Miracle-dz/UniFAR-FTUs huggingface dataset:
Centuries of Sociology in Millions of Books

The Google Books N-gram corpus contains an enormous volume of digitized data, which, to the best of our knowledge, sociologists have yet to fully utilize. In this paper, we mine this data to shed light on the discipline itself by conducting the first empirical study to map the disciplinary advancement of sociology from the mid-nineteenth century to 2008. We analyse the usage frequency of the most common terms in five major sociology categories: disciplinary advancement, scholars of sociology, theoretical dimensions, fields of sociology, and research methodologies. We also construct an overall index deriving from all sociology-related key words using the principal component method to demonstrate the overall influence of sociology as a discipline. Charting the historical evolution of the examined terms provides rich insights regarding the emergence and development of sociological norms, practices, and boundaries over the past two centuries. This novel application of massive content analysis using data of unprecedented size helps unpack the transformation of sociocultural dynamics over a long-term temporal scale.
Children's Peacekeeping and Peacemaking

Children, like all social species, must balance their need for personal and social resources (Roseth et al. 2011). After all, the benefit of controlling a toy likely decreases when depriving peers results in there being nobody left to play with (Vaughn & Santos 2007). Social competence therefore requires the development of conflict management skills that maintain peaceful relations (peacekeeping) as well as repair peer relationships after conflict occurs (peacemaking). This chapter provides a brief overview of contemporary understanding of the group‐ and individual‐level processes by which children keep and maintain peaceful relations. I bring an ethological perspective to the study of children’s peacekeeping and peacemaking, which means that I connect developmental questions to proximal considerations of what makes these processes occur (causation) and distal considerations of how they influence survival and reproductive success (ultimate function). Because this perspective differs in important ways from developmental psychology’s traditional approach, I begin the chapter by briefly contrasting the two perspectives. I then review the empirical literature on children’s peacekeeping and peacemaking, detailing what is known and unknown about the development of these processes and their capacity for change. Topics include the strategies that children use to control resources, social dominance, reconciliation, and third‐party intervention (e.g., peers and teachers). I focus on children’s peacekeeping and peacemaking with peers and refer interested readers to previous reviews about conflict management with siblings and parents (e.g., Verbeek et al. 2000; Ross et al. 2006).
Serum GST Activity and Total Thiols Status in Patients with Liver DiseaseSecondary to Various Disorders

Introduction: There have been several reports on levels of GST and thiol status in hepatocellular damage. Very few comparative studies are available to know the levels of GST and thiols in various disorders causing hepatocellular damage. Current study was undertaken to know serum GST activity and total thiols status in patients with various disorders causing liver damage. Subjects and methods: Study consisted of 95 patients with various disorders affecting liver leading to hepatocellular damage and 53 healthy controls not on any kind of medication or any therapeutic regimen. Serum GST activity and total thiols were measured using spectrophotometric methods, and standard liver function test was done using clinical chemistry analyzer Hitachi 912. Results: The serum GST activity in patients with acute viral hepatitis, cirrhosis with portal hypertension, leptospirosis, left ventricular failure and falciparum malaria did not differ markedly, however, there was significant increase in serum GST activity (p<0.001) in patients with sepsis and multi organ failure. Total thiols were significantly decreased (p<0.001) in all these patients. Discussion: With exception of sepsis with multi-organ failure, no statistically significant increase in serum GST activity was found in hepatocellular damage caused secondarily to various diseases. Low levels of total thiols in these patients indirectly indicate increased presence of oxidative stress.
Concrete Using Agro-Waste As Fine Aggregate

The most economic and environmental problems result from burial agricultural waste materials. The main objective of the present investigation is to assess the usefulness of agricultural waste in mortar admixture. These materials are expected to reduce the density of the admixture, and thus producing lightweight mortar.This study aims to study the effect of using pistachio shells as partial replacement of sand on the properties of cement mortar.
On the use of rate-less codes in underwater acoustic file transfers

