To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Background: The zona incerta (ZI) is a small structure in the deep brain first identified by Auguste Forel for which robust in vivo visualization has remained elusive. The increased inherent signal from ultra-high field (7-Tesla or greater; 7T) magnetic resonance imaging (MRI) presents an opportunity to see structures not previously visible. In this study, we investigated the possibility of using quantitative T1 mapping at 7T to visualize the ZI region. Methods: We recruited healthy participants (N=32) and patients being considered for deep brain stimulation therapy as part of a prospective imaging study at 7T. Computational methods were used to process and fuse images to produce a high-resolution group average from which ZI anatomy could be delineated. Results: We pooled 7T data using image fusion methods and found that the contrast from quantitative T1 mapping was strikingly similar to classic histological staining, permitting facile identification of the ZI and nearby structures in reference to conventional stereotactic atlases. Conclusions: Using computational neuroimaging techniques, we demonstrate for the first time that the ZI is visible in vivo. Furthermore, we determined that this nuclear region can be decoupled from surrounding fibre pathways. This work paves the way for more accurate patient-specific optimization of deep brain targets for neuromodulation.
Beijing–Tianjin–Hebei is the largest urban agglomeration in northern China, but the spatiotemporal patterns and risk factors concerning hepatitis B virus (HBV) incidence in this area have been unclear. The present study aimed to reveal the spatiotemporal epidemiological features of HBV infection and quantify the association between HBV infection and socio-economic risk factors. The data on HBV cases in Beijing–Tianjin–Hebei from 2007 to 2012 was collected for each county. The Bayesian space–time hierarchy model and the GeoDetector method were used to reveal spatiotemporal patterns and detect risk factors. High-risk regions were mainly distributed in the underdeveloped rural areas in the north and mid-south of the study region, while low-risk regions were mainly distributed in the urban and western areas. The HBV annual incidence rate decreased substantially over the 6-year period, dropping from 7.34/105 to 5.51/105. Compared with this overall trend, 38.5% of high-risk counties showed a faster decrease, and 35.9% of high-risk counties exhibited a slower decrease. Meanwhile, 29.7% of low-risk counties had a faster decrease, and 44.6% of low-risk counties exhibited a slower decrease. Socio-economic factors were strongly associated with the spatiotemporal patterns and variation. The population density and gross domestic product per capita were negatively associated with HBV transmission, with determinant powers of 0.17 and 0.12, respectively. The proportion of primary industry and the number of healthcare workers were positively associated with the disease incidence, with determinant powers of 0.11 and 0.8, respectively. The interactive effect between population density and the other factors exerted a greater influence on HBV transmission than that of these factors measured independently.
Environment can impact the wear behavior of metals and alloys substantially. The tribological properties of Al0.6CoCrFeNi high-entropy alloys (HEAs) were investigated in ambient air, deionized water, simulated acid rain, and simulated seawater conditions at frequencies of 2–5 Hz. The as-cast alloy was composed of simple face-centered cubic and body-centered cubic phases. The wear rate of the as-cast HEA in the ambient air condition was significantly higher than that in the liquid environment. The wear resistance in seawater was superior to that in ambient air, deionized water, and acid rain. Both the friction coefficient and wear rate in seawater were the lowest due to the formation of oxidation film, lubrication, and corrosion action in solution. The dominant wear mechanism in the ambient air condition and deionized water was abrasive wear, delamination wear, and oxidative wear. By contrast, the wear mechanism in acid rain and seawater was mainly corrosion wear, adhesive wear, abrasive wear, and oxidative wear.
The response of soil microbial communities to soil quality changes is a sensitive indicator of soil ecosystem health. The current work investigated soil microbial communities under different fertilization treatments in a 31-year experiment using the phospholipid fatty acid (PLFA) profile method. The experiment consisted of five fertilization treatments: without fertilizer input (CK), chemical fertilizer alone (MF), rice (Oryza sativa L.) straw residue and chemical fertilizer (RF), low manure rate and chemical fertilizer (LOM), and high manure rate and chemical fertilizer (HOM). Soil samples were collected from the plough layer and results indicated that the content of PLFAs were increased in all fertilization treatments compared with the control. The iC15:0 fatty acids increased significantly in MF treatment but decreased in RF, LOM and HOM, while aC15:0 fatty acids increased in these three treatments. Principal component (PC) analysis was conducted to determine factors defining soil microbial community structure using the 21 PLFAs detected in all treatments: the first and second PCs explained 89.8% of the total variance. All unsaturated and cyclopropyl PLFAs except C12:0 and C15:0 were highly weighted on the first PC. The first and second PC also explained 87.1% of the total variance among all fertilization treatments. There was no difference in the first and second PC between RF and HOM treatments. The results indicated that long-term combined application of straw residue or organic manure with chemical fertilizer practices improved soil microbial community structure more than the mineral fertilizer treatment in double-cropped paddy fields in Southern China.
