Multiple morbidities in companion dogs: a novel model for investigating age-related disease

The proportion of men and women surviving over 65 years has been steadily increasing over the last century. In their later years, many of these individuals are afflicted with multiple chronic conditions, placing increasing pressure on healthcare systems. The accumulation of multiple health problems with advanced age is well documented, yet the causes are poorly understood. Animal models have long been employed in attempts to elucidate these complex mechanisms with limited success. Recently, the domestic dog has been proposed as a promising model of human aging for several reasons. Mean lifespan shows twofold variation across dog breeds. In addition, dogs closely share the environments of their owners, and substantial veterinary resources are dedicated to comprehensive diagnosis of conditions in dogs. However, while dogs are therefore useful for studying multimorbidity, little is known about how aging influences the accumulation of multiple concurrent disease conditions across dog breeds. The current study examines how age, body weight, and breed contribute to variation in multimorbidity in over 2,000 companion dogs visiting private veterinary clinics in England. In common with humans, we find that the number of diagnoses increases significantly with age in dogs. However, we find no significant weight or breed effects on morbidity number. This surprising result reveals that while breeds may vary in their average longevity and causes of death, their age-related trajectories of morbidities differ little, suggesting that age of onset of disease may be the source of variation in lifespan across breeds. Future studies with increased sample sizes and longitudinal monitoring may help us discern more breed-specific patterns in morbidity. Overall, the large increase in multimorbidity seen with age in dogs mirrors that seen in humans and lends even more credence to the value of companion dogs as models for human morbidity and mortality

Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets

A fundamental problem in thermodynamics is the recovery of macroscopic equilibrated interaction energies from experimentally measured single-molecular interactions. The Jarzynski equality forms a theoretical basis in recovering the free energy difference between two states from exponentially averaged work performed to switch the states. In practice, the exponentially averaged work value is estimated as the mean of finite samples. Numerical simulations have shown that samples having thousands of measurements are not large enough for the mean to converge when the fluctuation of external work is above 4 kBT, which is easily observable in biomolecular interactions. We report the first example of a statistical gamma work distribution applied to single molecule pulling experiments. The Gibbs free energy of surface adsorption can be accurately evaluated even for a small sample size. The values obtained are comparable to those derived from multi-parametric surface plasmon resonance measurements and molecular dynamics simulations

Estimating Diagnosis Time of Emergency Situations in Digitalized Control Rooms

To secure the quality of a human reliability analysis regarding digitalized control rooms, it is necessary to obtain the empirical data of human behaviors in a digitalized environment. As a preliminary study of human performance in digitalized control rooms, we empirically estimated the time for diagnosis of emergency situations. From the full-scope simulators for APR1400, equipped with fully digitalized interface systems, the diagnosis time of human operators were extracted. The operators should follow the procedure of standard post-trip action and identify the causes of the emergency situations using the diagnosis procedure. From the time records including the procedure progression time, the basic statistics of the diagnosis time were produced and the parametric distribution best fitted to the data was derived. From the findings, the operational characteristics of human operators in digitalized control rooms were discussed

Epidemic models for plants infection under mixed effects of temperature and wetness

peer reviewedaudience: researcher, professional, student, popularization, otherThis paper deals with modeling and fitting for epidemic models and their applications to the field of plants disease. For this purpose, two models are proposed that are expressed as a blend of two functions which reflect the effect of the temperature and the wetness. In addition, we provide an original method to _t the proposed models by employing simple techniques that can constitute an easy-to-use tool for simulation, prediction and/or control. Moreover, the method accuracy and efficiency are evaluated for some reported works in the literature. Computational results are provided to show the validity and effectiveness of the proposed epidemic models for some plant infections