The network protocols developed for electromagnetic wireless communications in air cannot be directly used in underwater acoustic networks due to differences in channel characteristics, propagation speed, bandwidth and the half duplex nature of most acoustic modems. To ensure efficient use of the underwater acoustic channel, the protocol design needs to take propagation delay into account. In this paper, we address a common practical problem of transferring a data file reliably from one underwater node to another. Although this point-to-point model is simple, it captures relevant characteristics of the underwater acoustic channel and has immediate practical applications. We compare the efficiency of various file transfer protocols addressing this common need, where the efficiency is measured by the time taken to transfer the file reliably. The simplest of protocols to address reliable file delivery involves splitting the file into smaller data packets, transmitting each packet and ensuring reliable delivery of the packet via an acknowledgement from the receiving node. When the propagation delay is large, the protocol spends significant amounts of time waiting for acknowledgements and not utilizing the channel. This results in a poor efficiency. The efficiency of the protocol can be improved at the cost of complexity by combining multiple acknowledgements. We also consider a protocol based on rate-less codes, a class of erasure correcting codes where virtually an infinite number of symbols can be generated from the source data. The source data can be reconstructed from any set of the generated symbols provided the set contains a minimum number of independent symbols. This allows a file transfer protocol to be designed where the individual packets do not have to be acknowledged. This reduces the need for acknowledgements dramatically and hence the protocol efficiency is less dependent on the propagation delay.
Factors relating to teachers’ intention to change school: A multilevel perspective

The high turnover rates in public schools, especially in those hard-to-staff schools, remains a growing problem and has become the largest component of teacher supply problems in the US school system. The purpose of the study was to examine the individual and school organizational factors that were associated with teachers’ intentions to change school by using the dataset of the US TALIS 2013 administrated by the Organisation for Economic Co-operation and Development. The results of the multilevel models showed that although the variance in teacher turnover intentions was, to a substantial degree, explained by the individual variables, the school organizational-specific effects have notably contributed to the outcome as well. Additionally, the analysis of the cross-level interaction has detected both direct and indirect effects of disadvantaged schools on teacher transfer intention. The implications for teacher retention policies have been discussed as well.
Composite Systems with Uncertain Couplings of Fixed Structure: Scaled Riccati Equations and the Problem of Quadratic Stability

We consider large scale systems consisting of a finite number of separate uncertain subsystems which interact via uncertain couplings of arbitrarily prescribed structure. The couplings are viewed as structured perturbations of the block-diagonal system representing the collection of the separate nominal subsystems (the “nominal system”). We define spectral value sets and stability radii for these time-invariant structured perturbations and derive formulas for their computation. Scaled Riccati equations are introduced to obtain explicit formulas for the stability radii with respect to time-varying and possibly nonlinear perturbations of the given structure. From these we derive necessary and sufficient conditions under which the stability radii with respect to time-invariant and time-varying perturbations are equal. These results are obtained by constructing joint quadratic Liapunov functions of optimal robustness. With their help we prove necessary and sufficient conditions for quadratic stability and sufficient conditions for the validity of a generalized Aizerman conjecture.
Participatory planning through negotiated coordination

This contribution to Science & Society's special issue on socialist economic organisation brings together the basic model proposed in Devine (1988) and subsequent work developing and elaborating that model (Adaman and Devine 1994, 1996, 1997, mimeo; Devine 1992, 1997, forthcoming). It is part of a project which is designed to assist in the revival of the movement for socialism by developing a well-defined model of participatory democratic planning. The aim is to take seriously both the negative experience of the Soviet model of administrative command planning and the positive insights of the Austrian school's recent reworking of the socialist calculation debate.
Quasi-polynomial hitting-set for set-depth-Δ formulas

We call a depth-4 formula C <i>set-depth-4</i> if there exists a (unknown) partition X<sub>1</sub>⊔⋅⋅⋅⊔ X<sub>d</sub> of the variable indices [n] that the top product layer respects, i.e. C(term{x})=∑<sub>i=1</sub><sup>k</sup> ∏<sub>j=1</sub><sup>d</sup> f<sub>i,j</sub>(term{x}<sub>X<sub>j</sub></sub>), where f<sub>i,j</sub> is a <i>sparse</i> polynomial in F[term{x}<sub>X<sub>j</sub></sub>]. Extending this definition to any depth - we call a depth-D formula C (consisting of alternating layers of Σ and Π gates, with a Σ-gate on top) a <i>set-depth-D</i> formula if every Π-layer in C respects a (unknown) partition on the variables; if D is even then the product gates of the bottom-most Π-layer are allowed to compute arbitrary monomials. In this work, we give a hitting-set generator for set-depth-D formulas (over <i>any</i> field) with running time polynomial in exp((D<sup>2</sup>log s)<sup> Δ - 1</sup>), where s is the size bound on the input set-depth-D formula. In other words, we give a <i>quasi</i>-polynomial time <i>blackbox</i> polynomial identity test for such constant-depth formulas. Previously, the very special case of D=3 (also known as <i>set-multilinear</i> depth-3 circuits) had no known sub-exponential time hitting-set generator. This was declared as an open problem by Shpilka & Yehudayoff (FnT-TCS 2010); the model being first studied by Nisan & Wigderson (FOCS 1995) and recently by Forbes & Shpilka (STOC 2012 & ECCC TR12-115). Our work settles this question, not only for depth-3 but, up to depth εlog s / log log s, for a fixed constant ε < 1. The technique is to investigate depth-D formulas via depth-(D-1) formulas over a <i>Hadamard algebra</i>, after applying a 'shift' on the variables. We propose a new algebraic conjecture about the <i>low-support rank-concentration</i> in the latter formulas, and manage to prove it in the case of set-depth-D formulas.
Effect of a probiotic preparation (VSL#3) in critically ill patients: A randomized, double-blind, placebo-controlled trial (Pilot Study)

