Miracle-dz/UniFAR-FTUs huggingface dataset:
Supporting information_20130601

As shown in Table S1, there are three main approaches for the prediction of wildfire. Among them, regression is the most widely used, with the goal of deriving a relationship between fire parameters (e.g., area burned or probability) and meteorological, hydrological, and geographic variables. Different forms of regression have been adopted, The regression approach usually has a reasonable predictive capability, with R 2 ranging from 0.3 to 0.8. It is numerically efficient because it usually employs monthly or seasonal variables averaged over a large spatial scale (e.g., Flannigan et al., 2005; Littell et al., 2009). Obtaining satisfactory fits (or correlations) usually requires aggregating area burned data into large ecoregions The regression methods also have significant limitations. For the stepwise regression method, which selects predictors based on their correlations with the predictand, the more potential predictors used, the more robust the fit. However, an increase in the number of terms may also result in some terms closely correlating with each other. Such collinearity not only makes it difficult to isolate contributions from individual factors (Moritz et al., 2012), but also may result in mathematical instability in future projections (Philippi, 1993). Another limitation is that a change in the length of the time series or use of a different meteorological dataset may lead to a different order of terms in the regression fit (e.g. Littell et al., 2009), causing very different projections using meteorological output from a GCM. Other regression methods, such as MARS or a probabilistic approach, may avoid collinearity among predictors, but have their own limitations. For example, the MARS technique can develop good regression fits on small spatial scales, but interpretation of these fits may be challenging due to the complicated functional forms
Enhanced Content-Based Filtering Using Diverse Collaborative Prediction for Movie Recommendation

In recommender system, Collaborative filtering or Content-based filtering is one of the most popular methods used to predict items of interest for a user. Each method has their own advantage, though individually they possess several limitations. In order to minimize the limitation, we developed a hybrid recommender system incorporating components from both methods.Our approach includes a diverse-item selection algorithm that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input is fed into content-based filtering . We present experimental result on movielens dataset that show how our approach performs better than content-based filtering and Naive hybrid approach.
erifyin Spam SMS y Arabic CA C A

The present era, which has been called `the age of information and communication technology' (ICT), technologies such as the mobile phone have developed rapidly. These technologies have entailed various services and technologies based on them. The short message service, abbreviated to SMS, is one of the simple forms of the services used in mobile phones and has been warmly welcomed by the public throughout the word, esp. Asia and Europe. Using this service, individuals can write and send to each other short messages and also black and white pictures. One of the ways of advertising that some companies use is sending SMS messages in the form of short text messages to a wide spectrum of users. Such advertisements are sometimes sent in a way that one cannot recognize them from the regular messages. This article uses the CAPTCHA (completely automated public Turing test to tell computers and human apart) method based on the Persian and Arabic scripts to recognize commercial messages sent by computer programs. In this method, the picture of a Persian or Arabic word is selected and sent as an SMS picture message, asking the sender to type the word and send it back in reply as an SMS text message. As such words cannot be recognized by the Persian or Arabic OCR (optical character recognition) programs that are available now, only a Persian/Arabic human user can recognize the word. This article has been implemented with J2ME (Java 2 micro edition). It is a version of the Java language for small machines and has been implemented on a Nokia series 60 mobile phone
A supplement to the SAS survival guide - nonparametric regression

Along with the well-known Cox-model in the area of survival analysis there is an interesting alternative: The Additive Hazards Regression model, which is sometimes referred to as Aalen's Linear Regression model (or simply Aalenmodel). In contrast to the semi-parametric Cox-model, the Aalen-model is nonparametric. The concept permits an assessment of time dependency in covariate effects with regression functions and corresponding graphics. Those graphics are denoted as Aalen-plots. Beyond, the model allows the inclusion of time-varying covariates. The basic principles of this model will be presented throughout this paper, including estimates, confidence intervals and test statistics. Based on the statistical theory of counting processes and martingales the calculations turn out to be reasonable simple. Programming was done with SAS® software, incorporating SAS/Graph® and SAS/IML® . The model is applied to data from EVITA-HF (Evidence Based Treatment - Heart Failure) survey. Results are presented in short and different types of Aalen-plots are identified.
Two Angular Dioxygenases Contribute to the Metabolic Versatility of Dibenzofuran-Degrading Rhodococcus sp. Strain HA01

