Miracle-dz/UniFAR-FTUs huggingface dataset:
FREERIDE-G: Supporting Applications that Mine Remote Data Repositories ∗

Analysis of large geographically distributed scientific datasets, also referred to as distributed data-intensive science, has emerged as an important area in recent years. An application that processes data from a remote repository needs to be broken into several stages, including a data retrieval task at the data repository, a data movement task, and a data processing task at a computing site. Because of the volume of data that is involved and the amount of processing, it is desirable that both the data repository and computing site may be clusters. This can further complicate the development of such data processing applications. In this paper, we present a middleware, FREERIDE-G(FRamework for Rapid Implementation of Datamining Engines in Grid), which support a high-level interface for developing data mining and scientific data processing applications that involve data stored in remote repositories. Particularly, we had the following goals behind designing the FREERIDE-G middleware: 1) Support high-end processing, i.e., use parallel configurations for both hosting the data and processing the data, 2) Ease use of parallel configurations, i.e., support a high-level API for specifying the processing, and 3) Hide details of data movement and caching. We have evaluated our system using three popular data mining algorithms and two scientific data analysis applications. The main observations from our experiments are as follows. First, FREERIDE-G is able to scale the processing extremely well when the number of data server and compute nodes are scaled evenly. Second, when only the number of compute nodes are scaled, our target class of applications achieve modest additional speedups. Finally, for applications that involve multiple passes on the dataset, caching remote data provides significant improvement.
A Generic, Scalable and Fine-Grained Data Access System for Sharing Digital Objects in Honest but Curious Cloud Environments

This paper presents a generic, scalable and fine-grained data access system that realizes the main challenges which hinder the growth of using storage-as-a-service for sharing digital objects offered by honest but curious cloud environments. These main challenges are maintaining data confidentiality, enforcing fine-grained data access control, applying efficient user revocation mechanism, preventing the collusion between users to access unauthorized digital objects, achieving scalability and possessing generic construction desirable feature. In addition, the proposed system avails digital passport which is presented by the user to be granted access to any digital object in the cloud environment. The usage of digital passport minimizes the number of transactions needed to authenticate the specified user. Moreover, the digital passport simplifies the data management for users since the user has to keep his passport only to use it to access the cloud. Furthermore, the digital passport prevents a rejoined user who possesses different attributes to access his previously authorized data. Additionally, the digital passport prohibits the collusion between an authorized user and a revoked one to own the access privileges once assigned to the revoked user. The proposed system exploits public key infrastructure (PKI) to capitalize the usage of offline operations to enhance system performance and to secure the transmission of private data as well as defending man in the middle attack. It should be noted that the implementation of the proposed system has showed the system computational validity.
Weighing Neutrinos with Galaxy Surveys

We show that galaxy redshift surveys sensitively probe the neutrino mass, with eV mass neutrinos suppressing power by a factor of 2. The Sloan Digital Sky Survey can potentially detect $N$ nearly degenerate massive neutrino species with mass ${m}_{\ensuremath{\nu}}\ensuremath{\gtrsim}0.65({\ensuremath{\Omega}}_{m}{h}^{2}/0.1N{)}^{0.8}\phantom{\rule{0ex}{0ex}}\mathrm{eV}$ at better than $2\ensuremath{\sigma}$ once microwave background experiments measure two other cosmological parameters. Significant overlap exists between this region and that implied by the Liquid Scintillator Neutrino Detector experiment, and even ${m}_{\ensuremath{\nu}}\ensuremath{\sim}0.01\char21{}0.1\mathrm{eV}$, as implied by the atmospheric anomaly, can affect cosmological measurements.
Personal Profile Settings as Cultural Frames: Facebook Versus Vkontakte

In recent years, there has been a growing interest in cross-country comparative studies of multiple social networking site (SNS) platforms, and the aim of these studies is to uncover the impact of culture on the use of SNSs. The present article seeks to advance this line of research by drawing a distinction between platform difference and usage difference. It argues that culture affects both the design and use of an SNS platform. Through comparing and contrasting the personal profile settings of Facebook and Vkontakte, the article shows that the design features of these two SNS platforms reflect the cultural characteristics of the countries from which the platforms originated. The cultural patterns that are encoded in the design features of the platforms inevitably influence the use of the platforms. This finding suggests the need to control for platform difference while examining the impact of culture on usage difference in cross-country studies of multiple SNS platforms.
Evaluation of HMM-based laughter synthesis

