Miracle-dz/UniFAR-FTUs huggingface dataset:
Speaking Your Mind Without Elections, Surveys, or Social Movements

WHEN Paul Lazarsfeld gave his 1950 presidential address to the American Association for Public Opinion Research, he made his topic "The Obligations of the 1950 Pollster to the 1984 Historian. " In that characteristically wide-ranging talk, Lazarsfeld closed in on a simple but important point: Historians' explanations of social behavior often depend on imputations of attitudes to crucial actors, yet they usually have weaker evidence concerning attitudes than any other feature of their accounts. The pollster of 1950, said Lazarsfeld, being a specialist in the systematic documentation of attitudes, could greatly strengthen the position of future historians. "If for a given period we not only know the standard of living, but also the distribution of ratings on happiness and personal adjustment," he said, "the dynamics of social change will be much better understood" (Lazarsfeld, 1982:94). By 1984, Lazarsfeld thought, instead of the constant obliteration of the past described in George Orwell's totalitarian nightmare, we might have a kind of social bookkeeping that would integrate behaviors and attitudes into a better understanding of social change. The analysis of public opinion, he suggested, might even become a predictive science, a science of sentiments (Lazarsfeld, 1982:95).
Critical node lifetimes in random networks via the chen-stein method

This paper considers networks where nodes are connected randomly and can fail at random times. It provides scaling laws that allow to find the critical time at which isolated nodes begin to appear in the system as its size tends to infinity. Applications are in the areas of sensor and ad-hoc networks where nodes are subject to battery drainage and 'blind spots' formation becomes a primary concern. The techniques adopted are based on the Chen-Stein method of Poisson approximation, which allows to obtain elegant derivations that are shown to improve upon and simplify previous related results that appeared in the literature. Since blind spots are strongly related to full connectivity, we also obtain some scaling results about the latter
Abundance of Two Pelagibacter ubique Bacteriophage Genotypes along a Latitudinal Transect in the North and South Atlantic Oceans

This study characterizes viral and bacterial dynamics along a latitudinal transect in the Atlantic Ocean from approximately 10 N–40 S. Overall viral abundance decreased with depth, on average there were 1.64 ± 0.71 × 107 virus like particles (VLPs) in surface waters, decreasing to an average of 6.50 ± 2.26 × 105 VLPs in Antarctic Bottom Water. This decrease was highly correlated to bacterial abundance. There are six major water masses in the Southern Tropical Atlantic Ocean, and inclusion of water mass, temperature and salinity variables explained a majority of the variation in total viral abundance. Recent discovery of phages infecting bacteria of the SAR11 clade of Alphaproteobacteria (i.e., pelagiphages) leads to intriguing questions about the roles they play in shaping epipelagic communities. Viral-size fraction DNA from epipelagic water was used to quantify the abundance of two pelagiphages, using pelagiphage-specific quantitative PCR primers and probes along the transect. We found that HTVC010P, a member of a podoviridae sub-family, was most abundant in surface waters. Copy numbers ranged from an average of 1.03 ± 2.38 × 105 copies ml−1 in surface waters, to 5.79 ± 2.86 × 103 in the deep chlorophyll maximum. HTVC008M, a T4-like myovirus, was present in the deep chlorophyll maximum (5.42 ± 2.8 × 103 copies ml−1 on average), although it was not as highly abundant as HTVC010P in surface waters (6.05 ± 3.01 × 103 copies ml−1 on average). Interestingly, HTVC008M was only present at a few of the most southern stations, suggesting latitudinal biogeography of SAR11 phages.
Can a Psychological Theory of Ideological Differences Explain Contextual Variability in the Contents of Political Attitudes?

