Understanding uncertainty in temperature effects on vector-borne disease: A Bayesian approach

Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases, like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number $R_0$. However, understanding the mechanisms linking $R_0$ and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this we show how a Bayesian approach can help identify critical uncertainties in components of $R_0$ and how this uncertainty is propagated into the estimate of $R_0$. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15-25$^\circ$ C; fecundity across all temperatures, but especially $\sim$25-32$^\circ$ C; mortality from 20-30$^\circ$ C; parasite development rate at $\sim$15-16$^\circ$C and again at $\sim$33-35$^\circ$C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of $R_0$. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.Comment: 27 pages, including 1 table and 3 figure

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

The bear in Eurasian plant names: Motivations and models

Ethnolinguistic studies are important for understanding an ethnic group's ideas on the world, expressed in its language. Comparing corresponding aspects of such knowledge might help clarify problems of origin for certain concepts and words, e.g. whether they form common heritage, have an independent origin, are borrowings, or calques. The current study was conducted on the material in Slavonic, Baltic, Germanic, Romance, Finno-Ugrian, Turkic and Albanian languages. The bear was chosen as being a large, dangerous animal, important in traditional culture, whose name is widely reflected in folk plant names. The phytonyms for comparison were mostly obtained from dictionaries and other publications, and supplemented with data from databases, the co-authors' field data, and archival sources (dialect and folklore materials). More than 1200 phytonym use records (combinations of a local name and a meaning) for 364 plant and fungal taxa were recorded to help find out the reasoning behind bear-nomination in various languages, as well as differences and similarities between the patterns among them. Among the most common taxa with bear-related phytonyms were Arctostaphylos uva-ursi (L.) Spreng., Heracleum sphondylium L., Acanthus mollis L., and Allium ursinum L., with Latin loan translation contributing a high proportion of the phytonyms. Some plants have many and various bear-related phytonyms, while others have only one or two bear names. Features like form and/or surface generated the richest pool of names, while such features as colour seemed to provoke rather few associations with bears. The unevenness of bear phytonyms in the chosen languages was not related to the size of the language nor the present occurence of the Brown Bear in the region. However, this may, at least to certain extent, be related to the amount of the historical ethnolinguistic research done on the selected languages

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

The Green Premium : a study of the pricing of green bonds on the Swedish bond market

Issuing environmentally aligned green bonds has become an increasingly popular way to raise capital for green investments during the last decade. This thesis explores potential pricing differences between green and conventional bonds, known as the green premium, on the Swedish secondary bond market. Prior green bond research is inconclusive regarding the direction, size and even existence of such a premium. By creating a sample of 50 matched pairs of green and conventional bonds, we show an average positive green premium of 10 bps on the Swedish market, indicating that Swedish green bonds trade at higher yields than their conventional counterparts. We also study whether the size of the green premium is affected by credit ratings and third-party green certification but find no evidence of such effects. Overall, the results from this thesis add to current green bond research by showing a positive green premium, but the lack of shown effects from credit ratings and green certification indicate that further study is needed to fully understand the pricing mechanisms of green bonds.

Knowledge sharing when telework is involuntary : A quantitative cross-sectional study of how teleworker knowledge sharing is affected by the employees' willingness to telework

På grund av covid-19 har många organisationer tvingats implementera distansarbete i syfte att minska smittspridningen. Givet den snabba omställningen till distansarbete och de utmaningar som arbetssättet har på kunskapsdelning, ämnar denna kvantitativa tvärsnittsstudie undersöka hur viljan att arbeta på distans påverkar kunskapsdelning hos distansarbetande anställda. Kunskapsdelning operationaliseras genom de relationella faktorerna förtroende, sociala relationer samt organisatorisk förpliktelse. Studiens analysmodell baseras på fyra hypoteser som formulerats utifrån tidigare forskning. Respondenter samlades in via en webbenkät där den insamlade datan analyserades genom hierarkisk linjär regression. Resultaten från 170 distansarbetande anställda visade att viljan att arbeta på distans modererar effekten av förtroende på kunskapsdelning. För individer som har lågt förtroende till sina kollegor agerar viljan att arbeta på distans som en facilitator för kunskapsdelning. Därutöver bör organisationer ta hänsyn till de anställdas vilja att arbeta på distans eftersom resultaten från studien indikerar att viljan påverkar kunskapsdelning på den digitala arbetsplatsen.Due to the COVID-19 pandemic many organizations have been forced to implement telework in an effort to reduce the spread of the virus. Following the quick transition to telework and challenges associated with organizational knowledge sharing, this quantitative cross-sectional study aims to investigate how the willingness to telework impacts knowledge sharing. Knowledge sharing is operationalized through the relational factors trust, interpersonal bonds and organizational commitment. The study’s model of analysis is based on four hypotheses formulated from earlier research within the field. Data was gathered through an online survey where the collected data was analyzed through hierarchical linear regression. Results from 170 teleworkers show that the impact of trust on knowledge sharing is moderated by willingness to telework. For individuals with low levels of trust in their coworkers the willingness to teleworks acts as a facilitator for knowledge sharing. An implication for organizations is that employees’ willingness to telework needs to be considered as our results indicate that it affects knowledge sharing in a digital work environment

