bluuebunny/crossref_metadata_2025_split huggingface dataset:
Basal and longitudinal changes in serum levels of TSH in morbid obese patients experiencing failure or success of dietary treatment
Authors: Croce Laura , Pallavicini Cristina , Crotti Silvia , Coperchini Francesca , Minnelli Linda , Magri Flavia , Chiovato Luca , Rotondi Mario 
Published: October 2020

Abstract
Purpose
The relationship between thyroid function and obesity is a widely investigated one. The impact of thyroid hormones in determining the outcome of dietary/lifestyle interventions remains to be fully elucidated. The aim of this study was to compare basal and post dietary-intervention circulating thyroid-function parameters, lipid profile and fasting-glucose in euthyroid obese patients according to a success or failure of a dietary intervention program.

Methods
In a retrospective longitudinal case–control study we enrolled 50 euthyroid obese patients who experienced a success in dietary intervention, as defined by a BMI reduction of at least 5% from baseline (Success Group) and 50 sex and age-matched euthyroid obese patients who experienced failure in dietary intervention as defined by either stable or increased body weight throughout the follow-up (Failure Group). Serum thyroid function parameters and metabolic profile at baseline and at the end of follow-up were collected.

Results
At baseline, the two groups showed similar BMI, total-cholesterol, HDL-cholesterol and fasting-blood-glucose, but patients in Success Group had a significantly higher TSH as compared with Failure Group (2.20 ± 0.97 vs 1.66 ± 0.73, respectively, p < 0.001). Throughout a mean follow-up of 21.4 months TSH significantly decreased in Success Group (2.20 ± 0.97 vs 2.06 ± 0.98; p = 0.029) and increased in Failure Group (1.63 ± 0.72 vs 2.01 ± 0.99; p < 0.001). Multiple regression analysis showed that the outcome of the dietary intervention was significantly and independently related to baseline BMI (0.925; 0.861–0.993), age (0.957; 0.922–0.993), TSH (0.531; 0.290–0.973) and TSH-changes (1.011; 1.000–1.022) during follow-up.

Conclusions
Baseline serum TSH level is related to the final outcome of a dietary intervention program in obese patients.

Level of evidence III
Evidence obtained from a retrospective cohort or case–control analytic studies.
On Predicting the Ultimate Capacity of a Large-Span Soil–Steel Composite Bridge
Authors: Wadi Amer , Pettersson Lars , Karoumi Raid 
Published: October 2020

AbstractThe limit state design of large-span soil–steel composite bridges (SSCB) entails that understanding their structural behaviour in the ultimate state is as much needed as their performance under service conditions. Apart from box culverts, the largest loading-to-failure test was done on a 6.3-m span culvert. More tests on larger spans are believed essentially valuable for the development of the design methods. This paper presents the numerical simulation efforts of an 18.1-m span SSCB pertaining to its ongoing preparations for a full-scale field test. The effect of the different loading positions on the ultimate capacity is investigated. Comparisons are made between three-dimensional (3D) and two-dimensional (2D) models. The results enabled to realise the important role of the soil load effects on the ultimate capacity. It is found that the failure load is reduced when the structure is loaded in an asymmetrical manner. A local effect is more pronounced for the live load when the tandem load is placed closer to the crown. The study also illustrates the complex correlation between 3D and 2D models, especially if one attempts to simultaneously associate sectional forces and displacements.
Laser polished fused deposition poly-lactic acid objects for personalized orthopaedic application
Authors: Chai Yuan , Chen Xiao-Bo , Zhang Donghai , Lynch Joseph , Birbilis Nick , Qin Qing-Hua , Smith Paul N. , Li Rachel W. 
Published: October 2020

AbstractPatient-specific surgical guides are increasingly demanded. Material Extrusion (ME) is a popular 3D printing technique to fabricate personalized surgical guides. However, the ME process usually generates deleterious surface topography which is not suitable for orthopaedic emergencies. We designed and optimized parametric combinations of a laser polishing approach as post process to improve the surface quality of ME-made poly-lactic acid (PLA) objects. In this study, we investigated the contribution of processing variables to the mechanical properties and the biocompatibilities in vitro of the ME-made PLA objects. Conventional surface grinding was conducted as comparison. The results demonstrate that the ME-made PLA samples exhibit good mechanical properties and favourable biocompatibility after being post processed using laser polishing. The post laser polishing, as a powerful tool in manufacture of ME-made PLA objects, will open a new approach with a great promise in its applications in personalized and timely management of medical emergencies.
Disentangling the path of pollinator attraction in temporarily colored flowers
Authors: Boff Samuel , Henrique Jessica Amaral , Friedel Anna , Raizer Josué 
Published: October 2020

