Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural networks and Markov models for the iterated prisoner's dilemma

The study of strategic interaction among a society of agents is often handled using the machinery of game theory. This research examines how a Markov Decision Process (MDP) model may be applied to an important element of repeated game theory: the iterated prisoner's dilemma. Our study uses a Markovian approach to the game to represent the problem of in a computer simulation environment. A pure Markov approach is used on a simplified version of the iterated game and then we formulate the general game as a partially observable Markov decision process (POMDP). Finally, we use a cellular structure as an environment for players to compete and adapt. We apply both a simple replacement strategy and a cellular neural network to the environment.
Telemedicine : What Do We Know and What Do We Need To Know ?

With the implementation of veterans integrated service networks (VISNs) and the shift toward communitybased primary care, VA has made tremendous strides in improving access to veterans’ health care. We know, for example, that the number of veterans served by VA increased 30 percent from 1996 to 2000. In addition, more than 400 VA community-based outpatient clinics (CBOCs) currently provide care to veterans throughout the system. Moreover, 87 percent of veterans who enroll for VA health care services are able to be seen by a VA provider within 30 miles of their home. These are substantial accomplishments! Technological advances are also helping VA improve access to care. Telephone triage and advice programs have been implemented at all VA hospitals, and health education is available to veterans on the Internet. Last year, VA provided more than 350,000 consultations via telemedicine. Telemedicine and in-home teleconsultation programs have also been implemented for spinal cord injury patients. In 1998 and 1999, the Vet Center program implemented the Vet CenterLinked Primary Care Project, which uses telemedicine to make primary care more accessible for high-risk, under-served veterans. In addition, the use of computers and electronic communication is improving care coordination and cutting through barriers of care. One new software program, Web Top, allows VA physicians and nurses to view patient records from other sites. With “real-time” information sharing, the medical decision-making process is expedited and patients receive the services they need faster. VA has also made it easier for veterans to apply for VA health care by eliminating nearly threequarters of the forms we once required for application and enrollment. Veterans may now obtain applications for enrollment and medical care on the Internet. In addition, they can send the forms electronically to the VA health care facilities of their choice, or they can print out the completed forms and mail them.
A centralized algorithm for adaptive coverage in next generation cellular networks

Reducing the energy consumption in wireless networks while maintaining the promised Long Term Evolution (LTE) high data rate has become a significant problem for network providers. To tackle these two conflicting objectives, this paper proposes to use Pico-eNBs in conjunction with a centralized switch on/off algorithm to create an adaptive radio coverage to match the radio resources to the user demand. The proposed approach relies on developing advanced centralized Self Organizing Network (SON) techniques to deploy, monitor and manage radio resources. The simulation results show that the proposed algorithm for adaptive coverage has improved the average throughput from 5.9 Mbps using Macro-eNBs to 47.9 Mbps, and the power consumption was reduced.
Trip-time-based Congestion Detection

To regulate network traffic and ensure that every user can get a reasonable quality of service whatever the load, networking protocols need to implement some sort of congestion control. To be able to control congestion, one must first know when it occurs and to which extent. This is the scope of congestion detection. Till now, congestion detection has only been based on packet losses. Protocols like TCP assume that a packet loss is a consequence and a signal of the network’s overload. Anyway, this detection scheme has a number of flaws1. In this report, we discuss the possibility of detecting congestion from the packets’ trip times. We first analyse the characteristics and distribution of One-way Trip Time or OTT. We then design a scheme of detection based on OTT measurements, and validate this scheme by simulation over a large range of situations. 1 Distribution of the One-way Trip Time
Entropy-of-likelihood feature selection for image correspondence

Feature points for image correspondence are often selected according to subjective criteria (e.g. edge density, nostrils). In this paper, we present a general, nonsubjective criterion for selecting informative feature points, based on the correspondence model itself. We describe the approach within the framework of the Bayesian Markov random field (MRF) model, where the degree of feature point information is encoded by the entropy of the likelihood term. We propose that feature selection according to minimum entropy-of-likelihood (EOL) is less likely to lead to correspondence ambiguity, thus improving the optimization process in terms of speed and quality of solution. Experimental results demonstrate the criterion's ability to select optimal features points in a wide variety of image contexts (e.g. objects, faces). Comparison with the automatic Kanade-Lucas-Tomasi feature selection criterion shows correspondence to be significantly faster with feature points selected according to minimum EOL in difficult correspondence problems.
The Smoothed-Dirichlet distribution : Explaining KL-divergence based ranking in Information Retrieval

