CBLL1 promotes endometrial stromal cell senescence via inhibiting PTEN in recurrent spontaneous abortion.

Recurrent spontaneous abortion (RSA) is a common pregnancy-related disorder. Cbl proto-oncogene like 1 (CBLL1) is an E3 ubiquitin ligase, which has been reported to vary with the menstrual cycle in the endometrium. However, whether CBLL1 is involved in the occurrence and development of RSA remains unclear. This study aimed to investigate the effects of CBLL1 on RSA. We analyzed the expression of CBLL1 in the decidua of RSA patients, as well as its functional effects on cellular senescence, oxidative stress, and proliferation of human endometrial stromal cells (HESCs). RNA sequencing was employed to identify a key downstream target gene regulated by CBLL1. We found that CBLL1 was upregulated in the decidua of RSA patients. Additionally, overexpression of CBLL1 promoted HESC senescence, increased oxidative stress levels, and inhibited proliferation. Phosphatase and tensin homolog located on chromosome 10 (PTEN) was identified as one of the important downstream target genes of CBLL1. In vivo experiments demonstrated that CBLL1 overexpression in the endometrium caused higher embryo absorption rate in mice. Consequently, elevated CBLL1 expression is a potential cause of RSA, representing a novel therapeutic target for RSA.

CD8+ T cells in fetal membranes display a unique phenotype, and their activation is involved in the pathophysiology of spontaneous preterm birth.

Preterm labor/birth is the leading cause of perinatal mortality and morbidity worldwide. Previous studies demonstrated that T cells were crucial for maintaining maternal-fetal immune tolerance during the first trimester of pregnancy; however, their phenotypes and functions in labor and delivery remain largely unknown. We recruited three cohorts of women at delivery for T-cell immunophenotyping in the placentas, fetal membranes, umbilical cord blood, and maternal peripheral blood. Our data showed a differential enrichment of T cells during the third trimester of human pregnancy, with CD4+ T cells being more observable within the umbilical cord blood, whereas CD8+ T cells became relatively more abundant in fetal membranes. CD4+ and CD8+ T cells derived from fetal membranes were dominated by effector memory T cells and exhibited extensive expression of activation markers but decreased expression of homing receptor. In comparison with term births, fetal membrane CD8+ T cells, especially the central memory subset, were significantly increased in frequency and showed more profound activation in spontaneous preterm birth patients. Finally, using an allogeneic mouse model, we found that T-cell-activation-induced preterm birth could be alleviated by the depletion of CD8+ T but not CD4+ T cells in vivo. Collectively, we showed that CD8+ T cells in fetal membranes displayed a unique phenotype, and their activation was involved in the pathophysiology of spontaneous preterm birth, which provides novel insights into the immune mechanisms of preterm birth and potential targets for the prevention of this syndrome. © 2023 The Pathological Society of Great Britain and Ireland.

Epigenetic drug screening for trophoblast syncytialization reveals a novel role for MLL1 in regulating fetoplacental growth.

BACKGROUND: Abnormal placental development is a significant factor contributing to perinatal morbidity and mortality, affecting approximately 5-7% of pregnant women. Trophoblast syncytialization plays a pivotal role in the establishment and maturation of the placenta, and its dysregulation is closely associated with several pregnancy-related disorders, including preeclampsia and intrauterine growth restriction. However, the underlying mechanisms and genetic determinants of syncytialization are largely unknown. METHODS: We conducted a systematic drug screen using an epigenetic compound library to systematically investigate the epigenetic mechanism essential for syncytialization, and identified mixed lineage leukemia 1 (MLL1), a histone 3 lysine 4 methyltransferase, as a crucial regulator of trophoblast syncytialization. BeWo cells were utilized to investigate the role of MLL1 during trophoblast syncytialization. RNA sequencing and CUT&Tag were further performed to search for potential target genes and the molecular pathways involved. Human placenta tissue was used to investigate the role of MLL1 in TEA domain transcription factor 4 (TEAD4) expression and the upstream signaling during syncytialization. A mouse model was used to examine whether inhibition of MLL1-mediated H3K4me3 regulated placental TEAD4 expression and fetoplacental growth. RESULTS: Genetic knockdown of MLL1 or pharmacological inhibition of the MLL1 methyltransferase complex (by MI-3454) markedly enhanced syncytialization, while overexpression of MLL1 inhibited forskolin (FSK)-induced syncytiotrophoblast formation. In human placental villous tissue, MLL1 was predominantly localized in the nuclei of cytotrophoblasts. Moreover, a notable upregulation in MLL1 expression was observed in the villus tissue of patients with preeclampsia compared with that in the control group. Based on RNA sequencing and CUT&Tag analyses, depletion of MLL1 inhibited the Hippo signaling pathway by suppressing TEAD4 expression by modulating H3K4me3 levels on the TEAD4 promoter region. TEAD4 overexpression significantly reversed the FSK-induced or MLL1 silencing-mediated trophoblast syncytialization. Additionally, decreased hypoxia-inducible factor 1A (HIF1A) enrichment at the MLL1 promoter was observed during syncytialization. Under hypoxic conditions, HIF1A could bind to and upregulate MLL1, leading to the activation of the MLL1/TEAD4 axis. In vivo studies demonstrated that the administration of MI-3454 significantly enhanced fetal vessel development and increased the thickness of the syncytial layer, thereby supporting fetoplacental growth. CONCLUSIONS: These results revealed a novel epigenetic mechanism underlying the progression of syncytialization with MLL1, and suggest potential avenues for identifying new therapeutic targets for pregnancy-related disorders.

Decreased thrombospondin-1 impairs endometrial stromal decidualization in unexplained recurrent spontaneous abortion†.

Inappropriate endometrial stromal decidualization has been implied as an important reason of many pregnancy-related complications, such as unexplained recurrent spontaneous abortion, preeclampsia, and intrauterine growth restriction. Here, we observed that thrombospondin-1, an adhesive glycoprotein, was significantly downregulated in endometrial decidual cells from patients with unexplained recurrent spontaneous abortion. The immortalized human endometrial stromal cell line was used to investigate the possible THBS1-mediated regulation of decidualization. In vitro experiments found that the expression level of THBS1 increased with the normal decidualization process. Knockdown of THBS1 could decrease the expression levels of prolactin and insulin-like growth factor binding protein-1, two acknowledged human decidualization markers, whereas THBS1 overexpression could reverse these effects. The RNA sequencing results demonstrated that the extracellular regulated protein kinases signaling pathway was potentially affected by the knockdown of THBS1. We further confirmed that the regulation of THBS1 on decidualization was achieved through the ERK signaling pathway by the treatment of inhibitors. Moreover, knockdown of THBS1 in pregnant mice could impair decidualization and result in an increased fetus resorption rate. Altogether, our study demonstrated a crucial role of THBS1 in the pathophysiological process of unexplained recurrent spontaneous abortion and provided some new insights into the research of pregnancy-related complications.

Peroxiredoxin2 regulates trophoblast proliferation and migration through SPIB-HDAC2 pathway.

Adequate proliferation and migration of placental trophoblasts is the prerequisite of a successful pregnancy. Peroxiredoxin2 (Prdx2) is a multi-functional gene involved in various signal events to maintain essential biological functions and normal cellular homeostasis. In this study, substantially lower Prdx2 levels were found in the first trimester cytotrophoblasts of women who suffered from recurrent miscarriage (RM). Prdx2 downregulation inhibited trophoblast proliferation and migration. We demonstrated that histone deacetylase2 (HDAC2) acts downstream of Prdx2 in regulating trophoblast proliferation and migration. HDAC2 deacetylates histone-3-lysine-9 in E-cadherin (E-cad) promoter and reduces the transcription of E-cad epigenetically, whereas it promotes the expression of Slug and Snail genes. These molecular changes may contribute to the trophoblast epithelial-mesenchymal transition. We further verified whether Prdx2 modulated the expression of HDAC2 through SPIB. SPIB could bind to the HDAC2 promoter PU-box region and induce HDAC2 expression. In RM, down-regulated Prdx2 suppresses SPIB-HDAC2 pathway, leading to increased E-cad and decreased Slug and Snail, and eventually restrains trophoblast proliferation and migration. Our study unveils the role of Prdx2-regulated SPIB-HDAC2 pathway in the pathology of RM and provides diagnostic and therapeutic targets for RM as well as other "great obstetrical syndromes" including preeclampsia and intrauterine growth restriction.

