Miracle-dz/UniFAR-FTUs huggingface dataset:
Geoscientific Model Development A multi-resolution assessment of the Community Multiscale Air Quality ( CMAQ ) model v 4 . 7 wet deposition estimates for 2002 – 2006

This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ) model simulations for 2002–2006 using both 36-km and 12-km horizontal grid spacing, with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (SO=4 ), ammonium (NH + 4 ) and nitrate (NO − 3 ). Performance of the wet deposition estimates from the model is determined by comparing CMAQ predicted concentrations to concentrations measured by the National Acid Deposition Program (NADP), specifically the National Trends Network (NTN). For SO=4 wet deposition, the CMAQ model estimates were generally comparable between the 36-km and 12-km simulations for the eastern US, with the 12-km simulation giving slightly higher estimates of SO =4 wet deposition than the 36-km simulation on average. The result is a slightly larger normalized mean bias (NMB) for the 12-km simulation; however both simulations had annual biases that were less than±15 % for each of the five years. The model estimated SO=4 wet deposition values improved when they were adjusted to account for biases in the model estimated precipitation. The CMAQ model underestimates NH +4 wet deposition over the eastern US, with a slightly larger underestimation in the 36-km simulation. The largest underestimations occur in the winter and spring periods, while the summer and fall have slightly smaller underestimations of NH +4 wet deposition. The underestimation in NH +4 wet deposition is likely due in part to the poor temporal and spatial representation of ammonia (NH 3) emissions, particularly those Correspondence to: K. W. Appel (appel.wyat@epa.gov) emissions associated with fertilizer applications and NH 3 bidirectional exchange. The model performance for estimates of NO−3 wet deposition are mixed throughout the year, with the model largely underestimating NO −3 wet deposition in the spring and summer in the eastern US, while the model has a relatively small bias in the fall and winter. Model estimates of NO−3 wet deposition tend to be slightly lower for the 36-km simulation as compared to the 12-km simulation, particularly in the spring. The underestimation of NO −3 wet deposition in the spring and summer is due in part to a lack of lightning generated NO emissions in the upper troposphere, which can be a large source of NO in the spring and summer when lightning activity is the high. CMAQ model simulations that include production of NO from lightning show a significant improvement in the NO −3 wet deposition estimates in the eastern US in the summer. Overall, performance for the 36-km and 12-km CMAQ model simulations is similar for the eastern US, while for the western US the performance of the 36-km simulation is generally not as good as either eastern US simulation, which is not entire unexpected given the complex topography in the western US.
Functions of IL-4 and Control of Its Expression.

IL-4 has been called the "prototypic immunoregulatory cytokine. " Like many cytokines, it can affect a variety of target cells in multiple ways. IL-4 has an important role in regulating antibody production, hematopoiesis and inflammation, and the development of effector T-cell responses. It is produced only by a subset of activated hematopoietic cells, including T cells and FcεRl+ mast cells and basophils. Based on the different tissue distribution and access to distinct target cells, IL-4 derived from T and FcεRl+ cells may have quite different effects on these immunological processes. In view of this, as well as the clear correlation of aberrant expression with disease, it is of interest to understand the signals that regulate IL-4 expression in a cell-specific manner. Recently, progress has been made in defining the T-cell- and FcεRl-receptor-mediated signals that stimulate IL-4 gene expression. These studies have demonstrated that there are common and cell-specific signaling pathways that regulate production of this cytokine. In this review, we summarize the activities of IL-4 defined both in vitro and in vivo and compare the signals leading to IL-4 expression in cells of both T- and mast-cell lineage.
Dynamic simulation of water resource management focused on water allocation and water reclamation in Chinese mining cities

Mining cities have undergone the process of extensive exploitation, which always results in a series of water issues. Integrated water resource management is necessary in improving water supply, allocation and quality without damaging economic development. This article constructs a linear optimization model including a ‘Top-Down’ socio-economic mode, and ‘Bottom-Up’ water quality control and water supply–demand modes with integrated water resource management focused on water allocation and water reclamation. Based on computer simulation, the model can propose a water resource management under the constraints of water supply–demand and water quality control, and the model can precisely predict the influences of water resource management on economic development, water utilization and water quality. Taking Ordos, a Chinese national resource city, as a case study, this model addresses a detailed water resource management, including a water allocation plan among industries and water reclamation plan with technologies, selection, arrangement and subsidies. The implementation of water resource management can fulfill multiple objectives on water quantity, water quality and sustainable economic development. This study indicates that water resource management with a comprehensive dynamic model can be a maneuverable approach to realize the sustainable development of economic growth and water resource utilization, as well as formulate the regional development plan.
TESTING OF CAPITAL ASSET PRICING MODEL: AN APPLICATION OF FAMA MACBETH APPROACH IN INDIAN EQUITY MARKET

