nils-herrmann/clean_scirepeval huggingface dataset:
Standing rock and the Indigenous commons
Year: 2020

A new cycle of communications commons has become part of the contemporary repertoire of Indigenous first nations in North America. The mobilization of the Standing Rock Sioux is perhaps the best known example of a continent wide cycle of resistance in which Indigenous communities have employed a combination of collectively governed land based encampments and sophisticated trans media assemblages to challenge the further enclosure of their territories by the state and fossil fuel industries and instead represent their political and media sovereignty, and prefigure a more reciprocal relationship with other humans and with nature. Although their practices of commoning resemble other radical commons projects, the contemporary Indigenous commons begs for a reassessment of the critical framework of the commons. In this article, I discuss the critical commons literature and compare it with the practices of commoning in the anti extractivist encampments of Standing Rock.
Contribution a l'etude de la precipitation des phases intermetalliques dans l'alliage 718
Year: 2010

De nombreux alliages de structure doivent leurs proprietes mecaniques a la presence de precipites inter ou intragranulaires. Ainsi les superalliages a base nickel, de matrice austenique g, sont souvent renforces par des precipites de phases intermetalliques ordonnees. Au sein de l'alliage Inconel 718, outre la phase g' de structure L12 (cubique simple) on trouve des precipites de Ni3Nb sous la forme metastable g" (D022 tetragonal centre) ou sous la forme stable d (D0a orthorhombique) Le role des precipites g' g" et d sur les proprietes macroscopiques de l'alliage est connu et largement utilise en contexte industriel. Cependant les mecanismes de precipitation et de transformation de ces precipites ne sont toujours pas completement elucides, ce qui a motive ce travail. La microstructure de l'alliage a ete caracterisee par microscopie optique (MO) et electronique (a balayage et en transmission MEB et MET) dans l'etat de livraison et apres des traitements thermiques isothermes et anisothermes. Les essais d'analyse thermique differentielle (ATD) nous ont permis de preciser les domaines de temperature de precipitation et de dissolution des differentes phases presentes (g' g" et d) Differents etats de precipitation ont ete obtenus a l'aide de traitements thermiques isothermes bases sur les diagrammes temps temperaturetransformation (T.T.T. disponibles dans la litterature. Les observations en MET a haute resolution des precipites des phases d et g' ont permis de caracteriser certains des defauts structuraux presents dans ces precipites. Nous montrons ainsi que les defauts d'empilement au sein de la phase g' peuvent servir de germes pour la precipitation de Alors que la structure des interfaces d/g ainsi que les defauts d'orientation au sein des lamelles de d suggerent que la croissance de la phase d a lieu directement a partir de la matrice
Development and evaluation of a system that executes an interventional cardiology risk model based on patient phenotypes automatically extracted from the EMR
Venue: 2020 IEEE International Conference on Healthcare Informatics (ICHI)
Year: 2020

Lack of electronic medical record (EMR) integration hampers effective clinical operationalization of clinical decision support. Accordingly, this study sought to develop and evaluate a system that automatically executes an interventional cardiology risk model based on EMR content accessed through a web service. Phenotyping rules were developed to automatically determine the models risk factors, advanced age, anemia, congestive heart failure, diabetes, reduced eGFR and hypotension. Performance of the rules was determined using a ground truth based on chart review of 76 patients. Except for one instance, PPV and NPV of the phenotyping rules exceeded 0.93. The predictions produced by the risk model were accurate in 82% of patients. Performance of the phenotyping rules was determined by the ability to model the rules after the risk model's definition and the availability and accuracy of the accessed data sources. Data retrieved by the rules can be presented for efficient physician review and confirmation.
Quasiparabolic Subgroups of Coxeter Groups and Their Hecke Algebra Module Structures
Year: 2017

It is well known that the R polynomial can be defined for the Hecke algebra of Coxeter groups, and the Kazhdan Lusztig theory can be developed to understand the representations of Hecke algebra. There is also a generalization for the existence of R polynomial and Kazhdan Lusztig theory for the Hecke algebra module of standard parabolic subgroups of Coxeter groups. In recent work of Rains and Vazirani, a generalization of standard parabolic subgroups, called quasiparabolic subgroups, are introduced, and the corresponding Hecke algebra module is well defined. However, the existence of the analogous involution (Kazhdan Lusztig bar operator) on the Hecke algebra module of quasiparabolic subgroups is unknown in general. Assuming the existence of the bar operator, the corresponding R polynomials and Kazhdan Lusztig polynomials can be constructed. We prove the existence of the bar operator for the corresponding Hecke algebra modules of quasiparabolic subgroups in finite classical Coxeter groups with a case by case verification (Chapter 4) As preparation, we classify all quasiparabolic subgroups of finite classical Coxeter groups. The approach is to first find all rotation subgroups of finite classical Coxeter groups (Chapter 2) Then we exclude the non quasiparabolic subgroups and confirm the quasiparabolic subgroups (Chapter 3)
Continuous Production Mode as a Viable Process Engineering Tool for Efficient Poly(hydroxyalkanoate) (PHA) Bio Production
Year: 2014

