Theoretical Modeling of Protective Oxide Layer Growth in Non-isothermal Lead-Alloys Coolant Systems

The goal of the proposed research project is to provide basic understanding of the protective oxide layer behaviors and to develop oxide layer growth models of steels in non-isothermal leadalloys (lead or lead-bismuth eutectic) coolant systems. It is widely recognized that the corrosiveness of the lead-alloys is a critical obstacle and challenge for which it can be safely used or applied in the nuclear coolant systems. Active oxygen control technique can promote the formation of the “self-healing” oxide films on the structural material surface, drastically reducing steel corrosion and coolant contamination. Many experiments of steels exposed to flowing leadalloys have been carried out to study the protective oxide layer behaviors. However, the experimental data are still very incomplete at present and can not provide the dependence of the oxide behaviors on the system operating temperature, temperature profiles along the lead-alloys loop, oxygen concentration, flow velocity, etc. In addition, oxygen distribution in a nonisothermal lead-alloys coolant system is not well understood. Precise studies and simulations of all hydrodynamics with thermal conditions encountered in practical coolant loop systems by use of different flowing conditions in the laboratory are difficult and expensive, if not impossible. Therefore it is important and necessary to develop theoretical models to predict the protective oxide layer behaviors at the design stage of a practical lead-alloys coolant system, to properly interpret and apply experimental results from test loops, and to provide guidance for optimization in lead-alloys nuclear coolant systems. The research project, therefore, is aimed at filling the gaps of protective oxide layer growth and the oxygen concentration level before lead-alloys nuclear coolant is ready for programmatic implementations and industrial applications

Theoretical Modeling of Protective Oxide Layer Growth in Non-isothermal Lead Alloy Coolant Systems

The goal of the proposed research project is to provide basic understanding of the protective oxide layer behaviors and to develop oxide layer growth models of steels in non-isothermal lead-alloys (lead or lead-bismuth eutectic) coolant systems. Precise studies and simulations of all hydrodynamics with thermal conditions encountered in practical coolant loop systems by use of different flowing conditions in the laboratory are difficult and expensive, if not impossible. Therefore it is important and necessary to develop theoretical models to predict the protective oxide layer behaviors at the design stage of a practical lead-alloy coolant system, to properly interpret and apply experimental results from test loops, and to provide guidance for optimization in lead-alloy nuclear coolant systems. The research project, therefore, is aimed at understanding protective oxide layer growth and the optimal oxygen concentration level before lead-alloy nuclear coolants are ready for programmatic implementations and industrial applications

Influence of ridges for planting sweet potato on symbiotic ecological factors, photosynthetic abilities and population yield in relay intercropping system

Sweet potato (Ipomoea batatas L.) relay intercropping with maize exposes sweet potato to weak levels of sunlight due to the shadow maize creates during the symbiotic period. The insufficient light accordingly causes slow growth and development of vines and leaves of sweet potato in its early stage. The planting density and row direction of maize, the width of the intercropping strip, and the lodging type of sweet potato may form various photo conditions that influence sweet potato. The objective of this experiment was to research the effects of different ridging types on sweet potato and to elucidate the mechanisms of ecological conditions, photosynthetic physiology and intercropping benefits. The results indicated that, contrast to the one wide-ridge with planting two rows of sweet potato and two narrow ridges with planting two rows, mound planting was more superior in many aspects. Through mound planting sweet potato showed a larger range of temperature in air and soil, higher net photosynthetic rate, more active enzymes related with photosynthesis, and more benefits of relay intercropping

Theoretical Modeling of Protective Oxide Layer Growth in Non-isothermal Lead Alloy Coolant Systems

The goal of this research project is to provide a basic understanding of the protective oxide layer behaviors and to develop oxide layer growth models of steels in non-isothermal lead alloys (lead or lead-bismuth eutectic) coolant systems. Precise studies and simulations of all hydrodynamics with thermal conditions encountered in practical coolant loop systems by use of different flowing conditions in the laboratory are difficult and expensive, if not impossible. Therefore it is important and necessary to develop theoretical models to predict the protective oxide layer behaviors at the design stage of a practical lead-alloy coolant system, to properly interpret and apply experimental results from test loops, and to provide guidance for optimization in lead alloys nuclear coolant systems. The research project, therefore, is aimed at filling the gaps of protective oxide layer growth and the oxygen concentration level before lead-alloys nuclear coolant is ready for programmatic implementations and industrial applications

