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Larval biomass production from the co-digestion of mushroom root waste and soybean curd residues by black soldier fly larvae (Hermetia illucens L.)

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Environmental Science and Pollution research 2024年第20期31卷 30112-30125页

作者： Soomro, Abdul Aziz rehman, Kashif ur Cai, Minmin Laghari, Zubair Ahmed Zheng, Longyu Yu, Ziniu Zhang, Jibin State Key Laboratory of Agricultural Microbiology National Engineering Research Center of Microbial Pesticides College of Life Science and Technology Huazhong Agricultural University Wuhan430070 China Pakistan Agricultural Research Council–Arid Zone Research Centre Umerkot Pakistan Prof.-V.-Klitzing-Str. 7 Quakenbrück49610 Germany Department of Microbiology Faculty of Veterinary and Animal Sciences The Islamia University of Bahawalpur Punjab Bahawalpur Pakistan Hubei Hongshan Laboratory Wuhan China Institute of Hydrobiology Chinese Academy of Sciences Hubei Province Wuhan430072 China Department of Veterinary Parasitology Sindh Agriculture University Sindh Tandojam70060 Pakistan

People are increasingly using black soldier fly larvae (BSFL) as a sustainable waste management solution. They are high in protein and other essential nutrients, making them an ideal food source for livestock, poultry, and fish. Prior laboratory studies with BSFL developed on pure mushroom root waste (MrW) showed poor conversion efficiency compared to a regular artificial diet. Therefore, we mixed the nutrient-rich soybean curd residues (SCr) with MrW in different ratios (M2–M5). Pure mushroom root waste (M1, MrW 100%) had the lowest survival rate (86.2%), but it increased up to 96.9% with the SCr percentage increasing. M1 had the longest developmental period (31.1 days) and the lowest BSFL weight (7.4 g). However, the addition of SCr reduced the development time to 22.0 and 21.5 days in M4 (MrW 40%, SCr 60%) and M5 (MrW 20%, SCr 80%), respectively, and improved the larval weight to 10.9 g in M4 and 11.8 g in M5. Other groups did not have as much feed conversion ratio (FCr) (8.4 for M4 and M5), bioconversion (M4 5.4%;M5 5.9%), or lipid content (M4 25.2%;M5 24.3%). These mixtures did. Compare this to M1. We observed better results, with no significant differences between the M4 and M5 groups and their parameters. In the present study, our main target was to utilize more MrW. Therefore, we preferred the M4 group in our nutritional and safety investigation and further compared it with the artificial diet (M7). The heavy metals and essential amino acids (histidine 3.6%, methionine 2.7%, and threonine 3.8%) required for human consumption compared to WHO/FAO levels showed satisfactory levels. Furthermore, fatty acids (capric acid 1.9%, palmitic acid 15.3%, oleic acid 17.3%, and arachidonic acid 0.3%) also showed higher levels in M4 than M7. The SEM images and FT-Ir spectra from the residues showed that the BSFL in group M4 changed the structure of the compact fiber to crack and remove fibers, which made the co-conversion mixture better. © The Author(s), under exclusive li

关键词： Biomass

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GArd: A Geometry-Informed and Uncertainty-Aware Baseline Method for Zero-Shot roadside Monocular Object detection

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IEEE rOBOTICS ANd AUTOMATION LETTErS 2025年第2期10卷 1297-1304页

作者： Peng, Yuru Wang, Beibei Yu, Zijian Zhang, Lu Ji, Jianmin Zhang, Yu Zhang, Yanyong Univ Sci & Technol China Inst Adv Technol Hefei 230026 Peoples R China Hefei Comprehens Natl Sci Ctr Inst Artificial Intelligence Hefei 230026 Peoples R China Hefei Comprehens Natl Sci Ctr Inst Artificial Intelligence Hefei 230026 Peoples R China Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026 Peoples R China Suzhou Shuzhi Technol Grp Co Ltd Suzhou 215000 Peoples R China

roadside camera-based perception methods are in high demand for developing efficient vehicle-infrastructure collaborative perception systems. By focusing on object-level depth prediction, we explore the potential benefits of integrating environmental priors into such systems and propose a geometry-based roadside per-object depth estimation algorithm dubbed GArd. The proposed method capitalizes on the inherent geometric properties of the pinhole camera model to derive depth as well as 3d positions for given 2d targets in roadside-view images, alleviating the need for computationally intensive end-to-end learning architectures for monocular 3d detection. Using only a pre-trained 2d detection model, our approach does not require vast amounts of scene-specific training data and shows superior generalization abilities across varying environments and camera setups, making it a practical and cost-effective solution for monocular 3d object detection.

关键词： Three-dimensional displays Cameras roads depth measurement Object detection Estimation Feature extraction detectors deep learning Accuracy Computer vision for automation intelligent transport systems object detection

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Cross-level steam load smoothing and optimization in industrial parks using data-driven approaches

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Energy and AI 2024年第2期16卷 69-83页

作者： Xiaojie Lin Xueru Lin Wei Zhong Feiyun Cong Yi Zhou Zhejiang Key Laboratory of Clean Energy and Carbon Neutrality Zhejiang UniversityHangzhouChina Shanghai Institute for Advanced Study Zhejiang UniversityShanghaiChina College of Energy Engineering Zhejiang UniversityHangzhouChina Jiaxing Research Institute Zhejiang UniversityJiaxingChina School of Mechanical Engineering Zhejiang UniversityHangzhouChina

This study focuses on the integrated energy production system in industrial parks, addressing the problem of stable load dispatch of equipment under demand fluctuations. A cross-level method for steam load smoothing and optimization is proposed, aiming to achieve stable production and optimal economic performance through three levels of integration: load forecasting, load dispatch, and load regulation. Unlike traditional methods that directly use load forecasting values, heat network elasticity is presented as a buffer between demand and supply. Constraints for minimal changes in equipment load and operational parameters are established for smooth regulation. Industrial cases demonstrate that the load forecasting model has mean absolute percentage errors of 2.44% and 1.68% for medium-pressure and low-pressure steam, respectively, meeting accuracy requirements. The modified supply-side load smoothness is effectively improved by considering heat network elasticity. The method increases boiler efficiency by 1.92%, reducing average coal consumption by 0.92 t/h. Compared to manual operation, the proposed model leads to an average increase of 5.69 MW in power generation and an average reduction of 10.81% in coal-to-electricity ratio. This study verifies the importance of smooth integration across different levels and analyzes the effective response of the proposed method to the uncertainty in load forecasting. The method demonstrates the enormous potential of data-driven methods in achieving safe, economical, and sustainable production in industrial parks.

关键词： Industrial parks Heat network elasticity Load regulation Integrated optimization Load forecasting Production stability

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removal of pathogenic indicator microorganisms during partial nitrification:the role of free nitrous acid

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Frontiers of Environmental Science & Engineering 2024年第3期18卷 93-102页

作者： Jiaojiao Xu Xiaotian Chen rui Tang Jingwei Feng Shoujun Yuan Wei Wang Zhen-Hu Hu Anhui Engineering Laboratory of Rural Water Environment and Resource School of Civil EngineeringHefei University of TechnologyHefei 230009China Hefei 168 High School Hefei 230025China Shanghai Key Laboratory of Materials Protection and Advanced Materials in Electric Power Shanghai University of Electric PowerShanghai 200090China

digested wastewater contains pathogenic microorganisms and high ammonia concentrations,which can pose a potential risk to public *** removal of pathogens and nitrogen is crucial for the post-treatment of digested *** nitrification-anammox is an energy-saving nitrogen removal *** nitrous acid(FNA),an intermediate product of partial nitrification,has the potential to inactivate ***,the efficiency and mechanisms of FNA-related inactivation in pathogens during partial nitrification remains *** this study,Enterococcus and Escherichia coli(***)were selected to investigate the efficiency and mechanisms of FNA-related inactivation in partial nitrification *** results revealed that 83%±13%and 59%±27%of *** and Enterococcus were removed,respectively,in partial nitrification process at FNA concentrations of 0.023−0.028 mg/*** the concentration of FNA increased from 0 to 0.5 mg/L,the inactivation efficiencies of *** and Enterococcus increased from 0 to 99.9%and 89.9%,*** exhibited a higher resistance to FNA attack compared to ***.3d-laser scanning microscopy(3d-LSM)and scanning electron microscopy(SEM)revealed that FNA exposure caused the surface collapse of *** and Enterococcus,as well as visible pore formation on the surface of *** cells.4',6-diamidino-2-phenylindole dihydrochloride n-hydrate(dAPI)/propidium iodide(PI)and biomolecule leakage confirmed that inactivation of *** and Enterococcus occurred due to breakdown of cell walls and cell *** findings indicate that partial nitrification process can be used for the removal of residual pathogenic microorganisms.

