Modeling Tools and Techniques 11. Conceptual Design Tools and Techniques 12. Introduction to Photorealistic Renderings
A Student-Oriented Study: Analyzing the Relationship between Happiness and Satisfaction with Life

The purpose of this study is to analyse the happiness and life satisfaction levels of university students by various factors and to reveal the relationship between those two terms. The sample group of the study is composed of Necmettin Erbakan University Physical Education and Sports Teacher Department and Pamukkale University Sports Sciences Faculty students, who are 801 in number, 394 of them male and 407 of them female, and with an average age of 23.58±2.98. In the study the “Life Satisfaction Scale,” which has been developed by Diener et al. (1985) and adapted to Turkish by Durak et al. (2010), and the “Oxford Happiness Scale Short Version,” which has been developed by Hills and Argyle (2002) and adapted to Turkish by Doğan and Akıncı Çötok (2010), has been used. To determine the personal information distribution of participants percentage and frequency methods, and to determine whether the data has normal distribution or not Shapir Wilks normalcy test has been used and after establishing that the data is suitable for parametric test conditions, to analyse the data the independent t Test, Anova and Pearson Correlation tests have been used. According to the analysis results, a significant difference in life satisfaction has been observed with respect to age and regular exercise parameters (p < 0.05). According to the happiness scale a significant difference has been observed with respect to gender, department, grade and department satisfaction parameters (p < 0.05). Finally, a positive and meaningful relationship has been observed between the two scales. Consequently, it could be argued that life satisfaction and happiness levels of participants show significant differences with respect to some parameters and that the higher their life satisfaction, the higher their level of happiness.
A microfluidic setup for quantifying single-cell transcription regulatory dynamics

Bacteria are exposed to fluctuations in their environment and can respond to such changes by regulating gene expression, often at the level of transcription. Since gene expression is an inherently stochastic process, identical cells within a single environment display heterogeneous expression levels. To understand how the stochastic processes in gene expression affect the dynamics of single-cell gene regulation it is necessary to observe gene expression in single cells in changing environments. Recently developed microfluidic devices combined with quantitative fluorescence time-lapse microscopy allow lineages of single cells to be followed over long timescales and to measure their growth and gene expression phenotypes simultaneously. However these devices are missing the environmental control needed to study gene regulation. Therefore we set out to find a way to combine the longterm observation of single cells with precise environmental control in a single microfluidic chip. As a basis we chose a device called the Mother Machine in which single files of cells are growing in small dead end growth channels. These growth channels are connected to a main channel with a constant flow of medium for nutrient diffusion into the growth channels. The cells at the dead end of the growth channels are trapped and when dividing push their progeny into the main channel where they are removed by the flow. Therefore the trapped cell can be monitored essentially for its whole lifetime, while its progeny can only be observed for a short timeframe before they leave the growth channel. By combining the Mother Machine design with a specialized dual input junction and mixing serpentines for environmental control we developed a device that offers new prospects in studying gene regulation. Together with the device we developed an easy to use software solution to analyze data from Mother Machine like devices together with our collaboration partners. This integrated experimental and computational setup will be an important tool to understand the genetic basis for differences in single-cell expression distributions, and to understand how natural selection has shaped single-cell gene regulation. As a first example we show how single cells differ in the regulation of the expression of the lac operon when exposed to alternating changes in the available carbon source switching between glucose and lactose every 4h.
Outcome of Lung Cancer Patients Admitted to Intensive Care Unit

We investigate the outcome of lung cancer patients admitted to the medical intensive care unit (MICU) and examine potential predictors of mortality. A retrospective quality assurance study of primary lung cancer patients admitted to the MICUs at 2 local tertiary care university hospitals from January 1, 1994 to May 12, 2004 was conducted (n 69). Data on demographics and tumor-related data were collected using the hospital records of all patients admitted to MICU with a diagnosis of lung cancer. Statistical analysis was performed to determine the prognostic factors associated with MICU and hospital mortality as well as MICU and hospital lengths of stay. The MICU mortality rate was 50.7% and the mean MICU length of stay was 3.0 days. Multivariate analysis determined that Acute Physiology and Chronic Health Evaluation (APACHE II) scores, Therapeutic Intervention Scoring System scores, and non-small cell lung cancer were significantly associated with MICU mortality, whereas age and APACHE II scores were associated with hospital mortality. Respiratory failure upon admission and use of a Swan Ganz monitor were predictors of increased MICU length of stay, and chemotherapy administration and mechanical ventilation predicted increased hospital length of stay. The 50.7% mortality rate for patients with previously or newly diagnosed primary lung cancer admitted to the MICU is lower than the previously reported mortality rate of 66.7% for a period of 1986. Although the mortality remains high, an improvement over the previous decade has occurred and is comparable to that for patients requiring MICU admission for other indications.
Context-aware recommender systems for real-world applications. (Systèmes de recommandation contextuels pour les applications du monde réel)

Recommender systems have proven to be valuable tools to help users overcome the information overload, and significant advances have been made in the field over the last two decades. In particular, contextual information has been leveraged to model the dynamics occurring within users and items. Context is a complex notion and its traditional definition, which is adopted in most recommender systems, fails to cope with several issues occurring in real-world applications. In this thesis, we address the problems of partially observable and unobservable contexts in two particular applications, hotel recommendation and online recommendation, challenging several aspects of the traditional definition of context, including accessibility, relevance, acquisition, and modeling.The first part of the thesis investigates the problem of hotel recommendation which suffers from the continuous cold-start issue, limiting the performance of classical approaches for recommendation. Traveling is not a frequent activity and users tend to have multifaceted behaviors depending on their specific situation. Following an analysis of the user behavior in this domain, we propose novel recommendation approaches integrating partially observable context affecting users and we show how it contributes in improving the recommendation quality.The second part of the thesis addresses the problem of online adaptive recommendation in streaming environments where data is continuously generated. Users and items may depend on some unobservable context and can evolve in different ways and at different rates. We propose to perform online recommendation by actively detecting drifts and updating models accordingly in real-time. We design novel methods adapting to changes occurring in user preferences, item perceptions, and item descriptions, and show the importance of online adaptive recommendation to ensure a good performance over time.