Molecular modeling of perfluoro compounds

Perfluoro compounds receive much attention due to their distinctive properties and multiple applications. Consequently, it would be of great interest to be able to model those applications with molecular simulation techniques. To achieve this goal, a realistic potential model is needed. For perfluoroalkanes, such a model has been developed and reported. However, for perfluoroethers, no such model currently exists. In the first part of this work, a preliminary model, based on ab initio calculations and Gibbs ensemble phase equilibrium calculations, was developed for a single perfluoroether, perfluoromethylpropylether; this work has been accepted for publication. Then, using the above methods plus an extension of the Gibbs-Duhem integration method, a realistic united atom potential model has been developed and then optimized using all available vapor-liquid phase equilibrium data for perfluoroethers. This model is composed of a harmonic function for the bond bending potential, a 7th order polynomial function of cosine (l) for the torsional potential, partial charge, and Columbic interaction for the long-range interaction, and Lennard-Jones potential for van der Waals interaction. This model has been shown to reproduce the phase envelope and the critical properties of the perfluoroethers reasonably well

A Dynamic Growth Model for Flows of Foreign Direct Investment

In this work, we for the first time study the dynamic flows of the foreign direct investment (FDI) with a dynamic growth theory. We define the FDI flow as a process which transmits throughout a given social system by way of diverse communication channels. In model formulation, seven assumptions are thus proposed and the foreign capital policy of the host country is considered as an external influence; in addition, the investment policy of the investing country is modeled as an internal influence. Classification of influences is mainly according to the operational strategy as well as the consideration of economical/financial factors. The dynamic model of FDI flow is a differential equation which is solved numerically and verified with collected realistic data. Application of the developed model to explore, taking the electronics industry in Taiwan as an example, Taiwanese direct investment (TDI) in China (i.e. FDI flows from Taiwan to China) since 2001 is conducted. Our preliminary results successfully account for the dynamics of FDI flow for different amount of TDI outflows. It is found that the internal influence dominates the growth of TDI flow from Taiwan to China during 2001-2006.Foreign direct investment, dynamic flow theory, growth model, and numerical simulation

Efficient calibration for imperfect epidemic models with applications to the analysis of COVID-19

The estimation of unknown parameters in simulations, also known as calibration, is crucial for practical management of epidemics and prediction of pandemic risk. A simple yet widely used approach is to estimate the parameters by minimizing the sum of the squared distances between actual observations and simulation outputs. It is shown in this paper that this method is inefficient, particularly when the epidemic models are developed based on certain simplifications of reality, also known as imperfect models which are commonly used in practice. To address this issue, a new estimator is introduced that is asymptotically consistent, has a smaller estimation variance than the least squares estimator, and achieves the semiparametric efficiency. Numerical studies are performed to examine the finite sample performance. The proposed method is applied to the analysis of the COVID-19 pandemic for 20 countries based on the SEIR (Susceptible-Exposed-Infectious-Recovered) model with both deterministic and stochastic simulations. The estimation of the parameters, including the basic reproduction number and the average incubation period, reveal the risk of disease outbreaks in each country and provide insights to the design of public health interventions

Advancing inverse scattering with surrogate modeling and Bayesian inference for functional inputs

Inverse scattering aims to infer information about a hidden object by using the received scattered waves and training data collected from forward mathematical models. Recent advances in computing have led to increasing attention towards functional inverse inference, which can reveal more detailed properties of a hidden object. However, rigorous studies on functional inverse, including the reconstruction of the functional input and quantification of uncertainty, remain scarce. Motivated by an inverse scattering problem where the objective is to infer the functional input representing the refractive index of a bounded scatterer, a new Bayesian framework is proposed. It contains a surrogate model that takes into account the functional inputs directly through kernel functions, and a Bayesian procedure that infers functional inputs through the posterior distribution. Furthermore, the proposed Bayesian framework is extended to reconstruct functional inverse by integrating multi-fidelity simulations, including a high-fidelity simulator solved by finite element methods and a low-fidelity simulator called the Born approximation. When compared with existing alternatives developed by finite basis expansion, the proposed method provides more accurate functional recoveries with smaller prediction variations

