Miracle-dz/UniFAR-FTUs huggingface dataset:
Trend and Cycle in Bond Premia

Common statistical measures of bond risk premia are volatile and countercyclical. This paper uses survey data on interest rate forecasts to construct subjective bond risk premia. Subjective premia are less volatile and not very cyclical; instead they are high only around the early 1980s. The reason for the discrepancy is that survey forecasts of interest rates are made as if both the level and the slope of the yield curve are more persistent than under common statistical models. The paper then proposes a consumption based asset pricing model with learning to explain jointly the difference between survey and statistical forecasts, and the evolution of subjective premia. Adaptive learning gives rise to inertia in forecasts, as well as changes in conditional volatility that help understand both features.
Eigenvector-based characterization for hierarchical multi-agent dynamical systems with low rank interconnection

In this paper, we investigate hierarchical multi-agent dynamical systems with low rank interconnection based on a new concept of eigen-interconnection. The eigenvector plays an important role in our framework. We first define the eigen-interconnection matrix for the rank one case. Then, we show eigenvalue distribution of a hierarchical interconnection with rank one eigen-interconnection matrix. The obtained eigenvalue distribution has explicit parameter dependency and the result allows us to place the eigenvalue selectively. Thus it gives useful knowledge to design hierarchical interconnection structure. This concept is naturally extended to the rank two case and a similar result for eigenvalue distribution is obtained. Those results completely include the previous researches as special cases. Furthermore, our characterization has a potential of straightforward extension to the higher rank cases. Finally, we show a numerical example where a hierarchical interconnection structure is designed based on our result.
Thwarting Memory Disclosure with Efficient Hypervisor-enforced Intra-domain Isolation

Exploiting memory disclosure vulnerabilities like the HeartBleed bug may cause arbitrary reading of a victim's memory, leading to leakage of critical secrets such as crypto keys, personal identity and financial information. While isolating code that manipulates critical secrets into an isolated execution environment is a promising countermeasure, existing approaches are either too coarse-grained to prevent intra-domain attacks, or require excessive intervention from low-level software (e.g., hypervisor or OS), or both. Further, few of them are applicable to large-scale software with millions of lines of code. This paper describes a new approach, namely SeCage, which retrofits commodity hardware virtualization extensions to support efficient isolation of sensitive code manipulating critical secrets from the remaining code. SeCage is designed to work under a strong adversary model where a victim application or even the OS may be controlled by the adversary, while supporting large-scale software with small deployment cost. SeCage combines static and dynamic analysis to decompose monolithic software into several compart- ments, each of which may contain different secrets and their corresponding code. Following the idea of separating control and data plane, SeCage retrofits the VMFUNC mechanism and nested paging in Intel processors to transparently provide different memory views for different compartments, while allowing low-cost and transparent invocation across domains without hypervisor intervention. We have implemented SeCage in KVM on a commodity Intel machine. To demonstrate the effectiveness of SeCage, we deploy it to the Nginx and OpenSSH server with the OpenSSL library as well as CryptoLoop with small efforts. Security evaluation shows that SeCage can prevent the disclosure of private keys from HeartBleed attacks and memory scanning from rootkits. The evaluation shows that SeCage only incurs small performance and space overhead.
KARMA : A Secure Economic Framework for Peer-to-Peer Resource Sharing

Peer-to-peer systems are typically designed around the assumption that all peers will willingly contribute resources to a global pool. They thus suffer from freeloaders, that is, participants who consume many more resources than they contribute. In this paper, we propose a general economic framework for avoiding freeloaders in peer-to-peer systems. Our system works by keeping track of the resource consumption and resource contribution of each participant. The overall standing of each participant in the system is represented by a single scalar value, called their karma. A set of nodes, called a bankset, keeps track of each node’s karma, increasing it as resources are contributed, and decreasing it as they are consumed. Our framework is resistant to malicious attempts by the resource provider, consumer, and a fraction of the members of the bank set. We illustrate the application of this framework to a peer-to-peer filesharing
Interest, Learning, and the Psychological Processes That Mediate Their Relationship.

