Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of age- and disease-related alterations in circulating miRNAs in a mouse model of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized clinically by the progressive decline of memory and cognition. Histopathologically, two main hallmarks have been identified in AD: amyloid-β peptide extracellular neuritic plaques and neurofibrillary tangles formed by posttranslational modified tau protein. A definitive diagnosis can only be achieved after the post mortem verification of the histological mentioned alterations. Therefore, the development of biomarkers that allow an early diagnosis and/or predict disease progression is imperative. The prospect of a blood-based biomarker is possible with the finding of circulating microRNAs (miRNAs), a class of small non-coding RNAs of 22–25 nucleotides length that regulate mRNA translation rate. miRNAs travel through blood and recent studies performed in potential AD cases suggest the possibility of finding pathology-associated differences in circulating miRNA levels that may serve to assist in early diagnosis of the disease. However, these studies analyzed samples at a single time-point, limiting the use of miRNAs as biomarkers in AD progression. In this study we evaluated miRNA levels in plasma samples at different time-points of the evolution of an AD-like pathology in a transgenic mouse model of the disease (3xTg-AD). We performed multiplex qRT-PCR and compared the plasmatic levels of 84 miRNAs previously associated to central nervous system development and disease. No significant differences were detected between WT and transgenic young mice. However, age-related significant changes in miRNA abundance were observed for both WT and transgenic mice, and some of these were specific for the 3xTg-AD. In agreement, variations in the levels of particular miRNAs were identified between WT and transgenic old mice thus suggesting that the age-dependent evolution of the AD-like pathology, rather than the presence and expression of the transgenes, modifies the circulating miRNA levels in the 3xTg-AD mice.
Activity Recognition on 3 D Accelerometer Data ( Technical Report )

Physical activity is an important factor that is considered for the prevention of diseases like diabetes or hypertension and for rehabilitation. For this purpose, patients are required to fulfill a certain, regular pensum of activity which follow a training schedule that is integrated into daily life which cannot be supervised. In order to obtain reliable statements about achieved physical activity within a certain time period, accelerometers can act as tools that provide results which are superior to questionnaires filled by the patients. State-of-the-art activity recognition systems already provide good results, but the accuracy of classification algorithms including data preprocessing often depend on the position of the sensors and the data. This paper proposes an activity recognition system designed for accelerometers positioned at the ankle, which, in general, yields accurate and representative acceleration time-series data. An extensive evaluation on real-world datasets shows that, performing an additional reclassification step, excellent classification results outperforming recent work can be achieved.
A local wavelet transform implementation versus an optimal row-column algorithm for the 2D multilevel decomposition

A new method for the implementation of the binary-tree decomposition of the convolution-based wavelet transform, called the local wavelet transform (LWT) has been recently proposed in the literature. While it produces exactly the same results as the classical row-column implementation of the transform, it has many implementation benefits. This fact is shown experimentally for the first time for a general-purpose processor-based architecture, by comparing our C implementation of the LWT with an optimal C implementation of the lifting-scheme row-column algorithm. The comparisons are made for the forward multilevel binary-tree decomposition using the 9/7 filter pair, in the typical Intel Pentium processor family.
A tentative 4- isomeric state in Sr-98

In the frame of our systematic investigations of nuclear structure properties of neutron-rich A ≃ 100 nuclei at the isotope separator ISOLDE at CERN, an isomeric level at 1619 keV with the surprisingly long t 1 / 2 = 85 ns was observed in 100 Sr [1, 2]. In analogy to a K π =4 rotational band observed in the isotone 102 Zr [3], the half-life could be interpreted as a ∆K = 4 hindered decay from the two quasi-neutron conﬁguration ( ν [411]3/2 ⊗ ν [532]5/2)4 − . These conﬁgurations are supported by quantum Monte-Carlo deformed shell calculations, further indicating a strong weakening of the pairing residual interaction [4]. This initiated a reexamination of γ - γ -t coincidence data on the β -decay of 98 Rb collected at the former OSTIS separator at the ILL (Grenoble) and during the experiment on 100 Rb decay. As a ﬁrst result, the halﬂife of the 0 +2 level of 98 Sr at 215 kev could be remeasured with higher precision 6]. intense transitions 140, and 1693 the 140-1693 keV scheme of 98
Visual Tracking via Particle Filtering on the Affine Group

We present a particle filtering algorithm for visual tracking, in which the state equations for the object motion evolve on the two-dimensional affine group. We first formulate, in a coordinate-invariant and geometrically meaningful way, particle filtering on the affine group that allows for combined state—covariance estimation. Measurement likelihoods are also calculated from the image covariance descriptors using incremental principal geodesic analysis, a generalization of principal component analysis to curved spaces. Comparative visual tracking studies demonstrate the increased robustness of our tracking algorithm.
Prevalence of traditional cardiovascular risk factors among staff of Ladoke Akintola University of Technology, Ogbomoso, Nigeria.

