bluuebunny/crossref_metadata_2025_split huggingface dataset:
Avaliação comparativa das dimensões do enxerto do coracoide na cirurgia de Latarjet para instabilidade glenoumeral anterior
Authors: Alves Bernardo V.P. , Silva Gabriel S. , Matsumoto Fábio Y. , Ferreira Marco T. , Britto Almiro G. , Mothes Fernando C. 
Published: January 2020

Resumo
Objetivo O objetivo deste estudo foi descrever as dimensões do processo coracoide em nossas cirurgias de Latarjet e compará-las com os resultados descritos na literatura. Além disso, a viabilidade da regra dos 7 milímetros foi verificada.
Métodos Indivíduos com instabilidade glenoumeral anterior com ou sem erosão óssea participaram deste estudo. As dimensões de 31 enxertos de processo coracoide de pacientes operados pela técnica de Latarjet foram mensuradas com um paquímetro analógico e registradas para análise posterior.
Resultados As dimensões do processo coracoide não demonstraram diferença estatisticamente significativa de acordo com o sexo. A largura do enxerto obtida em nossa amostra apresentou semelhança com as dimensões descritas na literatura. No entanto, o comprimento e a espessura foram um pouco menores quando comparados com o estudo de referência (Young et al, 2013).15 A regra dos 7 milímetros foi considerada viável com as dimensões do enxerto obtidas em nossa amostra.
Conclusão As dimensões do enxerto do coracoide foram similares às descritas na literatura em relação à largura, mas o mesmo não foi encontrado quanto ao comprimento e espessura; e a regra dos 7 milímetros demonstrou viabilidade com as dimensões do enxerto obtidas em nossa amostra.
Polydatin ameliorates chemotherapy-induced cognitive impairment (chemobrain) by inhibiting oxidative stress, inflammatory response, and apoptosis in rats
Authors: Tong Yifan , Wang Kaijie , Sheng Shuhai , Cui Jianzhong 
Published: January 2020

ABSTRACTMost breast cancer survivors receiving chemotherapy have severe cognitive impairment, often referred to as “chemobrain.” Polydatin (PLD) is known to have many biological activities. Thus, this study aimed to determine whether symptoms of chemobrain can be prevented or relieved by PLD. The chemobrain models were established by intraperitoneal injection of doxorubicin (DOX, 2 mg/kg) in rats once a week for 4 weeks (DOX group and DOX+PLD group). In the PLD group and DOX+PLD group, PLD (50 mg/kg) was administered orally to rats every day. We found that PLD treatment significantly protected against DOX-induced learning and memory impairment, restored hippocampal histopathological architecture. Furthermore, PLD suppressed DOX-induced oxidative stress through up-regulating Nrf2, inhibited inflammatory response by activating the NF-κB pathway, and reduced hippocampal apoptosis. Therefore, the present study indicated that PLD offered neuroprotection against DOX-induced chemobrain. PLD may assist in preventing chemobrain after chemotherapy in patients with cancers.
Realization of a universal quantum pressure standard
Authors: Shen Pinrui , Madison Kirk W , Booth James L 
Published: January 2020

Abstract
We report the realization of the first cold-atom primary standard. This standard is based on a universal law governing quantum diffractive collisions between particles that allows an experimental determination of the velocity averaged total collision cross section, the only parameter required to quantify the pressure or flux of particles given a sensor particle collision rate measurement. Using an ensemble of 87Rb sensor atoms, we show that this new quantum pressure standard can be applied to gases of both atomic (He, Ar, and Xe) and molecular species (

N

2

,

C
O

2

, and

H

2

), surpassing the scope of existing orifice flow pressure standards. We verify the accuracy of this new standard using an ionization gauge (IG) calibrated for N2 by an orifice flow standard. The gauge calibration factors determined by the cold atom and orifice flow standards differ by less than 0.5% and, thus, agree within their uncertainties of 2% and 2.8% respectively. Using this standard, we evaluate the response of two different IGs to a variety of different gas species and report variations of up to 20% for their measured calibration factors. We also observe a non-linear response of the IG readings for CO2 gas. Finally, we demonstrate the use of a magneto-optical trap (MOT) as a transfer standard to extend the measurement range by a factor of 100 to include pressures up to P ~ 10−5 Pa.
A biarticular passive exosuit to support balance control can reduce metabolic cost of walking
Authors: Barazesh Hamid , Ahmad Sharbafi Maziar 
Published: January 2020

