According to global cancer data, lung cancer was the leading cause of cancer-related death in 2020. With the diversification of treatment strategies, the survival outcomes of patients with advanced lung cancer have improved significantly, but the 5-year overall survival rate remains <20%. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are the preferred treatment for lung adenocarcinoma patients with EGFR-sensitive mutations; however, acquired drug resistance is inevitable. Osimertinib (a third-generation EGFR inhibitor) is the most commonly used drug for cancers with a secondary T790M mutation. Unfortunately, acquired drug resistance against third-generation drugs still emerges. The C797s mutation is the primary acquired resistance mechanism against Osimertinib. Research on fourth-generation EGFR-TKI drugs with a C797s mutation is currently at various experimental stages, and no drug has been approved for clinical use. In addition to the resistance mechanisms described above, HER2 amplification, MET amplification, PIK3A mutation, KRAS mutation, BRAF mutation, transformation to small cell lung cancer, transformation to lung squamous cell carcinoma, and EMT have been reported as mechanisms of acquired drug resistance to first-, second-and third-generation EGFR-TKIs. These mechanisms are noted in a relatively high proportion of tumors, but treatment options are limited. In recent years, immunotherapy has made progress in the treatment of several cancers, including advanced EGFR-mutated non-small cell lung cancer (NSCLC). Due to the relatively high frequency of EGFR mutation in patients with lung adenocarcinoma in China, an increased number of patients develop EGFR-TKI resistance, and subsequent treatment options are critical. This article reviews the mechanisms of drug resistance to different EGFR-TKIs and treatment progression, providing ideas for the follow-up treatment for EGFR-resistant patients.

The design, research and development, test, operation and maintenance of power grid substation equipment are relatively independent. Related problems in each link cannot be comprehensively managed from the perspective of the full life cycle of equipment. Operation and maintenance personnel need to face data monitoring, network monitoring, equipment monitoring, business system monitoring, fault diagnosis and repair and other business scenarios. There are many types of information, complex association relationship, abstract and inefficient operation and maintenance information, “man-machine-object” can not be two-way cooperation and interaction, fault diagnosis and troubleshooting difficulties. Digital substation intelligent monitoring operational digital twin applications, digital intelligent substation operations provide operational monitoring service ability, realize the grid digital substation twin modeling and environment reconstruction, false or true merged superposition, two-way coordinated interaction, twin intelligence operations and panoramic visual monitoring, field devices for power grid operation maintenance, resource scheduling, and construction planning to provide guidance, Fully guarantee the safe and reliable operation of power grid equipment, realize the full life cycle management of power grid equipment, and improve the level of intelligence, visualization and digitalization of power grid.

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This research presents a decentralised incentive‐based demand response (DR) program using blockchain technology. Consumers self‐report baseline to the system operator (SO), the smart contract confirms the validity of the data to execute transactions and finally the validators record the information on the blockchain network. During the DR event, a set of consumers are randomly selected to deliver the required load reduction. The signalled consumer who delivers the load reduction is rewarded, and the non‐called consumers who diverge from their reported baseline are penalised. The randomness of choosing the consumers and penalty function restrict the baseline inflation. Here, we create a blockchain network and deploy a smart contract on the Ethereum build platform. A DR event scenario is adopted with residential houses data sets, all consumers report their baseline information to the SO through the Internet and smart meter. The SO calls four users to deliver the essential load reduction according to the probability of choosing a consumer. The smart contract verifies the received information to start transaction execution. We use proof of authority mechanism to select validation nodes from the participants using voting system. They validate each block before adding it to the blockchain. Last, the monetary transactions settle in participants' wallets. Our results confirm that decentralised systems like blockchain can significantly improve transparency, openness, and customer participation in the DR program. Also contributes to the security and privacy of user information with a minimal investment in new infrastructure.

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