Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic and adaptive cache prefetch policies

This paper begins an exploration of the applicability of traditional prefetching policies in multiprocessor architectures. In particular, the effectiveness of prefetching policies as a function of both the quality of the prefetching and the consumption of processor to memory bandwidth is an issue of interest. Addressing this issue, the concept of a dynamic and adaptive cache (DAC), two new prefetch policies, and the design of an instruction DAC, called the DAC/sup 3/, which dynamically changes its prefetch policy at runtime, in response to process execution characteristics, are introduced. In addition, a detailed performance analysis of the DAC/sup 3/ and two new prefetch policies, which the DAC/sup 3/ uses, are presented; the performance of the DAC/sup 3/ is compared to that of the SSB prefetch instruction cache, which is based on Jouppi's sequential stream buffer design. This performance analysis is based on a new metric called CompositeCPI, which captures the usefulness of prefetches and their cost in terms of consumed memory bandwidth. The performance analysis indicates that, for the cache configurations and multiprogram workloads studied, the DAC/sup 3/ is superior to the SSB instruction prefetch cache.
Defining the Role of BTLA in Breast Cancer Immunosurveillance and Selective Targeting of the BTLA-HVEM-LIGHT Costimulatory System

Abstract : Costimulatory (CD28, ICOS) and inhibitory (CTLA4, PD-1) molecules of the CD28 receptor family provide critical secondary signals regulating the balance between protective immunity and tissue injury. We recently cloned B- and T-lymphocyte attenuator (BTLA), the third inhibitory receptor of the CD28 family expressed on lymphocytes. Using BTLA-deficient mice and monoclonal antibodies specific for BTLA that we generated, we have studied several in vivo models of infection and autoimmunity, showing the importance of BTLA in regulating immune responses. The hypothesis of this application was that BTLA contributes to the inhibition of breast cancer immunosurveillance, and selective targeting of the BTLA-LIGHT-HVEM costimulatory system can enhance breast cancer immunity. The overall aim was to evaluate the role of BTLA in breast cancer immunosurveillance, and develop novel therapeutics targeting the BTLA-LIGHT-HVEM costimulatory system. We observed that (1) various HVEM mutants were generated that ablate binding of BTLA but preserve binding of LIGHT. However, wild type HVEM but not mutant HVEM is an effective molecular adjuvant in the context of DNA vaccination, (2) expression of BTLA in human breast cancers of various histologic types is restricted to only 1-3% of CD8 T cells in tumor and tumor-draining lymph nodes, (3) in a murine graft-versus-host disease (GVHD) model anti-BTLA therapy permanently prevented GVHD through blockade of alloreactive donor T cells, and, (4) BTLA is highly expressed on a subset of dendritic cells uniquely qualified for cross-presentation of antigen and generation of effective T cell immunity. In summary, progress has been made towards the goal of defining the role of BTLA in breast cancer immunosurveillance.
Stress, Stress Reactions, Job Stressors and Coping among Nurses Working in Intensive Care Units and General Wards of a Tertiary Care Hospital: A Comparative Study

Literature has presented nursing as a stressful profession. The present study was conducted to compare stress level and job stressors operating in two different units, i.e. intensive care units (ICU) and general wards of a tertiary care hospital of North India. This is a cross-sectional study involving 285 nurses (general wards = 176; ICU = 109). The nurses were selected conveniently. Demographic profile sheet, modified workplace stress scale (WSS), workplace stress symptom scale (WSSS) and coping checklist (CCL) of Rao, Subbakrishna and Prabhu (1989) was used in the study. Findings of the study revealed moderate to high stress level among general wards and ICU nurses with young female nurses experiencing more stress. Further, workload, role ambiguity and lesser social support accounted for significant amount stress among nurses working on both the units while external factors, such as physical environment and resources hardly contributed to stress. It was also found that the ICU nurses experienced stress more in the form of exhaustion (11.9%); irritation (11.9%) and reduced self-confidence (0.9%) that those working in general wards. However, the nurses on both the units use distraction, positive coping, problem-solving and religious strategies to manage and handle their stress. The findings of the study give insight into stress and stressors related to job which can be buffered using various stress management strategies by the nurse managers.
An Enhanced Image Descriptor Algorithm for Image Retrieval using SIFT – PCA

