Miracle-dz/UniFAR-FTUs huggingface dataset:
A feasibility study on using clustering algorithms in programming education research

Designing an experiment for programming education research, in which collecting and interpreting a large number of qualitative data about programmers is required, needs careful consideration in order to validate the experiment. When it comes to finding a pattern in the programming behaviour of a specific group of programmers (e,g. novice, intermediate or expert programmers), one of the critical issues is the selection of similar participants who can be placed in one group. In this study we were interested in finding a method that could shorten the path to finding participants. Therefore, the use of clustering algorithms to group similar participants was put to test in order to investigate the effectiveness and feasibility of this approach. The clustering algorithms that were used for this study were K-means and DBSCAN. The results showed that the use of these algorithms, for the mentioned purpose, is feasible and that both algorithms can identify similar participants and place them in the same group while participants who are not similar to others, and therefore are not the correct subject of the study, are recognised.
Named Entity Recognition: a Literature Survey

In this report, we explore various methods that are applied to solve NER. In section 1, we introduce the named entity problem. In section 2, various named entity recognition methods are discussed in three three broad categories of machine learning paradigm and explore few learning techniques in them. In the first part, we discuss various supervised techniques. Subsequently we move to semi-supervised and unsupervised techniques. In the end we discuss about the method from deep learning to solve NER.
Burden of Depressive Disorders by Country, Sex, Age, and Year: Findings from the Global Burden of Disease Study 2010

In this paper, Ferrari and colleagues analyzed the burden of depressive disorders in GBD 2010 and identified depressive disorders as a leading cause of burden. The authors present severity proportions; burden by country, region, age, sex, and year; as well as burden of depressive disorders as a risk factor for suicide and ischemic heart disease. Please see later in the article for the Editors' Summary
Music and 25% glucose pain relief for the premature infant: a randomized clinical trial 1

OBJECTIVE: to analyze the total Premature Infant Pain Profile scores of premature infants undergoing arterial puncture during music and 25% glucose interventions, and to assess their association with neonatal and therapeutic variables. METHOD: a randomized clinical trial with 80 premature infants; 24 in the Experimental Group 1 (music), 33 in the Experimental Group 2 (music and 25% glucose), 23 in the Positive Control Group (25% glucose). All premature infants were videotaped and a lullaby was played for ten minutes before puncture in Experimental Groups 1 and 2; 25% glucose administered in Experimental Group 2 and the Positive Control Group two minutes before puncture. RESULTS: 60.0% of premature infants had moderate or maximum pain; pain scores and intervention groups were not statistically significant. Statistically significant variables: Experimental Group 1: head and chest circumference, Apgar scores, corrected gestational age; Experimental Group 2: chest circumference, Apgar scores, oxygen therapy; Positive Control group: birth weight, head circumference. CONCLUSION: neonatal variables are associated with pain in premature infants. Brazilian Registry of Clinical Trials: UTN: U1111-1123-4821.
Forward engineering the object oriented analysis and design

Current object oriented modeling languages either concentrating on application domain characteristics or system functionalities but not on both. Hence the absence of a common modeling language to represent application domain and system functionalities will disintegrate the analysis and design phases. This paper proposes a framework which uses Unified Modeling Language (UML) as the common modeling language in the two phases thereby integrating both phases.
Comparison of Feed-Forward and Recurrent Neural Networks in Active Cancellation of Sound Noise

Passive techniques such as barriers, silencers and isolation are bulky, costly and ineffective at low frequencies. Active cancellation of noise was presented because of these problems. In this paper, we want to investigate the uses of neural networks in active noise control (ANC). Feed-forward and recurrent neural networks are compared for active cancellation of sound noise. In order to compare the two networks the number of layers and neurons are equal in both of the networks. Moreover, training and test samples are similar for networks. The noise signals that are used for training the networks are selected from SPIB database. The results of simulation show the ability of these networks in noise cancellation. As it is seen, recurrent neural network has better performance in noise attenuation than the feed-forward neural network.
Contextual Identity : Freedom to be All Your Selves

We examine contextual identity, a notion that individuals reveal different aspects of themselves depending on context. At any given time, an individual may act as a friend, relative, spouse, co-worker, acquaintance, or stranger. We analyze contextual identity from the perspective of user choice and control, survey contextual identity violations, and propose new research directions to enable users to have better control over their contextual identities.
A Research Pathway for Experimental Psychopathology: The Role of External Validity Criteria

