Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Aware Scheduling for Virtual Machine Workloads with Interference Models

Modern data centers use virtualization as a means to increase utilization of increasingly powerful multi-core servers. Applications often require only a fraction of the resources provided by modern hardware. Multiple concurrent workloads are therefore required to achieve adequate utilization levels. Current virtualization solutions allow hardware to be partitioned into Virtual Machines with appropriate isolation on most levels. However, unmanaged consolidation of resource intensive workloads can still lead to unexpected performance variance. Measures are required to avoid or reduce performance interference and provide predictable service levels for all applications. In this paper, we identify and reduce network-related interference effects using performance models based on the runtime characteristics of virtualized workloads. We increase the applicability of existing training data by adding network-related performance metrics and benchmarks. Using the extended set of training data, we predict performance degradation with existing modeling techniques as well as combinations thereof. Application clustering is used to identify several new network-related application types with clearly defined performance profiles. Finally, we validate the added value of the improved models by introducing new scheduling techniques and comparing them to previous efforts. We demonstrate how the inclusion of network-related parameters in performance models can significantly increase the performance of consolidated workloads.
Identifying refactoring opportunities by identifying dependency cycles

The purpose of refactoring is to improve the quality of a software system by changing its internal design so that it is easier to understand or modify, or less prone to errors and so on. One challenge in performing a refactoring is quickly determining where to apply it. We present a tool (Jepends) that analyses the source code of a system in order to identify classes as possible refactoring candidates. Our tool identifies dependency cycles among classes because long cycles are detrimental to understanding, testing and reuse. We demonstrate our tool on a widely-downloaded, open-source, medium-sized Java program and show how cycles can be eliminated through a simple refactoring.
Modeling and planning for stable walking of a novel 6-DOF biped robot

Most of current biped robots are active walking platforms. Though they have strong locomotion ability and good adaptability to environments, they have a lot of degrees of freedom (DoFs) and hence result in complex control and high energy consumption. On the other hand, passive or semi-passive walking robots require less DoFs and energy, but their walking capability and robustness are poor. To overcome these shortcomings, we have developed a novel active biped walking robot with only six DoFs. The robot consists of an arm as the main body and two wheels as the feet. With this novel configuration, the robot can walk in several special walking gaits different from those of traditional biped robots. And for these gaits, the criterion of stable walking needs to be developed and analyzed. In this paper, the biped robot is introduced, walking gaits, dynamic stability and walking pattern with moment compensation are presented. Simulations and experiments are carried out to verify the effectiveness and to illustrate the unique features of this novel walking robot.
Mammalian target of rapamycin pathway mutations cause hemimegalencephaly and focal cortical dysplasia

Focal malformations of cortical development, including focal cortical dysplasia (FCD) and hemimegalencephaly (HME), are important causes of intractable childhood epilepsy. Using targeted and exome sequencing on DNA from resected brain samples and nonbrain samples from 53 patients with FCD or HME, we identified pathogenic germline and mosaic mutations in multiple PI3K/AKT pathway genes in 9 patients, and a likely pathogenic variant in 1 additional patient. Our data confirm the association of DEPDC5 with sporadic FCD but also implicate this gene for the first time in HME. Our findings suggest that modulation of the mammalian target of rapamycin pathway may hold promise for malformation‐associated epilepsy. Ann Neurol 2015;77:720–725
Modeling the inter-individual variability of single-stemmed plant development

Modeling the development of single-stemmed plants is classically done by expressing the number of phytomers in the main axis as a function of the thermal time. In many cases, a strong inter-individual variability is encountered, that cannot be straightforwardly associated to any environmental or micro-environmental factors. We propose a methodological framework to describe the heterogeneity of individual responses in a population by hierarchical or mixed-effect models : some regression parameters are random variables identically distributed in the population. The method is illustrated using experimental data collected on young Acacia erioloba plants, grown in CEREEP greenhouse, for which two piecewise-linear models of organogenesis are identified using Expectation-Maximization (EM) algorithm and compared according to their adequacy to the data. The E-step and the M-step of the algorithm are analytic as long as the dependence is linear with respect to the individual parameters, i.e. the latent variables of the mixed-effect model. In the general case, the posterior distribution of the individual parameters cannot be analytically determined. Monte-Carlo Markov Chains are generated with Metropolis-Hasting during the E-step to estimate the distribution. Alternatively, a Laplace approximation of the posterior distribution appeared to be quite relevant in our case. Such framework will be adapted to the identification of a complete FSPM of Acacia growth combining organogenesis and functioning.
Morpheme Based Language Model for Tamil Speech Recognition System

