Miracle-dz/UniFAR-FTUs huggingface dataset:
A user profile-based personalization system for digital multimedia content

With the steadily increasing amount of digital multimedia content, the user will be more and more overstrained. This applies to content being permanently available like videos of online video services as well as broadcast content like in the TV or radio domain. A promising solution for this problem is personalization. In the context of this paper, we refer to the selection and recommendation of content with respect to user's interests and preferences as personalization. These recommendations can either be presented to the user herself or be further used by services like a personalized electronic program guide (EPG) in the TV domain or for automated and personalized selection of content of online video services. This paper introduces an approach to personalize digital multimedia content based on user profile information. For this, two main mechanisms were developed: a profile generator that automatically creates user profiles representing the user preferences, and a content-based recommendation algorithm that estimates the user's interest in unknown content by matching her profile to metadata descriptions of the content. Both features are integrated into a personalization system.
A Systematic Proteomic Study of Irradiated DNA Repair Deficient Nbn-Mice

Background The NBN gene codes for the protein nibrin, which is involved in the detection and repair of DNA double strand breaks (DSBs). The NBN gene is essential in mammals. Methodology/Principal Findings We have used a conditional null mutant mouse model in a proteomics approach to identify proteins with modified expression levels after 4 Gy ionizing irradiation in the absence of nibrin in vivo. Altogether, amongst ∼8,000 resolved proteins, 209 were differentially expressed in homozygous null mutant mice in comparison to control animals. One group of proteins significantly altered in null mutant mice were those involved in oxidative stress and cellular redox homeostasis (p<0.0001). In substantiation of this finding, analysis of Nbn null mutant fibroblasts indicated an increased production of reactive oxygen species following induction of DSBs. Conclusions/Significance In humans, biallelic hypomorphic mutations in NBN lead to Nijmegen breakage syndrome (NBS), an autosomal recessive genetic disease characterised by extreme radiosensitivity coupled with growth retardation, immunoinsufficiency and a very high risk of malignancy. This particularly high cancer risk in NBS may be attributable to the compound effect of a DSB repair defect and oxidative stress.
Embracing Discursive Paradox

This article addresses how diversity consultants manage the dual demands of social justice and organizational goals or priorities. I suggest that navigating this “discursive paradox” is one of—if not the—defining feature of diversity work. To investigate this discursive paradox, I analyze diversity work as a process (rather than a collection of products) as evidenced in interviews with 19 diversity consultants. The results offer two derivative discursive paradoxes that emerged in consultants’ talk about diversity work: the tension between broad and narrow constructions of human differences and the tension between emphasizing change at the organizational and individual levels. Rather than framing these tensions as inherently problematic, I examine how consultants use them to create possibilities for change. Consequently, this work offers a promising approach for understanding and facilitating other forms of socially motivated organizational change, such as organizational sustainability or health and well-being campaigns.
How adaptation shapes spike rate oscillations in recurrent neuronal networks

Neural mass signals from in-vivo recordings often show oscillations with frequencies ranging from <1 to 100 Hz. Fast rhythmic activity in the beta and gamma range can be generated by network-based mechanisms such as recurrent synaptic excitation-inhibition loops. Slower oscillations might instead depend on neuronal adaptation currents whose timescales range from tens of milliseconds to seconds. Here we investigate how the dynamics of such adaptation currents contribute to spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely coupled spiking model neurons with two types of adaptation current and conductance-based synapses with heterogeneous strengths and delays we use a mean-field approach to analyze oscillatory network activity. For constant external input, we find that spike-triggered adaptation currents provide a mechanism to generate slow oscillations over a wide range of adaptation timescales as long as recurrent synaptic excitation is sufficiently strong. Faster rhythms occur when recurrent inhibition is slower than excitation and oscillation frequency increases with the strength of inhibition. Adaptation facilitates such network-based oscillations for fast synaptic inhibition and leads to decreased frequencies. For oscillatory external input, adaptation currents amplify a narrow band of frequencies and cause phase advances for low frequencies in addition to phase delays at higher frequencies. Our results therefore identify the different key roles of neuronal adaptation dynamics for rhythmogenesis and selective signal propagation in recurrent networks.
Mathematical Modeling in Photoacoustic Imaging of Small Absorbers

This paper is devoted to mathematical modeling in photoacoustic imaging of small absorbers. We propose a new method for reconstructing small absorbing regions inside a bounded domain from boundary measurements of the induced acoustic signal. We also show the focusing property of the back-propagated acoustic signal. Indeed, we provide two different methods for locating a targeted optical absorber from boundary measurements of the induced acoustic signal. The first method consists of a MUltiple SIgnal Classification (MUSIC)-type algorithm and the second one uses a multifrequency approach. We also show results of computational experiments to demonstrate efficiency of the algorithms.
Taking Culture Seriously in Organization Development: A New Role for OD?