The present study examines the Capital Asset Pricing Model (CAPM) for the Indian stock market using monthly stock returns from 278 companies of BSE 500 Index listed on the Bombay stock exchange for the period of January 1996 to December 2009. The findings of this study are not substantiating the theory's basic result that higher risk (beta) is associated with higher levels of return. The theory's prediction for the intercept is that it should equal zero and the slope should equal the excess returns on the market portfolio. The results of the study lead to negate the above hypotheses and offer evidence against the CAPM. The tests conducted to examine the nonlinearity of the relationship between return and betas bolster the hypothesis that the expected returnbeta relationship is linear. Additionally, this study investigates whether the CAPM adequately captures all-important determinants of returns including the residual variance of stocks. The results exhibit that residual risk has effect on the expected returns of portfolios.
PREP-CHEM-SRC – 1.0: a preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models

Abstract. The preprocessor PREP-CHEM-SRC presented in the paper is a comprehensive tool aiming at preparing emission fields of trace gases and aerosols for use in atmospheric-chemistry transport models. The considered emissions are from the most recent databases of urban/industrial, biogenic, biomass burning, volcanic, biofuel use and burning from agricultural waste sources. For biomass burning, emissions can be also estimated directly from satellite fire detections using a fire emission model included in the tool. The preprocessor provides emission fields interpolated onto the transport model grid. Several map projections can be chosen. The inclusion of these emissions in transport models is also presented. The preprocessor is coded using Fortran90 and C and is driven by a namelist allowing the user to choose the type of emissions and the databases.
Carrion's Disease: the Sound of Silence

SUMMARY Carrion's disease (CD) is a neglected biphasic vector-borne illness related to Bartonella bacilliformis. It is found in the Andean valleys and is transmitted mainly by members of the Lutzomyia genus but also by blood transfusions and from mother to child. The acute phase, Oroya fever, presents severe anemia and fever. The lethality is high in the absence of adequate treatment, despite the organism being susceptible to most antibiotics. Partial immunity is developed after infection by B. bacilliformis, resulting in high numbers of asymptomatic carriers. Following infection there is the chronic phase, Peruvian warts, involving abnormal proliferation of the endothelial cells. Despite potentially being eradicable, CD has been expanded due to human migration and geographical expansion of the vector. Moreover, in vitro studies have demonstrated the risk of the development of antimicrobial resistance. These findings, together with the description of new Bartonella species producing CD-like infections, the presence of undescribed potential vectors in new areas, the lack of adequate diagnostic tools and knowledge of the immunology and bacterial pathogenesis of CD, and poor international visibility, have led to the risk of increasing the potential expansion of resistant strains which will challenge current treatment schemes as well as the possible appearance of CD in areas where it is not endemic.
Graph-based Transform Coding with Application to Image Compression

In this paper, we propose a new graph-based coding framework and illustrate its application to image compression. Our approach relies on the careful design of a graph that optimizes the overall rate-distortion performance through an effective graph-based transform. We introduce a novel graph estimation algorithm, which uncovers the connectivities between the graph signal values by taking into consideration the coding of both the signal and the graph topology in rate-distortion terms. In particular, we introduce a novel coding solution for the graph by treating the edge weights as another graph signal that lies on the dual graph. Then, the cost of the graph description is introduced in the optimization problem by minimizing the sparsity of the coefficients of its graph Fourier transform (GFT) on the dual graph. In this way, we obtain a convex optimization problem whose solution defines an efficient transform coding strategy. The proposed technique is a general framework that can be applied to different types of signals, and we show two possible application fields, namely natural image coding and piecewise smooth image coding. The experimental results show that the proposed method outperforms classical fixed transforms such as DCT, and, in the case of depth map coding, the obtained results are even comparable to the state-of-the-art graph-based coding method, that are specifically designed for depth map images.
On the joint Fourier–ESTAR testing of PPP

ABSTRACT The purchasing power parity (PPP) is the hypothesis that the real exchange rate series are stationary. This study briefly reviews and applies six competing unit root test procedures to test PPP. Reflecting the existing literature, the results are mixed. The Kiliç test is the most favourable while the Kapetanios, Shin, and Snell (KSS) test is the least favourable to PPP and the standard ADF test lies in between. The same conclusion applies to the Fourier extensions of those three tests. The results support a recently suggested F-test for the significance of Fourier terms in unit root test equations.
Citation classics: ranking of the top 100 most cited articles in nephrology

