nils-herrmann/clean_scirepeval huggingface dataset:
The Relationship between High Flow Nasal Cannula Flow Rate and Effort of Breathing in Children
Venue: The Journal of pediatrics
Year: 2017

To use an objective metric of effort of breathing to determine optimal high flow nasal cannula (HFNC) flow rates in children <3 years of age. Study design Single center prospective trial in a 24 bed pediatric intensive care unit of children <3 years of age on HFNC. We measured the percent change in pressure*rate product (PRP) (an objective measure of effort of breathing) as a function of weight indexed flow rates of 0.5, 1.0, 1.5, and 2.0 L/kg/minute. For a subgroup of patients, 2 different HFNC delivery systems (Fisher Paykel [Auckland, New Zealand] and Vapotherm [Exeter, New Hampshire] were compared.  Twenty one patients (49 titration episodes) were studied. The most common diagnoses were bronchiolitis and pneumonia. Overall, there was a significant difference in the percent change in PRP from baseline (of 0.5 L/kg/minute) with increasing flow rates for the entire cohort (P .001) with largest change at 2.0 L/kg/min 21% Subgroup analyses showed no significant difference in percent change in PRP from baseline when comparing the 2 different HFNC delivery systems (P .12) Patients =8 kg experienced a larger percent change in PRP as HFNC flow rates were increased (P .001) than patients >8 kg.  The optimal HFNC flow rate to reduce effort of breathing in infants and young children is approximately 1.5 2.0 L/kg/minute with more benefit seen in children =8 kg.
Active Learning for Domain Adaptation in the Supervised Classification of Remote Sensing Images
Venue: IEEE Transactions on Geoscience and Remote Sensing
Year: 2012

This paper presents a novel technique for addressing domain adaptation (DA) problems with active learning (AL) in the classification of remote sensing images. DA models the important problem of adapting a supervised classifier trained on a given image (source domain) to the classification of another similar but not identical image (target domain) acquired on a different area. The main idea of the proposed approach is iteratively labeling and adding to the training set the minimum number of the most informative samples from the target domain, while removing the source domain samples that do not fit with the distributions of the classes in the target domain. In this way, the classification system exploits already available information, i.e. the labeled samples of source domain, in order to minimize the number of target domain samples to be labeled, thus reducing the cost associated to the definition of the training set for the classification of the target domain. In addition, we define a convergence criterion that allows the technique to stop the iterative AL process on the target domain without relying on the availability of a test set for it. This is an important contribution, as in operational applications, it is not realistic to assume that a test set for the target domain is available. Experimental results obtained in the classification of very high resolution and hyperspectral images confirm the effectiveness of the proposed technique.
A autoestima e o comportamento suicida em estudantes universitarios: uma revisao da literatura
Venue: Revista Eletronica Acervo Saude
Year: 2019

Compreender as relacoes entre a autoestima e o comportamento suicida em estudantes universitarios.  Trata se de estudo de revisao narrativa da literatura, onde o autor interpreta e analisa a literatura cientifica conforme seu julgamento critico. Este estudo foi realizado de forma nao sistematica, com coleta de dados nas bases de dados cientificas gratuitas disponiveis, em dezembro de 2018, com leitura na integra e analise critica.  Na universidade sao enormes as diferencas observadas em estudantes que possuem baixa e alta autoestimas. O risco do comportamento suicida se torna real na presenca da baixa autoestima. Identifica se na universidade um local de possibilidade para ocorrencia e desenvolvimento de baixa autoestima com consequente comportamento suicida. Conclusao: Conclui se que e real a necessidade de desenvolvimento de acoes preventivas e de praticas especificas que visem a recuperacao da saude emocional dos estudantes universitarios.
PERSONALIZED CAMPAIGNS IN PARTY CENTRED POLITICS
Year: 2013

Social media like Facebook and Twitter place the focus on the individual politician rather than the political party, thereby expanding the political arena for increased for personalized campaigning. The need to use social media to communicate a personal image as a politician and to post personalized messages online seems less obvious in a party centred system such as the Norwegian. Within this framework, the personalized and dialogical aspects of social media may be contradicted by the political parties' structural communication strategies. The article uses data from interviews and status updates from two Norwegian election campaigns and asks for what purposes Norwegian politicians use social media as a tool for political communication. The findings show that politicians' report both marketing and dialogue with voters as motives for their social media use and their practices varied, too. Politicians' reported motive to use social media for marketing purposes was reflected in their actual use. The preferred social media platform for marketing purposes was Facebook. Twitter was more used for continuous dialogue compared to Facebook. Social media marketing was personalized and involved private exposure and individual initiatives. The article concludes by indicating hypotheses and need for further research.
Occlusion Free Road Segmentation Leveraging Semantics for Autonomous Vehicles
Venue: Sensors
Year: 2019

The deep convolutional neural network has led the trend of vision based road detection, however, obtaining a full road area despite the occlusion from monocular vision remains challenging due to the dynamic scenes in autonomous driving. Inferring the occluded road area requires a comprehensive understanding of the geometry and the semantics of the visible scene. To this end, we create a small but effective dataset based on the KITTI dataset named KITTI OFRS (KITTI occlusion free road segmentation) dataset and propose a lightweight and efficient, fully convolutional neural network called OFRSNet (occlusion free road segmentation network) that learns to predict occluded portions of the road in the semantic domain by looking around foreground objects and visible road layout. In particular, the global context module is used to build up the down sampling and joint context up sampling block in our network, which promotes the performance of the network. Moreover, a spatially weighted cross entropy loss is designed to significantly increases the accuracy of this task. Extensive experiments on different datasets verify the effectiveness of the proposed approach, and comparisons with current excellent methods show that the proposed method outperforms the baseline models by obtaining a better trade off between accuracy and runtime, which makes our approach is able to be applied to autonomous vehicles in real time.
Estimation of thermal conductivity of Al2O3/water (40% ethylene glycol (60% by artificial neural network and correlation using experimental data
Year: 2016

In this work, the estimation of thermal conductivity of Al 2 O 3 nanoparticles in water (40% ethylene glycol (60% has been investigated. An empirical relationship has been proposed based on experimental data and in terms of temperature and volume fraction. Besides, a model has been presented using feedforward multi layer perceptron (MLP) artificial neural network (ANN) The presented correlation relationship estimates empirical data very well. However, artificial neural network has a higher regression coefficient and lower error compared to the presented relationship. After examining different structures of neural network with different transfer functions, a structure was selected with two hidden layers and 5 neurons in the first and second layers and tangent sigmoid transfer function for both layers. The results indicate that artificial neural networks can precisely estimate the experimental data of thermal conductivity of Al 2 O 3 /water (40% ethylene glycol (60% nanofluids.
Applications of rigged Hilbert spaces in quantum mechanics and signal processing
Year: 2016

Simultaneous use of discrete and continuous bases in quantum systems is not possible in the context of Hilbert spaces, but only in the more general structure of rigged Hilbert spaces (RHS) In addition, the relevant operators in RHS (but not in Hilbert space) are a realization of elements of a Lie enveloping algebra and support representations of semigroups. We explicitly construct here basis dependent RHS of the line and half line and relate them to the universal enveloping algebras of the Weyl Heisenberg algebra and su(1, 1) respectively. The complete sub structure of both RHS and of the operators acting on them is obtained from their algebraic structures or from the related fractional Fourier transforms. This allows us to describe both quantum and signal processing states and their dynamics. Two relevant improvements are introduced: (i) new kinds of filters related to restrictions to subspaces and/or the elimination of high frequency fluctuations and (ii) an operatorial structure that, starting from f.
Effect of frying on the palm oil quality attributes A review
Year: 2016

Frying is one of the most versatile food processing operations employed since antiquity. The establishment of this process is evidenced by a great consumption of fried food around the globe. Despite palm oil is extensively utilised in various frying applications, the preservation of its quality attributes as a result of thermal processing is still a concern to food processors and consumers. This article, therefore, aims to provide an overview of published studies on the behaviour of palm oil, in their pure form and blended with other oils, during frying at various processing conditions. In this review, publications associated to frying stability of palm based oils were considered to ascertain a series of oil quality indices i.e. free fatty acid, smoke point, peroxide and p anisidine values, vitamin E, induction period, fatty acid composition, colour, and polar and polymer compounds under prolonged thermal processing conditions. Stability of palmbased oil, however, is not solely dependent to the inherent properties of the oils themselves. Hence, the effects of operating conditions (oil temperature, cooking time, frying duration or cycle, oil replenishment, frying system and cookware materials) and food compositions are also discussed in this article.
Online Learning: from Blended Learning to Connected Learning with Content Curation
Year: 2019

Information and digital literacy is still poor in undergraduate students in France and elsewhere, although emphasized by UNESCO, OCDE and European Society 2020 as major competence for workers in the near future. Blended learning combines traditional teaching and self learning using internet resources, leading to develop autonomy of trainees. Content curation is still a recent concept with applications in marketing but less in use for teaching and learning in colleges and universities.  Implementation of content curation tools (Scoop.it preferred because of potential) for blended learning and information literacy training during 5 years of #400 french (and chinese in the context of Nancy Wuhan medical training program) students in two knowledge domains: immunology in medical university, geography in "classes preparatoires litteraires"  Teachers opened and maintained one or more general topics related to the discipline as well as topics focusing on annual examinations programs. Students opened and maintained during various periods of time (from months to years) topics of their choice in related areas. They were evaluated on number of posts, regularity of posting, commentaries and tagging, pictures, sharing on social networks and impact of their topic.  Content curation allowed teachers to select relevant resources in rapidly evolving topics and share them with students. Using curation, researchers followed scientific knowledge evolution, detected new topics, build interest networks and became thought leaders. Content curation allowed students to (1) acquire and develop information, media and digital literacy learning by practicing focused information research, (2) discover usage of diverse resources (primary documents, secondary information, databases, press releases. (3) develop critical minds about sources and contents. Content curation stimulated reading, analyzing and mastering digital information, helping create scientific watching competencies. Reading, tagging, commenting information in foreign languages helps students improve reading and writing fluency. Students were able to build information portfolios, create their digital identity, useful for recruiting interviews. Content curation should be used in teaching in the context of blended learning programs to train students and trainees for multimodal literacy as well as future work capacities, research competencies and lifelong learning.
Dual Role of a Fluorescent Peptidyl Probe Based on Self Assembly for the Detection of Heparin and for the Inhibition of the Heparin Digestive Enzyme Reaction.
Venue: ACS applied materials interfaces
Year: 2018

The detection of fluorescent probes for biomolecules and control of the function of a complex through a recognition process have not been investigated intensively. A fluorescent peptidyl probe (1) based on the self assembly stimulated by heparin was synthesized. The fluorescent probe with an aggregation induced emission fluorophore formed a self assembling complex with heparin, resulting in a sensitive and selective turn on response to heparin compared to its biological competitors. The detection limits for heparin were measured to be 138.0 pM (R2 0.976) in aqueous solution and 2.6 nM (R2 0.996) in aqueous solution containing human serum. Nanosized aggregates formed through the self assembly of the complex showed potent resistance against the heparin digestive enzyme. The dual role of the probe for the detection of heparin and the inhibition of heparinase mediated digestion through the recognition process was used for the real time monitoring of the enzyme activity of heparinase for the digestion of heparin. Furthermore, the dual role of the probe was applied for the detection of the oversulfated chondroitin sulfate contaminant in heparin.
A Review on Neural Turing Machine (NTM)
Venue: SN Comput. Sci.
Year: 2020

One of the significant objectives of artificial intelligence is to design learning algorithms that are executed on general purpose computational machines inspired by the human brain. Neural Turing Machine (NTM) is a step towards realizing such a computational machine. In the literature, a variety of approaches have been presented for the NTM; however, there is no existing comprehensive survey and taxonomy for NTM methods. This article presents an overview of taxonomies characterizing the critical concepts of the NTM through a comprehensive survey on the related research activities. This in depth analysis of taxonomies can provide researchers, designers, and application developers with a clear guideline to compare NTM methods. The taxonomy of machine learning, neural networks, and the Turing machine is introduced. The NTM is also inspected in terms of concepts, structure, implemented tasks, and related works. The article further presents research discussions and future challenges in this area.
Efficient Implementation of a Generic Coprocessor for Elliptic Curve Cryptography on Reconfigurable Hardware
Year: 2015

This project is motivated by the need for a flexible and secure ECC implementation on FPGAs at Rohde Schwarz SIT GmbH. The coprocessor shall handle elliptic curves over Fp, p 3, prime with a verifiable pseudo random prime structure, so not only NIST curves should be possible. Different bit lengths of p must be supported. One main task is the use of DSPs for fast arithmetic computations as much as possible to save other resources on the FPGA. Particularly, the modular multiplication was examined more detailed. It is solved with the CIOS algorithm, a Montgomery multiplication algorithm design especially for hardware. The hardware design of the CIOS algorithm implemented in Mentens' PhD thesis was the basis for our design. For secure and efficient implementation of ECC scalar multiplication a special parallelized Montgomery ladder is used which uses projective coordinates in (X Z) representation. The coprocessor must be protected/protectable against all kinds of Side Channel Analysis. Montgomery ladder is used against SPA. Randomized projetive coordinates and prime randomization were supported as a countermeasure against DPA. We implemented the basic design of Mentens and modified it in various ways: First, the 16x16 multiplier has been replaced by a 17x17 multiplier. Then the full capabilities of multipliers on modern FPGAs has been used, i. e. a 17x24 multiplier. The design and implementation produced with various optimizations regarding the number of DSPs used and the number of pipeline stages. The coprocessor designed provides the improved Montgomery multiplication by Walter, modular addition/subtraction as well as modular inversion. The designed coprocessor is faster than Mentens' which is the most comparable design. Comparison with other implementations are not easy because of missing either countermeasures against SCA, implementations for curves over F2m, or approaches that do not allow flexible p.
A Diophantine Set Driven Approach to Part Sets Cycle Time Scheduling and Repetitive Flow Balancing
Venue: AUTOMATION
Year: 2018

