Stochastic generation of annual, monthly and daily climate data: A review

International audienceThe generation of rainfall and other climate data needs a range of models depending on the time and spatial scales involved. Most of the models used previously do not take into account year to year variations in the model parameters. Long periods of wet and dry years were observed in the past but were not taken into account. Recently, Thyer and Kuczera (1999) developed a hidden state Markov model to account for the wet and dry spells explicitly in annual rainfall. This review looks firstly at traditional time series models and then at the more complex models which take account of the pseudo-cycles in the data. Monthly rainfall data have been generated successfully by using the method of fragments. The main criticism of this approach is the repetitions of the same yearly pattern when only a limited number of years of historical data are available. This deficiency has been overcome by using synthetic fragments but this brings an additional problem of generating the right number of months with zero rainfall. Disaggregation schemes are effective in obtaining monthly data but the main problem is the large number of parameters to be estimated when dealing with many sites. Several simplifications have been proposed to overcome this problem. Models for generating daily rainfall are well developed. The transition probability matrix method preserves most of the characteristics of daily, monthly and annual characteristics and is shown to be the best performing model. The two-part model has been shown by many researchers to perform well across a range of climates at the daily level but has not been tested adequately at monthly or annual levels. A shortcoming of the existing models is the consistent underestimation of the variances of the simulated monthly and annual totals. As an alternative, conditioning model parameters on monthly amounts or perturbing the model parameters with the Southern Oscillation Index (SOI) result in better agreement between the variance of the simulated and observed annual rainfall and these approaches should be investigated further. As climate data are less variable than rainfall, but are correlated among themselves and with rainfall, multisite-type models have been used successfully to generate annual data. The monthly climate data can be obtained by disaggregating these annual data. On a daily time step at a site, climate data have been generated using a multisite type model conditional on the state of the present and previous days. The generation of daily climate data at a number of sites remains a challenging problem. If daily rainfall can be modelled successfully by a censored power of normal distribution then the model can be extended easily to generate daily climate data at several sites simultaneously. Most of the early work on the impacts of climate change used historical data adjusted for the climate change. In recent studies, stochastic daily weather generation models are used to compute climate data by adjusting the parameters appropriately for the future climates assumed

Continuous rainfall simulation: 1. A regionalized subdaily disaggregation approach

This paper is the first of two in the current issue that presents a framework for generating continuous (uninterrupted) rainfall sequences at both gaged and ungaged point locations. The ultimate objective is to present a methodology for stochastically generating continuous subdaily rainfall sequences at any location such that the statistics at a range of aggregation scales are preserved. This first paper presents a regionalized nonparametric daily disaggregation model in which, conditional on a daily rainfall amount and previous and next-day wetness states at the location of interest, subdaily fragments are resampled using continuous records at nearby locations. The second paper then focuses on a regionalized daily rainfall generation model.To enable the substitution of subdaily rainfall at nearby locations for subdaily rainfall at the location of interest, it is necessary to identify locations with ‘‘similar’’ daily to subdaily scaling characteristics. We use a two-sample, two-dimensional Kolmogorov-Smirnov (K-S) test to identify whether the daily to subdaily scaling relationships are statistically similar between all possible station pairs sampled from 232 gages located throughout Australia. This step is followed by a logistic regression to determine the influence of the covariates of latitude, longitude, elevation, and distance to the coast on the probability that the scaling at any two locations will be similar. The model is tested at five locations, where recorded subdaily data was available for comparison, and results indicate good model performance, particularly in preserving the probability distribution of extremes and the antecedent rainfall prior to the storm event.Seth Westra, Rajeshwar Mehrotra, Ashish Sharma and Ratnasingham Srikantha

The physicAl aCtivity Counselling for young adult cancEr SurvivorS (ACCESS) trial: a protocol for a parallel, two-arm pilot randomized controlled trial

