This study investigates the enhancement of the oxygen diffusion rate in the cathode channel of a proton exchange membrane fuel cell (PEMFC) by pure oscillating flow, which is the same as the mechanism of human breathe. Three-dimensional numerical simulation, which has the full model of the fuel cell including electrochemical reaction, ion and electronic conduction, mass transfer and thermal variation and so on, is performed to show the phenomena in the channel at the case of a steady state. This model could analysis the oscillating flow as a moving mesh calculation coupled with electrochemical reaction on the catalyst layer, however, it needs a lot of calculation time for each case. The two dimensional numerical simulation has carried on for the study of oscillating flow effect in the cathode channel of PEMFC in order to reduce the calculation time. This study shows the diffusion rate of the oxygen increased and the emission rate of the water vapor increased in the channel by oscillating flow without any forced flow.

An elliptic blending Reynolds stress transport equation model for Newtonian fluids has been extended to predict polymer-induced drag reduction FENE-P fluids. The conformation tensor equation which is related to the polymer stress is adopted from the model form of Resende et al., and the models of redistribution and dissipation rate terms for the Reynolds stress transport equation are considered by the elliptic blending equation. Also, the new model terms for viscoelastic turbulent transport and viscoelastic dissipation in the Reynolds stress transport equation are introduced to consider the polymer additives effect. The prediction results are directly compared to the DNS data to assess the performance of the present model predictions.

Introduction An important decision that a manufacturer has to make in distributing a product to customers is the degree of forward channel integration (Aulakh & Kotabe, 1997; Coughlan et al., 2001; John & Weitz, 1988). Transaction cost economics (TCE) developed by Williamson (1975, 1985, 1986, 1999) has been one of the leading theoretical frameworks used to explain the channel integration decision (Frazier, 1999; Watson et al., 2015). TCE is generally a theory for explaining the choice of an efficient governance structure in transactions and includes asset specificity, uncertainty, and frequency as its explanatory variables. According to Williamson (1985, 1986, 1999), much of the explanatory power of TCE is driven by asset specificity. TCE-based channel integration studies argue that as asset specificity increases, firms are expected to increase the degree of channel integration. This study proposes to extend existing research in four important ways. First, existing studies have not examined individual dimensions of asset specificity. This study examines two important dimensions discussed by TCE: human asset specificity and physical asset specificity. Second, existing studies have tended to measure asset specificity in a particular way (i.e., with a particular set of questionnaire items). This study examines the robustness of the estimated asset specificity-integration relationship to alternative measures of asset specificity. Third, existing studies have focused on firms in one country such as the United States, Canada, or Germany. This study empirically examines the roles and relative importance of human and physical asset specificity in channel integration in two countries with different cultures, the United States and Japan. Fourth, existing studies have not investigated the possibility of endogeneity between asset specificity and channel integration. This study tests whether asset specificity is endogenous in explaining channel integration through an instrumental variables and two-stage least squares (IV-2SLS) approach. Literature Review In the context of distribution channels, asset specificity refers to the extent to which durable, transaction-specific investments in human and/or physical assets are needed to distribute the product in question (John & Weitz, 1988; Klein et al., 1990; Shervani et al., 2007). Examples of such investments include (1) the time and effort employed to acquire the firm-specific, product-specific, and customer-specific knowledge needed for distribution activities, and (2) specialized physical equipment and facilities (e.g., warehouses, deliver vehicles, refrigeration equipment, demonstration facilities, and repair and service centers) (Anderson, 1985; Bello & Lohtia, 1995; Brettel et al., 2011a, 2011b; John & Weitz, 1988; Shervani et al., 2007; Williamson, 1985, 1986). According to TCE, when the assets needed to distribute a product are non-specific, the use of independent channels is a priori more efficient than the use of integrated channels based on the benefits of distribution specialists and competition in the market place (Anderson, 1985). Conversely, a high level of specific assets, whether human or physical, has important implications for the degree of channel integration. The primary consequence is to reduce a large number of relationships between a manufacturer and independent channel members to a small number of relationships, which may expose the transaction in question to opportunistic behavior. Because the unique productive value created by a high level of specific assets makes it costly to switch to a new relationship, the use of independent channels will not be effective as a safeguard against opportunism (John & Weitz, 1988; Shervani et al., 2007). Channel integration provides a safeguard against opportunism by permitting (1) the better monitoring and surveillance of integrated channels relative to independent channels, and (2) the reduction of profits from opportunistic behavior since employees in integrated channels do not ordinarily have claims to profit streams (John & Weitz, 1988). As a result, as asset specificity increases, manufacturers are expected to increase the degree of channel integration to exercise greater control over the channels (John & Weitz, 1988; Shervani et al., 2007). This leads to the following basic TCE hypothesis concerning asset specificity and channel integration: TCE hypothesis. Asset specificity will be positively related to the degree of channel integration. Existing studies of channel integration tend to provide support or partial support for the hypothesized positive relationship between asset specificity and channel integration. One limitation of key studies is that they have not fully explored the dimensions of asset specificity because they treat asset specificity as unidimensional or examine only one dimension of asset specificity. Specifically, Anderson and Schmittlein (1984), Anderson (1985), Anderson and Coughlan (1987), and Krafft et al. (2004) focus on human asset specificity. While John and Weitz (1988), Shervani et al. (2007), and Brettel et al. (2011a) consider both human and physical asset specificity in their theoretical discussions, their empirical analyses focus only on human asset specificity. Klein et al. (1990), Aulakh and Kotabe (1997), and Brettel et al. (2011a) use a single measure of asset specificity that contains distinct items measuring human and physical asset specificity. Importantly, none of these studies has examined the dimension of physical asset specificity while controlling for the impact of human asset specificity. These observations suggest that further research is needed that explicitly measures and evaluates the relative importance of human and physical asset specificity in the channel integration decision. Research Hypotheses Based on the above literature review, we seek to extend existing research by distinguishing between two types of asset specificity, human and physical asset specificity. As already explained, TCE and TCE-based channel integration studies argue that both human and physical asset specificity are positive drivers of the degree of channel integration. Thus, our research hypotheses are the following: Hypothesis 1. Human asset specificity will be positively related to the degree of channel integration. Hypothesis 2. Physical asset specificity will be positively related to the degree of channel integration. Research Methodology As shown in Table 1, previous empirical studies attempt to test the basic TCE hypothesis concerning asset specificity and channel integration using (1) a particular measure of asset specificity, (2) data from a single national survey of firms in the United States, Canada, or Germany, and (3) methods such as an ordinary least squares (OLS) regression analysis and a partial least squares structural equation modelling (PLS-SEM) approach. In contrast with these studies, we seek to test the above two hypotheses concerning two types of asset specificity and channel integration using (1) different measures of asset specificity, (2) data from parallel national surveys of firms in two countries with different cultures, the United States and Japan, and (3) the methods used in prior empirical analyses and an IV-2SLS approach, which is a widely accepted method for investigating the potential endogeneity problem of focal explanatory variables (Antonakis et al., 2010, 2014; Zaefarian et al., 2017). This research strategy is partly based on the guidelines for high-quality replication studies articulated by Bettis et al. (2016b). The aims are to assess the generalizability of important prior results using different survey data drawn from different research contexts and to assess the robustness of these results using different measures and methods, thereby providing important additional evidence that contributes to the establishment of repeatable cumulative knowledge (Bettis et al., 2016a, 2016b). We developed the survey questionnaire in several steps. Following John and Weitz (1988), Shervani et al. (2007), and Brettel et al. (2011b), the dependent variable, channel integration, was operationalized by the percentage of sales through direct channels. We measured the focal explanatory variable, asset specificity, in four ways: (1) a four-item scale of human asset specificity used by Shervani et al. (2007), (2) a four-item scale of physical asset specificity based on Bello and Lohtia (1995) and Klein et al. (1990), (3) a six-item scale of human and physical asset specificity used by Klein et al. (1990), and (4) a four-item scale of human and physical asset specificity used by Brettel et al. (2011a). We also included four control variables: environmental uncertainty, behavioral uncertainty, financial performance, and channel members’ capabilities. Based on existing studies, manufacturers of electronic and telecommunication, metal, and chemical products in industrial (business-to-business) markets were selected as the setting for the empirical test. The unit of analysis was the domestic channel integration decision made at a product-market level. Respondents were sales/marketing managers (or executives) knowledgeable about channel design and strategies. In the United States, a professional marketing research company administered the data collection. In Japan, respondents were surveyed by mail. In total, we obtained 235 usable responses from US managers and 279 responses from Japanese managers. Results and Conclusions Following similar studies (John & Weitz, 1988; Shervani et al., 2007), an OLS regression analysis was used to test the hypotheses. The results, shown in Table 1, exhibit significant explanatory power for each model. As expected, (1) human asset specificity exhibits significant positive relationships with the degree of channel integration in both the United States and Japan (Models 1 & 2). These findings support Hypothesis 1. Conversely, (2) physical asset specificity does not have the expected significant positive relationships with the degree of channel integration in both the United States and Japan (Models 1 & 3). These findings do not support Hypothesis 2. Also, (3) asset specificity (Klein et al., 1990) and (4) asset specificity (Brettel et al., 2011a), two composite measures of human and physical asset specificity, exhibit the expected significant coefficients (Models 4 & 5). Additionally, we conducted a similar analysis using a structural equation modelling approach. The results mirrored those of OLS regression, thus providing further support for it. To assess the problem of potential endogeneity between asset specificity and channel integration, we employed IV-2SLS. We used (1) the level of the product’s technical content and (2) the need for coordination between production and distribution activities as instruments for human/physical asset specificity. Our instruments were individually significant predictors of asset specificity and met the exclusion restriction. However, the endogeneity test revealed no evidence of endogeneity. Thus, asset specificity was treated as exogenous in the model. In summary, our preliminary results suggest that human asset specificity, not physical asset specificity, is relevant to the channel integration decision. This finding is significant in that TCE-based channel integration studies tend to measure only one type of asset specificity. We are currently conducting additional analyses to better understand the relationship between human and physical asset specificity, for example, (1) the effects of human and physical asset specificity on different kinds of direct distribution, and (2) a multiple equation model in which human asset specificity is a function of physical asset specificity and direct distribution is a function of both human and physical asset specificity. We believe that our results will have important implications for the ways in which managers approach the channel integration decision.

