Miracle-dz/UniFAR-FTUs huggingface dataset:
An experimental optical neuron

This thesis describes the experimental verification of a concept, named the injection seeding neuron. The conducted work is part of the Laser Neural Network project. The goal of this project is the realisation of a neural network in the optical domain by use of diode lasers. The injection seeding neuron is a concept of a fully optical neuron. Both the inputs and the output of this neuron are defined by optical powers. In realising such a neuron, one of the requirements is a nonlinear function. In the injection seeding neuron, this function is realised by the injection of light into a semiconductor laser diode. Two longitudinal modes of the laser diode are used, with one above and one below threshold. The nonlinear function is obtained by increasing the injected power in the belowthreshold mode. As a result, the below-threshold mode can start laser operation. A crucial technique in the injection seeding neuron is injection locking or injection seeding. This technique is theoretically investigated. The experimental setup consists of two parts. The main component of both parts is a laser diode with an external cavity. A tunable laser provides the input signal to the injection seeding neuron. The output wavelength of this tunable laser is very stable in order to achieve injection locking. The actual injection seeding neuron is formed by the so-called neuron laser. In the external cavity of this neuron laser, the applied feedback can be controlled for several longitudinal modes by use of a grating and a liquid crystal display. The experiments successfully verify the concept ofthe injection seeding neuron. If the laser diode has a low pumping current, the measured nonlinear functions are in agreement with previously performed simulations. If the current is increased, different nonlinear functions are found. A variation of the injected frequency also has an effect on the shape of the nonlinearity. Using the same experimental setup, a frequency converter is demonstrated. It was difficult to obtain multiple, reproducible measurements due to instabilities in the setup. Therefore, it is recommended that the same experiments be carried out with an improved setup.
A combined morphological and molecular phylogeny for sea urchins (Echinoidea: Echinodermata).

Phylogenetic relationships of higher taxa of echinoids have been investigated using a 163 character morphological data base and molecular sequences from large and small subunit (LSU and SSU) ribosomal RNA (rRNA) genes. The complete SSU rRNA gene has been sequenced for 21 taxa, with representatives from nine of the 14 extant orders of Echinoidea. Partial LSU sequences, representing the first 400 base pairs (b.p.) from the 5' end were also sequenced for three taxa to complement an existing data base of ten taxa. The two molecular sequences provided a total of 371 variable sites, of which 143 were phylogenetically informative (compared to 145 phylogenetically informative sites from morphological data). Morphological, LSU and SSU data have been analysed separately and together. Morphological and SSU sequence data generate topologies that are not significantly in conflict (under Templeton's test), but the strong signal pairing arbaciids with clypeasteroids in the LSU derived tree marks the LSU sequence data as anomalous for this taxon. A 'total evidence' approach derived a tree very similar in topology to that derived from morphological data. Rooted on the stem group echinoid Archaeocidaris, our total evidence tree suggested relationships of higher taxa as follows: Cidaroida (Phormosomatidae (Echinothuriidae (Diadematidae ((Spatangoida (Clypeasteroida, Cassiduloida)) ((Calycina, Arbacioida) (Stomopneustidae (Glyphocidaridae (Temnopleuridae (Echinometridae (Echinidae, Stronglyocentridae)))))))))). Phylogenetic analyses run both with and without key fossil taxa yielded slightly different topologies. It is important to include fossil taxa in a phylogenetic analysis where there are long stem-group branches or where the crown group is highly derived.
Thiopurine therapy in inflammatory bowel disease patients: Analyses of two 8‐year intercept cohorts

Background: Thiopurines have proven efficacy in long‐term maintenance therapy of inflammatory bowel disease (IBD). Limited data are available with regard to factors predicting effectiveness and failure of long‐term thiopurine use in IBD patients. Methods: The data in this retrospective study are based on an 8‐year intercept cohort of previous or present thiopurine‐using IBD patients. Both cohorts are assessed by descriptive and statistical analysis aimed at determining thiopurine effectiveness and the variables that are predictive for failure of thiopurine therapy. Results: In all, 363 IBD patients were included (60% female), 63% with Crohn's disease and 33% with ulcerative colitis. Overall, thiopurines were continued in 145/363 (40%) and discontinued in 208/363 (57%) patients. The proportion of patients still using thiopurines at 3, 6, 12, 24, and 60 months was 73%, 69%, 63%, 51%, and 42%, respectively. Patients discontinued thiopurines due to adverse events (39%), refractoriness (16%), and ongoing remission / patient's request (4%). 6‐methylmercaptopurine (6‐MMP) concentration and 6‐MMP/6‐thioguanine nucleotides (6‐TGN) ratio were significant higher in the failure group. Prolonged continuation of thiopurines was associated with a decreased risk of discontinuation. Conclusions: Azathioprine and 6‐mercaptopurine were considered effective in ≈40% of IBD patients after 5 years of treatment. A quarter of the patients discontinued thiopurines within 3 months, mostly due to adverse events. A high 6‐MMP concentration or 6‐MMP/6‐TGN ratio was associated with therapeutic failure. If thiopurine use was successfully initiated in the first months, its use was usually extended over many years, as long‐term use was associated with continuation of therapy. (Inflamm Bowel Dis 2010)
Modelling of foF2 using neural networks at an equatorial anomaly station

