nils-herrmann/clean_scirepeval huggingface dataset:
A Novel Optimization Technique for Combined Economic and Emission Dispatch Problem considering Congestion Management

In power systems, the dispatch of real power plays a pivotal role in mitigating the transmission congestion, yet at a very low and affordable cost. Thus, in this paper, the rescheduling of real power generation has been dealt with a view to manage the congestion in transmission.  In this paper, the congestion management in a deregulated electricity market has been endeavored for the problems of Combined Economic and Emission Dispatch (CEED) by employing a novel technique of optimization through Artificial Bee Colony (ABC) algorithm. In a real time transmission system, the congestion is an inevitable condition that occurs when the power flow in the line exceeds than that of its limit. In this work, the optimized solution for CEED problem has been obtained via ABC algorithm. An encoding scheme based on generating unit is used.  By employing a robust and efficient methodology using ABC algorithm, an optimal technique on congestion management has been proposed, which takes into account of corrective re dispatch of real power through the transmission system, under the CEED environment on a restructured power system. The proposed method has been tested on an IEEE 30 bus system and their results have also been validated to show the efficacy of the proposed methodology, which throw light upon the fact that it has emerged out as an effective tool in handling the transmission congestion in a deregulated environment that results in the minimization of cost of re dispatch on one hand and in a secured operating condition on the other.  This work can be extended in the future by including reactive power support, which can further minimize the total operating cost of the system.
Optimal real power rescheduling of generators for congestion management using a novel ant lion optimiser

Considering system uncertainties prevailing in the restructured power system, congestion management (CM) is a vital issue in power system operation and control. The objective of CM is to remove congestion in the lines while satisfying all the constraints with minimum congestion cost. This study proposes a generation rescheduling based approach for CM in electricity market using a novel ant lion optimiser (ALO) algorithm. ALO is a recently developed the nature inspired algorithm based on the hunting mechanism of antlions. The effectiveness of the proposed approach is tested on modified IEEE 30 bus, modified IEEE 57 bus and IEEE 118 bus test systems. The security constraints like load bus voltage and line loading impact are incorporated in this study. To prove the validity of the proposed technique, the obtained results are compared to the results offered by various recent optimisation algorithms. The results show that the proposed ALO algorithm outperforms the other comparative algorithms. The proposed approach uses less number of fitness function evaluations, not traps into local minima and offers promising convergence characteristic. The proposed approach will ease the system operator to remove the contingency rapidly for secured and reliable operation of the power system under deregulated environment.
Can machines talk? Comparison of Eliza with modern dialogue systems
Venue: Comput. Hum. Behav.

To find if current dialogue systems use the same, psychotherapist questioning technique as Joseph Weizenbaum's 1960 natural language understanding programme, Eliza, the authors carried out an original experiment comparing five successful artificial dialogue systems, Cleverbot, Elbot, Eugene Goostman, JFred and Ultra Hal with an online version of Eliza. More than one hundred male and female participants with 1st or non 1st English language, age range 13 64, interacted with the systems over the Internet scoring each for conversation ability. Developers of the modern conversation systems show they deploy a variety of techniques to initiate and maintain dialogue learning from interactions with humans over the Internet. Statistical significance shows these dialogue systems are an improvement on their predecessor. Embedded on the web affording round the clock interaction the nature of artificial dialogue systems is evolving as these systems learn from the way humans converse. The uses of modern Elizas are proven successful as virtual assistants in e commerce; their conversational basis is already extending into education. What we can say is modern artificial dialogue systems do talk. They are able to participate in conversation in a way their predecessor Eliza could not: they are able to share personal opinions, relay experience of family dramas, be relevant, but also be vague, and mislead just as humans do. Display Omitted 6 dialogue systems involved in study including online version of Eliza.116 human judges scored systems' conversation ability.Eugene Goostman and Cleverbot conversational ability scores 2 times over Eliza.Females judges scored dialogue systems higher than males.Judges in age group 25.
Diffraction gratings: from principles to applications in high intensity lasers

Diffraction gratings were discovered during the 18th century, and they are now widely used in spectrometry analysis, with outstanding achievements spanning from the probing of single molecules in biological samples to the analysis of solar systems in astronomy. The fabrication of high quality diffraction gratings requires precise control of the period at a nanometer scale. The discovery of lasers in the 1960s gave birth to optical beam lithography in the 1970s. This technology revolutionized the fabrication of diffraction gratings by offering highly precise control of the grating period over very large scales. It is surprising to see that a few years after, the unique spectral properties of diffraction gratings revolutionized, in turn, the field of high energy lasers. We review in this paper the physics of diffraction gratings and detail the interest in them for pulse compression of high power laser systems.
A minimization principle for the description of modes associated with finite time instabilities
Venue: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences

We introduce a minimization formulation for the determination of a finite dimensional, time dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have finite lifetime, they can play a crucial role either by altering the system dynamics through the activation of other instabilities or by creating sudden nonlinear energy transfers that lead to extreme responses. However, their essentially transient character makes their description a particularly challenging task. We develop a minimization framework that focuses on the optimal approximation of the system dynamics in the neighbourhood of the system state. This minimization formulation results in differential equations that evolve a time dependent basis so that it optimally approximates the most unstable directions. We demonstrate the capability of the method for two families of problems: (i) linear systems, including the advection diffusion operator in a strongly non normal regime as well as the Orr Sommerfeld/Squire operator, and (ii) nonlinear problems, including a low dimensional system with transient instabilities and the vertical jet in cross flow. We demonstrate that the time dependent subspace captures the strongly transient non normal energy growth (in the short time regime) while for longer times the modes capture the expected asymptotic behaviour.
A description of Canadian epilepsy monitoring units: An initial step toward developing nursing practice consensus guidelines
Venue: Epilepsy Behavior

The epilepsy monitoring unit (EMU) is a well established resource for investigating patients' seizures but is known to be heterogeneous in organization and clinical practice. The purpose of this study was to gain a better understanding of similarities and differences in EMU characteristics across Canada, with specific emphasis on EMU organization and nursing resources, which were currently unknown. Results would be used to develop a consensus on best nursing practice guidelines in EMUs with the goal to improve patient care and safety during epilepsy monitoring admissions.  An 18 item survey was developed addressing EMU locations, types, nursing ratios, nursing roles, and other allied health resources. Surveys were distributed to lead nurses, physicians, and administrators in 29 EMUs across Canada. Results were tabulated and presented for each question in the survey.  All EMUs were located in urban, teaching centers and divided similarly by patient age. The survey demonstrated considerable variability in EMU bed location and organization with the majority of EMUs being smaller, open units embedded in wards rather than larger, closed units. Independent of patient acuity, variability also existed in nurse to patient ratios, nursing skill level, specialty nursing support, and EEG technician availability. These findings highlight that EMU heterogeneity contributes to the challenges in the development of standardized safe care practices and that nursing education and nursing best practice recommendations need to be developed with baseline EMU nursing competencies, skills, and knowledge in mind.
The correlation between editorial delay and the ratio of highly cited papers in Nature, Science and Physical Review Letters
Venue: Scientometrics

Ideally, in a reviewing process, it is generally easier for referees to make faster and more reliable decisions for high quality papers, which ideally and on average will later attract more citations. Therefore, it is possible that the editorial delay time the time between dates of submission and acceptance or publication is correlated to the number of received citations, as has been weakly confirmed by previous studies. In this study, we propose a different measure for this correlation. Instead of directly calculating the correlation coefficient between the editorial delay and the number of citations, we define a ratio of above median highly cited papers and perform correlation analysis between editorial delay and that ratio for all academic papers published in Nature, Science and Physical Review Letters. Using this alternative measure, we find that on average papers with shorter editorial delay do have larger probabilities of becoming highly cited papers.
Does debt ceiling and government shutdown help in forecasting the us equity risk premium

This article evaluates the predictability of the equity risk premium in the United States by comparing the individual and complementary predictive power of macroeconomic variables which are popular in academia and technical indicators which are widely used by practitioners in the market using a comprehensive set of 16 economic and 14 technical predictors over a monthly out of sample period of 1995:1 to 2012:12 and an in sample period of 1986:1 1994:12. In order to do so we consider, in addition to the set of variables used in Neely et al. (2013) the forecasting ability of two other important variables namely government shutdown and debt ceiling. Using a more recent dataset compared to that of Neely et al. (2013) our results tend to support the better out of sample predictive ability of technical indicators when compared to economic variable but to a lesser extent. Our results also show that one of the newly added variables namely government shutdown provides statistically significant out of sample predictive power over the equity risk premium relative to the historical average based on the MSFE adjusted statistics. An important finding however is that, during recessions, the majority of our indicators including the newly added government shutdown variable can provide better out of sample predictive power when compared to the historical benchmark. Most of the variables, including government shutdown but not debt ceiling, also show significant economic gains for a risk averse investor especially during recessions which can be interpreted as a willingness to pay a portfolio management fee.
Equity Premium Prediction: The Role of Economic and Statistical Constraints

