Miracle-dz/UniFAR-FTUs huggingface dataset:
The 2dF QSO Redshift Survey — XI. The QSO power spectrum

We present a power spectrum analysis of the final 2dF Quasi-Stellar Object (QSO) Redshift Survey catalogue containing 22 652 QSOs. Utilizing the huge volume probed by the QSOs, we can accurately measure power out to scales of ∼500 h −1 Mpc and derive new constraints, at z ∼ 1.4, on the matter and baryonic contents of the Universe. Importantly, these new cosmological constraints are derived at an intermediate epoch between the cosmic microwave background observations at z ∼ 1000, and local (z ∼ 0) studies of large-scale structure; the average QSO redshift corresponds to a look-back time of approximately two-thirds of the age of the Universe. We find that the amplitude of clustering of the QSOs at z ∼ 1.4 is similar to that of present-day galaxies. The power spectra of the QSOs at high and low redshift are compared and we find � � �
Learning Distributed Representations

This paper describes a neural computing architecture which develops distributed symbolic representations of its environment. Experiments applied the neural system to the sensory and motor environment of a simulated robot navigating across a cluttered oor. The system autonomously deenes and adjusts the meanings of its symbols. Another feature of the system is its ability to remember an event in a single presentation.
A Hexagon Tessellation Approach for the Transmission Energy Efficiency in Underwater Wireless Sensor Networks

Abstract —The energy efficiency is a key design issue to improve the lifetime of the underwater sensor networks (UWSN) consisting of sensor nodes equipped with a small battery of limited energy resource. In this paper, we apply a hexagon tessellation with an ideal cell size to deploy the underwater sensor nodes for two-dimensional UWSN. Upon this setting, we propose an enhanced hybrid transmission method that forwards data packets in a mixed transmission way based on location dependent direct transmitting or uniform multi-hop forwarding. In order to select direct transmitting or uniform multi-hop forwarding, the proposed method applies the threshold annulus that is defined as the distance between the cluster head node and the base station (BS). Our simulation results show that the proposed method enhances the energy efficiency compared with the existing multi-hop forwarding methods and hybrid transmission methods Keywords —UWSN, Hexagon Tessellation, Energy Efficiency, Hybrid 1. I NTRODUCTION
Fault tolerance in cloud computing - survey

Cloud computing datacenter hosts hundreds of thousands of servers that coordinate users' tasks in order to deliver highly available computing service. These servers consist of multiple memory modules, network cards, storage disks, processors etc., each of these components while capable of failing. At such a large scale, hardware component failure is the norm rather than an exception. Hardware failure can lead to performance degradation to users and can result in losses to the business. Fault tolerant is one of efficient modules that keep hardware in operational mode as much as possible. In this paper, we survey the most famous fault tolerance technique in cloud computing, and list numerous FT methods proposed by the research experts in this field.
Semicircle law on short scales and delocalization of eigenvectors for Wigner random matrices

We consider $N\times N$ Hermitian random matrices with i.i. d. entries. The matrix is normalized so that the average spacing between consecutive eigenvalues is of order $1/N$. We study the connection between eigenvalue statistics on microscopic energy scales $\eta\ll1$ and (de)localization properties of the eigenvectors. Under suitable assumptions on the distribution of the single matrix elements, we first give an upper bound on the density of states on short energy scales of order $\eta \sim\log N/N$. We then prove that the density of states concentrates around the Wigner semicircle law on energy scales $\eta\gg N^{-2/3}$. We show that most eigenvectors are fully delocalized in the sense that their $\ell^p$-norms are comparable with $N^{{1}/{p}-{1}/{2}}$ for $p\ge2$, and we obtain the weaker bound $N^{{2}/{3}({1}/{p}-{1}/{2})}$ for all eigenvectors whose eigenvalues are separated away from the spectral edges. We also prove that, with a probability very close to one, no eigenvector can be localized. Finally, we give an optimal bound on the second moment of the Green function.
Model of concurrent MPI communications over SMP clusters

SMP clusters are one of the most common HPC platform used by scientific applications. The nodes of SMP cluster contain several computing elements. Scientific applications may be executed over a large number of such nodes introducing complex communication behaviors. Using for instance MPI, communications on a same node with a common interval time create concurrent accesses to resources of nodes. On SMP nodes, concurrent access implies resource sharing depending on the underlying network architecture and the MPI implementation used. This paper presents a model to predict communication times of simultaneous MPI communications over SMP clusters. This model considers the concurrency over resources of nodes and network predicting accurately communication time for many communications in conflict.
Changing School Autonomy: Academy Schools and Their Introduction to England's Education. CEE DP 123.

