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Identifying Brand Consistency by Product Differentiation Using CNN

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 685-709页

作者： hung-Hsiang Wang Chih-Ping Chen Department of Industrial Design National Taipei University of TechnologyTaipeiTaiwan Department of Product Design Ming Chuan UniversityTaoyuanTaiwan

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance *** Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and *** show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various *** investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late *** show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real *** relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style *** addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred *** study provides insights into practical problems for designers,manufacturers,and marketers in product *** not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand *** can use these techniques to find features that influence brand ***,capture these features as innovative design elements and maintain core brand values.

关键词： Machine learning product differentiation brand consistency principal component analysis convolutional neural network computer mouse

Single-base editing in IGF2 improves meat production and intramuscular fat deposition in Liang Guang Small Spotted pigs

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Journal of Animal Science and Biotechnology 2024年第1期15卷 108-126页

作者： Tianqi Duo Xiaohong Liu Delin Mo Yu Bian Shufang Cai Min Wang Ruiqiang Li Qi Zhu Xian Tong Ziyun Liang weilun Jiang Shiyi Chen Yaosheng Chen Zuyong He State Key Laboratory of Biocontrol School of Life SciencesSun Yat-Sen UniversityGuangzhou 510275GuangdongChina Department of Pharmacology(the State‑Province Key Laboratories of Biomedicine‑Pharmaceutics of China Key Laboratory of Cardiovascular ResearchMinistry of Education)College of PharmacyHarbin Medical UniversityHarbin 150081China Hunan Provincial Key Laboratory for Genetic Improvement of Domestic Animal College of Animal Science and TechnologyHunan Agricultural UniversityChangsha 410128China

Background Chinese indigenous pigs are popular with consumers for their juiciness,flavour and meat quality,but they have lower meat ***-like growth factor 2(IGF2) is a maternally imprinted growth factor that promotes skeletal muscle growth by regulating cell proliferation and differentiation.A single nucleotide polymorphism(SNP) within intron 3 of porcine IGF2 disrupts a binding site for the repressor,zinc finger BED-type containing 6(ZBED6),leading to up-regulation of IGF2 and causing major effects on muscle growth,heart size,and backfat *** favorable mutation is common in Western commercial pig populations,but absent in most Chinese indigenous pig *** improve meat production of Chinese indigenous pigs,we used cytosine base editor 3(CBE3)to introduce IGF2 intron3-C3071T mutation into porcine embryonic fibroblasts(PEFs) isolated from a male Liang Guang Small Spotted pig(LGSS),and single-cell clones harboring the desired mutation were selected for somatic cell nuclear transfer(SCNT) to generate the founder line of IGF2^(T/T) *** We found the heterozygous progeny IGF2^(C/T) pigs exhibited enhanced expression of IGF2,increased lean meat by 18%-36%,enlarged loin muscle area by 3%-17%,improved intramuscular fat(IMF) content by 18%-39%,marbling score by 0.75-1,meat color score by 0.53-1.25,and reduced backfat thickness by 5%-16%.The enhanced accumulation of intramuscular fat in IGF2^(C/T) pigs was identified to be regulated by the PI3K-AKT/AMPK pathway,which activated SREBP1 to promote *** We demonstrated the introduction of IGF2-intron3-C3071T in Chinese LGSS can improve both meat production and quality,and first identified the regulation of IMF deposition by IGF2 through SREBP1 via the PI3KAKT/AMPK signaling *** study provides a further understanding of the biological functions of IGF2and an example for improving porcine economic traits through precise base editing.

关键词： CBE3 IGF2 Intramuscular fat Meat production PI3K-AKT/AMPK ZBED6

Exponentially Bounded C-semigroup and the Cauchy Initial Value Problems in Complete Random Normed Modules

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Acta Mathematica Sinica,English Series 2024年第9期40卷 2195-2212页

作者： Son TA CONG Thang Dang hung Oanh Le THI Department of Mathematics University of ScienceVietnam National University 334 Nguyen TraiThanh XuanHanoiVietnam Faculty of Natural Sciences Hong Duc University565 Quang TrungDong VeThanh HoaVietnam

In this paper,the notion of C-semigroup of continuous module homomorphisms on a complete random normal(RN)module is introduced and *** existence and uniqueness of solution to the Cauchy problem with respect to exponen... 详细信息

