Miracle-dz/UniFAR-FTUs huggingface dataset:
Single case studies and theory-testing: the knots and dots of the process-tracing method

Single case studies can provide vital contributions to theory-testing in social science studies. Particularly, by applying the process-tracing method, case studies can test theoretical frameworks through a rigorous research design that ensures substantial empirical leverage. While most scholarly contributions on process-tracing focus on either theory-building or on explaining single outcomes, we discuss how to apply the process-tracing method in theory-testing case studies. Furthermore, unlike the tendency to use examples from classic social science studies, we refer to our own case study of tax reform in Georgia thereby providing a constructive reflection on the practical application of and relevant methodological challenges in applying process-tracing. The strength of the process-tracing method lies in its ability to provide depth and testable substance to theoretical causal explanations.
Transgenic Expression of Helios in B Lineage Cells Alters B Cell Properties and Promotes Lymphomagenesis1

Helios, a member of the Ikaros family of DNA-binding proteins, is expressed in multipotential lymphoid progenitors and throughout the T lineage. However, in most B lineage cells, Helios is not expressed, suggesting that its absence may be critical for B cell development and function. To test this possibility, transgenic mice were generated that express Helios under the control of an Ig μ enhancer. Commitment to the B cell lineage was unaltered in Helios transgenic mice, and numbers of surface IgM+ B cells were normal in the bone marrow and spleen. However, both bone marrow and splenic B cells exhibited prolonged survival and enhanced proliferation. B cells in Helios transgenic mice were also hyperresponsive to Ag stimulation. These alterations were observed even though the concentration of ectopic Helios in B lineage cells, like that of endogenous Helios in thymocytes, was well below the concentration of Ikaros. Further evidence that ectopic Helios expression contributes to B cell abnormalities was provided by the observation that Helios transgenic mice developed metastatic lymphoma as they aged. Taken together, these results demonstrate that silencing of Helios is critical for normal B cell function.
Minimizing leakage: What if every gate could have its individual threshold voltage?

Designers aim at fast but low-power consuming integrated circuits. Since high processing speed always comes with high energy demands, the literature provides several ways to reduce a circuit's power dissipation. Even though technologically not possible today, this paper hypothesizes that the design would allow for choosing a gate's from a continuous domain in order to explore options for future improvements. That is, the design goal consists in selecting a gate's delay such that both the circuit's delay and its power consumption assumes minimal values. Since the resulting optimization problem is multi-dimensional and might also contain local optima, this paper utilizes genetic algorithms for this task. On a selection of the well-known ISCACS test suite, the genetic algorithms reduced the circuits' leakage values by about 20-50 %; with respect to nonoptimized circuits, the improvement is about 60-80%.
An empirical research on the relationships between software product management and software project management

This paper is a dedicated research on the way the fields of Software Product Management and Software Project Management collaborate with each other, within software product companies. It analyzes the dependencies between software product and software project and the relationships between product and project managers. The software product is defined based on the market success, customer satisfaction and meeting the internal business goals. Software projects are defined based on the delivery time, the quality and the cost incurred from the project development. Product and project managers are characterized upon their role specific qualifications as well as their positioning within the organizational structure of a software product vendor. The research is theory oriented. It concludes with some theory propositions as the result of both a qualitative and a quantitative analysis. The theory propositions describe the relationships between Software Product Management and Software Project Management. The findings show that project’s quality is the most influential factor for the product’s market success as well as for the customer satisfaction. Product managers are proved to be more business oriented, focusing on Strategic and Tactical decision-making. Project managers need more technical skills and they are more involved with Operational and Tactical decisions. The purpose of the research is to provide the software product companies with a benchmarking information of the current status of the market in Software Product Management and Software Project Management aspects. The results answer current business issues such as the positioning of the roles of a product manager and a project manager within the company as well as their dependencies in the organizational structure, as they are used in the contemporary market.
Nonresident Father Involvement and Adolescent Well-Being: Father Effects or Child Effects?