Poly(hydroxyalkanoates) (PHAs) constitute promising biomaterials for substituting plastics of fossil origin. Until now, all commercial processes for PHA production were based on discontinuous fed batch cultivation of prokaryotes. Such processes embody several shortcomings: unpredictable product quality, restricted possibility for supply of toxic carbon substrates, and, most of all, low volumetric productivity. Continuous PHA biosynthesis as a remedy was already investigated on laboratory scale for production of highly crystalline PHA homopolyesters as well as for elastomeric and even functional PHA copolyesters. Apart from enhanced productivity, chemostat processes are a feasible method to elucidate kinetics of cell growth and PHA formation under constant environmental conditions. In order to adapt the process engineering to the microbial kinetic characteristics for growth and PHA accumulation, continuous single and multistage approaches are reported.
Predicting Bank Failure in Nigeria using Principal Component Analysis and D Score Model
Year: 2012

In this study, we coupled principal component analysis with discriminant model to predict the probability of bank failure in Nigeria. Our empirical analysis reveals that the warning signal so developed produces a robust result with high prediction accuracy. This is a very promising result as it indicates its invaluable usefulness for regulators in assessing the health status of banks of interest. The analysis of the regression model indicates that the measures of profitability, liquidity, credit risk and capital adequacy are the key predictive financial ratios. In other words, differences in profitability, liquidity, credit risk (asset quality) and capital adequacy (sustenance) are found to be the major distinguishing characteristics between the non failed (healthy) and failed banks. However, variables for management quality and other bank characteristics like economic conditions and staff productivity are potentially not important predictors of financial problems in Nigerian banks but might make a difference for the group of banks that are facing difficulties. The research methodology employed in this study could be applied to other financial and non financial sectors of the economy.  Bank failure prediction, D score model, principal component analysis, early warning signal, Nigerian banking crisis
Fundamentals and Catalytic Applications of CeO2 Based Materials.
Venue: Chemical reviews
Year: 2016

Cerium dioxide (CeO2, ceria) is becoming an ubiquitous constituent in catalytic systems for a variety of applications. 2016 sees the 40(th) anniversary since ceria was first employed by Ford Motor Company as an oxygen storage component in car converters, to become in the years since its inception an irreplaceable component in three way catalysts (TWCs) Apart from this well established use, ceria is looming as a catalyst component for a wide range of catalytic applications. For some of these, such as fuel cells, CeO2 based materials have almost reached the market stage, while for some other catalytic reactions, such as reforming processes, photocatalysis, water gas shift reaction, thermochemical water splitting, and organic reactions, ceria is emerging as a unique material, holding great promise for future market breakthroughs. While much knowledge about the fundamental characteristics of CeO2 based materials has already been acquired, new characterization techniques and powerful theoretical methods are deepening our understanding of these materials, helping us to predict their behavior and application potential. This review has a wide view on all those aspects related to ceria which promise to produce an important impact on our life, encompassing fundamental knowledge of CeO2 and its properties, characterization toolbox, emerging features, theoretical studies, and all the catalytic applications, organized by their degree of establishment on the market.
Power System Stabilization Using Energy Dissipating Hybrid Control
Venue: IEEE Transactions on Power Systems
Year: 2019

A new energy dissipating hybrid control framework is proposed in this paper. The proposed framework incorporates a plant with continuous dynamics connected in parallel with a hybrid controller that combines logical switches with continuous dynamics. The overall closed loop system can be described as a hybrid impulsive dynamical system in which the redundant energy preserved in the plant can be damped quickly and continuously due to the enhanced dissipativity of the closed loop system. The proposed framework is applied to design decentralized nonlinear excitation controllers for synchronous generators in a multimachine system to improve its transient stability, in which the synchronous generators are modeled as port controlled Hamiltonian systems. Simulation studies on the IEEE 10 generator, 39 bus New England power system are carried out to verify the effectiveness of the proposed energy dissipating hybrid excitation control to improve the transient stability and dissipativity of the interconnected power system under various fault conditions.
Construction of a Benchmark for the User Experience Questionnaire (UEQ)
Venue: Int. J. Interact. Multim. Artif. Intell.
Year: 2017

