A DRBEM model for harbor oscillation with the effect of energy dissipation

Abstract

In this study, the numerical scheme of dual reciprocity boundary element method (DRBEM) is adopted to investigate the resonant problem in a harbor while considering the effect of energy dissipation. The numerical model employed the mild slope equation as a basic equation. To avoid complicated procedures for solving the equation, DRBEM is used to improve numerical efficiency. Computation results are compared with the existing experimental data and other theoretical results. It shows that the present model is valid and effective to solve the harbor oscillation problem.     

An ISM,DEI, and ANP based approach for product family development

Product customization has been used for many years, and with this concept, product families can be designed that are better matched to the needs of customers through the use of market segmentation and modular architecture. This study is composed of two phases: the first phase establishes the modular architecture, and taking a bicycle as the case study, applies the Interpretive Structural Model (ISM) to modularize and cluster parts, and then models the connecting relations between the parts numerically using a Disassembly Effort Index (DEI). The second step involves the development of a product family using cluster analysis to divide the experimental samples and the employment of an Analytic Network Process (ANP) to obtain the optimal weight performance of the modules after establishing the market segmentation model. Results of the case study establish four product families and address construction performance of both the common and independent modules between the product families.     

A novel optical technique for observation of global particle distribution in toughened composites

One promising approach to improving fracture toughness is interleaved toughening. Past observations of toughened particles have typically been conducted using the optical microscope; however, such an approach may not be able to provide a 3-D, birds-eye view of how the toughened particles are distributed on a composite interlaminar surface. In this paper, we developed a simple yet novel optical technique for observing global particle distribution on a composite laminate surface. IM7/8551-7, a material used for the fan blades of the GE90, the world’s most powerful commercial aircraft jet engine, was used to demonstrate the strength of our optical technique, which produces high-quality morphological information. High-G_IC laminate had more uniform and denser particle distribution with a smaller particle size, whereas low-G_IC laminate had larger, but far less toughened particles. The same optical technique can also be used on other particle-toughened composite systems.     

Solution‐processable and electroactive aromatic polyamides with 3,5‐bis(trifluoromethyl)triphenylamine moiety

New fluorine‐containing, triphenylamine‐based diamine and dicarboxylic acid monomers, namely 3,5‐bis(trifluoromethyl)‐4′,4″‐diaminotriphenylamine and 3,5‐bis(trifluoromethyl)‐4′,4″‐dicarboxytriphenylamine, were synthesized and polymerized with commercially available aromatic dicarboxylic acids and diamines, respectively, leading to two series of aromatic polyamides, 5a–h and 7a–e . Most of the polyamides were amorphous and readily soluble in many common organic solvents and could be solution‐cast into transparent, flexible and strong films with good mechanical properties. The polyamides had useful levels of thermal stability associated with high glass transition temperatures of 273–305 °C and 10% weight‐loss temperatures in excess of 500 °C. Cyclic voltammograms of films of polymers 5a–h on indium–tin oxide‐coated glass substrates exhibited reversible oxidation redox couples with E_1/2 around 1.15 V versus Ag/AgCl in tetrabutylammonium perchlorate/acetonitrile solution, accompanied by a color change from colorless neutral state to reddish brown oxidized state. The 7 series polymers displayed a higher oxidation potential and less electrochemical stability as compared to the 5 series analogues. © 2017 Society of Chemical Industry     

Effects of photo-assisted electrodeposited on CuInSe2 thin films

Photo-assisted one-step electrodeposition has been applied to help in forming smooth and dense CuInSe₂ films. The difference in surface morphology and crystalline quality between CuInSe₂ films with various photo-assistance has been investigated. In the photo-assisted electrodeposition process, the many kinds of lamps providing maximum light intensity at about 380 to 620 nm were used as light source to be irradiated onto the surface of Mo-coated soda-lime glass substrates. The results suggested effects of photo-assistance including activating surface diffusion and growing high-crystalline quality films with reduced defects during electrodeposition.     