AIM The aim was to describe the frequency of occurrence of traditional cardiovascular (CV) risk factors among selected university workers in Ladoke Akintola University of Technology (LAUTECH) Nigeria. MATERIALS AND METHODS A cross-sectional study of 206 staff of LAUTECH, Ogbomoso, Nigeria had an assessment for nine traditional CV risk factors. Demographic and clinical parameters were taken. Blood sample was taken to determine the random blood sugar and lipid profile. 12-lead resting electrocardiography (ECG) was done for all participants. Statistical analysis was performed with the aid of Statistical Package for Social Sciences (SPSS) version 17.0 (Chicago Ill., USA) Results: The study population included 96 males (46.6%) and 110 females. The mean age was 45.3 ± 7.9 years (range 27-73 years). The prevalence of CV risk factors were as follows: Hypertension 84 (40.8%), visceral obesity 92 (44.7%), generalized obesity 79 (38.3%), low high density lipoprotein 113 (54.9%), impaired blood glucose 16 (7.8%), diabetes mellitus 3 (1.5%), hypercholesterolemia 102 (49.5%), left ventricular hypertrophy-ECG 24 (11.7%), elevated low density lipoprotein-cholesterol 99 (48.1%). About - (72.3%) had two or more CV risk factors clustered together. Females had a higher prevalence of CV risk factors and its clusters than their male counterparts. Of those diagnosed with hypertension in this study, more than half had never been told they were hypertensive 48 (57.1%). CONCLUSION This study suggests a very high prevalence of CV risk factors among University Staff in LAUTECH, Ogbomoso, Nigeria. Clustering of CV risk factors is more prevalent among women. Appropriate preventive strategy in terms of education and modification of risk factors are important to reduce the burden of CV diseases among this population.
Adapting Interaction Environments to Diverse Users through Online Action Set Selection

Interactive interfaces are a common feature of many systems ranging from field robotics to video games. In most applications, these interfaces must be used by a heterogeneous set of users, with substantial variety in effectiveness with the same interface when configured differently. We address the issue of personalizing such an interface, adapting parameters to present the user with an environment that is optimal with respect to their individual traits - enabling that particular user to achieve their personal optimum. We introduce a new class of problem in interface personalization where the task of the adaptive interface is to choose the subset of actions of the full interface to present to the user. In formalizing this problem, we model the user as a Markov decision process (MDP), wherein the transition dynamics within a task depends on the type (e.g., skill or dexterity) of the user, where the type parametrizes the MDP. The action set of the MDP is divided into disjoint set of actions, with different action-sets optimal for different type (transition dynamics). The task of the adaptive interface is then to choose the right action-set. Given this formalization, we present experiments with simulated and human users in a video game domain to show that (a) action set selection is an interesting class of problems (b) adaptively choosing the right action set improves performance over sticking to a fixed action set and (c) immediately applicable approaches such as bandits can be improved upon.
MMCI at the TREC 2010 Web Track

Term proximity scoring models incorporate distance information of query term occurrences and are an established means in information retrieval to improve retrieval quality. The integration of such proximity scoring models into efficient query processing, however, has not been equally well studied. Existing methods make use of precomputed lists of documents where tuples of terms, usually pairs, occur together, usually incurring a huge index size compared to term-only indexes. This paper uses a joint framework for trading off index size and result quality. The framework provides optimization techniques for tuning precomputed indexes towards either maximal result quality or maximal query processing performance under controlled result quality, given an upper bound for the index size.
A Systematic Optimized Comparison Algorithm for Fast LDPC Decoding

This paper proposes a novel systematic optimization algorithm for comparison operations required by a check node unit (CNU) in LDPC decoding, given any input number Nin. The algorithm can automatically synthesize an optimized fast comparison operations that guarantees a shortest comparison delay time of [log2 (Nm-1)]Tcmp and a minimized total number of two-input comparators, where Tcmp is the delay time of a comparator. High speed is achieved by adopting parallel divide-and-conquer comparison operations, while the required comparators are minimized by developing a novel set construction algorithm that maximizes shareable comparison operations. The designed CNU is favourable to the existing CNU designs which are non-systematically designed with either longer critical path delays or higher comparator counts than the proposed designs. The proposed design is particularly good for long code length cases, when it is impractical to do customized optimized designs by hand, due to high design complexity.
Explicit use-case representation in object-oriented programming languages

