Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy End-to-End Rate Control for Internet Transport Protocols

End-to-end Internet packet dynamics is a complex problem for which models available to date are at best incomplete. A major research problem in Internet transport layer protocols is the development of rate control mechanisms that can cope with the requirements of a growing diversity of technologies, applications and services. This paper describes novel mechanisms for intelligent end-to-end traffic rate control in Internet by means of fuzzy systems. We first outline a fuzzy logic based generalization of TCP (Transport Control Protocol) rate control principles. The design of a fuzzy TCP-like window-based rate controller is then described. A systematic fuzzy systems design methodology is used in order to simulate and implement the system as an experimental tool. A comparative evaluation of simulation and implementation results from the fuzzy rate controller as compared to that of traditional controllers is outlined. Besides being a useful modelling approach, the fuzzy rule based rate controller is shown to outperform other approaches with regards to a number of criteria.
TMT DEMOGRAPHY, CONFLICT AND (EFFECTIVE) DECISION MAKING: THE KEY ROLE OF VALUE CONGRUENCE.

The article examines the relationships among top management team (TMT) heterogeneity, conflict and decision making effectiveness. It analyzes the supposition that heterogeneity and conflict are complementary under the right conditions, which enable better TMT functioning and better decisions. The authors assert that TMTs with high value congruence and high demographic heterogeneity will experience higher task conflict while experiencing lower relationship conflict at the same time. It is also anticipated that the values of the TMT members will influence the ways in which they interpret and respond to disagreements.
Metaphorical Uses of Language in the Expression of Emotions

Two hypotheses concerning the function of metaphor production were examined in participants' descriptions of instances of emotional states and events. Participants provided verbal descriptions of emotional states they had experienced and of actions in which they had engaged as they experienced those states. Results showed that descriptions of emotional states contained more metaphorical language than did descriptions of behaviors. This is interpreted as supporting the hypothesis that an important function of metaphorical language is to permit the expression of that which is difficult to express using literal language alone. The results also indicated that intense emotions led to greater metaphor use than mild emotions for descriptions of feeling states but not for descriptions of actions associated with emotions. This result was interpreted as consistent with the view that metaphors provide a particularly vivid form of description.
Application of the high-risk strategy to control dental caries.

OBJECTIVE The aim of this prospective study was to determine whether a child population with low overall caries frequency benefits when prevention is targeted to high-risk individuals. METHODS Data from clinical examinations and salivary tests were used to assess caries risk in 12-year-olds (n=1465). Children who were regarded as being at high risk of developing caries were randomized into two groups. Half (HRI group) were offered intensive prevention (counseling, F-varnish applications, F-lozenges, sealants, chlorhexidine), and the other half (HRB group) were provided the same basic prevention given to low-risk children (counseling, one F-varnish application/year). A random sample of the low-risk children (LRB) was followed up for the same 3-year period as the high-risk children. The number of children completing the study was 216 in the LRB group, 199 in the HRI group and 174 in the HRB group. RESULTS The mean (SD) 3-year DMFS increment was 2.0 (2.4), 4.4 (4.7) and 5.1 (5.0) in the LRB, HRI and HRB groups, respectively. Comparison between the LRB and HRB groups revealed that risk assessment was fairly successful in terms of mean DMFS increment. However, 63% of the children in the LRB group developed at least one new lesion (max. 12). CONCLUSIONS The negligible difference between the HRI and HRB groups implies that intensifying prevention produced practically no additional benefit. By offering all children only basic prevention, virtually the same preventive effect could have been obtained with substantially less effort and lower costs.
Construction of Analytic Frameworks for Component-Based Architectures

Prediction of non-functional properties of software architectures requires technologies that enable the application of analytic theories to component models. However, available analytic techniques generally operate on formal models specified in notations that cannot flexibly and intuitively capture the architectures of large-scale distributed systems. The construction of model interpreters that transform architectural models into analysis models has proved to be a time-consuming and difficult task. This paper describes (1) how a reusable model interpreter framework can reduce the complexity involved in this task, and (2) how such a framework can be designed, implemented, utilized, and verified.
Organizational Learning: A Theory Of Action Perspective

