Miracle-dz/UniFAR-FTUs huggingface dataset:
Student Perceptions of the Role of Emotional Intelligence in College Success: A Phenomenological Study

ERIC Descriptors: Academic Achievement, Emotional Intelligence, Student Experience, Undergraduate Students, Business School Although there is an emerging body of literature demonstrating a relationship between Emotional Intelligence and academic success (i.e., GPA) and much speculation as to how Emotional Intelligence impacts academic performance, there are no studies to date, which examine students’ experiences of this phenomenon in-depth. There is a need to understand the experience of students with regard to how Emotional Intelligence impacts academic achievement from the students’ perspective. This dissertation presents a qualitative study based on the perceptions and lived experiences of eight undergraduate business students with respect to emotional intelligence and how it impacts perceived success.If Emotional Intelligence contributes to improved academic achievement, a greater understanding of the relationship between EI and student success, particularly within the realms of self-awareness, self-management, social awareness, and relationship management would benefit universities in both admissions decisions and interventions to improve student success, thereby increasing overall student retention. The knowledge gained from this research contributes to existing literature regarding how EI impacts students’ perceived success in an undergraduate business program. The goal of this research project was to gather rich descriptions and a depth of understanding of the students’ experiences of EI as it relates to perceived success. The most prevalent themes identified by respondents were relationship management, self-awareness, selfmanagement, and social awareness. The eight students who participated in this study emphasized and recognized that EI was an important factor in their decision-making process for academic success. Results of this research indicated that there was a strong, positive connection between EI and academic success and that the development of EI was influenced by identifiable factors. Emotions play a key role in decision making, and this research reinforced the awareness that emotional stability and EI are crucial components for academic
A meta-analysis to establish the construct validity and normative values of the Pain Catastrophising Scale

Introduction: Outcome measures in clinical psychology tend to be developed in an ad-hoc way, with psychological constructs added to theoretical understanding without formal evaluation of their validity and relationship with existing constructs. Pain catastrophising is an example of a construct with no proven differentiation from other pain-related cognitions. The Pain Catastrophising Scale (PCS) is widely used and several theories exist regarding its theoretical basis and causal relationship with pain outcomes. Aims: This thesis aims to establish psychometric properties for the PCS from a wide and varied population; to assess the sensitivity of the scale and create norms for pain types; and assess the construct validity of pain catastrophising. Method: A systematic review was conducted to collect baseline PCS scores from research studies since its development in 1995 to the present day. Meta-analysis including multivariate regression explored variables influencing pain catastrophising. Correlations between the PCS and other measures were used to evaluate the construct validity of pain catastrophising. Results: Good internal reliability (α=.92, 95% CI .91-.93) and test-retest reliability scores (Spearman correlation coefficient=.88, 95% CI .83-.93) were found for the PCS. Participants’ pain type was highly related to PCS scores, with those with generalized pain scoring highest. No significant effects of age or gender were found. Language of the PCS affected PCS scores. Study type influenced PCS scores, but was confounded with pain diagnosis, with controlled trials more likely than quasi-experimental studies to recruit clinical samples. Divergent validity of the construct of pain catastrophising was tentatively supported by limited data. Discussion: Within the limits of available data, the use of the PCS is supported as a valid and reliable measure. Pain catastrophising varies depending on the pain type and intensity experienced. Further research is recommended to clarify the construct validity of pain catastrophising through consistent use of outcome measures.
Identification of a recurrent breakpoint within the SHANK3 gene in the 22q13.3 deletion syndrome

Introduction: The 22q13.3 deletion syndrome (MIM 606232) is characterised by neonatal hypotonia, normal to accelerated growth, absent to severely delayed speech, global developmental delay, and minor dysmorphic facial features. We report the molecular characterisation of the deletion breakpoint in two unrelated chromosome 22q13.3 deletion cases. Methods: The deletions were characterised by FISH, checked for other abnormalities by array-CGH, and confirmed by Real-Time PCR, and finally the breakpoints were cloned, sequenced, and compared. Results: Both cases show the cardinal features of the 22q13.3 deletion syndrome associated with a deletion involving the last 100 kb of chromosome 22q13.3. The cases show a breakpoint within the same 15 bp repeat unit, overlapping the results obtained by Wong and colleagues in 1997 and suggesting that a recurrent deletion breakpoint exists within the SHANK3 gene. The direct repeat involved in these 22q13 deletion cases is presumably able to form slipped (hairpin) structures, but it also has a strong potential for forming tetraplex structures. Discussion: Three cases with a common breakpoint within SHANK3 share a number of common phenotypic features, such as mental retardation and developmental delay with severely delayed or absent expressive speech. The two cases presented here, having a deletion partially overlapping the commercial subtelomeric probe, highlight the difficulties in interpreting FISH results and suggest that many similar cases may be overlooked.
Streamroller : A Unified Compilation and Synthesis System for Streaming Applications

