Miracle-dz/UniFAR-FTUs huggingface dataset:
Method-level phase behavior in java workloads

Java workloads are becoming more and more prominent on various computing devices. Understanding the behavior of a Java workload which includes the interaction between the application and the virtual machine (VM), is thus of primary importance during performance analysis and optimization. Moreover, as contemporary software projects are increasing in complexity, automatic performance analysis techniques are indispensable. This paper proposes an off-line method-level phase analysis approach for Java workloads that consists of three steps. In the first step, the execution time is computed for each method invocation. Using an off-line tool, we subsequently analyze the dynamic call graph (that is annotated with the method invocations' execution times) to identify method-level phases. Finally, we measure performance characteristics for each of the selected phases. This is done using hardware performance monitors. As such, our approach allows for linking microprocessor-level information at the individual methods in the Java application's source code. This is extremely interesting information during performance analysis and optimization as programmers can use this information to optimize their code. We evaluate our approach in the Jikes RVM on an IA-32 platform using the SPECjvm98 and SPECjbb2000 benchmarks. This is done according to a number of important criteria: the overhead during profiling, the variability within and between the phases, its applicability in Java workload characterization (measuring performance characteristics of the various VM components) and application bottleneck identification.
Toward a statistical mechanics of four letter words

We consider words as a network of interacting letters, and approximate the probability distribution of states taken on by this network. Despite the intuition that the rules of English spelling are highly combinatorial and arbitrary, we find that maximum entropy models consistent with pairwise correlations among letters provide a surprisingly good approximation to the full statistics of words, capturing ∼92% of the multi-information in four-letter words and even "discovering" words that were not represented in the data. These maximum entropy models incorporate letter interactions through a set of pairwise potentials and thus define an energy landscape on the space of possible words. Guided by the large letter redundancy we seek a lower-dimensional encoding of the letter distribution and show that distinctions between local minima in the landscape account for ∼68% of the four-letter entropy. We suggest that these states provide an effective vocabulary which is matched to the frequency of word use and much smaller than the full lexicon.
Urban Aboriginal Leadership

It is challenging to find a book written from the viewpoint of Urban Aboriginal Leaders in Canada. A task that I assumed to understand what we as Aboriginal people in Canada could offer, in a sense bridging the understanding of leadership from a traditional Aboriginal worldview and western methodologies of leadership. In 2006, the Canadian census identified that more than 50% of Aboriginal people in Canada now live in urban centers. This phenomenon of migration to cities will have an increased effect on how companies and organizations work with urban Aboriginal people. Offering a potential workforce of highly educated young Aboriginal men and woman with unique leadership styles that need to be recognized and valued within western leadership methodologies. This book will share a perspective on how urban Aboriginal leadership worldviews differ and what can we learn as we move to value and appreciate the relationship with the original peoples of Canada. Originally written as a thesis, this book includes a preface containing details of what has transpired since the presentation and acceptance of the thesis in 2007.
How to accurately predict moisture front?

When comparing measurements to numerical simulations of moisture transfer through porous materials a rush of the experimental moisture front is commonly observed in several works shown in the literature, with transient models that consider only the diffusion process. Thus, to overcome the discrepancies between the experimental and the numerical models, this paper proposes to include the moisture advection transfer in the governing equation. To solve the advection-diffusion differential equation, it is first proposed two efficient numerical schemes and their efficiencies are investigated for both linear and nonlinear cases. The first scheme, Scharfetter-Gummel (SG), presents a Courant-Friedrichs-Lewy (CFL) condition but is more accurate and faster than the second scheme, the well-known Crank-Nicolson approach. Furthermore, the SG scheme has the advantages of being well-balanced and asymptotically preserved. Then, to conclude, results of the convective moisture transfer problem obtained with the SG numerical scheme are compared to experimental data from the literature. The inclusion of an advective term in the model may clearly lead to better results than purely diffusive models.
The design and implementation of learner models in online peer assessment to support learning

Most literature has shown that online peer assessment could improve students' learning in programming. However, how to help them reflect more detail about their knowledge and difficulties is challenge. Learner models can represent students' state in the learning process. Therefore, the study explores the design and implementation of learner models in online peer assessment to help students reflect their learning. A conceptual framework of learner model is proposed, which analyzes the learning process from two dimensions. The two-dimension learner model is open to not only students themselves but also peers. The results hope to advance the theoretical study and the application to opening the learner model to support learning programming.
Comparing Job Applicants to Non–Applicants Using An Item–Level Bifactor Model on the Hexaco Personality Inventory