The critical frequency of the F 2 -layer (foF 2 ) is an important parameter in estimating the total electron content (TEC) of the ionosphere, which is necessary for predicting the ionospheric time delay in GPS applications.The foF 2 data from Ahmedabad, which is in the equatorial anomaly region, are modelled using a multilayer neural network trained with back-propagation algorithm. The IRI-2001 model together with this neural network model can be used for predicting/forecasting of the foF 2 parameter within the Indian subcontinent. The foF 2 values thus predicted can be used to estimate the critical TEC parameter.
Asset-liability management for pension funds in a time-varying volatility environment

In this article, we develop a framework for asset-liability management for pension funds in a time-varying volatility environment. We use sophisticated dynamic econometric models for the variances–covariances of the asset classes in which the pension fund is investing, while for the liability structure we employ two standard approaches that have been used in the relevant actuarial literature. The models implemented are used in the asset allocation process of the pension fund, as well as for risk management purposes. The constructed portfolios have significant economic value according to well-known performance measures.
Finding relevant missing references in learning courses

Reference sites play an increasingly important role in learning processes. Teachers use these sites in order to identify topics that should be covered by a course or a lecture. Learners visit online encyclopedias and dictionaries to find alternative explanations of concepts, to learn more about a topic, or to better understand the context of a concept. Ideally, a course or lecture should cover all key concepts of the topic that it encompasses, but often time constraints prevent complete coverage. In this paper, we propose an approach to identify missing references and key concepts in a corpus of educational lectures. For this purpose, we link concepts in educational material to the organizational and linking structure of Wikipedia. Identifying missing resources enables learners to improve their understanding of a topic, and allows teachers to investigate whether their learning material covers all necessary concepts.
Contributing to social transformation through Communicative Research Methodology

Traditionally, researches on groups that suffer inequalities have not taken into account their voices in the research process. For this reason, they arrive to conclusions that have led to the reproduction of social exclusion in which they are living. The communicative research methodology encourages the participation of these social groups in all the research stages. This participation in the research process is built through an egalitarian and intersubjective dialogue. The accumulated scientific knowledge provided by researchers meets in this dialogue with the contributions from the life world of social actors, leading to transform situations of social inequality that people belonging to these groups are suffering. In this article we will also show how communicative research methodology is obtaining greater political and social impact from the research results.
Scalable Influence Estimation in Continuous-Time Diffusion Networks

If a piece of information is released from a media site, can we predict whether it may spread to one million web pages, in a month ? This influence estimation problem is very challenging since both the time-sensitive nature of the task and the requirement of scalability need to be addressed simultaneously. In this paper, we propose a randomized algorithm for influence estimation in continuous-time diffusion networks. Our algorithm can estimate the influence of every node in a network with |V| nodes and |ε| edges to an accuracy of ε using n = O(1/ε2) randomizations and up to logarithmic factors O(n|ε|+n|V|) computations. When used as a subroutine in a greedy influence maximization approach, our proposed algorithm is guaranteed to find a set of C nodes with the influence of at least (1 - 1/e) OPT - 2Cε , where OPT is the optimal value. Experiments on both synthetic and real-world data show that the proposed algorithm can easily scale up to networks of millions of nodes while significantly improves over previous state-of-the-arts in terms of the accuracy of the estimated influence and the quality of the selected nodes in maximizing the influence.
GPCRs, G-proteins, effectors and their interactions: human-gpDB, a database employing visualization tools and data integration techniques