BackgroundYoung adults aged 18–39 years commonly experience persistent side effects following cancer treatment that can impair their quality of life. Physical activity (PA) holds promise as a behavioral intervention to mitigate persistent side effects and improve quality of life. Yet, few young adults are active enough to incur these benefits and efforts to promote PA after cancer treatment ends are lacking. Therefore, we developed a novel theory-driven behavior change intervention to promote PA via videoconferencing technology in young adults who have completed cancer treatment, and are undertaking a pilot randomized controlled trial (RCT) to gather evidence to inform the design of a large, full-scale RCT. The specific aims of this parallel, two-arm pilot RCT are to: (1) assess intervention and trial protocol feasibility and acceptability; and (2) generate data on PA behavior. To promote transparency, improve reproducibility, and serve as a reference for forthcoming publication of results, we present the study protocol for this pilot RCT (version 7) within this paper.MethodsYoung adults who have completed cancer treatment are being recruited from across Canada. After informed consent is obtained and baseline assessments are completed, participants are randomized to the intervention group (i.e., a 12-week behavior change intervention delivered via videoconferencing technology by trained PA counsellors) or usual care group (i.e., no intervention). Several feasibility outcomes covering enrollment, allocation, follow-up, and analysis are tracked by study staff. Acceptability is assessed through interviews exploring participants’ experiences, thoughts, and perspectives of the trial protocol (i.e., intervention and usual care groups), as well as participants’ views of the intervention and its mode of delivery (i.e., intervention group only) and PA counsellors’ experiences delivering the intervention. PA behavior is measured using accelerometers at baseline (pre-randomization), post-intervention, and at follow-up (24 weeks post-baseline).DiscussionThere are growing calls to develop interventions to support young adults’ motivation to engage in PA and adopt an active lifestyle to improve their quality of life after cancer treatment ends. Real-time videoconferencing shows promise for disseminating behavior change interventions to young adults and addressing participation barriers. Considering the importance of establishing intervention and trial protocol feasibility and acceptability prior to evaluating intervention efficacy (or effectiveness), this pilot RCT is critical to understand how participants embrace, engage with, and complete the intervention and trial protocol. Indeed, these data will help to determine which refinements, if any, are required to the intervention and trial protocol (e.g., implementation approach, evaluation methods) prior to a large, full-scale RCT aiming to test the effects of the intervention on PA behavior. Additionally, the PA behavior data collected will be useful to inform the sample size calculation for a large, full-scale RCT.Trial registrationThe trial was registered with the ClinicalTrials.gov database (ID: NCT04163042) on November 14, 2019, prior to the start of the trial in February, 2021

Existence of a Strong Correlation of Biomarkers and Mirna in Females With Metabolic Syndrome and Obesity in a Population of West Virginia

Objectives: Metabolic syndrome causes complications like cardiovascular disease and type 2 diabetes mellitus (T2DM). As metabolic syndrome develops, altered levels of cytokines and microRNAs (miRNA) are measurable in the circulation. We aimed to construct a panel detecting abnormal levels of cytokines and miRNAs in patients at risk for metabolic syndrome. Methods: Participants included 54 patients from a Family Medicine Clinic at Marshall University School of Medicine, in groups of: Control, Obese, and Metabolic Syndrome (MetS). Results: Serum levels of leptin, adiponectin, leptin: adiponectin ratio, IL-6, six miRNAs (320a, 197-3p, 23-3p, 221-3p, 27a-3p, and 130a-3p), were measured. Among the three groups, leptin, and leptin: adiponectin ratio, and IL-6 levels were highest in MetS, and levels in Obese were greater than Control (p\u3e0.05). Adiponectin levels were lower in Obese compared to Control, but lowest in MetS (p0.05). Conclusion: Our results support the clinical application of biomarkers in diagnosing early stage MetS, which will enable attenuation of disease progression before onset of irreversible complications. Since West Virginians are high-risk for developing MetS, our biomarker panel could reduce the disease burden on our population

pNaKtide Attenuates Steatohepatitis and Atherosclerosis by Blocking Na/K-ATPase/ROS Amplification in C57BI6 and ApoE Knockout Mice Fed a Western Diet

