nils-herrmann/clean_scirepeval huggingface dataset:
Cloning, expression, purification, crystallization and initial crystallographic analysis of FleN from Pseudomonas aeruginosa.
Venue: Acta crystallographica. Section F, Structural biology communications

The assembly of bacterial flagella requires the coordinated expression of a large number of genes in a hierarchical manner. These genes code for structural components of flagella, regulatory components and components that are required for chemotaxis. Stringent spatial and numerical control of flagella biosynthesis is essential for promoting motility and pathogenesis in bacteria. These genes are regulated at the level of transcription. FleN, a P loop containing ATPase, plays an important role in maintaining flagellar number in Pseudomonas aeruginosa. FleN exhibits anti activator activity against FleQ, the global transcriptional regulator of flagellar genes. In order to gain insights into the regulatory mechanism of flagella synthesis, full length FleN was crystallized in complex with the nonhydrolyzable ATP analogue b,g imidoadenosine 5' triphosphate (AMPPNP) in space group C2221, with unit cell parameters a 49.1, b 206.9, c 103.3 A. The Matthews coefficient is 2.19 A(3) Da( 1) assuming the presence of two molecules in the asymmetric unit, and the corresponding solvent content is 43.7% X ray diffraction data were collected to a minimum Bragg spacing of 2.21 A and crystals of FleN AMPPNP were prepared with selenomethionine labelled FleN for ab initio phasing.
The Impact of Deferred Tax Assets, Discretionary Accrual, Leverage, Company Size and Tax Planning Onearnings Management Practices

The purpose of this study is to analyze and provide empirical evidence of the influence of deferred tax asset, discretionary accrual, leverage, company size, and tax planning on earnings management. Financial performance is an indicator that is required by company management to measure the effectiveness of company performance. This research used secondary data that was got from annual report published in www.idx.co.id and data from Indonesian Capital Market Directory (ICMD) Populations of the research are manufacturing companies listed on Indonesia Stock Exchange from 2011 2013. Samples were selected by using purposive sampling method. There are 208 observations that will examined by logistic regression analysis. The result shows that deferred tax asset has negative and not significant effect to the earnings management, discretionary accrual has negative and not significant effect to the earnings management, leverage has negative and significant effect to the earnings management, company size has positive and significant effect to the earnings management, tax planning has positive and not significant effect to the earnings management. Tujuan penelitian ini menganalisis bukti empiris mengenai pengaruh asset pajak tangguhan, discretionary accrual, leverage, ukuran perusahaan, dan perencanaan pajak terhadap manajemen laba. Kinerja keuangan adalah indikator untuk mengukur efektivitas perusahaan. Penelitian ini menggunakan data sekunder yang diperoleh dari www.idx.co.id serta data dari Indonesian Capital Market Directory (ICMD) Populasi penelitian ini adalah perusahaan manufaktur yang terdaftar di BEI tahun 2011 2013. Sampel dipilih dengan purposive sampling. Terdapat 208 observasi yang akan diuji dengan model analisis regresi logistik. Hasil penelitian ini menunjukkan bahwa asset pajak tangguhan memiliki pengaruh negatif dan tidak signifikan terhadap praktik manajemen laba, discretionary accrual memiliki pengaruh negatif dan tidak signifikan terhadap praktik manajemen laba, leverage memiliki pengaruh negatif dan signifikan terhadap praktik manajemen laba, ukuran perusahaan memiliki pengaruh positif dan signifikan terhadap praktik manajemen laba, perencanaan pajak memiliki pengaruh positif dan tidak signifikan terhadap praktik manajemen laba.
Making Smart Contracts Smarter
Venue: IACR Cryptol. ePrint Arch.

