Teacher and Student Well-being in the Covid-19 pandemic - Full report

This project sought to understand the perspectives of teachers and students in the lower North Island of Aotearoa New Zealand at the time of the first COVID-19 pandemic lockdown in March 2020 and during the following several months. Thirteen teachers from seven schools in the Manawatū-Horowhenua and Greater Wellington area and seven focus groups of Year 4 to 8 students from four of the schools participated in this project. This final report includes the findings from teachers and students’ perspectives of the affordances and challenges of lockdown and subsequent return to school, and their perspectives on helpful strategies in the event of similar situations given the unpredictable times. Analysis of teachers’ perspectives highlighted three interrelated themes –Stepping up Ngāwhiringatanga; Building Resilience and Reflecting and Recalibrating. The lockdown provided teachers time for introspection and have some time for their own personal well-being and growth. Although the challenge of adapting to online teaching sessions was stressful, the increased knowledge of the impact of COVID-19 on families and communities, had a profound impact on ongoing pedagogy of teachers. Teachers were resilient to the challenges and supported the resilience and well-being of students both during lockdown and on their return to school. They were supported by their school systems to ease pressure on academic learning and focus on holistic well-being of students such as spending quality time with their families. The lockdown highlighted the importance of work life balance, with teachers experiencing the benefits of having the time and space to focus on their personal well-being, which is critical for the well- being of their students, enabling them to support their students becoming resilient in the face of adversities caused by the ongoing presence of the pandemic. The students’ on the other hand while feeling isolated from their peers and anxious about the effects of the virus on their near and dear ones, appreciated the quality time that they could spend with their families and pets, and more importantly the flexibility that lockdown offered in terms of their learning. The key inter-related themes from their perspectives were: worry about safety and changes; restrictions and isolation; freedom and autonomy; friendship and connection; and quality family time.fals

Correcting the Bias of Empirical Frequency Parameter Estimators in Codon Models

Markov models of codon substitution are powerful inferential tools for studying biological processes such as natural selection and preferences in amino acid substitution. The equilibrium character distributions of these models are almost always estimated using nucleotide frequencies observed in a sequence alignment, primarily as a matter of historical convention. In this note, we demonstrate that a popular class of such estimators are biased, and that this bias has an adverse effect on goodness of fit and estimates of substitution rates. We propose a “corrected” empirical estimator that begins with observed nucleotide counts, but accounts for the nucleotide composition of stop codons. We show via simulation that the corrected estimates outperform the de facto standard estimates not just by providing better estimates of the frequencies themselves, but also by leading to improved estimation of other parameters in the evolutionary models. On a curated collection of sequence alignments, our estimators show a significant improvement in goodness of fit compared to the approach. Maximum likelihood estimation of the frequency parameters appears to be warranted in many cases, albeit at a greater computational cost. Our results demonstrate that there is little justification, either statistical or computational, for continued use of the -style estimators

HIV-Specific Probabilistic Models of Protein Evolution

Comparative sequence analyses, including such fundamental bioinformatics techniques as similarity searching, sequence alignment and phylogenetic inference, have become a mainstay for researchers studying type 1 Human Immunodeficiency Virus (HIV-1) genome structure and evolution. Implicit in comparative analyses is an underlying model of evolution, and the chosen model can significantly affect the results. In general, evolutionary models describe the probabilities of replacing one amino acid character with another over a period of time. Most widely used evolutionary models for protein sequences have been derived from curated alignments of hundreds of proteins, usually based on mammalian genomes. It is unclear to what extent these empirical models are generalizable to a very different organism, such as HIV-1–the most extensively sequenced organism in existence. We developed a maximum likelihood model fitting procedure to a collection of HIV-1 alignments sampled from different viral genes, and inferred two empirical substitution models, suitable for describing between-and within-host evolution. Our procedure pools the information from multiple sequence alignments, and provided software implementation can be run efficiently in parallel on a computer cluster. We describe how the inferred substitution models can be used to generate scoring matrices suitable for alignment and similarity searches. Our models had a consistently superior fit relative to the best existing models and to parameter-rich data-driven models when benchmarked on independent HIV-1 alignments, demonstrating evolutionary biases in amino-acid substitution that are unique to HIV, and that are not captured by the existing models. The scoring matrices derived from the models showed a marked difference from common amino-acid scoring matrices. The use of an appropriate evolutionary model recovered a known viral transmission history, whereas a poorly chosen model introduced phylogenetic error. We argue that our model derivation procedure is immediately applicable to other organisms with extensive sequence data available, such as Hepatitis C and Influenza A viruses

Modeling HIV-1 Drug Resistance as Episodic Directional Selection

The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance

CodonTest: Modeling Amino Acid Substitution Preferences in Coding Sequences

Codon models of evolution have facilitated the interpretation of selective forces operating on genomes. These models, however, assume a single rate of non-synonymous substitution irrespective of the nature of amino acids being exchanged. Recent developments have shown that models which allow for amino acid pairs to have independent rates of substitution offer improved fit over single rate models. However, these approaches have been limited by the necessity for large alignments in their estimation. An alternative approach is to assume that substitution rates between amino acid pairs can be subdivided into rate classes, dependent on the information content of the alignment. However, given the combinatorially large number of such models, an efficient model search strategy is needed. Here we develop a Genetic Algorithm (GA) method for the estimation of such models. A GA is used to assign amino acid substitution pairs to a series of rate classes, where is estimated from the alignment. Other parameters of the phylogenetic Markov model, including substitution rates, character frequencies and branch lengths are estimated using standard maximum likelihood optimization procedures. We apply the GA to empirical alignments and show improved model fit over existing models of codon evolution. Our results suggest that current models are poor approximations of protein evolution and thus gene and organism specific multi-rate models that incorporate amino acid substitution biases are preferred. We further anticipate that the clustering of amino acid substitution rates into classes will be biologically informative, such that genes with similar functions exhibit similar clustering, and hence this clustering will be useful for the evolutionary fingerprinting of genes

Blueprints for Green Communities: Climate change visioning and participatory landscape planning for resilient low-carbon communities

Emerging 3D visualization tools and future visioning methods offer new ways to make climate change impacts and potential responses explicit, and accelerate holistic solutions. Previous research at UBC’s Collaborative for Advanced Landscape Planning (CALP) and elsewhere confirms that 4D visioning processes using landscape visualizations of recognizable places under alternative future conditions can improve community engagement and awareness on complex environmental and planning issues (Tress and Tress, 2002; Sheppard and Meitner, 2005; Schroth, 2007). This paper examines a visioning process (Sheppard, 2008) that applies visualization and other landscape planning methods to explore high and low-carbon futures of the affluent, sub-urban hillside community of North Vancouver with climate change, and its surrounding scenic North Shore sub region of Metro Vancouver, BC, Canada

Calanus finmarchicus seasonal cycle and diapause in relation to gene expression, physiology, and endogenous clocks: Calanus finmarchicus seasonal rhythmicity

The copepod Calanus finmarchicus plays a crucial role in the north Atlantic food web. Its seasonal life cycle involves reproduction and development in surface waters before overwintering in diapause at depth. Although diapause has been studied for more than a century, the factors responsible for the initiation and termination of it are still unclear. Endogenous clocks have been identified as potent tools for photoperiod measurement and seasonal rhythmicity in many terrestrial species, but knowledge of these remains scarce in the marine realm. Focusing on the dominant CV copepodid stage, we sampled a population of C. finmarchicus from a Scottish sea loch to characterize population dynamics, several physiological parameters, and diel and seasonal expression rhythms of 35 genes representing different metabolic pathways, including the circadian clock machinery. This generated a detailed overview of the seasonal cycle of C. finmarchicus including the most extensive field dataset on circadian clock gene expression in a marine species to date. Gene expression patterns revealed distinct gene clusters upregulated at different phases of the copepod's seasonal cycle. While diel clock cycling was restricted to the active spring/summer phase, many clock genes exhibited the highest expression during diapause. Our results provide new insights into diapause on physiological and genetic levels. We suggest that photoperiod, in interaction with internal and external factors (lipid content, temperature, food availability) and the endogenous clock mechanism, plays an important role in the timing of diapause in C. finmarchicus

