nils-herrmann/clean_scirepeval huggingface dataset:
Earth evolution and dynamics a tribute to Kevin Burke

Kevin Burke's original and thought provoking contributions have been published steadily for the past 60 years, and more than a decade ago he set out to resolve how plate tectonics and mantle plumes interact by proposing a simple conceptual model, which we will refer to as the Burkian Earth. On the Burkian Earth, mantle plumes take us from the deepest mantle to sub lithospheric depths, where partial melting occurs, and to the surface, where hotspot lavas erupt today, and where large igneous provinces and kimberlites have erupted episodically in the past. The arrival of a plume head contributes to continental break up and punctuates plate tectonics by creating and modifying plate boundaries. Conversely, plate tectonics makes an essential contribution to the mantle through subduction. Slabs restore mass to the lowermost mantle and are the triggering mechanism for plumes that rise from the margins of the two large scale low shear wave velocity structures in the lowermost mantle, which Burke christened TUZO an.
Nastiness, morality and religiosity in 33 nations

This study aimed to identify the main dimensions of social attitudes across 33 countries. Altogether, 20 social attitude scales were administered, mostly to university students (N 6938) A series of factor analyses showed that three factors exist at the pancultural level: Morality, Nastiness and Religiosity. Furthermore, Morality and Nastiness did not correlate with each other, but Religiosity correlated with both Morality and Nastiness. This suggests that one can be religious and both moral or nasty. Only one factor Conservatism emerged at the ecological level (i.e. between countries analysis) The largest cross cultural differences were found on the dimension of Religiosity, followed by Nastiness and then by Morality. The clear distinction emerged between South East Asia, South Asia and Sub Saharan Africa on one hand, scoring high on all three factors, and Western Europe, Eastern Europe and Anglo regions on the other, scoring low on all three factors.
Toward a Psychological Atlas of the World With Mixture Modeling

This article presents findings based on the outcomes of research conducted with 8,883 participants from 33 countries. It employs mixture modeling (latent profile analysis) to classify countries into latent classes. The country level analyses are based on three social attitudes factor scores of Nastiness, Religiosity, and Morality. The results indicate that the main sources of cross cultural differences are with respect to a broadly defined Conservatism/Liberalism. Three groups of societies that is, "psychological continents" appear to exist in the world today. They are as follows: (a) liberal European countries plus Canada and Australia; (b) conservative countries from South and South East Asia, Sub Saharan Africa, and Latin America; and (c) all other countries, including the United States, Russia, and China, that are in between liberal and conservative groups. In addition, gross domestic product (GDP) per capita, cognitive test performance, and governance indicators were found to be low in the most conservative group and high in the most liberal group.
Comment on Lee and Conley (2016) "Does the Gender of Offspring Affect Parental Political Orientation?" Lee and Conley's Null Findings Are Likely due to Measurement Error in their Measure of Sex of First Child

Lee and Conley (2016) find null effects of sex of the first born child on political orientation in thirty six countries. Null effects in statistical analyses may occur because there is no relationship between the variables in the population, in this case, between sex of the first born child and political orientation. Null effects may also occur because of measurement error or noise in one or more of the variables. Unfortunately, Lee and Conley's null findings are likely due to the latter rather than the former, specifically measurement error in their measure of the sex of the first born child. When using data from the General Social Survey (henceforth GSS) Lee and Conley (2016) measure the sex of the respondent's first child by using the household register of individuals who usually live in the household. Since the wording of these questions is important, I give the actual GSS question wording verbatim here, although I have taken the liberty of bolding certain terms:
Susan Lee Lindquist (1949 2016) pioneer in the study of cellular protein folding and disease.
Venue: The EMBO journal

Susan Lee Lindquist. With permission from Ceal Capistrano/Whitehead Institute.  The scientific community is deeply saddened by the passing of Susan Lee Lindquist, Professor of Biology at MIT and a Howard Hughes Medical Institute Investigator, on October 27 after a year long battle with cancer. Her nearly 40 year career was distinguished by groundbreaking research in cell biology and genetics, and by an extraordinary passion for nurturing and mentoring the next generation of biologists. An inspiring and courageous innovator, Susan Lindquist has tackled and resolved a remarkable variety of difficult problems, ranging from delineating cellular responses to stress, prion based inheritance, and the role of protein misfolding in disease to uncovering genetic variation in evolution. Her interdisciplinary vision has empowered her to devise entirely new experimental approaches and create novel conceptual frameworks in several fields. Susan Lindquist's work began with pioneering studies of the heat shock response, a homeostatic mechanism to protect cells from protein folding problems during heat exposure and a variety of other stresses. As a graduate student of Matthew Meselson at Harvard in the 1970s, she launched, on her own initiative, an investigation of the heat shock response, using it as a model to understand eukaryotic gene regulation. She discovered that the heat shock response, previously only known from Drosophila salivary glands, also occurred in tissue culture cells, demonstrating its generality and making it tractable to molecular analysis. She then revealed that the response was governed by a combination of translational and transcriptional mechanisms. Thanks in large part to her  /embed/graphic 1.gif
Template free modeling by LEE and LEER in CASP11
Venue: Proteins

For the template free modeling of human targets of CASP11, we utilized two of our modeling protocols, LEE and LEER. The LEE protocol took CASP11 released server models as the input and used some of them as templates for 3D (three dimensional) modeling. The template selection procedure was based on the clustering of the server models aided by a community detection method of a server model network. Restraining energy terms generated from the selected templates together with physical and statistical energy terms were used to build 3D models. Side chains of the 3D models were rebuilt using target specific consensus side chain library along with the SCWRL4 rotamer library, which completed the LEE protocol. The first success factor of the LEE protocol was due to efficient server model screening. The average backbone accuracy of selected server models was similar to that of top 30% server models. The second factor was that a proper energy function along with our optimization method guided us, so that we successfully generated better quality models than the input template models. In 10 out of 24 cases, better backbone structures than the best of input template structures were generated. LEE models were further refined by performing restrained molecular dynamics simulations to generate LEER models. CASP11 results indicate that LEE models were better than the average template models in terms of both backbone structures and side chain orientations. LEER models were of improved physical realism and stereo chemistry compared to LEE models, and they were comparable to LEE models in the backbone accuracy. Proteins 2016; 84(Suppl 1):118 130.
Susan Lee Lindquist (1949 2016)
Venue: Nature

Lindquist was a visionary and pioneer who transformed our understanding of how protein folding sculpts biology, evolution, and disease. She revealed several unanticipatedmechanismsbywhich protein folding can buffer, release, and potentiate genetic variation in response to environmental stress, thereby enabling the rapid evolution of beneficial new traits. Her discoveries provide a rich framework for innovative therapeutic interventions in several fatal diseases, including Alzheimer's disease, Parkinson's disease, and cancer.
A Survey of Mobile Device Virtualization
Venue: ACM Comput. Surv.

Recent growth in the processing and memory resources of mobile devices has fueled research within the field of mobile virtualization. Mobile virtualization enables multiple persona on a single mobile device by hosting heterogeneous operating systems (OSs) concurrently. However, adding a virtualization layer to resource constrained mobile devices with real time requirements can lead to intolerable performance overheads. Hardware virtualization extensions that support efficient virtualization have been incorporated in recent mobile processors. Prior to hardware virtualization extensions, virtualization techniques that are enabled by performance prohibitive and resource consuming software were adopted for mobile devices. Moreover, mobile virtualization solutions lack standard procedures for device component sharing and interfacing between multiple OSSs. The objective of this article is to survey software and hardware based mobile virtualization techniques in light of the recent advancements fueled by the hardware support for mobile virtualization. Challenges and issues faced in virtualization of CPU, memory, I/O, interrupt, and network interfaces are highlighted. Moreover, various performance parameters are presented in a detailed comparative analysis to quantify the efficiency of mobile virtualization techniques and solutions.
Ozonization to Upgrade Waste Derived Soluble Lignin Like Substances to Higher Value Products

Soluble biobased lignin like polymeric substances (SBO) isolated from the alkaline hydrolysates of composted biowastes are promising chemical auxiliaries for multiple uses. They have good surfactant properties. Their black color spoils their performance in detergency and dyeing. Ozonization of SBO is reported now to yield bleached biosurfactants with improved performance. The work was performed, with SBO obtained from composted gardening residues, alone or mixed with kitchen wastes. They were dissolved in water at 3.3 concentration. Oxygen containing 4 mol/mol ozone was flown at 60 L h 1 for 48 h through the SBO solution. The crude ozonized products in ca. 80 yield were filtered through different molecular cut off membranes and characterized for chemical features, molecular weight, and surface tension in water. The ozonized fractions with 200 500 kDa molecular weights accounted for 12 29 of the total ozonized fractions's organic matter. They lowered water surface tension to 48 52 mN m 1. The lower molecular weight ozonized fractions had no surfactant activity, but their molecular features suggest other potentially valuable uses.
Removal of Erythrosine B dye from water effluents using crop waste pumpkin seed hulls as adsorbent

AbstractErythrosine B is widely used for coloring in various applications, especially in the food industry, despite its already proved toxicity and carcinogenicity. The agrowaste pumpkin seed hulls were applied as potential adsorbent for the removal of Erythrosine from aqueous solutions. Adsorption mechanism and kinetics were analyzed for design purposes. The seed hulls were characterized by specific techniques before and after dye retention. It was found that the attachment of Erythrosine B molecules on adsorbent surface may be attributed to the interactions between carboxyl and/or carbonyl groups of both dye and agrowaste wall components. A univariate approach followed by a factorial design was applied to study and analyze the experimental results as well as to estimate the combined effects of the process factors on the removal efficiency and dye uptake. Adsorption mechanism may be predominantly due to intraparticle diffusion, dependent on pore size. The four equilibrium models applied fitted the data w.
Neutrality as Identity? Finland's Quest for Security in the Cold War
Venue: Journal of Cold War Studies

This article examines Finland's Cold War neutrality, highlighting its political and ideational dimensions. In contrast to other scholars who have stressed the pragmatic realpolitik considerations behind Finnish policymaking, the article demonstrates that political and ideological considerations were at least as important in shaping Finnish Cold War neutrality. The ideological and political identity dimensions are connected to the strong national consensus that lay behind Finnish neutrality policy and its wide, sustained public support. Paying attention to these dimensions helps us also to understand continuities in Finnish foreign and security policy that have continued into the post Cold War period. The continuities of Cold War era neutrality formulations are illustrated by a discussion of Finnish foreign policymaking in the final phase of the Cold War and the early 1990s.
The Armed Neutrality Paradox: Sweden and Switzerland in US Cold War Armaments Policy

This article presents the first comparative study of US policy towards two European neutrals, Sweden and Switzerland, in the late 1940s and early 1950s. During this period, Sweden and Switzerland were integrated into the Western security regime through a series of diplomatic, economic and technological steps until certain parts of the Swedish and Swiss armed forces were hard to separate from their NATO counterparts. This pioneering multi archival study shows not only that US policy towards the neutrals was coordinated in order to make them conform to US security demands (a fact previously unnoticed by historians) but it also points towards another surprising and previously unknown conclusion which the article calls 'the armed neutrality paradox' The article argues that the transfers of military technology to Sweden and Switzerland, which were needed to make their neutrality credible, effectively undermined the very credibility that they were supposed to ensure. This technology became a conduit of foreign influence reaching straight into the nerve centre of the armed neutrals, and the more ubiquitous and advanced the technology got, the less control over its use the governments seemed to have. US policy, together with the efforts of the neutral governments to increase security, spawned this paradox.
A scalable GPU enabled framework for training deep neural networks
Venue: 2016 2nd International Conference on Green High Performance Computing (ICGHPC)

In the last fifteen years, Big Data created a new generation of data analysis problems, which does not only involve the problems themselves but also the way these data are handled. Since managing terabytes of data without a proper infrastructure is unfeasible, a smart way to process these data is also necessary. A solution to this aspect deals with the creation of general algorithms that learn from observations. In this context, Deep Learning promises general, powerful, and fast machine learning algorithms, moving them one step closer to artificial intelligence. Nevertheless, fitting a deep learning model may require an huge amount of time, thus, the need of scalable infrastructures for processing large scale data sets has become ever more meaningful. In this paper, we present a framework for training these deep neural networks using heterogeneous computing resources of either grid or cloud infrastructures. The framework lets the end users define the deep architecture they need for processing their own Big Data, while dealing with the execution of the learning algorithms on a distributed set of nodes (through Apache Flink) as well as with offloading the computation on multiple Graphics Processing Units.
DeepSpark: A Spark Based Distributed Deep Learning Framework for Commodity Clusters

