Miracle-dz/UniFAR-FTUs huggingface dataset:
A review of air-ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow

Snow in the environment acts as a host to rich chemistry and provides a matrix for physical exchange of contaminants within the ecosystem. The goal of this review is to summarise the current state of knowledge of physical processes and chemical reactivity in surface snow with relevance to polar regions. It focuses on a description of impurities in distinct compartments present in surface snow, such as snow crystals, grain boundaries, crystal surfaces, and liquid parts. It emphasises the microscopic description of the ice surface and its link with the environment. Distinct differences between the disordered air-ice interface, often termed quasi-liquid layer, and a liquid phase are highlighted. The reactivity in these different compartments of surface snow is discussed using many experimental studies, simulations, and selected snow models from the molecular to the macro-scale. Although new experimental techniques have extended our knowledge of the surface properties of ice and their impact on some single reactions and processes, others occurring on, at or within snow grains remain unquantified. The presence of liquid or liquid-like compartments either due to the formation of brine or disorder at surfaces of snow crystals below the freezing point may strongly modify reaction rates. Therefore, future experiments should include a detailed characterisation of the surface properties of the ice matrices. A further point that remains largely unresolved is the distribution of impurities between the different domains of the condensed phase inside the snowpack, i.e. in the bulk solid, in liquid at the surface or trapped in confined pockets within or between grains, or at the surface. While surface-sensitive laboratory techniques may in the future help to resolve this point for equilibrium conditions, additional uncertainty for the environmental snowpack may be caused by the highly dynamic nature of the snowpack due to the fast metamorphism occurring under certain environmental conditions. Due to these gaps in knowledge the first snow chemistry models have attempted to reproduce certain processes like the long-term incorporation of volatile compounds in snow and firn or the release of reactive species from the snowpack. Although so far none of the models offers a coupled approach of physical and chemical processes or a detailed representation of the different compartments, they have successfully been used to reproduce some field experiments. A fully coupled snow chemistry and physics model remains to be developed.
The Significance of National Wildlife Refuges in the Development of U.S. Conservation Policy

A retrospective of National Wildlife Refuge System conservation shows a promising trajectory. The system has overcome persistent neglect to contribute to conservation policy. Haltingly, it has kept pace with conservation science to remain the chief American contribution to large-scale wildlife protection. Early on, it pioneered the use of habitat acquisition to protect imperiled species. More recently, it has begun to implement the cutting-edge ecological mandate to maintain biological integrity, diversity, and environmental health. Perhaps the most meaningful feature of the history of the refuge system is how closely it mirrors the development of conservation policy in the twentieth century. This article reviews the evolution of refuge system management and shows how it reflects the major conservation developments over the past century. It begins by surveying the system with special reference to the Pelican Island National Wildlife Refuge and the Arctic National Wildlife Refuge. The article conducts a historical review of conservation policy developments, with particular emphasis on their legal dimensions. It then discusses the current conservation framework for the refuges, which is a form of ecosystem management. The article concludes by observing the ways in which the national wildlife refuges are now the most important federal lands for demonstrating sustainability and ecosystem management on a large scale.
Covering an uncountable square by countably many continuous functions

We prove that there exists a countable family of continuous real functions whose graphs together with their inverses cover an uncountable square, i.e. a set of the form X × X, where X ⊆ R is uncountable. This extends Sierpi nski’s theorem from 1919, saying that S ×S can be covered by countably many graphs of functions and inverses of functions if and only if |S| 6 ℵ1. Our result is also motivated by Shelah’s study of planar Borel sets without perfect rectangles.
Extending the Technology Acceptance Model for E-learning: A Case Study of Iran

In this study, we extended the Technology Acceptance Model to include subjective norm, personal innovativeness in domain of information technology and self-efficacy to evaluate the acceptance of E-learning. Responses from 155 university students were collected to evaluate the proposed structural model. The results indicated that Personal innovativeness in domain of information technology has a direct effect on self-efficacy. Both personal innovativeness in domain of information technology and self-efficacy have direct effect on perceived ease of use. Perceived usefulness has a direct effect on intention of students’ to accept an E-learning system. Implications are discussed.
Month-of-the-year and pre-holiday seasonality in African stock markets

