Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructing text:: Wiki as a toolkit for (collaborative?) learning

Writing a book from which others can learn is itself a powerful learning experience. Based on this proposition, we have launched Science Online, a wiki to support learning in high school science classrooms through the collaborative production of an online science resource. Our approach to designing educational uses of technology is based on an approach to education called constructionism, which advocates learning by working on personally meaningful projects. Our research examines the ways that constructionism connects to collective models of knowledge production and learning such as Knowledge Building. In this paper, we explore ways that collaboration using wiki tools fits into the constructionist approach, we examine learning goals for youth growing up in a read-write culture, and we discuss preliminary findings in an ongoing year-long study of Science Online in the classroom. Despite the radically open collaboration afforded by wiki, we observe that many factors conspired to stymie collaborative writing on the site. We expected to find cultural barriers to wiki adoption in schools. Unexpectedly, we are also finding that the design of the wiki tool itself contributed barriers to collaborative writing in the classroom.
Human Cytomegalovirus Entry into Epithelial and Endothelial Cells Depends on Genes UL128 to UL150 and Occurs by Endocytosis and Low-pH Fusion

ABSTRACT Human cytomegalovirus (HCMV) replication in epithelial and endothelial cells appears to be important in virus spread, disease, and persistence. It has been difficult to study infection of these cell types because HCMV laboratory strains (e.g., AD169 and Towne) have lost their ability to infect cultured epithelial and endothelial cells during extensive propagation in fibroblasts. Clinical strains of HCMV (e.g., TR and FIX) possess a cluster of genes (UL128 to UL150) that are largely mutated in laboratory strains, and recent studies have indicated that these genes facilitate replication in epithelial and endothelial cells. The mechanisms by which these genes promote infection of these two cell types are unclear. We derived an HCMV UL128-to-UL150 deletion mutant from strain TR, TRΔ4, and studied early events in HCMV infection of epithelial and endothelial cells, and the role of genes UL128 to UL150. Analysis of wild-type TR indicated that HCMV enters epithelial and endothelial cells by endocytosis followed by low-pH-dependent fusion, which is different from the pH-independent fusion with the plasma membrane observed with human fibroblasts. TRΔ4 displayed a number of defects in early infection processes. Adsorption and entry of TRΔ4 on epithelial cells were poor compared with those of TR, but these defects could be overcome with higher doses of virus and the use of polyethylene glycol (PEG) to promote fusion between virion and cellular membranes. High multiplicity and PEG treatment did not promote infection of endothelial cells by TRΔ4, yet virus particles were internalized. Together, these data indicate that genes UL128 to UL150 are required for HCMV adsorption and penetration of epithelial cells and to promote some early stage of virus replication, subsequent to virus entry, in endothelial cells.
Formation of Structure in Molecular Clouds: A Case Study

Molecular clouds (MCs) are highly structured and turbulent. Colliding gas streams of atomic hydrogen have been suggested as a possible source of MCs, imprinting the filamentary structure as a consequence of dynamical and thermal instabilities. We present a two-dimensional numerical analysis of MC formation via converging H I flows. Even with modest flow speeds and completely uniform inflows, nonlinear density perturbations arise as possible precursors of MCs. Thus, we suggest that MCs are inevitably formed with substantial structure, e.g., strong density and velocity fluctuations, which provide the initial conditions for subsequent gravitational collapse and star formation in a variety of Galactic and extragalactic environments.
Future Collaboration Prediction in Co-authorship Network

The advent of proliferation of social networking is high on use in present era. A co-authorship network which shows research collaborations, are an important class of social networks. Research collaborations often yield good results but organizing a research group is a tedious task. Every researcher is concerned to collaborate with the best expertise complimenting him. Although there was abundant research conducted to find future collaborators or links, very few of them are able to find out effective relationship among them. In this article, we propose a method that makes link predictions in co-authorship networks using supervised approach. The model extracts the features from the networks node and topological structure which can be good indicators of future collaborations. The proposed method was evaluated on synthetic as well as real social networks such as Net Science. Our experiment corroborated the results, and demonstrated the efficiency of the method.
Local Governance, Identity And Social Capital: A Framework For Administrative Reform

