nils-herrmann/clean_scirepeval huggingface dataset:
Singularity detection method of chaotic time series using wavelet multi resolution analysis
Venue: 2010 2nd International Conference on Industrial and Information Systems
Year: 2010

In this paper, wavelet multi resolution analysis (WMRA) is applied to detect singularity in chaotic time series. Based on the analysis of the relationship among wavelet multi resolution, Lipschitz exponent and signal singularity, we select Daubechies wavelet to decompose the chaotic signal in different scales. After reconstructing those signals decomposed, some of which contain singular information, the position of singularity in signals can be exactly found out. Furthermore, because of the case that the existence of noise in real chaotic system, we test the anti interference of WMRA with white noise. The research conclusions show that WMRA not only has a strong ability for detecting singularity of chaotic time series signal, but also has a good effect on anti interference.
Formal in the Informal: A Multi Level Analysis of Core Python Developers' Tweets
Venue: 2018 25th Australasian Software Engineering Conference (ASWEC)
Year: 2018

Contributors to Open Source Software (OSS) development projects use social media to discuss personal and work related issues. While there has been some interest in studying social media posts of developers, the investigation of the use of this medium by core contributors has not received much attention. Such an investigation could be useful given the technical and social insights such members bring to their team's development.  To bridge this gap, we have investigated Python core developers' posts on Twitter.  We systematically collected 27,805 tweets from 80 core developers' Twitter accounts of which 3,282 (11.8% were relevant to Python development. We performed multiple forms of analyses on these tweets, involving bottom up thematic analysis on three levels (topics, questions and answers, and decision making) We also conducted social network analysis of the topics of interest of core developers.  Core developers' Python related tweets fall under 23 different topics (in 5 higher level topic categories) The top two categories were software related and community related tweets. Core developers also used Twitter as a medium to discuss technical issues related to Python software development in the form of questions and answers (Q&As) to a large extent (45% of the tweets) Moreover, this informal medium is also used for decision making 2% of the time, supplementing the formal channels of decision making (i.e. mailing lists) Additionally, we have identified five different groups of core developers based on their topic interests.  Although informal in nature, social media platforms provide another window, beyond formal project repositories, for understanding OSS ecosystems. Consequently, informal sources must be integrated with formal sources to obtain a comprehensive view of OSS development activities.
The effect of altered head and tongue posture on upper airway volume based on a validated upper airway analysis An MRI pilot study.
Venue: Orthodontics craniofacial research
Year: 2019

To determine the influence of altered head or tongue posture on the upper airway (UA) volumes using MRI imaging based on a new objective and validated UA evaluation protocol.  One supine CBCT and five sagittal MRI scans were obtained from ten subjects in different head and tongue positions: (1) supine neutral head position (NHP) with the tongue in a natural resting position with tip of the tongue in contact with the lingual aspect of the lower incisors (TRP) (2) Head extension with TRP; (3) Head flexion with TRP; (4) NHP with the tip of the tongue in contact with the posterior edge of the hard palate (THP) and (5) NHP with the tip of the tongue in contact with the floor of the mouth in contact with Caruncula sublingualis.  Based on a validated CBCT UA analysis, the retropalatal oropharyngeal and the corresponding total volumes, were measured from each MRI scan. Wilcoxon sign rank test was applied to determine the statistically significant difference in mean volume between the baseline head and tongue posture (NHP with TRP) and the other postures.  Five females and five males with a mean age of 46,5 13.7 years volunteered for this pilot study. The UA volumes, particularly the oropharyngeal volume, increased significantly with head extension and NHP with THP, and decreased significantly with head flexion.  Altered head and tongue posture proved to affect the UA volumes thus representing confounding variables during three dimensional radiographic image acquisition.
Does Inducing Students to Schedule Lecture Watching in Online Classes Improve Their Academic Performance? An Experimental Analysis of a Time Management Intervention
Year: 2019