The growing complexity of applications has increased the need for higher processing power. In the embedded domain, the convergence of audio, video, and networking on a handheld device has prompted the need for low cost, low power, and high performance implementations of these applications in the form of custom hardware. In a more mainstream domain like gaming consoles, the move towards more realism in physics simulations and graphics has forced the industry towards multicore systems. Many of the applications in these domains are streaming in nature. The key challenge is to get efficient implementations of custom hardware from these applications and map these applications efficiently onto multicore architectures. This dissertation presents a unified methodology, referred to as Streamroller, that can be applied for the problem of scheduling stream programs to multicore architectures and to the problem of automatic synthesis of custom hardware for stream applications. Firstly, a method called stream-graph modulo scheduling is presented, which maps stream programs effectively onto a multicore architecture. Many aspects of a real system, like limited memory and explicit DMAs are modeled in the scheduler. The scheduler is evaluated for a set of stream programs on IBM's Cell processor. Secondly, an automated high-level synthesis system for creating custom hardware for stream applications is presented. The template for the custom hardware is a pipeline of accelerators. The synthesis involves designing loop accelerators for individual kernels, instantiating buffers to store data passed between kernels, and linking these building blocks to form a pipeline. A unique aspect of this system is the use of multifunction accelerators, which improves cost by efficiently sharing hardware between multiple kernels. Finally, a method to improve the integer linear program formulations used in the schedulers that exploits symmetry in the solution space is presented. Symmetry-breaking constraints are added to the formulation, and the performance of the solver is evaluated.
LGBTQ Youth Bullying Experiences in Schools: The Role of School Counselors Within a System of Oppression

ABSTRACT Sexual minority and gender expansive youth often experience bullying in schools. However, no study to date has provided school-wide LGBTQ-specific antibullying interventions grounded in current national and state laws and policies, nor the professional ethical responsibilities of school counselors. This literature review describes the context of school bullying for this marginalized population and highlights laws and policies preventing the necessary care LGBTQ students need to optimize their school and mental health outcomes. The role of counselors in preventing LGBTQ bullying—and creating a safe school climate—is explored and contextualized with respect to the professional ethics of school counselors. Finally, LGBTQ antibullying interventions that can be implemented by school counselors are examined.
Biclustering of gene expression data

Biclustering is an important problem that arises in diverse applications, including the analysis of gene expression and drug interaction data. A large number of clustering approaches have been proposed for gene expression data obtained from microarray experiments. However, the results from the application of standard clustering methods to genes are limited. This limitation is imposed by the existence of a number of experimental conditions or gene samples, where the expression levels of the same genes are uncorrelated. A similar limitation exists when condition-clustering is performed. The goal of biclustering is to find submatrices of genes and conditions, or samples where the genes have nearly the same expression levels for nearly all conditions. Some clustering methods have been adopted or proposed. However, some concerns still remain, such as the robustness of mining methods on the noise and input parameters. In this paper we tackle the problem of effectively clustering gene expression data by proposing an algorithm. We use a density-based approach to identify clusters. Our experimental results show that the algorithm is effective.
A novel computer assisted approach for diagnosis of skin disease

In this paper, a novel approach to segmentation of dermoscopic images based on fuzzy logic and Fuzzyc-means clustering is proposed. Skin disease is the most widespread disease in the world. There are many techniques and tests to diagnose skin disease. However, many of these techniques are extremely complex, subjective and depend deeply on the experience of the clinician. Melanoma is a kind of skin disease and deadliest form of skin cancer must be diagnosed early for effective treatment. So, it is necessary to develop a computer-aided diagnostic system to facilitate its early detection. To predict these problems, we use a fuzzy inference as promising modalities for detection of skin disease.
A remote sensing image self-adaptive blind watermarking algorithm based on wavelet transformation

Based on the statistical characters of remote sensing image, this paper proposed firstly partition remote sensing image into sub-block images of suitable sizes, and then decomposing these sub-block images with biorthogonal 7/5 wavelet. A novel construction method of wavelet set of coefficients is adopted to embed binary watermarking image into sub-bands except low frequency sub-bands, and realizing a blind detection algorithm. The visual model of biorthogonal 9/7 wavelet is extended to construct a visual weighted analysis method based on the biorthogonal 7/5 wavelet domain quantization noises, thus making the strength of the embedded watermarking could self-adapt to the sub-blocks of the remote sensing image. Experimental results show that the proposed algorithm has great imperceptibility and is robust to the image intensity attack such as geometric transformation, noise adding, filtering, and compression. It performs better than that of the watermarking algorithm proposed by Ho in the robust, and being a practical blind watermarking algorithm.
Cache Tracker: A Key Component for Flexible Many-Core Simulation on FPGAs