In this work, we analyze the popular KLdivergence ranking function in information retrieval. We uncover the generative distribution, namely the Smoothed Dirichlet distribution, underlying this ranking function and show that this distribution captures term occurrence distribution much better than the multinomial, thus offering, for the first time, a reason behind the success of the KLdivergence ranking function. We present theoretically motivated approximations to the distribution that lead to a closed form maximum likelihood solution, much like the multinomial, making it ideal for online IR tasks. We use the new distribution to construct a new, well-motivated ad-hoc retrieval algorithm. Our experiments show that this algorithm performs at least as well as similar algorithms that employ cross-entropy ranking. It also provides additional flexibility, e.g. in handling scenarios like a mixture of true and pseudo relevance feedback, due to a consistent generative framework.
MOLECULAR CHARACTERISATION OF RET TYROSINE KINASE SIGNALLING

10 1. REVIEW OF THE LITERATURE 11 1.1 RET RECEPTOR TYROSINE KINASE 11 1.1.1 RET gene and RET proteins 11 1.1.2 RET is a functional receptor for GDNF-family ligands (GFLs). 12 1.1.3 RET-dependent GFLs signaling 14 1.1.4 RET-independent GDNF/GFRα1 signaling 17 1.1. 5 Activation of RET by other growth factors 18 1.1. 6 Role of RET signaling during development 19 1.2 RET INTERACTINGPROTEINS 20 1.2. 1 Downstream signalling pathways 22 1.2. 2 Shc family adaptor proteins 23 1.3 RET ACTIVATION IN HUMAN CANCER 25 1.3.1 RET in papilary carcinomas of the thyroid gland 25 1.3.2 Other genes activated in papilary thyroid carcinomas (PTCs). 30 1.3.3 Medulary thyroid carcinoma 30 1.3.4 RET in MEN 2 syndromes 31 1.3.5 RET in sporadic medulary thyroid carcinoma (sMTC) 36 1.3.6 Diagnosis and management of MEN 2 38 1.4 RET GERMLINE INACTIVATING MUTATIONS IN HIRSCHSPRUNG’S DISEASE 40 2. AIMS OF THE PRESENT STUDY 45 3. MATERIALS AND METHODS 46 3.1 Cel lines 46 3.2 Antibodies,growth factors,recombinant proteins,chemical inhibitors. 46 3.3 DNA constructs 47 3.4 Transfection of cel lines 48 3.5 Adenovirus construction 49 3.6 Immunoprecipitations 49 3.7 GST proteins 50 3.8 Western bloting 50 3.9 In vitro kinase assays 50 3.10 Biotinylation of cel surface proteins 50 3.11 I-labeled GDNF and HGF binding, chemical cross-linking. 50 3.12 Cel migration and chemotaxis assays 51 3.13 Branching tubule formation assay in colagen gel 51 3.14 Cel apoptosis assays 51 3.15 Cel proliferation assays 51 3.16 Anchorage-independent growth assay 51 3.17 Kidney cultures 51
CloakingNote: A Novel Desktop Interface for Subtle Writing Using Decoy Texts

We present CloakingNote, a novel desktop interface for subtle writing. The main idea of CloakingNote is to misdirect observers' attention away from a real text by using a prominent decoy text. To assess the subtlety of CloakingNote, we conducted a subtlety test while varying the contrast ratio between the real text and its background. Our results demonstrated that the real text as well as the interface itself were subtle even when participants were aware that a writer might be engaged in suspicious activities. We also evaluated the feasibility of CloakingNote through a performance test and categorized the users' layout strategies.
Irregular transcription dynamics for rapid production of high-fidelity transcripts

Both genomic stability and sustenance of day-to-day life rely on efficient and accurate readout of the genetic code. Single-molecule experiments show that transcription and replication are highly stochastic and irregular processes, with the polymerases frequently pausing and even reversing direction. While such behavior is recognized as stemming from a sophisticated proofreading mechanism during replication, the origin and functional significance of irregular transcription dynamics remain controversial. Here, we theoretically examine the implications of RNA polymerase backtracking and transcript cleavage on transcription rates and fidelity. We illustrate how an extended state space for backtracking provides entropic fidelity enhancements that, together with additional fidelity checkpoints, can account for physiological error rates. To explore the competing demands of transcription fidelity, nucleotide triphosphate (NTP) consumption and transcription speed in a physiologically relevant setting, we establish an analytically framework for evaluating transcriptional performance at the level of extended sequences. Using this framework, we reveal a mechanism by which moderately irregular transcription results in astronomical gains in the rate at which extended high-fidelity transcripts can be produced under physiological conditions.
Intrusion Alert Correlation Technique Analysis for Heterogeneous Log

