Miracle-dz/UniFAR-FTUs huggingface dataset:
Populism—again, seemingly without end

The idea of popular disillusion with technocracy, the electoral process, bureaucracy, diplomacy, the law, and other forms of state activity and cultural or intellectual expertise is not new. Nor is the attempt by politicians of many stripes to take advantage of the fact through antistatist appeals to people who feel disenfranchised. Such campaigns are typically couched as being opposed to politics. They are made by demagogues posing as outsiders who are actually insiders, or wish to become so (Canovan, 1981; Ionescu & Gellner, 1969; Panizza, 2005; Taggart, 2000). But wholesale disaffection with the very nature of democracy and its checks and balances, to the point of deriding houses of review, the judiciary, policy analysis, scholarly knowledge, public service, and the press corps, as similarly tarnished with accusations of special pleading, corruption, and incompetence, is suddenly au courant. The sole trusted state figures are supposedly in the military, while populist politicians alone are seen to have direct lines to the consciousness of the populace, whose drives and dislikes are to be trusted, always and everywhere. Checks and balances are deemed as ludicrous as elections – what matters is the spirit-indwelling of the nation, as magically incarnated in charismatic leaders and their irrefutable, incomparable organic connection to ordinary life, be they Podemos and its political sociologists, Syriza’s political economists, the Tea Party’s white millionaires and obedient employees, or Colombian evangelicals dutifully following the lead of US pastors. Regardless of these entities’ links to universities, wealth, or churches, they appear to be outsiders – anti-politicians who are admired because of what they oppose, and for putatively emerging from beyond the conventional norms of electoral and bureaucratic organization (Cherniavsky, 2017; Curini, 2018; De La Torre, 2015; Kriesi & Pappas, 2015; Moffitt, 2016). It is as if the very triumph of liberal-capitalist democracy as a burgeoning norm ever since the end of the Second World War, the flowering of decolonization, and the decline of state socialism had masked an instability at the very heart of seemingly-established constitutional arrangements, signaled by the emergence of what are being called ‘electoral dictatorships. ’ The independent media are silenced, dissenters are threatened, jailed, or worse under the sign of democracy, with mass, if not universal, endorsement. This development has confounded the previous correlation between reasonable income distribution and political stability. Populism has stimulated a specialist and mass-market literature and media concern, and attracted numerous policy proposals to counter or exploit it (Mudde, 2017; Mudde & Kaltwasser, 2017; Muller, 2016; Mouffe, 2018; Mounk, 2018). Although advocacy of populism may come from the left or the right of politics, it is generally nationalistic and anti-immigrant in its American and European versions. For conservative
V. Szemerédi's Regularity Lemma 1. Preliminaries

The 'regularity lemma' of Endre Szemerédi [5] roughly asserts that, for each ε > 0, there exists a number k such that the vertex set V of any graph G = (V, E) can be partitioned into at most k almost equal-sized classes so that between almost any two classes, the edges are distributed almost homogeneously. Here the meaning of almost depends on ε. We will make this precise and prove it in Section 2. First, some 'ε-free' preliminaries. A partition of a set X is a collection of pairwise disjoint nonempty sets with union X.
The effect of husband-wife communication on marital power in decision-making

The purpose of this study was to investigate the effect of husband-wife communication on marital power in decision-making. Forty married couples were selected from the parents of children enrolled in the School of Home Economics Nursery School program at the University of North Carolina at Greensboro. The subjects were selected on the basis of their homogeneity of characteristics related to variables which had been reported by previous research to affect marital power. Couples were randomly assigned to an experimental and a control group. A Decision Power Index was used as a measure of each spouse's perceived power. A pretest and a posttest, both of which consisted of the same risk-taking decision, were administered to each spouse before and after a fifteen-minute period during which the experimental couples discussed the decision and the control couples listened to an unrelated musical tape and had no communication. Appropriate t tests were used to analyze the data. The significance level was set at the . 05 critical value for a two-tailed test.
Applying Formal Concept Analysis to Cascading Style Sheets

Cascading Style Sheets (CSS) are used in the HyperText Markup Language (HTML) to describe the style, size, color, and position of elements in a document. While simple styles are easy to specify, a style sheet for a complex site can become many thousands of lines long. One problem in style sheets is that as they grow there is a tendency for increasing duplication of styles and properties, especially when the style sheet is used for many pages created by multiple authors. Formal Concept Analysis (FCA) is a technique for eliminating redundancy while identifying common concepts in a complex space of property definitions. In this work we use FCA to optimize style sheets to reduce redundancy, merge several rules together, and group the selectors with their declarations to express general formatting concepts. Two problems we solved include converting complex style sheets into a form on which FCA can be applied, and interpreting the resulting concept lattice to avoid introducing too many styles for small concepts. We evaluate the effectiveness of the solution on several style sheets.
Situation Awareness in Dynamic Decision Making: Effects of Practice and Working Memory

