Miracle-dz/UniFAR-FTUs huggingface dataset:
Survey on CCL Based Co-Operative Caching in Disruption Tolerance Networks

: Disruption Tolerances Network (DTN) is characterized by low node density, lack of global network information, unpredictable node mobility. The current research efforts in DTNs focus on data forwarding limited work has been done on providing efficient data access to mobile users. In this paper we propose a novel approach to support cooperative caching in DTNs, which enables the sharing and coordination of cached data among multiple nodes and reduce data access delay. Our basic idea is to cache data at a set of network central locations (NCLs), which can be easily accessed by other nodes in the network. Extensive trace-driven simulations show that, our approach significantly improves data access performance compared to existing schemes.
A System for Energy Measurement on Accelerators (SEMA)

The fastest supercomputer in 2016 consumed over 17MW for a mere 33 Petaflops of performance. This makes energy efficiency a crucial obstacle to overcome in order to make Exascale computing a reality. Over 50% of the performance of this supercomputer is due to the presence of accelerators or coprocessors that are designed to do certain kind of mathematical operations in an energy efficient manner. Currently, accelerators such as NVIDIA GPGPUs and Intel Xeon Phi dominate this market. However, with the addition of FPGAs from Altera and Xilinx in HPC clusters, more options for accelerators are becoming available. Furthermore, several EU funded projects, including the Centre of Excellence and FETHPC projects such as ESCAPE, READEX, ESiWACE investigate HPC systems consisting of accelerators for Exascale-related applications. The dominance of such devices for energy efficient computing makes it crucial to understand the relationship between power consumption, performance and application code in order to exploit them in the most effective manner. The measurement of power consumption is supported at different levels of accuracy by different vendors through their platforms. However, they lack any standardized metrics between them making it difficult to compare them directly. Further, the accuracy they support is at a coarse level making it impossible to use the measurements to profile the application code and to extract insights that help the programmer. At the Irish Center for High-End Computing (ICHEC), we have developed a System for Energy Measurement on Accelerators (SEMA) that allows measurement of any accelerator or any number of them to an accuracy of milliwatt and a resolution of millisecond. SEMA works based on the standard current shunt-based power measurement technique. Such a methodology is not new and there has been prior work done within a lab environment. SEMA embarks to be different and we focus equally on usability as much as technical feasibility. To meet this endeavor, we have come up with set of novel ideas that abstract the technical details and provide the users with a very simple interface
Visual-Graphical Methods for Exploring Longitudinal Data

Longitudinal data typically have the characteristics of changes over time, nonlinear growth patterns, between-subjects variability, and the within errors exhibiting heteroscedasticity and dependence. The data exploration is more complicated than that of cross-sectional data. The purpose of this paper is to organize/integrate of various visual-graphical techniques to explore longitudinal data. From the application of the proposed methods, investigators can answer the research questions include characterizing or describing the growth patterns at both group and individual level, identifying the time points where important changes occur and unusual subjects, selecting suitable statistical models, and suggesting possible within-error variance. Keywords—Data exploration, exploratory analysis, HLMs/LMEs, longitudinal data, visual-graphical methods.
Kirsch Compass Kernel Edge Detection Algorithm for Micro Calcification Clusters in Mammograms

: Edge detection plays a vital role in the processing of images. In this process, Edge detection identifies and locate sharp edges of discontinuity in images andit has a great significance in computer-aided diagnosis system for the automatic detection of clustered micro calcifications in digitized mammograms. Numerous algorithms have been suggested so for extracting medical image edges, howeverfew of them are well suited for edge extraction of micro calcifications for obtaining discontinuous edges and continuous edges. This paper, intends an integrated new methodology for clustered micro calcifications edge detection of Kirsch edge operator and edge linking with Markov model. Kirsch edge operator extracts first, initial edges and then the thin initial edges since it is used as a derivative mask.It is also using an edge linking technique, fill many gaps in the edge image. Lastly closed boundaries micro calcifications are achieved by Markov model. Under this testing the algorithm highlights that it can detect closed edges with less over-detection points.
Diagnoses of Neisseria Bacteria via Neural Networks Techniques

This paper presented simple approach that automatically detects Neisseria Bacteria cell in the cerebrospinal fluid smear images. The proposed methodology mainly consists of cerebrospinal fluid smear images acquisition, transformation form red, green, blue smear images in to other color spaces. This step followed by subbing images and segmenting the images to extracting the images features then validation and classifying the Bacteria images based in features extracted using neural networks. The proposed diagnosis for Neisseria Bacteria through neural network techniques has performed high-precision performance in some suggested groups.
Impact of Bike Facilities on Residential Property Prices