Time management skills are an essential component of college student success, especially in online classes. Through a randomized control trial of students in a for credit online course at a public 4 year university, we test the efficacy of a scheduling intervention aimed at improving students' time management. Results indicate the intervention had positive effects on initial achievement scores; students who were given the opportunity to schedule their lecture watching in advance scored about a third of a standard deviation better on the first quiz than students who were not given that opportunity. These effects are concentrated in students with the lowest self reported time management skills. However, these effects diminish over time such that we see a marginally significant negative effect of treatment on the last week's quiz grade and no difference in overall course scores. We examine the effect of the intervention on plausible mechanisms to explain the observed achievement effects. We find no evidence that the intervention affected cramming, procrastination, or the time at which students did work.
Functional Assessment Based Interventions for Children At Risk for Emotional and Behavioral Disorders
Year: 2007

Functional assessments were conducted to identify the variables maintaining disruptive behavior in eight, typically developing fifth grade students enrolled in general education classrooms. Participants whose behavior was found to be functionally related to either task avoidance or attention seeking were randomly assigned to a treatment strategy that was primarily either antecedent or consequent based. An ABAB single case design was employed to analyze the effects of treatment strategies. The current study also conducted a comparison of treatment strategies that were primarily antecedent or consequent based. Results showed that antecedent based treatment strategies (i.e. self monitoring and task modification) were more effective than consequent based treatment strategies (i.e. differential reinforcement) for increasing academic engagement and reducing disruptive behavior. Implications regarding the use of functional assessment with typically developing students at risk for emotional and behavioral problems enrolled in general education classrooms and the effects of antecedent and consequent based treatment strategies as a function of behavior are discussed.
The dynamic moral self: A social psychological perspective.
Year: 2009

When psychologists explore the role of the self in moral motivation and behavior, they typically take a personological approach. Some seek to describe a general personality structure shared by widely recognized moral exemplars, whereas others examine individual differences in the centrality of mortality to one's personal goals. A social psychological approach to the moral self complements these personological perspectives by taking into account the situational malleability of moral self regard, or one's self perceived moral standing at any given moment. Recent research reviewed in this chapter demonstrates the value added by this perspective: First, when people are made secure about their morality, they sometimes act less morally (moral credentials) second, moral exemplars are disliked rather than admired when their behavior is seen as an indictment of people's own choices (moral resentment) and third, people sometimes boost their moral self regard to compensate for failures in other domains (moral compensation) These phenomena underscore the importance of understanding moral self regard as just one aspect of a highly dynamic self concept. THE SELF IN MORAL PSYCHOLOGY For decades, moral psychology mostly left the self out of its analyses. It focused instead on moral reasoning and on the cognitive underpinnings of decisions about right and wrong (Kohlberg, 1969) The neglect of the self and emphasis on the mechanics of moral reasoning was a reaction against the perceived murkiness of psychodynamic theories influential at the time, and the dearth of empirical support for concepts such as "superego strength" to explain moral learning (see Kohlberg, 1963)
Innovacion social y su importancia en la gestion del conocimiento y la participacion ciudadana (Social Innovation and Its Importance in Knowledge Management and Citizen Participation)
Year: 2017

Innovation promotes social development in science and technology. This reflection paper addresses it from two analytical perspectives: knowledge management and citizen participation. These two concepts must be considered to fully understand the intrinsic relationship among creative social innovation projects. The latter do not only solve specific problems, but also encourage collective action and inclusion. During their implementation, a great deal new of knowledge is generated, and this is essential to make a real impact on society or a target community. A detailed review was conducted to find signs of collaborative attitudes that foster values for the common good in democratic stability of communities seeking to innovate while solving complex social issues. This article aims to delve into the concepts of social innovation, knowledge societies and their contribution to science, technology and society.
Hierarchical structure ZSM 5/SBA 15 composite with improved hydrophobicity for adsorption desorption behavior of toluene
Year: 2020