关键词： C-semigroup Cauchy problem random normed modules L^(0)-Lipschitz

Data-Driven Modeling of Partially Observed Biological Systems

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Communications on Applied Mathematics and Computation 2024年第1期6卷 739-754页

作者： Wei-hung Su Ching-Shan Chou Dongbin Xiu Department of Mathematics The Ohio State UniversityColumbusOH43221USA

We present a numerical approach for modeling unknown dynamical systems using partially observed data,with a focus on biological systems with(relatively)complex dynamical *** an extension of the recently developed deep neural network(DNN)learning methods,our approach is particularly suitable for practical situations when(i)measurement data are available for only a subset of the state variables,and(ii)the system parameters cannot be observed or measured at *** demonstrate that,with a properly designed DNN structure with memory terms,effective DNN models can be learned from such partially observed data containing hidden *** learned DNN model serves as an accurate predictive tool for system *** a few representative biological problems,we demonstrate that such DNN models can capture qualitative dynamical behavior changes in the system,such as bifurcations,even when the parameters controlling such behavior changes are completely unknown throughout not only the model learning process but also the system prediction *** learned DNN model effectively creates a“closed”model involving only the observables when such a closed-form model does not exist mathematically.

关键词： Deep neural network(DNN) Governing equation discovery Biological system Partial observation

Study of relationship between motion of mechanisms in gas operated weapon and its shock absorber

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Defence Technology（防务技术） 2024年第3期33卷 42-54页

作者： Jiri Balla Roman Vitek Dung Nguyen Van Zbynek Krist hung Nguyen Van Department of Weapons and Ammunition University of Defence BrnoCzech Republic Department of Weapons Le Quy Don Technical UniversityHanoiViet Nam Department of Design and Special Engineering Alexander Dubcek University of TrencinSlovakia

The article deals with the motion of the breech block carrier and the weapon casing of an automatic weapon mounted on a flexible carriage and the base of the *** works,which did not consider the dynamic properties of the base of the weapon,did not allow to reconcile the calculated and experimental results of the weapon casing displacement when shooting from firing *** the analysis of the motion of individual parts,the methods of mathematical modelling and firing experiments using a high-speed camera were *** show the best accord with experiment when modelling the system with 4 degrees of *** oscillation of the system regarding the movement of the breech block carrier and the weapon casing was investigated under changed conditions of rate of fire,the use of a muzzle brake and different types of shock *** velocities and displacements of the weapon casing and the breech block carrier at different values of the impulse of the gases to the breech block carrier were determined.

关键词： Shock absorber Gas-operated weapon Force-impulse diagram Recoil system Breech block carrier

Heterogeneous decentralised machine unlearning with seed model distillation

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 608-619页

作者： Guanhua Ye Tong Chen Quoc Viet hung Nguyen Hongzhi Yin School of Information Technology and Electrical Engineering The University of QueenslandSt LuciaQueenslandAustralia School of Information and Communication Technology Griffith UniversityBrisbaneQueenslandAustralia

As some recent information security legislation endowed users with unconditional rights to be forgotten by any trained machine learning model,personalised IoT service pro-viders have to put unlearning functionality into their *** most straight-forward method to unlearn users'contribution is to retrain the model from the initial state,which is not realistic in high throughput applications with frequent unlearning *** some machine unlearning frameworks have been proposed to speed up the retraining process,they fail to match decentralised learning scenarios.A decentralised unlearning framework called heterogeneous decentralised unlearning framework with seed(HDUS)is designed,which uses distilled seed models to construct erasable en-sembles for all ***,the framework is compatible with heterogeneous on-device models,representing stronger scalability in real-world *** experiments on three real-world datasets show that our HDUS achieves state-of-the-art performance.

