nils-herrmann/clean_scirepeval huggingface dataset:
Computational analysis of fluid dynamics and heat transfer characteristics of a vibrating heated plate
Year: 2014

The introduction of vibrations to a horizontal plate can induce turbulence in the flow field adjacent to the plate under certain combinations of amplitudes and frequency. It is also known that beyond a threshold level of heating, the convective flow field over a heated plate will transition to turbulence. The characterization of the flow field with turbulence in the domain is of paramount importance to ensure a realistic simulation of the flow physics. In the present study, a computational analysis is carried out to characterize the flow regime over a transversely vibrating flat plate (unheated and heated) into laminar or turbulent. The range of frequency and amplitudes of vibrations considered for this analysis are 0 150 Hz and 0 2 mm respectively. Three different models viz. laminar; Reynolds Averaged Navier Stokes (RANS) approach with k o SST model; and Large Eddy Simulations (LES) approach with dynamic Smagorinsky Lilly model are employed, and the results of local, time and space averaged wall shear stress, and the Nusselt number are compared. It has been found that under conditions with unheated or heated vibrating plate, the wall shear stress predictions by all three models are in good agreement with each other with a maximum deviation of 9.5 However, when the predictions of local Nusselt number on the heated vibrating plate are compared, it is found that the laminar and LES predictions are in good agreement with each other; the k o SST model predictions deviate significantly from the other two models.
Scaled prioritized aggregation operators and their applications to decision making
Venue: Soft Comput.
Year: 2016

As an extension of the prioritized aggregation operators by Yager ( 2008) this paper uses the priority labels to express the prioritized relationship between criteria and presents some scaled prioritized aggregation operators, including the scaled prioritized score operator and the scaled prioritized averaging operator. Moreover, we consider the priority under uncertain environment and develop the uncertain prioritized aggregation operators, including the uncertain prioritized scoring operator and the uncertain prioritized averaging operator. We investigate the properties of these operators and build the models to derive the weights by maximizing square deviations from a possible range to distinguish the candidate alternatives mostly. Furthermore, approaches to multi attribute decision making based on the proposed operators are given, which have benefits over the TOPSIS method (Behzadian, Expert Syst Appl 39:13051 13069, 2012) and the methods based on the OWA operator (Zhou and Chen, Fuzzy Sets Syst 168:18 34, 2011) when prioritized relationship between criteria is considered. Finally, examples are illustrated to show the feasibility and validity of the new approaches to the application of decision making.
Association of morning blood pressure surge with carotid intima media thickness and cardiac dysfunction in patients with cardiac syndrome X
Venue: Blood pressure
Year: 2018

We hypothesized that exaggerated morning blood pressure surge, may contribute in cardiac dysfunction and arterial stiffness in patients with cardiac syndrome X. Thus we investigated the impact of morning blood pressure surge on cardiac function and carotid intima media thickness in subjects with cardiac syndrome X.  We studied patients with cardiac syndrome X using ambulatory blood pressure monitoring and investigated the association of morning blood pressure surge with carotid intima thickness, left atrial volume index and left ventricular filling (E/e' Seventy patients with cardiac syndrome X were enrolled for the study and compared with 70 age and sex matched controls.  Patients with cardiac syndrome X were stratified based on the systolic morning blood pressure surge value of control subjects to patients with exaggerated blood pressure surge (n 42) and those with normal morning blood pressure surge (n 28) Basal heart rate (p .05) high sensitive C reactive protein (p .01) left atrial volume index (p .01) E/e' (p .01) carotid intima media thickness (p .001) and percentage of detected plaque (p .005) were significantly higher in patients with exaggerated morning blood pressure surge group than those with morning blood pressure surge group. Morning blood pressure surge was significantly correlated with carotid intima media thickness, high sensitive C reactive protein, left atrial volume index and E/e' ratio in patients with cardiac syndrome X. In multivariate analysis, exaggerated morning blood pressure surge was the only independent predictor of increased carotid intima media thickness (OR 2.379; p .001) and diastolic dysfunction (OR 2.464; p .001) in patients with cardiac syndrome X.  Our data suggest that excessive morning blood pressure surge is an independent predictor for arterial stiffness and diastolic dysfunction in patients with cardiac syndrome X.
Application of biochar for the removal of pollutants from aqueous solutions.
Venue: Chemosphere
Year: 2015

