Miracle-dz/UniFAR-FTUs huggingface dataset:
Traffic-Related Air Pollution and DNA Damage: A Longitudinal Study in Taiwanese Traffic Conductors

Background There is accumulating epidemiologic evidence that exposure to traffic-related air pollutants, including particulate matter (PM) and polyaromatic hydro carbons (PAHs), plays a role in etiology and prognosis of a large scale of illnesses, although the role of specific causal agents and underlying mechanisms for different health outcomes remains unknown. Objective Our general objective was to assess the relations between personal exposure to traffic exhausts, in particular ambient PM2.5 and PAHs, and the occurrence of DNA strand breaks by applying personal monitoring of PM and biomarkers of exposure (urinary 1-hydroxypyrene-glucuronide, 1-OHPG) and effect (urinary 8-hydroxydeoxyguanosine, 8-OHdG and DNA strand breaks). Methods We recruited 91 traffic conductors and 53 indoor office workers between May 2009 and June 2011 in Taipei City, Taiwan. We used PM2.5 personal samplers to collect breathing-zone particulate PAHs samples. Spot urine and blood samples after work shift of 2 consecutive days were analyzed for 1-OHPG, 8-OHdG and DNA strand breaks, respectively. Statistical methods included linear regression and mixed models. Results Urinary 8-OHdG levels and the occurrence of DNA strand breaks in traffic conductors significantly exceeded those in indoor office workers in mixed models. Particulate PAHs levels showed a positive association with urinary 1-OHPG in the regression model (β = 0.056, p = 0.01). Urinary 1-OHPG levels were significantly associated with urinary 8-OHdG levels in the mixed model (β = 0.101, p = 0.023). Our results provide evidence that exposure to fine particulates causes DNA damage. Further, particulate PAHs could be biologically active constituents of PM2.5 with reference to the induction of oxidative DNA damages.
An Improved Algorithm for Materialized View Selection

The data warehouse is subject oriented, integrated, nonvolatile and time-varying data sets, which is used to support management decision-making. A data warehouse stores materialized views of data from one or more sources, with the purpose of efficiently implementing Decision-support or OLAP queries. One of the most important decisions in designing a data warehouse is the selection of materialized views to be maintained at the warehouse. The materialization of all views is not possible because of the space constraint and maintenance cost constraint. Selecting a suitable set of views that minimize the total cost associated with the materialized views is the key objective of data warehousing. In this paper, first the query cost view selection problem model is proposed. Second, the methods for selecting materialized views are presented. The genetic algorithm is applied to the materialized view selection problem. But with the development of genetic process, the legal solution produced become more and more difficult. Therefore, improved algorithm has been presented in this paper. Finally, in order to test the function and efficiency of our algorithms, experiment simulation is adopted. The experiments show that the given methods can provide near-optimal solutions in limited time and work well in practical cases. Randomized algorithms will become invaluable tools for data warehouse evolution.
This Draft: October 1998 WILL LABOUR INTENSIVE INDUSTRIES ALWAYS LOCATE IN LOW WAGE COUNTRIES?

This paper analyses how trade liberalisation affects location decisions of firms that are vertically linked and which differ in factor intensities. Firms can choose to locate either in a low wage or a low rental country. For some intermediate levels of trade costs all upstream and downstream firms agglomerate in one country, despite the advantage of lower factor costs in the other country. Whether the industries agglomerate in the low wage or the low rental country depends on the level of trade costs on intermediate and final goods and the relative differences in factor prices. ____________________________________________________________________________ * I would like to thank R.Fernandez, J.Francois, S.Jayasuriya, D. Prentice, R.Tourky, A.Venables and participants at seminars held at La Trobe University, Australian National University, New York University, Federal Reserve Bank of New York and ERWIT98 in Rotterdam, for helpful comments. An earlier version of this paper is entitled, 'Will Labour Intensive Industries Always Locate in Labour Abundant Countries', La Trobe University Discussion Paper A98.2.
Does the Participation in the Microcredit Programs Contribute to the Development of Women Entrepreneurship at the Household Level? Experience from Bangladesh

