Miracle-dz/UniFAR-FTUs huggingface dataset:
Stages of Behavioral Change for Physical Activity in High School Students

The aim was to estimate the prevalence of stages of change for physical activity and associated sociodemographic factors in students. The sample consisted of 942 students (44.7% males, 55.3% females; mean age = 16.1 years, SD = 1.1) in southern Brazil. Self-administered questionnaire was applied to identify stages of behavioral change for physical activity and sociodemographic variables (gender, age, maternal schooling, economic status, and school shift). Multinomial logistic regression was used to estimate the odds ratio (95%). Results showed that 9.6% were in the pre-contemplation stage, 18.4% in the contemplation, 17.6% in the preparation, 14.3% in the action, and 39.6% in the maintenance stages. Girls and adolescents with lower economic status were more likely to be at stages of behavioral risk. Students whose mothers had high education were more likely to be in the action stage.
The Factorial Structure of Teacher Work Values1

i. A summary report of sections of this paper was presented to the American Educational Research Association convention, Chicago, February 8, 1968. The author gratefully acknowledges the advice and assistance he received from Michael P. Burns, Robert W. Pranis, Donna J. Mohrsback, and Jane C. Shipp in carrying out this study. He would also like to express his appreciation to B. J. Chandler, B. Claude Mathis, and Robert Maidment for their comments on an earlier draft of the report from which this paper was drawn.
Serum Cystatin C can detect impaired graft function early after renal transplantation.

OBJECTIVES To study the significance of Cystatin C (Cys C) in early detection of the graft function after renal transplantation. MATERIAL The concentrations of Cys C, Blood urea nitrogen (BUN), Serum creatinine (SCr), and glomerular filtration rate (GFR) were measured. According to the results of the post-transplantation GFR; Seventy renal post-transplanted patients were assigned into 3 groups: group A (31 cases with the normal range of the renal function, GFR≥90 ml/min/1.73 m(2)), group B (27 cases with Scr<133 μmol/L and 60<GFR<90 ml/min/1.73 m(2)), and group C (12 cases with Scr≥133 μmol/L and 60<Ccr<90 ml/min/1.73 m(2)). Meanwhile, 60 cases with normal renal function were applied as control group. RESULTS The Cys C concentration in group B (1.37±0.14) was significantly higher than it in group A (0.96±0.10) (P<0.01). The SCr and the Cys C demonstrated linear correlations with the GFR in all groups of A, B and C. The correlation coefficients (r) in each group were -0.7272 and -0.7439, -0.7072 and -0.7543, -0.7430 and -0.7669; respectively. CONCLUSIONS Compared with Scr, Cys C has better correlations with GFR when the graft function was normal or renal function was slightly impaired. Cys C could be used in the early detection of renal function impairment after transplantation.
Aspect-Based Instrumentation for Locating Memory Leaks in Java Programs

Despite the built-in garbage collector, Java programs can still suffer the memory leak problem resulted from the unhealthy programming style of retaining unwanted references. This paper presents an aspect-based tool for assisting programmers in locating such references to fix the problem. This tool, FindLeaks, utilizes an aspect to collect memory consumption statistics and object references created during a program's execution and analyzes them for detecting memory leaks. The distinctive feature of FindLeaks is that it reports not only suspected classes of leaking objects but also where in the source the unwanted references were created. Besides, this paper also reports some preliminary experience with FindLeaks.
An Efficient Prediction-Based User Recruitment for Mobile Crowdsensing

Mobile crowdsensing is a new paradigm in which a group of mobile users exploit their smart devices to cooperatively perform a large-scale sensing job. One of the users’ main concerns is the cost of data uploading, which affects their willingness to participate in a crowdsensing task. In this paper, we propose an efficient Prediction-based User Recruitment for mobile crowdsEnsing (PURE), which separates the users into two groups corresponding to different price plans: Pay as you go (PAYG) and Pay monthly (PAYM). By regarding the PAYM users as destinations, the minimizing cost problem goes to recruiting the users that have the largest contact probability with a destination. We first propose a semi-Markov model to determine the probability distribution of user arrival time at points of interest (PoIs) and then get the inter-user contact probability. Next, an efficient prediction-based user-recruitment strategy for mobile crowdsensing is proposed to minimize the data uploading cost. We then propose PURE-DF by extending PURE to a case in which we address the tradeoff between the delivery ratio of sensing data and the recruiter number according to Delegation Forwarding. We conduct extensive simulations based on three widely-used real-world traces: roma/taxi, epfl, and geolife. The results show that, compared with other recruitment strategies, PURE achieves a lower recruitment payment and PURE-DF achieves the highest delivery efficiency.
The Effects of Neighborhood Disadvantage on Adolescent Development

