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Suburban inequality is the focus of this double issue of "RSF: The Russell Sage Foundation Journal of the Social Sciences." This introduction addresses the limited related scholarship, describes how inequality unfolds differently in suburban communities than in urban and rural communities, and draws attention to urgent issues related to stratification between and within suburban communities. We argue that inattention to the study of suburban space, methodological and disciplinary silos, and the changing nature of the suburbs have left large holes in our understanding of how inequality operates. This critical review covers areas such as measurement, forgotten suburban scholarship, demographic change, suburban poverty, social supports, race, immigration, education, politics, policing, and future directions for suburban studies. In our call for resisting amnesia, we also draw attention to forgotten suburban histories and studies of a diverse range of suburban communities.

In 1997, the Government of Jamaica signed a three-year cooperative agreement with the Government of Cuba to support Jamaican education through the provision of teachers of Spanish, mathematics and the sciences. After several renewals, the programme is in its 26th year, with 76 Cuban teachers currently resident in Jamaica and serving at the primary, secondary and tertiary levels of the country's education system. Through focus group discussions with 32 teachers in the 23rd cohort, this article reports on the linguistic insertion of the teachers into their Jamaican classroom environments. It assesses the strengths and limitations of the linguistico-cultural preparation of the teachers for working in the Jamaican education system, and documents their sociolinguistic and cultural adjustment experiences. Results indicate that while the information and training sessions on pedagogy were useful and informative, the intergovernmental cooperative agreement programme could benefit significantly from the inclusion of a strong and targeted initiative designed to initiate teachers into Jamaican sociolinguistic realities.

AI-assisted data analysis can help risk analysts better understand exposure-response relationships by making it relatively easy to apply advanced statistical and machine learning methods, check their assumptions, and interpret their results. This paper demonstrates the potential of large language models (LLMs), such as ChatGPT, to facilitate statistical analyses, including survival data analyses, for health risk assessments. Through AI-guided analyses using relatively recent and advanced methods such as Individual Conditional Expectation (ICE) plots using Random Survival Forests and Heterogeneous Treatment Effects (HTEs) estimated using Causal Survival Forests, population-level exposure-response functions can be disaggregated into individual-level exposure-response functions. These reveal the extent of heterogeneity in risks across individuals for different levels of exposure, holding other variables fixed. By applying these methods to an illustrative dataset on blood lead levels (BLL) and mortality risk among never-smoker men from the NHANES III survey, we show how AI can clarify inter-individual variations in exposure-associated risks. The results add insights not easily obtained from traditional parametric or semi-parametric models such as logistic regression and Cox proportional hazards models, illustrating the advantages of non-parametric approaches for quantifying heterogeneous causal effects on survival times. This paper also suggests some practical implications of using AI in regulatory health risk assessments and public policy decisions.

AimTo evaluate the impact of COVID-19 on clinical orthodontic services, orthodontic education, and the emotional well-being of orthodontists and orthodontic trainees in India.Materials and methodsThe survey was designed using Survey Monkey™ and distributed to members of the Indian Orthodontic Society via their registered email address and also via social media platforms (WhatsApp and LinkedIn).ResultsA total of 610 responses to the survey were received. The majority of respondents agreed on the negative impact of COVID-19 on clinical activity and the associated income of orthodontists. Respondents reported that this was mainly due to national restrictions (70.1%), increased cross infection measures (59.6%), state restrictions (55.9%), and social distancing (39.4%). Ninety one percent of respondents agreed that orthodontic staff should have evidence of vaccination before providing care.COVID-19 was found to have a negative impact on the trainees’ perceptions of their clinical dexterity (72.4%), their confidence with respect to academic knowledge (66.5%), their mental health (80.7%), and their stress levels during the pandemic (93.2%).ConclusionThe COVID-19 pandemic has had a negative impact on orthodontic specialists and post-graduate trainees in India. The impact on trainees’ mental health was significantly higher compared to trainees from other countries. Decreased clinical activity has reduced the opportunities for learning, and trainers must rise to the challenge of providing additional support to this cohort of trainees who will progress to become the future orthodontic workforce.

Several factors, including breed, lead to divergent performance of pigs for production and reproduction traits in different environments. A recent genomics study showed that Modern European (ME) pig breeds contribute to the ancestry of smallholder pigs in the Hoima and Kamuli districts, Uganda. These pigs were also involved in a longitudinal study with several traits recorded, including 540 body weights (WT) of 374 growing pigs, 195 records of total number of piglets born alive (TBA) of 157 sows, and 110 total number weaned (TNW) records of 94 sows. Linear mixed-effects models were used to test for the significance of environmental effects, including housing system, geographic location, and the season when the events occurred as well as animal-specific effects like age, sex, parity, and farrow-to-weaning interval. Stepwise model reduction starting from models with all main effects and pairwise interactions was applied. The final models were then expanded to include proportions of Modern European (ME) ancestry for the subset of animals genotyped, following genomic ancestry analysis based on a Porcine 50K SNP Chip. ME ancestry proportions ranged from 0.02 to 0.50 and were categorized into three classes (low/medium/high ME) based on 33.3% quantiles. The effects of ME classes on WT and TBA were not significant. ME showed a significant effect on TNW. Sows with a high proportion of ME weaned 2.4 piglets more than the low group, the medium ME group being intermediate. This study used genomic data to investigate the effects of genetic ancestry on the performance of smallholder pigs in Uganda. The proportion of Modern European ancestry did not exceed 0.50, therefore not allowing for the comparison of local versus pure “exotic” types of pigs. For the range of ancestries observed, which is the relevant one for current smallholder systems in Uganda, differences were small for the body weight of growing pigs and the number of piglets born alive, while higher proportions of ME ancestry resulted in significantly more piglets weaned. The availability of genotypes of a higher number of growing pigs would have been beneficial for drawing conclusions on the effect of ME ancestry on the growth rates of smallholder pigs in Uganda.

IntroductionLitter size in pigs has increased steadily since 1990. Because of unfavorable genetic correlations with piglet mortality, breeding goals should include survival traits next to litter size. Unbalanced breeding programs that neglect this requirement have produced increased mortality levels, attracting negative public attention. Balanced breeding does not have this disadvantage, but the general public is largely unaware of this.MethodsWe present long-term time trends as realized in commercial breeding. The data includes (i) phenotypes of litter size, piglet birth weight, and piglet mortality, as used in routine breeding value estimation; and (ii) the genomic Best Linear Unbiased Prediction (gBLUP) estimated breeding values thus obtained. Piglet mortality (2001–2022) and birth weight (2009–2022) phenotypes were related to litter size by recording year. Estimated breeding values (EBVs) for the mortality traits were regressed on those for litter size by birth year (2012–2022).ResultsAverage litter size is very weakly correlated to the mortality (R2 ≤ 0.06) and birth weight (0.07 ≤ R2 ≤ 0.26) traits, and those correlations are unfavorable (antagonistic) within each year. However, all traits analyzed here show favorable simultaneous phenotypic and genetic trends over time: the antagonisms are neutralized by balanced breeding. Above the annual mean litter size level, farrowing and lactation mortality rates increased with increasing litter size in every year (unfavorable), but the annual intercepts and the slopes decreased from 2001 to 2022 (favorable). Average litter birth weight decreased with litter size in every year (unfavorable), but the annual intercepts increased and the slopes decreased from 2009 to 2022 (favorable). The within-litter birth weight variation coefficient increased with litter size in every year (unfavorable), but the annual intercepts decreased from 2009 to 2022 (favorable). The proportion of low birth weights (i.e.,

