Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy Efficient Data-Intensive Computing With Mapreduce

ENERGY EFFICIENT DATA-INTENSIVE COMPUTING WITH MAPREDUCE Thomas S. Wirtz Marquette University, 2013 Power and energy consumption are critical constraints in data center design and operation. In data centers, MapReduce data-intensive applications demand significant resources and energy. Recognizing the importance and urgency of optimizing energy usage of MapReduce applications, this work aims to provide instrumental tools to measure and evaluate MapReduce energy efficiency and techniques to conserve energy without impacting performance. Energy conservation for data-intensive computing requires enabling technology to provide detailed and systemic energy information and to identify in the underlying system hardware and software. To address this need, we present eTune, a fine-grained, scalable energy profiling framework for data-intensive computing on large-scale distributed systems. eTune leverages performance monitoring counters (PMCs) on modern computer components and statistically builds power-performance correlation models. Using learned models, eTune augments direct measurement with a software-based power estimator that runs on compute nodes and reports power at multiple levels including node, core, memory, and disks with high accuracy. Data-intensive computing differs from traditional high performance computing as most execution time is spent in moving data between storage devices, nodes, and components. Since data movements are potential performance and energy bottlenecks, we propose an analysis framework with methods and metrics for evaluating and characterizing costly built-in MapReduce data movements. The revealed data movement energy characteristics can be exploited in system design and resource allocation to improve data-intensive computing energy efficiency. Finally, we present an optimization technique that targets inefficient built-in MapReduce data movements to conserve energy without impacting performance. The optimization technique allocates the optimal number of compute nodes to applications and dynamically schedules processor frequency during its execution based on data movement characteristics. Experimental results show significant energy savings, though improvements depend on both workload characteristics and policies of resource and dynamic voltage and frequency scheduling. As data volume doubles every two years and more data centers are put into production, energy consumption is expected to grow further. We expect these studies provide direction and insight in building more energy efficient data-intensive systems and applications, and the tools and techniques are adopted by other researchers for their energy efficient studies.
2 Tensors in Turbulent Combustion 2 . 1 Turbulent Combustion Modeling

Simulation and modeling of turbulent flow, and of turbulent r eacting flow in particular, involves solving for and analyzing time-dep endent and spatially dense tensor quantities, such as turbulent stress tensors. The in teractive visual exploration of these tensor quantities can effectively steer the comput ational modeling of combustion systems. In this chapter, we discuss the challenges i dense symmetrictensor visualization applied to turbulent combustion calc ul tion, and analyze the feasibility of using several established tensor visualiza tion techniques in the context of exploring space-time relationships in computation ally-simulated combustion tensor data. To tackle the pervasive problems of occlus ion and clutter, we propose a solution combining techniques from information and s cientific visualization. Specifically, the proposed solution combines a detailed 3D i nspection view based on volume rendering with glyph-based representations – use d a 2D probes –, while leveraging interactive filtering and flow salience cues to cl arify the structure of the tensor datasets. Side-by-side views of multiple timesteps facilitate the analysis of time-space relationships. The resulting prototype enable s an analysis style based on the overview first, zoom and filter, then details on demand par adigm originally proposed in information visualization. The result is a visual a nalysis tool to be utilized in debugging, benchmarking, and verification of models and s olutions in turbulent combustion. We demonstrate this analysis tool on three exam ple configurations and report feedback from combustion researchers. Adrian Maries, Md. Abedul Haque, G. Elisabeta Marai Department of Computer Science, University of Pittsburgh, Pitt sburgh, PA 15260, e-mail: {amaries, mdabedul, marai }@cs.pitt.edu S. Levent Yilmaz Center for Simulation and Modeling, University of Pittsburgh, Pittsburgh, PA 15260, e-mail: slyilmaz@pitt.edu Mehdi B. Nik Department of Mechanical Engineering and Materials Science , University of Pittsburgh, Pittsburgh, PA 15260, e-mail: smb51@pitt.edu
Suicide, Jews and Judaism