Abstract
Nowadays, the focus on the development of assistive devices just for people with mobility disorders has shifted towards enhancing physical abilities of able-bodied humans. As a result, the interest in the design of cheap and soft wearable exoskeletons (called exosuits) is distinctly growing. In this paper, a passive lower limb exosuit with two biarticular variable stiffness elements is introduced. These elements are in parallel to the hamstring muscles of the leg and controlled based on a new version of the FMCH (force modulated compliant hip) control framework in which the force feedback is replaced by the length feedback (called LMCH). The main insight to employ leg length feedback is to develop a passive exosuit. Fortunately, similar to FMCH, the LMCH method also predicts human-like balance control behaviours, such as the VPP (virtual pivot point) phenomenon, observed in human walking. Our simulation results, using a neuromuscular model of human walking, demonstrate that this method could reduce the metabolic cost of human walking by 10%. Furthermore, to validate the design and simulation results, a preliminary version of this exosuit comprised of springs with constant stiffness was built. An experiment with eight healthy subjects was performed. We made a comparison between the walking experiments while the exosuit is worn but the springs were slack and those when the appropriate springs were contributing. It shows that passive biarticular elasticity can result in a metabolic reduction of 14.7

4.27%. More importantly, compared to unassisted walking (when exosuit is not worn), such a passive device can reduce walking metabolic cost by 4.68

4.24%.
Estimating site-specific optimum air temperature and assessing its effect on the photosynthesis of grasslands in mid- to high-latitudes
Authors: Chang Qing , Xiao Xiangming , Wu Xiaocui , Doughty Russell , Jiao Wenzhe , Bajgain Rajen , Qin Yuanwei , Wang Jie 
Published: January 2020

Abstract
The effect of air temperature on photosynthesis is important for the terrestrial carbon cycle. The optimum air temperature for photosynthesis is one of the major parameters in data-driven and process-based photosynthesis models that estimate the gross primary production (GPP) of vegetation under a changing climate. To date, most models use the biome-specific optimum air temperature (

T

o
p
t
−
b

) parameter. To what degree will the site-specific optimum air temperature (

T

o
p
t
−
s

) affect GPP simulation results remains unclear. In this study, we estimated

T

o
p
t
−
s

by using GPP data from 11 grassland eddy flux tower sites (GPPEC) and satellite vegetation indices (NDVI and EVI). We found that T
opt-s parameter values estimated from EVI have good consistency with those from GPPEC at individual sites. We also evaluated the effects of site-specific and biome-specific optimum air temperature parameters on grassland photosynthesis. The results showed that the use of

T

o
p
t
−
s

in the Vegetation Photosynthesis Model improved to various degrees in both daily and annual GPP estimates in those grassland flux tower sites. Our results highlight the necessity and potential for the use of

T

o
p
t
−
s

in terrestrial GPP models, especially in those situations with large temperature variation (heatwave and cold spill events).
Sub-national variability of wind power generation in complex terrain and its correlation with large-scale meteorology
Authors: Pickering Bryn , Grams Christian M , Pfenninger Stefan 
Published: January 2020

