Miracle-dz/UniFAR-FTUs huggingface dataset:
Kefalidou, Genovefa and Sharples, Sarah (2016) Encouraging serendipity in research: designing

Mobile applications have the ability to present information to users that is influenced by their surroundings, activities and interests. Such applications have the potential to influence the likelihood of individuals experiencing ‘serendipity’, through a combination of information, context, insight and activity. This study reports the deployment of a system that sends push text suggestions to users We investigated the responses to and interactions with messages that varied in format and relevance, and which were received at different times throughout the day. Sixteen participants were asked to use a mobile diary application to record their experiences and thoughts regarding information that was received over a period of five consecutive days. Results suggest that participants’ perception of the received suggestions was influenced by the relevance of the suggestion to their interests, but that there were also positive attitudes towards seemingly irrelevant information. Qualitative data indicates that participants, if in an appropriate time and place, are willing to accept and act upon push suggestions as long as the number of suggestions that they receive is not overwhelming. This study contributes towards an understanding of how mobile users make connections with new information, furthering our understanding of how serendipitous connections and insightful thinking could be accommodated using technology. & 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Teetering between Cooperation and Competition: Social Comparisons and Peer Nominations

Within organizations, individuals both collaborate with peers in pursuit of common goals and compete with those same peers for rewards and promotions. Whether individuals perceive their peers in competitive or collaborative terms can fundamentally influence important organizational interactions and decisions. In this work, we document the prevalence of these labile relationships and we describe how subtle cues can shift individuals from identifying their peers as collaborators to identifying them as competitors. We demonstrate that prompting individuals to engage in a social comparison can generate envy and profoundly influence their willingness to nominate others for performance recognition. In a field experiment, we show that a social comparison cue reduces co-worker award nominations by 60%. In a laboratory study, we show that these cues reduce collaborators’ willingness to nominate one another when they are members of poorly performing groups, but that this effect is attenuated for highly effective groups. We discuss implications of these findings and highlight the importance of labile organizational identities for employee award programs and the broader managerial challenge of promoting collaboration in the workplace.
1 # 176 EXTENDING SPACE SYNTAX WITH EFFICIENT ENUMERATION Algorithms and Hypergraphs

In this research, we perform building‐scale analysis, and the use of a convex map may be considered first. However, partitioning an architectural space is not easy, due to the ambiguity of the space. We believe that an analysis method to decompose the space with moderate granularity while considering its ambiguity is necessary. Hiller, for example, has been analysing space by convex polygonal coverings from before. However, these methods contain the NP‐ hard set cover problem. Based on this background, we propose a novel method that enumerates all patterns covering a relatively small space, such as a floor plan of a building with finite areas like convex polygons, and quickly extracts the optimum cover from them. The obtained cover is translated into a graph based on the concept of the hypergraph, and a method for calculating network features within it is proposed. We apply this method to the building‐scale spatial data and examine the number of enumeration solutions, computational time, and network features of the obtained covering, etc. Finally, we show that the proposed method has excellent performance in these respects.
Nonperturbative Dynamics Of Reheating After Inflation: A Review

Our understanding of the state of the universe between the end of inflation and big bang nucleosynthesis (BBN) is incomplete. The dynamics at the end of inflation are rich and a potential source of observational signatures. Reheating, the energy transfer between the inflaton and Standard Model fields (possibly through intermediaries) and their subsequent thermalization, can provide clues to how inflation fits in with known high-energy physics. We provide an overview of our current understanding of the nonperturbative, nonlinear dynamics at the end of inflation, some salient features of realistic particle physics models of reheating, and how the universe reaches a thermal state before BBN. In addition, we review the analytical and numerical tools available in the literature to study preheating and reheating and discuss potential observational signatures from this fascinating era.
DIFFERENTIABLE PATH FINDING

Our motivation is to scale value iteration to larger environments without a huge increase in computational demand, and fix the problems inherent to Value Iteration Networks (VIN) such as spatial invariance and unstable optimization. We show that VINs, and even extended VINs which improve some of their shortcomings, are empirically difficult to optimize, exhibiting instability during training and sensitivity to random seeds. Furthermore, we explore whether the inductive biases utilized in past differentiable path planning modules are even necessary, and demonstrate that the requirement that the architectures strictly resemble pathfinding algorithms does not hold. We do this by designing a new path planning architecture called the LSTM-Iteration Network, which achieves better performance than VINs in metrics such as success rate, training stability, and sensitivity to random seeds.
Title: MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model. Authors:

