Effects of different running intensities on the micro-level failure strain of rat femoral cortical bone structures: a finite element investigation.

BACKGROUND: Running with the appropriate intensity may produce a positive influence on the mechanical properties of cortical bone structure. However, few studies have discussed the effects of different running intensities on the mechanical properties at different levels, especially at the micro-level, because the micromechanical parameters are difficult to measure experimentally. METHODS: An approach that combines finite element analysis and experimental data was proposed to predict a micromechanical parameter in the rat femoral cortical bone structure, namely, the micro-level failure strain. Based on the previous three-point bending experimental information, fracture simulations were performed on the femur finite element models to predict their failure process under the same bending load, and the micro-level failure strains in tension and compression of these models were back-calculated by fitting the experimental load-displacement curves. Then, the effects of different running intensities on the micro-level failure strain of rat femoral cortical bone structure were investigated. RESULTS: The micro-level failure strains of the cortical bone structures expressed statistical variations under different running intensities, which indicated that different mechanical stimuli of running had significant influences on the micromechanical properties. The greatest failure strain occurred in the cortical bone structure under low-intensity running, and the lowest failure strain occurred in the structure under high-intensity running. CONCLUSIONS: Moderate and low-intensity running were effective in enhancing the micromechanical properties, whereas high-intensity running led to the weakening of the micromechanical properties of cortical bone. Based on these, the changing trends in the micromechanical properties were exhibited, and the effects of different running intensities on the fracture performance of rat cortical bone structures could be discussed in combination with the known mechanical parameters at the macro- and nano-levels, which provided the theoretical basis for reducing fracture incidence through running exercise.

Unifying incidence and prevalence under a time-varying general branching process.

Renewal equations are a popular approach used in modelling the number of new infections, i.e., incidence, in an outbreak. We develop a stochastic model of an outbreak based on a time-varying variant of the Crump-Mode-Jagers branching process. This model accommodates a time-varying reproduction number and a time-varying distribution for the generation interval. We then derive renewal-like integral equations for incidence, cumulative incidence and prevalence under this model. We show that the equations for incidence and prevalence are consistent with the so-called back-calculation relationship. We analyse two particular cases of these integral equations, one that arises from a Bellman-Harris process and one that arises from an inhomogeneous Poisson process model of transmission. We also show that the incidence integral equations that arise from both of these specific models agree with the renewal equation used ubiquitously in infectious disease modelling. We present a numerical discretisation scheme to solve these equations, and use this scheme to estimate rates of transmission from serological prevalence of SARS-CoV-2 in the UK and historical incidence data on Influenza, Measles, SARS and Smallpox.

Evaluation of Undiagnosed HIV Estimates Computed from the CD4 Depletion Model in a Rural, Medium-low HIV Prevalence State.

The CD4 depletion model estimates diagnosis delays by approximating infection date from CD4 T-cell count at diagnosis, and back-calculation can compute the proportion of undiagnosed PLWHA. The model assumes the immigration of PLWHA to the U.S. is negligible and counts as a transmission event, which may be impractical outside high prevalence states. Duration of U.S. residency among foreign-born PLWHA and diagnosis delays were compared. The impact on estimates of undiagnosed PLWHA was tested through simulation with different proportions of foreign-born people assumed to have acquired HIV abroad. In 67% of foreign-born people, the mean (SD) years of delay (9.9 (6.3)) exceeded the duration of U.S. residency (2.0 (1.9)). Additionally, inaccuracies in the estimates for proportions of undiagnosed PLWHA were pronounced when foreign-born people who acquired HIV abroad comprised 30% of diagnoses. The CD4 model inadvertently misclassified some diagnoses as in-state transmission events. Consequently, simulated results demonstrated inaccuracies and unstable calculations.

Strain Transfer Function of Distributed Optical Fiber Sensors and Back-Calculation of the Base Strain Field.

Distributed optical fiber sensors are a promising technology for monitoring the structural health of large-scale structures. The fiber sensors are usually coated with nonfragile materials to protect the sensor and are bonded onto the structure using adhesive materials. However, local deformation of the relatively soft coating and adhesive layers hinders strain transfer from the base structure to the optical fiber sensor, which reduces and distorts its strain distribution. In this study, we analytically derive a strain transfer function in terms of strain periods, which enables us to understand how the strain reduces and is distorted in the optical fiber depending on the variation of the strain field. We also propose a method for back-calculating the base structure's strain field using the reduced and distorted strain distribution in the optical fiber sensor. We numerically demonstrate the back-calculation of the base strain using a composite beam model with an open hole and an attached distributed optical fiber sensor. The new strain transfer function and the proposed back-calculation method can enhance the strain field estimation accuracy in using a distributed optical fiber sensor. This enables us to use a highly durable distributed optical fiber sensor with thick protective layers in precision measurement.

