nils-herrmann/clean_scirepeval huggingface dataset:
Are Query Based Ontology Debuggers Really Helping Knowledge Engineers?
Venue: Knowl. Based Syst.
Year: 2019

Real world semantic or knowledge based systems can become large and complex, e.g. in the biomedical domain. Tool support for the localization and repair of faults within knowledge bases of such systems can therefore be essential for their practical success. Correspondingly, a number of knowledge base debugging approaches, in particular for ontology based systems, were proposed in recent years. Query based debugging is a comparably recent interactive approach that localizes the true cause of an observed problem by asking knowledge engineers a series of questions. Concrete implementations of this approach exist, such as the OntoDebug plug in for the ontology editor Protege. To validate that a newly proposed method is favorable over an existing one, researchers often rely on simulation based comparisons. Such an evaluation approach however has certain limitations and often cannot fully inform us about a method's true usefulness. We therefore conducted a range of user studies to assess the practical value of query based ontology debugging. One main insight from the studies is that the considered interactive approach is indeed more efficient than an alternative algorithmic debugging based on test cases. We also observed that users frequently made errors in the process, which highlights the importance of a careful design of the queries that users need to answer.
Educational poetics: an aesthetic approach to action research
Year: 2008

In this article, Gitlin and Peck argue that much of the development of action research has been based on a reconstructed view of science (i.e. a science that is more contextual, less law like, less causal, but still accurately represents reality and is teacher centered as opposed to researcher centered) In contrast to this reconstructed view of science, the authors suggest it is time to look at the limits and possibilities of basing action research on an aesthetic view of knowledge production. Gitlin and Peck do so by providing an outline of educational poetics that uses imagination and creativity to unearth and challenge limiting conceptions of commonsense as the action research participants enter into a freedom quest, to utilize imagination and creativity, our inherent human potential, to think beyond the categories and codes that tie us to the status quo.
Prevalence and genomic characteristics of zoonotic gastro intestinal pathogens and ESBL/pAmpC producing Enterobacteriaceae among Swedish corvid birds
Venue: Infection ecology epidemiology
Year: 2019

Wild birds pose a potential threat to animal and human health by spreading infectious diseases. In the present study, we studied the occurrence of bacterial zoonotic pathogens as well as enterobacteria with transferrable antimicrobial resistance genes among Swedish corvids.  Intestines from 66 jackdaws, crows, rooks and magpies from the vicinity of livestock farms at 14 locations in 7 counties were analysed by direct culture or PCR screening followed by culture. Isolates were investigated by whole genome sequencing.  Campylobacter jejuni were detected in 82% and Yersinia in 3% of the birds. ESBL producing E. coli were found in one sample (2% and carried blaCTX M 55. No Enterobacteriaceae with transferable carbapenem resistance were identified. No Salmonella or E. coli O157:H7 were found, but PCR analysis for enterohaemorrhagic E. coli virulence genes revealed 35% positive samples for intimin, 9% for verotoxin 1 and 17% for verotoxin 2. C. jejuni isolates from corvids were compared to previously published isolates from Swedish sources by multi locus sequence typing based on genome sequences. All corvid C. jejuni isolates formed a cluster, intermingled with human and chicken isolates. Our results indicate that C. jejuni is ubiquitous among Swedish corvid birds, with sporadic transmission to poultry and humans.
DSM IV Axis II personality disorders and suicide and attempted suicide in China.
Venue: The British journal of psychiatry the journal of mental science
Year: 2016

There are meagre data on Axis II personality disorders and suicidal behaviour in China.  To describe the prevalence of Axis II personality disorders in suicides and suicide attempts in China and to estimate risk for these outcomes associated with personality disorders.  People who died by suicide (n 151) people who attempted suicide (n 118) and living community controls (n 140) were randomly sampled from four Chinese counties and studied using the Structured Clinical Interviews for DSM IV TR Axis I Disorders (SCID I) and Axis II Personality Disorders (SCID II) We also determined the prevalence of subthreshold versions of ten DSM IV personality disorders.  Axis II personality disorders were present in 7% of the suicide group, 6% of the suicide attempt group and 1% of the control group. Threshold and subthreshold personality disorders had adjusted odds ratios (point estimates) in the range of 2.7 8.0 for suicide and for suicide attempts.  Axis II personality disorders may confer increased risk for suicidal behaviour in China, but their low prevalence in the community and among people with suicidal behaviour suggests that other personality constructs such as select dimensional traits may be a more fruitful avenue for understanding and preventing suicide in China.
Gestion ambiental de suelos, agua y sedimentos contaminados con bifenilos policlorados (PCB's) y su potencial aplicacion en el Ecuador
Year: 2016

