Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fully Polynomial Time Approximation Scheme for Updating Credal Networks of Bounded Treewidth and Number of Variable States

Credal networks lift the precise probability assumption of Bayesian networks, enabling a richer representation of uncertainty in the form of closed convex sets of probability measures. The increase in expressiveness comes at the expense of higher computational costs. In this paper we present a new algorithm which is an extension of the wellknown variable elimination algorithm for computing posterior inferences in extensively specified credal networks. The algorithm efficiency is empirically shown to outperform a state-of-the-art algorithm. We then provide the first fully polynomial time approximation scheme for inference in credal networks with bounded treewidth and number of states per variable.
Market Liquidity Risk as an Indicator of Financial Stability : The Case of Indonesia

Market liquidity, or liquidity in trading, has become an important aspect of financial stability. The measurement of market liquidity has been especially important for emerging markets as they are exposed to the flow of short term investment fund. We follow the liquidity measurement approach by Bervas (2006) and a combination of Value at Risk (VaR) and Liquidity-adjusted Value at Risk developed by Bangia, et al (1999) and produce the measurement of exogenous cost of liquidity (CoL) from the Indonesian stock market. The paper sheds light on the possibility of the use of this liquidity risk measure as part of the financial stability analysis. We also forecasted the value of CoL to see if it can be used as an early warning indicator. The results shows that especially for the series during the final quarter of 2008, the movement of the forecasted values can predict whether the liquidity risk will be worse. However, the magnitude of the forecasted increase of CoL undervalued the real increase of CoL. The forecast in the second semester of 2009 is roughly similar to the actual measurement as it is considered a more normal period. The methodology is deemed to be fairly simple and intuitive to help provide an objective assessment of the stock market liquidity condition. JEL Classification Codes: G14, G15
Feeling bad on Facebook: depression disclosures by college students on a social networking site

Background: Depression is common and frequently undiagnosed among college students. Social networking sites are popular among college students and can include displayed depression references. The purpose of this study was to evaluate college students' Facebook disclosures that met DSM criteria for a depression symptom or a major depressive episode (MDE). Methods: We selected public Facebook profiles from sophomore and junior undergraduates and evaluated personally written text: “status updates. ” We applied DSM criteria to 1‐year status updates from each profile to determine prevalence of displayed depression symptoms and MDE criteria. Negative binomial regression analysis was used to model the association between depression disclosures and demographics or Facebook use characteristics. Results: Two hundred profiles were evaluated, and profile owners were 43.5% female with a mean age of 20 years. Overall, 25% of profiles displayed depressive symptoms and 2.5% met criteria for MDE. Profile owners were more likely to reference depression, if they averaged at least one online response from their friends to a status update disclosing depressive symptoms (exp(B) = 2.1, P<. 001), or if they used Facebook more frequently (P<.001). Conclusion: College students commonly display symptoms consistent with depression on Facebook. Our findings suggest that those who receive online reinforcement from their friends are more likely to discuss their depressive symptoms publicly on Facebook. Given the frequency of depression symptom displays on public profiles, social networking sites could be an innovative avenue for combating stigma surrounding mental health conditions or for identifying students at risk for depression. Depression and Anxiety, 2011. © 2011 Wiley‐Liss, Inc.
A multi-phase transition model for dislocations with interfacial microstructure

We study, by means of -convergence, the asymptotic behavior of a variational model for dislocations moving on a slip plane. The variational functional is a two-dimensional multi-phase transition-type energy given by a nonlocal term and a nonlinear potential which penalizes noninteger values for the components of the phase. In the limit we obtain an anisotropic sharp interfaces model. The relevant feature of this problem is that optimal sequences in general are not given by a onedimensional profile, but they can create microstructure.
Nicotine Addiction in Schizophrenia, Availability of Better TreatmentOptions as are in General Population