Seasonal anomalies (calendar effects) may be loosely referred to as the tendency for financial asset returns to display systematic patterns at certain times of the day, week, month or year. Two popular calendar effects are investigated for African stock returns: the month-of-the-year and the pre-holiday effects, and their implication for stock market efficiency. We extend the traditional approach of modelling anomalies using OLS regressions and, examine both the mean and conditional variance. We find high and significant returns in days preceding a public holiday for South Africa, but this finding is not applicable to the other stock markets in our sample. Our results also indicate that the month-of-the-year effect is prevalent in African stock returns. However, due to liquidity and round trip transactions cost the anomalies uncovered may not necessarily violate the no-arbitrage condition. Finally we discuss promising areas for future research using developing stock markets data.
A Computational Tool Design for Evolutionary Artificial Neural Networks in Neutron Spectrometry and Dosimetry

Evolutionary Artificial Neural Networks have been studied widely in recent years. They provide not only an automatic method to design ANN, but also an approach to study evolution and learning in the same framework. In prior works was analyzed the intersection of artificial neural networks and evolutionary algorithms applied in the neutron spectrometry and dosimetry research area, however, several drawbacks were encountered, due mainly to the novel of this approach. Because this is an emergent technology, a lack of tools exists to carry out the analysis of the obtained results. In this work, it is presented the design of a computer tool which allows to analyze the neutron spectromtery and dosimetry results obtained by means of the hybrid technology based on evolutionary artificial neural networks. This tool was designed under the LabVIEW programming environment in a graphic user interface, which make easy, intuitive and friendly their use. At the same time,the operation speed of the program is high, carrying out the analysis in seconds.
Artificial Intelligence in Transportation Information for Application

resources of the entire scientific and technical communities to bear on national problems through its volunteer advisory committees. The Transportation Research Board is distributing this Circular to make the information contained herein available for use by individual practitioners in state and local transportation agencies, researchers in academic institutions, and other members of the transportation research community. Foreword he Transportation Research Board's Artificial Intelligence and Advanced Computing Committee (ABJ70) has as part of its mission to serve as a technical forum on the application of artificial intelligence (AI) to transportation problems, and to disseminate information about AI applications that is deemed credible and potentially useful to the transportation community. To this end, this Transportation Research Circular, created by members of ABJ70, provides six articles describing five general AI areas, namely, knowledge-based systems, neural networks, fuzzy sets, genetic algorithms, and agent-based models. It is designed to serve as an informational resource for transportation practitioners and managers with respect to AI tools within these general areas. Each article, for its related AI paradigm, details the types of problems to which the paradigm is best suited, its strengths and weaknesses, example applications, and guidelines for its application. The articles are meant, as one of the authors states, as a sort of Cliff Notes for AI Applications in Transportation. In describing the state of the art vis a vis these areas of AI, it is hoped that better decisions will be made about what tools to choose, under what conditions and for what specific applications for a wide range of transportation problems.
IPSec tunnel establishment for 3GPP-WLAN interworking

Interworking between the 3rd Generation Partnership Project (3GPP) such as Long Term Evolution (LTE) and Wireless Local Area Network (WLAN) forms a heterogeneous wireless network. Many advantages are attained by integrating 3GPP LTE and WLAN systems to form a 3GPP LTE-WLAN interworking architecture. However, securing this architecture is a great challenge due to the number of vulnerabilities introduced. Our research focuses first on securing network layer in case of handover, so IP security protocol (IPSec) present a great solution to us, and second on reducing authentication signaling traffic always in case of mobility events. In this paper, we propose new solutions to secure the interworking between 3GPP-LTE and WLAN by the establishment of a security tunnel between them and benefiting from MOBIKE which provides mobility extension to basic IKEv2 (Internet Key Exchange) protocol.
The Stabilizing Properties of a Nominal GNP Rule in an Open Economy

