Modeling of three-dimensional cutting forces in micro-end-milling

A new nominal uncut chip thickness algorithm for micro-scale end-milling is proposed by considering the combination of an exact trochoidal trajectory of the tool tip and tool run-out, and then the actual uncut chip thickness may be obtained from a comparison between the current accumulative uncut chip thickness and the minimum chip thickness. Due to the intermittency of the chip formation, the milling process is divided into an elastic-plastic deformation regime and a chip formation regime dominated by ploughing forces and shearing forces, respectively, and three-dimensional cutting forces are modeled according to different regimes. Based on the modeling and simulation technologies introduced, a simulation system for the prediction of three-dimensional cutting forces of a micro-scale end-milling process is developed. The simulation results show a very satisfactory agreement with those data from milling experiments.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58144/2/jmm7_4_001.pd

Analysis of Influencing Factors of Green Building Energy Consumption Based on Genetic Algorithm

With the advancement of modernization, high energy consumption buildings can no longer meet the needs of social development. Under the background of low carbon and energy saving, the development of green buildings has become the only way, but its energy-saving design effect needs to be further studied. Aiming at lighting and energy consumption, this study carried out multi-factor optimization analysis based on genetic algorithm on factors such as windowing ratio, wall heat transfer coefficient, window heat transfer coefficient, window transmittance and roof insulation coefficient. Firstly, the theory and technical scheme of applying data mining technology to solve the energy-saving design problems of different buildings are proposed and implemented, including the design of new and existing buildings, as well as the determination of decisive parameters and non-decisive parameters. Secondly, computer simulation and theoretical analysis are used to optimize the analysis of the building scheme, so as to find the optimal design range of each influencing factor and the optimal design method of green low-energy building. Multi-factor optimization theory and genetic algorithm principle are summarized, and the heat transfer coefficient of external wall and window of the building is selected as the optimization variable, so as to achieve low energy consumption and enclosure cost of the building. Aiming at better thermal comfort, an optimization model was established. Finally, through empirical research, an energysaving plan was designed, and genetic algorithm was used to obtain the optimal solution for maximizing the incremental benefits obtained by unit input incremental cost. The results indicate that the ideal incremental benefits come from a reasonable and effective combination of technologies, mainly from air conditioning systems and lighting systems; the setting of the benchmark return rate will directly affect the optimization effect of energy-saving plans, providing decision-makers with the optimal combination of energy-saving technologies

Nanoparticle-Mediated Therapeutic Agent Delivery for Treating Metastatic Breast Cancer—Challenges and Opportunities

Breast cancer (BC) is the second leading cause of cancer-related death in American women and more than 90% of BC-related death is caused by metastatic BC (MBC). This review stresses the limited success of traditional therapies as well as the use of nanomedicine for treating MBC. Understanding the biological barriers of MBC that nanoparticle in vivo trafficking must overcome could provide valuable new insights for translating nanomedicine from the bench side to the bedside. A view about nanomedicine applied in BC therapy has been summarized with their present status, which is gaining attention in the clinically-applied landscape. The progressions of drug/gene delivery systems, especially the status of their preclinical or clinical trials, are also discussed. Here we highlight that the treatment of metastasis, in addition to the extensively described inhibition of primary tumor growth, is an indispensable requirement for nanomedicine. Along with more innovations in material chemistry and more progressions in biology, nanomedicine will constantly supply more exciting new approaches for targeted drug/gene delivery against MBC

Fabrication of porous Al2O3-based ceramics using combustion synthesized powders

Porous Al2O3-based ceramics were fabricated from powders synthesized via a solution combustion process using starch and urea as fuels. Effects of the relative fuel-to-oxidant ratio (φe = 1.4, 1.6, 1.8 and 2.0, respectively) on open porosity, pore size distribution and flexural strength of the as-prepared porous Al2O3-based ceramics were investigated. Experimental results revealed that the densification ability of the as-synthesized powders increased significantly as φe increased, and open porosity, pore size distribution and flexural strength of the porous ceramics exhibited remarkable dependence on the densification ability of the powders instead of the weight fraction of the charred organic residuals in the powders. SEM micrographs disclosed that the porous ceramics from the precursors with φe = 1.8 or 2.0 exhibited significantly homogenous microstructures including pore size and pore distribution

XVoxel-Based Parametric Design Optimization of Feature Models

Parametric optimization is an important product design technique, especially in the context of the modern parametric feature-based CAD paradigm. Realizing its full potential, however, requires a closed loop between CAD and CAE (i.e., CAD/CAE integration) with automatic design modifications and simulation updates. Conventionally the approach of model conversion is often employed to form the loop, but this way of working is hard to automate and requires manual inputs. As a result, the overall optimization process is too laborious to be acceptable. To address this issue, a new method for parametric optimization is introduced in this paper, based on a unified model representation scheme called eXtended Voxels (XVoxels). This scheme hybridizes feature models and voxel models into a new concept of semantic voxels, where the voxel part is responsible for FEM solving, and the semantic part is responsible for high-level information to capture both design and simulation intents. As such, it can establish a direct mapping between design models and analysis models, which in turn enables automatic updates on simulation results for design modifications, and vice versa -- effectively a closed loop between CAD and CAE. In addition, robust and efficient geometric algorithms for manipulating XVoxel models and efficient numerical methods (based on the recent finite cell method) for simulating XVoxel models are provided. The presented method has been validated by a series of case studies of increasing complexity to demonstrate its effectiveness. In particular, a computational efficiency improvement of up to 55.8 times the existing FCM method has been seen.Comment: 22 page

