38th annual New England Intercollegiate Geological Excursion: Mount Washington, New Hampshire, October 5 and 6, 1946

Trip A: Percy Quadrangle: Trip B: Gorham and Mt. Washington quadrangles; Trip C: Northern part of Mt. Washington quadrangle; Trip D: Lower northern slopes of Mt. Adams and Mt. Madison; Trip E: Emergency trip

Understanding pregnant smokers’ adherence to nicotine replacement therapy during a quit attempt: a qualitative study

Background: Pregnant smokers may be offered nicotine replacement therapy (NRT) alongside behavioral support to assist with a quit attempt. Yet trials of NRT have found adherence to be low among pregnant women, and this has made it difficult to determine the efficacy of NRT. The aim of this study is to understand the experience of pregnant women who use NRT but discontinue this early or do not use the medication as recommended. Methods: Semi-structured telephone interviews were conducted with 14 pregnant smokers who had recently been prescribed NRT, but self-reported poor NRT adherence or discontinuing treatment prematurely. Data were transcribed and analyzed using inductive thematic analysis. Results: There were four main themes identified; expectations of NRT, experience of using NRT, safety concerns and experience of using e-cigarettes. Some women intentionally used NRT to substitute a proportion of their cigarette intake and smoked alongside. Most women smoked while using NRT. Women who underutilized NRT did so as they experienced side effects, or were concerned that using NRT instead of smoking could actually increase their nicotine exposure and potential for increased nicotine dependence or fetal harm. Most women spoke about the use of e-cigarettes as a smoking cessation method but only a few had actually experienced using them during pregnancy. Conclusion: Many women underused NRT but simultaneously smoked. Challenging negative perceptions about NRT and educating women further about the risks of smoking may encourage them to use NRT products as recommended.Implications: These findings add to the research surrounding the efficacy of NRT during pregnancy by providing insight into how pregnant women use NRT during a quit attempt and how this may influence adherence. It may assist health professionals to support pregnant smokers by increasing their understanding about the differing ways in which women use NRT and help them address concerns women may have about the safety of NRT

Lmx1b is required for the glutamatergic fates of a subset of spinal cord neurons

Background: Alterations in neurotransmitter phenotypes of specific neurons can cause imbalances in excitation and inhibition in the central nervous system (CNS), leading to diseases. Therefore, the correct specification and maintenance of neurotransmitter phenotypes is vital. As with other neuronal properties, neurotransmitter phenotypes are often specified and maintained by particular transcription factors. However, the specific molecular mechanisms and transcription factors that regulate neurotransmitter phenotypes remain largely unknown. Methods: In this paper we use single mutant, double mutant and transgenic zebrafish embryos to elucidate the functions of Lmx1ba and Lmx1bb in the regulation of spinal cord interneuron neurotransmitter phenotypes. Results: We demonstrate that lmx1ba and lmx1bb are both expressed in zebrafish spinal cord and that lmx1bb is expressed by both V0v cells and dI5 cells. Our functional analyses demonstrate that these transcription factors are not required for neurotransmitter fate specification at early stages of development, but that in embryos with at least two lmx1ba and/or lmx1bb mutant alleles there is a reduced number of excitatory (glutamatergic) spinal interneurons at later stages of development. In contrast, there is no change in the numbers of V0v or dI5 cells. These data suggest that lmx1b-expressing spinal neurons still form normally, but at least a subset of them lose, or do not form, their normal excitatory fates. As the reduction in glutamatergic cells is only seen at later stages of development, Lmx1b is probably required either for the maintenance of glutamatergic fates or to specify glutamatergic phenotypes of a subset of later forming neurons. Using double labeling experiments, we also show that at least some of the cells that lose their normal glutamatergic phenotype are V0v cells. Finally, we also establish that Evx1 and Evx2, two transcription factors that are required for V0v cells to acquire their excitatory neurotransmitter phenotype, are also required for lmx1ba and lmx1bb expression in these cells, suggesting that Lmx1ba and Lmx1bb act downstream of Evx1 and Evx2 in V0v cells. Conclusions: Lmx1ba and Lmx1bb function at least partially redundantly in the spinal cord and three functional lmx1b alleles are required in zebrafish for correct numbers of excitatory spinal interneurons at later developmental stages. Taken together, our data significantly enhance our understanding of how spinal cord neurotransmitter fates are regulated

Climate change adaptation and cross-sectoral policy coherence in southern Africa

To be effective, climate change adaptation needs to be mainstreamed across multiple sectors and greater policy coherence is essential. Using the cases of Malawi, Tanzania and Zambia, this paper investigates the extent of coherence in national policies across the water and agriculture sectors and to climate change adaptation goals outlined in national development plans. A two-pronged qualitative approach is applied using Qualitative Document Analysis of relevant policies and plans, combined with expert interviews from non-government actors in each country. Findings show that sector policies have differing degrees of coherence on climate change adaptation, currently being strongest in Zambia and weakest in Tanzania. We also identify that sectoral policies remain more coherent in addressing immediate-term disaster management issues of floods and droughts rather than longer-term strategies for climate adaptation. Coherence between sector and climate policies and strategies is strongest when the latter has been more recently developed. However to date, this has largely been achieved by repackaging of existing sectoral policy statements into climate policies drafted by external consultants to meet international reporting needs and not by the establishment of new connections between national sectoral planning processes. For more effective mainstreaming of climate change adaptation, governments need to actively embrace longer-term cross-sectoral planning through cross-Ministerial structures, such as initiated through Zambia’s Interim Climate Change Secretariat, to foster greater policy coherence and integrated adaptation planning

Views on and experiences of electronic cigarettes: a qualitative study of women who are pregnant or have recently given birth.

Background Electronic cigarettes (ECs) are increasingly used for reducing or stopping smoking, with some studies showing positive outcomes. However, little is known about views on ECs during pregnancy or postpartum and previous studies have nearly all been conducted in the US and have methodological limitations, such as not distinguishing between smokers and ex/non-smokers. A greater understanding of this topic will help to inform both clinicians and EC interventions. We elicited views and experiences of ECs among UK pregnant or recently pregnant women. Methods We conducted semi-structured telephone interviews, using topic guides, with pregnant or recently pregnant women, who were current or recent ex-smokers. To ensure broad views of ECs were obtained, recruitment was from several geographical locations and via various avenues of recruitment. This included stop smoking services, antenatal and health visitor clinics, a pregnancy website and an informal network. Participants were 15 pregnant and 15 postpartum women, including nine current EC users, 11 ex-users, and 10 never-users. Five women who were interviewed in pregnancy were later interviewed in postpartum to explore if their views had changed. Audio data was transcribed verbatim and framework analysis was applied. Results Five main themes emerged: motivations for use (e.g., for stopping or reducing smoking), social stigma (e.g., avoiding use in public, preferring ‘discrete’ NRT), using the EC (e.g., mostly used at home); consumer aspects (e.g., limited advice available), and harm perceptions (e.g., viewed as less harmful than smoking; concerns about safety and addiction). Conclusions ECs were viewed positively by some pregnant and postpartum women and seen as less harmful than smoking and useful as aids for reducing and stopping smoking. However, due to perceived social stigma, some women feel uncomfortable using ECs in public, especially during pregnancy, and had concerns about safety and nicotine dependence. Health professionals and designers of EC interventions need to provide women with up-to-date and consistent information and advice about safety and dependence, as well as considering the influence of social stigma

Plio‐Quaternary exhumation history of the central Nepalese Himalaya: 2. Thermokinematic and thermochronometer age prediction model

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95647/1/tect1875.pd

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages