Miracle-dz/UniFAR-FTUs huggingface dataset:
Using personality traits and a spatial ability test to identify talented aspiring designers in User-Centred Design methodologies

User-Centred Design (UCD) methodologies have been increasingly used during the past decade to develop software applications and products that are tailored to the needs of individuals and allow for human computer interactions on emotional and psychological levels. UCD designers and developers need to have special abilities and training to design products that meet the demands of users. This paper presents novel techniques to identify talented aspiring designers in UCD methodologies. Twenty-three undergraduate students, studying at a research-intensive metropolitan Australian university, participated in this study. Participants completed a spatial ability test, answered personality trait questionnaires and performed a design activity. Our results indicate that students who score high in the imagination personality factor and spatial ability tests are talented aspiring UCD designers. The implication of our study is that talented students who can design using UCD methodologies can be identified early in their studies and they can benefit by receiving advanced training. Likewise the less talented students can be given extra tutoring as abilities are not immutable and, interest and persistence is important in achieving expertise.
Formalization and Comparison of MCDC and Object Branch Coverage Criteria

This paper presents formal results derived from the COUVERTURE project, whose goal was to develop tools to support structural coverage analysis of uninstrumented safety-critical software. After briefly introducing the project context and explaining the need for formal foundations, we focus on the relationships between machine branch coverage and the DO-178B Modified Condition/Decision Coverage (MCDC) criterion. A thorough understanding of those relationships is important, since it provides the foundation for knowing where efficient execution trace techniques can be used to demonstrate compliance with the MCDC criterion. We first present several conjectures that were tested using Alloy models, then provide a formally verified characterization of the situations when coverage of object control-flow edges implies MCDC compliance.
IMAGE RETRIEVAL USING COLOR-SIZE MOMENTS AND WAVELET FEATURES 1

The rapid growth of digital imaging techniques and versatility among the images has motivated the development of Content Based Image Retrieval (CBIR). CBIR is the application of computer vision techniques which uses the visual contents to retrieve relevant images from large databases according to user's interests. The visual contents (color, texture, shape etc) serve as the features for the images. Features are measurements of extreme interest analysed from an image. This paper proposes a novel combined Color-Size and texture features for CBIR system. A new type of visual feature named Color-Size feature which integrates the information of both color and size of the image in terms of number of segments is proposed. To implement the system, initially the images are segmented using Watershed segmentation approach. Different images would yield different number of segments that has to be taken into account for the extraction of features. From the segmented image the Color-Size features are extracted using Color-Size Moments. Gabor filter and Haar wavelet are employed to extract texture features. Then the combination of color-size and texture features is formed. The feature extraction process is accomplished for both the query image and images stored in database. Finally, the relevant images are retrieved for the given user's query image.
Financing Innovation in New Small Firms: New Evidence from Canada

This paper investigates the financial characteristics of new small firms. The analysis develops a representative, small-firm financial profile and evaluates the extent to which the proportionate use of different instruments and sources is correlated with industry-level and firm-specific characteristics. Multivariate methods are then used to examine relationships among financial structure, R&D intensity, and innovation. Our results suggest that relationships between knowledge intensity and capital structure are bidirectional. After a range of industry- and firm-level covariates are controlled for, firms that devote a higher percentage of their investment expenditure to R&D also exhibit fewer debt-intensive structures. Conversely, debt-intensive structures also act to constrain investments in R&D. These relationships, however, depend upon the type of debt in the asset mix. It is the share of long-term debt to total assets that is negatively related to investments in knowledge.
Implication of CD38 gene in podocyte epithelial-to-mesenchymal transition and glomerular sclerosis

CD38 is a multifunctional protein involving in a number of signalling pathways. Given that the lack of CD38 is considered as a dedifferentiation marker of lymphocytes and other cells, we hypothesized that CD38 and its signalling pathway may participate in the epithelial‐to‐mesenchymal transition (EMT) process of podocytes and thereby regulates the integrity of glomerular structure and function. Western blot analysis and RT‐PCR demonstrated that renal tissue CD38 expression was lacking in CD38−/− mice or substantially reduced in renal CD38 shRNA‐transfected WT (CD38‐shRNA) mice compared to CD38+/+ littermates. Confocal fluorescent microscopy demonstrated the reduced expression of epithelial markers (P‐Cadherin, ZO‐1 and podocin) and increased expression of mesenchymal markers (FSP‐1, α‐SMA and desmin) in the glomeruli of CD38−/− and CD38‐shRNA mice compared to CD38+/+ mice. Morphological examinations showed profound injury in the glomeruli of CD38−/− or CD38‐shRNA mice compared to CD38+/+ mice. This enhanced glomerular injury in CD38−/− or CD38‐shRNA mice was accompanied by increased albuminuria and proteinuria. DOCA/high salt treatment further decreased the expression of epithelial markers and increased the abundance of mesenchymal markers, which were accompanied by more increased glomerular damage index and mean arterial pressure in CD38−/− and CD38‐shRNA mice than CD38+/+ mice. In vitro studies showed that inhibition of CD38 enhances the EMT in podocytes. In conclusion, our observations reveal that the normal expression of CD38 importantly contributes to the differentiation and function of podocytes and the defect of this gene expression may be a critical mechanism inducing EMT and consequently resulting in glomerular injury and sclerosis.
Spatiotemporal Modulation of Central Neural Pathway Underlying Acupuncture Action: A Systematic Review

