Instant Photorealistic Style Transfer: A Lightweight and Adaptive Approach

In this paper, we propose an Instant Photorealistic Style Transfer (IPST) approach, designed to achieve instant photorealistic style transfer on super-resolution inputs without the need for pre-training on pair-wise datasets or imposing extra constraints. Our method utilizes a lightweight StyleNet to enable style transfer from a style image to a content image while preserving non-color information. To further enhance the style transfer process, we introduce an instance-adaptive optimization to prioritize the photorealism of outputs and accelerate the convergence of the style network, leading to a rapid training completion within seconds. Moreover, IPST is well-suited for multi-frame style transfer tasks, as it retains temporal and multi-view consistency of the multi-frame inputs such as video and Neural Radiance Field (NeRF). Experimental results demonstrate that IPST requires less GPU memory usage, offers faster multi-frame transfer speed, and generates photorealistic outputs, making it a promising solution for various photorealistic transfer applications.Comment: 8 pages (reference excluded), 6 figures, 4 table

Study of Aerosol Influence on Nighttime Land Surface Temperature Retrieval Based on Two Methods

The aim of this study is to evaluate the aerosol influence on LST retrieval with two algorithms (split-window (SW) method and a four-channel based method) using simulated data under typical conditions. The results show that the root mean square error (RMSE) decreases to approximately 2.3 K for SW method and 1.5 K for four channel based method when VZA = 60° and visibility = 3 km; an RMSE would be increased by approximately 1.0 K when visibility varies from 3 km to 23 km. Moreover, a detailed sensitivity analysis under a visibility of 3 km and 23 km is performed in terms of uncertainties of land surface emissivity (LSE), water vapor content (WVC), and instrument noise, respectively. It is noted that the four-channel based method is more sensitive to LSE than SW method, especially for dry atmosphere; LST error caused by a WVC uncertainty of 20% is within 1.5 K for SW method and within 0.8 K for four-channel based method; the instrument noise would introduce LST error with a maximum standard deviation of 0.5 K and 0.04 K for the four-channel based method and SW method, respectively

The ITGB6 gene: its role in experimental and clinical biology.

Integrin αvβ6 is a membrane-spanning heterodimeric glycoprotein involved in wound healing and the pathogenesis of diseases including fibrosis and cancer. Therefore, it is of great clinical interest for us to understand the molecular mechanisms of its biology. As the limiting binding partner in the heterodimer, the β6 subunit controls αvβ6 expression and availability. Here we describe our understanding of the ITGB6 gene encoding the β6 subunit, including its structure, transcriptional and post-transcriptional regulation, the biological effects observed in ITGB6 deficient mice and clinical cases of ITGB6 mutations

TSC1/2 Signaling Complex Is Essential for Peripheral Naïve CD8+ T Cell Survival and Homeostasis in Mice

The PI3K-Akt-mTOR pathway plays crucial roles in regulating both innate and adaptive immunity. However, the role of TSC1, a critical negative regulator of mTOR, in peripheral T cell homeostasis remains elusive. With T cell-specific Tsc1 conditional knockout (Tsc1 KO) mice, we found that peripheral naïve CD8+ T cells but not CD4+ T cells were severely reduced. Tsc1 KO naïve CD8+ T cells showed profound survival defect in an adoptive transfer model and in culture with either stimulation of IL-7 or IL-15, despite comparable CD122 and CD127 expression between control and KO CD8+ T cells. IL-7 stimulated phosphorylation of Akt(S473) was diminished in Tsc1 KO naïve CD8+T cells due to hyperactive mTOR-mediated feedback suppression on PI3K-AKT signaling. Furthermore, impaired Foxo1/Foxo3a phosphorylation and increased pro-apoptotic Bim expression in Tsc1 KO naïve CD8+T cells were observed upon stimulation of IL-7. Collectively, our study suggests that TSC1 plays an essential role in regulating peripheral naïve CD8+ T cell homeostasis, possible via an mTOR-Akt-FoxO-Bim signaling pathway

Land Surface Temperature Retrieval Using Airborne Hyperspectral Scanner Daytime Mid-Infrared Data

Land surface temperature (LST) retrieval is a key issue in infrared quantitative remote sensing. In this paper, a split window algorithm is proposed to estimate LST with daytime data in two mid-infrared channels (channel 66 (3.746~4.084 μm) and channel 68 (4.418~4.785 μm)) from Airborne Hyperspectral Scanner (AHS). The estimation is conducted after eliminating reflected direct solar radiance with the aid of water vapor content (WVC), the view zenith angle (VZA), and the solar zenith angle (SZA). The results demonstrate that the LST can be well estimated with a root mean square error (RMSE) less than 1.0 K. Furthermore, an error analysis for the proposed method is also performed in terms of the uncertainty of LSE and WVC, as well as the Noise Equivalent Difference Temperature (NEΔT). The results show that the LST errors caused by a LSE uncertainty of 0.01, a NEΔT of 0.33 K, and a WVC uncertainty of 10% are 0.4~2.8 K, 0.6 K, and 0.2 K, respectively. Finally, the proposed method is applied to the AHS data of 4 July 2008. The results show that the differences between the estimated and the ground measured LST for water, bare soil and vegetation areas are approximately 0.7 K, 0.9 K and 2.3K, respectively

Parameter optimization of winnowing equipment for machine-harvested Lycium barbarum L.