The present study evaluated the ability of item–level bifactor models (a) to provide an alternative explanation to current theories of higher order factors of personality and (b) to explain socially desirable responding in both job applicant and non–applicant contexts. Participants (46% male; mean age = 42 years, SD = 11) completed the 200–item HEXACO Personality Inventory–Revised either as part of a job application (n = 1613) or as part of low–stakes research (n = 1613). A comprehensive set of invariance tests were performed. Applicants scored higher than non–applicants on honesty–humility (d = 0.86), extraversion (d = 0.73), agreeableness (d = 1.06), and conscientiousness (d = 0.77). The bifactor model provided improved model fit relative to a standard correlated factor model, and loadings on the evaluative factor of the bifactor model were highly correlated with other indicators of item social desirability. The bifactor model explained approximately two–thirds of the differences between applicants and non–applicants. Results suggest that rather than being a higher order construct, the general factor of personality may be caused by an item–level evaluative process. Results highlight the importance of modelling data at the item–level. Implications for conceptualizing social desirability, higher order structures in personality, test development, and job applicant faking are discussed. Copyright © 2017 European Association of Personality Psychology
Observing software-defined networks using a decentralized link monitoring approach

Scalable and automated monitoring processes for testing, debugging, and operation of VNFs and service-chains are crucial components towards achieving the aims of network softwarization - i.e., cheaper, faster, and shorter service deployment and network management processes. In this paper we present a decentralized monitoring approach aimed at supporting automated deployment and operation of VNFs and service-chains. The approach is inspired by network tomography and is designed to address observability limitations and scalability issues that arise from performing measurements from an SDN controller. From successive end-to-end measurements link metrics are derived via in-network parameter estimation with no need of forwarding raw measurements to the controller, which significantly reduces the measurement overhead compared to when monitoring individual links explicitly from an SDN controller.
State of the art: Oral antiplatelet therapy

Platelet adhesion, activation, and aggregation are central to the propagation of coronary thrombosis following rupture, fissure, or erosion of an atherosclerotic plaque. This chain of deleterious events underlies the pathophysiological process leading to an acute coronary syndrome. Therefore, oral antiplatelet therapy has become the cornerstone of therapy for the management of acute coronary syndrome and the prevention of ischemic complications associated with percutaneous coronary intervention. Landmark trials have established aspirin, and the addition of clopidogrel to aspirin, as key therapeutic agents in the context of acute coronary syndrome and percutaneous coronary intervention. Dual antiplatelet therapy has been the guideline-mandated standard of care in acute coronary syndrome and percutaneous coronary intervention. Despite the proven efficacy of dual antiplatelet therapy, adverse ischemic events continue to occur and this has stimulated the development of novel, more potent antiplatelet agents. We focus this state-of-the-art review on the most recent advances in oral antiplatelet therapy, treading the tightrope of potency versus bleeding risk, the quest to determine the optimal duration of dual antiplatelet therapy and future of personalized antiplatelet therapy.
Planning and Parallel Transition Networks: Animation's New Frontiers

Animating realistic human agents involves more than just creating movements that look "real". A principal characteristic of humans is their ability to plan and make decisions based on intentions and the local environmental context. "Animated agents" must therefore react to and deliberate about their environment and other agents. Our agent animation uses various low-level behaviors, sense-control-action loops, high-level planning, and parallel task networks. Several systems we developed will illustrate how these components contribute to the realism and efficacy of human agent animation.
Estimation of counterfactual distributions using quantile regression

This paper proposes estimators of unconditional distribution functions in the presence of covariates. The methods are based on the estimation of the conditional distribution by (parametric or nonparametric) quantile regression. The conditional distribution is then integrated over the range of the covariates, allowing for the estimation of counterfactual distributions. In the parametric settings, we propose an extension of the Oaxaca (1973) / Blinder (1973) decomposition of means to the full distribution. In the nonparametric setting, we develop an efficient local-linear regression estimator for quantile treatment effects. We show root n consistency and asymptotic normality of the estimators and present analytical estimators of their variance. Monte-Carlo simulations show that the procedures perform well in finite samples. An application to the black-white wage gap illustrates the usefulness of the estimators.
The Polish doughnuts revisited I. The angular momentum distribution and equipressure surfaces

We construct a new family of analytic models of black hole accretion disks in dynamical equilibria. Our construction is based on assuming distributions of angular momentum and entropy. For a particular choice of the distribution of angular momentum, we calculate the shapes of equipressure surfaces. The equipressure surfaces we find are similar to those in thick, slim and thin disks, and to those in ADAFs.
Interactive visualization of emerging topics in multiple social media streams

