bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correction-free force calibration for magnetic tweezers experiments
Authors: Ostrofet Eugen , Papini Flávia Stal , Dulin David 
Published: October 2018

AbstractMagnetic tweezers are a powerful technique to perform high-throughput and high-resolution force spectroscopy experiments at the single-molecule level. The camera-based detection of magnetic tweezers enables the observation of hundreds of magnetic beads in parallel, and therefore the characterization of the mechanochemical behavior of hundreds of nucleic acids and enzymes. However, magnetic tweezers experiments require an accurate force calibration to extract quantitative data, which is limited to low forces if the deleterious effect of the finite camera open shutter time (τsh) is not corrected. Here, we provide a simple method to perform correction-free force calibration for high-throughput magnetic tweezers at low image acquisition frequency (fac). By significantly reducing τsh to at most 1/4 the characteristic time of the tethered magnetic bead, we accurately evaluated the variance of the magnetic bead position along the axis parallel to the magnetic field, estimating the force with a relative error of ~10% (standard deviation), being only limited by the bead-to-bead difference. We calibrated several magnets - magnetic beads configurations, covering a force range from ~50 fN to ~60 pN. In addition, for the presented configurations, we provide a table with the mathematical expressions that describe the force as a function of the magnets position.
Disease networks identify specific conditions and pleiotropy influencing multimorbidity in the general population
Authors: Amell A. , Roso-Llorach A. , Palomero L. , Cuadras D. , Galván-Femenía I. , Serra-Musach J. , Comellas F. , de Cid R. , Pujana M. A. , Violán C. 
Published: October 2018

AbstractMultimorbidity is an emerging topic in public health policy because of its increasing prevalence and socio-economic impact. However, the age- and gender-dependent trends of disease associations at fine resolution, and the underlying genetic factors, remain incompletely understood. Here, by analyzing disease networks from electronic medical records of primary health care, we identify key conditions and shared genetic factors influencing multimorbidity. Three types of diseases are outlined: “central”, which include chronic and non-chronic conditions, have higher cumulative risks of disease associations; “community roots” have lower cumulative risks, but inform on continuing clustered disease associations with age; and “seeds of bursts”, which most are chronic, reveal outbreaks of disease associations leading to multimorbidity. The diseases with a major impact on multimorbidity are caused by genes that occupy central positions in the network of human disease genes. Alteration of lipid metabolism connects breast cancer, diabetic neuropathy and nutritional anemia. Evaluation of key disease associations by a genome-wide association study identifies shared genetic factors and further supports causal commonalities between nervous system diseases and nutritional anemias. This study also reveals many shared genetic signals with other diseases. Collectively, our results depict novel population-based multimorbidity patterns, identify key diseases within them, and highlight pleiotropy influencing multimorbidity.
Quantitative pupillometry and neuron-specific enolase independently predict return of spontaneous circulation following cardiogenic out-of-hospital cardiac arrest: a prospective pilot study
Authors: Yokobori Shoji , Wang Kevin K. K. , Yang Zhihui , Zhu Tian , Tyndall Joseph A. , Mondello Stefania , Shibata Yasushi , Tominaga Naoki , Kanaya Takahiro , Takiguchi Toru , Igarashi Yutaka , Hagiwara Jun , Nakae Ryuta , Onda Hidetaka , Masuno Tomohiko , Fuse Akira , Yokota Hiroyuki 
Published: October 2018