A conceptual framework for studying emerging neighborhood effects on individual development is presented, identifying specific mechanisms and processes by which neighborhood disadvantage influences adolescent developmental outcomes. Using path analyses, the authors test the hypothesis that these organizational and cultural features of neighborhoods mediate the effects of ecological disadvantage on adolescent development and behavior; they then estimate the unique contribution of neighborhood effects on development using hierarchical linear modeling (HLM). The study involves samples of neighborhoods from two sites, Chicago and Denver. The analyses support the hypothesis that the effects of ecological disadvantage are mediated by specific organizational and cultural features of the neighborhood. The unique influence of neighborhood effects is relatively small, but in most cases these effects account for a substantial part of the variance explained by the HLM model.
Methodologies for Qualitative Spatial and Temporal Reasoning Application Design

Although a wide range of sophisticated qualitative spatial and temporal reasoning (QSTR) formalisms have now been developed, there are relatively few applications that apply these commonsense methods. To address this problem we are developing methodologies that support QSTR application design. We establish a theoretical foundation for QSTR applications that includes the roles of application designers and users. We adapt formal software requirements that allow a designer to specify the customer’s operational requirements and the functional requirements of a QSTR application. We present design patterns for organising the components of QSTR applications, and a methodology for defining high level neighbourhoods that are derived from the system structure. Finally, we develop a methodology for QSTR application validation by defining a complexity metric called H-complexity that is used in test coverage analysis for assessing the quality of unit and integration test sets.
Localizing the Final Gathering for Dynamic Scenes using the Photon Map

Rendering of high quality animations with global illumination effects is very costly using traditional techniques designed for static scenes. In this paper we present an extension of the photon mapping algorithm to handle dynamic environments. First, for each animation segment the static irradiance cache is computed only once for the scene with all dynamic objects removed. Then, for each frame, the dynamic objects are inserted and the irradiance cache is updated locally in the scene regions whose lighting is strongly affected by the objects. In the remaining scene regions the photon map is used to correct the irradiance values in the static cache. As a result the overall animation rendering efficiency is significantly improved and the temporal aliasing is reduced.
Characterizing the rate-memory tradeoff in cache networks within a factor of 2

We consider a basic caching system, where a single server with a database of N files (e.g. movies) is connected to a set of K users through a shared bottleneck link. Each user has a local cache memory with a size of M files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the bottleneck link. We characterize the rate-memory tradeoff of the above caching system within a factor of 2.00884 for both the peak rate and the average rate (under uniform file popularity), where the best proved characterization in the current literature gives a factor of 4 and 4.7 respectively. Moreover, in the practically important case where the number of files (N) is large, we exactly characterize the tradeoff for systems with no more than 5 users, and characterize the tradeoff within a factor of 2 otherwise. We establish these results by developing novel information theoretic outer-bounds for the caching problem, which improves the state of the art and gives tight characterization in various cases.
M-VCR: Multi-View Consensus Recognition for Real-Time Experimentation

A major application area in the computer vision domain is gesture recognition, requiring real-time image classification to respond to human interactions. However, current state-of-the-art high-quality algorithms for image classification do not meet many dynamic real-time requirements. This paper presents the development of M-VCR - a novel approach for improving the reliability of real-time image classification. M-VCR increases the quality of classifications under real-time constraints through the adoption of fast classification algorithms, although these algorithms individually produce lower quality results, utilisation under a 'consensus' approach can achieve results equivalent to those of much higher-quality algorithms. The proposed approach also allows for different algorithms to be utilised in parallel, building on the fault tolerance technique of N-versioning. A significant improvement in image classification is experimentally demonstrated for both the SURF and MSER feature detectors through our integration consensus approach. This improvement is delivered entirely through the integration method without requiring modification of the source algorithms being used.
Aspergillus fumigatus-specific antibodies in allergic bronchopulmonary aspergillosis and aspergilloma: evidence for a polyclonal antibody response

Patients with the Aspergillus-induced diseases allergic bronchopulmonary aspergillosis (ABPA), aspergilloma (fungus ball), and Aspergillus skin test-positive asthma were differentiated immunologically by radioimmunoassay based on their total immunoglobulin E (IgE) and Aspergillus fumigatus-specific IgE levels. In this study, a new, highly sensitive biotin-avidin-linked immunosorbent assay was used to evaluate A. fumigatus-specific antibodies of all immunoglobulin classes. Studied populations included 13 patients with ABPA, 12 with aspergilloma, 9 with Aspergillus skin test-positive asthma, and 9 normal individuals without asthma. A. fumigatus-specific antibodies of all classes were elevated in patients with ABPA, variably elevated in those with aspergilloma, and lowest in the other two groups. This assay demonstrated significantly higher specific IgE antibody levels in the ABPA group over those of the other groups, even with 1:1,000 dilutions of the sera. This study demonstrated that ABPA is a disease characterized by a polyclonal antibody response to Aspergillus antigen and not just a response to IgE and IgG antibody classes. The measurement of other antibody classes, particularly IgD and IgA, could enhance the immunodiagnosis of ABPA. The biotin-avidin-linked immunosorbent assay was found to be a highly sensitive assay that can be a clinically useful alternative to radioimmunoassay in the measurement of A. fumigatus-specific antibodies.
Tests of Statistical Methods for Estimating Galaxy Luminosity Function and Applications to the Hubble Deep Field

