Calendar Times Research Articles

From policy to practice: How China's emissions trading scheme shapes ESG greenwashing at the firm level?

This study provides new insights into the causal relationship between implementing Emission Trading Schemes (ETS) and corporate behaviors related to Environmental, Social, and Governance (ESG) greenwashing from 2009 to 2022. Utilizing a concise empirical framework, our findings substantiate the catalytic role of China's ETS in reducing ESG greenwashing activities. However, the effectiveness of this mitigation varies depending on firm's size, governance quality, and pollution nature. Notably, the impact of the ETS also differs based on cohort, calendar times, and exposure duration. Furthermore, our analysis explores the complex mechanisms through which ETS influences ESG greenwashing across four key dimensions, revealing that factors like innovation (including R&D and green innovation) and supply chain dynamics enhance the scheme's ability to curb greenwashing. Conversely, financial constraints and the digital divide can undermine the effectiveness of China's ETS, potentially leading to increased greenwashing practices.

Abstract PR009: Tick tock trees: Reconstructing the evolutionary dynamics of human tissues using fluctuating methylation clocks

Abstract The development of cancer from healthy somatic cells is fundamentally an evolutionary process. Understanding this process is vital to improving its clinical management and developing new treatment strategies. Tracing individual human cells’ fates would simultaneously advance somatic evolutionary theory and our understanding of normal tissue function and its change through development, aging, and cancer progression. We cannot use human cell-labeling techniques in vivo. Still, population genetic and phylogenetic models can leverage the information recorded in heritable alterations to reconstruct the unobserved somatic cells’ history. Most such methods are limited by the few parameters they can estimate and restricted to neoplastic samples due to the lack of adequate evolutionary signal in healthy somatic cells. Gabbutt et al. recently ameliorated this limitation by introducing fluctuating methylation clocks (FMCs)—tissue-specific CpG sites that randomly change their methylation state—and a model that uses them to reconstruct the evolution of a clonal stem-cell population. In this application, all FMCs in a bulk sample are interrogated using a single standard methylation array to yield estimates of rates of methylation, demethylation and cell replacement, and the size of the stem-cell niche. This technique is especially suited to studying stem-cell niche dynamics in healthy or pre-malignant tissues organized in clonal cell populations where the whole population can be sampled together, like crypts (e.g., intestine, Barrett’s esophagus) and glands (e.g., endometrium). We have developed a multi-sample extension of this model that simultaneously reconstructs the evolutionary dynamics of stem cells within a niche and the niches within the tissue. This phylodynamic model produces additional estimates like ancestral relationships between sampled clonal populations, their calendar divergence times, the number of effective evolutionary niches, and how some of these parameters change over time. Here, we will present the method, demonstrate its validity, characterize its accuracy under a broad simulation parameter space, and showcase its application in analyzing human data from the following tissues: colon, small intestine, endometrium, and Barrett’s esophagus. We will also discuss the current model's limitations and future improvements that will discern between mechanisms of stem-cell-niche reproduction and incorporate geographical information. The stochastic nature of neoplastic progression makes it unlikely for any particular somatic alteration to be highly predictive of its outcome. This can explain why developing reliable traditional biomarkers has been so difficult. Alternatively, evolutionary biomarkers measure the characteristics of the process itself and thus should apply to all neoplasms. Parametric phylogenetic reconstruction models like the one introduced here will enable us to develop such universal biomarkers. Our ultimate goal is for evolutionary biomarkers to join evolutionary therapies in the revolution of the clinical management of cancer. Citation Format: Diego Mallo, Pablo Bousquets-Muñoz, Heather E. Grant, Darryl Shibata, Trevor A. Graham, Carlo C. Maley, Calum Gabbutt. Tick tock trees: Reconstructing the evolutionary dynamics of human tissues using fluctuating methylation clocks [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR009.