As many cities are investing in street improvements or transportation infrastructure upgrades to provide better bike access or more complete bike networks, many practitioners, planners, and policy makers are seeking more conclusive evidence about the economic value of bike infrastructure and bike facilities. With the use of residential property values as indicators of consumer preferences for bicycle infrastructure, many scholars have shown the importance of green space and off-street bike trails as amenities valuable to property owners. However, empirical evidence on the relationship of on-street bike facilities and property values remains relatively inconsistent. The unique focus of this study was advanced bike facilities that represented higher levels of bike priority or bike infrastructure investments shown to be more desirable to a larger portion of the population. Through the separate estimation of ordinary least squares hedonic pricing models and spatial autoregressive hedonic models of single and multifamily properties, it was found that proximity to advanced bike facilities (measured by distance) had significant and positive effects on all property values, which highlighted household preferences for high-quality bike infrastructure. Furthermore, the study showed that the extensiveness of the bike network (measured by density) was a positive and statistically significant contributor to the prices for all property types, even after proximity was controlled for with respect to bike facilities and other property, neighborhood, and transaction characteristics. Finally, estimated coefficients were applied to assess the property value impacts of the Green Loop (i.e., the proposed Portland, Oregon, signature bike infrastructure concept), which illustrated the importance of considering the accessibility and the extensiveness of bike facility networks.
Board 41: Development and Validation of the STEM Study Strategies Questionnaire for STEM College Students

In this research-based paper, we discuss the development of a measure of Rice University students’ STEM study strategies and then explore the measure’s correlation with several important psychological outcomes in a sample of underprepared first-year STEM students ( n =94). STEM attrition remains a pressing concern nationally, particularly for students who took less rigorous STEM courses in high school, a population that disproportionally comprises underrepresented minorities. The authors developed an 11-item measure of STEM-specific study strategies, termed the STEM Study Strategies Questionnaire. We explored STEM-specific identity, self-efficacy, and career aspirations, as well as perceived utility of attaining a STEM degree, using a model based on Eccles and Wigfield’s (2002) expectancy-value framework of achievement. An exploratory factor analysis found a four-factor solution to the newly developed scale: Group Work in STEM, Active STEM Learning, Interactions with STEM Professors, and STEM Exam Familiarity. The authors found significant moderate to strong correlations among all psychological variables, as well as with the Group Work and STEM Exam Familiarity factors. Next steps for this research are to develop further measure items to capture each of the four factors and to conduct confirmatory analyses on different samples of STEM students, both those who are relatively underprepared and appropriately prepared for college STEM coursework.
Optimal scheduling of energy storage under forecast uncertainties

Recent studies have concluded that battery energy storage will soon be economically competitive if its cost continues to decline. The authors propose a two-stage look-ahead daily scheduling strategy for distributed energy storage located in distribution networks with a substantial photovoltaic (PV) penetration. They assume that the load serving entity operates this energy storage to harness simultaneously multiple streams of benefits: energy arbitrage, peak shaving, minimising deviations from the load forecast and regulation service. To determine the optimal capacity bid into the day-ahead regulation market and address the price, load, and solar forecast uncertainties, they propose a two-stage optimisation model that bids regulation capacity on the day ahead and determines the storage dispatch schedule in real time. At the day-ahead stage, the load serving entity reserves a portion of the storage capacity for regulation, while the remaining capacity is dispatched for energy arbitrage, peak shaving and minimising the deviations from the forecast. Result suggests that regulation services account for the majority of these benefits. The energy storage is dispatched for peak shaving and forecast-deviation minimisation from around noon to late evening. During the rest of day, storage is dispatched primarily for regulation services.
Listeria monocytogenes Macrophages to Cell Death Induced by Production of Type I IFN Sensitizes

Type I IFNs (IFN- (cid:1) / (cid:2) ) modulate innate immune responses. Here we show activation of transcription factor IFN regulatory factor 3, the synthesis of large amounts of IFN- (cid:2) mRNA, and type I IFN signal transduction in macrophages infected with Listeria monocytogenes . Expression of the bacterial virulence protein listeriolysin O was necessary, but not sufﬁcient, for efﬁcient IFN- (cid:2) production. Signaling through a pathway involving the type I IFN receptor and Stat1 sensitized macrophages to L. monocytogenes induced cell death in a manner not requiring inducible NO synthase (nitric oxide synthase 2) or protein kinase R, potential effectors of type I IFN action during microbial infections. The data stress the importance of type I IFN for the course of infections with intracellular bacteria and suggest that factors other than listeriolysin O contribute to macrophage death during Listeria infection. The Journal of Immunology, 2002, 169: 6522–6529.
A Linked Dataverse Knows Better: Boosting Recommendation Quality Using Semantic Knowledge