We study statistical methods for the estimation of the luminosity function (LF) of galaxies. We focus on four nonparametric estimators: the 1/Vmax estimator, the stepwise maximum-likelihood estimator, Chołoniewski's estimator, and the improved Lynden-Bell estimator. The performance of the 1/Vmax estimator has recently been questioned, especially for the faint-end estimation of the LF. We improve these estimators for studies of the distant universe, and examine their performances for various classes of functional forms by Monte Carlo simulations. We also apply these estimation methods to the mock Two-Degree Field (2dF) redshift survey catalog prepared by Cole et al. We find that the 1/Vmax estimator yields a completely unbiased result if there is no inhomogeneity, but is not robust against clusters or voids. This is consistent with the well-known results, and we do not confirm the bias trend of 1/Vmax claimed by Willmer in the case of a homogeneous sample. We also find that the other three maximum-likelihood type estimators are quite robust and give consistent results with each other. In practice, we recommend Chołoniewski's estimator for two reasons: (1) it simultaneously provides the shape and normalization of the LF; and (2) it is the fastest among these four estimators, because of its algorithmic simplicity. We then analyze the photometric redshift data of the Hubble Deep Field prepared by Fernández-Soto et al. using the above four methods. We also derive the luminosity density, ρL, at the B and I bands. Our B-band estimation is roughly consistent with that of Sawicki, Lin, & Yee, but it is a few times lower at 2.0 < z < 3.0. The evolution of ρL(I) is found to be less prominent.
Thinking beyond Homonormativity: Performative Explorations of Diverse Gay Economies

This paper performatively decentres the role of mainstream gay consumption in contemporary thought about the economic and social lives of lesbians and gay men in the Global North. It is simultaneously critical and reparative in outlook. This paper critically engages with recent writing on homonormativity, suggesting that this work presents ‘homonormativity’ as an all-encompassing structure that becomes politically unassailable. In parallel with an analysis of contemporary lesbian and gay life as being complicit in the reproduction of various normativities, this paper takes the innovative and reparative stance of considering how such spaces and practices also produce interdependent relationships across social difference. Drawing on the recent work of Gibson-Graham (2006, A Postcapitalist Politics University of Minnesota Press, Minneapolis, MN) this paper considers the prospects for outlining the diversity of lesbian and gay economic practices, with the performative ambition of making existing noncapitalist practices more visible and viable. To this end, the paper examines a number of gay spaces and practices to consider the different forms of enterprise, transactions, and labour that take place within them. On the basis of its preliminary inventory of diverse gay economic practices and spaces, this paper proposes that there are many aspects of contemporary urban gay life that already offer alternatives to the homonormative practices of neoliberalism.
Efficient Network Path Verification for Policy-routedQueries

Resource discovery in unstructured peer-to-peer networks causes a search query to be flooded throughout the network via random nodes, leading to security and privacy issues. The owner of the search query does not have control over the transmission of its query through the network. Although algorithms have been proposed for policy-compliant query or data routing in a network, these algorithms mainly deal with authentic route computation and do not provide mechanisms to actually verify the network paths taken by the query. In this work, we propose an approach to deal with the problem of verifying network paths taken by a search query during resource discovery, and detection of malicious forwarding of search query. Our approach aims at being secure and yet very scalable, even in the presence of huge number of nodes in the network.
Computing contextual metric thresholds

Software metrics have been developed to measure the quality of software systems. A proper use of metrics requires thresholds to determine whether the value of a metric is acceptable or not. Many approaches propose to define thresholds based on large analyses of software systems. However it has been shown that thresholds depend greatly on the context of the project. Thus there is a need for an approach that computes thresholds by taking into account this context. In this paper we propose such approach with the objective to reach a trade-off between representativeness of the threshold and computation cost. Our approach is based on an unbiased selection of software entities and makes no assumptions on the statistical properties of the software metrics values. It can therefore be used by anyone, ranging from developer to manager, for computing a representative metric threshold tailored to their context.
Exploiting visual and textual neighborhood information to improve image-tag relevance