Although influences of interest on learning are well documented, mediating processes have not been clarified. The authors investigated how individual and situational interest factors contribute to topic interest and text learning. Traditional self-report measures were combined with novel interactive computerized methods of recording cognitive and affective reactions to science and popular culture texts, monitoring their development in real time. Australian and Canadian students read 4 expository texts. Both individual interest variables and specific text titles influenced topic interest. Examination of processes predictive of text learning indicated that topic interest was related to affective response, affect to persistence, and persistence to learning. Combining self-rating scales with dynamic measures of student activities provided new insight into how interest influences learning.
A multiscale model of partial melts: 2. Numerical results

[1] In the companion paper, equations for partially molten media were derived using two-scale homogenization theory. This approach begins with a grain-scale description and then coarsens it through multiple scale expansions into a macroscopic model. One advantage of homogenization is that effective material properties, such as permeability and the shear and bulk viscosity of the two-phase medium, are characterized by cell problems, boundary value problems posed on a representative microstructural cell. The solutions of these problems can be averaged to obtain macroscopic parameters that are consistent with a given microstructure. This is particularly important for estimating the “compaction length” which depends on the product of permeability and bulk viscosity and is the intrinsic length scale for viscously deformable two-phase flow. In this paper, we numerically solve ensembles of cell problems for several geometries. We begin with simple intersecting tubes, as this is a one parameter family of problems with well-known results for permeability. Using the data, we estimate relationships between the porosity and all of the effective parameters by curve fitting. For the model of intersecting tubes, permeability scales as ϕn, n ∼ 2, as expected, and the bulk viscosity scales as ϕ−m, m ∼ 1, which has been speculated but never shown directly for deformable porous media. The second set of cell problems adds spherical inclusions where the tubes intersect. For these geometries, the permeability is controlled the pore throats and not by the total porosity, as expected. However, the bulk viscosity remains inversely proportional to the porosity, and we conjecture that this quantity is insensitive to the specific microstructure. The computational machinery developed can be applied to more general geometries, such as texturally equilibrated pore shapes. However, we suspect that the qualitative behavior of our simplified models persists in these more realistic structures. In particular, our hybrid numerical-analytical model predicts that for purely mechanical coupling at the microscale, all homogenized models will have a compaction length that vanishes as porosity goes to zero. This has implications for numerical simulations, and it suggests that these models might not resist complete compaction.
Incremental, Predictive Parsing with Psycholinguistically Motivated Tree-Adjoining Grammar

Psycholinguistic research shows that key properties of the human sentence processor are incrementality, connectedness (partial structures contain no unattached nodes), and prediction (upcoming syntactic structure is anticipated). There is currently no broad-coverage parsing model with these properties, however. In this article, we present the first broad-coverage probabilistic parser for PLTAG, a variant of TAG that supports all three requirements. We train our parser on a TAG-transformed version of the Penn Treebank and show that it achieves performance comparable to existing TAG parsers that are incremental but not predictive. We also use our PLTAG model to predict human reading times, demonstrating a better fit on the Dundee eye-tracking corpus than a standard surprisal model.
On the Processor Sharing of File Transfers in Wireless LANs

We study the performance of FTP file transfers over a WLAN and propose a new analytic model that translates the highly complex dynamics of the FTP/TCP/IP/MAC-stack, and their interactions, into a single parameter, called the effective load ,a nd use this to describe the flow-level behavior of FTP- based file transfers over WLANs without admission control as an M/G/1 Processor-Sharing (PS)-model. This model is validated by comparing the model- based response times against simulations.
A Parallel & Distributed Implementation of the Harmony Search Based Supervised Training of Artificial Neural Networks

The authors have published earlier a novel technique for the supervised training of feed-forward artificial neural networks using the Harmony Search algorithm. This paper proposes a parallel and distributed implementation method to speedup the execution time to address the training of larger pattern-classification benchmarking problems. The proposed method is a hybrid technique that adopts form the merits of two common parallel and distributed training methods, namely network partitioning and pattern partitioning. Experimentation is carried out on a large pattern-classification benchmarking problem using two Master-Slave parallel systems, a homogeneous system using a cluster computer and a heterogeneous system using a set of commodity computers connected via switched network. Results show that the proposed method attains a considerable speedup in comparison to the sequential implementation.
Histological findings in human brucellosis

The histological findings in 14 cases of brucellosis are described. Unusual findings include the occurrence of brucellosis in a patient with Hodgkin's disease and in another with lymphosarcoma. A patient with hepatic cirrhosis apparently due to brucellosis is included in the series.
Determinants of Family's Self-Efficacy for Physical Activity;A Qualitative Study

Background & objectives: Perceived self-efficacy is an effective factor for physical activity. This qualitative study explores the determinants of family's self-efficacy for physical activity. Methods: This qualitative study was performed through content analysis method. Data were collected through semi-structured interview. 20 participants were included in the study using purposive sampling method. Constant comparative analysis was applied for data analysis. Results: The gathered data were included in four main categories; environmental status, parents’ role, competitive activities and readiness for physical activity. The main theme derived from this study was "Lack of priority for physical activity in family daily life". Conclusion: Regarded to the main theme and four categories derived from this study, physical activity has poor priority in families’ daily life. Introducing physical activity as a value and developing active lifestyle are recommended for families. Keywords: Self Efficacy; Family; Physical Activity.
Fast Video Completion using patch-based synthesis and image registration

