Miracle-dz/UniFAR-FTUs huggingface dataset:
Link Strength-Based Collaborative Filtering for Enhancing Prediction Accuracy

User-based collaborative filtering recommends items to users by analyzing user preferences. Nearest neighbors are identified based on similarity between users and preference prediction of items is performed by using the nearest neighbors. The prediction accuracy depends on how the nearest neighbors are identified among users. In this paper, we propose link strength-based user modeling by applying trust information between users and item ratings to enhance the prediction accuracy. In the proposed user modeling, nearest neighbor candidate is extracted in traditional manner and final nearest neighbor is identified by calculating user ranking with trust information. Trust information between users is presented by link and consists of direct and indirect relation. We evaluate the prediction accuracy on recommended items and experimental results show that the prediction accuracy is improved by applying the proposed method.
The Use of Three Long Non-Coding RNAs as Potential Prognostic Indicators of Astrocytoma

Long noncoding RNAs (lncRNAs) are pervasively transcribed and play a key role in tumorigenesis. The aim of the study was to determine the lncRNA expression profile in astrocytomas and to assess its potential clinical value. We performed a three-step analysis to establish the lncRNA profile for astrocytoma: a) the lncRNA expression was examined on 3 astrocytomas as well as 3 NATs (normal adjacent tissues) using the lncRNA microarray; b) the top-hits were validated in 40 astrocytomas (WHO grade II-IV) by quantitative real time-PCR (qRT-PCR); c) the hits with significant differences were re-evaluated using qRT-PCR in 90 astrocytomas. Finally, 7 lncRNAs were found to have a significantly different expression profile in astrocytoma samples compared to the NAT samples. Unsupervised clustering analysis further revealed the potential of the 7-lncRNA profile to differentiate between tumors and NAT samples. The upregulation of ENST00000545440 and NR_002809 was associated with advanced clinical stages of astrocytoma. Using Kaplan-Meier survival analysis, we showed that the low expression of BC002811 or XLOC_010967, or the high expression of NR_002809 was significantly associated with poor patient survival. Moreover, Cox proportional hazard regression analysis revealed that this prognostic impact was independent of other clinicopathological factors. Our results indicate that the lncRNA profile may be a potential prognostic biomarker for the prediction of post-surgical outcomes.
Using Convolutional Neural Networks to Classify Dog Breeds

Dog breed categorization is a very specific application of convolutional neural networks. It falls under the category of fine-grained image classification problem, where inter-class variations are small and often one small part of the image considered makes the difference in the classification. The various classes of ImageNet can have large inter-class variations, making it easier to categorize correctly. In this work, I aim to use a convolutional neural network framework to train and categorize dog breeds. I approach this first using CNNs based on LeNet and GoogLeNet architectures.
Key features for a successful model-driven development tool

The main focus of Software Engineering discipline is to establishing methods and processes for the effective and efficient development of software projects. One of the most relevant paradigms for achieving this goal is Model-Driven Development (MDD). MDD uses models at different abstraction levels to automatically generate software products by means of model-transformations. However, one of the main issues related to the development of MDD technologies is the lack of standardization in terms of the features that need to be considered to support the current industry needs. This difficults the comparison of existing technologies since there are not a reference point for the creation of new MDD approaches with their corresponding supporting tools. This paper analyses these industry needs through an exploratory study. From the results obtained, it states the main features that must be supported by MDD tools. In addition, this paper presents an analysis about the presence or absence of these features in a set of industrial MDD tools.
Small Area Estimation of the Homeless in Los Angeles: An Application of Cost-Sensitive stochastic Gradient Boosting