The study intends to assess the impact of the participation in the microcredit programs in Bangladesh on women entrepreneurship development at the household level. The main objective is to see whether the participation in the microcredit programs help participating women to start their own businesses and to create employment for other people. The analysis is based on a household-level survey of 920 (N=920) households. The sample households have been selected randomly from the participants of top three microfinance instructions, Grameen Bank, BRAC and ASA, in Bangladesh. The results indicate that the participation in the microcredit programs does not promote women entrepreneurship at the household level. But, the results indicate that the same participation significantly increases capital of existing businesses of participating households.
Navigating the Semantic Web with Logical Information Systems

Exploratory search is about browsing and understanding an information base. It requires a more interactive process than retrieval search, where the user sends a query and the system returns answers. Logical Information Systems (LIS) support exploratory search by guiding users in the construction of queries, and by giving summaries of query results. The contribution of this paper is to adapt and extend LIS to the Semantic Web. We define a summarization and navigation data structure that provides rich views over data, and guides users from view to view. This guiding is proved consistent (i.e., never leads to an empty result set), and complete (i.e., every query can be reached by navigation only). The query language covers a large fragment of SPARQL, and is more concise by using a syntax close to description logics. Our approach could be implemented on top of existing tools for storing, reasoning and querying.
FPGA Acceleration of a Subband Beamforming Algorithm for Speech Enhancement

Signal processing methods for speech enhancement are of vital interest for many equipment. In particular, beamforming algorithms, which perform spatial filtering to separate signals that have overlapping frequency content but are originated from different spatial locations, are important for a wide range of applications. In this paper, a particular beamforming algorithm based on the signal-to-noise ratio together with calibrated signals is described. In order to achieve computational efficiency, the algorithm is implemented in the frequency domain and is accelerated by FPGA.
Exact Ground State Energy of the Strong -

The polaron has been of interest in condensed matter theory and eld theory for about half a century, especially its strong coupling limit. It was not until 1983, however, that a proof of the asymptotic formula for the ground state energy was nally given by using diicult arguments involving the large deviation theory of path integrals. Here we derive the same asymptotic result, E 0 ? C 2 , and with explicit error bounds, by simple, rigorous methods applied directly to the Hamiltonian. Our method is easily generalizable to other settings, e.g., the excitonic and magnetic polarons. The polaron Hamiltonian of Frr ohlich 1] is a model for the Coulomb interaction of one or more electrons with the phonons of an ionic crystal. In the course of time it was also seen to be an interesting eld theory model of non-relativistic particles interacting with a scalar boson eld, and it was widely studied 2, 3, 4, 5, 6, 7] in both contexts. The model has one dimensionless coupling constant, , and it was noticed very early that there seems to be a qualitative diierence in the ground state between the weak coupling regime, well described by perturbation theory 8], in which the electron is spread out, and the strong coupling regime in which the electron appears to be trapped in a phonon hole of its own making. By now it seems doubtful that such a trapping actually occurs 7, 9, 10], but it remains true that the calculation of the ground state energy, E 0 (), is very diierent in the two regimes. The strong coupling theory was studied by Pekar 2] (see also 3, 4, 5])
Impact of Microfinance and Entrepreneurship on Poverty Alleviation: Does National Culture Matter?

