Reporting underage consensual sex after the Teddy Bear case: A different perspective

Doctors and researchers face a complex dilemma regarding the mandatory reporting of consensual underage sex, because of contradictions between the Children’s Act and the Sexual Offences Act. When providing underage children with sexual and reproductive health services, they have had to decide whether to provide these confidentially, in terms of the Children’s Act, or thereafter report the consensual but illegal sexual behaviour to the police, in terms of the Sexual Offences Act. The recent Teddy Bear Clinic for Abused Children, and Resources Aimed at the Prevention of Child Abuse and Neglect (RAPCAN) v. Minister of Justice and Constitutional Development case addressed whether consensual underage sex ought to be a criminal offence and thus reported. The court held that aspects of sections 15 and 16 of the Sexual Offences Act infringed on the constitutional rights of adolescents (aged 12 - 15 years) by proscribing many consensual sexual activities. McQuoid-Mason has described this case in detail. He submits that following the judgement, doctors are no longer under a reporting obligation in relation to consensual underage sex. We respectfully disagree. This article critiques McQuoid-Mason’s approach, sets out our views on the mandatory reporting obligations after the Teddy Bear case and concludes with some comments on the judgement’s implications for researchers and medical practitioners

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date

Interannual Variability and Trends of CH4, CO and OH Using the Computationally-Efficient CH4-CO-OH (ECCOH) Module

Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG). Its 100-year global warming potential (GWP) is 34 times larger than that for carbon dioxide. The 100-year integrated GWPof CH4 is sensitive to changes in hydroxyl radical (OH) levels.Oxidation of CH4 and carbon monoxide (CO) by OH is the main loss process, thus affecting the oxidizing capacity of the atmosphere and contributing to the global ozone background. Limitations of using archived, monthly OH fields for studies of methane's and COs evolution are that feedbacks of the CH4-CO-OH system on methane, CO and OH are not captured. In this study, we employ the computationally Efficient CH4-CO-OH (ECCOH) module (Elshorbany et al., 2015) to investigate the nonlinear feedbacks of the CH4-CO-OH system on the interannual variability and trends of the CH4, CO, OH system

Forecasting carbon monoxide on a global scale for the ATom-1 aircraft mission: insights from airborne and satellite observations and modeling

The first phase of the Atmospheric Tomography Mission (ATom-1) took place in July–August 2016 and included flights above the remote Pacific and Atlantic oceans. Sampling of atmospheric constituents during these flights is designed to provide new insights into the chemical reactivity and processes of the remote atmosphere and how these processes are affected by anthropogenic emissions. Model simulations provide a valuable tool for interpreting these measurements and understanding the origin of the observed trace gases and aerosols, so it is important to quantify model performance. Goddard Earth Observing System Model version 5 (GEOS-5) forecasts and analyses show considerable skill in predicting and simulating the CO distribution and the timing of CO enhancements observed during the ATom-1 aircraft mission. We use GEOS-5's tagged tracers for CO to assess the contribution of different emission sources to the regions sampled by ATom-1 to elucidate the dominant anthropogenic influences on different parts of the remote atmosphere. We find a dominant contribution from non-biomass-burning sources along the ATom transects except over the tropical Atlantic, where African biomass burning makes a large contribution to the CO concentration. One of the goals of ATom is to provide a chemical climatology over the oceans, so it is important to consider whether August 2016 was representative of typical boreal summer conditions. Using satellite observations of 700&thinsp;hPa and column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument, 215&thinsp;hPa&thinsp;CO from the Microwave Limb Sounder (MLS), and aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS), we find that CO concentrations and aerosol optical thickness in August 2016 were within the observed range of the satellite observations but below the decadal median for many of the regions sampled. This suggests that the ATom-1 measurements may represent relatively clean but not exceptional conditions for lower-tropospheric CO.</p

Trends in Global Tropospheric Ozone Inferred from a Composite Record of TOMS/OMI/MLS/OMPS Satellite Measurements and the MERRA-2 GMI Simulation

Past studies have suggested that ozone in the troposphere has increased globally throughout much of the 20th century due to increases in anthropogenic emissions and transport. We show, by combining satellite measurements with a chemical transport model, that during the last four decades tropospheric ozone does indeed indicate increases that are global in nature, yet still highly regional. Satellite ozone measurements from Nimbus-7 and Earth Probe Total Ozone Mapping Spectrometer (TOMS) are merged with ozone measurements from the Aura Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) to determine trends in tropospheric ozone for 19792016. Both TOMS (19792005) and OMI/MLS (20052016) depict large increases in tropospheric ozone from the Near East to India and East Asia and further eastward over the Pacific Ocean. The 38-year merged satellite record shows total net change over this region of about +6 to +7 Dobson units (DU) (i.e., 15 %20 % of average background ozone), with the largest increase (4 DU) occurring during the 20052016 Aura period. The Global Modeling Initiative (GMI) chemical transport model with time-varying emissions is used to aid in the interpretation of tropospheric ozone trends for 19802016. The GMI simulation for the combined record also depicts the greatest increases of +6 to +7 DU over India and East Asia, very similar to the satellite measurements. In regions of significant increases in tropospheric column ozone (TCO) the trends are a factor of 22.5 larger for the Aura record when compared to the earlier TOMS record; for India and East Asia the trends in TCO for both GMI and satellite measurements are +3 DU decade(exp 1) or greater during 20052016 compared to about +1.2 to +1.4 DU decade(exp 1) for 19792005. The GMI simulation and satellite data also reveal a tropospheric ozone increases in +4 to +5 DU for the 38-year record over central Africa and the tropical Atlantic Ocean. Both the GMI simulation and satellite-measured tropospheric ozone during the latter Aura time period show increases of +3 DU decade1 over the N Atlantic and NE Pacific

Differential transcription profiles inAedes aegyptidetoxification genes after temephos selection

The mosquito Aedes aegypti is the main vector of Dengue and Yellow Fever flaviviruses. The organophosphate insecticide temephos is a larvicide that is used globally to control Ae. aegypti populations; many of which have in turn evolved resistance. Target site alteration in the acetylcholine esterase of this species has not being identified. Instead, we tracked changes in transcription of metabolic detoxification genes using the Ae. aegypti ‘Detox Chip’ microarray during five generations of temephos selection. We selected for temephos resistance in three replicates in each of six collections, five from Mexico, and one from Peru. The response to selection was tracked in terms of lethal concentrations. Uniform upregulation was seen in the epsilon class glutathione-S-transferase (eGST) genes in strains from Mexico prior to laboratory selection, while eGSTs in the Iquitos Peru strain became upregulated after five generations of temephos selection. While expression of many carboxyl/cholinesterase esterase (CCE) genes increased with selection, no single esterase was consistently upregulated and this same pattern was noted in the cytochrome P450 monooxygenase (CYP) genes and in other genes involved in reduction or oxidation of xenobiotics. Bioassays using glutathione-S-transferase (GST), CCE and CYP inhibitors suggest that various CCEs instead of GSTs are the main metabolic mechanism conferring resistance to temephos. We show that temephos-selected strains show no cross resistance to permethrin and that genes associated with temephos selection are largely independent of those selected with permethrin in a previous study

Empirical Investigation on Agile Methods Usage: Issues Identified from Early Adopters in Malaysia

Agile Methods are a set of software practices that can help to produce products faster and at the same time deliver what customers want. Despite the benefits that Agile methods can deliver, however, we found few studies from the Southeast Asia region, particularly Malaysia. As a result, less empirical evidence can be obtained in the country making its implementation harder. To use a new method, experience from other practitioners is critical, which describes what is important, what is possible and what is not possible concerning Agile. We conducted a qualitative study to understand the issues faced by early adopters in Malaysia where Agile methods are still relatively new. The initial study involves 13 participants including project managers, CEOs, founders and software developers from seven organisations. Our study has shown that social and human aspects are important when using Agile methods. While technical aspects have always been considered to exist in software development, we found these factors to be less important when using Agile methods. The results obtained can serve as guidelines to practitioners in the country and the neighbouring regions

The effect of future ambient air pollution on human premature mortality to 2100 using output from the ACCMIP model ensemble

Ambient air pollution from ground-level ozone and fine particulate matter (PM2.5) is associated with premature mortality. Future concentrations of these air pollutants will be driven by natural and anthropogenic emissions and by climate change. Using anthropogenic and biomass burning emissions projected in the four Representative Concentration Pathway scenarios (RCPs), the ACCMIP ensemble of chemistry-climate models simulated future concentrations of ozone and PM2.5 at selected decades between 2000 and 2100. We use output from the ACCMIP ensemble, together with projections of future population and baseline mortality rates, to quantify the human premature mortality impacts of future ambient air pollution. Future air pollution-related premature mortality in 2030, 2050 and 2100 is estimated for each scenario and for each model using a health impact function based on changes in concentrations of ozone and PM2.5 relative to 2000 and projected future population and baseline mortality rates. Additionally, the global mortality burden of ozone and PM2.5 in 2000 and each future period is estimated relative to 1850 concentrations, using present-day and future population and baseline mortality rates. The change in future ozone concentrations relative to 2000 is associated with excess global premature mortality in some scenarios/periods, particularly in RCP8.5 in 2100 (316 thousand deaths/year), likely driven by the large increase in methane emissions and by the net effect of climate change projected in this scenario, but it leads to considerable avoided premature mortality for the three other RCPs. However, the global mortality burden of ozone markedly increases from 382,000 (121,000 to 728,000) deaths/year in 2000 to between 1.09 and 2.36 million deaths/year in 2100, across RCPs, mostly due to the effect of increases in population and baseline mortality rates. PM2.5 concentrations decrease relative to 2000 in all scenarios, due to projected reductions in emissions, and are associated with avoided premature mortality, particularly in 2100: between -2.39 and -1.31 million deaths/year for the four RCPs. The global mortality burden of PM2.5 is estimated to decrease from 1.70 (1.30 to 2.10) million deaths/year in 2000 to between 0.95 and 1.55 million deaths/year in 2100 for the four RCPs, due to the combined effect of decreases in PM2.5 concentrations and changes in population and baseline mortality rates. Trends in future air pollution-related mortality vary regionally across scenarios, reflecting assumptions for economic growth and air pollution control specific to each RCP and region. Mortality estimates differ among chemistry-climate models due to differences in simulated pollutant concentrations, which is the greatest contributor to overall mortality uncertainty for most cases assessed here, supporting the use of model ensembles to characterize uncertainty. Increases in exposed population and baseline mortality rates of respiratory diseases magnify the impact on premature mortality of changes in future air pollutant concentrations and explain why the future global mortality burden of air pollution can exceed the current burden, even where air pollutant concentrations decrease

Preindustrial to present-day changes in tropospheric hydroxyl radical and methane lifetime from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

