Membrane and Performance Study in Polymer Electrolyte Membrane Fuel Cells and Hydrogen Bromine Redox Flow Batteries

This dissertation represents the consideration of the problems of polymer electrolyte membrane fuel cells (PEMFC) and hydrogen-bromine redox flow batteries (RFB). Due to the importance of water management in PEMFCs, all the experiments were strictly controlled at different water hydration conditions. Water uptake and densities were measured for Nafion® and a series of 3M ionomer membranes. The thermodynamics of water and polymer was analyzed based on water uptake experiment and calorimetry. Furthermore, partial molar volumes (PMV) of water/membrane system was defined for the first time and used to analyze the interaction between water and polymers. Three states of water were identified. The performance of hydrogen bromine redox flow batteries was investigated. The experimental conditions were varied and optimized with respects of cell temperature, electrolyte concentration, membrane types and electrode layers. In addition, more detailed study of battery kinetics and transport limit issues was implemented by inserting a dynamic hydrogen reference electrode (DHE). Electrochemical Impedance Spectroscopy (EIS) method was utilized to further separate the losses occurred during battery charging and discharging process. It is believed that the bromine/bromide existence in the membrane, carbon paper electrode and Pt catalyst could harm the cell performance. The effective control of bromine and bromide ions is the key to improve the cell performance

Effect of Asafoetida Extract on Growth and Quality of Pleurotus ferulic

Different concentrations of asafoetida extract were added to the medium of Pleurotus ferulic and the effects of the extract on growth of P. ferulic mycelium and fruiting bodies was observed. As the amount of asafoetida extract additive was increased, the growth of Pleurotus mycelium was faster, the time formation of buds was shorter and that yield of fruiting bodies was stimulated. However, overdosing of asafoetida extract hampered the growth of Pleurotus ferulic. The amino acid composition and volatile components in three kinds of pleurotus’ were contrasted, including wild pleurotus (WP), cultivated pleurotus with asafoetida extract (CPAE) and cultivated pleurotus without asafoetida extract (CP). CPAE with 2.3 g/100 g asafoetida extract addition had the highest content of total amino acids, as well as essential amino acids. WP had a higher content of total amino acids and essential amino acids than CP. In addition, CPAE with 2.3 g/100 g had the highest score of protein content of pleurotus fruiting bodies, while WP had a higher score than CP. In the score of essential amino acid components of pleurotus fruiting bodies, CP had the highest score, while CPAE was higher than WP. Asafoetida extract influenced the volatile components of Pleurotus ferulic greatly, making the volatile components of cultivated pleurotus more similar to those of wild pleurotus (WP)

A CRM1 Inhibitor Alleviates Cardiac Hypertrophy and Increases the Nuclear Distribution of NT-PGC-1α in NRVMs

Chromosomal maintenance 1 (CRM1) inhibitors display antihypertrophic effects and control protein trafficking between the nucleus and the cytoplasm. PGC-1α (peroxisome proliferator-activated receptor gamma coactivator-1alpha) is a type of transcriptional coactivator that predominantly resides in the nucleus and is downregulated during heart failure. NT-PGC-1α is an alternative splicing variant of PGC-1α that is primarily distributed in the cytoplasm. We hypothesized that the use of a CRM1 inhibitor could shuttle NT-PGC-1α into the nucleus and activate PGC-1α target genes to potentially improve cardiac function in a mouse model of myocardial infarction (MI). We showed that PGC-1α and NT-PGC-1α were decreased in MI-induced heart failure mice. Phenylephrine and angiotensin II were applied to induce hypertrophy in neonatal rat ventricular myocytes (NRVMs). The antihypertrophic effects of the CRM1-inhibitor Selinexor was verified through profiling the expression of β-MHC and through visualizing the cell cross-sectional area. NRVMs were transfected with adenovirus-NT-PGC-1α or adenovirus-NLS (nucleus localization sequence)-NT-PGC-1α and then exposed to Selinexor. Confocal microscopy was then used to observe the shuttling of NT-PGC-1α. After NT-PGC-1α was shuttled into the nucleus, there was increased expression of its related genes, including PPAR-α, Tfam, ERR-γ, CPT1b, PDK4, and Nrf2. The effects of Selinexor on post-MI C57BL/6j mice were determined by echocardiography and qPCR. We found that Selinexor showed antihypertrophic effects but did not influence the ejection fraction of MI-mice. Interestingly, the antihypertrophic effects of Selinexor might be independent of NT-PGC-1α transportation

Mitofusin 2 Participates in Mitophagy and Mitochondrial Fusion Against Angiotensin II-Induced Cardiomyocyte Injury

