Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracting Facts from Performance Tuning History of Scientific Applications for Predicting Effective Optimization Patterns

To improve performance of large-scale scientific applications, scientists or tuning experts make various empirical attempts to change compiler options, program parameters or even the syntactic structure of programs. Those attempts followed by performance evaluation are repeated until satisfactory results are obtained. The task of performance tuning requires a great deal of time and effort. On account of combinatorial explosion of possible attempts, scientists/tuning experts have a tendency to make decisions on what to be explored just based on their intuition or good sense of tuning. We advocate evidence-based performance tuning (EBT) that facilitates the use of database of facts extracted from tuning histories of applications to guide the exploration of the search space. However, in general, performance tuning is conducted as transient tasks without version control systems. Tuning histories may lack explicit facts about what kind of program transformation contributed to the better performance or even about the chronological order of the source code snapshots. For reconstructing the missing information, we employ a state-of-the-art fine-grained change pattern identification tool for inferring applied transformation patterns only from an unordered set of source code snapshots. The extracted facts are intended to be stored and queried for further data mining. This paper reports on experiments of tuning pattern identification followed by predictive model construction conducted for a few scientific applications tuned for the K supercomputer.
Measuring Term Specificity Information for Assessing Sentiment Orientation of Documents in a Bayesian Learning Framework

The assessment of document sentiment orientation using term specificity information is advocated in this study. An interpretation of the mathematical meaning of term specificity information is given based on Shannon’s entropy. A general form of a specificity measure is introduced in terms of the interpretation. Sentiment classification using the specificity measures is proposed within a Bayesian learning framework, and some potential problems are clarified and solutions are suggested when the specificity measures are applied to estimation of posterior probabilities for the NB classifier. A novel method is proposed which allows each document to have multiple representations, each of which corresponds to a sentiment class. Our experimental results show, while both the proposed method and IR techniques can produce high performance for sentiment classification, that our method outperforms the IR techniques.
Regulation of Glucose Transport in Quiescent, Lactating, and Neoplastic Mammary Epithelia

Abstract : We studies developmental changes in glucose transporter (GT) targeting in mammary gland, a prerequisite for the understanding GT targeting in breast cancer. Previously, we established that GLUT1 is targeted to Golgi during lactation. To understand the regulation of this process, we carried out subcellular fractionation and density gradient centrifugation, Western blotting, and immunofluorescence in mammary glands of mothers whose pups were prematurely weaned. We conclude: (1) There is enrichment of Golgi by GLUT1 during lactation. This is lost by 5h of weaning. (2) Enrichment can be restored by returning the pups to the mother for 5h. (3) At 10h, total cellular content of GLUT1 begins to decrease. (4) A 72 kD protein recognized by the GLUT1 antibody showed even more striking Golgi enrichment than GLUT1. (5) Intermediate MW forms at 50 and 65 kD were also observed. These each demonstrate specific patterns of appearance, disappearance, and subcellular localization, and can be deglycosylated to give aglyco GLUT1. 6) The 72 kD protein was resistant to deglycosylation. Based on the kinetics of its appearance and disappearance, its physicochemical properties which suggest it is not a GT, and based on its subcellular localization in the Golgi, p72 is an excellent candidate for a protein involved in sequestering GTs within the Golgi. (7) Ubiquitin appears to play an important role in the rapid degradation of GLUT1 and p72 during premature weaning. Identification of the cellular proteins, perhaps including p72 and ubiquitin, that constitute the mechanism by which these changes in GT targeting and amount, respectively, are achieved is a necessary step if we are to take advantage of this mechanism to alter GT targeting in cancer cells.
Introduced red deer reduce tree regeneration in Pureora Forest, central North Island, New Zealand.

This study uses data from repeatedly measured forest monitoring plots (20 × 20 m) (n = 32) and nine ungulate exclosures (paired fenced and unfenced plots; 20 × 20 m) to show the effects of introduced ungulates on tree regeneration in Pureora Forest Park, central North Island, between 1974 and 2002. Results show that introduced ungulates, particularly red deer (Cervus elaphus scoticus), have suppressed the regeneration of hardwood species such as Coprosma grandifolia, Elaeocarpus dentatus, Griselinia littoralis, Melicytus ramiflorus , Schefflera digitata and Weinmannia racemosa. These species were only common as saplings and small trees in the complete absence of ungulate browsing. The results of this study suggest that red deer will need to be culled to low densities to assure regeneration of palatable tree species in Pureora Forest.
A Novel Two-port Model for Interconnect Lines Driving Arbitrary Loads