This paper introduces an interactive news flow visualization that reveals emerging topics in dynamic digital content archives. The presented approach combines several visual metaphors and can be easily adapted to present multi-source social media datasets. In the context of this work, we discuss various methods for improving visual interfaces for accessing aggregated media representations. We combine falling blocks with bar graphs and arcs, but keep these elements clearly separated in different areas of the display. The arc metaphor is adapted and enriched with interactive controls to help users understand the dataset's underlining meaning. The paper describes the implementation of the prototype and discusses design issues with a particular emphasis on visual metaphors to highlight hidden relations in digital content. We conclude with a summary of the lessons learnt and the integration of the visualization component into the Media Watch on Climate Change (www.ecoresearch.net/climate), a public Web portal that aggregates environmental information from a variety of online sources including news media, blogs and other social media such as Twitter, YouTube and Facebook.
Combining TDMA with Slotted Aloha for delay constrained traffic over lossy links

Reliability and real-timeliness of wireless communications are the major concerns that hamper the wide deployment of wireless technologies for mission- and time-critical applications. This paper investigates the problem of maximizing transmission reliability of delay constrained traffic in a single-hop network by exploring the advantages of TDMA and Slotted Aloha. In our scheme, each time slot is either exclusively allocated to a dedicated node or shared by a group of nodes. All nodes sharing the same time slot operate based on the Slotted Aloha protocol. The key problem we address is: given a delay constraint, how to construct the transmission schedule by allocating the dedicated and shared slots in such a way that the probability that all packets are received at the destination is maximized. We show that the optimal schedules have some good structures, and propose both optimal and heuristic scheduling schemes. Numerical simulation results demonstrate that our schemes significantly outperform the traditional TDMA scheduling scheme in which time slots are all exclusively allocated. Moreover, our heuristic scheme can construct schedules with success probability coming very close to the optimal schedules at much more modest computational cost.
AlGaN/GaN-on-SiC HEMT Technology Status

GaN-based devices offer significant advantages for next generation military and commercial systems. Military systems benefit from high power densities of 4 to 7 W/mm depending on bias conditions along with efficiencies over 60% at frequencies through X-band, and commercial systems take advantage of excellent linearity as well. In this paper, we will review a number of commercial products that only GaN technology can achieve. In addition to narrow-band circuits for highly linear commercial applications, results will be shown for two commercial GaN MMIC products that have been developed for general-purpose applications in the 2.5-6.0 GHz and DC-6.0 GHz bands. Additionally, results are shown for a 2-stage high efficiency S-band switch mode amplifier operating from 3.1-3.5 GHz. Significant progress has also been made in the development of 100-mm SiC substrates. Micropipe densities as low as 2.5 cm-2 have been demonstrated for 100-mm HPSI substrates.
Cytosolic 5′‐nucleotidase 1A autoimmunity in sporadic inclusion body myositis

We previously identified a circulating autoantibody against a 43 kDa muscle autoantigen in sporadic inclusion body myositis (IBM) and demonstrated the feasibility of an IBM diagnostic blood test. Here, we sought to identify the molecular target of this IBM autoantibody, understand the relationship between IBM autoimmunity and muscle degeneration, and develop an IBM blood test with high diagnostic accuracy.
Evolvable Modeling: structural adaptation through hierarchical evolution for 3-D model-based vision*

We present a system that lets 3-D models evolve over time, eventually producing novel models that are more desirable than initial models. The algorithm starts with some crude models given by the user, or randomly-generated models from a given modelgrammar with generic design rules and loose constraints. The underlying philosophy here is to gradually evolve the initial models into structurally novel and/or parametrically refined models over many generations. There is a close analog in the evolution of species where better-fit species gradually emerge and form specialized niches, a highly efficient process of complex structural and functional optimization. Simulation results for model jet plane design illustrate that our approach to model design and refinement is both feasible and effective.
A semantic tagging system for biomedical articles

With the popularity of Web 2.0, people start using tags to label web resources, some even go further by applying Semantic Web technologies to tags. While normal tags impose too many limitations thus not powerful enough, semantic tags are too flexible to address issues like efficiency and quality. We present a tagging system that is built upon Semantic Web technologies and a semantic element is only chosen if we have a clear objective. The system can be used in PubMed, a database of over 19 million citations of biomedical articles, as an auxiliary system to improve the article locating ability a lot with acceptable trade off. We describe the system architecture and the optimizations apply to the system, then we present test results of several random generated test cases. The test results show that when running on medium scale tag repository, our system has quick amortized response time and acceptable memory usage. At last we present validation and correction strategies to deal with unreasonable tag relations in our system.
The role of women in payment for environmental services programs in Osa, Costa Rica

