Heterogeneity in Costs and Second-Best Policies for Environmental Protection

This paper investigates heterogeneity in pollution abatement costs using a computable general equilibrium framework. Previous literature using aggregated data has found that "grandfathered" tradable permits are dominated by other instruments including emission taxes, performance standards, and technology mandates because of interactions with pre-existing taxes. However, when the underlying costs of abatement are heterogeneous, a disaggregate representation of costs yields qualitatively different findings. In a disaggregate model of NOX abatement in the United States, the relative performance of tradable permits improves significantly and out-performs command and control approaches over a wide range of emission reductions.

Using an Atomic Molecular Optics Laboratory for Undergraduate Research and Mentoring of Physics Students in Georgia

Using an Atomic Molecular Optics Laboratory for Undergraduate Research and Mentoring of Physics Students in Georgia An Atomic and Molecular Optical (AMO) Physics research lab is an excellent tool to train and mentor undergraduate students in advanced laboratory techniques. Students gain valuable basic experience in experimental designs, data acquisition techniques, working with high precision optical equipment, building electronics, and working in the machine shop. The current project is building and testing an enclosure for the diode laser to reduce sound and vibrational interference. In addition, we are developing and evaluating a new, more compact laser cavity which is 3d printed. Previously completed projects involved building a temperature controller, current supply circuit, machining the laser mount, milling the vacuum chamber mounts to support the chamber, and machining the Helmholtz coils for the chamber, which are being used to trap the atoms in a Magneto Optical Trap (MOT). This included designing, building, and baking out the vacuum chamber, constructing a trap for the Rb in the chamber, and building the lasers for a saturation-absorption system that is used to probe the 52S1/2→ 52P3/2 hyperfine energy transitions of the Rb-85 atom. These energy transitions have been used to frequency-lock a diode laser to trap Rb-85 atoms and then cool them to ultra-low temperatures. The atom cooling will permit observation and measurement of the fundamental properties of atoms. This lab has mentored and supported over twelve undergraduate students in the last four years, of which one became a High School Teacher, three joined Ph.D. programs, one continued in a master’s level engineering program, and one went to graduate school to study bioengineering

Service Dog Ramp

This project involves designing a device to help a service dog easily get into and out of a truck. It details the design and manufacturing process. The project was interrupted due to the COVID-19 pandemic, so detailed instructions are provided for whoever takes on the project in the future

Explainable Machine Learning for Hydrogen Diffusion in Metals and Random Binary Alloys

Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen diffusion, they often lack accuracy when making quantitative predictions. Machine learning models are capable of making accurate predictions, but their inner workings are obscured, rendering it unclear which physical features are truly important. To develop interpretable machine learning models to predict the activation energies of hydrogen diffusion in metals and random binary alloys, we create a database for physical and chemical properties of the species and use it to fit six machine learning models. Our models achieve root-mean-squared-errors between 98-119 meV on the testing data and accurately predict that elemental Ru has a large activation energy, while elemental Cr and Fe have small activation energies.By analyzing the feature importances of these fitted models, we identify relevant physical properties for predicting hydrogen diffusivity. While metrics for measuring the individual feature importances for machine learning models exist, correlations between the features lead to disagreement between models and limit the conclusions that can be drawn. Instead grouped feature importances, formed by combining the features via their correlations, agree across the six models and reveal that the two groups containing the packing factor and electronic specific heat are particularly significant for predicting hydrogen diffusion in metals and random binary alloys. This framework allows us to interpret machine learning models and enables rapid screening of new materials with the desired rates of hydrogen diffusion.Comment: 36 pages, 8 figures, supplemental materia

Universal Converter Using SiC

The grantee designed a high power (over 1MW) inverter for use in renewable and distributed energy systems, such as PV cells, fuel cells, variable speed wind turbines, micro turbines, variable speed gensets and various energy storage methods. The inverter uses 10,000V SiC power devices which enable the use of a straight-forward topology for medium voltage (4,160VAC) without the need to cascade devices or topologies as is done in all commercial, 4,160VAC inverters today. The use of medium voltage reduces the current by nearly an order of magnitude in all current carrying components of the energy system, thus reducing size and cost. The use of SiC not only enables medium voltage, but also the use of higher temperatures and switching frequencies, further reducing size and cost. In this project, the grantee addressed several technical issues that stand in the way of success. The two primary issues addressed are the determination of real heat losses in candidate SiC devices at elevated temperature and the development of high temperature packaging for SiC devices

National health and medical research council statement on electronic cigarettes: 2022 update