This paper presents an order-reduced model for the analysis of interconnects driving an arbitrary load. It is shown that this model can be used to approximate the two-port admittance matrix of a transmission line to arbitrary accuracy, bearing explicit physical senses. It is based on series expansion, and can generate a lumped passive circuit model, but is different from moment-matching, yielding a passive and thus stable circuit model. Comparison with other models shows the effectiveness and precision of the proposed model over a wide frequency range.
Effects of Factors Related to Water Quality and Population Density on the Sensitivity of Juvenile Largemouth Bass to Mortality Induced by Viral Infection

Abstract Environmental stressors can predispose fish to mortality from infectious disease. This study examined the effects of two factors, water quality and physical crowding, on the responses of fish to viral infection. Juvenile largemouth bass Micropterus salmoides were experimentally inoculated with largemouth bass virus (LMBV), an emerging pathogen in the family Iridoviridae. In separate experiments, fish were exposed to various concentrations of nitrate (0, 40, 200, and 400 mg/L) and were housed at either high or low population densities. Survival time, viral load (quantity of virus in tissues), and body condition were measured as outcomes. Nitrate, as well as other water quality parameters such as ammonia, nitrite, and pH, affected mortality rates and viral loads in complex ways. Paradoxically, increased nitrate concentrations were associated with reduced mortality rates in juveniles exposed to LMBV. In general, rapid fluctuations in the concentrations of dissolved toxins had greater impact on sensi.
How Plastic Can Phenotypic Plasticity Be? The Branching Coral Stylophora pistillata as a Model System

Phenotypic plasticity enables multicellular organisms to adjust morphologies and various life history traits to variable environmental challenges. Here, we elucidate fixed and plastic architectural rules for colony astogeny in multiple types of colonial ramets, propagated by cutting from genets of the branching coral Stylophora pistillata from Eilat, the Red Sea. We examined 16 morphometric parameters on 136 one-year old S. pistillata colonies (of seven genotypes), originating from small fragments belonging, each, to one of three single-branch types (single tips, start-up, and advanced bifurcating tips) or to structural preparative manipulations (representing a single or two growth axes). Experiments were guided by the rationale that in colonial forms, complexity of evolving phenotypic plasticity can be associated with a degree of structural modularity, where shapes are approached by erecting iterative growth patterns at different levels of coral-colony organization. Analyses revealed plastic morphometric characters at branch level, and predetermined morphometric traits at colony level (only single trait exhibited plasticity under extreme manipulation state). Therefore, under the experimental manipulations of this study, phenotypic plasticity in S. pistillata appears to be related to branch level of organization, whereas colony traits are controlled by predetermined genetic architectural rules. Each level of organization undergoes its own mode of astogeny. However, depending on the original ramet structure, the spherical 3-D colonial architecture in this species is orchestrated and assembled by both developmental trajectories at the branch level, and traits at the colony level of organization. In nature, branching colonial forms are often subjected to harsh environmental conditions that cause fragmentation of colony into ramets of different sizes and structures. Developmental traits that are plastic, responding to fragment structure and are not predetermine in controlling astogeny, allow formation of species-specific architecture product through integrated but variable developmental routes. This adaptive plasticity or regeneration is an efficient mechanism by which isolated fragments of branching coral species cope with external environmental forces.
Direct Imaging of Anisotropic Material Properties Using Photorefractive Laser Ultrasound

Anisotropic properties of materials can be determined by measuring the propagation of elastic waves in different directions. A laser imaging approach is presented that utilizes the adaptive property of photorefractive materials to produce a real-time measurement of the antisymmetric Lamb or flexural traveling wave mode displacement and phase. Continuous excitation is employed and the data is recorded and displayed in all directions simultaneously at video camera frame rates. Fourier transform of the data produces an image of the wave slowness in all planar directions. The results demonstrate imaging of microstructural isotropy and anisotropy and stress induced ansiotropy in plates.
Multiple Social Identities Enhance Health Post-Retirement Because They Are a Basis for Giving Social Support

We examine the extent to which multiple social identities are associated with enhanced health and well-being in retirement because they provide a basis for giving and receiving social support. Results from a cross-sectional study show that retirees (N = 171) who had multiple social identities following (but not prior to) retirement report being (a) more satisfied with retirement, (b) in better health, and (c) more satisfied with life in general. Furthermore, mediation analyses revealed an indirect path from multiple social identities to greater satisfaction with retirement and better health through greater provision, but not receipt, of social support to others. These findings are the first to point to the value of multiple group membership post-retirement as a basis for increased opportunities to give meaningful support to others. We discuss the theoretical and practical implications for the management of multiple identities in the process of significant life transitions such as retirement.
Psychological skills linked to success : examining the correlation between grit, stress mindset and decision making

