Gas transport in firn: multiple-tracer characterisation and model intercomparison for NEEM, Northern Greenland

Air was sampled from the porous firn layer at the NEEM site in Northern Greenland. We use an ensemble of ten reference tracers of known atmospheric history to characterise the transport properties of the site. By analysing uncertainties in both data and the reference gas atmospheric histories, we can objectively assign weights to each of the gases used for the depth-diffusivity reconstruction. We define an objective root mean square criterion that is minimised in the model tuning procedure. Each tracer constrains the firn profile differently through its unique atmospheric history and free air diffusivity, making our multiple-tracer characterisation method a clear improvement over the commonly used single-tracer tuning. Six firn air transport models are tuned to the NEEM site; all models successfully reproduce the data within a 1σ Gaussian distribution. A comparison between two replicate boreholes drilled 64 m apart shows differences in measured mixing ratio profiles that exceed the experimental error. We find evidence that diffusivity does not vanish completely in the lock-in zone, as is commonly assumed. The ice age- gas age difference (1 age) at the firn-ice transition is calculated to be 182+3−9 yr. We further present the first intercomparison study of firn air models, where we introduce diagnostic scenarios designed to probe specific aspects of the model physics. Our results show that there are major differences in the way the models handle advective transport. Furthermore, diffusive fractionation of isotopes in the firn is poorly constrained by the models, which has consequences for attempts to reconstruct the isotopic composition of trace gases back in time using firn air and ice core records.

Temperature Prediction Model for Bone Drilling Based on Density Distribution and In Vivo Experiments for Minimally Invasive Robotic Cochlear Implantation

Surgical robots have been proposed ex vivo to drill precise holes in the temporal bone for minimally invasive cochlear implantation. The main risk of the procedure is damage of the facial nerve due to mechanical interaction or due to temperature elevation during the drilling process. To evaluate the thermal risk of the drilling process, a simplified model is proposed which aims to enable an assessment of risk posed to the facial nerve for a given set of constant process parameters for different mastoid bone densities. The model uses the bone density distribution along the drilling trajectory in the mastoid bone to calculate a time dependent heat production function at the tip of the drill bit. Using a time dependent moving point source Green's function, the heat equation can be solved at a certain point in space so that the resulting temperatures can be calculated over time. The model was calibrated and initially verified with in vivo temperature data. The data was collected in minimally invasive robotic drilling of 12 holes in four different sheep. The sheep were anesthetized and the temperature elevations were measured with a thermocouple which was inserted in a previously drilled hole next to the planned drilling trajectory. Bone density distributions were extracted from pre-operative CT data by averaging Hounsfield values over the drill bit diameter. Post-operative [Formula: see text]CT data was used to verify the drilling accuracy of the trajectories. The comparison of measured and calculated temperatures shows a very good match for both heating and cooling phases. The average prediction error of the maximum temperature was less than 0.7 °C and the average root mean square error was approximately 0.5 °C. To analyze potential thermal damage, the model was used to calculate temperature profiles and cumulative equivalent minutes at 43 °C at a minimal distance to the facial nerve. For the selected drilling parameters, temperature elevation profiles and cumulative equivalent minutes suggest that thermal elevation of this minimally invasive cochlear implantation surgery may pose a risk to the facial nerve, especially in sclerotic or high density mastoid bones. Optimized drilling parameters need to be evaluated and the model could be used for future risk evaluation.

Development of a Tumour Growth Inhibition Model to Elucidate the Effects of Ritonavir on Intratumoural Metabolism and Anti-tumour Effect of Docetaxel in a Mouse Model for Hereditary Breast Cancer

