药物相互作用研究在新药研发和审评决策中的应用

药物相互作用改变了剂量效应关系，可能会降低疗效或增加毒性，是临床应用中合并用药治疗时重要的考虑因素。预测具有临床意义的药物相互作用是药物研发过程中获益风险评估的重要环节。本文概述了药物研发过程中药物相互作用研究的目的和意义，体内和体外研究的主要内容；梳理分析了2020年国家药品监督管理局（National Medical Products Administration, NMPA）和美国食品药品监督管理局（Food and Drug Administration, FDA）批准上市的新药药物相互作用研究情况，旨在为我国药物研发过程中药物相互作用研究及其监管审评提供参考。     

对“垃圾衍生燃料”RDF之探析

当前,我国水泥工业在可燃废弃物应用技术方面都还处于一家一户、自制自用、效率极低的初级阶段。发达国家的替代燃料:“垃圾衍生燃料”RDF、“固体回收燃料”SRF、“次煤”Subcoal和“纸塑垃圾衍生燃料”RPF制成的原材料都是可燃废弃物,只是处理工艺技术不同或者由垃圾中分拣出的可燃废弃物不同,制成颗粒状衍生燃料的品质不同,这些都可以替代部分甚或替代全部化石燃料在水泥窑炉中应用。我国大力发展“替代燃料”产业,有助于水泥工业消纳更多的“可燃废弃物”,为改善环境尤其是城镇环境和面貌,为我国的节能减排和绿色高质量发展发挥更大的作用。     

肇庆市固体废物产业发展方向探索

本文以肇庆市固体废物产业发展为实例,阐明全市固体废物产业发展现状以及发展方向,并提出了相应的策略。     

Statistical optimization of operating parameters of microbial electrolysis cell treating dairy industry wastewater using quadratic model to enhance energy generation

The performance of Microbial electrolysis cell (MEC) is affected by several operating conditions. Therefore, in the present study, an optimization study was done to determine the working efficiency of MEC in terms of COD (chemical oxygen demand) removal, hydrogen and current generation. Optimization was carried out using a quadratic mathematical model of response surface methodology (RSM). Thirteen sets of experimental runs were performed to optimize the applied voltage and hydraulic retention time (HRT) of single chambered batch fed MEC operated with dairy industry wastewater. The operating conditions (i.e) an applied voltage of 0.8 V and HRT of 2 days that showed a maximum COD removal response was chosen for further studies. The MEC operated at optimized condition (HRT- 2 days and applied voltage- 0.8 V) showed a COD removal efficiency of 95 ± 2%, hydrogen generation of 32 ± 5 mL/L/d, Power density of 152 mW/cm² and current generation of 19 mA. The results of the study implied that RSM, with its high degree of accuracy can be a reliable tool for optimizing the process of wastewater treatment. Also, dairy industry wastewater can be considered to be a potential source to generate hydrogen and energy through MEC at short HRT.     

Cold plasma for the disinfection of industrial food-contact surfaces: An overview of current status and opportunities

Food safety is the primary goal for food and drink manufacturers. Cleaning and disinfection practices applied to the processing environment are vital to maintain this safety; yet, current approaches can incur costly downtime and the potential for microorganisms to grow and establish, if not effectively removed. For that reason, manufacturers are seeking nonthermal, online, and continuous disinfection processes to control the microbial levels within the processing environment. One such emerging technique, with great potential, is cold atmospheric pressure plasma (CAP). This review presents the latest advances and challenges associated with CAP-based technologies for the decontamination of surfaces and equipment found within the food-processing environment. It provides a detailed overview of the technology and a comprehensive analysis of the many CAP-based antimicrobial studies on food-contact surfaces and materials. As CAP is considered an emerging technique, many of the recent studies are still in the preliminary stages, with results obtained under widely different conditions. This lack of cohesive information and an inability to directly compare CAP systems has greatly impeded technological development. The review further explores the challenge of scaling CAP technology to meet industry needs, considering aspects such as regulatory constraints, environmental credentials, and cost of use. Finally, a discussion is presented on the future outlook for CAP technology in this area, identifying key challenges that must be addressed to promote industry uptake.     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.     

Process knowledge-based random forest regression for model predictive control on a nonlinear production process with multiple working conditions

In process industry, predictive control approaches have been widely used for nonlinear production processes. Practically, the predictor in a predictive controller is extremely important since it provides future states for the optimization problem of controllers. The conventional predictive controller with precise mathematical predictors approximating the state space of physical systems is difficult and time-consuming for nonlinear production processes, and it performs poorly over a wide range of working conditions and with significant disturbances. To address the challenges, the trend of applying artificial intelligence emerges. However, the industrial process-specific knowledge is ignored in most cases. In this study, a predictive controller with a control process knowledge-based random forest (RF) model is proposed. Specifically, working data are clustered at first to handle diverse working conditions. Then, a process knowledge-based forest predictor, namely MIW-RF model with a redesigned cascading RF structure, is proposed to incorporate control process knowledge into modeling. Thus, future states of controlled variables could be more accurately acquired for the optimizer. A simplified version of the predictive model is also developed with quick model training and updating. The proposed predictive methods are finally introduced into the controller design. According to the empirical results, the proposed methods deliver a better control performance against benchmarks, including more accurate anticipated controlled-variable responses, better set-point tracking and disturbance rejection capability.     

我国纺织领域温室气体标准的现状研究

文章从数量、类别、时间等维度描述了我国温室气体标准以及我国纺织领域温室气体标准的发展现状。基于此,简要分析了纺织领域温室气体标准建设存在的问题及原因,提出了未来纺织行业温室气体标准体系建设的建议。     

Technical,economic, and environmental analyses of the modernization of a chamber furnace operating on natural gas or hydrogen

The paper presents a technical, economic and environmental analyses of a chamber furnace used to heat the charge before forging. The energy efficiency of the furnace before the modernization was 18%, after the modernization it was 31% (partial modernization due to large financial outlays). Other variants were also analysed: complete modernization, the variant of furnace modernization with 30% hydrogen content in the gas and the variant with 100% hydrogen as fuel. The analyses showed that with the current gas price (0.025 EUR/kWh) and the price of emission allowances (nearly 60 EUR/MgCO₂) and 100 cycles/year, the difference in Net Present Value (NPV) before base variant and partial modernization is around 900,000 EUR and before base variant and full modernization is 1,200,000 EUR. The introduction of the gas and 30% of hydrogen co-combustion option versus the base scenario option for 150 cycles per year results in a NPV difference of at least 2 million EUR. The option of 100% hydrogen as a fuel is the most advantageous from the point of view of reducing CO₂ emissions - it is largely influenced by the rising prices of CO₂ emission allowances.     

Mathematical Modeling of Drying Processes of Selected Fruits and Vegetables

This study investigates the behavior of fruit and vegetable samples during drying. The experimental data are fitted to several different thin-layer drying models. Regression analysis is used to determine model parameters, while statistical indicators serve to evaluate the goodness of fit. The power function model gives the best fit for all examined samples. Based on this model, different drying and heat storage technologies can be combined to ensure that the required residual moisture content of an agricultural product is reached. It is demonstrated on the case of a specific Togolese processing plant that under favorable conditions, fossil fuel consumption can be decreased by 33 %.