«. Intervenir es entrar en un conjunto de relaciones en desarrollo con el proposito de ser util. El tipo de ayuda en el que nos vamos a centrar consiste en aumentar la capacidad para una buena dialectica organizativa —es decir, la capacidad de indagacion organizativa para encajar errores, incongruencias e incompatibilidades en una teoria organizativa de la accion la cual necesariamente emerge a medida que el sistema organizativo/ambiental cambia» (p. 158). «. Nuestra actividad en la intervencion debe por tanto ocuparse de tres propositos. Estos son: 1) ayudar al cliente a ser consciente y a descongelar sus teorias al uso del Modelo I y sistemas de aprendizaje O-I, y 2) educar al cliente a usar el Modelo II y a crear sistemas de aprendizaje O-II, para 3) usar este nuevo conocimiento con el fin de lograr una buena dialectica organizativa. Llamamos a la actividad de intervencion que incluye las tres intenciones una intervencion extensa» (p. 166).
The label knows better: The impact of labeling effects on perceived quality of HD and UHD video streaming

There is an ongoing debate in the research community over the improved visual quality of UHD video in comparison to the still widely-deployed HD standard. It is the inspiration of many scientific studies, yet UHD displays and services are continuously spreading on the consumer market. This paper presents the results of a subjective paired-comparison test with both upscaled HD and UHD video sequences, investigating the primary research question of whether UHD can offer a significant improvement over HD for common viewing conditions. In our study, subjects rated their visual preference on video-only clips without lossy encoding. In addition we studied cognitive biases, by presenting a label of what users were about to see (HD or UHD) before the sequence, purposely manipulating the labels in some conditions to suggest different resolutions than actually shown. Finally, we investigated the impact of different rating scales on the precision of the results. Our studies show that HD clips appear indistinguishable from UHD clips when the rating scale chosen is not fine-grained enough. We also found that the labeling effect has a significant impact on the perceived quality, overriding the actual visual perception. Even with a precise scale, users cannot detect major improvements of UHD compared to HD, which may let us question the added value offered by UHD.
When less is more: Meaningful learning from visual and verbal summaries of science textbook lessons.

In a series of 3 experiments, college students who read a summary that contained a sequence of short captions with simple illustrations depicting the main steps in the process of lightning recalled these steps and solved transfer problems as well as or better than students who received the full text along with the summary or the full text alone. In Experiment 2, taking away the illustrations or the captions eliminated the effectiveness of the summary. In Experiment 3, adding text to the summary reduced its effectiveness. Implications for a cognitive theory of multimedia learning are discussed; implications for instructional design pertain to the need for conciseness, coherence, and coordination in presenting scientific explanations. Consider the following scenario. A student who is inexperienced in meteorology reads a textbook lesson explaining the cause-and-effect chain of events involved in how lightning storms develop. The explanation is clearly contained within the 600 words and five illustrations of the lesson. A few minutes later, we ask the student to write down the explanation (as a retention test) and to solve some problems that require using the explanation from the lesson (as a transfer test). For example, as a transfer problem, we ask the student to write an explanation for why there can be clouds in the sky but no lightning. Despite exerting considerable effort, the student performs poorly on both the retention and the transfer task, indicating a lack of understanding of the process of lightning.
Young-Adult Male Rats' Vulnerability to Chronic Mild Stress Is Reflected by Anxious-Like instead of Depressive-Like Behaviors

In a previous study, we found that chronic mild stress (CMS) paradigm did not induce anhedonia in young-adult male rats but it reduced their body weight gain. These contrasting results encouraged us to explore other indicators of animal's vulnerability to stress such as anxious-like behaviors, since stress is an etiologic factor also for anxiety. Thus, in this study, we evaluated the vulnerability of these animals to CMS using behavioral tests of depression or anxiety and measuring serum corticosterone. Male Wistar rats were exposed to four weeks of CMS; the animals' body weight and sucrose preference (indicator of anhedonia) were assessed after three weeks, and, after the fourth week, some animals were evaluated in a behavioral battery (elevated plus maze, defensive burying behavior, and forced swimming tests); meanwhile, others were used to measure serum corticosterone. We found that CMS (1) did not affect sucrose preference, immobility behavior in the forced swimming test, or serum corticosterone; (2) decreased body weight gain; and (3) increased the rat's entries into closed arms of the plus maze and the cumulative burying behavior. These data indicate that young male rats' vulnerability to CMS is reflected as poor body weight gain and anxious-like instead of depressive-like behaviors.
Personal Advertisements: Sources of Data about Relationships

Personal advertisements are a growing means of meeting other people and establishing relationships. The variety of these advertisements makes them an excellent source of data for social science research, but this interesting resource is presently underutilized. This article attempts to persuade more social scientists to use personal ads as a source of research data and it discusses the positive features of this data source and outlines various research methods possible with them. Existing studies using personal advertisements as a source of data are reviewed as illustrations of the methods presented.
How Affect Shapes Risky Choice: Distorted Probability Weighting Versus Probability Neglect

