Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges

Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas. This fascination extends particularly to the Internet of Things (IoT), a landscape characterized by the interconnection of countless devices, sensors, and systems, collectively gathering and sharing data to enable intelligent decision-making and automation. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the IoT. Specifically, it starts by outlining the fundamental principles of IoT and the critical role of Artificial Intelligence (AI) in IoT systems. Subsequently, it delves into AGI fundamentals, culminating in the formulation of a conceptual framework for AGI's seamless integration within IoT. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education. However, adapting AGI to resource-constrained IoT settings necessitates dedicated research efforts. Furthermore, the paper addresses constraints imposed by limited computing resources, intricacies associated with large-scale IoT communication, as well as the critical concerns pertaining to security and privacy

A frequency domain iterative learning control for low bandwidth system

In this paper, a frequency-domain learning scheme based on the modified Fourier series for the tracking control of system with a low bandwidth limit is presented. The proposed controller consists of two parts: a PD controller and an online updated learning controller. The proposed method can reduce the tracking error more effectively than the same type of controller based on the conventional Fourier series approximation when the controlled system has a low-bandwidth. Experimental results on a belt-driven positioning table have shown that a considerable improvement can be achieved

A Fourier series based iterative learning control for nonlinear uncertain systems

In this paper, a Fourier series based learning controller for the tracking control of nonlinear uncertain systems is proposed. The Fourier series based learning controller consists of a PD part and a learning part. The learning part generates feed forward term based on the Fourier series approximation of the PD output. By introducing a system Input-Output (I/O) mapping matrix, the coupling effects of the PD output harmonics in the Fourier space are considered in our algorithm instead of treating them individually. Trajectory tracking experiments conducted on a belt driven positioning table indicated that the proposed method was more effective than the same type of controller without the I/O matrix

Fast ℓ₁-regularized space-Time adaptive processing using alternating direction method of multipliers

Motivated by the sparsity of filter coefficients in full-dimension space-Time adaptive processing (STAP) algorithms, this paper proposes a fast ℓ1-regularized STAP algorithm based on the alternating direction method of multipliers to accelerate the convergence and reduce the calculations. The proposed algorithm uses a splitting variable to obtain an equivalent optimization formulation, which is addressed with an augmented Lagrangian method. Using the alternating recursive algorithm, the method can rapidly result in a low minimum mean-square error without a large number of calculations. Through theoretical analysis and experimental verification, we demonstrate that the proposed algorithm provides a better output signal-To-clutter-noise ratio performance than other algorithms.Microwave Sensing, Signals & System

Hydrolysis of chitosan under microwave irradiation in ionic liquids promoted by sulfonic acid-functionalized ionic liquids

Natural Science Foundation of China [20673102]; Zhejiang Provincial Natural Science Foundation of China [Y404305]; Science and Technology Ministry of Zhejiang Province in China [2009C31084]; Chinese Zhaolong Bao & Yugang Bao scholarshipHydrolysis of chitosan in ionic liquids was carried out under microwave irradiation (MW) using sulfonic acid-functionalized ionic liquids (SFILs) as catalysts. The effect of microwave power, irradiation time, dosage of SFILs and DMSO was investigated by orthogonal tests. Under the optimal reaction conditions, the yield of total reducing sugars (TRS) reached over 90% within 2 min. The viscosity-average molecular weight of degraded chitosan was determined by viscosity method. The structures of the original and degraded chitosan were characterized by Fourier-transform infrared (FUR) spectra, X-ray powder diffraction (XRD) analysis and carbon-13 nuclear magnetic resonance spectroscopy (C-13 NMR). The influence of microwave power and irradiation time on the TRS and M-v was further studied. This method can dramatically reduce reaction time. (C) 2011 Elsevier Ltd. All rights reserved

Characterization of Residual Stress in SOI Wafers by Using MEMS Cantilever Beams

Silicon-on-insulator (SOI) wafers are crucial raw materials in the manufacturing process of microelectromechanical systems (MEMS). Residual stresses generated inside the wafers during the fabrication process can seriously affect the performance, reliability, and yield of MEMS devices. In this paper, a low-cost method based on mechanical modeling is proposed to characterize the residual stresses in SOI wafers in order to calculate the residual stress values based on the deformation of the beams. Based on this method, the residual strain of the MEMS beam, and thus the residual stress in the SOI wafer, were experimentally determined. The results were also compared with the residual stress results calculated from the deflection of the rotating beam to demonstrate the validity of the results obtained by this method. This method provides valuable theoretical reference and data support for the design and optimization of devices based on SOI-MEMS technology. It provides a lower-cost solution for the residual stress measurement technique, making it available for a wide range of applications

