检索结果-内蒙古大学图书馆

How Differences in Rice Texture and Oral Physiology Affect Sensory Preference and Eating Behavior of Consumers: A Generalized Additive Models (Gams) Approach

SSRN

引用

SSRN 2025年

作者： Zhao, Zhen Wang, Zuo Zhu, Jingye Xu, Ancha McClements, David Julian Chen, Jianshe Chen, Yong School of Food Science and Biotechnology Zhejiang Gongshang University Zhejiang Hangzhou310018 China Zhejiang-UK Joint Laboratory of Food Sensory Science Zhejiang Gongshang University Hangzhou310018 China School of Statistics and Mathematics Zhejiang Gongshang University Hangzhou310018 China Collaborative Innovation Center of Statistical Data Engineering Technology & Application Zhejiang Gongshang University Hangzhou310018 China Biopolymers and Colloids Laboratory Department of Food Science University of Massachusetts AmherstMA01003 United States

Both food texture and human oral physiology impact consumer preferences and eating behavior. However, the complex relationships between them are difficult to explain using simple mathematical models. For this reason, the potential of a generalized additive model (GAM) to relate food texture to oral physiology during the development of healthier foods was investigated. This semiparametric model combines the advantages of both parametric and nonparametric models. The oral behavior of a modified Japonica rice (JM), a low glycemic index (GI) food rich in resistant starch, was compared to that of regular Japonica rice (JR). Both JM and JR were cooked at three water-to-rice (W/R) ratios (low, recommended, high) to obtain samples with different textural properties. The oral physiological parameters of seventeen participants were measured, including biting force and saliva properties. Furthermore, time-intensity (TI) analysis, video recording and electromyography (EMG) were used to provide multiple dynamic sensory analyses. JM required more chewing cycles and longer chewing durations than JR, due to its firmer textural attributes. Linear GAM analysis demonstrated that high hardness and low stickiness of rice led to more chews, chewing duration, and muscle activities, raising the oral processing load and lowering consumer preference. Additionally, nonlinear GAM analysis indicated that saliva flow rate and mucin concentration were negatively correlated with both chewing frequency and duration. A simulated gastrointestinal model showed that JM was digested more slowly than JR. In summary, this study provided valuable insights for optimizing the sensory attributes of high-resistant starch rice to enhance its palatability and consumer acceptance. © 2025, The Authors. All rights reserved.

关键词： Sensory analysis

来源：评论

学校读者我要写书评

暂无评论

Vision-Based Vehicle Detection in Foggy Days by Convolutional Neural Network

Vision-Based Vehicle Detection in Foggy Days by Convolutiona...

引用

Chinese Intelligent Systems Conference, CISC 2019

作者： Yu, Guizhen Wang, Sifen Li, Mingxing Guo, Yaxin Wang, Zhangyu School of Transportation Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China

ISBN: (纸本)9789813296978

Vehicle detection plays an important role in advanced driving assisted system and autonomous driving system. However, the existing vehicle detection methods are not robust in harsh environments, especially in foggy environment. To solve this problem, a vision-based vehicle detection structure using convolutional neural network is presented to detect the vehicle in foggy days. In our vehicle detection structure, a pair of encoders and decoders is used to estimate atmospheric illumination and transmissivity, and to establish the defogging image firstly. And then, the vehicle detection is implemented by a proposed vehicle detection method which predict the left-top key point as well as the right- bottom key point of the vehicle, thus get the bounding box of the vehicle. To verify the effectiveness of the new method, a data set based on the video generated from PreScan simulation platform is set up. And the new vehicle detection method is tested in multiple scenarios such as left turn, right turn, uphill, downhill. Experimental results show that our vehicle detection structure can effectively detect vehicles in foggy days. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Anti-Collision System for Accident Prevention in Underground Mines using Computer Vision 22

Anti-Collision System for Accident Prevention in Underground...

引用

Proceedings of the 6th International Conference on Advances in Artificial Intelligence

作者： Mohamed Imam Karim Baïna Youness Tabii Intissar Benzakour Youssef Adlaoui El Mostafa Ressami El Hassan Abdelwahed Alqualsadi Research Team Rabat IT Center ENSIAS Mohammed V University in Rabat ENSIAS Morocco and Digitalization & Microelectronic Smart Devices - MAScIR Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Morocco Alqualsadi Research Team Rabat IT Center ENSIAS Mohammed V University in Rabat ENSIAS Morocco Information Retrieval and Data Analytics (IRDA) Research Team Rabat IT Center ENSIAS ENSIAS Morocco Reminex Research and Engineering center MANAGEM Group REMINEX Morocco Digitalization & Microelectronic Smart Devices - MAScIR Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Morocco Laboratory of Computer Systems Engineering (LISI) FSSM Cadi Ayyad University FSSM Morocco

ISBN: (纸本)9781450396943

Underground prospecting operations are often characterized by critical safety issues mainly due to poor visibility and blind spots around large vehicles and equipment. This can result in vehicle-to-vehicle collisions, as well as vehicle-to-pedestrian or structural-element collisions, resulting in accidents. In this article, we discuss an anti-collision system for pedestrian identification in deep mines under the premise that we are looking to prevent collisions with moving machinery. This study presents the findings from testing an image processing module and sensory system based on deep learnig in the context of "smart connected mine" project.

关键词： Yolov5 Pedestrian detection Deep Learning Underground mining

来源：评论

学校读者我要写书评

暂无评论

Selection for Cheaper Amino Acids Drives Nucleotide Usage at the Start of Translation in Eukaryotic Genes

引用

Genomics, Proteomics & Bioinformatics 2021年第6期19卷 949-957页

作者： Na L.Gao Zilong He Qianhui Zhu Puzi Jiang Songnian Hu Wei-Hua Chen Key Laboratory of Molecular Biophysics of the Ministry of Education Hubei Key Laboratory of Bioinformatics and Molecular-imagingDepartment of Bioinformatics and Systems BiologyCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Institute for Computer Science and Cluster of Excellence on Plant Sciences Heinrich Heine UniversityD-40225 DuesseldorfGermany CAS Key Laboratory of Genome Sciences and Information Beijing Institute of GenomicsChinese Academy of SciencesBeijing 100101China State Key Laboratory of Microbial Resources Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Interdisciplinary Innovation Institute of Medicine and EngineeringBeihang UniversityBeijing 100191China University of Chinese Academy of Sciences Beijing 100049China

Coding regions have complex interactions among multiple selective forces,which are manifested as biases in nucleotide *** studies have revealed a decreasing GC gradient from the 5′-end to 3′-end of coding regions in various *** confirmed that this gradient is universal in eukaryotic genes,but the decrease only starts from the~25th *** trend is mostly found in nonsynonymous(ns)sites at which the GC gradient is universal across the eukaryotic *** GC contents at ns sites result in cheaper amino acids,indicating a universal selection for energy efficiency toward the N-termini of encoded *** a genome,the decreasing GC gradient is intensified from lowly to highly expressed genes(more and more protein products),further supporting this *** reveals a conserved selective constraint for cheaper amino acids at the translation start that drives the increased GC contents at ns *** GC contents can facilitate transcription but result in a more stable local secondary structure around the start codon and subsequently impede translation ***,the GC gradients at four-fold and two-fold synonymous sites vary across *** could decrease or increase,suggesting different constraints acting at the GC contents of different codon sites in different *** study reveals that the overall GC contents at the translation start are consequences of complex interactions among several major biological processes that shape the nucleotide sequences,especially efficient energy usage.

关键词： Macroevolution Prioritization of selective forces Energy efficiency Transcription Translation initiation

来源：评论

学校读者我要写书评

暂无评论

Facile synthesis of zinc-based organic framework for aqueous Hg (Ⅱ) removal: Adsorption performance and mechanism

引用

Nano Materials science 2021年第4期3卷 429-439页

作者： Biao Zeng Wei Wang Sijin He Guo Lin Wenjia Du Jun Chang Zhao Ding The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan430081PR China Key Laboratory for Ferrous Mtallurgy and Resources Utilization of Ministry of Education Wuhan University of Science and TechnologyWuhan430081PR China China E-port Data Center Division of Chengdu Chengdu610041PR China Electrochemical Innovation Lab Department of Chemical EngineeringUniversity College London(UCL)LondonWC1E 68TUK College of Material and Chemical Engineering Tongren University Tongren554300GuizhouPR China Department of Mechanical Materials and Aerospace Engineering Illinois Institute of TechnologyChicagoIL60616 USA

