Cost-Benefit Analysis : Proposed Safety Upgrades to Currently Operating Nuclear Power Plants

In the wake of nuclear accidents such as Three Mile Island Unit 2 and Fukushima, the nuclear power industry’s safety record is scrutinized. Today the main concerns lies with hydrogen production in a nuclear reactor core when the zirconium fuel cladding reacts with the water coolant during an accident, creating combustible hydrogen gas. This concern is being addressed with new technologies for new nuclear power plants and the development of hydrogen mitigation techniques for currently operating plants. This study looks at a few potential safety upgrades including hydrogen mitigation upgrades such as hydrogen ignitors and Passive Autocatalytic Recombiners (PARs). As well as some radionuclide release mitigation safety upgrades, filtered vents and hardened vents. Using event tree/fault tree analysis to obtain probabilities and consequences of accidents and a newly developed “Economic Safety Factor (ESF)” has been proposed. The ESF is a metric that is aimed at helping utilities and regulators decide whether a particular safety upgrade is beneficial for the cost. While the ESF is not the only mechanism a utility or regulator will consider when evaluating plant changes, it can give a good indication of whether or not a safety upgrade, or another type of upgrade is a good idea. It was found that hydrogen ignitors and PAR should be implemented. The addition of filtered vents is dependent on their cost based on the results of an ESF cost-benefit analysis method. As a response to the accidents at Fukushima, hardened vents have been required on all Mk. I and Mk. II Boiling Water Reactors by the US Nuclear Regulatory Commission

Assessing the associations between known genetic variants and substance use in people with HIV in the United States

Background The prevalence of substance use in people with HIV (PWH) in the United States is higher than in the general population and is an important driver of HIV-related outcomes. We sought to assess if previously identified genetic associations that contribute to substance use are also observed in a population of PWH. Methods We performed genome-wide association studies (GWAS) of alcohol, smoking, and cannabis use phenotypes in a multi-ancestry population of 7,542 PWH from the Center for AIDS Research Network of Integrated Clinical Systems (CNICS). We conducted multi-ancestry GWAS for individuals of African (n = 3,748), Admixed American (n = 1,334), and European (n = 2,460) ancestry. Phenotype data were self-reported and collected using patient reported outcomes (PROs) and three questions from AUDIT-C, an alcohol screening tool. We analyzed nine phenotypes: 1) frequency of alcohol consumption, 2) typical number of drinks on a day when drinking alcohol, 3) frequency of five or more alcoholic drinks in a 30-day period, 4) smoking initiation, 5) smoking cessation, 6) cigarettes per day, 7) cannabis use initiation, 8) cannabis use cessation, 9) frequency of cannabis use during the previous 30 days. For each phenotype we considered a) variants previously identified as associated with a substance use trait and b) novel associations. Results We observed evidence for effects of previously reported single nucleotide polymorphisms (SNPs) related to alcohol (rs1229984, p = 0.001), tobacco (rs11783093, p = 2.22E-4), and cannabis use (rs2875907, p = 0.005). We also report two novel loci (19p13.2, p = 1.3E-8; and 20p11.21, p = 2.1E-8) associated with cannabis use cessation. Conclusions Our analyses contribute to understanding the genetic bases of substance use in a population with relatively higher rates of use compared to the general population

A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Geneenvironment interactions (G x E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G x E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G x E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G x E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant GxBMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer

Statistical Emulation of Winter Ambient Fine Particulate Matter Concentrations From Emission Changes in China

Air pollution exposure remains a leading public health problem in China. The use of chemical transport models to quantify the impacts of various emission changes on air quality is limited by their large computational demands. Machine learning models can emulate chemical transport models to provide computationally efficient predictions of outputs based on statistical associations with inputs. We developed novel emulators relating emission changes in five key anthropogenic sectors (residential, industry, land transport, agriculture, and power generation) to winter ambient fine particulate matter (PM2.5) concentrations across China. The emulators were optimized based on Gaussian process regressors with Matern kernels. The emulators predicted 99.9% of the variance in PM2.5 concentrations for a given input configuration of emission changes. PM2.5 concentrations are primarily sensitive to residential (51%–94% of first‐order sensitivity index), industrial (7%–31%), and agricultural emissions (0%–24%). Sensitivities of PM2.5 concentrations to land transport and power generation emissions are all under 5%, except in South West China where land transport emissions contributed 13%. The largest reduction in winter PM2.5 exposure for changes in the five emission sectors is by 68%–81%, down to 15.3–25.9 μg m−3, remaining above the World Health Organization annual guideline of 10 μg m−3. The greatest reductions in PM2.5 exposure are driven by reducing residential and industrial emissions, emphasizing the importance of emission reductions in these key sectors. We show that the annual National Air Quality Target of 35 μg m−3 is unlikely to be achieved during winter without strong emission reductions from the residential and industrial sectors

Comparison of Greenhouse-Based Inoculation Methods to Study Aggressiveness of Diaporthe helianthi Isolates Causing Phomopsis Stem Canker of Sunflower (Helianthus annuus)

Phomopsis stem canker is an economically important disease of sunflower (Helianthus annuus), and Diaporthe helianthi is one of the primary causal agents of the disease in the United States. The objective of this study was to evaluate inoculation methods of D. helianthi isolates on sunflower in the greenhouse. Four isolates of D. helianthi were selected to test the effectiveness of four inoculation methods using mycelial plugs as the inoculum, including stem wound, wound inoculation, petiole wound, and straw test. Infection was established by the D. helianthi isolates at 14 days after inoculation for all inoculation methods used. However, recovery of the pathogen from the inoculated plants differed significantly (P \u3c 0.0001) among inoculation methods. Given higher mean recovery of D. helianthi isolates from the inoculated plants and the size of the lesions caused by the pathogen, the stem-wound inoculation method was found to be the most user friendly of the four inoculation methods

First Report of Stem Disease of Soybean (Glycine max) Caused by Diaporthe gulyae in North Dakota

The planted soybean (Glycine max L.) acreage in North Dakota increased approximately six-fold in the last two decades to over 6 million acres in 2016. In September 2012, soybean plants exhibiting reddish-brown stem cankers (∼60 mm length) were observed in a production field in Grand Forks county (49°11′N; 98°09′W). Incidence of infected stems was estimated in excess of 95% in parts of the field. Ten plants exhibiting symptoms were randomly sampled and brought to the Department of Plant Pathology at NDSU to identify the causal pathogen