Abstract The inter-cattle growth variations stem from the interaction of many metabolic processes making animal selection difficult. We hypothesized that growth could be predicted using metabolomics. Urinary biomarkers of cattle feed efficiency were explored using mass spectrometry-based untargeted and targeted metabolomics. Feed intake and weight-gain was measured in steers (n = 75) on forage-based growing rations (stage-1, 84 days) followed by high-concentrate finishing rations (stage-2, 84 days). Urine from days 0, 21, 42, 63, and 83 in each stage were analyzed from steers with the greater (n = 14) and least (n = 14) average-daily-gain (ADG) and comparable dry-matter-intake (DMI; within 0.32 SD of the mean). Steers were slaughtered after stage-2. Adjusted fat-thickness and carcass-yield-grade increased in greater-ADG-cattle selected in stage-1, but carcass traits did not differ between ADG-selected in stage-2. Overall 85 untargeted metabolites segregated greater- and least-ADG animals, with overlap across diets (both stages) and breed type, despite sampling time effects. Total 18-bile acids (BAs) and 5-steroids were quantified and associated with performance and carcass quality across ADG-classification depending on the stage. Stepwise logistic regression of urinary BA and steroids had > 90% accuracy identifying efficient-ADG-steers. Urine metabolomics provides new insight into the physiological mechanisms and potential biomarkers for feed efficiency.

Protecting the health and safety of workers in industrial operations is a top priority. One of the resources used in industry to ensure worker safety is the occupational exposure limit (OEL). OELs are derived from the assessment and interpretation of empirical data from animal and/or human studies. There are various guidelines for the derivation and implementation of OELs globally, with a range of stakeholders (including regulatory bodies, governmental agencies, expert groups and others). The purpose of this manuscript is to supplement existing guidance with learnings from a multidisciplinary team approach within an industry setting. The framework we present is similar in construct to other risk assessment frameworks and includes: (1) problem formulation, (2) literature review, (3) weight of evidence considerations, (4) point of departure selection/derivation, (5) application of assessment factors, and the final step, (6) derivation of the OEL. Within each step are descriptions and examples to consider when incorporating data from various disciplines such as toxicology, epidemiology, and exposure science. This manuscript describes a technical framework by which available data relevant for occupational exposures is compiled, analyzed, and utilized to inform safety threshold derivation applicable to OELs.

St. Augustinegrass is a warm-season grass species widely utilized as turf in the southeastern U.S. It shows significant variation in plant growth and morphological characteristics, some of which are potentially associated with drought tolerance. However, the genetic basis of these variations is not well understood. Detecting quantitative trait loci (QTL) associated with morphological traits will provide a foundation for the application of genetic and molecular breeding in St. Augustinegrass. In this study, we report QTL associated with morphological traits, including leaf blade width (LW), leaf blade length (LL), canopy density (CD), and shoot growth orientation (SGO) in a St. Augustinegrass 'Raleigh' x 'Seville' mapping population containing 115 F1 hybrids. Phenotypic data were collected from one greenhouse and two field trials. Single and joint trial analyses were performed, finding significant phenotypic variance among the hybrids for all traits. Interval mapping (IM) and multiple QTL method (MQM) analysis detected seven QTL for CD, four for LL, five for LW, and two for SGO, which were distributed on linkage groups RLG1, RLG9, SLG3, SLG7, SLG8 and SLG9. In addition, three genomic regions where QTL colocalized were identified on Raleigh LG1 and Seville LG3. One genomic region on Seville LG3 overlapped with two previously reported drought-related QTL for leaf relative water content (RWC) and percent green cover (GC). Several candidate genes related to plant development and drought stress response were identified within QTL intervals. The QTL identified in this study represent a first step in identifying genes controlling morphological traits that might accelerate progress in selection of St. Augustinegrass lines with lower water usage.

The aim of this visualization is to highlight sociodemographic variation among Black suburbs and spur further research on them. The authors provide a sociodemographic portrait of Black suburbs, defined as those that are more than 50 percent Black, to highlight their prevalence and variety. The 100 largest metropolitan statistical areas in 2018 contained 413 Black suburbs, representing 5 percent of all suburbs. The authors examine distributions of Black suburbs on two characteristics, median household income and housing age, to make two points. First, Black suburbs feature substantial sociodemographic variation in terms of both income and housing age. Second, this variation is not primarily a function of suburbs’ Black population share. Contrary to common assumptions, Black suburbs are not all older suburbs populated by the socioeconomically disadvantaged but include newer, middle-class, and affluent places as well.