In this paper, we show that the equity premium is predictable out of sample when we use a predictive regression that conditions on a large set of economic fundamentals, subject to: (1) economic constraints on the sign of coefficients and return forecasts, and (2) statistical constraints imposed by shrinkage estimation. Equity premium predictability delivers a certainty equivalent return of about 2.7% per year over the benchmark for a mean variance investor. Our predictive framework outperforms a large group of competing models that also condition on economic fundamentals, as well as models that condition on technical indicators.
Technical Analysis and Risk Premium in Indian Equity Market: A Multiple Regression Analysis

The purpose of this paper is to estimate the effectiveness of technical trading strategies and examine the extent to which trading profitability using technical analysis indicators explains the 'risk premium' or 'risk compensation' for investing in equity markets as against assets that are relatively risk free using multiple regression analysis. The technical indicators selected for the analysis are Bollinger bands (volatility indicator) moving average (trend indicator) Relative Strength Index (momentum indicator) and Elliot wave theory (mass psychology indicator) The paper finds evidence for risk premium being explained by technical indicators. The technical trading strategy based on trend, momentum, volatility indicators, including the Elliot wave theory has the ability to explain the excess return of a stock. The findings have important implications for traders and practitioners. A positive relationship implies that technical indicators can be explored while evaluating strategies for investment. So, it suggests that traders, retail investors and fund managers, while evaluating portfolios, can rely on technical indicators based trading strategies other than fundamental analysis.
geoRge: A Computational Tool To Detect the Presence of Stable Isotope Labeling in LC/MS Based Untargeted Metabolomics.
Venue: Analytical chemistry

Studying the flow of chemical moieties through the complex set of metabolic reactions that happen in the cell is essential to understanding the alterations in homeostasis that occur in disease. Recently, LC/MS based untargeted metabolomics and isotopically labeled metabolites have been used to facilitate the unbiased mapping of labeled moieties through metabolic pathways. However, due to the complexity of the resulting experimental data sets few computational tools are available for data analysis. Here we introduce geoRge, a novel computational approach capable of analyzing untargeted LC/MS data from stable isotope labeling experiments. geoRge is written in the open language R and runs on the output structure of the XCMS package, which is in widespread use. As opposed to the few existing tools, which use labeled samples to track stable isotopes by iterating over all MS signals using the theoretical mass difference between the light and heavy isotopes, geoRge uses unlabeled and labeled biologically equivalent samples to compare isotopic distributions in the mass spectra. Isotopically enriched compounds change their isotopic distribution as compared to unlabeled compounds. This is directly reflected in a number of new m/z peaks and higher intensity peaks in the mass spectra of labeled samples relative to the unlabeled equivalents. The automated untargeted isotope annotation and relative quantification capabilities of geoRge are demonstrated by the analysis of LC/MS data from a human retinal pigment epithelium cell line (ARPE 19) grown on normal and high glucose concentrations mimicking diabetic retinopathy conditions in vitro. In addition, we compared the results of geoRge with the outcome of X(13)CMS, since both approaches rely entirely on XCMS parameters for feature selection, namely m/z and retention time values. To ensure data traceability and reproducibility, and enabling for comparison with other existing and future approaches, raw LC/MS files have been deposited in MetaboLights (MTBLS213) and geoRge is available as an R script at https:/github.com/jcapelladesto/geoRge.
Hyperdimensional biosignal processing: A case study for EMG based hand gesture recognition
Venue: 2016 IEEE International Conference on Rebooting Computing (ICRC)

The mathematical properties of high dimensional spaces seem remarkably suited for describing behaviors produces by brains. Brain inspired hyperdimensional computing (HDC) explores the emulation of cognition by computing with hypervectors as an alternative to computing with numbers. Hypervectors are high dimensional, holographic, and (pseudo)random with independent and identically distributed (i.i.d. components. These features provide an opportunity for energy efficient computing applied to cyberbiological and cybernetic systems. We describe the use of HDC in a smart prosthetic application, namely hand gesture recognition from a stream of Electromyography (EMG) signals. Our algorithm encodes a stream of analog EMG signals that are simultaneously generated from four channels to a single hypervector. The proposed encoding effectively captures spatial and temporal relations across and within the channels to represent a gesture. This HDC encoder achieves a high level of classification accuracy (97.8% with only 1/3 the training data required by state of the art SVM on the same task. HDC exhibits fast and accurate learning explicitly allowing online and continuous learning. We further enhance the encoder to adaptively mitigate the effect of gesture timing uncertainties across different subjects endogenously; further, the encoder inherently maintains the same accuracy when there is up to 30% overlapping between two consecutive gestures in a classification window.
A Robust and Energy Efficient Classifier Using Brain Inspired Hyperdimensional Computing
Venue: ISLPED