Mercury(Hg)ions can lead to a serious impact on the environment;therefore,it was necessary to find an effective method for absorbing these toxic Hg ***,the adsorbent(Zn-AHMT)was synthesized from zinc nitrate and 4-amino 3-hydrazine-5 mercapto-1,2,4-triazole(AHMT)by one-step method and,characterized the microstruc-ture and absorption performance by fourier transform infrared spectroscopy(FTIR),field emission scanning electron microscopy(FESEM),X-ray diffraction(XRD),Brunauer-Emmett Teller(BET),Thermal Gravimetric Analyzer(TGA)and X-ray photoelectron spectroscopy(XPS).Through a plethora of measurements,we found that the maximum adsorption capacity was 802.8 mg/g when the optimal pH of Zn-AHMT was *** isothermal and kinetic experiments confirm that the reaction process of Zn-AHMT was chemisorption,while the adsorption process conforms to the Hill model and pseudo second order kinetic *** experiments showed that the adsorption process was spontaneous and *** experiments were performed in the simulated wastewater containing Mn,Mg,Cr,Al,Co,Ni,Hg *** results showed that the Zn-AHMT has a stronger affinity for Hg *** removal rate of Zn-AHMT remained above 98%,indicating that the Zn-AHMT had a good stability validated by three adsorption-desorption repeatable *** to the XPS results,the adsorption reaction of Zn-AHMT was mainly attributed to the chelation and ion *** was further explained by both density functional theory(DFT)calculation and frontier molecular orbital *** therefore propose the adsorption mechanism of *** adsorption reaction facilitates via the synergistic action of S and N ***,the bonding between the adsorbent and the N atom has been proved to be more *** study demonstrated that Zn-AHMT had a promising application prospect in mercury removal.

关键词： Metal-organic frameworks(MOFs) Hg(Ⅱ) Selectivity Adsorption mechanism

来源：评论

学校读者我要写书评

暂无评论

Improved Multi-Head Self-Attention Classification Network for Multi-View Fetal Echocardiography Recognition

Improved Multi-Head Self-Attention Classification Network fo...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Yingying Zhang Haogang Zhu Yan Wang Jingyi Wang Yihua He School of Biological Science and Medical Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing China School of Computer Science and Engineering Beihang University Beijing China School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China Echocardiography Medical Center Beijing Anzhen Hospital Capital Medical University Beijing China Maternal-Fetal Medicine Center in Fetal Heart Disease Beijing Anzhen Hospital Beijing China

The accurate acquisition of multiview fetal cardiac ultrasound images is very important for the diagnosis of fetal congenital heart disease (FCHD). However, these manual clinical procedures have drawbacks, e.g., varying technical capabilities and inefficiency. Therefore, exploring automatic recognition method for multiview images of fetal heart ultrasound scans is highly desirable to improve prenatal diagnosis efficiency and accuracy. In this work, we propose an improved multi-head self-attention mechanism called IMSA combined with residual networks to stably solve the problem of multiview identification and anatomical structure localization. In details, IMSA can capture short- and long-range dependencies from different subspaces and merge them to extract more precise features, thus making use of the correlation between fetal heart structures to make view recognition more focused on anatomical structures rather than disturbing regions, such as artifacts and speckle noises. We validate our proposed method on fetal cardiac ultrasound imaging datasets from a single center and 38 multicenter studies and the results outperform other state-of-the-art networks by 3%-15% of F1 scores in fetal heart six standard view *** Relevance— This technology has great potential in assisting cardiologists to complete the automatic acquisition of multi-section fetal echocardiography images.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Edmcv: An Unsupervised Method for Classifying Thermophilic Proteins Based on Sequences

SSRN

引用

SSRN 2024年

作者： Cheng, Lin Du, Qimeng Yu, Zhuohang Mao, Anqi Zhang, Junpeng Peng, Chong Wu, Xin Zhou, Chichun Gao, Le School of Engineering Dali University Yunnan Dali671003 China Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences National Technology Innovation Center of Synthetic Biology Tianjin China No. 32 Xiqi Road Tianjin Airport Economic Park Tianjin300308 China College of Biotechnology Tianjin University of Science and Technology Tianjin300457 China Air-Space-Ground Integrated Intelligence and Big Data Application Engineering Research Center of Yunnan Provincial Department of Education Yunnan Dali671003 China