Due to the growth of internet and social media sites there has been a proliferation of images which makes image retrieval a challenging job. The proposed an Enhanced Image Descriptor Algorithm for Image Retrieval using SIFT-PCA involves three steps: feature detection (Harris Detector), feature description (SIFT), dimension reduction (PCA). The features of all images in database are retrieved and stored in feature database in the form of histogram. When a query image is given, the generated histogram of query image is matched with feature database of all image histograms and those images with minimum distance are retrieved. Euclidean distance is used as the distance measure. For analyzing the performance of the algorithm, average precision and recall are used. Precision is the measure of ability of a system to present all the relevant items and Recall is defined as the ability to present only relevant items.
A coordinated study of 1 h mesoscale gravity waves propagating from Logan to Boulder with CRRL Na Doppler lidars and temperature mapper

We present the first coordinated study using two lidars at two separate locations to characterize a 1 h mesoscale gravity wave event in the mesopause region. The simultaneous observations were made with the Student Training and Atmospheric Research (STAR) Na Doppler lidar at Boulder, CO, and the Utah State University Na Doppler lidar and temperature mapper at Logan, UT, on 27 November 2013. The high precision possessed by the STAR lidar enabled these waves to be detected in vertical wind. The mean wave amplitudes are ~0.44 m/s in vertical wind and ~1% in relative temperature at altitudes of 82–107 km. Those in the zonal and meridional winds are 6.1 and 5.2 m/s averaged from 84 to 99 km. The horizontal and vertical wavelengths inferred from the mapper and lidars are ~219 ± 4 and 16.0 ± 0.3 km, respectively. The intrinsic period is ~1.3 h for the airglow layer, Doppler shifted by a mean wind of ~17 m/s. The wave packet propagates from Logan to Boulder with an azimuth angle of ~135° clockwise from north and an elevation angle of ~ 3° from the horizon. The observed phase difference between the two locations can be explained by the traveling time of the 1 h wave from Logan to Boulder, which is about ~2.4 h. The wave polarization relations are examined through the simultaneous quantifications of the three wind components and temperature. This study has developed a systematic methodology for fully characterizing mesoscale gravity waves, inspecting their intrinsic properties and validating the derivation of horizontal wave structures by applying multiple instruments from coordinated stations.
Do Language Learners Recognize Pragmatic Violations? Pragmatic Versus Grammatical Awareness in Instructed L2 Learning.

L2 learners often develop grammatical competence in the absence of concomitant pragmatic competence (Bardovi-Harlig & Hartford, 1990, 1993). In an attempt to better understand how this developmental stage arises, this study explores the extent to which instructed L2 learners of English are aware of differences in learners' and target-language production in grammar, which addresses the accuracy of utterances, and pragmatics, which addresses the appropriateness of utterances given specific situations, speakers, and content. We used a videotape with 20 scenarios to test 543 learners and their teachers (N = 53) in two countries (Hungary and the U.S.) as well as a secondary sample of 112 EFL speakers in Italy. The results show that whereas EFL learners and their teachers consistently identified and ranked grammatical errors as more serious than pragmatic errors, ESL learners and their teachers showed the opposite pattern, ranking pragmatic errors as more serious than grammatical errors. We discuss the possible causes of this pattern and its implications for teaching.
LYMPHOID CELLS OF GERM-FREE MICE

Previous studies of enzymatically iodinated splenocytes from normal BALB/c mice indicate that cell surface Ig is primarily 8S IgM (1) which is rapidly released on a fragment of plasma membrane (shedding) during incubation of iodinated cells (2). In contrast, labeling of the same cell population with [SH]tyrosine results in secretion of radioactive IgG, 19S IgM, and 8S IgM all unassociated with plasma membrane (2). To explain these findings, we suggested (3) that Ig might be transported to the cell surface in post Golgi vesicles where Ig destined to have a surface phase would be attached to the inner surface of a Golgi vesicle and Ig to be secreted would be "free" in the vesicle. We also suggested that the exteriorization of cell surface and secreted Ig might be independently regulated.
Flexible A-scan rate MHz OCT: computational downscaling by coherent averaging

In order to realize fast OCT-systems with adjustable line rate, we investigate averaging of image data from an FDML based MHz-OCT-system. The line rate can be reduced in software and traded in for increased system sensitivity and image quality. We compare coherent and incoherent averaging to effectively scale down the system speed of a 3.2 MHz FDML OCT system to around 100 kHz in postprocessing. We demonstrate that coherent averaging is possible with MHz systems without special interferometer designs or digital phase stabilisation. We show OCT images of a human finger knuckle joint in vivo with very high quality and deep penetration.
ALBATROSS : a learning based transportation oriented simulation system

This paper describes the conceptual development, operationalization and empirical testing of Albatross: A Learning Based Transportation Oriented Simulation System. This activity-based model of activity-travel behavior is derived from theories of choice heuristics that consumers apply when making decisions in complex environments. The model, one of the most comprehensive of its kind, predicts which activities are conducted when, where, for how long, with whom, and the transport mode involved. In addition, various situational, temporal, spatial, spatial-temporal and institutional constraints are incorporated in the model. The decision tree is proposed as a formalism to represent an exhaustive set of mutual exclusive rules for each decision step in the model. A CHAID decision tree induction method is used to derive decision trees from activity diary data. The case study conducted to develop and test the model indicates that performance of the model is very satisfactory. We conclude therefore that the methodology proposed in this article is useful to develop computational process models of activity-travel choice behavior.
Original Paper Challenge to go: Systematic development of a theory-based and target group-adapted mobile app intervention to improve eating habits of adolescents and young adults

Background Due to the widespread use of smartphones, dietary mobile apps are promising tools for preventing diet-related non-communicable diseases early in life. But, most of currently available nutrition apps lack scientific evaluation and user acceptance. Objectives The objective of the present study was the systematic design of a theory-driven and target groupadapted dietary mobile app concept to promote healthy eating habits with a focus on drinking habits as well as consumption of fruits and vegetables in adolescents and young adults, especially in deprived life situations. Methods The design process was guided by the behaviour change wheel (BCW). The development process consisted of three stages. In stage 1, the target behavior was specified, and facilitators and barriers were identified. Furthermore, important insights into target group interests, needs and values in the field of nutrition and apps were revealed. To this end, two empirical studies were conducted with the target group. In stage 2, results of stage 1 were translated into behavior change techniques (BCTs) and finally into app functionalities and features. Consequently, in stage 3, the concept was evaluated and optimized through expert interviews. Results Facilitators and barriers for achieving the target behavior were psychological capabilities (e.g. selfefficacy), reflective motivation (e.g. fitness), automatic motivation, social support, and physical opportunity (e.g. time). Target group interests, needs and values in the field of nutrition were translated into target group preferences for app usage, e.g. low usage effort, visual feedback or recipes. Education, training, incentives, persuasion, and enablement were identified as relevant interventions functions. Together with the target group preferences, these were translated via 14 BCTs, such as rewards, graded tasks or self-monitoring, into the app concept Challenge to go (C2go). The expert evaluation suggested changes of some app features for improving adherence, positive health effects and technical feasibility. The C2go concept consists of three worlds: (i) drinking, (ii) vegetable, and (iii) fruit world. In each world, the users are faced with challenges including feedbacks and a quiz. Tips were developed based on the health action process approach and help users to gain challenges and thereby achieve the target behavior. Challenges can be played alone or against someone in the community. Due to different activities, points can be collected, and levels can be achieved. Collected points open access to an infothek, where users can choose content that interest them. An avatar guides user through the app. Conclusions
Creating Modern Community Conservation Organizations and Institutions to Effect Successful Forest Conservation Change

