nils-herrmann/clean_scirepeval huggingface dataset:
Can proportional ventilation modes facilitate exercise in critically ill patients? A physiological cross over study
Venue: Annals of Intensive Care
Year: 2017

BackgroundEarly exercise of critically ill patients may have beneficial effects on muscle strength, mass and systemic inflammation. During pressure support ventilation (PSV) a mismatch between demand and assist could increase work of breathing and limit exercise. A better exercise tolerance is possible with a proportional mode of ventilation (Proportional Assist Ventilation, PAV+ and Neurally Adjusted Ventilatory Assist, NAVA) We examined whether, in critically ill patients, PSV and proportional ventilation have different effects on respiratory muscles unloading and work efficiency during exercise.MethodsProspective pilot randomized cross over study performed in a medico surgical ICU. Patients requiring mechanical ventilation >48 h were enrolled. At initiation, the patients underwent an incremental workload test on a cycloergometer to determine the maximum level capacity. The next day, 2 15 min exercise, at 60% of the maximum capacity, were performed while patients were randomly ventilated with PSV and PAV+ or NAVA. The change in oxygen consumption (DVO2, indirect calorimetry) and the work efficiency (ratio of DVO2 per mean power) were computed.ResultsTen patients were examined, 6 ventilated with PSV/PAV+ and 4 with PSV/NAVA. Despite the same mean inspiratory pressure at baseline between the modes, baseline VO2 (median, IQR) was higher during proportional ventilation (301 ml/min, 270 342) compared to PSV (249 ml/min, 206 353) Exercise with PSV was associated with a significant increase in VO2 (DVO2, median, IQR) (77.6 ml/min, 59.9 96.5) while VO2 did not significantly change during exercise with proportional modes (46.3 ml/min, 5.7 63.7, p 0.05) As a result, exercise with proportional modes was associated with a better work efficiency than with PSV. The ventilator modes did not affect patient's dyspnea, limb fatigue, distance, hemodynamics and breathing pattern.ConclusionsProportional ventilation during exercise results in higher work efficiency and less increase in VO2 compared to ventilation with PSV. These preliminary findings suggest that proportional ventilation could enhance the training effect and facilitate rehabilitation.
New insights into Prevotella diversity and medical microbiology.
Venue: Future microbiology
Year: 2010

In light of recent studies based on cultivation independent methods, it appears that the diversity of Prevotella in human microbiota is greater than was previously assumed from cultivation based studies, and that the implication of these bacteria in several human diseases was unrecognized. While some Prevotella taxa were found during opportunistic infections, changes in Prevotella abundance and diversity were discovered during dysbiosis associated diseases. As member of the microbiota, Prevotella may also be considered as a reservoir for resistance genes. Greater knowledge on Prevotella diversity, as well as new insights into its pathogenic potential and implication in dysbiosis are expected from the use of human microbe identification microarrays, from whole genome sequence analyse, and from the NIH Human Microbiome Project data. New approaches, including molecular based methods, could contribute to improve the diagnosis of Prevotella infections.
The Effect of Influencer Marketing on Consumers' Brand Admiration and Online Purchase Intentions: An Emerging Market Perspective
Year: 2019

This paper focuses on consumer electronics products and observes the comparative effect of celebrity vis a vis expert influencers on consumers' online purchase intentions. The mediating role played by brand admiration and brand attitude between influencer marketing and online purchase intentions are tested. The moderating role played by message involvement between influencer marketing and brand attitude is also observed. The survey method was employed to conduct this research, and data were collected from 438 respondents. The proposed hypotheses were tested using structural equation modeling, hierarchical regression analysis, and Hayes process method. The results submit that there is a definite advantage in choosing an expert influencer over an attractive celebrity influencer while planning the marketing communications of consumer electronics products. The mediating role of brand attitude and brand admiration is empirically evident. The moderating effect of involvement is also established.
Legitimite, omnivorite et eclectisme: gouts et degouts en matiere d'ameublement et de decoration domestique. Etude qualitative aupres de jeunes representants des classes moyennes superieures
Year: 2018

Resume La theorie de la legitimite culturelle telle que proposee par Pierre Bourdieu a suscite de nombreuses critiques, qui ont donne lieu a de nouveaux developpements theoriques. Sans veritablement s'affranchir des theses enoncees dans La Distinction, le modele de l'omnivorite initie par Richard Peterson et celui de l'eclectisme defendu par Olivier Donnat ont, entre autres, passablement insiste sur la tolerance des elites et leur inclination a esthetiser la culture populaire Nous appuyant sur une recherche qualitative conduite en Suisse romande, notre propos est de discuter ces theories en prenant pour objet d'etude les gouts en matiere d'ameublement et de decoration domestique.
Types of Lamp for Homework and Myopia among Chinese School Aged Children
Venue: Ophthalmic epidemiology
Year: 2018

We aim to determine the association of the types of lamp for homework including incandescent lamp, fluorescent lamp, and light emitting diode (LED) lamp with the prevalence of myopia in Chinese children.  2346 grade 7 students from ten middle schools (93.5% response rate) aged 13 to 14 years in Mojiang, a small county located in Southwestern China, participated in the study. Refractive error was measured with cycloplegia using an autorefractor by optometrists or trained technicians. An IOL Master was used to measure ocular biometric parameters including axial length (AL) Information regarding the types of lamp for homework af``ter schools was collected by questionnaires.  Of all the study participants, 693 (29.5% were affected by myopia, with the prevalence estimates being higher in girls (36.8% 95% confidence interval [CI] 34.0, 39.6) than in boys (22.8% 95% CI: 20.4, 25.1) (P 0.001) After adjusting for potential confounders such as gender, height, parental history of myopia, time on computer use, time on watching TV, time outdoors, and time on reading and writing, participants using LED lamps for homework had a more myopic refractive error and a longer AL compared with those using incandescent or fluorescent lamps. There were no significant differences in myopia prevalence between children using incandescent and fluorescent lamps for homework. The population attributable risk percentage for myopia associated with using LED lamps for homework after schools was 11.2%  Using LED lamps for homework after schools might contribute to the development of myopia among school aged children.
Casas, casos y cosas: la herencia de Juan Deibe o la poesia que humaniza un protocolo notarial
Year: 2008

Es posible que el amable lector, si apuesta por llegar a la ultima linea, pueda preguntarse quien es este personaje, si verdaderamente ha llegado a existir o es invencion de una mente fantasiosa. El ficticio personaje es real valga la paradoja o lo ha sido y habita en muchas de las ancestrales casas brigantinas. Podremos encontrarlo y a su vera, muchos mas conciudadanos con variados patronimicosaferrado a los anaqueles de los archivos notariales, en donde documentados papeles permaneceran ocultos en carcomidos arcones de madera. Tambien es posible que, hoy por hoy, haya desaparecido este tipo de paisanaje o que su modus operandi se encuentre desfasado. La interpretacion de esta historia que ahora desentranamos solo se ha podido deducir a partir de datos recogidos pacientemente a lo largo de un documentado sondeo y, si bien, cualquier investigacion requiere una parte bibliografica o citas a pie de pagina, aqui ha sido desestimado en aras de una mayor claridad y una mas facil, desenfadada y comprensiva lectura. En mi alejada infancia, acompanando a mi padre a los archivos, con soltura me movia entre legajos y viejos libracos prenados de sentencias manuscritas por escrupulosos Casas, casos y cosas
miR 125b 1 and miR 378a are predictive biomarkers for the efficacy of vaccine treatment against colorectal cancer
Venue: Cancer science
Year: 2017

Many clinical trials of peptide vaccines have been conducted. However, these vaccines have provided clinical benefits in only a small fraction of patients. The purpose of the present study was to explore microRNAs (miRNAs) as novel predictive biomarkers for the efficacy of vaccine treatment against colorectal cancer. First, we carried out microarray analysis of pretreatment cancer tissues in a phase I study, in which peptide vaccines alone were given. Candidate miRNAs were selected by comparison of the better prognosis group with the poorer prognosis group. Next, we conducted microarray analysis of cancer tissues in a phase II study, in which peptide vaccines combined with chemotherapy were given. Candidate miRNAs were further selected by a similar comparison of prognosis. Subsequently, we carried out reverse transcription PCR analysis of phase II cases, separating cancer tissues into cancer cells and stromal tissue using laser capture microdissection. Treatment effect in relation to overall survival (OS) and miRNA expression was analyzed. Three miRNA predictors were negatively associated with OS: miR 125b 1 in cancer cells (P 0.040) and miR 378a in both cancer cells (P 0.009) and stromal cells (P 0.001) Multivariate analysis showed that expression of miR 378a in stromal cells was the best among the three predictors (HR, 2.730; 95% CI, 1.027 7.585; P 0.044) In conclusion, miR 125b 1 and miR 378a expression might be considered as novel biomarkers to predict the efficacy of vaccine treatment against colorectal cancer.
Cyber Espionage and International Law. By Russell Buchan. Oxford: Hart, 2018 (Book Review)
Year: 2019

In 2015, then US President Barack Obama referred to cyberspace as the "new Wild West" vast, lawless, and without a sheriff in sight. Given these qualities, it is unsurprising that actors leverage cyberspace to perpetrate crime, terrorism, foreign influence, and espionage with increasing effectiveness. Meanwhile, the international community has struggled to find common ground on the application, let alone enforcement, of international law in cyberspace. While there have been a number of high level commitments made by allied states to work together to develop "norms of cyberspace," the prominent and decade long effort of the United Nations Group of Governmental Experts to address state behaviour in cyberspace collapsed in 2017 due to a lack of consensus. Two separate and open ended working groups have since taken its place; one effort led by the United States, the other by Russia. In his text, Cyber Espionage and International Law, Russell Buchan not only takes on the notion that cyberspace is a lawless domain, but he also challenges the oft repeated assertion that state sponsored espionage is lawful under international law.
Towards Scalable Image Classifier Learning with Noisy Labels via Domain Adaptation
Year: 2020

In this chapter we focus on learning image classifiers with noisy labels through domain adaptation. Existing approaches for learning image classifiers with noisy labels using human supervision are generally difficult to scale to large set of classes as manual labeling images for all classes are expensive and time consuming. Approaches that address noisy labels without manual labeling efforts are scalable but less effective in lack of reliable supervision. Transfer learning reconciles this conflict through transferring knowledge from classes with exemplary human supervision (source domains) to classes where data are not manually verified (target domains) relaxing the requirement of human efforts. In this chapter, we introduce a transfer learning set up for tackling noisy labels, and review CleanNet, the first neural network model that practically implements this set up, and explore future directions of this topic.
MovieNet: A Holistic Dataset for Movie Understanding
Venue: ECCV
Year: 2020

Recent years have seen remarkable advances in visual understanding. However, how to understand a story based long video with artistic styles, e.g. movie, remains challenging. In this paper, we introduce MovieNet a holistic dataset for movie understanding. MovieNet contains 1,100 movies with a large amount of multi modal data, e.g. trailers, photos, plot descriptions, etc. Besides, different aspects of manual annotations are provided in MovieNet, including 1.1M characters with bounding boxes and identities, 42K scene boundaries, 2.5K aligned description sentences, 65K tags of place and action, and 92K tags of cinematic style. To the best of our knowledge, MovieNet is the largest dataset with richest annotations for comprehensive movie understanding. Based on MovieNet, we set up several benchmarks for movie understanding from different angles. Extensive experiments are executed on these benchmarks to show the immeasurable value of MovieNet and the gap of current approaches towards comprehensive movie understanding. We believe that such a holistic dataset would promote the researches on story based long video understanding and beyond. MovieNet will be published in compliance with regulations at this https URL.
Making Biosciences Visible for Popular Consumption: Approaching Image Text Relations in Newscientist.com Through a Critical Multimodal Analysis
Year: 2019

Salience or visibility of science related issues can be strategically projected by means of linguistic and visual resources. This article presents a methodology for examining the relations between the textual properties of popular science discourse and the visual features of accompanying images. The advantages of this approach are demonstrated through a multimodal analysis of a sample of biomedical articles from New Scientist, which reveals the frequency and distribution of selected properties of visual images, typical aspects of layout, attributed functions of the images, and their relation to the text. Humanization, domestication, and aesthetization are dominant discursive strategies of popularity driven science journalism.
The Effect of SBSN, ISSI, Inflation and BI 7 DAY REPO Rate Toward Net Asset Value of Islamic Mutual Funds in 2016 2019
Year: 2020

This research aimed to analyze the effect of SBSN, ISSI, Inflation and BI 7 Day Repo Rate toward Net Asset Value (NAB) Data used in this research were data of 2016 2019. The research method used multiple linear regression using Eviews 9 data processing. The results of the research showed that the t test statistic of SBSN and ISSI had a positive effect toward NAV with probability values of 0.0462 and 0.0000 <0.05. BI 7 Day Repo Rate had a negative effect with a probability value of 0.0365 <0.05. Furthermore, for inflation, it had no effect toward NAV because the probability was 0.3159> 0.05.
Automatic Building Extraction on High Resolution Remote Sensing Imagery Using Deep Convolutional Encoder Decoder With Spatial Pyramid Pooling
Venue: IEEE Access
Year: 2019

Automatic extraction of buildings from remote sensing imagery plays a significant role in many applications, such as urban planning and monitoring changes to land cover. Various building segmentation methods have been proposed for visible remote sensing images, especially state of the art methods based on convolutional neural networks (CNNs) However, high accuracy building segmentation from high resolution remote sensing imagery is still a challenging task due to the potentially complex texture of buildings in general and image background. Repeated pooling and striding operations used in CNNs reduce feature resolution causing a loss of detailed information. To address this issue, we propose a light weight deep learning model integrating spatial pyramid pooling with an encoder decoder structure. The proposed model takes advantage of a spatial pyramid pooling module to capture and aggregate multi scale contextual information and of the ability of encoder decoder networks to restore losses of information. The proposed model is evaluated on two publicly available datasets; the Massachusetts roads and buildings dataset and the INRIA Aerial Image Labeling Dataset. The experimental results on these datasets show qualitative and quantitative improvement against established image segmentation models, including SegNet, FCN, U Net, Tiramisu, and FRRN. For instance, compared to the standard U Net, the overall accuracy gain is 1.0% (0.913 vs. 0.904) and 3.6% (0.909 vs. 0.877) with a maximal increase of 3.6% in model training time on these two datasets. These results demonstrate that the proposed model has the potential to deliver automatic building segmentation from high resolution remote sensing images at an accuracy that makes it a useful tool for practical application scenarios.
An overview of motor skill performance and balance in hearing impaired children
Venue: Italian journal of pediatrics
Year: 2011

Childhood hearing impairment is a common chronic condition that may have a major impact on acquisition of speech, social and physical development. Numerous literature states that injury to the vestibular organs may result in accompanying balance and motor development disorders. But still postural control and motor assessments are not a routine procedure in hearing impaired children. Hence, we aim to provide an overview on motor skill performance and balance in hearing impaired children.
A Mask Detection System Based on Yolov3 Tiny
Year: 2020

Currently, there is a global outbreak of novel coronavirus pneumonia, which infected many people. One of the most efficient ways to prevent infection is to wear a mask. Thus, mask detection, which essentially belongs to object detection is meaningful for the authorities to prevent and control the epidemic. After comparing different methods utilized in object detection and conducting relevant analysis, YOLO v3 tiny is proved to be suitable for real time detection.
Adaptive Robust Nonlinear Active Suspension Control Using an Observer Based Modified Sliding Mode Interval Type 2 Fuzzy Neural Network
Venue: IEEE Transactions on Intelligent Vehicles
Year: 2020