Thermophilic proteins, characterized by unique thermal stability, offer valuable insights into protein design and optimization. Correct classification of this property enhances the catalytic efficiency of the enzyme and serves as a prerequisite for exploring the relationship between sequence and thermal stability. Traditional supervised learning methods depend on expensive experimental annotations to classify properties, increase expenses and restrict the analysis of unannotated sequence data. Here, we introduce the ESM-based deep multi-clustering voting (EDMCV) method, an unsupervised method that achieves high accuracy in thermophilic proteins classification without relying on annotated data. EDMCV involves three key steps: 1) initial encoding of thermophilic proteins sequences using the feature extraction capabilities of ESM;2) optimization through deep clustering algorithms;and 3) introduction of a multi-clustering voting strategy to ensure reliable results. EDMCV achieved clustering accuracies of 96.04%, 96.23% and 95.16% on three publicly available thermophilic proteins datasets, surpassing or matching existing supervised classification approaches. Furthermore, analysis of the clustering results enabled the identification of sequence motifs closely related to thermal stability within the classified thermophilic protein sequences. EDMCV provides a new unsupervised method for classifying thermophilic proteins represented by thermal stability, which offers a low-cost way to classify the properties of unlabeled sequences, thereby improving the mining of unknown sequence data. In addition, mining feature motifs from classified thermophilic protein sequences provides important guidance for building a knowledge base and further optimizing protein property designs. The efficiency and scalability of this method lay a solid foundation for research into thermophilic proteins and their applications. © 2024, The Authors. All rights reserved.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Quantitative analysis of the content of nitrogen and sulfur in coal based on laserinduced breakdown spectroscopy: effects of variable selection

引用

Plasma science and Technology 2020年第7期22卷 36-43页

作者： Fan DENG Yu DING Yujuan CHEN Shaonong ZHU Feifan CHEN Jiangsu Key Laboratory of Big Data Analysis Technology Nanjing University of Information Science&TechnologyNanjing 210044People's Republic of China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 210044People's Republic of China Jiangsu Engineering Research Center on Meteorological Energy Using and Control Nanjing University of Information Science&TechnologyNanjing 210044People's Republic of China

Coal is a crucial fossil energy in today’s society,and the detection of sulfir(S) and nitrogen(N)in coal is essential for the evaluation of coal ***,an efficient method is needed to quantitatively analyze N and S content in coal,to achieve the purpose of clean utilization of *** study applied laser-induced breakdown spectroscopy(LIBS) to test coal quality,and combined two variable selection algorithms,competitive adaptive reweighted sampling(CARS) and the successive projections algorithm(SPA),to establish the corresponding partial least square(PLS) *** results of the experiment were as *** PLS modeled with the full spectrum of 27,620 variables has poor accuracy,the coefficient of determination of the test set(R^2 P) and root mean square error of the test set(RMSEP) of nitrogen were 0.5172 and 0.2263,respectively,and those of sulfur were0.5784 and 0.5811,*** CARS-PLS screened 37 and 25 variables respectively in the detection of N and S elements,but the prediction ability of the model did not improve ***-PLS finally screened 14 and 11 variables respectively through successive projections,and obtained the best prediction effect among the three *** R^2 P and RMSEP of nitrogen were0.9873 and 0.0208,respectively,and those of sulfur were 0.9451 and 0.2082,*** general,the predictive results of the two elements increased by about 90% for RMSEP and 60% for R2 P compared with *** results show that LIBS combined with SPA-PLS has good potential for detecting N and S content in coal,and is a very promising technology for industrial application.

关键词： variable selection LIBS coal CARS and SPA

来源：评论

学校读者我要写书评

暂无评论

Dolomite catalyst for fast pyrolysis of waste cooking oil into hydrocarbon fuel

引用

South African Journal of Chemical engineering 2023年 45卷 60-72页

作者： Buyang, Yorinda Nugraha, Reva Edra Holilah, Holilah Bahruji, Hasliza Suprapto, Suprapto Jalil, Aishah Abdul Muryani, Muryani Prasetyoko, Didik Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Keputih Sukolilo Surabaya 60111 Indonesia Department of Chemistry Education Faculty of Teacher Training and Education Musamus University Papua Merauke 99600 Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Pembangunan Nasional “Veteran” Jawa Timur Surabaya 60294 Indonesia Research Center for Biomass and Bioproducts National Research and Innovation Agency of Indonesia (BRIN) Cibinong 16911 Indonesia Centre of Advanced Material and Energy Sciences Universiti Brunei Darussalam BE Jalan Tungku Link 1410 Brunei Darussalam Department of Chemical Engineering Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia 81310 UTM Skudai Johor Johor Bahru Malaysia Centre of Hydrogen Energy Institute of Future Energy Universiti Teknologi Malaysia Johor Skudai Johor Bahru 81310 Malaysia Department of Municipal Waste East Java Blitar District Indonesia

