bluuebunny/crossref_metadata_2025_split huggingface dataset:
Consumption of ultra-processed foods decreases the quality of the overall diet of middle-aged Japanese adults
Authors: Koiwai Kaori , Takemi Yukari , Hayashi Fumi , Ogata Hiromitsu , Matsumoto Saika , Ozawa Keiko , Machado Priscila Pereira , Monteiro Carlos Augusto 
Published: June 2019

AbstractObjective:To estimate the consumption of ultra-processed foods and determine its association with dietary quality among middle-aged Japanese adults.Design:Cross-sectional study using data from the Saitama Prefecture Health and Nutrition Survey 2011. Dietary intake was assessed using one- or two-day dietary records. Sociodemographic and lifestyle factors were obtained via self-administered questionnaire. Food items were classified according to the NOVA system into four groups: unprocessed or minimally processed foods; processed culinary ingredients; processed foods; and ultra-processed foods. The dietary share of each NOVA food group and their subgroups was calculated in relation to total energy intake, and the average dietary content of key nutrients was determined across tertiles of the dietary energy share of ultra-processed foods (low, middle and high intake).Setting:Saitama Prefecture in Japan.Participants:Community-dwelling adults aged 30–59 years (256 men, 361 women).Results:Consumption of unprocessed or minimally processed foods, processed culinary ingredients, processed foods and ultra-processed foods contributed 44·9 (se0·8) %, 5·5 (se0·2) %, 11·3 (se0·4) % and 38·2 (se0·9) % of total daily energy intake, respectively. A positive and statistically significant linear trend was found between the dietary share of ultra-processed foods (tertiles) and the dietary content of total and saturated fat, while an inverse relationship was observed for protein, vitamin K, vitamin B6, dietary fibre, magnesium, phosphorus and iron.Conclusions:Our findings show that higher consumption of ultra-processed foods was associated with decreased dietary quality among Japanese adults.
Utilising virtual bolus in superficial planning target volume dose optimisation (TomoTherapy): a phantom study
Authors: Ooi Gim Chee , Bin Mustafa Iskandar Shahrim 
Published: June 2019

AbstractAim:This is a phantom study to evaluate the dosimetry effects of using virtual bolus (VB) in TomoTherapy Treatment Planning System (TPS) optimisation for superficial planning target volume (PTV) that extends to the body surface. Without VB, the inverse-planning TPS will continuously boost the photon fluence at the surface of the superficial PTV due to lack of build-up region. VB is used during TPS optimisation only and will not be present in actual treatment delivery.Materials and methods:In this study, a dummy planning target was contoured on a cylindrical phantom which extends to the phantom surface, and VB of various combinations of thickness and density was used in treatment planning optimisation with TomoTherapy TPS. The plans were then delivered with the treatment modality TomoTherapy. Radiochromic films (Gafchromic EBT3) were calibrated and used for dose profiles measurements. TomoTherapy Planned-Adaptive software was used to analyse the delivered Dose-Volume Histograms (DVHs).Results:The use of 2 mm VB was not providing adequate build-up area and was unable to reduce the hot spots during treatment planning and actual delivery. The use of 4 mm VB was able to negate the photon fluence boosting effect by the TPS, and the actual delivery showed relatively small deviations from the treatment plan. The use of 6 mm VB caused significant dose overestimation by the TPS in the superficial regions resulting in insufficient dose coverage delivered.Findings:VB with the combination of 4 mm thickness and 1·0 g/cc density provides the most robust solution for the TomoTherapy TPS optimisation of superficial PTV.
An Ensemble Data Set of Sea Surface Temperature Change From 1850: The Met Office Hadley Centre HadSST.4.0.0.0 Data Set
Authors: Kennedy J. J. , Rayner N. A. , Atkinson C. P. , Killick R. E. 
Published: June 2019

