Miracle-dz/UniFAR-FTUs huggingface dataset:
Deriving Topics in Twitter by Exploiting Tweet Interactions

Twitter as a big data social network becomes one of the most important sources for capturing the up-to-date events happening in the world. Topic derivation from Twitter is important for various applications such as situation awareness, market analysis, content filtering, and recommendations. However, tweets are short messages, which makes topic derivation challenging. Current methods employ various semantic features of tweet content but mostly overlook the interactions among tweets. In this paper, we propose a novel topic derivation method that takes into account the interactions among tweets, defined as the reciprocal activities related to people who send the tweets, as well as actions and tweet contents. In particular, topics are derived by performing a two-step matrix factorization jointly over the interactions and semantic features of the tweets. We have conducted a number of experiments on tweets collected over a period of time, showing that the proposed method consistently outperforms other advanced topic derivation methods in the literature. Our experiments also reveal that the interactions among tweets do significantly relieve the sparsity problem caused by the short-text nature of Twitter.
Which, Why, and for How Long Do IPOs Underperform?

Based on a sample of 7,378 firms going public in the 1975-2005 period, we document a significant underperformance of IPO firms over the first year after going public, while there is virtually no underperformance thereafter. Moreover, by decomposing the Carhart-alpha we find that IPO underperformance, where present, is mainly due to fundamental differences in firm characteristics (e.g., market-to-book ratio, leverage, and R&D expenditures scaled by sales) between IPO companies and more seasoned, non-issuing firms. In fact, our results indicate that IPO firms neither perform materially better nor worse than mature companies with similar firm characteristics. Finally, we show that IPO underperformance is partially predictable. IPOs associated with overly optimistic growth prospects (and correspondingly high valuation levels) and IPOs going public during hot issue periods perform substantially worse than other IPOs.
Material Considerations in Architectural Design: A Study of the Aspects Identified by Architects for Selecting Materials

Material selection in architecture is not only about choosing the strongest, cheapest, or most obvious materials available. Architects also choose warm, formal, functional, or local materials for buildings. And the material options are not limited by only these considerations. The material selection process is a complex process that is influenced and determined by numerous preconditions, decisions and considerations. The current material selection tools, however, focus mainly on the technical aspects of materials. In order to make well-considered and justifiable material choices, architects have a need for information on the whole spectrum of aspects considered during the design and selection process. Earlier work presented a framework, based on a literature study and the analysis of in-depth interviews, in which the different attributes of materials that contribute to a design project were identified and organized. To refine this framework and make it available for architects during the material selection process, a group of architects was selected and assembled into a focus group. This study presents how the focus group identified, classified and commented on the considerations that are made by architects while selecting materials for a project. The evaluation of the collected data, and the discussion within the group, permitted the formulation of comments and resulted in a revised framework of material considerations, useful during the design and selection process of a material. Material properties (1), Experience (2), Manufacturing process (3), and Context (4) were identified as the different elements that are related to the material selection process. The four groups are presented here in detail.
Five Questions on Complexity

I have been interested by all forms of complexity and self-organization since my childhood. I was always a keen observer of nature, being fascinated by complex phenomena such as ants walking apparently randomly across a branch, the cracks that would appear in drying mud, or the frost crystals that would form on grass during winter nights. As an adolescent, one of my hobbies was keeping aquariums, in which I would try to build a miniature ecosystem complete with soil, plants, invertebrates, and fish. The fish would still need to get food from time to time, and I still had to clean the filter that would collect the dirt they produced, but ideally I would have liked to create a system that is completely autonomous, and is able to sustain itself even in the absence of a caretaker. That would have required more plant life to sustain the food chain, and especially less fish to produce waste products, so it would have made the aquarium less interesting to look at. Therefore, I did compromise in practice. But in my imagination, I was fascinated by what I called “a little world on its own”. In my present scientific vocabulary, I would define this idea as a system that is complex and self-organizing to such a degree that it could be viewed almost as a separate, autonomous universe. (Later I discovered a similar idea in the science fiction stories of Stanislaw Lem, a Polish author influenced by cybernetics.) My fascination for rocks, plants, animals and other phenomena of nature also found an outlet in my early inquiry into the theory of evolution. Like most children nowadays, I had been exposed from an early age to pictures and stories about dinosaurs. The difference, perhaps, is that my grandfather who had collected or drawn these pictures for me was rather scientifically minded, although he was just a primary school teacher. He taught me not only their Latin names, such as Brontosaurus, Triceratops and Tyrannosaurus Rex, but also about the periods in which they lived, and the kinds of creatures that preceded and followed them in the course of natural history. So, from an age of eight or so, I was well aware that life on Earth had evolved, and that plants and animals looked very different in different time periods. As I became a little older, I started reading introductory books on biology, which explained the mechanism of natural selection behind this evolution. This idea became one of the two fundamental principles on which I have based my scientific worldview. As an adolescent, this mechanism seemed so obvious to me that I was quick to generalize it to other domains, noting that for example ideas and societies also evolved through variation and selection. I called this “the generalized principle of natural selection”. Much later, while working on my PhD, I came into contact with other scientists (in particular the great Donald T. Campbell and his disciples Gary Cziko and Mark Bickhard) who had developed a similar philosophy, which they called “selectionism” or “universal selection theory”. Its basic assumption is that all complex
PENGARUH GAYA HIDUP DAN MOTIVASI BELAJAR TERHADAP PRESTASI BELAJAR MATEMATIKA

Penelitian ini bertujuan untuk menemukan dan menganalisis secara empiris pengaruh gaya hidup dan motivasi belajar terhadap prestasi belajar matematika siswa Sampel dipilih secara random sebanyak 130 siswa. Analisis dilakukan dengan metode regresi. Hasil penelitian menunjukkan ada pengaruh pada setiap variable. Ditunjukkan pada setiap kenaikan satu unit gaya hidup akan diikuti dengan kenaikan prestasi belajar matematika sebesar 0.137. Setiap kenaikan satu unit motivasi akan diikuti dengan kenaikan Prestasi Belajar Matematika sebesar 0.906. Setiap kenaikan satu unit gaya hidup dan sekaligus dengan kenaikan satu unit motivasi akan diikuti dengan kenaikan Prestasi Belajar Matematika sebesar 1.043. Secara bersama sama variabel gaya hidup dan variabel motivasi belajar dapat menentukan variabel hasil belajar sebesar 91. 6 persen. Hal ini terdiri dari sumbangan variabel gaya hidup sebesar 6.32 persen, dan dari variabel motivasi belajar sebesar 85,22 persen. Atau tingkat efektifitas sumbangan menunjukkan bahwa ternyata gaya hidup hanya 6.9 persen dibandingkan dengan variabel motivasi belajar yang menyumbang sebesar 93,1 persen. Kata kunci: Gaya Hidup, Motivasi Belajar, Prestasi Belajar Matematika.
Retrieving attributes using web tables

In this paper we propose an attribute retrieval approach which extracts and ranks attributes from Web tables. We combine simple heuristics to filter out improbable attributes and we rank attributes based on frequencies and a table match score. Ranking is reinforced with external evidence from Web search, DBPedia and Wikipedia. Our approach can be applied to whatever instance (e.g. Canada) to retrieve its attributes (capital, GDP). It is shown it has a much higher recall than DBPedia and Wikipedia and that it works better than lexico-syntactic rules for the same purpose.
Adapting a State-of-the-art Anaphora Resolution System for Resource-poor Language

In this paper we present our work on adapting a state-of-the-art anaphora resolution system for a resource poor language, namely Bengali. Performance of any anaphoric resolver greatly depends on the quality of a high accurate mention detector. We develop a number of models for mention detection based on heuristics and machine learning. Our experiments show that, a language-dependent system can attain reasonably good performance when re-trained on a new language with a proper subset of features. The system yields the MUC recall, precision and F-measure values of 57.80%, 79.00% and 66.70%, respectively. Our experiments with other available scorers show the F-measure values of 59.47%, 49.83%, 31.81% and 70.82% for BCUB, CEAFM, CEAFE and BLANC, respectively.
Dissecting components of population‐level variation in seed production and the evolution of masting behavior