In this paper, we study a high profile case - the introduction of academy schools into the English secondary school sector - that has allowed schools to gain more autonomy and flexible governance by changing their school structure. We consider the impact of an academy school conversion on their pupil intake and pupil performance and possible external effects working through changes in the pupil intake and pupil performance of neighbouring schools. These lines of enquiry are considered over the school years 2001-02 to 2008-09. We bypass the selection bias inherent in previous evaluations of academy schools by comparing the outcomes of interest in academy schools to a specific group of comparison schools, namely those state-maintained schools that go on to become academies after our sample period ends. This approach allows us to produce a well-balanced treatment and control group. Our results suggest that moving to a more autonomous school structure through academy conversion generates a significant improvement in the quality of their pupil intake and a significant improvement in pupil performance. We also find significant external effects on the pupil intake and the pupil performance of neighbouring schools. All of these results are strongest for the schools that have been academies for longer and for those who experienced the largest increase in their school autonomy. In essence, the results paint a (relatively) positive picture of the academy schools that were introduced by the Labour government of 1997-2010. The caveat is that such benefits have, at least for the schools we consider, taken a while to materialise.
Risk assessment of multi-order dependencies between critical ICT infrastructures

Assessing risk in information and communication infrastructures is a challenging topic due to the complexity of critical infrastructures (CIs) and of the various dependencies between such infrastructures. This chapter discusses the basic concepts of risk assessment for CIs. Moreover, it describes a recently proposed methodology for criticality assessment. The main goal of this methodology is to assess the risk of an infrastructure (or a sector of critical infrastructures), taking into account the dependencies between CIs and/or sectors. The methodology is compatible with current information systems practices. The basic characteristic of the presented methodology is that it attempts to capture both organizationoriented and society-oriented consequences of possible security events, a feature which is not always embedded in mainstream information security risk assessment methodologies. INTRODUCTION Although assessing security risk in critical information and communication infrastructures (CI) has similarities with risk assessment in traditional information systems, it also requires an extended approach, in order to capture CI complexities (Bialas, 2006). The process of assessing the impacts and the likelihood of occurrence of security incidents affecting CIs, is closely related to traditional information security risk assessment methods. It is also a basis for estimating which infrastructures are more critical than others, and, respectively, which sectors present higher criticality and require more sophisticated protective mechanisms. In the case of a potential threat affecting availability, but also information integrity or confidentiality of a CI, apart from the consequences to the infrastructure itself, a risk assessment methodology should mainly focus on possible impacts to the society. Risk assessment in CIs requires that the policy makers and security experts do consider possible societal impacts, which are external to the organization hosting a critical infrastructure (Theoharidou et al. 2010). An additional difficulty in risk assessment for CIs is the fact that these infrastructures are generally connected with many others and thus the effects of a disruption or failure may spread both geographically and across multiple sectors. The identification of 1-order dependencies may be sufficient in order to assess the risk of a particular infrastructure; however, capturing 1-order dependencies may fail in some cases to capture cascading risk to other infrastructures. For example, one or more relatively minor, security incidents on one CI may cause cascading and escalating impacts to a second or third dependent CI. Identifying multi-order dependencies leads to a more accurate
An Investigation of the Effectiveness of Doing Sports Situation, Gender and Age Variations in Sadness Management in Children

This study was conducted with the aim of investigating the effect of doing sports, gender and age variables on sadness management of students. The universe of the research was 558 students (age average = 11,96 ± 1,29), including 308 female and 250 male students studying in the secondary school of in Karaman between 2017-2018 period. In addition to the personal information form prepared by the researcher as a data collection tool in the research, "Child Sadness Management Scale" developed by Zeman et al., adapted to the Turkish language by Akin et al. was used. MANOVA and ANOVA analysis were performed in the solution and interpretation of the data. At the end of the study; it can be said that the levels of Inhibition from the sadness management sub-dimensions of the participants are in the middle level, Emotion Regulation Coping levels are above the mid - level and Dysregulated-Expression levels are low. There was a significant difference between doing sports variable of the participants and the Inhibition dimension and between the gender variable and sub-dimension of the Dysregulated-Expression, but there was no significant difference between age variable and sub-dimensions of the sadness management.
Optimal Policy in OG Models

In the present paper general stationary overlapping generations economies with many commodities in every period and many different consumers in every generation are considered. A government maximizes an utilitarian social welfare function, that is the sum of weighted averages of utilities for generations, through fiscal policy, i.e. monetary transfers and taxes. Both situations with and without time discounting are considered. It is shown that if the discount factor is sufficiently close to one then the optimal policy stabilizes the economy, i.e. the equilibrium path has the turnpike property. Moreover the fiscal policy is shown to be time-consistent.
Assessment of Left Ventricular Mass by Cardiovascular Magnetic Resonance