AbstractOne of the largest sources of uncertainty in estimates of global temperature change is that associated with the correction of systematic errors in sea surface temperature (SST) measurements. Despite recent work to quantify and reduce these errors throughout the historical record, differences between analyses remain larger than can be explained by the estimated uncertainties. We revisited the method used to estimate systematic errors and their uncertainties in version 3 of the Met Office Hadley Centre SST data set, HadSST. Using comparisons with oceanographic temperature profiles, we make estimates of biases associated with engine room measurements and insulated buckets and constrain the ranges of two of the more uncertain parameters in the bias estimation: the timing of the transition from uninsulated to insulated buckets in the middle twentieth century and the estimated fractions of different measurement methods used. Here, we present HadSST.4.0.0.0, based on release 3.0.0 and 3.0.1 of the International Comprehensive Ocean‐Atmosphere Data Set supplemented by drifting buoy measurements from the Copernicus Marine Environmental Monitoring Service. HadSST.4.0.0.0 comprises a 200‐member “ensemble” in which uncertain parameters in the SST bias scheme are varied to generate a range of adjustments. The evolution of global average SST in the new data set is similar to that in other SST data sets, and the difference between data sets is reduced during the middle twentieth century. However, the changes also highlight a discrepancy in the global‐average difference between adjusted SST and marine air temperature in the early 1990s and hence between HadSST.4.0.0.0 and, the National Oceanic and Atmospheric Administration SST data set, ERSSTv5.
Natural Variability in Projections of Climate Change Impacts on Fine Particulate Matter Pollution
Authors: Pienkosz Bret D. , Saari Rebecca K. , Monier Erwan , Garcia‐Menendez Fernando 
Published: June 2019

AbstractVariations in meteorology associated with climate change can impact fine particulate matter (PM2.5) pollution by affecting natural emissions, atmospheric chemistry, and pollutant transport. However, substantial discrepancies exist among model‐based projections of PM2.5 impacts driven by anthropogenic climate change. Natural variability can significantly contribute to the uncertainty in these estimates. Using a large ensemble of climate and atmospheric chemistry simulations, we evaluate the influence of natural variability on projections of climate change impacts on PM2.5 pollution in the United States. We find that natural variability in simulated PM2.5 can be comparable or larger than reported estimates of anthropogenic‐induced climate impacts. Relative to mean concentrations, the variability in projected PM2.5 climate impacts can also exceed that of ozone impacts. Based on our projections, we recommend that analyses aiming to isolate the effect climate change on PM2.5 use 10 years or more of modeling to capture the internal variability in air quality and increase confidence that the anthropogenic‐forced effect is differentiated from the noise introduced by natural variability. Projections at a regional scale or under greenhouse gas mitigation scenarios can require additional modeling to attribute impacts to climate change. Adequately considering natural variability can be an important step toward explaining the inconsistencies in estimates of climate‐induced impacts on PM2.5. Improved treatment of natural variability through extended modeling lengths or initial condition ensembles can reduce uncertainty in air quality projections and improve assessments of climate policy risks and benefits.
Evaluating a Moist Isentropic Framework for Poleward Moisture Transport: Implications for Water Isotopes Over Antarctica
Authors: Bailey Adriana , Singh Hansi K. A. , Nusbaumer Jesse 
Published: June 2019

AbstractThe ability to identify moisture source regions and sinks and to model the transport pathways that link them in simple yet physical ways is critical for understanding climate today and in the past. Using water tagging and isotopic tracer experiments in the Community Earth System Model, this work shows that poleward moisture transport largely follows surfaces of constant moist entropy. The analysis not only provides insight into why distinct zonal bands supply moisture to high‐ and low‐elevation polar sites but also explains why changes in these source regions are inherently linked to changes in temperature and rainout. Moreover, because the geometry, and specifically length, of the moist isentropic surfaces describes how much integrated rainout occurs, the analysis provides a physical framework for interpreting the isotopic composition of water in poleward‐moving air, thus indicating how variations in moisture transport might influence Antarctic ice cores.
Automatically Finding Ship Tracks to Enable Large‐Scale Analysis of Aerosol‐Cloud Interactions
Authors: Yuan Tianle , Wang Chenxi , Song Hua , Platnick Steven , Meyer Kerry , Oreopoulos Lazaros 
Published: June 2019

AbstractShip tracks appear as long winding linear features in satellite images and are produced by aerosols from ship exhausts changing low cloud properties. They are one of the best examples of aerosol‐cloud interaction experiments. However, manually finding ship tracks from satellite data on a large scale is prohibitively costly while a large number of samples are required to improve our understanding. Here we train a deep neural network to automate finding ship tracks. The neural network model generalizes well as it not only finds ship tracks labeled by human experts but also detects those that are occasionally missed by humans. It finds more ship tracks than all previous studies combined and produces a map of ship track distributions off the California coast that matches well with known shipping traffic. Our technique will enable studying aerosol effects on low clouds using ship tracks on a large scale, which will potentially narrow the uncertainty of the aerosol‐cloud interactions.
Manufacturing of 3D multifunctional microelectronic devices: challenges and opportunities
Authors: Guo Xiaogang , Xue Zhaoguo , Zhang Yihui 
Published: June 2019

AbstractSophisticated three-dimensional (3D) forms are expected to be one of the significant development trends in next-generation microelectronics because of their capabilities of rendering substantially enhanced performances, a high degree of integration, and novel functionalities. To date, a diversity of manufacturing methods has been developed for 3D microelectronic devices with different structural and functional features. Most of these methods fall into two categories, i.e., micromanufacturing technologies and mechanically guided 3D assembly approaches. From this perspective, we review the different manufacturing methods and their specific features as well as their limitations. At present, there is still no universal method that can deterministically form 3D microelectronic devices with very high geometric complexity and nanoscale precision. We offer an outlook on future developments in the manufacturing of 3D multifunctional microelectronics devices and provide some perspectives on the remaining challenges as well as possible solutions. Mechanically guided 3D assembly based on compressive buckling is proposed as a versatile platform that can be merged with micromanufacturing technologies and/or other assembly methods to provide access to microelectronic devices with more types of integrated functions and highly increased densities of functional components.
A novel ABCC6 variant causative of pseudoxanthoma elasticum
Authors: Contrò Gianluca , Tallerico Rossana , Dattilo Vincenzo , Fabiani Fernanda , Enzo Maria Vittoria , Hladnik Uros , Dastoli Stefano , Nisticò Steven Paul , Colao Emma , Perrotti Nicola , Iuliano Rodolfo 
Published: June 2019

AbstractPseudoxanthoma elasticum is an autosomal recessive heritable disorder caused by mutations in ABCC6. We describe two siblings showing typical skin lesions and a clinical diagnosis of pseudoxanthoma elasticum. Genetic analysis of ABCC6 revealed a novel homozygous c.4041G > A variant located in the last position of exon 28 that compromises the splicing donor site, resulting in a shorter messenger RNA. The deletion impairs the nucleotide-binding fold region, which is crucial for ABCC6 function.
Programmable terahertz chip-scale sensing interface with direct digital reconfiguration at sub-wavelength scales
Authors: Wu Xue , Lu Huaixi , Sengupta Kaushik 
Published: June 2019

AbstractThe ability to sense terahertz waves in a chip-scale technology operable at room temperature has potential for transformative applications in chemical sensing, biomedical imaging, spectroscopy and security. However, terahertz sensors are typically limited in their responsivity to a narrow slice of the incident field properties including frequency, angle of incidence and polarization. Sensor fusions across these field properties can revolutionize THz sensing allowing robustness, versatility and real-time imaging. Here, we present an approach that incorporates frequency, pattern and polarization programmability into a miniaturized chip-scale THz sensor. Through direct programming of a continuous electromagnetic interface at deep subwavelength scales, we demonstrate the ability to program the sensor across the spectrum (0.1–1.0 THz), angle of incidence and polarization simultaneously in a single chip implemented in an industry standard 65-nm CMOS process. The methodology is compatible with other technology substrates that can allow extension of such programmability into other spectral regions.
Targeting enhancer switching overcomes non-genetic drug resistance in acute myeloid leukaemia
Authors: Bell Charles C. , Fennell Katie A. , Chan Yih-Chih , Rambow Florian , Yeung Miriam M. , Vassiliadis Dane , Lara Luis , Yeh Paul , Martelotto Luciano G. , Rogiers Aljosja , Kremer Brandon E. , Barbash Olena , Mohammad Helai P. , Johanson Timothy M. , Burr Marian L. , Dhar Arindam , Karpinich Natalie , Tian Luyi , Tyler Dean S. , MacPherson Laura , Shi Junwei , Pinnawala Nathan , Yew Fong Chun , Papenfuss Anthony T. , Grimmond Sean M. , Dawson Sarah-Jane , Allan Rhys S. , Kruger Ryan G. , Vakoc Christopher R. , Goode David L. , Naik Shalin H. , Gilan Omer , Lam Enid Y. N. , Marine Jean-Christophe , Prinjha Rab K. , Dawson Mark A. 
Published: June 2019

