Best approximation of $(\mathcal{G}_{1},\mathcal{G}_{2})$-random operator inequality in matrix Menger Banach algebras with application of stochastic Mittag-Leffler and $\mathbb{H}$-Fox control functions

We stabilize pseudostochastic $(\mathcal{G}_{1},\mathcal{G}_{2})$ ( G 1 , G 2 ) -random operator inequality using a class of stochastic matrix control functions in matrix Menger Banach algebras. We get an approximation for stochastic $(\mathcal{G}_{1},\mathcal{G}_{2})$ ( G 1 , G 2 ) -random operator inequality by means of both direct and fixed point methods. As an application, we apply both stochastic Mittag-Leffler and $\mathbb{H}$ H -fox control functions to get a better approximation in a random operator inequality.

Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data

The extracellular matrix (ECM) has historically been explored through proteomic methods. Whether or not global transcriptomics can yield meaningful information on the human matrisome is unknown. Gene expression data from 17,382 samples across 52 tissues, were obtained from the Genotype-Tissue Expression (GTEx) project. Additional datasets were obtained from The Cancer Genome Atlas (TCGA) program and the Gene Expression Omnibus for comparisons. Gene expression levels generally matched proteome-derived matrisome expression patterns. Further, matrisome gene expression properly clustered tissue types, with some matrisome genes including SERPIN family members having tissue-restricted expression patterns. Deeper analyses revealed 382 gene transcripts varied by age and 315 varied by sex in at least one tissue, with expression correlating with digitally imaged histologic tissue features. A comparison of TCGA tumor, TCGA adjacent normal and GTEx normal tissues demonstrated robustness of the GTEx samples as a generalized matrix control, while also determining a common primary tumor matrisome. Additionally, GTEx tissues served as a useful non-diseased control in a separate study of idiopathic pulmonary fibrosis (IPF) matrix changes, while identifying 22 matrix genes upregulated in IPF. Altogether, these findings indicate that the transcriptome, in general, and GTEx in particular, has value in understanding the state of organ ECM.

Cyber-physical systems matrix control model

The Industry 4.0 technologies oriented for the modern industry as an application to solve the cyber-physical production control general task are viewed. A task to control is positioned as a hierarchy, which require some special schemes cyber-physical systems interaction organization to be developed. The control task hierarchy is converted to the control means hierarchy, within which they preserve the cyber-physical systems groups coordination unity organized in the company functional divisions in structure principle with variable equipment consistency. Information and functional cyber-physical systems interconnection are proposed to be defined within the technical architecture providing cyber-physical production complex automatizing. In the control system they underline the information component realizing not only calculation functions measuring but also net communication. Controlling and being controlled cyber-physical systems are proposed to be united into structures actively interacting with functional company divisions into closed automatic loops working out information and signal actions. There is a cyber-physical production hierarchy structure example given based on control processes tides formalized in physical and virtual levels. There is a cyber-physical systems matrix control model given to coordinate calculations, communications and industrial automatics functionality.

Load Match-Oriented Coordinated Control for Modular High Temperature Gas-Cooled Reactor Based on Dynamic Matrix Control

To cope with the flexibility from both load side and supply side, nuclear power generation should provide flexible operation services to improve its economic competitiveness. The prerequisite of flexible operation is the real-time realization of the operation point which is usually achieved by unit coordinated control finding the setpoints of nuclear power, coolant flow and feedwater flow to meet various load demand and keep key parameters within reasonable limits. Modular high temperature gas-cooled reactor (MHTGR) is typically a small reactor and adopt adjustable helium flow, graphite and once through steam generator (OTSG) as coolant, moderator, heat exchanger, respectively. The thermal hydraulic characteristics of MHTGR are of significant difference compared with that of pressurized water reactor (PWR). As a result, the coordinated control design for MHTGR plant is quite different from the PWR. In this paper, the feedwater flow and control rods are solely used to regulate the steam temperature and nuclear power, respectively. Moreover, the so-called dynamic matrix control (DMC) then is utilized to realize the load match for MHTGR thermal power, where the setpoint of helium flow is regarded as manipulated variables and the modular thermal power is regarded as controlled variables to be optimized. The effectiveness of the proposed method is then tested and verified by a hardware-in-loop simulation through a commercial distributed control system (DCS).

Characterization of SARS-CoV-2 Genetic Material in Wastewater

SARS-CoV-2 genetic material has been detected in raw wastewater around the world throughout the COVID-19 pandemic and has served as a useful tool for monitoring community levels of SARS-CoV-2 infections. SARS-CoV-2 genetic material is highly detectable in a patient feces and the household wastewater for several days before and after a positive COVID-19 qPCR test from throat or sputum samples. Here, we characterize genetic material collected from raw wastewater samples and determine recovery efficiency during a concentration process. We find that pasteurization of raw wastewater samples did not reduce SARS-CoV-2 signal if RNA is extracted immediately after pasteurization. On the contrary, we find that signal decreased by approximately half when RNA was extracted 24-36 hours post-pasteurization and ~90% when freeze-thawed prior to concentration. As a matrix control, we use an engineered enveloped RNA virus. Surprisingly, after concentration, the recovery of SARS-CoV-2 signal is consistently higher than the recovery of the control virus leading us to question the nature of the SARS-CoV-2 genetic material detected in wastewater. We see no significant difference in signal after different 24-hour temperature changes; however, treatment with detergent decreases signal ~100-fold. Furthermore, the density of the samples is comparable to enveloped retrovirus particles, yet, interestingly, when raw wastewater samples were used to inoculate cells, no cytopathic effects were seen indicating that wastewater samples do not contain infectious SARS-CoV-2. Together, this suggests that wastewater contains fully intact enveloped particles.

Adding Matrix Control: Insertion-Deletion Systems with Substitutions III

Insertion-deletion systems have been introduced as a formalism to model operations that find their counterparts in ideas of bio-computing, more specifically, when using DNA or RNA strings and biological mechanisms that work on these strings. So-called matrix control has been introduced to insertion-deletion systems in order to enable writing short program fragments. We discuss substitutions as a further type of operation, added to matrix insertion-deletion systems. For such systems, we additionally discuss the effect of appearance checking. This way, we obtain new characterizations of the family of context-sensitive and the family of recursively enumerable languages. Not much context is needed for systems with appearance checking to reach computational completeness. This also suggests that bio-computers may run rather traditionally written programs, as our simulations also show how Turing machines, like any other computational device, can be simulated by certain matrix insertion-deletion-substitution systems.

Dynamic multi-objective matrix control for a class of switched systems

This article focuses on the tracking and stabilizing issues of a class of discrete switched systems. These systems are characterized by unknown switching sequences, a non-minimum phase, and time-varying or dead modes. In particular, for those governed by an indeterminate switching signal, it is very complicated to synthesize a control law able to systematically approach general reference-tracking difficulties. Taking into account the difficulty to express the dynamic of this class of systems, the present paper presents a new Dynamic matrix control method based on the multi-objective optimization and the truncated impulse response model. The formulation of the optimization problem aims to approach the general step-tracking issues under persistent and indeterminate mode changes and to overcome the stability problem along with retaining as many desirable features of the standard dynamic matrix control (DMC) method as possible. In addition, the formulated optimization problem integrates estimator variables able to manipulate the optimization procedure in favor of the active mode with an appropriate adjustment. It also provides a progressive and smooth multi-objective control law even in the presence of problems whether in subsystems or switching sequences. Finally, simulation examples and comparison tests are conducted to illustrate the potentiality and effectiveness of the developed method.