Chrysomya albiceps (Wiedemann) and Hemilucilia segmentaria (Fabricius) (Diptera, Calliphoridae) used to estimate the postmortem interval in a forensic case in Minas Gerais, Brazil

ABSTRACT. Chrysomya albiceps (Wiedemann) and Hemilucilia segmentaria (Fabricius) (Diptera, Calliphoridae) used to estimate the postmortem interval in a forensic case in Minas Gerais, Brazil. The corpse of a man was found in a Brazilian highland savanna (cerrado) in the state of Minas Gerais. Fly larvae were collected at the crime scene and arrived at the laboratory three days afterwards. From the eight pre-pupae, seven adults of Chrysomya albiceps (Wiedemann, 1819) emerged and, from the two larvae, two adults of Hemilucilia segmentaria (Fabricius, 1805) were obtained. As necrophagous insects use corpses as a feeding resource, their development rate can be used as a tool to estimate the postmortem interval. The post-embryonary development stage of the immature collected on the body was estimated as the difference between the total development time and the time required for them to become adults in the lab. The estimated age of the maggots from both species and the minimum postmortem interval were four days. This is the first time that H. segmentaria is used to estimate the postmortem interval in a forensic case.

Forecasting the effects of global warming on biodiversity

The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting have limitations. in this article, we compare and discuss the different uses of four forecasting methods: (1) models that consider species individually, (2) niche-theory models that group species by habitat (more specifically, by environmental conditions under which a species can persist or does persist), (3) general circulation models and coupled ocean-atmosphere-biosphere models, and (4) specics-area curve models that consider all species or large aggregates of species. After outlining the different uses and limitations of these methods, we make eight primary suggestions for improving forecasts. We find that greater use of the fossil record and of modern genetic studies would improve forecasting methods. We note a Quaternary conundrum: While current empirical and theoretical ecological results suggest that many species could be at risk from global warming, during the recent ice ages surprisingly few species became extinct. The potential resolution of this conundrum gives insights into the requirements for more accurate and reliable forecasting. Our eight suggestions also point to constructive synergies in the solution to the different problems.

On the concept of optimality interval

The approximants to regular continued fractions constitute `best approximations' to the numbers they converge to in two ways known as of the first and the second kind.This property of continued fractions provides a solution to Gosper's problem of the batting average: if the batting average of a baseball player is 0.334, what is the minimum number of times he has been at bat? In this paper, we tackle somehow the inverse question: given a rational number P/Q, what is the set of all numbers for which P/Q is a `best approximation' of one or the other kind? We prove that inboth cases these `Optimality Sets' are intervals and we give aprecise description of their endpoints.

One-sided tolerance interval in a two-way balanced nested model with mixed effects

In many research areas (such as public health, environmental contamination, and others) one deals with the necessity of using data to infer whether some proportion (%) of a population of interest is (or one wants it to be) below and/or over some threshold, through the computation of tolerance interval. The idea is, once a threshold is given, one computes the tolerance interval or limit (which might be one or two - sided bounded) and then to check if it satisfies the given threshold. Since in this work we deal with the computation of one - sided tolerance interval, for the two-sided case we recomend, for instance, Krishnamoorthy and Mathew [5]. Krishnamoorthy and Mathew [4] performed the computation of upper tolerance limit in balanced and unbalanced one-way random effects models, whereas Fonseca et al [3] performed it based in a similar ideas but in a tow-way nested mixed or random effects model. In case of random effects model, Fonseca et al [3] performed the computation of such interval only for the balanced data, whereas in the mixed effects case they dit it only for the unbalanced data. For the computation of twosided tolerance interval in models with mixed and/or random effects we recomend, for instance, Sharma and Mathew [7]. The purpose of this paper is the computation of upper and lower tolerance interval in a two-way nested mixed effects models in balanced data. For the case of unbalanced data, as mentioned above, Fonseca et al [3] have already computed upper tolerance interval. Hence, using the notions persented in Fonseca et al [3] and Krishnamoorthy and Mathew [4], we present some results on the construction of one-sided tolerance interval for the balanced case. Thus, in order to do so at first instance we perform the construction for the upper case, and then the construction for the lower case.

Flowering date of taxonomic families predicts phenological sensitivity to temperature: Implications for forecasting the effects of climate change on unstudied taxa.