AbstractNon-genetic drug resistance is increasingly recognised in various cancers. Molecular insights into this process are lacking and it is unknown whether stable non-genetic resistance can be overcome. Using single cell RNA-sequencing of paired drug naïve and resistant AML patient samples and cellular barcoding in a unique mouse model of non-genetic resistance, here we demonstrate that transcriptional plasticity drives stable epigenetic resistance. With a CRISPR-Cas9 screen we identify regulators of enhancer function as important modulators of the resistant cell state. We show that inhibition of Lsd1 (Kdm1a) is able to overcome stable epigenetic resistance by facilitating the binding of the pioneer factor, Pu.1 and cofactor, Irf8, to nucleate new enhancers that regulate the expression of key survival genes. This enhancer switching results in the re-distribution of transcriptional co-activators, including Brd4, and provides the opportunity to disable their activity and overcome epigenetic resistance. Together these findings highlight key principles to help counteract non-genetic drug resistance.
Synergetic iridium and amine catalysis enables asymmetric [4+2] cycloadditions of vinyl aminoalcohols with carbonyls
Authors: Zhang Mao-Mao , Wang Ya-Ni , Wang Bao-Cheng , Chen Xiao-Wang , Lu Liang-Qiu , Xiao Wen-Jing 
Published: June 2019

AbstractCatalytic asymmetric cycloadditions via transition-metal-containing dipolar intermediates are a powerful tool for synthesizing chiral heterocycles. However, within the field of palladium catalysis, compared with the well-developed normal electron-demand cycloadditions with electrophilic dipolarophiles, a general strategy for inverse electron-demand ones with nucleophilic dipolarophiles remains elusive, due to the inherent linear selectivity in the key palladium-catalyzed intermolecular allylations. Herein, based on the switched regioselectivity of iridium-catalyzed allylations, we achieved two asymmetric [4+2] cycloadditions of vinyl aminoalcohols with aldehydes and β,γ-unsaturated ketones through synergetic iridium and amine catalysis. The activation of vinyl aminoalcohols by iridium catalysts and carbonyls by amine catalysts provide a foundation for the subsequent asymmetric [4+2] cycloadditions of the resulting iridium-containing 1,4-dipoles and (di)enamine dipolarophiles. The former provides a straightforward route to a diverse set of enantio-enriched hydroquinolines bearing chiral quaternary stereocenters, and the later represent an enantio- and diastereodivergent synthesis of chiral hydroquinolines.
Atomic-scale perturbation of oxygen octahedra via surface ion exchange in perovskite nickelates boosts water oxidation
Authors: Bak Jumi , Bin Bae Hyung , Chung Sung-Yoon 
Published: June 2019

AbstractA substantial amount of interest has been focused on ABO3-type perovskite oxides over the past decade as oxygen electrocatalysts. Despite many studies on various compositions, the correlation between the structure of the oxygen octahedra and electrocatalytic property has been overlooked, and there accordingly have been a very limited number of attempts regarding control of atomistic structure. Utilizing epitaxial LnNiO3 (Ln = La, Pr, Nd) thin films, here we demonstrate that simple electrochemical exchange of Fe in the surface region with several-unit-cell thickness is notably effective to boost the catalytic activity for the oxygen evolution reaction by different orders of magnitude. Furthermore, we directly establish that strong distortion of oxygen octahedra at the angstrom scale is readily induced during the Fe exchange, and that this structural perturbation permits easier charge transfer. The findings suggest that structural alteration can be an efficient approach to achieve exceptional electrocatalysis in crystalline oxides.
Whole genome resequencing data for three rockfish species of Sebastes
Authors: Xu Shengyong , Zhao Linlin , Xiao Shijun , Gao Tianxiang 
Published: June 2019