This paper describes the design of a morpheme based language model for Tamil language. It aims to alleviate the main problems encountered in processing the Tamil language, like enormous vocabulary growth caused by large number of different forms derived for one word. The size of the vocabulary is reduced by decomposing the words into stems and endings and storing these sub word units (morphemes) for training the language model The modified morpheme based language model was applied to avoid the ambiguities in the recognized Tamil words. The perplexity, Out Of Vocabulary (OOV) rate and Word Error Rate (WER) parameters were obtained to check the efficiency of the model for Tamil speech recognition system. The results were compared with the traditional word based statistical bigram and trigram language models. From the results, it was analyzed that the modified morpheme based trigram model with Katz back off smoothing effect improved the performance of the Tamil speech recognition system when compared to the word based N-Gram language models.
A study of three‐node triangular plate bending elements

SUMMARY An assessment of flat triangular plate bending elements with displacement degrees-of-freedom at the three comer nodes only is presented, with the purpose of identifying the most effective for thin plate analysis. Based on a review of currently available elements, specific attention is given to the theoretical and numerical evaluation of three triangular 9 degrees-of-freedom elements; namely, a discrete Kirchhoff theory (DKT) element, a hybrid stress model (HSM) element and a selective reduced integration (SRI) element. New and efficient formulations of these elements are discussed in detail and the results of several example analyses are given. It is concluded that the most efficient and reliable three-node plate bending elements are the DKT and HSM elements.
TR 04-009 Highly Adaptive Lookup Systems for Peer-to-Peer Computing

The performance of file sharing peer-to-peer systemsdependsto a largedegreeon thespeedof lookup operation. A number of proposedsolutionsrely on distrib uted hashing techniques. Traditionally nodesare assignedfixed length identifiers which doesnot allow the table to expand or shrink with the increaseor decreasein the node count. With the fixed length identifiers, the performancedeteriorates when the number of nodesreachesa high value. On the other hand, the overheadof maintaining per-nodestate (i.e., information of all adjacent nodes)can be unnecessar ily large if the number of nodesis small. The focusof our study is to proposea way to combinethe distributed and dynamic nature of the systemin a way that allows large and unpredictable changesin both the number and the distribution of nodeswhile providing scalability and good performance. Our approach is basedon dynamic distrib uted hashing techniques; node identifier length varies with the number of nodesin thesystem.Hence,the systemcanadapt to the changingconditionsand maintain goodperformance. In this paper, we describe the operations of the proposed adaptive systemand verify its performance thr ough simulations.
Examining associations between civic engagement and depressive symptoms from adolescence to young adulthood in a national U.S. sample

ABSTRACT Many scholars posit that engaging in civic actions enhances mental health, yet existing evidence is limited. To address gaps in the literature and advance understanding of benefits of civic engagement from adolescence to young adulthood, we estimated a longitudinal structural model to test bidirectional associations between civic engagement (i.e., voting, community engagement, political behaviors) and depressive symptoms using nationally representative longitudinal U.S. data. Adolescent and early young adulthood (EYA) depressive symptoms predicted decreases in later voting. Adolescent and EYA community engagement predicted decreases in later depressive symptoms. Analyses suggested that findings generalized across gender, age, socioeconomic status, race/ethnicity, and EYA social roles. Despite key limitations in measurement of civic engagement over time, results provide some support the notion that community engagement may have mental health benefits for youth, and that depression may reduce later civic engagement.
Renin‐Angiotensin System Inhibition in Acute Myocardial Infarction in Dogs Effects on Systemic Hemodynamics, Myocardial Blood Flow, Segmental Myocardial Function and Infarct Size

Acute left anterior descending coronary artery occlusion was produced in 21 conscious, chronically instrumented dogs. Forty minutes after coronary occlusion, nine dogs were given i.v. teprotide, 25, ug/kg/min, followed by oral doses of captopril, 10 mg/kg every 8 hours for 24 hours. The remaining 12 dogs served as saline‐infused controls. In all dogs, acute coronary occlusion increased plasma renin activity and peripheral vascular resistance and reduced cardiac output, but did not change mean aortic blood pressure significantly. Teprotide significantly (p < 0.05) decreased peripheral vascular resistance (from 3804 ± 1158 to 2876 ± 816 dyn‐sec‐cm-5) ( ± SD) and mean aortic pressure (from 117 ± 12 to 107 ± 15 mm Hg), and increased cardiac output (from 2.63 ± 0.67 to 3.12 ± 0.74 I/min). Teprotide also produced a relative increase in flow to the renal and splanchnic circulations compared with the saline-treated controls. There were, however, no differences in segmental systolic shortening, blood flow in the normal or ischemic myocardium, or infarct size. These results indicate that the renin-angiotensin system may play an important role in dogs with acute coronary occlusion and that blockade of this system lowers systemic blood pressure and improves cardiac output. However, direct effects of renin-angiotensin system blockade on the myocardium are lacking; there were no changes in myocardial blood flow, myocardial mechanics or infarct size.
Return on Trust is Lower for Immigrants