Abstract
The future European electricity system will depend heavily on variable renewable generation, including wind power. To plan and operate reliable electricity supply systems, an understanding of wind power variability over a range of spatio-temporal scales is critical. In complex terrain, such as that found in mountainous Switzerland, wind speeds are influenced by a multitude of meteorological phenomena, many of which occur on scales too fine to capture with commonly used meteorological reanalysis datasets. Past work has shown that anticorrelation at a continental scale is an important way to help balance variable generation. Here, we investigate systematically for the first time the possibility of balancing wind variability by exploiting anticorrelation between weather patterns in complex terrain. We assess the capability for the Consortium for Small-scale Modeling (COSMO)-REA2 and COSMO-REA6 reanalyses (with a 2 and 6 km horizontal resolution, respectively) to reproduce historical measured data from weather stations, hub height anemometers, and wind turbine electricity generation across Switzerland. Both reanalyses are insufficient to reproduce site-specific wind speeds in Switzerland’s complex terrain. We find however that mountain-valley breezes, orographic channelling, and variability imposed by European-scale weather regimes are represented by COSMO-REA2. We discover multi-day periods of wind electricity generation in regions of Switzerland which are anticorrelated with neighbouring European countries. Our results suggest that significantly more work is needed to understand the impact of fine scale wind power variability on national and continental electricity systems, and that higher-resolution reanalyses are necessary to accurately understand the local variability of renewable generation in complex terrain.
Synthesis of WS2/CNT hybrid nanoparticles for fabrication of hybrid aluminum matrix nanocomposite
Authors: Vaziri Hossein Salehi , Shokuhfar Ali , Afghahi Seyyed Salman Seyyed 
Published: January 2020

Abstract
In this study, a simple, safe and cost-effective method was developed for fabricating the tungsten disulfide/carbon nanotube (WS2/CNT) hybrid nanoparticles via chemical vapor deposition (CVD) process. Hybrid nanoparticles used for reinforcing the aluminum matrix. The hybrid nanocomposites were prepared by powder metallurgy processing and consolidated by the Hot-Pressing process. The chemical composition and morphology of the WS2/CNT hybrid particles were studied by x-ray diffraction (XRD), filed emission scanning electron microscopy (FESEM), Raman spectra, Fourier-transform infrared spectroscopy (FTIR) and thermo gravimetric analysis (TGA). The results proved that the uniform, pure and tubular WS2/ CNT hybrid nanoparticles were produced and WS2 nanoparticles were decorated the CNT surface successfully. Optical microscopy (OM) and FESEM used for characterization of the microstructure of hybrid nanocomposite, indicate a good distribution of hybrid nanoparticles in the aluminum matrix. Maximum values of relative density, hardness and compressive strength were measured for sample with WS2/CNT ratio of 1:1. A relative density of more than 99.5% was obtained for this sample. Hardness and compressive strength were improved by 43% and 60% compared with pure aluminum respectively.
High performance Fe–N–C oxygen reduction electrocatalysts by solid-phase preparation of metal–organic frameworks
Authors: Hou Bingxue , Wang Cheng Cheng , Tang Rui , Zhang Qi , Cui Xumei 
Published: January 2020

Abstract
Iron-nitrogen-carbon (Fe–N–C) compounds have been regarded as efficient and non-precious metal electrocatalysts for oxygen reduction reaction (ORR). The environmentally friendly preparation of Fe–N–C electrocatalysts is desirable but still challenging. Here, several Fe–N–C catalysts incorporated by ZIF-8 has been simply prepared by solid state reaction method. Fe–N–C containing 2% mole percentage Fe electrocatalysts fired at 900 °C exhibited superior intrinsic activities in oxygen saturated-0.1 M KOH for ORR with half wave potential of 0.831 V (versus RHE), comparable with Pt/C from JM (0.838 V). It also exhibited higher stability than those of Pt–C in alkaline condition. The higher intrinsic ORR activity and remarkable stability can be due to the more dispersed Fe–Nx active sites, which indicate that Fe–N–C by 2% mole percentage Fe electrocatalyst is an excellent alternative electrocatalyst for energy applications.
Cu(II) and Gd(III) doped boehmite nanostructures: a comparative study of electrical property and thermal stability
Authors: Roy Shubham , Bardhan Souravi , Chanda Dipak Kr , Maity Anupam , Ghosh Saheli , Mondal Dhananjoy , Singh Subhankar , Das Sukhen 
Published: January 2020