437. Does “Long COVID” Resolve by One Year in U.S. Military Health System Beneficiaries?

Abstract Background The long-term duration of post COVID condition (PCC, “Long COVID”) remains unclear. In this study, we estimated the risk of healthcare encounters in Military Health System (MHS) beneficiaries for the 12 months post SARS-CoV-2 diagnosis, adjusting for prior healthcare use, and compared to those without known prior SARS-COV-2 diagnosis. Methods Follow up continues for the Epidemiology, Immunology and Clinical Characteristics of Emerging Infectious Diseases of Pandemic Potential (EPICC) COVID-19 cohort study MHS beneficiaries who were tested for SARS-COV-2 or vaccinated from March 2020 to April 2022. Participants with SARS-COV-2 diagnosis from 3/1/20 through 12/31/21 were matched 1:1 with participants in the same age group with no record of SARS-COV-2 diagnosis. We identified categories of ICD-10 diagnoses occurring from 3 months before through 12 months after first SARS-COV-2 diagnosis (or matched time point) from electronic medical records. Multivariable Poisson regression models were used to estimate the risk of ICD-10 diagnosis categories for those with past SARS-COV-2 diagnosis, compared to those with no SARS-COV-2 diagnosis, adjusting for age, sex, BMI, variant era, and prior healthcare use.Table 1.Characteristics of matched Epidemiology, Immunology and Clinical Characteristics of Emerging Infectious Diseases of Pandemic Potential (EPICC) participants included in analyses. Statistical comparisons are Pearson’s Chi squared tests, unless otherwise specified. Results Analyses included 1,819 matched pairs with a median age of 35 years. Participants were primarily male (63.0%) or white (57.3%) (Table 1) and severe acute COVID-19 was infrequent (9.6% hospitalized). Compared to those without a history of SARS-COV-2 diagnosis, medical encounters for all diagnosis groups (pulmonary, cardiovascular, diabetes, anxiety/depression, and neurology) were elevated in the first month after SARS-COV-2 diagnosis (Figures 1 and 2). Among the different diagnosis categories, only pulmonary diagnoses remained elevated at 9 months post-infection compared to those without a history of SARS-COV-2 diagnosis (risk ratio: 1.95 (95% CI 1.34, 2.83)). Percent of EPICC participants with medical encounters / diagnoses (by organ system or other domain) in health records. Participants without a history of SARS-CoV-2 infection were assigned the infection date of their matched case. Poisson regression analysis run using each category of healthcare encounters (pulmonary, cardiovascular, diabetes, neurology, and anxiety/depression) as the outcome. The models included time in 30-day periods around SARS-CoV-2 diagnosis date (or matched time point), SARS-CoV-2 diagnosis status, age, sex, BMI category, and variant/calendar period (calendar times with predominant Ancestral, Alpha, or Delta circulation), as well as a random effect for participant. Conclusion MHS beneficiaries with prior SARS-COV-2 diagnosis were at higher risk of pulmonary-associated healthcare encounters through 9 months post-infection compared to those without prior SARS-COV-2 diagnosis, even after adjusting for baseline characteristics and calendar time. Future work will assess the effect of vaccination and boosting on this relationship. Disclosures Michael Morris, MD, Janssen Pharmaceuticals: Paid speaker (unrelated to this project and COVID-19 in general) Ryan C. Maves, MD, Sound Pharmaceuticals: Grant/Research Support Mark Simons, PhD, AstraZeneca: TBD Timothy Burgess, MD, AstraZeneca: TBD Simon Pollett, MBBS, AstraZeneca: The IDCRP and the Henry M. Jackson Foundation (HJF) were funded to conduct an unrelated phase III COVID-19 monoclonal antibody immunoprophylaxis trial

Antibody correlates of protection against Delta infection after vaccination: A nested case-control within the UK-based SIREN study

To investigate serological correlates of protection against SARS-CoV-2 B.1.617.2 (Delta) infection after two vaccinations. We performed a case-control study, where cases were Delta infections after the second vaccine dose and controls were vaccinated, never infected participants, matched by age, gender and region. Sera were tested for anti-SARS-CoV-2 Spike antibody levels (anti-S) and neutralising antibody titres (nAbT), using live virus microneutralisation against Ancestral, Delta and Omicron (BA.1, B.1.1.529). We modelled the decay of anti-S and nAbT for both groups, inferring levels at matched calendar times since the second vaccination. We assessed differences in inferred antibody titres between groups and used conditional logistic regression to explore the relationship between titres and odds of infection. In total, 130 sequence-confirmed Delta cases and 318 controls were included. Anti-S and Ancestral nAbT decayed similarly between groups, but faster in cases for Delta nAbT (p=0.02) and Omicron nAbT (p=0.002). At seven days before infection, controls had higher anti-S levels (p<0.0001) and nAbT (p<0.0001; all variants) at matched calendar time. A two-fold increase in anti-S levels was associated with a 29% ([95% CI 14-42%]; p=0.001) reduction in odds of Delta infection. Delta nAbT>40 were associated with reduced odds of Delta infection (89%, [69-96%]; p<0.0001), with additional benefits for titres >100 (p=0.009) and >400 (p=0.007). We have identified correlates of protection against SARS-CoV-2 Delta, with potential implications for vaccine deployment, development, and public health response.

1319-P: Vascular Multimorbidity in Danish Persons with Type 2 Diabetes Is Decreasing, Contributing to Mortality Decline

Background: Multimorbidity in persons with type 2 diabetes (T2D) has not been studied in population wide settings. We used a Danish nation-wide diabetes register to assess trends in incidence and prevalence of vascular multimorbidity. Methods: All Danish persons with T2D since 1996 were followed from diagnosis to death or 2020-12-31. Follow-up was classified by the number of vascular morbidities from: atrial fibrillation, heart failure, myocardial infarction, ischemic stroke, hemorragic stroke, transient cerebral ischemia, amputation, retinopathy and nephropathy. Persons could enter with any number of vascular morbidities. We analyzed mortality rates and rates of each additional morbidity, using age, calendar time and number of attained morbidities as predictors. Prevalence of morbidities at diagnosis and at calendar times was modeled by binomial regression. Results: 505,124 persons entered the study. Occurrence of first morbidity increased mortality by a factor 2. Further morbidities increased mortality by a factor of 1.5. Mortality decreased 4%/year regardless of morbidity status. Incidence of additional morbidities increased only for the first 2 acquired morbidities by factors 1.8 and 1.2 and decreased by 3%/year regardless of morbidity status. The prevalence of morbidities at date of T2D increased until 2015. The prevalence of 1+ morbidity in all persons with T2D increased till 2008 and remained stable at 40% for men and 25% for women at age 65, and for 2+ at 10 and 5%. Conclusion: The decrease in morbidity and mortality rates is an indication of successful treatment of Danish persons with diabetes with respect to adverse vascular outcomes. This could be the result of earlier diagnosis of T2D; including persons earlier in the course of T2D would result in a “healthier” population. The increase in prevalence of morbidities at T2D diagnosis and the constant prevalence over time among all T2D persons may be an indication that management of morbidities is improving. Disclosure B.Carstensen: Stock/Shareholder; Novo Nordisk. K.K.B.Clemmensen: Employee; Novo Nordisk A/S, Stock/Shareholder; Novo Nordisk A/S. V.Kosjerina: Research Support; Sanofi-Aventis Deutschland GmbH. F.Persson: Advisory Panel; AstraZeneca, Bayer Consumer Care AG, Boehringer-Ingelheim, Novo Nordisk A/S, Consultant; AstraZeneca, Boehringer-Ingelheim, Novo Nordisk A/S, Research Support; Boehringer-Ingelheim, Novo Nordisk A/S, Speaker's Bureau; AstraZeneca, Bayer Consumer Care AG, Boehringer-Ingelheim, Novo Nordisk A/S, Sanofi.