Hydrophobic zeolites have been considered as one of the most promising adsorbents for capturing volatile organic compounds (VOCs) In this contribution, hierarchically structured ZSM 5/SBA 15 composites with different morphologies including platelet, hexagonal prism, long hexagonal prism, and long rod were prepared. All materials were characterized using XRD, SEM, and TEM EDX, which confirmed that the high dispersion of two zeolites within the composites. Due to the presence of intracrystalline mesopores that could shorten the diffusion pathway of toluene, the composites resulted in increased effective diffusion and higher adsorption capacity. The composites also possess higher hydrophobicity, leading to much better toluene adsorption performance under humid conditions. The water contact angle of ZSM 5 could be increased from 15.6deg to 44.9deg by forming well dispersed zeolite composites. The 29Si MAS NMR results confirmed that the composites possess higher amount of Q4 groups (75.3% 80.1% which is the intrinsic reason for higher hydrophobicity. Notably, ZSM 5/SBA 15 hexagonal prism resulted in the best adsorption performance and cycling stability when compared with pure ZSM 5, the breakthrough time was increased from 20.8 to 49.4 min under dry conditions and from 5.9 to 27.3 min in the presence of 50% relative humidity. This work represents an important scheme for making hydrophobic zeolite based VOCs adsorbents with also improved toluene diffusion properties due to the unique hierarchical porous structure.
Two dimensional graphene/g C3N4 in plane hybrid heterostructure for enhanced photocatalytic activity with surface adsorbed pollutants assistant
Year: 2020

A two dimensional graphene/g C3N4 in plane hybrid heterostructure (DCN Cg) which achieved ~32.0 fold enhanced visible light photocatalytic performance for pollutant degradation compared to bulk g C3N4, was prepared by a self conversion process. The characterizations indicated that graphene was stitched onto the edge of carbon nitride, not only extending the photoabsorption to energies below intrinsic bandgap, but also strengthening the interaction between pollutants and catalyst surface by p p and hydrogen bonds. The stronger interaction promoted the polarization of charge distribution of DCN Cg to further enhance the separation and transfer of photogenerated e /h+ providing an efficient pathway for electron transfer from pollutants to DCN Cg. Both interfacial electron transfer processes were verified that the photoexcited electrons are rapidly transferred from carbon nitride part to graphene by p conjugated bond stitched structure and trapped by O2 to generate O2 for degradation of pollutants. Meanwhile, adsorbed pollutants is decomposed by transferring electrons to the positive holes on the valence band of DCN Cg.
Triangle Formation Based Multiple Targets Search Using a Swarm of Robots
Venue: ICSI
Year: 2016

As a distributed system, swarm robotics is well suited for multiple targets search tasks. In this paper, a new approach based on triangle formation and random search is proposed for high efficiency, demonstrating excellent abilities of exploration and exploitation in experiments. In addition, a new random walk strategy of linear ballistic motion, integrated with triangle estimation, is put forward as a comparison algorithm, the performance of which can serve as a benchmark.
Softmax based Classification is k means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring
Venue: ArXiv
Year: 2020

We formally prove the connection between k means clustering and the predictions of neural networks based on the softmax activation layer. In existing work, this connection has been analyzed empirically, but it has never before been mathematically derived. The softmax function partitions the transformed input space into cones, each of which encompasses a class. This is equivalent to putting a number of centroids in this transformed space at equal distance from the origin, and k means clustering the data points by proximity to these centroids. Softmax only cares in which cone a data point falls, and not how far from the centroid it is within that cone. We formally prove that networks with a small Lipschitz modulus (which corresponds to a low susceptibility to adversarial attacks) map data points closer to the cluster centroids, which results in a mapping to a k means friendly space. To leverage this knowledge, we propose Centroid Based Tailoring as an alternative to the softmax function in the last layer of a neural network. The resulting Gauss network has similar predictive accuracy as traditional networks, but is less susceptible to one pixel attacks; while the main contribution of this paper is theoretical in nature, the Gauss network contributes empirical auxiliary benefits.
Multiple classifiers in biometrics. Part 2: Trends and challenges
Venue: Inf. Fusion
Year: 2018