In recent years, many studies have been devoted to investigate the application of biochar for pollutants removal from aqueous solutions. Biochar exhibits a great potential to efficiently tackle water contaminants considering the wide availability of feedstock, low cost and favorable physical/chemical surface characteristics. This review provides an overview of biochar production technologies, biochar properties, and recent advances in the removal of heavy metals, organic pollutants and other inorganic pollutants using biochar. Experimental studies related to the adsorption behaviors of biochar toward various contaminants, key affecting factors and the underlying mechanisms proposed to explain the adsorption behaviors, have been comprehensively reviewed. Furthermore, research gaps and uncertainties that exist in the use of biochar as an adsorbent are identified. Further research needs for biochar and potential areas for future application of biochars are also proposed.
Mining Patterns in Source Code Using Tree Mining Algorithms
Venue: DS
Year: 2019

Discovering regularities in source code is of great interest to software engineers, both in academia and in industry, as regularities can provide useful information to help in a variety of tasks such as code comprehension, code refactoring, and fault localisation. However, traditional pattern mining algorithms often find too many patterns of little use and hence are not suitable for discovering useful regularities. In this paper we propose FREQTALS, a new algorithm for mining patterns in source code based on the FREQT tree mining algorithm. First, we introduce several constraints that effectively enable us to find more useful patterns; then, we show how to efficiently include them in FREQT. To illustrate the usefulness of the constraints we carried out a case study in collaboration with software engineers, where we identified a number of interesting patterns in a repository of Java code.
Multi Objective Graph Heuristic Search for Terrestrial Robot Design
Venue: ArXiv
Year: 2021

We present methods for co designing rigid robots over control and morphology (including discrete topology) over multiple objectives. Previous work has addressed problems in single objective robot co design or multi objective control. However, the joint multi objective co design problem is extremely important for generating capable, versatile, algorithmically designed robots. In this work, we present Multi Objective Graph Heuristic Search, which extends a single objective graph heuristic search from previous work to enable a highly efficient multi objective search in a combinatorial design topology space. Core to this approach, we introduce a new universal, multiobjective heuristic function based on graph neural networks that is able to effectively leverage learned information between different task trade offs. We demonstrate our approach on six combinations of seven terrestrial locomotion and design tasks, including one three objective example. We compare the captured Pareto fronts across different methods and demonstrate that our multi objective graph heuristic search quantitatively and qualitatively outperforms other techniques.
Tuning store operated calcium entry to modulate Ca2+ dependent physiological processes.
Venue: Biochimica et biophysica acta. Molecular cell research
Year: 2019

The intracellular calcium signaling processes are tightly regulated to ensure the generation of calcium signals with the specific spatiotemporal characteristics required for regulating various cell functions. Compartmentalization of the molecular components involved in the generation of these signals at discrete intracellular sites ensures the signaling specificity and transduction fidelity of the signal for regulating downstream effector processes. Store operated calcium entry (SOCE) is ubiquitously present in cells and is critical for essential cell functions in a variety of tissues. SOCE is mediated via plasma membrane Ca2+ channels that are activated when luminal [Ca2+ of the endoplasmic reticulum [Ca2+]ER) is decreased. The ER resident stromal interaction molecules, STIM1 and STIM2, respond to decreases in [Ca2+]ER by undergoing conformational changes that cause them to aggregate at the cell periphery in ER plasma membrane (ER PM) junctions. At these sites, STIM proteins recruit Orai1 channels and trigger their activation. Importantly, the two STIM proteins concertedly modulate Orai1 function as well as the sensitivity of SOCE to ER Ca2+ store depletion. Another family of plasma membrane Ca2+ channels, known as the Transient Receptor Potential Canonical (TRPC) channels (TRPC1 7) also contribute to sustained [Ca2+]i elevation. Although Ca2+ signals generated by these channels overlap with those of Orai1, they regulate distinct functions in the cells. Importantly, STIM1 is also required for plasma membrane localization and activation of some TRPCs. In this review, we will discuss various molecular components and factors that govern the activation, regulation and modulation of the Ca2+ signal generated by Ca2+ entry pathways in response to depletion of ER Ca2+ stores. This article is part of a Special Issue entitled: ECS Meeting edited by Claus Heizmann, Joachim Krebs and Jacques Haiech.
Advancing the Research and Development of Assured Artificial Intelligence and Machine Learning Capabilities
Venue: ArXiv
Year: 2020