Names of Yuletide Mummers in the Russian Subdialects of Perm Krai

This article deals with the main groups of nominations denoting mummers (Rus. ряженые) in the Russian colloquialisms of Perm Region. The aim of the study is to describe the semantic groups of such terms associated with various ideas of dressing up: ritual dressing up, attributes and methods of dressing up, mythological ideas, and calendar time; to demonstrate the geographical distribution of units of these groups in the region. The study refers to field materials collected under the direction of A. V. Chernykh in various districts of Perm Region, data from Perm dialect dictionaries, collections and monographs, and data from the card index of the Dictionary of Russian Colloquialisms of the North of Perm Region (ed. by I. I. Rusinov) of Perm State National Research University. The various nominations of mummers reflect the complexity and polyfunctionality of the phenomenon of mummers; together they represent a certain set of attributes perceived as essential. The names of these attributes serve as motivators of the denominations of mummers. Several most frequent groups of units motivationally connected with the names of ritual transformation can be distinguished among the regional nominations of disguised persons (наряжунчики, посряжунчики, ряженки, ряженчики, ряжунчики, снаряжёнцы, снаряженщики, срядчики, сряженцы, сряжунчики, сряжушки), features of their appearances (замаскированные, маскарованные, маскированные, машкарованные, машкированные, мышкарики), means and ways of dressing up (горбуницы, горбунки, горбунцы, горбунчики, горбушки; старушки), lower demonology characters (ошуликаны, силикуны, сюликуны, чиликуны, шеликуны, шиликуны, шулеконы, шулиганы, шуликаны, шуликины, шуликуны, шулихуны, шульганы, шульканы, шулюкины; шиши, шишочки; полуденки, полудники, полудницы; мухтари, мухтарики, мухтары), calendar times (святки, святошни, святошники, святошные), which, at the same time, form areas on the territory of Perm Krai and are conditioned by the peculiarities of settlement. One can talk about a significant variability of the terminology of mummers in Perm Krai. Some nominations are often recorded in the region, others are less frequent and are characteristic only of specific areas and local traditions. Perm data demonstrate the use of terms both widely spread in Russian traditions in general and several names characteristic only of the region.

Detection of Dynamic Phenomena Associated with Underground Nuclear Explosion Using Multiple Seismic Surveys and Machine Learning

The application of an active seismic method for detecting the source location of an underground nuclear explosion (UNE) is an ongoing field of research. The objective of active seismic in On-Site Inspection (OSI) is to detect the static signatures such as the cavity created by the UNE. Along with characteristic static signatures, UNEs produce dynamic phenomena such as groundwater mounding, which gradually revert to pre-test conditions. These dynamic phenomena are observable for an extended period, even up to several decades. The magnitude of these phenomena is prominent near the source origin and results from the redistribution of residual energy, such as pressure, temperature, and saturation. These dynamic changes in sub-surface rock and fluid properties will affect the seismic property of the rock, resulting in changes of P-wave velocity. These changes can be detected by using an active seismic survey. This study highlights the potential of using time-lapse seismic to identify ground zero by monitoring post-explosion variation in the seismic signature. Time-lapse seismic, also known as 4D seismic, is a well-known technology, used in the oil and gas industry for several decades for petroleum production monitoring and management. It involves taking more than one 2D/3D survey at different calendar times over the same reservoir and studying the difference in seismic attributes. This study investigates the characteristic dynamic phenomena associated with the UNE and their impact on the emplacement rock’s seismic property. Groundwater mounding (GWM) is one of the phenomena with a high gradient of dissipation during the initial days immediately after the explosion. We look at the impact of GWM variation on seismic P-wave velocity and discuss the potential of using time-lapse seismic for its detection. The challenges of implementing time-lapse seismic, such as non-repeatability, seasonal variations and time constraints, are discussed. A frequent seismic monitoring survey method (time-lapse seismic) is proposed to monitor rock and fluid properties changes due to the post-UNE dynamic phenomena. Due to the time constraint for the OSI activity, conventional time-lapse seismic processing would not be suitable. Therefore, a machine learning-based 4D detection workflow is presented. The near-real-time 4D detection workflow using machine learning can be implemented during the OSI to identify the source location or ground zero.

General independent censoring in event-driven trials with staggered entry.

Randomized clinical trials with time-to-event endpoints are frequently stopped after a prespecified number of events has been observed. This practice leads to dependent data and nonrandom censoring, which can in general not be solved by conditioning on the underlying baseline information. In case of staggered study entry, matters are complicated substantially. The present paper demonstrates that the study design at hand entails general independent censoring in the counting process sense, provided that the analysis is based on study time information only. To illustrate that the filtrations must not use abundant information, we simulated data of event-driven trials and evaluated them by means of Cox regression models with covariates for the calendar times. The Breslow curves of the cumulative baseline hazard showed considerable deviations, which implies that the analysis is disturbed by conditioning on the calendar time variables. A second simulation study further revealed that Efron's classical bootstrap, unlike the (martingale-based) wild bootstrap, may lead to biased results in the given setting, as the assumption of random censoring is violated. This is exemplified by an analysis of data on immunotherapy in patients with advanced, previously treated nonsmall cell lungcancer.

In-field degradation of soil-biodegradable plastic mulch films in a Mediterranean climate

Soil-biodegradable plastic mulch films are a promising alternative to polyethylene mulches, but adoption has been slow, in part because of uncertainties about in-field degradation. The international biodegradability standard EN-17033 requires 90% degradation within 2 years in an aerobic incubation at constant temperature (20–28 °C). However, in-laboratory biodegradability does not guarantee in-field degradation will follow the same timeframe. Field test protocols are needed to assess biodegradable mulches under a range of environmental conditions and collate site-specific information to predict degradation. Our objectives were to (1) monitor in-field degradation of soil-biodegradable plastic mulches following successive applications and incorporations, (2) quantify mulch recovery 2 years after the final incorporation, and (3) compare in-field degradation with the laboratory standard in terms of calendar and thermal times based on a zeroth-order kinetics model. A field experiment was established in spring 2015 in Mount Vernon, WA testing five biodegradable mulches laid each spring and incorporated each fall until 2018. Mulch recovery was quantified every 6 months until fall 2020, 2 years after the final incorporation. While mulches were incorporated annually, recovery of visible fragments (>2.36 mm) was constant or decreasing over time, indicating mulch deterioration kept pace with new additions. In fall 2020, mulch recovery was 4–16% of total mulch mass incorporated. A zeroth-order kinetics model was used to analyze mulch degradation after the final application. Model extrapolations indicate it would take 21 to 58 months to reach 10% recovery (90% degradation), exceeding the laboratory standard's 24-month benchmark by up to a factor of 2.4. However, when the analysis is done with thermal time, better agreement between in-field and laboratory degradation rates is observed. While other factors, including soil type, soil moisture, and mulch fragment size are also at play, thermal time, rather than calendar time, will be more applicable for assessing site-specific, in-field mulch degradation.

ПОВЫШЕНИЕ ЭФФЕКТИВНОСТИ РАБОТЫ ТЕПЛООБМЕННЫХ АППАРАТОВ С ВНУТРИТРУБНЫМИ ОТЛОЖЕНИЯМИ

The article studies the effect of scale formation on the efficiency of heat exchangers, as applied to condensers of steam turbines, steam-water heaters and boilers of boiler installations. The purpose of the study is to generate recommendations on how to increase the efficiency of steam turbine units (STU) condensers. This was achieved by studying the chemical and physical properties of the inorganic depositslayer and their structure obtaining the dependencies to calculate the thermal resistance of the sediment layer on the surfaces of smooth and profiled pipes; analyzing various methods of cleaning surfaces and developing recommendations on the cleaning frequency for the capacitors. The paper also describes the results of the physicochemical analysis of inorganic salt deposition. The thermal resistance of the deposits was determined by the thickness of the scale layer and its coefficient of thermal conductivity. The layer thickness was measured with a microscope and a profilograph-profilometeron thin sections. The obtained relationship is the one between the intensity of salt deposition and the main factors determining the process: the speed of water, its average temperature and hardness, the geometry of the channel, the duration of work. Based on that it one can predict a decrease in the heat load of the heat exchanger in operation. The dependence of the influence of the temperature of the coolant and the porosity of the scale on the thermal conductivity is obtained. It is shown that in profiled pipes the scale de¬position is less intensive than in the smooth ones. With a decrease in the relative depth and roll pitch, an increase in inorganic deposits is observed. The height of the knurled ridges has a greater influence than the pitch between them. The paper presents recommendations for the calculation of the relative contamination of smooth and helical-shaped tubes. The use of profiled tubes instead of smooth ones in power plants is an effective means of increasing the efficiency of power equipment. Various methods of surface cleaning are considered. An optimization technique is proposed and a technical and economic substantiation of the frequency of cleaning of heat exchangers is carried out. Rational terms of cleaning were obtained for different calendar times of the start of operation of the heat exchanger.

The Application of 4D Seismic in Niger Delta Basin: A Review

Time-lapse seismic also known as 4D seismic is one of the advanced techniques employed in the oil and gas industry for petroleum production management and monitoring for over 20years. It involves carrying out two or more 3D seismic at different calendar times, before and after production over the same reservoir. We present advances in Time Lapse 3D seismic (also known as 4D seismic) and its application in the Niger Delta basin of Nigeria. Over the years, the technique has been used in Niger Delta to understand reservoir drainage performance, enable better well placement, identifying bypassed oil, detecting fluid communication, understanding of internal architecture of the reservoirs, and locating infill wells for future re-development. 4D seismic has demonstrated its potential and it is fast becoming a standard tool in the oil companies. DOI : 10.7176/APTA/83-05 Publication date: February 29 th 2020

Prevalent cohort studies and unobserved heterogeneity.

Consider lifetimes originating at a series of calendar times [Formula: see text]. At a certain time [Formula: see text] a cross-sectional sample is taken, generating a sample of current durations (backward recurrence times) of survivors until [Formula: see text] and a prevalent cohort study consisting of survival times left-truncated at the current durations. A Lexis diagram is helpful in visualizing this situation. Survival analysis based on current durations and prevalent cohort studies is now well-established as long as all covariates are observed. The general problems with unobserved covariates have been well understood for ordinary prospective follow-up studies, with the good help of hazard rate models incorporating frailties: as for ordinary regression models, the added noise generates attenuation in the regression parameter estimates. For prevalent cohort studies this attenuation remains, but in addition one needs to take account of the differential selection of the survivors from initiation [Formula: see text] to cross-sectional sampling at [Formula: see text]. This paper intends to survey the recent development of these matters and the consequences for routine use of hazard rate models or accelerated failure time models in the many cases where unobserved heterogeneity may be an issue. The study was inspired by concrete problems in the study of time-to-pregnancy, and we present various simulation results inspired by this particular application.

Group-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes.

We discuss the multivariate (2L-variate) correlation structure and the asymptotic distribution for the group-sequential weighted logrank statistics formulated when monitoring two correlated event-time outcomes in clinical trials. The asymptotic distribution and the variance-covariance for the 2L-variate weighted logrank statistic are derived as available in various group-sequential trial designs. These methods are used to determine a group-sequential testing procedure based on calendar times or information fractions. We apply the theoretical results to a group-sequential method for monitoring a clinical trial with early stopping for efficacy when the trial is designed to evaluate the joint effect on two correlated event-time outcomes. We illustrate the method with application to a clinical trial and describe how to calculate the required sample sizes and numbers of events.