Abstract
The present article reports the effect of transition (Cu2+) and rare earth metal (Gd3+) ion doping on structural, microstructural and electrical properties of boehmite nanoparticles. Rietveld refinement is adopted here to refine the x-ray diffractograms for further analyzing the microstructural details and their alteration due to the incorporation of foreign cations. This is probably the first time when dielectric properties of these doped boehmite samples having been reported herein. These samples show remarkably high dielectric constant values which corroborate that doping enhances the microstrain values inside the orthorhombic structure and results in higher crystallographic defects. Enhancement in defect sites causes the augmentation of relative permittivity and ac conductivity. Temperature stability has also been enhanced significantly in our Cu-doped sample. The present study enables us to determine a relationship between crystalline deformation and electrical properties of nanomaterials which may be highly beneficial in fabricating cost-effective energy harvesting devices.
High-temperature mechanical properties of cast Al–Si–Cu–Mg alloy by combined additions of cerium and zirconium
Authors: Bevilaqua William Lemos , Stadtlander Antonio Ricardo , Froehlich Andre Ronaldo , Lemos Guilherme Vieira Braga , Reguly Afonso 
Published: January 2020

Abstract
The main aim of this work is to investigate the effects of combinative Ce and Zr additions (0.3 wt% Ce + 0.16 wt% Zr; 0.3 wt% Ce + 0.27 wt% Zr and 0.3 wt% Ce + 0.36 wt% Zr) on the microstructure and mechanical properties in cast Al–Si–Cu–Mg alloy. The microstructures features were investigated by optical microscope, scanning electron microscope and hardness measurements. The microstructural analysis has shown that the increase of Ce and Zr contents increases the volume fraction of intermetallics formed during the solidification leading to grain refinement and changes in silicon morphology of the as-cast microstructure. The intermetallics formed do not dissolve during the solution heating treatment (T6). The mechanical behavior at room and high temperatures (175, 210, 245 and 275 °C) was determined from uniaxial tensile tests. The high thermal stability of Al–Si–Cu–La–Ce and Al–Si–Zr–Ti–Mg phases found in microstructure, in particular for the alloy containing 0.3 wt% Ce + 0.27 wt% Zr, is responsible for the increase to 6.7% and 5.1% the ultimate strength at 210 °C and 275 °C respectively, compared with the standard alloy.
Automatic phase space generation for Monte Carlo calculations of intensity modulated particle therapy
Authors: Wang Qianxia , Zhu Cong , Bai Xuemin , Deng Yu , Schlegel Nicki , Adair Antony , Chen Zhi , Li Yongqiang , Moyers Michael , Yepes Pablo 
Published: January 2020

Abstract
Monte Carlo (MC) is generally considered as the most accurate dose calculation tool for particle therapy. However, a proper description of the beam particle kinematics is a necessary input for a realistic simulation. Such a description can be stored in phase space (PS) files for different beam energies. A PS file contains kinetic information such as energies, positions and travelling directions for particles traversing a plane perpendicular to the beam direction. The accuracy of PS files plays a critical role in the performance of the MC method for dose calculations. A PS file can be generated with a set of parameters describing analytically the beam kinematics. However, determining such parameters can be tedious and time consuming. Thus, we have developed an algorithm to obtain those parameters automatically and efficiently. In this paper, we presented such an algorithm and compared dose calculations using PS automatically generated for the Shanghai Proton and Heavy Ion Center (SPHIC) with measurements. The gamma-index for comparing calculated depth dose distributions (DDD) with measurements are above 96.0% with criterion 0.6%/0.6 mm. For each single energy, the mean difference percentage between calculated lateral spot sizes at 5 different locations along beam direction and measurements are below 3.5%.
Invited Commentary: Methods for Estimating Effects of Minimum Wages on Health
Authors: Leigh J Paul 
Published: January 2020