In many metropolitan areas, eorts are made to count the homeless to ensure proper provision of social services. Some areas are very large, which makes spatial sampling a viable alternative to an enumeration of the entire terrain. Counts are observed in sampled regions but must be imputed in unvisited areas. Along with the imputation process, the costs of underestimating and overestimating may be dierent. For example, if precise estimation in areas with large homeless counts is critical, then underestimation should be penalized more than overestimation in the loss function. We analyze data from the 2004-2005 Los Angeles County homeless study using an augmentation of L1 stochastic gradient boosting that can weight overestimates and underestimates asymmetrically. We discuss our choice to utilize stochastic gradient boosting over other function estimation procedures. In-sample tted and out-of-sample imputed values, as well as relationships between the response and predictors, are analyzed for various cost functions. We gratefully acknowledge numerous helpful discussions with Greg Ridgeway. The work of Brian Kriegler and Richard Berk was supported by the National Science Foundation under grant SES-0437179, \Ensemble Methods for Data Analysis in the Behavior, Social, and Economic Sciences. "
Detection of Helicobacter pylori in City Water, Dental Units' Water, and Bottled Mineral Water in Isfahan, Iran

Helicobacter pylori infection in human is one of the most common infections worldwide. However, the origin and transmission of this bacterium has not been clearly explained. One of the suggested theories is transmission via water. This study was conducted to determine the prevalence rate of H. pylori in tap water, dental units' water, and bottled mineral water in Iran. In the present study, totally 200 water samples were collected in Isfahan province and tested for H. pylori by cultural method and polymerase chain reaction (PCR) by the detection of the ureC (glmM) gene. Using cultural method totally 5 cultures were positive. Two out of 50 tap water samples (4%), 2 out of 35 dental units' water (5.8%) samples, and 1 out of 40 (2.5% ) from water cooler in public places were found to be contaminated with H. pylori. H. pylori ureC gene was detected in 14 (7%) of water samples including 5 tap water (10%), 4 dental units' water (11.4%), 1 refrigerated water with filtration, and 4 (10%) water cooler in public places samples. This may be due to the coccoid form of bacteria which is detected by PCR method.
Inference in Credal Networks with Branch-and-Bound Algorithms

A credal network associates sets of probability distributions with directed acyclic graphs. Under strong independence assumptions, inference with credal networks is equivalent to a signomial program under linear constraints, a problem that is NP-hard even for categorical variables and polytree models. We describe an approach for inference with polytrees that is based on branch-and-bound optimization/search algorithms. We use bounds generated by Tessem’s A/R algorithm, and consider various branch-and-bound schemes.
Routing in unmanned aerial ad hoc networks: A recovery strategy for Greedy geographic forwarding failure

Unmanned Aeronautical Ad Hoc Networks (UAANETs) are a type of Mobile Ad Hoc Networks (MANETs) which are infrastructureless and self-organizing networks. The specificity of UAANETs is that they are formed by small and medium sized Unmanned Aerial Vehicles (UAVs) also known as drones. In UAANETs as well as in MANETs, geographic routing is widely used. Geographic routing relies on Greedy Forwarding (GF), also called Greedy Geographic Forwarding (GGF). GGF fails when a packet arrives at a node that has no neighbor closer to the destination than it is. The node in this situation is referred to as a void node. In this paper, we propose a strategy that salvages packets in void node situations. We thereafter append this strategy to a protocol that features GGF. Simulations in OPNET show an increase in packet delivery ratio of about 2% at virtually no additional cost.
A non-parametric CFAR detector based on SAR sea clutter statistical modeling

A fast non-parametric CFAR ship detector based on the statistical modeling of sea clutter in SAR images is proposed. Typical CFAR detectors, like the double parameter model (DPM), assume a Gaussian sea clutter model and usually degrade the image resolution using target windows. The proposed detector works in a pixel-by-pixel fashion, adaptively selecting a decision threshold for every single patch the SAR image is divided into. Sea clutter is modeled using the Generalized Gamma distribution. Therefore, the presence of different-sized ships will not become an issue and they will be better characterized, allowing the extraction of the target information, which could be used for refocusing, feature extraction, modeling and classification, while maintaining the resolution of the SAR image.
A Hybrid of Clonal Selection Algorithm and Frequency Sampling Method for Designing a 2-D FIR Filter