In this brief reply, we explore the ways in which a psychological theory of ideology as motivated social cognition (e.g., Jost, Glaser, Kruglanski, & Sulloway, 2003a, 2003b) can explain several distinct but related empirical phenomena, including why (a) epistemic and existential needs to reduce uncertainty and threat would be positively associated with social or cultural conservatism in virtually all societal contexts and yet be associated with support for either capitalism or socialism, depending upon the local context; (b) conservatives eventually come to support policy positions that were once considered to be liberal or progressive; (c) liberals are more likely than conservatives to exhibit cognitive complexity and engage in “value trade-offs” between equality and freedom; and (d) time pressure and cognitive load produce “conservative shifts” in political opinion, even among liberal respondents. By clarifying the similarities and differences between the two core dimensions of Left–Right ideology (i.e., advocating vs. resisting social change and rejecting vs. accepting inequality) and highlighting the role of status quo acceptance in conservative ideology, we hope to demonstrate that a psychological theory of Left–Right differences can account for contextual variability in the contents of political attitudes.
Interpersonal modification in the English noun phrase

This article gives an overview of the various interpersonal modifiers in the English noun phrase, several of which seem to have been overlooked in formal as well as functional grammars. On the theoretical side, this article is concerned with how to bring the constructions at issue under a Functional Discourse Grammar representation (Hengeveld and Mackenzie 2006, in prep.).
Collection and storage of human blood and adipose for genomic analysis of clinical samples.

In this methods article, we describe collection and storage of clinically acquired blood and adipose samples for transcript analysis in an ongoing study exploring obesity in renal transplant recipients. Total ribonucleic acid (RNA) was isolated from whole blood using the LeukoLOCK™ Total RNA Isolation System (n = 4), and comparisons between fresh and frozen samples were made. Abdominal subcutaneous adipose samples (n = 4) were obtained during kidney transplantation, flash frozen, and stored at -80°C. Adipose RNA was extracted using either the STAT-60 method modified for lipids or Trizol plus RNeasy extraction. Affymetrix HG-U133 plus 2.0 arrays and Affymetrix Human Gene 1.0 ST arrays were used for both blood and adipose transcriptome analysis. Purity, quality, and quantity of RNA were high with comparable results using both array platforms.
The Product Cut

We introduce a theoretical and algorithmic framework for multi-way graph partitioning that relies on a multiplicative cut-based objective. We refer to this objective as the Product Cut. We provide a detailed investigation of the mathematical properties of this objective and an effective algorithm for its optimization. The proposed model has strong mathematical underpinnings, and the corresponding algorithm achieves state-of-the-art performance on benchmark data sets.
A task-oriented agent-based mechanism for mathematical assistant systems

We present an agent-based mechanism that acts as a mediator module between theorem proving systems and mathematical knowledge bases containing information that is necessary for the constructions of proofs. Unlike the more popular user-oriented mediators who work as information agents to provide the so-called value-added services to the collected data before presenting it to users or user applications, our (multi-) agents are more task-oriented. That is, our agents work in tandem with the user or user application on the tasks the user is trying to solve. This approach is particularly suitable to mathematical knowledge retrieval in theorem proving as (i) checking for applicable axioms/definitions/theorems from the knowledge base can be done independently from the proof search process concurrently carried out by the prover, and (ii) the prover and the mediator operate on two different search spaces and the search outcome brought about by the mediator can be of great benefit to the prover, e.g. to avoid the prover from exploring many unnecessary or irrelevant proof steps, to keep the prover's search space more manageable and the constructed proof more comprehensible.
The World’s First Real-Time Testbed for Massive MIMO: Design, Implementation, and Validation

This paper sets up a framework for designing a massive multiple-input multiple-output (MIMO) testbed by investigating hardware (HW) and system-level requirements, such as processing complexity, duplexing mode, and frame structure. Taking these into account, a generic system and processing partitioning is proposed, which allows flexible scaling and processing distribution onto a multitude of physically separated devices. Based on the given HW constraints such as maximum number of links and maximum throughput for peer-to-peer interconnections combined with processing capabilities, the framework allows to evaluate modular HW components. To verify our design approach, we present the Lund University Massive MIMO testbed, which constitutes the first reconfigurable real-time HW platform for prototyping massive MIMO. Utilizing up to 100 base station antennas and more than 50 field programmable gate array, up to 12 user equipment are served on the same time/frequency resource using an LTE-like orthogonal frequency division multiplexing time-division duplex-based transmission scheme. Proof-of-concept tests with this system show that massive MIMO can simultaneously serve a multitude of users in a static indoor and static outdoor environment utilizing the same time/frequency resource.
Efficient adaptive failure detection for Query/Response based wireless sensor networks