ABSTRACT Rhodococcus sp. strain HA01, isolated through its ability to utilize dibenzofuran (DBF) as the sole carbon and energy source, was also capable, albeit with low activity, of transforming dibenzo-p-dioxin (DD). This strain could also transform 3-chlorodibenzofuran (3CDBF), mainly by angular oxygenation at the ether bond-carrying carbon (the angular position) and an adjacent carbon atom, to 4-chlorosalicylate as the end product. Similarly, 2-chlorodibenzofuran (2CDBF) was transformed to 5-chlorosalicylate. However, lateral oxygenation at the 3,4-positions was also observed and yielded the novel product 2-chloro-3,4-dihydro-3,4-dihydroxydibenzofuran. Two gene clusters encoding enzymes for angular oxygenation (dfdA1A2A3A4 and dbfA1A2) were isolated, and expression of both was observed during growth on DBF. Heterologous expression revealed that both oxygenase systems catalyze angular oxygenation of DBF and DD but exhibited complementary substrate specificity with respect to CDBF transformation. While DfdA1A2A3A4 oxygenase, with high similarity to DfdA1A2A3A4 oxygenase from Terrabacter sp. strain YK3, transforms 3CDBF by angular dioxygenation at a rate of 29% ± 4% that of DBF, 2CDBF was not transformed. In contrast, DbfA1A2 oxygenase, with high similarity to the DbfA1A2 oxygenase from Terrabacter sp. strain DBF63, exhibited complementary activity with angular oxygenase activity against 2CDBF but negligible activity against 3CDBF. Thus, Rhodococcus sp. strain HA01 constitutes the first described example of a bacterial strain where coexpression of two angular dioxygenases was observed. Such complementary activity allows for the efficient transformation of chlorinated DBFs.
The Absence of Crystalline Silicates in the Diffuse Interstellar Medium

Infrared spectroscopy provides a direct handle on the composition and structure of interstellar dust. We have studied the dust along the line of sight toward the Galactic center using Short Wavelength Spectrometer data obtained with the Infrared Space Observatory (ISO). We focused on the wavelength region from 8 to 13 μm, which is dominated by the strong silicate absorption feature. Using the absorption profiles observed toward Galactic center sources 3 and 4, which are C-rich Wolf-Rayet Stars, as reference objects, we are able to disentangle the interstellar silicate absorption and the silicate emission intrinsic to the source, toward Sgr A* and derive a very accurate profile for the intrinsic 9.7 μm band. The interstellar absorption band is smooth and featureless and is well reproduced using a mixture of 15.1% amorphous pyroxene and 84.9% of amorphous olivine by mass, all in spherical submicron-sized grains. There is no direct evidence for substructure due to interstellar crystalline silicates. By minimizing χ2 of spectral fits to the absorption feature, we are able to determine an upper limit to the degree of crystallinity of silicates in the diffuse interstellar medium (ISM) and conclude that the crystalline fraction of the interstellar silicates is 0.2% ± 0.2% by mass. This is much lower than the degree of crystallinity observed in silicates in the circumstellar environment of evolved stars, the main contributors of dust to the ISM. There are two possible explanations for this discrepancy. First, an amorphization process occurs in the ISM on a timescale significantly shorter than the destruction timescale, possibly caused by particle bombardment by heavyweight ions. Second, we consider the possibility that the crystalline silicates in stellar ejecta are diluted by an additional source of amorphous silicates, in particular supernovae. We also compare our results with a study on silicate presolar grains found in interplanetary dust particles.
A Content Adaptation Approach for On-Line Gaming on Various Networks and Terminals