In this paper we explore the potential of Hidden Markov Models (HMMs) for laughter synthesis. Several versions of HMMs are developed, with varying contextual information and algorithms for estimating the parameters of the source-filter synthesis model. These methods are compared, in a perceptive tests, to the naturalness of actual human laughs and copy-synthesis laughs. The evaluation shows that 1) the addition of contextual information did not increase the naturalness, 2) the proposed method is significantly less natural than human and copy-synthesized laughs, but 3) significantly improves laughter synthesis naturalness compared to the state of the art. The evaluation also demonstrates that the duration of the laughter units can be efficiently learnt by the HMM-based parametric synthesis methods.
Adapting a speech into sign language translation system to a new domain

This paper presents a methodology for adapting an advanced communication system for deaf people in a new domain. This methodology is a user-centered design approach consisting of four main steps: requirement analysis, parallel corpus generation, technology adaptation to the new domain, and finally, system evaluation. In this paper, the new considered domain has been the dialogues in a hotel reception. With this methodology, it was possible to develop the system in a few months, obtaining very good performance: good speech recognition and translation rates (around 90%) with small processing times.
Realization of Askant Glance Camera Vision System by Using Extended Hough Transform

We propose a new vision mechanism which can saccadicly move its fixation point for detecting straight lines within tlie image frame. Tliis system, askant glance camera vision ( AGCV ) system, can extract straight lines precisely around the fixation point and ratlier coarsely at tlie periphery of the fixation point. Tliis camera system works in such a way that tlie fixation point catches tlie moving object by tlie information of the center of b~avity of edges, and the edges of tlie moving object can be extracted ratlier finely than the edges of the sleeping object. Tliis system demonstrates a model of tlie center - fine / peripheral coarse characteristics of human vision. This system is constn~cted by a sub-system which uses extended Hougli transform filnctions and another sub-system which tracks an object and shifts its fixation point to tlie center of gravity. In tliis paper, we show some experimental results to sliow tlie performance of AGCV system. basic configuration of AGCV system and how to track the moving objects in a manner of askant glance. Finally we present some experimental results to demonstrate the effectivity of the AGCV system. Although this camera vision imitates sidelong glance, it is different from such a camera vision that pursues an object by moving its camera head. AGCV system extracts straight lines precisely around the fixation point and rather coarsely at tlie periphery of tlie fixation point in a software contrivance using an extended Hougli transform ( EHT ) fiinction. In section 3, we sliow the basis theory of EHT fiinction, and in section 4, we show an example of AGCV system which tracks moving objects. In section 5, the concept of the askant glance is extended to the angular sensitivity for line detection.
Identification and Characterization of Noncoding Small RNAs in Streptococcus pneumoniae Serotype 2 Strain D 39 †

We report a search for small RNAs (sRNAs) in the low-GC, Gram-positive human pathogen Streptococcus pneumoniae. Based on bioinformatic analyses by Livny et al. (J. Livny, A. Brencic, S. Lory, and M. K. Waldor, Nucleic Acids Res. 34:3484–3493, 2006), we tested 40 candidates by Northern blotting and confirmed the expression of nine new and one previously reported (CcnA) sRNAs in strain D39. CcnA is one of five redundant sRNAs reported by Halfmann et al. (A. Halfmann, M. Kovacs, R. Hakenbeck, and R. Bruckner, Mol. Microbiol. 66:110–126, 2007) that are positively controlled by the CiaR response regulator. We characterized 3 of these 14 sRNAs: Spd-sr17 (144 nucleotides [nt]; decreased in stationary phase), Spd-sr37 (80 nt; strongly expressed in all growth phases), and CcnA (93 nt; induced by competence stimulatory peptide). Spd-sr17 and CcnA likely fold into structures containing single-stranded regions between hairpin structures, whereas Spd-sr37 forms a base-paired structure. Primer extension mapping and ectopic expression in deletion/insertion mutants confirmed the independent expression of the three sRNAs. Microarray analyses indicated that insertion/deletion mutants in spd-sr37 and ccnA exerted strong cis-acting effects on the transcription of adjacent genes, indicating that these sRNA regions are also cotranscribed in operons. Deletion or overexpression of the three sRNAs did not cause changes in growth, certain stress responses, global transcription, or virulence. Constitutive ectopic expression of CcnA reversed some phenotypes of D39 ciaR mutants, but attempts to link CcnA to -E to comC as a target were inconclusive in ciaR strains. These results show that S. pneumoniae, which lacks known RNA chaperones, expresses numerous sRNAs, but three of these sRNAs do not strongly affect common phenotypes or transcription patterns.
Impacts of Climate Change under the Threat of Global Warming for an Agricultural Watershed of the Kangsabati River