Left ventricular hypertrophy is associated with significant excess mortality and morbidity. The study and treatment of this condition, in particular the prognostic implications of changes in left ventricular mass, require an accurate, safe, and reproducible method of measurement. Cardiovascular magnetic resonance is a suitable tool for this purpose, and this review assesses the technique in comparison with others and examines the clinical and research implications of the improved reproducibility.
Calcineurin inhibition blocks within-, but not between-session fear extinction in mice

Memory extinction involves the formation of a new associative memory that inhibits a previously conditioned association. Nonetheless, it could also depend on weakening of the original memory trace if extinction is assumed to have multiple components. The phosphatase calcineurin (CaN) has been described as being involved in extinction but not in the initial consolidation of fear learning. With this in mind, we set to study whether CaN could have different roles in distinct components of extinction. Systemic treatment with the CaN inhibitors cyclosporin A (CsA) or FK-506, as well as i.c. v. administration of CsA, blocked within-session, but not between-session extinction or initial learning of contextual fear conditioning. Similar effects were found in multiple-session extinction of contextual fear conditioning and in auditory fear conditioning, indicating that CaN is involved in different types of short-term extinction. Meanwhile, inhibition of protein synthesis by cycloheximide (CHX) treatment did not affect within-session extinction, but disrupted fear acquisition and slightly impaired between-session extinction. Our results point to a dissociation of within- and between-session extinction of fear conditioning, with the former being more dependent on CaN activity and the latter on protein synthesis. Moreover, the modulation of within-session extinction did not affect between-session extinction, suggesting that these components are at least partially independent.
The Study on Classification and Prediction for Data Mining

The information age needs to master the technique of data mining, the data were analyzed. The classification and prediction through data mining can grasp the basic trend of the development of the unknown data. In this paper, by decision tree, partition the steps of data classification refinement, through discussion on linear regression, multiple linear regression and non-linear regression forecast method, to deepen the understanding of the data prediction accuracy evaluation method, then introduces the classification and prediction of the similarities and differences by classification method.
Curve clustering based on polynomial splines and nonsmooth optimisation

This paper examines clustering in datasets where each record is presented as a curve (trend). Our clustering approach is based on nonsmooth and nonconvex optimisation, namely the clustering problems have been formulated as mathematical programming problems and several optimisation methods from GANSO optimisation library have been applied to solve the problems. The least squares and uniform optimisation criteria have been examined. The numerical experiments have been carried out on the Pezzack dataset. The obtained results encourage the continuation of the research.
Multi‐objective particle swarm optimization for generating optimal trade‐offs in reservoir operation

A multi‐objective particle swarm optimization (MOPSO) approach is presented for generating Pareto‐optimal solutions for reservoir operation problems. This method is developed by integrating Pareto dominance principles into particle swarm optimization (PSO) algorithm. In addition, a variable size external repository and an efficient elitist‐mutation (EM) operator are introduced. The proposed EM‐MOPSO approach is first tested for few test problems taken from the literature and evaluated with standard performance measures. It is found that the EM‐MOPSO yields efficient solutions in terms of giving a wide spread of solutions with good convergence to true Pareto optimal solutions. On achieving good results for test cases, the approach was applied to a case study of multi‐objective reservoir operation problem, namely the Bhadra reservoir system in India. The solutions of EM‐MOPSOs yield a trade‐off curve/surface, identifying a set of alternatives that define optimal solutions to the problem. Finally, to facilitate easy implementation for the reservoir operator, a simple but effective decision‐making approach was presented. The results obtained show that the proposed approach is a viable alternative to solve multi‐objective water resources and hydrology problems. Copyright © 2007 John Wiley & Sons, Ltd.
Automated Computer System Diagnosis by Machine Learning Approaches ∗

Computer systems are growing more and more complex, towards or even beyond the limit that humans can handle. The consequence of the trend is that systems become more fragile, harder to manage, and therefore have lower availability and usability. This paper surveys the systems and their algorithms that can automatically learn the behaviors of those complex systems and diagnose the rootcauses of failures without the detailed knowledge of the system structures. We propose a unified common framework for automated fault diagnosis. Under the same framework, we present four case studies in different application domains, including program debugging, configuration troubleshooting and Internet service diagnosis, using different machine learning algorithms, such as logistic regression, decision trees, Bayesian estimation, and treeaugmented näıve Bayesian networks. Their advantages and disadvantages are discussed and compared. Finally, we provide some thoughts on the possible future directions. ∗Last Update Date: 2005/08/04 03:21:13 CVS Revision: 1.24
Hypothesis: inappropriate colonization of the premature intestine can cause neonatal necrotizing enterocolitis