AbstractPlants may use different strategies to attract pollinators in long distance (e.g. floral display) and in short distance (e.g. ratio between differentially colored flowers) scales. The Verbenaceae Lantana canescens Kunth is a wide spread species in open sites of the Brazilian Pantanal wetland. Individuals of this generalist species can produce a variable number of open inflorescences with yellow and white flowers that are organized in whorls. In this study we tested the hypothesis that increased floral display (long distance attraction) and the ratio between yellow and white flowers (short distance attraction) enhances the number of pollinator species and individuals. We observed flower visitors and calculated floral parameters in 38 plots of 1 m2 each, that contained a varying number of flowering L. canescens individuals. Non-metric multidimensional scaling and Bray-Curtis distances were used to account for flower visitor composition and the relative visitation rate, respectively. We used a structural equation model to test the power of each predictor variable on the visitation rate and a covariance analysis to disentangle the effect of each independent variable on the frequency of plant-pollinator interactions. We found that the number of flower visitors and the visitation rate increased with increasing number of inflorescences. Disentangling long and short distance attraction indicated that the number of inflorescences (per plot) and the number of yellow flowers (yellowing effect) contributed most to flower visitation at long and short distance, respectively.
Implementation of Newton’s Algorithm Using FORTRAN
Authors: Siddiqui Shahida Anusha , Ahmad Ali 
Published: October 2020

AbstractA lot of software today dealing with various domains of engineering and life sciences have to deal with non-linear problems. In order to reduce the problem to a linear problem, a lot of state of the art solutions already exist. This work focus on the implementation of Newton’s Algorithm (also known as Newton’s method), to determine the roots of a given function within a specific user defined interval. The software for this implementation is FORTRAN. Even though FORTRAN is considered to be outdated, it still has a lot of application due to its long history and the existing legacy code. The code is written in such a manner that a user can provide a function and a specific interval and the code should in turn run iterations over the interval and should display all the possible roots within that interval. The results are compared at the end for their accuracy. The program is successful in finding out all the roots within an interval.
PIMD: An Integrative Approach for Drug Repositioning using Multiple Characterization Fusion
Authors: He Song , Wen Yuqi , Yang Xiaoxi , Liu Zhen , Song Xinyu , Huang Xin , Bo Xiaochen 
Published: October 2020

Abstract
The accumulation of various types of drug informatics data and computational approaches for drug repositioning can accelerate pharmaceutical research and development. However, the integration of multi-dimensional drug data for precision repositioning remains a pressing challenge. Here, we propose a systematic framework named PIMD to predict drug therapeutic properties by integrating multi-dimensional data for drug repositioning. In PIMD, drug similarity networks (DSNs) based on chemical, pharmacological, and clinical data are fused into an integrated DSN (iDSN) composed of many clusters. Rather than simple fusion, PIMD offers a systematic way to annotate clusters. Unexpected drugs within clusters and drug pairs with a high iDSN similarity score are therefore identified to predict novel therapeutic uses. PIMD provides new insights into the universality, individuality, and complementarity of different drug properties by evaluating the contribution of each property data. To test the performance of PIMD, we use chemical, pharmacological, and clinical properties to generate an iDSN. Analyses of the contributions of each drug property indicate that this iDSN was driven by all data types and performs better than other DSNs. Within the top 20 recommended drug pairs, 7 drugs have been reported to be repurposed. The source code for PIMD is available at https://github.com/Sepstar/PIMD/.
Endoscopic sinus surgery and aspirin desensitization improve otologic‐specific SNOT‐22 scores
Authors: Naples James G. , Corr Andrew , Tripathi Siddhant , Berman Morgan , Brant Jason A. , Ruckenstein Michael J. , Bosso John 
Published: October 2020