People's choices between prospects with relatively affect-rich outcomes (e.g., medical side effects) can diverge markedly from their choices between prospects with relatively affect-poor outcomes (e.g., monetary losses). We investigate the cognitive mechanisms underlying this 'affect gap' in risky choice. One possibility is that affect-rich prospects give rise to more distortion in probability weighting. Another is that they lead to the neglect of probabilities. To pit these two possibilities against each other, we fitted cumulative prospect theory (CPT) to the choices of individual participants, separately for choices between options with affect-rich outcomes (adverse medical side effects) and options with affect-poor outcomes (monetary losses); additionally, we tested a simple model of probability neglect, the minimax rule. The results indicated a qualitative difference in cognitive mechanisms between the affect-rich and affect-poor problems. Specifically, in affect-poor problems, the large majority of participants were best described by CPT; in affect-rich problems, the proportion of participants best described by the minimax rule was substantially higher. The affect gap persisted even when affect-rich outcomes were supplemented by numerical information, thus providing no support for the thesis that choices in affect-rich and affect-poor problems diverge because the information provided in the former is nonnumerical. Our findings suggest that the traditional expectation-based framework for modeling risky decision making may not readily generalize to affect-rich choices. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
MR Imaging of Central Nervous System Tumors that Do Not Display Increase in Tl or T2

A retrospective review of brain tumors examined with magnetic resonance imaging has shown that \2% of tumors or their components do not display evidence of an increase in Tl or T2 when examined with highly Tl dependent inversion recovery or highly T2 dependent spin echo sequences. This was observed in lipid containing tumors, malignant melanomas, tumors containing hemorrhage, acoustic neuromas, meningiomas, hamartomas, a pituitary prolactinoma, astrocytomas (grade I) treated with radiotherapy, pediatric tumors, and cases of unknown cause.
Nonlinear EGR and VGT Control with Integral Action for Diesel Engines

A non-linear multivariable control design with integral action is proposed and investigated for control of Exhaust Gas Recirculation (EGR) and Variable Geometry Turbocharger (VGT) in heavy duty diesel engines. The main control goal is to regulate oxygen/fuel ratio and intake manifold EGR-fraction, and they are specified in an outer loop. These are chosen as main performance variables since they are strongly coupled to the emissions. An existing non-linear control design based on feedback linearization is extended with integral action. In particular the control design method utilizes a control Lyapunov function, inverse optimal control, and a non-linear compensator. Comparisons between different control structures are performed in simulations showing the following four points. Firstly, integral action is necessary to handle model errors so that the controller can track the performance variables specified in the outer loop. Secondly, the proposed control design handles the non-linear effects in the diesel engine that results in less control errors compared to a control structure with PID controllers. Thirdly, it is important to use the non-linear compensator and it is sufficient to use a control structure with PID controllers and a non-linear compensator to handle the non-linear effects. Fourthly, the proposed control design is sensitive to model errors in the EGR and turbine flow model while a control structure with PID controllers and a non-linear compensator handles these model errors.
Image annotation by composite kernel learning with group structure

We can obtain more and more kinds of heterogeneous features (such as color, shape and texture) in images which can be extracted to describe various aspects of visual characteristics. Those high-dimensional heterogeneous visual features are intrinsically embedded in a non-linear space. In order to effectively utilize these heterogeneous features, this paper proposes an approach, called Composite Kernel Learning with Group Structure (CKLGS), to select groups of discriminative features for image annotation. For each image label, the CKLGS method embeds the nonlinear image data with discriminative features into different Reproducing Kernel Hilbert Spaces (RKHS), and then composes these kernels to select groups of discriminative features. Thus a classification model can be trained for image annotation. By the comparisons with other image annotation algorithms, experiments show that the proposed CKLGS for image annotation achieves a better performance.
Hearing impaired adolescents' signed and written expression of locative state relations

ABSTRACT Hearing impaired adolescents from three schools were asked to produce sentences expressing simple locative state relations. Subjects varied on three hearing levels, two ages, and the use or nonuse of sign language. All subjects wrote English sentences to describe pictures; signers also described pictures in sign. Data were analyzed using chi-square procedures. Errors of noun reversal and pragmatic focus were apparent in 7% of the signed responses and 15% of the written responses. Errors were produced by subjects at each age and hearing level, and by signers and nonsigners as well. Most errors were produced by profoundly hearing impaired signers attending public day school (as compared to residential school). Implications for instruction and for further research are discussed.
Normalization of Cdna Microarray Data Based on Least Absolute Deviation Regression

