A semiempirical dynamic model of reversible open circuit voltage drop in a PEM fuel cell

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149313/1/er4127_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149313/2/er4127.pd

Challenges and Opportunities for Second-life Batteries: A Review of Key Technologies and Economy

Due to the increasing volume of Electric Vehicles in automotive markets and the limited lifetime of onboard lithium-ion batteries (LIBs), the large-scale retirement of LIBs is imminent. The battery packs retired from Electric Vehicles still own 70%-80% of the initial capacity, thus having the potential to be utilized in scenarios with lower energy and power requirements to maximize the value of LIBs. However, spent batteries are commonly less reliable than fresh batteries due to their degraded performance, thereby necessitating a comprehensive assessment from safety and economic perspectives before further utilization. To this end, this paper reviews the key technological and economic aspects of second-life batteries (SLBs). Firstly, we introduce various degradation models for first-life batteries and identify an opportunity to combine physics-based theories with data-driven methods to establish explainable models with physical laws that can be generalized. However, degradation models specifically tailored to SLBs are currently absent. Therefore, we analyze the applicability of existing battery degradation models developed for first-life batteries in SLB applications. Secondly, we investigate fast screening and regrouping techniques and discuss the regrouping standards for the first time to guide the classification procedure and enhance the performance and safety of SLBs. Thirdly, we scrutinize the economic analysis of SLBs and summarize the potentially profitable applications. Finally, we comprehensively examine and compare power electronics technologies that can substantially improve the performance of SLBs, including high-efficiency energy transformation technologies, active equalization technologies, and technologies to improve reliability and safety

Immunohistochemical localization of mu opioid receptor in the marginal division with comparison to patches in the neostriatum of the rat brain

<p>Abstract</p> <p>Background</p> <p>Mu opioid receptor (MOR), which plays key roles in analgesia and also has effects on learning and memory, was reported to distribute abundantly in the patches of the neostriatum. The marginal division (MrD) of the neostriatum, which located at the caudomedial border of the neostriatum, was found to stain for enkephalin and substance P immunoreactivities and this region was found to be involved in learning and memory in our previous study. However, whether MOR also exists in the MrD has not yet been determined.</p> <p>Methods</p> <p>In this study, we used western blot analysis and immunoperoxidase histochemical methods with glucose oxidase-DAB-nickel staining to investigate the expression of MOR in the MrD by comparison to the patches in the neostriatum.</p> <p>Results</p> <p>The results from western blot analyses revealed that the antibody to MOR detected a 53 kDa protein band, which corresponded directly to the molecular weight of MOR. Immunohistochemical results showed that punctate MOR-immunoreacted fibers were observed in the "patch" areas in the rostrodorsal part of the neostriatum but these previous studies showed neither labelled neuronal cell bodies, nor were they shown in the caudal part of the neostriatum. Dorsoventrally oriented dark MOR-immunoreactive nerve fibers with individual labelled fusiform cell bodies were firstly observed in the band at the caudomedial border, the MrD, of the neostriatum. The location of the MOR-immunoreactivity was in the caudomedial border of the neostriatum. The morphology of the labelled fusiform neuronal somatas and the dorsoventrally oriented MOR-immunoreacted fibers in the MrD was distinct from the punctate MOR-immunoreactive diffuse mosaic-patterned patches in the neostriatum.</p> <p>Conclusions</p> <p>The results indicated that MOR was expressed in the MrD as well as in patches in the neostriatum of the rat brain, but with different morphological characteristics. The punctate MOR-immunoreactive and diffuse mosaic-patterned patches were located in the rostrodorsal part of the neostriatum. By contrast, in the MrD, the dorsoventrally parallel oriented MOR-immunoreactive fibers with individual labelled fusiform neuronal somatas were densely packed in the caudomedial border of the neostriatum. The morphological difference in MOR immunoreactivity between the MrD and the patches indicated potential functional differences between them. The MOR most likely plays a role in learning and memory associated functions of the MrD.</p

Eco-reliable path finding in time-variant and stochastic networks

This paper addresses a route guidance problem for finding the most eco-reliable path in time-variant and stochastic networks such that travelers can arrive at the destination with the maximum on-time probability while meeting vehicle emission standards imposed by government regulators. To characterize the dynamics and randomness of transportation networks, the link travel times and emissions are assumed to be time-variant random variables correlated over the entire network. A 0–1 integer mathematical programming model is formulated to minimize the probability of late arrival by simultaneously considering the least expected emission constraint. Using the Lagrangian relaxation approach, the primal model is relaxed into a dualized model which is further decomposed into two simple sub-problems. A sub-gradient method is developed to reduce gaps between upper and lower bounds. Three sets of numerical experiments are tested to demonstrate the efficiency and performance of our proposed model and algorithm

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Does the patellar tendon reflex affect the postural stability in stroke patients with blocked vision?

Stroke patients often show postural instability. The patellar tendon reflex is a basic physical examination for stroke patients. This study aimed to explore the correlation between patellar tendon reflex grade and postural stability among stroke patients

Computationally efficient train timetable generation of metro networks with uncertain transfer walking time to reduce passenger waiting time: A generalized Benders decomposition-based method

With more and more interchange stations in a large-scale metro network, passengers tend to transfer between different metro lines from origination to destination, sometimes even more than once. Passenger waiting time is one of the critical standards for measuring the quality of urban public transport services. To support high service quality, this paper proposes a mixed integer nonlinear programming (MINLP) model for the train timetable generation problem of a metro network that minimizes the transfer waiting times and access passenger waiting times. In the mathematical formulation of the model, the transfer walking times at the interchange stations between two connected lines are treated as uncertain parameters. The robust train timetable generation model is formulated to optimize timetables by adjusting arrival and departure times of each train in the metro network to reduce access and transfer passenger waiting times. A robust counterpart is further derived that transforms the formulated robust model into a deterministic one. Moreover, a generalized Benders decomposition technique based approach is developed to decompose the robust counterpart into a subproblem and a master problem. The subproblem is a convex quadratic programming problem that can be solved efficiently. Finally, two sets of numerical examples, consisting of a small case and a large-scale case based on a real-world portion of the Beijing metro network, are performed to demonstrate the validity and practicability of the proposed model and solution approach

DeepEdge: A Novel Appliance Identification Edge Platform for Data Gathering, Capturing and Labeling

With the development of the Internet of Things for smart grid, the requirement for appliance monitoring has become an important topic. The first and most important step in appliance monitoring is to identify the type of appliance. Most of the existing appliance identification platforms are cloud based, thus they consume large computing resources and memory. Therefore, it is necessary to explore an edge identification platform with a low cost. In this work, a novel appliance identification edge platform for data gathering, capturing and labeling is proposed. Experiments show that this platform can achieve an average appliance identification accuracy of 98.5% and improve the accuracy of non-intrusive load disaggregation algorithms