Miracle-dz/UniFAR-FTUs huggingface dataset:
Nearest-Neighbor Guided Evaluation of Data Reliability and Its Applications

The intuition of data reliability has recently been incorporated into the main stream of research on ordered weighted averaging (OWA) operators. Instead of relying on human-guided variables, the aggregation behavior is determined in accordance with the underlying characteristics of the data being aggregated. Data-oriented operators such as the dependent OWA (DOWA) utilize centralized data structures to generate reliable weights, however. Despite their simplicity, the approach taken by these operators neglects entirely any local data structure that represents a strong agreement or consensus. To address this issue, the cluster-based OWA (Clus-DOWA) operator has been proposed. It employs a cluster-based reliability measure that is effective to differentiate the accountability of different input arguments. Yet, its actual application is constrained by the high computational requirement. This paper presents a more efficient nearest-neighbor-based reliability assessment for which an expensive clustering process is not required. The proposed measure can be perceived as a stress function, from which the OWA weights and associated decision-support explanations can be generated. To illustrate the potential of this measure, it is applied to both the problem of information aggregation for alias detection and the problem of unsupervised feature selection (in which unreliable features are excluded from an actual learning process). Experimental results demonstrate that these techniques usually outperform their conventional state-of-the-art counterparts.
Default mode network neurodegeneration reveals the remote effects of ischaemic stroke

Dementia is estimated to occur in 15%–30% patients after ischaemic stroke.1 Stroke may initiate or accelerate neurodegeneration associated with cognitive impairment.1 Brain atrophy is an important marker of neurodegeneration, preceding the emergence of cognitive symptoms in Alzheimer’s disease (AD). 2 Atrophy occurs in distributed regions that collectively mirror known brain networks, including the default mode network (DMN). Atrophy and dysfunction within the DMN is evident in healthy ageing, accelerated in pathological ageing2 and evident in acute and subacute stroke.3 Lesion location rarely predicts long-term outcome in stroke. Network-wide changes may better explain neurodegeneration and conversion to dementia after stroke. Atrophy after stroke has not been well investigated and has been limited to cross-sectional studies and regional volume changes. Structural covariance is an increasingly popular method of examining network-wide correlations in morphometric estimates of brain structure, such as cortical thickness or grey matter volume. There is a close relationship between estimates of network-based structural covariance and intrinsic functional network architecture.4 Structural covariance can be tracked over time to reveal changes in brain organisation, either developmental or degenerative, via cross-sectional comparisons within and between groups.4 Cross-sectional differences can be difficult to detect when there is normal variability across individuals.5 Longitudinal imaging has the benefit of overcoming interindividual differences in cortical morphology by using each individual as their own control.5 Longitudinal imaging also provides an opportunity for more direct examination of atrophy within networks by looking at correlations in the rate of cortical atrophy (see figure 1 in the online Supplementary file 1) across the brain, rather than just correlations in the morphometric measure itself. Atrophy across the brain can also be examined by …
Composite objects revisited

In object-oriented systems, an object may recursively reference any number of other objects. The references, however, do not capture any special relationships between objects. An important semantic relationship which may be superimposed on a reference is the IS-PART-OF relationship between a pair of objects. A set of objects related by the IS-PART-OF relationship is collectively called a composite object. An earlier paper [KIM87b] presented a model of composite objects which has been implemented in the ORION object-oriented database system at MCC. Although the composite-object feature has been found quite useful, the model suffers from a number of serious shortcomings, primarily because it overloads a number of orthogonal semantics on the references. In this paper, first we present a more general model of composite objects which does not suffer from these shortcomings. Further, [KIM87b] made an important contribution by exploring the use of composite objects as a unit for versions, physical clustering, and concurrency control. The extended model of composite objects necessitates non-trivial changes to the results of [KIM87b]. This paper describes the new results on the use of composite objects as a unit of not only versions, physical clustering and concurrency control, but also authorization.
RNA transcription modulates phase transition-driven nuclear body assembly