We have previously reported that the alpha1 subunit of sodium potassium adenosine triphosphatase (Na/K-ATPase), acts as a receptor and an amplifier for reactive oxygen species, in addition to its distinct pumping function. On this background, we speculated that blockade of Na/K-ATPase-induced ROS amplification with a specific peptide, pNaKtide, might attenuate the development of steatohepatitis. To test this hypothesis, pNaKtide was administered to a murine model of NASH: the C57Bl6 mouse fed a western diet containing high amounts of fat and fructose. The administration of pNaKtide reduced obesity as well as hepatic steatosis, inflammation and fibrosis. Of interest, we also noted marked improvement in mitochondrial fatty acid oxidation, insulin sensitivity, dyslipidemia and aortic streaking in this mouse model. To further elucidate the effects of pNaKtide on atherosclerosis, similar studies were performed in ApoE knockout mice also exposed to the western diet. In these mice, pNaKtide not only improved steatohepatitis, dyslipidemia, and insulin sensitivity, but also ameliorated significant aortic atherosclerosis. Collectively, this study demonstrates that the Na/K-ATPase/ROS amplification loop contributes significantly to the development and progression of steatohepatitis and atherosclerosis. And furthermore, this study presents a potential treatment, the pNaKtide, for the metabolic syndrome phenotype

Relative magnitudes of sources of uncertainty in assessing climate change impacts on water supply security for the southern Adelaide water supply system

The sources of uncertainty in projecting the impacts of climate change on runoff are increasingly well recognized; however, translating these uncertainties to urban water security has received less attention in the literature. Furthermore, runoff cannot be used as a surrogate for water supply security when studying the impacts of climate change due to the nonlinear transformations in modeling water supply and the effects of additional uncertainties, such as demand. Consequently, this study presents a scenario-based sensitivity analysis to qualitatively rank the relative contributions of major sources of uncertainty in projecting the impacts of climate change on water supply security through time. This can then be used by water authorities to guide water planning and management decisions. The southern system of Adelaide, South Australia, is used to illustrate the methodology for which water supply system reliability is examined across six greenhouse gas (GHG) emissions scenarios, seven general circulation models, six demand projections, and 1000 stochastic rainfall time series. Results indicate the order of the relative contributions of uncertainty changes through time; however, demand is always the greatest source of uncertainty and GHG emissions scenarios the least. In general, reliability decreases over the planning horizon, illustrating the need for additional water sources or demand mitigation, while increasing uncertainty with time suggests flexible management is required to ensure future supply security with minimum regret.F.L. Paton, H.R. Maier and G.C. Dand

Effect of Background Water Matrices on Pharmaceutical and Personal Care Product Removal by UV-LED/TiO2

In this study, we evaluated the effectiveness of UV-LED-irradiated TiO2 in removing 24 commonly detected PPCPs in two water matrices (municipal wastewater effluent and Suwannee River NOM–synthetic water) and compared their performance with that of ultrapure water. Relatively fast removal kinetics were observed for 29% and 12% of the PPCPs in ultrapure water and synthetic surface water, respectively (kapp of 1–2 min−1). However, they all remained recalcitrant to photocatalysis when using wastewater effluent as the background matrix (kapp < 0.1 min−1). We also observed that the pH-corrected octanol/water partition coefficient (log Dow) correlated well with PPCP degradation rate constants in ultrapure water, whereas molecular weight was strongly associated with the rate constants in both synthetic surface water and wastewater. The electrical energy per order (EEO) values calculated at the end of the experiments suggest that UV-LED/P25 can be an energy-efficient method for water treatment applications (2.96, 4.77, and 16.36 kW h m−3 in ultrapure water, synthetic surface water, and wastewater effluents, respectively). Although TiO2 photocatalysis is a promising approach in removing PPCPs, our results indicate that additional challenges need to be overcome for PPCPs in more complex water matrices, including an assessment of photocatalytic removal under different background water matrices.Canada Research Chair||Natural Sciences and Engineering Research Council||Strategic Project Grant (STPGP 430654-12)||Schwartz-Resiman Foundatio

Sarcopenia Exacerbates Obesity-Associated Insulin Resistance and Dysglycemia: Findings from the National Health and Nutrition Examination Survey III