AbstractEconomists have been researching effects of minimum wages on unemployment, poverty, income inequality, and educational attainment for over 60 years. Epidemiologists have only recently begun researching minimum wages even though unemployment through education are central topics within social epidemiology. Buszkiewicz et al. (Am J Epidemiol. 2021;190(1):21–30) offer a welcome addition to this nascent literature. A commanding advantage of Buszkiewicz et al.’s study over others is its distinction between a “likely affected” group comprised of workers with ≤12 years of schooling versus “not likely affected” groups with ≥13 years of schooling. But there are disadvantages, common to other studies. Buszkiewicz et al. use cross-sectional data; they include the self-employed as well as part-time and part-year workers in their treatment groups. Their definitions of affected groups based on education create samples with 75% or more of workers who earn significantly above minimum wages; definitions are not based on wages. Inclusion of workers not subject to (e.g., self-employed) or affected by minimum wages biases estimates toward the null. Finally, within any minimum wage data set, it is the state—not federal—increases that account for the lion’s share of increases and that form the natural experiments; however, state increases can occur annually whereas the development of chronic diseases might take decades.
Towards intercrop ideotypes: non-random trait assembly can promote overyielding and stability of species proportion in simulated legume-based mixtures
Authors: Louarn Gaëtan , Barillot Romain , Combes Didier , Escobar-Gutiérrez Abraham 
Published: January 2020

Abstract

Backgrounds and Aims
A major challenge when supporting the development of intercropping systems remains the design of efficient species mixtures. The ecological processes that sustain overyielding of legume-based mixtures compared to pure crops are well known, but their links to plant traits remain to be unravelled. A common assumption is that enhancing trait divergence among species for resource acquisition when assembling plant mixtures should increase species complementarity and improve community performance.

Methods
The Virtual Grassland model was used to assess how divergence in trait values between species on four physiological functions (namely light and mineral N acquisition, temporal development, and C–N use efficiency) affected overyielding and mixture stability in legume-based binary mixtures. A first step allowed us to identify the model parameters that were most important to interspecies competition. A second step involved testing the impact of convergent and divergent parameter (or trait) values between species on virtual mixture performance.

Results
Maximal overyielding was achieved in cases where trait values were divergent for the physiological functions controlling N acquisition and temporal development but convergent for light interception. It was also found that trait divergence should not affect competitive abilities of legume and non-legumes at random. Indeed, random trait combinations frequently led to reduced mixture yields when compared to a perfectly convergent neutral model. Combinations with the highest overyielding also tended to be associated with mixture instability and decreasing legume biomass proportion. Achieving both high overyielding and mixture stability was only found to be possible under low or moderate N levels, using combinations of traits adapted to each environment.

Conclusions
No simple assembly rule based on trait divergence could be confirmed. Plant models able to infer plant–plant interactions can be helpful for the identification of major interaction traits and the definition of ideotypes adapted to a targeted intercropping system.
Parameter estimation for functional–structural plant models when data are scarce: using multiple patterns for rejecting unsuitable parameter sets
Authors: Wang Ming , White Neil , Hanan Jim , He Di , Wang Enli , Cribb Bronwen , Kriticos Darren J , Paini Dean , Grimm Volker 
Published: January 2020

Abstract

Background and Aims
Functional–structural plant (FSP) models provide insights into the complex interactions between plant architecture and underlying developmental mechanisms. However, parameter estimation of FSP models remains challenging. We therefore used pattern-oriented modelling (POM) to test whether parameterization of FSP models can be made more efficient, systematic and powerful. With POM, a set of weak patterns is used to determine uncertain parameter values, instead of measuring them in experiments or observations, which often is infeasible.

Methods
We used an existing FSP model of avocado (Persea americana ‘Hass’) and tested whether POM parameterization would converge to an existing manual parameterization. The model was run for 10 000 parameter sets and model outputs were compared with verification patterns. Each verification pattern served as a filter for rejecting unrealistic parameter sets. The model was then validated by running it with the surviving parameter sets that passed all filters and then comparing their pooled model outputs with additional validation patterns that were not used for parameterization.

Key Results
POM calibration led to 22 surviving parameter sets. Within these sets, most individual parameters varied over a large range. One of the resulting sets was similar to the manually parameterized set. Using the entire suite of surviving parameter sets, the model successfully predicted all validation patterns. However, two of the surviving parameter sets could not make the model predict all validation patterns.

Conclusions
Our findings suggest strong interactions among model parameters and their corresponding processes, respectively. Using all surviving parameter sets takes these interactions into account fully, thereby improving model performance regarding validation and model output uncertainty. We conclude that POM calibration allows FSP models to be developed in a timely manner without having to rely on field or laboratory experiments, or on cumbersome manual parameterization. POM also increases the predictive power of FSP models.