Objective : Reactive oxygen species (ROS) are a major contributing factor in diseases pathophysiology in critically ill patients. Oxidative stress usually occurs in critical illnesses, specifically during sepsis, and organ dysfunction. The anti-oxidative properties of probiotics may serve as a defense in intestine and overcome various oxidative stresses. The aim of this trial was to determine the effect of probiotics on inflammation, antioxidant capacity and lipid peroxidation in critically ill patients. Methodology : Forty patients admitted to the intensive care unit were enrolled in this double-blind, randomized controlled trial. They were randomized to receive placebo or probiotic for 7 days. Serum levels of Total Antioxidant Capacity (TAC), Malodialdehyde (MDA), C-Reactive Protein (CRP) and Acute Physiology and Chronic Health Evaluation (APACHE II) score were measured before initiation of the study and on the 7th day. Results: There was a significant difference in CRP levels and APACHE II score between two groups at the end of the study (P= 0.003 and 0.001, respectively). There was not a significant difference in levels of TAC and MDA between two groups. Conclusions: Administration of probiotics to critically ill patients caused reduction in inflammation and improvement of clinical outcome. However, there were not significant changes in markers of oxidative stress.
Indoor Scene Recognition CS 229 Autumn 2011 Final Project Writeup

While scene recognition problem is not new, it is still a challenging, open-ended problem on which a lot of further work can be done to improve feature selection and applicable learning algorithms. Several computer vision research groups at MIT have worked on scene recognition, with many classes of scenery images ranging from outdoor landscapes to indoor rooms or areas [6, 7]. While the accuracy rate is high for some outdoor landscapes [6], classifying the indoor specific areas still posts a difficult task due to similar image features across categories and huge variation within category. Our primary goal was to be able to identify the bathroom images given a set of images of all areas in a home. We first selected bathroom simply because of its unique visual features. Later on we extended our work to also include binary classification of other classes as well as multi-class classification. Our dataset was downloaded from [5], which Ariadna Quattoni et al. also used on for their work on indoor scene recognition (with a larger set of scene categories) [6]. For our work, all algorithms were run on SIFT feature space. We chose to work with SIFT feature as it was reported by Jianxiong Xiao et al. to be one of the few top choices yielding high recognition accuracy [7]. In addition, most images of indoor home areas share a lot of common edge-, curveand corner-related characteristics, which SIFT features can well capture.
Structured covariance estimation for state prediction

In this paper we propose a structurally constrained expectation-maximization (EM) algorithm for estimating noise covariances in state-space models, for the purpose of state prediction and control. More specifically, we generalize the problem of covariance estimation on the basis of given i.i. d sample sequence to the dynamic setting where the samples (i.e. state and observation noises) are observed only through the measurement data, or equivalently, drawn from the conditional distribution governed by the dynamic model. By applying the expectation maximization (EM) algorithm to the innovation model representation, we view the resulting ML covariance estimates as the conditional sample covariances, and augment the negative log-likelihood function with matrix norm penalty terms that enforce low-rank and low cardinality structure in the estimated covariances or their inverses. These constraints serve to reflect realistic problem structure expected from model knowledge, yet are still general and flexible enough to be broadly applicable. In addition, the new derivation of the EM algorithm based on the innovation representation gives the common sufficient statistic for both the process and observation noise covariances. This illustrates the coupling between the two covariance estimates, and in simulated cases, enables the calculation of an upper performance bound against which the EM estimates can be compared. The use of the innovation representation also provides a tractable connection to the existing techniques such as the Autocovariance Least Squares (ALS) algorithm. Numerical results comparing the constrained EM and the ALS algorithms are also provided, showing favorable performance for the EM covariance estimates.
Distributed Cooperative Transmission with Unreliable and Untrustworthy Relay Channels