The emergence of a new marketing channel affects the economy by expanding the consumer's choice of products, altering the competitiveness of retail markets and having an influence on manufacturers' profitability. The electronic commerce channel through the Internet constitutes a typical marketing channel with these features. In this paper, we construct a vertical product differentiation model comprising an upstream manufacturer and two downstream retailers. Our model is closely related to that in Chiang, Chhajed and Hess (2003). We incorporate cost asymmetry across the retailers into the model, a new feature which is not in their model. In this model, the manufacturer not only produces a physical product it sells to the downstream retailers, but also has an option of "versioning" to open a new direct channel for an alternate digital product. We find that, when the marginal cost of the physical product is in some range given other cost parameters, the direct digital channel reduces the quantity of the physical product sold by the inefficient retailer even if it increases total quantity of the physical product. We also find that, when it is higher than the above-mentioned range, the direct digital channel increases the quantity of the physical product sold by the efficient retailer even if it reduces its total quantity. Cost asymmetry across the retailers plays a role in these results. Taking the above results into account, we discuss managerial implications for a manufacturer supplying the physical and digital products.

The flourishing trend of using multiple technology-based self-service channels (hereafter, SSCs) can be found across various service industries. So far, no studies have explored the effect of multichannel interaction on breadth consumer relationship breadth (i.e., cross-buying intention). Based on brand extension theory and the cross-buying literature, this study proposed a conceptual model for understanding the key determinants of consumer cross-buying intention in the context of multiple SSCs. A total of 262 respondents who had experience with using both online and mobile banking were collected. The result revealed that perceived online banking quality (i.e., original SSC), image congruity, and value congruity facilitate consumer trust and satisfaction toward a mobile banking service (i.e., extension SSC). In addition, the trust and satisfaction toward mobile banking have a positive influence on crossbuying intention. The result of this study not only provides an academic contribution to the multichannel service and SSC literature but also provides suggestions for service providers who wish to develop their multiple-SSC strategies.

The channel transformation to omni-channel is currently in progress in the retail industry. For the progress to occur, facilitating meaningful experiences of customers in their customer journeys, capturing such experiences through various channels and touch points, and then analyzing the information acquired as big data are required (Lemon and Verhoef, 2016). With the increase in the number of customer experiences being observed through the internet and mobile communication, the focus is now on engagement. However, there have not yet been many studies conducted to deliberate comprehensively on how the engagements of behavioral aspects captured through various channels and the evaluation indicators of customers, as represented by the RFM or LTV, are related in a broader sense. The purpose of this research is to clarify the relational structure from a comprehensive perspective that are not constrained by monetary amounts. This paper showed results using data from the retailer. This research is divided broadly into two stages. The first stage identifies the engagements of behavioral aspects and the relationship between the respective behaviors, as well as the typification of behavioral patterns. The second stage involves clarifying the relationship between the customer’s evaluation indicators and engagement behaviors. The engagement behaviors are basically correlated with RFM, however authors found that there is no relationship between specific engagement behavior and RFM in the group of low rank customers. On the other hand, using different types of services or shops from the core business strengthens the customer relationship. Finally, the relationship between the types of engagement behaviors and the respective customer evaluation indicators is presented in the conclusion.

