Miracle-dz/UniFAR-FTUs huggingface dataset:
Constancy in the perception of speech when the level of room-reflections varies

A speech message played several metres from the listener in a room is usually heard to have much the same phonetic content as it does when played nearby, even though the different amounts of reflected sound make the temporal envelopes of these signals very different. To study this ‘constancy’ effect, listeners heard speech messages and speech-like sounds comprising 8 auditory-filter shaped noise-bands that had temporal envelopes corresponding to those in these filters when the speech message is played. The ‘contexts’ were “next you’ll get _to click on”, into which a “sir” or “stir” test word was inserted. These test words were from an 11-step continuum, formed by amplitude modulation. Listeners identified the test words appropriately, even in the 8-band conditions where the speech had a ‘robotic’ quality. Constancy was assessed by comparing the influence of room reflections on the test word across conditions where the context had either the same level of room reflections (i.e. from the same, far distance), or where it had a much lower level (i.e. from nearby). Constancy effects were obtained with both the natural- and the 8-band speech. Results are considered in terms of the degree of ‘matching’ between the context’s and test-word’s bands.
CyLKs: Unsupervised Cycle Lucas-Kanade Network for Landmark Tracking

Across a majority of modern learning-based tracking systems, expensive annotations are needed to achieve state-of-the-art performance. In contrast, the Lucas-Kanade (LK) algorithm works well without any annotation. However, LK has a strong assumption of photometric (brightness) consistency on image intensity and is easy to drift because of large motion, occlusion, and aperture problem. To relax the assumption and alleviate the drift problem, we propose CyLKs, a data-driven way of training Lucas-Kanade in an unsupervised manner. CyLKs learns a feature transformation through CNNs, transforming the input images to a feature space which is especially favorable to LK tracking. During training, we perform differentiable Lucas-Kanade forward and backward on the convolutional feature maps, and then minimize the re-projection error. During testing, we perform the LK tracking on the learned features. We apply our model to the task of landmark tracking and perform experiments on datasets of THUMOS and 300VW.
Patients with Peri-Implantitis, unlike Those with a Healthy Peri-Implant Microenvironment, Display Antibodies to More Than One Heat Shock Protein (HSP 27, HSP 65 and HSP 90) Linear Epitope

The success of a dental implant treatment requires hard and soft tissue integration and osseointegration, mechanisms that entail a direct anchorage of the implant in the bone without interposition of soft tissue. Peri-implantitis is defined as an inflammatory reaction of the tissues surrounding a functioning dental implant. During inflammation, a high incidence of autoantibodies has been reported. The hypothesis of the present study is that the occurrence of autoantibodies to self-antigens including extracellular matrix (ECM) molecules and heat shock proteins (HSPs) might affect the dental implant outcome. Therefore, we evaluated the occurrence of antibodies to ECM molecules (Collagen (C) I, III, IV, V, fibronectin, laminin) and HSPs (HSP 27, HSP 65, HSP 90) in subjects with a healthy peri-implant microenvironment (n=29) as compared to patients with peri-implantitis (n=13). We also evaluated the HSP 27 expression in gingival fibroblasts grown in an inflammatory microenvironment. Antibodies to conformational ECM epitopes of CI, CIII and laminin were observed both in subjects with healthy peri-implant conditions and peri-implantitis. Antibodies to more than one HSP linear epitope were found in patients with peri-implantitis but not with healthy peri-implant conditions (p=0.024). Gingival fibroblasts grown in an inflammatory microenvironment showed increased HSP 27 cytoplasmic and plasma membrane expression as compared to fibroblasts grown in normal conditions. Immunity to multiple linear HSPs epitopes in patients with peri-implantitis and not in patients with a healthy peri-implant microenvironment might be relevant for monitoring the implant outcome and help to understand the role of subsets of autoantibodies in implant osseointegration.
Temporal analysis of determinants for respiratory emergency department visits in a large German hospital