The goal of this research is (a) to investigate the effects of task practice on situation awareness (SA); (b) to investigate how cognitive ability – in particular, working memory – moderates this practice effect on SA; and (c) to investigate effects of the SA measurement procedure (covering or uncovering the display while queries are answered). Task practice and working memory influence SA. However, the dynamics of the relationship between working memory and SA over time are not well understood, particularly with regard to using different SA measures. This research reports an experiment in which different SA measurement methods were used while participants played a computer simulation over several days. SA was measured using two query methods: a covered method in which questions were asked while the display was blanked out, and an uncovered method in which questions were asked while the display was shown. A working memory measure was collected from participants. Results indicate that the relationship between working memory and SA diminishes with task practice and differs between a covered and uncovered method. We also found that SA improvement with practice depends on the way in which SA is measured. We discuss the implications of these findings for understanding SA development, SA measurement, and the relationship of working memory in this process. The results from this study have clear implications for systems design, for the design of learning aids, and for SA measurement.
Super-Gaussian Mixture Model

We propose an extension of the mixture of factor (or independent component) analyzers model to include strongly super-gaussian mixture source densities. This allows greater economy in representation of densities with (multiple) peaked modes or heavy tails than using several Gaussians to represent these features. We derive an EM algorithm to find the maximum likelihood estimate of the model, and show that it converges globally to a local optimum of the actual non-gaussian mixture model without requiring any approximations. This extends considerably the class of source densities that can be used in exact estimation, and shows that strongly super-gaussian densities are as natural as Gaussian densities for these models. We also derive an adaptive Generalized Gaussian algorithm that learns the shape parameters of Generalized Gaussian mixture components. Experiments verify the validity of the algorithm.
Developing cuprous oxide thin film characterization techniques to illuminate efficiency-limiting mechanisms in photovoltaic applications

Future fossil fuel scarcity and environmental degradation have demonstrated the need for renewable, low-carbon sources of energy to power an increasingly industrialized world. Solar energy, with its extraordinary resource base, is one of the most feasible long-term options for satisfying energy demand with minimal environmental impact. However, solar photovoltaic panels remain expensive and employ materials whose resource bases cannot satisfy global, terawatt-level penetration. This necessitates the development of cheap, earth-abundant semiconductors for solar conversion such as cuprous oxide (Cu2O). Poor solar energy conversion efficiency (<2%) has hindered the development of this material, yet it is not well understood what is preventing the material from approaching the idealized maximum efficiency of 20%. The present work aims to develop a thorough characterization method for Cu2O thin films fabricated through a physical vapor deposition (PVD) process known as reactive direct-current magnetron sputtering. This both provides a platform for material analysis and an opportunity to adapt a typically high-throughput manufacturing method to make high quality thin films. Spectrophotometry, Hall Effect mobility measurement, and photoelectrochemical cell techniques are used in succession to determine the absorption and transport properties. The films are found to have a direct forbidden bandgap of 1.93 eV, with an absorption coefficient of greater than 10 cm for photons carrying energy in excess of 2.6 eV. Majority carrier mobility is measured as 58.1 cm/V⋅s, approaching the levels of monocrystalline oxidized films in literature. These high mobilities indicate that with carrier lifetime >10 nanoseconds, minority carrier diffusion length could easily exceed the film thickness. The photoelectrochemical minority carrier diffusion length measurement achieves success on gallium arsenide test samples, determining flat-band potential, quantum efficiency, and minority carrier diffusion length, paving the way for future Cu2O measurement. Future work may apply this test procedure to fully characterize other materials, and eventually lead to solar cell fabrication. Thesis Supervisor: Tonio Buonassisi Title: SMA Assistant Professor of Mechanical Engineering and Manufacturing
A duplicate address resolution protocol in mobile ad hoc networks

In an IP-based network, automated dynamic assignment of IP addresses is preferable. In most wired networks, a node relies on a centralized server by using dynamic host configuration protocol (DHCP) to obtain a dynamic IP address. However, the DHCP-based approach cannot be employed in a mobile ad hoc network (MANET) due to the uncertainty of any centralized DHCP server. That is, a MANET may become partitioned due to host mobility. Therefore, there is no guarantee to access a DHCP server. A general approach to address this issue is to allow a mobile host to pick a tentative address randomly, and then use duplicate address resolution (DAR) protocol to resolve any duplicate addresses. In this paper, an innovative distributed dynamic host configuration protocol designed to configure nodes in MANET is presented. The proposed protocol not only can detect the duplicate address, but also can resolve the problem caused by duplicate address. It shows that the proposed protocol works correctly and is more universal than earlier approaches. An enhanced version of DAR scheme is also proposed in this paper to solve the situation of duplicate MAC address. The new and innovative approach proposed in this paper can make the nodes in MANET provide services to other networks and avoid packets from being delivered to incorrect destinations.
The Effect of Single-Leg Stance on Dancer and Control Group Static Balance