Most current multi-player 3D games can only be played on dedicated platforms, requiring specifically designed content and communication over a predefined network. To overcome these limitations, the OLGA (On-Line GAming) consortium has devised a framework to develop real distributive, multiplayer 3D games. Scalability at the level of content, platforms and networks is exploited to achieve the best complexity vs. quality. Additionally, standardised content representation and compression formats (MPEG-4, JPEG 2000) are used in OLGA's framework, enabling easy deployment over existing infrastructure, while keeping hooks to well-established practices in the game industry
SOME STATISTICAL PROBLEMS ASSOCIATED WITH BIOLOGICAL ASSESSMENT-IMPLICATIONS AND SOLUTIONS

One of the methods used to define biological resources is biological surveys. Results from biological surveys are often used to make comparisons between populations of organisms above and below discharges, or between reference sites and suspected impacted sites. One of the metrics from these biological surveys is count data that are based on replicate samples taken from sites or stations. These data present challenges for the analyst because they are often clumped, with zero values and potential outliers. In this paper we present some approaches that will increase the ability of the analyst to apply the appropriate models to these data. Access to the programs described are given along with contacts for help in using the compiled programs. KEY TERMS: biological assessments; statistics; clumped distributions; negative binomial
Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis

The frequently changing user preferences and/or item profiles have put essential importance on the dynamic modeling of users and items in personalized recommender systems. However, due to the insufficiency of per user/item records when splitting the already sparse data across time dimension, previous methods have to restrict the drifting purchasing patterns to pre-assumed distributions, and were hardly able to model them rather directly with, for example, time series analysis. Integrating content information helps to alleviate the problem in practical systems, but the domain-dependent content knowledge is expensive to obtain due to the large amount of manual efforts. In this paper, we make use of the large volume of textual reviews for the automatic extraction of domain knowledge, namely, the explicit features/aspects in a specific product domain. We thus degrade the product-level modeling of user preferences, which suffers from the lack of data, to the feature-level modeling, which not only grants us the ability to predict user preferences through direct time series analysis, but also allows us to know the essence under the surface of product-level changes in purchasing patterns. Besides, the expanded feature space also helps to make cold-start recommendations for users with few purchasing records. Technically, we develop the Fourier-assisted Auto-Regressive Integrated Moving Average (FARIMA) process to tackle with the year-long seasonal period of purchasing data to achieve daily-aware preference predictions, and we leverage the conditional opportunity models for daily-aware personalized recommendation. Extensive experimental results on real-world cosmetic purchasing data from a major e-commerce website (JD.com) in China verified both the effectiveness and efficiency of our approach.
Response of the Cholesterol Metabolism to a Negative Energy Balance in Dairy Cows Depends on the Lactational Stage

The response of cholesterol metabolism to a negative energy balance (NEB) induced by feed restriction for 3 weeks starting at 100 days in milk (DIM) compared to the physiologically occurring NEB in week 1 postpartum (p.p.) was investigated in 50 dairy cows (25 control (CON) and 25 feed-restricted (RES)). Blood samples, liver biopsies and milk samples were taken in week 1 p.p., and in weeks 0 and 3 of feed restriction. Plasma concentrations of total cholesterol (C), phospholipids (PL), triglycerides (TAG), very low density lipoprotein-cholesterol (VLDL-C) and low density lipoprotein-cholesterol (LDL-C) increased in RES cows from week 0 to 3 during feed restriction and were higher in week 3 compared to CON cows. In contrast, during the physiologically occurring NEB in week 1 p.p., C, PL, TAG and lipoprotein concentrations were at a minimum. Plasma phospholipid transfer protein (PLTP) and lecithin:cholesterol acyltransferase (LCAT) activities did not differ between week 0 and 3 for both groups, whereas during NEB in week 1 p.p. PLTP activity was increased and LCAT activity was decreased. Milk C concentration was not affected by feed restriction in both groups, whereas milk C mass was decreased in week 3 for RES cows. In comparison, C concentration and mass in milk were elevated in week 1 p.p. Hepatic mRNA abundance of sterol regulatory element-binding factor-2 (SREBF-2), 3-hydroxy-3-methylglutaryl-coenzyme A synthase 1 (HMGCS1), 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR), and ATP-binding cassette transporter (ABCA1) were similar in CON and RES cows during feed restriction, but were upregulated during NEB in week 1 p.p. compared to the non-lactating stage without a NEB. In conclusion, cholesterol metabolism in dairy cows is affected by nutrient and energy deficiency depending on the stage of lactation.
Energy-efficient multiple-metric data delivery for wireless sensor networks