Artificial intelligence (AI) and machine learning (ML) have become increasingly vital in the development of novel defense and intelligence capabilities across all domains of warfare. An adversarial AI (A2I) and adversarial ML (AML) attack seeks to deceive and manipulate AI/ML models. It is imperative that AI/ML models can defend against these attacks. A2I/AML defenses will help provide the necessary assurance of these advanced capabilities that use AI/ML models. The A2I Working Group (A2IWG) seeks to advance the research and development of assured AI/ML capabilities via new A2I/AML defenses by fostering a collaborative environment across the U.S. Department of Defense and U.S. Intelligence Community. The A2IWG aims to identify specific challenges that it can help solve or address more directly, with initial focus on three topics: AI Trusted Robustness, AI System Security, and AI/ML Architecture Vulnerabilities.
Extracorporeal Cardiopulmonary Resuscitation (E CPR) During Pediatric In Hospital Cardiopulmonary Arrest Is Associated With Improved Survival to Discharge: A Report from the American Heart Association's Get With The Guidelines Resuscitation (GWTG R) Registry
Venue: Circulation
Year: 2016

Although extracorporeal cardiopulmonary resuscitation (E CPR) can result in survival after failed conventional CPR (C CPR) no large, systematic comparison of pediatric E CPR and continued C CPR has been reported.  Consecutive patients <18 years old with CPR events =10 minutes in duration reported to the Get With the Guidelines Resuscitation registry between January 2000 and December 2011 were identified. Hospitals were grouped by teaching status and location. Primary outcome was survival to discharge. Regression modeling was performed, conditioning on hospital groups. A secondary analysis was performed with the use of propensity score matching. Of 3756 evaluable patients, 591 (16% received E CPR and 3165 (84% received C CPR only. Survival to hospital discharge and survival with favorable neurological outcome (Pediatric Cerebral Performance Category score of 1 3 or unchanged from admission) were greater for E CPR (40% [237 of 591] and 27% [133 of 496] versus C CPR patients (27% [862 of 3165] and 18% [512 of 2840] Odds ratios (ORs) for survival to hospital discharge and survival with favorable neurological outcome were greater for E CPR versus C CPR. After adjustment for covariates, patients receiving E CPR had higher odds of survival to discharge (OR, 2.80; 95% confidence interval, 2.13 3.69; P<0.001) and survival with favorable neurological outcome (OR, 2.64; 95% confidence interval, 1.91 3.64; P<0.001) than patients who received C CPR. This association persisted when analyzed by propensity score matched cohorts (OR, 1.70; 95% confidence interval, 1.33 2.18; P<0.001; and OR, 1.78; 95% confidence interval, 1.31 2.41; P<0.001, respectively]  For children with in hospital CPR of =10 minutes duration, E CPR was associated with improved survival to hospital discharge and survival with favorable neurological outcome compared with C CPR.
New Online/Offline Signature Schemes Without Random Oracles
Venue: Public Key Cryptography
Year: 2006