Will there be any more classical scrapie cases in sheep in Great Britain? A modelling study to predict future cases.

The aim of this study was to apply a back-calculation model to Great Britain (GB) classical scrapie surveillance data, and use this model to estimate how many more cases might be expected, and over what time frame these cases might occur. A back-calculation model was applied to scrapie surveillance data between 2005 and 2019 to estimate the annual rate of decline of classical scrapie. This rate was then extrapolated to predict the number of future cases each year going forward. The model shows that there may be yet further cases of classical scrapie in GB. These will most likely occur in the fallen stock scheme, with approximately a 25% probability of at least 1 further scrapie positive, with a very low probability (~0.2%) of having up to three additional scrapie positives. This highlights the difficulty of completely eliminating all further cases, even in the presence of very effective control measures.

Monitoring the hepatitis C epidemic in England and evaluating intervention scale-up using routinely collected data.

In England, 160 000 individuals were estimated to be chronically infected with hepatitis C virus (HCV) in 2005 and the burden of severe HCV-related liver disease has increased steadily for the past 15 years. Direct-acting antiviral treatments can clear infection in most patients, motivating HCV elimination targets. However, the current burden of HCV is unknown and new methods are required to monitor progress. We employed a Bayesian back-calculation approach, combining data on severe HCV-related liver disease and disease progression, to reconstruct historical HCV incidence and estimate current prevalence in England. We explicitly modelled infections occurring in people who inject drugs, the key risk group, allowing information on the size of this population and surveillance data on HCV prevalence to inform recent incidence. We estimated that there were 143 000 chronic infections in 2015 (95% credible interval 123 000-161 000), with 34% and 54% in those with recent and past injecting drug use, respectively. Following the planned scale-up of new treatments, chronic infections were predicted to fall to 113 400 (94 900-132 400) by the end of 2018 and to 89 500 (71 300-108 600) by the end of 2020. Numbers developing severe HCV-related liver disease were predicted to fall by at least 24% from 2015 to 2020. Thus, we describe a coherent framework to monitor progress using routinely collected data, which can be extended to incorporate additional data sources. Planned treatment scale-up is likely to achieve 2020 WHO targets for HCV morbidity, but substantial efforts will be required to ensure that HCV testing and patient engagement are sufficiently high.

Precision and accuracy of Dahl-Lea back-calculated smolt lengths from adult scales of Atlantic salmon Salmo salar.

Using tagged and recaptured Atlantic salmon Salmo salar (n = 106) the present analysis shows that the most commonly applied linear back-calculation method for estimating past length, the Dahl-Lea method, resulted in overestimation of the length of large smolts and underestimation of small smolts. A correction equation (y = 0.53x + 6.23) for estimating true smolt length (y) from lengths back-calculated from adult scale measures (x) to account for these systematic discrepancies is proposed.

Extending Bayesian back-calculation to estimate age and time specific HIV incidence.

CD4-based multi-state back-calculation methods are key for monitoring the HIV epidemic, providing estimates of HIV incidence and diagnosis rates by disentangling their inter-related contribution to the observed surveillance data. This paper, extends existing approaches to age-specific settings, permitting the joint estimation of age- and time-specific incidence and diagnosis rates and the derivation of other epidemiological quantities of interest. This allows the identification of specific age-groups at higher risk of infection, which is crucial in directing public health interventions. We investigate, through simulation studies, the suitability of various bivariate splines for the non-parametric modelling of the latent age- and time-specific incidence and illustrate our method on routinely collected data from the HIV epidemic among gay and bisexual men in England and Wales.

A spatiotemporal back-calculation approach to estimate cancer incidence measures.

Incidence rates are an important population-level disease risk measure. Cancer incidence data in the United States, which are collected by disease registries, have been spatiotemporally sparse. Back-calculation methods can yield incidence estimates for a spatial domain by solving a convolution equation that relates mortality to incidence through survival estimates. We propose a novel back-calculation approach that uses spatiotemporal age-period-cohort (APC) modeling to estimate incidence for spatial units within a region. The method is applied to state-specific lung cancer data in the United States for males ages 30 to 84 in years 1975-2004. SEER data are used to model cancer progression from incidence to mortality along three timescales (APC) and across four regions. Using mortality data from National Vital Statistics System, incidence is back-calculated for unique birth cohorts in 49 states. A conditionally autoregressive model with cubic splines for temporal effects is used to smooth back-calculated estimates. Bayesian estimates of model parameters are obtained using integrated nested Laplace approximation. Results show varying time trends in lung cancer risk across states, which may quantify effects of state policies.

Is there a decline in bovine spongiform encephalopathy cases born after reinforced feed bans? A modelling study in EU member states.

Occasional cases of classical bovine spongiform encephalopathy (BSE) still continue to occur within the European Union (EU) for animals born after reinforced feed bans (BARBs), which should in theory have eliminated all risk of infection. The study aimed to determine (i) whether a common rate of decline of BSE infection was evident across EU member states, i.e. to determine whether control measures have been equally effective in all member states, (ii) whether there was any evidence of spontaneous occurrence of BSE in the data and (iii) the expected date for the last BSE case in UK. It was found that there was no significant difference in the rate of decline of BSE prevalence between member states, with a common rate of decline of 33·9% per annum (95% CI 30·9-37%) in successive annual birth cohorts. Trend analysis indicated an ultimate decline to 0 prevalence, suggesting that spontaneous occurrence does not explain the majority of cases. Projecting forward the trends from the back-calculation model indicated that there was approximately a 50% probability of further cases in the UK, and should the current rate of decline continue, there remains the possibility of further occasional cases up until 2026.

Improving uncertainty in Widmark equation calculations: Alcohol volume, strength and density.

The Widmark equation is probably the most commonly used calculation for medicolegal purposes. Recently the National Research Council (USA) and the Forensic Science Regulator (UK) have called for the uncertainty of all results to be given with all forensic measurements and calculations. To improve the uncertainty of measurement of results from Widmark calculations we have concentrated on the uncertainties of measurement involved in the calculation of amount of alcohol, that of the volume of alcohol, the concentration of alcohol and the density of alcohol as previous studies have investigated some of the other factors involved. Using experimental studies, the scientific literature and legal statutes, we have determined revised and improved uncertainties of the concentration of ethanol for Widmark calculations for both the USA and UK. Based on the calculations that we have performed we recommend the use of Monte Carlo Simulation for the determination of uncertainty of measurement for Widmark Calculations.

A methodical approach for the assessment of waste sorting plants.

A techno-economical evaluation of the processing result of waste sorting plants should at least provide a realistic assessment of the recovery yields of valuable materials and of the qualities of the obtained products. This practical data is generated by weighing all the output products and sampling these products. Due to the technological complexity of sorting plants, for example, lightweight packaging waste treatments plants and the high expenditures concerning time and costs of sampling with subsequent manual sorting for quality determination, usually only final products undergo such an investigation. Thereby, the transferability of the results depends decisively on the boundary conditions (extent, throughput of the plant, process parameterization). Given that the process is too complex, not all relevant information of the process steps can be determined by sampling. By model calculations and/or adjustment of reasonable assumptions, information concerning weak points in the process can be identified, which can be used for further plant optimization. For the example of the recovery of beverage cartons from co-collected and mechanically recovered mixtures of lightweight packaging waste, a methodical approach for the assessment of processing results will be presented.

Age-Period-Cohort approaches to back-calculation of cancer incidence rate.

A compartment model for cancer incidence and mortality is developed in which healthy subjects may develop cancer and subsequently die of cancer or another cause. In order to adequately represent the experience of a defined population, it is also necessary to allow for subjects who are diagnosed at death, as well as subjects who migrate and are subsequently lost to follow-up. Expressions are derived for the number of cancer deaths as a function of the number of incidence cases and vice versa, which allows for the use of mortality statistics to obtain estimates of incidence using survival information. In addition, the model can be used to obtain estimates of cancer prevalence, which is useful for health care planning. The method is illustrated using data on lung cancer among males in Connecticut.

Increased uptake and new therapies are needed to avert rising hepatitis C-related end stage liver disease in England: modelling the predicted impact of treatment under different scenarios.

BACKGROUND & AIMS: Hepatitis C (HCV) related disease in England is predicted to rise, and it is unclear whether treatment at current levels will be able to avert this. The aim of this study was to estimate the number of people with chronic HCV infection in England that are treated and assess the impact and costs of increasing treatment uptake. METHODS: Numbers treated were estimated using national data sources for pegylated interferon supplied, dispensed, or purchased from 2006 to 2011. A back-calculation approach was used to project disease burden over the next 30 years and determine outcomes under various scenarios of treatment uptake. RESULTS: 5000 patients were estimated to have been treated in 2011 and 28,000 in total from 2006 to 2011; approximately 3.1% and 17% respectively of estimated chronic infections. Without treatment, incident cases of decompensated cirrhosis and hepatocellular carcinoma were predicted to increase until 2035 and reach 2290 cases per year. Treatment at current levels should reduce incidence by 600 cases per year, with a peak around 2030. Large increases in treatment are needed to halt the rise; and with more effective treatment the best case scenario predicts incidence of around 500 cases in 2030, although treatment uptake must still be increased considerably to achieve this. CONCLUSIONS: If the infected population is left untreated, the number of patients with severe HCV-related disease will continue to increase and represent a substantial future burden on healthcare resources. This can be mitigated by increasing treatment uptake, which will have the greatest impact if implemented quickly.

Thermal Diffusivity of Concrete Samples Assessment Using a Solar Simulator.

The thermal properties of pavement layers made of concrete with varying bulk densities are a particularly interesting topic in the context of development road technologies. If a hybrid layer system is used as a starting point, with thin asphalt layers (from 1 cm to 4 cm) laid on top of a foam concrete layer, thermal properties begin to play a crucial role. The main research problem was to create a test method enabling the assessment of the influence of solar heating on the thermal parameters of the building material, especially cement concrete. For this reason, this paper is concerned specifically with the assessment of a new methodology for testing and calculating the value of the thermal diffusivity coefficient of samples made of concrete varying bulk densities. In this case, using the proprietary concept the authors built a solar simulator using a multi-source lighting system. The analysis of the results of laboratory tests and numerical analyses allowed the authors to observe that there is a strong correlation between the bulk density of samples heated and the thermal diffusivity parameter, which appears in the unidirectional heat transfer equation. The strength of this relationship has been expressed with the coefficient of determination and amounts to 99%. The calculated values of the coefficient of thermal diffusivity for samples made of foam concrete range from 0.16×10-6m2s to 0.52×10-6m2s and are lower (from 2.5 to 8 times) than the value determined for samples made of typical cement concrete.

Blood alcohol concentration and road accidents: Underestimation due to time of the arrival to the emergency department (ED) or delay in blood sampling. A 4-Year Retrospective Study in Rome.

Alcohol is a significant public health issue, according to the World Health Organization. Our study aims to analyze the correlation between blood alcohol concentrations (BACs) of drivers, their demographic features, and the possible underestimation of BACs due to the time elapsed between hospital admission and blood sampling. Methods: This study includes patients evaluated for BAC levels in the emergency department (ED) of Fondazione Policlinico Universitario A. Gemelli IRCCS from January 2013 to December 2016. BAC levels were compared in patients involved in road crashes according to age group, sex, and time of the accident. The delays in blood sampling and BAC measurement in the ED were recorded for each patient. The time between the accident and access to the hospital in most cases was unknown. Results: A total of 398 patients were included in the analysis, 107 of them had BACs more than 0.05 g/L., and 86 of these individuals had BAC levels more than 0.5 g/L. Road accident patients had higher rates of positive BAC readings at night and on weekends. A significant delay in blood sampling for BAC determination was observed. Discussion: This study demonstrates a critical bias due to the arrival time at the ED and the delay in blood sampling that inevitably influences and underestimates the BAC, resulting in possible false negative results (BAC values below the cutoff). Zero tolerance or a retrospective BAC calculation could mitigate this bias. It is necessary to implement preventive strategies to reduce instances of driving under the influence (DUI) of alcohol.

Evidence of hatch-time based growth compensation in the early life history of two salmonid fishes.