Due to limited resources of individual senor nodes, there is usually a trade-off between energy spending for packets transmissions and the appropriate level of reliability. Since link failures and packet losses are unavoidable, sensor networks may tolerate a certain level of reliability without significantly affecting packets delivery performance and data aggregation accuracy in favor of efficient energy consumption. However a certain degree of reliability is needed, especially when hop count increases between source sensor nodes and the base station as a single lost packet may result in loss of a large amount of aggregated data along longer hops. An effective solution is to trade off between energy and reliability while improving packet delivery and minimizing unnecessary packet transmissions in favor of high success reception rates of representative data packets. Based on this approach, the proposed scheme achieves moderate energy consumption and high packet delivery ratio. The proposed scheme was experimentally investigated on a testbed of TelosB motes and proven to be more robust and energy efficient than the current implementation of TinyOS2.x MultihopLQI.
Protective Role of the Cholinergic Anti-Inflammatory Pathway in a Mouse Model of Viral Myocarditis

Background Activation of the cholinergic anti-inflammatory pathway, which relies on the α7nAchR (alpha 7 nicotinic acetylcholine receptor), has been shown to decrease proinflammatory cytokines. This relieves inflammatory responses and improves the prognosis of patients with experimental sepsis, endotoxemia, ischemia/reperfusion injury, hemorrhagic shock, pancreatitis, arthritis and other inflammatory syndromes. However, whether the cholinergic anti-inflammatory pathway has an effect on acute viral myocarditis has not been investigated. Here, we studied the effects of the cholinergic anti-inflammatory pathway on acute viral myocarditis. Methodology/Principal Findings In a coxsackievirus B3 murine myocarditis model (Balb/c), nicotine and methyllycaconitine were used to stimulate and block the cholinergic anti-inflammatory pathway, respectively. Relevant signal pathways were studied to compare their effects on myocarditis, survival rate, histopathological changes, ultrastructural changes, and cytokine levels. Nicotine treatments significantly improved survival rate, attenuated myocardial lesions, and downregulated the expression of TNF-α and IL-6. Methyllycaconitine decreased survival rate, aggravated myocardial lesions, and upregulated the expression of TNF-α and IL-6. In addition, levels of the signaling protein phosphorylated STAT3 were higher in the nicotine group and lower in the methyllycaconitine group compared with the untreated myocarditis group. Conclusions/Significance These results show that nicotine protects mice from CVB3-induced viral myocarditis and that methyllycaconitine aggravates viral myocarditis in mice. Because nicotine is a α7nAchR agonist and methyllycaconitine is a α7nAchR antagonist, we conclude that α7nAchR activation increases the phosphorylation of STAT3, reduces the expression of TNF-α and IL-6, and, ultimately, alleviates viral myocarditis. We also conclude that blocking α7nAchR reduces the phosphorylation of STAT3, increases the expression of TNF-α and IL-6, aggravating viral myocarditis.
COMPORTAMENTO ECOLOGICAMENTE CONSCIENTE DO CONSUMIDOR: ADAPTAÇÃO DA ESCALA ECCB PARA O CONTEXTO BRASILEIRO