Koenig, W. D. , Kelly, D. , Sork, V. L. , Duncan, R. P., Elkinton, J. S. , Peltonen, M. S. and Westfall, R. D. 2003. Dissecting components of population-level variation in seed production and the evolution of masting behavior. – Oikos 102: 581–591. Mast-fruiting or masting behavior is the cumulative result of the reproductive patterns of individuals within a population and thus involves components of individual variability, between-individual synchrony, and endogenous cycles of temporal autocorrelation. Extending prior work by Herrera, we explore the interrelationships of these components using data on individual seed production in 59 populations of plants from 24 species spanning a large range of annual variability, from species exhibiting strong masting to others with little annual variability in seed production. Estimates of population and individual variability were not biased by sample size or average overall seed production when based on untransformed seed production values, but these values declined as log-transformed seed production increased. Population variability was more strongly correlated with individual variability (r= 0.86) than individual synchrony (r=0.73). These latter two components were also significantly correlated (r=0.45), but randomizations confirm that they need not covary closely. Thus, selection can act separately on inter-annual variability and between-individual synchrony. We illustrate the potential for such fine-tuned selection on seed production patterns by discussing several examples and by demonstrating significant differences in components of population-level variation in seed production among species related to their life-history.
Developing a Tool to Support Communication of Parental Concerns When a Child is in Hospital

The involvement of parents in their child’s hospital care has been strongly advocated in paediatric healthcare policy and practice. However, incorporating parental worries about their child’s condition into clinical care can be difficult for both parents and healthcare professionals. Through our “Listening To You” quality improvement project we developed and piloted an innovative approach to listening, incorporating and responding to parental concerns regarding their child’s condition when in hospital. Here we describe the phases of work undertaken to develop our “Listening To You” communications bundle, including a survey, literature review and consultation with parents and staff, before findings from the project evaluation are presented and discussed.
Generalising Tree Traversals to DAGs: Exploiting Sharing without the Pain

We present a recursion scheme based on attribute grammars that can be transparently applied to trees and acyclic graphs. Our recursion scheme allows the programmer to implement a tree traversal and then apply it to compact graph representations of trees instead. The resulting graph traversals avoid recomputation of intermediate results for shared nodes -- even if intermediate results are used in different contexts. Consequently, this approach leads to asymptotic speedup proportional to the compression provided by the graph representation. In general, however, this sharing of intermediate results is not sound. Therefore, we complement our implementation of the recursion scheme with a number of correspondence theorems that ensure soundness for various classes of traversals. We illustrate the practical applicability of the implementation as well as the complementing theory with a number of examples.
Interpolation of Novel Object Views from Sample Views

In this article we address the problem of threedimensional object recognition from two-dimensional views. We use a viewer-centered model of object representation and interpolate novel views from stored sample views. The sample views are represented by graphs which are labeled with Gabor wavelet responses as local descriptors of object points. The positions of the object points in a novel view are linear combinations of the corresponding point positions in the sample views, and the novel feature vectors are linear combinations of the Gabor responses in the sample views. From such an interpolated graph we reconstruct the novel view and analyse its quality for different poses of the novel view in relation to the sample views. Within the covered range of about 30◦ tilt and 40◦ pan viewing angle between the sample views we obtain good interpolation qualities. This leads to a number of about 36 views which is sufficient to represent the upper viewing hemisphere of an arbitrary object. Our results are consistent with current findings of biological and psychological research. In addition, the idea of the proposed algorithm is suitable to be applied in data compression.
Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks

Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript.
Probabilistic Graph Models for Debugging Software

Of all software development activities, debugging—locating the defective source code statements that cause a failure—can be by far the most time-consuming. We employ probabilistic modeling to support programmers in finding defective code. Most defects are identifiable in control flow graphs of software traces. A trace is represented by a sequence of code positions (line numbers in source filenames) that are executed when the software runs. The control flow graph represents the finite state machine of the program, in which states depict code positions and arcs indicate valid follow up code positions. In this work, we extend this definition towards an n-gram control flow graph, where a state represents a fragment of subsequent code positions, also referred to as an n-gram of code positions. We devise a probabilistic model for such graphs in order to infer code positions in which anomalous program behavior can be observed. This model is evaluated on real world data obtained from the open source AspectJ project and compared to the well known multinomial and multi-variate Bernoulli model [1].
Market-Based QoS Control for Voluntary Services