We consider the problem of failure management in wireless sensor networks (WSN). In such networks, nodes can be subject to frequent failures due to energy depletion and the hostile deployment environment. Our work focuses on local crash process detection in WSN considering intermittent failures due to lossy radio links. As a part of this problem, we introduce a new type of Adaptive Neighborhood Failure Detection mechanism (ANFD) that relies on adaptive timers. Then we analyze properties of the introduced failure detection algorithm and determine how and when timers' update is necessary. We carried out intensive simulations using TinyOS-2 and evaluated the performance of our solution. Simulation results show that our solution improves failure detection rate and delay, and reduces fault positive detections and packet loss ratio. Moreover, we analyzed energy consumption using PowerTossimZ and results demonstrate that our solution does not induce extra energy consumption compared to other solutions in the literature.
Active Sensing

Labels are often expensive to get, and this motivates active learning which chooses the most informative samples for label acquisition. In this paper we study active sensing in a multi-view setting, motivated from many problems where grouped features are also expensive to obtain and need to be acquired (or sensed) actively (e.g., in cancer diagnosis each patient might go through many tests such as CT, Ultrasound and MRI to get valuable features). The strength of this model is that one actively sensed (sample, view) pair would improve the joint multi-view classification on all the samples. For this purpose we extend the Bayesian co-training framework such that it can handle missing views in a principled way, and introduce two criteria for view acquisition. Experiments on one toy data and two real-world medical problems show the effectiveness of this model.
Ellerman's Labor Theory of Property and the Injustice of Capitalist Exploitation

The traditional Marxian arguments for the injustice of capitalist exploitation generally focus on the ownership patterns of productive property. Exploitation is thus viewed either as the result of illegitimate private ownership or as the result of the unequal distribution of productive assets. This paper seeks to contribute a different perspective on the injustice of exploitation. It argues that exploitation violates principles of appropriative and contractual justice, rather than distributive justice. To make this case, the paper shows how Ellerman's labor theory of property might be combined with Resnick and Wolff's Marxian theory of exploitation and enriched by Nussbaum's interpretation of Aristotelian moral theory to challenge the justice of the wage-for-labor-time exchange, without making reference to the existence or distribution of private property.
Examining the Relationships Between Resources and Online Health Information Seeking Among Patients With Chronic Diseases and Healthy People

The Internet is increasingly used as an important source of health and medical-related information for people with chronic diseases. It is recognized that online health information seeking (OHIS) is influenced by individuals’ multi-dimensional factors, such as demographics, socio-economic factors, perceptions of the Internet, and health conditions. This study applies the conservation of resource theory to examine relationships between various multi-dimensional factors, daily challenges, and OHIS depending on individuals’ health conditions. The data used in this study was taken from the U.S. Health Tracking Survey (2012). In this study, Internet users aged 18 and older were classified into patients (N = 518) and healthy people (N = 677) based on their health status related to chronic diseases. Multiple regression analysis was used to examine the relationships between multi-dimensional factors (resources), self-rated health, and OHIS. Patients’ various resources (e.g., age, income, education, having a smartphone, and health tracking) significantly predicted their self-rated health and OHIS; in addition, self-rated health significantly mediated the relationships between focal resources and OHIS. However, the mediating effects of self-rated health were not found in healthy people.
Dynamic shading enhancement for reflectance transformation imaging