Video completion has many applications in movie post-production, such as removing unwanted objects, artifacts, or logos. Most state-of-the-art video completion techniques are time-consuming in order to ensure spatial-temporal coherence. This paper presents a Fast Video Completion (FVC) technique that is based on patch-based synthesis and image registration. FVC generates key frames without the unwanted objects over the input video using a patch-based synthesis. The rest of the video completion process requires a low computing time using the registered prior frame. The results of the proposed technique show that FVC preserves the spatial-temporal coherence in an acceptable time, that makes the proposed technique is applicable for long videos.
Psychological Restoration Practices Among College Students

The transition into adulthood during college is one of the most stressful phases of an individual’s life (Fogle & Pettijohn, 2013). In fact, stress and poor psychological wellbeing among US undergraduate students have been on the rise (American College Health Association, 2016; Chao, 2012). College comes with academic, social, and financial responsibilities (e.g., maintaining a certain grade point average, forming inter personal relationships, and dealing with financial doubt) that can be a burden to an undergraduate (Brougham, Zail, Mendoza, & Miller, 2009; Chao, 2012; S. Staats, Cosmar, & Kaffenberger, 2007). Furthermore, 31.8% of undergraduates reported stress to be a factor affecting their academic performance (American College, 2016). Stressors and daily demands can cause a depletion of mental and emotional resources (Kaplan & Kaplan, 1989). Stress is not always harmful and can help students work harder to meet deadlines; however, prolonged stress can lead to both short-term and long-term physiological and mental health illnesses (Selye, 1956). Maintaining psychological well-being and reducing stress during college are important because stress relief is essential for a healthy life (Garcia, Castillo, & Queralt, 2011). Thus, effective stress reduction strategies are vital for student health and well-being. Research has shown that social interactions and developing meaningful relationships (Bowman, 2010) as well as student involvement on campus (e.g., intramural sports, student organizations) can have positive effects on psychological wellbeing (Kilgo, Mollet, & Pascarella, 2016). Psychological well-being can also be realized through psychological restoration processes, which focus on relieving stress and replenishing attention fatigue. Two key theories that discuss psychological restoration, Kaplan and Kaplan’s attention restoration theory (ART; 1989) and Ulrich’s psychoevolutionary theory (PET; Ulrich et al., 1991), focus on the importance of natural environments for escape from daily demands and stressors. ART suggests that the constant use of directed attention— actively and intentionally focusing on a task—will contribute to mental fatigue and that involuntary attention—attention that requires little to no effort—is needed to reduce directed attention fatigue. PET indicates that psychological restoration can positively impact psychological states, behaviors, and activity within physiological systems. On the contrary, positive psychology suggests that student well-being and stress relief can occur through optimal experiences known as flow, which involve voluntarily participating in an
Digoxin for patients with atrial fibrillation and heart failure: paradise lost or not?

This editorial refers to ‘Increased mortality among patients taking digoxin—analysis from the AFFIRM study’, by M.G. Whitbeck et al. , doi:10.1093/eurheartj/ehs348 Digoxin is one of the oldest drugs in cardiovascular medicine, and it was traditionally used in patients with atrial fibrillation (AF) and heart failure (HF). 1 In the last 20 years, the use of this drug has markedly declined, and in the most recent 2012 European Society of Cardiology (ESC) HF Guidelines,2 it is stated that for patients with HF and a left ventricular ejection fraction (LVEF) ≤40%, who are in sinus rhythm ‘digoxin may be used’. This recommendation is based on the Digitalis Investigation Group (DIG) trial,3 in which the effect of digoxin on outcome was examined in 6800 patients with HF. For HF patients with AF, other drugs (in particular beta-blockers) should be preferred,2 since they provide better rate control. In the 2010 ESC AF Guidelines,4 it is stated that digoxin is effective for long-term rate control at rest, but not during exercise. Prospective, randomized, placebo-controlled outcome studies examining the effect of digoxin in patients with AF (with or without HF) are not available. In the past, it was assumed that the beneficial effect of digoxin in HF was due to its (positive) inotropic properties, which were more pronounced at higher doses of the drug.1,5 However, a large number of studies in patients with HF has shown that positive inotropic drugs lead to an unfavourable effect on outcome, and these drugs are now contraindicated in patients with (chronic) HF. In contrast to this inotropic effect, digoxin also exerts potentially favourable autonomic- or neurohormonal-inhibiting properties,6,7 which primarily occur at lower serum digoxin concentrations (SDCs). 1,5–7 This has been increasingly recognized in the last 25 years, …
ELECTRON-CLOUD SIMULATIONS FOR SPS AND LHC