We have analysed time-slice simulations from 17 global models, participating in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), to explore changes in present-day (2000) hydroxyl radical (OH) concentration and methane (CH4) lifetime relative to preindustrial times (1850) and to 1980. A comparison of modeled and observation-derived methane and methyl chloroform lifetimes suggests that the present-day global multi-model mean OH concentration is overestimated by 5 to 10% but is within the range of uncertainties. The models consistently simulate higher OH concentrations in the Northern Hemisphere (NH) compared with the Southern Hemisphere (SH) for the present-day (2000; inter-hemispheric ratios of 1.13 to 1.42), in contrast to observation-based approaches which generally indicate higher OH in the SH although uncertainties are large. Evaluation of simulated carbon monoxide (CO) concentrations, the primary sink for OH, against ground-based and satellite observations suggests low biases in the NH that may contribute to the high north–south OH asymmetry in the models. The models vary widely in their regional distribution of present-day OH concentrations (up to 34%). Despite large regional changes, the multi-model global mean (mass-weighted) OH concentration changes little over the past 150 yr, due to concurrent increases in factors that enhance OH (humidity, tropospheric ozone, nitrogen oxide (NOx) emissions, and UV radiation due to decreases in stratospheric ozone), compensated by increases in OH sinks (methane abundance, carbon monoxide and non-methane volatile organic carbon (NMVOC) emissions). The large inter-model diversity in the sign and magnitude of preindustrial to present-day OH changes (ranging from a decrease of 12.7% to an increase of 14.6%) indicate that uncertainty remains in our understanding of the long-term trends in OH and methane lifetime. We show that this diversity is largely explained by the different ratio of the change in global mean tropospheric CO and NOx burdens (ΔCO/ΔNOx, approximately represents changes in OH sinks versus changes in OH sources) in the models, pointing to a need for better constraints on natural precursor emissions and on the chemical mechanisms in the current generation of chemistry-climate models. For the 1980 to 2000 period, we find that climate warming and a slight increase in mean OH (3.5 ± 2.2%) leads to a 4.3 ± 1.9% decrease in the methane lifetime. Analysing sensitivity simulations performed by 10 models, we find that preindustrial to present-day climate change decreased the methane lifetime by about four months, representing a negative feedback on the climate system. Further, we analysed attribution experiments performed by a subset of models relative to 2000 conditions with only one precursor at a time set to 1860 levels. We find that global mean OH increased by 46.4 ± 12.2% in response to preindustrial to present-day anthropogenic NOx emission increases, and decreased by 17.3 ± 2.3%, 7.6 ± 1.5%, and 3.1 ± 3.0% due to methane burden, and anthropogenic CO, and NMVOC emissions increases, respectively

Prevalence and predictors of HIV-related stigma among institutional- and community-based caregivers of orphans and vulnerable children living in five less-wealthy countries

<p>Abstract</p> <p>Background</p> <p>In the face of the HIV/AIDS epidemic that has contributed to the dramatic increase in orphans and abandoned children (OAC) worldwide, caregiver attitudes about HIV, and HIV-related stigma, are two attributes that may affect caregiving. Little research has considered the relationship between caregiver attributes and caregiver-reported HIV-related stigma. In light of the paucity of this literature, this paper will describe HIV-related stigma among caregivers of OAC in five less wealthy nations.</p> <p>Methods</p> <p>Baseline data were collected between May 2006 through February 2008. The sample included 1,480 community-based and 192 institution-based caregivers. Characteristics of the community-based and institution-based caregivers are described using means and standard deviations for continuous variables or counts and percentages for categorical variables. We fit logistic regression models, both for the full sample and separately for community-based and institution-based caregivers, to explore predictors of acceptance of HIV.</p> <p>Results</p> <p>Approximately 80% of both community-based and institution-based caregivers were female; and 84% of institution-based caregivers, compared to 66% of community-based caregivers, said that they would be willing to care for a relative with HIV. Similar proportions were reported when caregivers were asked if they were willing to let their child play with an HIV-infected child. In a multivariable model predicting willingness to care for an HIV-infected relative, adjusted for site fixed effects, being an institution-based caregiver was associated with greater willingness (less stigma) than community-based caregivers. Decreased willingness was reported by older respondents, while willingness increased with greater formal education. In the adjusted models predicting willingness to allow one's child to play with an HIV-infected child, female gender and older age was associated with less willingness. However, willingness was positively associated with years of formal education.</p> <p>Conclusions</p> <p>The caregiver-child relationship is central to a child's development. OAC already face stigma as a result of their orphaned or abandoned status; the addition of HIV-related stigma represents a double burden for these children. Further research on the prevalence of HIV-related acceptance and stigma among caregivers and implications of such stigma for child development will be critical as the policy community responds to the global HIV/AIDS orphan crisis.</p