This article reviews literature regarding smoking cessation in Schizophrenia population, its harmful effects on health, finances, role of mental health care providers and better available options for treatment as are in general population. This population not only smokes at higher rates, but also has higher nicotine dependence with lower cessation rates than general population, people of schizophrenia have truncated life span due to smoking related diseases and premature mortality compared with the general population. Contrary to traditional reasoning that this population is not motivated or able to tolerate smoking cessation, but there is extensive literature that negates such rationale, even provides better treatment options to address this huge public health burden. Our review will mainly focusing treatment options particularly drug Varenicline, that shows most effective and promising results in patients of schizophrenia for smoking cessation as in general population, moreover different combination therapies, few new interventions, as well as some clinical areas will be discussed those need to be studied further in future.
Government Expenditure and Economic Growth: Evidence from India

The literature regarding the impact of government expenditure on economic growth is at best mixed. Given the conflicting results, we examine the impact of government developmental expenditure on India’s economic growth. Our study spans the period from 1950 to 2007. We have employed standard time series technique (unit root test and cointegration analysis) for our analysis. By applying Engle and Granger two-step methodology for cointegration analysis, we found that investment and trade have positive impact on economic growth, as their coefficients are significant at 5% level of confidence. The impact of government expenditure on economic growth, which is the focus of this study, is found to be positive and significant at 1% confidence level. From short run analysis, it is clear that government expenditure is also significant, indicating that it has a permanent and transitory effect. The Error Correction Model (ECM) term suggests that if we insert a shock into the model through one of these variables, approximately 33% of the deviation will be corrected within the first year. This is a rather slow adjustment process.
A View on the Risk-Neutral Density Forecasting of the Dax30 Returns

Option-implied risk-neutral densities incorporate market expectations with respect to the future course of option underlyings. Under the risk neutrality assumption various methods have been developed. In this paper, we look into two of them: parametric mixture of lognormals method and non-parametric Rookley method. We use option data on the DAX30 index. The Berkowitz test is employed to check the goodness of fit of the estimated densities, while we use the llikelihood criterion to compare their performance. Our results show that risk-neutral densities can be good predictors for horizons of 4, 5 and 6 weeks, while for horizons of 2 and 3 weeks the null hypothesis that risk neutral densities are accurate predictors of the distribution of the DAX30 returns is rejected.
Graphical interface for gene network inference application

A gene network shows the interactions between genes. Previous research has successfully infer gene network from microarray gene expression data using techniques from diverse fields such as pattern detection, machine learning and data mining. In this research, we applied the statistical language R for gene network inference. R provides statistical language and programming environment for statistical computing and graphics. We observed that R only provides command line interface with basic comand buttons. Hence, we built a gene network inference application with Microsoft Visual C# as the visual front-end and R as the back-end for novice R users who are interested to use our gene network inference tool. Th application has tabs which represents each phase of our inference methodology. Each time a user select and click, the command will be executed through the visual interface. Therefore, users no longer need to use the command line. The inference of gene network from gene expression data is useful for predicting relationships between genes. Gene network inference is important because it enhances the understanding on genomic function and directly helps development in bioinformatics and medical field.
A framework for reducing the modeling and simulation complexity of Cyberphysical Systems

As systems continue to evolve they rely less on human decision-making and more on computational intelligence. This trend in conjunction to the available technologies for providing advanced sensing, measurement, process control, and communication leads us towards the new field of Cyber-Physical System (CPS). Although these systems exhibit remarkable characteristics, the increased complexity imposed by numerous components and services makes their design extremely difficult. This paper proposes a software-supported framework for reducing the design complexity regarding the modeling, as well as the simulation of CPS. For this purpose, a novel technique based on system scenarios is applied. Evaluation results prove the effectiveness of introduced framework, as we achieve to reduce mentionable the modeling and simulation complexity with a controllable overhead in accuracy.
A Novel Block-Based Scheme for Arithmetic Coding

It is well-known that for a given sequence, its optimal codeword length is fixed. Many coding schemes have been proposed to make the codeword length as close to the optimal value as possible. In this paper, a new block-based coding scheme operating on the subsequences of a source sequence is proposed. It is proved that the optimal codeword lengths of the subsequences are not larger than that of the given sequence. Experimental results using arithmetic coding will be presented.
Effect of the voltage waveforms and power on hydrogen and hydrogen peroxide formation in water-spray gliding arc reactor

