Design and Application of Neural Network PID Decoupling Controller

Abstract. Aiming at the multivariant, nonlinear, time variat-ion and strong coupling plant, and neural network PID decoupling controller is proposed. Firstly, a DRNN-PID controller is constructed based on diagonal recurrent neural network and then several DRNN-PID controllers are adopted in parallel as the neural network decoupling controller, which accomplish decoupling and controlling simultaneously. Finally, the stability condition of the controller is presented based on the Lyapunov theory. Simulation results show that the proposed decoupling controller is effectively

ACSS2 coupled with KAT7 regulates histone β-hydroxybutyrylation to enhance transcription

Histone lysine β-hydroxybutyrylation (Kbhb) is an epigenetic mark linking ketone metabolism to transcription. However, the molecular mechanism by which β-hydroxybutyrate is converted to β-hydroxybutyryl–coenzyme A (BHB-CoA), the cofactor for Kbhb, remains unknown. Here, we report that acetyl-CoA synthetase short-chain family member 2 (ACSS2) coupled with lysine acetyltransferase 7 (KAT7) modulates β-hydroxybutyrylation on lysine 9 of histone H3 (H3K9bhb) to promote transcription. We show that KAT7 serves as a β-hydroxybutyryltransferase and preferably catalyzes histone Kbhb, especially H3K9bhb, in 1171 identified Kbhb substrates. ACSS2 is a BHB-CoA synthetase. This enzyme can sense cellular β-hydroxybutyrate and translocate into the nucleus, where it binds to and colocalizes with KAT7 at specific locus of chromatin. The ACSS2-generated BHB-CoA can fuel KAT7 for histone H3K9bhb. We demonstrate that the β-hydroxybutyrate drives the ACSS2-KAT7-H3K9bhb axis to promote epigenetic regulation and tumor cell growth. Our study not only identifies the founding member of BHB-CoA ligase but also reveals the mechanism underlying KAT7-catalyzed histone Kbhb using ACSS2-generated BHB-CoA

Synthesis, Magnetic Anisotropy and Optical Properties of Preferred Oriented Zinc Ferrite Nanowire Arrays

Preferred oriented ZnFe2O4 nanowire arrays with an average diameter of 16 nm were fabricated by post-annealing of ZnFe2 nanowires within anodic aluminum oxide templates in atmosphere. Selected area electron diffraction and X-ray diffraction exhibit that the nanowires are in cubic spinel-type structure with a [110] preferred crystallite orientation. Magnetic measurement indicates that the as-prepared ZnFe2O4 nanowire arrays reveal uniaxial magnetic anisotropy, and the easy magnetization direction is parallel to the axis of nanowire. The optical properties show the ZnFe2O4 nanowire arrays give out 370–520 nm blue-violet light, and their UV absorption edge is around 700 nm. The estimated values of direct and indirect band gaps for the nanowires are 2.23 and 1.73 eV, respectively

A multicentre single arm phase 2 trial of neoadjuvant pyrotinib and letrozole plus dalpiciclib for triple-positive breast cancer.

peer reviewedCurrent therapies for HER2-positive breast cancer have limited efficacy in patients with triple-positive breast cancer (TPBC). We conduct a multi-center single-arm phase 2 trial to test the efficacy and safety of an oral neoadjuvant therapy with pyrotinib, letrozole and dalpiciclib (a CDK4/6 inhibitor) in patients with treatment-naïve, stage II-III TPBC with a Karnofsky score of ≥70 (NCT04486911). The primary endpoint is the proportion of patients with pathological complete response (pCR) in the breast and axilla. The secondary endpoints include residual cancer burden (RCB)-0 or RCB-I, objective response rate (ORR), breast pCR (bpCR), safety and changes in molecular targets (Ki67) from baseline to surgery. Following 5 cycles of 4-week treatment, the results meet the primary endpoint with a pCR rate of 30.4% (24 of 79; 95% confidence interval (CI), 21.3-41.3). RCB-0/I is 55.7% (95% CI, 44.7-66.1). ORR is 87.4%, (95% CI, 78.1-93.2) and bpCR is 35.4% (95% CI, 25.8-46.5). The mean Ki67 expression reduces from 40.4% at baseline to 17.9% (P < 0.001) at time of surgery. The most frequent grade 3 or 4 adverse events are neutropenia, leukopenia, and diarrhoea. There is no serious adverse event- or treatment-related death. This fully oral, chemotherapy-free, triplet combined therapy has the potential to be an alternative neoadjuvant regimen for patients with TPBC