With the development of services computing technology, more and more voluntary services have been available on the Internet. When using voluntary services, users tend to obtain higher QoS (e.g., get more computational resources to improve throughput of the services) than they actually need because there is no cost. To control QoS of the voluntary services appropriately, it is necessary to design resource allocation mechanism using utilities on both service users and providers. Therefore, we have proposed market-oriented resource allocation where users and providers exchange system resources and QoS based on their utilities. In our proposed approach, service users obtain more utilities if higher QoS is allocated according to their preferences in using the services, while service providers get more utilities if their services are more effectively used by their preferred users. In order to validate the proposed method, we have compared market-based approach with demand-based approach by simulation. The simulation results show that our approach motivated users to give true demands more than demand-based approach.
Novel-fuzzy-model based modeling and control of nonlinear chaotic systems with uncertainty

Chaos is observed in many practical applications in engineering, biology and economics, which is an interdisciplinary research topic and received great attention from various kinds of fields. Chaos studies the behavior of dynamical systems that are highly sensitive to initial conditions. Therefore, a practical tool for mathematical modeling is essential. Ge and Li provide a simple fuzzy model to extend the classical Takagi-Sugeno fuzzy model and try to re-annotate the possibility of Fuzzy logic concept in the end of 2011. This novel model brings the idea of modeling each equation and has been cited by several research and application articles and reports over 20 times covered with chemistry simulation, time delay model and so on. In this study, Sprott series system with uncertainties is illustrated in numerical simulations to show the effectiveness and feasibility of the proposed fuzzy model and the corresponding control scheme.
The role of implicit fear in the process of mental effort mobilization

The purpose of the present thesis was to extend knowledge of the impact of implicit affect in the process of effort mobilization. The implicit-affect-primes-effort model (Gendolla, 2012, 2015) makes specific predictions and gives explanations for the influence of implicit affect on effort mobilization. Briefly, the IAPE model posits that implicit affect influences effort through its impact on subjective demand, which in turn influences effort according to the principles of motivational intensity theory (Brehm & Self, 1989). The present thesis focused on implicit fear, which is an implicit affect that was not studied to date. Based on the IAPE model (2012, 2015) implicit fear should activate the difficulty concept, which should increase experienced task demand and in turn determine effort mobilization according to the principles of motivational intensity theory (Brehm & Self, 1989). We conducted four studies to test these predictions.
MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging.

The type, frequency, and extent of MR signal abnormalities in Alzheimer's disease and normal aging are a subject of controversy. With a 1.5-MR unit we studied 12 Alzheimer patients, four subjects suffering from multiinfarct dementia and nine age-matched controls. Punctate or early confluent high-signal abnormalities in the deep white matter, noted in 60% of both Alzheimer patients and controls, were unrelated to the presence of hypertension or other vascular risk factors. A significant number of Alzheimer patients exhibited a more extensive smooth "halo" of periventricular hyperintensity when compared with controls (p = .024). Widespread deep white-matter hyperintensity (two patients) and extensive, irregular periventricular hyperintensity (three patients) were seen in multiinfarct dementia. Areas of high signal intensity affecting hippocampal and sylvian cortex were also present in five Alzheimer and two multiinfarct dementia patients, but absent in controls. Discrete, small foci of deep white-matter hyperintensity are not characteristic of Alzheimer's disease nor do they appear to imply a vascular cause for the dementing illness. The frequently observed "halo" of periventricular hyperintensity in Alzheimer's disease may be of diagnostic importance. High-signal abnormalities in specific cortical regions are likely to reflect disease processes localized to those structures.
Power allocation for non-regenerative OFDM relaying channels

Relayed transmission is an efficient way to combat wireless channel fading and to increase system throughput. By allocating the overall power to the transmitter and the relay optimally, the system performance can be further improved. This paper discusses the optimal power allocation in frequency-selective non-regenerative relaying channels, where OFDM is employed. Firstly, the optimal power allocation between a cooperative subcarrier pair is analyzed and an equivalent channel gain model for subcarrier pairs is developed. Based on this, a sub-optimal subcarrier pair selection method is given by applying the Hungarian algorithm. Finally, the optimal power allocation on the selected subcarrier pairs can be obtained by the water-filling approach. Simulation results show that the proposed power allocation algorithm not only outperforms the direct OFDM transmission with optimal power allocation, but also achieves a higher system capacity than uniform power allocation scheme between the transmitter and relay.