A Secure Scheme for Distributed Consensus Estimation against Data Falsification in Heterogeneous Wireless Sensor Networks.

Heterogeneous wireless sensor networks (HWSNs) can achieve more tasks and prolong the network lifetime. However, they are vulnerable to attacks from the environment or malicious nodes. This paper is concerned with the issues of a consensus secure scheme in HWSNs consisting of two types of sensor nodes. Sensor nodes (SNs) have more computation power, while relay nodes (RNs) with low power can only transmit information for sensor nodes. To address the security issues of distributed estimation in HWSNs, we apply the heterogeneity of responsibilities between the two types of sensors and then propose a parameter adjusted-based consensus scheme (PACS) to mitigate the effect of the malicious node. Finally, the convergence property is proven to be guaranteed, and the simulation results validate the effectiveness and efficiency of PACS.

Balancing energy consumption with hybrid clustering and routing strategy in wireless sensor networks.

Multi-hop data collection in wireless sensor networks (WSNs) is a challenge issue due to the limited energy resource and transmission range of wireless sensors. The hybrid clustering and routing (HCR) strategy has provided an effective solution, which can generate a connected and efficient cluster-based topology for multi-hop data collection in WSNs. However, it suffers from imbalanced energy consumption, which results in the poor performance of the network lifetime. In this paper, we evaluate the energy consumption of HCR and discover an important result: the imbalanced energy consumption generally appears in gradient k = 1, i.e., the nodes that can communicate with the sink directly. Based on this observation, we propose a new protocol called HCR-1, which includes the adaptive relay selection and tunable cost functions to balance the energy consumption. The guideline of setting the parameters in HCR-1 is provided based on simulations. The analytical and numerical results prove that, with minor modification of the topology in Sensors 2015, 15 26584 gradient k = 1, the HCR-1 protocol effectively balances the energy consumption and prolongs the network lifetime.

An energy-efficient underground localization system based on heterogeneous wireless networks.

A precision positioning system with energy efficiency is of great necessity for guaranteeing personnel safety in underground mines. The location information of the miners' should be transmitted to the control center timely and reliably; therefore, a heterogeneous network with the backbone based on high speed Industrial Ethernet is deployed. Since the mobile wireless nodes are working in an irregular tunnel, a specific wireless propagation model cannot fit all situations. In this paper, an underground localization system is designed to enable the adaptation to kinds of harsh tunnel environments, but also to reduce the energy consumption and thus prolong the lifetime of the network. Three key techniques are developed and implemented to improve the system performance, including a step counting algorithm with accelerometers, a power control algorithm and an adaptive packets scheduling scheme. The simulation study and experimental results show the effectiveness of the proposed algorithms and the implementation.

An automatic progressive chromosome segmentation approach using deep learning with traditional image processing.

The fully automatic chromosome analysis system plays an important role in the detection of genetic diseases, which in turn can reduce the diagnosis burden for cytogenetic experts. Chromosome segmentation is a critical step for such a system. However, due to the non-rigid structure of chromosomes, chromosomes may curve in any direction, and two or more chromosomes may touch or overlap to form unpredictable chromosome clusters in metaphase chromosome images, leading to automatic chromosome segmentation as a challenge. In this paper, we propose an automatic progressive segmentation approach to perform the entire metaphase chromosome image segmentation using deep learning with traditional image processing. It follows three stages. In the first stage, thresholding-based and geometric-based methods are employed to divide all chromosomes as single ones and chromosome clusters. To tackle the segmentation for unpredictable chromosome clusters, we first present a new chromosome cluster identification network named CCI-Net to classify all chromosome clusters into different types in the second stage, and then in the third stage, we combine traditional image processing with deep CNNs to accomplish chromosome instance segmentation from different types of clusters. Evaluation results on a clinical dataset of 1148 metaphase chromosome images show that the proposed automatic progressive segmentation method achieves 94.60% chromosome cluster identification accuracy and 99.15% instance segmentation accuracy. The experimental results exhibit that our proposed approach can effectively identify chromosome clusters and successfully perform fully automatic chromosome segmentation.

Bearing-Based Robust Formation Tracking Control of Underactuated AUVs With Optimal Parameter Tuning.

This article investigates the control problem of bearing-based formation tracking for underactuated autonomous underwater vehicles (AUVs) considering actuator constraints and unknown disturbances. A leader-follower structure is adopted, where the leaders move with an unknown reference velocity. For the followers, an integrated strategy is proposed, which includes i) a bearing-based control method composed of a reference velocity estimator, a virtual velocity for achieving the desired formation, and an adaptive robust formation controller to track the virtual velocity under disturbances; and ii) a parameter tuning method based on control parameterization approaches and heuristic algorithms. By employing the cascade system theory, asymptotic convergence of errors in the overall system is proved in the presence of unknown disturbances. The tuning method optimizes controller gains to ensure, all while preserving the convergence properties of the closed-loop error system constraint feasibility and performance optimality. As a result, convergence, robustness, feasibility, and optimality are all achieved. Extension to the case where AUVs have sideslip motions in 3-D space is also discussed. Simulation results are presented to demonstrate the effectiveness of the proposed strategy.

Bearing Rigidity-Based Flocking Control of AUVs via Semi-Supervised Incremental Broad Learning.

Flocking control of autonomous underwater vehicles (AUVs) has been regarded as the basis of many sophisticated marine coordination missions. However, there is still a research gap on the flocking of AUVs in weak communication and complex marine environment. This article attempts to fill up the above research gap from graph theory and intelligent learning perspectives. We first employ the bearing rigidity graph to describe the topology relationships of AUVs, through which an iterative gradient decent-based localization estimator is provided to obtain the position information. In order to improve the localization accuracy and energy efficiency, a min-weighted bearing rigidity graph generation strategy is developed. Along with this, we adopt the semi-supervised broad learning system (BLS) to design the model-free flocking controllers for AUVs in obstacle environment. The innovations of this article are summarized as follows: 1) the min-weighted bearing rigidity-based localization strategy can balance the localization accuracy and communication consumption as compared to the neighboring rule-based solutions and 2) the semi-supervised broad learning-based flocking controller can decrease the training time and solve the label limit over the supervised learning-based controllers. Finally, simulation and experimental studies are provided to verify the effectiveness.

PDE12 disrupts mitochondrial oxidative phosphorylation and mediates mitochondrial dysfunction to induce oral mucosal epithelial barrier damage in oral submucous fibrosis.