Acupuncture, an ancient therapeutic technique, is currently gaining popularity as an important modality of alternative and complementary medicine in the West world. Concurrently, scientific interests in exploring whether acupuncture is therapeutically effective are raised alongside those about the means by which it may operate. Modern neuroimaging techniques such as functional magnetic resonance imaging, positron emission tomography, electroencephalography, and magnetoencephalography provide a means to safely monitor brain activity in humans. In this review, we have summarized evidence derived from the neuroimaging studies and tried to elucidate the neurophysiological correlates of acupuncture. Previous investigations on the neural responses to acupuncture mainly focus on its acute effects and explore the correlation between the specific acupoints and cortical activations only in the spatial domain. However, abundant clinical reports and psychophysical analysis suggest the kinetics of acupuncture is longer acting as a function of time. Consequentially, an accurate interpretation of acupuncture actions depends on how effectively we can characterize the nature of temporal variations underlying neural activities, rather than simply detect the occurrence of such changes. This emerging picture indicates that both designing paradigms and statistical models involved in acupuncture studies should be applied with great care.
Slacken Piercing Point Based Subproblem Algorithm for the LP Relaxation of Crew Rostering

Crew rostering is one of the most important scheduling problems that airlines have to face regularly. The goal is to assign a set of tasks to a group of workers as fairly as possible while following various business rules. Difficulties of the optimization mainly arise from its large scale. In this paper, a modified subproblem based algorithm for the LP relaxations of crew rostering problem is proposed, whose benefit comes from two main ideas. Firstly, it needn’t consider all non-basic variables in any iteration. Secondly, it is beneficial to consider primal and dual problems at the same time. The computational experiments on the real-world problems showed that time savings about 50% over previous universal subproblem based algorithm can be obtained.
How Important Is Secondary School Duration for Postsecondary Education Decisions? Evidence from a Natural Experiment

To enable earlier graduation, most German states have abolished the final year of secondary schooling while leaving the curriculum unchanged. We evaluate how this reform affects postsecondary education decisions using primary data from the state of Saxony-Anhalt. In this state, the reform was implemented in a very short time, providing a natural experiment. The results show heterogeneous effects according to gender. Females delay university enrollment and are more likely to start vocational education. The reform also changes the pattern of university subject choice. These findings can be attributed to an orientation effect and a performance effect inherent in the reform effect.
The Welfare Effects of Farm Household Activity Choices in Post-War Mozambique

This paper analyses the effects of activity choices on farm household income and consumption in a war-affected developing country. The study uses household survey data from Mozambique and controls for the endogeneity of activity choices with instrumental variables. War-time activity choices (such as subsistence farming) are shown to enhance welfare in the post-war period. Market and social exchange induce limited welfare gains. Cotton adoption reduces household welfare, which contradicts previous studies not controlling for endogenous activity choices. The study thus demonstrates how standard predictions of economics may become invalid in post-war economies. Furthermore, the paper identifies pro-poor reconstruction policies.
AUI&GIV: Recommendation with Asymmetric User Influence and Global Importance Value

The user-based collaborative filtering (CF) algorithm is one of the most popular approaches for making recommendation. Despite its success, the traditional user-based CF algorithm suffers one serious problem that it only measures the influence between two users based on their symmetric similarities calculated by their consumption histories. It means that, for a pair of users, the influences on each other are the same, which however may not be true. Intuitively, an expert may have an impact on a novice user but a novice user may not affect an expert at all. Besides, each user may possess a global importance factor that affects his/her influence to the remaining users. To this end, in this paper, we propose an asymmetric user influence model to measure the directed influence between two users and adopt the PageRank algorithm to calculate the global importance value of each user. And then the directed influence values and the global importance values are integrated to deduce the final influence values between two users. Finally, we use the final influence values to improve the performance of the traditional user-based CF algorithm. Extensive experiments have been conducted, the results of which have confirmed that both the asymmetric user influence model and global importance value play key roles in improving recommendation accuracy, and hence the proposed method significantly outperforms the existing recommendation algorithms, in particular the user-based CF algorithm on the datasets of high rating density.
Terms and Document Representation with Generalized Latent Semantic Analysis