In a mouse tumour model for hereditary breast cancer, we previously explored the anti-cancer effects of docetaxel, ritonavir and the combination of both and studied the effect of ritonavir on the intratumoural concentration of docetaxel. The objective of the current study was to apply pharmacokinetic (PK)-pharmacodynamic (PD) modelling on this previous study to further elucidate and quantify the effects of docetaxel when co-administered with ritonavir. PK models of docetaxel and ritonavir in plasma and in tumour were developed. The effect of ritonavir on docetaxel concentration in the systemic circulation of Cyp3a knock-out mice and in the implanted tumour (with inherent Cyp3a expression) was studied, respectively. Subsequently, we designed a tumour growth inhibition model that included the inhibitory effects of both docetaxel and ritonavir. Ritonavir decreased docetaxel systemic clearance with 8% (relative standard error 0.4%) in the co-treated group compared to that in the docetaxel only-treated group. The docetaxel concentration in tumour tissues was significantly increased by ritonavir with mean area under the concentration-time curve 2.5-fold higher when combined with ritonavir. Observed tumour volume profiles in mice could be properly described by the PK/PD model. In the co-treated group, the enhanced anti-tumour effect was mainly due to increased docetaxel tumour concentration; however, we demonstrated a small but significant anti-tumour effect of ritonavir addition (p value <0.001). In conclusion, we showed that the increased anti-tumour effect observed when docetaxel is combined with ritonavir is mainly caused by enhanced docetaxel tumour concentration and to a minor extent by a direct anti-tumour effect of ritonavir.

Time-order errors and standard-position effects in duration discrimination: An experimental study and an analysis by the sensation-weighting model

Studies have shown that the discriminability of successive time intervals depends on the presentation order of the standard (St) and the comparison (Co) stimuli. Also, this order affects the point of subjective equality. The first effect is here called the standard-position effect (SPE); the latter is known as the time-order error. In the present study, we investigated how these two effects vary across interval types and standard durations, using Hellström’s sensation-weighting model to describe the results and relate them to stimulus comparison mechanisms. In Experiment 1, four modes of interval presentation were used, factorially combining interval type (filled, empty) and sensory modality (auditory, visual). For each mode, two presentation orders (St–Co, Co–St) and two standard durations (100 ms, 1,000 ms) were used; half of the participants received correctness feedback, and half of them did not. The interstimulus interval was 900 ms. The SPEs were negative (i.e., a smaller difference limen for St–Co than for Co–St), except for the filled-auditory and empty-visual 100-ms standards, for which a positive effect was obtained. In Experiment 2, duration discrimination was investigated for filled auditory intervals with four standards between 100 and 1,000 ms, an interstimulus interval of 900 ms, and no feedback. Standard duration interacted with presentation order, here yielding SPEs that were negative for standards of 100 and 1,000 ms, but positive for 215 and 464 ms. Our findings indicate that the SPE can be positive as well as negative, depending on the interval type and standard duration, reflecting the relative weighting of the stimulus information, as is described by the sensation-weighting model.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Validation of a Spatially Continuous EDEN Water-Surface Model for the Everglades, Florida

The Everglades Depth Estimation Network (EDEN) is an integrated network of realtime water-level monitoring, ground-elevation modeling, and water-surface modeling that provides scientists and managers with current (2000-present), online water-stage and water-depth information for the entire freshwater portion of the Greater Everglades. Continuous daily spatial interpolations of the EDEN network stage data are presented on grid with 400-square-meter spacing. EDEN offers a consistent and documented dataset that can be used by scientists and managers to: (1) guide large-scale field operations, (2) integrate hydrologic and ecological responses, and (3) support biological and ecological assessments that measure ecosystem responses to the implementation of the Comprehensive Everglades Restoration Plan (CERP) (U.S. Army Corps of Engineers, 1999). The target users are biologists and ecologists examining trophic level responses to hydrodynamic changes in the Everglades. The first objective of this report is to validate the spatially continuous EDEN water-surface model for the Everglades, Florida developed by Pearlstine et al. (2007) by using an independent field-measured data-set. The second objective is to demonstrate two applications of the EDEN water-surface model: to estimate site-specific ground elevation by using the validated EDEN water-surface model and observed water depth data; and to create water-depth hydrographs for tree islands. We found that there are no statistically significant differences between model-predicted and field-observed water-stage data in both southern Water Conservation Area (WCA) 3A and WCA 3B. Tree island elevations were derived by subtracting field water-depth measurements from the predicted EDEN water-surface. Water-depth hydrographs were then computed by subtracting tree island elevations from the EDEN water stage. Overall, the model is reliable by a root mean square error (RMSE) of 3.31 cm. By region, the RMSE is 2.49 cm and 7.77 cm in WCA 3A and 3B, respectively. This new landscape-scale hydrological model has wide applications for ongoing research and management efforts that are vital to restoration of the Florida Everglades. The accurate, high-resolution hydrological data, generated over broad spatial and temporal scales by the EDEN model, provides a previously missing key to understanding the habitat requirements and linkages among native and invasive populations, including fish, wildlife, wading birds, and plants. The EDEN model is a powerful tool that could be adapted for other ecosystem-scale restoration and management programs worldwide.