BackgroundMitochondrial dynamics play a critical role in mitochondrial function. The mitofusin 2 (MFN2) gene encodes a mitochondrial membrane protein that participates in mitochondrial fusion to maintain and operate the mitochondrial network. Moreover, MFN2 is essential for mitophagy. In Ang II-induced cardiac remodeling, the combined effects of MFN2-mediated mitochondrial fusion and mitophagy are unclear. This study was designed to explore a novel strategy for preventing cardiomyocyte injury via modulation of mitochondrial dynamics.MethodsWe studied the function of MFN2 in mitochondrial fusion and mitophagy in Ang II-stimulated cardiomyocyte injury. Cardiomyocyte injury experiments, including reactive oxygen species (ROS) production, mitochondrial membrane potential (MMP), and apoptosis rate of cardiomyocytes were performed. The mitochondrial morphology in cardiomyocytes was examined via transmission electron microscopy (TEM) and confocal microscopy. Autophagic levels in response to Ang II were examined by immunoblotting of autophagy-related proteins. Moreover, PINK1/MFN2/Parkin pathway-related proteins were examined.ResultsWith stimulation by Ang II, MFN2 expression was progressively reduced. MFN2 deficiency impaired mitochondrial quality, resulting in exacerbated mitochondrial damage induced by Ang II. The Ang II-induced increases in ROS production and apoptosis rate were alleviated by MFN2 overexpression. Moreover, MFN2 alleviated the Ang II-induced reduction in MMP. MFN2 promoted mitochondrial fusion, and MFN2 promoted Parkin translocation and phosphorylation, leading to mitochondrial autophagy. The effects of MFN2 overexpression were reversed by autophagy inhibitors.ConclusionMitofusin 2 promotes Parkin translocation and phosphorylation, leading to mitophagy to clear damaged mitochondria. However, the beneficial effects of MFN2 were reversed by autophagy inhibitors. Additionally, MFN2 participates in mitochondrial fusion to maintain mitochondrial quality. Thus, MFN2 participated in mitophagy and mitochondrial fusion against Ang II-induced cardiomyocyte injury

Relative Income and Subjective Well-being: an analysis of the relative income effect in the United States and Globally

Past research investigating the relative income effect have found mixed results. In the current research, we test the relative income effect in the United States and globally using large population-level surveys and derive three different types of relative income: geographic median income, demographic median income, and random forest predicted income. Results suggest that while the relative income effect exists in the US, magnitudes of the relative income effect differ depending on the type of relative income derived. Across two studies, random forest predicted income consistently showed the largest magnitude, followed by demographic median income and geographic median income. Further, the relative income effect was found to vary across the globe, with cultural and macroeconomic differences between countries rendering possibilities for causal explanations of variations in the effect

A Hybrid Prediction Model for Solar Radiation Based on Long Short-Term Memory, Empirical Mode Decomposition, and Solar Profiles for Energy Harvesting Wireless Sensor Networks

For power management in the energy harvesting wireless sensor networks (EH-WSNs), it is necessary to know in advance the collectable solar energy data of each node in the network. Our work aims to improve the accuracy of solar energy predictions. Therefore, several existing prediction algorithms in the literature are surveyed, and then this paper proposes a solar radiance prediction model based on a long short-term memory (LSTM) neural network in combination with the signal processing algorithm empirical mode decomposition (EMD). The EMD method is used to decompose the time sequence data into a series of relatively stable component sequences. For improving the prediction accuracy further by utilizing the current day solar radiation profile in one-hour-ahead predictions, similar solar radiation profile data were selected for training LSTM neural networks. Simulation results show that the hybrid model achieves better prediction performance than traditional prediction methods, such as the exponentially-weighted moving average (EWMA), weather conditioned moving average (WCMA), and only LSTM models

Effect of Particles Size on Dielectric Properties of Nano-ZnO/LDPE Composites

The melt blending was used to prepare 3 wt% ZnO/low density polyethylene (ZnO/LDPE) nanocomposites in this article. The effect of different inorganic ZnO particles doping on the dielectrical property and crystal habit of LDPE matrix was explored. The nanoparticles size was 9 nm, 30 nm, 100 nm, and 200 nm respectively. Scanning electron microscope (SEM) was used to characterize ZnO nanoparticles whereas differential scanning calorimetry (DSC) was used to make thermal characterization of the samples. Besides, the AC (alternating current), DC (direct current breakdown characteristics and electrical conductivity of the nanocomposites was studied in this article. The experimental results showed that nano-ZnO/LDPE composites had the advantages such as small crystal size, high crystallization rate and crystallinity owing to nano-ZnO particles doping, when doping nano-ZnO particles size was 30 nm, the ZnO/LDPE nanocomposite crystallinity crest value 39.77% appeared. At the mean time, the DC and AC breakdown field strength values of composites were 138.0 kV/mm and 340.4 kV/mm respectively. They were the maximal values which improved 8.24% and 13.85% than LDPE. The AC breakdown field strength of samples decreased with specimen thickness increase. The DC breakdown field strength of LDPE and ZnO/LDPE composites were greater than AC breakdown field strength. From the conductivity experimental result it could be seen that when the experimental temperature and electric field intensity rose, the current density and conductivity of ZnO/LDPE composites increased with the enlargement of ZnO particles size. But the values were less than which of LDPE

Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform

To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σ B = 1.63 × 10 − 4 ( ° ) , σ L = 1.35 × 10 − 4 ( ° ) , σ H = 15.8 ( m ) , σ s u m = 27.6 ( m ) , where σ B represents the longitude error, σ L represents the latitude error, σ H represents the altitude error, and σ s u m represents the error radius