The present work deals with the formation of molecular hydrogen (H2) and hydrogen peroxide (H2O2) from liquid water sprayed into a non-thermal plasma formed by a gliding arc discharge. Previous work has demonstrated enhanced efficiency, as measured by specific energy yield, for the production of these species using a low power-pulsed plasma-gliding arc formed in a reactor with two divergent electrodes, water sprayed through a two way nozzle, and power generated by an ignition coil driven by a pulse generator. In the present work, H2 in the gas phase and H2O2 in the liquid water are determined for different values of the power injected into the reactor, as well for different waveforms (pulsed and alternating current AC), with Ar carrier. A comparison of the pulsed and AC waveforms of the voltage, for the same power injected into plasma (6 W), on the efficiency of the H2 and H2O2 production was made.
Query Expansion Using Wikipedia and Dbpedia

In this paper, we describe our query expansion approach submitted for the Semantic Enrichment task in Cultural Heritage in CLEF (CHiC) 2012. Our approach makes use of an external knowledge base such as Wikipedia and DBpedia. It consists of two major steps, concept candidates generation from knowledge bases and the selection of K-best related concepts. For selecting the K-best concepts, we ranked them according to their semantic relatedness with the query. We used Wikipedia-based Explicit Semantic Analysis to calculate the semantic relatedness scores. We evaluate our approach on 25 queries from the CHiC Semantic Enrichment dataset.
Extreme Software Scaling

The advent of SMP (symmetric multiprocessing) added a new degree of scalability to computer systems. Rather than deriving additional performance from an incrementally faster microprocessor, an SMP system leverages multiple processors to obtain large gains in total system performance. Parallelism in software allows multiple jobs to execute concurrently on the system, increasing system throughput accordingly. Given sufficient software parallelism, these systems have proved to scale to several hundred processors.
VALUE OF TIME FOR COMMUTING MOTORISTS

THE VALUE OF TRAVEL-TIME SAVINGS FOR COMMUTING MOTORISTS IS ESTIMATED FROM THE BEHAVIOR OF MOTORISTS IN EIGHT AREAS OF THE COUNTRY WHO FACED A CHOICE BETWEEN A TOLL ROAD AND A FREE ROAD IN THEIR TRIPS TO AND FROM WORK. THE VALUE OF TRAVEL TIME IS CALCULATED FROM THE ESTIMATED COEFFICIENTS OF TOLL AND TRAVEL-TIME VARIABLES IN ROUTE-CHOICE MODELS FOR THESE MOTORISTS. THE ROUTE-CHOICE MODELS ARE NONLINEAR AND ESTIMATED BY LEAST SQUARES TECHNIQUES. DATA ON THE CHARACTERISTICS OF THE ALTERNATE ROUTES WERE COLLECTED BY BOTH MOTORIST INTERVIEWS AND TEST-VEHICLE MEASUREMENTS, AND EACH WAS USED TO ESTIMATE INDEPENDENTLY THE VALUE OF TRAVEL TIME. THIS STUDY RECOMMENDS THE USE OF $2.82 PER PERSON PER HOUR AS THE VALUE OF TRAVEL-TIME SAVINGS FOR COMMUTER TRIPS OF MORE THAN TEN MINUTES AND MORE THAN FIVE MILES IN HIGHWAY ECONOMY STUDIES. WHILE THE MAIN OBJECTIVE OF THE STUDY WAS TO MEASURE THE VALUE OF TRAVEL TIME, THE SCOPE OF THE ANALYSIS INCLUDED STUDY OF A WIDE VARIETY OF POSSIBLE FACTORS AFFECTING ROUTE CHOICE--FOR EXAMPLE, MEASURES OF ROUTE CONGESTION OR SAFETY, FAMILY INCOME, AND SEX OF THE MOTORIST. IN ADDITION, SPECIAL ATTENTION IS GIVEN TO A CRITIQUE OF BOTH THE METHODOLOGY USED IN ESTIMATING THE VALUE OF TRAVEL TIME AND THE USE OF THE ESTIMATES IN HIGHWAY ECONOMY STUDIES. /AUTHOR/
An attempt to assess price elasticity of demand for pine wood on the primary wood market in the Bytnica Forest Division in the years 1997-2005