Questionnaires are a cheap and highly efficient tool for achieving a quantitative measure of a product's user experience (UX) However, it is not always easy to decide, if a questionnaire result can really show whether a product satisfies this quality aspect. So a benchmark is useful. It allows comparing the results of one product to a large set of other products. In this paper we describe a benchmark for the User Experience Questionnaire (UEQ) a widely used evaluation tool for interactive products. We also describe how the benchmark can be applied to the quality assurance process for concrete projects.
Intensity of Stem Rot Disease in Dragon Fruit (Hylocereus polyrhizus) at Samboja Regency
Venue: Jurnal Agroekoteknologi Tropika Lembab
Year: 2019

This study aims to determine the intensity of stem rot disease in dragon fruit plants in Samboja District Kutai Kartanegara Regency. This research was condu cted from November to December 2017 which is represented by four land i.e. two land located in Sungai Merdeka Village and two land located in Kelurahan Karya Merdeka. The method used in this research was interview and direct observation (survey) The sample was determined by purposive sampling or judgemental sampling method, that is method that chooses subject based on specified specific criteria (symptomatic plants) and sample of dragon fruits tems that attack disease in the field. The sample then isolated and identified the pathogen causing the disease at the Pest and Plant Disease Laboratory, Faculty of Agriculture Mulawarman University. The results of this study indicated that the percentage of stem rot disease in the District of Samboja KutaiKartanegara Regency of 60.83% with the severity of disease 36.12% Results from the isolation of the ten drills of dragon fruit plants affected by stem rot disease identified the fungus Fusarium sp. Aspergillus sp. And Trichoderma sp.
Robust Model Free Nonsingular Terminal Sliding Mode Control for PMSM Demagnetization Fault
Venue: IEEE Access
Year: 2019

In this paper, a robust model free nonsingular terminal sliding mode control (MFNTSMC) algorithm based on the ultra local model is proposed to reduce the influence of permanent magnet (PM) demagnetization for PM synchronous motors (PMSMs) First, the PMSM mathematical model in normal and demagnetization is described, and the ultra local model of speed loop and current loop is constructed based on the input and the output of the PMSM vector control system. Then, the MFNTSMC method is proposed and adopted to design the speed controller and d q axis current controller, and the sliding mode observer is designed to estimate the unknown terms of the ultra local model. Finally, compared with the PI control method and model free control method, the results of simulations and experimentations show that the MFNTSMC method can improve the dynamic response while maintaining robustness of PMSM driven system, reduce the dependence of the design of controller on the precise PMSM model, and has fault tolerant control function for PM demagnetization fault.
The effect of Rational Emotive Behaviour Therapy (REBT) on poor study habits among secondary school students in Calabar Municipality
Year: 2016

The rate of failure of secondary school students in public examinations such as West African Examination Council (WAEC) and Joint Admissions and Matriculation Board (JAMB) examinations and the seemingly increasing rate of examination malpractice in schools, have been a growing cause for concern among stakeholders in the educational system in Nigeria. Research has identified Poor study habits as one of the key factors responsible for this high rate of failure and widespread examination malpractice among students. REBT is a cognitive behavior therapy that deals with modifying maladjusted behavior that has to do with a faulty belief system. The purpose of this study is to investigate the effect of REBT on poor study habit of senior secondary School students in Calabar municipality. The research design employed in this study was the Pretest Posttest Control Group Experimental design. One hypothesis was formulated for this study and tested at 0.05 level of significance. Three research questions were asked to guide this study. 80 senior secondary school students were purposively sampled for this study. Data was collected using the Students Study Habits Questionnaire (SSHQ) and Oral interview of participants. Data generated from the study was analyzed using the Analysis of Co variance (ANCOVA) statistical procedure. Results revealed a positive impact of REBT on poor study habits. Recommendations were made based on the findings for this study.
A Deep Graph Wavelet Convolutional Neural Network for Semi supervised Node Classification
Venue: 2021 International Joint Conference on Neural Networks (IJCNN)
Year: 2021

Graph convolutional neural network provides good solutions for node classification and other tasks with non Euclidean data. There are several graph convolutional models that attempt to develop deep networks but do not cause serious over smoothing at the same time. Considering that the wavelet transform generally has a stronger ability to extract useful information than the Fourier transform, we propose a new deep graph wavelet convolutional network (DeepGWC) for semi supervised node classification tasks. Based on the optimized static filtering matrix parameters of vanilla graph wavelet neural networks and the combination of Fourier bases and wavelet ones, DeepGWC is constructed together with the reuse of residual connection and identity mappings in network architectures. Extensive experiments on three benchmark datasets including Cora, Citeseer, and Pubmed are conducted. The experimental results demonstrate that our DeepGWC outperforms existing graph deep models with the help of additional wavelet bases and achieves new state of the art performances eventually.
Generic thermal analysis for phone and tablet systems
Venue: 2012 IEEE 62nd Electronic Components and Technology Conference
Year: 2012

Thermal management of handheld systems such as smart phones and tablet systems is becoming increasingly challenging due to increasing power dissipation. These mobile systems pose a significant challenge for implementation of traditional cooling schemes such as heat sinks and fans due to form factor limitations. Instead, new advanced cooling schemes have been developed. This article presents thermal model development from an analysis of today's smart phone thermal management schemes and application of these techniques to a tablet system. Application processor temperature rise and tablet skin temperature are reported for thermal enhancement simulations using this tablet system. Some guiding principles are provided for efficient thermal design of handheld systems.
Differential Effect of Plant Lipids on Membrane Organization
Venue: The Journal of Biological Chemistry
Year: 2015

The effect of the wide variety of plant lipids on membrane organization is still poorly understood.  The local amounts of phytosphingolipids and free and conjugated phytosterols control the relative proportion and spatial distribution of ordered domains.  Plant lipids differently modulate, alone or in combination, membrane heterogeneity.  Our results highlight how plant lipid diversity might drive the plasma membrane subcompartmentalization. The high diversity of the plant lipid mixture raises the question of their respective involvement in the definition of membrane organization. This is particularly the case for plant plasma membrane, which is enriched in specific lipids, such as free and conjugated forms of phytosterols and typical phytosphingolipids, such as glycosylinositolphosphoceramides. This question was here addressed extensively by characterizing the order level of membrane from vesicles prepared using various plant lipid mixtures and labeled with an environment sensitive probe. Fluorescence spectroscopy experiments showed that among major phytosterols, campesterol exhibits a stronger ability than b sitosterol and stigmasterol to order model membranes. Multispectral confocal microscopy, allowing spatial analysis of membrane organization, demonstrated accordingly the strong ability of campesterol to promote ordered domain formation and to organize their spatial distribution at the membrane surface. Conjugated sterol forms, alone and in synergy with free sterols, exhibit a striking ability to order membrane. Plant sphingolipids, particularly glycosylinositolphosphoceramides, enhanced the sterol induced ordering effect, emphasizing the formation and increasing the size of sterol dependent ordered domains. Altogether, our results support a differential involvement of free and conjugated phytosterols in the formation of ordered domains and suggest that the diversity of plant lipids, allowing various local combinations of lipid species, could be a major contributor to membrane organization in particular through the formation of sphingolipid sterol interacting domains.
Valuing Value in Innovation Ecosystems: How Cross Sector Actors Overcome Tensions in Collaborative Sustainable Business Model Development
Year: 2020

This article aims to uncover the processes of developing sustainable business models in innovation ecosystems. Innovation ecosystems with sustainability goals often consist of cross sector partners and need to manage three tensions: the tension of value creation versus value capture, the tension of mutual value versus individual value, and the tension of gaining value versus losing value. The fact that these tensions affect all actors differently makes the process of developing a sustainable business model challenging. Based on a study of four sustainably innovative cross sector collaborations, we propose that innovation ecosystems that develop a sustainable business model engage in a process of valuing value in which they search for a result that satisfies all actors. We find two different patterns of valuing value: collective orchestration and continuous search. We describe these patterns and the conditions that give rise to them. The identification of the two patterns opens up a research agenda that can shed further light on the conditions that need to be in place in order for an innovation ecosystem to develop effective sustainable business models. For practice, our findings show how cross sector actors in innovation ecosystems may collaborate when developing a business model around emerging sustainability oriented innovations.
PyFeat: a Python based effective feature generation tool for DNA, RNA and protein sequences
Venue: Bioinform.
Year: 2019

Extracting useful feature set which contains significant discriminatory information is a critical step in effectively presenting sequence data to predict structural, functional, interaction and expression of proteins, DNAs, and RNAs. Also, being able to filter features with significant information and avoid sparsity in the extracted features require the employment of efficient feature selection techniques. Here we present PyFeat as a practical and easy to use toolkit implemented in Python for extracting various features from proteins, DNAs, and RNAs. To build PyFeat we mainly focused on extracting features that capture information about the interaction of neighboring residues to be able to provide more local information. We then employ AdaBoost technique to select features with maximum discriminatory information. In this way, we can significantly reduce the number of extracted features and enable PyFeat to represent the combination of effective features from large neighboring residues. As a result, PyFeat is able to extract features from 13 different techniques and represent context free combination of effective features. The source code for PyFeat standalone toolkit and employed benchmarks with a comprehensive user manual explaining its system and workflow in a step by step manner are publicly available.  https:/github.com/mrzResearchArena/PyFeat/blob/master/RESULTS.md. AVAILABILITY Toolkit, source code, and manual to use PyFeat: https:/github.com/mrzResearchArena/PyFeat/