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The first two decades of the twenty-first century witnessed the blossoming of frameworks to conceptualize "21st-century skills" both in school and career. However, there is still a lack of consensus about what we are talking about when using the term "21st-century skills," as the existing frameworks on "21st-century skills" are different from each other. Drawing upon 471 existing sources published in 2000-2017 regarding "21st-century skills," identified from six research databases, this study was intended to answer the following research question via a systematic review: What skills had been considered as "21st-century skills" in the existing educational research literature? Seven categories or domains of knowledge and skills emerged when investigating this literature. Implications and future research directions about how adaptive learning and adaptive testing in the new century can empower educational and vocational guidance were briefly discussed at the end of this paper.

Abstract Background Anxiety disorders in middle-aged and older adults are an important public health concern in China. Based on the data in the global disease burden (GDB) research database, this study evaluated and analyzed the trend of the disease burden of middle-aged and older patients living with anxiety in China in the past 30 years. Methods The incidence and disability-adjusted life years (DALYs) data of anxiety disorders in China for individuals aged 45–89 years were collected from the Global Burden of Disease Study 2019, and the effects of age, period, and cohort on the incidence of and DALY rate for anxiety disorders were analysed using an age-period-cohort model. Because of the COVID-19 pandemic, the global disease burden research database has not been updated since 2019. However, this did not affect the analysis of future trends in this study, which combined data in the past three decades from 1990 to 2019. Results (1) The overall age-standardised incidence rate (ASIR) and age-standardised DALY rate (ASDR) for anxiety disorders in middle-aged and older adults in China decreased by 4.0 and 7.7% from 1990 to 2019, respectively, and the ASIR and ASDR were always higher in women than in men. (2)Age-period-cohort analysis showed that the net drifts for incidence and DALY rate were − 0.27% and − 0.55% per year, respectively. For both genders, the local drifts for incidence were lower than zero in those aged 45–79 years and higher than zero in those aged 80–89 years; the local drifts for the DALY rate were lower than zero in all groups. (3) From the 1990–1994 to 2015–2019, the relative risks of anxiety disorder incidence and DALY decreased by 5.6 and 7.3% in men and 4.3 and 11.7% in women, respectively. Conclusion The disease burden of anxiety disorders in middle-aged and older adults in China has been relieved over the past 30 years; however, recent ASDR, ASDR, period, and cohort effects have shown adverse trends. The incidence and DALY rate decreased with age in women, while men showed a trend of increasing first and decreasing afterwards.