A hybrid of Clonal Selection Algorithm and Frequency Sampling Method (CSA-FSM) is employed to design a 2D FIR filter in this paper. The algorithm is applied to optimize the sampled frequencies of transition band of digital filters, then producing a planar response matrix of a 2D FIR digital filter. The stimulation results show the passband ripples and stopband attenuation of 2D FIR filters, the proposed methodology is better than those designed by well-known methods.
Is the Semantic Web a Small World

In this paper, we describe a comprehensive analysis of graph-theoretical properties of online social networks based on the Friend-of-a-Friend (FOAF) ontology. Of particular interest for this work were properties related to the small-world phenomenon. More than 1.6 million of the FOAF documents collected on the Semantic Web met our requirements and were analyzed in depth. Most FOAF documents are created and published by social networking services, blog hosting services, or combinations of the two as a matter of routine; only a fractional amount are maintained by individuals. Although the FOAF ontology defines unique identifiers for persons in theory, retrieval and particularly fusion of personal information is difficult and error-prone in practice. Nevertheless, we identified the largest strongly connected components of various community networks based on FOAF documents and analyzed them in regard to the small-world phenomenon. Interestingly, all components examined exhibited a characteristic path length comparable to the smallest length achievable for a graph of the respective size, and the clustering coefficient was much greater than expected for an equivalent random graph; along with power law degree distributions, both are typical features of small-world graphs.
Spatially Resolved Spitzer Spectroscopy of the Starburst Nucleus in NGC 5253

We present new Spitzer Space Telescope data on the nearby, low-metallicity starburst galaxy NGC 5253, from the Infrared Array Camera (IRAC) and the Infrared Spectrograph (IRS). The mid-IR luminosity profile of NGC 5253 is clearly dominated by an unresolved cluster near the center, which outshines the rest of the galaxy at longer wavelengths. We find that the [Ne III]/[Ne II] ratio decreases from ~8.5 at the center to ~2.5 at a distance of ~250 pc. The [S IV]/[S III] follows the [Ne III]/[Ne II] ratio remarkably well, being about 4-5 times lower at all distances. Our spectra reveal for the first time a PAH emission feature at 11.3 μm, and its equivalent width increases significantly with distance from the center. The good anticorrelation between the PAH strength and the product between hardness and luminosity of the UV radiation field suggests photodestruction of the PAH molecules in the central region. The high-excitation [O IV] 25.91 μm line was detected at 0.42 × 10-20 W cm-2. Our results demonstrate the importance of spatially resolved mid-IR spectroscopy.
Transition to Democracy in Eastern Europe and Russia: Impact on Politics, Economy and Culture

Preface Introduction Integration of the Processes and Components of Transition to Democracy by Barbara Wejnert Transition to Democracy: Implications on Politics McCarthyism has a New Name--"Lustration": A Personal Recount of Political Events by Jan Kavan The Contribution of Collective Protests to the Softening of Communist Regimes in East Central Europe by Barbara Wejnert A Line of Blood: How December, 1970 Prepared Polish Workers for Political Transition in 1989 by Jack M. Bloom Transition to Democracy: Impact on Ecomomy Transitional Economies and Income Inequality: The Case of Estonia by Nancy Brandon Tuma, Mikk Titma, and Rein Murakas Fiscal Policy and Capital Formation in Transition Economies by Grzegorz W. Kolodko Privatization Politics in Russia: Success or Failure? Privatization and the Development of Corporate Governance Structure by Alexei Makeshin Transition to Democracy: Social Problems and Policy Issues Nouveaux Riches vs Nouveaux Pauvres: Policy Making in Transition Economies by Grzegorz W. Kolodko Polish Working Class's Vision of a Well Ordered Economy by Juliusz Gardawski A Country in Transition: Health Crisis in Ukraine with Focus on Tobacco and Alcohol by Lara A. Romaniuk Polish Women during Transition to Democracy: A Preliminary Research Report by J. Mayone Stycos and Barbara Wejnert Transition to Democracy: Impact on Culture Cultural and Civic Movements Prefiguring the Breakdown of the Socialist Regime in Yugoslavia by Stjepan Gredelj The Artist's Freedom and Democracy by Maria Nowakowska Stycos and Grazyna Borkowska The Politics of Architecture and Architecture of Politics by Sergei Zherebkin and Barbara Wejnert Concluding Remarks The Impact of Democratic Transitions on Politics, Economy, and Culture: Lessons from Eastern Europe and Russia by Barbara Wejnert Bibliography Index
Understanding News Sharing in Social Media from the Diffusion of Innovations Perspective