Dolomite as the catalyst for pyrolysis of waste cooking oil (WCO) was investigated to produce hydrocarbon fuels. Optimization of pyrolysis parameters i.e. time, temperature and catalysts loading, achieved high selectivity of WCO to diesel hydrocarbon, compared to thermal pyrolysis that produced mainly carboxylic acids. Dolomite catalysed deoxygenation of fatty acid in WCO into hydrocarbon, consequently accelerating the pyrolysis time to 75 min. Bio-oil at 68.06% yield with 57.27% selectivity towards diesel and gasoline hydrocarbons was obtained at 450 °C while using 6% of dolomite. Dolomite exhibited partial phase separation into dolomite/CaCO₃ mixtures within 15 min of pyrolysis, initiated by the generated CO₂ during pyrolisis of WCO. The catalyst is stable for up to three reaction cycles suggesting the activity was achieved from the synergy between the dolomite/CaCO₃ phases. © 2023

关键词： Bio-oil Catalytic fast pyrolysis Dolomite Hydrocarbon Waste cooking oil

来源：评论

学校读者我要写书评

暂无评论

Ginsenoside compound-K attenuates OVX-induced osteoporosis via the suppression of RANKL-induced osteoclastogenesis and oxidative stress

引用

Natural Products and Bioprospecting 2023年第1期13卷 159-170页

作者： Lingli Ding Zhao Gao Siluo Wu Chen Chen Yamei Liu Min Wang Yage Zhang Ling Li Hong Zou Guoping Zhao Shengnan Qin Liangliang Xu Key Laboratory of Orthopaedics and Traumatology Lingnan Medical Research CenterThe First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhou University of Chinese MedicineGuangzhouChina Er Sha Sports Training Center of Guangdong Province GuangzhouChina School of Basic Medical Science Guangzhou University of Chinese MedicineGuangzhouChina Engineering Laboratory for Nutrition Shanghai Institute of Nutrition and HealthChinese Academy of SciencesShanghaiChina Master Lab for Innovative Application of Nature Products National Center of Technology Innovation for Synthetic BiologyTianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjinChina CAS Key Laboratory of Quantitative Engineering Biology Shenzhen Institute of Synthetic BiologyShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina CAS-Key Laboratory of Synthetic Biology CAS Center for Excellence in Molecular Plant SciencesShanghai Institute of Plant Physiology and EcologyChinese Academy of SciencesShanghaiChina Bio-Med Big Data Center Shanghai Institute of Nutrition and HealthChinese Academy of SciencesShanghaiChina State Key Laboratory of Genetic Engineering Department of Microbiology and ImmunologySchool of Life SciencesFudan UniversityShanghaiChina Department of Microbiology The Chinese University of Hong KongHong KongChina Department of Orthopaedics Guangzhou Institute of Traumatic SurgeryGuangzhou Red Cross HospitalMedical CollegeJinan UniversityGuangzhouChina

Osteoporosis(OP),a systemic and chronic bone disease,is distinguished by low bone mass and destruction of bone *** Compound-K(CK),one of the metabolites of ginsenoside Rb1,has anti-aging,anti-inflammatory,anti-cancer,and hypolipidemic *** have demonstrated CK could promote osteogenesis and fracture healing in our previous ***,the contribution of CK to osteoporosis has not been *** the present study,we investigated the effect of CK on osteoclastogenesis and ovariectomy(OVX)-induced *** results showed that CK inhibited receptor activator for nuclear factor-κB ligand(RANKL)-mediated osteoclast differentiation and reactive oxygen species(ROS)activity by inhibiting the phosphorylation of NF-κB p65 and oxidative stress in RAW264.7 *** addition,we also demonstrated that CK could inhibit bone resorption using bone marrow-derived ***,we demonstrated that CK attenuated bone loss by suppressing the activity of osteoclast and alleviating oxidative stress in *** together,these results showed CK could inhibit osteoclastogenesis and prevent OVX-induced bone loss by inhibiting NF-κB signaling pathway.

关键词： Ginsenoside CK NF-κB signaling pathway Osteoporosis Oxidative stress

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：