ON THE FORMATION OF CZTS (CU2ZNSNS4) BASED FILMS FOR PHOTOVOLTAIC APPLICATIONS

Ph.DDOCTOR OF PHILOSOPH

Exploring the Correlation Between Ultrasound Speed and the State of Health of LiFePO4_4 Prismatic Cells

Electric vehicles (EVs) have become a popular mode of transportation, with their performance depending on the ageing of the Li-ion batteries used to power them. However, it can be challenging and time-consuming to determine the capacity retention of a battery in service. A rapid and reliable testing method for state of health (SoH) determination is desired. Ultrasonic testing techniques are promising due to their efficient, portable, and non-destructive features. In this study, we demonstrate that ultrasonic speed decreases with the degradation of the capacity of an LFP prismatic cell. We explain this correlation through numerical simulation, which describes wave propagation in porous media. We propose that the reduction of binder stiffness can be a primary cause of the change in ultrasonic speed during battery ageing. This work brings new insights into ultrasonic SoH estimation techniques

An Empirical Air-to-Ground Channel Model Based on Passive Measurements in LTE

In this paper, a recently conducted measurement campaign for unmanned-aerial-vehicle (UAV) channels is introduced. The downlink signals of an in-service long-time-evolution (LTE) network which is deployed in a suburban scenario were acquired. Five horizontal and five vertical flight routes were considered. The channel impulse responses (CIRs) are extracted from the received data by exploiting the cell specific signals (CRSs). Based on the CIRs, the parameters of multipath components (MPCs) are estimated by using a high-resolution algorithm derived according to the space-alternating generalized expectation-maximization (SAGE) principle. Based on the SAGE results, channel characteristics including the path loss, shadow fading, fast fading, delay spread and Doppler frequency spread are thoroughly investigated for different heights and horizontal distances, which constitute a stochastic model.Comment: 15 pages, submitted version to IEEE Transactions on Vehicular Technology. Current status: Early acces

Effect of recombinant human erythropoietin expressions of apoptosis genes in rats following traumatic brain injury

Purpose: To explore the effect of recombinant human erythropoietin (r-HuEPO) on apoptosis in rats after traumatic brain injury.Methods: A total of 48 traumatic brain-injured Sprague Dawley (SD) rats were obtained by improved Feeney’s traumatic brain injury model, and were randomly divided into four groups: normal salinetreated rats (control) and rats treated with r-HuEPO at doses of 1000 U/kg, 3000 U/kg and 5000 U/kg. Brain tissues were collected on the 7th day after trauma surgery. Apoptotic cells, and NF-kappa B (NFĸB)-, c-myc-, and Fas/Fasl-positive cells were identified in brain tissues by immunohistochemical assay.Results: After treatment with r-HuEPO (3000 and 5000 U/kg), expression of NF-κB and Fas/Fasl were significantly decreased (p < 0.05) compared to control rats, especially at the 5000 U/kg dose (p < 0.01). However, for c-myc, no significant difference was observed between r-HuEPO treatment and control groups (p > 0.05). Compared to the 1000 U/kg r-HuEPO group, Fas/Fasl expression levels were significantly lower in the 3000 and 5000 U/kg r-HuEPO groups (p < 0.05). Additionally, expression of NF-κB and Fasl in the 5000 U/kg r-HuEPO group was significantly lower than that in the 3000 U/kg r- HuEPO group (p < 0.05). Moreover, the number of apoptotic cells in the r-HuEPO group (5000 U/kg) was significantly lower than in the control group (p < 0.05).Conclusion: Thus, r-HuEPO may be beneficial for treating traumatic brain injury via inhibition of NFkappa B and Fas/Fasl expressions.Keywords: Recombinant human erythropoietin, NF-kappa B, Traumatic brain injury, Apoptosis, Neuronal damage, Fas/Fasl expressio

Air-to-Ground Channel Characterization for Low-Height UAVs in Realistic Network Deployments

Due to the decrease in cost, size and weight, \acp{UAV} are becoming more and more popular for general-purpose civil and commercial applications. Provision of communication services to \acp{UAV} both for user data and control messaging by using off-the-shelf terrestrial cellular deployments introduces several technical challenges. In this paper, an approach to the air-to-ground channel characterization for low-height \acp{UAV} based on an extensive measurement campaign is proposed, giving special attention to the comparison of the results when a typical directional antenna for network deployments is used and when a quasi-omnidirectional one is considered. Channel characteristics like path loss, shadow fading, root mean square delay and Doppler frequency spreads and the K-factor are statistically characterized for different suburban scenarios.Comment: 15 pages, accepted in IEEE Transactions on Antennas and Propagatio

More comprehensive facial inversion for more effective expression recognition

Facial expression recognition (FER) plays a significant role in the ubiquitous application of computer vision. We revisit this problem with a new perspective on whether it can acquire useful representations that improve FER performance in the image generation process, and propose a novel generative method based on the image inversion mechanism for the FER task, termed Inversion FER (IFER). Particularly, we devise a novel Adversarial Style Inversion Transformer (ASIT) towards IFER to comprehensively extract features of generated facial images. In addition, ASIT is equipped with an image inversion discriminator that measures the cosine similarity of semantic features between source and generated images, constrained by a distribution alignment loss. Finally, we introduce a feature modulation module to fuse the structural code and latent codes from ASIT for the subsequent FER work. We extensively evaluate ASIT on facial datasets such as FFHQ and CelebA-HQ, showing that our approach achieves state-of-the-art facial inversion performance. IFER also achieves competitive results in facial expression recognition datasets such as RAF-DB, SFEW and AffectNet. The code and models are available at https://github.com/Talented-Q/IFER-master