El presente proyecto de titulacion tiene como objetivo presentar en forma bibliografica varias alternativas de tratamiento de agua contaminada con PCB's, y determinar cual de ellas tiene mayor potencial de aplicacion en el Ecuador. Para el estudio de suelos contaminados se establece un protocolo de muestreo, realizado en una parroquia del sur de Quito que cuenta con su respectivo registro fotografico. Para determinar cuales son las mejores alternativas de tratamiento se utilizo el metodo de la Matriz Delphi con la intervencion de algunos expertos en el tema, obteniendo como resultados, que los procesos mas factibles de aplicacion en aguas contaminadas son la Degradacion electroquimica y la Fotocatalisis Heterogenea con TiO2 En el caso de suelos contaminados, los metodos de factible aplicacion son la incineracion en el exterior y la celda de seguridad, en ambos casos se presenta una logistica del proceso de transporte y un presupuesto general elaborado con empresas ecuatorianas que se encargan de la gestion de residuos peligrosos.
Usefulness of bedside testing for brain natriuretic peptide to identify right ventricular dysfunction and outcome in normotensive patients with acute pulmonary embolism.
Venue: The American journal of cardiology
Year: 2006

Echocardiographic right ventricular (RV) dysfunction is a well established prognostic indicator in patients with acute pulmonary embolism. However, the possibility of implementing a rapid and effective triage with biohumoral markers such as brain natriuretic peptide (BNP) may be of value. Sixty one patients with a first documented episode of acute pulmonary embolism without shock and previous left ventricular dysfunction were prospectively studied. All patients underwent echocardiography and rapid BNP testing on admission. Patients were followed up for in hospital death, progression to shock, and nonfatal pulmonary embolism recurrence. Overall, 35 patients (57% had echocardiographic evidence of RV dysfunction on admission, and its prevalence increased progressively with increasing levels of BNP. A BNP level <85 pg/ml was highly accurate in excluding RV dysfunction. No patient in the lower tertile of BNP values (1.1 to 85.0 pg/ml) had RV dysfunction, compared with 75% in the middle tertile (88.7 to 487.0 pg/ml) and 100% in the upper tertile (527 to 1,300 pg/ml) Overall, 11 patients (18% belonging to the upper tertile, progressed to shock during admission, 4 of whom died. The association of RV dysfunction with a BNP level in the upper tertile >or=527 pg/ml) showed incremental prognostic value over RV dysfunction alone (in hospital death and progression to shock were 55% and 31% respectively) In the present study, BNP represented a powerful predictor of in hospital clinical deterioration, with substantial incremental prognostic value over echocardiography alone.
Image reconstruction in reduced circular sinusoidal cone beam CT.
Venue: Journal of X ray science and technology
Year: 2009

Non circular scanning geometries such as helix or circular sinusoid have been used or proposed for cone beam computed tomography (CBCT) because they provide sufficient data for numerically stable and exact image reconstruction within the scanned volume. Analytic algorithms have been developed for image reconstruction from cone beam data acquired with a full scan circular sinusoidal trajectory. In this work, we propose an innovative imaging approach in which a reduced scan circular sinusoidal trajectory is used for acquiring data sufficient for exact 3D image reconstruction. A filtered backprojection (FBP) algorithm based on Pack Noo's reconstruction formula is applied for image reconstruction in reduced scan circular sinusoidal scans. We have conducted numerical studies to demonstrate the reduced scan approach and to validate the FBP reconstruction algorithm in the proposed approach. The proposed scanning method can contribute to increasing the throughput of a scanner, while improving the image quality compared to a conventional circular scan.
Activation of Mo and V oxides supported on ZSM 5 zeolite catalysts followed by in situ XAS and XRD and their uses in oxydehydration of glycerol
Year: 2020

This paper describes the activation and catalytic performance of a multifunctional catalyst consisting of mixed oxides of vanadium and molybdenum supported on an acidic ZSM 5 zeolite. The zeolite was wet impregnated with an aqueous solution containing a mixture of NH4VO3 and (NH4)6Mo7O24 precursors at a V/(Mo+V) molar ratio of 0.6. Evolution of the phases during activation (by calcination under 20% O2/He) was followed by synchrotron X ray diffraction (XRD) but detection of mixed oxides of MoxVyOz was difficult, due to the high degree of dispersion on the zeolite surface. On the other hand, X ray absorption spectroscopy (XAS) performed simultaneously at the Mo and V K edges enabled confirmation of formation of the MoV2O8 phase on the acidic ZSM 5 zeolite. The combination of the MoV2O8 phase and the zeolite acid sites produced a highly active catalyst for gas phase glycerol dehydration oxidation coupled reactions in which acrylic acid was the main product. The multifunctional catalyst presented only 6% of deactivation during a period of 8 h under glycerol stream, while the activities of the bulk mixed oxide and the pure ZSM 5 zeolite decreased by almost 20 and 31% respectively.
Mindfulness based interventions for women with breast cancer: an updated systematic review and meta analysis
Venue: Acta oncologica
Year: 2017

The aim of this meta analysis was to systematically update the evidence for mindfulness based stress reduction (MBSR) and mindfulness based cognitive therapy (MBCT) in women with breast cancer.  In October 2016, PubMed, Scopus, and Central were searched for randomized controlled trials on MBSR/MBCT in breast cancer patients. The primary outcome was health related quality of life. Secondary outcomes were fatigue, sleep stress, depression, anxiety, and safety. For each outcome, standardized mean differences (SMD/Hedges' g) and 95% confidence intervals (CI) were calculated. Risk of bias was assessed by the Cochrane risk of bias tool.  The Literature search identified 14 articles on 10 studies that included 1709 participants. The overall risk of bias was unclear, except for risk of low attrition bias and low other bias. Compared to usual care, significant post intervention effects of MBSR/MBCT were found for health related quality of life (SMD .21; 95%CI .04 .39] fatigue (SMD .28; 95%CI .43 to .14] sleep (SMD .23; 95%CI .40 to .05] stress (SMD .33; 95%CI .61 to .05] anxiety (SMD .28; 95%CI .39 to .16] and depression (SMD .34; 95%CI .46 to .21] Up to 6 months after baseline effects were significant for: anxiety (SMD .28; 95%CI .47 to .09] and depression (SMD .26; 95%CI .47 to .04] and significant for anxiety (SMD .21; 95%CI .40 to .03] up to 12 months after baseline. Compared to other active interventions, significant effects were only found post intervention and only for anxiety (SMD .45; 95%CI .71 to .18] and depression (SMD .39; 95%CI .65 to .14] However, average effects were all below the threshold of minimal clinically important differences. Effects were robust against potential methodological bias. Adverse events were insufficiently reported.  This meta analysis revealed evidence for the short term effectiveness and safety of mindfulness based interventions in women with breast cancer. However, their clinical relevance remains unclear. Further research is needed.
Slime mold inspired routing protocols for wireless sensor networks
Venue: Swarm Intelligence
Year: 2011

Many biological systems are composed of unreliable components which self organize effectively into systems that achieve a balance between efficiency and robustness. One such example is the true slime mold Physarum polycephalum which is an amoeba like organism that seeks and connects food sources and efficiently distributes nutrients throughout its cell body. The distribution of nutrients is accomplished by a self assembled resource distribution network of small tubes with varying diameter which can evolve with changing environmental conditions without any global control. In this paper, we exploit two different mechanisms of the slime mold's tubular network formation process via laboratory experiments and mathematical behavior modeling to design two corresponding localized routing protocols for wireless sensor networks (WSNs) that take both efficiency and robustness into account. In the first mechanism of path growth, slime mold explores its immediate surroundings to discover and connect new food sources during its growth cycle. We adapt this mechanism for a path growth routing protocol by treating data sources and sinks as singular potentials to establish routes from the sinks to all the data sources. The second mechanism of path evolution is the temporal evolution of existing tubes through nonlinear feedback in order to distribute nutrients efficiently throughout the organism. Specifically, the diameters of tubes carrying large fluxes of nutrients grow to expand their capacities, and tubes that are not used decline and disappear entirely. We adapt the tube dynamics of the slime mold for a path evolution routing protocol. In our protocol, we identify one key adaptation parameter to adjust the tradeoff between efficiency and robustness of network routes. Through extensive realistic network simulations and ideal closed form or numerical computations, we validate the effectiveness of both protocols, as well as the efficiency and robustness of the resulting network connectivity.
Antioxidants: Characterization, natural sources, extraction and analysis.
Venue: Food research international
Year: 2015

Recently many review papers regarding antioxidants from different sources and different extraction and quantification procedures have been published. However none of them has all the information regarding antioxidants (chemistry, sources, extraction and quantification) This article tries to take a different perspective on antioxidants for the new researcher involved in this field. Antioxidants from fruit, vegetables and beverages play an important role in human health, for example preventing cancer and cardiovascular diseases, and lowering the incidence of different diseases. In this paper the main classes of antioxidants are presented: vitamins, carotenoids and polyphenols. Recently, many analytical methodologies involving diverse instrumental techniques have been developed for the extraction, separation, identification and quantification of these compounds. Antioxidants have been quantified by different researchers using one or more of these methods: in vivo, in vitro, electrochemical, chemiluminescent, electron spin resonance, chromatography, capillary electrophoresis, nuclear magnetic resonance, near infrared spectroscopy and mass spectrometry methods.
Deep reinforcement learning for the control of conjugate heat transfer
Venue: J. Comput. Phys.
Year: 2021

