Adaptive Inverse Nonlinear Optimal Control Based on Finite-Time Concurrent Learning and Semidefinite Programming.

This article investigates the problem of inverse optimal control (IOC) for a class of nonlinear affine systems. An adaptive IOC approach is proposed to recover the cost functional using only the system state data, which integrates the finite-time concurrent learning (FTCL) technique and the semidefinite programming (SDP) technique. First, an identifier neural network (NN) is employed to approximate the unknown nonlinear control policy, and an FTCL-based update law is proposed to estimate the weights of the identifier NN online, which removes the traditional persistent excitation (PE) condition. Moreover, the finite-time convergence as well as the uniformly ultimately boundness (UUB) of estimation error of the identifier NN weights are analysed according to whether or not there exists the identifier NN approximation error. Then, with the help of a value NN for approximating the value function, an SDP problem with a quadratic objective function can be set up for determining the weighting matrices of the cost functional. Finally, simulation results are presented to validate the proposed method.

The safety of benzodiazepines and related drugs during pregnancy: an updated meta-analysis of cohort studies.

PURPOSE: The prevalence of benzodiazepines and related drugs (BZRDs) use during pregnancy increased sharply in recent years. Thus, there are concerns regarding the pregnancy outcomes following exposure to BZRDs. METHODS: Two electronic databases were thoroughly searched to identify related clinical studies published from inception until June 2023. English-language cohort studies with high-quality comparing antenatal BZRDs exposure to an unexposed group on any delivery outcome were included. RESULTS: Ten cohort studies that estimated adverse neonatal outcomes associated with exposure to BZRDs during pregnancy were included. Exposure to BZRDs during pregnancy was associated with an increased risk of congenital malformation [odds ratio (OR) 1.09, 95% confidence interval (CI) 1.05-1.13, p < 0.001], heart malformation (OR 1.13, 95% CI 1.04-1.22, p = 0.003), preterm birth (OR 1.45, 95% CI 1.23-1.7, p < 0.001), SGA (OR 1.18, 95% CI 1.08-1.29, P < 0.001), LBW (OR 1.42, 95% CI 1.25-1.6, p = 0.001) or low Apgar score (OR 1.42, 95% CI 1.08-1.87, p = 0.011),compared with no exposure. Further analyses limited to the first trimester exposure yielded consistent results. CONCLUSIONS: Exposure to BZRDs during pregnancy may be associated with several adverse neonatal outcomes. However, we could not rule out the potential indication confounding factor, further studies with high-quality that control for important confounders are still needed to verify our findings.

Nationwide survey of ticks on domesticated animals in Taiwan: Revealing the hidden threat to animal and public health.

Ticks are not only bloodsucking ectoparasites but also important vectors of tick-borne diseases (TBDs), posing significant threats to public and animal health. Domesticated animals serve as critical hosts for numerous ticks, highlighting the importance of understanding tick infestations in Taiwan. To address this knowledge gap, we conducted a nationwide survey to identify ticks on domesticated animals and associated environments in 2018 and 2019. A total of 6,205 ticks were collected from 1,337 host animals, revealing the presence of seven tick species, with Rhipicephalus microplus, and Rhipicephalus sanguineus being the dominant species. High infestation rates and widespread distribution of ticks were observed on domesticated animals, especially on dogs and cattle (yellow cattle and angus cattle), and the neighbouring grassland of yellow cattle. While this study has certain limitations, it provides valuable insights into the distribution and prevalence of ticks on domesticated animals in Taiwan and their implications for controlling TBDs. Further research is needed to comprehensively understand the complex interactions among ticks, hosts and pathogens.

Contralateral axillary lymph node metastasis in breast cancer: An oligometastatic-like disease.

BACKGROUND: Contralateral axillary lymph node metastasis (CAM) is rare. It remains controversial whether CAM should be regarded as a regional or distant metastatic disease. Our study aims to investigate the accurate clinical orientation and management of CAM. METHODS: Two hundred and ninety-nine female patients diagnosed with breast cancer from 2000 to 2014 and confirmed to develop CAM, oligometastasis (OM) or locoregional recurrence (LRR) at Fudan University Shanghai Cancer Center (FUSCC) were included in this study. Baseline information and survival outcomes were analyzed and compared among the three groups. RESULTS: Patients with CAM exhibited similar overall survival (OS) and progression-free survival (PFS) to those with OM, but worse than those with LRR (HR: 0.47 [95 % CI: 0.27-0.85], p = 0.0097; HR:0.39 [95 % CI: 0.24-0.63], p < 0.0001, respectively). Considering the patients presented with CAM or OM as a whole, we found that local treatment combined with systemic treatment did not provide a superior survival benefit over systemic treatment alone. CONCLUSION: CAM was similar to an oligometastatic-like disease, and patients with these diseases may benefit from systemic treatment. Adding local treatment failed to significantly improve OS.

Fuzzy Boundary Sampled-Data Control for Nonlinear Parabolic DPSs.

For a nonlinear parabolic distributed parameter system (DPS), a fuzzy boundary sampled-data (SD) control method is introduced in this article, where distributed SD measurement and boundary SD measurement are respected. Initially, this nonlinear parabolic DPS is represented precisely by a Takagi-Sugeno (T-S) fuzzy parabolic partial differential equation (PDE) model. Subsequently, under distributed SD measurement and boundary SD measurement, a fuzzy boundary SD control design is obtained via linear matrix inequalities (LMIs) on the basis of the T-S fuzzy parabolic PDE model to guarantee exponential stability for closed-loop parabolic DPS by using inequality techniques and a LF. Furthermore, respecting the property of membership functions, we present some LMI-based fuzzy boundary SD control design conditions. Finally, the effectiveness of the designed fuzzy boundary SD controller is demonstrated via two simulation examples.

From H12C4N2CdI4 to H11C4N2CdI3: a highly polarizable CdNI3 tetrahedron induced a sharp enhancement of second harmonic generation response and birefringence.

In this study, we identify a novel class of second-order nonlinear optical (NLO) crystals, non-π-conjugated piperazine (H10C4N2, PIP) metal halides, represented by two centimeter-sized, noncentrosymmetric organic-inorganic metal halides (OIMHs), namely H12C4N2CdI4 (P212121) and H11C4N2CdI3 (Cc). H12C4N2CdI4 is the first to be prepared, and its structure contains a CdI4 tetrahedron, which led to a poor NLO performance, including a weak and non-phase-matchable second harmonic generation (SHG) response of 0.5 × KH2PO4 (KDP), a small birefringence of 0.047 @1064 nm and a narrow bandgap of 3.86 eV. Moreover, H12C4N2CdI4 is regarded as the model compound, and we further obtain H11C4N2CdI3via the replacement of CdI4 with a highly polarizable CdNI3 tetrahedron, which results in a sharp enhancement of SHG response and birefringence. H11C4N2CdI3 exhibits a promising NLO performance including 6 × KDP, 4.10 eV, Δn = 0.074 @1064 nm and phase matchability, indicating that it is the first OIMH to simultaneously exhibit strong SHG response (>5 × KDP) and a wide bandgap (>4.0 eV). Our work presents a novel direction for designing high-performance NLO crystals based on organic-inorganic halides and provides important insights into the role of the hybridized tetrahedron in enhancing the SHG response and birefringence.

Adaptive event-triggered extended dissipative synchronization of delayed reaction-diffusion neural networks under deception attacks.

Under spatially averaged measurements (SAMs) and deception attacks, this article mainly studies the problem of extended dissipativity output synchronization of delayed reaction-diffusion neural networks via an adaptive event-triggered sampled-data (AETSD) control strategy. Compared with the existing ETSD control methods with constant thresholds, our scheme can be adaptively adjusted according to the current sampling and latest transmitted signals and is realized based on limited sensors and actuators. Firstly, an AETSD control scheme is proposed to save the limited transmission channel. Secondly, some synchronization criteria under SAMs and deception attacks are established by utilizing Lyapunov-Krasovskii functional and inequality techniques. Then, by solving linear matrix inequalities (LMIs), we obtain the desired AETSD controller, which can satisfy the specified level of extended dissipativity behaviors. Lastly, one numerical example is given to demonstrate the validity of the proposed method.

Prognostic factors and clinical outcomes of breast cancer patients with disease progression during neoadjuvant systemic therapy.

BACKGROUND: Disease progression during neoadjuvant systemic therapy for breast cancer indicates poor prognosis, while predictors of the clinical outcomes of these patients remain unclear. By comparing the clinical outcomes of patients with different patterns of salvage treatment strategies, we try to evaluate the factors predicting distant failure and explore the favourable treatment for them. METHODS: Patients with disease progression during neoadjuvant systemic therapy for stage I-III breast cancer diagnosed between January 1, 2008 and July 31, 2021 in Fudan University Shanghai Cancer Center were enrolled. Disease progression was defined as at least a 20% increase in the sum of diameters of target lesions or the appearance of new breast or nodal lesions. Kaplan-Meier, univariate and multivariate Cox proportional hazard regressions were utilized to compare survival outcomes between different salvage treatment strategies. RESULTS: Among 3775 patients treated with NST, 60 (1.6%) patients encountered disease progression. A significant difference between the outcomes of patients receiving direct surgery and other salvage modalities was found (p = 0.007). Triple-negative breast cancer (p = 0.010) and not receiving direct surgery (p = 0.016) were independently associated with distant disease-free survival on multivariate analysis. CONCLUSIONS: Predictors of distant failure in patients with disease progression include triple-negative breast cancer and not receiving direct surgery. Direct surgery seems to be more favourable than other treatments for patients with disease progression. For inoperable patients, neoadjuvant radiation can increase their operability but not improve their prognosis.

Plasma lipid profiles and homocysteine levels in anti-N-methyl-D-aspartate receptor encephalitis.

Introduction: We aimed to investigate whether lipid profiles and homocysteine levels in patients with anti-N-methyl-D-aspartate receptor encephalitis are related to clinical presentation and prognosis, which may contribute to further research on the pathogenesis and treatment of this disease. Methods: This study included a total of 43 patients with anti-N-methyl-D-aspartate receptor encephalitis and 43 sex-age-matched healthy controls. Baseline demography, clinical data, patient outcomes, and ancillary examination results were recorded. Patients were followed up every 2-3 months during the first year. The modified Rankin Scale score was used to evaluate the therapeutic effect and clinical outcome. Results: Among the 43 patients included in this study, 55.81% were male, the mean age of onset was 27 years old, and the median modified Rankin Scale score on admission was 3.0. Apolipoprotein A-1 was significantly lower in patients with anti-N-methyl-D-aspartate receptor encephalitis compared with healthy controls (p = 0.004). Compared with healthy controls, homocysteine (p = 0.002), apolipoprotein B (p = 0.004), Lpa (p = 0.045), and apolipoprotein B/apolipoprotein A-1 (p = 0.001) were significantly increased in patients with anti-N-methyl-D-aspartate receptor encephalitis. According to the modified Rankin Scale scores, 6 months after discharge, 72.09% of patients had a good prognosis and 27.91% had a poor prognosis. In the good prognosis group, age (p = 0.031), lipoprotein a (p = 0.023), apolipoprotein A-1 (p = 0.027) at baseline, and the modified Rankin Scale score on admission (p = 0.019) were significantly higher than those in the poor prognosis group. Conclusion: This study suggests the possibility that serum lipid profile and homocysteine play an important role in the pathogenesis of anti-N-methyl-D-aspartate receptor encephalitis, providing support for lipid-lowering treatment of anti-N-methyl-D-aspartate receptor encephalitis patients.

Learning Human Behavior in Shared Control: Adaptive Inverse Differential Game Approach.

To enhance the collaborative intelligence of a machine, it is important for the machine to understand what behavior a human may adopt to interact with the machine when performing a task in shared control. In this study, an online behavior learning method is proposed for continuous-time linear human-in-the-loop shared control systems by using the system state data only. A two-player nonzero-sum linear quadratic dynamic game paradigm is used for modeling the control interaction between a human operator and an automation that actively compensates for human control action. In this game model, the cost function representing the human behavior is assumed to have an unknown weighting matrix. Here, we want to learn the human behavior or retrieve the weighting matrix by using the system state data only. Accordingly, a new adaptive inverse differential game (IDG) method, which integrates concurrent learning (CL) and linear matrix inequality (LMI) optimization, is proposed. First, a CL-based adaptive law and an interactive controller of the automation are developed to estimate the feedback gain matrix of the human online, and second, an LMI optimization problem is solved to determine the weighting matrix of the human cost function. Finally, simulation results on a cooperative shared control driver assistance system are provided to elucidate the feasibility of the developed method.

Human-in-the-Loop Behavior Modeling via an Integral Concurrent Adaptive Inverse Reinforcement Learning.

One goal of artificial intelligence (AI) research is to teach machines how to learn from humans, such that they can perform a certain task in a natural human-like way. In this article, an online adaptive inverse reinforcement learning (IRL) approach to human behavior modeling is proposed to enhance machine intelligence for a class of linear human-in-the-loop (HiTL) systems using the state data only, where the human behavior is described by a linear quadratic optimal control model with an unknown weighting matrix for the quadratic cost function. First, an integral concurrent adaptive law is developed to learn the human feedback gain matrix online using the demonstrated state data only, which removes the persistent excitation (PE) conditions required by traditional adaptive estimation approaches and thus is more in line with real applications. Then, with the learned feedback gain matrix, the IRL problem is formulated as a linear matrix inequality (LMI) optimization problem, which can be efficiently solved to retrieve the weighting matrix of the human cost function. Finally, a simulation example is provided to illustrate the effectiveness of the proposed approach.

The main e-cigarette component vegetable glycerin enhances neutrophil migration and fibrosis in endotoxin-induced lung injury via p38 MAPK activation.

We investigated the effects of vegetable glycerin (VG), a main e-cigarette constituent, on endotoxin-induced acute lung injury (ALI). Mice received intratracheal administration of 30% VG in phosphate buffered saline (PBS) vehicle or only PBS (control) for 4 days. On Day 5, mice received an intratracheal instillation of lipopolysaccharide (LPS) (LPS group and VG + LPS group) or PBS (VG group and control group). Lung histopathology, expression of chemokine receptors, and regulatory signaling were analyzed 24 h after the Day 5 treatment. VG significantly increased ALI-associated histopathological and fibrotic changes in both the VG group and LPS-induced ALI mice (VG + LPS group). Immunohistochemistry (IHC) and western blot analyses revealed that VG administration resulted in upregulation of neutrophil markers [lymphocyte antigen 6 complex locus G6D (Ly6G) and myeloperoxidase (MPO)] as well as upregulation of the expression of transforming growth factor-ß (TGF-ß), a central mediator of fibrogenesis, in the lungs of both VG and VG + LPS groups. VG enhanced the expression of adhesion molecules [very late antigen 4 (VLA-4) and vascular cell adhesion molecule 1 (VCAM-1)] and increased activation of p38 mitogen-activated protein kinase (p38 MAPK) to prompt neutrophil recruitment in the lungs of mice with ALI. Intraperitoneal administration of a p38 inhibitor attenuated these histopathological changes significantly as well as VG-induced upregulation in expression of Ly6G, MPO, VLA-4, VCAM-1, TGF-ß, and collagen-1 in mice with ALI. In conclusion, VG enhances neutrophil chemotaxis and fibrosis and it amplifies the inflammatory response associated with LPS-induced ALI in the lungs via enhancement of p38 MAPK activity.

All HER2-negative breast cancer patients need gBRCA testing: cost-effectiveness and clinical benefits.

BACKGROUND: The OlympiA trial demonstrated the benefits of adjuvant usage of olaparib for high-risk patients with human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC) and germline BRCA (gBRCA) mutation. This provoked thoughts on the clinical criteria of gBRCA testing. This study aims to estimate the costs and benefits of gBRCA testing and adjuvant olaparib therapy for patients with triple-negative breast cancer (TNBC) and hormone-receptor (HR)-positive and HER2-negative BC in China and the United States of America (USA). METHODS: We used a Markov chain decision tree analytic model to compare three gBRCA screening policies in China and the USA: (1) no gBRCA testing; (2) selected gBRCA testing and (3) universal gBRCA testing for nonmetastatic TNBC and HR-positive HER2-negative BC patients. We modelled the benefit of systemic therapy and risk-reducing surgeries among patients identified with pathogenic or likely pathogenic variants (PVs) in BRCA1 and BRCA2. RESULTS: Changing from the selected gBRCA testing to the universal gBRCA testing in TNBC patients is cost-effective, with the incremental cost-effectiveness ratios (ICERs) being 10991.1 and 56518.2 USD/QALY in China and the USA, respectively. Expanding universal gBRCA testing to HR-positive HER2-negative BC and TNBC patients has ICERs of 2023.3 and 16611.1 USD/QALY in China and the USA, respectively. DISCUSSION: By performing gBRCA testing on all HER2-negative BC patients, adjuvant olaparib can be offered to high-risk patients with a PV in BRCA1 or BRCA2. These patients are also candidates for risk-reducing surgeries, an important aspect of their survivorship care, and these interventions can improve survival outcomes. With the willingness-to-pay thresholds being 31,500.0 and 100,000.0 USD per QALY gained in China and the USA, respectively, universal gBRCA testing is likely cost-effective for all HER2-negative BC patients. This simplified criterion of gBRCA testing for BC is recommended for adoption by current guidelines in China and the USA.

Passivity and Finite-Time Passivity for Multi-Weighted Fractional-Order Complex Networks With Fixed and Adaptive Couplings.

This article presents several new α -passivity and α -finite-time passivity ( α -FTP) concepts for the fractional-order systems with different input and output dimensions, which are distinct from the concepts for integer-order systems and extend the existing passivity and FTP definitions to some extent. On one hand, we not only develop some sufficient conditions for ensuring the α -passivity of the multi-weighted fractional-order complex dynamical networks (MWFOCDNs) with fixed and adaptive couplings, but also discuss the synchronization for the MWFOCDNs based on the α -output-strict passivity ( α -OSP). On the other hand, the α -FTP for the MWFOCDNs with fixed and adaptive couplings are also studied on the basis of the designed state feedback controller, and the relationship between finite-time synchronization (FTS) and α -FTP for the MWFOCDNs is also illustrated. Finally, two numerical examples with simulation results are used to demonstrate the validity of the obtained criteria.

Fuzzy Boundary Control for Nonlinear Delayed DPSs Under Boundary Measurements.

For nonlinear delayed distributed parameter systems (DDPSs), this article considers a fuzzy boundary control (FBC) under boundary measurements (BMs). Initially, we accurately describe the nonlinear DDPS through a Takagi-Sugeno (T-S) fuzzy partial differential-difference equation (PDDE). Then, in accordance with the T-S fuzzy PDDE model, an FBC design under BMs ensuring the exponential stability for closed-loop DDPS is subsequently presented by spatial linear matrix inequalities (SLMIs) via using Wirtinger's inequality, Halanay's inequality, and the Lyapunov direct method, which respects the fast-varying and slow-varying delays. Moreover, we formulate SLMIs as LMIs for solving the fuzzy boundary controller design of nonlinear DDPSs under BMs. Finally, the effectiveness of the proposed FBC strategy is presented via simulation examples.

Pinning Spatiotemporal Sampled-Data Synchronization of Coupled Reaction-Diffusion Neural Networks Under Deception Attacks.

In this article, we investigate the pinning spatiotemporal sampled-data (SD) synchronization of coupled reaction-diffusion neural networks (CRDNNs), which are directed networks with SD in time and space communications under random deception attacks. In order to handle with the random deception attacks, we establish a directed CRDNN model, which respects the impacts of variable sampling and random deception attacks within a unified framework. Through the designed pinning spatiotemporal SD controller, sufficient conditions are obtained by linear matrix inequalities (LMIs) that guarantee the mean square exponential stability of the synchronization error system (SES) derived by utilizing inequality techniques, the stochastic analysis technique, and Lyapunov-Krasovskii functional (LKF). Finally, a numerical example is utilized to support the presented pinning spatiotemporal SD synchronization method.

Finite-Time Passivity for Coupled Fractional-Order Neural Networks With Multistate or Multiderivative Couplings.

This article mainly delves into the finite-time passivity (FTP) for coupled fractional-order neural networks with multistate couplings (CFNNMSCs) or coupled fractional-order neural networks with multiderivative couplings (CFNNMDCs). Distinguishing from the traditional FTP definitions, several concepts of FTP for fractional-order systems are given. On one hand, we present several sufficient conditions to ensure the FTP for CFNNMSCs by artfully designing a state-feedback controller and an adaptive state-feedback controller. On the other hand, by utilizing some inequality techniques, two sets of FTP criteria for CFNNMDCs are also established on the basis of the state-feedback and adaptive state-feedback controllers. Finally, numerical examples are used to demonstrate the validity of the derived FTP criteria.

Exceptional Entanglement Phenomena: Non-Hermiticity Meeting Nonclassicality.

Non-Hermitian (NH) extension of quantum-mechanical Hamiltonians represents one of the most significant advancements in physics. During the past two decades, numerous captivating NH phenomena have been revealed and demonstrated, but all of which can appear in both quantum and classical systems. This leads to the fundamental question: what NH signature presents a radical departure from classical physics? The solution of this problem is indispensable for exploring genuine NH quantum mechanics, but remains experimentally untouched so far. Here, we resolve this basic issue by unveiling distinct exceptional entanglement phenomena, exemplified by an entanglement transition, occurring at the exceptional point of NH interacting quantum systems. We illustrate and demonstrate such purely quantum-mechanical NH effects with a naturally dissipative light-matter system, engineered in a circuit quantum electrodynamics architecture. Our results lay the foundation for studies of genuinely quantum-mechanical NH physics, signified by exceptional-point-enabled entanglement behaviors.