The study presents information on changes in the d emand for wood on the primary wood market in the years 1997-2005. Results of analyses are presented together with an assessment of the relationship between chan ges i demand and changes in prices for wood assortments. The paper also discusses resu lts of investigations concerning an analysis of sales of pine round wood, taking into c onsideration the analysis of price elasticity of demand. The study was also an attempt to present current problems connected with timber market.
A Multiplexed Quantitative Strategy for Membrane Proteomics

Toward multiplexed, comprehensive, and robust quantitation of the membrane proteome, we report a strategy combining gel-assisted digestion, iTRAQ (isobaric tags for relative and absolute quantitation) labeling, and LC-MS/MS. Quantitation of four independently purified membrane fractions from HeLa cells gave high accuracy (<8% error) and precision (<12% relative S.D.), demonstrating a high degree of consistency and reproducibility of this quantitation platform. Under stringent identification criteria (false discovery rate = 0%), the strategy efficiently quantified membrane proteins; as many as 520 proteins (91%) were membrane proteins, each quantified based on an average of 14.1 peptides per integral membrane protein. In addition to significant improvements in signal intensity for most quantified proteins, most remarkably, topological analysis revealed that the biggest improvement was achieved in detection of transmembrane peptides from integral membrane proteins with up to 19 transmembrane helices. To the best of our knowledge, this level of coverage exceeds that achieved previously using MS and provides superior quantitation accuracy compared with other methods. We applied this approach to the first proteomics delineation of phenotypic expression in a mouse model of autosomal dominant polycystic kidney disease (ADPKD). By characterizing kidney cell plasma membrane from wild-type versus PKD1 knock-out mice, 791 proteins were quantified, and 67 and 37 proteins showed ≥2-fold up-regulation and down-regulation, respectively. Some of these differentially expressed membrane proteins are involved in the mechanisms underlying major abnormalities in ADPKD, including epithelial cell proliferation and apoptosis, cell-cell and cell-matrix interactions, ion and fluid secretion, and membrane protein polarity. Among these proteins, targeting therapeutics to certain transporters/receptors, such as epidermal growth factor receptor, has proven effective in preclinical studies of ADPKD; others are known drug targets in various diseases. Our method demonstrates how comparative membrane proteomics can provide insight into the molecular mechanisms underlying ADPKD and the identification of potential drug targets, which may lead to new therapeutic opportunities to prevent or retard the disease.
Stop motion goggle: augmented visual perception by subtraction method using high speed liquid crystal

Stop Motion Goggle (SMG) expands visual perception by allowing users to perceive visual information selectively through a high speed shutter. In this system, the user can easily observe not only periodic rotational motion such as rotating fans or wheels, but also random motion like bouncing balls. In this research, we developed SMG and evaluated the effect of SMG on visual perception of high speed moving objects. Furthermore this paper describes users' behaviors under the expanded visual experience.
Measuring Word Similarity Based on Pattern Vector Space Model

It is an important work in natural language processing to measure the semantic similarity between two words. This paper proposes a new method for computing word similarity based on pattern vector space model. Analogous to traditional vector space model in information retrieval, a word is represented as a vector in this paper. Each dimension corresponds to a contextual pattern. The similarity between two words is calculated by the cosine of the angle between their vectors. In the experiment, the proposed model is compared to other two baseline models on a Chinese version Miller-Charles data set. It shows that this method achieves competitive results.
Locating Matching Rules by Mining Software Change Log

A software system maintenance activity is typically performed under an environment of lacking knowledge about how to process it. This scarcity of knowledge may be caused by various factors, such as the large size and complexity of the systems, high staff turnover, poor documentation and long-term system maintenance. The study applies Apriori algorithm to extract information from software change logs. Unfortunately, the software change logs generate many rules. Because searches the suitable rule from many rules is difficult and important matter, especially. This study focuses on the software co-change dependency and proposes a classification model based on association mining, to deal with such kind of dependency. The model combines data mining technologies, the traditional decision-tree and neural learning capabilities, to handle the complicated and real cases, and then improve the rule searching efficiency and the matching accuracy.
Zinc and copper status in children with high family risk of premature cardiovascular disease.