Online estimation of the case fatality rate using a run-off triangle data approach: An application to the Korean MERS outbreak in 2015.

This work is motivated by the recent Korean Middle East respiratory syndrome outbreak. We propose an easy online estimation procedure for the case fatality rate, ie, the proportion of deaths among the total cases during the course of an epidemic disease, which is an important indicator of the severity of a disease. The key step in our procedure is representing the data with the run-off triangle, which simultaneously takes into account two time axes, namely, the calendar and disease-duration times. We restructure the original data into run-off triangle data, where the cells contain the numbers of cured patients, deceased patients, and patients still having the disease at a given combination of calendar and disease-duration times. Based on the restructured run-off triangle data, we propose an online estimator of the case fatality rate. We numerically show the advantages of the proposed estimator compared to the existing estimators in the literature. Finally, we apply our procedure to the 2015 Korean Middle East respiratory syndrome outbreak data.

Prediction of Multiple Recurrent Events: A Comparison of Extended Cox Models in Bladder Cancer.

Recurrence of bladder cancer can occur repeatedly in the same patient after treatment of the primary tumor. Models predicting the risk of a next recurrence may inform individualized decision-making on surveillance frequency. We aimed to assess the usefulness of extensions of the Cox proportional hazards model for repeated events in this context. We analyzed 531 Dutch patients with bladder cancer (1990-2012) with information on 7 prespecified predictors at the time of diagnosis of the primary and recurrent tumors. We considered 3 aspects of model variants: how to model time to the repeated events (calendar time, gap time, elapsed time); the number of preceding events (predictor, stratum variable); and the within-subject correlation (ignored in a simple Cox model, robust standard errors in a variance-correction model, random effect in a frailty model). First to fourth recurrences of bladder cancer occurred in 313, 174, 103, and 66 patients, respectively, with median calendar follow-up times of 1.1, 2.5, 3.8, and 4.5 years, respectively. We focused on gap time in the detailed analyses, allowing for clinically meaningful predictions. Variance-correction models may be useful if predictor selection is part of the model development. Frailty models may be useful when within-subject correlation is strong.

Calendar-based age replacement policy with dependent renewal cycles

ABSTRACTIn this article, we introduce an age-based replacement policy in which the preventive replacements are restricted to specific calendar times. Under the new policy, the assets are renewed at failure or if their ages are greater than or equal to a replacement age at given calendar times, whichever occurs first. This policy is logistically applicable in industries such as utilities where there are large and geographically diverse populations of deteriorating assets with different installation times. Since preventive replacements are performed at fixed times, the renewal cycles are dependent random variables. Therefore, the classic renewal reward theorem cannot be directly applied. Using the theory of Markov chains with general state space and a suitably defined ergodic measure, we analyze the problem to find the optimal replacement age, minimizing the long-run expected cost per time unit. We further find the limiting distributions of the backward and forward recurrence times for this policy and show how our ergodic measure can be used to analyze more complicated policies. Finally, using a real data set of utility wood poles’ maintenance records, we numerically illustrate some of our results including the importance of defining an appropriate ergodic measure in reducing the computational expense.

Risperidone and Risk of Gynecomastia in Young Men.