Throughout history, environmental epidemiology has proven crucial to identify certain threats to human health and to provide a basis for the development of life-saving public health policies. However, epidemiologists are facing challenges when studying tenuous threats such as environmental exposure to chemicals, whose association with adverse health effects may be difficult to characterize. As a result, epidemiological data can seldom be fully leveraged for quantitative risk assessment and decision-making. Despite two decades of efforts to improve a more systematic integration of human data to evaluate human health risks, assessors still heavily rely on animal data to do so, while epidemiology plays more of a secondary role. Although the need for more and better collaboration between risk assessors and epidemiologists is widely recognized, both fields tend to remain siloed. In 2017, the Health and Environmental Sciences Institute initiated a project engaging the epidemiology, exposure science, and regulatory communities with tripartite representation from regulators, industry, and academia in a dialogue on the use of environmental epidemiology for regulatory decision-making. Several focus groups attended by epidemiology, exposure science, and risk assessment experts were organized to explore incentives and barriers to collaboration, to ultimately bridge the gap between the various disciplines, and to realize the full potential of epidemiological data in risk assessment. Various ideas that have emerged from these meetings could help ensure the better integration of epidemiological data in quantitative risk assessment and contribute to building confidence in a robust and science-based regulatory decision-making process.

OBJECTIVES: To understand the impact of the COVID-19 pandemic on orthodontic clinical services in Jordan. MATERIALS AND METHODS: Google Forms electronic questionnaires were distributed between March and June 2021 using the WhatsApp platform of the Jordanian Orthodontic Society and via direct WhatsApp messages. The survey was identical and contemporaneous to that used in the United Kingdom.[9] RESULTS: The survey yielded 127 unique responses, giving a response rate of 53.1%. The factors that had the greatest impact on service delivery were government guidance (78%), patients' fear of attending (70.1%), and increased cross-infection measures (65.4%). The survey revealed that there had been a perceived deterioration in oral hygiene (60.3%) and levels of compliance (61.9%) in patients in active treatment even though patients in treatment were prioritized during the pandemic. Also, 56.8% of respondents felt clinical staff should be vaccinated and undergo regular testing for COVID-19. Orthodontists within Jordan were optimistic regarding the speed at which clinical services would return to pre-pandemic levels of activity with 32.5% anticipating this would take less than 6 months. CONCLUSIONS: Patients in active orthodontic treatment, during COVID-19, have been prioritized but at the expense of new and review patients. Respondents in Jordan felt COVID-19 would have ongoing effects on clinical care, professional practice, and society. Most respondents supported the vaccination of orthodontic staff and were optimistic about the effect of a vaccination program on restoring clinical services.

Venom peptides are potent and selective modulators of voltage-gated ion channels that regulate neuronal function both in health and in disease. We previously identified the spider venom peptide Tap1a from the Venezuelan tarantula Theraphosa apophysis that targeted multiple voltage-gated sodium and calcium channels in visceral pain pathways and inhibited visceral mechano-sensing neurons contributing to irritable bowel syndrome. In this work, alanine scanning and domain activity analysis revealed Tap1a inhibited sodium channels by binding with nanomolar affinity to the voltage-sensor domain II utilising conserved structure-function features characteristic of spider peptides belonging to family NaSpTx1. In order to speed up the development of optimized NaV-targeting peptides with greater inhibitory potency and enhanced in vivo activity, we tested the hypothesis that incorporating residues identified from other optimized NaSpTx1 peptides into Tap1a could also optimize its potency for NaVs. Applying this approach, we designed the peptides Tap1a-OPT1 and Tap1a-OPT2 exhibiting significant increased potency for NaV1.1, NaV1.2, NaV1.3, NaV1.6 and NaV1.7 involved in several neurological disorders including acute and chronic pain, motor neuron disease and epilepsy. Tap1a-OPT1 showed increased potency for the off-target NaV1.4, while this off-target activity was absent in Tap1a-OPT2. This enhanced potency arose through a slowed off-rate mechanism. Optimized inhibition of NaV channels observed in vitro translated in vivo, with reversal of nocifensive behaviours in a murine model of NaV-mediated pain also enhanced by Tap1a-OPT. Molecular docking studies suggested that improved interactions within loops 3 and 4, and C-terminal of Tap1a-OPT and the NaV channel voltage-sensor domain II were the main drivers of potency optimization. Overall, the rationally designed peptide Tap1a-OPT displayed new and refined structure-function features which are likely the major contributors to its enhanced bioactive properties observed in vivo. This work contributes to the rapid engineering and optimization of potent spider peptides multi-targeting NaV channels, and the research into novel drugs to treat neurological diseases.