Despite increased investment, current conservation strategies have failed to stop environmental degradation and loss of biodiversity of the earth’s ecosystems with consequent climate change. Community Conservation’s (CC) 30 years of experience has produced a successful, cost-effective, field-tested flexible formula to catalyze communities to stop deforestation and biodiversity loss. Our method focuses on four concepts: 1) catalyzing projects, leaving ownership to on-site community-based organizations (CBOs) or local nongovernmental organizations (NGOs); 2) encourag‐ ing creation of CBOs; 3) helping build complex federations or networks for a stronger community voice; and 4) creating conservation contagion for regional change. Based on trust, we initially make the community aware of their special forests and wildlife and ask their help in protecting them. Then we help them create CBOs and build federations of conservation activists to strengthen and empower them to manage their projects and their natural resources. By bringing community members to interact together from within a large region, we strive to create conservation contagion. Case histories from Assam, India; northern Peru; the Huon Peninsula in Papua New Guinea; Madagascar; Belize; and Wisconsin, USA demonstrate successes based on the formation of CBOs and community federations, allowing communities to play a powerful role in protecting and restoring forests.
Casual Information Visualization on Mobile Devices considering the Museum Context

With 79%, smartphones were the most used devices for accessing the internet in the EU in 2016 (Eurostat, 2016). High-speed mobile data connectivity reaches even remote locations. Increasing computational power and display size provides users a comfortable user experience. However, mobile visualizations which profit from those circumstances are hardly widespread these days. Problems of visualizations on mobile devices are the limited screen size and inexact touch input. Benefits of mobile devices are the high availability and the broad palette of built-in sensors and input options. This might make mobile devices, for example, smartphones, great devices in the museum context. Keeping the needs of casual museum visitors in mind when finding appropriate visualization techniques is a critical task. The present work gives a broad overview of the state of the art of mobile visualizations and the design, implementation, and evaluation of a visualization of an art museum’s collection. Therefore, the collection of the museum of modern art mumok located in Vienna is accessed through the Open Data Portal Österreich. This data is visualized with the libraries D3.js, Google Maps and ngx-charts. For the frontend of the application, the mobile framework Ionic is used. At the end, the application was evaluated in mumok with 21 participants.
ONE DAY INTERNATIONAL CRICKET MATCHES USING MACHINE LEARNING

Player selection is one the most important tasks for any sport and cricket is no exception. The performance of the players depends on various factors such as the opposition team, the venue, his current form etc. The team management, the coach and the captain select 11 players for each match from a squad of 15 to 20 players. They analyze different characteristics and the statistics of the players to select the best playing 11 for each match. Each batsman contributes by scoring maximum runs possible and each bowler contributes by taking maximum wickets and conceding minimum runs. This paper attempts to predict the performance of players as how many runs will each batsman score and how many wickets will each bowler take for both the teams. Both the problems are targeted as classification problems where number of runs and number of wickets are classified in different ranges. We used naïve bayes, random forest, multiclass SVM and decision tree classifiers to generate the prediction models for both the problems. Random Forest classifier was found to be the most accurate for both the problems.
Tutorial on Static Inference of Numeric