The main paper examines the ability of a nominal GNP rule for monetary policy to stabilize output and inflation in an open economy. Other regimes considered are a money rule, an exchange rate or gold price rule, a price level rule and discretion. The rules compare favorably to discretion to the extent that a timeconsistent commitment to a nominal anchor is needed to eliminate an inflationary bias in the economy. The choice among the three rules depends on the relative magnitudes of the three sorts of disturbances considered: supply shocks, money demand shocks, and exchange rate shocks. The paper computes the actual variances of these shocks, to allow a more definitive comparison of regimes. When the shocks are assumed uncorrelated, nominal GNP targeting dominates the other regimes for an extremely wide range of parameter values. When allowance is made for the correlation between money demand shocks and exchange rate shocks, for some major countries there exist some parameter values where the nominal GNP rule does not dominate the exchange rate rule, but the overall case for the nominal GNP rule is still strong, especially for the United States. The Appendix documents at length the various approaches that were taken to estimating the supply, velocity, and exchange rate shocks. It then presents the tables showing the numerical implications for the loss function of the alternative regimes considered, and how the choice of regime depends on the magnitude of the two key parameters. key words: nominal GNP, monetary targeting, rules vs. discretion JEL nos: 311, 431 longer abstract of main paper
An implementation of opinion mining using fuzzy inference system

Opinion mining is a technique by which we can find the semantic strength of reviews on an object using Fuzzy Inference System. Today people use information space to broadcast their opinions or views on any object or situation across the world. Analyses of these views yield a very useful information i.e. overall thinking about any object or situation. In this paper we have taken data from social networking site facebook on samsung mobile phones for analysis. After applying FIS on data collected we will give overall view on Samsung mobile phones across the virtual reality.
Why We Should Consider Belief Functions in Auditing Research and Practice

The Auditor's Report, Vol. 28, No. 2, March 2005 Why We Should Consider Belief Functions in Auditing Research and Practice Rajendra P. Srivastava, University of Kansas, and Theodore J. Mock, University of Southern California and Maastricht University Recent events in the auditing profession [sometimes called the ‘accounting’ profession] have clearly called for a reconsideration of the paradigms currently in vogue in both auditing research and practice. Although early audit research and standard setting explored more rigorous frameworks for risk assessment such as a specific algebraic definition of audit risk and rigorous guidance concerning statistical sampling, more recently audit practice has moved away from these approaches in favor of judgment sampling and relegating precise formulations of audit risk to providing ‘general guidance’ for audit planning. As academics we have the responsibility to help improve audit practice and research by exploring alternative, more rigorous frameworks for risk assessment, evidential reasoning and audit planning. In this note we briefly discuss one framework that offers advantages in this quest The Dempster-Shafer theory of belief functions 2 Although there is no generally accepted set of criteria that would allow researchers or practitioners to select one framework over another [Smets, 1999], there are a number of features of belief functions that argue for their more extensive use in auditing. These are briefly discussed below starting with perhaps the most compelling one, how risk and uncertainty should be treated.
Pre-Conditioners and Relations between Different Measures of Conditioning for Conic Linear Systems

In recent years, new and powerful research into "condition numbers" for convex optimization has been developed, aimed at capturing the intuitive notion of problem behavior. This research has been shown to be important in studying the efficiency of algorithms, including interior-point algorithms, for convex optimization as well as other behavioral characteristics of these problems such as problem geometry, deformation under data perturbation, etc. This paper studies measures of conditioning for a conic linear system of the form (FPd): Ax = b, x E Cx, whose data is d = (A, b). We present a new measure of conditioning, denoted pd, and we show implications of lid for problem geometry and algorithm complexity, and demonstrate that the value of = id is independent of the specific data representation of (FPd). We then prove certain relations among a variety of condition measures for (FPd), including ld, pad, Xd, and C(d). We discuss some drawbacks of using the condition number C(d) as the sole measure of conditioning of a conic linear system, and we then introduce the notion of a "pre-conditioner" for (FPd) which results in an equivalent formulation (FPj) of (FPd) with a better condition number C(d). We characterize the best such pre-conditioner and provide an algorithm for constructing an equivalent data instance d whose condition number C(d) is within a known factor of the best possible. AMS Subject Classification: 90C, 90C05, 90C25, 90C60
Routing tree construction in WiMAX mesh networks

