A Dynamics-Learning Multirate Estimation Approach for the Feeding Condition Perception of Complex Industry Processes.

In this study, we propose a dynamics-learning multirate estimation approach to perceive the quality-related indices (QRIs) of the feeding solution of a unit process. A quality-related index for estimation is an intermediate technical indicator between a unit process and a proceeding unit process; hence, the estimation problem is formulated as a two-stage estimation problem utilizing the production data of both unit processes. Dynamics-learning bidirectional long short-term memory (BiLSTM) with different inputs for the forward and backward layers is proposed to manage the input data from the different unit processes. In the dynamics-learning BiLSTM, a cycle control gate is added in the memory cell to learn the dynamics of the QRIs, thereby enabling a high-rate estimation under multirate conditions. A Bayesian estimation model is then combined with the dynamics-learning BiLSTM model to manage the process delay. Ablation and comparative experiments are conducted to evaluate the feasibility and effectiveness of the proposed estimation approach. The experimental results illustrate the performance and high-rate estimation ability of the proposed approach.

Simplified LDPC-assisted CNC algorithm for entropy-loaded discrete multi-tone in a 100G flexible-rate PON.

Passive optical networks (PONs) have been widely used in optical access networks to meet the requirement of the rapidly growing data traffic. However, the optical power budget of the worst optical network unit certainly limits the maximum capacity of PON. In this paper, we demonstrate a flexible-rate PON based on entropy-loaded clipping discrete multi-tone (DMT) for increasing the capacity. Meanwhile, clipping operation and simplified low-density parity-check (LDPC) assisted clipping-noise-cancellation (CNC) algorithm are proposed to improve the performance of DMT in peak-power constrained PON. In the simplified LDPC-assisted CNC algorithm, the iteration number of the sum-product algorithm in the LDPC decoding can be reduced to decrease the computational complexity almost without performance loss. The experimental results show that the simplified CNC algorithm can achieve approximately 1.8dB improvement of the optical receiver sensitivity at the 20% soft-decision forward-error-correction limit. The proposed flexible-rate PON has a wide-range data-rate adjustment from 12.5Gb/s to 100Gb/s under the optical power budget from 40dB to 26dB.

Zearalenone Induces Blood-Testis Barrier Damage through Endoplasmic Reticulum Stress-Mediated Paraptosis of Sertoli Cells in Goats.

Zearalenone (ZEA) is present worldwide as a serious contaminant of food and feed and causes male reproductive toxicity. The implication of paraptosis, which is a nonclassical paradigm of cell death, is unclear in ZEA-induced male reproductive disorders. In this study, the toxic effects of ZEA on the blood-testis barrier (BTB) and the related mechanisms of paraptosis were detected in goats. ZEA exposure, in vivo, caused a significant decrease in spermatozoon quality, the destruction of seminiferous tubules, and damage to the BTB integrity. Furthermore, ZEA exposure to Sertoli cells (SCs) in vitro showed similar dysfunction in structure and barrier function. Importantly, the formation of massive cytoplasmic vacuoles in ZEA-treated SCs corresponded to the highly swollen and dilative endoplasmic reticulum (ER), and paraptosis inhibition significantly alleviated ZEA-induced SC death and vacuolization, which indicated the important contribution of paraptosis in ZEA-induced BTB damage. Meanwhile, the expression of ER stress marker proteins was increased after ZEA treatment but decreased under the inhibition of paraptosis. The vacuole formation and SC death, induced by ZEA, were remarkably blocked by ER stress inhibition. In conclusion, these results facilitate the exploration of the mechanisms of the SC paraptosis involved in ZEA-induced BTB damage in goats.

Demonstration of a carrier frequency offset estimator for 16-/32-QAM coherent receivers: a hardware perspective.

We propose and implement a hardware-efficient frequency offset estimator (FOE) optimized for 16- and 32-QAM coherent optical receivers with low hardware cost and high estimation accuracy. The proposed FOE combines a wide-range coarse estimator and a narrow-range highly accurate estimator in a feedforward architecture. We numerically and experimentally investigate the performance of the proposed estimator by using a field-programmable-logic-array (FPGA) based real-time coherent receiver. Compared with other state-of-the-art estimators in literature, the proposed method reduces over 40% of hardware utilizations while maintaining the same level of estimation accuracy in terms of mean-squared-error (MSE) and optical signal-to-noise ratio (OSNR) sensitivity. These results enable the development of next generation DSP circuit capable of supporting high capacity coherent optical communication link with advanced modulation formats.

Blind modulation format identification using nonlinear power transformation.

This paper proposes and experimentally demonstrates a blind modulation format identification (MFI) method delivering high accuracy (> 99%) even in a low OSNR regime (< 10 dB). By using nonlinear power transformation and peak detection, the proposed MFI can recognize whether the signal modulation format is BPSK, QPSK, 8-PSK or 16-QAM. Experimental results demonstrate that the proposed MFI can achieve a successful identification rate as high as 99% when the incoming signal OSNR is 7 dB. Key parameters, such as FFT length and laser phase noise tolerance of the proposed method, have been characterized.