Summary Intrusion alert correlation is multi-step processes that receives alerts from heterogeneous log resources as input and produce a high-level description of the malicious activity on the network. The objective of this study is to analyse the current alert correlation technique and identify the significant criteria in each technique that can improve the Intrusion Detection System (IDS) problem such as prone to alert flooding, contextual problem, false alert and scalability. The existing alert correlation techniques had been reviewed and analysed. From the analysis, six capability criteria have been identified to improve the current alert correlation technique. They are capability to do alert reduction, alert clustering, identify multistep attack, reduce false alert, detect known attack and detect unknown attack.
Childhood Psychopathology and Autonomic Dysregulation: Exploring the Links using Heart Rate Variability

Changes in cardiovascular reactivity have been used as a psychophysiological marker of various emotional states in both children and adults. Recent decades have seen increasing use of heart rate variability as a non-invasive marker of cardiac autonomic function and of central processes involved in autonomic function regulation. Developmental research has linked cardiac vagal tone to an individual’s responsivity to environmental challenges and a decrease in vagal component of heart rate variability may reflect deficiencies in emotional regulatory system. Studies with children and adolescents suggest that attenuated cardiac vagal function is seen in various pathophysiological conditions characterised by emotional dysregulation. Thus, alteration in cardiac vagal modulation may be the common mechanism underpinning the association between negative affective states, emotional dysregulation and risk for cardiac disease.
Automatic extraction of content on the Web with intelligent algorithm

-Since the INTERNET outburst, consumer perception turned into a complex issue to be measured. Non-traditional advertising methods and new product exhibition alternatives emerged. Forums and review sites allow end users to suggest, recommend or rate products according to their experiences. This gave raise to the study of such data collections. After analyze, store and process them properly, they are used to make reports used to assist in middle to high staff decision making. This research aims to implement concepts and approaches of artificial intelligence to this area. The framework proposed here (named GDARIM), is able to be parameterized and handled to other similar problems in different fields. To do that it first performs deep problem analysis to determine the specific domain variables and attributes. Then, it implements specific functionality for the current data collection and available storage. Next, data is analyzed and processed, using Genetic Algorithms to retro feed the keywords initially loaded. Finally, properly reports of the results are displayed to stakeholders.
EaSd: A System for Extracting and Annotating Structured Data

Many Web pages are generated dynamically inr esponse to an online query. Structured data are contained in those pages and will be useful for information integration. In this paper, we propose a system, EaSd, to automatically extract data records from those Web pages and annotate the record attributes. Using the VIPS as the data representation format of the Web pages, we deal with those two problems in a uniform process based on the query instance. For data extraction, the VIPS is a better way for Web page representation than tag-tree and makes the extraction result better correspond. EaSd annotates the record attributes with integrated interface schema and has a more consistent and complete annotation result. Also, the experimental results we got show the promise of our approach.
Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors “Mathematical Test Anxiety” (MTA) and “Numerical Anxiety” (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established.
The Prevalence of Anger Rumination and its Relationship with Coping Strategies and Assertiveness in Students

Objectives: The aim of this study was to examine the prevalence of anger rumination and its relationship with coping strategies and assertiveness in students of Mohaghegh Ardebili University. Methods: the present research was a descriptive correlational study. The study population consisted of all students enrolled in the academic year 1390-91 (N = 8344). In the first step, to determine the prevalence of anger rumination, 400 students were selected based on multistage cluster sampling method and Sadolwsky’s anger rumination questionnaires was completed by students. Next, 100 of these students were selected based on simple random sampling and the Lazarus and Folkman, coping strategies questionnaire, and the Shrink assertiveness questionnaire were administered on them. Data were analyzed by descriptive indicators, Pearson’s correlation coefficient and multiple regression analysis. Results: The results showed that the prevalence of anger rumination in students of Mohaghegh Ardabil University is 11%. Anger rumination with problem-oriented coping strategies and assertiveness showed a negative and significant correlation while (anger rumination) with emotion-oriented coping strategies showed positive and significant correlation. Also results of multiple regression analysis showed that emotion-oriented coping strategy and assertiveness could predict significantly the student's anger rumination. Discussion: Since the identification of different kinds of obsessive and intrusive thoughts is important achieve to desirable control of thoughts, so, investigate of prevalence of anger rumination in order to manage it is valuable. So teaching problem-oriented coping and assertiveness ability as a factor of anger control could reduce the prevalence of anger rumination among students and thereby help to management vicious cycle of aggressive behavior.
Internal-growth Strategies for Dynamic Process Optimization with Differential-algebraic Equations