Neonatal necrotizing enterocolitis (NEC) is a major cause of morbidity in preterm infants. We hypothesize that the intestinal injury in this disease is a consequence of synergy among three of the major risk factors for NEC: prematurity, enteral feeding, and bacterial colonization. Together these factors result in an exaggerated inflammatory response, leading to ischemic bowel necrosis. Human milk may decrease the incidence of NEC by decreasing pathogenic bacterial colonization, promoting growth of nonpathogenic flora, promoting maturation of the intestinal barrier, and ameliorating the proinflammatory response. — Claud, E. C. , Walker, W. A. Hypothesis: inappropriate colonization of the premature intestine can cause neonatal necrotizing enterocolitis. The FASEB J. 15, 1398–1403 (2001)
W-Period Technique for Parallel String Matching

Summary In this paper, we present new approach for parallel string matching. Some known parallel string matching algorithms are considered based on duels by witness which focuses on the strengths and weaknesses of the currently known methods. This has applications such as string databases, Information Retrieval and computational biology. The new ‘divide and conquer’ approach has been introduced for parallel string matching, called the W-period, which is used for parallel preprocessing of the pattern and has optimal implementations in a various models of computation. The idea, common for every parallel string matching algorithm is slightly different from sequential ones as Knuth-Morris-Pratt or Boyer-Moore algorithm.
Working Paper No . 2012 / 78 Microcredit and Poverty Alleviation : Can microcredit close the deal ?

This paper explores the relationship between microcredit and poverty reduction. To investigate this question, we posit a bare-bone, household model that outlines the economic environment within which various types of family microenterprises operate. It highlights a number of issues that impinge on household earnings such as the nature of the labour market, technology, product demand and entrepreneurial skills. The paper argues that the impact of microcredit is likely to be different across household types as well as across different economic environments. The paper identifies several important demand and supply constraints to the household’s graduation from poverty. These constraints are difficult to overcome in a traditional economic environment, marked by stagnant technology and market saturation. Finally, it is suggested that microcredit has a positive effect on female empowerment—i.e., the agency to make household decisions which helps to improve the quality of family consumption and ‘human development indicators’ of the family. This claim may hold sway in some contexts. However, our a priori reasoning, as well as the available contrary empirical evidence, suggests that .
The Glass Ceiling and Women in Accounting: New Zealand Experiences and Perceptions

This paper investigates whether women and men accountants' perceive that there is a "glass ceiling" in the accounting profession for women, and whether they have experienced it in the past and currently. Semi-structured interviews of ten accountants from a range of settings found that the majority perceive that the glass ceiling in the New Zealand accounting profession still exists, as do the bias-centred, person-centred and structural-centred barriers that contribute to gender inequity. However, especially in the last 10 years, it has changed. These findings have implications for the New Zealand Institute of Chartered Accountants (NZICA), organisations and the members of the accounting profession in regards to discrimination and mentoring policies and the promotion of flexible work arrangements.
Universality of First and Second Order Phase Transition in Solar Activity: Evidence for Nonextensive Tsallis Statistics

In this work, we present the coexistence of self-organized criticality (SOC) and low-dimensional chaos at solar activity with results obtained by using the intermittent turbulence theory, the nonextensive q-statistics of Tsallis as well as the singular value decomposition analysis. Particularly, we show the independent dynamics of sunspot system related to the convection zone of sun and the solar flare system related to the lower solar atmosphere. However, both systems reveal nonequilibrium phase transition process from a high-dimensional intermittent turbulence state with SOC profile to a low-dimensional and chaotic intermittent turbulence state. The high-dimensional SOC state in both dynamical systems underlying the sunspot and solar flare signal is related with low q-values and low Flatness values (F) while the low-dimensional chaotic state is related with higher q-values and Flatness F-values. The higher q- and F-values reveal strong character of long-range correlations corresponding to system-wide global process while the lower q- and F-values reveal scale invariant local avalanche process. Also, the high-dimensional SOC state corresponds to second order nonequilibrium critical phase transition process while the low-dimensional chaotic state corresponds to first order nonequilibrium phase transition process. Finally, for both dynamics underlying sunspot index and solar flare, at both states of phase transition process, the multiscale and multifractal character was found to exist but with different profile or strength.