关键词： Partial nitrification Free nitrous acid Pathogenic indicator microorganism Inactivation Cell structure

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Component modeling and updating method of integrated energy systems based on knowledge distillation

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Energy and AI 2024年第2期16卷 184-199页

作者： Xueru Lin Wei Zhong Xiaojie Lin Yi Zhou Long Jiang Liuliu du-Ikonen Long Huang Shanghai Institute for Advanced Study Zhejiang UniversityShanghaiChina College of Energy Engineering Zhejiang UniversityHangzhouChina Jiaxing Research Institute Zhejiang UniversityJiaxingChina Department of Sustainability Science LUT UniversityLappeenrantaFinland School of Intelligent Manufacturing Ecosystem Xi'an Jiaotong-Liverpool UniversitySuzhouChina

Amid the backdrop of carbon neutrality, traditional energy production is transitioning towards integrated energy systems (IES), where model-based scheduling is key in scenarios with multiple uncertainties on both supply and demand sides. The development of artificial intelligence algorithms, has resolved issues related to model accuracy. However, under conditions of high proportion renewable energy integration, component load adjustments require increased flexibility, so the mathematical model of the component must adapt to constantly changing operating conditions. Therefore, the identification of operating condition changes and rapid model updating are pressing issues. This study proposes a modeling and updating method for IES components based on knowledge distillation. The core of this modeling method is the light weighting of the model, which is achieved through a knowledge distillation method, using a teacher-student mode to compress complex neural network models. The triggering of model updates is achieved through principal component analysis. The study also analyzes the impact of model errors caused by delayed model updates on the overall scheduling of IES. Case studies are conducted on critical components in IES, including coal-fired boilers and turbines. The results show that the time consumption for model updating is reduced by 76.67 % using the proposed method. Under changing conditions, compared with two traditional models, the average deviation of this method is reduced by 12.61 % and 3.49 %, respectively, thereby improving the model's adaptability. The necessity of updating the component model is further analyzed, as a 1.00 % mean squared error in the component model may lead to a power deviation of 0.075 MW. This method provides real-time, adaptable support for IES data modeling and updates.

关键词： Component modeling Adaptive update Knowledge distillation Variable operating conditions Integrated energy system data-driven

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CellMsg: graph convolutional networks for ligand-receptor-mediated cell-cell communication analysis

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BrIEFINGS IN BIOINFOrMATICS 2025年第1期26卷 bbae716页

作者： Xia, Hong Ji, Boya Qiao, debin Peng, Shaoliang Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Peoples R China Zhengzhou Univ Sch Comp & Artificial Intelligence Zhengzhou 450001 Peoples R China

The role of cell-cell communications (CCCs) is increasingly recognized as being important to differentiation, invasion, metastasis, and drug resistance in tumoral tissues. developing CCC inference methods using traditional experimental methods are time-consuming, labor-intensive, cannot handle large amounts of data. To facilitate inference of CCCs, we proposed a computational framework, called CellMsg, which involves two primary steps: identifying ligand-receptor interactions (LrIs) and measuring the strength of LrIs-mediated CCCs. Specifically, CellMsg first identifies high-confident LrIs based on multimodal features of ligands and receptors and graph convolutional networks. Then, CellMsg measures the strength of intercellular communication by combining the identified LrIs and single-cell rNA-seq data using a three-point estimation method. Performance evaluation on four benchmark LrI datasets by five-fold cross validation demonstrated that CellMsg accurately captured the relationships between ligands and receptors, resulting in the identification of high-confident LrIs. Compared with other methods of identifying LrIs, CellMsg has better prediction performance and robustness. Furthermore, the LrIs identified by CellMsg were successfully validated through molecular docking. Finally, we examined the overlap of LrIs between CellMsg and five other classical CCC databases, as well as the intercellular crosstalk among seven cell types within a human melanoma tissue. In summary, CellMsg establishes a complete, reliable, and well-organized LrI database and an effective CCC strength evaluation method for each single-cell rNA-seq data. It provides a computational tool allowing researchers to decipher intercellular communications. CellMsg is freely available at https://***/pengsl-lab/CellMsg.

关键词： cell-cell communications ligand-receptor interactions graph convolutional networks three-point estimation method

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A double crosslinking MXene/cellulose nanofiber layered film for improving mechanical properties and stable electromagnetic interference shielding performance

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Journal of Materials Science & Technology 2022年第34期129卷 127-134页

作者： Shilu Luo Tiantian Xiang Jingwen dong Fengmei Su Youxin Ji Chuntai Liu Yuezhan Feng Key Laboratory of Materials Processing and Mold Ministry of Education National Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China

With the discovery of the two-dimensional(2d) MXene, it shows a great application potential in the field of electromagnetic interference(EMI) shielding, but the mechanical brittleness and easy oxidation of MXene limit its wide application. For this reason, a double crosslinking strategy is provided to solve the above problems in a nacre-like “brick-mortar” layered MXene/cellulose nanofiber(MXene/CNF) ***, the film was firstly suffered by dopamine modification, then was further reinforced by secondary Ca^(2+)bridging, so as to obtain excellent mechanical properties and antioxidative EMI shielding performance. Comparing with the single crosslinking, the double crosslinking strategy reveals a higher efficiency in improving the mechanical property. The mechanical strength and toughness of the double crosslinking MXene/CNF film can increase to 142.2 MPa and 9.48 MJ/m^(3), respectively. More importantly, while achieving good mechanical properties, the MXene composite film still holds a very stable EMI shielding performance of more than 44.6 dB when suffering from the oxidation treatment of hightemperature annealing, showing excellent anti-oxidation ability and environment tolerance. Therefore,this work provides a universal but effective double crosslinking strategy to solve the mechanical brittleness and easy oxidation of MXene-based composites, thus showing a huge potential in flexible EMI shielding applications.