We conducted an experiment with a representative sample of the Dutch population to study whether trustworthiness depends on the ethnicity of the interaction partner. Native Dutch trustees play with an anonymous trustor, who is either another native Dutch or a non-Western immigrant. We find that trustees reciprocate trust up to 12% less if the trustor is a non-Western immigrant than if he/she is native Dutch. This percentage increases up to 23% for trustees who report disliking ethnic diversity in an independent survey. Since the decision to reciprocate does not involve behavioural risk, our results provide evidence of taste-based discrimination.
Detecting Data Errors with Employing Negative Association Rules

Ever increasing amount of data has led to the fact that the data quality has had a crucial impact on almost any IT applications. Nonetheless, data quality issues are nearly omnipresent. Recently, a great deal of researches has focused on improving data quality. Bad quality of the data can cause incorrect decision making. It is normally infeasible to guarantee sufficient data quality through manual inspection. Therefore (semi-)automatic data cleansing methods have to be employed. Data mining methods are ideal for this purpose, since they are aimed at finding abnormal patterns in large volumes of data. In this paper, we show the utility of negative association rules for detecting dubious data. The evaluations show that employing negative association rules provide interesting results for identifying incorrect data entries.
Making Sense of Institutionalizing Information Systems Security Management in Organizations

Information Systems (IS) security management has gained renewed importance for the past few years resulting from the rising numbers of security incidences and compliance pressure. While majority of IS security research has been focusing on the technical value and the effectiveness of IS security implementation, studies on the organizational process of implementation is rather limited. This paper employs a socio-cognitive perspective to examine the sense-making process of IS security BS 7799 Part 2 certification among different stakeholder groups in the organization. Using a qualitative case study approach, the findings reveal different understandings on the strategy and consequence of IS security implementation. We argue that socio-cognitive perspective, in particular the concept of frames analysis, can act an analytical tool to interpret meanings and anticipate actions in managing IS security in organizations.
Environmental Exposures and Mammary Gland Development: State of the Science, Public Health Implications, and Research Recommendations

Objectives: Perturbations in mammary gland (MG) development may increase risk for later adverse effects, including lactation impairment, gynecomastia (in males), and breast cancer. Animal studies indicate that exposure to hormonally active agents leads to this type of developmental effect and related later life susceptibilities. In this review we describe current science, public health issues, and research recommendations for evaluating MG development. Data sources: The Mammary Gland Evaluation and Risk Assessment Workshop was convened in Oakland, California, USA, 16–17 November 2009, to integrate the expertise and perspectives of scientists, risk assessors, and public health advocates. Interviews were conducted with 18 experts, and seven laboratories conducted an MG slide evaluation exercise. Workshop participants discussed effects of gestational and early life exposures to hormonally active agents on MG development, the relationship of these developmental effects to lactation and cancer, the relative sensitivity of MG and other developmental end points, the relevance of animal models to humans, and methods for evaluating MG effects. Synthesis: Normal MG development and MG carcinogenesis demonstrate temporal, morphological, and mechanistic similarities among test animal species and humans. Diverse chemicals, including many not considered primarily estrogenic, alter MG development in rodents. Inconsistent reporting methods hinder comparison across studies, and relationships between altered development and effects on lactation or carcinogenesis are still being defined. In some studies, altered MG development is the most sensitive endocrine end point. Conclusions: Early life environmental exposures can alter MG development, disrupt lactation, and increase susceptibility to breast cancer. Assessment of MG development should be incorporated in chemical test guidelines and risk assessment.
Preliminary report: Embedded platform for inertial based underwater navigation

A diver uses typically a compass, a depth gauge and a timer for underwater navigation. Especially when it comes to advanced diving in caves or wrecks, navigation and knowledge about the current position is extremely important, otherwise the diver might not find his way back to the surface and drown as soon as the breathing gas supply is finished. Other approaches are based on ultrasound transmitters that allow simple navigation tasks, however they are useless for applications like cave, wreck or long distance diving. The current paper describes a navigation platform for divers which is based on a handset with a depth sensor and a display, an inertial measurement unit incorporation gyroscopes, accelerometers and magentometers and an interface to attach different kinds of flow sensors for velocity measurement. A first prototype was developed. Additionally a buoy with an integrated GSM/GPS transmitter and a reference system for laboratory measurements can be attached. The prototype was validated in a pool and tests with the GPS reference system were carried out in the open sea.
HAND MOTION PROCESSING IN APPLICATIONS: A CONCISE SURVEY AND ANALYSIS OF TECHNOLOGIES