BACKGROUND Zinc and copper are beneficial to health, growth and development, and also for the prevention of cardiovascular disease (CVD) with regards to improved dietary habits as a preliminary step in CVD prevention. This study was conducted among 2-18-year-old children with high family risk of premature CVD in comparison to controls. SUBJECTS AND METHODS One hundred randomly selected children whose parents had premature myocardial infarction were included in the study. The controls were 100 individuals randomly selected from the case group's neighbors and matched for age, sex, and socioeconomic status. A four-day food record questionnaire was used to assess zinc and copper intakes, and their serum levels were determined using Flame-Atomic Absorption Spectrophotometry. The data were analyzed by SPSS/Windows V6 software, using the Student's t and Mantel-Hanzel tests. Significance of differences was considered at P<0.05. RESULTS The daily zinc intake was significantly lower in the case than control group (6.89+/-2.97 vs. 8.30+/-2.45 mg, P=0.047). The mean serum zinc level was not significantly different between both groups (82.12+/-14.1 vs. 92.26+/-23.7 microg/dL, P>0.05). Zinc deficiency was more prevalent among the case in boys than their controls (58% vs. 18%, P=0.04). This difference was not significantly in girls (44% vs. 40%). The daily intake and serum level of copper were not significantly different between the case and control groups. No case of copper deficiency was found. The mean systolic blood pressure was not significantly different between the zinc-deficient and zinc-sufficient subjects. Although the mean diastolic blood pressure of the former was higher than the latter, there was no statistically significant difference. About 23.7% of all studied sample had mild-to-moderate degrees of failure to thrive, with significantly lower daily intake and serum zinc level than other subjects (5.14+/-1.06 mg, 82.09+/-12.74 microg/dL vs. 6.89+/-2.14 mg, 99.25+/-27.15 microg/dL, respectively, P<0.05). CONCLUSION It is recommended that emphasis be placed on the consumption of food rich in zinc by children, especially those with high family risk of premature CVD.
A novel shot boundary detection framework

Shot boundary detection servers as a preliminary step to structure the content of videos. Up to now, a large number of methods have been proposed. We give a brief overview of previous works with a novel view, focusing on the solutions of the two main disturbances, i.e., abrupt illuminance change and great camera or object motion. Then this paper presents a novel shot boundary detection framework, consisting of three components: fade out/in (abbreviated as FOI) detector, cut detector and gradual transition (abbreviated as GT) detector. The key technique of FOI detector is the recognition of monochrome frames. For cut detection, a second-order difference method is firstly applied to obtain candidate cuts, and then a post-processing procedure is taken to eliminate the false positives. In GT detector, the twin-comparison approach is employed to detect short gradual transition which lasts less than six frames, while for long gradual transition, an improvement of twin-comparison algorithm is designed. Firstly, to effectively reduce the false alarms of quick motion, the lower threshold is self-adaptive to motion feature. Secondly, an FSA (finite state automata) model is adopted to replace the twin-comparison strategy. This framework makes good use of various features and successfully integrates all the modules together. Finally, the system is evaluated on the TRECVID benchmarking platform and the experimental results reveal the effectiveness of our system.
Synchronous and metachronous gastric gist with pancreatic adenocarcinoma: report of 2 cases and a review of literature

We report two cases of a Gastrointestinal Stromal Tumor (GIST) synchronous and metachronous, respectively, with pancreatic adenocarcinoma. To our knowledge, this is the first report of a GIST involved 3 years after a ductal pancreatic adenocarcinoma. Data from the literature and our cases seem to suggest that incidental GIST may occur synchronously and metachronously with other cancers more frequently than expected. Thus, the patients with a diagnosis of pancreatic adenocarcinoma may have undergone a strict follow up for GIST