Autonomous Light Management in Flexible Photoelectrochromic Films Integrating High Performance Silicon Solar Microcells

Commercial smart window technologies for dynamic light and heat management in building and automotive environments traditionally rely on electrochromic (EC) materials powered by an external source. This design complicates building-scale installation requirements and substantially increases costs for applications in retrofit construction. Self-powered photoelectrochromic (PEC) windows are an intuitive alternative wherein a photovoltaic (PV) material is used to power the electrochromic device, which modulates the transmission of the incident solar flux. The PV component in this application must be sufficiently transparent and produce enough power to efficiently modulate the EC device transmission. Here, we propose Si solar microcells (μ-cells) that are i) small enough to be visually transparent to the eye, and ii) thin enough to enable flexible PEC devices. Visual transparency is achieved when Si μ-cells are arranged in high pitch (i.e. low-integration density) form factors while maintaining the advantages of a single-crystalline PV material (i.e., long lifetime and high performance). Additionally, the thin dimensions of these Si μ-cells enable fabrication on flexible substrates to realize these flexible PEC devices. The current work demonstrates this concept using WO₃ as the EC material and V₂O₅ as the ion storage layer, where each component is fabricated via sol-gel methods that afford improved prospects for scalability and tunability in comparison to thermal evaporation methods. The EC devices display fast switching times, as low as 8 seconds, with a modulation in transmission as high as 33%. Integration with two Si μ-cells in series (affording a 1.12 V output) demonstrates an integrated PEC module design with switching times of less than 3 minutes, and a modulation in transmission of 32% with an unprecedented EC:PV areal ratio

Assessing the impact of biofumigation and anaerobic soil disinfestation on soil biology, nitrogen cycling, crop establishment and yield in vegetable cropping systems

The need to develop alternative, environmentally benign pest management practices is one of the major challenges facing agriculture today. Novel alternatives to conventional fumigation practices in horticultural production systems can impact the chemical, biological and physical qualities of the soil in complex ways. Two such practices, biofumigation (BF) and anaerobic soil disinfestation (ASD) have demonstrated success in controlling certain soilborne pests, although results are often inconsistent. In some cases, negative impacts on crop establishment and yields have been observed following the application of these treatments. The objectives of this research were to: 1) investigate delayed seeding of crops as a method to reduce stand inhibition following BF, 2) monitor the impacts of BF and ASD on nitrogen availability, soil temperatures and microbial activity, and 3) evaluate the impact of BF and ASD on yields of warm season vegetable crops in southern Michigan. Experiments were conducted at the Southwest Michigan Research and Extension Center (Benton Harbor, MI) and the Horticulture Teaching and Research Center (Holt, MI) to address these objectives. In the first experiment, delayed seeding of a susceptible crop (Cucumis melo `Athena') 10-15 days after BF resulted in satisfactory emergence. Yields of melon decreased significantly as planting date was delayed, however, highlighting the importance of early seeding of long-season vegetable crops during the short growing season of Michigan. In the second experiment, combinations of spring-sown brassica cover crops and plastic mulching treatments were established to evaluate the potential for BF and ASD to improve yields of fresh market tomato (Lycoperison lycopersicum `Big Beef') and slicing cucumber (Cucumis sativus `Cortez') while also evaluating the impact on nitrogen availability, soil temperatures and microbial biomass. As a standard ASD control, molassess was added as a carbon source for ASD in 2013 and caused dramatic reductions in N availability for the early part of the growing season while visibly stunting tomato growth. Although cover crop treatments did not significantly impact yields or N availability, black plastic mulch treatments had substantially higher NO3- and NH4+ during and immediately following ASD. Extremely high soil temperatures were also observed under plastic mulches in 2012 and are believed to have caused lower total marketable yields in tomato than bare ground treatments (under which soil temperatures were closer to the optimal root-zone temperatures for tomato growth). Results of this research highlight the importance of understanding how both alternative and commonly utilized cropping practices can influence environmental conditions in vegetable production, while identifying areas that must be addressed to effectively implement BF and ASD in the future for vegetable producers in southwest Michigan.Thesis (M.S.)--Michigan State University. Horticulture, 2014Includes bibliographical reference

Expression and trans-specific polymorphism of self-incompatibility RNases in Coffea (Rubiaceae)

Self-incompatibility (SI) is widespread in the angiosperms, but identifying the biochemical components of SI mechanisms has proven to be difficult in most lineages. Coffea (coffee; Rubiaceae) is a genus of old-world tropical understory trees in which the vast majority of diploid species utilize a mechanism of gametophytic self-incompatibility (GSI). The S-RNase GSI system was one of the first SI mechanisms to be biochemically characterized, and likely represents the ancestral Eudicot condition as evidenced by its functional characterization in both asterid (Solanaceae, Plantaginaceae) and rosid (Rosaceae) lineages. The S-RNase GSI mechanism employs the activity of class III RNase T2 proteins to terminate the growth of "self" pollen tubes. Here, we investigate the mechanism of Coffea GSI and specifically examine the potential for homology to S-RNase GSI by sequencing class III RNase T2 genes in populations of 14 African and Madagascan Coffea species and the closely related self-compatible species Psilanthus ebracteolatus. Phylogenetic analyses of these sequences aligned to a diverse sample of plant RNase T2 genes show that the Coffea genome contains at least three class III RNase T2 genes. Patterns of tissue-specific gene expression identify one of these RNase T2 genes as the putative Coffea S-RNase gene. We show that populations of SI Coffea are remarkably polymorphic for putative S-RNase alleles, and exhibit a persistent pattern of trans-specific polymorphism characteristic of all S-RNase genes previously isolated from GSI Eudicot lineages. We thus conclude that Coffea GSI is most likely homologous to the classic Eudicot S-RNase system, which was retained since the divergence of the Rubiaceae lineage from an ancient SI Eudicot ancestor, nearly 90 million years ago.United States National Science Foundation [0849186]; Society of Systematic Biologists; American Society of Plant Taxonomists; Duke University Graduate Schoolinfo:eu-repo/semantics/publishedVersio