AbstractThis study aimed to identify neurological and pathophysiological factors that predicted return of spontaneous circulation (ROSC) among patients with out-of-hospital cardiac arrest (OHCA). This prospective 1-year observational study evaluated patients with cardiogenic OHCA who were admitted to a tertiary medical center, Nippon Medical School Hospital. Physiological and neurological examinations were performed at admission for quantitative infrared pupillometry (measured with NPi-200, NeurOptics, CA, USA), arterial blood gas, and blood chemistry. Simultaneous blood samples were also collected to determine levels of neuron-specific enolase (NSE), S-100b, phosphorylated neurofilament heavy subunit, and interleukin-6. In-hospital standard advanced cardiac life support was performed for 30 minutes.The ROSC (n = 26) and non-ROSC (n = 26) groups were compared, which a revealed significantly higher pupillary light reflex ratio, which was defined as the percent change between maximum pupil diameter before light stimuli and minimum pupil diameter after light stimuli, in the ROSC group (median: 1.3% [interquartile range (IQR): 0.0–2.0%] vs. non-ROSC: (median: 0%), (Cut-off: 0.63%). Furthermore, NSE provided the great sensitivity and specificity for predicting ROSC, with an area under the receiver operating characteristic curve of 0.86, which was created by plotting sensitivity and 1-specificity. Multivariable logistic regression analyses revealed that the independent predictors of ROSC were maximum pupillary diameter (odds ratio: 0.25, 95% confidence interval: 0.07–0.94, P = 0.04) and NSE at admission (odds ratio: 0.96, 95% confidence interval: 0.93–0.99, P = 0.04). Pupillary diameter was also significantly correlated with NSE concentrations (r = 0.31, P = 0.027). Conclusively, the strongest predictors of ROSC among patients with OHCA were accurate pupillary diameter and a neuronal biomarker, NSE. Quantitative pupillometry may help guide the decision to terminate resuscitation in emergency departments using a neuropathological rationale. Further large-scale studies are needed.
Distinct phenotypic traits of Staphylococcus aureus are associated with persistent, contagious bovine intramammary infections
Authors: Grunert Tom , Stessl Beatrix , Wolf Franz , Sordelli Daniel O. , Buzzola Fernanda R. , Ehling-Schulz Monika 
Published: October 2018

AbstractStaphylococcus aureus causing persistent, recurrent bovine intramammary infections are still a major challenge to dairy farming. Generally, one or a few clonal lineages are predominant in dairy herds, indicating animal-to-animal transfers and the existence of distinct pathotypic traits. The aim of this study was to determine if long term persistence and spreading of S. aureus are associated with specific phenotypic traits, including cellular invasion, cytotoxicity and biofilm formation. Mastitis isolates were collected over a 3-years period from a single dairy herd, resulting in two persistent subtypes, the high within-herd prevalent subtype ST9 (CC9)-methicillin-susceptible S. aureus (MSSA), designated HP/ST9, and the low within-herd prevalent subtype ST504 (CC705)-MSSA, designated LP/ST504. Characterization of the two different coexisting persistent subtypes showed that the following phenotypic traits are particularly associated with high within-herd prevalence: lack of capsular polysaccharide expression, high cellular invasiveness, low cytotoxicity and high biofilm/ poly-N-acetylglucosamine (PNAG) production, which may concomitantly contribute to the spreading of HP/ST9 within the herd. By contrast to HP/ST9, LP/ST504 is characterized by the formation of colony dendrites, which may help the bacteria to access deeper tissues as niches for persistence in single animals. Thus, within a single herd, two different types of persistence can be found in parallel, allowing longtime persistence of S. aureus in dairy cattle. Furthermore, this study indicates that ST9 (CC9)-MSSA strains, which are currently thought to have their primary reservoir in swine and humans, can also successfully spread to new hosts and persist in dairy herds for years.
Measurement of wavelength-dependent radiation pressure from photon reflection and absorption due to thin film interference
Authors: Ma Dakang , Munday Jeremy N. 
Published: October 2018

AbstractOpto-mechanical forces result from the momentum transfer that occurs during light-matter interactions. One of the most common examples of this phenomenon is the radiation pressure that is exerted on a reflective surface upon photon reflection. For an ideal mirror, the radiation pressure is independent of the wavelength of light and depends only on the incident power. Here we consider a different regime where, for a constant input optical power, wavelength-dependent radiation pressure is observed due to coherent thin film Fabry-Perot interference effects. We perform measurements using a Si microcantilever and utilize an in-situ optical transmission technique to determine the local thickness of the cantilever and the light beam’s angle of incidence. Although Si is absorptive in the visible part of the spectrum, by exploiting the Fabry-Perot modes of the cantilever, we can determine whether momentum is transferred via reflection or absorption by tuning the incident wavelength by only ~20 nm. Finally, we demonstrate that the tunable wavelength excitation measurement can be used to separate photothermal effects and radiation pressure.
3D printed dielectric ceramic without a sintering stage
Authors: Väätäjä Maria , Kähäri Hanna , Ohenoja Katja , Sobocinski Maciej , Juuti Jari , Jantunen Heli 
Published: October 2018

AbstractThis paper presents for the first time the fabrication of dielectric ceramic parts by 3D printing without sintering. The printable paste was prepared by mixing a carefully selected amount of water-soluble Li2MoO4powder with water. A viscous mixture of solid ceramic particles and saturated aqueous phase was formed with a solid content of 60.0 vol.%. Printing of the sample discs was conducted with material extrusion using a low-cost syringe-style 3D printer. The consolidation and densification of the printed parts occurred during both printing and drying of the paste due to extrusion pressure, capillary forces, and recrystallization of the dissolved Li2MoO4. Complete drying of the paste was ensured by heating at 120 °C. The microstructure showed no delamination of the printed layers. Relatively high densities and good dielectric properties were obtained, especially when considering that no sintering and only pressure from the extrusion was employed. This approach is expected to be feasible for similar ceramics and ceramic composites.
Dog bite and injury awareness and prevention in migrant and left-behind children in China
Authors: Chen Ying , Tan Yafei , Yan Shuzhen , Li Liping 
Published: October 2018

AbstractDog-incurred injury is a serious public health concern worldwide, especially for children, responsible for numerous infectious diseases, such as rabies. Our study aims to investigate the current status of dog-incurred injury and its prevention among special groups of children. A cross-sectional study was conducted among migrant children (MC) and non-MC, “left-behind” children (LBC) and non-LBC in two cities in southern China. A questionnaire was used to collect socio-demographic data and experience with dog-incurred injury, to assess knowledge of dog behaviour and rabies prevention and attitudes in risk identification and practice in risk behaviour. A total of 9,380 children aged 6–19 years old participated in this study. The self-reported prevalence of overall lifetime dog-incurred injuries in MC was 19.4% (vs. 11.2% in non-MC, χ2 = 175.8) and LBC was 20.6% (vs. 13.5% in non-LBC, χ2 = 114.1). MC were more likely to provoke a dog before the injury happened (12.7% vs 11.0%), while LBC (13.3% vs. 10.7%) and non-MC (13.1% vs. 12.2%) did not manage their wounds (all P < 0.001). 45.6% of victims were alone when the attack happened. MC from other provinces who live in rural areas and LBC with their mother absent had the lowest levels of knowledge among the groups. Taken together, MC and LBC are at greater risk for dog-incurred injury. They had lower knowledge of and attitudes towards prevention and more high-risk behaviour. Therefore, an appropriate public health education intervention is needed for schoolchildren regarding the prevention and management of dog-incurred injury and disease.
Exploring the potential of PROCOSINE and close-range hyperspectral imaging to study the effects of fungal diseases on leaf physiology
Authors: Morel Julien , Jay Sylvain , Féret Jean-Baptiste , Bakache Adel , Bendoula Ryad , Carreel Francoise , Gorretta Nathalie 
Published: October 2018

AbstractThe detection of plant diseases, including fungi, is a major challenge for reducing yield gaps of crops across the world. We explored the potential of the PROCOSINE radiative transfer model to assess the effect of the fungus Pseudocercospora fijiensis on leaf tissues using laboratory-acquired submillimetre-scale hyperspectral images in the visible and near-infrared spectral range. The objectives were (i) to assess the dynamics of leaf biochemical and biophysical parameters estimated using PROCOSINE inversion as a function of the disease stages, and (ii) to discriminate the disease stages by using a Linear Discriminant Analysis model built from the inversion results. The inversion results show that most of the parameter dynamics are consistent with expectations: for example, the chlorophyll content progressively decreased as the disease spreads, and the brown pigments content increased. An overall accuracy of 78.7% was obtained for the discrimination of the six disease stages, with errors mainly occurring between asymptomatic samples and first visible disease stages. PROCOSINE inversion provides relevant ecophysiological information to better understand how P. fijiensis affects the leaf at each disease stage. More particularly, the results suggest that monitoring anthocyanins may be critical for the early detection of this disease.
Electron Scattering via Interface Optical Phonons with High Group Velocity in Wurtzite GaN-based Quantum Well Heterostructure
Authors: Park Kihoon , Mohamed Ahmed , Dutta Mitra , Stroscio Michael A. , Bayram Can 
Published: October 2018