The scrambling of quantum information in a many-body system leads to the emergence of statistical mechanics and chaotic behaviour. Here the authors establish quantitative relationships between experimentally-measureable correlators, the Rényi entropy and Lyapunov exponents in the Dicke model.

Pig herds in Africa comprise genotypes ranging from local ecotypes to commercial breeds. Many animals are composites of these two types and the best levels of crossbreeding for particular production systems are largely unknown. These pigs are managed without structured breeding programs and inbreeding is potentially limiting. The objective of this study was to quantify ancestry contributions and inbreeding levels in a population of smallholder pigs in Uganda. The study was set in the districts of Hoima and Kamuli in Uganda and involved 422 pigs. Pig hair samples were taken from adult and growing pigs in the framework of a longitudinal study investigating productivity and profitability of smallholder pig production. The samples were genotyped using the porcine GeneSeek Genomic Profiler (GGP) 50K SNP Chip. The SNP data was analyzed to infer breed ancestry and autozygosity of the Uganda pigs. The results showed that exotic breeds (modern European and old British) contributed an average of 22.8% with a range of 2–50% while “local” blood contributed 69.2% (36.9–95.2%) to the ancestry of the pigs. Runs of homozygosity (ROH) greater than 2 megabase (Mb) quantified the average genomic inbreeding coefficient of the pigs as 0.043. The scarcity of long ROH indicated low recent inbreeding. We conclude that the genomic background of the pig population in the study is a mix of old British and modern pig ancestries. Best levels of admixture for smallholder pigs are yet to be determined, by linking genotypes and phenotypic records.

We theoretically study the dynamical phase diagram of the Dicke model in both classical and quantum limits using large, experimentally relevant system sizes. Our analysis elucidates that the model features dynamical critical points that are strongly influenced by features of chaos and emergent integrability in the model. Moreover, our numerical calculations demonstrate that mean-field features of the dynamics remain valid in the exact quantum dynamics, but we also find that in regimes where quantum effects dominate signatures of the dynamical phases and chaos can persist in purely quantum metrics such as entanglement and correlations. Our predictions can be verified in current quantum simulators of the Dicke model including arrays of trapped ions.

Understanding public attitudes towards death is needed to inform health policies to foster community death awareness and preparedness. Linguistic sentiment analysis of how people describe their feelings about death can add to knowledge gained from traditional self-reports. This study provided the first description of emotive attitudes expressed towards death utilising textual sentiment analysis for the dimensions of valence, arousal and dominance. A linguistic lexicon of sentiment norms was applied to activities conducted in an online course for the general-public designed to generate discussion about death. We analysed the sentiment of words people chose to describe feelings about death, for themselves, for perceptions of the feelings of 'others', and for longitudinal changes over the time-period of exposure to a course about death (n = 1491). The results demonstrated that sadness pervades affective responses to death, and that inevitability, peace, and fear were also frequent reactions. However, words chosen to represent perceptions of others' feelings towards death suggested that participants perceived others as feeling more negative about death than they do themselves. Analysis of valence, arousal and dominance dimensions of sentiment pre-to-post course participation demonstrated that participants chose significantly happier (more positive) valence words, less arousing (calmer) words, and more dominant (in-control) words to express their feelings about death by the course end. This suggests that the course may have been helpful in participants becoming more emotionally accepting in their feelings and attitude towards death. Furthermore, the change over time appeared greater for younger participants, who showed more increase in the dominance (power/control) and pleasantness (valence) in words chosen at course completion. Sentiment analysis of words to describe death usefully extended our understanding of community death attitudes and emotions. Future application of sentiment analysis to other related areas of health policy interest such as attitudes towards Advance Care Planning and palliative care may prove fruitful.

