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旨在为低温压榨鲜青花椒油的工业生产、贮藏和质量控制提供借鉴，利用超高效液相色谱-二极管阵列检测器-高分辨质谱（UPLC-DAD-HRMS）技术对低温压榨鲜青花椒油中色素进行测定，并研究贮藏过程中光、氧、温度对低温压榨鲜青花椒油的色素含量和色泽L*、a*、b*的影响。结果表明：从低温压榨鲜青花椒油中鉴定出32种叶绿素和10种类胡萝卜素；叶绿素中主要含有叶绿素a、C132-羟基-叶绿素a、叶绿素b和脱镁叶绿素a；类胡萝卜素中主要含有叶黄素和β-胡萝卜素；叶绿素总量为9.44 mg/kg，类胡萝卜素总量为4.95 mg/kg。贮藏过程中影响低温压榨鲜青花椒油中色素降解最主要的因素是光，其次是温度，氧气几乎没有影响。另外，a*可以作为衡量低温压榨鲜青花椒油色素含量及色泽控制的指标。Aiming to contribute to the industrial production, storage and quality control of cold-pressed fresh green Huajiao oil, the change of pigment in cold-pressed fresh green Huajiao oil was analyzed by ultra-high performance liquid chromatography-diode array detector-high resolution mass spectrometry (UPLC-DAD-HRMS), and the effects of light, oxygen, temperature on the pigment content and color(L*, a*, b*) of fresh green Huajiao oil in storage were determined. The results showed that 32 chlorophylls and 10 carotenoids were identified from the cold-pressed fresh green Huajiao oil. The main chlorophylls were chlorophyll a, C132-hydroxy chlorophyll a, chlorophyll b and pheophytin a; the main carotenoids were lutein and β-carotene. The total chlorophyll content was 9.44 mg/kg, and the total carotenoid content was 4.95 mg/kg. During storage, the main factor affecting the degradation of pigment in fresh green Huajiao oil was light, followed by temperature, and oxygen had little effect. In addition, the color index a* can be used as an index for pigment content and color control.

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Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Liver cancer is a significant global disease burden with a major impact on population health, and it is one of the important concerns in terms of public health worldwide. Cancer risk prediction models can estimate an individual’s absolute risk of developing cancer. Individual risk assessment allows targeted screening of high-risk populations, which is essential for primary and secondary cancer prevention. In this review, we examine existing epidemiological studies to explore key issues in the design, predictive variables, and performance of risk prediction models for liver cancer in the general population. The aim is to provide an important reference for the future development of highly comprehensive liver cancer risk prediction models. [ABSTRACT FROM AUTHOR]

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为解决高电动汽车渗透率下充电需求受到配电设施容量限制的矛盾，提出了基于充电权在“微市场”中进行交易的电动汽车集群运行控制技术。在配电网中某一特定区域内某一时间段充电桩集群总充电功率受限时，通过电动汽车充电权在“微市场”机制下交易的市场化手段，实现在用户参与下的电动汽车充电需求自动调整，从而减少用电高峰时段的总充电功率，实现配电网特定区域内用电负荷削峰填谷。应用该策略，安装于一个配网变压器下的充电桩的总功率可以大于变压器容量与其它负荷用电尖峰的差值，大幅增加充电桩安装数量，满足更多用户的充电需求，同时保障用电安全，提高供电设施利用率，延缓供电设施升级改造的需求。

Copyright of Journal of South China Agricultural University is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The sea area where the cross-sea bridge is located has the characteristics of deep water, high waves and high flow velocity, and the wave current force is one of the control loads of the foundation structure. In this paper, a calculation method for wave current forces of bridge foundations with complex bridge piers-cap-pile foundations was established by constructing a wave and flow model of pile foundation, bridge piers and cap structure, and combining with the results of wave and flow coupling flume model test. The method has reliable calculation accuracy and high calculation efficiency. The error between the model and the physical model is less than 10%, and the calculated value is slightly safe. The method proposed in this paper has been applied to the comparison and selection of foundation structures for the Dongwuyang cross-sea bridge, and a better design scheme has been obtained. The research results can be applied to the calculation of wave current force for similar cross-sea bridges and offshore wind power foundations, providing convenience for the comparison and selection of foundation structure schemes in the early stage of construction. [ABSTRACT FROM AUTHOR]

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Ensuring the safe production of offshore oil and gas is an important requirement for the implementation of the national energy strategy. CNOOC has carried out predictive maintenance based on offline status monitoring and wired online monitoring to ensure the safety of oil and gas production through the integrity management of equipment and facilities. With the rapid development of industrial Internet technology, CNOOC has put forward the "1534" overall development strategy to leap over digital management and carry out the construction and development of cloud platform services; For intelligent application scenarios such as intelligent oil field construction and unmanned platform construction, the demand for digital equipment and intelligent management services is increasing, and the construction cost of conventional wired monitoring is relatively high, mainly for key units; In addition, the particularity of offshore oil, network environment and production environment are easy to affect digital management. At present, wireless monitoring can better meet the requirements of cluster digital inspection, intelligent analysis and evaluation, low-cost management and control. Combined with the existing digital conditions such as CNOOC Cloud, this paper studies and designs the wireless monitoring system architecture based on cloud computing and key technologies of cloud edge collaboration. Through field application, the wireless monitoring system based on cloud edge collaboration can effectively capture equipment abnormal status information and intelligently identify equipment risks, guide oil and gas production sites to carry out predictive maintenance, and reduce system construction and equipment operation and maintenance costs. [ABSTRACT FROM AUTHOR]

In recent years, supervised machine learning-based Android malware detection methods have made some progress. However, due to the difficulty in collecting malware samples, the size of labeled datasets is generally small, which leads to limited generalization ability of the trained supervised models. To address this problem, an unsupervised and supervised combined malware detection method is proposed. Firstly, a language model is pre-trained on a large amount of unlabeled APK samples using unsupervised methods to learn the rich and complex semantic relationships between different operators. Then, the pre-trained language model is fine-tuned by the labeled malware samples to realize the malware detecting ability. Experiments on datasets such as Drebin demonstrate that the proposed method has better generalization ability and detection performance compared with the baseline method, which achieves a maximum accuracy of 98.7%. [ABSTRACT FROM AUTHOR]

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为解决经典AODV（按需距离矢量）路由协议中目的节点在已建立路由链路信号覆盖范围内随机移动时脱离其原来直接通信节点而断路、通信恢复时间长以及网络负载大等问题,对利用AODV协议Hello消息报文激活中间节点与目的节点的通信切换实现快速路由修复进行了研究,并得到改进后的路由协议AODVL。仿真结果表明,AODVL比经典的AODV路由协议减小了网络负载并缩短了路由修复时间。AODVL更适用于目的节点在已建立路由链路信号覆盖范围内随机移动的网络,节点间通信具有更高的实时性。

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