Exploring First Responders\u27 Use and Perceptions on Continuous Health and Environmental Monitoring

First responders lose their lives in the line of duty each year, and many of these deaths result from strenuous physical exertion and exposure to harmful environmental agents. Continuous health monitoring may detect diseases and alert the first responder when vital signs are reaching critical levels. However, continuous monitoring must be acceptable to first responders. The purpose of this study was to discover first responders\u27 current use of wearable technology, their perceptions of what health and environmental indicators should be monitored, and who should be permitted to monitor them. The survey was sent to 645 first responders employed by 24 local fire department stations. A total of 115 (17.8%) first responders answered the survey and 112 were used for analysis. Results found first responders perceived a need for health and environmental monitoring. The health and environmental indicators that respondents perceived as most important for monitoring in the field were heart rate (98.2%) and carbon monoxide (100%), respectively. Overall, using and wearing monitoring devices was not age-dependent and health and environmental concerns were important for first responders at any stage of their career. However, current wearable technology does not seem to be a viable solution for first responders due to device expense and durability issues

Autonomous Light Management in Flexible Photoelectrochromic Films Integrating High Performance Silicon Solar Microcells

Commercial smart window technologies for dynamic light and heat management in building and automotive environments traditionally rely on electrochromic (EC) materials powered by an external source. This design complicates building-scale installation requirements and substantially increases costs for applications in retrofit construction. Self-powered photoelectrochromic (PEC) windows are an intuitive alternative wherein a photovoltaic (PV) material is used to power the electrochromic device, which modulates the transmission of the incident solar flux. The PV component in this application must be sufficiently transparent and produce enough power to efficiently modulate the EC device transmission. Here, we propose Si solar microcells (μ-cells) that are i) small enough to be visually transparent to the eye, and ii) thin enough to enable flexible PEC devices. Visual transparency is achieved when Si μ-cells are arranged in high pitch (i.e. low-integration density) form factors while maintaining the advantages of a single-crystalline PV material (i.e., long lifetime and high performance). Additionally, the thin dimensions of these Si μ-cells enable fabrication on flexible substrates to realize these flexible PEC devices. The current work demonstrates this concept using WO₃ as the EC material and V₂O₅ as the ion storage layer, where each component is fabricated via sol-gel methods that afford improved prospects for scalability and tunability in comparison to thermal evaporation methods. The EC devices display fast switching times, as low as 8 seconds, with a modulation in transmission as high as 33%. Integration with two Si μ-cells in series (affording a 1.12 V output) demonstrates an integrated PEC module design with switching times of less than 3 minutes, and a modulation in transmission of 32% with an unprecedented EC:PV areal ratio

CG dinucleotide clustering is a species-specific property of the genome

Cytosines at cytosine-guanine (CG) dinucleotides are the near-exclusive target of DNA methyltransferases in mammalian genomes. Spontaneous deamination of methylcytosine to thymine makes methylated cytosines unusually susceptible to mutation and consequent depletion. The loci where CG dinucleotides remain relatively enriched, presumably due to their unmethylated status during the germ cell cycle, have been referred to as CpG islands. Currently, CpG islands are solely defined by base compositional criteria, allowing annotation of any sequenced genome. Using a novel bioinformatic approach, we show that CG clusters can be identified as an inherent property of genomic sequence without imposing a base compositional a priori assumption. We also show that the CG clusters co-localize in the human genome with hypomethylated loci and annotated transcription start sites to a greater extent than annotations produced by prior CpG island definitions. Moreover, this new approach allows CG clusters to be identified in a species-specific manner, revealing a degree of orthologous conservation that is not revealed by current base compositional approaches. Finally, our approach is able to identify methylating genomes (such as Takifugu rubripes) that lack CG clustering entirely, in which it is inappropriate to annotate CpG islands or CG clusters

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

The spotted gar genome illuminates vertebrate evolution and facilitates human-teleost comparisons

To connect human biology to fish biomedical models, we sequenced the genome of spotted gar (Lepisosteus oculatus), whose lineage diverged from teleosts before teleost genome duplication (TGD). The slowly evolving gar genome has conserved in content and size many entire chromosomes from bony vertebrate ancestors. Gar bridges teleosts to tetrapods by illuminating the evolution of immunity, mineralization and development (mediated, for example, by Hox, ParaHox and microRNA genes). Numerous conserved noncoding elements (CNEs; often cis regulatory) undetectable in direct human-teleost comparisons become apparent using gar: functional studies uncovered conserved roles for such cryptic CNEs, facilitating annotation of sequences identified in human genome-wide association studies. Transcriptomic analyses showed that the sums of expression domains and expression levels for duplicated teleost genes often approximate the patterns and levels of expression for gar genes, consistent with subfunctionalization. The gar genome provides a resource for understanding evolution after genome duplication, the origin of vertebrate genomes and the function of human regulatory sequences

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