关键词： data mining data privacy machine learning

Community perspectives on the effectiveness of watershed management institutions in the Himalayas

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Journal of Mountain Science 2024年第4期21卷 1119-1139页

作者： Nisha SILWAL Nabin DhungANA Rajan SUBEDI Suraj UPADHAYA Chun-hung LEE Natural Resources Conservation Nepal(NRCN) ChitwanP.O.Box 44200Nepal Department of Natural Resources and Environmental Studies College of Environmental StudiesNational Dong Hwa UniversityHualien 97401Chinese Taipei Institute of Forestry Tribhuvan UniversityPokharaP.O.Box 43Nepal School of Agriculture and Natural Resources Kentucky State UniversityFrankfortKY 40601USA Himalayan Conservation and Research Institute DolpaP.O.Box 21400Nepal

The sustainability of environmental management initiatives,such as watershed management programs,relies on the presence of effective institutions at the watershed ***,there needs to be more empirical evidence from evaluating the effectiveness of watershed-level ***,this study presents a pioneering effort to evaluate the effectiveness of Nepal’s first watershed conservation committee at the watershed scale,focusing on the case of the Khageri Khola watershed in Central *** study involved conducting a household survey,key informant interviews,focus group discussions,and field observations to collect and analyze the *** analysis,index value calculation,and chi-square statistics were then employed to summarize the results regarding local respondents’perceptions of twelve institutional characteristics,their rationalities,and their association with socio-demographic *** results reveal that the watershed conservation committee was perceived as performing well in managing the ***,good interaction,appropriate scale,technical,environmental,social,organizational,and government rationality were perceived as highly effective,with an average index value of less than *** contrast,clarity of objectives and economic rationality showed moderate effectiveness,with an average index value ranging from 0.36 to ***,the results suggested that adaptiveness,compliance capacity,and financial rationality merit increased attention,intending to improve their ***,the results showed the association of socio-demographics with respondents’perceptions of various indicators of institutional characteristics and their ***,the study provides valuable insights for policymakers,researchers,and development practitioners charged with designing sustainable and effective programs and *** enhance the effectiveness and sustainability of watershed management programs,we recommen

关键词： Watershed Watershed institutions Indicators Institutional characteristics Rationalities Nepal.

Forecasting measured responses of structures using temporal deep learning and dual attention

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 832-850页

作者： Viet-hung DANG Trong-Phu NGUYEN Thi-Lien PHAM Huan X.NGUYEN Department of Structural Mechanics Hanoi University of Civil EngineeringHanoi 11600Vietnam Faculty of Applied Science University of Economics-Technology for IndustriesHanoi 11600Vietnam London Digital Twin Research Centre Faculty of Science and TechnologyMiddlesex UniversityLondon NW44BTUK International School Vietnam National UniversityHanoi 11600Vietnam

The objective of this study is to develop a novel and efficient model for forecasting the nonlinear behavior of structures in response to time-varying random *** key idea is to design a deep learning architecture to leverage the relationships,between external excitations and structure's vibration signals,and between historical values and future values,within multiple time-series *** proposed method consists of two main steps:the first step applies a global attention mechanism to combine multiple-measured time series and time-varying excitation into a weighted time series before feeding it to a temporal architecture;the second step utilizes a self-attention mechanism followed by a fully connected layer to predict multi-step future *** viability of the proposed method is demonstrated via two case studies involving synthetic data from a three-dimensional(3D)reinforced concrete structure and experimental data from an 18-story steel ***,comparison and robustness studies are carried out,showing that the proposed method outperforms conventional methods and maintains high performance in the presence of noise with an amplitude of less than 10%.

关键词： structural dynamic time-varying excitation deep learning signal processing response forecasting

Autolysosomal acidification impairment as a mediator for TNFR1 induced neuronal necroptosis in Alzheimer’s disease

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Neural Regeneration Research 2024年第9期19卷 1869-1870页

作者： Evridiki Asimakidou Richard Reynolds Anna M.Barron Chih hung Lo Department of Clinical Neurosciences University of CambridgeCambridgeUK Department of Brain Sciences Faculty of MedicineImperial College LondonLondonUK Lee Kong Chian School of Medicine Nanyang Technological UniversitySingaporeSingapore

Neuronal necroptosis-an emerging form of regulated cell death associated with neuroinflammatory signaling:Alzheimer’s disease(AD)is characterized by the presence of extracellular amyloid-β(Aβ)plaques and intracellular tau neurofibrillary tangles as well as progressive neuronal *** evidence has suggested that prolonged neuroinflammation with increased levels of cytokines,arising from neuronal injury,innate immune responses from glial cells,and peripheral inflammation,leads to neuronal death and AD progression.

关键词： Alzheimer death tau Aβ