Abstract Costa Rica was the first country in the world to implement a nation-wide payment for environmental services (a.k.a. ‘payment for ecosystem services’), or PES, system in 1996. This research investigates the role of women in PES programs in Costa Rica’s Osa peninsula in response to the current dearth of such gendered research on this topic. Osa, one of the least-developed regions of the country, is still heavily forested and replete with properties under PES contracts which are aimed at forest conservation. Extended, structured interviews of 80 landowners in Osa (40 women and 40 men) culled both quantitative and qualitative information about PES participation, environmental perceptions, and both economic and conservation goals. Salient results were, first, that women see current levels of PES funding as more helpful and useful than do men. Second, women much more often perceive themselves as the sole entity responsible for protecting the environment. Third, women more commonly than men listed ‘helping the environment and animals’ as a personal benefit of their PES participation, while men more commonly focused on financial rewards. Last, according to the study herein, women in PES households currently display less decision-making power than those in non-PES households. This dynamic is analyzed through the lens of patriarchal hierarchies as well as women’s mitigation of those hierarchies through the deployment of ideology and agency. Based on these general findings, the researcher recommends that FONAFIFO, the government agency in charge of PES payments, take specific steps to increase PES funding to female-headed households.
Mistreatment in assisted living facilities: complaints, substantiations, and risk factors.

PURPOSE OF THE STUDY Use archived public data from Arizona to explore relationships among selected institutional and resident risk and situation-specific factors and complaints and substantiated allegations of various types of mistreatment in assisted living facilities (ALFs). DESIGN AND METHODS An exploratory/descriptive 2-group design was used. Facilities in the complaint group were identified from narrative data that appeared suspicious for mistreatment based on definitions for physical, verbal, psychological, medication, sexual abuse, neglect, financial exploitation, and physical restraint. Facilities in the comparison group were those that had no citations or complaints in 2007-2008. Narrative data were content analyzed, and chi-square analysis was used to answer 3 research questions. RESULTS The complaint group was comprised of significantly more assisted living centers, large facilities (51-101+), facilities licensed to provide personal care services, and facilities owned by national corporations. Substantiated allegations were significantly more frequent in assisted living centers, facilities with more than 51 beds, and those owned by national corporations. Facility risk factors were related to some types of substantiated mistreatment and not others. IMPLICATIONS Findings suggest the need to evaluate use of only unlicensed assistive personnel in facilities, increase oversight of care by professional nurses, rethink the practice of not licensing small facilities, and monitor more closely practices and procedures in facilities operated by national corporations.
A Derandomized Approach to Self-Adaptation of Evolution Strategies

Comparable to other optimization techniques, the performance of evolution strategies (ESs) depends on a suitable choice of internal strategy control parameters. Apart from a fixed setting, ESs facilitate an adjustment of such parameters within a self-adaptation process. For step-size control in particular, various adaptation concepts have been evolved early in the development of ESs. These algorithms mostly work very efficiently as long as the scaling of the parameters to be optimized is known. If the scaling is not known, the strategy has to adapt individual step-sizes for all the parameters. In general, the number of necessary step-sizes (variances) equals the dimension of the problem. In this case, step-size adaptation proves to be difficult, and the algorithms known are not satisfactory. The algorithm presented in this paper is based on the well-known concept of mutative step-size control. Our investigations indicate that the adaptation by this concept declines due to an interaction of the random elements involved. We show that this weak point of mutative step-size control can be avoided by relatively small changes in the algorithm. The modifications may be summarized by the word derandomization. The derandomized scheme of mutative step-size control facilitates a reliable self-adaptation of individual step-sizes.
Internet delays and packet losses sensor/actuator for UDP based networked control systems

The performance of networked control systems (NCS) in non-deterministic networks, such as the Internet depends largely on the network delays and packet losses. The reproduction of these delays and packet losses in a NCS implies the use of network simulators and emulators. In this paper, a system that performs as a sensor and as an actuator of Internet delays and packet losses is presented. It collects these parameters from the Internet and reproduces them into a local network data flow. The paper presents some comparative results and makes a performance analysis of the whole system.