Brain Imaging of Nicotinic Receptors in Alzheimer's Disease

Neuronal nicotinic acetylcholine receptors (nAChRs) are a family of ligand-gated ion channels which are widely distributed in the human brain. Several lines of evidence suggest that two major subtypes (α4β2 and α7) of nAChRs play an important role in the pathophysiology of Alzheimer's disease (AD). Postmortem studies demonstrated alterations in the density of these subtypes of nAChRs in the brain of patients with AD. Currently, nAChRs are one of the most attractive therapeutic targets for AD. Therefore, several researchers have made an effort to develop novel radioligands that can be used to study quantitatively the distribution of these two subtypes in the human brain with positron emission tomography (PET) and single-photon emission computed tomography (SPECT). In this paper, we discuss the current topics on in vivo imaging of two subtypes of nAChRs in the brain of patients with AD

New Noise-Tolerant ZNN Models With Predefined-Time Convergence for Time-Variant Sylvester Equation Solving

Sylvester equation is often applied to various fields, such as mathematics and control systems due to its importance. Zeroing neural network (ZNN), as a systematic design method for time-variant problems, has been proved to be effective on solving Sylvester equation in the ideal conditions. In this paper, in order to realize the predefined-time convergence of the ZNN model and modify its robustness, two new noise-tolerant ZNNs (NNTZNNs) are established by devising two novelly constructed nonlinear activation functions (AFs) to find the accurate solution of the time-variant Sylvester equation in the presence of various noises. Unlike the original ZNN models activated by known AFs, the proposed two NNTZNN models are activated by two novel AFs, therefore, possessing the excellent predefined-time convergence and strong robustness even in the presence of various noises. Besides, the detailed theoretical analyses of the predefined-time convergence and robustness ability for the NNTZNN models are given by considering different kinds of noises. Simulation comparative results further verify the excellent performance of the proposed NNTZNN models, when applied to online solution of the time-variant Sylvester equation

Mobile Charging as a Service: A Reservation-Based Approach

This paper aims to design an intelligent mobile charging control mechanism for Electric Vehicles (EVs), by promoting charging reservations (including service start time, expected charging time, and charging location, etc.). EV mobile charging could be implemented as an alternative recharging solution, wherein charge replenishment is provided by economically mobile plug-in chargers, capable of providing on-site charging services. With intelligent charging management, readily available mobile chargers are predictable and could be efficiently scheduled towards EVs with charging demand, based on updated context collected from across the charging network. The context can include critical information relating to charging sessions as well as charging demand, etc. Further with reservations introduced, accurate estimations on charging demand for a future moment are achievable, and correspondingly, optimal mobile chargersselection can be obtained. Therefore, charging demands across the network can be efficiently and effectively satisfied, with the support of intelligent system-level decisions. In order to evaluate critical performance attributes, we further carry out extensive simulation experiments with practical concerns to verify our insights observed from the theoretical analysis. Results show great performance gains by promoting the reservation-based mobile charger-selection, especially for mobile chargers equipped with suffice power capacity

A Noise-Tolerant Zeroing Neural Network for Time-Dependent Complex Matrix Inversion Under Various Kinds of Noises