In this paper, we propose new signature schemes provably secure under the strong RSA assumption in the standard model. Our proposals utilize Shamir Tauman's generic construction for building EF CMA secure online/offline signature schemes from trapdoor commitments and less secure basic signature schemes. We introduce a new natural intractability assumption for hash functions, which can be interpreted as a generalization of second pre image collision resistance. Assuming the validity of this assumption, we are able to construct new signature schemes provably secure under the strong RSA assumption without random oracles. In contrast to Cramer Shoup's signature scheme based on strong RSA in the standard model, no costly generation of prime numbers is required for the signer in our proposed schemes. Moreover, the security of our schemes relies on weaker assumptions placed on the hash function than Gennaro, Halevi and Rabin's solution.
The Tears of Re: Beekeeping in Ancient Egypt
Year: 2016

The Tears of Re: Beekeeping in Ancient Egypt Gene Kritsky 2015; 160 pages, 103 plates Oxford University Press, New York, NY ISBN: 978 0 199 36138 0 $29.95 (hardcover) [Graphic][1] According to a papyrus written around 300 BCE, the Egyptian sun god Re "wept and the tears from his eyes fell on the ground and turned into a bee" This origin story sets the scene for The Tears of Re in which author Gene Kritsky explores archaeological evidence of early beekeeping and its place in Egyptian culture. Kritsky, who received a Fulbright Scholar grant to teach entomology at Minya University in Upper Egypt in the early 1980s, has been smitten with both bees and Egyptian history for years. In his newest book, he emphasizes the difference between honey hunting and the birth of beekeeping. Humans have harvested honey for at least 8,000 years, robbing combs from wild colonies, but the Egyptian civilization was the first to practice large scale, organized beekeeping. The first known archaeological evidence of human made beehives comes from Egypt's Old Kingdom, when pharaoh Newoserre Any built his spectacular solar temple in the 25th century BCE. On five limestone blocks, together measuring only two feet by six  /embed/inline graphic 1.gif
Potential roles of volatile organic compounds in plant competition
Venue: Perspectives in Plant Ecology, Evolution and Systematics
Year: 2019

Volatile organic compounds (VOCs) are a major currency in plant communication where they mediate above and below ground interactions between plants and the surrounding organisms (i.e. other plants, microorganisms, pollinators, seed dispersers, herbivores, and their natural enemies) Considering the multiple interactions mediated by VOCs and their impact on a plant's reproductive success and survival, they can be a crucial weapon in plant plant competition. However, this particular role of VOCs is underrepresented in the literature. Mechanisms by which volatiles can mediate plant competition can be direct or indirect. Direct mechanisms include establishing a neighbour's identity and status to select adequate responses and affecting competitor's seed germination or growth through VOC mediated allelopathy. Indirect mechanisms can affect the plant's competitive ability by modifying interactions with other trophic levels, for instance, through associational resistance or chemical camouflage. These mechanisms are not mutually exclusive and can be seen as part of a continuum. In this review, we present evidence from the literature to illustrate these roles and indicate how they could influence competition in plant communities. We propose new research avenues to test if and how these mechanisms affect competitive outcomes and suggest that, in addition to morphological traits, future competition studies should also incorporate data on plant volatile emissions and measure their effects on the surrounding plants and other trophic levels. This information would allow us to understand competition from a broader perspective by acknowledging the existence of multiple (possibly coexisting) competition strategies and the role of other trophic levels in shaping competitive outcomes.
Diagnosis of the mechanisms of different types of discordances between phylogenies inferred from nuclear and mitochondrial markers
Venue: Vavilovskii zhurnal genetiki i selektsii
Year: 2020