Introduction: Electronic cigarette (e-cigarette) use in Australia has rapidly increased since the 2017 National Health and Medical Research Council (NHMRC) Chief Executive Officer (CEO) statement on e-cigarettes. The type of products available and the demographic characteristics of people using these products have changed. New evidence has been published and there is growing concern among public health professionals about the increased use, particularly among young people who do not currently smoke combustible cigarettes. The combination of these issues led NHMRC to review the current evidence and provide an updated statement on e-cigarettes. In this article, we describe the comprehensive process used to review the evidence and develop the 2022 NHMRC CEO statement on electronic cigarettes. Main recommendations: E-cigarettes can be harmful; all e-cigarette users are exposed to chemicals and toxins that have the potential to cause adverse health effects. There are no health benefits of using e-cigarettes if you do not currently smoke tobacco cigarettes. Adolescents are more likely to try e-cigarettes if they are exposed to e-cigarettes on social media. Short term e-cigarette use may help some smokers to quit who have been previously unsuccessful with other smoking cessation aids. There are other proven safe and effective options available to help smokers to quit. Changes in management as a result of this statement: The evidence base for the harms of e-cigarette use has strengthened since the previous NHMRC statement. Significant gaps in the evidence base remain, especially about the longer term health harms of using e-cigarettes and the toxicity of many chemicals in e-cigarettes inhaled as an aerosol

The microtubule-associated protein DCAMKL1 regulates osteoblast function via repression of Runx2

Osteoblasts are responsible for the formation and mineralization of the skeleton. To identify novel regulators of osteoblast differentiation, we conducted an unbiased forward genetic screen using a lentiviral-based shRNA library. This functional genomics analysis led to the identification of the microtubule-associated protein DCAMKL1 (Doublecortin-like and CAM kinase–like 1) as a novel regulator of osteogenesis. Mice with a targeted disruption of Dcamkl1 displayed elevated bone mass secondary to increased bone formation by osteoblasts. Molecular experiments demonstrated that DCAMKL1 represses osteoblast activation by antagonizing Runx2, the master transcription factor in osteoblasts. Key elements of the cleidocranial dysplasia phenotype observed in Runx2+/− mice are reversed by the introduction of a Dcamkl1-null allele. Our results establish a genetic linkage between these two proteins in vivo and demonstrate that DCAMKL1 is a physiologically relevant regulator of anabolic bone formation

Hydrogen sulfide regulates hippocampal neuron excitability via S-sulfhydration of Kv2.1

Hydrogen sulfide (H2S) is gaining interest as a mammalian signalling molecule with wide ranging effects. S-sulfhydration is one mechanism that is emerging as a key post translational modification through which H2S acts. Ion channels and neuronal receptors are key target proteins for S-sulfhydration and this can influence a range of neuronal functions. Voltage-gated K+ channels, including Kv2.1, are fundamental components of neuronal excitability. Here, we show that both recombinant and native rat Kv2.1 channels are inhibited by the H2S donors, NaHS and GYY4137. Biochemical investigations revealed that NaHS treatment leads to S-sulfhydration of the full length wild type Kv2.1 protein which was absent (as was functional regulation by H2S) in the C73A mutant form of the channel. Functional experiments utilising primary rat hippocampal neurons indicated that NaHS augments action potential firing and thereby increases neuronal excitability. These studies highlight an important role for H2S in shaping cellular excitability through S-sulfhydration of Kv2.1 at C73 within the central nervous system

Dual Mechanism of Interleukin-3 Receptor Blockade by an Anti-Cancer Antibody

SummaryInterleukin-3 (IL-3) is an activated T cell product that bridges innate and adaptive immunity and contributes to several immunopathologies. Here, we report the crystal structure of the IL-3 receptor α chain (IL3Rα) in complex with the anti-leukemia antibody CSL362 that reveals the N-terminal domain (NTD), a domain also present in the granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-5, and IL-13 receptors, adopting unique “open” and classical “closed” conformations. Although extensive mutational analyses of the NTD epitope of CSL362 show minor overlap with the IL-3 binding site, CSL362 only inhibits IL-3 binding to the closed conformation, indicating alternative mechanisms for blocking IL-3 signaling. Significantly, whereas “open-like” IL3Rα mutants can simultaneously bind IL-3 and CSL362, CSL362 still prevents the assembly of a higher-order IL-3 receptor-signaling complex. The discovery of open forms of cytokine receptors provides the framework for development of potent antibodies that can achieve a “double hit” cytokine receptor blockade

Seeing the landscape for the trees: metrics to guide riparian shade management in river catchments

Rising water temperature (Tw) due to anthropogenic climate change may have serious consequences for river ecosystems. Conservation and/or expansion of riparian shade could counter warming and buy time for ecosystems to adapt. However, sensitivity of river reaches to direct solar radiation is highly heterogeneous in space and time, so benefits of shading are also expected to be site specific. We use a network of high-resolution temperature measurements from two upland rivers in the UK, in conjunction with topographic shade modelling, to assess the relative significance of landscape and riparian shade to the thermal behaviour of river reaches. Trees occupy 7% of the study catchments (comparable with the UK national average) yet shade covers 52% of the area and is concentrated along river corridors. Riparian shade is most beneficial for managing Tw at distances 5 to 20 km downstream from the source of the rivers where discharge is modest, flow is dominated by near-surface hydrological pathways, there is a wide floodplain with little landscape shade, and where cumulative solar exposure times are sufficient to affect Tw. For the rivers studied, we find that approximately 0.5 km of complete shade is necessary to off-set Tw by 1°C during July (the month with peak Tw) at a headwater site; whereas 1.1 km of shade is required 25 km downstream. Further research is needed to assess the integrated effect of future changes in air temperature, sunshine duration, direct solar radiation and downward diffuse radiation on Tw to help tree planting schemes achieve intended outcomes