� Abstract—The effects of global warming on India vary from the submergence of low-lying islands and coastal lands to the melting of glaciers in the Indian Himalayas, threatening the volumetric flow rate of many of the most important rivers of India and South Asia. In India, such effects are projected to impact millions of lives. As a result of ongoing climate change, the climate of India has become increasingly volatile over the past several decades; this trend is expected to continue. Climate change is one of the most important global environmental challenges, with implications for food production, water supply, health, energy, etc. Addressing climate change requires a good scientific understanding as well as coordinated action at national and global level. The climate change issue is part of the larger challenge of sustainable development. As a result, climate policies can be more effective when consistently embedded within broader strategies designed to make national and regional development paths more sustainable. The impact of climate variability and change, climate policy responses, and associated socio-economic development will affect the ability of countries to achieve sustainable development goals. A very well calibrated Soil and Water Assessment Tool (R 2 = 0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the Kangsabati River watershed in Bankura district of West Bengal, India, in order to evaluate projected parameters for agricultural activities. Evapotranspiration, Transmission Losses, Potential Evapotranspiration and Lateral Flow to reach are evaluated from the years 2041-2050 in order to generate a picture for sustainable development of the river basin and its inhabitants. India has a significant stake in scientific advancement as well as an international understanding to promote mitigation and adaptation. This requires improved scientific understanding, capacity building, networking and broad consultation processes. This paper is a commitment towards the planning, management and development of the water resources of the Kangsabati River by presenting detailed future scenarios of the Kangsabati river basin, Khatra sub basin, over the mentioned time period. India's economy and societal infrastructures are finely tuned to the remarkable stability of the Indian monsoon, with the consequence that vulnerability to small changes in monsoon rainfall is very high. In 2002 the monsoon rains failed during July, causing profound loss of agricultural production with a drop of over 3% in India's GDP. Neither the prolonged break in the monsoon nor the seasonal rainfall deficit was predicted. While the general features of monsoon variability and change are fairly well-documented, the causal mechanisms and the role of regional ecosystems in modulating the changes are still not clear. Current climate models are very poor at modelling the Asian monsoon: this is a challenging and critical region where the ocean, atmosphere, land surface and mountains all
Splitting Methods Based on Algebraic Factorization for Fluid-Structure Interaction

We discuss in this paper the numerical approximation of fluid-structure interaction (FSI) problems dealing with strong added-mass effect. We propose new semi-implicit algorithms based on inexact block-$LU$ factorization of the linear system obtained after the space-time discretization and linearization of the FSI problem. As a result, the fluid velocity is computed separately from the coupled pressure-structure velocity system at each iteration, reducing the computational cost. We investigate explicit-implicit decomposition through algebraic splitting techniques originally designed for the FSI problem. This approach leads to two different families of methods which extend to FSI the algebraic pressure correction method and the Yosida method, two schemes that were previously adopted for pure fluid problems. Furthermore, we have considered the inexact factorization of the fluid-structure system as a preconditioner. The numerical properties of these methods have been tested on a model problem representing a blood-vessel system.
A Simple Asynchronous Shared Memory Consensus Algorithm Based on Omega and Closing Sets

This paper is on the design of a consensus object in the context of asynchronous shared memory systems where any number of process can suffer a crash failure. These systems are becoming more and more important with the advent of multicore architectures. To circumvent the impossibility of implementing a consensus object in such a context, the paper considers that the base read/write system model is enriched with an eventual leader failure detector (traditionally denoted Ω). This failure detector can easily be used to ensure that all the invocations of the consensus object issued by processes that do not crash eventually terminate(wait-freedom termination property). Hence, when one has to implement a consensus object in such an enriched system model, the main issue consists in designing an object (from base atomic read/write registers) on which the implementation can rely to ensure that no two different values can be decided from the consensus object. This paper presents such an object, called closing set. The main feature of this object is that it takes advantage of the system asynchrony by reducing the number of values that can be deposited: only concurrent deposits of values in an empty set are successful. The paper presents then a simple consensus algorithm based on closing sets. This algorithm is round-based and uses a closing set per round.
Development of sentiment classification system for Indonesian public policy tweet

We propose a sentiment classification system for Indonesian public policy tweet. The system consists of two subsystems: relevant tweet classification and tweet sentiment classification. Using Indonesian public policy tweet, we conduct the experiment to measure the performance for each subsystem and their combination. The purposes of the experiments are to find the best feature and algorithm for each subsystem. We emphasize to employ clustering technique for relevant tweet classification and supervised learning algorithm for sentiment classification. The best setting for clustering technique is using K-means algorithm and 2-gram feature. The best setting for tweet sentiment classification is using maximum entropy algorithm and 1-gram feature with accuracy 71.62%.
Vision-based moving target interception with a mobile robot based on motion prediction and online planning