Abstract Background The number of citations of a scientific article is considered a weight of that work in the field of interest. Bibliometric analysis of the most cited articles conducted in some medical disciplines has identified the most relevant scientific contributions that pushed forward knowledge and clinical practice of that discipline. Methods We conducted a bibliometric analysis of the most cited articles in nephrology, by extracting relevant words that identify issues of nephrological interest and querying the Google Scholar database. A rank with the 100 most cited articles was obtained, based on the absolute number of citations. Articles were clustered in different areas of interest. Results Word(s) extracted from the Google Scholar database that restituted at least 100 000 hits were 50. The extracted 100 most cited articles collected cumulatively >285 000 citations. Nine subcategories were identified and the most populated one was ‘Renal function assessment’ (16 articles and 68 000 citations, 24% of total). The other relevant group of articles (16, with 46 652 citations) belonged to the category ‘Randomized trials and pharmacology’. Almost 70% of the articles in the top 100 were published by eight major international journals. The top 100 list included 62 articles generated from USA scientists and the author with higher number of articles was A.S. Levey (10). Conclusions The top 100 list of articles in nephrology helps delineate the major interests of this medical discipline. Assessment of renal functions, probably for its multidisciplinary relevance, is the heaviest topic, based on number of citations.
Leveraging Social Signal to Improve Item Recommendation for Matrix Factorization

Although Recommender Systems have been comprehensively studied in the past decade both in industry and academia, most of current recommender systems suffer from the following issues: 1) The data sparsity of the user-item matrix seriously affect the recommender system quality. As a result, most of traditional recommender system approaches are not able to deal with the users who have rated few items, which is known as cold start problem in recommender system. 2) Traditional recommender systems assume that users are independently and identically distributed and ignore the social relation between users. However, in real life scenario, due to the exponential growth of social networking service, such as facebook and Twitter, social connections between different users play an significant role for recommender system task. In this work, aiming at providing a better recommender systems by incorporating user social network information, we propose a matrix factorization framework with user social connection constraints. Experimental results on the real-life dataset shows that the proposed method performs significantly better than the state-of-the-art approaches in terms of MAE and RMSE, especially for the cold start users.
Are Stock Price More Informative after Dual-Listing in Emerging Markets? Evidence from Hong Kong-Listed Chinese Companies

We study how the information and trading environments of Hong Kong-listed Chinese companies (H-share firms) change once the companies return to the China A-share markets for listing. We examine the stock price synchronicity, liquidity commonality, and stock liquidity after dual-listing and investigate three channels related to possible changes. We find that added A-share analyst coverage influences the stock liquidity, but not the price synchronicity or liquidity commonality. Moreover, Qualified Direct Institutional Investors' trading affects price synchronicity, liquidity commonality, and stock liquidity while Qualified Foreign Institutional Investors' trading affects price synchronicity and liquidity commonality, but not stock liquidity.
Towards an Automatic Assessment of Crowdsourced Data for NLU

Recent development of spoken dialog systems has moved away from a command-style input and aims at allowing a natural input style. Obtaining suitable data for training and testing such systems is a signiﬁcant challenge. We investigate with which methods data elicited via crowdsourcing can be assessed with respect to its naturalness and usefulness. Since the criteria with which to assess usefulness depend on the application purpose of crowdsourced data we investigate various facets such as noisy data, naturalness and building natural language understanding (NLU) models. Our results show that valid data can be automatically identiﬁed with the help of a word based language model. A comparison of crowdsourced data and system usage data on lexical, syntactic and pragmatic level reveals detailed information on the differences between both data sets. However, we show that using crowdsourced data for training NLU services achieves similar results as system usage data.
It's All in a Meme: A Content Analysis of Memes Posted to 2012 Presidential Election Facebook Pages