Significance Living cells contain various membraneless organelles whose size and assembly appear to be governed by equilibrium thermodynamic phase separation. However, the dynamics of this process are poorly understood. Here, we quantify the assembly dynamics of liquid-phase nuclear bodies and find that they can be explained by classical models of phase separation and coarsening. In addition, active nonequilibrium processes, particularly rRNA transcription, can locally modulate thermodynamic parameters to stabilize nucleoli. Our findings demonstrate that the classical phase separation mechanisms long associated with nonliving condensed matter can mediate organelle assembly in living cells, whereas chemical activity may serve to regulate these processes in response to developmental or environmental conditions. Nuclear bodies are RNA and protein-rich, membraneless organelles that play important roles in gene regulation. The largest and most well-known nuclear body is the nucleolus, an organelle whose primary function in ribosome biogenesis makes it key for cell growth and size homeostasis. The nucleolus and other nuclear bodies behave like liquid-phase droplets and appear to condense from the nucleoplasm by concentration-dependent phase separation. However, nucleoli actively consume chemical energy, and it is unclear how such nonequilibrium activity might impact classical liquid–liquid phase separation. Here, we combine in vivo and in vitro experiments with theory and simulation to characterize the assembly and disassembly dynamics of nucleoli in early Caenorhabditis elegans embryos. In addition to classical nucleoli that assemble at the transcriptionally active nucleolar organizing regions, we observe dozens of “extranucleolar droplets” (ENDs) that condense in the nucleoplasm in a transcription-independent manner. We show that growth of nucleoli and ENDs is consistent with a first-order phase transition in which late-stage coarsening dynamics are mediated by Brownian coalescence and, to a lesser degree, Ostwald ripening. By manipulating C. elegans cell size, we change nucleolar component concentration and confirm several key model predictions. Our results show that rRNA transcription and other nonequilibrium biological activity can modulate the effective thermodynamic parameters governing nucleolar and END assembly, but do not appear to fundamentally alter the passive phase separation mechanism.
Eco Friendly Synthesis, Spectroscopic Investigation of Copper and Its Oxide Nanoparticles with Excellent Electrical Conductivity

Metal Nanoparticles have attracted considerable attention because of their excellent electronic and optical properties. They have been used in many fields, such as displays, solar cells, touchscreens, sensors, and electromagnetic interference shielding [1]. However, for most of these applications, metal Nanoparticles with high electrical conductance are required. Compared with various other metals, copper is more abundant and less expensive, while having favourable mechanical, electrical, and optical properties [2]. Copper Nanoparticles have thus been suggested as a low cost alternative to indium tin oxide (ITO), investigated extensively and compared against conductive polymers, carbon nanotubes, graphenes and Ag nanowires [3-6]. To date, various methods have been developed for synthesizing Copper and its oxide Nanoparticles (CuO NPs), including electrochemical deposition, electrospinning, template processes, hydrothermal reduction and reverse micellar systems [7-12]. On the other hand, the microwave-assisted synthesis [13,14], which is generally quite fast, simple and efficient in energy, has been developed and is widely used in various fields such as molecular sieve preparation, radiopharmaceuticals, the preparation of inorganic complexes and oxide, organic reactions, plasma chemistry, analytical chemistry and catalysis. Generally speaking, the power, heating frequency and on/off irradiation cycles are the main heating parameters of a microwave oven and each of them may have a great effect on the structure and properties of the products. To the best of our knowledge, although such a heating method has been a focus of research, most of previous reports were limited to fixed working conditions of the microwave oven [15-20] and there is no comprehensive report addressing the effects of these heating parameters on the synthesis of nanomaterials [21-23]. Furthermore, there are few reports on synthesizing the Copper and its oxide Nanoparticles without template at mild condition by the use of microwave method. Here, we report a simple microwave method to fabricate well aligned Copper and its oxide Nanoparticles (CuO NPs) on a Copper surface without any template and surfactant [24-26].
Hurst parameter estimation for epleptic seizure detection

Estimation of the Hurst parameter provides information about the memory range or correlations (long vs. short) of processes (time-series). A new application for the Hurst parameter, real-time event detection, is identified. Hurst estimates using rescaled range, dispersional and bridge- detrended scaled windowed variance analyses of seizure time-series recorded from human subjects reliably detect their onset, termination and intensity. Detection sensitivity is unaltered by signal decimation and window size increases. The high sensitivity to brain state changes, ability to operate in real time and small computational requirements make Hurst parameter estimation using any of these three methods well suited for implementation into miniature implantable devices for contingent delivery of anti-seizure therapies. industrialized world's population, and up to 10% of people in under-developed coun- tries. As seizures are brief and relatively unpredictable, continuous EEG/ECoG moni- toring is needed to implement new therapies, such as contingent electrical stimulation for seizure blockage, via implantable devices, in subjects with pharmaco-resistant epilepsies. Hurst parameter (1) estimation has been applied to many natural (non-biological) (2) and also biological phenomena, such as neuron membrane channel kinetics (10), a fundamental functional operation of the brain. The behavior of membrane channels seems to exhibit long-term correlation (H > 0.78, implying "persistence") and the currents recorded through individual ion channels have self-similar properties, that is, they are fractals and may be best modeled using fractional Brownian motion. The fractal behavior may extend to the whole neuron as measured simultaneously across many channels. This raises the possibility that brain electrical processes may be fractal or self-similar, or that, at a minimum, useful information may be obtained from treating them as such in analyzing data or signals generated by these processes in the brain. The Hurst parameter (H) (1, 2) may provide information about the behavior of continuous and discrete event time series and its estimation in the EEG/ECoG of
Convergence in Backward Error of Relaxed GMRES