A PID Decoupling Controller Based on DRNN

decoupling controller, DRNN, stability condition Abstract � For the multivariant, nonlinear, time variation and strong coupling plant, a PID decoupling controller based on DRNN is proposed. Firstly, a PID controller based on DRNN is constructed. And then several PID controllers based on DRNN are adopted in parallel as the decoupling controller, which can accomplish decoupling and controlling simultaneously. Finally, the convergence condition of the controller is presented based on the Lyapunov theory. Simulation results show that the proposed PID decoupling controller is more effective. 1

Emotion transfer in audio using mel-cepstral representation and CycleGANs

Abstract The field of audio synthesis is currently confronted with two major challenges: to more effectively eliminate non-emotional influences in emotional feature extraction work, and to improve the emotional expression when reference audio is scarce. Therefore, an innovative audio deep feature decoupling and emotion adaptive fusion model, which combines Mel Frequency Cepstral Coefficients (MFCCs) with Cycle-consistent Generative Adversarial Networks (CycleGANs), is proposed in this paper. We designed a Deep Feature Decoupled Encoder Group (DFDEG), which is based on Gated Linear Units (GLU), Self-Attention, and Average Pooling. Meanwhile, we designed a feature fusion method called Emotion Adaptive Instance Normalization (Emo-AdaIN), which is based on AdaIN. By integrating the DFDEG, Emo-AdaIN, and CycleGANs, an unsupervised bidirectional multi-emotion transfer method within the MFCCs is successfully achieved. This method performs well in terms of emotion decoupling and transfer on unseen datasets: for different speakers, the transfer result’s Lowest Emotional Similarity (LES) is 94.56%, and Average Confidence Level (ACL) is 0.51. This demonstrates the generalization performance across different speakers and the robustness across different emotion granularity

Design on Optimization of Argon Bottom Blowing of Molten Steel ladle

AbstractThe cause of controlling argon blowing on steel-making process is analyzed. The strategy of controlling argon stirring energy is proposed, and the scheme controlling flow rate and fixing the pressure is achieved. The argon blowing of molten steel ladle is controlled automatically and properly, which is based on fuzzy control theory and Pulse Code Modulation. The intelligent control system has worked well in several steel plants

Image stitching algorithm based on two-stage optimal seam line search

Traditional feature matching algorithms often struggle with poor performance in scenarios involving local detail deformations under varying perspectives. Additionally, traditional optimal seamline search-based image stitching algorithms tend to overlook structural and texture information, resulting in ghosting and visible seams. To address these issues, this paper proposes an image stitching algorithm based on a two-stage optimal seamline search. The algorithm leverages a Homography Network as the foundation, incorporating a homography detail-aware network (HDAN) for feature point matching. By introducing a cost volume in the feature matching layer, the algorithm enhances the description of local detail deformation relationships, thereby improving feature matching performance under different perspectives. The two-stage optimal seamline search algorithm designed for image fusion introduces gradient and structural similarity features on top of traditional color-based optimal seamline search algorithms. The algorithm steps include: (1) Searching for structurally similar regions, i.e., high-frequency regions in high-gradient images, and using a color-based graph cut algorithm to search for seamlines within all high-frequency regions, excluding horizontal seamlines; (2) Using a dynamic programming algorithm to complete each vertical seamline, where the pixel energy is comprehensively calculated based on its differences in color and gradient with the surrounding area. The complete seamline energies are then calculated using color, gradient, and structural similarity differences within the seamline neighborhood, and the seamline with the minimum energy is selected as the optimal seamline. A simulation experiment was conducted using 30 image pairs from the UDIS-D dataset (Unsupervised Deep Image Stitching Dataset). The results demonstrate significant improvements in PSNR and SSIM metrics compared to other image stitching algorithms, with PSNR improvements ranging from 5.63% to 11.25% and SSIM improvements ranging from 11.09% to 24.54%, confirming the superiority of this algorithm in image stitching tasks. The proposed image stitching algorithm based on two-stage optimal seamline search, whether evaluated through subjective visual perception or objective data comparison, outperforms other algorithms by enhancing the natural transition of seamlines in terms of structure and texture, reducing ghosting and visible seams in stitched images