In this paper, a vision-based moving target interception approach is proposed based on motion prediction and online path and velocity planning. For motion prediction, a fusion method of two motion prediction approaches with historical motion data is proposed to forecast the robot motion. With the predicted target pose as the subgoal, an optimal path is selected from a set of the third order Bezier curves based on their length and curvature cost. Finally, the control input can be calculated through the curvature function from the generated path. Simulation results show the effectiveness of the proposed method. The seamless integration of motion prediction and online planning makes the moving target interception more efficient and predictable.
High Levels of BCOX1 Expression Are Associated with Poor Prognosis in Patients with Invasive Ductal Carcinomas of the Breast

This study was to examine the breast cancer-overexpressed gene 1 (BCOX1) expression in invasive ductal carcinomas (IDC) of the breast and its value in the prognosis of the disease. The levels of BCOX1 expression in 491 paired IDC and surrounding non-tumor breast tissues as well as 40 paired fresh specimens were evaluated by tissue microarray, immunohistochemistry and quantitative RT-PCR. The potential associations of high BCOX1 expression with clinicopathological variables and the overall survival of these patients were analyzed. The relative levels of BCOX1 mRNA transcripts in the IDC breast tissues were significantly higher than that in the corresponding non-tumor tissues (P = 0.005). The anti-BCOX1 was predominantly stained in the cytoplasm of breast tissue cells and the levels of BCOX1 expression in the majority of breast cancer tissues were obviously higher than that in the corresponding non-tumor breast tissues. High levels of BCOX1 expression were found in 59.5% (292/491) of breast cancer tissues. The high BCOX1 expression was significantly associated with high histological grade (P = 0.037), positive expression of human epidermal growth factor receptor 2 (HER2, P = 0.031) and triple negative breast cancer (P = 0.027). The high BCOX1 expression in breast cancers was significantly associated with a shorter overall survival of these patients (P = 0.023), particularly in patients with triple negative breast cancer (P = 0.005). Therefore, the high BCOX1 expression may serve as a novel marker of poor prognosis and a potential therapeutic target for patients with IDC of the breast.
A Heuristic-Based Approach for Planning Federated SPARQL Queries

A large number of SPARQL endpoints are available to access the Linked Open Data cloud, but query capabilities still remain very limited. Thus, to support efficient semantic data management of federations of endpoints, existing SPARQL query engines require to be equipped with new functionalities. First, queries need to be decomposed into sub-queries not only answered by the available endpoints, but also executable in a way that the bandwidth usage is minimized. Second, query engines have to be able to gather the answers produced by the endpoints and merge them following a plan that reduces intermediate results.We address these problems and propose techniques that only rely on information about the predicates of the datasets accessible through the endpoints, to identify bushy plans comprise of sub-queries that can be efficiently executed. These techniques have been implemented on top of one existing RDF engine, and their performance has been studied on the FedBench benchmark. Experimental results show that our approach may support successful evaluation of queries, when other federated query engines fail, either because endpoints are unable to execute the sub-queries or federated query plans are too expensive.
Spiral construction of syntactically annotated spoken language corpus

Spontaneous speech includes a broad range of linguistic phenomena characteristic of spoken language, and therefore a statistical approach would be effective for robust parsing of spoken language. Though a large-scale syntactically annotated corpus is required for the stochastic parsing, its construction requires a lot of human resources. We propose a method of efficiently constructing a spoken language corpus for which the dependency analysis is provided. This method uses an existing spoken language corpus. A stochastic dependency parse is employed to tag spoken language sentences with the dependency structures, and the results are corrected manually. The tagged corpus is constructed in a spiral fashion where in the corrected data is utilized as the statistical information for automatic parsing of other data. Taking this spiral approach reduces the parsing errors, also allowing us to reduce the correction cost. An experiment using 10995 Japanese utterances shows the spiral approach to be effective for efficient corpus construction.
WrapRec: an easy extension of recommender system libraries

WrapRec is an easy-to-use Recommender Systems toolkit, which allows users to easily implement or wrap recommendation algorithms from other frameworks. The main goals of WrapRec are to provide a flexible I/O, evaluation mechanism and code reusability. WrapRec provides a rich data model which makes it easy to implement algorithms for different recommender system problems, such as context-aware and cross-domain recommendation. The toolkit is written in C# and the source code is publicly available on Github under the GPL license.
Bioinformatics Applications Note Systems Biology Spacem 3 : a Software for Biological Module Detection When Data Is Incomplete, High Dimensional and Dependent

Among classical methods for module detection, SpaCEM 3 provides ad hoc algorithms that were shown to be particularly well adapted to specific features of biological data: high-dimensionality, interactions between components (genes) and integrated treatment of missingness in observations. The software, currently in its version 2.0, is developed in C++ and can be used either via command line or with the GUI under Linux and Windows environments. Availability: The SpaCEM 3 software, a documentation and datasets are available from