Local governments are increasingly seen as key facilitators of networked community governance, enabling collaborative local action. A better understanding local government’s role in enhancing citizen participation is necessary. This new agenda implies an important expansion of the notion of inclusion in political decisions and relies on the adequate institutional design. Although scholarship emphasizes individuals’ engagement, it lacks the recognition of community’s identity heterogeneity. We advance a framework that takes into consideration the fact that these assumptions demand a new way of looking at scale uncertainty and of what defines social ties and its implications on policy and institutional design.
Numerical method for bifurcation analysis in an impact oscillator with fixed border

Impact oscillators appear in various fields such as nervous system, ecological system, and mechanical system. These systems have a characteristic property that the dynamics discontinuously behaves due to jumps at hitting borders in the state space. In general, it is difficult to obtain analytical solutions in this class. Thus a numerical method is indispensable for the bifurcation analysis in the impact oscillators; however, unfortunately, it has not been established. Therefore, we proposed a numerical method for the bifurcation analyses in the impact oscillator with a fixed border and applied the proposed method to the Rayleigh-type oscillator.
Mapping the Journey toward the Principalship: Using Standards as a Guide.

This article presents the findings from a longitudinal study of preservice principals during their required internship. The authors investigated interns’ perceived acquisition of skills to meet licensure standards using scaled scores on the Colorado Standards Knowledge (CSK) instrument and structured reflective journaling. The findings revealed interns’ perceived increased knowledge of the standards and the integration of the standards throughout their internships. This indicated that requiring guided reflective journaling throughout principal internships clearly incorporated the broad knowledge outlined by the standards established for principals.
Establishing a cointegrating relationship between the exchange rate and relative efficiency

The intention of this work is to examine whether the real or nominal exchange rate of an nation reflects information regarding the relative efficiency of the economy. This research reviews work carried out in the area of economic convergence, economic development and the exchange rate. A basic model for income is presented and residuals are analysed for further information on relative performance. These residuals are interpreted as a total factor productivity or Solow residual type measure coupled with information contained from the labour side of the economy. The sample covers the G7 countries and Australia, for the period 1950 to 1990. The model is estimated using the Johansen Maximum Likelihood Procedure (reduced rank condition) and not the residual based method associated with normal cointegrating analysis. The latter method has a number of drawbacks. The unit roots present in the time series are identified using an Augmented Dickey Fuller. Results imply the existence of unit roots, but the author cautions that this conclusion is limited by low power of unit root tests in general. Non-stationarity may be a temporary post-war phenomenon, and the conclusion of a unit root is dependent on the sample period chosen. The hypothesis is supported for six of the eight economies for the sample period 1960 to 1990. In some cases a statistical relationship exists between relative efficiency measures and the real exchange rate. This relationship is strongest in the 1950 to 1970 period. For the second half of the sample, results are less promising. A moving average is required to reduce the variability of the exchange rate measures. This produces results which are much more consistent and support the hypothesis. The residuals generated by the model are imperfect is various ways. Nevertheless, the work supports a relative efficiency argument. The estimation procedure is also noteworthy. It examines relative efficiency by combining the information contained within the labour side of the economy with possible Solow residuals, while establishing a link between real and monetary phenomena.
Integration of Existing Programs into CORBA

In distributed object-oriented systems, middleware products like CORBA are employed to perform the actual distribution on a network of computers. Existing programs that are subject to distribution fall into two categories: (1) they lack structure and can only be reused by using wrapping and/or reengineering techniques, (2) the system was developed using object-based abstractions, but cannot directly be distributed in form of a CORBA system. In this paper we will focus on the second case, while pointing out the relationship between the two cases. Some problems that arise when distributing existing object-oriented programs via CORBA are caused by the need to specify signatures in an interface deenition language (IDL). Not all data types have corresponding IDL deenitions. Another example of a necessary change is the replacement of local object creation by the invocation of a remote factory object. Besides the preconditions new, non-functional requirements have to be met by the distributed system. We want to avoid future legacy systems, therefore these aspects, such as synchronization, parameter conversion and performance optimizations should not augment the application code | ideas innuenced by the concept of aspect oriented programming. We are currently developing a tool which integrates reengineering and distribution tasks.
Sustainable Urban Systems