Abstract Simultaneous methods based on numerical differentiation for process dynamic optimization are discussed, and succinct variants of the full discretized models, which are collocated by Lobatto methods, are proposed. With the same original dynamic problem, its discretized models with different number of finite elements have good structural similarity, and their optimal results can also fit well with each other. A novel solving idea is proposed that the low-density discretized solution is interpolated as the starting point for solving high-density discretized model, then the warm-start technology for the interior point method and the initial value setting method of barrier parameter are integrated to develop a fast solving strategy for dynamic optimization, named internal-growth approach. Finally, several test models, including the crystallization process optimization problem, are solved by the proposed approach, and the excellent solving efficiency is illustrated.
L 2 strategies of morphological variability in the morphosyntactic acquisition of German DPs

Cette recherche se propose d’explorer, au sein du cadre générativiste, l’interface syntaxe-morphologie du domaine nominal en L2 chez un groupe d’adultes de langue maternelle italienne apprenant l’allemand. En particulier, nous nous sommes intéressés à la relation qui lie le placement des modificateurs nominaux par rapport aux noms et l’insertion à la fois de matériel morphologique sur les adjectifs attributifs et du –s du génitif possessif. Nos résultats montrent que les apprenants adultes n’ont aucune difficulté en ce qui concerne l’ordre linéaire cible de la L2. En revanche, la flexion morphologique des modificateurs nominaux est un domaine problématique pour les apprenants L2 qui font appel à différentes stratégies non seulement en fonction de l’élément concerné (le –s du génitif vs les adjectifs) mais aussi en fonction de la configuration syntaxique impliquée dans le processus flexionnel.
Extracellular matrix signatures of human mammary carcinoma identify novel metastasis promoters

The extracellular matrix (ECM) is a major component of tumors and a significant contributor to cancer progression. In this study, we use proteomics to investigate the ECM of human mammary carcinoma xenografts and show that primary tumors of differing metastatic potential differ in ECM composition. Both tumor cells and stromal cells contribute to the tumor matrix and tumors of differing metastatic ability differ in both tumor- and stroma-derived ECM components. We define ECM signatures of poorly and highly metastatic mammary carcinomas and these signatures reveal up-regulation of signaling pathways including TGFβ and VEGF. We further demonstrate that several proteins characteristic of highly metastatic tumors (LTBP3, SNED1, EGLN1, and S100A2) play causal roles in metastasis, albeit at different steps. Finally we show that high expression of LTBP3 and SNED1 correlates with poor outcome for ER−/PR−breast cancer patients. This study thus identifies novel biomarkers that may serve as prognostic and diagnostic tools. DOI: http://dx.doi. org/10.7554/eLife.01308. 001
Distinct Functions of Egr Gene Family Members in Cognitive Processes

The different gene members of the Egr family of transcriptional regulators have often been considered to have related functions in brain, based on their co-expression in many cell-types and structures, the relatively high homology of the translated proteins and their ability to bind to the same consensus DNA binding sequence. Recent research, however, suggest this might not be the case. In this review, we focus on the current understanding of the functional roles of the different Egr family members in learning and memory. We briefly outline evidence from mutant mice that Egr1 is required specifically for the consolidation of long-term memory, while Egr3 is primarily essential for short-term memory. We also review our own recent findings from newly generated forebrain-specific conditional Egr2 mutant mice, which revealed that Egr2, as opposed to Egr1 and Egr3, is dispensable for several forms of learning and memory and on the contrary can act as an inhibitory constraint for certain cognitive functions. The studies reviewed here highlight the fact that Egr family members may have different, and in certain circumstances antagonistic functions in the adult brain.
A Genetic Algorithm to Optimize a Tweet for Retweetability

Twitter is a popular microblogging platform. When users send out messages, other users have the ability to forward these messages to their own subgraph. Most research focuses on increasing retweetability from a node's perspective. Here, we center on improving message style to increase the chance of a message being forwarded. To this end, we simulate an artificial Twitter-like network with nodes deciding deterministically on retweeting a message or not. A genetic algorithm is used to optimize message composition, so that the reach of a message is increased. When analyzing the algorithm's runtime behavior across a set of different node types, we find that the algorithm consistently succeeds in significantly improving the retweetability of a message.
The role of long-term working memory in text comprehension.

A distinction is made between short-term working memory, which is capacity limited, and long-term working memory , which is available to experts in their domain of expertise . Text comprehension is viewed as expert performance. The role of long-term working memory in text comprehension is analyzed, with an emphasis on the activation of relevant knowledge during comprehension . Latent semantic analysis used to model knowledge activation in text comprehension.