This paper deals with various hand motion processing technologies that can be used to input shape information to a computer aided shape conceptualizing system. Direct incomplete, direct complete, indirect incomplete and indirect complete information processing approaches and scanning technologies were identified. We briefly survey the technologies and systems for hand motion processing, the related application methodologies, and confront the technologies with the requirements originating in application of hand motions in shape conceptualization. Our conclusion is that many useful technologies are available, but more research is needed to provide the most effective technological solution for a hand motion based shape conceptualization.
A complete, co-inductive syntactic theory of sequential control and state

We present a new co-inductive syntactic theory, eager normal form bisimilarity, for the untyped call-by-value lambda calculus extended with continuations and mutable references.We demonstrate that the associated bisimulation proof principle is easy to use and that it is a powerful tool for proving equivalences between recursive imperative higher-order programs.The theory is modular in the sense that eager normal form bisimilarity for each of the calculi extended with continuations and/or mutable references is a fully abstract extension of eager normal form bisimilarity for its sub-calculi. For each calculus, we prove that eager normal form bisimilarity is a congruence and is sound with respect to contextual equivalence. Furthermore, for the calculus with both continuations and mutable references, we show that eager normal form bisimilarity is complete: it coincides with contextual equivalence.
Resource Flexibility with Responsive Pricing

This article studies two types of flexibility used by firms to better respond to uncertain market conditions: resource flexibility and responsive pricing. We consider a situation in which a single flexible resource can be used to satisfy two distinct demand classes. While the resource capacity must be decided based on uncertain demand functions, the resource allocation as well as the pricing decision are made based on the realized demand functions.We characterize the effects of two key drivers of flexibility: demand variability and demand correlation, assuming normally distributed demand curve intercepts. Demand variability creates opportunity costs and, with fixed prices, decreases the firm's profit. We show that with the additional flexibility gained from responsive pricing, the firm can maximize the benefits of favorable demand conditions and mitigate the effects of poor demand conditions, ultimately profiting from variability. Positive demand correlation, on the other hand, remains undesirable under responsive pricing. The optimal capacity of the flexible resource is always increasing in both demand variability and demand correlation. This contrasts with the scenarios based on fixed prices, highlighting the crucial difference that responsive pricing makes in the management of flexible resources. We further quantify the value of flexibility for the firm and its customers by considering, as a benchmark, a firm relying on two dedicated resources. The value of flexibility is most significant if the demand levels are highly variable and negatively correlated. In such cases, the firm benefits from demand variability due to responsive pricing, while facing limited demand risk due to resource flexibility. Finally, we endogenize the input price of the flexible resource by considering the pricing decision of the resource supplier.
The Evolution of Evolvability in Gene Transcription Networks

We present a case of a genotype-phenotype map, that when evolved in variable environments optimizes its genetic representation to structure phenotypic variability properties, allowing rapid adaptation to novel environments. How genetic representations evolved is a relatively neglected topic in evolutionary theory. Furthermore, the “black art” of genetic algorithms depends on the practitioner to choose a representation that captures problem structure. Nature has achieved remarkably efficient heuristic search mechanisms without top-down design. We propose that an important example of this, ubiquitous in biology is the structuring of the phenotypic variability properties of gene networks. By studying a simple model of gene networks in which topology is a function of interactions between transcription factor proteins and transcription factor binding sites (TFBS), we show that transcription factor binding matrices (TFBM) evolve to positively constrain phenotypic variability in response to transcription factor binding sequence mutations.
Spatial audition in a static virtual environment : the role of auditory-visual interaction

JVRB, 6(2009), no. 5. - The integration of the auditory modality in virtual reality environments is known to promote the sensations of immersion and presence. However it is also known from psychophysics studies that auditory-visual interaction obey to complex rules and that multisensory conflicts may disrupt the adhesion of the participant to the presented virtual scene. It is thus important to measure the accuracy of the auditory spatial cues reproduced by the auditory display and their consistency with the spatial visual cues. This study evaluates auditory localization performances under various unimodal and auditory-visual bimodal conditions in a virtual reality (VR) setup using a stereoscopic display and binaural reproduction over headphones in static conditions. The auditory localization performances observed in the present study are in line with those reported in real conditions, suggesting that VR gives rise to consistent auditory and visual spatial cues. These results validate the use of VR for future psychophysics experiments with auditory and visual stimuli. They also emphasize the importance of a spatially accurate auditory and visual rendering for VR setups.