Culture as a concept impacts organization development (OD) in two fundamental ways. First, it is increasingly evident that the practice of OD has to learn to deal with the cultures and subcultures of client systems. Dealing with cultures and sub-cultures requires conceptual models and intervention skills that deal realistically with what culture is and how culture works. Second, OD as an occupational community has developed a culture and sub-cultures within itself and has to learn what the strengths and weaknesses are of those occupational cultures and sub-cultures. Of particular importance is the recognition that the sub-cultures within OD may be in conflict with each other and not be aware of this. In this paper I will present a working model of culture and then analyze each of the two issues.
In the Nature of Cities: Urban Political Ecology and the Politics of Urban Metabolism

Forward David Harvey Part 1 The Production of Urban Natures and Urban Political Ecology 1. Introduction Erik Swyngedouw, Nik Heynen and Maria Kaika 2. Sylvan City: The social production of urban nature Eliza Darling and Neil Smith 3. Urbanizing Political Ecology: A perspective from Toronto Roger Keil and Julie-Anne Bourdreau Part 2: Urban Metabolisms 4. Circulations and Metabolism: Hybrid natures and cyborg cities Erik Swyngedouw 5. The Desire to Metabolize Nature Stuart Oliver 6. Cyborg Urbanization: Water, urban infrastructure and the modern city Matthew Gandy 7. Monuments, Medians and Metabolims: Contradictions inherent to the appropriation of Avenida De La Reforma's built environment for consumption Nik Heynen 8 Clogging up the City: The metabolism of fat in bodies, sewers and cities Simon Marvin and Will Medd 9. Urban Metabolism as Target: Contemporary war as forced demodernisation Stephen Graham Part 3: The Ecology of Urban Politics 10. Transnational Alliances and Global Politics: New geographies of urban environmental justice struggles David N Pellow 11. Constructing Scarcity and Sensationalising Water Politics: 170 days that shook Athens Maria Kaika 12. Dead Spaces in the City of Extremes: Observations from the great Chicago heat wave Eric Klinenberg 13. Reconnecting with the Means of Existence in Durban Alex Loftus 14. Looking at the Public/Private Water Debate in South Africa Through the Prism of an Urban Political Ecology Framework Laila Smith 15. Turfgrass Subjects: The political economy of suburban lawn monoculture Paul Robbins 16. At the Edge: Fragmented ecologies in Philadelphia Alec Brownlow Conclusions and the Way Forward Erik Swyngedouw, Nik Heynen and Maria Kaika
Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd

Object detection and 6D pose estimation in the crowd (scenes with multiple object instances, severe foreground occlusions and background distractors), has become an important problem in many rapidly evolving technological areas such as robotics and augmented reality. Single shotbased 6D pose estimators with manually designed features are still unable to tackle the above challenges, motivating the research towards unsupervised feature learning and next-best-view estimation. In this work, we present a complete framework for both single shot-based 6D object pose estimation and next-best-view prediction based on Hough Forests, the state of the art object pose estimator that performs classification and regression jointly. Rather than using manually designed features we a) propose an unsupervised feature learnt from depth-invariant patches using a Sparse Autoencoder and b) offer an extensive evaluation of various state of the art features. Furthermore, taking advantage of the clustering performed in the leaf nodes of Hough Forests, we learn to estimate the reduction of uncertainty in other views, formulating the problem of selecting the next-best-view. To further improve pose estimation, we propose an improved joint registration and hypotheses verification module as a final refinement step to reject false detections. We provide two additional challenging datasets inspired from realistic scenarios to extensively evaluate the state of the art and our framework. One is related to domestic environments and the other depicts a bin-picking scenario mostly found in industrial settings. We show that our framework significantly outperforms state of the art both on public and on our datasets.
Smooth Representations of Gl M (d)

We give a complete description of the category of smooth complex representations of the multiplicative group of a central simple algebra over a locally compact nonarchimedean local eld. More precisely, for each inertial class in the Bernstein spectrum, we construct a type and compute its Hecke algebra. The Hecke algebras that arise are all naturally isomorphic to products of a ne Hecke algebras of type A. We also prove that, for cuspidal classes, the simple type is unique up to conjugacy.
A Longitudinal Study of Teacher Change: What makes professional development effective? Report of the second year of the study

This article reports on an ongoing longitudinal investigation of the influence of professional development on teaching strategies. The study has so far identified models of type and duration of professional development activity for a national sample of primary subject co-ordinators and secondary heads of department of English, mathematics and science. This article reports on participants' changes in type of professional development activity over time, extent of subject content emphasis of the development activity and subsequent changes to teaching practice effected by involvement in a longer term professional development activity.
Noise Levels in Hong Kong Primary Schools: Implications for classroom listening

Many researchers have stressed that the acoustic environment is crucial to the speech perception, academic performance, attention, and participation of students in classrooms. Classrooms in highly urbanised locations are especially vulnerable to noise, a major influence on the acoustic environment. The purpose of this investigation was to determine noise levels in one such urban environment, Hong Kong. The ambient noise level, and its relationship to the speech intensity levels of both teachers and students was surveyed in 47 primary school classrooms. Moreover, the presence of acoustical treatments for noise reduction and the use of classroom amplification systems were documented for each classroom. The survey found that the mean occupied noise level was 60.74 dB (A); the mean unamplified and amplified speech‐to‐noise ratios of teachers were 13.53 dB and 18.45 dB, respectively; while the mean unamplified speech‐to‐noise ratio for students was 4.13 dB. Most of the classrooms exhibited insufficient acoustical treatments to provide significant noise reduction. The listening environment in many Hong Kong primary schools was not favourable for optimal classroom learning. Recommendations for improving the acoustical environment in classrooms in highly urbanised locations such as Hong Kong are discussed.
Edge Map Improvement on Spiral Architecture

Edge map is considered as an important entity containing most of object features in an image. Many computer vision systems rely on the use of the boundary line information to perform the object recognition tasks. However. with the exception of images acquired from highly restricted environment, common edge detectors do not guarantee the production of continuous boundaries of objects. In this paper. a local processing based edge-linking algorithm is proposed. We set a criterion involving multiple properties of the pixel to find the best candidate points for edge linking. In addition, this algorithm is implemented on Spiral Architecture.
Public Efficiency and Private Choice in Higher Education

Students tend to enter college when college appeals to them, when appropriate college choices are available, and when at least one of the available colleges has a larger value than the other available options. When any of these conditions is not met, or appears not to be met, students tend to choose otherwise. There are occasions in which enrollment choices differ from what is optimal for society, and in such cases the logical public objective is to change some students' minds. For enrollment patterns in higher education to change, students must move from the "choose other" to the "choose college" group; merely reinforcing students' convictions that they have chosen wisely is of no benefit. Three possible strategies ensue: (1) changing the situation, which comprises students' preferences, the options among which they choose, and the characteristics of specific options; (2) improving available information about specific colleges and jobs, so that student perceptions are accurate (or at least favor college choices); or (3) reducing the role of chance in student choices. Among these strategies only two, changing the situation and improving information, translate readily into practical policy, because only for these do theory and research suggest specific tactics. These tactics range from expensive ones, such as building new colleges, to relatively
Automatic Transformation of Raw Clinical Data Into Clean Data Using Decision Tree Learning Combining with String Similarity Algorithm

It is challenging to conduct statistical analyses of complex scientific datasets. It is a timeconsuming process to find the relationships within data for whether a scientist or a statistician. The process involves preprocessing the raw data, the selection of appropriate statistics, performing analysis and providing correct interpretations, among which, the data pre-processing is tedious and a particular time drain. In a large amount of data provided for analysis, there is not a standard for recording the information, and some errors either of spelling, typing or transmission. Thus, there will be many expressions for the same meaning in the data, but it will be impossible for analysis system to automatically deal with these inaccuracies. What is needed is an automatic method for transforming the raw clinical data into data which it is possible to process automatically. In this paper we propose a method combining decision tree learning with the string similarity algorithm, which is fast and accuracy to clinical data cleaning. Experimental results show that it outperforms individual string similarity algorithms and traditional data cleaning process.
Supervised LDA for Image Annotation

Region-based Image Annotation has received increasing attention in recent years. Topic models such as probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA) have shown great success in object recognition and localization. In this paper, we introduce a supervised topic model for region-based image annotation. Images are segmented into superpixels, and visual features are extracted from each superpixel region. Boosted classifiers are then trained for each class, and the output of boosted classifiers are quantized as boosted visual words. The proposed model builds a generative model on both visual words and corresponding class labels. We tested the model on the 21-class MSRC dataset. Experimental results show that our model improves the annotation performance comparing with boosted classifiers.
Work–life balance: A review of the meaning of the balance construct

Although the term workâ€“family/life balance is widely employed, an agreed definition of this term has proved elusive. Instead, an array of definitions and measures populate the literature. The variety of workâ€“life definitions and measures provide limited value for both the theoretical advancement of the construct and for practical human resource (HR) interventions. In this article, we review six conceptualisations of workâ€“life balance found in the literature: (1) multiple roles; (2) equity across multiple roles; (3) satisfaction between multiple roles; (4) fulfilment of role salience between multiple roles; (5) a relationship between conflict and facilitation; and (6) perceived control between multiple roles. Based on our review of this research we identify the two primary features of the workâ€“life balance definitions and propose a new definition of this construct.
The Language of Acceptance

