Knowledge-Data Driven Optimal Control for Nonlinear Systems and Its Application to Wastewater Treatment Process.

Optimal control is developed to guarantee nonlinear systems run in an optimum operating state. However, since the operation demands of systems are dynamically changeable, it is difficult for optimal control to obtain reliable optimal solutions to achieve satisfying operation performance. To overcome this problem, a knowledge-data driven optimal control (KDDOC) for nonlinear systems is designed in this article. First, an adaptive initialization strategy, using the knowledge from historical operation information of nonlinear systems, is employed to dynamically preset parameters of KDDOC. Then, the initial performance of KDDOC can be enhanced for nonlinear systems. Second, a knowledge guide-based global best selection mechanism is used to assist KDDOC in searching for the optimal solutions under different operation demands. Then, dynamic optimal solutions of KDDOC can be obtained to adapt to flexible changes in nonlinear systems. Third, a knowledge direct-based exploitation mechanism is presented to accelerate the solving process of KDDOC. Then, the demand response speed of KDDOC can be improved to ensure nonlinear systems with optimal operation performance in different states. Finally, the performance of KDDOC is validated on a simulation and a practical process. Several experimental results illustrate the effectiveness of the proposed optimal control for nonlinear systems.

Sampled-Data H∞ Dynamic Output-Feedback Control for NCSs With Successive Packet Losses and Stochastic Sampling.

The problem of sampled-data H∞ dynamic output-feedback control for networked control systems with successive packet losses (SPLs) and stochastic sampling is investigated in this article. The aim of using sampled-data control techniques is to alleviate network congestion. SPLs that occur in the sensor-to-controller (S-C) and controller-to-actuator (C-A) channels are modeled using a packet loss model. Additionally, it is assumed that stochastic sampling follows a Bernoulli distribution. A model is established to capture the stochastic characteristics of both the SPL model and stochastic sampling. This model is crucial as it allows us to determine the probability distribution of the sampling interval between successive update instants, which is essential for stability analysis. An exponential mean-square stability condition for the constructed equivalent discrete-time stochastic system, which also guarantees the prescribed H∞ performance, is established by incorporating probability theory. The desired controller is designed using a step-by-step synthesis approach, which may offer lower design conservatism compared to some existing methods. Finally, our designed approach using a networked F-404 engine system model is validated and its merits relative to existing results are discussed. The proposed method is finally validated by employing a networked model of the F-404 engine system. Furthermore, the advantages of our method are presented in comparison to previous results.

Initial nutrient condition determines the recovery speed of quiescent cells in fission yeast.

Most of microbe cells spend the majority of their times in quiescence due to unfavorable environmental conditions. The study of this dominant state is crucial for understanding the basic cell physiology. Retained recovery ability is a critical property of quiescent cells, which consists of two features: how long the cells can survive (the survivability) and how fast they can recover (the recovery activity). While the survivability has been extensively studied under the background of chronological aging, how the recovery activity depends on the quiescent time and what factors influence its dynamics have not been addressed quantitatively. In this work, we systematically quantified both the survivability and the recovery activity of long-lived quiescent fission yeast cells at the single cell level under various nutrient conditions. It provides the most profound evolutionary dynamics of quiescent cell regeneration ability described to date. We found that the single cell recovery time linearly increased with the starvation time before the survivability significantly declined. This linearity was robust under various nutrient conditions and the recovery speed was predetermined by the initial nutrient condition. Transcriptome profiling further revealed that quiescence states under different nutrient conditions evolve in a common trajectory but with different speed. Our results demonstrated that cellular quiescence has a continuous spectrum of depths and its physiology is greatly influenced by environmental conditions.

Compositional Shifts and Assembly in Rhizosphere-Associated Fungal Microbiota Throughout the Life Cycle of Japonica Rice Under Increased Nitrogen Fertilization.

Soil fungal microbiomes facilitate a range of beneficial functions for their host plants, and rhizosphere fungal community composition, richness, and diversity affect plant growth and development, and crop yield. Therefore, exploring the community structure and assembly of the rhizosphere fungal microbiome and its relationship with soil biochemical properties are fundamental to elucidating how rice plants benefit from their fungal symbionts. In this study, soil samples were collected at seedling, tillering, heading, and ripening stages of rice subjected to three levels of nitrogen fertilization. Plant growth demonstrates a substantial influence on fungal community composition and diversity. From the tillering to the ripening stage, the fungal communities were governed by homogenizing dispersal and dispersal limitation. The prevalence of Glomeromycota, the beneficial fungi, was considerably higher during the heading stage compared to the three other growth stages. This increase in abundance was strongly associated with increased levels of soil nutrients and enhanced activity of nitrogen acquisition enzymes. This may be a strategy developed by rice grown in flooded soil to recruit beneficial fungi in the rhizosphere to meet high nitrogen demands. Our study findings contribute to elucidating the influence of plant development and nitrogen fertilization on the structure and composition of the fungal community as well as its relationship with soil key soil nutrient content and nitrogen-related enzyme activities. They also illustrate how a shift in the fungal community mediates and reflects the effects of nitrogen fertilization input in rice agroecosystems. These findings provide new insights into the effects of changes in nitrogen application in rice rhizosphere at different growth stages on fungal communities and soil biochemical characteristics.