ObjectiveThere are few studies evaluating the impact of Aspirin‐exacerbated respiratory disease (AERD) treatment on otologic symptoms. The aim of this study is to evaluate the effects of endoscopic sinus surgery (ESS) and aspirin desensitization (AD) on otologic symptoms in subjects with AERD.MethodsRetrospective chart review of adult patients diagnosed with AERD at our tertiary Care Academic Medical Center ‐ Otorhinolaryngology Department. Charts of adult patients diagnosed with AERD who underwent ESS and ASA desensitization at our institution's AERD Center from 2016 to 2019 were reviewed. Sino‐Nasal Outcomes Test 22‐item survey (SNOT‐22) scores were evaluated for patients at various time points including: pre‐surgery, post‐surgery/pre‐aspirin desensitization, and various times post‐desensitization up to >12 months. Within the SNOT‐22, otologic‐specific subdomain scores were evaluated at similar time points. Patients on immunomodulatory medications other than corticosteroids were excluded from analysis.ResultsSNOT‐22 scores were analyzed for 121 patients. There was a significant improvement in overall SNOT scores from pre‐surgery (44.62) to post surgery/pre‐desensitization (23.34) (P < 0.0005). Similarly, SNOT‐22 otologic‐specific scores also improved after surgery prior to desensitization (3.19–2.04) (P = 0.005). Following AD, the improvement in the overall SNOT‐22 continued to improve for up to 12 months (P < 0.005). While the otologic‐specific SNOT‐22 scores remained stable after surgery and ASA desensitization.ConclusionESS and AD reduce otologic‐specific SNOT‐22 scores and parallel trends in overall SNOT‐22 scores. The effect of treatment is durable over the course of 12 months. Future work should aim to correlate otologic SNOT‐22 scores with objective otologic data.
A Gray‐Box Model for a Probabilistic Estimate of Regional Ground Magnetic Perturbations: Enhancing the NOAA Operational Geospace Model With Machine Learning
Authors: Camporeale E. , Cash M. D. , Singer H. J. , Balch C. C. , Huang Z. , Toth G. 
Published: October 2020

AbstractWe present a novel algorithm that predicts the probability that the time derivative of the horizontal component of the ground magnetic fielddB/dtexceeds a specified threshold at a given location. This quantity provides important information that is physically relevant to geomagnetically induced currents (GICs), which are electric currents associated with sudden changes in the Earth's magnetic field due to space weather events. The model follows a “gray‐box” approach by combining the output of a physics‐based model with machine learning. Specifically, we combine the University of Michigan's Geospace model that is operational at the National Oceanic and Atmospheric Administration (NOAA) Space Weather Prediction Center, with a boosted ensemble of classification trees. We discuss the problem of recalibrating the output of the decision tree to obtain reliable probabilities. The performance of the model is assessed by typical metrics for probabilistic forecasts: Probability of Detection and False Detection, True Skill Statistic, Heidke Skill Score, and Receiver Operating Characteristic curve. We show that the ML‐enhanced algorithm consistently improves all the metrics considered.
Comparison of the Flank Magnetopause at Near‐Earth and Lunar Distances: MMS and ARTEMIS Observations
Authors: Lukin A. S. , Panov E. V. , Artemyev A. V. , Petrukovich A. A. , Haaland S. , Nakamura R. , Angelopoulos V. , Runov A. , Yushkov E. V. , Avanov L. A. , Giles B. L. , Russell C. T. , Strangeway R. J. 
Published: October 2020

AbstractOne of the main sources of magnetospheric particles is solar wind penetration through the magnetopause—a current sheet separating the cold, dense magnetosheath from the hot, rarified magnetospheric plasmas. The mechanism responsible for magnetosheath particle transport across the magnetopause has been better investigated for the near‐Earth dayside magnetopause (contrary to the nightside), where it was found that such a transport is controlled by the current sheet thickness, structure, and dynamics. Because plasma properties and magnetic field intensity in the magnetosheath significantly change as a function of radial distance from the Earth, the current sheet characteristics are different near Earth and at distant nightside magnetopause. Comparative investigations between near‐Earth and distant magnetopauses, however, require statistical observations at the two locations during the same time interval, that enable control for the same upstream solar wind driving conditions. In this paper, we perform such a study using the four Magnetosheric Multiscale (MMS) and two Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) probes to compare the characteristics of magnetic field and plasma populations during magnetopause crossings, which are separated by about 50 RE. We find that the current sheet profiles is similar at two locations. We also show that the magnetopause current sheet thickness scales with the local magnetosheath ion gyroradius. A weaker magnetic field on both sides of the current sheet is correlated with smaller current density at lunar distances.
Crustal Stress State in Taiwan: Moderately Strong Crust Supporting Gravitational and Flexural Loading
Authors: Yang Yi‐Rong , Johnson Kaj M. 
Published: October 2020