A systematic review was conducted to investigate the effectiveness of fibroblast growth factor-2 on the regeneration of tympanic membrane perforation.
The PubMed database was searched for relevant studies. Experimental studies, human randomised controlled trials, prospective single-arm studies and retrospective studies reporting acute and chronic tympanic membrane perforations in relation to two healing outcomes (success rate and closure time), were selected.
All 11 clinical studies investigating the effect of fibroblast growth factor-2 on traumatic tympanic membrane perforations in humans reported a success rate of 89.3–100 per cent, with a closure time of around 2 weeks. Three studies of fibroblast growth factor-2 combined with Gelfoam showed that the success rate of chronic tympanic membrane perforation was 83–98.1 per cent in the fibroblast growth factor-2 group, but 10 per cent in the gelatine sponge groups.
Fibroblast growth factor-2 with or without biological material patching promotes regeneration in cases of acute and chronic tympanic membrane perforation, and is safe and efficient. However, the best dosage, application time and administration pathway of fibroblast growth factor-2 are still to be elucidated.
Plant height and lodging resistance can affect rice yield significantly, but these traits have always conflicted in crop cultivation and breeding. The current study aimed to establish a rapid and accurate plant type evaluation mechanism to provide a basis for breeding tall but lodging-resistant super rice varieties. A comprehensive approach integrating plant anatomy and histochemistry was used to investigate variations in flexural strength (a material property, defined as the stress in a material just before it yields in a flexure test) of the rice stem and the lodging index of 15 rice accessions at different growth stages to understand trends in these parameters and the potential factors influencing them. Rice stem anatomical structure was observed and the lignin content the cell wall was determined at different developmental stages. Three rice lodging evaluation models were established using correlation analysis, multivariate regression and artificial radial basis function (RBF) neural network analysis, and the results were compared to identify the most suitable model for predicting optimal rice plant types. Among the three evaluation methods, the mean residual and relative prediction errors were lowest using the RBF network, indicating that it was highly accurate and robust and could be used to establish a mathematical model of the morphological characteristics and lodging resistance of rice to identify optimal varieties.
The Binary Population and Spectral Synthesis suite of binary stellar evolution models and synthetic stellar populations provides a framework for the physically motivated analysis of both the integrated light from distant stellar populations and the detailed properties of those nearby. We present a new version 2.1 data release of these models, detailing the methodology by which Binary Population and Spectral Synthesis incorporates binary mass transfer and its effect on stellar evolution pathways, as well as the construction of simple stellar populations. We demonstrate key tests of the latest Binary Population and Spectral Synthesis model suite demonstrating its ability to reproduce the colours and derived properties of resolved stellar populations, including well-constrained eclipsing binaries. We consider observational constraints on the ratio of massive star types and the distribution of stellar remnant masses. We describe the identification of supernova progenitors in our models, and demonstrate a good agreement to the properties of observed progenitors. We also test our models against photometric and spectroscopic observations of unresolved stellar populations, both in the local and distant Universe, finding that binary models provide a self-consistent explanation for observed galaxy properties across a broad redshift range. Finally, we carefully describe the limitations of our models, and areas where we expect to see significant improvement in future versions.
Hand, foot and mouth disease (HFMD) risk has become an increasing concern in the Beijing–Tianjin–Hebei region, which is the biggest urban agglomeration in north-eastern Asia. In the study, spatiotemporal epidemiological features of HFMD were analysed, and a Bayesian space–time hierarchy model was used to detect local spatial relative risk (RR) and to assess the effect of meteorological factors. From 2009 to 2013, there was an obvious seasonal pattern of HFMD risk. The highest risk period was in the summer, with an average monthly incidence of 4·17/103, whereas the index in wintertime was 0·16/103. Meteorological variables influenced temporal changes in HFMD. A 1 °C rise in air temperature was associated with an 11·5% increase in HFMD (corresponding RR 1·122). A 1% rise in relative humidity was related to a 9·51% increase in the number of HFMD cases (corresponding RR 1·100). A 1 hPa increment in air pressure was related to a 0·11% decrease in HFMD (corresponding RR 0·999). A 1 h increase in sunshine was associated with a 0·28% rise in HFMD cases (corresponding RR 1·003). A 1 m/s rise in wind speed was related to a 6·2% increase in HFMD (corresponding RR 1·064). High-risk areas were mainly large cities, such as Beijing, Tianjin, Shijiazhuang and their neighbouring areas. These findings can contribute to risk control and implementation of disease-prevention policies.