The electron cloud causes an increase in the vacuum pressure. It also induces slow multi-bunch and fast singlebunch instabilities, and, for the LHC, it significantly increases the heat load on the cryogenics system. This report describes our computer model of the electron cloud build up, presents simulation results for SPS and LHC, and investigates how the electron-cloud density can be reduced by modified fill patterns.
Unfinished Business: Nested Acquisitions, Managerial Capacity, and Firm Performance

We highlight a largely unstudied phenomenon that affects postacquisition performance: nested acquisitions. Nested acquisitions occur when a firm acquires a target firm that has itself recently acquired another firm. In our study of publicly traded U.S. acquirers and targets from 2000 to 2014, we theorize that nested acquirers face unique integration difficulties that reduce acquirer postacquisition performance. Specifically, we build on Penrosian logic and theorize that nested acquisitions tax the managerial capacity of the acquiring and acquired firms more than nonnested ones and that, as nested acquisition complexity increases due to variance within the embedded nested targets (i.e., greater number, more recent, less related, and larger nested targets), the drain on managerial capacity also increases. Ultimately, these challenges increase the likelihood of reduced postacquisition performance. Given these suggested difficulties, we theorize that retaining focal target managers can aid the acquiring firm and thereby help to reduce negative performance outcomes. In our unique sample of matched-pair firms, we find that nested acquisitions are associated with lower postacquisition performance but that retaining target firm managers can reduce this effect.
A Thematic Framework of Observed Mothers’ Socialization Messages Regarding Sexual Orientation

All youth are exposed to a variety of messages about sexual orientation, which shape their beliefs and values regarding sexual orientation. Parents are powerful contributors to this process of sexual socialization. However, the majority of existing research on parents’ socialization messages regarding sexual orientation relies on retrospective self-report. This study included 23 mother–child dyads, in which both members of each dyad identified as heterosexual. Participants were given standardized prompts to discuss relationships and sexual orientation. Each conversation was video recorded and transcribed. Qualitative content analysis was used to identify mothers’ sexual orientation messages observed during these video-recorded conversations. Observed sexual orientation socialization messages were organized into seven categories: (a) factual information and stereotypes, (b) opinions about sexual minority rights, issues, and organizations, (c) degree of support for and comfort with sexual minority people, (d) relationship of sexual orientation to character or personality, (e) origins and stability of sexual orientation, (f) how to interact with sexual minority people, and (g) implicit messages. Within each category, the observed messages ranged in valence from positive to negative. The results of this study provide an in depth view of how mothers communicate with their heterosexual children about sexual orientation and sexual minority people, across a range of topics. With this new empirical framework, future research can now examine the potential influence of these messages on youths’ attitudes regarding sexual minority issues. Implications for research, training, and parent education are discussed.
Dll3 is expressed in developing hair cells in the mammalian cochlea

Notch mediates the process of lateral inhibition that controls the production of hair cells in the inner ear. Hair cells are known to express Notch ligands Dll1 and Jag2, which signal through Notch1 in adjacent supporting cells. However, recent genetic and pharmacological studies indicate that the level of Notch‐mediated lateral inhibition is greater than can be accounted for by Dll1 and Jag2. Here, we report that another Notch ligand, Dll3, is expressed in developing hair cells, in a pattern that overlaps that of Dll1 and Jag2. We analyzed the cochleae of Dll3pu mutant mice, but did not detect any abnormalities. However, earlier studies have demonstrated that there is functional redundancy among Notch ligands in cochlear development and loss of one ligand can be at least partially compensated for by another. Thus Dll3 may play a role in lateral inhibition similar to that of Dll1 and Jag2. Developmental Dynamics 236:2875–2883, 2007. © 2007 Wiley‐Liss, Inc.
Cluster and Calendar Based Visualization of Time Series Data

A new method is presented to get an insight into univariate time series data. The problem addressed is how to identify patterns and trends on multiple time scales (days, weeks, seasons) simultaneously. The solution presented is to cluster similar daily data patterns, and to visualize the average patterns as graphs and the corresponding days on a calendar. This presentation provides a quick insight into both standard and exceptional patterns. Furthermore, it is well suited to interactive exploration. Two applications, numbers of employees present and energy consumption, are presented.
D S ] 8 J un 1 99 8 Trajectory and Attractor Convergence for a Nonlocal Kuramoto-Sivashinsky Equation October

The nonlocal Kuramoto-Sivashinsky equation arises in the modeling of the flow of a thin film of viscous liquid falling down an inclined plane, subject to an applied electric field. In this paper, the authors show that, as the coefficient of the nonlocal integral term goes to zero, the solution trajectories and the maximal attractor of the nonlocal Kuramoto-Sivashinsky equation converge to those of the usual Kuramoto-Sivashinsky equation. AMS subject classification: 35Q35, 58F39