Representative Sampling Strategy Research Articles

Impact of Covid-19 Epidemic on Public Views of Tourist Travel Danger and Management

The goal of this study is to see how the Covid-19 outbreak has affected travellers' perceptions of travel risk and management. Using a sample of 156 respondents, we study visitors' perceptions of travel risk and management, as well as the impact of the epidemic on society. The data was acquired using a representative sampling strategy on social media networks and analysed using the PLS-SEM tool. According to the data, the Covid-19 epidemic has had a significant impact on travel risk and management views. The perception of travel risk and management was linked to risk management, service delivery, transportation patterns, distribution channels, avoiding overcrowded places, and hygiene and safety. The findings also revealed that travel risk and management attitudes have a moderating influence. This study's findings contribute to tourism crises and provide future research insights in the travel and tourism sector, as well as responses to improve visitors' views of travel risk and management in the post-covid recovery period.

An Empirical Study on the Public Views of Tourist Travel Risk and Crisis Management: A Case of South Sulawesi, Indonesia

The goal of this study is to see how the Covid-19 outbreak has affected travellers' perceptions of travel risk and management. Using a sample of 156 respondents, we study visitors' perceptions of travel risk and management, as well as the impact of the epidemic on society. The data was acquired using a representative sampling strategy on social media networks and analysed using the PLS-SEM tool. According to the data, the Covid-19 epidemic has had a significant impact on travel risk and management views. The perception of travel risk and management was linked to risk management, service delivery, transportation patterns, distribution channels, avoiding overcrowded places, and hygiene and safety. The findings also revealed that travel risk and management attitudes have a moderating influence. This study's findings contribute to tourism crises and provide future research insights in the travel and tourism sector, as well as responses to improve visitors' views of travel risk and management in the post-covid recovery period.

Prevalence and antimicrobial resistance of Salmonella enterica subsp. diarizonae serovar 61:k:1,5,(7) in Swiss sheep flocks

Salmonella (S.) enterica subspecies diarizonae (IIIb) serovar 61:k:1,5,(7) (S. IIIb 61:k:1,5,(7)) is considered to be sheep-associated, as it can be found in the intestine, tonsils and nose of clinically healthy sheep, but it has also been described in separate clinical disorders in sheep. In particular, S. IIIb 61:k:1,5,(7) is described as the causative agent of chronic proliferative rhinitis (CPR) in sheep. In Switzerland, CPR in sheep due to S. IIIb 61:k:1,5,(7) was first described in 2017 in a flock of Texel sheep. Therefore, we assessed the prevalence of S. IIIb 61:k:1,5,(7) within the Swiss sheep population using a representative sampling strategy. From May 2017 to June 2018 a total of 681 nasal swabs from individual clinically healthy sheep of 141 different flocks throughout Switzerland were taken. Swabs were analysed by selective enrichment for the presence of S. IIIb 61:k:1,5,(7). Additionally, antimicrobial resistance of the isolates was determined by broth microdilution. A total of 146 out of 681 nasal swabs tested positive for S. IIIb 61:k:1,5,(7), which corresponds to a prevalence on animal level of 21% (95%CI 18%−25%). In 73 out of 141 flocks tested, at least one sheep tested positive for S. IIIb 61:k:1.5,(7), resulting in a minimal prevalence on flock level of 52% (95%CI 43%−60%). Positive flocks were found in all cantons except the canton of Jura. Adults were significantly more affected than sheep under one year/lambs and positive sheep were found in several breeds. No microbiologically resistant isolates were detected, except for one isolate showing resistance against ampicillin. Because of its widespread occurrence in the Swiss sheep population, further research should focus on the pathogenic impact of S. IIIb 61:k:1,5,(7) on the health status of sheep.