This paper outlines a putative pathway for experimental psychopathology research developing psychological models of clinical disorders. The pathway uses established external validity criteria to define the pathway and clarifies the important role that research conducted on healthy participants can play in our understanding of clinical disorders. Defining a research pathway for experimental psychopathology in this way has a number of benefits It would (1) make explicit the need to address the external validity of developed models, (2) provide a clear set of criteria that would be required to extend research on healthy individuals to diagnostic populations, and (3) recommend using general psychological knowledge when developing models of psychopathology.
PATH DEPENDENT OPTIONS AND THE EFFECT OF STOCHASTIC VOLATILITY

In modern asset price models, stochastic volatility plays a crucial role explaining several stylized facts of returns. Recently, Barndorff-Nielsen and Shephard [4] introduced a class of stochastic volatility models (the so called BNS SV model) based on superposition of Ornstein-Uhlenbeck processes driven by subordinators. The BNS SV model forms a flexible class, which can easily explain heavy-tails and skewness in returns and the typical time-dependency structures seen in asset return data. In this paper the effect of stochastic volatility on path-dependent options is studied. This is done by simulation studies of comparable models, one with and one without stochastic volatility.
Transmission, infectivity and survival of Diplostomum spathaceum cercariae

The transmission dynamics of the cercariae of Diplostomum spathaceum were investigated under laboratory conditions using cercariae collected from naturally infected Lymnaea stagnalis. Cercariae were kept in a constant temperature of 20 °C and the survival and infectivity to naïve young rainbow trout recorded at 3-h intervals until few cercariae were alive. Mortality initially remained constant but increased rapidly after 20 h. While a model of constant mortality fitted the survival data, an age-dependent model provided a better fit and implied that cercariae tended to carry similar quantities of resources and once these were exhausted the cercariae died. Cercarial infectivity also showed an age-dependent pattern although infectivity tended (P=0·09) to increase with age over the first 6 h of life and then fall. The per capita transmission rate of cercariae was investigated by experimentally infecting rainbow trout under standardized conditions, first with an increasing cercarial density and second, by keeping density constant but increasing numbers of cercariae. The per capita transmission rate was frequency dependent and averaged 0·341/h (±0·036).
Ventilator Weaning and Spontaneous Breathing Trials; an Educational Review

The term "weaning" is used to describe the gradual process of decreasing ventilator support. It is estimated that 40% of the duration of mechanical ventilation is dedicated to the process of weaning. Spontaneous breathing trial (SBT) assesses the patient's ability to breathe while receiving minimal or no ventilator support. The collective task force in 2001 stated that the process of SBT and weaning should start by assessing whether the underlying cause of respiratory failure has been resolved or not. Weaning predictors are parameters that are intended to help clinicians predict whether weaning attempts will be successful or not. Although the international consensus conference in 2005 did not recommend their routine use for clinical decision making, researchers did not stop working in this area. In the present article, we review some of the recent studies about weaning predictors, criteria, procedure, as well as assessment for extubation a mechanically ventilated patient.
Over a Century of Neuron Culture: From the Hanging Drop to Microfluidic Devices

The brain is the most intricate, energetically active, and plastic organ in the body. These features extend to its cellular elements, the neurons and glia. Understanding neurons, or nerve cells, at the cellular and molecular levels is the cornerstone of modern neuroscience. The complexities of neuron structure and function require unusual methods of culture to determine how aberrations in or between cells give rise to brain dysfunction and disease. Here we review the methods that have emerged over the past century for culturing neurons in vitro, from the landmark finding by Harrison (1910) — that neurons can be cultured outside the body — to studies utilizing culture vessels, micro-islands, Campenot and brain slice chambers, and microfluidic technologies. We conclude with future prospects for neuronal culture and considerations for advancement. We anticipate that continued innovation in culture methods will enhance design capabilities for temporal control of media and reagents (chemotemporal control) within sub-cellular environments of three-dimensional fluidic spaces (microfluidic devices) and materials (e.g., hydrogels). They will enable new insights into the complexities of neuronal development and pathology.
Healing With Books: A Literature Review of Bibliotherapy Used With Children and Youth Who Have Experienced Trauma

Bibliotherapy can assist children and youth (3–18 years old) in healing and developing effective coping skills after they experience trauma. The use of literature and identifying how to live more effectively through the characters and problems featured in a book enables children and youth to increase their insight and understanding of the themes and experiences as it relates to their own lives. Bibliotherapy is reinforced through the use of a variety of techniques such as discussion, therapeutic use of art, dramatization, puppetry, and creative writing (Early, 1993; Pardeck, 1990a; Pardeck, 1991a, 1991b; Pardeck & Pardeck, 1984, 1997). This literature review examines the outcomes of bibliotherapy when used with children who have experienced trauma. The use of bibliotherapy as a recreational therapy intervention will be discussed in terms of improving child outcomes and advancing recreational therapy professional practice. Subscribe to TRJ
Content-based hierarchies in DHT-based peer-to-peer systems

Peer-to-peer systems allowing fast and easy search for information shared by the users of a communication network, are considered to have a huge impact on next generation mobile service platforms. To support applications that employ content categories or limit services to certain contexts more efficiently, we describe a hierarchical P2P system in this paper. In particular, our system introduces hierarchies in a DHT-based P2P system to allow topic-based queries. Based on the query statement, which is based on XPath, queries can traverse the hierarchy if the content is not found in one topic-space. Examples illustrate how our concept is used for file sharing and location-aware applications
A method for emotional speech synthesis based on the position of emotional state in Valence-Activation space

Speech to Speech translation (S2ST) systems are very important for processing by which a spoken utterance in one language is used to produce a spoken output in another language. In S2ST techniques, so far, linguistic information has been mainly adopted without para- and non-linguistic information (emotion, individuality and gender, etc.). Therefore, this systems have a limitation in synthesizing affective speech, for example emotional speech, instead of neutral one. To deal with affective speech, a system that can recognize and synthesize emotional speech is required. Although most studies focused on emotions categorically, emotional styles are not categorical but continuously spread in emotion space that are spanned by two dimensions (Valence and Activation). This paper proposes a method for synthesizing emotional speech based on the positions in Valence-Activation (V-A) space. In order to model relationships between acoustic features and V-A space, Fuzzy Inference Systems (FISs) were constructed. Twenty-one acoustic features were morphed using FISs. To verify whether synthesized speech can be perceived as the same intended position in V-A space, listening tests were carried out. The results indicate that the synthesized speech can give the same impression in the V-A space as the intended speech does.
OBSERVATIONS OF THE CRAB PULSAR BETWEEN 25 AND 100 GeV WITH THE MAGIC I TELESCOPE

We report on the observation of γ-rays above 25 GeV from the Crab pulsar (PSR B0532+21) using the MAGIC I telescope. Two data sets from observations during the winter period 2007/2008 and 2008/2009 are used. In order to discuss the spectral shape from 100 MeV to 100 GeV, one year of public Fermi Large Area Telescope (Fermi-LAT) data are also analyzed to complement the MAGIC data. The extrapolation of the exponential cutoff spectrum determined with the Fermi-LAT data is inconsistent with MAGIC measurements, which requires a modification of the standard pulsar emission models. In the energy region between 25 and 100 GeV, the emission in the P1 phase (from −0.06 to 0.04, location of the main pulse) and the P2 phase (from 0.32 to 0.43, location of the interpulse) can be described by power laws with spectral indices of −3.1 ± 1.0stat ± 0.3syst and −3.5 ± 0.5stat ± 0.3syst, respectively. Assuming an asymmetric Lorentzian for the pulse shape, the peak positions of the main pulse and the interpulse are estimated to be at phases −0.009 ± 0.007 and 0.393 ± 0.009, while the full widths at half-maximum are 0.025 ± 0.008 and 0.053 ± 0.015, respectively.
Datawarehouse design for educational data mining

Business intelligence (BI) builds upon a set of tools and applications that enable the analysis of vast amounts of information (Big Data). Educational institutions handle large volumes of Big Data every year. There is a strong need for the use of BI in these institutions to improve their processes and support decision making. The core technology in a BI project is a datawarehouse (DW). This paper describes the design considerations for the implementation of the DW in an educational scenario. The DW will be used in a knowledge discovery process to handle the information for the analysis of key performance indicators using educational data mining (EDM) techniques. The DW along with an enterprise architecture (EA) repository are the key technological assets of a knowledge management framework (KMF). This framework was designed to put order in the creation, capture, transfer and digitalization of knowledge. This guide and the framework are two of the outcomes of a research project in a private university. Furthermore, a case study suggests how to choose the best methodology in higher institutions. In the case study the steps for the DW design are presented. This study can be useful for academics and practitioners that plan to design a DW to analyze information using EDM techniques.
Playing for real : play therapy with children traumatised by maltreatment : a pilot study : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Psychology at Massey University

The aim of the present study was to develop and pilot a play therapy manual for use with maltreated children presenting with trauma symptoms or post traumatic stress disorder. Four children (aged 6-8 years) with trauma symptoms and their caregivers participated in the study. Pre and post-treatment measures included a structured diagnostic interview with the children to determine PTSD diagnosis, parent report, teacher report, and child self-report measures. While some treatment gains were observed, these were most evident where there was greater PTSD symptomatology. The play therapy manual developed for the study appeared to allow the processing of trauma for the four children involved in the study, with children responding well to the therapeutic tools utilised. Findings offer preliminary support for manualised, trauma-specific play therapy intervention with maltreated children, with further research indicated to determine both effectiveness and efficacy.
Compressive imaging based on coefficients cutting in DLWT domain and approximate message passing

In compressive imaging (CI), accurate coefficients recovery is possible when the transform coefficients for an image are sufficiently sparse. However, conventional transforms, such as discrete cosine transform (DCT) and discrete wavelet transform (DWT), can not acquire a sufficiently sparse representation. A large amount of small coefficients indeed bring interference to the the recovery of large ones. This paper aims to improve the recovery performance by accurately reconstructing the large coefficients as many as possible. Thus, a compressive imaging scheme based on coefficients cutting in directional lifting wavelet transform (DLWT) domain and low-complexity iterative Bayesian algorithm is proposed. The proposed scheme is an improved version of our previous work. In this paper, relations between the best-fitted cutoff ratio and sampling rate are further analyzed. Due to the efficient Bayesian recovery algorithm, the proposed method offers better recovery performance with much lower complexity than our previous work. Experimental results show that our method outperforms many state-of-the-art compressive imaging recovery methods.
Combining safety margins and user preferences into a driving criterion for optimal control-based computation of reference maneuvers for an ADAS of the next generation

This paper outlines a methodology for combining user's preferred driving style and safety margins into an ADAS's module for optimal reference maneuver computation. The module for optimal reference maneuver computation is part of the system decision planning chain, which links scenario interpretation to warning intervention strategies. The module objective is the computation of a reference maneuver and produce a measure of the related risk by solving an optimal control problem. In this case, the optimal control problem consists in finding the control functions that minimize the integral of a given penalty function over a planning distance subject to a set of constraints. The penalty function is the mean to implement the safe maneuver concept, which has to comply with three top-level requirements: safety-margins, user acceptance and mobility. In the present work only the safe-speed functionality is addressed and a new penalty function formulation is proposed in order to include both safety criteria and preferred driving style. In this paper it is shown that each user's personal driving style can be characterized through a small set of parameters from the analysis of car longitudinal and lateral accelerations that can be easily used in optimal control formulation.
T Cells Express Functional CCR7 + CD4In Vivo Differentiated Cytokine-Producing

Chemokines and their receptors fulﬁll specialized roles in inﬂammation and under homeostatic conditions. CCR7 and its ligands, CCL19 and CCL21, are involved in lymphocyte recirculation through secondary lymphoid organs and additionally navigate lymphocytes into distinct tissue compartments. The role of CCR7 in the migration of polarized T effector/memory cell subsets in vivo is still poorly understood. We therefore analyzed murine and human CD4 (cid:1) cytokine-producing cells developed in vivo for their chemotactic reactivity to CCR7 ligands. The responses of cells producing cytokines, such as IFN- (cid:2) , IL-4, and IL-10, as well as of subsets deﬁned by memory or activation markers were comparable to that of naive CD4 (cid:1) cells, with slightly lower reactivity in cells expressing IL-10 or CD69. This indicates that CCR7 ligands are able to attract naive as well as the vast majority of activated and effector/memory T cell stages. Chemotactic reactivity of these cells toward CCL21 was absent in CCR7-deﬁcient cells, proving that effector cells do not use alternative receptors for this chemokine. Th1 cells generated from CCR7 (cid:3) / (cid:3) mice failed to enter lymph nodes and Peyer’s patches, but did enter a site of inﬂammation. These ﬁndings indicate that CD4 (cid:1) cells producing effector cytokines upon stimulation retain the capacity to recirculate through lymphoid tissues via CCR7. The Journal of Immunology, 2002, 168: 5441–5447.
Outlier overcoming using resampling techniques

Machine learning has extensively and successfully used statistical resampling techniques for generation of classifier an d predictor ensembles. It has been frequently shown that combining so called unst able predictors has a stabilizing effect on and improves the performance of the prediction system generated in this way. In this paper we use the resampling techniques in the context of Principal Component Analysis (PCA). We sho w that the proposed PCA ensembles exhibit a much more robust behaviour i n the presence of outliers which can seriously affect the performance of an individual PCA algorithm. The performance and characteristics of t he proposed approaches are illustrated on a number of experimental studies whe re an individual PCA is compared to the introduced PCA ensemble.
E TH E L : Toward a Principled Ethical Eldercare Robot

We have developed an approach to computing ethics that entails the discovery of ethical principles through machine learning and the incorporation of these principles into a system’s decision procedure. We summarize our pertinent previous work in machine ethics and present an extension of this work in the domain of eldercare: E TH E L , a prototype system that uses a machine-discovered ethical principle to provide guidance for its actions. I.2. 0 [ Artificial Intelligence ]: General – philosophical foundations. K.4. 2 [ Computers and Society ]: Social Issues – Assistive technologies for persons with disabilities. Additional