G-protein coupled receptors (GPCRs) are a major family of membrane receptors in eukaryotic cells. They play a crucial role in the communication of a cell with the environment. Ligands bind to GPCRs on the outside of the cell, activating them by causing a conformational change, and allowing them to bind to G-proteins. Through their interaction with G-proteins, several effector molecules are activated leading to many kinds of cellular and physiological responses. The great importance of GPCRs and their corresponding signal transduction pathways is indicated by the fact that they take part in many diverse disease processes and that a large part of efforts towards drug development today is focused on them. We present Human-gpDB, a database which currently holds information about 713 human GPCRs, 36 human G-proteins and 99 human effectors. The collection of information about the interactions between these molecules was done manually and the current version of Human-gpDB holds information for about 1663 connections between GPCRs and G-proteins and 1618 connections between G-proteins and effectors. Major advantages of Human-gpDB are the integration of several external data sources and the support of advanced visualization techniques. Human-gpDB is a simple, yet a powerful tool for researchers in the life sciences field as it integrates an up-to-date, carefully curated collection of human GPCRs, G-proteins, effectors and their interactions. The database may be a reference guide for medical and pharmaceutical research, especially in the areas of understanding human diseases and chemical and drug discovery. Database URLs: http://schneider.embl. de/human_gpdb; http://bioinformatics.biol.uoa.gr/human_gpdb/
Spelling and Society: The Culture and Politics of Orthography Around the World

Introduction: society and orthography 1. Approaching orthography 2. Orthography as social practice 3. Language contact, linguists and the emergence of orthographies 4. 'Postcolonial' orthographies 5. Between language and dialect: orthography in unstandardised and standardising vernaculars 6. Reform or revolution: where angels fear to tread 7. Why do we spell?
Iterative Switching Filter for High Density Noise Removal

This paper proposes an efficient filter for the restoration of images that are corrupted by high density of impulse noise. In this method an iterative switching filter is used that switches between two cases depending on the noise percentage in the input image. For low noise percentage it searches for the noise-free pixels within a small neighborhood. The noisy-pixel is then replaced with the average estimated from noise-free pixels. For high noise percentage weighted median is used to replace the corrupted pixels. The iterative process continues until all noisy-pixels of the corrupted image are filtered. The proposed filtering method is tested using standard test images and found to be more efficient than already existing high density noise removal techniques.
FIU-Miner: a fast, integrated, and user-friendly system for data mining in distributed environment

The advent of Big Data era drives data analysts from different domains to use data mining techniques for data analysis. However, performing data analysis in a specific domain is not trivial; it often requires complex task configuration, onerous integration of algorithms, and efficient execution in distributed environments.Few efforts have been paid on developing effective tools to facilitate data analysts in conducting complex data analysis tasks. In this paper, we design and implement FIU-Miner, a Fast, Integrated, and User-friendly system to ease data analysis. FIU-Miner allows users to rapidly configure a complex data analysis task without writing a single line of code. It also helps users conveniently import and integrate different analysis programs. Further, it significantly balances resource utilization and task execution in heterogeneous environments. A case study of a real-world application demonstrates the efficacy and effectiveness of our proposed system.
Role of the iroquois3 homeobox gene in organizer formation

In zebrafish, the organizer is thought to consist of two regions, the yolk syncytial layer (YSL) and the shield. The dorsal YSL appears to send signals that affect formation of the shield in the overlying mesendoderm. We show here that a domain of dorsal deep cells located between the YSL and the shield is marked by expression of the iro3 gene. As gastrulation proceeds, the iro3 positive domain involutes and migrates to the animal pole. Iro3 expression is regulated by Nodal and bone morphogenic protein antagonists. Overexpression of iro3 induced ectopic expression of shield-specific genes. This effect was mimicked by an Iro3-Engrailed transcriptional repressor domain fusion, whereas an Iro3-VP16 activator domain fusion behaved as a dominant negative or antimorphic form. These results suggest that Iro3 acts as a transcriptional repressor and further implicate the iro3 gene in regulating organizer formation. We propose that the iro3-expressing dorsal deep cells represent a distinct organizer domain that receives signals from the YSL and in turn sends signals to the forming shield, thereby influencing its expansion and differentiation.
Evaluación Psicométrica de una Versión Modificada de la Escala de Experiencias Disociativas (DES-M)

En este trabajo se presenta evidencia de validez y fiabilidad para un instrumento breve deevaluacion de fenomenos disociativos. Se trata de una version modificada de la Dissociative ExperiencesScale (DES-M). La nueva version es mas simple y breve que la original, lo que facilita sucomprension y reduce los tiempos de administracion. Se trabajo con una muestra de poblacion generalde la ciudad de Mar del Plata, Argentina (n=301). Los resultados sugieren un comportamientomuy satisfactorio del instrumento en el ambito local (estructura factorial similar a la original,niveles adecuados de consistencia interna y un patron robusto de correlaciones con medidas devalidacion). Se espera que la nueva escala proporcione una herramienta valida para la evaluacione investigacion de fenomenos disociativos. Se requieren mas estudios que amplien la evidenciade validez.
Personality in multiple sclerosis (MS): impact on health, psychological well-being, coping, and overall quality of life