Is active fathering by nonresident fathers a cause or a consequence of adolescent wellbeing? Past studies of nonresident father involvement assume a father effects model in which active parenting by fathers improves adolescent adjustment. A child effects model, in which fathers respond to levels of well-being among their adolescent offspring by becoming more or less involved parents, could also account for the positive association between active fathering and adolescent adjustment. We use nationally representative data from the 1995 and 1996 waves of the National Longitudinal Study of Adolescent Health (Add Health) to estimate the cross-lagged associations between nonresident father involvement and the externalizing problems, internalizing problems, and academic achievement of 3,394 adolescents. Contrary to assumptions from a socialization perspective and findings from past research on nonresident fathers, our results do not support a father effects model. Our data are more consistent with a child effects model in which levels of adolescent well-being cause, rather than result from, levels of nonresident father involvement.
The Effect of Technology on Alienation from Work

This article presents new evidence on the effect of technology on alienation from work that is pertinent to Blauner's inverted U-curve hypothesis. One data set permits comparative analysis at the organizational level and addresses a gap in the literature on worker alienation because most research uses individual level data grouped by industrial categories. This organizational level approach is applied to individual level data on retrained union printers to analyze the impact of automation on the work of skilled craftsmen. Humanization of work in postindustrial society is examined. The relationship between technological advance and alienation is more negatively linear than curvilinear.
Fast Template Matching Method Based on Optimized Metrics for Face Localization

Recently, Template matching approach has been widely used for face localization problem. Normalized Crosscorrelation (NCC) is a measurement method normally utilized to compute the similarity matching between the templates and the rectangular blocks of the input image to locate the face position. However, the NCC metric is always suffering to locate the face especially in the images with illumination variations. In this paper we proposed a fast template matching technique based on Optimized similarity measurement metrics namely: Sum of Absolute Difference (OSAD) and Sum of Square Difference (SSD) to overcome the drawback of NCC. Our results show the highest performance of OSAD compared with other measurements and the improvement of OSSD comparing with SSD as well. Two sets of faces namely Yale Dataset and MIT-CBCL Dataset were used to evaluate our technique with success localization accuracy up to 100%. KeywordsFace localization; Template matching; Similarity measurements; Sum of Absolute Difference
Cooperative localization under message dropouts via a partially decentralized EKF scheme

For a team of mobile robots with limited onboard resources, we propose a partially decentralized implementation of an extended Kalman filter for cooperative localization. In the proposed algorithm, unlike a fully centralized scheme that requires, at each timestep, information from the entire team to be gathered together and be processed by a single device, we only require that the robots communicate with a central command unit at the time of a measurement update. In addition, the computational and storage cost per robot in terms of the size of the team is reduced to O(1). Moreover, the algorithm is robust to occasional in-network communication link failures while the estimation update of the robots receiving the update message is of minimum variance. We demonstrate the performance of the algorithm in simulations.
How Do Internal and External CSR Affect Employees' Organizational Identification? A Perspective from the Group Engagement Model

The literature examines the impact of firms' corporate social responsibility (CSR) activities on employees' organizational identification without considering that such activities tend to have different targets. This study explores how perceived external CSR (efforts directed toward external stakeholders) and perceived internal CSR (efforts directed toward employees) activities influence employees' organizational identification. In so doing, it examines the alternative underlying mechanisms through which perceived external and internal CSR activities build employees' identification. Applying the taxonomy prescribed by the group engagement model, the study argues that the effects of perceived external and internal CSR flow through two competing mechanisms: perceived external prestige and perceived internal respect, respectively. Further, it is suggested that calling orientation (how employees see their work contributions) moderates the effects induced by these alternative forms of CSR. The model draws on survey data collected from a sample of 414 employees across five large multinationals in Pakistan. The results obtained using structural equation modeling support these hypotheses, reinforcing the notion that internal and external CSR operate through different mediating mechanisms and more interestingly employees' calling orientation moderates these relationships to a significant degree. Theoretical contributions and practical implications of results are discussed in detail.
High performance traffic sign recognition based on sparse representation and SVM classification

The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. In this paper, an occlusion-robust traffic sign recognition method is proposed. To achieve occlusion-robust detection, we design a cascaded tree detector based on the MN-LBP features and a cascaded tree. For occlusion-robust traffic sign classification, the occlusion-robust dictionaries for sparse representation of multiclass traffic signs are designed. Then, the results of sparse representation are classified with SVM method. The classification results of SVM are more robust than that of the sparse representation classification (SRC) which directly uses judgment. The experiments on test set show that the proposed method is more robust and accurate to detect signs with partial occlusion than the methods based on SVM or SRC.
Code Generation and Optimization for Transactional Memory Constructs in an Unmanaged Language

