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We here present a comparison of methods for the pretreatment of a batch of tree rings for high-precision measurement of radiocarbon at the Aarhus AMS Centre (AARAMS), Aarhus University, Denmark. The aim was to develop an efficient and high-throughput method able to pretreat ca. 50 samples at a time. We tested two methods for extracting α-cellulose from wood to find the most optimal for our use. One method used acetic acid, the other used HCl acid for the delignification. The testing was conducted on background 14C samples, in order to assess the effect of the different pretreatment methods on low-activity samples. Furthermore, the extracted wood and cellulose fractions were analyzed using Fourier transform infrared (FTIR) spectroscopy, which showed a successful extraction of α-cellulose from the samples. Cellulose samples were pretreated at AARAMS, and the graphitization and radiocarbon analysis of these samples were done at both AARAMS and the radiocarbon dating laboratory at Lund University to compare the graphitization and AMS machine performance. No significant offset was found between the two sets of measurements. Based on these tests, the pretreatment of tree rings for high-precision radiocarbon analysis at AARAMS will henceforth use HCI for the delignification.
The prespecification of the network is one of the biggest hurdles for applied researchers in undertaking spatial analysis. In this letter, we demonstrate two results. First, we derive bounds for the bias in nonspatial models with omitted spatially-lagged predictors or outcomes. These bias expressions can be obtained without prior knowledge of the network, and are more informative than familiar omitted variable bias formulas. Second, we derive bounds for the bias in spatial econometric models with nondifferential error in the specification of the weights matrix. Under these conditions, we demonstrate that an omitted spatial input is the limit condition of including a misspecificed spatial weights matrix. Simulated experiments further demonstrate that spatial models with a misspecified weights matrix weakly dominate nonspatial models. Our results imply that, where cross-sectional dependence is presumed, researchers should pursue spatial analysis even with limited information on network ties.
Radiocarbon (14C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.
Connecting calendar ages to radiocarbon (14C) ages, i.e. constructing a calibration curve, requires 14C samples that represent, or are closely connected to, atmospheric 14C values and that can also be independently dated. In addition to these data, there is information that can serve as independent tests of the calibration curve. For example, information from ice core radionuclide data cannot be directly incorporated into the calibration curve construction as it delivers less direct information on the 14C age–calendar age relationship but it can provide tests of the quality of the calibration curve. Furthermore, ice core ages on 14C-dated volcanic eruptions provide key information on the agreement of ice core and radiocarbon time scales. Due to their scarcity such data would have little impact if directly incorporated into the calibration curve. However, these serve as important “anchor points” in time for independently testing the calibration curve and/or ice-core time scales. Here we will show that such information largely supports the new IntCal20 calibration record. Furthermore, we discuss how floating tree-ring sequences on ice-core time scales agree with the new calibration curve. For the period around 40,000 years ago we discuss unresolved differences between ice core 10Be and 14C records that are possibly related to our limited understanding of carbon cycle influences on the atmospheric 14C concentration during the last glacial period. Finally, we review the results on the time scale comparison between the Greenland ice-core time scale (GICC05) and IntCal20 that effectively allow a direct comparison of 14C-dated records with the Greenland ice core data.
This paper presents a novel GaN-based digital outphasing power amplifier (PA) for the 800 MHz range. The PA reaches a maximum output power of 5.8 W at 30 V final-stage (FS) drain supply voltage. A novel output combiner circuit is used and efficiency is improved by resonant commutation of the FSs and optimized driver circuits for the two GaN push-pull FSs. 3D electromagnetic simulation of output network has been conducted to extract an equivalent circuit model and to access full information in terms of functionality and broadband impedance characteristics for optimized outphasing operation in the final design. Measured total efficiencies (ηtot) of 59 and 25% at 0 and 10 dB power back-off are achieved, respectively, fitting the simulation quite well. The proposed digital outphasing module is a promising candidate for fully digitized base-station architectures in future wireless communications.
Sketching is a natural and intuitive communication tool used for expressing concepts or ideas which are difficult to communicate through text or speech alone. Sketching is therefore used for a variety of purposes, from the expression of ideas on two-dimensional (2D) physical media, to object creation, manipulation, or deformation in three-dimensional (3D) immersive environments. This variety in sketching activities brings about a range of technologies which, while having similar scope, namely that of recording and interpreting the sketch gesture to effect some interaction, adopt different interpretation approaches according to the environment in which the sketch is drawn. In fields such as product design, sketches are drawn at various stages of the design process, and therefore, designers would benefit from sketch interpretation technologies which support these differing interactions. However, research typically focuses on one aspect of sketch interpretation and modeling such that literature on available technologies is fragmented and dispersed. In this paper, we bring together the relevant literature describing technologies which can support the product design industry, namely technologies which support the interpretation of sketches drawn on 2D media, sketch-based search interactions, as well as sketch gestures drawn in 3D media. This paper, therefore, gives a holistic view of the algorithmic support that can be provided in the design process. In so doing, we highlight the research gaps and future research directions required to provide full sketch-based interaction support.
Despite its numerous side effects, clozapine is still the most effective antipsychotics making it an ideal reference substance to validate the efficacy of novel compounds for the treatment of schizophrenia. However, blood–brain barrier permeability for most new molecular entities is unknown, requiring central delivery. Thus, we performed a dose-finding study for chronic intracerebroventricular (icv) delivery of clozapine in mice.
Specifically, we implanted wild-type C57BL/6J mice with osmotic minipumps (Alzet) delivering clozapine at a rate of 0.15 µl/h at different concentrations (0, 3.5, 7 and 14 mg/ml, i.e. 0, 12.5, 25 and 50 µg/day). Mice were tested weekly in a modified SHIRPA paradigm, for locomotor activity in the open field and for prepulse inhibition (PPI) of the acoustic startle response (ASR) for a period of 3 weeks.
None of the clozapine concentrations caused neurological deficits or evident gross behavioural alterations in the SHIRPA paradigm. In male mice, clozapine had no significant effect on locomotor activity or PPI of the ASR. In female mice, the 7 and 14 mg/ml dose of clozapine significantly affected both open field activity and PPI, while 3.5 mg/ml of clozapine increased PPI but had no effects on locomotor activity.
Our findings indicate that 7 mg/ml may be the optimal dose for chronic icv delivery of clozapine in mice, allowing comparison to screen for novel antipsychotic compounds.
The Large and Small Magellanic Cloud (LMC and SMC) are the most luminous dwarf galaxy satellites of the Milky Way. Thanks to their close proximity (50-60 kpc), they provide one of the best opportunities to study in detail the kinematics of resolved stellar populations in an interacting pair of galaxies. Large photometric surveys like the ongoing Gaia mission and the near-infrared VISTA survey of the Magellanic Cloud system (VMC) will have a significant impact on our insight into the Magellanic system. We have combined the individual strengths of VMC and Gaia DR2 data to improve our understanding of the internal kinematics of the galaxies. In this study, we present results from our ongoing project dedicated to measure and analyse the proper motions of large samples of stars across the Magellanic Clouds, efficiently removing Milk Way foreground stars utilising distances derived with the StarHorse code.
Instrumental variable (IV) methods are widely used to address endogeneity concerns. Yet, a specific kind of endogeneity – spatial interdependence – is regularly ignored. We show that ignoring spatial interdependence in the outcome results in asymptotically biased estimates even when instruments are randomly assigned. The extent of this bias increases when the instrument is also spatially clustered, as is the case for many widely used instruments: rainfall, natural disasters, economic shocks, and regionally- or globally-weighted averages. Because the biases due to spatial interdependence and predictor endogeneity can offset, addressing only one can increase the bias relative to ordinary least squares. We demonstrate the extent of these biases both analytically and via Monte Carlo simulation. Finally, we discuss a general estimation strategy – S-2SLS – that accounts for both outcome interdependence and predictor endogeneity, thereby recovering consistent estimates of predictor effects.
Previous qualitative research analyzing social media and online community discussions highlighted the symptomatic burden of cough and mucus (sputum), alongside shortness of breath, in patients with chronic obstructive pulmonary disease (COPD). The objective of this study was to determine the relative importance of these symptoms and their consequences (for example, disturbed sleep) to COPD patients, compared with conventional COPD endpoints (lung function and exacerbations).
A total of 1,050 patients (at least 40 years of age) with moderate to severe COPD or chronic bronchitis, and regular symptoms of cough and excess mucus production, are to be recruited through patient advocacy groups (PAGs) from five countries (Australia, France, Japan, the United Kingdom, and the United States; 150 to 400 patients per country). A discrete choice experiment was designed with input from clinical experts and the PAGs, plus scientific advice from the National Institute for Health and Care Excellence (NICE) in the United Kingdom. Patients’ preferences for the conditional relative importance of symptoms and impact of COPD will be quantified based on trade-offs they are willing to make among hypothetical COPD disease state profiles, described by differing attributes and levels. Hierarchical Bayesian analysis with effect-coding parameterization will be undertaken on the choice data to estimate (using Gibbs sampling) the relative value each respondent places on an attribute level.
The feedback from NICE informed the selection of screening criteria and the statistical analysis plan, as well as the inclusion of a health status measure, the EQ-5D-3L. Qualitative patient interviews and pilot testing of the attributes and levels grid have been completed, informing finalization of the online survey design.
Patient preference studies evaluating the relative importance of symptom burden through assessment of disease state preference values are an important new form of patient-based evidence for informing value-based decision making in HTA. The present study should facilitate a more patient-centered approach to developing new treatments for and improving the care of patients with COPD.
Instruments based on realizations of the endogenous variable in other units—for instance, regional or global weighted averages—are commonly used in political science. Such spatial instruments have proved attractive: they are convenient to obtain, typically have power, and are plausibly exogenous. We argue that the assumptions underlying spatial instruments remain poorly understood and challenge whether spatial instruments can satisfy the conditions required for valid instruments. First, when cross-unit dependence exists in the endogenous predictor, other cross-unit relationships—spillovers and interdependence—likely exist as well and risk violations of the exclusion restriction. Second, spatial instruments produce simultaneity in the first-stage equation, as left-hand side outcomes are included as right-hand side predictors. Because the instrument and the endogenous variable are simultaneously determined, the exclusion restriction is, necessarily and by construction, violated. Taken together, these concerns lead us to conclude that spatial instruments are rarely, if ever, valid.
Depression and obesity are highly prevalent, and major impacts on public health frequently co-occur. Recently, we reported that having depression moderates the effect of the FTO gene, suggesting its implication in the association between depression and obesity.
To confirm these findings by investigating the FTO polymorphism rs9939609 in new cohorts, and subsequently in a meta-analysis.
The sample consists of 6902 individuals with depression and 6799 controls from three replication cohorts and two original discovery cohorts. Linear regression models were performed to test for association between rs9939609 and body mass index (BMI), and for the interaction between rs9939609 and depression status for an effect on BMI. Fixed and random effects meta-analyses were performed using METASOFT.
In the replication cohorts, we observed a significant interaction between FTO, BMI and depression with fixed effects meta-analysis (β=0.12, P = 2.7 × 10−4) and with the Han/Eskin random effects method (P = 1.4 × 10−7) but not with traditional random effects (β = 0.1, P = 0.35). When combined with the discovery cohorts, random effects meta-analysis also supports the interaction (β = 0.12, P = 0.027) being highly significant based on the Han/Eskin model (P = 6.9 × 10−8). On average, carriers of the risk allele who have depression have a 2.2% higher BMI for each risk allele, over and above the main effect of FTO.
This meta-analysis provides additional support for a significant interaction between FTO, depression and BMI, indicating that depression increases the effect of FTO on BMI. The findings provide a useful starting point in understanding the biological mechanism involved in the association between obesity and depression.
Giant ragweed has been increasing as a major weed of row crops in the last
30 yr, but quantitative data regarding its pattern and mechanisms of spread
in crop fields are lacking. To address this gap, we conducted a Web-based
survey of certified crop advisors in the U.S. Corn Belt and Ontario, Canada.
Participants were asked questions regarding giant ragweed and crop
production practices for the county of their choice. Responses were mapped
and correlation analyses were conducted among the responses to determine
factors associated with giant ragweed populations. Respondents rated giant
ragweed as the most or one of the most difficult weeds to manage in 45% of
421 U.S. counties responding, and 57% of responding counties reported giant
ragweed populations with herbicide resistance to acetolactate synthase
inhibitors, glyphosate, or both herbicides. Results suggest that giant
ragweed is increasing in crop fields outward from the east-central U.S. Corn
Belt in most directions. Crop production practices associated with giant
ragweed populations included minimum tillage, continuous soybean, and
multiple-application herbicide programs; ecological factors included giant
ragweed presence in noncrop edge habitats, early and prolonged emergence,
and presence of the seed-burying common earthworm in crop fields. Managing
giant ragweed in noncrop areas could reduce giant ragweed migration from
noncrop habitats into crop fields and slow its spread. Where giant ragweed
is already established in crop fields, including a more diverse combination
of crop species, tillage practices, and herbicide sites of action will be
critical to reduce populations, disrupt emergence patterns, and select
against herbicide-resistant giant ragweed genotypes. Incorporation of a
cereal grain into the crop rotation may help suppress early giant ragweed
emergence and provide chemical or mechanical control options for
late-emerging giant ragweed.
We show that alloying with rare earth metals (REMs) can dramatically improve the machineability of a range of titanium alloys, even though the REM is not incorporated in the alloy matrix. The mechanism for this is that under cutting, shear bands are formed within which the nano-precipitates of REM are shear mixed. This lowers the melting point such that the mechanism of deformation changes from dislocation mechanism to localised amorphisation and shear softening. The material then fractures along the thin, amorphous shear-band. Outside the shear band, the REM remains as precipitates. The new alloys have similar mechanical properties and biocompatibility to conventional materials.
In 2006, F. Luca and I. E. Shparlinski (Proc. Indian Acad. Sci. (Math. Sci.)116(1) (2006), 1–8) proved that there are only finitely many pairs (n, m) of positive integers which satisfy the Diophantine equation |τ(n!)|=m!, where τ is the Ramanujan function. In this paper, we follow the same approach of Luca and Shparlinski (Proc. Indian Acad. Sci. (Math. Sci.)116(1) (2006), 1–8) to determine all solutions of the above equation. The proof of our main theorem uses linear forms in two logarithms and arithmetic properties of the Ramanujan function.
X-ray powder diffraction data, unit-cell parameters, and space group for a sodium azobarbituric acid dihydrate are presented [a = 3.546 (1) Å, b = 9.210 (2) Å, c = 9.738 (4) Å, α = 104.07 (4)°, β = 98.09 (6)°, γ = 98.80 (2)°, unit-cell volume V = 299.6 Å3, Z = 1, and space group P − 1]. All the measured lines were indexed. No detectable impurities were observed.