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Ecosystem modeling, a pillar of the systems ecology paradigm (SEP), addresses questions such as, how much carbon and nitrogen are cycled within ecological sites, landscapes, or indeed the earth system? Or how are human activities modifying these flows? Modeling, when coupled with field and laboratory studies, represents the essence of the SEP in that they embody accumulated knowledge and generate hypotheses to test understanding of ecosystem processes and behavior. Initially, ecosystem models were primarily used to improve our understanding about how biophysical aspects of ecosystems operate. However, current ecosystem models are widely used to make accurate predictions about how large-scale phenomena such as climate change and management practices impact ecosystem dynamics and assess potential effects of these changes on economic activity and policy making. In sum, ecosystem models embedded in the SEP remain our best mechanism to integrate diverse types of knowledge regarding how the earth system functions and to make quantitative predictions that can be confronted with observations of reality. Modeling efforts discussed are the Century ecosystem model, DayCent ecosystem model, Grassland Ecosystem Model ELM, food web models, Savanna model, agent-based and coupled systems modeling, and Bayesian modeling.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding of Earth's sensitivity to carbon dioxide, finds that permafrost thaw could release more carbon emissions than expected and that the uptake of carbon in tropical ecosystems is weakening. Adverse impacts on human society include increasing water shortages and impacts on mental health. Options for solutions emerge from rethinking economic models, rights-based litigation, strengthened governance systems and a new social contract. The disruption caused by COVID-19 could be seized as an opportunity for positive change, directing economic stimulus towards sustainable investments.
A synthesis is made of ten fields within climate science where there have been significant advances since mid-2019, through an expert elicitation process with broad disciplinary scope. Findings include: (1) a better understanding of equilibrium climate sensitivity; (2) abrupt thaw as an accelerator of carbon release from permafrost; (3) changes to global and regional land carbon sinks; (4) impacts of climate change on water crises, including equity perspectives; (5) adverse effects on mental health from climate change; (6) immediate effects on climate of the COVID-19 pandemic and requirements for recovery packages to deliver on the Paris Agreement; (7) suggested long-term changes to governance and a social contract to address climate change, learning from the current pandemic, (8) updated positive cost–benefit ratio and new perspectives on the potential for green growth in the short- and long-term perspective; (9) urban electrification as a strategy to move towards low-carbon energy systems and (10) rights-based litigation as an increasingly important method to address climate change, with recent clarifications on the legal standing and representation of future generations.
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Stronger permafrost thaw, COVID-19 effects and growing mental health impacts among highlights of latest climate science.
Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.
Unit cohesion may protect service member mental health by mitigating effects of combat exposure; however, questions remain about the origins of potential stress-buffering effects. We examined buffering effects associated with two forms of unit cohesion (peer-oriented horizontal cohesion and subordinate-leader vertical cohesion) defined as either individual-level or aggregated unit-level variables.
Longitudinal survey data from US Army soldiers who deployed to Afghanistan in 2012 were analyzed using mixed-effects regression. Models evaluated individual- and unit-level interaction effects of combat exposure and cohesion during deployment on symptoms of post-traumatic stress disorder (PTSD), depression, and suicidal ideation reported at 3 months post-deployment (model n's = 6684 to 6826). Given the small effective sample size (k = 89), the significance of unit-level interactions was evaluated at a 90% confidence level.
At the individual-level, buffering effects of horizontal cohesion were found for PTSD symptoms [B = −0.11, 95% CI (−0.18 to −0.04), p < 0.01] and depressive symptoms [B = −0.06, 95% CI (−0.10 to −0.01), p < 0.05]; while a buffering effect of vertical cohesion was observed for PTSD symptoms only [B = −0.03, 95% CI (−0.06 to −0.0001), p < 0.05]. At the unit-level, buffering effects of horizontal (but not vertical) cohesion were observed for PTSD symptoms [B = −0.91, 90% CI (−1.70 to −0.11), p = 0.06], depressive symptoms [B = −0.83, 90% CI (−1.24 to −0.41), p < 0.01], and suicidal ideation [B = −0.32, 90% CI (−0.62 to −0.01), p = 0.08].
Policies and interventions that enhance horizontal cohesion may protect combat-exposed units against post-deployment mental health problems. Efforts to support individual soldiers who report low levels of horizontal or vertical cohesion may also yield mental health benefits.
Glyphosate-resistant (GR) canola is a widely grown crop across western Canada and has quickly become a prolific volunteer weed. Glyphosate-resistant soybean is rapidly gaining acreage in western Canada. Thus, there is a need to evaluate herbicide options to manage volunteer GR canola in GR soybean crops. We conducted an experiment to evaluate the efficacy of various PRE and POST herbicides applied sequentially to volunteer GR canola and to evaluate soybean injury caused by these herbicides. Trials were conducted across Saskatchewan and Manitoba in 2014 and 2015. All treatments provided a range of suppression (>70%) to control (>80%) of volunteer canola. All treatments with the exception of the glyphosate-treated control reduced aboveground canola biomass by an average of 96%. As well, canola seed contamination was reduced from 36% to less than 5% when a PRE and POST herbicide were both used. Moreover, all combinations of herbicides used had excellent crop safety (<10%). All PRE and POST herbicide combinations provided better control of volunteer canola compared with the glyphosate-only control, but tribenuron followed by bentazon and tribenuron followed by imazamox plus bentazon provided solutions that were low cost, currently available (registered in western Canada), and had the potential to minimize development of herbicide resistance in other weeds.
Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy.
Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions.
One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit.
If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term.
The science of studying diamond inclusions for understanding Earth history has developed significantly over the past decades, with new instrumentation and techniques applied to diamond sample archives revealing the stories contained within diamond inclusions. This chapter reviews what diamonds can tell us about the deep carbon cycle over the course of Earth’s history. It reviews how the geochemistry of diamonds and their inclusions inform us about the deep carbon cycle, the origin of the diamonds in Earth’s mantle, and the evolution of diamonds through time.
In recent years, soybean acreage has increased significantly in western Canada. One of the challenges associated with growing soybean in western Canada is the control of volunteer glyphosate-resistant (GR) canola, because most soybean cultivars are also glyphosate resistant. The objective of this research was to determine the impact of soybean seeding rate and planting date on competition with volunteer canola. We also attempted to determine how high seeding rate could be raised while still being economically feasible for producers. Soybean was seeded at five different seeding rates (targeted 10, 20, 40, 80, and 160 plants m−2) and three planting dates (targeted mid-May, late May, and early June) at four sites across western Canada in 2014 and 2015. Soybean yield consistently increased with higher seeding rates, whereas volunteer canola biomass decreased. Planting date generally produced variable results across site-years. An economic analysis determined that the optimal rate was 40 to 60 plants m−2, depending on market price, and the optimal planting date range was from May 20 to June 1.
The sternocleidomastoid can be used as a pedicled flap in head and neck reconstruction. It has previously been associated with high complication rates, likely due in part to the variable nature of its blood supply.
To provide clinicians with an up-to-date review of clinical outcomes of sternocleidomastoid flap surgery in head and neck reconstruction, integrated with a review of vascular anatomical studies of the sternocleidomastoid.
A literature search of the Medline and Web of Science databases was conducted. Complications were analysed for each study. The trend in success rates was analysed by date of the study.
Reported complication rates have improved over time. The preservation of two vascular pedicles rather than one may have contributed to improved outcomes.
The sternocleidomastoid flap is a versatile option for patients where prolonged free flap surgery is inappropriate. Modern vascular imaging techniques could optimise pre-operative planning.
Apolipoprotein E (APOE) E4 is the main genetic risk factor for Alzheimer’s disease (AD). Due to the consistent association, there is interest as to whether E4 influences the risk of other neurodegenerative diseases. Further, there is a constant search for other genetic biomarkers contributing to these phenotypes, such as microtubule-associated protein tau (MAPT) haplotypes. Here, participants from the Ontario Neurodegenerative Disease Research Initiative were genotyped to investigate whether the APOE E4 allele or MAPT H1 haplotype are associated with five neurodegenerative diseases: (1) AD and mild cognitive impairment (MCI), (2) amyotrophic lateral sclerosis, (3) frontotemporal dementia (FTD), (4) Parkinson’s disease, and (5) vascular cognitive impairment.
Genotypes were defined for their respective APOE allele and MAPT haplotype calls for each participant, and logistic regression analyses were performed to identify the associations with the presentations of neurodegenerative diseases.
Our work confirmed the association of the E4 allele with a dose-dependent increased presentation of AD, and an association between the E4 allele alone and MCI; however, the other four diseases were not associated with E4. Further, the APOE E2 allele was associated with decreased presentation of both AD and MCI. No associations were identified between MAPT haplotype and the neurodegenerative disease cohorts; but following subtyping of the FTD cohort, the H1 haplotype was significantly associated with progressive supranuclear palsy.
This is the first study to concurrently analyze the association of APOE isoforms and MAPT haplotypes with five neurodegenerative diseases using consistent enrollment criteria and broad phenotypic analysis.
Clinical Enterobacteriacae isolates with a colistin minimum inhibitory concentration (MIC) ≥4 mg/L from a United States hospital were screened for the mcr-1 gene using real-time polymerase chain reaction (RT-PCR) and confirmed by whole-genome sequencing. Four colistin-resistant Escherichia coli isolates contained mcr-1. Two isolates belonged to the same sequence type (ST-632). All subjects had prior international travel and antimicrobial exposure.
Medical procedures and patient care activities may facilitate environmental dissemination of healthcare-associated pathogens such as methicillin-resistant Staphylococcus aureus (MRSA).
Observational cohort study of MRSA-colonized patients to determine the frequency of and risk factors for environmental shedding of MRSA during procedures and care activities in carriers with positive nares and/or wound cultures. Bivariate analyses were performed to identify factors associated with environmental shedding.
