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

Prognostic and immunological significance of calcium-related gene signatures in renal clear cell carcinoma

Background: Calcium signaling is implicated in multiple processes including immune response that important in tumor progression. Kidney renal clear cell carcinoma (KIRC) is the most frequent histological type of renal cell carcinoma with up to a third of cases develop metastases. As a result of a lack of in-depth understanding of the mechanisms underlying KIRC, treatment options have been limited. Here, we aim to comprehensively investigate the landscape of Ca2+ channels, pumps and exchangers in KIRC patients.Methods: The mRNA expression profiles and gene variations of 58 calcium-related genes (CRGs) in KIRC patients and normal control cases were downloaded from TCGA database. CRGs-related risk score was constructed to quantify calcium patterns by using least absolute shrinkage and selection operator (LASSO) regression. The prognostic value, biological functions, immune landscape and therapeutic sensitivities based on CRGs-related risk score were then evaluated using multiple methods. Finally, key gene of CRGs was identified by weighted gene co-expression network analysis (WGCNA). TCGA-CPTAC, GSE53757 datasets, as well as human tissues were used for validation.Results: KIRC patients had significant differences in CRG expression, prognosis, and biological functions between two CRG clusters. CRGs-related risk score was then determined. The prognosis, tumor mutation burden, immune cell infiltration, immune checkpoints, and the response of targeted inhibitors were remarkably different between high and low CRGs-related risk subtypes. CRGs-related high-risk subtype was characterized by immunosuppressive microenvironment with poor prognosis. Meanwhile, several targeted drugs showed distinct sensitivity between CRGs-related risk subtypes. Finally, TRPM3 was identified as a key CRG based on risk score in KIRC patients. TRPM3 mRNA and protein expression were significantly lower in KIRC tumors than in normal controls. Low TRPM3 expression was associated with poor prognosis in KIRC patients.Conclusion: Our study highlighted the promising prognostic value of CRGs in KIRC tumors. The evaluation of CRGs-related risk score will contribute to predicting prognosis and clinical therapy in KIRC patients

Simulation of carbon peaking process of high energy consuming manufacturing industry in Shaanxi Province: A hybrid model based on LMDI and TentSSA-ENN

To achieve the goals of carbon peaking and carbon neutrality in Shaanxi, the high energy consuming manufacturing industry (HMI), as an important contributor, is a key link and important channel for energy conservation. In this paper, the logarithmic mean Divisia index (LMDI) method is applied to determine the driving factors of carbon emissions from the aspects of economy, energy and society, and the contribution of these factors was analyzed. Meanwhile, the improved sparrow search algorithm is used to optimize Elman neural network (ENN) to construct a new hybrid prediction model. Finally, three different development scenarios are designed using scenario analysis method to explore the potential of HMI in Shaanxi Province to achieve carbon peak in the future. The results show that: (1) The biggest promoting factor is industrial structure, and the biggest inhibiting factor is energy intensity among the drivers of carbon emissions, which are analyzed effectively in HMI using the LMDI method. (2) Compared with other neural network models, the proposed hybrid prediction model has higher accuracy and better stability in predicting industrial carbon emissions, it is more suitable for simulating the carbon peaking process of HMI. (3) Only in the coordinated development scenario, the HMI in Shaanxi is likely to achieve the carbon peak in 2030, and the carbon emission curve of the other two scenarios has not reached the peak. Then, according to the results of scenario analysis, specific and evaluable suggestions on carbon emission reduction for HMI in Shaanxi are put forward, such as optimizing energy and industrial structure and making full use of innovative resources of Shaanxi characteristic units

Time Sequence Map for Interpreting the Thermal Runaway Mechanism of Lithium-Ion Batteries With LiNixCoyMnzO2 Cathode

Thermal runaway is one of the key failure reasons for the lithium-ion batteries. The potential of thermal runaway in applications increases when the industry starts to use high energy LiNixCoyMnzO2 cathode. The thermal runaway mechanism is still unclear, because the side reactions are complex. Heat generation during thermal runaway can be caused by the decomposition of individual cell components, or by interactive reactions between multiple components. This paper tries to comb the heat sources during thermal runaway using a novel method named the “Time Sequence Map” (TSM). The TSM tracks the heat sources according to the notion of thermodynamic systems. The thermodynamic system means a combination of materials that stay and react together, and generate heat independently without interruptions from other thermodynamic systems. With the help of the defined thermodynamic systems, researchers will be rescued from being trapped in the complex reactions, and the heat sources during thermal runaway can be clearly explained from bottom up. The thermal runaway results for two battery samples demonstrate the validity of the TSM. The TSM shows the heat sources including that: (1) fire, (2) internal short circuit, (3) oxidation-reduction reaction between the cathode and anode, etc. The contributions for the heat sources to the thermal runaway are further discussed. Conclusions come to: (1) the major heat source is the oxidation-reduction reaction; (2) the fire releases lots of heat, but most of the heat is not to heat the cell itself; (3) the internal short circuit is critical to trigger the oxidation-reduction reaction; (4) the internal short circuit is not the major heat source that heat the cell to 800°C or higher; (5) the oxidation-reduction reaction is triggered when the temperature reaches a critical temperature. The TSM helps depict the frontiers in the researches of battery thermal runaway. It suggests that we focus on: (1) the relationship between internal short circuit and thermal runaway; (2) the mechanism of the oxidation-reduction reaction between the cathode and anode; (3) the detailed reaction mechanisms for a specific thermodynamic system within the cell

A win-win marginal rent analysis for operator and consumer under battery leasing mode in China electric vehicle market

Recently battery leasing has been introduced into the market by automobile manufacturers and power suppliers due to its potential to reduce the purchase cost of electric vehicles (EVs). However, the profit prospect of battery leasing is still uncertain. This paper takes the views of both the operators and consumers and calculates the 'win-win' marginal rent, which not only ensures the profitability of operators, but also allows consumers a lower expenditure than using Internal combustion engine vehicles (ICVs) and EVs with embedded batteries. Battery cost, vehicle weight, gasoline and electricity price, and the discount rate have impacts on the rent. Battery cost plays a dominant role and a battery cost >5 ¥/W h fails to enable the survival of battery leasing to all types of EVs. Battery leasing would be more competitive when focusing on heavier EVs. At least one of the three thresholds is required for the existence of rent pricing range for a 1000 kg EV: gasoline retail price >6 ¥/L, electricity priceWin-win marginal rent EV battery leasing China market

Binary Morphological Filtering of Dominant Scattering Area Residues for SAR Target Recognition

A synthetic aperture radar (SAR) target recognition method is proposed in this study based on the dominant scattering area (DSA). DSA is a binary image recording the positions of the dominant scattering centers in the original SAR image. It can reflect the distribution of the scattering centers as well as the preliminary shape of the target, thus providing discriminative information for SAR target recognition. By subtracting the DSA of the test image with those of its corresponding templates from different classes, the DSA residues represent the differences between the test image and various classes. To further enhance the differences, the DSA residues are subject to the binary morphological filtering, i.e., the opening operation. Afterwards, a similarity measure is defined based on the filtered DSA residues after the binary opening operation. Considering the possible variations of the constructed DSA, several different structuring elements are used during the binary morphological filtering. And a score-level fusion is performed afterwards to obtain a robust similarity. By comparing the similarities between the test image and various template classes, the target label is determined to be the one with the maximum similarity. To validate the effectiveness and robustness of the proposed method, experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and compared with several state-of-the-art SAR target recognition methods

Energy flow modeling and real-time control design basing on mean values for maximizing driving mileage of a fuel cell bus

This paper proposes an energy flow model and an optimal energy management strategy based on mean values for maximizing driving mileage of a fuel cell bus (FCB), which is powered by a polymer electrolyte membrane (PEM) fuel cell system and a lithium battery. Firstly, an energy flow model describing the relations between vehicle performance and power flow parameters is quantitatively established. An optimization problem for maximizing driving mileage on a predetermined route is defined, and an analytical solution with clear physical meanings is derived. Next, a practical real-time supervisory Energy Management strategy basing on Mean Values (EMMV) is proposed. The strategy, which doesn't require a priori knowledge of the driving trip, is then compared with several well-known strategies, e.g. charge depleting and charge-sustaining (CDCS), Blended, dynamic programming (DP), and Pontryagin's Minimum Principle (PMP). Simulation results show that, the proposed strategy achieves a near-optimal effect, and converges after one driving cycle on a predetermined bus route. Finally, on-road testing is carried out. The proposed strategy achieves an average endurance mileage on a real bus route of 162 km with a usable battery state of charge (SOC) of 90% and 20 kg hydrogen gas for a fully loaded fuel cell city bus