The purpose of this study was to quantify the risk of gynecomastia with risperidone in adolescent and young adult males. We created a cohort of males 15-25 years of age from the IMS LifeLink database, and conducted a case-control study within the cohort by identifying all new cases of gynecomastia. For each case, 10 controls were selected and matched to the cases by age, follow-up, and calendar times (cases and controls had the same follow up time and cohort entry date). Rate ratios (RR) for current use of risperidone were computed adjusting for potential confounding variables. First diagnosis of gynecomastia was made based on International Classification of Diseases, 9th revision (ICD-9) for gynecomastia. There were 401,924 males ages 15-25 in the primary cohort. There were 1556 cases of gynecomastia and 15,560 corresponding controls. Current users of risperidone had approximately four times the risk of developing gynecomastia than non-users (RR=3.91, 95% CI=2.01-7.62). When the analysis was stratified to children and adolescents (≤18 years of age) taking risperidone, the risk of gynecomastia was five times higher than for non-users (RR=5.44, 95% CI=1.50-19.74). Risperidone is associated with an increase with the risk of gynecomastia in adolescent and young adult males.

Reservoir characterization based upon the onset of time-lapse amplitude changes

Time-lapse geophysical monitoring has potential as a tool for reservoir characterization, that is, for determining reservoir properties such as permeability. Onset times, the calendar times at which geophysical observations begin to deviate from their initial or background values, provide a useful basis for such characterization. We found that, in contrast to time-lapse amplitude changes, onset times were not sensitive to the exact method used to related changes in fluid saturation to changes in seismic velocities. As a consequence of this, we found that an inversion for effective permeability based upon onset times was robust with respect to variations in the rock-physics model. In particular, inversions of synthetic onset times calculated using Voigt and Reuss averaging techniques, but inverted using sensitivities from Hill’s averaging method, resulted in almost identical misfit reductions and similar permeability models. All solutions based on onset times recovered the large-scale, resolvable features of the reference model. Synthetic tests indicated that reliable onset times can be obtained from noisy seismic amplitudes. Testing also indicated that large-scale permeability variations can be recovered even if we used onset times from seismic surveys that were spaced as much as 300 days apart.

In-sample forecasting applied to reserving and mesothelioma mortality

This paper shows that recent published mortality projections with unobserved exposure can be understood as structured density estimation. The structured density is only observed on a sub-sample corresponding to historical calendar times. The mortality forecast is obtained by extrapolating the structured density to future calendar times using that the components of the density are identified within sample. The new method is illustrated on the important practical problem of forecasting mesothelioma for the UK population. Full asymptotic theory is provided. The theory is given in such generality that it also introduces mathematical statistical theory for the recent continuous chain ladder model. This allows a modern approach to classical reserving techniques used every day in any non-life insurance company around the globe. Applications to mortality data and non-life insurance data are provided along with relevant small sample simulation studies.

Modeling the Effects of Environmental Conditions on HT2 and T2 Toxin Accumulation in Field Oat Grains

Fusarium head blight (FHB) of wheat and barley has been extensively researched worldwide; in contrast, there is limited information on the effects of environmental conditions on Fusarium toxin accumulation in oat grains. More than 300 samples of oat grain from various regions of the United Kingdom from 2006 to 2008 were analyzed for mycotoxin contamination due to infection by Fusarium spp. HT2 and T2 toxins were the two most commonly detected, and their concentrations in individual samples were highly correlated. Hourly weather data were obtained from meteorological recording stations near most of the sampling sites. Statistical modeling was applied to both the original toxin (HT2 plus T2) data and the toxin data adjusted for oat cultivars and number of cereal crops in the previous four seasons. Accumulation of HT2 and T2 toxin was positively correlated with warm and wet conditions during early May and dry conditions thereafter. Using a collection of 51 environmental variables summarized over three lengths (10, 15, and 20 days) of time periods encompassing early May, late May, and early July, all-subsets regression showed that many models, consisting of three to six predictor variables, could be identified with similar explanatory strength for the effect of environmental conditions on toxin accumulation. Most important predictor variables were related to wet conditions during the early-May period, which was before anthesis. These results suggest that the predominant period for Fusarium langsethiae infection of oat is likely to be before rather than during anthesis, as for other head blight pathogens. These empirical models may be further improved by using quantified pathogen biomass within the grains and weather predictor variables summarized in relation to plant growth stages (instead of calendar times).