Complex-valued time-dependent matrix inversion (TDMI) is extensively exploited in practical industrial and engineering fields. Many current neural models are presented to find the inverse of a matrix in an ideal noise-free environment. However, the outer interferences are normally believed to be ubiquitous and avoidable in practice. If these neural models are applied to complex-valued TDMI in a noise environment, they need to take a lot of precious time to deal with outer noise disturbances in advance. Thus, a noise-suppression model is urgent to be proposed to address this problem. In this article, a complex-valued noise-tolerant zeroing neural network (CVNTZNN) on the basis of an integral-type design formula is established and investigated for finding complex-valued TDMI under a wide variety of noises. Furthermore, both convergence and robustness of the CVNTZNN model are carefully analyzed and rigorously proved. For comparison and verification purposes, the existing zeroing neural network (ZNN) and gradient neural network (GNN) have been presented to address the same problem under the same conditions. Numerical simulation consequences demonstrate the effectiveness and excellence of the proposed CVNTZNN model for complex-valued TDMI under various kinds of noises, by comparing the existing ZNN and GNN models

Recent Advancements and Remaining Challenges Associated With Inner Magnetosphere Cross‐Energy/Population Interactions (IMCEPI)

The geospace inner magnetosphere, within about 10 Earth radii, contains various plasma populations with energy from a few electron volts to megaelectron volts and plays important roles in regulating the energy density of the magnetosphere, the magnetic field configuration, and wave dynamics. As an integrated part of the magnetosphere, the inner magnetosphere region also ties to other regions and can change the global geospace circulation. Therefore, understanding both internal and external cross‐energy/population interactions can help further our knowledge of the inner magnetosphere dynamics and nonlinear feedback processes. In view of this, in the past 5 years (2014–2018), the Geospace Environment Modeling (GEM) Focus Group “inner magnetosphere cross‐energy/population interactions (IMCEPI)” has gathered and boosted community‐wide interactions among observation, simulation, and modeling studies. This commentary reports some major accomplishments of the interactive inner magnetosphere community that were advanced by the IMCEPI Focus Group discussions and layouts remaining challenges that need to be carried on.Key PointsAdvancements on first‐principle ring current models, new empirical models on IM fields/waves/plasma and application of innovative techniquesAdvanced knowledge of IM characteristics, e.g., compositions, fields, coupling with ionosphere/tail region, and wave particle interactionsChallenges remain in numerical representation of IM and its linkage with other related areas; validation needed across various IM modelsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148385/1/jgra54772_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148385/2/jgra54772.pd

Association Between the Ratio of Ovarian Stimulation Duration to Original Follicular Phase Length and In Vitro Fertilization Outcomes: A Novel Index to Optimise Clinical Trigger Time

The duration of ovarian stimulation which is largely dependent on the ovarian response to hormonal stimulation may influence in vitro fertilization (IVF) outcomes. Menstrual cycle length is potentially a good indicator of ovarian reserve and can predict ovarian response. Ovarian stimulation and the follicular phase of the menstrual cycle are both processes of follicular development. There is no published research to predict the duration of ovarian stimulation based on the length of the menstrual cycle. Our retrospective cohort study included 6110 women with regular menstrual cycles who underwent their first IVF treatment between January 2015 and October 2020. Cycles were classified according to quartiles of the ratio of ovarian stimulation duration to original follicular phase length (OS/FP). Multivariate generalized linear models were applied to assess the association between OS/FP and IVF outcomes. The odds ratio (OR) or relative risk (RR) was estimated for each quartile with the lowest quartile as the comparison group. OS/FP of 0.67 to 0.77 had more retrieved and mature oocytes (adjusted RR 1.11, 95% confidence interval [CI] 1.07–1.15, p for trend = 0.001; adjusted RR 1.14, 95% CI 1.09–1.19, p for trend = 0.001). OS/FP of 0.67 to 0.77 showed the highest rate of fertilization (adjusted OR 1.11, 95% CI 1.05–1.17, p for trend = 0.001). OS/FP > 0.77 had the lowest rate of high-quality blastocyst formation (adjusted OR 0.81, 95% CI 0.71–0.93, p for trend = 0.01). No apparent association was noted between OS/FP and clinical pregnancy, live birth, or early miscarriage rate. In conclusion, OS/FP has a significant effect on the number of oocytes, fertilization rate, and high-quality blastocyst formation rate. MCL could be used to predict the duration of ovarian stimulation with an OS/FP of 0.67 to 0.77, which provides a new indicator for the individualized clinical optimization of the trigger time