This special issue demonstrates how practical solutions to the development of sustainable cities can be achieved through studying urban metabolism, urban ecology, city carbon and water footprints, the dynamics of city growth, and the interdependency between social actors, institutions, and biophysical system flows. than half the world’s people and about 80% of those in developed nations live in cities and urban areas. These vast urban populations consume a majority of the world’s resources, contribute to environmental degradation locally, regionally, and globally; and simultaneously are highly vulnerable to the consequent impacts of such changes (e.g., climate change). Developing environmentally sustainable cities is one of society’s grand challenges in the coming decades. Transformation of infrastructure systems is understood to be key to developing sustainable, resourceefficient cities (Boyle et al. 2010; Sahely et al. 2005). The framework for urban green growth developed by the Organisation for Economic Co-operation and Development (OECD) sees infrastructure, along with innovation and human capital, as being the starting conditions for achieving green jobs, green supply and consumption, and urban attractiveness (Hammer et al. 2011). The United Nations Environment Programme (UNEP 2012) identifies five key thematic infrastructure areas for achieving resource efficient cities—building energy efficiency, waste management, sustainable urban transport, water/wastewater, and urban ecosystem management—but stresses that it is integration between sectors and across scales that is most important. Our goal with this special issue on sustainable urban systems is to apply methods of industrial ecology toward the sustainable development of cities, their supporting hinterlands, and the networked infrastructure that connects them. The methods include familiar tools of industrial ecology, such as life cycle assessment (LCA), material flow analysis (MFA), environmental footprinting, and scenario modeling; but there is also an effort to push the interdisciplinary boundaries of in-
Price level targeting with strategic fiscal policy and the value of fiscal leadership

This paper investigate the stabilization bias that arises in a model of non-cooperative monetary and fiscal policy stabilisation of the economy, when monetary authority implements price level targeting but fiscal policy remains benevolent. We demonstrate the gain in welfare improvement depends on the level of steady state debt. If the steady state level of the government debt is low, then the monetary price level targeting unambiguously leads to social welfare gains, even if the fiscal authority acts strategically and faces different objectives and has incentives to pursue its own benefit and therefore offsets some or all of monetary policy actions. Moreover, if the fiscal policymaker is able to conduct itself as an intra-period leader, the social welfare gain of the monetary price level targeting regime can be further improved. However, if the economy has a high steady state debt level, the gain of the price level targeting is outweighed by the loss arising from the conflicts between the policy makers, and leads to a lower social welfare than under cooperative discretionary inflation targeting.
Single Frame Based Video Geo-Localisation Using Structure Projection

Community image and video platforms like FlickR and Youtube offer large image collections from different perspectives. However, the majority of publicly available imagery from online communities lack a reasonable exact location and orientation information, which is important for many geo-spatial applications like object geo-referencing, knowledge transfer or augmented reality. In this work we exploit publicly available drone videos in order to bridge the gap between ground and aerial imagery. We propose a framework for the fast determination of full 6-D georeferenced motion trajectories of online community drone video footage using geo-localized map data. Our method requires the registration of a single video frame from a video sequence in order to exactly geo-reference complete motion trajectories w.r. t. to existing geo-referenced map data. The method relies on SfM and SLAM techniques in combination with a simple, yet efficient appearance and structure matching based on rendered map data (e.g. LiDAR) in order to generate geo-registered 3D feature maps. These maps enable a simple and fast global appearance based geo-registration of visually overlapping community videos and images. We evaluate our method on a large set of community drone videos. Our method produces drift free geo-data overlays at an average speed of 29,7 frames per second with an average positional error of 0,4m. In addition we release a large scale processed LiDAR dataset and geo-registered feature maps as an extension to the converging perspectives dataset. This data may provide visual links from ground based sensors to aerial imagery. Possible applications are numerous and include autonomous navigation, map updating/extension, image and video dehazing, object localisation or augmented reality.
Where is the root of the universal tree of life?

The currently accepted universal tree of life based on molecular phylogenies is characterised by a prokaryotic root and the sisterhood of archaea and eukaryotes. The recent discovery that each domain (bacteria, archaea, and eucarya) represents a mosaic of the two others in terms of its gene content has suggested various alternatives in which eukaryotes were derived from the merging of bacteria and archaea. In all these scenarios, life evolved from simple prokaryotes to complex eukaryotes. We argue here that these models are biased by overconfidence in molecular phylogenies and prejudices regarding the primitive nature of prokaryotes. We propose instead a universal tree of life with the root in the eukaryotic branch and suggest that many prokaryotic features of the information processing mechanisms originated by simplification through gene loss and non-orthologous displacement.
Implementation of sentence parser for Hungarian language in natural language processing

One of the main research areas in current intelligent systems is the development of natural language interfaces for applications. The paper presents an overview of NLP structure and analyses the importance of semantic in understanding of a language. In the work, an ECG-based sentence analyzer is proposed that translates the incoming natural language sentences into API level function calls.
Slight differences in incubation temperature affect early growth and stress endocrinology of wood duck (Aix sponsa) ducklings