Abstract Background St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] is a warm-season, perennial turfgrass species well adapted for home lawns and commercial landscapes with economic and ecological value. However, a lack of genomic resources in St. Augustinegrass has hindered the full utilization of genetic variance for maximizing genetic gain and limited our understanding of the species’ evolution. Results In this study, we constructed the first high-density linkage map for St. Augustinegrass using a genotyping by sequencing (GBS) approach. The integrated linkage map consists of 2871 single nucleotide polymorphism (SNP) and 81 simple sequence repeat (SSR) markers, spanning 1241.7 cM, with an average distance of 0.4 cM between markers, and thus represents the densest genetic map for St. Augustinegrass to date. Comparative genomic analysis revealed inter-chromosome arrangements and independent nested chromosome fusion events that occurred after St. Augustinegrass, foxtail millet, sorghum, and rice diverged from a common ancestor. Forty-eight candidate quantitative trait loci (QTL) were detected for turf quality-related traits, including overall turf quality, leaf texture, genetic color, and turf density. Three hot spot regions were identified on linkage groups LG3 and LG8, where multi-QTL for different traits overlapped. Several leaf development related genes were contained within these identified QTL regions. Conclusions This study developed the first high-density genetic map and identified putative QTL related to turf quality, which provide valuable genetic resources for marker-assisted selection (MAS) in St. Augustinegrass.

We use the quantum Fisher information (QFI) to diagnose a dynamical phase transition (DPT) in a closed quantum system, which is usually defined in terms of nonanalytic behavior of a time-averaged order parameter. Employing the Lipkin-Meshkov-Glick model as an illustrative example, we find that the DPT correlates with a peak in the QFI that can be explained by a generic connection to an underlying excited-state quantum phase transition that also enables us to relate the scaling of the QFI with the behavior of the order parameter. Motivated by the QFI as a quantifier of metrologically useful correlations and entanglement, we also present a robust interferometric protocol that can enable DPTs as a platform for quantum-enhanced sensing.

Abstract Background Tobacco (Nicotiana tabacum) is an important plant model system that has played a key role in the early development of molecular plant biology. The tobacco genome is large and its characterisation challenging because it is an allotetraploid, likely arising from hybridisation between diploid N. sylvestris and N. tomentosiformis ancestors. A draft assembly was recently published for N. tabacum, but because of the aforementioned genome complexities it was of limited utility due to a high level of fragmentation. Results Here we report an improved tobacco genome assembly, which, aided by the application of optical mapping, achieves an N50 size of 2.17 Mb and enables anchoring of 64% of the genome to pseudomolecules; a significant increase from the previous value of 19%. We use this assembly to identify two homeologous genes that explain the differentiation of the burley tobacco market class, with potential for greater understanding of Nitrogen Utilization Efficiency and Nitrogen Use Efficiency in plants; an important trait for future sustainability of agricultural production. Conclusions Development of an improved genome assembly for N. tabacum enables what we believe to be the first successful map-based gene discovery for the species, and demonstrates the value of an improved assembly for future research in this model and commercially-important species.