The problem studied in this paper is a cyclic job shop problem with multiple AGVs. Job batches, which follow specific production routes, are processed in order of their operations on multiple machines with standard processing times, and the fleet of AGVs perform the transportation operations of moving job batches between the workstations. In this system, part sets of items are produced at fixed time intervals. In the adopted model, a layer of station to station transport, which is a network of local loops connecting subsets of workstations serviced cyclically by dedicated AGVs, and a layer of repetitive production flows which comprise task batches following a given set of production routes are distinguished. A set of nonlinear Diophantine equations describes the relationship between the elements of the structure of the system and its potential behavior. The resulting Diophantine sets enable fast evaluation, although limited to integers, of production flow parameters including part sets, cycle time and takt time, as well as repetitive flow balancing aimed at maximization of the rate of system resource utilization. The high efficiency of the proposed Diophantine set driven approach is a consequence of omitting the time consuming calculation of task timing and sequencing.
Disability citizenship and independence through mobile technology? A study exploring adoption and use of a mobile technology platform
Year: 2016

This article explores the use of a mobile technology platform as experienced by people with disability, their significant other and service providers. An interpretive qualitative study design was adopted involving observations and interviews. The data were analysed using the combined lenses of the social approach to disability and the PHAATE model which represents the factors for consideration in service design for assistive technology. The findings suggest that the adoption of the technology by those in the study could be characterised by a typology of users. The implications of the typology are discussed together with the influencing factors that affected social participation and disability citizenship.
Parsimony and Complexity: Developing and Testing Theories of Affective Intelligence
Year: 2011

The theory of affective intelligence posits that an individual's emotions help govern a reliance on political habits or, alternatively, deliberation and attention to new political information. Some of the evidence adduced draws on the fact that voters who are anxious about their own party's candidate do not rely blindly on their partisanship but instead consider policy and personality when they vote. In a provocative paper, Ladd and Lenz (2008) argue that emotions reflect an evaluative judgment, akin to likes and dislikes, that has little to say about attention and habit. Here we examine the ANES data from 1980 to 2004 and find that the affective intelligence theory's original findings remain statistically robust. On closer examination, we also learn that Ladd and Lenz reformulated the theoretical test by using a different operationalization of affect and a different dependent variable and found results at variance from ours. We find it an inappropriate test. In the end, we agree with Ladd and Lenz that cross sectional data cannot crisply test the short term impact of emotions on attention and habit and concur that ultimately experiments will move the debate forward. We further observe that Brader's (2005, 2006) powerful field experiments explicitly test the special effect of emotions on attention and judgment and support the affective intelligence model.
The Application of Sliding Micrometer in Pile Strain Testing
Year: 2007

Field monitoring is demanded in testing pile bearing capacity,so the reliability of test methods and the accuracy of monitoring data are very important.In this paper,a kind of new instrument named Sliding Micrometer as well as its principle and the application in pile testing,is introduced.The field of its application relates to the measurement for the inner deformation distribution of tested pile.Projects show it is a kind of high precision and easy to use instrument with extensity prospect in Geotechnical engineering.
Systematic review of methods used to study the intersecting impact of sex and social locations on health outcomes
Venue: SSM population health
Year: 2020

Independent health impacts of sex or social circumstances are well studied, particularly among older adults. Less theorized or examined is how combinations or intersections of these underpin differential health effects. Nevertheless, and often without naming it as such, an intersectional framework aligns with studies of social determinants of health, life course epidemiology and eco epidemiology. In this systematic review we examined and aimed to identify research methods used to operationalize, whether intentionally or inadvertently, interconnected effects of sex and social locations on health outcomes for 45+ year olds.  Using broad search terms, numerous databases, and following Prisma guidelines, 732 of 9214 papers initially identified, met inclusion criteria for full review.  Of the 501 papers included after full review, methods used in considering intersections of sex and social circumstances/location(s) included regression (112 of 365 papers) growth curves (7 of 22) multilevel (15 of 25) decomposition (6 of 9) mediation (10 of 17) structural equation modelling (23 of 25) and other (2 of 3) Most (n 157) approximated intersectional analyses by including interaction terms or sex stratifying results.  Few authors used the inherent strength of some study methods to examine intersecting traits. As even fewer began with an intersectionality framework their subsequent failure to deliver cannot be faulted, despite many studies including data and methodologies that would support intersectional analyses. There appeared to be a gap, not in analytic potential but rather in theorizing that differential distributions of social locations describe heterogeneity within the categories 'men' and 'women' that can underlie differential, gendered effects on older adults' health. While SEM, mediation and decomposition analyses emerged as particularly robust methods, the unexpected outcome was finding how few researchers consider intersectionality as a potential predictor of health.