Microfinance, national culture, entrepreneurship and poverty alleviation are four concepts which have not always gone together or been worked upon within the same context. In recent years however, we have come across new elements, instruments and ideas which place increasing emphasis on the link among these concepts. The purpose of this paper was to analyze the relationship among national culture dimensions, entrepreneurship, the need of microfinance services, and the impact of this relationship on poverty alleviation. Microfinance is regarded by the World Bank and governments as a powerful tool in combating poverty. Nevertheless, there is still a disagreement among scholars on its impact on poverty alleviation for the poor because not all the poor in the society are eligible for microfinance interventions for some of them lack entrepreneurial skills. Furthermore, even though entrepreneurs in different countries share some universal traits, they may also have other traits that are specific to their own national culture. Based on a methodical literature survey, this study provides a combination of critical argument and scholarly analysis. There is empirical evidence that entrepreneurship attitude is highly influenced by cultural values, and this association is based on the framework of Hofstede’s cultural dimensions hence substantiating the existence of a correlational relationship among national culture, entrepreneurship and microfinance towards poverty alleviation. Keywords: National Culture dimensions, Entrepreneurship, Microfinance, Poverty Alleviation
Statistical feature extraction for cross-language web content quality assessment

Web content quality assessment is a typical static ranking problem. Heuristic content and TFIDF features based statistical systems have proven effective for Web content quality assessment. But they are all language dependent features, which are not suitable for cross-language ranking. In this paper, we fuse a series of language-independent features including hostname features, domain registration features, two-layer hyperlink analysis features and third-party Web service features to assess the Web content quality. The experiments on ECML/PKDD 2010 Discovery Challenge cross-language datasets show that the assessment is effective.
e-Chimera : Rapid In-Situ Mobile Experimentation through Integrated Design , Test , and Deployment

The advent of smartphones and Internet tablets provides unique opportunities for running large-scale, insitu experiments in the wild. However, the steep learning curve of building mobile applications makes it difficult for researchers in most fields to design and deploy cognitive, behavioral, and social experiments on mobile platforms. Inspired by contextual inquiries with domain researchers and a comprehensive literature survey, we present e-Chimera, a visual end-user programming environment for designing and prototyping experiments on mobile devices. The e-Chimera IDE provides a statechart-based, multi-level visual language to create experiments at the workflow, trial, and screen interaction level. The e-Chimera runtime, driven by a Domain-Specific Language (DSL), enables high fidelity, cross-platform application deployment. Overall, e-Chimera integrates design, test, deployment, and analysis of mobile experiments. Through a 12-subject user study, we found e-Chimera effective and easy to use.
Distributed Entropy Minimization Discretizer for Big Data Analysis under Apache Spark

The astonishing rate of data generation on the Internet nowadays has caused that many classical knowledge extraction techniques have become obsolete. Data reduction techniques are required in order to reduce the complexity order held by these techniques. Among reduction techniques, discretization is one of the most important tasks in data mining process, aimed at simplifying and reducing continuous-valued data in large datasets. In spite of the great interest in this reduction mechanism, only a few simple discretization techniques have been implemented in the literature for Big Data. Thereby we propose a distributed implementation of the entropy minimization discretizer proposed by Fayyad and Irani using Apache Spark platform. Our solution goes beyond a simple parallelization, transforming the iterativity yielded by the original proposal in a single-step computation. Experimental results on two large-scale datasets show that our solution is able to improve the classification accuracy as well as boosting the underlying learning process.
On Performance Enhancement of Circuit Simulation Using Multithreaded Techniques

This paper presents the multithreaded programming techniques used in parallelizing SPICE3 circuit simulator. Two approaches in multithread programming are proposed to parallelize SPICE3 simulator program in multi-core SMP systems. We have used OpenMP and Pthreads, two shared memory programming-interface standards, to realize our approaches, in order to redesign the SPICE3 device-loading functions. We have presented case studies using SRAM circuit as our input data, which consists of MOS devices that is modeled by a widely used BSIM3 model. Experimental result exhibits the performance improvement for the multithreaded implementation of SPICE3 circuit simulator.
Distributed Switching Control to Achieve Almost Sure Safety for Leader-Follower Nonholonomic Systems