This paper presents a cache tracker, a hardware component to track the cache state of hundreds of caches serving processors modeled using threads on a single MIPS64 processor. This host-multithreading approach allows a single, low-cost FPGA to model large systems to allow quick and broad architectural exploration with reasonable simulation performance. The cache tracker stores all state in DRAM to allow maximum scalability in both number of processors and in cache sizes. We describe our approach of scalability versus simulation performance, our implementation in Bluespec SystemVerilog, and give a sample study of a parallel merge-sort over various processor numbers, cache sizes and arrangements.
Privacy preserving video surveillance using pedestrian tracking mechanism

Video surveillance has become a ubiquitous feature of the modern day life. However, the widespread use of video surveillance has raised concerns about the privacy of people. In this paper, we propose a novel video surveillance with a privacy preserving mechanism. We achieve this by combining the techniques of pedestrian tracking based on a Markov chain with two hidden states, elliptical head contour detection and encryption. The detected pedestrian face/head is obscured by encrypting with a unique key derived from a master key for the privacy preservation purpose. The surveillance video can be viewed with complete privacy or by revoking the privacy of any subset of pedestrians while ensuring complete privacy of the remaining pedestrians.The performance evaluation on many challenging surveillance scenarios shows that the proposed mechanism can effectively and robustly track multiple pedestrians and obscure their faces/head in real time.
Role in host cell invasion of Trypanosoma cruzi-induced cytosolic-free Ca2+ transients

Trypanosoma cruzi enters cells by a unique mechanism, distinct from phagocytosis. Invasion is facilitated by disruption of host cell actin microfilaments, and involves recruitment and fusion of host lysosomes at the site of parasite entry. These findings implied the existence of transmembrane signaling mechanisms triggered by the parasites in the host cells before invasion. Here we show that infective trypomastigotes or their isolated membranes, but not the noninfective epimastigotes, induce repetitive cytosolic-free Ca2+ transients in individual normal rat kidney fibroblasts, in a pertussis toxin-sensitive manner. Parasite entry is inhibited by buffering or depleting host cell cytosolic-free Ca2+, or by pretreatment with Ca2+ channel blockers or pertussis toxin. In contrast, invasion is enhanced by brief exposure of the host cells to cytochalasin D. These results indicate that a trypomastigote membrane factor triggers cytosolic-free Ca2+ transients in host cells through a G-protein-coupled pathway. This signaling event may promote invasion through modulation of the host cell actin cytoskeleton.
Y-chart based system design: a discussion on approaches

Embedded systems are a source of technology that facilitates our modern lifestyle. In order to do so, they tend to increase in complexity as well as integrate in are day-to-day activities. To meet the market's expectations on technological improvement, time-to-market objectives for introducing innovative embedded systems are shorter than ever. Over the last decade, model-based design has been a subject of great interest as a means to accelerate the design of embedded systems. The Y-chart paradigm is a principal approach to model-based embedded system design. Despite the simplicity and conciseness of this paradigm, it has been implemented in several di®erent ways by various methodologies. This variety in implementation designs is due to the particular emphasis a methodology puts on the di®erent steps of the paradigm (application modeling, platform modeling, mapping, analysis and synthesis). This article explores this variety by examining and comparing three Y-chart based design methodologies: Metropolis, the Distributed Operation Layer incorporating Modular Performance Analysis and the Y-chart variant of the Software/Hardware Engineering methodology. These methodologies have been chosen because they: cover a broad domain of applications, have been developed on a relatively long period of time and are representative of typical Y chart approaches. Moreover, these implementations of the paradigm present interesting design approaches which are worth comparing
SelectiveDES: A Distributed Event Service Add-On for Invocation-Based Middleware supporting Selective Multi-Channel Communication and Notification Delivery

Mobile enterprise applications typically access data from the enterprise's various applications to support collaborative working processes. Allowing the mobile application to access these data online only would be a major hindrance for mobile workers that cannot assume a constantly available network connection. This problem can be handled by middleware systems, which provide a way to pre-fetch data on the mobile device. But changes and events on the central data cannot be foreseen; moreover, they cannot be delivered to disconnected mobile clients. We introduce a distributed event service named SelectiveDES for managing and delivering events to mobile clients in unpredictable network environments. SelectiveDES is designed as an add-on to common invocation-based middleware systems; it is based on the publish-subscribe paradigm and supports selective multi-channel communication and notification delivery
Required Extra Capacity : Estimating Overprovisioning in a Single Class-of-Service IP Backbone