Strictness of adherence to Jewish law varies. Jewish groups are often categorised by strictness of adherence expected or recommended by the synagogue which forms a centre of religious and social life: strictly orthodox, traditionally and modern orthodox, reform and other non-orthodox groups, non-observant and nonaffiliated. In Israel a common categorisation of religious grouping is strictly orthodox, traditional and secular. Within these very broad groups there are many sub-groups but it will not be helpful to describe them here. It is useful to bear in mind that while Jews may vary in adherence to and knowledge of Jewish religious law (Halacha) we cannot make firm predictions about adherence and knowledge from group identification. Nevertheless we can ask in this paper whether and how identification as a Jew, and as a Jew of particular degree of religiosity, might relate to suicide beliefs and behaviour.
CHAPTER 14 Antimicrobial Resistance in Gram Positive and Gram Negative Bacteria Progress and Challenges

Serious infections caused by bacteria that have become resistant to commonly used antibiotics have become a major global healthcare problem in the 21st century. Antibiotic resistance, initially a problem of the hospital setting associated with an increased number of hospitals acquired infections usually in critically ill and immuno-suppressed patients, has now extended into the community causing severe infections difficult to diagnose and treat. In hospitals, most common resistant bacteria include methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci and gram-negative rods including Enterobacteriaceae and Pseudomonas aeruginosa. Vancomycin intermediate and resistant S. aureus, represent a new treatment challenge. In the community, penicillin and macrolide-resistant pneumococci developed several decades ago and are now present all over the world. More recently, community-acquired methicillin-resistant S. aureus has become a problem in several countries causing skin infections but also severe diseases. The molecular mechanisms by which bacteria have become resistant to antibiotics are diverse and complex. Bacteria have developed resistance to all different classes of antibiotics discovered to date. The most frequent type of resistance is acquired and transmitted horizontally via the conjugation of a plasmid. In recent times new mechanisms of resistance have resulted in the simultaneous development of resistance to several antibiotic classes creating very dangerous multidrug-resistant (MDR) bacterial strains, some also known as ‘‘superbugs’’. In many cases the use of
Effect of vegetation density, height, and connectivity on the oviposition pattern of the leaf beetle Galeruca tanaceti

Vegetation structure can profoundly influence patterns of abundance, distribution, and reproduction of herbivorous insects and their susceptibility to natural enemies. The three main structural traits of herbaceous vegetation are density, height, and connectivity. This study determined the herbivore response to each of these three parameters by analysing oviposition patterns in the field and studying the underlying mechanisms in laboratory bioassays. The generalist leaf beetle, Galeruca tanaceti L. (Coleoptera: Chrysomelidae), preferentially deposits its egg clutches on non‐host plants such as grasses. Earlier studies revealed that oviposition within structurally complex vegetation reduces the risk of egg parasitism. Consequently, leaf beetle females should prefer patches with dense, tall, or connected vegetation for oviposition in order to increase their reproductive success. In the present study, we tested the following three hypotheses on the effect of stem density, height, and connectivity on oviposition: (1) Within habitats, the number of egg clutches in areas with high stem densities is disproportionately higher than in low‐density areas. The number of egg clutches on (2) tall stems or (3) in vegetation with high connectivity is higher than expected for a random distribution. In the field, stem density and height were positively correlated with egg clutch presence. Moreover, a disproportionately high presence of egg clutches was determined in patches with high stem densities. Stem height had a positive influence on oviposition, also in a laboratory two‐choice bioassay, whereas stem density and connectivity did not affect oviposition preferences in the laboratory. Therefore, stem height and, potentially, density, but not connectivity, seem to trigger oviposition site selection of the herbivore. This study made evident that certain, but not all traits of the vegetation structure can impose a strong influence on oviposition patterns of herbivorous insects. The results were finally compared with data on the movement patterns of the specialised egg parasitoid of the herbivore in comparable types of vegetation structure.
Harmonic averages, exact difference schemes and local Green’s functions in variable coefficient PDE problems