The motivation behind this research was to examine the relationships between the psychological variables grit, stress mindset and decision making style. Measures used included the 12-item Grit Scale, Stress Mindset Measure-General and the Maximization Scale. Participation was voluntary and obtained from a convenience sample. The design was correlational and the responses were collected via an online survey. As hypothesized, a Pearson r Correlation revealed that high levels of grit were positively correlated with a satisficing style of decision making. A multiple regression analysis revealed that, as hypothesized stress mindset and maximization significantly predict grit. Existing research has shown the importance of these variables in terms of wellbeing and success. The main conclusions drawn from the results are that further research in this area would be of value.
An automatic co-stimulation algorithm for LAN artificial immune systems

Co-stimulations are very important in LAN AISs, but there are few automatic co-stimulation algorithms or approaches at present, and almost all of co-stimulations are implemented by network-administrators. We try to find an automatic co-stimulation algorithm to replace the administrators in LAN AISs. Detectors employed to detect abnormal packets are called NS-detectors. Detectors employed to detect normal packets are called PS-detectors. Each NS-detector can detect a different kind of potential abnormal packets. Each PS-detector can describe a different kind of normal network behaviors. The NS-detector generation algorithm and the PS-detector generation algorithm are presented first. Based on them, an automatic co-stimulation algorithm for LAN AISs is described in detail. Co-stimulations in LAN AISs can be implemented automatically with the algorithm. The administrators can still implement co-stimulations, but their co-stimulations are not important. The feasibility of the algorithm is illustrated with our experiments in laboratory. Our further work is to illustrate more the feasibility of the algorithm in the Internet environment.
S2D-ProM: A Strategy Oriented Process Model for Secure Software Development

Building secure software is about taking security into account during all phases of software development. This practice is missing in, widely used, traditional developments due to domain immaturity, newness of the field and process complexity. Software development includes two views, a product view and a process view. Product view defines what the product is, whereas process view describes how the product is developed. Here we are concerned with the process view. Modelling the process allows simulate and analyze a software development process, which can help developers better understand, manage and optimize the software development process. In this paper we present our approach S2D-ProM, for Secure Software Development Process Model, which is a strategy oriented process model. This latter, capture steps and strategies that are required for the development of secure software and provide a two level guidance. The first level guidance is strategic helping developers choosing one among several strategies. The second level guidance is tactical helping developers achieving their selection for producing secure software. The proposed process model is easily extensible and allows building customized processes adapted to context, developer's finalities and product state. This flexibility allows the environment evolving through time to support new securing strategies.
HRAID : a High-speed Router based Anomaly / Intrusion Detection System

Traffic anomalies and attacks are commonplace in today’s networks, and identifying them rapidly and accurately is critical for large network operators. We propose a High-speed Router-based Anomaly and Intrusion Detection system, HRAID, leveraging our recent work on data streaming computation and in particular, sketches. We analyze the attributes in TCP/IP headers and select an optimal small set of metrics for flow-level sketch-based traffic monitoring and intrusion detection. To overcome the limitations of existing single dimension sketches, we design an efficient and accurate two-dimensional sketch to distinguish different types of attacks for mitigation. We further propose several heuristics to reduce the false positive rate for SYN flooding detection. Simulation with several router traces shows that HRAID is highly accurate, efficient, uses very small memory, and can effectively detect multiple types of attacks simultaneously. To the best of our knowledge, HRAID is the first online flow-level anomaly/intrusion detection system for high-speed networks, even for the worst case traffic of 40-byte-packet streams with each packet forming a flow.
Automatic summarisation of discussion fora

Abstract Web-based discussion fora proliferate on the Internet. These fora consist of threads about specific matters. Existing forum search facilities provide an easy way for finding threads of interest. However, understanding the content of threads is not always trivial. This problem becomes more pressing as threads become longer. It frustrates users that are looking for specific information and also makes it more difficult to make valuable contributions to a discussion. We postulate that having a concise summary of a thread would greatly help forum users. But, how would we best create such summaries? In this paper, we present an automated method of summarising threads in discussion fora. Compared with summarisation of unstructured texts and spoken dialogues, the structural characteristics of threads give important advantages. We studied how to best exploit these characteristics. Messages in threads contain both explicit and implicit references to each other and are structured. Therefore, we term the threads hierarchical dialogues. Our proposed summarisation algorithm produces one summary of an hierarchical dialogue by ‘cherry-picking’ sentences out of the original messages that make up a thread. We try to select sentences usable for obtaining an overview of the discussion. Our method is built around a set of heuristics based on observations of real fora discussions. The data used for this research was in Dutch, but the developed method equally applies to other languages. We evaluated our approach using a prototype. Users judged our summariser as very useful, half of them indicating they would use it regularly or always when visiting fora.
The e ff ect of lightning NO x production on surface ozone in the continental United States