This paper proposes a method of normalization of cDNA microarray data. This approach uses all gene data to estimate the normalization parameters and it obtains these parameters using an algorithm based on least absolute deviation (LAD) regression. This method normalizes iteratively each microarray set after the estimation of the normalization parameters which uses a LAD regression algorithm. The normalization method has a robust performance since it assumes that the errors between arrays follow a Laplacian distribution, leading to the mean absolute error minimization as a performance criterion to be achieved. The proposed normalization method was evaluated using three performance measures and they show that LAD based normalization method minimizes the errors and provides a more consistent replicated data spread with respect to a least square based method
RET gene mutations (genotype and phenotype) of multiple endocrine neoplasia type 2 and familial medullary thyroid carcinoma

The rapid technical advances in molecular biology and accelerating improvements in genomic and proteomic diagnostics have led to increasingly personalized strategies for cancer therapy. Such an approach integrates the genomic, proteomic, and molecular information unique to the individual to provide an accurate genetic diagnosis, molecular risk assessment, informed family counseling, therapeutic profiling, and early preventative management that best fits the particular needs of each patient. The discovery of mutations in the RET proto‐oncogene resulting in variable onset and severity of multiple endocrine neoplasia type 2 (MEN2) was the first step in developing direct genetic testing for at‐risk individuals. Patients with germline RET mutations may undergo risk assessment and appropriate intervention based on specific mutations. Moreover, family members of affected individuals receive counseling based on understanding of the genetic transmission of the disease. Increasingly, clinicians are able to make therapeutic choices guided by an informative biomarker code. Improvements in detection and management of patients with MEN2 resulting from understanding of the RET proto‐oncogene are evidence of the benefits of personalized cancer medicine. This review describes the discovery of the RET proto‐oncogene, the association between genotype and phenotype, and the role of mutation analysis on diagnosis and treatment of MEN2. Cancer 2014;120:1920–1931. © 2014 American Cancer Society.
A highly conserved transcriptional repressor controls a large regulon involved in lipid degradation in Mycobacterium smegmatis and Mycobacterium tuberculosis

The Mycobacterium tuberculosis TetR‐type regulator Rv3574 has been implicated in pathogenesis as it is induced in vivo, and genome‐wide essentiality studies show it is required for infection. As the gene is highly conserved in the mycobacteria, we deleted the Rv3574 orthologue in Mycobacterium smegmatis (MSMEG_6042) and used real‐time quantitative polymerase chain reaction and microarray analyses to show that it represses the transcription both of itself and of a large number of genes involved in lipid metabolism. We identified a conserved motif within its own promoter (TnnAACnnGTTnnA) and showed that it binds as a dimer to 29 bp probes containing the motif. We found 16 and 31 other instances of the motif in intergenic regions of M. tuberculosis and M. smegmatis respectively. Combining the results of the microarray studies with the motif analyses, we predict that Rv3574 directly controls the expression of 83 genes in M. smegmatis, and 74 in M. tuberculosis. Many of these genes are known to be induced by growth on cholesterol in rhodococci, and palmitate in M. tuberculosis. We conclude that this regulator, designated elsewhere as kstR, controls the expression of genes used for utilizing diverse lipids as energy sources, possibly imported through the mce4 system.
Visualization techniques utilizing the sensitivity analysis of models

Models of real world systems are being increasingly generated from data that describes the behaviour of systems. Data mining techniques, such as Artificial Neural Networks (ANN), generate models almost independently and deliver accurate models in a very short time. These models (sometimes called black box models) have complex internal structures that are difficult to interpret and we have very limited information about the credibility of their output. A model can be trusted just for certain configurations of input variables, but it is hard to determine which output is based on training data and which is random. In this paper, we present visualization techniques for exploration of models. Primary goal is to consider the behavior of the model in the neighborhood of the data vectors. The next goal is to estimate and locate the ranges in input space where the models are credible. We have developed visualization techniques both for regression and classification problems. Finally, we present an algorithm that is able to automatically locate the most interesting visualizations in the vast multidimensional space of input variables.
Object Clitic Omission in French-Speaking Children: Effects of the Elicitation Task

In French, the acquisition of object clitics seems delayed, and omissions are documented. In this article, we look at the experimental paradigm traditionally used to elicit object clitics and propose a new elicitation procedure that is closer to how clitics are produced in spontaneous production. We show that under the proposed new experiment, the results in elicited production align with those in spontaneous production, and omission of object clitics is minimal. We briefly outline the implications for the analysis of the omission phenomenon.
Stability analysis for an improved power optimization method applied to a wind energy conversion system

The aim of this paper is to analyse the closed-loop stability of a squirrel-cage-induction-generator-based wind energy conversion system equipped with an improved power optimization control law. This control imposes a dependence between the generator torque and its rotational speed, thus heavily modifying the system dynamics and control efforts. A stability analysis made through numerical simulation gives the operating limits of the proposed control.