—The advent of Linked Open Data (LOD) gave birth to a plethora of open datasets freely available to everyone. Accompanied with LOD, a new research ﬁeld arises focusing on how to handle and to take advantage of this huge amount of data. In this paper, we introduce a novel approach utilizing and aggregating open datasets to compute the most-related entities for a set of weighted input entities. We optimize different algorithms for large semantic datasets enabling combining data from different semantic open sources and providing high quality results even if only limited resources are available. We evaluate our approach on a large encyclopedic dataset. The evaluation results show that our approach efﬁciently supports different semantic edge types. The application build on our framework provides highly relevant results and visual explanations helping the user to understand the semantic relationship between the computed entities.
Pooled ORF Expression Technology (POET) USING PROTEOMICS TO SCREEN POOLS OF OPEN READING FRAMES FOR PROTEIN EXPRESSION* □ S

We have developed a pooled ORF expression technology, POET, that uses recombinational cloning and proteomic methods (two-dimensional gel electrophoresis and mass spectrometry) to identify ORFs that when expressed are likely to yield high levels of soluble, purified protein. Because the method works on pools of ORFs, the procedures needed to subclone, express, purify, and assay protein expression for hundreds of clones are greatly simplified. Small scale expression and purification of 12 positive clones identified by POET from a pool of 688 Caenorhabditis elegans ORFs expressed in Escherichia coli yielded on average 6 times as much protein as 12 negative clones. Larger scale expression and purification of six of the positive clones yielded 47–374 mg of purified protein/liter. Using POET, pools of ORFs can be con-structed, and the pools of the resulting proteins can be analyzed and manipulated to rapidly acquire information about the attributes of hundreds of proteins simulta-neously. of Predicted a dish A of 0.5, isopropyl 1-thio- (cid:3) D -galactopyranoside m expressed overnight 16 determine fraction of soluble and Epicenter), and
Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at root s = 13 TeV using the ATLAS detector

Aaboud, M. ; Aad, G. ; Abbott, B. ; Abdallah, J.; Abdinov, O. ; Abeloos, B; Aben, R. ; AbouZeid, O.S. ; Abraham, NL; Abramowicz, H. ; Dam, Mogens; Hansen, Jørn Dines; Hansen, Jørgen Beck; Xella, Stefania; Hansen, Peter Henrik; Petersen, Troels Christian; Thomsen, Lotte Ansgaard; Pingel, Almut Maria; Løvschall-Jensen, Ask Emil; Alonso Diaz, Alejandro; Monk, James William; Pedersen, Lars Egholm; Wiglesworth, Graig; Galster, Gorm Aske Gram Krohn
VaccinationConformational Viral Epitope by DNA Responses Against an Isolated, Priming Biologically Active Antibody

The immunodominant, conformational “a” determinant of hepatitis B surface Ag (HBsAg) elicits Ab responses. We selectively expressed the Ab-binding, glycosylated, native a determinant (residue 120–147) of HBsAg in a fusion protein containing C-terminally the HBsAg fragment SII (residue 80–180) fused to a SV40 T-Ag-derived hsp73-binding 77 aa (T 77 ) or non-hsp-binding 60 aa (T 60 ) N terminus. A DNA vaccine encoding non-hsp-binding secreted T 60 -SII fusion protein-stimulated murine Ab responses with a similar efﬁcacy as a DNA vaccine encoding the secreted, native, small HBsAg. A DNA vaccine encoding hsp73-binding, intracellular T 77 -SII fusion protein-stimulated murine Ab responses less efﬁciently but comparable to a DNA vaccine encoding the intracellular, native, large HBsAg. HBsAg-speciﬁc Abs elicited by either the T 60 -SII-expressing or the T 77 -SII-expressing DNA vaccine suppressed HBsAg antigenemia in transgenic mice that produce HBsAg from a transgene in the liver; hence, a biologically active B cell response cross-reacting with the native, viral envelope epitope was primed by both DNA vaccine constructs. HBsAg-speciﬁc Ab and CTL responses were coprimed when an S 20–50 fragment (containing the immunodominant, L d -binding epitope S 28–39 ) of HBsAg was fused C-terminally to the pCI/T 77 -SII sequence (pCI/T 77 -SII-L d DNA vaccine). Chimeric, polyepitope DNA vaccines encoding conformational, Ab-binding epitopes and MHC class I-binding epitopes can thus efﬁciently deliver antigenic information to different compartments of the immune system in an immunogenic
ATVB in Focus Vascular Cell Lineage Determination and Differentiation