This work is the follow-up of the experimental study presented in [A. Bouras and V. Fraysse´, SIAM J. Matrix Anal. Appl. , 26 (2005), pp. 660-678]. It is based on and extends some theoretical results in [V. Simoncini and D. B. Szyld, SIAM J. Sci. Comput. , 25 (2003), pp. 454-477; J. van den Eshof and G. L. G. Sleijpen, SIAM J. Matrix Anal. Appl. , 26 (2004), pp. 125-153]. In a backward error framework we study the convergence of GMRES when the matrix-vector products are performed inaccurately. This inaccuracy is modeled by a perturbation of the original matrix. We prove the convergence of GMRES when the perturbation size is proportional to the inverse of the computed residual norm; this implies that the accuracy can be relaxed as the method proceeds which gives rise to the terminology “relaxed GMRES. ” As for the exact GMRES we show under proper assumptions that only happy breakdowns can occur. Furthermore, the convergence can be detected using a byproduct of the algorithm. We explore the links between relaxed right-preconditioned GMRES and flexible GMRES (FGMRES). In particular, this enables us to derive a proof of convergence of FGMRES. Finally, we report results of numerical experiments to illustrate the behavior of the relaxed GMRES monitored by the proposed relaxation strategies.
Structure and Performance: The Task of Economic History

JHE CLIOMETRIC revolution in ecoknomic history wedded neoclassical economics and quantitative methods in order to describe and explain the performance of economies in the past. ' Economic history gained in rigor and scientific pretension, but at the expense of exploring a much more fundamental set of questions about the evolving structure of economies that underlies performance.2 Cliometricians have turned their backs on a long tradition stretching back from Joseph Schumpeter to Karl Marx to Adam Smith. These scholars regarded economic history as essential because it added a dimension to economics. Its purpose was to analyze the parameters held constant by the economist. If economics is a theory of choice subject to specified constraints, a task of economic history was to theorize about those evolving constraints. The failure of economic historians to provide their colleagues with a historical dimension to their perspective has reduced the effectiveness of economists in dealing with contemporary problems. Failure of economists to appreciate the transitory character of the assumed constraints and to understand the source and direction of these changing constraints is a fundamental handicap to further development of economic theory. The challenge to the economic historian which has equally compelling implications for the economic theorist is to explain the transformation of the structure of the American Economy in the past century.3 In the rest of this essay I shall explore this issue in order to specify some of the dimensions of the economic historian's task.
A fast panoramic imaging system and intelligent imaging technique for mobile robots

Mobile robots often require a full 360/spl deg/ view of their environment in order to perform navigational tasks such identifying landmarks, localizing within the environment, and determining free paths in which to move. In the past few years, several research efforts have focused on obtaining panoramic views (i.e. 360/spl deg/ images) around the robot using wide angle lenses, spherical or conic mirrors, or rotating a camera while imaging. Although the wide angle lens and mirror techniques can provide rapid image acquisition, they lack high azimuth angle resolution required by many mobile robot navigational tasks. Panning (i.e. rotating) a camera on the other hand can provide high azimuth angle resolution, but the process requires a long time to obtain a panoramic view. We introduce a new system that can acquire panoramic images quickly, using the camera panning technique. The system makes use of a fast line scan camera, instead of a slower, conventional area scan camera. In addition, we have developed a coarse-to-fine panoramic imaging technique that is based on smart sensing principles. Using the active vision paradigm, we control the motion of the rotating camera using feedback from the images. This results in high acquisition speeds and proportionally low storage requirements. Preliminary experimentation has been carried out, and results we given.
Social Capital: Reaching Out, Reaching In

Contents: Introduction: The Yet Undiscovered Value of Social Capital, Viva Ona Bartkus and James H. Davis PART I: OVERVIEW 1. What is Social Capital? Elinor Ostrom 2. Network Duality of Social Capital, Ronald S. Burt 3. On the Costs of Conceptualizing Social Ties as Social Capital, Robert M. Fishman PART II: SOCIAL CAPITAL: REACHING OUT 4. How's the Job? Are Trust and Social Capital Neglected Workplace Investments? John F. Helliwell, Haifang Huang and Robert D. Putnam 5. Social Capital Effects on Student Outcomes, Maureen T. Hallinan 6. Communities, Schools and Voter Turnout: A Case Study in Social Norms, David E. Campbell 7. Experimental Approaches to the Diffusion of Norms, David W. Nickerson 8. Capitalizing on Connections: Social Capital and Strategic Management, Janine Nahapiet PART III: SOCIAL CAPITAL: REACHING IN 9. Social Capital Creation: Collective Identities and Collective Action, Roderick M. Kramer 10. Connecting to Brokers: Strategies for Acquiring Social Capital, Daniel J. Brass 11. Trust, Distrust and Building Social Capital, Roy. J. Lewicki and Chad T. Brinsfield 12. Understanding Social Capital: In Whom do we Trust? Darryl Stickel, Roger C. Mayer and Sim B. Sitkin 13. Organizational Trust and Social Capital, James H. Davis and Viva Ona Bartkus Conclusion: Frontiers of Social Capital Research, Viva Ona Bartkus and James H. Davis Index
Five ways of doing qualitative analysis: Phenomenological psychology, grounded theory, discourse analysis, narrative research, and intuitive inquiry

