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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi Bui Dam Duc Nguyen Hiep Van Le Indra Prakash Binh Thai Pham Civil Engineering department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

Breast cancer resistance protein(BCRP/ABCG2):its role in multidrug resistance and regulation of its gene expression

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Chinese Journal of Cancer 2012年第2期31卷 73-99页

作者： Takeo Nakanishi Douglas D.Ross department of membrane transport and biopharmaceutics Kanazawa University School of Pharmaceutical SciencesKanazawa 920-1192Japan University of Maryland Greenebaum Cancer Center the departments of Medicine Pathology and Pharmacology and Experimental TherapeuticsUniversity of Maryland School of Medicineand the Baltimore VA Medical CenterBaltimoreMaryland 21201USA

Breast cancer resistance protein(BCRP)/ATP-binding cassette subfamily G member 2(ABCG2) is an ATP-binding cassette(ABC) transporter identified as a molecular cause of multidrug resistance(MDR) in diverse cancer *** physiologically functions as a part of a self-defense mechanism for the organism;it enhances elimination of toxic xenobiotic substances and harmful agents in the gut and biliary tract,as well as through the blood-brain,placental,and possibly blood-testis *** recognizes and transports numerous anticancer drugs including conventional chemotherapeutic and targeted small therapeutic molecules relatively new in clinical ***,BCRP expression in cancer cells directly causes MDR by active efflux of anticancer *** BCRP is also known to be a stem cell marker,its expression in cancer cells could be a manifestation of metabolic and signaling pathways that confer multiple mechanisms of drug resistance,self-renewal(stemness),and invasiveness(aggressiveness),and thereby impart a poor ***,blocking BCRP-mediated active efflux may provide a therapeutic benefit for *** the precise molecular mechanisms for BCRP gene expression may lead to identification of a novel molecular target to modulate BCRP-mediated *** evidence suggests that BCRP gene transcription is regulated by a number of trans-acting elements including hypoxia inducible factor 1α,estrogen receptor,and peroxisome proliferator-activated ***,alternative promoter usage,demethylation of the BCRP promoter,and histone modification are likely associated with drug-induced BCRP overexpression in cancer ***,PI3K/AKT signaling may play a critical role in modulating BCRP function under a variety of *** biological events seem involved in a complicated *** the events would be an essential first step to developing a method to modulate BCRP function to aid patients with *** review will present a sy

关键词：多重耐药性基因表达调控组蛋白修饰乳腺癌过氧化物酶体增殖物激活受体分子机制多药耐药肿瘤细胞

Development of a fast and precise method for simultaneous quantification of the PLGA monomers lactic and glycolic acid by HPLC

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Journal of Pharmaceutical Analysis 2019年第2期9卷 100-107页

作者： Marcel Pourasghar Aljoscha Koenneke Peter Meiers Marc Schneider department of Pharmacy Biopharmaceutics and Pharmaceutical TechnologySaarland University

Poly(lactide-co-glycolide acid)(PLGA) is an extraordinary well-described polymer and has excellent pharmaceutical properties like high biocompatibility and good biodegradability. Hence, it is one of the most used materials for drug delivery and biomedical systems, also being present in several US Food and Drug Administration-approved carrier systems and therapeutic devices. For both applications, the quantification of the polymer is inalienable. During the development of a production process, parameters like yield or loading efficacy are essential to be determined. Although PLGA is a well-defined biomaterial,it still lacks a sensitive and convenient quantification approach for PLGA-based systems. Thus, we present a novel method for the fast and precise quantification of PLGA by RP-HPLC. The polymer is hydrolyzed into its monomers, glycolic acid and lactic acid. Afterwards, the monomers are derivatized with the absorption-enhancing molecule 2,4′-dibromoacetophenone. Furthermore, the wavelength of the derivatized monomers is shifted to higher wavelengths, where the used solvents show a lower absorption,increasing the sensitivity and detectability. The developed method has a detection limit of 0.1 mg/mL,enabling the quantification of low amounts of PLGA. By quantifying both monomers separately, information about the PLGA monomer ratio can be also directly obtained, being relevant for degradation behavior. Compared to existing approaches, like gravimetric or nuclear magnetic resonance measurements, which are tedious or expensive, the developed method is fast, ideal for routine screening, and it is selective since no stabilizer or excipient is interfering. Due to the high sensitivity and rapidity of the method, it is suitable for both laboratory and industrial uses.