We propose a set of dynamic shading enhancement techniques for improving the perception of details, features, and overall shape characteristics from images created with Reflectance Transformation Imaging (RTI) techniques. Selection of these perceptual enhancement filters can significantly improve the user's ability to interactively inspect the content of 2D RTI media by zooming, panning, and changing the illumination direction. In particular, we present two groups of strategies for RTI image enhancement based on two main ideas: exploiting the unsharp masking methodology in the RTI-specific context; and locally optimizing the incident light direction for improved RTI image sharpness and illumination of surface features. The Result section will present a number of datasets and compare them with existing techniques.
Not Excluded From Analyses

Because research on ethnic-racial identity development largely excludes multiethno-racial youth, we used a mixed-methods approach to examine ethno-racial meanings and identification among 102 early adolescents (M = 11.45, SD = 0.70 years) with multiethno-racial (n = 45), mono-majority (i.e., European American; n = 29), or mono-minority (e.g., Latino, African American; n = 28) heritage. Results indicated more similarity than difference between multiethno-racial and mono-minority youth—most understood their heritage through tangible connections (e.g., language). Social (e.g., stereotypes) and individual (e.g., pride) meanings of ethno-racial heritage were also discussed. Last, we observed that most multiethno-racial youth identified with either one (53.3%) or all components of their heritage (35.6%), and these identification choices were linked to tangible experiences (e.g., travel or language proficiency). Developmental and contextual reasons for these findings are discussed.
A Novel Semantic Smoothing Method Based on Higher Order Paths for Text Classification

It has been shown that Latent Semantic Indexing (LSI) takes advantage of implicit higher-order (or latent) structure in the association of terms and documents. Higher order relations in LSI capture "latent semantics". Inspired by this, a novel Bayesian framework for classification named Higher Order Naïve Bayes (HONB), which can explicitly make use of these higher-order relations, has been introduced previously. We present a novel semantic smoothing method named Higher Order Smoothing (HOS) for the Naive Bayes algorithm. HOS is built on a similar graph based data representation of HONB which allows semantics in higher order paths to be exploited. Additionally, we take the concept one step further in HOS and exploited the relationships between instances of different classes in order to improve the parameter estimation when dealing with insufficient labeled data. As a result, we have not only been able to move beyond instance boundaries, but also class boundaries to exploit the latent information in higher-order paths. The results of our extensive experiments demonstrate the value of HOS on several benchmark datasets.
An Evaluation of the Nokomis Challenge Program in Michigan

The Nokomis Challenge Program is an innovative correctional program, run by the Michigan Department of Social Services (DSS), which combines 3 months of residence and programming in a remote wilderness setting with 9 months of intensive community-based aftercare. RAND is evaluating the impact of the Nokomis program under grants from the National Institute of Justice and DSS. This article describes the various elements of the Nokomis program and presents data on the characteristics of youth in the experimental and comparison samples.
Credit Rationing, Wealth Inequality, and Allocation of Talent

We study an economy where agents are heterogeneous in terms of observable wealth and unobservable talent. Adverse selection forces creditors to ask for collateral. We study the two-way interaction between rationing in the credit market and the wages offered in the labour market. Both pooling and separating credit contracts can be offered in equilibrium. The minimum wealth needed to obtain a separating contract is decreasing in the wage, whereas the minimum wealth needed for a pooling contract is increasing in the wage. If the first effect dominates, the derived labour demand can be upward sloping, resulting in the possibility of multiple equilibria.
Brain-inspired computing with spin torque devices