Introduction. Part 1. A Story of Qualitative Research in Psychology. From Innovative Practices to the Call for Methodology. The Establishment of Methodological Traditions. Contemporary Movement, Methodological Pluralism, and Challenges. Part 2. Five Approaches to Qualitative Data Analysis. The Teresa Texts: Thick Description of Living through Misfortune. F. J. Wertz, A Phenomenological Psychological Approach to Trauma and Resiliency. K. Charmaz, A Constructivist Grounded Theory Analysis of Losing and Regaining a Valued Self. L. McMullen, A Discursive Analysis of Teresa's Protocol: Enhancing Oneself, Diminishing Others. R. Josselson, Narrative Research: Constructing, Deconstructing, and Reconstructing Story. R. Anderson, Intuitive Inquiry: Exploring the Mirroring Discourse of Disease. Part 3. Pluralism, Participation, and Unity in Qualitative Research. Comparisons through Five Lenses. The Participant's Response. Ethics, Participant Involvement, and Analytic Methodology. Appendix: Gail's Texts.
Faktor-faktor Penyebab Terjadinya Perkawinan Usia Muda Dikalangan Remaja di Desa Tembung Kecamatan Percut Sei Tuan Kabupaten Deli Serdang

ii This thesis is entitled "Factors Causing Occurrence Amongst Young Age Teens Marriage in the Village District Tembung Percut Sei Tuan Deli Serdang regency". This study aimed to describe the factors that lead to early marriage among teenagers and to describe the forms of family upbringing young couples. Results from this study are expected to be material for parents to enter, so do not rush to immediately marry children in adolescence. Because teens have not been able to face and resolve domestic problems as well. The teens still need to stock a lot of good stock of physical maturity, mental and social economics, general science, religion, life experiences in married life. The study was conducted in the village of Sei Tuan Tembung Percut District Deli Serdang regency. This research is descriptive, where the informants in this study were adolescents who had been married at a young age as many as 3 people and parents of informants. Data collection techniques to the study of literature, field studies, in-depth interviews and observation. The data obtained in the field and then analyzed and compiled in a draft of questions and answers between researchers described qualitatively. The results show conclusively that the environmental factors and parental considerable influence on the formation of self-concept in children, because the child saw her mother who also did a lot of early marriage. Factors parents of low economic level caused many parents marry off their children at a young age. Keywords: factors of early marriage, teenage.
Modeling and analysis of HetNet interference using Poisson Cluster Processes

Future mobile networks are converging towards being heterogeneous, owing to the co-existence of multi-tier networks within the same geographical area, including macro, pico- and femto-cells. The deployment of such networks is generally based on user demand, which is irregular and random, implying that the deployment of base stations (BSs) is random as well. As a result, analyzing the communication protocols over heterogeneous networks (HetNets) is very challenging. A popular approach is to use stochastic geometry and treat the location of the BSs as points distributed according to a spatial Point Process. Most of the related work on the interference modeling normally assumes homogeneous Poisson point process (PPP). This assumption holds when the nodes are uniformly distributed in space, such as sensor networks or ad-hoc networks. Due to geographical factors, it may be the case for mobile users to cluster around highly populated cities and the PPP assumption does not provide an accurate model for the interference in these conditions. This motivates us to find better ways to characterize the aggregate interference when the transmitting nodes are clustered following a Poisson Cluster Process (PCP). Furthermore, the BSs belonging to different tiers may differ in terms of the transmit power, the node densities, and their link reliabilities. To this end, we consider K-tier HetNets, where, by using the Laplace transform approach, we characterize the aggregate interference at a given destination as a heavy-tailed distribution. Using the derived distribution, we investigate the probability of outage and coverage for such networks. Due to some difficulty in obtaining closed-form expressions for these measures, we derive tight bounds and verify that through numerical examples. We also compare the performance of HetNets when the nodes are clustered and otherwise. We observe that using the PPP results in larger success probability, but using the clustered process results in a larger coverage probability. We also observe that there is an optimal intensity, i.e., number of nodes, that achieves the maximum coverage probability for the given SINR (signal-to-interference-plus-noise ratio) threshold.