To accurately and efficiently remove unripe fruit, flowers, leaves, and other impurities in machine-harvested Lycium barbarum L., winnowing equipment for machine-harvested L. barbarum based on the principle that different materials have different flight coefficients was designed. To optimize the structure and working parameters of winnowing equipment, this study adopted the free flow resistance model to establish a horizontal airflow model based on C++ in Microsoft Visual Studio. A discrete element method (DEM) simulation of ripe fruit in the horizontal airflow was performed using EDEM software. Results showed that the optimal parameters included an airflow speed of 5-6 m/s, input conveyor speed of 0.4-0.6 m/s, and input-output conveyor distance of 260-270 mm. We used three factors and three levels in a quadratic orthogonal rotation design to establish mathematical models regarding the rate of impurity change and the clearance rate of ripe fruit based on the airflow speed, input conveyor speed, and input-output conveyor distance. We also analyzed the effects of all factors on the rate of impurity change and the clearance rate of ripe fruit. The optimal parameter combination was an airflow speed of 5.52 m/s, input conveyor speed of 0.5 m/s, and input-output conveyor distance of 265.04 mm. The field experiment showed that the rate of impurity change and the clearance rate of ripe fruit were 89.74% and 8.71%, respectively. Findings provide a design basis for future research on winnowing equipment for machine-harvested L. barbarum

Deep Mixture Model-Based Land Surface Temperature Retrieval for Hyperspectral Thermal IASI Sensor

International audienceA deep mixture model was developed to retrieve land surface temperatures (LSTs) from infrared atmospheric sounding interferometer (IASI) observations. The IASI brightness temperature (Tb) data and the Advanced Very High Resolution Radiometer onboard MetOp (AVHRR/MetOp) LST data were randomly divided into training and test datasets, and a deep mixture model was constructed to simulate radiation transmission in order to invert the LST. The constructed model could evaluate dataset characteristics that included global features, local features, and time-domain predictions, covering most of the features of the satellite dataset. For the test datasets, the root mean square error (RMSE) indicated that the LST in Algeria and South Africa could be retrieved with an error of less than 2 K and 2.5 K, respectively. Compared with the AVHRR/MetOp LST product in March and December 2019 for Algeria and South Africa, the LST could be retrieved with the maximum RMSE of 2.5 K. The LST retrievals at nighttime had an RMSE of less than 2.0 K, which was superior to those retrieved during daytime for Algeria. This deep mixture model can be applied to time-series temperature prediction. INDEX TERMS Hyperspectral thermal infrared, land surface temperature retrieval, IASI, deep learning

An Improved Linear Spectral Emissivity Constraint Method for Temperature and Emissivity Separation Using Hyperspectral Thermal Infrared Data

International audienceThe linear spectral emissivity constraint (LSEC) method has been proposed to separate temperature and emissivity in hyperspectral thermal infrared data with an assumption that land surface emissivity (LSE) can be described by an equal interval piecewise linear function. This paper combines a pre-estimate shape method with the LSEC method to provide an initial-shape estimation of LSE which will create a new piecewise scheme for land surface temperature (LST) and LSE separation. This new scheme is designated as the pre-estimate shape (PES)-LSEC method. Comparisons with the LSEC method using simulated data sets show that the PES-LSEC method has better performance in terms of accuracy for both LSE and LST. With an at-ground error of 0.5 K, the root-mean-square errors (RMSEs) of LST and LSE are 0.07 K and 0.0045, respectively, and with the scale factor of moisture profile 0.8 and 1.2, the RMSEs of LST are 1.11 K and 1.14 K, respectively. The RMSEs of LSE in each channel are mostly below 0.02 and 0.04, respectively, which are better than for the LSEC method. In situ experimental data are adopted to validate our method: The results show that RMSE of LST is 0.9 K and the mean value of LSE accuracy is 0.01. The PES-LSEC method with fewer segments achieves better accuracy than that of LSEC and preserves most of the crest and trough information of emissivity

Measurement of Soot Volume Fraction and Temperature for Oxygen-Enriched Ethylene Combustion Based on Flame Image Processing

A method for simultaneously visualizing the two-dimensional distributions of temperature and soot volume fraction in an ethylene flame was presented. A single-color charge-coupled device (CCD) camera was used to capture the flame image in the visible spectrum considering the broad-response spectrum of the R and G bands of the camera. The directional emissive power of the R and G bands were calibrated and used for measurement. Slightly increased temperatures and reduced soot concentration were predicted in the central flame without self-absorption effects considered, an iterative algorithm was used for eliminating the effect of self-absorption. Nine different cases were presented in the experiment to demonstrate the effects of fuel mass flow rate and oxygen concentration on temperature and soot concentration in three different atmospheres. For ethylene combustion in pure-air atmosphere, as the fuel mass flow rate increased, the maximum temperature slightly decreased, and the maximum soot volume fraction slightly increased. For oxygen fractions of 30%, 40%, and 50% combustion in O2/N2 oxygen-enhanced atmospheres, the maximum flame temperatures were 2276, 2451, and 2678 K, whereas combustion in O2/CO2 atmospheres were 1916, 2322, and 2535 K. The maximum soot volume fractions were 4.5, 7.0, and 9.5 ppm in oxygen-enriched O2/N2 atmosphere and 13.6, 15.3, and 14.8 ppm in oxygen-enriched O2/CO2 atmosphere. Compared with the O2/CO2 atmosphere, combustion in the oxygen-enriched O2/N2 atmosphere produced higher flame temperature and larger soot volume fraction. Preliminary results indicated that this technique is reliable and can be used for combustion diagnosis