Cryptocurrencies record transactions in a decentralized data structure called a blockchain. Two of the most popular cryptocurrencies, Bitcoin and Ethereum, support the feature to encode rules or scripts for processing transactions. This feature has evolved to give practical shape to the ideas of smart contracts, or full fledged programs that are run on blockchains. Recently, Ethereum's smart contract system has seen steady adoption, supporting tens of thousands of contracts, holding millions dollars worth of virtual coins. In this paper, we investigate the security of running smart contracts based on Ethereum in an open distributed network like those of cryptocurrencies. We introduce several new security problems in which an adversary can manipulate smart contract execution to gain profit. These bugs suggest subtle gaps in the understanding of the distributed semantics of the underlying platform. As a refinement, we propose ways to enhance the operational semantics of Ethereum to make contracts less vulnerable. For developers writing contracts for the existing Ethereum system, we build a symbolic execution tool called Oyente to find potential security bugs. Among 19, 336 existing Ethereum contracts, Oyente flags 8, 833 of them as vulnerable, including the TheDAO bug which led to a 60 million US dollar loss in June 2016. We also discuss the severity of other attacks for several case studies which have source code available and confirm the attacks (which target only our accounts) in the main Ethereum network.
Sensitive electromechanical sensors using viscoelastic graphene polymer nanocomposites
Venue: Science

Super sensitive, not so silly, putty Many composites blend stiff materials, such as glass or carbon fibers, into a softer elastic polymer matrix to generate a material with better overall mechanical toughness. Boland et al. added graphene to a lightly cross linked silicone polymer (also known as Silly Putty) The resulting composite has unusual mechanical properties, allowing the manufacture of strain sensors that can detect respiration and the footsteps of spiders. Science, this issue p. 1257 A composite of graphene and a viscoelastic polymer results in a material with unexpected electromechanical properties. Despite its widespread use in nanocomposites, the effect of embedding graphene in highly viscoelastic polymer matrices is not well understood. We added graphene to a lightly cross linked polysilicone, often encountered as Silly Putty, changing its electromechanical properties substantially. The resulting nanocomposites display unusual electromechanical behavior, such as postdeformation temporal relaxation of electrical resistance and nonmonotonic changes in resistivity with strain. These phenomena are associated with the mobility of the nanosheets in the low viscosity polymer matrix. By considering both the connectivity and mobility of the nanosheets, we developed a quantitative model that completely describes the electromechanical properties. These nanocomposites are sensitive electromechanical sensors with gauge factors >500 that can measure pulse, blood pressure, and even the impact associated with the footsteps of a small spider.
Automatic Detection and Classification of Diabetic Retinopathy Using Retinal Fundus Images

Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT) Contrast Limited Adaptive Histogram Equalization (CLAHE) Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90% 87.5% and 91.4% respectively.
Modeling Survival Data Extending The Cox Model

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An Exploration of Effects of Bullying Victimization From a Complete Mental Health Perspective

This study explored the effects of being bullied from a dual factor lens, specifically examining the relation between victimization and constructs that contribute to social emotional well being. Prior to carrying out the main analyses, the factor structure of self report items related to experiencing bullying and harassment from the California Healthy Kids Survey, which was administered to more than 14,000 high school students, was examined to establish that these items represent an overall factor: students' experience of victimization. This factor was then used as an independent variable in a series of planned comparisons with a dependent variable represented by constructs addressed by the Social Emotional Health Survey Secondary: belief in self, emotional competence, belief in others, and engaged living. With increased frequency of victimization, suicidality increased and belief in others decreased. For other constructs, belief in self, engaged living, and depression, there were significant differences found between individuals who had experienced frequencies of bullying as low as less than once a month and those who did not experience bullying at all but no further detrimental impacts were seen with even higher frequencies of victimization, indicating that being victimized at all is significantly worse than not being victimized for these variables. Implications and future directions for research are explored.
Loss of the co repressor GPS2 sensitizes macrophage activation upon metabolic stress induced by obesity and type 2 diabetes
Venue: Nature Medicine

Humans with obesity differ in their susceptibility to developing insulin resistance and type 2 diabetes (T2D) This variation may relate to the extent of adipose tissue (AT) inflammation that develops as their obesity progresses. The state of macrophage activation has a central role in determining the degree of AT inflammation and thus its dysfunction, and these states are driven by epigenomic alterations linked to gene expression. The underlying mechanisms that regulate these alterations, however, are poorly defined. Here we demonstrate that a co repressor complex containing G protein pathway suppressor 2 (GPS2) crucially controls the macrophage epigenome during activation by metabolic stress. The study of AT from humans with and without obesity revealed correlations between reduced GPS2 expression in macrophages, elevated systemic and AT inflammation, and diabetic status. The causality of this relationship was confirmed by using macrophage specific Gps2 knockout (KO) mice, in which inappropriate co repressor complex function caused enhancer activation, pro inflammatory gene expression and hypersensitivity toward metabolic stress signals. By contrast, transplantation of GPS2 overexpressing bone marrow into two mouse models of obesity (ob/ob and diet induced obesity) reduced inflammation and improved insulin sensitivity. Thus, our data reveal a potentially reversible disease mechanism that links co repressor dependent epigenomic alterations in macrophages to AT inflammation and the development of T2D.
The effect of financing sources on real estate development in Kenya