A brief survey is given to show that harmonic averages enter in a natural way in the numerical solution of various variable coefficient problems, such as in elliptic and transport equations, also of singular perturbation types. Local Green’s functions used as test functions in the Petrov-Galerkin finite element method combined with harmonic averages can be very efficient and are related to exact difference schemes.
Measurements of sub-3 nm particles using a particle size magnifier in different environments: from clean mountain top to polluted megacities

Abstract. The measurement of sub-3 nm aerosol particles is technically challenging. Therefore, there is a lack of knowledge about the concentrations of atmospheric sub-3 nm particles and their variation in different environments. In this study, the concentrations of ∼ 1–3 nm particles measured with a particle size magnifier (PSM) were investigated at nine sites around the world. Sub-3 nm particle concentrations were highest at the sites with strong anthropogenic influence. In boreal forest, measured particle concentrations were clearly higher in summer than in winter, suggesting the importance of biogenic precursor vapors in this environment. At all sites, sub-3 nm particle concentrations had daytime maxima, which are likely linked to the photochemical production of precursor vapors and the emissions of precursor vapors or particles from different sources. When comparing ion concentrations to the total sub-3 nm particle concentrations, electrically neutral particles were observed to dominate in polluted environments and in boreal forest during spring and summer. Generally, the concentrations of sub-3 nm particles seem to be determined by the availability of precursor vapors rather than the level of the sink caused by preexisting aerosol particles. The results also indicate that the formation of the smallest particles and their subsequent growth to larger sizes are two separate processes, and therefore studying the concentration of sub-3 nm particles separately in different size ranges is essential.
Low-Cost and High-Gain SIW Circularly Polarized Circular-Horn-Loaded Antenna for Broadband Millimeter-Wave Applications

A wideband, low-cost and high-gain circularly polarized (CP) circular-horn-loaded antenna based on substrate integrated waveguide (SIW) technology operating at Ka band is presented. The proposed antenna, which is built on a single-layer substrate, consists of five parts: a short-ended SIW, a center-symmetric wide slot, an L-shaped probe, a circular horn and a transition from SIW to air-filled rectangular waveguide for measurement. The slot is etched on the upper ground of the SIW, while the L-shaped probe for generating CP wave is printed inside the slot and connected to the SIW. A circular horn is also loaded on the surface of the SIW slot for high gain. Then, the proposed antenna with a dimension of 45  45  24.16 mm was fabricated and measured. The measured results show that the antenna has a wide impedance bandwidth of 28.6% from 30 to 40 GHz for |S11|  10 dB and a wide axial ratio (AR) bandwidth of 22.2% from 32 to 40 GHz for AR  3 dB. The measured maximum gain is 15.6 dBi at 36 GHz with slight fluctuations over the 30–40-GHz frequency range.
Bank Size , Capital Requirements , and Systemic Risk : Some International Evidence

This paper studies the significant variation in the cross-section of individual and systemic risk of large banks during the recent financial crisis to identify bank specific factors that determine risk. The results indicate that individual and systemic risk grows with bank size and is inversely related to bank capital, consistent with the presence of agency conflicts in large organizations and too big to fail considerations. Our results contribute to the ongoing debate on the merits of imposing systemic risk-based capital requirements on banks. JEL classification: G01; G21; G28
Applying CHAID for logistic regression diagnostics and classification accuracy improvement