The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large scale data processing pipelines for handling massive data and parameters involved in DNN training. Distributed computing platforms and GPGPU based acceleration provide a mainstream solution to this computational challenge. In this paper, we propose DeepSpark, a distributed and parallel deep learning framework that exploits Apache Spark on commodity clusters. To support parallel operations, DeepSpark automatically distributes workloads and parameters to Caffe/Tensorflow running nodes using Spark, and iteratively aggregates training results by a novel lock free asynchronous variant of the popular elastic averaging stochastic gradient descent based update scheme, effectively complementing the synchronized processing capabilities of Spark. DeepSpark is an on going project, and the current release is available at this http URL
Efficient implementation of power analysis attack resistant advanced encryption standard algorithm on side channel attack standard evaluation board

This paper presents a practical smart card implementation of advanced encryption standard AES 128 algorithm combined with a simple yet effective masking scheme to protect it against first order power analysis attacks in both time and frequency domain. The proposed masking method which is a generalisation of the conventional masking method, stores randomly masked S box data in a masked table in a more efficient way than conventional masking scheme such that each addressed data in the table uses a different random value which makes the actual processed values uncorrelated to power consumption of the device. The proposed implementation has advantage of easy software implementation, low memory and clock cycle requirement. The target device for evaluating the efficiency of the implementation and countermeasure is the smart card of side channel attack standard evaluation board SASEBO W.
Accessibility barriers to online education for young adults with intellectual disabilities
Venue: W4A

In postsecondary education, technology and online resources have become a pervasive component of learning, but they are not always accessible. For students with intellectual disabilities, completing technology dependent tasks may pose unique challenges that are not always addressed by the disability support services offered at the university level. During our fieldwork, we have observed several barriers to online education tools in a postsecondary environment for students with intellectual disabilities. For example, a student with an intellectual disability submitting an assignment via email to an instructor may encounter difficulties recalling and navigating to the location of their attachment file. In this paper, we describe core skills and common interfaces that we have identified as problematic for this population through an emic ethnography. We offer emic (perceptions from within a given environment) experience accounts to highlight the obstacles we have observed in a) information retrieval, b) navigation and information architecture c) file management, and d) password management. As researchers and educators involved in a postsecondary program for young adults with intellectual disability (ID) we have spent considerable time working with this population. For each scenario, we offer examples from our own experience of the techniques and technologies that did or did not help students accomplish these tasks. Based on these experiences, we provide recommendations for mitigating these barriers including education and training for students and developers and the use of existing interventions and tools. We also discuss future directions for this work. We believe that heightened awareness and communication between educators, designers, and students with disabilities will help address these problems and generate solutions which provide more accessible education experiences for learners with diverse needs.
A new class of image filters without normalization
Venue: 2016 IEEE International Conference on Image Processing (ICIP)

When applying a filter to an image, it often makes practical sense to maintain the local brightness level from input to output image. This is achieved by normalizing the filter coefficients so that they sum to one. This concept is generally taken for granted, but is particularly important where nonlinear filters such as the bilateral or and non local means are concerned, where the effect on local brightness and contrast can be complex. Here we present a method for achieving the same level of control over the local filter behavior without the need for this normalization. Namely, we show how to closely approximate any normalized filter without in fact needing this normalization step. This yields a new class of filters. We derive a closed form expression for the approximating filter and analyze its behavior, showing it to be easily controlled for quality and nearness to the exact filter, with a single parameter. Our experiments demonstrate that the un normalized affinity weights can be effectively used in applications such as image smoothing, sharpening and detail enhancement.
Towards Green Cloud Computing: Impact of carbon footprint on environment
Venue: 2016 6th International Conference Cloud System and Big Data Engineering (Confluence)

Latest research states that by the end of 2020 carbon emission footprints will increase by 20% This emission is mainly taking place due to Data Centers used to achieve the cloud computing architecture. Data centers and new technology adoptions are mainly causing this carbon emission. These Data Centers uses cloud energy to serve the user generated request and this energy consumption is the basic cause of carbon emission. This paper is basically an attempt to look for the possible solutions which we can adopt to reduce the carbon footprints and produce a green cloud computing which will help the humanity in saving our environment.