The purpose of this study was to establish the sources of financing real estate in Kenya. In specific terms the study reviewed whether financing in the real estate originates from; mortgage financing, savings, venture capital and equity financing. This study employed descriptive survey design. The population of this study was all the real estate firms in Nairobi. This study used secondary data for five years. Data was analyzed using Statistical Package for Social Sciences (SPSS) and results were presented in frequency tables and charts. The data was then analyzed in terms of descriptive statistics like frequencies, means and percentages. The findings indicated that mortgage financing is the most used source of financing, with equity and venture capital being the least source of financing used. The findings also indicated that there is a significantly positive relationship between mortgage financing and real estate development. The study recommended that to increase use of equity and venture capital as a source of financing will require businesses to sell their ideas to people who have money to invest. Equity and venture capital financing can be a good source of financing but with combining them with other sources of financing. Further research should be on the effects of sources of financing in unsuitable economic conditions, political instability and a global economic crisis and internal and external factors that affect the decision on sources of financing for real estate firms in Kenya.
A methodological framework to operationalize climate risk management: managing sovereign climate related extreme event risk in Austria
Venue: Mitigation and Adaptation Strategies for Global Change

Despite considerable uncertainties regarding the exact contribution of anthropogenic climate change to disaster risk, rising losses from extreme events have highlighted the need to comprehensively address climate related risk. This requires linking climate adaptation to disaster risk management (DRM) leading to what has been broadly referred to as climate risk management (CRM) While this concept has received attention in debate, important gaps remain in terms of operationalizing it with applicable methods and tools for specific risks and decision contexts. By developing and applying a methodological approach to CRM in the decision context of sovereign risk (flooding) in Austria we test the usefulness of CRM, and based on these insights, inform applications in other decision contexts. Our methodological approach builds on multiple lines of evidence and methods. These comprise of a broad stakeholder engagement process, empirical analysis of public budgets, and risk focused economic modelling. We find that a CRM framework is able to inform instrumental as well as reflexive and participatory debate in practice. Due to the complex interaction of social ecological systems with climate risks, and taking into account the likelihood of future contingent climate related fiscal liabilities increasing substantially as a result of socioeconomic developments and climate change, we identify the need for advanced learning processes and iterative updates of CRM management plans. We suggest that strategies comprising a portfolio of policy measures to reduce and manage climate related risks are particularly effective if they tailor individual instruments to the specific requirements of different risk layers.
An intelligent system for online exam monitoring
Venue: 2016 International Conference on Information Science (ICIS)

For the past few years, e learning has become popular across countries because of its flexibility, availability and user friendliness. As far as online examinations are concerned; the major challenge faced by the research community is the proctoring techniques used. In this paper, we present a method to avoid the physical presence of a proctor throughout the exam by creating a comprehensive multi modal system. We have used hardware such as web cam to capture audio and video along with active window capture. This combination forms the inputs to an intelligent rule based inference system which has the capability to decide whether any malpractices have happened. Examinee's face is detected and is used to extract feature points thereby estimating a head pose. Misconduct is detected based on yaw angle variations, audio presence and active window capture. Our system has been tested in an e learning scenario and we were able to make exam monitoring easy. Experiment results proved that our system performed well than the existing systems.
Stride Towards Proposing Multi Modal Biometric Authentication for Online Exam
Venue: Int. J. Netw. Secur.