Optimal Test for Parameter Instability When the Unstable Process and the Error Distribution are Unknown

This paper proposes asymptotically optimal tests for unstable parameter process under the feasible circumstance that the researcher has little information about the unstable parameter process and the error distribution, and suggests conditions under which the knowledge of those processes does not provide asymptotic power gains. I first derive a test under known error distribution, which is asymptotically equivalent to LR tests for correctly identified unstable parameter processes under suitable conditions. The conditions are weak enough to cover a wide range of unstable processes such as various types of structural breaks and time varying parameter processes. The test is then extended to semiparametric models in which the underlying distribution in unknown but treated as unknown infinite dimensional nuisance parameter. The semiparametric test is adaptive in the sense that its asymptotic power function is equivalent to the power envelope under known error distribution.

Design of long-term animal bioassay for low-dose extrapolation using a multistage model

Conventional designs of animal bioassays allocate the same number of animals into control and dose groups to explore the spontaneous and induced tumor incidence rates, respectively. The purpose of such bioassays are (a) to determine whether or not the substance exhibits carcinogenic properties, and (b) if so, to estimate the human response at relatively low doses. In this study, it has been found that the optimal allocation to the experimental groups which, in some sense, minimize the error of the estimated response for low dose extrapolation is associated with the dose level and tumor risk. The number of dose levels has been investigated at the affordable experimental cost. The pattern of the administered dose, 1 MTD, 1/2 MTD, 1/4 MTD,....., etc. plus control, gives the most reasonable arrangement for the low dose extrapolation purpose. The arrangement of five dose groups may make the highest dose trivial. A four-dose design can circumvent this problem and has also one degree of freedom for testing the goodness-of-fit of the response model.^ An example using the data on liver tumors induced in mice in a lifetime study of feeding dieldrin (Walker et al., 1973) is implemented with the methodology. The results are compared with conclusions drawn from other studies. ^

Bayesian estimation of multilevel item response model with missing data

This study proposed a novel statistical method that modeled the multiple outcomes and missing data process jointly using item response theory. This method follows the "intent-to-treat" principle in clinical trials and accounts for the correlation between outcomes and missing data process. This method may provide a good solution to chronic mental disorder study. ^ The simulation study demonstrated that if the true model is the proposed model with moderate or strong correlation, ignoring the within correlation may lead to overestimate of the treatment effect and result in more type I error than specified level. Even if the within correlation is small, the performance of proposed model is as good as naïve response model. Thus, the proposed model is robust for different correlation settings if the data is generated by the proposed model.^

Model - data comparison of western African rainfall evolutions during the Last Interglacial (130-115 ka)

This dataset characterizes the evolution of western African precipitation indicated by marine sediment geochemical records in comparison to transient simulations using CCSM3 global climate model throughout the Last Interglacial (130-115 ka). It contains (1) defined tie-points (age models), newly published stable isotopes of benthic foraminifera and Al/Si log-ratios of eight marine sediment cores from the western African margin and (2) annual and seasonal rainfall anomalies (relative to pre-industrial values) for six characteristic latitudinal bands in western Africa simulated by CCSM3 (two transient simulations: one non-accelerated and one accelerated experiment).