The present paper is Part 2 in this series of two papers. In Part 1 we provided an introduction to Multiple Classifier Systems (MCS) with a focus into the fundamentals: basic nomenclature, key elements, architecture, main methods, and prevalent theory and framework. Part 1 then overviewed the application of MCS to the particular field of multimodal biometric person authentication in the last 25 years, as a prototypical area in which MCS has resulted in important achievements. Here in Part 2 we present in more technical detail recent trends and developments in MCS coming from multimodal biometrics that incorporate context information in an adaptive way. These new MCS architectures exploit input quality measures and pattern specific particularities that move apart from general population statistics, resulting in robust multimodal biometric systems. Similarly as in Part 1, methods here are described in a general way so they can be applied to other information fusion problems as well. Finally, we also discuss here open challenges in biometrics in which MCS can play a key role.
Generating Sentences from a Continuous Space
Venue: CoNLL
Year: 2016

The standard recurrent neural network language model (RNNLM) generates sentences one word at a time and does not work from an explicit global sentence representation. In this work, we introduce and study an RNN based variational autoencoder generative model that incorporates distributed latent representations of entire sentences. This factorization allows it to explicitly model holistic properties of sentences such as style, topic, and high level syntactic features. Samples from the prior over these sentence representations remarkably produce diverse and well formed sentences through simple deterministic decoding. By examining paths through this latent space, we are able to generate coherent novel sentences that interpolate between known sentences. We present techniques for solving the difficult learning problem presented by this model, demonstrate its effectiveness in imputing missing words, explore many interesting properties of the model's latent sentence space, and present negative results on the use of the model in language modeling.
Method for Increasing the Efficiency of a Biaxial Solar Tracker with Exact Solar Orientation
Year: 2018

Modern solar follow up systems make it possible to increase a solar cell's efficiency and, as a result, solar energy utilization. The paper considers modern solar follow up methods and their operational principles. Trackers are separated onto uniaxial and biaxial according to the plane which tracking occurs. Biaxial trackers are the most efficient. The operational principles of active and passive trackers are studied. A laboratory model of a biaxial solar tracker with precise solar orientation is described, based on an algorithm for calculating the voltage with current sensors. The following are given in the paper: the current voltage characteristic obtained for different solar array positions and using trackers; the relationships between the power and measured currents and voltages. The efficiency is calculated for different solar array positions and using a tracker.
Greedy and Local Ratio Algorithms in the MapReduce Model
Venue: SPAA
Year: 2018

MapReduce has become the de facto standard model for designing distributed algorithms to process big data on a cluster. There has been considerable research on designing efficient MapReduce algorithms for clustering, graph optimization, and submodular optimization problems. We develop new techniques for designing greedy and local ratio algorithms in this setting. Our randomized local ratio technique gives $2$ approximations for weighted vertex cover and weighted matching, and an f approximation for weighted set cover, all in a constant number of MapReduce rounds. Our randomized greedy technique gives algorithms for maximal independent set, maximal clique, and a (1+e)1n D approximation for weighted set cover. We also give greedy algorithms for vertex colouring with (1+o(1))D colours and edge colouring with (1+o(1))D colours.
Particle Swarm Optimization Of a Hybrid Wind/Tidal/PV/Battery Energy System. Application To a Remote Area In Bretagne, France
Venue: Energy Procedia
Year: 2019