Use-cases are considered an integral part of most contemporary development processes since they describe a software system's expected behavior from the perspective of its prospective users. However, the presence of and traceability to use-cases is increasingly lost in later more code-centric development activities. Use-cases, being well-encapsulated at the level of requirements descriptions, eventually lead to crosscutting concerns in system design and source code. Tracing which parts of the system contribute to which use-cases is therefore hard and so limits understandability. In this paper, we propose an approach to making use-cases first-class entities in both the programming language and the runtime environment. Having use-cases present in the code and the running system will allow developers, maintainers, and operators to easily associate their units of work with what matters to the users. We suggest the combination of use-cases, acceptance tests, and dynamic analysis to automatically associate source code with use-cases. We present UseCasePy, an implementation of our approach to use-case-centered development in Python, and its application to the Django Web framework.
An automated test oracle for XML processing programs

XML processing programs play an important role in the achievement of XML data querying, manipulation, and construction operations to compose XML data structures for very diverse purposes regarding information representation, storing and exchange on XML-based systems. Testing of XML processing programs is a challenging task since the test input and output data involved in the test executions may be complex and large in volume, which makes it difficult to determine the correctness of the execution results. However, existing approaches on XML-based testing pay scarce attention to the specification and automation of so-called test oracles in charge of judging the execution results from XML processing programs. This paper deals with the definition of an automated test oracle for XML processing programs which operates with differentiated levels of specification. The oracle automation is achieved by transforming these specification levels into program code, and the resulting oracle implementation is evaluated through an experimental study that reveals promising results.
Semi-automatic construction of topic ontology

In this paper, we review two techniques for topic discovery in collections of text documents (Latent Semantic Indexing and K-Means clustering) and present how we integrated them into a system for semiautomatic topic ontology construction. The system offers supports to the user during the construction process by suggesting topics and analysing them in real time.
Performance Prediction of Parallel Computation of Streaming Applications on FPGA Platform

This paper analyzes possible performance improvement of streaming applications by the parallel computation platform of FPGAs. Software developers still are not familiar with the hardware implementation details of applications and will benefit from this analysis. First the available logic and memory resources of modern FPGAs like Xilinx’s Virtex-5 and Virtex-6 devices are explored to determine how many parallel processors can be configured with the available logic resources and how many parallel processors’ speed can be sustained by simultaneous data access from the on-chip memory. A portion of the on-chip memory is first set aside for pre-fetching of reconfiguration bits for dynamic reconfiguration of FPGA. The rest of the on- chip memory is used for data memory requirements of the concurrent processors. Based on input data rate and required output throughput of data, a number of on-chip cache memory locations and their sizes are determined. Finally a quantitative analysis of possible performance gain of streaming applications by FPGA implementation is compared to that of sequential implementations by a 2.5 GHz dual-core Intel microprocessor.
MARKET POTENTIAL AND SPATIAL AUTOCORRELATION IN THE EUROPEAN REGIONS

The concept of market potential developed by Harris (1954) has several shortcomings but it has proved its practical utility even when compared with more sophisticated versions derived from the wage equation of the New Economic Geography. We stress the ability of this variable to summarize regional markets accessibility and their spatial distribution. We specially highlight a feature of the market potential/market access concept in its foreign or external form (without computing own region�s market potential). Namely, External Market Potential is a non-standardized inverse distance spatial lag of the regional internal markets. Considered together, internal and external market potential, a variable of Harris�s Market Potential is able to capture the core-periphery pattern of economic activity and per capita Gross Value Added in the European regions. This long-distance spatial dependence is different from the short-distance spatial dependence emphasized by Spatial Econometrics, with its standardized spatial weights for a reduced number of neighbours. But capturing these spatial patterns in a regression with a variable of Market Potential comes at a cost of spatial autocorrelation. We show how the Spatial Econometrics procedures allow a correction of the spatial autocorrelation keeping the interpretation of Market Potential in terms of the accessibility to the markets and as an indicator of peripherality. So, both types of spatial dependences should be considered together.
Overview: Weblog mining, privacy issues and application of Web Log mining

In this decade there is a nonlinear growth in the data available on the World Wide Web, with this growth there arises a need for finding and analyzing useful data available on the web. The behavior of webpage and how the users use the web can be found in the weblog. The process of extracting knowledge from weblog is called Web Log mining. This extracted knowledge can be used to enhance the quality of information being shared on the web. Web log are generally noisy and ambiguous, so data preprocessing is an very important step in Data mining. This paper gives overview on weblog mining using decision tree, privacy issues and a glimpse of various applications of web log mining.
Monte Carlo Study of Ambipolar Transport and Quantum Effects in Carbon Nanotube Transistors

