Miracle-dz/UniFAR-FTUs huggingface dataset:
The Syndicated Loan Market: Developments in the North American Context

The author describes the rapid development of the syndicated corporate loan market in the 1990s. He explores the historical forces that led to the development of the contemporary U.S. syndicated loan market, which is effectively a hybrid of the investment banking and commercial banking worlds. He suggests that there has been a notable change in large corporate lending over the past decade, as the old bilateral bank-client lending relationships have been replaced by a world that is much more transaction-oriented and market-oriented. The Canadian syndicated loan market has been strongly influenced by its U.S. counterpart, but it is not yet at the same level of development. The author explores potential risk issues for the new corporate loan market, including implications for the distribution of credit risk in the system, risks in the underwriting process, the monitoring function, and the potential for risk arising from asymmetric information.
Point pattern analysis with spatially varying covariate effects, applied to the study of cerebrovascular deaths

This article proposes a modeling approach for handling spatial heterogeneity present in the study of the geographical pattern of deaths due to cerebrovascular disease.The framework involvesa point pattern analysis with components exhibiting spatial variation. Preliminary studies indicate that mortality of this disease and the effect of relevant covariates do not exhibit uniform geographic distribution. Our model extends a previously proposed model in the literature that uses spatial and non‐spatial variables by allowing for spatial variation of the effect of non‐spatial covariates. A number of relative risk indicators are derived by comparing different covariate levels, different geographic locations, or both. The methodology is applied to the study of the geographical death pattern of cerebrovascular deaths in the city of Rio de Janeiro. The results compare well against existing alternatives, including fixed covariate effects. Our model is able to capture and highlight important data information that would not be noticed otherwise, providing information that is required for appropriate health decision‐making. Copyright © 2014 John Wiley & Sons, Ltd.
DynaMMo: mining and summarization of coevolving sequences with missing values

Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn their dynamics, making our algorithm able to function even when there are missing values. We performed experiments on both real and synthetic datasets spanning several megabytes, including motion capture sequences and chlorine levels in drinking water. We show that our proposed DynaMMo method (a) can successfully learn the latent variables and their evolution; (b) can provide high compression for little loss of reconstruction accuracy; (c) can extract compact but powerful features for segmentation, interpretation, and forecasting; (d) has complexity linear on the duration of sequences.
The Effect of Universal Influenza Immunization on Mortality and Health Care Use

Background In 2000, Ontario, Canada, initiated a universal influenza immunization program (UIIP) to provide free influenza vaccines for the entire population aged 6 mo or older. Influenza immunization increased more rapidly in younger age groups in Ontario compared to other Canadian provinces, which all maintained targeted immunization programs. We evaluated the effect of Ontario's UIIP on influenza-associated mortality, hospitalizations, emergency department (ED) use, and visits to doctors' offices. Methods and Findings Mortality and hospitalization data from 1997 to 2004 for all ten Canadian provinces were obtained from national datasets. Physician billing claims for visits to EDs and doctors' offices were obtained from provincial administrative datasets for four provinces with comprehensive data. Since outcomes coded as influenza are known to underestimate the true burden of influenza, we studied more broadly defined conditions. Hospitalizations, ED use, doctors' office visits for pneumonia and influenza, and all-cause mortality from 1997 to 2004 were modelled using Poisson regression, controlling for age, sex, province, influenza surveillance data, and temporal trends, and used to estimate the expected baseline outcome rates in the absence of influenza activity. The primary outcome was then defined as influenza-associated events, or the difference between the observed events and the expected baseline events. Changes in influenza-associated outcome rates before and after UIIP introduction in Ontario were compared to the corresponding changes in other provinces. After UIIP introduction, influenza-associated mortality decreased more in Ontario (relative rate [RR] = 0.26) than in other provinces (RR = 0.43) (ratio of RRs = 0.61, p = 0.002). Similar differences between Ontario and other provinces were observed for influenza-associated hospitalizations (RR = 0.25 versus 0.44, ratio of RRs = 0.58, p < 0.001), ED use (RR = 0.31 versus 0.69, ratio of RRs = 0.45, p < 0.001), and doctors' office visits (RR = 0.21 versus 0.52, ratio of RRs = 0.41, p < 0.001). Sensitivity analyses were carried out to assess consistency, specificity, and the presence of a dose-response relationship. Limitations of this study include the ecological study design, the nonspecific outcomes, difficulty in modeling baseline events, data quality and availability, and the inability to control for potentially important confounders. Conclusions Compared to targeted programs in other provinces, introduction of universal vaccination in Ontario in 2000 was associated with relative reductions in influenza-associated mortality and health care use. The results of this large-scale natural experiment suggest that universal vaccination may be an effective public health measure for reducing the annual burden of influenza.
Galaxy groups in the 2dF Galaxy Redshift Survey: the catalogue

