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.     

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes.     

Mechanical characterization of nanoindented graphene via molecular dynamics simulations

The mechanical behavior of graphene under various indentation depths, velocities, and temperatures is studied using molecular dynamics analysis. The results show that the load, elastic and plastic energies, and relaxation force increased with increasing indentation depth and velocity. Nanoindentation induced pile ups and corrugations of the graphene. Resistance to deformation decreased at higher temperature. Strong adhesion caused topological defects and vacancies during the unloading process.     

Detection of viable antibiotic‐resistant/sensitive Acinetobacter baumannii in indoor air by propidium monoazide quantitative polymerase chain reaction

Acinetobacter baumannii represents a significant cause of nosocomial infections. Therefore, we combined real‐time quantitative polymerase chain reaction (PCR) with the propidium monoazide (PMA‐qPCR) to assess the feasibility of detecting viable, airborne A. baumannii. The biological collection efficiencies of three samplers for collecting airborne A. baumannii were evaluated by PMA‐qPCR in a chamber study. After sampling, the effects of storage in collection fluid on A. baumannii were evaluated. The results showed that the culturable ratio of A. baumannii measured using the culture method was significantly correlated with the viable ratio measured using PMA‐qPCR, but was not significantly correlated with the qPCR results. It was indicated that the AGI‐30 impinger and the BioSampler were much more effective than the Nuclepore filter sampler for collecting airborne A. baumannii. The storage temperature was critical for aerosol samples, as the loss of viable A. baumannii was minimized when the PMA‐bound DNA was stored at ?20°C or if the collected cells were stored at 4°C and subsequently processed by PMA‐qPCR within 1 month. The PMA‐qPCR method was also to distinguish between colistin‐sensitive and colistin‐resistant A. baumannii, and no colistin‐sensitive A. baumannii was detected by PMA‐qPCR upon treatment of the BioSampler collection medium with 2 μg/ml colistin for 5 min.     

Using structural equation model to explore occupational lead exposure pathways

The aim of the present study was to demonstrate the use of a structural equation model to explore the complicated lead exposure pathways in a lead battery plant. A total of 96 out of 113 assembly workers were recruited in this study. Lead measurements included blood lead, respirable airborne lead, and body surface lead loadings. Latent variables of inadvertent contact of lead on fingers and ingested lead had indirect and direct effects on the blood lead levels, respectively, and so did the variables of respirable airborne lead, smoking, and the working-place clothes being washed. A model chi(22)2 value of 31.1 (P=0.094) for a goodness of fit test indicates that the derived structural equation model appropriately accounted for the variation of blood lead levels. It is concluded that lead loadings on fingers and lips had significant effects on occupational lead uptake, and, after-work hours and break times at work were the critical time periods for inadvertent lead exposure.     

Survival of bifidobacteria after spray-drying

To investigate the survival of bifidobacteria after spray-drying, Bifidobacterium infantis CCRC 14633, B. infantis CCRC 14661, B. longum ATCC 15708, B. longum CCRC 14634 and B. longum B6 were first spray-dried with different carrier media including 10% (w/w) gelatin, gum arabic and soluble starch. B. infantis CCRC 14633 and B. longum were also determined in skim milk. It was found that survival of bifidobacteria after spray-drying varied with strains and is highly dependent on the carriers used. Among the test organisms, B. longum B6 exhibited the least sensitivity to spray-drying and showed the highest survival of ca. 82.6% after drying with skim milk. Comparisons of the effect of carrier concentrations revealed that spray-drying at 10% (w/w) gelatin, gum arabic or soluble starch resulted in the highest survival of bifidobacteria. In addition, among the various outlet-air temperatures tested, bifidobacteria showed the highest survival after drying at 50 degrees C. Elevation of outlet-air temperature caused increased inactivation of bifidobacteria. However, the inactivation caused by increased outlet-air temperature varied with the carrier used, with the greatest reduction observed using soluble starch and the least with skim milk.     

The Impact of Short-Sale Constraints on Asset Allocation Strategies via the Backward Markov Chain Approximation Method

This paper considers an asset allocation strategy over a finite period under investment uncertainty and short-sale constraints as a continuous-time stochastic control problem. Investment uncertainty is characterised by a stochastic interest rate and inflation risk. If there are no short-sale constraints, the optimal asset allocation strategy can be obtained analytically. We consider several kinds of short-sale constraints and employ the backward Markov chain approximation method to explore the impact of short-sale constraints on asset allocation decisions. Our results show that the short-sale constraints do indeed have a significant impact on these decisions.     

Robust support vector regression networks for function approximation with outliers

Support vector regression (SVR) employs the support vector machine (SVM) to tackle problems of function approximation and regression estimation. SVR has been shown to have good robust properties against noise. When the parameters used in SVR are improperly selected, overfitting phenomena may still occur. However, the selection of various parameters is not straightforward. Besides, in SVR, outliers may also possibly be taken as support vectors. Such an inclusion of outliers in support vectors may lead to seriously overfitting phenomena. In this paper, a novel regression approach, termed as the robust support vector regression (RSVR) network, is proposed to enhance the robust capability of SVR. In the approach, traditional robust learning approaches are employed to improve the learning performance for any selected parameters. From the simulation results, our RSVR can always improve the performance of the learned systems for all cases. Besides, it can be found that even the training lasted for a long period, the testing errors would not go up. In other words, the overfitting phenomenon is indeed suppressed.     

A comparison of different postures for scaffold end-frame disassembly

Overexertion and fall injuries comprise the largest category of nonfatal injuries among scaffold workers. This study was conducted to identify the most favourable scaffold end-frame disassembly techniques and evaluate the associated slip potential by measuring whole-body isometric strength capability and required coefficient of friction (RCOF) to reduce the incidence of injury. Forty-six male construction workers were used to study seven typical postures associated with scaffold end-frame disassembly. An analysis of variance (ANOVA) showed that the isometric forces (334.4-676.3 N) resulting from the seven postures were significantly different (p < 0.05). Three of the disassembly postures resulted in considerable biomechanical stress to workers. The symmetric front-lift method with hand locations at knuckle height would be the most favourable posture; at least 93% of the male construction worker population could handle the end frame with minimum overexertion risk. The static RCOF value resulting from this posture during the disassembly phase was less than 0.2, thus the likelihood of a slip should be low.