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Development trend of urban design in “digital age”: Pan-dimensionality and individual-ubiquity

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 3, Pages 569-575 doi: 10.1007/s11709-021-0735-7

Abstract: ., the urban development is moving toward “pan-dimensionality” and “individual ubiquity”.

Keywords： digital age urban design multiple objectives human-computer interaction pan-dimensionality individual-ubiquity

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Fuel optimal control of parallel hybrid electric vehicles

PU Jinhuan, YIN Chenliang, ZHANG Jianwu

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 3, Pages 337-342 doi: 10.1007/s11465-008-0057-7

Abstract: To overcome the problem of numerical DP dimensionality, an algorithm to restrict the exploring region

Keywords： mathematical Comparison computational complexity dimensionality corresponding

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A MATLAB code for the material-field series-expansion topology optimization method

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 3, Pages 607-622 doi: 10.1007/s11465-021-0637-3

Abstract: description and the finite element discretization, and greatly reduces the number of design variables after dimensionality

Keywords： implementation topology optimization material-field series-expansion method bounded material field dimensionality

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Optimization design of spar cap layup for wind turbine blade

Jie ZHU, Xin CAI, Pan PAN, Rongrong GU

Frontiers of Structural and Civil Engineering 2012, Volume 6, Issue 1, Pages 53-56 doi: 10.1007/s11709-012-0147-9

Abstract: Based on the aerodynamic shape and structural form of the blade are fixed, a mathematical model of optimization design for wind turbine blade is established. The model is pursued with respect to minimum the blade mass to reduce the cost of wind turbine production. The material layup numbers of the spar cap are chosen as the design variables; while the demands of strength, stiffness and stability of the blade are employed as the constraint conditions. The optimization design for a 1.5 MW wind turbine blade is carried out by combing above objective and constraint conditions at the action of ultimate flapwise loads with the finite element software ANSYS. Compared with the original design, the optimization design result achieves a reduction of 7.2% of the blade mass, the stress and strain distribution of the blade is more reasonable, and there is no occurrence of resonance, therefore its effectiveness is verified.

Keywords： wind turbine blade spar cap layup optimization design blade mass

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Recent advances in the catalytic pyrolysis of biomass

Changwei HU, Yu YANG, Jia LUO, Pan PAN, Dongmei TONG, Guiying LI

Frontiers of Chemical Science and Engineering 2011, Volume 5, Issue 2, Pages 188-193 doi: 10.1007/s11705-010-1015-6

Abstract: Biomass is considered as a renewable and alternative resource for the production of fuels and chemicals, since it is the only carbon and hydrogen containing resource that we can find in the world except for fossil resources, capable of being converted to hydrocarbons. The pyrolytic liquefaction of biomass is a promising way to convert biomass to useful products. This paper briefly surveys the present status of the direct catalytic pyrolysis for the liquefaction of biomass. The direct use of catalysts could decrease the pyrolysis temperature, increase the conversion of biomass and the yield of bio-oil, and change the distribution of the pyrolytic liquid products then improve the quality of the bio-oil obtained. The fact that biomass is in solid state present great challenges for its conversion and for the effective use of catalysts due to the bad heat transfer characteristics and bad mass transfer properties. These barriers appeal for the development of a new catalyst and new catalytic process as well as the integration of both. Process design and process intensification are of significant importance in the catalytic conversion of biomass.

Keywords： biomass liquefaction catalysis bio-oil process intensification

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Early-onset diabetes: an epidemic in China

Jiemin Pan, Weiping Jia

Frontiers of Medicine 2018, Volume 12, Issue 6, Pages 624-633 doi: 10.1007/s11684-018-0669-1

Abstract:

Although type 2 diabetes is a disease often associated with aging, the global prevalence of early-onset diabetes has been increasing due to man’s sedentary lifestyle, low-physical activity, obesity, and some non-modifiable risk factors. Many studies have found that individuals with early-onset type 2 diabetes were at higher risk of developing vascular complications than those with late-onset diabetes. Individuals with early-onset diabetes are usually unwilling to visit hospital and have more confidence in their health, which results in poor glycemic control and the delayed detection of diabetes-related complications. Few studies have focused on the treatment and prevention of complications in specific population of individuals with early-onset type 2 diabetes. Therefore, focusing on this particular population is critical for the government and academic societies. Screening for T2DM is imminent for young adults with a family history of diabetes, obesity, markers of insulin resistance, or alcohol consumption. More data are definitely required to establish a reasonable risk model to screen for early-onset diabetes.