Leader-follower formation control is a widely used distributed control strategy that needs systems to exchange their information over a wireless radio communication network to attain and maintain formations. These wireless networks are often subject to deep fades, where a severe drop in the quality of the communication link occurs. Such deep fades inevitably inject a great deal of stochastic uncertainties into the system, which significantly impacts the system’s performance and stability, and causes unexpected safety problems in application like smart transportation system. Assuming an exponentially bursty channel that varies as a function of the vehicular states, this paper proposes a distributed switching control scheme under which the local controller is reconfigured in response to the changes of channel state, to assure almost sure safety for a chain of leader follower nonholonomic system. Here almost sure safety means that the likelihood of vehicular states entering a safe region asymptotically goes to one as time goes to infinity. Sufficient conditions are provided for each local vehicle to decide which controller is placed in the feedback loop to assure almost sure safety in the presence of deep fades. The simulation results of a chain of leader follower formation are used to illustrate the findings.
γ-Secretase activity requires the presenilin-dependent trafficking of nicastrin through the Golgi apparatus but not its complex glycosylation

Nicastrin and presenilin are two major components of the γ-secretase complex, which executes the intramembrane proteolysis of type I integral membrane proteins such as the amyloid precursor protein (APP) and Notch. Nicastrin is synthesized in fibroblasts and neurons as an endoglycosidase-H-sensitive glycosylated precursor protein (immature nicastrin) and is then modified by complex glycosylation in the Golgi apparatus and by sialylation in the trans-Golgi network (mature nicastrin). These modifications are not observed with exogenously overexpressed nicastrin. Under normal cell culture conditions, only mature nicastrin is expressed at the cell surface and binds to the presenilin heterodimers. Mature nicastrin has a half-life of more than 24 hours. In the absence of presenilin 1 and 2, nicastrin remains entirely endoglycosidase H sensitive, is retained in the endoplasmic reticulum and is slowly degraded. Single presenilin 1 or presenilin 2 deficiency affects glycosylation of nicastrin to a lesser extent than the combined presenilin deficiencies, suggesting a correlation between either the transport of nicastrin out of the endoplasmic reticulum or the concomitant complex glycosylation of nicastrin, and γ-secretase activity. However, when complex glycosylation of nicastrin was inhibited using mannosidase I inhibitors, γ-secretase cleavage of APP or Notch was not inhibited and the immature nicastrin still associates with presenilin and appears at the cell surface. Complex glycosylation of nicastrin is therefore not needed for γ-secretase activity. Because the trafficking of nicastrin to the Golgi apparatus is dependent on presenilins, our data point to a central role of presenilin in nicastrin maturation/localization, which could help to partially resolve the `spatial paradox'.
L2 Acquisition and Production of the English Rhotic Pharyngeal Gesture

This study is an investigation of L2 speakers’ production of the pharyngeal gesture in the English /ɹ/. Real-time MRI recordings from one L1 French/L2 English and one L1 Greek/L2 English speaker were analyzed and compared with recordings from a native English speaker to examine whether the gestural composition of the rhotic consonant(s) in a speaker’s L1, particularly the presence and location of a pharyngeal gesture, influences their production of English /ɹ/. While the L1 French speaker produced the expected high pharyngeal constriction in their production of the French rhotic, he did not appear to consistently produce an Englishlike low pharyngeal constriction in his production of English /ɹ/. Similarly, the native Greek speaker did not consistently produce a pharyngeal constriction of any kind in either his L1 rhotic (as expected) or in English /ɹ/. These results suggest that the acquisition and production of the pharyngeal gesture in the English rhotic approximant is particularly difficult for learners whose L1 rhotics lack an identical constriction, potentially due to a general difficulty of acquiring pharyngeal gestures that are not in the L1, the similarity of the acoustic consequences of the different components of a rhotic, or L1 transfer into the L2.
Resource-Light Approaches to Computational Morphology Part 1: Monolingual Approaches