In this study a CHAID-based approach to detecting classification accuracy heterogeneity across segments of observations is proposed. This helps to solve some important problems, facing a model-builder: (1) How to automatically detect segments in which the model significantly underperforms? and (2) How to incorporate the knowledge about classification accuracy heterogeneity across segments to partition observations in order to achieve better predictive accuracy? The approach was applied to churn data from the UCI Repository of Machine Learning Databases. By splitting the data set into four parts, which are based on the decision tree, and building a separate logistic regression scoring model for each segment we increased the accuracy by more than 7 percentage points on the test sample. Significant increase in recall and precision was also observed. It was shown that different segments may have absolutely different churn predictors. Therefore such a partitioning gives a better insight into factors influencing customer behavior.
Utilising buffer management to manage patient flow

TOC buffer management has been successfully developed to improve patient flow across emergency and planned health and social care within the UK and Holland. This paper details these developments before attempting to uncover the theoretical basis of the approach through multi-case research across three UK hospitals. The authors demonstrate how buffer management concepts can be used to emulate the kanban control principles in a health and social care environment and thereby strategically support lean implementations.
Radiocarbon distributions in Southern Ocean dissolved and particulate organic matter

Dissolved organic carbon (DOC) is the largest actively exchanging pool of organic carbon in the ocean, yet its sources and sinks are not well constrained. The average 14C ages of DOC in the deep N. Atlantic and N. Pacific Oceans are 4,000 [Bauer et al., 1992; Druffel et al., 1992] and 6,000 years [Williams and Druffel, 1987], respectively, and represent the beginning and end of the deep ocean conveyor [Broecker, 1991]. Here we report that the deep Southern Ocean DOC has a 14C age (5,600 y) much closer to that of the deep N. Pacific, but its concentration in seawater (41±2 µM) is nearly equal to that of the deep N. Atlantic. The radiocarbon and concentration data indicate that most, but not all, deep DOC is transported conservatively with the ocean's conveyor. A younger (post‐bomb) source of DOC to the N. Atlantic is the most likely explanation for the large age difference we observe between deep DOC in the Atlantic and Southern Oceans. Other possibilities are a source of older DOC or a smaller microbial sink in the S. Ocean, or perhaps a possible slowdown of S. Ocean deep water formation during the past century [Broecker et al., 1999].
1 Supplementing dairy ewes grazing low quality 2 pastures with plant-derived oils and rumen-protected 3 EPA + DHA pellets improves lactation traits and body 4 condition score 5

The Australian dairy sheep industry is small and mostly based on a natural grass grazing 30 system which can limit productivity. The current study tested different plant oil-infused and rumen 31 protected polyunsaturated fats and their interactions with sire breeds to improve lactation traits and 32 body condition score (BCS) of ewes grazing low quality pastures. It was hypothesised that 33 supplementing lactating ewe diets plant-derived polyunsaturated oils will improve milk production and 34 composition without compromising BCS. Sixty ewes (n=10/treatment) in mid-lactation, balanced by sire 35 breed, parity, milk yield, body condition score, and liveweight were supplemented with: 1) control: 36 wheat-based pellets without oil inclusion; wheat-based pellets including 2) canola oil (CO); 3) rice 37 bran oil (RBO); 4) flaxseed oil (FSO), 5); safflower oil (SFO) and 6) rumen protected fat containing 38 eicosapentaenoic acid and docosahexaenoic acid (RPO). Except for the control group, all 39 supplementary diets included the same level of 50 ml/kg DM of oil and all diets were isocaloric and 40 isonitrogenous. Experimental animals were grazed in the same paddock with ad libitum access to 41 pasture, hay and water during the 10-week study. RPO was the most effective diet that enhanced 42 milk, fat and protein yields by approximately 30, 13, and 31% respectively (P<0.0001). Significant 43 increase in milk production was also observed in CO, RBO, and SFO (P<0.0001). Breed significantly 44 influenced animal performance with higher milk yield recorded for crossbred Awassi x East Friesian 45 (AW x EF) (578 g/day) vs purebred Awassi (452 g/day) (P<0.0001). This study provides empirical 46 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 13 November 2018 doi:10.20944/preprints201811.0307. v1 © 2018 by the author(s). Distributed under a Creative Commons CC BY license. Peer-reviewed version available at Animals 2018, 8, 241; doi:10.3390/ani8120241
Rendering Vibrotactile Flow on Backside of the Head: Initial Study