Keywords： diabetes early-onset diabetes complications

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Expanding the Scope of Multivariate Regression Approaches in Cross-Omics Research Article

Xiaoxi Hu, Yue Ma, Yakun Xu, Peiyao Zhao, Jun Wang

Engineering 2021, Volume 7, Issue 12, Pages 1725-1731 doi: 10.1016/j.eng.2020.05.028

Abstract:

Recent technological advancements and developments have led to a dramatic increase in the amount of high-dimensional data and thus have increased the demand for proper and efficient multivariate regression methods. Numerous traditional multivariate approaches such as principal component analysis have been used broadly in various research areas, including investment analysis, image identification, and population genetic structure analysis. However, these common approaches have the limitations of ignoring the correlations between responses and a low variable selection efficiency. Therefore, in this article, we introduce the reduced rank regression method and its extensions, sparse reduced rank regression and subspace assisted regression with row sparsity, which hold potential to meet the above demands and thus improve the interpretability of regression models. We conducted a simulation study to evaluate their performance and compared them with several other variable selection methods. For different application scenarios, we also provide selection suggestions based on predictive ability and variable selection accuracy. Finally, to demonstrate the practical value of these methods in the field of microbiome research, we applied our chosen method to real population-level microbiome data, the results of which validated our method. Our method extensions provide valuable guidelines for future omics research, especially with respect to multivariate regression, and could pave the way for novel discoveries in microbiome and related research fields.

Keywords： Multivariate regression methods Reduced rank regression Sparsity Dimensionality reduction Variable

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Dimensionality reduction and prediction of soil consolidation coefficient using random forest coupling

Hai-Bang LY; Huong-Lan Thi VU; Lanh Si HO; Binh Thai PHAM

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 2, Pages 224-238 doi: 10.1007/s11709-022-0812-6

Abstract: The consolidation coefficient of soil (C_v) is a crucial parameter used for the design of structures leaned on soft soi. In general, the C_v is determined experimentally in the laboratory. However, the experimental tests are time-consuming as well as expensive. Therefore, researchers tried several ways to determine C_v via other simple soil parameters. In this study, we developed a hybrid model of Random Forest coupling with a Relief algorithm (RF-RL) to predict the C_v of soil. To conduct this study, a database of soil parameters collected from a case study region in Vietnam was used for modeling. The performance of the proposed models was assessed via statistical indicators, namely Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). The proposal models were constructed with four sets of soil variables, including 6, 7, 8, and 13 inputs. The results revealed that all models performed well with a high performance (R² > 0.980). Although the RF-RL model with 13 variables has the highest prediction accuracy ( R² = 0.9869), the difference compared with other models was negligible (i.e., R² = 0.9824, 0.9850, 0.9825 for the cases with 6, 7, 8 inputs, respectively). Thus, it can be concluded that the hybrid model of RF-RL can be employed to predict C_v based on the basic soil parameters.

Keywords： soil consolidation coefficient machine learning random forest Relief

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Digital switched hydraulics

Min PAN, Andrew PLUMMER

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2, Pages 225-231 doi: 10.1007/s11465-018-0509-7

Abstract:

This paper reviews recent developments in digital switched hydraulics particularly the switched inertance hydraulic systems (SIHSs). The performance of SIHSs is presented in brief with a discussion of several possible configurations and control strategies. The soft switching technology and high-speed switching valve design techniques are discussed. Challenges and recommendations are given based on the current research achievements.

Keywords： digital hydraulics switched inertance hydraulic systems energy efficiency high-speed switching valve fluid-borne noise

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Feature selection techniques for microarray datasets: a comprehensive review, taxonomy, and future directions Review

Kulanthaivel BALAKRISHNAN, Ramasamy DHANALAKSHMI,bala.k.btech@gmail.com,r_dhanalakshmi@yahoo.com

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 10, Pages 1451-1478 doi: 10.1631/FITEE.2100569

Abstract:

For optimal results, retrieving a relevant feature from a has become a hot topic for researchers involved in the study of (FS) techniques. The aim of this review is to provide a thorough description of various, recent FS techniques. This review also focuses on the techniques proposed for s to work on multiclass classification problems and on different ways to enhance the performance of learning algorithms. We attempt to understand and resolve the imbalance problem of datasets to substantiate the work of researchers working on s. An analysis of the literature paves the way for comprehending and highlighting the multitude of challenges and issues in finding the optimal feature subset using various FS techniques. A case study is provided to demonstrate the process of implementation, in which three microarray cancer datasets are used to evaluate the classification accuracy and convergence ability of several wrappers and hybrid algorithms to identify the optimal feature subset.