O proposito deste estudo foi o de atestar a aplicabilidade da Escala de Comportamento Ecologicamente Consciente do Consumidor (ECCB), desenvolvida por Roberts (1996), na realidade local. Para tanto, o objetivo principal do artigo foi o de validar a escala ECCB para o contexto nacional e propor os ajustes necessarios. O estudo foi realizado com 176 alunos do curso de graduacao em Administracao de uma universidade do RS, caracterizando-se como uma pesquisa descritiva e quantitativa do tipo survey. A adequacao da Analise Fatorial Exploratoria foi comprovada com o valor do KMO 0,915 e Barlett significativo e seu resultado, apos a exclusao de tres variaveis com comunalidades inferiores a 0,50, gerou uma estrutura de tres fatores (reciclagem, mudanca de comportamento e saude) que explicam 56,9% da variância total. Atraves da Analise Fatorial Confirmatoria, identificou-se a necessidade de dois procedimentos de melhoria do modelo: a inclusao de uma correlacao entre os itens r3 (produtos que possuem grande quantidade de embalagens) e p5 (produtos feitos de recursos naturais escassos); e exclusao do item s3 (pagar mais por produtos sem elementos quimicos). Com estas alteracoes, obteve-se um modelo com indices que comprovam um bom ajuste (χ² = 192,610; χ²/gl = 1,65; RMR = 0,082; CFI = 0,933; NFI = 0,873; NNFI = 0,922; RMSEA = 0,064) e, desta forma, o estudo comprova que apos algumas adaptacoes, a escala apresenta consistencia para ser aplicada no contexto nacional.
Ballumiere: Real-Time Tracking and Spherical Projection for High-Speed Moving Balls

Projections on moving objects have a problem in that the projection may slip because of the delay between tracking and projection. Here, we propose a new prediction method combining a Kalman filter and a three-frame feedback model that switches between these models according to the ball's state of motion. We developed a real-time tracking and projection system named "Ballumiere", which uses motion capture cameras for tracking and multiple projectors for spherical projection. We conducted a comparative experiment with an existing prediction model and showed that our method minimizes slipping and increases the accuracy of the projection.
Documento de Trabajo Working Paper N ° 210 N ° 210 TRADE REFORMS AND MANUFACTURING INDUSTRY IN CHILE

The Chilean economy underwent a deep structural change in the mid-seventies, through several economic reforms. Among these, the most impressive one was trade liberalization. This process caused a string of bankruptcies in the manufacturing industry and a reduction in the share of this sector in GDP, which some authors have used to imply that Chile has become a less industrialized economy. This paper describes the main policy changes that are relevant to understand the evolution of the manufacturing industry in Chile after the reforms, and analyzes the evolution of productivity using plant-level data. Our findings challenge the hypothesis that trade liberalization stifled the manufacturing sector and pushed the economy toward exporting raw materials. Also, our results show that the Chilean industry, after these economic reforms, became more efficient and competitive. ___________________ Paper prepared for Structure and Structural Change in the Chilean Economy , edited by P. Aroca and G.J.D. Hewings. We are grateful for the useful discussions with Antonio Escandón, Ricardo Vicuña and the participants in the XXXVII Anual Meeting of the Asociación Argentina de Economía Política. The views and conclusions presented in the paper are exclusively those of the authors and do not necessarily reflect the position of the Central Bank of Chile or of the Board members. E-mails: ralvarez@anderson.ucla. edu; rfuentes@bcentral.cl.
Long-Term Memory for Odors: Influences of Familiarity and Identification Across 64 Days

Few studies have investigated long-term odor recognition memory, although some early observations suggested that the forgetting rate of olfactory representations is slower than for other sensory modalities. This study investigated recognition memory across 64 days for high and low familiar odors and faces. Memory was assessed in 83 young participants at 4 occasions; immediate, 4, 16, and 64 days after encoding. The results indicated significant forgetting for odors and faces across the 64 days. The forgetting functions for the 2 modalities were not fundamentally different. Moreover, high familiar odors and faces were better remembered than low familiar ones, indicating an important role of semantic knowledge on recognition proficiency for both modalities. Although odor recognition was significantly better than chance at the 64 days testing, memory for the low familiar odors was relatively poor. Also, the results indicated that odor identification consistency across sessions, irrespective of accuracy, was positively related to successful recognition.