The benefit of Class-of-Service (CoS) is an important topic in the “Network Neutrality” debate. Some proponents of network neutrality suggest that over-provisioning is a viable alternative to CoS, and that there is no need for differentiated services in an IP backbone for users needing better-than-be steffort service. In this paper, we quantify the extra capacit y requirement for an over-provisioned classless (i.e., best -effort) network compared to a CoS network providing the same delay or loss performance for premium traffic. We first develop a link model that quantifies the Required Extra Capacity (REC). To illustrate key parameters involved inanalytically quantifying REC, we start with simple traffic distributions. Then, for more bu rsty and realistic traffic distributions (e.g., long-range dependent), we find the REC using ns-2 simulations of CoS and classless links . We, then, use these link models to quantify the REC for realis tic network topologies under various scenarios including situ ations with “closed loop” traffic generated by many TCP sources that adapt to the available capacity. We also study the REC under link and node failures. We show that REC can be significant eve n when the proportion of premium traffic requiring performanc e assurances is small, a situation often considered benign fo r the over-provisioning alternative. We also show that the impac t of CoS on best-effort traffic is relatively small while still providing the desired performance for premium traffic.
Color Algorithms for a General Vision System

We show that an intelligent approach to color can be used to significantly improve the capabilities of a vision system. In previous work, we adopted general physical models which describe how objects interact with light. These models are far more general than those typically used in computer vision. In this report, we use our physical models to derive powerful algorithms for extracting invariant properties of objects from images. The first algorithm is used for the generic classification of objects according to material. The second algorithm provides a solution to the color constancy problem. These algorithms have been implemented and produce correct results on real images. Some examples of experimental results are presented.
Phosphorylation of HopQ1, a Type III Effector from Pseudomonas syringae, Creates a Binding Site for Host 14-3-3 Proteins1[C][W][OA]

A pathogen effector protein undergoes specific phosphorylation and associates with host 14-3-3 proteins, which affects its subcellular distribution and stability. HopQ1 (for Hrp outer protein Q), a type III effector secreted by Pseudomonas syringae pv phaseolicola, is widely conserved among diverse genera of plant bacteria. It promotes the development of halo blight in common bean (Phaseolus vulgaris). However, when this same effector is injected into Nicotiana benthamiana cells, it is recognized by the immune system and prevents infection. Although the ability to synthesize HopQ1 determines host specificity, the role it plays inside plant cells remains unexplored. Following transient expression in planta, HopQ1 was shown to copurify with host 14-3-3 proteins. The physical interaction between HopQ1 and 14-3-3a was confirmed in planta using the fluorescence resonance energy transfer-fluorescence lifetime imaging microscopy technique. Moreover, mass spectrometric analyses detected specific phosphorylation of the canonical 14-3-3 binding site (RSXpSXP, where pS denotes phosphoserine) located in the amino-terminal region of HopQ1. Amino acid substitution within this motif abrogated the association and led to altered subcellular localization of HopQ1. In addition, the mutated HopQ1 protein showed reduced stability in planta. These data suggest that the association between host 14-3-3 proteins and HopQ1 is important for modulating the properties of this bacterial effector.
Approaches to Temporal Expression Recognition in Hindi

Temporal annotation of plain text is considered a useful component of modern information retrieval tasks. In this work, different approaches for identification and classification of temporal expressions in Hindi are developed and analyzed. First, a rule-based approach is developed, which takes plain text as input and based on a set of hand-crafted rules, produces a tagged output with identified temporal expressions. This approach performs with a strict F1-measure of 0.83. In another approach, a CRF-based classifier is trained with human tagged data and is then tested on a test dataset. The trained classifier identifies the time expressions from plain text and further classifies them to various classes. This approach performs with a strict F1-measure of 0.78. Next, the CRF is replaced by an SVM-based classifier and the same experiment is performed with the same features. This approach is shown to be comparable to the CRF and performs with a strict F1-measure of 0.77. Using the rule base information as an additional feature enhances the performances to 0.86 and 0.84 for the CRF and SVM respectively. With three different comparable systems performing the extraction task, merging them to take advantage of their positives is the next step. As the first merge experiment, rule-based tagged data is fed to the CRF and SVM classifiers as additional training data. Evaluation results report an increase in F1-measure of the CRF from 0.78 to 0.8. Second, a voting-based approach is implemented, which chooses the best class for each token from the outputs of the three approaches. This approach results in the best performance for this task with a strict F1-measure of 0.88. In this process a reusable gold standard dataset for temporal tagging in Hindi is also developed. Named the ILTIMEX2012 corpus, it consists of 300 manually tagged Hindi news documents.