Knowledge sharing when telework is involuntary : A quantitative cross-sectional study of how teleworker knowledge sharing is affected by the employees' willingness to telework

På grund av covid-19 har många organisationer tvingats implementera distansarbete i syfte att minska smittspridningen. Givet den snabba omställningen till distansarbete och de utmaningar som arbetssättet har på kunskapsdelning, ämnar denna kvantitativa tvärsnittsstudie undersöka hur viljan att arbeta på distans påverkar kunskapsdelning hos distansarbetande anställda. Kunskapsdelning operationaliseras genom de relationella faktorerna förtroende, sociala relationer samt organisatorisk förpliktelse. Studiens analysmodell baseras på fyra hypoteser som formulerats utifrån tidigare forskning. Respondenter samlades in via en webbenkät där den insamlade datan analyserades genom hierarkisk linjär regression. Resultaten från 170 distansarbetande anställda visade att viljan att arbeta på distans modererar effekten av förtroende på kunskapsdelning. För individer som har lågt förtroende till sina kollegor agerar viljan att arbeta på distans som en facilitator för kunskapsdelning. Därutöver bör organisationer ta hänsyn till de anställdas vilja att arbeta på distans eftersom resultaten från studien indikerar att viljan påverkar kunskapsdelning på den digitala arbetsplatsen.Due to the COVID-19 pandemic many organizations have been forced to implement telework in an effort to reduce the spread of the virus. Following the quick transition to telework and challenges associated with organizational knowledge sharing, this quantitative cross-sectional study aims to investigate how the willingness to telework impacts knowledge sharing. Knowledge sharing is operationalized through the relational factors trust, interpersonal bonds and organizational commitment. The study’s model of analysis is based on four hypotheses formulated from earlier research within the field. Data was gathered through an online survey where the collected data was analyzed through hierarchical linear regression. Results from 170 teleworkers show that the impact of trust on knowledge sharing is moderated by willingness to telework. For individuals with low levels of trust in their coworkers the willingness to teleworks acts as a facilitator for knowledge sharing. An implication for organizations is that employees’ willingness to telework needs to be considered as our results indicate that it affects knowledge sharing in a digital work environment

The Green Premium : a study of the pricing of green bonds on the Swedish bond market

Issuing environmentally aligned green bonds has become an increasingly popular way to raise capital for green investments during the last decade. This thesis explores potential pricing differences between green and conventional bonds, known as the green premium, on the Swedish secondary bond market. Prior green bond research is inconclusive regarding the direction, size and even existence of such a premium. By creating a sample of 50 matched pairs of green and conventional bonds, we show an average positive green premium of 10 bps on the Swedish market, indicating that Swedish green bonds trade at higher yields than their conventional counterparts. We also study whether the size of the green premium is affected by credit ratings and third-party green certification but find no evidence of such effects. Overall, the results from this thesis add to current green bond research by showing a positive green premium, but the lack of shown effects from credit ratings and green certification indicate that further study is needed to fully understand the pricing mechanisms of green bonds.

Feasibility Study of Carbon Dioxide Plume Geothermal Systems in Germany−Utilising Carbon Dioxide for Energy

To manage greenhouse gas emissions, directives on renewable energy usage have been developed by the European Commission with the objective to reduce overall emissions by 40% by 2030 which presents a significant potential for renewable energy sources. At the same time, it is a challenge for these energy technologies which can only be solved by integrated solutions. Carbon capture and storage combined with geothermal energy could serve as a novel approach to reduce CO2 emissions and at the same time facilitate some of the negative impacts associated with fossil fuel-based power plants. This study focuses on the technical and economic feasibility of combining these technologies based on a published model, data and market research. In the European Union, Germany is the most energy intensive country, and it also has an untapped potential for geothermal energy in the northern as well as the western regions. The CO2 plume geothermal system using supercritical carbon dioxide as the working fluid can be utilized in natural high porosity (10–20%) and permeability (2.5 × 10−14–8.4 × 10−16 m2) reservoirs with temperatures as low as 65.8 ◦C. The feasibility of the project was assessed based on market conditions and policy support in Germany as well as the geologic background of sandstone reservoirs near industrialized areas (Dortmund, Frankfurt) and the possibility of carbon capture integration and CO2 injection. The levelized cost of electricity for a base case results in € 0.060/kWh. Optimal system type was assessed in a system optimization model. The project has a potential to supply 6600/12000 households with clean energy (electricity/heat) and sequester carbon dioxide at the same time. A trading scheme for carbon dioxide further expands potential opportunities

Intelligent image-based in situ single-cell isolation

Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample