Miracle-dz/UniFAR-FTUs huggingface dataset:
ON THE FINITE-TIME SPLASH & SPLAT SINGULARITIES FOR THE 3-D FREE-SURFACE EULER EQUATIONS by

We prove that the 3-D free-surface incompressible Euler equations with regular initial geometries and velocity fields have solutions which can form a finite-time “splash” (or “splat”) singularity first introduced in [9], wherein the evolving 2-D hypersurface, the moving boundary of the fluid domain, self-intersects at a point (or on surface). Such singularities can occur when the crest of a breaking wave falls unto its trough, or in the study of drop impact upon liquid surfaces. Our approach is founded upon the Lagrangian description of the free-boundary problem, combined with a novel approximation scheme of a finite collection of local coordinate charts; as such we are able to analyze a rather general set of geometries for the evolving 2-D free-surface of the fluid. We do not assume the fluid is irrotational, and as such, our method can be used for a number of other fluid interface problems, including compressible flows, plasmas, as well as the inclusion of surface tension effects.
Proceedings of the Lifelong User Modelling Workshop , at UMAP ' 09 User Modeling Adaptation , and Personalization

This paper explores an architecture for very long term user modelling, based upon personal user model clouds. These ensure that the individual’s applications can access their model whenever it is needed. At the same time, the user can control the use of their user model. So, they can ensure it is accessed only when and where they wish, by applications that they wish. We consider the challenges of representing user models so that they can be reused by multiple applications. We indicate potential synergies between distributed and centralised user modelling architectures, proposing an architecture which combines both. Finally we discuss implications of our approach for consistency and freshness of the user model information.
Durable vesicles for reconstitution of membrane proteins in biotechnology

The application of membrane proteins in biotechnology requires robust, durable reconstitution systems that enhance their stability and support their functionality in a range of working environments. Vesicular architectures are highly desirable to provide the compartmentalisation to utilise the functional transmembrane transport and signalling properties of membrane proteins. Proteoliposomes provide a native-like membrane environment to support membrane protein function, but can lack the required chemical and physical stability. Amphiphilic block copolymers can also self-assemble into polymersomes: tough vesicles with improved stability compared with liposomes. This review discusses the reconstitution of membrane proteins into polymersomes and the more recent development of hybrid vesicles, which blend the robust nature of block copolymers with the biofunctionality of lipids. These novel synthetic vesicles hold great promise for enabling membrane proteins within biotechnologies by supporting their enhanced in vitro performance and could also contribute to fundamental biochemical and biophysical research by improving the stability of membrane proteins that are challenging to work with.
Topological Defects in SUSY

Topological defects are general consequences of almost all symmetry breaking processes. They arise naturally when a system goes through a phase transition from a symmetric phase to a phase in which the symmetry is broken. The formation and the evolution of cosmic topological defects in the early (or late) Universe has many direct and observable consequences that may allow us to constrain possible models of physics at high energy scales. In this paper, we discuss the formation, stability, and evolution of topological defects arising from standard field theory and in supersymmetric field theories. Then, we review how cosmological observations constrain the various theories.
Is formal environmental education friendly to nature? Environmental ethics in science textbooks for primary school pupils in Poland

Abstract Due to the increased interest in ecology, global warming and numerous environmental problems, ecological issues are becoming extremely important in education. Many researchers and thinkers believe that solutions to environmental problems are affected by the environmental ethics adopted. This article identifies which of the three branches of environmental ethics (anthropocentric, biocentric and holistic ethics) are present in formal environmental education in Poland. This has been achieved by analysing the content of textbooks used by science teachers in the fourth grade of elementary schools (Stage II of education). The results show that (moderate) anthropocentric ethics is dominant in the content of formal environmental education, while biocentric ethics is less frequent and there is also some focus on holistic ethics and the declaration that man is part of nature.
Moderating Effects of Gender and Coping Style on the Relationship Between Childhood Maltreatment and Social Anxiety

The relationship between childhood maltreatment and maladaptive outcomes, such as increased rates of psychopathology, is well-documented in the literature. Specifically, research has indicated that higher rates of social anxiety are observed in maltreatment victims in comparison to the general population. These rates also appear to differ according to gender, with higher prevalence rates being observed among females. However, although the relationship between childhood maltreatment and social anxiety has been substantiated, little is known about the mechanisms that contribute to its development and perpetuation over time. A developing body of literature has suggested that coping styles (i.e., task-oriented, emotion-oriented, avoidance) may influence the relationship between maltreatment and subsequent outcomes, and additional research has indicated that endorsement of particular coping styles may also differ by gender. Given this, the present study sought to examine the moderating effects of both coping styles and gender on the relationship between childhood maltreatment severity and social anxiety. Gender differences in coping style were also explored. Participants included 213 undergraduate students at a medium-sized, northeastern university. Participants completed a packet of self-report questionnaires and were provided with extra credit for their participation. Childhood maltreatment severity, social anxiety, and each of the three coping styles was scored continuously. Moderator analyses were conducted utilizing hierarchical multiple regression, and gender differences in coping style were examined through a multivariate analysis of variance (MANOVA). In contrast to the proposed hypotheses, neither coping style nor gender moderated the relationship between maltreatment severity and social anxiety. Additionally, no gender differences in coping style were observed. The present results suggest that the relationship between childhood maltreatment severity and social anxiety is vastly complex and necessitates additional research. Implications, limitations, and future directions for research are discussed in light of these results.
COMPRESSION OF ANISOTROPIC TENSOR-PRODUCT DISCRETIZATIONS

This paper is concerned with the discretization and compression of integral operators. It continues the work of [19]. Based on the framework of tensor-product biorthogonal wavelet bases we construct compression schemes for operator adapted sparse grid type discretizations. These discretization and compression schemes preserve the approximation order of the standard full-grid spaces. We give detailed information on the cases in which the curse of dimension can be broken. We show that our compression schemes are optimal up to logarithmic factors. AMS subject classification. 41A17, 41A25, 41A30, 41A65, 45L05, 45L10, 65D99, 65N12, 65N30, 65N38, 65N55
A text graphics character CAPTCHA for password authentication

We propose a new construct, the Text-Graphics Character (TGC) CAPTCHA, for preventing dictionary attacks against password authenticated systems allowing remote access via dumb terminals. Password authentication is commonly used for computer access control. But password authenticated systems are prone to dictionary attacks, in which attackers repeatedly attempt to gain access using the entries in a list of frequently-used passwords. CAPTCHAs (Completely Automated Public Turing tests to tell Computers and Humans Apart) are currently being used to prevent automated "bots" from registering for email accounts. They have also been suggested as a means for preventing dictionary attacks. However, current CAPTCHAs are unsuitable for text-based remote access. Our TGC CAPTCHA fills this gap. In this paper, we define the TGC CAPTCHA, prove that it is a (secure) CAPTCHA, demonstrate its utility in a prototype based on the SSH (Secure Shell) protocol suite and provide empirical evidence that the test is easy for humans and hard for machines. We believe that the system will not only help improve the security of servers allowing remote terminal access, but also encourage a healthy spirit of competition in the fields of pattern recognition, computer graphics and psychology.
Research and application on metadata integration for data warehouses

Metadata integration is an important issue in metadata management. It presents a metadata integration strategy based on SOA architecture for data warehouses. In this strategy, Web Service is adopted as application frame; Metadata is modeled by CWM and metadata encapsulation is designed in XML. The metadata from distributed data warehouses has been efficiently integrated and reused. It focuses on the architecture of the system, the structure design of CWM, as well as various Web Service methods creation and call. Finally, verify the feasibility, effectiveness and practicability of this solution by experiment.
My-Bookstore: The Design of a Management Game to Promote Classroom Reading Activity

Modeled Sustained Silent Reading (MSSR) is one of significant approaches for pupils to developing early literacy. To promote MSSR, different follow-up activities are used. Due to the game characteristic of active participation, digital games are potentially regarded as a promising means to promote reading activity. Thus, the purpose of this study is to develop a management-based game, My-Bookstore, to investigate its feasibility and influence. My-Bookstore was used by primary school students, and some preliminary observations were discussed in this study.
Collaborative development of data curation profiles on a wiki platform: experience from free and open source software projects and communities

Wiki technologies have proven to be versatile and successful in aiding collaborative authoring of web content. Multitude of users can collaboratively add, edit, and revise wiki pages on the fly, with ease. This functionality makes wikis ideal platforms to support research communities curate data. However, without appropriate customization and a model to support collaborative editing of pages, wikis will fall sort in providing the functionalities needed to support collaborative work. In this paper, we present the architecture and design of a wiki platform, as well as a model that allow scientific communities, especially disaster response scientists, collaborative edit and append data to their wiki pages. Our experience in the implementation of the platform on MediaWiki demonstrates how wiki technologies can be used to support data curation, and how the dynamics of the FLOSS development process, its user and developer communities are increasingly informing our understanding about supporting collaboration and coordination on wikis.
The Relative Impact of Aligning Tier 2 Intervention Materials with Classroom Core Reading Materials in Grades K–2

This randomized controlled trial in 55 low-performing schools across Florida compared 2 early literacy interventions—1 using stand-alone materials and 1 using materials embedded in the existing core reading/language arts program. A total of 3,447 students who were below the 30th percentile in vocabulary and reading-related skills participated in the study. Both interventions were implemented with fidelity for 45 minutes daily for 27 weeks in small groups of 4 students (or 5 in grade 2). The stand-alone intervention significantly improved grade 2 spelling outcomes relative to the embedded intervention; there were some differential impacts due to cohort and baseline and, in kindergarten, to English-learner status. On average, students in schools in both interventions showed similar improvement in reading and language outcomes and similar percentile gains to those in recent systematic reviews. Results are discussed with respect to alignment of Tier 2 instruction with Tier 1 instruction.
Traumatisierung und Depression

Traumatisierung oder eine Vorgeschichte von belastenden Erfahrungen in der Kindheit finden sich bei bis zu 60 % der Patienten mit einer depressiven Störung. Vermeidungsverhalten und fehlende Emotionsregulation beeinflussen dabei die interpersonellen Beziehungen der Patienten. Eine (traumabezogene) Verhaltenstherapie kann hier mit spezifischen Interventionen helfen – insbesondere mit Techniken des Fertigkeitentrainings.
Comparative analysis of carry select adder using 8T and 10T full adder cells

This paper present a comparison between the design of the 8T adder based Carry Select Adder (CSA) and 10T adder based CSA. Using both the designs of adders 4-bit CSA architecture has been developed and compared with the 28T adder 4-bit CSA. The 10T CSA design has reduced delay, power and area as compared with the 28T CSA with a slight tradeoff for area as compared to 8T CSA. The analysis shows that the 10T CSA is better than both 8T adder based CSA and 28T CSA. This work evaluates the performance of the 10T CSA design in terms of power, delay and area using 180nm CMOS process technology Cadence Virtuoso tool and Spectre simulator.
Strategies for training large scale neural network language models

We describe how to effectively train neural network based language models on large data sets. Fast convergence during training and better overall performance is observed when the training data are sorted by their relevance. We introduce hash-based implementation of a maximum entropy model, that can be trained as a part of the neural network model. This leads to significant reduction of computational complexity. We achieved around 10% relative reduction of word error rate on English Broadcast News speech recognition task, against large 4-gram model trained on 400M tokens.
Analysis of T cell stimulation by superantigen plus major histocompatibility complex class II molecules or by CD3 monoclonal antibody: costimulation by purified adhesion ligands VCAM-1, ICAM-1, but not ELAM-1

Many ligands of adhesion molecules mediate costimulation of T cell activation. The generality of this emerging concept is best determined by using model systems which exploit physiologically relevant ligands. We developed such an "antigen-specific" model system for stimulation of resting CD4+ human T cells using the following purified ligands: (a) major histocompatibility complex class II plus the superantigen Staphylococcus enterotoxin A, to engage the T cell receptor (TCR); (b) adhesion proteins vascular cell adhesion molecule 1 (VCAM-1), intercellular adhesion molecule 1 (ICAM-1), and endothelial leukocyte adhesion molecule 1 (ELAM-1), to provide potential cell surface costimulatory signals; and (c) recombinant interleukin 1 beta (rIL-1 beta)/rIL-6 as costimulatory cytokines. In this biochemically defined system, we find that resting CD4+ T cells require costimulation in order to respond to TCR engagement. This costimulation can be provided by VCAM-1 or ICAM-1; however adhesion alone is not sufficient since ELAM-1 mediates adhesion but not costimulation. The cytokines IL-1 beta and IL-6 by themselves cannot mediate costimulation, but augment the adhesion ligand-mediated costimulation. Direct comparison with the model of TCR/CD3 engagement by CD3 monoclonal antibody demonstrated comparable costimulatory requirements in both systems, thereby authenticating the commonly used CD3 model. The costimulation mediated by the activation-dependent interaction of the VLA-4 and LFA-1 integrins with their respective ligands VCAM-1 and ICAM-1 leads to increased IL-2R alpha (CD25) expression and proliferation in both CD45RA+ CD4+ and CD45RO+ CD4+ T cells. The integrins also regulate the secretion of IL-2, IL-4, and granulocyte/macrophage colony-stimulating factor. In contrast the activation-independent adhesion of CD4+ T cell to ELAM-1 molecules does not lead to T cell stimulation as measured by proliferation, IL-2R alpha expression, or cytokine release. These findings imply that adhesion per se is not sufficient for costimulation, but rather that the costimulation conferred by the VLA- 4/VCAM-1 and LFA-1/ICAM-1 interactions reflects specialized accessory functions of these integrin pathways. The new finding that VLA-4/VCAM-1 mediates costimulation adds significance to observations that VCAM-1 is expressed on a unique set of potential antigen-presenting cells in vivo.
Protein-protein interaction and gene co-expression maps of ARFs and Aux/IAAs in Arabidopsis

The phytohormone auxin regulates nearly all aspects of plant growth and development. Based on the current model in Arabidopsis thaliana, Auxin/indole-3-acetic acid (Aux/IAA) proteins repress auxin-inducible genes by inhibiting auxin response transcription factors (ARFs). Experimental evidence suggests that heterodimerization between Aux/IAA and ARF proteins are related to their unique biological functions. The objective of this study was to generate the Aux/IAA-ARF protein-protein interaction map using full length sequences and locate the interacting protein pairs to specific gene co-expression networks in order to define tissue-specific responses of the Aux/IAA-ARF interactome. Pairwise interactions between 19 ARFs and 29 Aux/IAAs resulted in the identification of 213 specific interactions of which 79 interactions were previously unknown. The incorporation of co-expression profiles with protein-protein interaction data revealed a strong correlation of gene co-expression for 70% of the ARF-Aux/IAA interacting pairs in at least one tissue/organ, indicative of the biological significance of these interactions. Importantly, ARF4-8 and 19, which were found to interact with almost all Aux-Aux/IAA showed broad co-expression relationships with Aux/IAA genes, thus, formed the central hubs of the co-expression network. Our analyses provide new insights into the biological significance of ARF-Aux/IAA associations in the morphogenesis and development of various plant tissues and organs.
Self-regulated learning: current and future directions.

The context of Educational Psychology has seen profound changes over the last 30 years; due to these, self-regulated learning has become a current focus for research, and one of the essential axes of educational practice. Since Zimmerman and Schunk's (1989) publication, Self-Regulated Learning and Academic Achievement: Theory, Research, and Practice, a great deal of research on self-regulated learning has been undertaken. Taking these and other current publications as our reference, this paper's objective is to gather the main concerns being addressed in studies on self-regulated learning. In addition, we highlight a series of directions that may guide future research in this field.
SigSpec - I. Frequency- and Phase-Resolved Significance in Fourier Space

Identifying frequencies with low signal-to-noise ratios in time series of stellar photometry and spectroscopy, and measuring their amplitude ratios and peak widths accurately, are critical goals for asteroseismology. These are also challenges for time series with gaps or whose data are not sampled at a constant rate, even with modern Discrete Fourier Transform (DFT) software. Also the False-Alarm Probability introduced by Lomb and Scargle is an approximation which becomes less reliable in time series with longer data gaps. A rigorous statistical treatment of how to determine the significance of a peak in a DFT, called SigSpec, is presented here. SigSpec is based on an analytical solution of the probability that a DFT peak of a given amplitude does not arise from white noise in a non-equally spaced data set. The underlying Probability Density Function (PDF) of the amplitude spectrum generated by white noise can be derived explicitly if both frequency and phase are incorporated into the solution. In this paper, I define and evaluate an unbiased statistical estimator, the "spectral significance", which depends on frequency, amplitude, and phase in the DFT, and which takes into account the time-domain sampling. I also compare this estimator to results from other well established techniques and demonstrate the effectiveness of SigSpec with a few examples of ground- and space-based photometric data, illustratring how SigSpec deals with the effects of noise and time-domain sampling in determining significant frequencies.
TinkerSheets: using paper forms to control and visualize tangible simulations

This paper describes TinkerSheets, a paper-based interface to tangible simulations. The proposed interface combines the advantages of form-based input and paper. Form-based input allows to set an arbitrary number of parameters. Using paper as a medium for the interface keeps the interaction modality consistently physical. TinkerSheets are also used as an output screen to display summarized information about the simulation. A user study conducted in an authentic context shows how the characteristics of the interface shape real world usage. We also describe how the affordances of this control and visualization interface support the co-design of interaction with end-users.
Using big data from the web to train Chinese traffic word representation model in vector space

Words and texts are particularly important big data sources for intelligent transportation systems. There is relevance between the traffic condition and the text content which people published in the internet within a period of time. In order to predict traffic condition by the text content we need to analysis these words and texts for all kinds of means. Many traditional researches on neuro linguistic program have provided us a variety of methods for processing these words and texts. In this paper we propose a novel method to generate word representation model focus on transportation domain. Big data set of 83.9 G words we collected from the web by web spider. After data mining, we first do word segmentation process then using the segmented word to train a Chinese transportation word model. The proposed representation model we obtained can help to convert Chinese word into vector space which preserve the semantic-syntactic words relationship. Experiments demonstrate that accurate and fast word cluster can improved a lot by the word vector we generated.