Document indexing and representation of term-document relations are very important issues for document clustering and retrieval. In this paper, we present Generalized Latent Semantic Analysis as a framework for computing semantically motivated term and document vectors. Our focus on term vectors is motivated by recent success of co-occurrence based measures of semantic similarity obtained from very large corpora. Our experiments demonstrate that GLSA term vectors efficiently capture semantic relations between terms and outperform related approaches on the synonymy test. We also show that termbased document representation improves performance on the document classification test.
Real-World-Time Simulation of Memory Consolidation in a Large-Scale Cerebellar Model

We report development of a large-scale spiking network model of the cerebellum composed of more than 1 million neurons. The model is implemented on graphics processing units (GPUs), which are dedicated hardware for parallel computing. Using 4 GPUs simultaneously, we achieve realtime simulation, in which computer simulation of cerebellar activity for 1 s completes within 1 s in the real-world time, with temporal resolution of 1 ms. This allows us to carry out a very long-term computer simulation of cerebellar activity in a practical time with millisecond temporal resolution. Using the model, we carry out computer simulation of long-term gain adaptation of optokinetic response (OKR) eye movements for 5 days aimed to study the neural mechanisms of posttraining memory consolidation. The simulation results are consistent with animal experiments and our theory of posttraining memory consolidation. These results suggest that realtime computing provides a useful means to study a very slow neural process such as memory consolidation in the brain.
Identifying seismicity patterns leading flank eruptions at Mt. Etna Volcano during 1981–1996

Seismicity time properties of the Etna Volcano (Italy) are investigated through a systematic pattern recognition analysis. Mean Hypothesis Testing (MHT) has been applied to a long time database of instrumental data recorded from 1981 to 1996 to identify relevant correlation among seismic patterns, main seismogenic volumes and the eight flank eruptions occured in the same period. Time evolution of the test statistic (T‐Ratio), calculated on a temporal window starting 75 days prior to a volcanic eruption and extending 25 days after, reveals that there is a pattern of seismic activity prior to the eruptions that can be used as a diagnostic tool as well as a physical modeling support in eruption forecasting.
The relative predictive ability of earnings and cash flows: Evidence from Shariah compliant companies in India

Purpose - – The purpose of this paper is to examine the relative predictive abilities of current earnings (and its components) and cash flows for next period cash flows in case of Shariah-compliant companies in India. Design/methodology/approach - – The study uses the list of CRISIL NSE Index (CNX) Nifty Shariah Index companies as its sample for a period of 10 years for conducting the analysis. The study utilizes the cash flow prediction models to examine the relative predictive abilities of current earnings (and its components) and cash flows for next period cash flows. Findings - – The study report that contrary to Financial Accounting Standard Board assertion, current cash flows have superior predictive ability of next period cash flows than current aggregate earnings in case of Shariah-compliant companies in India. The results further show that there are no gains from decomposing earnings into accruals and cash flows in predicting future cash flows. There is no increase in explanatory power (measured by adjusted Practical implications - – The empirical findings of the study will enable the Shariah compliant investors to understand the role of current earnings (and its components) and cash flows in predicting next period cash flows in case of Shariah-compliant companies in India. Originality/value - – To the best of author’s knowledge, this is the first study which examines the relative predictive abilities of current earnings (and its components) and cash flows for next period cash flows in case of Shariah-compliant companies in India.
Parsing Fortress syntax

In this paper, we report our experience with parsing the syntax of the Fortress programming language. Fortress is a new programming language designed for scientific and high-performance computing. Features include: implicit parallelism, transactions, and concrete syntax that emulates mathematical notation. Fortress is intended to grow over time to accommodate the changing needs of its users. Parsing the Fortress syntax is nontrivial due to its support for mathematical syntax and growable syntax. Mathematical syntax is highly ambiguous and growable syntax allows a program itself to define how it is parsed. Fortress currently runs entirely on the JVM, which requires internal representation of Fortress as Java classes. We describe our trials to parse the entire Fortress syntax, in the presence of constant changes of the language syntax and its internal representation. and the lessons we learned from the experience.
Foreign Direct Investment and Transformation: Evolution and Impacts in the Polish Economy