关键词： Ti_(2)C_(3)T_(x)MXene Layered structure double crosslinking Mechanical properties EMI shielding performance

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Analytical solutions to the precession relaxation of magnetization with uniaxial anisotropy

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Chinese Physics B 2024年第4期33卷 656-660页

作者：张泽南贾镇林薛德胜 Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education Lanzhou UniversityLanzhou 730000China

Based on the Landau-Lifshitz-Gilbert(LLG)equation,the precession relaxation of magnetization is studied when the external field H is parallel to the uniaxial anisotropic field H_(k).The evolution of three-component magnetization is solved analytically under the condition of H=nH_(k)(n=3,1 and 0).It is found that with an increase of H or a decrease of the initial polar angle of magnetization,the relaxation time decreases and the angular frequency of magnetization *** comparison,the analytical solution for H_(k)=0 is also *** the magnetization becomes stable,the angular frequency is proportional to the total effective field acting on the *** analytical solutions are not only conducive to the understanding of the precession relaxation of magnetization,but also can be used as a standard model to test the numerical calculation of LLG equation.

关键词： precession relaxation Landau-Lifshitz-Gilbert(LLG)equation uniaxial anisotropy analytical solutions

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High-performance transparent graphene-based antennas

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Science China(Technological Sciences) 2025年第2期68卷 306-314页

作者： Chaoye HONG Lusong WEI Weijia WANG Youmei TANG Qinghai ZHU Jiangtao HUANGFU Mingsheng XU College of Integrated Circuits State Key Laboratory of Silicon and Advanced Semiconductor MaterialsZhejiang UniversityHangzhou 310027China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China

With the continuous development of wireless communication technology,applications in the military,aerospace,and vehicle wireless communication sectors have demanded miniaturized and aesthetically pleasing *** antennas,which combine the advantages of optical and radio-frequency(rF)technologies,have become a popular research ***,existing transparent antennas often suffer from complex preparation processes,fragile materials,poor conductivity,and low optical ***,we develop hybrid conductive thin films using graphene and silver nanowires,achieving a transmittance of 86% and a sheet resistance of 7.8Ω/sq with high environmental *** demonstrate the suitability of this nanocomposite in two applications:a transparent ultrahigh-frequency rF-identification tag folded dipole antenna and a transparent X-band microwave half-wave dipole *** antennas offer high gain,high radiation efficiency,and small size,indicating that transparent graphene-based antennas have remarkable potential for intelligent information sensor systems.

关键词： antenna transparent rFId small size graphene silver nanowires

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real-time operational parameter recommendation system for tunnel boring machines:Application and performance analysis

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Journal of Mountain Science 2025年第5期22卷 1819-1831页

作者： WANG Shuangjing WU Leijie LI Xu Key Laboratory of Urban Underground Engineering of Ministry of Education Beijing Jiaotong UniversityBeijing 100044China China Railway Engineering Equipment Group Co. Ltd.Zhengzhou 450016China

The accurate selection of operational parameters is critical for ensuring the safety,efficiency,and automation of Tunnel Boring Machine(TBM)*** study proposes a similarity-based framework integrating model-based boring indexes(derived from rock fragmentation mechanisms)and Euclidean distance analysis to achieve real-time recommendations of TBM operational *** performance indicators-thrust(F),torque(T),and penetration(p)-were used to calculate three model-based boring indexes(a,b,k),which quantify dynamic rock fragmentation behavior.A dataset of 359 candidate samples,reflecting diverse geological conditions from the Yin-Chao water conveyance project in Inner Mongolia,China,was utilized to validate the *** system dynamically recommends parameters by matching real-time data with historical cases through standardized Euclidean distance,achieving high ***,the mean absolute error(MAE)for rotation speed(n)was 0.10 r/min,corresponding to a mean absolute percentage error(MAPE)of 1.09%.For advance rate(v),the MAE was 3.4 mm/min,with a MAPE of 4.50%.The predicted thrust(F)and torque(T)values exhibited strong agreement with field measurements,with MAEs of 270 kN and 178 kN∙m,*** applications demonstrated a 30%reduction in parameter adjustment time compared to empirical *** work provides a robust solution for real-time TBM control,advancing intelligent tunneling in complex geological environments.

关键词： Tunnel Boring Machine Similarity based method Boring indexes Operational parameters realtime recommendation

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