In this article, we present an initial study of phantom sensation synthesis on the back side of the head. We proposed to render a vibrotactile flow between the temple, occipital, and parietal regions on the head using four actuators. Taking into account that humans perceive a vibrotactile stimulation on selected locations differently loud, we normalized a perceived amplitude of respective actuators through psychophysical experiment. By pairwise actuating of adjoined actuators, we rendered ten patterns of vibrotactile flow in different directions and evaluated through additional psychophysical experiment. The results shown 86 percent of the identification accuracy where the user felt continuous vibrotactile flow between active actuators.
A POS Tagging Model Adapted to Learner English

There has been very limited work on the adaptation of Part-Of-Speech (POS) tagging to learner English despite the fact that POS tagging is widely used in related tasks. In this paper, we explore how we can adapt POS tagging to learner English efficiently and effectively. Based on the discussion of possible causes of POS tagging errors in learner English, we show that deep neural models are particularly suitable for this. Considering the previous findings and the discussion, we introduce the design of our model based on bidirectional Long Short-Term Memory. In addition, we describe how to adapt it to a wide variety of native languages (potentially, hundreds of them). In the evaluation section, we empirically show that it is effective for POS tagging in learner English, achieving an accuracy of 0.964, which significantly outperforms the state-of-the-art POS-tagger. We further investigate the tagging results in detail, revealing which part of the model design does or does not improve the performance.
ournal of Statistical Mechanics: J Theory and Experiment The eigenmode analysis of human motion

Rapid advances in modern communication technology are enabling the accumulation of large-scale, high-resolution observational data of the spatiotemporal movements of humans. Classiﬁcation and prediction of human mobility based on the analysis of such data has great potential in applications such as urban planning in addition to being a subject of theoretical interest. A robust theoretical framework is therefore required to study and properly understand human motion. Here we perform the eigenmode analysis of human motion data gathered from mobile communication records, which allows us to explore the scaling properties and characteristics of human motion.
Ironing Out the Kinks in Executive Compensation: Linking Incentive Pay to Average Stock Prices

Traditional stock option grant is the most common form of incentive pay in executive compensation. Applying a principal-agent analysis, we find this common practice suboptimal and firms are better off linking incentive pay to average stock prices. Among other benefits, averaging reduces volatility by about 42%, making the incentive pay more attractive to risk-averse executives. Holding the cost of the option grant to the firm constant, Asian stock options are more cost effective than traditional stock options and provide stronger incentives to increase stock price. More importantly, the improvement is achieved with little impact on the option grant’s risk incentives (after adjusting for option cost). Finally, averaging also improves the value and incentive effects of indexed stock options.
Utilization of Reflective Semiconductor Optical Amplifier (RSOA) for Multiwavelength and Wavelength-Tunable Fiber Lasers

In this chapter, there are three sections to demonstrate the reflective semiconductor opti‐ cal amplifier (RSOA)-based fiber laser architectures for multiwavelength and wave‐ length-tunable operations. In the first section, we introduce an L-band multiwavelength laser by utilizing a C-band RSOA with a linear cavity, which is produced by a polariza‐ tion controller (PC), an optical coupler (OCP), and a reflected fiber mirror (RFM). In the proposed RSOA laser scheme, two to seven wavelengths could be lased and created si‐ multaneously in the L-band range, while the RSOA operates at various bias currents. In the second section, we demonstrate a multiwavelength laser source by utilizing a C- band RSOA with dual-ring fiber cavity. In the measurement, the laser cavity is construct‐ ed by an RSOA, a 1×2 OCP, a 2×2 OCP, and a PC, respectively. Thus, 13–18 wavelengths around L-band could be produced simultaneously, as the bias current of C-band RSOA is driven at 30–70 mA.