Abstract Personality has long been considered a factor that can account for differences in health, well-being, and overall quality of life (QOL). A ‘Distressed or Type D Personality’ has been studied in medical populations as a predictor of several outcomes. The purpose of the present investigation was to determine the presence of Type D Personality in multiple sclerosis (MS) and its role on disease symptoms, disease management, health-related behaviors, coping, psychological well-being, and overall QOL and functioning. Two hundred and thirty (230) individuals with MS completed a survey assessing personality, disease symptoms, disease management, coping, self-efficacy, locus of control (LOC), psychological well-being, and QOL. Thirty-seven (16%) individuals were found to be ‘Type D+. ’ Such individuals reported greater fatigue, pain, depression, and anxiety and worse disease management and adherence. They also reported engaging in maladaptive means of coping. Compared to ‘Type D−’ they reported lower self-efficacy, LOC, QOL and greater perceived stress. Finally, ‘Type D+’ individuals were more likely to be considering leaving the workforce. Findings suggest that ‘Type D’ Personality is associated with various negative outcomes in MS. Consideration of the routine assessment of personality in MS seems warranted and may better inform interventions and ward off poor outcomes.
May I take your order? A Neural Model for Extracting Structured Information from Conversations

In this paper we tackle a unique and important problem of extracting a structured order from the conversation a customer has with an order taker at a restaurant. This is motivated by an actual system under development to assist in the order taking process. We develop a sequence-to-sequence model that is able to map from unstructured conversational input to the structured form that is conveyed to the kitchen and appears on the customer receipt. This problem is critically different from other tasks like machine translation where sequence-to-sequence models have been used: the input includes two sides of a conversation; the output is highly structured; and logical manipulations must be performed, for example when the customer changes his mind while ordering. We present a novel sequence-to-sequence model that incorporates a special attention-memory gating mechanism and conversational role markers. The proposed model improves performance over both a phrase-based machine translation approach and a standard sequence-to-sequence model.
Analysis of Herbaceous Plant Succession and Dispersal Mechanisms in Deglaciated Terrain on Mt. Yulong, China

Ecological succession itself could be a theoretical reference for ecosystem restoration and reconstruction. Glacier forelands are ideal places for investigating plant succession because there are representative ecological succession records at long temporal scales. Based on field observations and experimental data on the foreland of Baishui number 1 Glacier on Mt. Yulong, the succession and dispersal mechanisms of dominant plant species were examined by using numerical classification and ordination methods. Fifty samples were first classified into nine community types and then into three succession stages. The three succession stages occurred about 9–13, 13–102, and 110–400 years ago, respectively. The earliest succession stage contained the association of Arenaria delavayi + Meconopsis horridula. The middle stage contained the associations of Arenaria delavayi + Kobresia fragilis, Carex capilliformis + Polygonum macrophyllum, Carex kansuensis, and also Pedicularis rupicola. The last stage included the associations of Kobresia fragilis + Carex capilliformis, Kobresia fragilis, Kobresia fragilis + Ligusticum rechingerana, and Kobresia fragilis + Ligusticum sikiangense. The tendency of the succession was from bare land to sparse vegetation and then to alpine meadow. In addition, three modes of dispersal were observed, namely, anemochory, mammalichory, and myrmecochory. The dispersal modes of dominant species in plant succession process were evolved from anemochory to zoochory.
Multiplex PCR Assay for Rapid and Accurate Capsular Typing of Group B Streptococci

ABSTRACT We developed a simple, specific, and sensitive two-multiplex-PCR assay that enabled the detection of all known group B streptococcal (GBS) capsular polysaccharides. This test is well adapted for GBS capsular polysaccharide typing in large-scale epidemiological studies.
Deliberative communication goes to college: the ‘Deliberation Forum’ project as a democratic agent of empowerment for communication students

A new field of research has developed over the last few decades, called ‘Deliberative Communication’. It focuses on the potential contribution of public deliberations to strengthening the foundations of democracy and the promotion of social–political goals and objectives. The current research focuses on a unique case study, the ‘Deliberation Forum’ project, conducted by the Department of Communication at the Yezreel Valley College, Israel. The researcher sought to learn about students' experience of participating in this online forum and the effects they attributed to it, through unstructured interviews she held with them. The students indicated that, for the most part, the experience of participating in the deliberation forum was very positive: it enhanced their self-image as thinking people; strengthened their sense of self-importance as students within the department; developed and reinforced habits of keeping abreast of current affairs as well as critical thinking; and finally, the experience developed and strengthened habits of active participation in pluralistic debates. The study findings indicate that participation in projects of this kind has a clear empowerment potential, while also improving participants' attitude toward public deliberation and decision-making processes.