Social media is becoming increasingly used as sources of news. The present study thus investigates the factors that may influence news sharing behavior in social media. Based on the diffusion of innovations theory, we propose several influential factors derived from online social networks which include opinion leadership, homophily, tie strength, and news preference. By incorporating social network analysis with the support of other statistical methods, we found that opinion leadership was the strongest factor predicting news sharing, followed by news preference and tie strength. Notably, we looked into the phenomenon of homophily at the network and individual levels. While homophily existed at the network level, such similarity actually hampered news sharing in users' local networks. Implications of our work are also discussed.
Automatic animation skeleton using repulsive force field

A method is proposed in this paper to automatically generate the animation skeleton of a model such that the model can be manipulated according to the skeleton. With our method, users can construct the skeleton in a short time, and bring a static model both dynamic and alive. The primary steps of our method are finding skeleton joints, connecting the joints to form an animation skeleton, and binding skin vertices to the skeleton. Initially, a repulsive force field is constructed inside a given model, and a set of points with local minimal force magnitude are found based on the force field. Then, a modified thinning algorithm is applied to generate an initial skeleton, which is further refined to become the final result. When the skeleton construction completes, skin vertices are anchored to the skeleton joints according to the distances between the vertices and joints. In order to build the repulsive force field, hundreds of rays are shot radially from positions inside the model, and it leads to that the force field computation takes most of the execution time. Therefore, an octree structure is used to accelerate this process. Currently, the skeleton generated from a typical 3D model with 1000 to 10000 polygons takes less than 2 minutes on a Intel Pentium 4 2.4 GHz PC.
Band-Limited Volterra Series-Based Digital Predistortion for Wideband RF Power Amplifiers

The continuously increasing demand for wide bandwidth creates great difficulties in employing digital predistortion (DPD) for radio frequency (RF) power amplifiers (PAs) in future ultra-wideband systems because the existing DPD system requires multiple times the input signal bandwidth in the transmitter and receiver chain, which is sometimes almost impossible to implement in practice. In this paper, we present a novel band-limited digital predistortion technique in which a band-limiting function is inserted into the general Volterra operators in the DPD model to control the signal bandwidth under modeling, which logically transforms the general Volterra series-based model into a band-limited version. This new approach eliminates the system bandwidth constraints of the conventional DPD techniques, and it allows users to arbitrarily choose the bandwidth to be linearized in the PA output according to the system requirement without sacrificing performance, which makes the DPD system design much more flexible and feasible. In order to validate this idea, a high-power LDMOS Doherty PA excited by various wideband signals, including 100-MHz long-term evolution advanced signals, was tested. Experimental results showed that excellent linearization performance can be obtained by employing the proposed approach. Furthermore, this technique can be applied to other linear-in-parameter models. In future ultra-wideband systems, this new technique can significantly improve system performance and reduce DPD implementation cost.
The Use of the Dictionary of Occupational Titles as a Source of Estimates of Educational and Training Requirements