Development of in vitro models by which to study smooth muscle cell (SMC) differentiation has been hindered by some peculiarities intrinsic to these cells, namely their different embryological origins and their ability to undergo phenotypic modulation in cell culture. Although many in vitro models are available for studying SMC differentiation, careful consideration should be taken so that the model chosen fits the questions being posed. In this review, we summarize several well-established in vitro models available to study SMC differentiation from stem cells and outline novel mechanisms recently identified as underlying SMC differentiation programs. (Arterioscler Thromb Vasc Biol. 2011;31:1485-1494.)
A Site-speciﬁc Measure for Rate Difference After Gene Duplication or Speciation

Gene family proliferation by gene (genome) duplication has provided the raw materials for functional innovations (Ohno 1970; Lundin 1993; Holland et al. 1994; Henikoff et al. 1997; Golding and Dean 1998). Several models were proposed for functional divergence among member genes (e.g., Li 1983; Clark 1994; Hughes 1994; Fryxell 1996; Nei, Gu, and Sitnikova 1997; Force et al. 1999), but the details remain largely unknown. Gu (1999) developed a statistical method for testing type I functional divergence, i.e., changes in protein function between two gene clusters result in changes in selective constraints (and therefore shifted evolutionary rates) at some residues. It stands in contrast to type II functional divergence, i.e., changes in protein function between two gene clusters do not alter the level of selective constraints. Amino acid residues with rate shifts are the sites that have either gained or lost importance as a consequence of the change of function during evolution, as proposed by the hypothesis of type I functional divergence (Gu 1999). Moreover, type I functional divergence provides a biological basis for the covarion theory of molecular evolution (Fitch and Markowitz 1970). If a statistical testing shows a significant rate difference between two gene clusters, it is of great interest to predict important amino acid residues, which can be further verified by available functional-structural evidence (Dermitzakis and Clark 2001; Gaucher, Miyamoto, and Benner 2001; Wang and Gu 2001). The posterior probability of each site is suitable to develop a statistically sound profile for selecting critical amino acid residues (Gu 1999), but little information is provided about how much rate difference is generated at these sites after gene duplication. In this article, we report a new site-specific profile for the rate difference, which is useful for studying the pattern of protein sequence evolution. Consider two gene clusters generated by gene duplication (or speciation), e.g., see figure 1, the bone morphogenetic proteins (BMP) gene family tree. In each cluster, a site can be in either of two states: (1) F0, which means no altered functional constraint after gene duplication, and (2) F1, which means altered functional constraint at this site after gene duplication. As a result, there are four combined states in the case of two gene clusters: (1) F0 in both clusters, denoted by S0 5 (F0, F0), resulting in no rate difference between clusters; and
and Progressive Lymphopenia Receptor-Deficient Mice Results in Profound Homeostatic Proliferation in Lamin B Reduced Lymphocyte Longevity and

The lamin B receptor (LBR) is a highly unusual inner nuclear membrane protein with multiple functions. Reduced levels are associated with decreased neutrophil lobularity, whereas complete absence of LBR results in severe skeletal dysplasia and in utero/ perinatal lethality. We describe a mouse pedigree, Lym3 , with normal bone marrow and thymic development but profound and progressive lymphopenia particularly within the T cell compartment. This defect arises from a point mutation within the Lbr gene with only trace mutant protein detectable in homozygotes, albeit sufﬁcient for normal development. Reduced T cell homeostatic proliferative potential and life span in vivo were found to contribute to lymphopenia. To investigate the role of LBR in gene silencing in hematopoietic cells, we examined gene expression in wild-type and mutant lymph node CD8 T cells and bone marrow neutrophils. Although LBR deﬁciency had a very mild impact on gene expression overall, for common genes differentially expressed in both LBR-deﬁcient CD8 T cells and neutrophils, gene upregulation prevailed, supporting a role for LBR in their suppression. In summary, this study demonstrates that LBR deﬁciency affects not only nuclear architecture but also proliferation, cell viability, and gene expression of hematopoietic cells. The Journal of Immunology , 2012, 188: 122–134. outer and inner mem-branes, separated by luminal space, and is nuclear pore complexes. inner nuclear is a scaffolding structure known as the lamina, which the nucleoplasm.
Applying Technology to Enhance Student Satisfaction and Engagement: Case of Business Students

- Extending learning beyond the walls of classroom is inevitable to enhance student satisfaction. Past studies have researched blended learning in silo, and not much attention has been paid to learner’s characteristics. The objective of this study is to examine the complex relationship among stuent satisfaction, engagement, blended learning and learner’s characteristics. Data was collected from LMS records, focus-group interviews and self-administered surveys. The findings depict that business students were highly engaged and satisfied with blended learning. The present study contributes to the literature and proposes an integrated framework of blended learning and student engagement with moderating role of learner’s proficiency.