The effect of the inflow of foreign direct investment (FDI) can be investigated with the theory of international production offering useful insights into the expansion of firms in foreign countries, which can also be applied to host countries undergoing economic transformation--in this paper's case, Poland. A thorough analysis of changing FDI inflows (and inward stocks) and its various patterns, as well as their impact on the Polish economy, has disclosed certain nuances of evolving FDI contribution and effects on the processes of transformation and, to some extent, on economic development and European Union regional integration. The conclusion is that it was not just the transition of the Polish economy but, rather, a complex and long-term process of systemic transformation that attracted FDI in the 1990s, and to which FDI and foreign-capital companies have made significant contributions. However, the contribution of FDI and transnational corporations in changing the stage of Poland's economic development is insufficient.
Novel serial code concatenation strategies for error floor mitigation of low-density parity-check and turbo product codes

This paper presents a novel multiple serial code concatenation (SCC) strategy to combat the error-floor problem in iterated sparse graph-based error correcting codes such as turbo product-codes (TPC) and low-density parity-check (LDPC) codes. Although SCC has been widely used in the past to reduce the error-floor in iterative decoders, the main stumbling block for its practical application in high-speed communication systems has been the need for long and complex outer codes. Alternative, short outer block codes with interleaving have been shown to provide a good tradeoff between complexity and performance. Nevertheless, their application to next-generation high-speed communication systems is still a major challenge as a result of the careful design of long complex interleavers needed to meet the requirements of these applications. The SCC scheme proposed in this work is based on the use of short outer block codes. Departing from techniques used in previous proposals, the long outer code and interleaver are replaced by a simple block code combined with a novel encoding/decoding strategy. This allows the proposed SCC to provide a better tradeoff between performance and complexity than previous techniques. Several application examples showing the benefits of the proposed SCC are described. Particularly, a new coding scheme suitable for high-speed optical communication is introduced.
Networked Consensus Agents Dynamics through Matrix Eigenvalue

The collective behavior system depends strongly on the efficiency of communication paths, in other words, network topology. Network connectivity affects the properties of networked agents. Synchronous behavior is also affected by the network structure. A consensus problem is also related to the problem of synchronization. A consensus algorithm is an interaction rule that specifies the information exchange between an agent and all of its neighbors on the network. A class of local control laws is investigated for a collection of agents that result in global order their motion in convergence of their movement to a common. In large groups of agents the information sharing should be local in some sense, due to energy limitation, reliability, and other constraints. However, local information exchange limits the speed of convergence of such protocols. A consensus protocol is an iteractive method that provides the group with a common coordination variable. In this paper, we describe the occurrence of flocking behavior and the underlying connection between agents. The occurrence of flocking behavior in the synchronization of networked agents is directly associated with the connectivity properties of the interconnection network. Each node of the network represents a dynamical system. Individual systems are coupled according to the network topology. It is possible to think about the network topology through local control action by exploiting the graph theoretic properties of the agent networks. We consider the network by the Laplacian matrix eigenvalue viewpoint.
Activated Carbon, Carbon Nanofiber and Carbon Nanotube Supported Molybdenum Carbide Catalysts for the Hydrodeoxygenation of Guaiacol

Molybdenum carbide was supported on three types of carbon support—activated carbon; multi-walled carbon nanotubes; and carbon nanofibers—using ammonium molybdate and molybdic acid as Mo precursors. The use of activated carbon as support afforded an X-ray amorphous Mo phase, whereas crystalline molybdenum carbide phases were obtained on carbon nanofibers and, in some cases, on carbon nanotubes. When the resulting catalysts were tested in the hydrodeoxygenation (HDO) of guaiacol in dodecane, catechol and phenol were obtained as the main products, although in some instances significant amounts of cyclohexane were produced. The observation of catechol in all reaction mixtures suggests that guaiacol was converted into phenol via sequential demethylation and HDO, although the simultaneous occurrence of a direct demethoxylation pathway cannot be discounted. Catalysts based on carbon nanofibers generally afforded the highest yields of phenol; notably, the only crystalline phase detected in these samples was Mo2C or Mo2C-ζ, suggesting that crystalline Mo2C is particularly selective to phenol. At 350 °C, carbon nanofiber supported Mo2C afforded near quantitative guaiacol conversion, the selectivity to phenol approaching 50%. When guaiacol HDO was performed in the presence of acetic acid and furfural, guaiacol conversion decreased, although the selectivity to both catechol and phenol was increased.
A Rule-Based Relation Extraction System using DBpedia and Syntactic Parsing

In this paper, we present a rule-based relation extraction approach which uses DBpedia and linguistic information provided by the syntactic parser Fips. Our goal is twofold: (i) the morpho-syntactic patterns are defined using the syntactic parser Fips to identify relations between named entities (ii) the RDF triples extracted from DBpedia are used to improve RE task by creating gazetteer relations.