The mathematical properties of high dimensional (HD) spaces show remarkable agreement with behaviors controlled by the brain. Computing with HD vectors, referred to as "hypervectors," is a brain inspired alternative to computing with numbers. Hypervectors are high dimensional, holographic, and (pseudo)random with independent and identically distributed (i.i.d. components. They provide for energy efficient computing while tolerating hardware variation typical of nanoscale fabrics. We describe a hardware architecture for a hypervector based classifier and demonstrate it with language identification from letter trigrams. The HD classifier is 96.7% accurate, 1.2% lower than a conventional machine learning method, operating with half the energy. Moreover, the HD classifier is able to tolerate 8.8 fold probability of failure of memory cells while maintaining 94% accuracy. This robust behavior with erroneous memory cells can significantly improve energy efficiency.
Hyperdimensional Computing for Text Classification

Hyperdimensional computing explores the emulation of cognition by computing with hypervectors as an alternative to computing with numbers. Hypervectors are highdimensional, holographic, and (pseudo)random with i.i.d. components. These properties provide an opportunity for efficient computing. We focus on an application of hyperdimensional computing for text classification. Accordingly, we present an algorithm for classifying news articles from a stream of input letters. Using pentagrams of letters, the algorithm achieves a classification accuracy above 94% on eight news topics, surpassing other techniques reported in the literature, including Bayes, K NN, and SVM. We demonstrate a software framework that enables efficient execution of such algorithms on contemporary hardware fabrics.
Tribology and wear resistance of the stainless steel. The sol gel coating impact on the friction and damage

The sol gel coating method is considered to be simple, easy to adopt, requires low processing temperature and leads to high degree of purity oxide coatings. Moreover, the fabrication of metal oxide thin films by sol gel technic is cost effective, reproducible and applicable to large substrates without any shape restriction. This work focuses on optimizing conditions for depositing alumina coatings by sol gel method on stainless steel substrates with a low annealing temperature, in order not to degrade the metal substrate. Moreover, to obtain coatings of several micron thick, the sol gel was adapted by adding ceramic powder or by successive layers deposition which reduces the stresses occurring in the coatings during the heat treatment. The various as obtained layers are characterized in terms of morphological features, microstructure, hardness and the tribological behavior and wear resistance. The results showed that the deposited alumina coating at low temperature crystallized in d Al 2 O 3 Adding to that, the increase of the temperature favors the presence of a Al 2 O 3 structure. Moreover, the measurements demonstrate that the mechanical properties of sol gel deposited alumina coatings in terms of hardness, wear resistance are improved in comparison with uncoated stainless steel or the classic nitrited steel.
Social determinants of HIV infection among men who have sex with men in the Philippines

Since 2007, the number of prevalent HIV cases in the Philippines has been growing exponentially each year. In 2014, 84% of the new cases were attributed to sexual transmission by men who have sex with men (MSM) To provide insight on this rising epidemic, social determinants of HIV infection among MSM were analyzed using a social ecological model, consisting of individual, network, community, and public policy levels. The following determinants were found most relevant to MSM in the Philippines: (1) individual: genital ulcer disease, number of male partners, injection drug use (IDU) and non IDU substance abuse; (2) network: receptive and unprotected anal sex, and social media usage; (3) community: the lack of access to preventive services, VCT and ART, and stigma; (4) public policy: homophobia, condom availability, and sexual health education. Stigma was found to interact with multiple determinants at every level. Condom use was found to be a key determinant to target for expansion. Using health belief model constructs, barriers to self efficacious behavior might be identified for future interventions. Lastly, individual, network, and community levels might be the most feasible in HIV prevention for MSM until attitudes toward MSM and condom use change at the societal level.
Why do Asian Americans academically outperform Whites? The cultural explanation revisited.
Venue: Social science research

We advocate an interactive approach to examining the role of culture and SES in explaining Asian Americans' achievement. We use Education Longitudinal Study (ELS) 2002 baseline data to test our proposition that the cultural orientation of Asian American families is different from that of white American families in ways that mediate the effects of family SES on children's academic achievement. The results support our hypothesis, indicating that: (1) SES's positive effects on achievement are stronger among white students than among Asian Americans; (2) the association between a family's SES and behaviors and attitudes is weaker among Asian Americans than among Whites; (3) a fraction of the Asian White achievement gap can be accounted for by ethnic differences in behaviors and attitudes, particularly ethnic differences in family SES's effects on behaviors and attitudes. We find that Asian Americans' behaviors and attitudes are less influenced by family SES than those of Whites are and that this difference helps generate Asians' premium in achievement. This is especially evident at lower levels of family SES.