Sarcopenia often co-exists with obesity, and may have additive effects on insulin resistance. Sarcopenic obese individuals could be at increased risk for type 2 diabetes. We performed a study to determine whether sarcopenia is associated with impairment in insulin sensitivity and glucose homeostasis in obese and non-obese individuals.We performed a cross-sectional analysis of National Health and Nutrition Examination Survey III data utilizing subjects of 20 years or older, non-pregnant (N = 14,528). Sarcopenia was identified from bioelectrical impedance measurement of muscle mass. Obesity was identified from body mass index. Outcomes were homeostasis model assessment of insulin resistance (HOMA IR), glycosylated hemoglobin level (HbA1C), and prevalence of pre-diabetes (6.0≤ HbA1C<6.5 and not on medication) and type 2 diabetes. Covariates in multiple regression were age, educational level, ethnicity and sex.Sarcopenia was associated with insulin resistance in non-obese (HOMA IR ratio 1.39, 95% confidence interval (CI) 1.26 to 1.52) and obese individuals (HOMA-IR ratio 1.16, 95% CI 1.12 to 1.18). Sarcopenia was associated with dysglycemia in obese individuals (HbA1C ratio 1.021, 95% CI 1.011 to 1.043) but not in non-obese individuals. Associations were stronger in those under 60 years of age. We acknowledge that the cross-sectional study design limits our ability to draw causal inferences.Sarcopenia, independent of obesity, is associated with adverse glucose metabolism, and the association is strongest in individuals under 60 years of age, which suggests that low muscle mass may be an early predictor of diabetes susceptibility. Given the increasing prevalence of obesity, further research is urgently needed to develop interventions to prevent sarcopenic obesity and its metabolic consequences

Multiplex RT-qPCR assay (N200) to detect and estimate prevalence of multiple SARS-CoV-2 Variants of Concern in wastewater

Wastewater-based surveillance (WBS) has become an effective tool around the globe for indirect monitoring of COVID-19 in communities. Quantities of viral fragments of SARS-CoV-2 in wastewater are related to numbers of clinical cases of COVID-19 reported within the corresponding sewershed. Variants of Concern (VOCs) have been detected in wastewater by use of reverse transcription quantitative polymerase chain reaction (RT-qPCR) or sequencing. A multiplex RT-qPCR assay to detect and estimate the prevalence of multiple VOCs, including Omicron/Alpha, Beta, Gamma, and Delta, in wastewater RNA extracts was developed and validated. The probe-based multiplex assay, named “N200” focuses on amino acids 199-202, a region of the N gene that contains several mutations that are associated with variants of SARS- CoV-2 within a single amplicon. Each of the probes in the N200 assay are specific to the targeted mutations and worked equally well in single- and multi-plex modes. To estimate prevalence of each VOC, the abundance of the targeted mutation was compared with a non- mutated region within the same amplified region. The N200 assay was applied to monitor frequencies of VOCs in wastewater extracts from six sewersheds in Ontario, Canada collected between December 1, 2021, and January 4, 2022. Using the N200 assay, the replacement of the Delta variant along with the introduction and rapid dominance of the Omicron variant were monitored in near real-time, as they occurred nearly simultaneously at all six locations. The N200 assay is robust and efficient for wastewater surveillance can be adopted into VOC monitoring programs or replace more laborious assays currently being used to monitor SARS- CoV-2 and its VOCs.Ontario Ministry of the Environment, Conservation and Parks||Natural Sciences and Engineering Research Council of Canad

Anthropomorphic Measurements That Include Central Fat Distribution Are More Closely Related with Key Risk Factors than BMI in CKD Stage 3

Background: Body Mass Index (BMI) as a marker of obesity is an established risk factor for chronic kidney disease (CKD) and cardiovascular disease (CVD). However, BMI can overestimate obesity. Anthropomorphic measurements that include central fat deposition are emerging as a more important risk factor. We studied BMI, waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR) and conicity index (CI) in a cohort of patients with CKD stage 3 and compared the associations with other known risk factors for CKD progression and CVD. Methods: 1740 patients with CKD stage 3 were recruited from primary care for the Renal Risk in Derby study. Each participant underwent clinical assessment, including anthropomorphic measurements and pulse wave velocity (PWV), as well as urine and serum biochemistry tests. Results: The mean age of the cohort was 72.969 years with 60 % females. The mean eGFR was 52.5610.4 ml/min/1.73 m 2 and 16.9 % of the cohort had diabetes. With the cohort divided into normal and increased risk of morbidity and mortality using each anthropomorphic measurement, those measurements that included increased central fat distribution were significantly associated with more risk factors for CKD progression and CVD than increased BMI. Univariable analysis demonstrated central fat distribution was correlated with more risk factors than BMI. Subgroup analyses using recognised BMI cut-offs to define obesity and quartiles of WHR and CI demonstrated that increasing central fat distribution wa