关键词： Poly(lactide-co-glycolide acid)(PLGA) Alkaline hydrolysis Quantification Drug delivery system RP-HPLC

An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 835-867页

作者： Sumaia Mohamed Elhassan Saad Mohamed Darwish Saleh Mesbah Elkaffas department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of Computing and Information Technology Arab Academy for ScienceTechnology and Maritime TransportAlexandriaP.O.Box 1029Egypt

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic *** detection of lung tumors significantly increases the chances of successful treatment and ***,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung ***-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate ***,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor *** overcome these disadvantages,dual-model or multi-model approaches can be *** research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of *** automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung ***8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single *** is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to ***,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive *** combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applicati

关键词： Lung cancer detection dual-model deep learning technique data augmentation CNN YOLOv8

DEM speedup: Stiffness effects on behavior of bulk material

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Particuology 2014年第1期12卷 107-112页

作者： Stef Lommen Dingena Schott Gabriel Lodewijks department of Maritime and transport Technology Delft University of Technology

A number of techniques exist for minimizing the computational cost of discrete element simulations （DEMs）. One such method is a reduction of particle stiffness, which allows for bigger time steps and therefore fewer iterations in a simulation. However, the limits and drawbacks of this approach are still unclear, and may lead to invalid results. This paper investigates the effect of a stiffness reduction on bulk behavior by examining three case studies. Two cases demonstrate that particle stiffness can be reduced without affecting the bulk material behavior, whereas the third test shows that a stiffness reduction influences the bulk behavior.

关键词： Discrete element methodSpeedupStiffness reductionLimitOverlap

Optimization of product characteristics of porous carbon agglomerates using a design of experiments in fluidized bed agglomeration

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Particuology 2024年第6期89卷 258-269页

作者： Martin Oelofse Robert Rack Marcelle Hilden Peter Langguth department of Pharmaceutical Technology and biopharmaceutics Johannes Gutenberg UniversityMainzGermany Carbon Advanced Solutions GmbH HeuchelheimGermany

Spraying parameters during particle agglomeration processes can affect the agglomeration kinetics and particle *** study was conducted to better understand the influence of the spraying parameters in a fluidized bed wet agglomeration process,and the influence on the stability characteristics of carbon tablets.A formulation based on fine carbon and peroxide powder,as well as carboxymethyl cellulose as a binder,was used to produce agglomerates in a first production *** in a second production step carbon tablets with a high porosity were molded for the customer goods *** optimization of the compressive strength of these carbon tablets was the goal of the *** agglomerates were produced with a laboratory scale granulator called“ProCell”and were compressed with a five-cavity mechanical *** screening of the agglomeration process parameters and their influence on the agglomerates quality,as well as the performance characteristics of the carbon tablets,were investigated using a multilevel factorial *** experimental runs were done by varying atomized air pressure and feed rate of the *** was determined by the design *** findings of the statistical trials showed that low atomized air pressure and a low feed rate lead to a higher tablet compressive strength.

关键词： Wet agglomeration Fluidized bed Design of experiments Carbon agglomerates and tablets

Immune checkpoint inhibitors:breakthroughs in cancer treatment

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Cancer Biology & Medicine 2024年第6期21卷 451-472页

作者： Xueqing Kong Jinyi Zhang Shuwei Chen Xianyang Wang Qing Xi Han Shen Rongxin Zhang Laboratory of Immunology and Inflammation School of Life Sciences and BiopharmaceuticsGuangdong Pharmaceutical UniversityGuangzhou 510006China department of Biology School of Life Sciences and BiopharmaceuticsGuangdong Pharmaceutical UniversityGuangzhou 510006China