The effect of lightning NOx production on surface ozone in the continental United States B. Kaynak, Y. Hu, R. V. Martin, A. G. Russell, Y. Choi, and Y. Wang School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA Department of Physics and Atmospheric Science, Dalhousie University Halifax, NS, Canada Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA Received: 22 January 2008 – Accepted: 2 February 2008 – Published: 7 March 2008 Correspondence to: A. G. Russell (ted.russel@ce.gatech.edu) Published by Copernicus Publications on behalf of the European Geosciences Union.
A mathematical growth model of the viral population in early HIV-1 infections

A MATHEMATICAL GROWTH MODEL OF THE VIRAL POPULATION IN EARLY HIV-1 INFECTIONS SEPTEMBER 2011 ELENA EDI GIORGI, ”Laurea,” UNIVERSITA’ DI PISA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST M.S., UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Panayotis Kevrekidis In this thesis we develop a mathematical model to describe HIV-1 evolution during the first stages of infection (approximately within 40-60 days since onset), when one can assume exponential growth and random accumulation of mutations under a neutral drift. We analyze the Hamming distance (HD) distribution under different models (synchronous and asynchronous) in the absence of selection and recombination. In the second chapter of the thesis, we introduce recombination and develop a combinatorial approach to estimate the new HD distribution. We conclude describing a T statistic to test significance differences between the HD of two genetic samples, which we derive using U-statistics.
Intelligenz: Fakten und Mythen Intelligence: Facts and Myths

Detlev H. Rost is a leading expert in investigating intelligence, deriving research-based solutions for controversial educational issues, and developing procedures for identifying and counselling gifted children. “Intelligence: Facts and Myths” is not just just another book about a “new” theory of intelligence, or about unsolicited recipes and recommendations on how to increase everyone’s IQ scores. In fact, according to Rost, books like this are completely superfluous. Rost is not trying to make the jungle of theories, determinants and predictive consequences of intelligence even more impenetrable than it already is. In fact, he accomplishes the opposite! This book is an extremely valuable and fascinating guide which provides a clear orientation for all readers – even for experts in the field – who are searching for an effective and reliable path through the existing jungle of development and research on intelligence. For this state-of-the-art compilation, the author has thoroughly analysed and structured more than 2,000 publications.
Keratoderma Hereditaria Mutilans (Vohwinkel's Syndrome): A Trial of Isotretinoin

Abstract: An 8‐year‐old girl with the classic findings of keraloderma heredilaria mutilans (Vohwinkel's syndrome) was seen. Treatment with isotretinoin was instituted to decrease the hyperkeratosis and to prevent further autoamputation. After a 12‐week course at 2 mg per kg per day, the patient had only minimal decrease in the amount of hyperkeratosis. Because of Ihe well‐known long‐term risks of systematic retinoids and her suboptimal improvement, therapy was discontinued.
Semisupervised Multitask Learning

Context plays an important role when performing classification, and in this paper we examine context from two perspectives. First, the classification of items within a single task is placed within the context of distinct concurrent or previous classification tasks (multiple distinct data collections). This is referred to as multi-task learning (MTL), and is implemented here in a statistical manner, using a simplified form of the Dirichlet process. In addition, when performing many classification tasks one has simultaneous access to all unlabeled data that must be classified, and therefore there is an opportunity to place the classification of any one feature vector within the context of all unlabeled feature vectors; this is referred to as semi-supervised learning. In this paper we integrate MTL and semi-supervised learning into a single framework, thereby exploiting two forms of contextual information. Example results are presented on a "toy" example, to demonstrate the concept, and the algorithm is also applied to three real data sets.
Optimizing Timing of Immunotherapy Improves Control of Tumors by Hypofractionated Radiation Therapy

The anecdotal reports of promising results seen with immunotherapy and radiation in advanced malignancies have prompted several trials combining immunotherapy and radiation. However, the ideal timing of immunotherapy with radiation has not been clarified. Tumor bearing mice were treated with 20Gy radiation delivered only to the tumor combined with either anti-CTLA4 antibody or anti-OX40 agonist antibody. Immunotherapy was delivered at a single timepoint around radiation. Surprisingly, the optimal timing of these therapies varied. Anti-CTLA4 was most effective when given prior to radiation therapy, in part due to regulatory T cell depletion. Administration of anti-OX40 agonist antibody was optimal when delivered one day following radiation during the post-radiation window of increased antigen presentation. Combination treatment of anti-CTLA4, radiation, and anti-OX40 using the ideal timing in a transplanted spontaneous mammary tumor model demonstrated tumor cures. These data demonstrate that the combination of immunotherapy and radiation results in improved therapeutic efficacy, and that the ideal timing of administration with radiation is dependent on the mechanism of action of the immunotherapy utilized.