A Veterans Affairs hospital.
This study included 75 patients in contact precautions for MRSA colonization or infection.
Of 75 patients in contact precautions for MRSA, 55 (73%) had MRSA in nares and/or wounds and 25 (33%) had positive skin cultures. For the 52 patients with MRSA in nares and/or wounds and at least 1 observed procedure, environmental shedding of MRSA occurred more frequently during procedures and care activities than in the absence of a procedure (59 of 138, 43% vs 8 of 83, 10%; P < .001). During procedures, increased shedding occurred ≤0.9 m versus >0.9 m from the patient (52 of 138, 38% vs 25 of 138, 18%; P = .0004). Contamination occurred frequently on surfaces touched by personnel (12 of 38, 32%) and on portable equipment used for procedures (25 of 101, 25%). By bivariate analysis, the presence of a wound with MRSA was associated with shedding (17 of 29, 59% versus 6 of 23, 26%; P = .04).
Environmental shedding of MRSA occurs frequently during medical procedures and patient care activities. There is a need for effective strategies to disinfect surfaces and equipment after procedures.
Herbicide active ingredients, formulation type, ambient temperature, and humidity can influence volatility. A method was developed using volatility chambers to compare relative volatility of different synthetic auxin herbicide formulations in controlled environments. 2,4-D or dicamba acid vapors emanating after application were captured in air-sampling tubes at 24, 48, 72, and 96 h after herbicide application. The 2,4-D or dicamba was extracted from sample tubes and quantified using liquid chromatography and tandem mass spectrometry. Volatility from 2,4-D dimethylamine (DMA) was determined to be greater than that of 2,4-D choline in chambers where temperatures were held at 30 or 40 C and relative humidity (RH) was 20% or 50%. Air concentration of 2,4-D DMA was 0.399 µg m−3 at 40 C and 20% RH compared with 0.005 µg m−3 for 2,4-D choline at the same temperature and humidity at 24 h after application. Volatility from 2,4-D DMA and 2,4-D choline increased as temperature increased from 30 to 40 C. However, volatility from 2,4-D choline was lower than observed from 2,4-D DMA. Volatility from 2,4-D choline at 40 C increased from 0.00458 to 0.0263 µg m−3 and from 0.00341 to 0.025 µg m−3 when humidity increased from 20% to 50% at 72 and 96 h after treatment, respectively, whereas, volatility from 2,4-D DMA tended to be higher at 20% RH compared with 50% RH. Air concentration of dicamba diglycolamine was similar at all time points when measured at 40 C and 20% RH. By 96 h after treatment, there was a trend for lower air concentration of dicamba compared with earlier timings. This method using volatility chambers provided good repeatability with low variability across replications, experiments, and herbicides.
Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits.
Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics.
Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58).
A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.
An internationally approved and globally used classification scheme for the diagnosis of CHD has long been sought. The International Paediatric and Congenital Cardiac Code (IPCCC), which was produced and has been maintained by the International Society for Nomenclature of Paediatric and Congenital Heart Disease (the International Nomenclature Society), is used widely, but has spawned many “short list” versions that differ in content depending on the user. Thus, efforts to have a uniform identification of patients with CHD using a single up-to-date and coordinated nomenclature system continue to be thwarted, even if a common nomenclature has been used as a basis for composing various “short lists”. In an attempt to solve this problem, the International Nomenclature Society has linked its efforts with those of the World Health Organization to obtain a globally accepted nomenclature tree for CHD within the 11th iteration of the International Classification of Diseases (ICD-11). The International Nomenclature Society has submitted a hierarchical nomenclature tree for CHD to the World Health Organization that is expected to serve increasingly as the “short list” for all communities interested in coding for congenital cardiology. This article reviews the history of the International Classification of Diseases and of the IPCCC, and outlines the process used in developing the ICD-11 congenital cardiac disease diagnostic list and the definitions for each term on the list. An overview of the content of the congenital heart anomaly section of the Foundation Component of ICD-11, published herein in its entirety, is also included. Future plans for the International Nomenclature Society include linking again with the World Health Organization to tackle procedural nomenclature as it relates to cardiac malformations. By doing so, the Society will continue its role in standardising nomenclature for CHD across the globe, thereby promoting research and better outcomes for fetuses, children, and adults with congenital heart anomalies.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
Over the past 30 years, the number of US doctoral anthropology graduates has increased by about 70%, but there has not been a corresponding increase in the availability of new faculty positions. Consequently, doctoral degree-holding archaeologists face more competition than ever before when applying for faculty positions. Here we examine where US and Canadian anthropological archaeology faculty originate and where they ultimately end up teaching. Using data derived from the 2014–2015 AnthroGuide, we rank doctoral programs whose graduates in archaeology have been most successful in the academic job market; identify long-term and ongoing trends in doctoral programs; and discuss gender division in academic archaeology in the US and Canada. We conclude that success in obtaining a faculty position upon graduation is predicated in large part on where one attends graduate school.