Over the past two decades,immunotherapies have increasingly been considered as first-line treatments for most *** such treatment is immune checkpoint blockade(ICB),which has demonstrated promising results against various solid tumors in clinical *** antibodies(mAbs)are currently available as immune checkpoint inhibitors(ICIs).These ICIs target specific immune checkpoints,including cytotoxic T-lymphocyte-associated antigen-4(CTLA-4)and programmed cell death protein 1(PD-1).Clinical trial results strongly support the feasibility of this immunotherapeutic ***,a substantial proportion of patients with cancer develop resistance or tolerance to treatment,owing to tumor immune evasion mechanisms that counteract the host immune ***,substantial research focus has been aimed at identifying additional ICIs or synergistic inhibitory receptors to enhance the effectiveness of anti-PD-1,anti-programmed cell death ligand 1(anti-PD-L1),and anti-CTLA-4 ***,several immune checkpoint molecular targets have been identified,such as T cell immunoreceptor with Ig and ITIM domains(TIGIT),mucin domain containing-3(TIM-3),lymphocyte activation gene-3(LAG-3),V-domain immunoglobulin suppressor of T cell activation(VISTA),B and T lymphocyte attenuator(BTLA),and signal-regulatory proteinα(SIRPα).Functional m Abs targeting these molecules are under ***-4,PD-1/PD-L1,and other recently discovered immune checkpoint proteins with distinct structures are at the forefront of *** review discusses these structures,as well as clinical progress in m Abs targeting these immune checkpoint molecules and their potential applications.

关键词： Immunotherapy cancer ICIs PD-1 CTLA-4

Influence of friction on buckling of a drill string in the circular channel of a bore hole

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Petroleum Science 2016年第4期13卷 698-711页

作者： Valery Gulyayev Natalya Shlyun department of Mathematics National Transport UniversityKiev Ukraine

Enhancement of technology and techniques for drilling deep directed oil and gas bore hole is one of the most important problems of the current petroleum *** infrequently, the drilling of these bore holes is attended by occurrence of extraordinary situations associated with technical accidents. Among these is the Eulerian loss of stability of a drill string in the channel of a curvilinear bore hole. Methods of computer simulation should play a dominant role in prediction of these states. In this paper, a new statement of the problem of critical buckling of the drill strings in 3D curvilinear bore holes is proposed. It is based on combined use of the theory of curvilinear elastic rods, Eulerian theory of stability, theory of channel surfaces, and methods of classical mechanics of systems with nonlinear constraints. It is noted that the stated problem is singularly perturbed and its solutions have the shapes of localized harmonic wavelets. The calculation results showed that the friction effects lead to essential redistribution of internal axial forces, as well as changing the eigenmode shapes and sites of their localization. These features make the buckling phenomena less predictable and raise the role of computer simulation of these effects.

关键词： Directed bore hole Drill string Critical states Singular perturbation Friction forces Harmonic wavelet

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam Nguyen Nguyen Viet Tiep Quynh-Anh Thi Bui Hiep Van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil Engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic Engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania department of Civil Engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India department of Civil Engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees and optimization algorithms

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Frontiers of Structural and Civil Engineering 2022年第10期16卷 1267-1286页

作者： Thuy-Anh NGUYEN Hai-Bang LY Van Quan TRAN department of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam

Shear failure of slender reinforced concrete beams without stirrups has surely been a complicated occurrence that has proven challenging to adequately *** primary purpose of this work is to develop machine learning models capable of reliably predicting the shear strength of non-shear-reinforced slender beams(SB).A database encompassing 1118 experimental findings from the relevant literature was compiled,containing eight distinct *** Boosting(GB)technique was developed and evaluated in combination with three different optimization algorithms,namely Particle Swarm Optimization(PSO),Random Annealing Optimization(RA),and Simulated Annealing Optimization(SA).The findings suggested that GB-SA could deliver strong prediction results and effectively generalizes the connection between the input and output *** values and two-dimensional PDP analysis were then carried *** may use the findings in this work to define beam’s geometrical components and material used to achieve the desired shear strength of SB without reinforcement.

关键词： slender beam shear strength gradient boosting optimization algorithms