The prevalence of comorbid serious mental illnesses and substance use disorders in prison populations: a systematic review and meta-analysis

SummaryBackgroundComorbid mental illnesses and substance use disorders are associated with adverse criminal, social, and health outcomes. Yet, their burden is not reliably known among prison populations. We therefore aimed to estimate the prevalence of comorbid serious mental illnesses and substance use disorders (dual disorders) among people in prison worldwide.MethodsIn this systematic review and meta-analysis, we searched 15 electronic databases (ASSIA, CAB s, Criminal Justice Database, Embase, Global Health, Global Index Medicus, IBSS, MEDLINE, NCJRS, PAIS Index, PsycINFO, Russian Science Citation Index, Scielo, Social Services s, and Web of Science) and the grey literature (Open Grey and ProQuest Dissertations & Theses Global) for studies reporting the prevalence of serious mental illnesses and substance use disorders in prison populations published between Jan 1, 1980, and Sept 25, 2021, and contacted the authors of relevant studies. Empirical studies among unselected adult prison populations that applied representative sampling strategies and validated diagnostic instruments, and either reported the prevalence of dual disorders or had authors who could provide prevalence data in correspondence, were included. Two reviewers (GB and SDL) independently extracted data from the eligible studies; both current (up to 1 year) and lifetime prevalence were extracted, if available. We sought summary estimates. Our primary outcomes were comorbid non-affective psychosis with substance use disorders and comorbid major depression with substance use disorders. We conducted a random-effects meta-analysis, explored between-sample heterogeneity with meta-regression, and calculated odds ratios (ORs) to assess bidirectional relationships between mental and substance use disorders. Risk of bias was assessed by use of a standard tool. The study protocol was registered with PROSPERO, CRD42020207301.FindingsOf 11 346 records screened, we identified 34 studies reporting the prevalence of dual disorders among individuals in prison and received unpublished prevalence data for 16 studies, totalling 50 eligible studies and 24 915 people. The mean quality score of included studies was 7·8 (SD 1·2). We found that 3·5% (95% CI 2·2–5·0) had current non-affective psychosis with any comorbid substance use disorder, representing 443 (49·2%) of 900 people with non-affective psychosis, and 9·1% (5·6–13·3) had current major depression and comorbid substance use disorders, representing 1105 (51·6%) of 2143 people with major depression. Between-sample heterogeneity was high (I2>80%). People in prison with current non-affective psychosis were significantly more likely to have substance use disorders compared with those without (OR 1·7, 95% CI 1·4–2·2). People with major depression had higher odds of substance use disorders than those without (1·6, 1·3–2·0).InterpretationAround half of the prison population with non-affective psychosis or major depression have a comorbid substance use disorder. Consideration should be given to screening for dual disorders and implementing integrated and scalable treatments.FundingEconomic and Social Research Council, Agencia Nacional de Investigación y Desarrollo (Chile), and the Wellcome Trust.

Food Insecurity on College and University Campuses: A Context and Rationale for Solutions

Food Insecurity on College and University Campuses: A Context and Rationale for Solutions

A multiple soil properties oriented representative sampling strategy for digital soil mapping

Sampling design plays a key role in digital soil mapping (DSM). Efficient sampling design for multiple soil properties is increasingly needed for multivariate soil survey and mapping. However, most of the present sampling methods are not developed for multiple soil properties. Different soil properties have different influential covariates, but usually only one set of covariates is used in designing samples for multiple soil properties which makes simultaneously mapping multiple soil properties accurately difficult. This paper proposed a multiple soil properties oriented representative sampling strategy (MPRS) by considering the influential environmental covariates for each soil property. The method first selects the most influential set of environmental covariates for each soil property, then uses fuzzy c-means (FCM) clustering to generate environmental clusters relating to spatial variation patterns for each soil property, and the selected samples are representative of as many typical locations of environmental clusters for multiple soil properties as possible. The proposed sampling method was applied for mapping soil sand content and soil organic matter content at surface (0–20 cm) and subsurface (20–40 cm) layers in a study area with 5900 km2 located in Anhui Province, China, and compared with two methods, the purposive sampling (PS) method and integrative hierarchical stepwise sampling (IHS) method. The results showed that the proposed sampling method achieved the most accurate prediction for most of the four soil properties over different sample sizes. The proposed sampling method also has an advantage to extract representative samples which can better cover multiple soil properties with a limit of a small sample size. On average, the improvement of prediction accuracy by using the MPRS method was 38.1% and 36.3% compared with PS and IHS in terms of R2, 4.8% and 4.6% in terms of RMSE, and 11.7% and 13.7% in terms of CCC, respectively. Our case study confirmed the necessity to consider the difference of the influential environmental variable combinations for the multiple soil properties oriented sampling design. We conclude that MPRS is a potential effective method for supporting DSM for multiple soil properties.