Circadian Clock Involvement in Zooplankton Diel Vertical Migration

Biological clocks are a ubiquitous ancient and adaptive mechanism enabling organisms to anticipate environmental cycles and to regulate behavioral and physiological processes accordingly [1]. Although terrestrial circadian clocks are well understood, knowledge of clocks in marine organisms is still very limited [2, 3, 4, 5]. This is particularly true for abundant species displaying large-scale rhythms like diel vertical migration (DVM) that contribute significantly to shaping their respective ecosystems [6]. Here we describe exogenous cycles and endogenous rhythms associated with DVM of the ecologically important and highly abundant planktic copepod Calanus finmarchicus. In the laboratory, C. finmarchicus shows circadian rhythms of DVM, metabolism, and most core circadian clock genes (clock, period1, period2, timeless, cryptochrome2, and clockwork orange). Most of these genes also cycle in animals assessed in the wild, though expression is less rhythmic at depth (50–140 m) relative to shallow-caught animals (0–50 m). Further, peak expressions of clock genes generally occurred at either sunset or sunrise, coinciding with peak migration times. Including one of the first field investigations of clock genes in a marine species [5, 7], this study couples clock gene measurements with laboratory and field data on DVM. While the mechanistic connection remains elusive, our results imply a high degree of causality between clock gene expression and one of the planet’s largest daily migrations of biomass. We thus suggest that circadian clocks increase zooplankton fitness by optimizing the temporal trade-off between feeding and predator avoidance, especially when environmental drivers are weak or absent [8]

Cardiopulmonary Mortality and Fine Particulate Air Pollution by Species and Source in a National U.S. Cohort

The purpose of this study was to estimate cardiopulmonary mortality associations for long-term exposure to PM2.5 species and sources (i.e., components) within the U.S. National Health Interview Survey cohort. Exposures were estimated through a chemical transport model for six species (i.e., elemental carbon (EC), primary organic aerosols (POA), secondary organic aerosols (SOA), sulfate (SO4), ammonium (NH4), nitrate (NO3)) and five sources of PM2.5 (i.e., vehicles, electricity-generating units (EGU), non-EGU industrial sources, biogenic sources (bio), “other” sources). In single-pollutant models, we found positive, significant (p < 0.05) mortality associations for all components, except POA. After adjusting for remaining PM2.5 (total PM2.5 minus component), we found significant mortality associations for EC (hazard ratio (HR) = 1.36; 95% CI [1.12, 1.64]), SOA (HR = 1.11; 95% CI [1.05, 1.17]), and vehicle sources (HR = 1.06; 95% CI [1.03, 1.10]). HRs for EC, SOA, and vehicle sources were significantly larger in comparison to those for remaining PM2.5 (per unit μg/m3). Our findings suggest that cardiopulmonary mortality associations vary by species and source, with evidence that EC, SOA, and vehicle sources are important contributors to the PM2.5 mortality relationship. With further validation, these findings could facilitate targeted pollution regulations that more efficiently reduce air pollution mortality.This publication was developed as part of the Center for Air, Climate, and Energy Solutions (CACES), which was supported under Assistance Agreement No. R835873 awarded by the U.S. Environmental Protection Agency. It has not been formally reviewed by EPA. The views expressed in this document are solely those of authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. We also acknowledge support from the European Union’s Horizon 2020 Research and Innovation project REMEDIA under grant agreement No 874753.Peer Reviewed"Article signat per 13 autors/es:" Zachari A. Pond, Carlos S. Hernandez, Peter J. Adams, Spyros N. Pandis, George R. Garcia, Allen L. Robinson, Julian D. Marshall, Richard Burnett, Ksakousti Skyllakou, Pablo Garcia Rivera, Eleni Karnezi, Carver J. Coleman, C. Arden Pope III"Postprint (author's final draft

Neutronic study on conversion of SAFARI-1 to LEU silicide fuel

This paper marks the initial study into the technical and economic feasibility of converting the SAFARI-1 reactor in South Africa to LEU silicide fuel. Several MTR assembly geometries and LEU uranium densities have been studied and compared with MEU and HEU fuels. Two factors of primary importance for conversion of SAFARI-1 to LEU fuel are the economy of the fuel cycle and the performance of the incore and excore irradiation positions