In this paper we discuss the potential of emerging spin-torque devices for computing applications. Recent proposals for spin-based computing schemes may be differentiated as `all-spin' vs. hybrid, programmable vs. fixed, and, Boolean vs. non-Boolean. Allspin logic-styles may offer high area-density due to small form-factor of nano-magnetic devices. However, circuit and system-level design techniques need to be explored that leaverage the specific spin-device characterisitcs to achieve energy-efficiency, performance and reliability comparable to those of CMOS. The non-volatility of nano-magnets can be exploited in the design of energy and area-efficient programmable logic. In such logic-styles, spin-devices may play the dual-role of computing as well as memory-elements that provide field-programmability. Spin-based threshold logic design is presented as an example. Emerging spintronic phenomena may lead to ultra-low-voltage, current-mode, spin-torque switches that can offer attractive computing capabilities, beyond digital switches. Such devices may be suitable for non-Boolean data-processing applications which involve analog processing. Integration of such spin-torque devices with charge-based devices like CMOS and resistive memory can lead to highly energy-efficient information processing hardware for applicatons like pattern-matching, neuromorphic-computing, image-processing and data-conversion. Finally, we discuss the possibility of using coupled spin-torque nano oscillators for low-power non-Boolean computing.
Variable reordering for a parallel envelope method

We use a parallel direct solver based on the Schur complement method for solving large sparse linear systems arising from the finite element (FE) method. A FE mesh is decomposed into the submeshes by a domain decomposition method. The submatrices formed from the submeshes consist of internal and boundary variables. The internal variables are factorized by an envelope method. Prior to the solution, the variables of each submatrix are reordered to minimize the size of its envelope. The boundary variables are ordered last. The Sloan algorithm is used to perform the reordering, but it does not distinguish between internal and boundary variables. We discuss issues of reordering variables in submatrices and introduce a modified version of the Sloan algorithm that takes the boundary variables into consideration . Experiments on 2 sets of benchmarks show that submatrices produced by the proposed modified Sloan algorithm have profiles smaller by approximately 15%. The new reordering algorithm improved the time of solving FE problems with a parallel envelope solver using a standard domain decomposition method by 23%.
Effects of metabolic syndrome on kidney transplantation outcomes: a systematic review and meta‐analysis

Metabolic syndrome (MS) has been associated with proteinuria and reduced glomerular filtration rate. Immunosuppressive agents increase the incidence of traditional risk factors for cardiovascular disease (CVD) and have known effects on MS components after kidney transplantation. The purpose of this meta‐analysis was to evaluate the impact of MS on relevant outcomes after kidney transplantation. MEDLINE, EMBASE, and Cochrane Library were searched up to November 7, 2015. Papers that compared patients with and without MS and assessed one of the following outcomes, graft loss, death by cardiovascular disease, and all‐cause mortality, were included. Of 585 studies identified, five studies including 1269 patients were evaluated. MS was identified as a risk factor for graft loss [relative risk, 3.06; 95% confidence interval (CI), 2.17, 4.32; I² = 0%; P heterogeneity = 0.72] and death by CVD (relative risk, 3.53; 95% CI, 1.27, 9.85; I² = 0%; P heterogeneity = 0.40). Results on the association between MS and all‐cause mortality were inconclusive (relative risk, 2.61; 95% CI, 0.70, 9.81; I² = 58%; P heterogeneity = 0.09). Graft loss and death by CVD were associated with the presence of MS after transplantation. Randomized clinical trials should be conducted to define whether interventions on each MS component would result in better outcomes after transplantation.
Storytelling in a digital age: digital storytelling as an emerging narrative method for preserving and promoting indigenous oral wisdom

This article outlines the methodological process of a transdisciplinary team of indigenous and nonindigenous individuals, who came together in early 2009 to develop a digital narrative method to engage a remote community in northern Labrador in a research project examining the linkages between climate change and physical, mental, emotional, and spiritual health and well-being. Desiring to find a method that was locally appropriate and resonant with the narrative wisdom of the community, yet cognizant of the limitations of interview-based narrative research, our team sought to discover an indigenous method that united the digital media with storytelling. Using a case study that illustrates the usage of digital storytelling within an indigenous community, this article will share how digital storytelling can stand as a community-driven methodological strategy that addresses, and moves beyond, the limitations of narrative research and the issues of colonization of research and the Western analytic project. In so doing, this emerging method can preserve and promote indigenous oral wisdom, while engaging community members, developing capacities, and celebrating myriad stories, lived experiences, and lifeworlds.