This research gauges the ability of deep reinforcement learning (DRL) techniques to assist the control of conjugate heat transfer systems. It uses a novel, "degenerate" version of the proximal policy optimization (PPO) algorithm to train a neural network in optimizing said system only once per learning episode, and an in house stabilized finite elements environment combining variational multiscale (VMS) modeling of the governing equations, immerse volume method, and multi component anisotropic mesh adaptation to compute the numerical reward fed to the neural network. Several test cases of natural and forced convection are used as testbed for developing the methodology, that proves successful to alleviate the heat transfer enhancement related to the onset of convection in a two dimensional, differentially heated square cavity, and to improve the homogeneity of temperature across the surface of two and three dimensional hot workpieces under impingement cooling. Beyond adding value to the shallow literature on this subject, these findings establish the potential of single step PPO for reliable black box optimization of computational fluid dynamics (CFD) systems, and pave the way for future progress in the optimal control of conjugate heat transfer using this new class of methods.
Adaptive Optimal Control of Highly Dissipative Nonlinear Spatially Distributed Processes With Neuro Dynamic Programming
Venue: IEEE Transactions on Neural Networks and Learning Systems
Year: 2015

Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs) In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro dynamic programming (NDP) Initially, Karhunen Loeve decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton Jacobi Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion convection reaction process and applied to a temperature cooling fin of high speed aerospace vehicle, and the achieved results show its effectiveness.
High flow nasal cannula therapy beyond the perinatal period
Venue: Current opinion in pediatrics
Year: 2017

High flow nasal cannula (HFNC) is emerging as a means of oxygen delivery and respiratory support for a range of conditions outside the perinatal period. We aim to review the mechanisms of action and advantages of HFNC and to summarize current findings regarding clinical benefit in specific pediatric disease processes and in patients with significant respiratory distress. Recent findings Currently published studies outside the neonatal population demonstrate both safety and efficacy of this mode of respiratory support. Retrospective and prospective observational trials have shown improvements in oxygenation and respiratory distress, as well as reductions in the need for intubation in select patient populations. Randomized controlled trials are ongoing.  HFNC is emerging as a means of oxygen delivery and respiratory support across a wide range of pediatric conditions. Available data suggest that it is well tolerated by children and can have a favorable effect on clinical outcomes. Future research will better define optimal patient populations and best practices for use.
Efficient Stock Market Prediction Using Ensemble Support Vector Machine
Venue: Open Comput. Sci.
Year: 2020

Predicting stock price remains an important subject of discussion among financial analysts and researchers. However, the advancement in technologies such as artificial intelligence and machine learning techniques has paved the way for better and accurate prediction of stock price in recent years. Of late, Support Vector Machines (SVM) have earned popularity among Machine Learning (ML) algorithms used for predicting stock price. However, a high percentage of studies in algorithmic investments based on SVM overlooked the overfitting nature of SVM when the input dataset is of high noise and high dimension. Therefore, this study proposes a novel homogeneous ensemble classifier called GASVM based on support vector machine enhanced with Genetic Algorithm (GA) for feature selection and SVM kernel parameter optimisation for predicting the stock market. The GA was introduced in this study to achieve a simultaneous optimal of the diverse design factors of the SVM. Experiments carried out with over eleven (11) years' stock data from the Ghana Stock Exchange (GSE) yielded compelling results. The outcome shows that the proposed model (named GASVM) outperformed other classical ML algorithms (Decision Tree (DT) Random Forest (RF) and Neural Network (NN) in predicting a 10 day ahead stock price movement. The proposed (GASVM) showed a better prediction accuracy of 93.7% compared with 82.3% (RF) 75.3% (DT) and 80.1% (NN) It can, therefore, be deduced from the fallouts that the proposed (GASVM) technique puts up a practical approach feature selection and parameter optimisation of the different design features of the SVM and thus remove the need for the labour intensive parameter optimisation.
Indigenizing Science Education Curriculum Content using Concept Cartoons in Nigeria
Year: 2017

Scientific knowledge is very important as it is a shield against poisonous hands of global competitive economy. There is no doubt about it; societies operating at lower digital divide are at the verge of contracting neo modern enslavement. Information and Communication Technology (ICT) is dissolving both national and international geographical boundaries, revolutionizing the way information is sent, received, organized, analyzed and interpreted. This article highlights on the importance of considering the learners' cultural environment when designing ICT teaching and learning resources to suit our indigenous setting. However, the success of Information and Communication Technology revolution will not be complete until developing countries generate their content and build their own tools. This paper highlights on the importance of harnessing ICT resources to suit learners' cultural environment (Indigenized Concept Cartoons in Science Education) for intellectual restitution.