AbstractHere we present a detailed theoretical analysis of the interaction between electrons and optical phonons of interface and confined modes in a wurtzite AlN/GaN/AlN quantum well heterostructure based on the uniaxial dielectric continuum model. The formalism describing the interface and confined mode optical phonon dispersion relation, electron–phonon scattering rates, and average group velocity of emitted optical phonons are developed and numerically calculated. The dispersion relation of the interface phonons shows a convergence to the resonant phonon frequencies 577.8 and 832.3 cm−1 with a steep slope around the zone center indicating a large group velocity. At the onset of interface phonon emission, the average group velocity is small due to the large contribution of interface and confined mode phonons with close-to-zero group velocity, but eventually increases up to larger values than the bulk GaN acoustic phonon velocity along the wurtzite crystal c-axis (8 nm/ps). By adjusting the GaN thickness in the double heterostructure, the average group velocity can be engineered to become larger than the velocity of acoustic phonons at a specific electron energy. This suggests that the high group velocity interface mode optical phonons can be exploited to remove heat more effectively and reduce junction temperatures in GaN-based heterostructures.
A record of changes in the Gran Sasso groundwater before, during and after the 2016 Amatrice earthquake, central Italy
Authors: De Luca Gaetano , Di Carlo Giuseppe , Tallini Marco 
Published: October 2018

AbstractWe performed continuous recordings (May 2015 – January 2017) of hydraulic pressure and electrical conductivity of groundwater in the 190 m-long horizontal S13 borehole drilled next to the deep underground laboratories of Gran Sasso (LNGS-INFN), located in the core of the Gran Sasso carbonate aquifer (central Italy) at a distance of about 39 km south-eastward from the 24 August 2016 Amatrice earthquake (6.0 Mw) epicenter. Using a 3-channel, 24-bit ADC we achieved a sampling rate of groundwater physical properties up to 50 Hz for each channel. We focused on the analysis of data recorded before, during and after the Amatrice earthquake, describing and discussing in detail the evidence for significant hydraulic pressure and electrical conductivity anomalies recorded before the main shock. We identified unambiguous signals in the hydraulic pressure data starting on 19 August, i.e. five days before the 24 August mainshock. A more careful analysis allowed us to detect the inception of a weak change up to 40 days before the Amatrice earthquake and a significant variation in the electrical conductivity data about 60 days before. The data revealed highly dynamic aquifer behaviour associated with the uprising of geogas probably related to the preparation stage of the Amatrice earthquake.
In-depth data on the network structure and hourly activity of the Central Chilean power grid
Authors: Kim Heetae , Olave-Rojas David , Álvarez-Miranda Eduardo , Son Seung-Woo 
Published: October 2018

AbstractNetwork science enables us to improve the performance of complex systems such as traffic, communication, and power grids. To do so, it is necessary to use a well-constructed flawless network dataset associated with the system of interest. In this study, we present the dataset of the Chilean power grid. We harmonized data from three diverse sources to generate a unified dataset. Through an intensive review on the raw data, we filter out inconsistent errors and unrealistic faults, making the data more trustworthy. In contrast to other network dataset for power grids, we especially focus on preserving the physical structure of nodes’ connection incorporating the ‘tap’ structure. As a result, we provide three different versions of the dataset: ‘with-tap’, ‘without-tap’, and ‘reduced versions’. Along with structure, we incorporate various attributes of the nodes and edges such as the geo-coordinates, voltage of transmission lines, and the time series data of generation or consumption. These data are useful for network scientists to analyze the performance and dynamic stability of power grids.
Exploiting deep learning and volunteered geographic information for mapping buildings in Kano, Nigeria
Authors: Yuan Jiangye , Roy Chowdhury Pranab K. , McKee Jacob , Yang Hsiuhan Lexie , Weaver Jeanette , Bhaduri Budhendra 
Published: October 2018

AbstractBuildings in the developing world are inadequately mapped. Lack of such critical geospatial data adds unnecessary challenges to locating and reaching a large segment of the world’s most vulnerable population, impeding sustainability goals ranging from disaster relief to poverty reduction. Use of volunteered geographic information (VGI) has emerged as a widely accepted source to fill such voids. Despite its promise, availability of building maps for developing countries significantly lags behind demand. We present a new approach, coupling deep convolutional neural networks (CNNs) with VGI for automating building map generation from high-resolution satellite images for Kano state, Nigeria. Specifically, we trained a CNN with VGI building outlines of limited quality and quantity and generated building maps for a 50,000 km2 area. Resulting maps are in strong agreement with existing settlement maps and require a fraction of the manual input needed for the latter. The VGI-based maps will provide support across multiple facets of socioeconomic development in Kano state, and demonstrates potential advancements in current mapping capabilities in resource constrained countries.
Household economy, forest dependency & opportunity costs of conservation in eastern rainforests of Madagascar
Authors: Poudyal Mahesh , Rakotonarivo O. Sarobidy , Razafimanahaka Julie H. , Hockley Neal , Jones Julia P. G. 
Published: October 2018

AbstractThe Government of Madagascar is trying to reduce deforestation and conserve biodiversity through creating new protected areas in the eastern rainforests. While this has many benefits, forest use restriction may bring costs to farmers at the forest frontier. We explored this through a series of surveys in five sites around the Corridor Ankeniheny Zahamena new protected area and adjacent national parks. In phase one a stratified random sample of 603 households completed a household survey covering demographic and socio-economic characteristics, and a choice experiment to estimate the opportunity costs of conservation. A stratified sub-sample (n = 171) then completed a detailed agricultural survey (including recording inputs and outputs from 721 plots) and wild-harvested product survey. The data have been archived with ReShare (UK Data Service). Together these allow a deeper understanding of the household economy on the forest frontier in eastern Madagascar and their swidden agricultural system, the benefits households derive from the forests through wild-harvested products, and the costs of conservation restrictions to forest edge communities.
Spread of a model invasive alien species, the harlequin ladybird Harmonia axyridis in Britain and Ireland
Authors: Brown P. M. J. , Roy D. B. , Harrower C. , Dean H. J. , Rorke S. L. , Roy H. E. 
Published: October 2018

AbstractInvasive alien species are widely recognized as one of the main threats to global biodiversity. Rapid flow of information on the occurrence of invasive alien species is critical to underpin effective action. Citizen science, i.e. the involvement of volunteers in science, provides an opportunity to improve the information available on invasive alien species. Here we describe the dataset created via a citizen science approach to track the spread of a well-studied invasive alien species, the harlequin ladybird Harmonia axyridis (Coleoptera: Coccinellidae) in Britain and Ireland. This dataset comprises 48 510 verified and validated spatio-temporal records of the occurrence of H. axyridis in Britain and Ireland, from first arrival in 2003, to the end of 2016. A clear and rapid spread of the species within Britain and Ireland is evident. A major reuse value of the dataset is in modelling the spread of an invasive species and applying this to other potential invasive alien species in order to predict and prevent their further spread.
Online blend‐type identification during co‐firing coal and biomass using SVM and flame emission spectrum in a pilot‐scale furnace
Authors: Zhou Hao , Li Yuan , Cen Kefa 
Published: October 2018

Co‐firing coal and biomass has been applied in existing coal‐fired power stations recently. Online blend‐type identification was investigated by support vector machine (SVM) using flame emission spectrum for combustion optimisation. A spectrometer was used to capture the flame emission spectrum during co‐combustion in a 0.3 MW furnace. A total of 22 flame features were defined and extracted from the flame emission spectrum for blend‐type identification. ReliefF was applied to calculate the important weights of the extracted fame features. Alkali metals atomic excitation spectral intensities and the means of spectral signals show obviously higher important weights than the other flame features. Ultraviolet signal is more important than visible and infrared signals for blend‐type identification. SVM was adopted to identify the blend types. The method of ‘ReliefF + SVM’ was proposed to obtain the optimum feature vector. The number of optimum features can be reduced from 22 to 17 if only the prediction accuracy is considered. The optimum sampling number is 12. At the optimum feature vector (17 features) and the optimum sampling number (12), the average prediction accuracy of the five fuels is 99.67%. The results demonstrate that combining SVM and flame emission spectrum is suitable for online blend‐type identification during co‐combustion.