AbstractIn Taiwan and other contractional tectonic wedges, there is evidence that the basal detachment is very weak and the overlying crust is relatively strong. In this study, we compute the absolute deviatoric 3‐D stress field in Taiwan using focal mechanism data and coseismic stress changes for the 1999 M7.6 Chi‐Chi earthquake. We estimate a minimum coefficient of friction of 0.3 in the upper 15 km crust, assuming hydrostatic pore pressure, consistent with a moderately strong crust. The estimated stress state is consistent with primary tectonic structures of Taiwan. The maximum compressive stress in the fold and thrust belt and the Coastal Range is approximately aligned with relative motion of the Eurasian and the Philippine Sea Plates, but the minimum and intermediate principal stresses vary laterally and with depth. A reverse‐faulting stress regime wraps around the Peikang high in western Taiwan suggesting inherited basement structure influences crustal stress state. Vertical maximum compressive stress is inferred under the high topography of the Central Range mountains. We present a simple stress model for Taiwan assuming spatial variations in gravitational potential energy are supported elastically. The model stress state is broadly consistent with the stress inversion result. The model shows that vertical maximum compressive stress in the Central Range is a result of high topography and thick crustal root. Consistent with a moderately strong crust, the model deviatoric stresses in areas of high seismicity in Taiwan are of the order 50–100 MPa. Lower deviatoric stresses under the Central Range are consistent with low rates of observed seismicity.
An Automatic Model Selection‐Based Machine Learning Framework to Estimate FORC Distributions
Authors: Heslop D. , Roberts A. P. , Oda H. , Zhao X. , Harrison R. J. , Muxworthy A. R. , Hu P.‐X. , Sato T. 
Published: October 2020

AbstractFirst‐order reversal curve (FORC) distributions are a powerful diagnostic tool for characterizing and quantifying magnetization processes in fine magnetic particle systems. Estimation of FORC distributions requires the computation of the second‐order mixed derivative of noisy magnetic hysteresis data. This operation amplifies measurement noise, and for weakly magnetic systems, it can compromise estimation of a FORC distribution. Previous processing schemes, which are based typically on local polynomial regression, have been developed to smooth FORC data to suppress detrimental noise. Importantly, the smoothed FORC distribution needs to be consistent with the measurement data from which it was estimated. This can be a challenging task even for expert users, who must adjust subjectively parameters that define the form and extent of smoothing until a “satisfactory” FORC distribution is obtained. For nonexpert users, estimation of FORC distributions using inappropriate smoothing parameters can produce distorted results corrupted by processing artifacts, which can lead to spurious inferences concerning the magnetic system under investigation. We have developed a statistical machine learning framework based on a probabilistic model comparison to guide the estimation of FORC distributions. An intuitive approach is presented that reveals regions of a FORC distribution that may have been smoothed inappropriately. An associated metric can also be used to compare data preparation and local regression schemes to assess their suitability for processing a given FORC data set. Ultimately, our approach selects FORC smoothing parameters in a probabilistic fashion, which automates the derivative estimation process regardless of user expertise.
Seismic Anisotropy of Temperate Ice in Polar Ice Sheets
Authors: Llorens M.‐G. , Griera A. , Bons P. D. , Gomez‐Rivas E. , Weikusat I. , Prior D. J. , Kerch J. , Lebensohn R. A. 
Published: October 2020

