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

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

CONTINUOUS CAPACITIVE DEIONIZATION (CDI) PROCESSES TREATING HIGH-CASO4 FEEDS FOR POTENTIAL INDUSTRIAL BRINE MANAGEMENT – IMPACTS, MECHANISMS AND MITIGATIONS

Ph.DDOCTOR OF PHILOSOPHY (FOE

A WEIGHTED INVERSE MINIMUM CUT PROBLEM UNDER THE BOTTLENECK TYPE HAMMING DISTANCE

An inverse optimization problem is defined as follows. Let S denote the set of feasible solutions of an optimization problem P, let c be a specified cost (capacity) vector, and x0 ∈ S. We want to perturb the cost (capacity) vector c to d so that x0 is an optimal solution of P with respect to the cost (capacity) vector d, and to minimize some objective function. In this paper, we consider the weighted inverse minimum cut problem under the bottleneck type Hamming distance. For the general case, we present a combinatorial algorithm that runs in strongly polynomial time.Minimum cut, inverse problem, hamming distance, strongly polynomial algorithm

Weighted inverse maximum perfect matching problems under the Hamming distance

National Natural Science Foundation of China [11001232]; Fundamental Research Funds for the Central Universities [2010121004]Given an undirected network G(V, E, c) and a perfect matching M (0), the inverse maximum perfect matching problem is to modify the cost vector as little as possible such that the given perfect matching M (0) can form a maximum perfect matching. The modification can be measured by different norms. In this paper, we consider the weighted inverse maximum perfect matching problems under the Hamming distance, where we use the weighted Hamming distance to measure the modification of the edges. We consider both of the sum-type and the bottleneck-type problems. For the general case of the sum-type case, we show it is NP-hard. For the bottleneck-type, we present a strongly polynomial algorithm which can be done in O(m center dot n (3))

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

An open-closed-loop iterative learning control for trajectory tracking of a high-speed 4-dof parallel robot

Precise control is of importance for robots, whereas, due to the presence of modeling errors and uncertainties under the complex working environment, it is difficult to obtain an accurate dynamic model of the robot, leading to decreased control performances. This work presents an open-closed-loop iterative learning control applied to a four-limb parallel Schönflies-motion robot, aiming to improve the tracking accuracy with high movement, in which the controller can learn from the iterative errors to make the robot end-effector approximate to the expected trajectory. The control algorithm is compared with classical D-ILC, which is illustrated along with an industrial trajectory of pick-and-place operation. External repetitive and non-repetitive disturbances are added to verify the robustness of the proposed approach. To verify the overall performance of the proposed control law, multiple trajectories within the workspace, different working frequencies for a prescribed trajectory, and different design methods are selected, which show the effectiveness and the generalization ability of the designed controller

Minimizing the maximum bump cost in linear extensions of a poset

National Nature Science Foundation of China [10971191, 11001232]; Fundamental Research Funds for the Central Universities [2010121004]; Department of Education of Zhejiang Province of China [Y200909535]A linear extension of a poset P=(X,a parts per thousand(0)) is a permutation x (1),x (2),aEuro broken vertical bar,x (|X|) of X such that i < j whenever x (i) a parts per thousand(0)x (j) . For a given poset P=(X,a parts per thousand(0)) and a cost function c(x,y) defined on XxX, we want to find a linear extension of P such that maximum cost is as small as possible. For the general case, it is NP-complete. In this paper we consider the linear extension problem with the assumption that c(x,y)=0 whenever x and y are incomparable. First, we prove the discussed problem is polynomially solvable for a special poset. And then, we present a polynomial algorithm to obtain an approximate solution