SUMMARY Early developmental experiences, such as incubation conditions, can have important consequences for post-hatching fitness in birds. Although the effects of incubation temperature on phenotype of avian hatchlings are poorly understood, recent research suggests that subtle changes in incubation conditions can influence hatchling characteristics, including body size and condition. We designed an experiment to explore the effects of incubation temperature on hatching success, survival to 9 days post hatch, growth and the hypothalamo–pituitary–adrenal (HPA) axis in wood ducks (Aix sponsa). Wood duck eggs were collected from nest boxes and experimentally incubated at three temperatures (35.0, 35.9 and 37.0°C), each falling within the range of temperatures of naturally incubated wood duck nests. Survival and growth were monitored in ducklings fed ad libitum for 9 days post hatch. In addition, baseline and stress-induced plasma corticosterone concentrations were measured in 2 and 9 day old ducklings. Hatching success and survival to 9 days was greatest in ducks incubated at the intermediate temperature. Ducklings incubated at 35.9°C and 37.0°C had 43% higher growth rates than ducklings incubated at 35.0°C. In addition, ducklings incubated at 35.0°C had higher baseline (17–50%) and stress-induced (32–84%) corticosterone concentrations than ducklings incubated at 35.9°C and 37.0°C at 2 and 9 days post hatch. We also found a significant negative correlation between body size and plasma corticosterone concentrations (baseline and stress-induced) in 9 day old ducklings. To our knowledge, this is the first study to demonstrate that thermal conditions experienced during embryonic development can influence the HPA axis of young birds. Our results illustrate that subtle changes (<1.0°C) in the incubation environment can have important consequences for physiological traits important to fitness.
Dynamic covariance estimation via positive semidefinite dictionary learning

Time series are among the most prevalent forms of data we encounter in the real world, whether it be a sequence of audio, biomedical, demographic, climate, or financial measurements. Covariance estimation, where we try to estimate the covariance matrix of a time series, is a classic and important problem that can provide us predictive power in many applications. The vast majority of covariance estimation methods assume that time series are stationary, i.e., the covariance matrix remains unchanged throughout the lifetime of the variables. However, in reality the covariance of most real time series changes over time—for example, the covariance of stock prices is conceivably different in periods of market growth and market decline. We could compute sample covariance matrices over successive windows of the time series, but the resulting sequence of sample covariance matrices offers no insight into what particular features and structures of the covariance are evolving over time. Given this sequence of sample covariance matrices, how can we learn a meaningful, compact parameterization of how the covariance is changing? We take inspiration from dictionary learning, an approach where dictionary atoms Di ∈ R, i = 1, . , K for some small K, are learned via some optimization algorithm such that each of N K samples xj ∈ R, j = 1, . , N , can be expressed as a linear combination of the dictionary atoms. Dictionary learning simultaneously 1) compresses the dataset since we only need the dictionary D = [D1 . DK ] and the linear combination coefficients to restore it, and 2) provides a model for understanding the data, by parameterizing it in terms of the few “fundamental” atoms Di. Each atom can be thought of as capturing a basic prototype of how the variables covary.
Spectral Characterization of Hierarchical Network Modularity and Limits of Modularity Detection

Many real world networks are reported to have hierarchically modular organization. However, there exists no algorithm-independent metric to characterize hierarchical modularity in a complex system. The main results of the paper are a set of methods to address this problem. First, classical results from random matrix theory are used to derive the spectrum of a typical stochastic block model hierarchical modular network form. Second, it is shown that hierarchical modularity can be fingerprinted using the spectrum of its largest eigenvalues and gaps between clusters of closely spaced eigenvalues that are well separated from the bulk distribution of eigenvalues around the origin. Third, some well-known results on fingerprinting non-hierarchical modularity in networks automatically follow as special cases, threreby unifying these previously fragmented results. Finally, using these spectral results, it is found that the limits of detection of modularity can be empirically established by studying the mean values of the largest eigenvalues and the limits of the bulk distribution of eigenvalues for an ensemble of networks. It is shown that even when modularity and hierarchical modularity are present in a weak form in the network, they are impossible to detect, because some of the leading eigenvalues fall within the bulk distribution. This provides a threshold for the detection of modularity. Eigenvalue distributions of some technological, social, and biological networks are studied, and the implications of detecting hierarchical modularity in real world networks are discussed.