In this paper, we investigate the device operation of CNFETs using Monte Carlo simulation. Two types of contacts (ohmic and Schottky) are considered and the effect of ambipolar transport with Schottky barriers is analysed. We also discuss the actual influence of quantum effects on the basis of Wigner simulation results. The output and high-frequency characteristics of different structures are presented and discussed.
An Analytical Framework and Its Applications for Studying Brick Storage Reliability

The reliability of a large-scale storage system is influenced by a complex set of inter-dependent factors. This paper presents a comprehensive and extensible analytical framework that offers quantitative answers to many design tradeoffs. We apply the framework to a number of important design strategies that a designer and/or administrator must face in reality, including topology-aware replica placement, proactive replication that uses small background network bandwidth and unused disk space to create additional copies. We also quantify the impact of slow (but potentially more accurate) failure detection and lazy replacement of failed disks. We use detailed simulation to verify and refine our analytical model. These results demonstrate the versatility of the framework and serve as a solid step towards more quantitative studies of fundamental system tradeoffs between reliability, performance, and cost in large-scale distributed storage systems.
Now We Stronger than Ever: African-American English Syntax in Twitter

African American English (AAE) is a well-established dialect that exhibits a distinctive syntax, including constructions like habitual be . Using data mined from the social media service Twitter, the proposed senior thesis project intends to study the demographic distribution of a sub-set of AAE syntactic constructions. This study expands on previous sociolinguistic Twitter work (Eisenstein et al., 2011) by adding part-of-speech tags to the data, thus enabling detection of short-range syntactic features. Through an analysis of ethnic and gender data associated with AAE tweets, this project will provide a more accurate description of the dialect’s speakers and distribution.
Enhanced Learning ( RecSysTEL 2010 ) Exploring user-based recommender results in large learning object repositories : the case of MERLOT

Collaborative filtering (CF) techniques have proved to be effective in their application to e-commerce and other application domains. However, their applicability to the recommendation of learning resources deserve separate attention as seeking learning resources can be hypothesized to be substantially different from selecting information resources or products for purchase. To date there are only a few scattered studies reporting on the application of well known user-based CF algorithms to learning object repositories. This paper reports an empirical study carried out by using MERLOT data and existing user-based CF algorithms. The aim of this preliminary study was that of finding evidence on accuracy measures of existing CF algorithms, and the relation of the items recommended with other elements of the repository. The results can be used as a starting point for future studies that account for the specific context of learning object repositories and the different aspects of preference in learning resource selection.
Toward theory-based measures of conflict management

The theory of the managerial grid, a model of interrelations among styles of management, was used as the criterion for validating the two best-known self-report measures of conflict management styles. We re-analyzed six studies that used those measures and found that both appeared to be moderately valid. However, the measures failed to reflect the underlying theory in a few respects, which suggested specific areas for improving them.
Optimization of SVD over Graphic Processor

Many of the engineering applications employ linear algebra to furnish the analysis. Image Processing deals with Eigen values/vectors, Machine Design requires principal component analysis of stress, Statistics and Data compression requires minimization of dimensionality in data. Singular Value Decomposition serves as the answer to all these varied needs. This method alone serves many computational & analytical purposes. Although the computation of SVD of a matrix is bulky, the process involves a sequence of vector operations. This makes it a good candidate for parallelization of over Graphic Processors. This paper proposes parallelization of SVD modules in LAPACK over GPGPU using OpenCL. OpenCL is crucial for making the implementation platform independent. Narayanan[1] too considers parallelization of SVD over CUDA using CUBLAS. This work proposes a scheme which is platform independent, and focuses on routines beyond BLAS.
STRINGS AND BRANES IN NON-ABELIAN GAUGE THEORY

It is an old speculation that SU(N) gauge theory can alternatively be formulated as a string theory. Recently this subject has been revived, in the wake of the discovery of D-branes. In particular, it has been argued that at least some conformally invariant cousins of the theory have such a string representation. This is a pedagogical introduction to these developments for nonstring theorists. Some of the existing arguments are simplified.
Individual Development Accounts and Post-Secondary Education: Evidence from a Randomized Experiment

This paper presents evidence from a randomized field experiment testing the impact of a 3-year matched savings program on educational outcomes 10 years later. We examine the effect of an Individual Development Account (IDA) program on educational enrollment, degree completion, and increased education level. The IDA program, which ran from 1998 to 2003 in Tulsa, Oklahoma, provided low-income households with financial education and matching funds for qualified savings withdrawals, including a 1:1 match for educational uses. We find a significant impact on education enrollment and positive, but non-significant impacts on degree completion and increase in level of education. We also examine the interaction between gender and treatment assignment and find that the IDA had a strong positive effect on increased educational attainment for males, but not for females.