We construct a galaxy groups catalogue from the public 100-K data release of the 2dF Galaxy Redshift Survey. The group identification is carried out using a slightly modified version of the group-finding algorithm developed by Huchra & Geller. Several tests using mock catalogues allow us to find the optimal conditions to increase the reliability of the final group sample. A minimum number of four members, an outer number density enhancement of 80 and a linking radial cut-off of 200 km s' are the best obtained values from the analysis. Using these parameters, approximately 90 per cent of groups identified in real space have a redshift space counterpart. On the other hand, the level of contamination in redshift space reaches 30 per cent, including ∼6 per cent of artificial groups and ∼24 per cent of groups associated with binaries or triplets in real space. The final sample comprises 2209 galaxy groups covering the sky region described by Colless et al. spanning over the redshift range of 0.003 ≤ z ≤ 0.25 with a mean redshift of 0.1.
Bringing Modern Web Applications to Disconnected Networks

Opportunistic networking is one way to realize pervasive applications while placing little demand on network infrastructure, especially for operating in less well connected environments. In contrast to the ubiquitous network access model inherent to many cloud-based applications, for which the web browser forms the user front end, opportunistic applications require installing software on mobile devices. Even though app stores (when accessible) offer scalable distribution mechanisms for applications, a designer needs to support multiple OS platforms and only some of those are suitable for opportunistic operation to begin with. In this paper, we present a web browser-based interaction framework that 1) allows users to interact with opportunistic application content without installing the respective app and 2) even supports users whose mobile OSes do not support opportunistic networking at all via minimal stand-alone infrastructure. We describe our system and protocol design, validate its operation using simulations, and report on our implementation including support for six opportunistic applications.
Association for Information Systems AIS Electronic Library ( AISeL ) Selected Papers of the IRIS Scandinavian ( IRIS ) 2014 Design Principles for Online Information Security Laboratory

In this paper, we reported an online InfoSec Lab based on initial design principles derived from kernel theories such as Conversational Framework (CF), Constructive Alignment (CA), and Personalized System of Instruction (PSI). The overall research was conducted using the action design research approach. In doing so, the iterative cycles and critical reflections during the process helped to refine a set of existing design principles. The study contributes to the IS community by providing design principles for an online InfoSec Lab that utilizes state-of-the art technology for mixed classrooms.
Using "History Matters" with a Ninth Grade Class

I WANDER AROUND the computer lab watching my ninth grade class, all of whom appear absorbed by what they are discovering on the Intemrnet. Even the sometimes frustrating hunt for new information seems to fascinate them. Occasionally one student calls across the room to another when she stumbles on a new site that might be helpful to someone else. Or students ask me for help in making sense of what they are finding, or in determining whether a site is trustworthy, or in searching for sources on their topic. It's like a community of scholars, I think, except that they are ninth graders in a United States history class in a Jewish Day School in Rockville, Md. , all of whom carry a double load of classes. (They must takes courses in Jewish subjects, like Rabbinics and Bible, in addition to the usual high school schedule.) If I forget to give a "two minute warning" before the bell rings so that they can save, log off, and figure out their homework for that night, they work through the bell. They have lost track of time. It's not exactly my doing as their teacher, much as it pleases me to create projects and watch them learn. It's the Internet; and sites like www.historymatters. gmu.edu that help make the Intemrnet safe and accessible for ninth graders. When there is a limit on the amount of information available in a classroom, the students need to depend on the teacher as the master of information. Conversely, when accurate information is widely available,
An Optimal Level Sets Method for Lung Nodules Detection in CT Images

Chan-Vese's image segmentation method proposed based on level sets method is studied and improved in this paper. A new level set method has been presented, which combines the average values of global regions and local boundary information, and it is used for lung nodules detection for CT images. The experiment results verify that it is a robust way for the segmentation of lung body and the detection for lung nodules, the speed of calculation is faster than that of Chan-Vese's. Moreover, the detection results are independed on the initial settings, so the manual mutuality can be reduced to the minimum, it is an effective method for CT image lung nodule detection automatically
The Cognitive Benefits of Playing a Casual Exergame