Ride comfort and road holding are two substantial performance criteria related to the suspension system of road vehicles. These performance criteria are critical in controller design and chassis stability of automated driving vehicles. Control demands in terms of accuracy, quick response and robustness to matched and mismatched uncertainties are suggestive of employing adaptive robust controllers. Herein, a state observer based modified sliding mode interval fuzzy type 2 neural network (FT2NN) controller is designed to suppress the vibrations from a typical rough terrain imposed to the nonlinear suspension system of the vehicles. The nonlinear system dynamics are estimated using the universal approximation capacity of the neuro fuzzy type 2 approach and the states are obtained by the adaptive robust state observer. The membership functions (MFs) of the fuzzy type 2 system are employed to deal with the uncertainties through variable mean and variances for upper and lower MFs. Furthermore, the proposed controller has the advantage of relaxing the condition for the approximation error boundaries while the estimation step is utilized to observe the boundaries adaptively. A new adaptive compensator is employed to withstand the effect of the external disturbance, the approximation errors related to the unknown nonlinear functions and state estimations. The results obtained from the proposed controller are suggestive of the higher effectiveness of the proposed controller compared to the tested Neuro PID controller, and also the passive suspension system. The high fidelity MSC ADAMS based co simulations were implemented to validate the practicality of the proposed controller.
Integrated co pyrolysis and coating for the synthesis of a new coated biochar based fertilizer with enhanced slow release performance
Year: 2020

Although biochar based fertilizers prepared by the co pyrolysis of biomass and other nutrients containing feedstocks have been extensively demonstrated to be promising slow release fertilizers, a further improvement of their slow release performance is still highly required. Here, new coated biochar based slow release fertilizers (CSRFs) by the integrated co pyrolysis and coating technology. The results indicate that the application of coating to the surface of biochar based slow release fertilizers (BSRFs) derived from the co pyrolysis of cotton straw, Mg3(PO4)2 and bentonite can significantly improve the slow release performance. The cumulative release concentration of P is found to be 1.98 g/L from BSRFs within 30 days, while the maximum cumulative release concentration of P from CSRFs is only 0.82 g/L. The P release rate constants of CSRFs are only about half of those of BSRFs. In addition, the as prepared CSRFs exhibit superior degradability compared to BSRFs, and 35.21% of CSRFs is degraded within 60 days, which is much higher than that of BSRFs. Finally, pot experiments reveal that pepper seedlings fertilized by CSRFs grow much better than those fertilized by BSRFs.
Analysis of risk management tools applicable in managing farm risks: A literature review
Year: 2015

The objective of this study was to list and analyse risk management tools applicable in managing farm risks. A literature search of several large literature databases was conducted. By using risk management related keywords, a total of 13,559 articles discussing risk management were identified. Of these, 157 articles were selected for closer analysis applicable to dairy, cattle, pig or crop production. Both journal articles and book chapters in English were included. The articles were categorized based on the applied risk focus and type of risk management tools presented. In accordance with this, potential farm risk management tools were searched from the research studies associated with production, assets, economics and finance, human health and safety, and the environmental risks on farms. An important outcome of the study was a tool case for farm risk management stages, in which either the potential farm risk tools can each be used to address a single risk or the tools can be holistically applied. Farmers face multi risk management demands, but comprehensive literature studies on multi risk management tools on farms have been rare. Farm risk management tools and information provided to farmers are not at a sufficient level if we compare them to the current risks and social demands that farmers are facing. The possible farm risks should be clarified to farmers that they can identify them on farms. Furthermore, in order to integrate farm risk management tools, the links between the risks should be made visible among farm operations and farm production processes. Complexity and usability are future challenges in the further development of tools for managing farm risks. Applying the new farm risk tools in a sustainable manner requires farm managers to adopt new knowledge management techniques. Education programmes are needed to address the new skills that are required, and communication and co operation between different research disciplines is also necessary.