Identification of BBX gene family and its function in the regulation of microtuber formation in yam.

BBX proteins play important roles in all of the major light-regulated developmental processes. However, no systematic analysis of BBX gene family regarding the regulation of photoperiodic microtuber formation has been previously performed in yam. In this study, a systematic analysis on the BBX gene family was conducted in three yam species, with the results, indicating that this gene plays a role in regulating photoperiodic microtuber formation. These analyses included identification the BBX gene family in three yam species, their evolutionary relationships, conserved domains, motifs, gene structure, cis-acting elements, and expressional patterns. Based on these analyses, DoBBX2/DoCOL5 and DoBBX8/DoCOL8 showing the most opposite pattern of expression during microtuber formation were selected as candidate genes for further investigation. Gene expression analysis showed DoBBX2/DoCOL5 and DoBBX8/DoCOL8 were highest expressed in leaves and exhibited photoperiod responsive expression patterns. Besides, the overexpression of DoBBX2/DoCOL5 and DoBBX8/DoCOL8 in potato accelerated tuber formation under short-day (SD) conditions, whereas only the overexpression of DoBBX8/DoCOL8 enhanced the accelerating effect of dark conditions on tuber induction. Tuber number was increased in DoBBX8/DoCOL8 overexpressing plants under dark, as well as in DoBBX2/DoCOL5 overexpressing plants under SD. Overall, the data generated in this study may form the basis of future functional characterizations of BBX genes in yam, especially regarding their regulation of microtuber formation via the photoperiodic response pathway.

Multiobjective Integrated Optimal Control for Nonlinear Systems.

The multiobjective optimal control method optimizes the performance indexes of nonlinear systems to obtain setpoints, and designs a controller to track the setpoints. However, the stepwise optimal control method that independently analyzes the optimization process may obtain unfeasible and difficult to track setpoints, which will reduce the operation and control performance of the systems. To solve this problem, a multiobjective integrated optimal control (MIOC) strategy is proposed for nonlinear systems in this article. The main contributions of MIOC are threefold. First, in the framework of multiobjective model predictive control, an integrated control structure with a comprehensive cost function and a collaborative optimization algorithm is designed to achieve the coordinate optimal control. Second, for the time inconformity of setpoints and control laws caused by the characteristic of tracking control, the different prediction horizons are designed for the comprehensive cost function. Then, the collaborative optimization algorithm is proposed for the comprehensive cost function to achieve the integrated solution of setpoints and control laws to enhance the operation and control performance of nonlinear systems. Third, the stability and control performance analysis of MIOC is provided. Finally, the proposed MIOC method is applied for a nonlinear system to demonstrate its effectiveness.

Consensus of MASs With Input and Communication Delays by Predictor-Based Protocol.

In this article, the consensus problem of multiagent systems (MASs) affected by input and communication delays is investigated. A predictor-based state feedback protocol is used to reach the consensus of linear MASs by delay compensation. In order to analyze the maximum delay under the predictor-based protocol, the overall MASs are equivalent to the feedback interconnection system, including a linear time-invariant system and a time-delay operator, in view of the characteristic of the Laplacian matrix. Then, the maximum delay corresponding to the predictor-based protocol is evaluated by using the small gain theorem (SGT). Finally, two numerical examples are given to verify the effectiveness of the obtained consensus condition.

Rhizosphere-Associated Microbiomes of Rice (Oryza sativa L.) Under the Effect of Increased Nitrogen Fertilization.

Crops assemble and rely on rhizosphere-associated microbiomes for plant nutrition, which is crucial to their productivity. Historically, excessive nitrogen fertilization did not result in continuously increasing yields but rather caused environmental issues. A comprehensive understanding should be developed regarding the ways in which crops shape rhizosphere-associated microbiomes under conditions of increased nitrogen fertilization. In this study, we applied 16S and 18S ribosomal RNA gene profiling to characterize bacterial and fungal communities in bulk and rhizosphere soil of rice subjected to three levels of nitrogen fertilization for 5 years. Soil biochemical properties were characterized, and carbon-, nitrogen-, and phosphorus-related soil enzyme activities were investigated, by assays. Increasing nitrogen fertilization led to a decreasing trend in the variation of microbial community structures and demonstrated a more definite influence on fungal rather than bacterial community compositions and functions. Changes in the level of nitrogen fertilization significantly affected chemical properties such as soil pH, nutrient content, and microbial biomass levels in both rhizosphere and bulk soil. Soil enzyme activity levels varied substantially across nitrogen fertilization intensities and correlated more with the fungal than with the bacterial community. Our results indicated that increased nitrogen input drives alterations in the structures and functions of microbial communities, properties of soil carbon, nitrogen, and phosphorus, as well as enzyme activities. These results provide novel insights into the associations among increased nitrogen input, changes in biochemical properties, and shifts in microbial communities in the rhizosphere of agriculturally intensive ecosystems.

Strontium/Chitosan/Hydroxyapatite/Norcantharidin Composite That Inhibits Osteosarcoma and Promotes Osteogenesis In Vitro.

Hydroxyapatite can deliver drugs, and its composite material is capable of repairing bone defects in tumors. This study was conducted to evaluate the effect of composite materials on tumor growth inhibition and bone growth induction. Composites containing drug delivery compounds were synthesized by coprecipitation and freeze-drying and then characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR). In addition, the effect of hydroxyapatite nanoparticles (nano-SHAP) on proliferation of an osteosarcoma cell line (MG-63) and an osteoblast cell line (MC3T3-E1) was evaluated, and its mechanism was studied. The use of nano-SHAP alone did not affect the proliferation of normal cell lines. However, nanoparticles containing different amounts of norcantharidin in the composite materials and had different inhibitory effects on osteosarcoma and different effects on osteoblasts. And, with the increase of the content of norcantharidin, the antitumor performance of the composite has been enhanced. In summary, the nano-SHAP system developed in this study is a drug delivery material that can inhibit the growth of tumors and induce the proliferation of osteoblasts.

The apricot (Prunus armeniaca L.) genome elucidates Rosaceae evolution and beta-carotenoid synthesis.

Apricots, scientifically known as Prunus armeniaca L, are drupes that resemble and are closely related to peaches or plums. As one of the top consumed fruits, apricots are widely grown worldwide except in Antarctica. A high-quality reference genome for apricot is still unavailable, which has become a handicap that has dramatically limited the elucidation of the associations of phenotypes with the genetic background, evolutionary diversity, and population diversity in apricot. DNA from P. armeniaca was used to generate a standard, size-selected library with an average DNA fragment size of ~20 kb. The library was run on Sequel SMRT Cells, generating a total of 16.54 Gb of PacBio subreads (N50 = 13.55 kb). The high-quality P. armeniaca reference genome presented here was assembled using long-read single-molecule sequencing at approximately 70× coverage and 171× Illumina reads (40.46 Gb), combined with a genetic map for chromosome scaffolding. The assembled genome size was 221.9 Mb, with a contig NG50 size of 1.02 Mb. Scaffolds covering 92.88% of the assembled genome were anchored on eight chromosomes. Benchmarking Universal Single-Copy Orthologs analysis showed 98.0% complete genes. We predicted 30,436 protein-coding genes, and 38.28% of the genome was predicted to be repetitive. We found 981 contracted gene families, 1324 expanded gene families and 2300 apricot-specific genes. The differentially expressed gene (DEG) analysis indicated that a change in the expression of the 9-cis-epoxycarotenoid dioxygenase (NCED) gene but not lycopene beta-cyclase (LcyB) gene results in a low ß-carotenoid content in the white cultivar "Dabaixing". This complete and highly contiguous P. armeniaca reference genome will be of help for future studies of resistance to plum pox virus (PPV) and the identification and characterization of important agronomic genes and breeding strategies in apricot.

A systematic study of the determinants of protein abundance memory in cell lineage.

Proteins are essential players of life activities. Intracellular protein levels directly affect cellular functions and cell fate. Upon cell division, the proteins in the mother cell are inherited by the daughters. However, what factors and by how much they affect this epigenetic inheritance of protein abundance remains unclear. Using both computational and experimental approaches, we systematically investigated this problem. We derived an analytical expression for the dependence of protein inheritance on various factors and showed that it agreed with numerical simulations of protein production and experimental results. Our work provides a framework for quantitative studies of protein inheritance and for the potential application of protein memory manipulation.

Analysis of related risk factors and reversal value of renal injury in elderly patients with multiple myeloma.

PURPOSE: To study risk factors associated with renal injuries in elderly patients with multiple myeloma. METHODS: From January 2012 to January 2015 135 elderly patients with multiple myeloma who were treated in Xuzhou No.1 People's Hospital were enrolled in this study. Risk factors associated with their renal function, such as gender, serum levels of hemoglobin, uric acid, serum calcium and phosphorus, serum and urinary levels of ß2 microglobulin, diastolic blood pressure and light chain protein distribution were assessed before and after relative treatments. RESULTS: Compared with patients with normal renal function, the proportion of severe anemia, serum uric acid, calcium, and phosphorus levels were significantly higher in patients with abnormal renal function. Also, serum and urinary ß2 microglobulin levels and diastolic blood pressure were significantly higher in patients with abnormal renal function. Light chain protein of patients with abnormal renal function (mostly λ protein), severe anemia, abnormally increased calcium and high diastolic blood pressure were independent risk factors in renal injuries. Blood urea nitrogen (BUN) and creatinine levels in both groups returned to normal after the anemia was corrected. Compared with the abnormal renal function group, one-year survival rate in the normal renal function group with myeloma was significantly higher. CONCLUSION: Increased diastolic blood pressure, moderate and severe anemia as well as elevated level of serum calcium were independent risk factors for renal injuries in multiple myeloma. Blood pressure control (especially diastolic blood pressure) and correcting the anemia were proved to be effective means for reversing the disturbed renal function and ameliorating patients' quality of life .