Acute cognitive benefits, such as temporary improvements in concentration, can result from as few as ten minutes of exercise; however, most people do not take exercise breaks throughout the day. To motivate people to receive the cognitive benefits of exercising in short bursts multiple times per day, we designed an engaging casual exergame. To determine whether there are cognitive benefits after playing our game, we conducted two studies to compare playing ten minutes of our casual exergame to a sedentary version of the game or exercise on a treadmill. We found acute cognitive benefits of the casual exergame over the sedentary version (but not treadmill exercise), demonstrated by significantly improved performance on two cognitive tests that require focus and concentration. Finally, our casual exergame produces similar exertion levels to treadmill exercise, but is perceived as more fun.
Real-Time Vehicle Make and Model Recognition Based on a Bag of SURF Features

In this paper, we propose and evaluate unexplored approaches for real-time automated vehicle make and model recognition (VMMR) based on a bag of speeded-up robust features (BoSURF) and demonstrate the suitability of these approaches for vehicle identification systems. The proposed approaches use SURF features of vehicles' front- or rear-facing images and retain the dominant characteristic features (codewords) in a dictionary. Two schemes of dictionary building are evaluated: “single dictionary” and “modular dictionary. ” Based on the optimized dictionaries, the SURF features of vehicles' front- or rear-face images are embedded into BoSURF histograms, which are used to train multiclass support vector machines (SVMs) for classification. Two real-time VMMR classification schemes are proposed and evaluated: a single multiclass SVM and an ensemble of multiclass SVM based on attribute bagging. The processing speed and accuracy of the VMMR system are affected greatly by the size of the dictionary. The tradeoff between speed and accuracy is studied to determine optimal dictionary sizes for the VMMR problem. The effectiveness of our approaches is demonstrated through cross-validation tests on a recent publicly accessible VMMR data set. The experimental results prove the superiority of our work over the state of the art, in terms of both processing speed and accuracy, making it highly applicable to real-time VMMR systems.
Link-Adaptive and QoS-Provisioning Cooperative ARQ—Applications to Relay-Assisted Land Mobile Satellite Communications

In a cooperative relay network, a relay (R) node may facilitate data transmission to the destination (D) node when the latter node cannot correctly decode the source (S) node data. This paper considers such a system model and presents a cross-layer approach to jointly design adaptive modulation and coding (AMC) at the physical layer and the truncated cooperative automatic repeat request (C-ARQ) protocol at the data-link layer for quality-of-service (QoS)-constrained applications. The average spectral efficiency and packet loss rate of the joint C-ARQ and AMC scheme are first derived in closed form. Aiming to maximize the system spectral efficiency, AMC schemes for the S-D and R-D links are optimized, whereas a prescribed packet-loss-rate constraint is satisfied. As an interesting application, joint link adaptation and blockage mitigation in land mobile satellite communications (LMSC) with temporally correlated channels is then investigated. In LMSC, the S node data can be delivered to the D node when the S-D is in the outage, therefore provisioning the QoS requirements. For applications without instantaneous feedback, an optimized rate selection scheme based on the channel statistics is also devised. Detailed and insightful numerical results are presented, which indicate the superior performance of the proposed joint AMC and C-ARQ schemes over their optimized joint AMC and traditional ARQ counterparts.
High-Confidence Glycosome Proteome for Procyclic Form Trypanosoma brucei by Epitope-Tag Organelle Enrichment and SILAC Proteomics

The glycosome of the pathogenic African trypanosome Trypanosoma brucei is a specialized peroxisome that contains most of the enzymes of glycolysis and several other metabolic and catabolic pathways. The contents and transporters of this membrane-bounded organelle are of considerable interest as potential drug targets. Here we use epitope tagging, magnetic bead enrichment, and SILAC quantitative proteomics to determine a high-confidence glycosome proteome for the procyclic life cycle stage of the parasite using isotope ratios to discriminate glycosomal from mitochondrial and other contaminating proteins. The data confirm the presence of several previously demonstrated and suggested pathways in the organelle and identify previously unanticipated activities, such as protein phosphatases. The implications of the findings are discussed.
Flux concentrations in turbulent convection

Abstract We present preliminary results from high resolution magneto-convection simulations where we find the formation of flux concentrations from an initially uniform magnetic field. The structures appear in roughly ten convective turnover times and live close to a turbulent diffusion time. The time scales are compatible with the negative effective magnetic pressure instability (NEMPI), although structure formation is not restricted to regions where the effective magnetic pressure is negative.
In Situ Hybridization Detection of Calcitonin mRNA in Routinely Fixed, Paraffin-Embedded Tissue Sections: A Comparison of Different Types of Probes Combined With Tyramide Signal Amplification