PREMISE OF THE STUDY: Numerous long-term studies in seasonal habitats have tracked interannual variation in first flowering date (FFD) in relation to climate, documenting the effect of warming on the FFD of many species. Despite these efforts, long-term phenological observations are still lacking for many species. If we could forecast responses based on taxonomic affinity, however, then we could leverage existing data to predict the climate-related phenological shifts of many taxa not yet studied. METHODS: We examined phenological time series of 1226 species occurrences (1031 unique species in 119 families) across seven sites in North America and England to determine whether family membership (or family mean FFD) predicts the sensitivity of FFD to standardized interannual changes in temperature and precipitation during seasonal periods before flowering and whether families differ significantly in the direction of their phenological shifts. KEY RESULTS: Patterns observed among species within and across sites are mirrored among family means across sites; early-flowering families advance their FFD in response to warming more than late-flowering families. By contrast, we found no consistent relationships among taxa between mean FFD and sensitivity to precipitation as measured here. CONCLUSIONS: Family membership can be used to identify taxa of high and low sensitivity to temperature within the seasonal, temperate zone plant communities analyzed here. The high sensitivity of early-flowering families (and the absence of early-flowering families not sensitive to temperature) may reflect plasticity in flowering time, which may be adaptive in environments where early-season conditions are highly variable among years.

Improving electricity market price scenarios by means of forecasting factor models

In liberalized electricity markets, generation Companies must build an hourly bidthat is sent to the market operator. The price at which the energy will be paid is unknown during the bidding process and has to be forecast. In this work we apply forecasting factor models to this framework and study its suitability.

A Dynamic forecasting model for the Finnish pulp export price

Summary

Pharmacokinetic variability of extended interval tobramycin in burn patients.

BACKGROUND: Aminoglycosides are mandatory in the treatment of severe infections in burns. However, their pharmacokinetics are difficult to predict in critically ill patients. Our objective was to describe the pharmacokinetic parameters of high doses of tobramycin administered at extended intervals in severely burned patients. METHODS: We prospectively enrolled 23 burned patients receiving tobramycin in combination therapy for Pseudomonas species infections in a burn ICU over 2 years in a therapeutic drug monitoring program. Trough and post peak tobramycin levels were measured to adjust drug dosage. Pharmacokinetic parameters were derived from two points first order kinetics. RESULTS: Tobramycin peak concentration was 7.4 (3.1-19.6)microg/ml and Cmax/MIC ratio 14.8 (2.8-39.2). Half-life was 6.9 (range 1.8-24.6)h with a distribution volume of 0.4 (0.2-1.0)l/kg. Clearance was 35 (14-121)ml/min and was weakly but significantly correlated with creatinine clearance. CONCLUSION: Tobramycin had a normal clearance, but an increased volume of distribution and a prolonged half-life in burned patients. However, the pharmacokinetic parameters of tobramycin are highly variable in burned patients. These data support extended interval administration and strongly suggest that aminoglycosides should only be used within a structured pharmacokinetic monitoring program.

Forecasting cosmic doomsday from CMB-LSS cross-correlations.

A broad class of dark energy models, which have been proposed in attempts at solving the cosmological constant problems, predict a late time variation of the equation of state with redshift. The variation occurs as a scalar field picks up speed on its way to negative values of the potential. The negative potential energy eventually turns the expansion into contraction and the local universe undergoes a big crunch. In this paper we show that cross-correlations of the cosmic microwave background anisotropy and matter distribution, in combination with other cosmological data, can be used to forecast the imminence of such cosmic doomsday.

U.S.-Norway Comparison of Interval Breast Cancers

Background: Publications from the International Breast Screening Network (IBSN) have shown that varying definitions create hurdles for comparison of screening performance. Interval breast cancer rates are particularly affected. Objective: to test whether variations in definition of interval cancer rates (ICR) affect comparisons of international ICR, specific to a comparison of ICR in Norway and North Carolina (NC). Methods: An interval cancer (IC) was defined as a cancer diagnosed following a negative screening mammogram in a defined follow-up period. ICR was calculated for women ages 50-69, at subsequent screening in Norway and NC, during the time period 1996 - 2002. ICR was defined using three different denominators (negative screens, negative final assessments and all screens) and three different numerators (DCIS, invasive cancer and all cancers). ICR was then calculated with two methods: 1) number of ICs divided by the number of screens, and ICs divided by the number of women-years at risk for IC. Results: There were no differences in ICR depending on the definition used. In the 1-12 month follow up period ICR (based on number of screens) were: 0.53, 0.54, and 0.54 for Norway; and 1.20, 1.25 and 1.17 for NC, for negative screens, negative final assessment and all screens, respectively: The same trend was seen for 13-24 and 1-24 months follow-up. Using women-years for the analysis did not change the trend. ICR was higher in NC compared to Norway under all definitions and in all follow-up time periods, regardless of calculation method. Conclusion: The ICR within or between Norway and NC did not differ by definition used. ICR were higher in NC than Norway. There are many potential explanations for the difference.