Palmitic Acid-Induced Neuron Cell Cycle G2/M Arrest and Endoplasmic Reticular Stress through Protein Palmitoylation in SH-SY5Y Human Neuroblastoma Cells

Obesity-related neurodegenerative diseases are associated with elevated saturated fatty acids (SFAs) in the brain. An increase in SFAs, especially palmitic acid (PA), triggers neuron cell apoptosis, causing cognitive function to deteriorate. In the present study, we focused on the specific mechanism by which PA triggers SH-SY5Y neuron cell apoptosis. We found that PA induces significant neuron cell cycle arrest in the G₂/M phase in SH-SY5Y cells. Our data further showed that G₂/M arrest is involved in elevation of endoplasmic reticular (ER) stress according to an increase in p-eukaryotic translation inhibition factor 2α, an ER stress marker. Chronic exposure to PA also accelerates beta-amyloid accumulation, a pathological characteristic of Alzheimer’s disease. Interestingly, SFA-induced ER stress, G₂/M arrest and cell apoptosis were reversed by treatment with 2-bromopalmitate, a protein palmitoylation inhibitor. These findings suggest that protein palmitoylation plays a crucial role in SFA-induced neuron cell cycle G₂/M arrest, ER stress and apoptosis; this provides a novel strategy for preventing SFA-induced neuron cell dysfunction.     

Assessing the efficiency of supply chain scheduling algorithms using data envelopment analysis

Where different supply chain planning algorithms are used, generally similar results may pose some challenges on the differentiating powers of evaluating different production schedules because of the increasing complexity of a supply chain network structure. For the comparison purpose, performance evaluation of different supply chain planning algorithms aims to use different supply chains models with different demands, capacities, and commonality through efficiency perspective by using a modified network rational data envelopment analysis (DEA) model. The proposed DEA model has the abilities: (1) to treat only undesirable outputs that exist without normal output, and the situation where input and output are both zero by introducing two new parameters to denote the maximum inventory and amount of delayed demands of a given node in a given time period; and (2) to evaluate the effect of the undesirable outputs/inputs on efficiency with assumption that they leave the system at the end of the current time period and re-enter the system at the beginning of the next time period. To prove the effectiveness of this DEA model, eighteen scenarios with different demands, capacities, and multiple periods are compared. In addition, this study tests the DEA model on a wafer testing/probing operation of a leading global semiconductor manufacturing and testing company in Taiwan by internal supply chain perspective. Results show that the DEA model proposed in this study can be used to assess the efficiency of a real-world operation with undesirable outputs/inputs, such as inventory and delayed demands.     

An intelligent skin‐color capture method based on fuzzy C‐means with applications

Consumer behavior is complicated. In the cosmetic market, personal intuition and fashion trends for color selection are guidelines for consumers. A systematic method for female facial skin‐color classification and an application in the makeup market are proposed in this study. In this article, face recognition with a large number of images is first discussed. Then, an innovative method to capture color at selected points is presented and complexion‐aggregated analysis is performed. This innovative method is an extension of face‐recognition theory. Images in RGB format are converted to CIELAB format during data collection and then Fuzzy C‐means theory is used to cluster and group the data. The results are classified and grouped in Lab value and RGB index. Two programs are created. The first program, “FaceRGB,” captures color automatically from images. The second program, “ColorFCM,” clusters and groups the skin‐color information. The results can be used to assist an expert system in the selection of customized colors during makeup and new‐product development.     

Buoyancy effects on the laminar boundary layer heat transfer along vertically moving cylinders

Abstract

The effects of buoyancy forces on the laminar boundary layer flow and heat transfer along vertically moving cylinders are analyzed for the cases of prescribed surface temperature and prescribed wall heat flux in power of streamwise distance. Local similarity solutions are obtained to show the effects of buoyancy parameters and the transverse curvature of the cylinder on the surface friction and heat transfer rate.     

What drives smartwatch purchase intention? Perspectives from hardware,software, design,and value

Although wearable devices are popular in recent years, the market share of smartwatches is relatively low. The main goal of this research is to investigate the antecedents of the intention to purchase a smartwatch. This research develops a conceptual model and hypotheses based on the theory of reasoned action and perceived values from the perspectives of software, hardware, and aesthetic design. An online questionnaire was developed and distributed on popular websites to collect data, and 260 usable responses are collected from the potential users of the Apple Watch in Taiwan. The thirteen hypotheses were validated by using partial least squares (PLS) techniques. Among the antecedents of purchase intention in the model, the attitude towards using smartwatches was found to have the strongest direct effect. Among the factors of the attitude, design aesthetics have the most significant effect. The results also show that all of the factors about smartwatch attributes directly affected the related perceived values. However, social value and performance/quality value did not affect the intention. The model demonstrated relatively good explanatory power for purchase intention in the context of smartwatches. The proposed model can provide insights to smartwatch vendors to develop their new products and marketing strategies.