Psychosocial and inflammatory factors have been associated with fatigue in breast cancer survivors. Nevertheless, the relative contribution and/or interaction of these factors with cancer-related fatigue have not been well documented.
This cross-sectional study enrolled 111 stage 0–III breast cancer patients treated with breast surgery followed by whole breast radiotherapy. Fatigue was measured by the total score of the Multidimensional Fatigue Inventory-20. Potential risk factors included inflammatory markers (plasma cytokines and their receptors and C-reactive protein; CRP), depressive symptoms (as assessed by the Inventory of Depressive Symptomatology–Self Reported), sleep (as assessed by the Pittsburgh Sleep Quality Index) and perceived stress (as assessed by the Perceived Stress Scale) as well as age, race, marital status, smoking history, menopause status, endocrine treatment, chemotherapy and cancer stage. Linear regression modeling was employed to examine risk factors of fatigue. Only risk factors with a significance level <0.10 were included in the initial regression model. A post-hoc mediation model using PROCESS SPSS was conducted to examine the association among depressive symptoms, sleep problems, stress, inflammation and fatigue.
At 1 year post-radiotherapy, depressive symptoms (p<0.0001) and inflammatory markers (CRP: p = 0.015; interleukin-1 receptor antagonist: p = 0.014; soluble tumor necrosis factor receptor-2: p = 0.009 in separate models) were independent risk factors of fatigue. Mediation analysis showed that depressive symptoms also mediated the associations of fatigue with sleep and stress.
Depressive symptoms and inflammation were independent risk factors for cancer-related fatigue at 1 year post-radiotherapy, and thus represent independent treatment targets for this debilitating symptom.
We carried out a pivot experiment to select distant luminous late-type stars on the basis on their 2MASS and GLIMPSE photometry. Low-resolution infrared spectra enabled us to measure the equivalent widths (EWs) of their CO band-heads at 2.293 μm, and to confirm an extraordinarily high detection rate of red supergiants (RSGs), i.e. 61% (Messineo et al. (2016)).
We present a number of notable results from the VLT-FLAMES Tarantula Survey (VFTS), an ESO Large Program during which we obtained multi-epoch medium-resolution optical spectroscopy of a very large sample of over 800 massive stars in the 30 Doradus region of the Large Magellanic Cloud (LMC). This unprecedented data-set has enabled us to address some key questions regarding atmospheres and winds, as well as the evolution of (very) massive stars. Here we focus on O-type runaways, the width of the main sequence, and the mass-loss rates for (very) massive stars. We also provide indications for the presence of a top-heavy initial mass function (IMF) in 30 Dor.
Eta Carinae is one of the most massive observable binaries. Yet determination of its orbital and physical parameters is hampered by obscuring winds. However the effects of the strong, colliding winds changes with phase due to the high orbital eccentricity. We wanted to improve measures of the orbital parameters and to determine the mechanisms that produce the relatively brief, phase-locked minimum as detected throughout the electromagnetic spectrum. We conducted intense monitoring of the He ii λ4686 line in η Carinae for 10 months in the year 2014, gathering ~300 high S/N spectra with ground- and space-based telescopes. We also used published spectra at the FOS4 SE polar region of the Homunculus, which views the minimum from a different direction. We used a model in which the He ii λ4686 emission is produced by two mechanisms: a) one linked to the intensity of the wind-wind collision which occurs along the whole orbit and is proportional to the inverse square of the separation between the companion stars; and b) the other produced by the ‘bore hole’ effect which occurs at phases across the periastron passage. The opacity (computed from 3D SPH simulations) as convolved with the emission reproduces the behavior of equivalent widths both for direct and reflected light. Our main results are: a) a demonstration that the He ii λ4686 light curve is exquisitely repeatable from cycle to cycle, contrary to previous claims for large changes; b) an accurate determination of the longitude of periastron, indicating that the secondary star is ‘behind’ the primary at periastron, a dispute extended over the past decade; c) a determination of the time of periastron passage, at ~4 days after the onset of the deep light curve minimum; and d) show that the minimum is simultaneous for observers at different lines of sight, indicating that it is not caused by an eclipse of the secondary star, but rather by the immersion of the wind-wind collision interior to the inner wind of the primary.