Nd, Sr and Sm isotopic composition and model ages of rocks from the Anginskaya and Talanchanskaya formations, Lake Baikal

The paper presents data on the Nd-Sr systematics of magmatic rocks of the Khaidaiskii Series of the Anginskaya Formation in the Ol'khon region, western Baikal area, and rocks of the Talanchanskaya Formation on the eastern shore of Lake Baikal. Geochemical characteristics of these rocks are identical and testify to their arc provenance. At the same time, the epsilon(t)Nd of rocks of the Khaidaiskii Series in the Ol'khon area has positive values, and the data points of these rocks plot near the mantle succession line in the epsilon(t)Nd-87Sr/86Sr diagram, whereas the epsilon(t)Nd values of rocks of the Talanchanskaya Formation are negative, and the data points of these rocks fall into the fourth quadrant in the epsilon(t)Nd -87Sr/86Sr diagram. This testifies to a mantle genesis of the parental magmas of the Khaidaiskii Series and to the significant involvement of older crustal material in the generation of the melts that produced the orthorocks on the eastern shore of the lake. These conclusions are corroborated by model ages of magmatic rocks in the Ol'khon area (close to 1 Ga) and of rocks of the Talanchanskaya Formation (approximately 2 Ga). The comparison of our data with those obtained by other researchers on the Nd-Sr isotopic age of granulites of the Ol'khon Group and metavolcanics in various structural zones in the northern Baikal area suggests, with regard for the geochemistry of these rocks, the accretion of tectonic nappes that had different isotopic histories: some of them were derived from the mantle wedge and localized in the island arc itself (magmatic rocks of the Anginskaya Formation) or backarc spreading zone (mafic metamagmatic rocks of the Ol'khon Group), while others were partial melts derived, with the participation of crustal material, from sources of various age (metagraywackes in the backarc basin in the Ol'khon Group and the ensialic basement of the island arc in the Talanchanskaya Formation).

"En el monumento Resuçitest, fust alos ynfiernos" : ¿Error del poeta o influencia de una fuente en el Cantar de Mio Cid?

El presente trabajo vuelve a los vv. 358-361 del Cantar de Mio Cid sobre un tema que ha perturbado a la crítica: el texto conservado en el Códice de Vivar refiere que Jesús resucitó primero, y luego descendió a los Infiernos, lo cual implica una inversión del orden tradicional de los acontecimientos. En consecuencia, se revisan aquí las distintas opiniones sobre el particular, que en general pueden dividirse básicamente en dos grupos -aquellas que sostienen que el poeta cometió un error, y otras que afirman que el autor del poema adhirió a un determinado modelo, proveniente ya de la épica francesa, ya de la liturgia-, y se intenta arribar a una solución que considere más satisfactoriamente la especificidad del texto manuscrito.

"En el monumento Resuçitest, fust alos ynfiernos" : ¿Error del poeta o influencia de una fuente en el Cantar de Mio Cid?

El presente trabajo vuelve a los vv. 358-361 del Cantar de Mio Cid sobre un tema que ha perturbado a la crítica: el texto conservado en el Códice de Vivar refiere que Jesús resucitó primero, y luego descendió a los Infiernos, lo cual implica una inversión del orden tradicional de los acontecimientos. En consecuencia, se revisan aquí las distintas opiniones sobre el particular, que en general pueden dividirse básicamente en dos grupos -aquellas que sostienen que el poeta cometió un error, y otras que afirman que el autor del poema adhirió a un determinado modelo, proveniente ya de la épica francesa, ya de la liturgia-, y se intenta arribar a una solución que considere más satisfactoriamente la especificidad del texto manuscrito.

Altered neurotransmitter function in CO2-exposed stickleback (Gasterosteus aculeatus): a temperate model species for ocean acidification research

Studies on the consequences of ocean acidification for the marine ecosystem have revealed behavioural changes in coral reef fishes exposed to sustained near-future CO2 levels. The changes have been linked to altered function of GABAergic neurotransmitter systems, because the behavioural alterations can be reversed rapidly by treatment with the GABAA receptor antagonist gabazine. Characterization of the molecular mechanisms involved would be greatly aided if these can be examined in a well-characterized model organism with a sequenced genome. It was recently shown that CO2-induced behavioural alterations are not confined to tropical species, but also affect the three-spined stickleback, although an involvement of the GABAA receptor was not examined. Here, we show that loss of lateralization in the stickleback can be restored rapidly and completely by gabazine treatment. This points towards a worrying universality of disturbed GABAA function after high-CO2 exposure in fishes from tropical to temperate marine habitats. Importantly, the stickleback is a model species with a sequenced and annotated genome, which greatly facilitates future studies on underlying molecular mechanisms.