What is the role of firearms in nonfatal intimate partner violence? Findings from civil protective order case data

BackgroundPerpetrators of intimate partner violence (IPV) use firearms to injure, scare, and manipulate their partners. Abusers who have a firearm in their homes are more likely to threaten and/or kill their partner. To date, however, limited research documents the nature of IPV perpetrator firearm access or the prevalence of nonfatal firearm abuse behaviors. MethodsFederal law restricts firearm access for IPV perpetrators in qualifying domestic violence protective order (DVPO) cases and information about firearms should be disclosed during the DVPO process. We used secondary data from civil DVPO cases (n = 406) in North Carolina that were collected using a representative sampling strategy. Data were from DVPO case files and structured DVPO hearing observations. We conducted a content analysis to record IPV perpetrator access to guns and reported firearm abuse behaviors. We used a linear regression analysis to determine whether IPV perpetrator gun access was associated with higher levels of reported abuse. We also examined factors associated with perpetration of nonfatal firearm abuse. ResultsWe found evidence of perpetrator firearm access in nearly half of all cases (46%, n = 108). Controlling for covariates, gun access was significantly associated with higher levels of reported IPV (b = 0.5, p < .001). Firearm abuse was reported in nearly one out of four cases (23.1%, n = 101), and often entailed spoken threats, displaying a gun, or holding a partner at gun point. The only factors associated with firearm abuse in the multivariate models were related to English language speaking/fluency. ConclusionsGun access should be considered an indicator for severe IPV. We must ensure that existing legal mechanisms to identify and restrict abuser access to firearms are fully implemented and enforced. Firearm abuse often manifests as non-physical coercive control which is traumatic and has the potential to escalate to homicide, even in the absence of past physical violence.

Effects of non-representative sampling design on multi-scale habitat models: flammulated owls in the Rocky Mountains.

Sampling bias and autocorrelation can lead to erroneous estimates of habitat selection, model overfitting and elevated omission rates. We developed a multi-scale habitat suitability model of the flammulated owl (Psiloscops flammeolus) in the Northern Rocky Mountains based on extensive but spatially clustered survey data, and then used simulations to evaluate the effects of spatially non-representative and spatially representative sampling strategies on model performance and predictions. Our hypothesis was that models trained with spatially non-representative simulated datasets would suffer from bias in parameter estimates, and would show lower predictive performance. The models trained with the spatially representative simulated datasets greatly outperformed the models trained with the spatially non-representative simulated datasets judged on standard metrics of model performance. However, the spatially non-representative models produced superior predictions based on their ability to identify the correct spatial scales, covariates, signs and magnitudes of the species-environment relationships, when compared to the spatially representative models. Thus, it is likely that representative spatial sampling across a broad range of environmental gradients also resulted in over-dispersion of sampling data, with a higher proportion of samples falling in areas of low probability of presence, leading to lower ability to resolve the relationships between species presence-absence and environmental covariates. In contrast, the spatially non-representative sampling, by concentrating sampling along environmental gradients that are characterized by higher probability of presence of the modelled species, produced predictions that, while seeming to be weaker based on standard measures of model performance (e.g., AUC, Kappa, PCC), greatly outperformed the spatially representative models based on measures of true model prediction (e.g., correctly describing the actual spatial scales, direction and strength of species-environment relationships). Further work using simulation approaches is warranted to more fully evaluate the ability of species distribution modelling techniques to correctly identify scales, driving covariates, signs and magnitudes of relationships between species presence-absence patterns, and environmental covariates.

Estimating population lung cancer risk from radon using a resource efficient stratified population weighted sample survey protocol – Lessons and results from Ireland

A 2018 estimate indicates that there were 226,057 radon-attributable lung cancer deaths in 66 countries that had representative radon surveys. This is a shocking figure, and as it comes from only 66 countries it underestimates the worldwide death toll. Any research that enables countries to conduct representative radon surveys and to understand better the risk to citizens from radon is surely welcome. We hope this paper provides a useful methodology for estimating population risk.The estimation of population weighted average indoor radon levels requires statistically valid sampling methodologies that use a representative sample of occupied homes throughout the country. A literature review indicates that in many population weighted surveys, the sampling methodology may not have been designed to do this. This paper describes a simple, resource efficient methodology which produces statistically valid and reliable estimates based on a small scale sample that is representative of the population distribution. The resource efficient design of this study enables it to be repeated at frequent intervals providing for a longitudinal analysis of the population risk from indoor radon.This survey was conducted in Ireland using 653 measurements and a representative sampling strategy to provide a baseline population weighted radon exposure for future comparisons. This study estimates the average population weighted indoor radon concentration in Ireland to be 97.83 Bq m−3 (95% Confidence Interval 90.69 Bq m−3 to 105.53 Bq m−3), and that there are an estimated 350 lung cancer cases and 255 deaths per year due to radon exposure. The mortality rate of 5.3 per 100,000 due to indoor radon, demonstrates that radon remains one of the highest preventable causes of death in Ireland.

Recruiting a representative sample of urban South Australian Aboriginal adults for a survey on alcohol consumption

BackgroundPopulation estimates of alcohol consumption vary widely among samples of Aboriginal and Torres Strait Islander (Indigenous) Australians. Some of this difference may relate to non-representative sampling. In some communities, household surveys are not appropriate and phone surveys not feasible. Here we describe activities undertaken to implement a representative sampling strategy in an urban Aboriginal setting. We also assess our likely success.MethodsWe used a quota-based convenience sample, stratified by age, gender and socioeconomic status to recruit Indigenous Australian adults (aged 16+) in an urban location in South Australia. Between July and October 2019, trained research staff (n = 7/10, Aboriginal) recruited community members to complete a tablet computer-based survey on drinking. Recruitment occurred from local services, community events and public spaces. The sampling frame and recruitment approach were documented, including contacts between research staff and services, and then analysed. To assess representativeness of the sample, demographic features were compared to the 2016 Australian Bureau of Statistics Census of Population and Housing.ResultsThirty-two services assisted with data collection. Many contacts (1217) were made by the research team to recruit organisations to the study (emails: n = 610; phone calls: n = 539; texts n = 33; meetings: n = 34, and one Facebook message). Surveys were completed by 706 individuals – equating to more than one third of the local population (37.9%). Of these, half were women (52.5%), and the average age was 37.8 years. Sample characteristics were comparable with the 2016 Census in relation to gender, age, weekly individual income, Indigenous language spoken at home and educational attainment.ConclusionElements key to recruitment included: 1) stratified sampling with multi-site, service-based recruitment, as well as data collection events in public spaces; 2) local services’ involvement in developing and refining the sampling strategy; and 3) expertise and local relationships of local Aboriginal research assistants, including health professionals from the local Aboriginal health and drug and alcohol services. This strategy was able to reach a range of individuals, including those usually excluded from alcohol surveys (i.e. with no fixed address). Carefully pre-planned stratified convenience sampling organised in collaboration with local Aboriginal health staff was central to the approach taken.

Small-Scale Heterogeneity in Drinking Water Biofilms.

Biofilm heterogeneity has been characterized on various scales for both natural and engineered ecosystems. This heterogeneity has been attributed to spatial differences in environmental factors. Understanding their impact on localized biofilm heterogeneity in building plumbing systems is important for both management and representative sampling strategies. We assessed heterogeneity within the confined engineered ecosystem of a shower hose by high-resolution sampling (200 individual biofilm sections per hose) on varying scales (μm to m). We postulated that a biofilm grown on a single material under uniform conditions should be homogeneous in its structure, bacterial numbers, and community composition. A biofilm grown for 12 months under controlled laboratory conditions, showed homogeneity on large-scale. However, some small-scale heterogeneity was clearly observed. For example, biofilm thickness of cm-sections varied up to 4-fold, total cell concentrations (TCC) 3-fold, and relative abundance of dominant taxa up to 5-fold. A biofilm grown under real (i.e., uncontrolled) use conditions developed considerably more heterogeneity in all variables which was attributed to more discontinuity in environmental conditions. Interestingly, biofilm communities from both hoses showed comparably low diversity, with <400 taxa each, and only three taxa accounting for 57%, respectively, 73% of the community. This low diversity was attributed to a strong selective pressure, originating in migrating carbon from the flexible hoses as major carbon source. High-resolution sampling strategy enabled detailed analysis of spatial heterogeneity within an individual drinking water biofilm. This study gives insight into biofilm structure and community composition on cm-to m-scale and is useful for decision-making on sampling strategies in biofilm research and monitoring.

A high-throughput delayed fluorescence method reveals underlying differences in the control of circadian rhythms in Triticum aestivum and Brassica napus

BackgroundA robust circadian clock has been implicated in plant resilience, resource-use efficiency, competitive growth and yield. A huge number of physiological processes are under circadian control in plants including: responses to biotic and abiotic stresses; flowering time; plant metabolism; and mineral uptake. Understanding how the clock functions in crops such as Triticum aestivum (bread wheat) and Brassica napus (oilseed rape) therefore has great agricultural potential. Delayed fluorescence (DF) imaging has been shown to be applicable to a wide range of plant species and requires no genetic transformation. Although DF has been used to measure period length of both mutants and wild ecotypes of Arabidopsis, this assay has never been systematically optimised for crop plants. The physical size of both B. napus and T. aestivum led us to develop a representative sampling strategy which enables high-throughput imaging of these crops.ResultsIn this study, we describe the plant-specific optimisation of DF imaging to obtain reliable circadian phenotypes with the robustness and reproducibility to detect diverging periods between cultivars of the same species. We find that the age of plant material, light regime and temperature conditions all significantly effect DF rhythms and describe the optimal conditions for measuring robust rhythms in each species. We also show that sections of leaf can be used to obtain period estimates with improved throughput for larger sample size experiments.ConclusionsWe present an optimized protocol for high-throughput phenotyping of circadian period specific to two economically valuable crop plants. Application of this method revealed significant differences between the periods of several widely grown elite cultivars. This method also identified intriguing differential responses of circadian rhythms in T. aestivum compared to B. napus; specifically the dramatic change to rhythm robustness when plants were imaged under constant light versus constant darkness. This points towards diverging networks underlying circadian control in these two species.

An integrated method of selecting environmental covariates for predictive soil depth mapping

Environmental covariates are the basis of predictive soil mapping. Their selection determines the performance of soil mapping to a great extent, especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high. In this study, we proposed an integrated method to select environmental covariates for predictive soil depth mapping. First, candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge. Second, three conventional methods (Pearson correlation analysis (PsCA), generalized additive models (GAMs), and Random Forest (RF)) were used to generate optimal combinations of environmental covariates. Finally, three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate. We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China. A total of 129 soil sampling sites were collected using a representative sampling strategy, and RF and support vector machine (SVM) models were used to map soil depth. The results showed that compared to the set of environmental covariates selected by the three conventional selection methods, the set of environmental covariates selected by the proposed method achieved higher mapping accuracy. The combination from the proposed method obtained a root mean square error (RMSE) of 11.88 cm, which was 2.25–7.64 cm lower than the other methods, and an R2 value of 0.76, which was 0.08–0.26 higher than the other methods. The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.

Incremental sampling methodology for petroleum hydrocarbon contaminated soils: volume estimates and remediation strategies

ABSTRACTCurrent environmental assessments for petroleum hydrocarbon (PHC) contaminated sites are dependent on discrete soil sampling to estimate the degree and extent of contamination, leading to unreliable and non-reproducible results. Incremental sampling methodology (ISM) involves collecting and combining samples within a targeted area and holds promise for being a cost-effective, representative, and reproducible sampling strategy for contaminated site characterization. We hypothesized that traditional Phase II Environmental Site Assessments (ESA) discrete and ISM sampling protocols were not mutually exclusive, and the two approaches can be used to formulate a responsible land management strategy. Results gathered through ISM were compared to those from Phase II ESA for two PHC contaminated sites in Canada. Both methods indicated the sites were impacted with PHC beyond Saskatchewan Tier I guidance, however, the delineation of the PHC plume differed by as much as 75% for the heavier hydrocarbons. The Phase II ESA methods had higher incidences of false positive results and an overestimation of contamination at depth. A laboratory experiment confirmed that ISM does not “dilute” the samples as to cause underestimation, whereby the hydrocarbon concentrations for a single combined sample was equivalent to the mean of 30 discrete samples. Based on our results, sites should undergo risk assessment based on the estimates of the Phase II ESA results using vapor phase logs to estimate contaminant extent. If exposure pathways cannot be eliminated through the risk assessment process, remediation planning based on the ISM results is justified given the demonstrated cost-effectiveness, representativeness, and reproducibility.