Bovine mastitis is an inflammation-driven disease of the bovine mammary gland that costs the global dairy industry several billion dollars per annum. Because disease susceptibility is a multi-factorial complex phenotype, an integrative biology approach is required to dissect the molecular networks involved. Here, we report such an approach, using next generation sequencing combined with advanced network and pathway biology methods to simultaneously profile mRNA and miRNA expression at multiple time-points (0, 12, 24, 36 and 48h) in both milk and blood FACS-isolated CD14+ monocytes from animals infected in vivo with Streptococcus uberis. More than 3,700 differentially expressed (DE) genes were identified in milk-isolated monocytes (MIMs), a key immune cell recruited to the site of infection during mastitis. Up-regulated genes were significantly enriched for inflammatory pathways, while down-regulated genes were enriched for non-glycolytic metabolic pathways. Monocyte transcriptional changes in the blood, however, were more subtle but highlighted the impact of this infection systemically. Genes up-regulated in bloodisolated-monocytes (BIMs) showed a significant association with interferon and chemokine signalling. Furthermore, twenty-six miRNAs were differentially expressed in MIMs and three in BIMs. Pathway analysis revealed that predicted targets of downregulated miRNAs were highly enriched for roles in innate immunity (FDR < 3.4E-8) in particular TLR signalling, while up-regulated miRNAs preferentially targeted genes involved in metabolism. We conclude that during S. uberis infection miRNAs are key amplifiers of monocyte inflammatory response networks and repressors of several metabolic pathways.
Multiepoch Very Long Baseline Array Observations of EGRET-detected Quasars and BL Lacertae Objects: Superluminal Motion of Gamma-Ray Bright Blazars

We present the results of a program to monitor the structure of the radio emission in 42 γ-ray bright blazars (31 quasars and 11 BL Lac objects) with the Very Long Baseline Array (VLBA) at 43, 22, and occasionally 15 and 8.4 GHz, over the period from 1993 November to 1997 July. We determine proper motions in 33 sources and find that the apparent superluminal motions in γ-ray sources are much faster than for the general population of bright compact radio sources. This follows the strong dependence of the γ-ray flux on the level of relativistic beaming for both external radiation Compton and synchrotron self-Compton emission. There is a positive correlation (correlation coefficient r = 0.45) between the flux density of the VLBI core and the γ-ray flux and a moderate correlation (partial correlation coefficient r = 0.31) between γ-ray apparent luminosity and superluminal velocities of jet components, as expected if the γ-ray emission originates in a very compact region of the relativistic jet and is highly beamed. In 43% of the sources the jet bends by more than 20° on parsec scales, which is consistent with amplification by projection effects of modest actual changes in position angle. In 27 of the sources in the sample there is at least one non-core component that appears to be stationary during our observations. Different characteristics of stationary features close to and farther from the core lead us to suggest two different classes of stationary components: those within about 2 mas of the core, probably associated with standing hydrodynamical compressions, and those farther down the jet, which tend to be associated with bends in the jet.
A HYBRID FEATURE SELECTION MODEL FOR SOFTWARE FAULT PREDICTION

Software fault prediction plays a vital role in software quality assurance. Identifying the faulty modules helps to better concentrate on those modules and helps improve the quality of the software. With increasing complexity of software nowadays feature selection is important to remove the redundant, irrelevant and erroneous data from the dataset. In general, Feature selection is done mainly based on filter and wrapper. In this paper a hybrid feature selection method is proposed which gives a better prediction than the traditional methods. NASA’s public dataset KC1 available at promise software engineering repository is used. To evaluate the performance of the software fault prediction models Accuracy, Mean absolute error (MAE), Root mean squared error (RMSE) values are used.
Genetics and Osteoporosis

Osteoporosis is a multifactorial disease influenced by multiple factors and characterized by an imbalance in the regulation of bone remodeling that cause microarchitectural deterioration which compromises the bone strength and leads to bone fragility increasing the fracture risk. Since several years ago, the World Health Organization has considered osteoporosis as one of the most important public health issues worldwide, with a great repercussion in patients’ life quality and in their familiar, social and work environments. Osteoporosis is an important problem in Latin America, currently its prevalence is similar to that in South Europe and slightly lower than in North Europe and among white population in the USA; World Health Organization estimates that in the forthcoming 50 years, osteoporosis prevalence will increase in Latin America until reach those of the currently observable in Europe and USA (World Health Organization [WHO], 1994; National Institute of Health [NIH], 2001 Consensus Development Panel on Osteoporosis Prevention, Diagnosis and Therapy; Cole ZA et al., 2008). During the last decades, the life expectancy has been increased notoriously and the number of subjects older than 60 years old has been increased. This situation in combination with the adverse environmental conditions and the life style, will cause a notorious increment in the incidence of chronic-degenerative diseases in the next decades, as will occur with osteoporosis. Certainly, primary osteoporosis use to be more frequent in posmenopausal women (Greespan et al., 1993); however occasionally it appears in premenopausal women which present several risk factors and even males may be affected by this disorder. It is important to mention that the actual life style favours the inadequate bone quality of children and young people (Asociacion Mexicana de Metabolismo Oseo y Mineral, 2001). There are two forms of osteoporosis; primary OP, named posmenopausal or senile form and secondary OP, which is related to diverse endocrine, renal, rheumatic and genetic diseases, and with the prolonged administration of some drugs which induce bone loss (Riggs et al., 1986; Elliot-Gibson et al., 2004). Discussing about osteoporosis it is necessary to mention the term “peak bone mass” (PBM), which refers to the maximum bone mass that an individual reaches in his life and it occurs between 20-30 years old approximately. PBM is the result of the interaction of multiple genetic and environmental factors; upon the PBM is reached, progressive loss of bone mass occurs naturally, depending on the magnitude and speed of subsequent bone loss (Burclar et al., 1989; Kanis et al., 1994; Gueguen et al., 1995.). The annual average bone loss in posmenopausal women is estimated in 1-2%, and 0.2. -0.5 % in males. It is considered that
Fatigue from sleep loss and circadian misalignment jeopardizes cognitive performance and safety of individuals

Form Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 222024302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) 29 May 2008 2. REPORT TYPE Final Report 3. DATES COVERED (From To) 1 Jan 2005 – 29 Feb 2008 4. TITLE AND SUBTITLE Individualized Biomathematical Modeling of 5a. CONTRACT NUMBER
Degassing History of Water, Sulfur, and Carbon in Submarine Lavas from Kilauea Volcano, Hawaii

Major, minor, and dissolved volatile element concentrations were measured in tholeiitic glasses from the submarine portion (Puna Ridge) of the east rift zone of Kilauea Volcano, Hawaii. Dissolved $$H_{2}O$$ and S concentrations display a wide range relative to nonvolatile incompatible elements at all depths. This range cannot be readily explained by fractional crystallization, degassing of $$H_{2}O$$ and S during eruption on the seafloor, or source region heterogeneities. Dissolved $$CO_{2}$$ concentrations, in contrast, show a positive correlation with eruption depth and typically agree within error with the solubility at that depth. We propose that most magmas along the Puna Ridge result from (1) mixing of a relatively volatile-rich, unde-gassed component with magmas that experienced low pressure (perhaps subaerial) degassing during which substantial $$H_{2}O$$, S, and $$CO_{2}$$ were lost, followed by (2) fractional crystallization of olivine, clinopyroxene, and plagioclase from this mixture to generate a residual liquid; and (3) further degassing, principally of $$CO_{2}$$ for samples erupted deeper than 1000 m, during eruption on the seafloor. The degassed end member may form at upper levels of the summit magma chamber (assuming less than lithostatic pressure gradients), during residence at shallow levels in the crust, or during sustained summit eruptions. The final phase of degassing during eruption on the seafloor occurs slowly enough to achieve melt/vapor equilibrium during exsolution of the typically $$CO_{2}$$-rich vapor phase. We predict that average Kilauean primary magmas with 16% MgO contain $$~0.47 wt \% CO_{2}$$, ~900 ppm S, and have $$\delta D$$ values of ~-30 to -40‰. Our model predicts that submarine lavas from wholly submarine volcanoes (i.e., Loihi), for which there is no opportunity to generate the degassed end member by low pressure degassing, will be enriched in volatiles relative to those from volcanoes whose summits have breached the sea surface (i.e., Kilauea and Mauna Loa).
Real Time Robust Embedded Face Detection Using High Level Description