Transactional memory offers significant advantages for concurrency control compared to locks. This paper presents the design and implementation of transactional memory constructs in an unmanaged language. Unmanaged languages pose a unique set of challenges to transactional memory constructs - for example, lack of type and memory safety, use of function pointers, aliasing of local variables, and others. This paper describes novel compiler and runtime mechanisms that address these challenges and optimize the performance of transactions in an unmanaged environment. We have implemented these mechanisms in a production-quality C compiler and a high-performance software transactional memory runtime. We measure the effectiveness of these optimizations and compare the performance of lock-based versus transaction-based programming on a set of concurrent data structures and the SPLASH-2 benchmark suite. On a 16 processor SMP system, the transaction-based version of the SPLASH-2 benchmarks scales much better than the coarse-grain locking version and performs comparably to the fine-grain locking version. Compiler optimizations significantly reduce the overheads of transactional memory so that, on a single thread, the transaction-based version incurs only about 6.4% overhead compared to the lock-based version for the SPLASH-2 benchmark suite. Thus, our system is the first to demonstrate that transactions integrate well with an unmanaged language, and can perform as well as fine-grain locking while providing the programming ease of coarse-grain locking even on an unmanaged environment
Researcher development: the impact of undergraduate research opportunity programmes on students in the UK

Undergraduate research opportunity programmes (UROP) are common in North America where research has confirmed their benefits. These schemes are gaining ground in the UK, and this article provides evidence for how UK students are benefiting from the experience. Results suggest UROP makes a significant contribution to the research capabilities and confidence of participating students, boosting their understanding of both research and their own subjects. Whilst offering considerable benefits to student learning, there is no evidence that UROP schemes on their current small scale attract additional students to postgraduate research, since the majority that participate are already interested in postgraduate study. However, at an individual level, most students report increased confidence and appreciation of the realities of the research process, and desire to progress on to postgraduate study following the placement, indicating that schemes may have the potential to cultivate new research confidence and interest if expanded.
Tremor detection using motion filtering and SVM

The hand tremor is one of the most common motion disorders caused by various neurological diseases. Currently diagnostic procedures for tremor evaluation are subjective, and there are no examinations available that can accurately indicate whether tremors are present in a patient's daily life. Early detection of tremor is extremely important for the cure of the disease that causes the tremor. Thus, in this study we aim to develop a computational method based on machine learning that can automatically detect hand tremors from a video of a patient when the patient is doing his/her daily activities. The main challenge in tremor detection is that motion is very subtle, and the signature of the motion can vary from patient to patient. We first generate a training data set consisting of 173 simulated tremor/non-tremor video files. They contain very subtle and less discriminative motions. The main contributions of our study are the personalized skin detection, motion filtering and feature extraction pipeline. We evaluated our method through leave-one-out cross validation (LOOCV) testing and showed that in preliminary tests our method achieved 95.4% recognition accuracy.
High-Efficiency Single-Phase Transformerless PV H6 Inverter With Hybrid Modulation Method

The main contribution of this paper is the derivation rules summarized from existing high-performance inverters with H6-type configuration, which makes novel topologies possible. In addition, a novel high-efficiency single-phase transformerless photovoltaic inverter with hybrid modulation method is also proposed and evaluated as an example. Without input split capacitors, common-mode voltage and leakage current issues in a nonisolated system with H6-type configuration are eliminated, and the feature of a three-level output voltage in the inverter bridge's middle point helps inductors and power quality optimization. The detailed operation principles with hybrid modulation strategy combined with unipolar and bipolar pulsewidth modulation schemes are presented. Experimental results of a 2200VA prototype verify the proposed topology with hybrid modulation method.
A Structural Model of Sentiment Relations

The paper presents a modification of the Holland-Leinhardt transitivity model of the structure of positive sentiment relations. The new model, based on a system of weighted triples, derives from an effort to eliminate theoretical weaknesses in earlier models and to create a more accurate formal expressions of propositions from consistency theory on sentiment relations. The model is tested on two data pools, Davis and Leinhardt's 742 sociograms gathered from secondary sources and 51 sociograms collected by the author using a technique designed to minimize measurement error in sociometric data. The results are compared to a test of the unweighted model on both data sets using a statistical index defined for comparative analyses. The author's model is found to be considerable more successful than the previous model in both data pools.
Performance of High Flow Rate Samplers for Respirable Particle Collection