In ancient freshwater lakes, an abnormally large species diversity is observed. The mechanisms that generated extremely high biodiversity in the ancient lakes have not been sufficiently studied and remain only partially known. Sequences of environmental changes in highly complex ecosystems such as Lake Baikal, may induce sophisticated combinations of microevolutionary processes. These processes are likely to result in unusual "patterns" of genetic variability of species. The most unusual patterns include the ones when speciation is followed by incomplete lineage sorting as well as mitochondrial or nuclear introgression. All these phenomena are diagnosed by comparing the topologies of phylogenetic trees inferred from molecular markers of evolution located in mitochondria and nuclei. Mitochondrial and nuclear introgression is a particularly interesting and complex case, which is the process of incorporating the gene alleles of one species into the gene pool of a sister species due to interspecific hybridization (introgressive hybridization) In many cases, existing methods for molecular phylogenetic analysis do not automatically allow the observed patterns of polymorphism to be explained and, therefore, cannot provide hypotheses that would explain the mechanisms which resulted to these patterns. Here we use adaptive dynamics models to study neutral molecular evolution under various scenarios of interaction between sister species and the environment. We propose and justify a set of criteria for detecting how two evolutionary trees may differ, with a special focus on comparing a tree inferred from nuclear DNA to one from mitochondrial DNA. The criteria react to branching pattern and branch lengths, including relative distances from ancestral lineages. Simulations show that the criteria allow fast and automated detection of various types of introgression, secondary breaches of reproductive barriers, and incomplete lineage sorting.
Algo Trading Strategy for Intraweek Foreign Exchange Speculation Based on Random Forest and Probit Regression
Venue: Appl. Comput. Intell. Soft Comput.
Year: 2019

In the Forex market, the price of the currencies increases and decreases rapidly based on many economic and political factors such as commercial balance, the growth index, the inflation rate, and the employment indicators. Having a good strategy to buy and sell can make a profit from the above changes. A successful strategy in Forex should take into consideration the relation between benefits and risks. In this work, we propose an intraweek foreign exchange speculation strategy for currency markets based on a combination of technical indicators. This system has a two level decision and is composed of the Probit regression model and rules discovery using Random Forest. There are two minimum requirements for a trading strategy: a rule to enter the market and a rule to exit it. Our proposed system, to enter the currency market, should validate two conditions. First, it should validate Random Forest access rules over the following week while in the second one the predicted value of the next day using Probit should be positive. To exit the currency market just one negative warning from Probit or Random Forest is enough. This system was used to develop dynamic portfolio trading systems. The profitability of the model was examined for USD/(EUR, JYN, BRP) variation within the period from January 2014 to January 2016. The proposed system allows improving the prediction accuracy. This indicates a good prediction of the behavior market and it helps to identify the good times to enter it or to leave it.
An Adaptive Weighted Multiscale Convolutional Neural Network for Rotating Machinery Fault Diagnosis Under Variable Operating Conditions
Venue: IEEE Access
Year: 2019

Extracting robust fault sensitive features of vibration signals remains a challenge for rotating machinery fault diagnosis under variable operating conditions. Most existing fault diagnosis methods based on the convolutional neural network (CNN) can only extract single scale features, which not only loss fault sensitive information on other scales, but also suffer from the domain shift problem. In this work, a novel end to end deep learning network named adaptive weighted multiscale convolutional neural network (AWMSCNN) is proposed to adaptively extract robust and discriminative multiscale fusion features from raw vibration signals. The AWMSCNN consists of three main components: the denoising layer, the adaptive weighted multiscale convolutional (AWMSC) block, and the multiscale feature fusion layer. The AWMSC block can learn rich and complementary features on multiple scales in parallel. Then, an adaptive weight vector is introduced to modulate multiscale features to emphasize fault sensitive features and suppress features that are sensitive to operating conditions. The train wheelset bearing dataset and the bearing dataset provided by Case Western Reserve University (CWRU) are used to verify the superiority of the proposed model over the basic CNN and other multiscale CNN models. The experiment results show that the proposed model has strong fault discriminative ability and domain adaptive ability against variable operating conditions.
The Italian Left Periphery: A View from Locality
Venue: Linguistic Inquiry
Year: 2012

In this article, I discuss the interaction of locality phenomena with the left periphery in Italian as elaborated in Rizzi 1997, 2001a, 2004b. It turns out that long distance crossing possibilities fully predict the local orderings entailed by Rizzi's left peripheral template. In fact, both descriptive gains (in terms of topic positions) and explanatory gains (regarding the position and behavior of topics and of Rizzi's (2001a) Int) can be made if local ordering is reduced to locality. This suggests that the left peripheral template should be derived from some appropriate theory of locality and should not be taken as a theoretical primitive.