Assessments of methodological and reporting quality are critical to adequately judging the credibility of a study's conclusions and to gauging its potential reproducibility. To aid those seeking to assess the methodological or reporting quality of studies relevant to toxicology, we conducted a scoping review of the available guidance with respect to four types of studies: in vivo and in vitro, (quantitative) structure-activity relationships ([Q]SARs), physico-chemical, and human observational studies. Our aims were to identify the available guidance in this diverse literature, briefly summarize each document, and distill the common elements of these documents for each study type. In general, we found considerable guidance for in vivo and human studies, but only one paper addressed in vitro studies exclusively. The guidance for (Q)SAR studies and physico-chemical studies was scant but authoritative. There was substantial overlap across guidance documents in the proposed criteria for both methodological and reporting quality. Some guidance documents address toxicology research directly, whereas others address preclinical research generally or clinical research and therefore may not be fully applicable to the toxicology context without some translation. Another challenge is the degree to which assessments of methodological quality in toxicology should focus on risk of bias – as in clinical medicine and healthcare – or be broadened to include other quality measures, such as confirming the identity of test substances prior to exposure. Our review is intended primarily for those in toxicology and risk assessment seeking an entry point into the extensive and diverse literature on methodological and reporting quality applicable to their work. Keywords: Methodological quality, Reporting quality, Risk of bias, Scoping review, Toxicity studies

Single point estimates of human health hazard/toxicity values such as a reference dose (RfD) are generally used in chemical hazard and risk assessment programs for assessing potential risks associated with site- or use-specific exposures. The resulting point estimates are often used by risk managers for regulatory decision-making, including standard setting, determination of emission controls, and mitigation of exposures to chemical substances. Risk managers, as well as stakeholders (interested and affected parties), often have limited information regarding assumptions and uncertainty factors in numerical estimates of both hazards and risks. Further, the use of different approaches for addressing uncertainty, which vary in transparency, can lead to a lack of confidence in the scientific underpinning of regulatory decision-making. The overarching goal of this paper, which was developed from an invited participant workshop, is to offer five approaches for presenting toxicity values in a transparent manner in order to improve the understanding, consideration, and informed use of uncertainty by risk assessors, risk managers, and stakeholders. The five approaches for improving the presentation and communication of uncertainty are described using U.S. Environmental Protection Agency's (EPA's) Integrated Risk Information System (IRIS) as a case study. These approaches will ensure transparency in the documentation, development, and use of toxicity values at EPA, the Agency for Toxic Substances and Disease Registry (ATSDR), and other similar assessment programs in the public and private sector. Further empirical testing will help to inform the approaches that will work best for specific audiences and situations. Keywords: Uncertainty, Hazard, Risk assessment, Risk communication, Hazard communication, Toxicity characterization

St. Augustinegrass (Stenotaphrum secundatum) is a warm-season grass species commonly utilized as turf in the southeastern US. Improvement in the drought tolerance of St. Augustinegrass has significant value within the turfgrass industry. Detecting quantitative trait loci (QTL) associated with drought tolerance will allow for advanced breeding strategies to identify St. Augustinegrass germplasm with improved performance for this trait. A multi-year and multi-environment study was performed to identify QTL in a 'Raleigh' x 'Seville' mapping population segregating for phenotypic traits associated with drought tolerance. Phenotypic data was collected from a field trial and a two-year greenhouse study, which included relative water content (RWC), chlorophyll content (CHC), leaf firing (LF), leaf wilting (LW), green cover (GC) and normalized difference vegetative index (NDVI). Significant phenotypic variance was observed and a total of 70 QTL were detected for all traits. A genomic region on linkage group R6 simultaneously harbored QTL for RWC, LF and LW in different experiments. In addition, overlapping QTL for GC, LF, LW and NDVI were found on linkage groups R1, R5, R7 and S2. Sequence alignment analysis revealed several drought response genes within these regions. The QTL identified in this study have potential to be used in the future to identify genes associated with drought tolerance and for use in marker-assisted breeding.

We measure the charge sensitivity, Se, of a single electron transistor (SET) in the presence of strong (Vrf ∼ e/Cg) spurious radio frequency (rf) signals at frequencies up to 50 MHz, where Cg is the gate capacitance. Although Se appears to degrade when exposed to Vrf, we find that broadening of conduction peaks is largely due to the measurement technique and show that Se is maintained even with strong Vrf present. We show cancellation of a known Vrf signal at 1 MHz, demonstrating that a stable bias point in the presence of rf signals is possible.