Initial body size can indicate quality within-species, with large size increasing the likelihood of survival. However, some populations or individuals may have body size disadvantages due to spatial/temporal differences in temperature, photoperiod, or food. Across-populations, animals often have locally adapted physiology to compensate for relatively poor environmental influences on development and growth, while within-population individual behavioral adjustments can increase food intake after periods of deprivation and provide opportunities to catch up (growth compensation). Previous work has shown that growth compensation should include within-population differences related to short growing seasons due to delayed hatch time. We tested the hypothesis that individual fish that hatch later grow faster than those that hatch earlier. The relative magnitude of such a response was compared with growth variation among populations. We sampled young of the year Arctic charr and brook trout from five rivers in northern Labrador. Daily increments from otoliths were used to back-calculate size to a common age and calculate growth rates. Supporting the hypothesis, older fish were not larger at capture than younger fish because animals that hatched later grew faster, which may indicate age-based growth compensation.

Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation.

The modulus of asphalt pavement material is a necessary parameter for the design, strength measuring and stability evaluation of asphalt pavement. To get more precise test data for asphalt pavement material modulus, a new modulus back calculation method is proposed in this article, named as the Firefly Asphalt Back Calculation Method (FABCM). This novel method uses the firefly optimization algorithm, which is a kind of particle swarm intelligence algorithm imitating the information transfer process among fireflies. To demonstrate the reliability and stability of FABCM, and to study the feasibility of multi-parameter modulus back calculation methods, this article used theoretical deflection curves calculated by BISAR3.0 and the actual measurement data of deflection curves and vertical pressures on the subgrade top surfaces on the full-scale test circular track in the Research Institute of Highway, Ministry of Transport (RIOHTrack) to conduct a modulus back calculation. The results show that FABCM only takes 0.5-1 s for each calculation, and the back calculation errors in the verification of FABCM are mostly smaller than 1%, which means that the firefly optimization algorithm was modified effectively in this article. Moreover, this article also indicates some key factors influencing the accuracy of modulus back calculation, and several reasonable suggestions to the application of modulus back calculation.

The second wave: estimating the hidden asymptomatic prevalence of COVID-19 in Ireland as we plan for imminent immunisation.

Since the first case of COVID-19 in Ireland was recorded policy makers have introduced mitigation measures to control the spread of infection. Infection is spread by both known cases and hidden, undetected asymptomatic cases.  Asymptomatic individuals are people who transmit the virus but display no clinical symptoms. Current evidence reveals that this population is a major contributing factor to the spread of the disease. There is little or no knowledge of the scale of the hidden prevalence of all infections both asymptomatic and symptomatic in Ireland. Furthermore, as governments plan for the roll out of imminent immunisation programmes, the need to know the scale of the hidden prevalence and hence knowledge of the level of immunisation required is essential. We describe and analyse the numbers of reported cases of COVID-19 in Ireland from the first case in February 2020 to mid-December 2020. Using the method of back-calculation we provide estimates of the asymptomatic prevalence of cases from June to December 2020. The descriptive analysis highlighted two epidemic waves of known cases in the time period. Wave two from June to December included twice as many cases as wave one and cases were significantly younger. The back-calculation estimates of asymptomatic prevalence during this time period revealed that for every case known there was an additional unknown case and total prevalence in wave two was estimated to be approximately 95,000 as opposed to the reported 48,390 cases. As prevalence in wave two is known to be spreading within and from younger age groups the role of mixing patterns on spread needs to be disseminated to the wider public to adequately inform them how personal modifications in behaviour can contribute to the control of the epidemic. While universally imposed lockdowns and mitigation measures may be essential, personal behavioural mixing choices are powerful protectors.

Growth Modeling of the Giant Electric Ray Narcine entemedor in the Southern Gulf of California: Analyzing the Uncertainty of Three Data Sets.

The age and growth rate of the giant electric ray, Narcine entemedor, was estimated using growth bands deposited in the vertebral centra of 245 specimens. Differences in size and age distribution were found between the sexes, a pattern that suggests the annual deposition of band pairs, possibly occurring in April. Multimodel inference and back-calculation were performed to three age data sets of females considering their reproductive cycle and time of capture, among which the von Bertalanffy growth function was found to be the most appropriate (L∞ = 81.87 cm TL, k = 0.17 year-1). Our research supports the idea that age can be determined via biological features such as birth date and growth band periodicity. We concluded that N. entemedor is of a moderate body size, moderate longevity and is a fast-growing elasmobranch species.