Interfacial Engineering Promoting Electrosynthesis of Ammonia over Mo/Phosphotungstic Acid with High Performance

Electrochemical nitrogen reduction reaction (eNRR) is recognized as a promising approach for ammonia synthesis, which is, however, impeded by the inert nitrogen and the unavoidable competing hydrogen evolution reaction (HER). Here, a Mo-PTA@CNT electrocatalyst in which Mo species are anchored on the fourfold hollow sites of phosphotungstic acid (PTA) and closely embedded in multi-walled carbon nanotubes (CNT) for immobilization is designed and synthesized. Interestingly, the catalyst presents a high ammonia yield rate of 51 +/- 1 mu g h(-1) mg(cat.)(-1) and an excellent Faradaic efficiency of 83 +/- 1% at -0.1 V versus RHE under ambient conditions. The concentrations of NH4+ are also quantitatively calculated by H-1 NMR spectra and ion chromatography. Isotopic labeling identifies that the N atom of the formed NH3 originates from N-2. The controlled experiments confirm a strong interaction between Mo-PTA and N-2 with an adsorption energy of 50.46 kJ mol(-1) and activation energy of 21.36 kJ mol(-1). More importantly, due to CNT's gas storage and hydrophobicity properties, there is a fourfold increase in N-2 content. The concentration of H2O is reduced by more than half at the interface of the electrode. Thus, the activity of eNRR can be significantly improved with ultrahigh electron selectivity

E3 ligase TRIM28 promotes anti-PD-1 resistance in non-small cell lung cancer by enhancing the recruitment of myeloid-derived suppressor cells

Abstract Background Alterations in several tripartite motif-containing (TRIM) family proteins have been implicated in the pathogenesis of lung cancer. TRIM28, a member of the TRIM E3 ligase family, has been associated with tumorigenesis, cell proliferation, and inflammation. However, little is known about TRIM28 expression and its role in the immune microenvironment of non-small cell lung cancer (NSCLC). Methods We assessed the clinical significance of TRIM28 in tissue microarrays and TCGA cohorts. We investigated the function of TRIM28 in syngeneic mouse tumor models, the Kras LSL−G12D/+ ; Tp53 fl/fl (KP) mouse model, and humanized mice. Immune cell composition was analyzed using flow cytometry and immunohistochemistry. Results Our findings revealed a positive correlation between TRIM28 expression and the infiltration of suppressive myeloid-derived suppressor cells (MDSCs) in NSCLC. Moreover, silencing TRIM28 enhanced the efficacy of anti-PD-1 immunotherapy by reshaping the inflamed tumor microenvironment. Mechanistically, we demonstrated that TRIM28 could physically interact with receptor-interacting protein kinase 1 (RIPK1) and promote K63-linked ubiquitination of RIPK1, which is crucial for sustaining activation of the NF-κB pathway. Mutagenesis of the E3 ligase domain corroborated the essential role of E3 ligase activity in TRIM28-mediated NF-κB activation. Further experiments revealed that TRIM28 could upregulate the expression of CXCL1 by activating NF-κB signaling. CXCL1 could bind to CXCR2 on MDSCs and promote their migration to the tumor microenvironment. TRIM28 knockdown increased responsiveness to anti-PD-1 therapy in immunocompetent mice, characterized by increased CD8+T tumor-infiltrating lymphocytes and decreased MDSCs. Conclusion The present study identified TRIM28 as a promoter of chemokine-driven recruitment of MDSCs through RIPK1-mediated NF-κB activation, leading to the suppression of infiltrating activated CD8+T cells and the development of anti-PD-1 resistance. Understanding the regulation of MDSC recruitment and function by TRIM28 provides crucial insights into the association between TRIM28 signaling and the development of an immunosuppressive tumor microenvironment. These insights may inform the development of combination therapies to enhance the effectiveness of immune checkpoint blockade therapy in NSCLC