Assessing Drivers of Coastal Primary Production in Northern Marguerite Bay, Antarctica

The coastal ocean of the climatically-sensitive west Antarctic Peninsula is experiencing changes in the physical and (photo)chemical properties that strongly affect the phytoplankton. Consequently, a shift from diatoms, pivotal in the Antarctic food web, to more mobile and smaller flagellates has been observed. We seek to identify the main drivers behind primary production (PP) without any assumptions beforehand to obtain the best possible model of PP. We employed a combination of field measurements and modeling to discern and quantify the influences of variability in physical, (photo)chemical and biological parameters on PP in northern Marguerite Bay. Field data of high-temporal resolution (November 2013 – March 2014) collected at a long-term monitoring site here were combined with estimates of PP derived from photosynthesis-irradiance incubations and modeled using mechanistic and statistical models. Daily PP varied greatly and averaged 1764 mg C m-2 d-1 with a maximum of 6908 mg C m-2 d-1 after the melting of sea ice and the likely release of diatoms concentrated therein. A non-assumptive random forest model (RF) with all possibly relevant parameters (MRFmax) showed that variability in PP was best explained by light availability and chlorophyll a followed by physical (temperature, mixed layer depth and salinity) and chemical (phosphate, total nitrogen and silicate) water column properties. The predictive power from the relative abundances of diatoms, cryptophytes and haptophytes (as determined by pigment fingerprinting) to PP was minimal. However, the variability in PP due to changes in species composition was most likely underestimated due to the contrasting strategies of these phytoplankton groups as we observed significant negative relations between PP and the relative abundance of flagellates groups. Our reduced model (MRFmin) showed how light availability, chlorophyll a and total nitrogen concentrations can be used to obtain the best estimate of PP (R2 = 0.93). The resulting estimates from our models suggest summer PP to have been between 214.4 g and 176.1 g C m-2. Through the employment of a modeling technique without any assumptions apart from a representative sampling strategy, we showed and estimated how PP in this climatically sensitive and changing region can best be predicted and described.

Regional Soil Mapping Using Multi-Grade Representative Sampling and a Fuzzy Membership-Based Mapping Approach

High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management. For areas with no point data, regional soil mapping includes two steps: soil sampling and soil mapping. Because sampling over a large area is costly, efficient sampling strategies are required. A multi-grade representative sampling strategy, which designs a small number of representative samples with different representative grades to depict soil spatial variations at different scales, could be a potentially efficient sampling strategy for regional soil mapping. Additionally, a suitable soil mapping approach is needed to map regional soil variations based on a small number of samples. In this study, the multi-grade representative sampling strategy was applied and a fuzzy membership-weighted soil mapping approach was developed to map soil sand percentage and soil organic carbon (SOC) at 0–20 and 20–40 cm depths in a study area of 5 900 km2 in Anhui Province of China. First, geographical sub-areas were delineated using a parent lithology data layer. Next, fuzzy c-means clustering was applied to two climate and four terrain variables in each stratum. The clustering results (environmental cluster chains) were used to locate representative samples. Evaluations based on an independent validation sample set showed that the addition of samples with lower representativeness generally led to a decrease of root mean square error (RMSE). The declining rates of RMSE with the addition of samples slowed down for 20–40 cm depth, but fluctuated for 0–20 cm depth. The predicted SOC maps based on the representative samples exhibited higher accuracy, especially for soil depth 20–40 cm, as compared to those based on legacy soil data. Multi-grade representative sampling could be an effective sampling strategy at a regional scale. This sampling strategy, combined with the fuzzy membership-based mapping approach, could be an optional effective framework for regional soil property mapping. A more detailed and accurate soil parent material map and the addition of environmental variables representing human activities would improve mapping accuracy.

Heterogeneous Rates of Molecular Evolution and Diversification Could Explain the Triassic Age Estimate for Angiosperms.

Dating analyses based on molecular data imply that crown angiosperms existed in the Triassic, long before their undisputed appearance in the fossil record in the Early Cretaceous. Following a re-analysis of the age of angiosperms using updated sequences and fossil calibrations, we use a series of simulations to explore the possibility that the older age estimates are a consequence of (i) major shifts in the rate of sequence evolution near the base of the angiosperms and/or (ii) the representative taxon sampling strategy employed in such studies. We show that both of these factors do tend to yield substantially older age estimates. These analyses do not prove that younger age estimates based on the fossil record are correct, but they do suggest caution in accepting the older age estimates obtained using current relaxed-clock methods. Although we have focused here on the angiosperms, we suspect that these results will shed light on dating discrepancies in other major clades.

Detection and quantification of hepatitis A virus and norovirus in Spanish authorized shellfish harvesting areas

An 18-month survey was conducted in ten class “B” harvesting areas from two Galician Rias (NW of Spain), the most important bivalve production area in Europe, to determine the prevalence of hepatitis A virus (HAV) and human norovirus (NoV), including genogroups I (GI) and II (GII). Quantification was performed by reverse transcription real-time PCR (RT-qPCR), according to the recently developed standard method ISO/TS 15216-1:2013. Four bivalve species were studied, including wild and cultured mussels (Mytilus galloprovincialis), clams (Venerupis philippinarum and Venerupis decussata) and cockles (Cerastoderma edule). Overall, 55.4% of samples were contaminated by at least one of the studied viruses, being detected the simultaneous presence of two or three viruses in 11.3% of the cases. NoV GI was the most prevalent virus (32.1%), followed by NoV GII (25.6%) and HAV (10.1%). Cultured mussels showed the highest percentage of positive samples (61.4%), followed by cockles (59.4%), wild mussels (54.3%) and clams (38.7%). Viral contamination levels for most of the positive samples ranged from 102 to 103 RNA copies/g of digestive tissue (RNAc/g DT). The presence of viral contamination was statistically higher (P<0.0001) in warm months (April to September) than in cold months (October to March). The data presented here may contribute to the development of more representative sampling strategies, in monitoring and management of shellfish growing areas as well as being useful in a future scenario in which viral critical values are adopted in legislation.

Radial line-scans as representative sampling strategy in dried-droplet laser ablation of liquid samples deposited on pre-cut filter paper disks

Nebulising liquid samples and using the aerosol thus obtained for further analysis is the standard method in many current analytical techniques, also with inductively coupled plasma (ICP)-based devices. With such a set-up, quantification via external calibration is usually straightforward for samples with aqueous or close-to-aqueous matrix composition. However, there is a variety of more complex samples. Such samples can be found in medical, biological, technological and industrial contexts and can range from body fluids, like blood or urine, to fuel additives or fermentation broths. Specialized nebulizer systems or careful digestion and dilution are required to tackle such demanding sample matrices. One alternative approach is to convert the liquid into a dried solid and to use laser ablation for sample introduction. Up to now, this approach required the application of internal standards or matrix-adjusted calibration due to matrix effects. In this contribution, we show a way to circumvent these matrix effects while using simple external calibration for quantification. The principle of representative sampling that we propose uses radial line-scans across the dried residue. This compensates for centro-symmetric inhomogeneities typically observed in dried spots. The effectiveness of the proposed sampling strategy is exemplified via the determination of phosphorus in biochemical fermentation media. However, the universal viability of the presented measurement protocol is postulated. Detection limits using laser ablation-ICP-optical emission spectrometry were in the order of 40μgmL−1 with a reproducibility of 10 % relative standard deviation (n=4, concentration=10 times the quantification limit). The reported sensitivity is fit-for-purpose in the biochemical context described here, but could be improved using ICP-mass spectrometry, if future analytical tasks would require it. Trueness of the proposed method was investigated by cross-validation with conventional liquid measurements, and by analyzing IAEA-153 reference material (Trace Elements in Milk Powder); a good agreement with the certified value for phosphorus was obtained.

The "backbone" of stigma: identifying the global core of public prejudice associated with mental illness.

We used the Stigma in Global Context-Mental Health Study to assess the core sentiments that represent consistent, salient public health intervention targets. Data from 16 countries employed a nationally representative sampling strategy, international collaboration for instrument development, and case vignettes with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition depression and schizophrenia criteria. We measured knowledge and prejudice with existing questions and scales, and employed exploratory data analysis to examine the public response to 43 items. Across countries, levels of recognition, acceptance of neurobiological attributions, and treatment endorsement were high. However, a core of 5 prejudice items was consistently high, even in countries with low overall stigma levels. The levels were generally lower for depression than schizophrenia, and exclusionary sentiments for more intimate venues and in authority-based roles showed the greatest stigma. Negative responses to schizophrenia and depression were highly correlated across countries. These results challenge researchers to reconfigure measurement strategies and policymakers to reconsider efforts to improve population mental health. Efforts should prioritize inclusion, integration, and competences for the reduction of cultural barriers to recognition, response, and recovery.