Biometric authentication has been getting widespread attention over the past decade with growing demands in automated secured personal identification and has been employed in diverse fields. It ensures actual presence of biometric entity of a person in contrast to a fake self manufactured synthetic or reconstructed sample is a significant problem. Also in the previous work they use face and dress color as hard and soft biometric traits. The major drawback of the existing continuous authentication system is, it is able to successfully authenticate the user continuously with high tolerance to the user posture. So, to overcome this drawback and improve the systems robustness against illumination changes and cluttered background, in this paper we use additional biometric traits which are mole, ornament details and face dimensions in addition to the dress color and face color. Also, we extend it to the online exam application. That is, continuously monitoring of a person in an online exam is proposed employing hard biometric like facial recognition and soft biometrics. Modified PCA (Principal Component Analysis) is employed here for the facial recognition part. Both the hard biometric (face) and soft biometrics is fused with the help of optimization algorithm based similarity technique. Finally the authentication is performed and evaluated using standard evaluation metrics. The technique is implemented in MATLAB and will be compared to prominent existing techniques.
Computational Methods For Fluid Dynamics

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Mr. Rossi, Mr. Hu and politics. The role of immigration in shaping natives' voting behavior

Using Italian municipality level data on national elections and IV estimation strategy, we find that immigration generates a sizable causal increase in votes for the center right coalition, which has a political platform less favorable to immigrants.  (i) the effect is heterogeneous across municipalities with different sizes; (ii) the gain in votes for the center right coalition corresponds to a loss of votes for the center and center left parties, a decrease in voter turnout, and a rise in protest votes; (iii) the relationship between immigration and electoral gains percolates to mayoral election at the municipality level; (iv) cultural diversity, competition in the labor market and for public services, and political competition are the most relevant channels at work.
Single Target Implicit Association Tests (ST IAT) Predict Voting Behavior of Decided and Undecided Voters in Swiss Referendums
Venue: PloS one

Undecided voters represent a major challenge to political pollsters. Recently, political psychologists have proposed the use of implicit association tests (IAT) to measure implicit attitudes toward political parties and candidates and predict voting behavior of undecided voters. A number of studies have shown that both implicit and explicit (i.e. self reported) attitudes contribute to the prediction of voting behavior. More importantly, recent research suggests that implicit attitudes may be more useful for predicting the vote of undecided voters in the case of specific political issues rather than elections. Due to its direct democratic political system, Switzerland represents an ideal place to investigate the predictive validity of IATs in the context of political votes. In this article, I present evidence from three studies in which both explicit and implicit measures were used ahead of the vote on four different referendums. Explicit measures predicted voting better than implicit attitudes for decided voters while implicit and explicit attitudes were equally good predictors among undecided voters. In addition, implicit attitudes predicted voting behavior descriptively, but not significantly better for undecided voters while, also from a descriptive point of view, explicit attitudes predicted voting better for decided respondents. In sum, results suggest that, as argued in previous research, the predictive value of implicit attitudes may be higher in the context of issue related votes but still not as high as initially hoped for.
Implicit measures of attitudes and political voting behavior

Implicit measures have contributed to the prediction of behavior in numerous domains including the political realm. Some theoretical arguments suggest that implicit measures are unlikely to substantially improve the prediction of political voting behavior. Other arguments are more optimistic, especially regarding the prediction of undecided voters' behavior. Here, we review the evidence regarding the extent to which implicit measures improve the prediction of political voting behavior beyond explicit self report measures. Results reveal that implicit measures are often statistically significant predictors. However, the inclusion of an implicit measure leads to modest or even no improvement of the overall accuracy of the original prediction. We conclude that implicit measures are likely to be practically relevant for predicting voting behavior only if researchers can identify new approaches. Related findings in political psychology may pave the way as they demonstrate that implicit measures can contribute unique knowledge not accounted for in other ways.
Do Information Releases Increase or Decrease Information Asymmetry? New Evidence from Analyst Forecast Announcements

Prior literature documents that both earnings announcements and management earnings forecasts increase information asymmetry at announcement. In contrast, we predict and document that analyst earnings forecasts decrease information asymmetry at announcement. As expected, this directional contrast is temporary, in that all three information release types lead to a decrease in information asymmetry following the short window announcement period. Our evidence demonstrates that the direction of the effect of a public information release on announcement period information asymmetry is determined by how the information contained in the release relates to prior information held by sophisticated and unsophisticated investors, which supports extant disclosure theory.