A generalized Gaussian process model for computer experiments with binary time series

Non-Gaussian observations such as binary responses are common in some computer experiments. Motivated by the analysis of a class of cell adhesion experiments, we introduce a generalized Gaussian process model for binary responses, which shares some common features with standard GP models. In addition, the proposed model incorporates a flexible mean function that can capture different types of time series structures. Asymptotic properties of the estimators are derived, and an optimal predictor as well as its predictive distribution are constructed. Their performance is examined via two simulation studies. The methodology is applied to study computer simulations for cell adhesion experiments. The fitted model reveals important biological information in repeated cell bindings, which is not directly observable in lab experiments.Comment: 49 pages, 4 figure

An empirical study of the impact of internet financial reporting on stock prices

This study examines the economic consequences of internet financial reporting (IFR) in Taiwan. The results show that the stock prices of IFR firms change more quickly than those of the non-FR firms using Akaike’s (1969) Final Prediction Error (FPE) methodology. Second, the results from the event study methodology show that the cumulative abnormal returns of the firms with IFR are significantly higher than those of the firms without IFR. Lastly, the results indicate that firms with a higher degree of information transparency yield a higher abnormal return on theirstock prices

The role of immunonutrients in the prevention of necrotizing enterocolitis in preterm very low birth weight infants

Necrotizing enterocolitis (NEC) is a critical intestinal emergency condition, which mainly occurs in preterm very low birth weight (PVLBW) infants. Despite remarkable advances in the care of PVLBW infants, with considerable improvement of the survival rate in recent decades, the incidence of NEC and NEC-related mortality have not declined accordingly. The fast progression from nonspecific signs to extensive necrosis also makes primary prevention the first priority. Recently, increasing evidence has indicated the important role of several nutrients in primary prevention of NEC. Therefore, the aim of this review is to summarize some potential immunomodulatory nutrients in the prevention of NEC, including bovine colostrum, probiotics, prebiotics (e.g., human milk oligosaccharides), long chain polyunsaturated fatty acids, and amino acids (glutamine, cysteine and N-acetylcysteine, l-arginine and l-citrulline). Based on current research evidence, probiotics are the most documented effective method to prevent NEC, while others still require further investigation in animal studies and clinical randomized controlled trials

Asic3−/− Female Mice with Hearing Deficit Affects Social Development of Pups

BACKGROUND: Infant crying is an important cue for mothers to respond adequately. Inappropriate response to infant crying can hinder social development in infants. In rodents, the pup-mother interaction largely depends on pup's calls. Mouse pups emit high frequency to ultrasonic vocalization (2-90 kHz) to communicate with their dam for maternal care. However, little is known about how the maternal response to infant crying or pup calls affects social development over the long term. METHODOLOGY/PRINCIPAL FINDINGS: Here we used mice lacking acid-sensing ion channel 3 (Asic3(-/-)) to create a hearing deficit to probe the effect of caregiver hearing on maternal care and adolescent social development. Female Asic3(-/-) mice showed elevated hearing thresholds for low to ultrasonic frequency (4-32 kHz) on auditory brain stem response, which thus hindered their response to their pups' wriggling calls and ultrasonic vocalization, as well as their retrieval of pups. In adolescence, pups reared by Asic3(-/-) mice showed a social deficit in juvenile social behaviors as compared with those reared by wild-type or heterozygous dams. The social-deficit phenotype in juvenile mice reared by Asic3(-/-) mice was associated with the reduced serotonin transmission of the brain. However, Asic3(-/-) pups cross-fostered to wild-type dams showed rescued social deficit. CONCLUSIONS/SIGNIFICANCE: Inadequate response to pups' calls as a result of ASIC3-dependent hearing loss confers maternal deficits in caregivers and social development deficits in their young