Introduction Associations between air pollutants, meteorological conditions and respiratory diseases have been extensively shown. The aim of this study was to investigate associations between daily meteorological data, data on air pollution and emergency department (ED) visits depending on the day of the week, season and year (study period from 2013 to 2015). Methods Highly correlated environmental data entered a categorical principal components analysis (CATPCA). We analysed cross-correlation functions between the time series of the respective daily environmental factors and daily ED visits. Time lags with peak correlations of environmental variables obtained by the CATPCA on ED visits together with day of the week, year, running day (linear, quadratic and cubic), season and interaction terms entered the univariate analysis of variance (UNIANOVA) model. Results The analyses demonstrated main effects on ED visits for the day of the week with highest admission rates on Mondays (B=10.69; ƞ2=0.333; p<0.001). A significant time trend could be observed showing increasing numbers of ED visits per each year (p<0.001). The variable ‘running day’ (linear, quadratic and cubic) indicated a significant non-linear effect over time. The variable season showed significant results with winter, spring and summer recording fewer ED visits compared with the reference season autumn. Environmental variables showed no direct associations with respiratory ED visits. Discussion ED visits were significantly associated with temporal variables. Our data did not show direct associations between environmental variables and ED visits. In times of rapid urbanisation, increases in respiratory diseases, temperature and air pollution, our analyses can help focus future studies and enhance strategies to reduce increasing numbers of respiratory diseases and ED visits. Because the potential costs of medical care in hospitals can be high compared with physicians, public health recommendations for reducing the increasing ED visits should be promoted and evaluated.
Análisis conceptual e investigación en didáctica de la matemática

En este capitulo se resalta la importancia del analisis conceptual como herramienta metodologica que permite controlar la complejidad, seleccionar las opciones conceptuales idoneas y disponer del aparato teorico adecuado en una investigacion. Se ubica el analisis conceptual dentro del proceso de diseno de una investigacion y se presenta un ejemplo de esta herramienta para la nocion de modelo. In this chapter we emphasize the conceptual analysis as a methodological instrument which allows in a research to control the complexity, to choose the conceptual suitable options and to lay out a theoretical framework. The conceptual analysis is embedded in the process of designing a research and is presented as an instrument for the notion of a model.
A Multilevel Analysis of Job Characteristics, Emotion Regulation, and Teacher Well-Being: A Job Demands-Resources Model

This study integrated personal factors into the job demands-resources (JD-R) model to examine school- and individual-level predictors of teacher well-being. Survey data were gathered from 1,656 teachers from 54 schools. The results of hierarchical linear modeling indicated that the school-level emotional job demands of teaching and suppression at the individual level were positively related to teachers' anxiety and depression whereas school-level trust in colleagues and individual-level reappraisal were positively associated with enthusiasm and contentment. Positive relationship between emotional job demands and suppression was also found. These findings support the claim that reappraisal should be considered a personal resource and suppression a personal demand.
The Effects of Same- and Other-Race Facial Expressions of Pain on Temporal Perception

Previous studies suggested that threatening stimuli lengthen subjective duration, while facial expressions of pain were found to produce a shortening effect on temporal perception in a recent study. Moreover, individuals’ responses to others’ pain were influenced by the individuals’ relationship to a racial group. However, the effects of same- and other-race pained facial expressions on temporal perception, remain unknown. The aim of this present study was to identify the effect expressions of pain have on temporal perception and to explore whether this effect was modulated by the relationship to a racial group. In a temporal bisection task, Chinese participants were presented with pain or neutral facial expressions displayed by Caucasian (other-race) or Chinese (same-race) models in a 400–1600 ms or 200–800 ms condition. Expressions of pain were rated as more arousing, negative and disagreeable, than neutral facial expressions. These scores were not significantly different between same- and other-race facial expressions. Based on the results of the temporal bisection task, both same- and other-race pained facial expressions lengthened the perceived duration in the 400–1600 ms condition, but only same-race pained facial expressions produced this effect in the 200–800 ms condition. We postulate that the existence of a short-lived effect of pained facial expressions on lengthening temporal perception caused by arousal and attention, occurs at an earlier time point for same-race pained facial expressions than for other-race pained facial expressions.
The Analysis of Temporally Ordered Configurations: Challenges and Solutions

textabstractIn organizational research there is an increasing interest in the study of configurations, i.e., of “multidimensional constellations of conceptually distinct characteristics that occur together” (Meyer, Tsui and Hinings, 1993: 1175). Frequently, the object of study is a process, i.e., a complex of activities that unfolds over time (e.g., an innovation project, a reorganisation, an implementation process). The characteristics that form the configuration are “conditions” (e.g., conditions A, B, and C) that are present (A, B, C) or absent (a, b, c). The notation ABC, thus, represents the observation that the three conditions A, B, and C are present in a process that is studied. Temporally ordered configurations can be defined as those configurations in which conditions occur in a specific temporal order (e.g., C→A→B, meaning that, in one case, C appears first, A next, and finally B). In this chapter we use the term “(temporal) sequence” for such a temporally ordered configuration. Note that the term “(temporal) order” is used here empirically as a synonym of the word “(temporal or chronological) pattern” and is not meant normatively (as opposed to “disorder”). Specific temporal sequences might generate or allow outcomes that are not generated or allowed by the same configuration of conditions if they appear in another temporal order (e.g., A→B→C or B→A→C). The terms “generating” and “allowing” (an outcome), which are used here in order to avoid the term “cause”, will be discussed below in the section on necessary conditions.
HIERARCHICAL PHRASE-BASED ENGLISH – INDONESIAN MACHINE TRANSLATION USING ADJ TECHNIQUE

In this paper, annotated disjunct (ADJ) technique is employed to develop hierarchical phrase-based transfer rules. We also developed an English to Indonesian Machine Translation (MT) system using those transfer rules to be compared with the phrase-based system, which is our previous version that outperforms other available English to Indonesian MT systems.
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A language for access control

We present a language for access control. The language is organized around the notion of execution on behalf of a principal. This is characterized using an indexed lax modality. Central to the language is the idea of manifest security – accessing a resource requires presenting a proof of accessibility to the resource monitor. Proofs are generated at runtime by actions such as typing in password, looking up an access-control list or by composing other proofs etc. In the present work, we consider a simplified setting in which the access-control theory is static. In such a case proofs can be regarded as static entities. Proof generation can be hoisted away from resource access since proofs become permanent. Also, the actual proofs are irrelevant. The results of runtime checks can therefore be reflected as types and the program can be verified statically to ensure that relevant runtime checks would be passed before accessing any resource. We prove a theorem stating that the language is safe in terms of how all a principal can get to access a resource.
Flight Classification Method Based on Unit Time Delay Cost

Traditional flight classification methods are usually based on the geometry of the aircraft or the size of the wake of the aircraft. In the actual operation of airports, the classification of aircraft based on the delay cost of flights was more conducive to airport operation and management, and improve the economic benefits of airlines and passengers. A new arrival and departure flights classification method based on the transitive closure algorithm was proposed. The fuzzy sets theory and the transitive closure algorithm were introduced. Four different factors were selected to establish the flights classification model. The formulas to calculate the delay cost for each class were given.
Flexible VNE algorithms analysis using ALEVIN

Network virtualization is recognized as an enabling technology for the Future Internet that overcomes network ossification. However, it introduces a set of challenges. In any network virtualization environment, the problem of optimally mapping virtual demands to physical resources, known as virtual network embedding (VNE), is a crucial challenge. This paper analyses the behaviour of the main algorithms proposed to solve VNE by means of the ALEVIN framework. The VNE algorithms are evaluated with regard to appropriate metrics such as: cost, revenue, and virtual network acceptance ratio. We also analyse the impact of the recently introduced hidden hop demand concept in the performance of the VNE algorithms.
TWIRL and RSA Key Size

The present invention relates to a process for the purification of effluent which results in the textile, paper and leather industries and in the manufacture of dyestuffs, and which contains water-soluble, anionic dyestuffs or optical brighteners, the said process comprising the addition of a water-soluble formaldehyde condensation product to the said effluent and the subsequent removal of the occurring flocculate from the effluent.
Fast reasoning in a rule-based system with uncertainty

The knowledge processed in empirical domains is more or less uncertain. In order to support people who deal with them, expert systems with uncertainty are used. The expert systems that serve for planning or simulation purposes are often implemented as rule-based systems. To express the uncertainty of facts and rules, different mathematical methods are used: from probability factors and modal logics to the Zadeh’s fuzzy logic. The last method is the most general, and it helps to conclude very reliable hypotheses. In the simulation systems both the conclusions’ reliability and the time necessary for reasonings are of great importance. In this paper we point at the rule of convergence as a method of reasoning which allows to speed up reasonings performed in rule-based systems with uncertainty. We discuss its advantages, limitations and possible applications.
An empirical investigation into the interpretability of data mining models based on decision trees, tables and rules

While data mining research has largely focused on developing ever more accurate predictive models, a much smaller body of research has investigated to which extent these models are actually interpretable by decision makers. Given the importance of this aspect on the model's validation, acceptance and successful application, we will discuss an experimental study in which we empirically compare the interpretability of various representation forms, viz. decision tables, decision trees, propositional rules and oblique rules, as well as explore the effect of size or complexity on their usefulness.
Efficiently Predicting Taxi Future Location based on Square Error Estimation

The future locations of taxis can reflect both human activities and urban dynamics in a city. Existing approaches to predict taxi future location are inefficient due to their high complexity. In this paper, we propose an efficient method the proposed method reduces the average computation time by 5.7%, while retaining almost the same prediction accuracy.
XML Schema Essentials

From the Publisher: Replacing XML DTDs (Document Type Definitions) as the way in which XML documents are described and validated, XML Schema allows you to describe the structure of information in an XML document and is essential for ensuring the accuracy and security of information in B2B transactions and other XML applications. Since XML Schema defines a greater and more complex set of datatypes than XML DTDs -- such as numbers, dates, times, and currencies -- it is an invaluable tool for e-commerce applications. XML Schema also offers more flexibility than XML DTDs, with its ability to have users define datatypes for data (for example, an "address" can be further refined as a "postal address," "billing address," or "shipping address") and its ability to validate documents based on namespaces, which allows for the distinction between identical terms being used in different contexts. This hands-on guide uses extensive examples and source code to provide you with all the information you'll need to understand and use XML Schema. Beginning with an example of a simple schema, the authors provide you with the opportunity to quickly become familiar with coding structure, and offer in-depth explanations for each example. The book progresses logically through basic schema concepts and applications such as datatypes and structures, and then gradually moves to more complex examples and advanced topics such as unique element and attribute values and keys.
Can Clustering Improve Requirements Traceability? A Tracelab-enabled Study

Software permeates every aspect of our modern lives. In many applications, such in the software for airplane flight controls, or nuclear power control systems software failures can have catastrophic consequences. As we place so much trust in software, how can we know if it is trustworthy? Through software assurance, we can attempt to quantify just that. Building complex, high assurance software is no simple task. The difficult information landscape of a software engineering project can make verification and validation, the process by which the assurance of a software is assessed, very difficult. In order to manage the inevitable information overload of complex software projects, we need software traceability, "the ability to describe and follow the life of a requirement, in both forwards and backwards direction. " The Center of Excellence for Software Traceability (CoEST) has created a compelling research agenda with the goal of ubiquitous traceability by 2035. As part of this goal, they have developed TraceLab, a visual experimental workbench built to support design, implementation, and execution of traceability experiments. Through our collaboration with CoEST, we have made several contributions to TraceLab and its community. This work contributes to the goals of the traceability research community. The three key contributions are (a) a machine learning component package for TraceLab featuring six (6) classifier algorithms, five (5) clustering algorithms, and a total of over 40 components for creating TraceLab experiments, built upon the WEKA machine learning package, as well as implementing methods outside of WEKA; (b) the design for an automated tracing system that uses clustering to decompose the task of tracing into many smaller tracing subproblems; and (c) an implementation of several key components of this tracing system using TraceLab and its experimental evaluation.
Cerebellar Contributions to Major Depression

Extending beyond the motor domain, the cerebellum is involved in various aspects of cognition and affect. Multidisciplinary evidence has demonstrated topographic organization of higher-order cognitive functions within the cerebellum. We here review recent neuroimaging research that indicates cerebellar contributions to major depressive disorder (MDD). At the structural level, increased volume of lobule IX has been demonstrated in MDD patients, independent of acute or remitted disease state. Successful treatment with electroconvulsive therapy has been associated with increased lobule VIIA volume in depressed patients. At the functional level, connectivity analyses have shown reduced cerebro-cerebellar coupling of lobules VI and VIIA/B with prefrontal, posterior parietal, and limbic regions in patients with MDD. As a limitation, most of this evidence is based on smaller patient samples with incomplete phenotypic and neuropsychological characterization and with heterogenous medication. Some studies did not apply cerebellum-optimized data analysis protocols. Taken together, MDD pathophysiology affects distinct subregions of the cerebellum that communicate with cortical networks subserving cognitive and self-referential processing. This mini-review synthesizes research evidence from cerebellar structural and functional neuroimaging in depression, and provides future perspectives for neuroimaging of cerebellar contributions to MDD.