In the paper we investigate the methods of constructing the routing tree in WiMAX networks with mesh topology. The concept of network efficiency optimization by building the routing tree characterized by selected topological properties that are independent on network load is presented. As an important partial result, correlations between topological parameters of the tree and network efficiency have been estimated. The parameters exhibiting the strongest correlations allow creation of well performing routing trees by optimizing the tree topology only. In order to estimate the network performance under load a fast, modular WiMAX network simulator has been created.
Financial activity mining from online multilingual news

We develop a financial knowledge management system, known as FAM, which is able to digest online news and conduct financial activity mining. Financial online news articles are automatically fetched from the Web. By analyzing the text content, metadata capturing major attributes such as company names and people names are automatically extracted. The metadata together with content terms are processed to mine financial activities via an unsupervised learning algorithm. FAM is capable of dealing with multilingual news including English and Chinese.
Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement

The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available.
AKARI Detection of the Infrared-Bright Supernova Remnant B0104-72.3 in the Small Magellanic Cloud

We present a serendipitous detection of the infrared-bright supernova remnant (SNR) B0104-72.3 in the Small Magellanic Cloud by the Infrared Camera (IRC) onboard AKARI. An elongated, partially complete shell is detected in all four observed IRC bands covering 2.6-15 um. The infrared shell surrounds radio, optical, and X-ray emission associated with the SNR and is probably a radiative SNR shell. This is the first detection of a SNR shell in this near/mid-infrared waveband in the Small Magellanic Cloud. The IRC color indicates that the infrared emission might be from shocked H2 molecules with some possible contributions from ionic lines. We conclude that B0104-72.3 is a middle-aged SNR interacting with molecular clouds, similar to the Galactic SNR IC 443. Our results highlight the potential of AKARI IRC observations in studying SNRs, especially for diagnosing SNR shocks.
Transparency in public-private partnerships : Not so bad after all?

Scholars' criticism of transparency in public-private partnerships (PPPs) often focuses on ‘external’ transparency, that is, the extent to which internal information is visible to the outside world. However, to achieve external transparency, internal transparency - the availability and inferability of information for the public procurer and the private party - is crucial. In this article we analyse input, process, and output transparency from three different perspectives (institutional, cognitive, and strategic) in four PPPs in the Netherlands. We conclude that input transparency is high, but process and output transparency less so. Moreover, output transparency has gained importance in PPPs. Whether this is problematic depends on the PPPs' institutional environment. In some partnerships the desired output is uncontested and predetermined by clear standards in the institutional environment, whereas other PPPs deal with contested output norms, decreasing the partnerships' transparency. These results nuance the current debate on the lack of transparency in PPPs.
Temporal query processing in Teradata

The importance of temporal data management is evident by the temporal features recently released in major commercial database systems. In Teradata, the temporal feature is based on the TSQL2 specification. In this paper, we present Teradata's implementation approach for temporal query processing. There are two common approaches to support temporal query processing in a database engine. One is through functional query rewrites to convert a temporal query to a semantically-equivalent non-temporal counterpart, mostly by adding time-based constraints. The other is a native support that implements temporal database operations such as scans and joins directly in the DBMS internals. These approaches have competing pros and cons. The rewrite approach is generally simpler to implement. But it adds a structural complexity to original query, which can pose a potential challenge to query optimizer and cause it to generate sub-optimal plans. A native support is expected to perform better. But it usually involves a higher cost of implementation, maintenance, and extension. We discuss why and describe how Teradata adopted the rewrite approach. In addition, we present an evaluation of our approach through a performance study conducted on a variation of the TPC-H benchmark with temporal tables and queries.
The Role of Remittances in Financial Crisis: Empirical Evidence from Macedonia

Abstract The recent global financial crisis has heated the debate among economists on the role of migrant workers’ remittances in times of financial crisis: Are they a shock absorber or a shock transmitter? The objective of this paper is to find out whether the remittances sent to Macedonia have a stabilizing or destabilizing effect. By specifying a vector error correction (VEC) model, we find evidence that real remittances have a destabilizing effect on the output both of the home country (Macedonia) and the host country (Germany). Consequently, they could not cushion large fluctuations in Macedonian output in stage of economic downturn.