The American Conference of Governmental Industrial hygienists (ACGIH) lowered the threshold limit value (TLV) for respirable crystalline silica (RCS) exposure from 0.05 to 0.025 mg m−3 in 2006. For a working environment with an airborne dust concentration near this lowered TLV, the sample collected with current standard respirable aerosol samplers might not provide enough RCS for quantitative analysis. Adopting high flow rate sampling devices for respirable dust containing silica may provide a sufficient amount of RCS to be above the limit of quantification even for samples collected for less than full shift. The performances of three high flow rate respirable samplers (CIP10-R, GK2.69, and FSP10) have been evaluated in this study. Eleven different sizes of monodisperse aerosols of ammonium fluorescein were generated with a vibrating orifice aerosol generator in a calm air chamber in order to determine the sampling efficiency of each sampler. Aluminum oxide particles generated by a fluidized bed aerosol generator were used to test (i) the uniformity of a modified calm air chamber, (ii) the effect of loading on the sampling efficiency, and (iii) the performance of dust collection compared to lower flow rate cyclones in common use in the USA (10-mm nylon and Higgins–Dewell cyclones). The coefficient of variation for eight simultaneous samples in the modified calm air chamber ranged from 1.9 to 6.1% for triplicate measures of three different aerosols. The 50% cutoff size (50dae) of the high flow rate samplers operated at the flow rates recommended by manufacturers were determined as 4.7, 4.1, and 4.8 μm for CIP10-R, GK2.69, and FSP10, respectively. The mass concentration ratio of the high flow rate samplers to the low flow rate cyclones decreased with decreasing mass median aerodynamic diameter (MMAD) and high flow rate samplers collected more dust than low flow rate samplers by a range of 2–11 times based on gravimetric analysis. Dust loading inside the high flow rate samplers does not appear to affect the particle separation in either FSP10 or GK2.69. The high flow rate samplers overestimated compared to the International Standards Organization/Comité Européen de Normalisation/ACGIH respirable convention [up to 40% at large MMAD (27.5 μm)] and could provide overestimated exposure data with the current flow rates. However, both cyclones appeared to be able to provide relatively unbiased assessments of RCS when their flow rates were adjusted.
Atomic scenes for scalable traffic scene recognition in monocular videos

The efficacy of advance warning systems (AWS) in automobiles can be significantly enhanced by semantic recognition of traffic scenes that pose a potential danger. However, the complexity of road scenes and the need for real-time solutions pose key challenges. This paper proposes a novel framework for monocular traffic scene recognition, relying on a decomposition into high-order and atomic scenes to meet those challenges. High-order scenes carry semantic meaning useful for AWS applications, while atomic scenes are easy to learn and represent elemental behaviors based on 3D localization of individual traffic participants. Atomic scenes allow our framework to be scalable, since a few of them combine to influence prediction for a wide array of high-order scenes. We propose a novel hierarchical model that captures co-occurence and mutual exclusion relationships while incorporating both low-level trajectory features and high-level scene features, with parameters learned using a structured support vector machine. We propose efficient inference that exploits the structure of our model to obtain real-time rates. Further, we demonstrate experiments in a large-scale dataset for scene recognition that consists of challenging traffic videos of inner-city scenes with ground truth annotations of scene types and object bounding boxes, as well as state-of-the-art 3D object localization outputs. Our experiments show the advantages of our approach relative to several baselines on a novel Inner-City dataset.
A Markovian random field approach to information retrieval

A Markovian random field approach is proposed for automatic information retrieval in full text documents. We draw up an analogy between a flow of queries/document images connections and statistical mechanics systems. The Markovian flow process machine (MFP) models the interaction between queries and document images as a dynamical system. The MFP machine searches to fit the user's queries by changing the set of descriptors contained in the document images. There is hence a constant transformation of the informational states of the fund. For each state, a certain degradation of the system is considered. We use simulated annealing algorithm to isolate low energy states: this corresponds to the best "matching" in some sense between queries and images.
Services for children with dyslexia – the child’s experience

This study evaluates and compares special educational services for children with dyslexia in three different Irish educational settings: special schools, reading units and mainstream resource provision. The emphasis is on the child’s experience of special education. Participants were dyslexic children aged 8–13 who had been accessing special educational services for two academic years. Data collection involved individual interviews with each of the 100 children. Further data about the child’s experience were collected by parental questionnaire. Results suggested that while children overall were happy and evaluated special educational services positively across all three settings, children in special schools and reading units seemed to be happier and to have more positive experiences than children attending mainstream resource provision. The discussion considers the implications of these findings in the context of the inclusion debate in special education. It also considers the limitations of this small‐scale study and the need for further research.
Measuring Geographical Environments through Adjectives: The Environmental Check List

The Environmental Check List, a 140-item adjective check list developed to measure geographical environments, is presented. The list was developed from 304 open-ended descriptions, and its utility illustrated by three studies: (1) a pre-post study over 1 yr. of 108 newcomers to Tucson, AZ; (2) a 5-yr. study of initial reaction to a desert environment as related to subsequent mobility; and (3) a comparison of responses to the check list and to the Environmental Response Inventory.