The purpose of this study was to compare kinetic differences of static balance between female dancers (D) with at least seven years of dance experience and female non-dancers (ND) who were typical college students. Participants were tested in single-leg stance. Both the dominant leg (DL) and non-dominant leg (NDL) were tested with the participants shod (S) and barefoot (BF). Kinetic variables (vertical, medio-lateral [ML], antero-posterior [AP] maximum ground reaction forces (GRF), and center of pressure (COP) ML and AP) were measured by a Bertec force platform at 1000 Hz with participants S and BF. Each subject’s stance was measured over 3 × 30-second intervals. No significant differences (p≥0.05) existed between groups for height, body mass, or age. Significant differences existed between groups for balance time, AP GRF in both BF and S conditions for both DL and NDL, and ML GRF in BF NDL and S DL and NDL conditions. D and ND in BF and S conditions with DL and NDL static stance demonstrate different AP and ML GRF when balancing over a 30-second time interval. Data may suggest that ND are more prone to lose their balance. Further investigation is warranted to understand whether individuals in the rehabilitative field and athletic populations can use dance therapy for injury prevention and rehabilitation.
On Sensor Frameworks for Pervasive Systems

We believe an important part of any pervasive or wearable computing environment is an infrastructure for selecting and employing various sensors into an effective pervasive system. Without a uniform framework, researchers need to design their own ad-hoc structures and there is no common ground for system comparison and evaluation. Thus, our focus is on formulating a framework that can be used to support pervasive computing using sensors systematically. In this paper in particular, we address some of the fundamental issues in applying sensing and tracking to pervasive environments.
2016 Third International Conference on Information Retrieval and Knowledge Management Prediction of Rating from Comments Based on Information Retrieval and Sentiment Analysis

—The number of users of an on-line shopping websites is continuously increasing. Such website often provides facility for the users to give comments and ratings to the products being sold on the websites. This information can be useful as the recommendation for other users in making their purchase decision. This paper investigates the problem of predicting rating based on users' comments. A classifier based on information retrieval model is proposed for the prediction. In addition, the effect of integrating sentiment analysis for the rating prediction is also investigated. Based on the results, an improvement in prediction performance can be expected with sentiment analysis where an increase of 54% is achieved.
Associations between socioeconomic status and hunting license sales among census tracts in Cook County, Illinois

ABSTRACT Hunting license sales have declined in many U.S. states over recent decades, and efforts are underway to recruit new hunters. Research suggests socioeconomic status influences hunting participation and license sales. A limited number of studies, however, actually connect socioeconomic status and license sales on an aggregated community level or spatial context. This article examined relationships between socioeconomic factors and hunting license sales in Cook County, Illinois. A principal component analysis is used to create indices aggregating census tract socioeconomic indicators. Spatial and statistical analyses using both linear regression and multinomial logistic regression explored relationships between indices and percentage of license sales for each census tract. Spatial correlation and quantitative relationships were found between the indices and hunting license sales. Models developed through this study may provide current state hunter recruitment programs with an understanding of the interaction of socioeconomic factors and hunting license sales.
Guest Editorial: Challenges and Perspectives for Affective Analysis in Multimedia

THERE has been an increasing interest in the research on multimedia indexing and retrieval based on subjective concepts, such as emotion, preference and aesthetics. The research efforts in this direction are considered human-centered and beyond the conventional keywordor (semantic) object-based multimedia analysis paradigm [1]. In addition, the problems addressed by these efforts are considered challenging since they require multidisciplinary understanding of human behavior and perception as well as multimodal approaches integrating different modalities, e.g., audio, visual and text, to reach an acceptable level of performance. In addition to the multimedia content and to better take into account the human factors, users’ spontaneous responses, either explicit (e.g., rating) or implicit (laughing, gaze direction, physiological responses) are increasingly also integrated as input in such approaches. This special section focuses on affective analysis of multimedia, that is, the analysis focusing on estimating the expected emotional state of the user when interacting with multimedia content. The result of such analysis can enhance multimedia retrieval and recommendation systems by adding the emotion-related factor into the assessment of the appropriateness of the content for the user [2]. The mission of the special section is to provide a view at the state-of-the-art in this domain and point to the potentially interesting future research directions. It therefore features articles concerning multimedia affective understanding from different perspectives, including predicting likability and emotions from users’ responses [3], [4], content analysis for music affective understanding [5], [6], [7], visual content analysis for aesthetics and emotional understanding [8], [9], [10], and an application for sentiment analysis [11]. In response to an open call for our special section, we initially received 35 submissions [4], [10] from which we accepted nine original articles. In the next section, we summarize the articles and their key findings. In the final section, we summarize the challenges for future research on affective analysis in multimedia.
Structural analysis of the yeast Dhh1–Pat1 complex reveals how Dhh1 engages Pat1, Edc3 and RNA in mutually exclusive interactions

Translational repression and deadenylation of eukaryotic mRNAs result either in the sequestration of the transcripts in a nontranslatable pool or in their degradation. Removal of the 5′ cap structure is a crucial step that commits deadenylated mRNAs to 5′-to-3′ degradation. Pat1, Edc3 and the DEAD-box protein Dhh1 are evolutionary conserved factors known to participate in both translational repression and decapping, but their interplay is currently unclear. We report the 2.8 Å resolution structure of yeast Dhh1 bound to the N-terminal domain of Pat1. The structure shows how Pat1 wraps around the C-terminal RecA domain of Dhh1, docking onto the Phe-Asp-Phe (FDF) binding site. The FDF-binding site of Dhh1 also recognizes Edc3, revealing why the binding of Pat1 and Edc3 on Dhh1 are mutually exclusive events. Using co-immunoprecipitation assays and structure-based mutants, we demonstrate that the mode of Dhh1-Pat1 recognition is conserved in humans. Pat1 and Edc3 also interfere and compete with the RNA-binding properties of Dhh1. Mapping the RNA-binding sites on Dhh1 with a crosslinking–mass spectrometry approach shows a large RNA-binding surface around the C-terminal RecA domain, including the FDF-binding pocket. The results suggest a model for how Dhh1-containing messenger ribonucleoprotein particles might be remodeled upon Pat1 and Edc3 binding.
Model Based Segmentation of Clinical Knee MRI

A method for model based segmentation of 3D Magnetic Resonance Imaging (MRI) scans of the human knee is presented. A probabilistic model describing the spatial relationships between features of the human knee is constructed from 3D manually segmented data. In conjunction with feature detection techniques from low-level computer vision, this model is used to segment knee MRI scans in a Bayesian
MODELING AND DYNAMIC ANALYSIS OF ATOMIC FORCE MICROSCOPE BASED ON EULER-BERNOULLI BEAM THEORY

Operation of atomic force microscope in dynamic mode has received great attention due to its ability to image compliant materials and also due to the fact that it can prevent the tip and sample damages during scanning. In this paper a model is proposed for AFM microcantilever-tip system based on Euler-Bernoulli beam theory and is solved numerically in order to study the behavior of a continuous cantilever beam in dynamic mode subject to changes in tip mass, cantilever density, length and the interaction force between the cantilever-tip and the sample. This is accomplished by linearizing the surface coupling force.
Anfis based a two-phase interleaved boost converter for photovoltaic system

In this paper, A two-phase interleaved boost converter (IBC), which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for photovoltaic (PV) system is proposed. The proposed system has two inputs and 1 output. Two inputs of the proposed system consist of solar irradiation and temperature. Meanwhile, the output of the proposed system is aduty cycle. The duty cycle is used to generate Pulsed Width Modulation (PWM), which serves to activate MOSFET. Furthermore, the proposed ANFIS features 20 epochs and utilizes hybrid mechanism to train data. Some simulations of IBC combined with PV system have been performed using Matlab/SIMULINK. Furthermore, some comparisons of two different methods have been carried out to validate the results. The comparison analysis results indicate that the system using ANFIS can obtain higher voltage than the system using FLC. In addition, the proposed system is also able to reduce overshoot and be able to increase the output power.
OnboardICNg: a Secure Protocol for On-boarding IoT Devices in ICN

Information-Centric Networking (ICN) is an emerging networking paradigm that focuses on content distribution and aims at replacing the current IP stack. Implementations of ICN have demonstrated its advantages over IP, in terms of network performance and resource requirements. Because of these advantages, ICN is also considered to be a good network paradigm candidate for the Internet-of-Things (IoT), especially in scenarios involving resource constrained devices. In this paper we propose OnboardICNg, the first secure protocol for on-boarding (authenticating and authorizing) IoT devices in ICN mesh networks. OnboardICNg can securely onboard resource constrained devices into an existing IoT network, outperforming the authentication protocol selected for the ZigBee-IP specification: EAP-PANA, i.e., the Protocol for carrying Authentication for Network Access (PANA) combined with the Extensible Authentication Protocol (EAP). In particular we show that, compared with EAP-PANA, OnboardICNg reduces the communication and energy consumption, by 87% and 66%, respectively.