This thesis was an exploratory study to understand how Democrats and Republicans design memes, use traditional media framing, and how memes fit into modern humor theories. The study explores the relationship between the traditional media frames of the ideal candidate, populist campaigner, and the sure loser (Grabe & Bucy, 2009) and the commentary added by Internet users to these images in the memes. The study also applies the benign-violation theory (McGraw & Warren, 2010) to the analysis of memes to understand the design choices made by meme creators. The benignviolation theory states that a physical or psychological violation is benign if 1) an alternative norm suggests the violation is acceptable, 2) the users have a weak or loose connection to the violated norm, and 3) there is a physical and psychological distance between the users and the violated norm (McGraw & Warren, 2010). The majority of memes used san serif font, in multiple colors, and a mix of capital and lowercase letters. A chi-square revealed no significant relationship between party leaning and meme design. Most of Obama’s memes portrayed him as the ideal candidate, and most of Romney’s memes portrayed him as the populist campaigner. A chi-square revealed a significant relationship between Romney’s image and incongruity, and the results suggest that his image as the populist campaigner were transformed into an “un-populist campaigner” frame. A chi-square revealed a significant relationship between Obama’s image and the use of photographic manipulation, but Obama’s images appears to be more flattering in all of his memes. Finally, all three of the benign-violation theory criteria were applied to discuss why the memes were designed and posted for specific Facebook pages in 2012.
Automating Document Discovery in the Systematic Review Process: How to Use Chaff to Extract Wheat

Systematic reviews in e.g. empirical medicine address research questions by comprehensively examining the entire published literature. Conventionally, manual literature surveys decide inclusion in two steps, first based on abstracts and title, then by full text, yet current methods to automate the process make no distinction between gold data from these two stages. In this work we compare the impact different schemes for choosing positive and negative examples from the different screening stages have on the training of automated systems. We train a ranker using logistic regression and evaluate it on a new gold standard dataset for clinical NLP, and on an existing gold standard dataset for drug class efficacy. The classification and ranking achieves an average AUC of 0.803 and 0.768 when relying on gold standard decisions based on title and abstracts of articles, and an AUC of 0.625 and 0.839 when relying on gold standard decisions based on full text. Our results suggest that it makes little difference which screening stage the gold standard decisions are drawn from, and that the decisions need not be based on the full text. The results further suggest that common-off-the-shelf algorithms can reduce the amount of work required to retrieve relevant literature.
Surface Texture-Based Surface Treatments on Ti6Al4V Titanium Alloys for Tribological and Biological Applications: A Mini Review

Surface texture (ST) has been confirmed as an effective and economical surface treatment technique that can be applied to a great range of materials and presents growing interests in various engineering fields. Ti6Al4V which is the most frequently and successfully used titanium alloy has long been restricted in tribological-related operations due to the shortcomings of low surface hardness, high friction coefficient, and poor abrasive wear resistance. Ti6Al4V has benefited from surface texture-based surface treatments over the last decade. This review begins with a brief introduction, analysis approaches, and processing methods of surface texture. The specific applications of the surface texture-based surface treatments for improving surface performance of Ti6Al4V are thoroughly reviewed from the point of view of tribology and biology.
UAGOL : A guide for qualitative data analysis rnadette

Background: Data analysis is a complex and contested part of the qualitative research process, which has received limited theoretical attention. Researchers are often in need of useful instructions or guidelines on how to analyze the mass of qualitative data, but face the lack of clear guidance for using particular analytic methods. Objectives: The aim of this paper is to propose and discuss the Qualitative Analysis Guide of Leuven (QUAGOL), a guide that was developed in order to be able to truly capture the rich insights of qualitative interview data. Method: The article describes six major problems researchers are often struggling with during the process of qualitative data analysis. Consequently, the QUAGOL is proposed as a guide to facilitate the process of analysis. Challenges emerged and lessons learned from own extensive experiences with qualitative data analysis within the Grounded Theory Approach, as well as from those of other researchers (as described in the literature), were discussed and recommendations were presented. Strengths and pitfalls of the proposed method were discussed in detail. Results: The Qualitative Analysis Guide of Leuven (QUAGOL) offers a comprehensive method to guide the process of qualitative data analysis. The process consists of two parts, each consisting of five stages. The method is systematic but not rigid. It is characterized by iterative processes of digging deeper, constantly moving between the various stages of the process. As such, it aims to stimulate the researcher’s intuition and creativity as optimal as possible. Conclusion: The QUAGOL guide is a theory and practice-based guide that supports and facilitates the process of analysis of qualitative interview data. Although the method can facilitate the process of analysis, it cannot guarantee automatic quality. The skills of the researcher and the quality of the research team remain the most crucial components of a successful process of analysis. Additionally, the importance of constantly moving between the various stages throughout the research process cannot be overstated. 2011 Elsevier Ltd. All rights reserved. Corresponding author. E-mail address: Bernadette.DierckxdeCasterle@med.kuleuven. be . Dierckx de Casterlé).