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To satisfy the high-rate power demand fluctuations in the complicated driving cycle, electric vehicle (EV) energy storage systems should have both high power density and high energy density. In order to obtain better energy and power performances, a combination of battery and supercapacitor are utilized in this work to form a semi-active hybrid energy storage system (HESS). A parameter matching method of battery-supercapacitor HESS for electric vehicles (EVs) is proposed. This method can meet the performance indicators of EVs in terms of power and energy for parameter matching. The result shows that optimized parameter matching is obtained by reducing the weight and cost.

The shape memory alloy (SMA) actuator is widely used in aerospace, medical and robot fields because of its advantages of low driving voltage, large driving force, no noise and high-power–weight ratio. Therefore, it is of great significance to establish the theoretical model of the SMA actuator and analyze the driving characteristics of the SMA actuator. On the basis of summarizing the constitutive model of the shape memory alloy spring, the phase transformation dynamics model of SMA including the minor hysteresis loop is established using the Duhem model in this paper, and the theoretical models of the bias and differential SMA spring actuator are established. At the same time, a PID position controller including anti-saturation and anti-overheating functions is proposed to control the position of the SMA actuator. Finally, the position control simulation model of the SMA spring actuator is established and simulated. Simulation results show that the position of the SMA actuator can be well controlled by using the model and control method established in this paper.

Background Measles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States. Clustering of disease susceptibility can threaten herd immunity and impact the likelihood of disease outbreaks in a highly vaccinated population. Previous studies have examined the role of contact tracing to control infectious diseases among clustered populations, but have not explicitly modeled the public health response using an agent-based model. Methods We developed an agent-based simulation model of measles transmission using the Framework for Reconstructing Epidemiological Dynamics (FRED) and the Synthetic Population Database maintained by RTI International. The simulation of measles transmission was based on interactions among individuals in different places: households, schools, daycares, workplaces, and neighborhoods. The model simulated different levels of immunity clustering, vaccination coverage, and contact investigations with delays caused by individuals’ behaviors and/or the delay in a health department’s response. We examined the effects of these characteristics on the probability of uncontrolled measles outbreaks and the outbreak size in 365 days after the introduction of one index case into a synthetic population. Results We found that large measles outbreaks can be prevented with contact investigations and moderate contact rates by having (1) a very high vaccination coverage (≥ 95%) with a moderate to low level of immunity clustering (≤ 0.5) for individuals aged less than or equal to 18 years, or (2) a moderate vaccination coverage (85% or 90%) with no immunity clustering for individuals (≤18 years of age), a short intervention delay, and a high probability that a contact can be traced. Without contact investigations, measles outbreaks may be prevented by the highest vaccination coverage with no immunity clustering for individuals (≤18 years of age) with moderate contact rates; but for the highest contact rates, even the highest coverage with no immunity clustering for individuals (≤18 years of age) cannot completely prevent measles outbreaks. Conclusions The simulation results demonstrated the importance of vaccination coverage, clustering of immunity, and contact investigations in preventing uncontrolled measles outbreaks.

Introduction: With the aggravation of aging and the growing number of stroke patients suffering from hemiplegia in China, rehabilitation robots have become an integral part of rehabilitation training. However, traditional rehabilitation robots cannot modify the training parameters adaptively to match the upper limbs’ rehabilitation status automatically and apply them in rehabilitation training effectively, which will improve the efficacy of rehabilitation training. Methods: In this study, a two-degree-of-freedom flexible drive joint rehabilitation robot platform was built. The forgetting factor recursive least squares method (FFRLS) was utilized to estimate the impedance parameters of human upper limb end. A reward function was established to select the optimal stiffness parameters of the rehabilitation robot. Results: The results confirmed the effectiveness of the adaptive impedance control strategy. The findings of the adaptive impedance control studies showed that the adaptive impedance control had a significantly greater reward than the constant impedance control, which was in line with the simulation results of the variable impedance control. Moreover, it was observed that the levels of robot assistance could be suitably modified based on the subject’s different participation. Discussion: The results facilitated stroke patients’ upper limb rehabilitation by enabling the rehabilitation robot to adaptively change the impedance parameters according to the functional status of the affected limb. In clinic therapy, the proposed control strategy may help to adjust the reward function for different patients to improve the rehabilitation efficacy eventually.

Inhibitor of κB kinase (IKK) family proteins are key signaling molecules in the animal innate immune system and are considered master regulators of inflammation and innate immunity that act by controlling the activation of transcription factors such as NF-κB. However, few functional studies on IKK in invertebrates have been conducted, especially in marine mollusks. In this study, we cloned the IKK gene in the Zhikong scallop Chlamys farreri and named it CfIKK3 . CfIKK3 encodes a 773-amino acid-long protein, and phylogenetic analysis showed that CfIKK3 belongs to the invertebrate TBK1/IKKϵ protein family. Quantitative real-time PCR analysis showed that CfIKK3 mRNA is ubiquitously expressed in all tested scallop tissues. The expression of CfIKK3 transcripts was significantly induced after challenge with lipopolysaccharide, peptidoglycan, or poly(I:C). Co-immunoprecipitation (co-IP) assays confirmed the direct interaction of CfIKK3 with MyD88 (the key adaptor in the TLR pathway) and MAVS (the key adaptor in the RLR pathway), suggesting that this IKK protein plays a crucial role in scallop innate immune signal transduction. In addition, the CfIKK3 protein formed homodimers and bound to CfIKK2, which may be a key step in the activation of its own and downstream transcription factors. Finally, in HEK293T cells, dual-luciferase reporter gene experiments showed that overexpression of CfIKK3 protein activated the NF-κB reporter gene in a dose-dependent manner. In conclusion, our experimental results confirmed that CfIKK3 could respond to PAMPs challenge and participate in scallop TLR and RLR pathway signaling, ultimately activating NF-κB. Therefore, as a key signaling molecule and modulator of immune activity, CfIKK3 plays an important role in the innate immune system of scallops.

Measles cases continue to occur despite its elimination status in the United States. To control transmission, public health officials confirm the measles diagnosis, identify close contacts of infectious cases, deliver public health interventions (i.e., post-exposure prophylaxis) among those who are eligible, and follow-up with the close contacts to determine overall health outcomes. A stochastic network simulation of measles contact tracing was conducted using existing agent-based modeling software and a synthetic population with high levels of immunity in order to estimate the impact of different interventions in controlling measles transmission. The synthetic population was created to simulate California`s population in terms of population demographics, household, workplace, school, and neighborhood characteristics using California Department of Finance 2010 census data. Parameters for the model were obtained from a review of the literature, California measles case surveillance data, and expert opinion. Eight different scenarios defined by the use of three different public health interventions were evaluated: (a) post-exposure measles, mumps, and rubella (MMR) vaccine, (b) post-exposure immune globulin (IG), and (c) voluntary isolation and home quarantine in the presence or absence of public health response delays. Voluntary isolation and home quarantine coupled with one or two other interventions had the greatest reduction in the number of secondary cases infected by the index case and the probability of escape situations (i.e., the outbreak continues after 90 days). Interrupting contact patterns via voluntary isolation and home quarantine are particularly important in reducing the number of secondary cases infected by the index case and the probability of uncontrolled outbreaks.

We conducted an expert survey of leprosy (Hansen's Disease) and neglected tropical disease experts in February 2016. Experts were asked to forecast the next year of reported cases for the world, for the top three countries, and for selected states and territories of India. A total of 103 respondents answered at least one forecasting question. We elicited lower and upper confidence bounds. Comparing these results to regression and exponential smoothing, we found no evidence that any forecasting method outperformed the others. We found evidence that experts who believed it was more likely to achieve global interruption of transmission goals and disability reduction goals had higher error scores for India and Indonesia, but lower for Brazil. Even for a disease whose epidemiology changes on a slow time scale, forecasting exercises such as we conducted are simple and practical. We believe they can be used on a routine basis in public health.

Distributions were derived from Holt-Winters, regression (ordinary least squares for the world data, linear mixed effects regression for the three countries), and expert survey. The median is indicated with a white dot; the bright central band (orange, yellow, green, respectively) corresponds to the interquartile region, and the remainder of the 95 percent central coverage region is indicated by the darker region (brown, olive, dark green, respectively).

The 2014-2015 Ebola outbreak is the largest and most widespread to date. In order to estimate ongoing transmission in the affected countries, we estimated the weekly average number of secondary cases caused by one individual infected with Ebola throughout the infectious period for each affected West African country using a stochastic hidden Markov model fitted to case data from the World Health Organization. If the average number of infections caused by one Ebola infection is less than 1.0, the epidemic is subcritical and cannot sustain itself. The epidemics in Liberia and Sierra Leone have approached subcriticality at some point during the epidemic; the epidemic in Guinea is ongoing with no evidence that it is subcritical. Response efforts to control the epidemic should continue in order to eliminate Ebola cases in West Africa.