AbstractHere we report Illumina-based whole genome sequencing of three rockfish species ofSebastesin northwest Pacific. The whole genomic DNA was used to prepare 350-bp pair-end libraries and the high-throughput sequencing yielded 128.5, 137.5, and 124.8 million mapped reads corresponding to 38.54, 41.26, and 37.43 Gb sequence data forS. schlegelii,S. koreanus, andS. nudus, respectively. The k-mer analyses revealed genome sizes were 846.4, 832.5, and 813.1 Mb and the sequencing coverages were 45×, 49×, and 46× for three rockfish, respectively. Comparative genomic analyses identified 46,624 genome-wide single nucleotide polymorphisms (SNPs). Phylogenetic analysis revealed closer relationships of the three species, compared to other six rockfish species. Demographic analysis identified contrasting changes betweenS. schlegeliiand other two species, suggesting drastically different response to climate changes. The reported genome data in this study are valuable for further studies on comparative genomics and evolutionary biology of rockfish species.
Manganese oxide synthesized from spent Zn-C battery for supercapacitor electrode application
Authors: Farzana Rifat , Hassan Kamrul , Sahajwalla Veena 
Published: June 2019

AbstractManganese oxide (Mn3O4) nanomaterials have promising potential to be used as supercapacitor electrode materials due to its high energy storage performance and environmental compatibility. Besides, every year huge volume of waste batteries including Zn-C battery ends up in landfill, which aggravates the burden of waste disposal in landfill and creates environmental and health threat. Thus, transformation of waste battery back into energy application, is of great significance for sustainable strategies. Compared with complex chemical routes which mostly apply toxic acids to recover materials from Zn-C battery, this study establishes the recovery of Mn3O4 particles via thermal route within 900 °C under controlled atmosphere. Synthesized Mn3O4 were confirmed by XRD, EDS, FTIR, XPS and Raman analysis and FESEM micrographs confirmed the coexistence of spherical and cubic Mn3O4 particles. Mn3O4 electrode derived from waste Zn-C battery demonstrate compatible electrochemical performance with standard materials and conventional synthesis techniques. Mn3O4 electrode exhibited highest capacitance value of 125 Fg−1 at 5 mVs−1 scan rate. The stability of the electrode showed good retention in discharge and charge capacity by about 80% after 2100 cycles. This study demonstrates that waste Zn-C battery can be further utilized for energy storage application, providing sustainable and economic benefits.
Turing Patterns of Non-linear S-I Model on Random and Real-Structure Networks with Diarrhea Data
Authors: Putra Prama Setia , Susanto Hadi , Nuraini Nuning 
Published: June 2019

AbstractMost developed models for solving problems in epidemiology use deterministic approach. To cover the lack of spatial sense in the method, one uses statistical modeling, reaction-diffusion in continuous medium, or multi-patch model to depict epidemic activities in several connected locations. Here, we show that an epidemic model that is set as an organized system on networks can yield Turing patterns and other interesting behaviors that are sensitive to the initial conditions. The formed patterns can be used to determine the epidemic arrival time, its first peak occurrence and the peak duration. These epidemic quantities are beneficial to identify contribution of a disease source node to the others. Using a real structure network, the system also exhibits a comparable disease spread pattern of Diarrhea in Jakarta.
Intelligently chosen interventions have potential to outperform the diode bridge in power conditioning
Authors: Liu Feiyang , Zhang Yulong , Dahlsten Oscar , Wang Fei 
Published: June 2019

AbstractWe probe the potential for intelligent intervention to enhance the power output of energy harvesters. We investigate general principles and a case study: a bi-resonant piezo electric harvester. We consider intelligent interventions via pre-programmed reversible energy-conserving operations. These include voltage bias flips and voltage phase shifts. These can be used to rectify voltages and to remove destructive interference. We choose the intervention type based on past data, using machine learning techniques. We find that in important parameter regimes the resulting interventions can outperform diode-based intervention, which in contrast has a fundamental minimum power dissipation bound.