In situ hybridization (ISH) is a powerful molecular tool used to visualize nucleic acids in tissues and cells. However, its use is limited by the relative lack of sensitivity in detecting low copy numbers of nucleic acids. Several strategies have been developed to improve the threshold levels of in situ detection of nucleic acid by amplification of either target nucleic acid sequences before ISH (such as in situ polymerase chain reaction) or after the hybridization procedure (such as tyramide signal amplification [TSA]). The authors compared the use of different types of probes to detect calcitonin mRNA in 10 cases of formalin-fixed, paraffin-embedded medullary thyroid carcinoma with and without TSA. In addition, dot blot hybridization was used to compare the signal amplification by TSA with oligonucleotide, cDNA, and cRNA probes. These results show that cRNA probes are the most sensitive types of probes for detecting mRNA molecules in formalin-fixed, paraffin-embedded tissue sections and that tyramide amplification can increase the sensitivity for detection of calcitonin mRNA in formalin-fixed, paraffin-embedded tissue sections at least 2-to 4-fold with cRNA probes.
Structure-Based Brushes: A Mechanism for Navigating Hierarchically Organized Data and Information Spaces

Interactive selection is a critical component in exploratory visualization, allowing users to isolate subsets of the displayed information for highlighting, deleting, analysis, or focused investigation. Brushing, a popular method for implementing the selection process, has traditionally been performed in either screen space or data space. In this paper, we introduce an alternate, and potentially powerful, mode of selection that we term structure-based brushing, for selection in data sets with natural or imposed structure. Our initial implementation has focused on hierarchically structured data, specifically very large multivariate data sets structured via hierarchical clustering and partitioning algorithms. The structure-based brush allows users to navigate hierarchies by specifying focal extents and level-of-detail on a visual representation of the structure. Proximity-based coloring, which maps similar colors to data that are closely related within the structure, helps convey both structural relationships and anomalies. We describe the design and implementation of our structure-based brushing tool. We also validate its usefulness using two distinct hierarchical visualization techniques, namely hierarchical parallel coordinates and tree-maps. Finally, we discuss relationships between different classes of brushes and identify methods by which structure-based brushing could be extended to alternate data structures.
Psychosocial adjustment in adolescence: The importance of the family ecology

Adolescence is a period of development associated with a host of biological, psychological, cognitive, and social changes, and it has been widely acknowledged that the family is a persistent and powerful context in which these changes occur. To further understand the links between the family ecology and youth well-being, each of the three studies comprising this dissertation examined how distinct aspects of family ecology were related to youths’ psychosocial adjustment. Study 1 used a sample of high school students from the National Study of Adolescent Health (N = 7,786) to identify patterns of positive development and examine the role family capital played in these patterns. A four-profile solution revealed Average, High SelfEsteem, Below Average, and High Achiever Profiles. Multinomial logistic regressions revealed that parent human and economic capital predicted increased odds of being in the High Achiever Profile, and social capital predicted increased odds of being in the High Self-Esteem Profile. Moderator analyses produced evidence of cumulative promotive effects by revealing that family social capital exacerbated the benefits of other types of family capital for positive development. Studies 2 and 3 focused on parental knowledge, which refers to the degree to which parents are informed about their youths’ daily experiences. Study 2 explored how youth gender, age, and family members’ relationship quality predicted five sources of mothers’ and fathers’ knowledge in a relatively understudied population: two-parent African American families with two youth (N = 187). Multilevel models revealed that older siblings disclosed less to parents than younger siblings. A quadratic youth age pattern indicated that fathers asked youth fewer questions in early adolescence compared to childhood and later adolescence, which coincided with higher levels of relying on spouse and siblings. Warmer parent-child relationships predicted higher levels of relying on multiple sources of knowledge for mothers and fathers, including child disclosure and solicitation. Drawing from family systems perspective, warmer marital
Block Iterative Methods and Recycling for Improved Scalability of Linear Solvers

Contemporary large-scale Partial Differential Equation (PDE) simulations usually require the solution of large and sparse linear systems. Moreover, it is often needed to solve these linear systems with different or multiple Right-Hand Sides (RHSs). In this paper, various strategies will be presented to extend the scalability of existing multigrid or domain decomposition linear solvers using appropriate recycling strategies or block methods—i.e., by treating multiple right-hand sides simultaneously. The scalability of this work is assessed by performing simulations on up to 8,192 cores for solving linear systems arising from various physical phenomena modeled by Poisson's equation, the system of linear elasticity, or Maxwell's equation. This work is shipped as part of on open-source software, readily available and usable in any C/C++, Python, or Fortran code. In particular, some simulations are performed on top of a well-established library, PETSc, and it is shown how our approaches can be used to decrease time to solution down by 30%.