The present study examines perceived acceptance from one’s ingroup (i.e., intragroup acceptance) and collective self-esteem among Latinos as a function of Spanish proficiency. Using a correlational design, Study 1 demonstrates that Latinos’ (n = 53) Spanish-speaking inability is associated with lower private regard, membership, and less felt similarity to other Latinos, which was explained in part by greater perceptions of intragroup rejection. Moreover, Study 1 results were not moderated by overall Latino identification. Utilizing an experimental design, Study 2 demonstrates that non-Spanish-speaking Latinos (n = 40) put in a situation wherein they must disclose their inability to speak Spanish to another Latino were less likely to categorize themselves as Latinos, reported lower collective self-esteem, and reported less connectedness to other Latinos. These findings are discussed within a broader model of intragroup acceptance and identification, whereby cultural practices serve as markers of credibility that aid in felt acceptance within ethnic minority communities. Implications for acculturation are discussed.
The Relationship Between Life Style, Coping Strategies and Religiosity with General Health in Iranian Students

General health has been associated with many variables that from most important can be noted Life Style, Coping Strategies and Religiosity. This study examined the relationship between life style, coping strategies, religiosity and general health among Iranian students. This cross sectional study was conducted on 180 students 15-17 year olds who were selected via multi step cluster sampling method design from schools in the Varamin suburb, Iran in 2013. All students completed the questionnaires of life style, coping strategies, religiosity and general health and regression was used for data analyses. The statistical analysis revealed a positive relationship between life style, problem solving strategy and internal religiosity with general health (P<0.01) and a negative relationship between emotional coping strategy with general health (P<0.05). Life style, internal religiosity and problem-focused strategy predicted 32 percent of variance of general health and also share of life style in prediction general health was over of other variables. These results highlight the importance in considering life style at further understanding general health in students.
Effect of Relaying on Coverage in 3GPP LTE-Advanced

Current broadband wireless networks are characterized by large cell sizes. Yet, even in advanced networks that will be built using 3 GPP Long Term Evolution (LTE), also referred to as 3GPP LTE-Advanced, or mobile WiMAX radio interface, users on the cell edge will face relatively low signal-to-interference-plus-noise-ratio (SINR). An attractive solution for this problem is provided by multihop technologies. In this paper we consider the feasibility of Decode and Forward (DF) Relay Nodes (RNs) from 3GPP LTE-Advanced perspective. We propose a novel evaluation methodology that can be used to find a relation of RN transmission power, ratio between number of Base Stations (BSs) and RNs, and performance of the system. Evaluation of DF relays in 3GPP LTE-Advanced framework indicates a good performance gain.
Uncorrected proofs — not for distribution 3 Pathway Analysis of Microarray Data

During the past decade remarkable new techniques for transcriptional profiling have been developed. These include transcriptional profiling using hybridization microarrays as well as methods to sequence transcribed RNAs. No matter which technology is used, these experiments generate data on thousands of genes across multiple conditions and therefore the analysis of these data is often a daunting task. One of the most promising avenues for interpreting large datasets of expression profiles involves pathway-based analysis. Although pathway analysis of expression data is a relatively new field, many important advances have been made over the past few years. Below we outline some the most significant developments in this area of research. Introduction Pathways are collections of genes and proteins that perform a well-defined biological task. For instance, proteins that work to successively synthesize metabolites within a cell are grouped into metabolic pathways. Similarly, proteins that are involved in the transduction of a signal from the cell membrane to the nucleus are grouped into signal transduction pathways. These pathways have been established through decades of molecular biology research and are collected in a variety of public pathway repositories (Kanehisa et al., 2004; Ashburner et al., 2000). Since the number of known pathways within cells is significantly smaller than the number of genes that is typically profiled, the transformation of data from a gene-centric view to a pathways-centered one represents a dramatic reduction in the number of dimensions. Such a reduction allows a biologist to interpret and understand the data in a manner that is not possible when it is viewed as a collection of individual genes. Although pathway analysis of expression data is a relatively new field, many important advances have been made over the past few years. Below we outline some the most significant developments in this area of research. These include analyses that attempt to identify the pathways that are overrepresented among significantly perturbed genes in an experiment along with methods that attempt to identify pathways and networks of molecular interactions directly from expression data. Despite the fact that these analyses will undoubtedly continue to evolve rapidly over the next few years, they have already enhanced our ability to understand the biology that underlies complex experiments.