A new method proposed in this work to optimize the power generated by a hybrid renewable energy system which consists of Wind turbine/Tidal turbine/PV module/Batteries. This system has been designed to satisfy a stand alone area in Brittany, France, as an example of load demand. The Particle Swarm Optimization technique (PSO) was proposed and developed to minimize the cost of energy. Where the ability of this algorithm was developed to reach the best results in double speeds, at a time rate better than 80% of conventional technology time and less than 20 repetitions only. The problem is defined as an economic problem, taking into consideration the optimal sizing of the system, high reliability, planning expansion for future development, the state of charge of the battery. The total net present cost (TNPSC) is introduced as the objective function, taking into consideration the minimum fitness values in the particle swarm process. The (PSO) algorithm developed has several characteristics and advantages over other traditional techniques and algorithms. In fact, it allows to achieve the optimal solution and to reduce the overall cost with high speed and accuracy. The PSO algorithm program was developed using MATLAB software.
Everyday ethics
Venue: In Practice
Year: 2007

THIS series gives readers the opportunity to consider and contribute to the discussion of some of the ethical dilemmas that can arise in veterinary practice. Each month, a case scenario is presented, followed by discussion of some of the issues involved. In addition, a possible way forward is suggested; however, there is rarely a cut and dried answer in such cases, and readers may wish to suggest an alternative approach. This month's dilemma, entitled 'Has small animal practice gone too far? is presented and discussed by Andrew Gardiner. Readers with comments to contribute are invited to send them as soon as possible, so that they can be considered for publication in the next issue. Discussion of the dilemma 'Veterinary nurse uneasy with vets' approach' which was published in the last issue, appears on page 554. The series is being coordinated by Siobhan Mullan, of the University of Bristol. It is hoped it will provide a framework that will help practices find solutions when facing similar dilemmas.
Computational Methods For Fluid Dynamics
Year: 2016

Thank you for reading computational methods for fluid dynamics. Maybe you have knowledge that, people have look numerous times for their chosen novels like this computational methods for fluid dynamics, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some infectious virus inside their laptop. computational methods for fluid dynamics is available in our book collection an online access to it is set as public so you can download it instantly. Our digital library spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the computational methods for fluid dynamics is universally compatible with any devices to read.
Algunas aproximaciones a los modelos de autoridad y poder en el teatro del Siglo de Oro
Year: 2017

Amplios territorios en la literatura y el arte del Siglo de Oro se caracterizan por la exploracion de los mecanismos del poder y sus limites, por el ejercicio de la autoridad y sus requisitos, por las intersecciones entre los ambitos de la realidad y la produccion literaria. Es conocida la interpretacion que defendio sobre todo Jose Antonio Maravall, quien veia en el teatro del Siglo de Oro una maquina de propaganda del poder. Las cosas, naturalmente, no son tan simples. No lo pueden ser en u.
CD36 as a Molecular Target of Functional DNA Aptamer NAFLD01 Selected against NAFLD Cells.
Venue: Analytical chemistry
Year: 2021

The aim of this study was to identify the target of nonalcoholic fatty liver disease (NAFLD) cell specific aptamer NAFLD01 and investigate its effect on lipid metabolism in vitro. A distinct membrane protein of NAFLD cells pulled down by NAFLD01 was analyzed by mass spectrometry to determine target candidates, and affinity of NAFLD01 to target protein silent NAFLD cells was detected to validate it. Knockdown of CD36 abolished the binding of NAFLD01, and its binding affinity was associated with membrane bound CD36. NAFLD01 affinity for NAFLD cells was proportional to the CD36 expression level. Moreover, compared to random sequences, NAFLD01 showed better recognition for both mouse and human tissue sections of NAFLD. Importantly, NAFLD01 could ameliorate liver fat deposition through interaction with CD36 in vitro. Therefore, aptamer NAFLD01 could act as an effective and safe targeted drug for NAFLD. NAFLD01 is the first reported CD36 specific aptamer. This aptamer can improve hepatocyte steatosis via specifically binding to CD36. This study provides a molecular tool to investigate the mechanism of CD36 in NAFLD.