Face detection is a fundamental prerequisite step in the process of face recognition. It consists of automatically finding all the faces in an image despite the considerable variations of lighting, background, appearance of people, position/orientation of faces, and their sizes. This type of object detection has the distinction of having a very large intra-class, making it a particularly difficult problem to solve, especially when one wishes to achieve real time processing. A human being has a great ability to analyze images. He can extract the information about it and focus only on areas of interest (the phenomenon of attention). Thereafter he can detect faces in an extremely reliable way. Indeed, a human being is able to easily locate faces in its environment despite difficult conditions such as occlusions of parts of a face and bad lightening. Many studies have been conducted to try to replicate this process, automatically using machines, because face detection is considered as a prerequisite for many computer vision application areas such as security, surveillance, and content based image retrieval. Over the last two decades multiple robust algorithmic solutions were proposed. However, researches in the field of computer vision and pattern recognition in particular tend to focus on the algorithmic and functional parts. This generally leads to implementations with little constraints of time, computing power and memory. Most of these techniques, even if they achieve good performance in terms of detection, are not suited for real time application systems. Nonetheless, Boosting–based methods, firstly introduced by Viola and Jones in (Viola & Jones, 2001; 2002), has led the state-of-the-art in face detection systems. These methods present the first near real time robust solution and by far the best speed / detection compromise in the state-of-the-art (up to 15 frames/s and 90% detection on 320x240 images). This family of detectors relies upon a cascade of several classification stages of progressive complexity (around 20-40 stages for face detection). Depending on its complexity, each stage contains several classifiers trained by a boosting algorithm (Freund & Schapire, 1995; Lienhart, Kuranov, & Pisarevsky, 2003; Viola & Jones, 2002) These algorithms help achieving a linear combination of weak classifiers (often a single threshold), capable of real time face detection with high detection rates. Such a technique can be divided into two phases: Training and detection (through the cascade). While the training phase can be done offline and might take several days of processing, the final cascade detector should enable real-time processing. The goal is to run through a given
Molar Mass and Molecular Weight Distribution Determination Of UHMWPE Synthesized Using a Living Homogeneous Catalyst

Understanding of the physical characteristics of a polymer requires molar mass determination. For the commercially available polymers, having average molar mass below 1 000 000 g/mol, chromatography is the method that is often applied to determine the molar mass and molar mass distribution. However, the application of conventional chromatography techniques for polymers having molar mass >1 000 000 g/mol becomes very challenging, and often the results are disputed. In this article, melt rheometry based on the “modulus model” is utilized to measure the molar mass and polydispersity of ultra high-molecular-weight polyethylenes (UHMWPEs) having molar mass >1 000 000 g/mol. Results are compared with the chromatography data of the same polymer samples and the boundary conditions where the chromatography technique fails, whereas the rheometry provides the desired information is discussed. The rheological method is based on converting the relaxation spectrum from the time domain to the molecular weight domain and.
AWARD NUMBER: W81XWH-04-1-0046 TITLE: Identify the impact of TGF-ß signaling on the stroma in the progression of prostate cancer

• Placencio, V.R. , Sharif-Afshar, A. -R. , Simon W. Hayward, and Bhowmick N.A. (2005) Prostatic Epithelial Transformation and Androgen Responsiveness Regulated by Stromal-Epithelial Interactions. (oral presentation) Society For Basic Urologic Research Meeting. Miami, FL. Awards received based on work supported by this grant None Products CDNA construct, cell lines, and animal models developed • Development of a in vivo tissue recombination model that incorporates large T antigen expressing prostatic epithelia with stromal cells defi cient in TGFß responsivity. • Transgenic mouse line termed FßKO/TOPGal that enables the study of canonical Wnt signaling in the context of stromal cells defi cient for TGFß responsivity.
6.047/6.878 Lecture 2: Sequence Alignment and Dynamic Programming

Evolution has preserved functional elements in the genome. Such elements often manifest themselves as homologues, or similar sequences in descendants of a common ancestor. The two main types of homologous sequences are orthologous and paralogous sequences. Orthologous sequences typically have similar functions in both the ancestor and the descendant and arise through speciation events, while paralagous sequences arise from common ancestors through gene duplication. Furthermore, paralagous genes imply a common ancestor but, due to mutation and evolution the functionality of that particular gene has shifted considerably. In order to “read” evolution we will mostly be interested in studying orthologous gene sequences since such intergenic regions are extremely well preserved. Aligning sequences is one of the main ways of discovering such similarities between different ancestors. And in solving sequence alignment problems, the primary computational tool will be Dynamic Programming.
Building EÆcient and E ective Metasearch Engines

Frequently a user's information needs are stored in the databases of multiple search engines. It is inconvenient and ineÆcient for an ordinary user to invoke multiple search engines and identify useful documents from the returned results. To support uni ed access to multiple search engines, a metasearch engine can be constructed. When a metasearch engine receives a query from a user, it invokes the underlying search engines to retrieve useful information for the user. Metasearch engines have other bene ts as a search tool such as increasing the search coverage of the Web and improving the scalability of the search. In this article, we survey techniques that have been proposed to tackle several underlying challenges for building a good metasearch engine. Among the main challenges, the database selection problem is to identify search engines that are likely to return useful documents to a given query. The document selection problem is to determine what documents to retrieve from each identi ed search engine. The result merging problem is to combine the documents returned from multiple search engines. We will also point out some problems that need to be further researched.