Oral submucous fibrosis (OSF) is a chronic oral mucosal disease. The pathological changes of OSF include epithelial damage and subepithelial matrix fibrosis. This study aimed to reveal the epithelial injury mechanism of OSF. A histopathological method was used to analyze oral mucosal tissue from OSF patients and OSF rats. The expression of PDE12 in the oral epithelium was analyzed by immunohistochemistry. The epithelial-mesenchymal transition (EMT) and tight junction proteins in arecoline-treated HOKs were explored by western blotting. Epithelial leakage was assessed by transepithelial electrical resistance and lucifer yellow permeability. The expression of PDE12 and the mitochondrial morphology, mitochondrial permeability transition pore opening, mitochondrial membrane potential, and mitochondrial reactive oxygen species (mtROS) were evaluated in arecoline-induced HOKs. Oxidative phosphorylation (OXPHOS) complexes and ATP content were also explored in HOKs. The results showed significant overexpression of PDE12 in oral mucosal tissue from OSF patients and rats. PDE12 was also overexpressed and aggregated in mitochondria in arecoline-induced HOKs, resulting in dysfunction of OXPHOS and impaired mitochondrial function. An EMT, disruption of tight junctions with epithelial leakage, and extracellular matrix remodeling were also observed. PDE12 overexpression induced by PDE12 plasmid transfection enhanced the mtROS level and interfered with occludin protein localization in HOKs. Interestingly, knockdown of PDE12 clearly ameliorated arecoline-induced mitochondrial dysfunction and epithelial barrier dysfunction in HOKs. Therefore, we concluded that overexpression of PDE12 impaired mitochondrial OXPHOS and mitochondrial function and subsequently impaired epithelial barrier function, ultimately leading to OSF. We suggest that PDE12 may be a new potential target against OSF.

DOCK1 insufficiency disrupts trophoblast function and pregnancy outcomes via DUSP4-ERK pathway.

Abnormal trophoblast function is associated with diseases such as recurrent spontaneous abortion, pre-eclampsia, and preterm birth, and endangers maternal and fetal health. However, the underlying regulatory mechanisms remain unclear. In this study, we found DOCK1 expression is decreased in the placental villi of patients with recurrent spontaneous abortion, and that its expression determined the invasive properties of extravillous trophoblasts (EVTs), highlighting a previously unknown role of DOCK1 in regulating EVT function. Furthermore, DOCK1 deficiency disturbed the ubiquitinated degradation of DUSP4, leading to its accumulation. This caused inactivation of the ERK signaling pathway, resulting in inadequate EVT migration and invasion. DOCK1 was implicated in regulating the ubiquitin levels of DUSP4, possibly by modulating the E3 ligase enzyme HUWE1. The results of our in vivo experiments confirmed that the DOCK1 inhibitor TBOPP caused miscarriage in mice by inactivating the DUSP4/ERK pathway. Collectively, our results revealed the crucial role of DOCK1 in the regulation of EVT function via the DUSP4-ERK pathway and a basis for the development of novel treatments for adverse pregnancy outcomes caused by trophoblast dysfunction.

Effect of maternal serum albumin level on birthweight and gestational age: an analysis of 39200 singleton newborns.

Background: Serum albumin plays a pivotal role in regulating plasma oncotic pressure and modulating fluid distribution among various body compartments. Previous research examining the association between maternal serum albumin levels and fetal growth yielded limited and inconclusive findings. Therefore, the specific influence of serum albumin on fetal growth remains poorly understood and warrants further investigation. Methods: A retrospective study involved 39200 women who had a singleton live birth at a tertiary-care academic medical center during the period from January 2017 to December 2020. Women were categorized into four groups according to the quartile of albumin concentration during early pregnancy: Q1 group, ≤41.0 g/L; Q2 group, 41.1-42.6 g/L; Q3 group, 42.7-44.3 g/L and Q4 group, >44.3 g/L. The main outcome measures were mid-term estimated fetal weight, birthweight and gestational age. Multivariate linear and logistic regression analysis were performed to detect the independent effect of maternal serum albumin level on fetal growth after adjusting for important confounding variables. Results: In the crude analysis, a significant inverse correlation was found between early pregnancy maternal serum albumin levels and fetal growth status, including mid-term ultrasound measurements, mid-term estimated fetal weight, birthweight, and gestational age. After adjustment for a number of confounding factors, mid-term estimated fetal weight, birthweight, and birth height decreased significantly with increasing albumin levels. Compared to the Q2 group, the Q4 group had higher rates of preterm birth (aOR, 1.16; 95% CI, 1.01-1.34), small-for-gestational-age (aOR, 1.27; 95% CI, 1.11-1.45) and low birthweight (aOR, 1.41; 95% CI, 1.18-1.69), and lower rate of large-for-gestational-age (aOR, 0.85; 95% CI, 0.78-0.94). Moreover, to achieve the optimal neonatal outcome, women with higher early pregnancy albumin levels required a greater reduction in albumin levels in later pregnancy stages. Conclusions: A higher maternal serum albumin level during early pregnancy was associated with poor fetal growth, with the detrimental effects becoming apparent as early as the mid-gestation period. These findings provided vital information for clinicians to predict fetal growth status and identify cases with a high risk of adverse neonatal outcomes early on.

Energy-Efficient Optimal Sensor Scheduling for State Estimation Over Multihop Sensor Networks.

In this article, we consider the power scheduling problem of the multihop transmission with limited power resources. For a discrete-time linear time-invariant process, we consider a more practical scenario where the forward-error-correcting (FEC) coding scheme is utilized. An approximate communication model is introduced to formulate the nonanalytical relationship between the consumption of power and the successful-decoding-probability. For the single-hop transmission, we propose an analytical method to figure out the optimal offline scheduling for the finite-time case and the optimal periodic schedule for the infinite-time case. We consider the process and terminal errors simultaneously, and explicitly discuss how different values of parameters affect the optimality. Moreover, we extend our conclusions to the multihop case. In order to deal with the difficulty and complexity brought by the multihop scenario, a novel method based on the equivalent-scheduling matrix (ESM) is proposed to describe the accumulated effects through the multihop transmission. Meanwhile, explicit solutions of the multihop case are provided for finite- and infinite-time cases, respectively. Numerical examples are provided to demonstrate the effectiveness of the proposed methods.

Bearing-Based Formation Tracking Control With Time-Varying Velocity Estimation.

This article studies the bearing-based formation tracking control problem of multiple double-integrator agents. A leader-following structure, where the leader moves with the reference dynamics, is adopted. Different from the existing methods, which require complete information of the time-varying reference velocity, in this article, only the time-varying reference orientation information is known by part of the followers and the amplitude of the reference velocity is unknown. To solve the problem, this article proposes a velocity-estimation-based control scheme, which consists of an estimator for estimating the varying rate of the reference orientation, an adaptation law for estimating the amplitude of the reference velocity, and bearing-based control inputs for tracking the leader and achieving the bearing-based formation based on the estimations. Moreover, the scaling formation maneuver can be achieved by using an auxiliary distance measurement. It shows that both the estimation errors and control errors converge to zero under the connectivity of the topology and properties of bearing rigidity. The closed-loop system is analyzed to be semiglobally uniformly asymptotically stable based on the cascaded system theory. Numerical simulations are presented to demonstrate the effectiveness of our method.

Adverse obstetric and perinatal outcomes of patients with history of recurrent miscarriage: a retrospective cohort study.

OBJECTIVE: To examine the associations between a history of recurrent miscarriage (RM) and adverse obstetric and perinatal outcomes in the subsequent pregnancy that progressed beyond 24 weeks. DESIGN: Retrospective cohort study. SETTING: A large tertiary maternity hospital. PATIENT(S): All women who booked for antenatal care and delivery between January 2014 and August 2021 were recorded. The study was limited to women with a singleton pregnancy, and to avoid intraperson correlation, we selected the first record of delivery from each mother in the study, leaving 108,792 deliveries for analysis. Obstetric and perinatal outcomes were compared among 1994 women (1.83%) with a history of ≥2 miscarriages (RM), 11,477 women (10.55%) with a history of 1 miscarriage, and 95,321 women (87.62%) with no history of miscarriage, respectively. INTERVENTION(S): Women with a history of ≥2 miscarriages or RM. MAIN OUTCOME MEASURE(S): Obstetric complications included gestational diabetes mellitus, preeclampsia (subclassified as preterm and term preeclampsia), placenta previa, placenta accreta, and fetal distress. Perinatal outcomes included emergency cesarean section, elective cesarean section, induction, postpartum hemorrhage, preterm birth, stillbirth, Apgar score <7 at 5 minutes, neonatal asphyxia, neonatal sex, congenital; malformation, low birth weight, and neonatal death. RESULT(S): After adjusting for relevant confounders, there was an increased risk of adverse obstetric and perinatal outcomes in a subsequent pregnancy for women with a history of RM, specifically for placental dysfunction disorders: preterm preeclampsia (risk ratio [RR] = 1.58; 95% confidence interval [CI], 1.03-2.32), preterm birth (RR = 1.34; 95% CI, 1.15-1.54)], and abnormal placentation, that is placenta previa (RR = 1.78; 95% CI, 1.36-2.28), and placenta accreta (RR = 4.19; 95% CI, 2.75-6.13). CONCLUSION(S): Significant associations existed between a history of RM and the occurrence of adverse obstetric and perinatal outcomes including placental dysfunction disorders and abnormal placentation. These findings may contribute to the early detection and appropriate intervention for placenta-associated diseases in women with a history of RM, with the goal of avoiding or reducing the associated detrimental effects.

Communication-Efficient and Collision-Free Motion Planning of Underwater Vehicles via Integral Reinforcement Learning.

Motion planning of underwater vehicles is regarded as a promising technique to make up the flexibility deficiency of underwater sensor networks (USNs). Nonetheless, the unique characteristics of underwater channel and environment make it challenging to achieve the above mission. This article is concerned with a communication-efficient and collision-free motion planning issue for underwater vehicles in fading channel and obstacle environment. We first develop a model-based integral reinforcement learning (IRL) estimator to predict the stochastic signal-to-noise ratio (SNR). With the estimated SNR, an integrated optimization problem for the codesign of communication efficiency and motion planning is constructed, in which the underwater vehicle dynamics, communication capacity, collision avoidance, and position control are all considered. In order to tackle this problem, a model-free IRL algorithm is designed to drive underwater vehicles to the desired position points while maximizing the communication capacity and avoiding the collision. It is worth mentioning that, the proposed motion planning solution in this article considers a realistic underwater communication channel, as well as a realistic dynamic model for underwater vehicles. Finally, simulation and experimental results are demonstrated to verify the effectiveness of the proposed approach.

Edge Sensing and Control Co-Design for Industrial Cyber-Physical Systems: Observability Guaranteed Method.

The new generation of the industrial cyber-physical system (ICPS) supported by the edge computing technology facilitates the deep integration of sensing and control. System observability is the key factor to characterize the internal relationship of them. In most existing works, the observability is regarded as the assumption for subsequent sensing and control. But, in fact, with the gradually expanded network scale, this assumption is more difficult to directly satisfy sensing design. For this problem, we propose the observability guaranteed method (OGM) for edge sensing and control co-design. Specifically, the nonconvex observability condition is transformed into the convex range of key parameters of the sensing strategy based on the graph signal processing (GSP) technology. Then, we establish the relationship between these parameters and control performance. In OGM, except the previous design from sensing to control, we reversely adjust the sensing design for control demands to satisfy observability. Finally, our algorithm is applied into the hot rolling laminar cooling process based on the semiphysical evaluation. The effectiveness is verified by the results.

Sensor scheduling for relay-assisted wireless control systems with limited power resources.

In this paper, we investigate the transmission scheduling problem for wireless control systems (WCSs) with limited power resources. Different from the existing works, for a discrete-time linear process, we consider a more practical WCS, where a relay is introduced into the framework for remote transmission and control. To achieve the best control performance of the system, we propose a global optimal offline scheduling algorithm. Then, based on ACK-feedback framework, two different online scheduling schemes are further designed respectively under the given power resources. Theoretically, we prove the superiority of online schedule to the offline one under the same energy budget. Simulations are conducted to demonstrate and verify the effectiveness of the proposed algorithms.