Keywords： Feature selection High dimensionality Learning techniques Microarray dataset

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CFD simulation on membrane distillation of NaCl solution

Zhaoguang XU, Yanqiu PAN, Yalan YU

Frontiers of Chemical Science and Engineering 2009, Volume 3, Issue 3, Pages 293-297 doi: 10.1007/s11705-009-0204-7

Abstract: A computational fluid dynamics (CFD) simulation that coupled an established heat and mass transfer model was carried out for the air-gap membrane distillation (AGMD) of NaCl solution to predict mass and heat behaviors of the process. The effects of temperature and flowrate on fluxes were first simulated and compared with available experimental data to verify the approach. The profiles of temperature, temperature polarization factor, and mass flux adjacent to the tubular carbon membrane surface were then examined under different feed Reynolds number in the computational domain. Results show that the temperature polarization phenomena can be reduced, and mass flux can be enhanced with increase in the feed Reynolds number.

Keywords： membrane distillation computational fluid dynamics (CFD) simulation temperature polarization carbon membrane

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Thin-liquid-film evaporation at contact line

Hao WANG, Zhenai PAN, Zhao CHEN

Frontiers in Energy 2009, Volume 3, Issue 2, Pages 141-151 doi: 10.1007/s11708-009-0020-2

Abstract: When a liquid wets a solid wall, the extended meniscus near the contact line may be divided into three regions: a nonevaporating region, where the liquid is adsorbed on the wall; a transition region or thin-film region, where effects of long-range molecular forces (disjoining pressure) are felt; and an intrinsic meniscus region, where capillary forces dominate. The thin liquid film, with thickness from nanometers up to micrometers, covering the transition region and part of intrinsic meniscus, is gaining interest due to its high heat transfer rates. In this paper, a review was made of the researches on thin-liquid-film evaporation. The major characteristics of thin film, thin-film modeling based on continuum theory, simulations based on molecular dynamics, and thin-film profile and temperature measurements were summarized.

Keywords： meniscus thin film contact line disjoining pressure evaporation

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Enhanced penetration strategies for transdermal delivery

Qiaofei Pan, Yinglin Yu, Dong Chen, Genlong Jiao, Xiaowen Liu

Frontiers of Chemical Science and Engineering 2020, Volume 14, Issue 3, Pages 378-388 doi: 10.1007/s11705-019-1913-1

Abstract: Transdermal delivery offers several advantages in drug distribution, including convenience, painless administration, avoidance of first-pass metabolism, and ease of termination. However, the natural protective barriers of the skin, such as the stratum corneum, the topmost layer of skin, limit the systemic absorption of external therapeutics via transdermal delivery. Therefore, extensive application of transdermal delivery in medical treatment has been limited. Over the past few years, many formulation strategies and physical technologies, therefore, have been developed to enhance transdermal delivery. This review summarizes various formulation strategies proposed for transdermal delivery and their application in medical treatment.

Keywords： transdermal delivery stratum corneum enhanced penetration therapeutics

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Passive millimeter-wave target recognition based on Laplacian eigenmaps

Luo Lei,Li Yuehua,Luan Yinghong

Strategic Study of CAE 2010, Volume 12, Issue 3, Pages 77-81

Abstract: experiments show that the method gets higher recognition rate than other linear and kernel-based nonlinear dimensionality

Keywords： manifold learning Laplacian eigenmaps nonlinear dimensionality reduction low dimensional manifold MMW

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Combustion characteristics of a direct-injection diesel engine fueled with Fischer-Tropsch diesel

HUANG Yongcheng, ZHOU Longbao, PAN Keyu

Frontiers in Energy 2007, Volume 1, Issue 2, Pages 239-244 doi: 10.1007/s11708-007-0033-7

Abstract: Fischer-Tropsch (F-T) diesel fuel is characterized by a high cetane number, a near-zero sulphur content and a very low aromatic level. On the basis of the recorded incylinder pressures and injector needle lifts, the combustion characteristics of an unmodified single-cylinder direct-injection diesel engine operating on F-T diesel fuel are analyzed and compared with those of conventional diesel fuel operation. The results show that F-T diesel fuel exhibits a slightly longer injection delay and injection duration, an average of 18.7% shorter ignition delay, and a comparable total combustion duration when compared to those of conventional diesel fuel. Meanwhile, F-T diesel fuel displays an average of 26.8% lower peak value of premixed burning rate and a higher peak value of diffusive burning rate. In addition, the F-T diesel engine has a slightly lower peak combustion pressure, a far lower rate of pressure rise, and a lower mechanical load and combustion noise than the conventional diesel engine. The brake specific fuel consumption is lower and the effective thermal efficiency is higher for F-T diesel fuel operation.

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Title Author Date Type Operation

Development trend of urban design in “digital age”: Pan-dimensionality and individual-ubiquity

Journal Article

Fuel optimal control of parallel hybrid electric vehicles

PU Jinhuan, YIN Chenliang, ZHANG Jianwu

Journal Article

A MATLAB code for the material-field series-expansion topology optimization method

Journal Article

Optimization design of spar cap layup for wind turbine blade

Jie ZHU, Xin CAI, Pan PAN, Rongrong GU

Journal Article