Adaptive Consensus of the Stochastic Leader-Following Multi-Agent System with Time Delay

For the multi-agent system with time delay and noise, the adaptive consensus of tracking control problems is discussed by the Lyapunov function. The main purpose of this study is to design an adaptive control protocol for the system, such that even if there exists time delay among agents, the protocol can still ensure the consensus of the stochastic system. The main contribution is to revise the protocols that were previously only applicable to system without time delay. Because the system is inevitably disrupted by time delay and noise during the interactive process, achieving coordination and consensus is difficult. To enable the followers to track the leader, a novel adaptive law depending on the Riccati equation is firstly proposed, and the adaptive law is different from previous mandatory control law completely depending on a known function. The ability to be altered online based on the state of system is a major feature of the adaptive law. When there are interactive noise and time delay between the followers and leader of the system, a special Lyapunov function is constructed to prove the adaptive consensus. And the upper bound of time delay is obtained by using the Itô integral theory. Finally, if the time delay of the system approaches zero, it is shown that the adaptive law still ensures that each follower tracks the leader under simpler conditions

Heat shock factors in tomatoes: genome-wide identification, phylogenetic analysis and expression profiling under development and heat stress

The HSF (heat shock factor) gene family contains highly conserved plant-specific transcription factors that play an important role in plant high-temperature stress responses. The present study aimed to characterize the HSF transcription factor genes in tomato (Solanum lycopersicum), which is an important vegetable crop worldwide and the model plant for fruit development studies. Twenty-six SlyHSF genes were identified in tomato, and the phylogenetic analysis showed the possible evolution profile of subgroups among in the plant kingdom. A new group O was identified that involved HSF genes in primitive plant species, like in the green algae, mosses and lycophytes. The gene structure and motifs of each SlyHSF were comprehensively analyzed. We identified orthologous, co-orthologous and paralogous HSF gene pairs in tomato, Arabidopsis and rice, and constructed a complex interaction network among these genes. The SlyHSF genes were expressed differentially in different species and at a higher level in mature fruits. The qPCR analysis was performed and showed SlyHSF genes greatly participate in plant heat tolerant pathways. Our comprehensive genome-wide analysis provided insights into the HSF gene family of tomatoes

Transcriptome analysis reveals association of carotenoid metabolism pathway with fruit color in melon

Abstract Flesh color is an important quality of melon (Cucumis melo L.) and is determined mainly by carotenoid content, awarding them with colors, aromas, and nutrients. enhancing the nutritional and health benefits of fruits and vegetables for humans. In this study, we performed transcriptomic analysis of two melon inbred line “B-14” (orange-flesh) and “B-6” (white-flesh) at three developmental stages. We observed that the β-carotene content of inbred line “B-6” (14.232 μg/g) was significantly lower than that of inbred line “B-14” (0.534 μg/g). RNA-sequencing and quantitative reverse transcription PCR analyses were performed to identify differentially expressed genes (DEGs) between the two inbred lines at different stages; the DEGs were analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes databases (KEGG). We identified 33 structural DEGs in different developmental periods of the two lines that were related to carotenoid metabolism. Among them, PSY, Z-ISO, ZDS, CRTISO, CCD4, VDE1, and NCED2 were highly correlated with carotenoid content. Thus, this study provides a basis for molecular mechanism of carotenoid biosynthesis and flesh color in melon fruit

Biochemical Hormone Parameters in Seminal and Blood Plasma Samples Correlate With Histopathologic Properties of Testicular Biopsy in Azoospermic Patients

OBJECTIVE To investigate the relationship between histopathologic patterns of testicular biopsy and biochemical semen and blood plasma parameters, including neutral a-glucosidase (NAG), fructose, follicle-stimulating hormone (FSH), luteinizing hormone (LH), testosterone, and prolactin (PRL) in patients with azoospermia. MATERIALS AND METHODS A total of 471 azoospermic patients with definitive pathologic diagnosis were enrolled in this study. Six biochemical parameters, including 2 seminal (NAG and fructose) and 4 blood (FSH, LH, testosterone, and PRL) plasma markers, were analyzed. RESULTS NAG, fructose, FSH, and LH levels were significantly higher in patients with Sertoli-cell-only (SCO) syndrome and severe hypospermatogenesis than in those with normal spermatogenesis or mild hypospermatogenesis (P < .05). In addition, NAG levels positively correlated with fructose amounts in azoospermic patients (P < .05); a significant correlation between FSH and LH levels was also observed in azoospermic patients. Furthermore, PRL levels were higher in SCO syndrome patients compared with subjects showing normal spermatogenesis and the levels positively correlated with NAG, FSH, and LH amounts. However, testosterone levels in SCO syndrome patients were significantly reduced compared with individuals having normal spermatogenesis. CONCLUSION The levels of biochemical parameters in seminal (NAG and fructose) and blood (FSH, LH, testosterone, and PRL) plasma samples correlate with the histologic diagnosis in azoospermic patients, providing potential benefits in predicting the pathologic diagnosis of male infertility. (C) 2015 Elsevier Inc

A Hybrid Model Based on Deep Convolutional Network for Medical Named Entity Recognition

The typical pretrained model’s feature extraction capabilities are insufficient for medical named entity identification, and it is challenging to express word polysemy, resulting in a low recognition accuracy for electronic medical records. In order to solve this problem, this paper proposes a new model that combines the BERT pretraining model and the BilSTM-CRF model. First, word embedding with semantic information is obtained by pretraining the corpus input to the BERT model. Then, the BiLSTM module is utilized to extract further features from the encoded outputs of BERT in order to account for context information and improve the accuracy of semantic coding. Then, CRF is used to modify the results of BiLSTM to screen out the annotation sequence with the largest score. Finally, extensive experimental results show that the performance of the proposed model is effectively improved compared with other models

Dynamic Characteristics of the Chain Drive System under Multiple Working Conditions

The chain drive system, being one of the core subsystems of the scraper conveyor, greatly influences the coal-conveying efficiency due to its dynamic characteristics. Therefore, this paper employed an experimental method to compare the dynamic characteristics of the chain rings at various positions within the chain drive system. This article simulated the three most common working conditions. The results indicated that the chain speed, load, and surface undulation had a stimulating effect on chain vibration, with the most significant impact observed on the chain ring located in the middle of the adjacent scraper. The scraper exerted an inhibitory effect on the vibration of the chain ring. Among the factors studied, the load had the most significant influence on the transverse direction. When there was surface undulation, the vibration of the chain ring in the running direction formed an ‘N’ shape. This condition intensified the vibration during uphill and downhill stages while suppressing vibration at the slope peak. This research holds great significance in enhancing operation stability