AbstractWe present a series of simple shear numerical simulations of dynamic recrystallization of two‐phase nonlinear viscous materials that represent temperate ice. First, we investigate the effect of the presence of water on the resulting microstructures and, second, how water influences on P wave (V

p
) and fast S wave (V

s
) velocities. Regardless the water percentage, all simulations evolve from a random fabric to a vertical single maximum. For a purely solid aggregate, the highest V

p
quickly aligns with the maximum c‐axis orientation. At the same time, the maximum c‐axis development reduces V

s
in this orientation. When water is present, the developed maximum c‐axis orientation is less intense, which results in lower V

p
and V

s
. At high percentage of water, V

p
does not align with the maximum c‐axis orientation. If the bulk modulus of ice is assumed for the water phase (i.e., implying that water is at high pressure), we find a remarkable decrease of V

s
while V

p
remains close to the value for purely solid ice. These results suggest that the decrease in V

s
observed at the base of the ice sheets could be explained by the presence of water at elevated pressure, which would reside in isolated pockets at grain triple junctions. Under these conditions water would not favor sliding between ice grains. However, if we consider that deformation dominates over recrystallization, water pockets get continuously stretched, allowing water films to be located at grain boundaries. This configuration would modify and even overprint the maximum c‐axis‐dependent orientation and the magnitude of seismic anisotropy.
GFDL SHiELD: A Unified System for Weather‐to‐Seasonal Prediction
Authors: Harris Lucas , Zhou Linjiong , Lin Shian‐Jiann , Chen Jan‐Huey , Chen Xi , Gao Kun , Morin Matthew , Rees Shannon , Sun Yongqiang , Tong Mingjing , Xiang Baoqiang , Bender Morris , Benson Rusty , Cheng Kai‐Yuan , Clark Spencer , Elbert Oliver D. , Hazelton Andrew , Huff J. Jacob , Kaltenbaugh Alex , Liang Zhi , Marchok Timothy , Shin Hyeyum Hailey , Stern William 
Published: October 2020

AbstractWe present the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken from the Global Forecast System. SHiELD is designed to demonstrate new capabilities within its components, explore new model applications, and to answer scientific questions through these new functionalities. A variety of configurations are presented, including short‐to‐medium‐range and subseasonal‐to‐seasonal prediction, global‐to‐regional convective‐scale hurricane and contiguous U.S. precipitation forecasts, and global cloud‐resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System or FV3‐based models, including operational implementations of the Unified Forecast System. Continued development of SHiELD has shown improvement upon existing models. The flagship 13‐km SHiELD demonstrates steadily improved large‐scale prediction skill and precipitation prediction skill. SHiELD and the coarser‐resolution S‐SHiELD demonstrate a superior diurnal cycle compared to existing climate models; the latter also demonstrates 28 days of useful prediction skill for the Madden‐Julian Oscillation. The global‐to‐regional nested configurations T‐SHiELD (tropical Atlantic) and C‐SHiELD (contiguous United States) show significant improvement in hurricane structure from a new tracer advection scheme and promise for medium‐range prediction of convective storms.
Models for Predicting Water Retention in Pyrogenic Carbon (Biochar) and Biochar‐Amended Soil at Low Water Contents
Authors: Nakhli Seyyed Ali Akbar , Imhoff Paul T. 
Published: October 2020

AbstractThe dry end of the soil water retention curve (WRC) plays an important role in various hydrologic, solute transport, plant, and microbial processes. Despite increasing application of biochar as a soil amendment, knowledge about water retention in biochars and biochar‐amended soils under dry conditions is lacking. Mechanistic models are presented to predict the WRC for biochars and biochar‐amended soils at matric potential (ψ) < ~−1 MPa. For biochars, the amount of water retained is linked to biochar surficial oxygen content and pore volume and surface area distributions. The WRC for soils at dry conditions is predicted using specific surface area. The WRC model for biochar‐amended soils is the sum of the contributions of models for biochar and soil. The model's utility was examined for three natural soils and a uniform sand, a wood‐based biochar, and 10 different combinations of these soils and biochar. The accuracy of the model for biochars was further tested for six other pyrogenic carbonaceous materials (PCMs). The models agreed well with experimental data: for the biochar and PCMs, soils, and biochar‐amended soils, the root mean square error normalized to the range of water content was almost always <10%. The line of best fit for predicted versus measured gravimetric water content at permanent wilting point had slope of 0.935 ± 0.013 and a coefficient of determination of 0.997. The applicability of these models for different biochars, soils, and their mixtures is discussed.