Simultaneously and coherently studying the large-scale magnetic field and the stellar pulsations of a massive star provides strong complementary diagnostics suitable for detailed stellar modelling. This hybrid method is called magneto-asteroseismology and permits the determination of the internal structure and conditions within magnetic massive pulsators, for example the effect of magnetism on non-standard mixing processes. Here, we overview this technique, its requirements, and list the currently known suitable stars to apply the method.
A substantial number of core-collapse supernovae (CCSNe) are expected to be hosted by starbursting luminous infrared galaxies (LIRGs). However, so far very few CCSNe have been discovered in LIRGs, most likely as a result of dust extinction and lack of contrast in their typically luminous and complex nuclear regions. We present the first results of Project SUNBIRD (Supernovae UNmasked By InfraRed Detection), where we aim to uncover dust-obscured nuclear supernovae by monitoring over 30 LIRGs, using near-infrared state-of-the-art Laser Guide Star Adaptive Optics (LGSAO) imaging on the Gemini South and Keck telescopes. Such discoveries are vital for determining the fraction of supernovae which will be missed as a result of dust obscuration by current and future optical surveys.
In the last decades, stellar atmosphere models have become a key tool in understanding massive stars. Applied for spectroscopic analysis, these models provide quantitative information on stellar wind properties as well as fundamental stellar parameters. The intricate non-LTE conditions in stellar winds dictate the development of adequate sophisticated model atmosphere codes. The increase in both, the computational power and our understanding of physical processes in stellar atmospheres, led to an increasing complexity in the models. As a result, codes emerged that can tackle a wide range of stellar and wind parameters.
After a brief address of the fundamentals of stellar atmosphere modeling, the current stage of clumped and line-blanketed model atmospheres will be discussed. Finally, the path for the next generation of stellar atmosphere models will be outlined. Apart from discussing multi-dimensional approaches, I will emphasize on the coupling of hydrodynamics with a sophisticated treatment of the radiative transfer. This next generation of models will be able to predict wind parameters from first principles, which could open new doors for our understanding of the various facets of massive star physics, evolution, and death.
We present the first detailed three-dimensional hydrodynamic implicit large eddy simulations of turbulent convection for carbon burning. The simulations start with an initial radial profile mapped from a carbon burning shell within a 15 M⊙ stellar evolution model. We considered 4 resolutions from 1283 to 10243 zones. These simulations confirm that convective boundary mixing (CBM) occurs via turbulent entrainment as in the case of oxygen burning. The expansion of the boundary into the surrounding stable region and the entrainment rate are smaller at the bottom boundary because it is stiffer than the upper boundary. The results of this and similar studies call for improved CBM prescriptions in 1D stellar evolution models.
While the imparting of velocity ‘kicks’ to compact remnants from supernovae is widely accepted, the relationship of the ‘kick’ to the progenitor is not. We propose the ‘kick’ is predominantly a result of conservation of momentum between the ejected and compact remnant masses. We propose the ‘kick’ velocity is given by vkick = α(Mejecta/Mremnant)+β, where α and β are constants we wish to determine. To test this we use the BPASS v2 (Binary Population and Spectral Synthesis) code to create stellar populations from both single star and binary star evolutionary pathways. We then use our Remnant Ejecta and Progenitor Explosion Relationship (REAPER) code to apply ‘kicks’ to neutron stars from supernovae in these models using a grid of α and β values, (from 0 to 200 km s−1 in steps of 10 km s−1), in three different ‘kick’ orientations, (isotropic, spin-axis aligned and orthogonal to spin-axis) and weighted by three different Salpeter initial mass functions (IMF’s), with slopes of -2.0, -2.35 and -2.70. We compare our synthetic 2D and 3D velocity probability distributions to the distributions provided by Hobbs et al. (1995).
We have recently released version 2.0 of the Binary Population and Spectral Synthesis (BPASS) population synthesis code. This is designed to construct the spectra and related properties of stellar populations built from ~200,000 detailed, individual stellar models of known age and metallicity. The output products enable a broad range of theoretical predictions for individual stars, binaries, resolved and unresolved stellar populations, supernovae and their progenitors, and compact remnant mergers. Here we summarise key applications that demonstrate that binary populations typically reproduce observations better than single star models.