[Objective]The InterPlanetary File System (IPFS) is a peer-to-peer distributed file system, aiming to establish a global, open, and decentralized network for storage and sharing. Combining the IPFS and blockchain technology could alleviate the pressure on blockchain storage. The distinct features of the supply chain for agricultural products in the plantation industry, including extended production cycles, multiple, heterogeneous data sources, and relatively fragmented production, which can readily result in information gaps and opacity throughout the supply chain; in the traceability process of agricultural products, there are issues with sensitive data being prone to leakage and a lack of security, and the supply chain of plantation agricultural products is long, and the traceability data is often stored in multiple blocks, which requires frequent block tracing operations during tracing, resulting in low efficiency. Consequently, the aim of this study is to fully encapsulate the decentralized nature of blockchain, safeguard the privacy of sensitive data, and alleviate the storage strain of blockchain.[Method]A traceability model for plantation-based agricultural products was developed, leveraging the hyperledger fabric consortium chain and the IPFS. Based on data type, traceability data was categorized into structured and unstructured data. Given that blockchain ledgers were not optimized for direct storage of unstructured data, such as images and videos, to alleviate the storage strain on the blockchain, unstructured data was persisted in the IPFS, while structured data remains within the blockchain ledger. Based on data privacy categories, traceability data was categorized into public data and sensitive data. Public data was stored in the public ledger of hyperledger fabric, while sensitive data was stored in the private data collection of hyperledger fabric. This method allowed for efficient data access while maintaining data security, enhancing the efficiency of traceability. Hyperledger Fabric was the foundational platform for the development of the prototype system. The front-end website was based on the TCP/IP protocol stack. The website visualization was implemented through the React framework. Smart contracts were crafted using the Java programming language. The performance of the application layer interface was tested using the testing tool Postman.[Conclusions and Discussions]The blockchain-based plantation agricultural product traceability system was structured into a five-tiered architecture, starting from the top: the application layer, gateway layer, contract layer, consensus layer, and data storage layer. The primary service providers at the application layer were the enterprises and consumers involved in each stage of the traceability process. The gateway layer served as the middleware between users and the blockchain, primarily providing interface support for the front-end interface of the application layer. The contract layer mainly included smart contracts for planting, processing, warehousing, transportation, and sales. The consensus layer used the EtcdRaft consensus algorithm. The data storage layer was divided into the on-chain storage layer of the blockchain ledger and the off-chain storage layer of the IPFS cluster. In terms of data types, each piece of traceability data was categorized into structured data items and unstructured data items. Unstructured data was stored in the Interstellar File System cluster, and the returned content identifiers were integrated with the structured data items into the blockchain nodes within the traceability system. In the realm of data privacy, smart contracts were employed to segregate public and sensitive data, with public data directly integrating onto the blockchain, and sensitive data, adhering to predefined sharing policies, being stored in a private dataset designated by hyperledger fabric. In terms of user queries, consumers could retrieve product traceability information via a traceability system overseen by a reputable authority. The developed model website consisted of three parts: a login section, an agricultural product circulation information management and user data management section for enterprises in various links, and a traceability data query section for consumers. When using synchronous and asynchronous Application Program Interfaces, the average data on-chain latency was 2 138.9 and 37.6 ms, respectively, and the average data query latency was 12.3 ms. Blockchain, as the foundational data storage technology, enhances the credibility and transaction efficiency in agricultural product traceability.[Conclusions]This study designed and implemented a plantation agricultural product traceability model leveraging blockchain technology's private dataset and the IPFS cluster. This model ensured secure sharing and storage of traceability data, particularly sensitive data, across all stages. Compared to traditional centralized traceability models, it enhanced the reliability of the traceability data. Based on the evaluation through experimental systems, the traceability model proposed in this study effectively safeguarded the privacy of sensitive data in enterprises. Additionally, it offered high efficiency in data linking and querying. Applicable to the real-world traceability environment of plantation agricultural products, it showed potential for widespread application and promotion, offering fresh insights for designing blockchain traceability models in this sector. The model is still in its experimental phase and lacks applications across various types of crops in the farming industry. The subsequent step is to apply the model in real-world scenarios, continually enhance its efficiency, refine the model, advance the practical application of blockchain technology, and lay the foundation for agricultural modernization.

The association of thyroid hormone antibodies and glycolipid metabolism indicators with Type 2 diabetes mellitus (T2DM) was explored. As the disease worsens, the levels of thyroglobulin antibody (TGAb), thyroid peroxidase antibody (TPOAb), and thyroid-stimulating hormone (TSH) was increased, and the levels of total tri-iodothyronine (TT3) and total thyroxine (TT4) was decreased (P < 0.001). The severe, medium, and light group had higher level of high-density lipoprotein (HDL), lower level of total cholesterol (TC), low-density lipoprotein (LDL), glycosylated hemoglobin (HbA1c), triacylglycerol (TAG), and fasting blood sugar (FBG) than the control group (P ＜ 0.05). The level of HDL was lower in the severe group than the light group and the medium group, but the levels of TC, LDL, HbA1c, TAG, and FBG were increased with the progress of T2DM (P ＜ 0.001). The levels of TGAb, TPOAb, and TSH in patients with T2DM were positively correlated with the levels of TC, LDL, HbA1c, TAG, and FBG (P < 0.05), and were negatively correlated with HDL levels (P < 0.05). The life quality score was lower in the severe group than the light and the medium group (P < 0.001). Among the above indicators, the predictive value of TT3, TT4, and HbA1c in T2DM was better. Clinically, detecting the levels of thyroid hormone antibodies and glycolipid metabolism indicators had a certain predictive value for the severity of T2DM.

We used multivariate generalizability theory to examine the reliability of hand-scoring and automated essay scoring (AES) and to identify how these scoring methods could be used in conjunction to optimize writing assessment. Students (n = 113) included subsamples of struggling writers and non-struggling writers in Grades 3-5 drawn from a larger study. Students wrote six essays across three genres. All essays were hand-scored by four raters and an AES system called Project Essay Grade (PEG). Both scoring methods were highly reliable, but PEG was more reliable for non-struggling students, while hand-scoring was more reliable for struggling students. We provide recommendations regarding ways of optimizing writing assessment and blending hand-scoring with AES.