Born in the late 70s, Abstract Interpretation has proven an effective method to construct static analyzers. It has led to successful program analysis tools routinely used in avionic, automotive, and space industries to help ensuring the correctness of mission-critical software. This tutorial presents Abstract Interpretation and its use to create static analyzers that infer numeric invariants on programs. We first present the theoretical bases of Abstract Interpretation: how to assign a well-defined formal semantics to programs, construct computable approximations to derive effective analyzers, and ensure soundness, i.e., any property derived by the analyzer is true of all actual executions — although some properties may be missed due to approximations, a necessary compromise to keep the analysis automatic, sound, and terminating when inferring uncomputable properties. We describe the classic numeric abstractions readily available to an analysis designer: intervals, polyhedra, congruences, octagons, etc., as well as domain combiners: the reduced product and various disjunctive completions. This tutorial focuses not only on the semantic aspect, but also on the algorithmic one, providing a description of the data-structures and algorithms necessary to effectively implement all our abstractions. We will encounter many trade-offs between cost on the one hand, and precision and expressiveness on the other hand. Invariant inference is formalized on an idealized, toy-language, manipulating perfect numbers, but the principles and algorithms we present are effectively used in analyzers for real industrial programs, although this is out of the scope of this tutorial. This tutorial is intended as an entry course in Abstract Interpretation, after which the reader should be ready to read the research literature on current advances in Abstract Interpretation and on the design of static analyzers for real languages. A. Miné. Tutorial on Static Inference of Numeric Invariants by Abstract Interpretation. Foundations and Trends © in Programming Languages, vol. 4, no. 3-4, pp. 120–372, 2017. DOI: 10.1561/2500000034. Full text available at: http://dx.doi. org/10.1561/2500000034
Weibo Footprint: A Web-based Visualization System to Analyzing Spatial-temporal Movement of Geo-tagged Social Media Users

Vis PKU xiaoru.yuan@pku.edu.cn http://vis.pku.edu.cn Contact Introduction Visualization We propose a visualization system allowing users to explore their own trajectories from geo-tagged social media. Our system enables users to understand the global movement trends and spot interesting and memorable behaviors. We can observe many interesting patternsshared by users and their friends. With our tool, we aim to bridge the gap of general public and their understanding of data. Data Xiaoru Yuan
An EÆcient Text Summarizer Using Lexical Chains

We present a system which uses lexical chains as an intermediate representation for automatic text summarization. This system builds on previous research by implementing a lexical chain extraction algorithm in linear time. The system is reasonably domain independent and takes as input any text or HTML document. The system outputs a short summary based on the most salient concepts from the original document. The length of the extracted summary can be either controlled automatically, or manually based on length or percentage of compression. While still under development, the system provides useful summaries which compare well in information content to human generated summaries. Additionally, the system provides a robust test bed for future summary generation research.
Mutual modulation of femarelle and vitamin D analog activities in human derived female cultured osteoblasts

Abstract Introduction: Pre-, post-menopausal, and male human osteoblasts (hObs) express estradiol-17β (E2) receptors α and β (ERα, ERβ), vitamin D receptor (VDR), and 25-hydroxy vitamin D3 1-α hydroxylase (1OHase) and produce 1,25 (OH)2D3 (1,25D). Pre-treatment with JKF (JKF 1624F2–2) up-regulated estrogenic responsiveness, via modulation of ERs expression and E2 binding. These estrogens induce VDR and 1OHase expression and 1,25D production. Purpose: Compared the effects of femarelle (F) to daidzein (D) and E2 by themselves and their modulation by JKF. Methods: hObs derived from human bones at different ages and sex were cultured, treated with different hormones and analyzed for the different parameters. Results: (1) F, D and E2 stimulated 3[H] thymidine incorporation (DNA) and creatine kinase specific activity (CK) in female but not in male hObs. The responses to E2 and to D unlike to F were up-regulated by JKF. (2) All hormones increased ERα and decreased ERβ mRNA in all hObs. (3) JKF modulated in different ways the expressions of ERα and ERβ mRNA in all hObs. (4) JKF did not significantly modulate the expressions of ERα and ERβ mRNA in all hObs. (5) JKF increased intracellular competitive binding of E2 by all hormones only in female hObs. (6) Pre-treatment with all hormones increased VDR and 1OHase expression and 1,25D formation in pre- and post-, but only JKF modulated it in male hObs. Conclusions: F, D and E2 increase different parameters in hObs. However, pre-treatment with JKF modulates the effect of E2 and D but not of F. F reciprocally modulates mRNA expression and activity of 1OHase which in turn up-regulate ERs expression and activity. These finding may contribute to F’s beneficial role in treatment of post-menopausal bone loss even in vitamin D deficiency.