The use of estimates of educational and training requirements to measure educational investment must distinguish between (1) functional or performance requirements, (2) employer or hiring requirements, and (3) educational attainment. Each has its uses, but only the first provides the basic information needed for manpower planning and development. The use of the functional scales developed for the revised 1965 Dictionary of Occupational Titles is explained. The provision of such estimates in a Supplement to the Dictionary now provides basic reference points for scholars in the field. Also described is the structure of definitions in the Dictionary, the language controls which these definitions provide, and how the definitions integrate with the estimates of functional educational and training requirements.
PHARMACOGNOSTICAL , PHYTOCHEMICAL AND CARDIOPROTECTIVE ACTIVITY OF TAMARINDS INDICA LINN

Many herbal remedies have been employed in various medicine systems for the treatment and management of the different diseases. The Tamarinds indica commonly known as ‘imali’ has been recognized in different system of traditional medicines for the treatment of different diseases and aliments of human being. This review supports of all updated information on its pharmacognostical, pharmacological activity and traditional uses. Preliminary phytochemical screening of this plant revealed the presences of, flavonoids, steroid, glycoside alkaloid and Triterpenoids. It has been reported as Antihelminthic, antimicrobial, antiseptic, antiviral, asthma, astringent, bacterial skin infections, constipation (chronic or acute), and diabetes. There is no report available on isolated constituents of bioactive compound from plant bark of Tamarinds indica which supports it’s further to isolating a useful pharmacologically active compound as a drug. INTRODUCTION: All over the world, plants were used as main source of medicines by ancestors. The rise of modern Western medicine was initially accompanied by a decline in the practice of herbalism in all cultures and it was believed that synthetic chemicals were best medicines to treat illness and cure disease. The quest for a healthier lifestyle has made people to once again recognize the healing power of herbs. Even in the west, natural products are now widely available and herbalism is again coming into lime light in a world which is becoming healthier and environmentally conscious. Herbal remedies can work without many of the unpleasant side effects of modern medicines . The World Health Organization (WHO) estimates that about 80% of the population living in the developing countries relies almost exclusively on traditional medicine for their primary health care needs. Antioxidant: A free radical is any chemical species (capable of independent existence) possessing one or more unpaired electrons, an unpaired electron being one that is alone in an atomic or molecular orbital. Free radicals are formed from molecules via the breakage of a chemical bond such that each fragment keeps one electron (free radicals may also be formed by collision of the non radical species by a reaction between a radical and a molecule which must then result in a radical since the total number of electrons is odd), by cleavage of a radical to give another radical and, finally via redox reactions. Three partially reduced species of oxygen are generated depending upon the number of electrons transferred. These are: Super oxide oxygen (O2): one electron Hydrogen peroxide (H2O2): two electrons Hydroxyl radical (OH): three electrons
Decoding the Locus of Covert Visuospatial Attention from EEG Signals

Visuospatial attention can be deployed to different locations in space independently of ocular fixation, and studies have shown that event-related potential (ERP) components can effectively index whether such covert visuospatial attention is deployed to the left or right visual field. However, it is not clear whether we may obtain a more precise spatial localization of the focus of attention based on the EEG signals during central fixation. In this study, we used a modified Posner cueing task with an endogenous cue to determine the degree to which information in the EEG signal can be used to track visual spatial attention in presentation sequences lasting 200 ms. We used a machine learning classification method to evaluate how well EEG signals discriminate between four different locations of the focus of attention. We then used a multi-class support vector machine (SVM) and a leave-one-out cross-validation framework to evaluate the decoding accuracy (DA). We found that ERP-based features from occipital and parietal regions showed a statistically significant valid prediction of the location of the focus of visuospatial attention (DA = 57%, p < .001, chance-level 25%). The mean distance between the predicted and the true focus of attention was 0.62 letter positions, which represented a mean error of 0.55 degrees of visual angle. In addition, ERP responses also successfully predicted whether spatial attention was allocated or not to a given location with an accuracy of 79% (p < .001). These findings are discussed in terms of their implications for visuospatial attention decoding and future paths for research are proposed.