Many applications, such as image searching, image indexing, and image label recommendations, have started using tagged images to benefit from user input. However, tags tend to be imprecise, incomplete, and ambiguous. Moreover, tags are also biased towards the user's perspective which degrades the performance of tag-based systems. Most of the existing methods use visual neighborhoods and/or tags to estimate image-tag relevance. We improve image-tag relevance by combining visual neighborhood of images and textual neighborhood of tags. By doing this, we boost the ranking of informative tags of an image. Most of the image-tag relevance measures work well when large supporting data is available, which is typically not sufficient in real datasets. This problem of Void of Information (VoI) is addressed by exploiting tags of visual neighbors of the images. We also exploit external resources like Wikipedia and WordNet to strengthen the tags. The proposed approach, TVNTag (Textual Visual Neighborhood based Tag) exhibits up to 46.1% relative improvement in tag ranking and 79.5% in image ranking, with respect to the current state-of-the-art methods. The experiments are conducted for different tasks and evaluation scenarios on benchmarked social data, such as MIRFlickr, NUS-WIDE, and train10k.
How Secondary Students Interpret Instances of Biological Adaptation.

This article reports an interview study with 84 students aged 12–16 years designed to document their understanding of biological adaptation. Analysis of transcripts suggests that secondary students find this subject area difficult and that many explain adaptation in teleological and anthropomorphic terms. Separate analysis of results from students of different ages indicated little progress in understanding from 12 to 14 years, but noticeable improvement by 16 years. Nevertheless, several alternative frameworks persisted in the older age group. Some possible implications for teachers are discussed. Since there is evidence that students come to formal teaching oj adaptation with a range of ideas, it is suggested that much more attention should be given to these in the laboratory. The authors propose that study of the historical development of thought on evolutionary processes may be a helpful strategy and that some teaching on the subject might usefully take place before its traditional place in the fifth .
Getting Children With Attention Deficit Hyperactivity Disorder to School on Time

This article details the school-readying routines Western Australian mothers employ in their efforts to dispatch children diagnosed with attention deficit hyperactivity disorder off to school in a timely manner. A grounded theory of instilling an awareness of time emerged from the data. In seeking to instill an awareness of time, mothers reveal their experiences of dealing with the chaos that arises out of their children's untimely actions from the point of waking them to the point of getting them out of the house and off to school. In an attempt to eliminate sources of stress contributing to the chaos mothers reflect on their children's idiosyncratic concept of time and analyze the mismatch between their and their child's attitude toward time management. The article concludes by detailing strategies mothers put in place to instill in their child an awareness of time and to establish a workable school-readying routine.
Intelligent mapping of hyperspace

We address some particular issues related to the difficult task of automatically structuring information available in illstructured environments, through a distributed hypermedia system like the Web. We present an original approach to this problem, which coordinates different aspects of automatic computation of relations between nodes in hyperspace, through dynamic linking, using intelligent mapping of the domain material, by the application of spatial reasoning. We present a multipurpose framework to dynamically structure information in the Web and a proof-of-concept prototype, dubbed hypermap, implemented to build the spatial cognitive maps of the hyperspace, inspired by the human cognitive mapping process.
Resolving Contradictions in Human Brand Celebrity and Iconicity

Abstract Purpose The academic discourse around celebrity and iconicity has resulted in the same human brand as labeled as an inauthentic and illegitimate celebrity and as a culturally important symbol of legitimate achievement. We address the research question of how are contradictions between celebrity and iconicity resolved in creating and managing a human brand. Methodology/approach Using structuration theory, we analyzed David Bowie’s 50 year career, from 1964 to 2013, totaling 562 documents. Applying Langley’s (1999) stages of data collection of grounding, organizing, and replicating, we develop a process of model of celebrity and iconicity. Findings We identify three stages of human brand symbolic associations: forming, fixing, and transitioning associations. These represent alternate trajectories that Bowie and Ziggy Stardust followed to become icons. In resolving his trajectories across these stages, Bowie adapts and adopts commercial materials, business practices, and new technologies to converge his symbolic associations into a coherent iconic human brand. Research limitations/implications Limitations of this paper lie in focusing on one human brand in a particular industry. Future research is suggested in three areas: (1) the relationship between the proposed model and other human brand activities; (2) to explore how the process is manipulated by other market agents; and (3) whether a human brand’s association shifts can precede culture. Originality/value This perspective challenges existing conceptualizations of celebrity and iconicity by framing them as inter-related processes, where celebrity associations are fixed in time, while iconic associations transition across time periods to reflect changing cultural values and concerns.
Communications to Self and Others: Emotional Experience and its Skills

According to the Communicative Theory of Emotions, we experience emotions when events occur that are important for our goals and plans. A method of choice for studying these matters is the emotion diary. Emotions configure our cognitive systems and our relationships. Many of our emotions concern our relationships, and empathy is central to our experience of them. We do not always recognize our emotions or the emotions of others, but literary fiction can help improve our skills of recognition and understanding.