Cooperative transmission is an emerging wireless communication technique that improves wireless channel capacity through multiuser cooperation in the physical layer. It is expected to have a profound impact on network performance and design. However, cooperative transmission can be vulnerable to selfish behaviors and malicious attacks, especially in its current design. In this paper, we investigate two fundamental questions Does cooperative transmission provide new opportunities to malicious parties to undermine the network performance? Are there new ways to defend wireless networks through physical layer cooperation? Particularly, we study the security vulnerabilities of the traditional cooperative transmission schemes and show the performance degradation resulting from the misbehaviors of relay nodes. Then, we design a trust-assisted cooperative scheme that can detect attacks and has self-healing capability. The proposed scheme performs much better than the traditional schemes when there are malicious/selfish nodes or severe channel estimation errors. Finally, we investigate the advantage of cooperative transmission in terms of defending against jamming attacks. A reduction in link outage probability is achieved.
SCHEMATA , LEARNING AND CONCEPTUAL LANDSCAPES

How are concepts represented? This is a question that must be asked and at least partially answered by any theory of cognition. Within cognitive liguistics one argues that the nature of the cognitive representations determines the structure of language (e. g. Lakoff 1987). The usual approach is to try to reveal the underlying representations by an extensive analysis of human language. I will try the opposite approach and start with an analysis of the representations in neural networks and show that they impose some non-trivial constraints on the nature of conceptual representations that can be used to predict some general properties of human language and its acquisition.
Multi-Scale Visual Quality Assessment for Cluster Analysis with Self-Organizing Maps

Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.
Neuroimaging in Psychology: The Portrayal of Key Radiological Techniques in Contemporary Texts

Neuroimaging is increasingly important in psychology, yet psychologists can fall prey to misconceptions. We examined the presentation of key radiological techniques in 12 widely distributed contemporary psychology texts. Errors were common in descriptions of computed tomography (CT), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). For example, PET images are generated by detecting pairs of photons, not the direct measurement of positrons. Similarly, many authors omit the need for a radio frequency pulse in MRI, implying that the technique simply relies on the application of a magnetic field. Misconceptions should be addressed in an attempt to reduce levels of confusion and maximise the contribution of neuroimaging data to psychological theorising.
A Preliminary Investigation of Learner Characteristics for Unsupervised Dialogue Act Classification

For tutorial dialogue systems, classifying the dialogue act (such as questions, requests for feedback, or statements) of student natural language utterances is a central challenge. Recently, momentum is building for the use of unsupervised machine learning approaches to address this problem because they reduce the manual tagging required to build dialogue act models from corpora. However, unsupervised models still do not perform as well as supervised models in terms of accuracy. This paper presents an unsupervised dialogue act modeling approach that leverages the influence of learner characteristics, particularly students’ perceptions of their own skill, on their language use. The experimental findings show that leveraging skill perception within dialogue act classification improves performance of the models, producing better accuracy. This line of investigation will inform the design of nextgeneration tutorial dialogue systems, which leverage machinelearned models to adapt to their users.
Programmable neuromorphic circuits for spike-based neural dynamics

Hardware implementations of spiking neural networks offer promising solutions for a wide set of tasks, ranging from autonomous robotics to brain machine interfaces. We propose a set of programmable hybrid analog/digital neuromorphic circuits than can be used to build compact low-power neural processing systems. In particular, we present both CMOS and hybrid memristor/CMOS synaptic circuits that have programmable synaptic weights and exhibit biologically plausible response properties. For the CMOS circuits, we present experimental results demonstrating that they operate correctly over a wide range input frequencies; for the hybrid memristor/CMOS circuits we present circuit simulation results validating their expected response properties.
Innovative Ideas in Requirements Engineering For E-Commerce Applications

: Innovative ideas are characterized by commercial products yet unknown to the market, enabled by information technology. How to develop such products is hardly known. We propose a interdisciplinary approach, e3-value, to explore an innovative Ideas with the aim to understand such an idea thoroughly and to evaluate it for potential Profitability. Our methodology exploits a requirements engineering’s way of working, but employs concepts and terminology from business science, marketing and axiology. It shows how to model business requirements and improve Business-IT alignment, in sophisticated multi-actor value constellations that are common in electronic commerce.