This article surveys resource-light monolingual approaches to morphological analysis and tagging. While supervised analyzers and taggers are very accurate, they are extremely expensive to create. Therefore, most of the world languages and dialects have no realistic prospect for morphological tools created in this way. The weakly-supervised approaches aim to minimize time, expertise and/or nancial cost needed for their development. We discuss the algorithms and their performance considering issues such as accuracy, portability, development time and granularity of the output.
A Novel Statistical Approach for Segmentation of Single-Channel Brain MRI Using an Improved EM algorithm

This paper presents a novel statistical method for segmentation of single-channel brain magnetic resonance (MR) image data. The method based on an improved expectation maximization (EM) algorithm proposed in this paper involves three steps. Firstly, after pre-processing the image with the curvature anisotropic diffusion filter, the background (BG) and brain masks of the image are obtained by applying a combination approach of thresholding with morphology. Secondly, the connected threshold region growing technique is employed to get the preliminary results of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) on a brain MRI. Finally, the previous results are served as the priori knowledge for the improved EM algorithm to segment the brain MRI. The performance of the proposed method is compared with that of the popular used fuzzy-C means (FCM) segmentation. Experimental results show our approach is effective, robust and significantly faster than the conventional EM based method.
Electrical Engineering and Computer Science SSL INT : A Tool for Detecting TLS Certificate Validation Vulnerabilities April 2016

Secure Sockets Layer (SSL) and Transport Layer Security (TLS) protocols have become the security backbone of the Web and Internet today. Many systems including mobile and desktop applications are protected by SSL/TLS protocols against network attacks. However, many vulnerabilities caused by incorrect use of SSL/TLS APIs have been uncovered in recent years. Such vulnerabilities, many of which are caused due to poor API design and inexperience of application developers, often lead to confidential data leakage or man-in-the-middle attacks. In this paper, to guarantee code quality and logic correctness of SSL/TLS applications, we design and implement SSLINT, a scalable, automated, static analysis system for detecting incorrect use of SSL/TLS APIs. SSLINT is capable of performing automatic logic verification with high efficiency and good accuracy. To demonstrate it, we apply SSLINT to one of the most popular Linux distributions – Ubuntu. We find 29 previously unknown SSL/TLS vulnerabilities in Ubuntu applications, most of which are also distributed with other Linux distributions.
Recognizing English Grammar Using Predictive Parser

We describe a Context Free Grammar (CFG) for English language and hence we propose a English parser based on the context free grammar. Our approach is very much general to apply in English Sentences and the method is well accepted for parsing a language of a grammar. The proposed parser is a predictive parser and we construct the parse table for recognizing English grammar. Using the parse table we recognize syntactical mistakes of English sentences when there is no entry for a terminal in the parse table. If a natural language can be successfully parsed then grammar checking from this language becomes possible. The proposed scheme is based on Top down parsing method and we have avoided the left recursion of the CFG using the idea of left factoring. KeywordsContext Free Grammar (CFG), Predictive Parser, Parse Table, Top down and Bottom up Parser, Left Recursion.
Nominal time series representation for the clustering problem

In this paper we considered time series dimension reduction for clustering problem. The techniques of reduction of dimension of time series is based on the concept of envelopes, aggregation of the envelopes and extracting essential attributes. Essential attributes were nominalized. The reduced representation of time series is characterized by nominal attributes. For such representation of time series we applied a definition of conditions domination within each pair of clusters. We proposed a hierarchical agglomerative approach to clustering nominal data. There is considered a case of data series clustering problem as an illustrative example.
Online Bandwidth Reduction Using Dynamic Partial Reconfiguration

Online compression of I/O-data streams in Custom Computing Machines will enhance the effective network band-width of computing systems as well as storage bandwidth and capacity. In this paper a self-adaptive dynamic partial reconfigurable architecture for online compression is proposed. The proposed architecture will bring new possibilities in online compression due to its adaptivity to dynamic environments. In this study, network traffic, and input data distribution are considered as two dynamic behaviors. The degree of improvement provided by the architecture depends on data distribution, bandwidth, and available resources. Our analysis shows an improvement of up to 20% in compression ratios in comparison to non-adaptive approaches.