Miracle-dz/UniFAR-FTUs huggingface dataset:
The Ethos of Science and Its Correlates: An Empirical Analysis of Scientists’ Endorsement of Mertonian Norms

Mertonian norms of science have long been subject to various criticisms, one of which concerns a ‘story book image’ of science that those norms portray for science to justify the independence of science from social control. Despite much criticism of Merton’s work on the normative structure of science, little research has been undertaken on the degree to which practicing scientists indeed hold onto such norms. This study presents an empirical analysis of Mertonian norms using the survey of 633 Korean scientists. The Korean scientific community offers a strategic research site. With predominantly US-educated researchers, it contains a sizeable membership of academic scientists who have become sensitised to ethical and normative problems due to Dr Hwang’s notorious research fraud scandal. Our empirical analysis analyses scientists’ endorsement of Mertonian norms based on a framework incorporating demographic factors and the socialisation into science. Among the four Mertonian norms, we find communalism to be strongly influenced by professional conditions such as size of research funding, professional network and involvement of non-academic affairs. This finding confirms the growing concerns with the norm of communal ownership of scientific output in the face of increasing academic commercialisation.
A time scheduling scheme in MIMO Y channels with reduced antenna configurations

This paper develops a time scheduling scheme for generalized K-user multiple-input multiple-output (MIMO) Y channels where multiple terminals communicate with each other in a bi-directional manner via the relay. The objective is to decrease the system configuration requirements in terms of antenna numbers at the relay station and user nodes. Specifically, the scheme splits the user nodes into multiple groups and spreads the transmissions over a larger number of time slots (TSs) compared with the original MIMO Y channel scheme. While the latter scheme uses only one medium access control (MAC) and one broadcast (BC) phase, the proposed time scheduling arranges bi-directional data exchanges using specialized precoding in two or more MAC and BC phases between smaller number of users. As a result, the required numbers of antennas at the relay and the user nodes are decreased at the expense of reduced effective throughput. The lower complexity antenna configurations in MIMO Y channels will make the whole system more amenable to practical implementations.
Coronal Heating Distribution Due to Low-Frequency, Wave-driven Turbulence

The heating of the lower solar corona is examined using numerical simulations and theoretical models of magnetohydrodynamic turbulence in open magnetic regions. A turbulent energy cascade to small length scales perpendicular to the mean magnetic field can be sustained by driving with low-frequency Alfvén waves reflected from mean density and magnetic field gradients. This mechanism deposits energy efficiently in the lower corona, and we show that the spatial distribution of the heating is determined by the mean density through the Alfvén speed profile. This provides a robust heating mechanism which can explain observed high coronal temperatures and accounts for the significant heating (per unit volume) distribution below 2 solar radii needed in models of the origin of the solar wind. The obtained heating per unit mass, on the other hand, is much more extended, indicating that the heating on a per-particle basis persists throughout all the lower coronal region considered here.
An overview of the regulation of influenza vaccines in the United States

Influenza virus vaccines are unique among currently licensed viral vaccines. The vaccines designed to protect against seasonal influenza illness must be updated periodically in an effort to match the vaccine strain with currently circulating viruses, and the vaccine manufacturing timeline includes multiple, overlapping processes with a very limited amount of flexibility. In the United States (U.S.), over 150 million doses of seasonal trivalent and quadrivalent vaccine are produced annually, a mammoth effort, particularly in the context of a vaccine with components that usually change on a yearly basis. In addition, emergence of an influenza virus containing an HA subtype that has not recently circulated in humans is an ever present possibility. Recently, pandemic influenza vaccines have been licensed, and the pathways for licensure of pandemic vaccines and subsequent strain updating have been defined. Thus, there are formidable challenges for the regulation of currently licensed influenza vaccines, as well as for the regulation of influenza vaccines under development. This review describes the process of licensing influenza vaccines in the U.S., the process and steps involved in the annual updating of seasonal influenza vaccines, and some recent experiences and regulatory challenges faced in development and evaluation of novel influenza vaccines.
Conservation Genetics of Crested Newt Species Triturus cristatus and T. carnifex within a Contact Zone in Central Europe: Impact of Interspecific Introgression and Gene Flow

We have studied the population genetic structure of slightly admixed populations of crested newts (Triturus cristatus and T. carnifex) in a continuously fragmented landscape, located in northern Salzburg (Austria) and neighbouring Bavaria (Germany). Crested newts are listed as Critically Endangered in the provincial Red List of Salzburg and strictly protected by the EU Habitats Directive. We used seven polymorphic microsatellite loci to evaluate genetic diversity and processes that may determine the genetic architecture of populations. Genetic diversity was moderate, pairwise FST-values were comparatively high showing significant genetic differentiation and limited gene flow. Isolation by distance was significant for the whole data set, but not significant when calculated for T. cristatus- and T. carnifex-like populations separately. Bayesian analyses of population structure, using three different programs showed similar results. Spatial statistics reveal that the geographical isolation of populations is very high.
Using Realistic Simulation to Identify I/O Bottlenecks in MapReduce Setups

The exponentially growing data demands of modern enterprise and scientific applications poses critical challenges in sustaining the applications at scale. The MapReduce [1] programming model has served as the key enabler for executing resource-intensive applications over huge datasets. However, its configuration design-space has not been studied in detail. This is a complex problem as a typical MapReduce configuration can encompass hundreds of parameters, e.g., node configuration (number of disks and compute capacity), network topology (inter and intra-rack), choice of file system, data partitioning and layout, types of schedulers, etc – all of which affect application performance. While empirical insights for certain specific configurations, e.g., Google’s MapReduce infrastructure [1], do exist, they cannot be simply extended to other setups. Moreover, no tool or model is available to the community for studyingMapReduce application performance. In this work, we explore how choices about cluster design, run-time parameters, multi-tenancy and application design, affect I/O patterns, network communication and performance of MapReduce applications. Since the scale of the system precludes using actual machines for this exploration, we are developing an accurate MapReduce simulator, Dumbo, to facilitate performance analysis. The insights gained through Dumbo will be useful in comprehending the factors that affect MapReduce application performance. We expect Dumbo to be used by researchers and practitioners to understand how their MapReduce applications will behave on a particular configuration, and how they can improve the applications and platforms to optimize performance. Dumbo, used as a planning tool, will make MapReduce deployment far easier by reducing the number of parameters that currently have to be hand-tuned using trial-and-error and rules of thumb.
The Pathological Big Five: An attempt to build a bridge between the psychiatric classification of personality disorders and the trait model of normal personality

The fifth edition of the DSM diagnostic manual has presented a hybrid system of personality disorder diagnosis, which integrates categorical and dimensional approach to diagnosis, building a kind of bridge between psychiatric classifications of disorders and psychological research on the structure of normal personality. The key element of this system is a new dimensional model of pathological personality traits. This article presents the results of the empirical verification of this model in Poland. The participants in the study were 754 individuals from the nonclinical population, aged 16–86 ( M = 36.45, SD = 16.65), including 52% women. Normal personality traits were measured by means of the Revised NEO Personality Inventory (NEO-PI-R), and pathological personality traits – by means of the Personality Inventory for DSM-5 (PID-5); the risk of personality disorders was determined on the basis of SCID-II (Structured Clinical Interview for DSM-IV Axis II) questionnaire scores. The obtained results proved to be consistent with the expectations: (1) on the level of the five broad traits, the pathological DSM-5 model strongly corresponds to the Five-Factor Model of normal personality; (2) the DSM-5 model predicts the categories of disorders better than the Five-Factor Model does.
Probable cause: The deanonymizing effects of approximate DRAM

Approximate computing research seeks to trade-off the accuracy of computation for increases in performance or reductions in power consumption. The observation driving approximate computing is that many applications tolerate small amounts of error which allows for an opportunistic relaxation of guard bands (e.g., clock rate and voltage). Besides affecting performance and power, reducing guard bands exposes analog properties of traditionally digital components. For DRAM, one analog property exposed by approximation is the variability of memory cell decay times. In this paper, we show how the differing cell decay times of approximate DRAM creates an error pattern that serves as a system identifying fingerprint. To validate this observation, we build an approximate memory platform and perform experiments that show that the fingerprint due to approximation is device dependent and resilient to changes in environment and level of approximation. To identify a DRAM chip given an approximate output, we develop a distance metric that yields a two-orders-of-magnitude difference in the distance between approximate results produced by the same DRAM chip and those produced by other DRAM chips. We use these results to create a mathematical model of approximate DRAM that we leverage to explore the end-to-end deanonymizing effects of approximate memory using a commodity system running an image manipulation program. The results from our experiment show that given less than 100 approximate outputs, the fingerprint for an approximate DRAM begins to converge to a single, machine identifying fingerprint.
Wireless network recommendation system in heterogeneous networks

In this paper, we propose a novel wireless network recommendation system to deal with the user association problem with the existence of small cells. In the proposed system, by rating the base stations (BSs), user equipments (UEs) interact with each other for accurate information about the quality of service (QoS) of multimedia services. A UE desires to acquire better recommendation quality while saving computational resources and protecting its privacy. This tradeoff is formulated as a satisfaction game. We use a utility function to measure a UE's satisfaction, describe the concept of satisfaction equilibrium (SE), and put forward the algorithm to learn the SE.
Comparative Study of Data Mining Tools and Analysis with Unified Data Mining Theory

Today almost everyone has access to huge amount of data. Several wide spread organizations have their own large data repositories, data warehouses, which are still expanding with queries over data and the need for extraction of most beneficial data pattern and refined knowledge. This necessity is followed by the requirement of an apt data mining tool to help with decision making and query pre-processing. However, in this paper, a study will be presented of analysis of the selected tools to deal with the selection of the most apt tool for mining suitable for a particular data type. This research provides with the complete analysis of a tool regarding the features and functionalities offered by them. The tools are compared based on their specification and techniques and algorithms used in these tools along with the features it provides. This paper also introduces the Unification theory, one of the major issues with data mining and presents methodologies which can be used for formulation of this theory. At the end the shortcomings with these methodologies is also discussed.
Contact order, transition state placement and the refolding rates of single domain proteins.

Theoretical studies have suggested relationships between the size, stability and topology of a protein fold and the rate and mechanisms by which it is achieved. The recent characterization of the refolding of a number of simple, single domain proteins has provided a means of testing these assertions. Our investigations have revealed statistically significant correlations between the average sequence separation between contacting residues in the native state and the rate and transition state placement of folding for a non-homologous set of simple, single domain proteins. These indicate that proteins featuring primarily sequence-local contacts tend to fold more rapidly and exhibit less compact folding transition states than those characterized by more non-local interactions. No significant relationship is apparent between protein length and folding rates, but a weak correlation is observed between length and the fraction of solvent-exposed surface area buried in the transition state. Anticipated strong relationships between equilibrium folding free energy and folding kinetics, or between chemical denaturant and temperature dependence-derived measures of transition state placement, are not apparent. The observed correlations are consistent with a model of protein folding in which the size and stability of the polypeptide segments organized in the transition state are largely independent of protein length, but are related to the topological complexity of the native state. The correlation between topological complexity and folding rates may reflect chain entropy contributions to the folding barrier.
The COBE Diffuse Infrared Background Experiment Search for the Cosmic Infrared Background. IV. Cosmological Implications

A direct measurement of the extragalactic background light (EBL) can provide important constraints on the integrated cosmological history of star formation, metal and dust production, and the conversion of starlight into infrared emission by dust. In this paper we examine the cosmological implications of the recent detection of the EBL in the 125 to 5000 μm wavelength region by the Diffuse Infrared Background Experiment (DIRBE) and Far Infrared Absolute Spectrophotometer (FIRAS) on board the Cosmic Background Explorer (COBE). We first show that the 140 and 240 μm isotropic residual emission found in the DIRBE data cannot be produced by foreground emission sources in the solar system or the Galaxy. The DIRBE 140 and 240 μm isotropic residuals, and by inference the FIRAS residuals as well, are therefore extragalactic. Assuming that most of the 140 and 240 μm emission is from dust yields a 2 σ lower limit of νI(ν) ≈ 5 nW m-2 sr-1 for the EBL at 100 μm. The integrated EBL detected by the COBE between 140 and 5000 μm is ~16 nW m-2 sr-1, roughly 20%-50% of the integrated EBL intensity expected from energy release by nucleosynthesis throughout cosmic history. This also implies that at least ~5%-15% of the baryonic mass density implied by big bang nucleosynthesis has been processed through stars. The COBE observations provide important constraints on the cosmic star formation rate, and we calculate the EBL spectrum for various star formation histories. The results show that the UV and optically determined cosmic star formation rates fall short in producing the observed 140 to 5000 μm background. The COBE observations require the star formation rate at redshifts of z ≈ 1.5 to be larger than that inferred from UV-optical observations by at least a factor of 2. This excess stellar energy must be mainly generated by massive stars, since it otherwise would result in a local K-band luminosity density that is larger than observed. The energy sources could either be yet undetected dust-enshrouded galaxies, or extremely dusty star-forming regions in observed galaxies, and they may be responsible for the observed iron enrichment in the intracluster medium. The exact star formation history or scenarios required to produce the EBL at far-IR wavelengths cannot be unambiguously resolved by the COBE observations and must await future observations.
Discovery of thermal X-ray emission in the supernova remnant G337.8-0.1 (Kes 41)

Aims. We report here on the first detection at X-ray wavelengths of the Supernova Remnant (SNR) G337.8−0.1, carried out with the XMM-Newton Observatory. Methods. Using the X-ray observations, we studied the X-ray morphology of the remnant at different energy ranges, analysed the spectral properties and investigated a possible variable behavior. Results. The SNR shows a diffuse filled-center structure in the X-ray region with an absence of a compact source in its center. We find a high column density of NH > 6.9 × 10 22 cm −2 , which supports a relatively distant location (d ≥ 7 kpc). The X-ray spectrum exhibits emission lines, indicating that the X-ray emission has a thin thermal plasma origin, and is well represented by a non-equilibrium ionization (NEI) plasma model. The X-ray characteristics and well-known radio parameters show that G337.8−0.1 belongs to the emerging class of mixed-morphology (MM) SNRs.
Drought onset mechanisms revealed by satellite solar‐induced chlorophyll fluorescence: Insights from two contrasting extreme events