Diversity of archaea and bacteria in a biogas reactor fed with Pennisetum sinese Roxb by 16S rRNA sequence analysis

Purpose: To investigate the structure and function of the complex rumen microbial community in a biogas reactor by 16S rRNA gene analysis, which was fed with Pennisetum sinese Roxb as the monosubstrate.Methods: Two 16S ribosomal RNA (rRNA) clone libraries of bacteria and archaea were established by polymerase chain reaction. Community structure was determined by phylogenetic analyses of 119 and 100 16S rRNA gene clones from the bacterial and archaeal libraries, respectively.Results: In the bacterial library, 13.4 % of clones were affiliated with Treponema porcinum, 5.9 % with Eubacterium limosum, 5 % with Clostridium, 5 % with Bacteroidetes, 4.2 % with Firmicutes, 2.5 % with Anaerofilum and a total of 64 % clones belonged to unclassified or uncultured bacteria. In the archaeal library, Methanobacterium curvum made up 12 % of known clones, Methanosarcina barkeri represented 8 %, Methanobacterium bryantii represented 4 % and Methanofollis ethanolicus represented 2 %, respectively; the remaining 74 % of the clones were unclassified archaebacteria.Conclusion: T. porcinum and M. curvum are the most predominant bacteria and archaea in a biogas reactor fed with P. sinese as the sole substrate.Keywords: Pennisetum sinese Roxb, Archaea, Bacteria, Biogas reactor, 16S rDNA sequencin

Comparison for Chinese subordinates as a motivation approach: scale development and psychometric properties

Purpose: Chinese people are motivated by social comparison and temporal comparison. Based on this finding, we conceptualized lateral comparison and vertical comparison as two distinct constructs that represent individual self-enhancement toward the nature of social comparison with others and temporal comparison with self over time. We hypothesized that as stable individual psychological difference, lateral comparison and vertical comparison would have differential effects on people’s working behavior in the Chinese organizational context. Design/methodology/approach: Based on a conceptualization approach to Chinese management research, we conducted three studies to develop and validate a two-factor comparison scale which includes three-item lateral comparison and a three-item vertical comparison. Findings: Results from qualitative data in Study 1 provide evidence of convergent and discriminate validity of the scale, while Study 2 demonstrates the scale’s predictive validity. Furthermore, in Study two, a field survey in multiple Chinese organizations showed that lateral comparison and vertical comparison had differential effects on employee task performance and organizational citizenship behavior. Research implications: The theoretical and practical implications of this study are discussed in the working context in Chinese organizations and beyond. Originality/value: This finding integrates insights from previous research in social comparison and temporal comparison into a motivation approach that supervisors use toward subordinates in the Chinese organizational context.Peer Reviewe

Fog and Cloud Computing Assisted IoT Model Based Personal Emergency Monitoring and Diseases Prediction Services

Along with the rapid development of modern high-tech and the change of people's awareness of healthy life, the demand for personal healthcare services is gradually increasing. The rapid progress of information and communication technology and medical and bio technology not only improves personal healthcare services, but also brings the fact that the human being has entered the era of longevity. At present, there are many researches focused on various wearable sensing devices and implant devices and Internet of Things in order to capture personal daily life health information more conveniently and effectively, and significant results have been obtained, such as fog computing. To provide personal healthcare services, the fog and cloud computing is an effective solution for sharing health information. The health big data analysis model can provide personal health situation reports on a daily basis, and the gene sequencing can provide hereditary disease prediction. However, the injury mortality and emergency diseases since long ago caused death and great pain for the family. And there are no effective rescue methods to save precious lives and no methods to predict the disease morbidity likelihood. The purpose of this research is to capture personal daily health information based on sensors and monitoring emergency situations with the help of fog computing and mobile applications, and disease prediction based on cloud computing and big data analysis. Through the comparison of test results it was proved that the proposed emergency monitoring based on fog and cloud computing and the diseases prediction model based on big data analysis not only gain more of the rescue time than the traditional emergency treatment method, but they also accumulate lots of different personal healthcare related experience. The Taian 960 hospital of PLA and the Yanbian Hospital as IM testbed were joined to provide emergency monitoring tests, and to ensure the CVD and CVA morbidity likelihood medical big data analysis, the people around Taian city participated in personal health tests. Through the project, the five network layers architecture and integrated MAPE-K Model based EMDPS platform not only made the cooperation between hospitals feasible to deal with emergency situations, but also the Internet medicine for the disease prediction was built

Analysis of labor resources wastage in China’s real estate brokerage: from the perspective of opportunity costs

Real estate brokerage has experienced the rapid growth over the past two decades in China, with a significant increase of employees. In particular, in the megacities like Beijing, the growth of employees exceeds the growth of real estate transaction volume. This may lead to the wastage of labor resources. In this regard, the optimal employee size (OES) in China’s real estate brokerage is proposed from the perspective of opportunity costs, which include both under-size and over-size costs. In the proposed OES models, a real estate brokerage firm makes the optimal decisions of number of employees by minimizing expected opportunity costs. In addition, an iterative algorithm is employed to obtain the optimal employee size in different scenarios. The result reveals that high profit gained from the business does attract more employees than what is needed. By addressing various scenarios based on the game model, it is found that asymmetric competition, the increase of market participants, and demand fluctuations also contribute to the labor resources wastage in real estate brokerage industry. The theoretical analysis results are verified by taking Beijing as the case study. Finally, suggestions for reducing labor resources wastage in real estate brokerage of China are provided