This study uses the droughts of 2011 in Texas and 2012 over the central Great Plains as case studies to explore the potential of satellite‐observed solar‐induced chlorophyll fluorescence (SIF) for monitoring drought dynamics. We find that the spatial patterns of negative SIF anomalies from the Global Ozone Monitoring Experiment 2 (GOME‐2) closely resembled drought intensity maps from the U.S. Drought Monitor for both events. The drought‐induced suppression of SIF occurred throughout 2011 but was exacerbated in summer in the Texas drought. This event was characterized by a persistent depletion of root zone soil moisture caused by yearlong below‐normal precipitation. In contrast, for the central Great Plains drought, warmer temperatures and relatively normal precipitation boosted SIF in the spring of 2012; however, a sudden drop in precipitation coupled with unusually high temperatures rapidly depleted soil moisture through evapotranspiration, leading to a rapid onset of drought in early summer. Accordingly, SIF reversed from above to below normal. For both regions, the GOME‐2 SIF anomalies were significantly correlated with those of root zone soil moisture, indicating that the former can potentially be used as proxy of the latter for monitoring agricultural droughts with different onset mechanisms. Further analyses indicate that the contrasting dynamics of SIF during these two extreme events were caused by changes in both fraction of absorbed photosynthetically active radiation fPAR and fluorescence yield, suggesting that satellite SIF is sensitive to both structural and physiological/biochemical variations of vegetation. We conclude that the emerging satellite SIF has excellent potential for dynamic drought monitoring.
SDN-NFV-cloud introduction in the context of service chaining

This paper firstly introduces the concepts of Software Defined Networking (SDN), Network Function Virtualization (NFV), and Cloud Computing Technologies with their interdependencies and then focuses on the SDN based technology named “Service Chaining. ” Service Chaining applications provide a means to dimension and utilize services such as Firewall, Deep Packet Inspection (DPI) and Intrusion Detection System (IDS) in the most efficient manner, attempting to only carry the flows that only require a particular service to that particular service box. Efficient service chaining requires some topics to be investigated such as relation between Network/Cloud Management System and service chaining application, task distribution among NFV and SDN Controller and the case when a particular service can be provided over the cloud in a Network as a Service model (NaaS). Second half of the paper is dedicated to describing these problems which are open research areas.
Hybrid Approach of Facial Expression Recognition

In recent year facial expression recognition system has gained much popularity in the field of security because facial expression recognition system integrates with the face recognition system make entrenched and improve its strength. Automatic recognition of facial expression achieves greater attraction of researcher and human facial expressions have the ability to communicate emotion and play a major role in the study of psychological phenomena and the progress of nonverbal communication. This paper present facial expression detection method by first skin color segmentation for detecting face and then extract facial feature like eyes and lips after finding the interest point on these facial landmark. Then drawing Bezier curve of these facial points and on the basis of changes in muscles around the eyes, nose and mouths we recognize the three basic facial expressions and achieved expected results. Keywords— Facial expression recognition, Bezier curve, Haar like feature, corner points, muscles movement.
The Monadic Theory of Morphic Infinite Words and Generalizations

We present new examples of infinite words which have a decidable monadic theory. Formally, we consider structures (N, <, P) which expand the ordering (N, <) of the natural numbers by a unary predicate P; the corresponding infinite word is the characteristic 0-1-sequence xP of P. We show that for a morphic predicate P the associated monadic second-order theory MTh(N, <, P) is decidable, thus extending results of Elgot and Rabin (1966) and Maes (1999). The solution is obtained in the framework of semigroup theory, which is then connected to the known automata theoretic approach of Elgot and Rabin. Finally, a large class of predicates P is exhibited such that the monadic theory MTh(N, <, P) is decidable, which unifies and extends the previously known examples.
A primer on cytokines: sources, receptors, effects, and inducers

Protection against pathogens is a prerequisite for survival of most organisms. To cope with this continuous challenge, complex defense mechanisms have evolved. The construction, adaptation, and maintenance of these mechanisms are under control of an extensive network of regulatory proteins called cytokines. A great number of cytokines have been described over the last 2 decades. This review consists of an overview of cytokines that are involved in immune responses and describes some historical and general aspects as well as prospective clinical applications. Major biological effects together with information on cytokine receptors, producers, inducers, and biochemical and molecular characteristics are listed in tables. In addition, some basic information is given on cytokine receptor signal transduction. Finally, the recent discoveries of cytokine receptors functioning as coreceptors in the pathogenesis of human immunodeficiency virus are summarized.