Currently, dramatic change had led to the growth of the distribution environment and the retailer’s distribution channel. This change had shifted the ‘single channel’ to ‘multi channel’, and from ‘cross channel’ to ‘omni channel’. While fashion companies using omni channel are rapidly growing, few research regarding omni channel had been done in academic field. In this study, we examined the influence of omni channel characteristics on consumers’ perceived risk as well as consumers’ perceived risk toward attitude and intention to use omni channel. We surveyed 696 male and female respondents aged 20 to 40 who lived in Seoul and the metropolitan area. Using AMOS 20.0, factor analysis, reliability analysis, and structural equation model analysis were performed to verify the model of this study. The results were as follows. First, omni channel’s instant connectivity, location-based provability, interactivity, and entertainment factors did not decrease impacts on the perceived risk related to privacy and annoyance. Second, omni channel’s instant connectivity and entertainment did not increase effects on the perceived financial risk, and location-based provability and interactivity did not increase effect on perceived financial risk. Third, the perceived risk concerning omni channel did not decrease on consumer attitude toward omni channel. Fourth, consumer attitude toward omni channel influenced the intention to use omni channel significantly.

본 연구에서는 비용매 유도 상분리와 소결 공정을 혼용하여 기체 및 액체에 대하여 슈퍼플럭스 거동을 보이는 니켈 모세관 지지체를 성공적으로 제조하였다. 니켈 모세관 전구체는 니켈, 폴리술폰, DMAC, PEG를 이용하여 도프용액을 제 조한 후 NIPS 공정에 의하여 제조된 후에, 다양한 소결온도에서 수소 분위기 조건에서 소결하여 니켈 모세관 지지체를 제조 하였다. 최적의 니켈 모세관 지지체는 950°C 소결온도에서 얻어졌는데 외경 722 μm, 내경 550 μm, 두께 94 μm이었다. 니켈 모세관 지지체 기공율은 26%, 평균 기공경은 4 μm이었으며 3차원으로 서로 연결된 기공구조를 갖고 있었다. 그리고 파괴하 중은 2.84 kgf, 파괴 연신율은 13%이었다. 니켈 모세관 지지체의 He, N2, O2, CO2에 대한 단일 기체 투과도는 상온에서 각각 432,327, 281,119, 264,259, 193,143 GPU로 슈퍼플럭스 거동을 보였다. 이는 3차원적으로 서로 연결된 4 μm 크기 마크로기 공을 통하여 viscous flow가 일어났기 때문에 나타나는 현상으로 설명되었다.

목 적：Parallel 영상기법은 영상획득시간을 단축시키기 위해 개발된 기법으로 신호강도가 저하되는 문제점이 있다. 이러한 문제점을 해결하기 위해 코일의 channel 수를 증가시키는데, 저자들은 코일의 channel 증가가 영상의 신호강도에 어떠한 영향을 미치는지 정량적으로 알아보고자 하였다. 대상 및 방법：연구방법은, 8과 16 channel의 knee 코일에 동일한 phantom(31.5mmol/L of NiCl2-6H2O, gainesville, florida USA)을 장착한 후 reduction factor(0, 1, 2)에 따른 T1, T2, 강조영상을 획득하 여 신호강도를 비교평가 하였다. 영상획득은 3.0T 자기공명영상 장치(Archiva, Philips, Germany)와 8 channel과 16 channel knee 코일을 사용하여 축상면 영상을 획득 하였으며, 획득한 영상은 신호강도 를 측정한 후 대응표본 T검정(SPSS ver.18, SPSS Inc., Chicago IL, USA)을 이용하여 유의한 차이가 있는지 판단하였다. 결 과：연구결과, 8 channel 보다 16 channel 코일을 사용하였을 때 T1 강조영상은 평균 43.67%(reduction factor 0: 43.89%, 1: 44.11%, 2: 42.99%), T2 강조영상은 평균 43.43%(reduction factor 0: 42.77%, 1: 43.50%, 2: 44.04%) 신호강도가 증가하였다. 대응표본 T 검정 결과 T1, T2 강조영상 모두 유의확률이 0.05 이하로 나타나 코일의 channel 증가에 따라 신호강도가 유의하게 증가함을 알 수 있었다. 결 론：결론적으로 코일의 channel 증가는 parallel 영상기법의 reduction factor에 관계없이 영상의 신호강도 를 증가시키므로 가능하다면 channel 수가 많은 코일을 사용하는 것이 MRI에서 가장 중요한 신호강도 를 높일 수 있는 방안이라 사료된다.

Small hive beetle (Aethina tumida) (SHB) is an invasive species to most northern hemisphere countries, including Korea. In an attempt to obtain basic information for efficient management of SHB, genes encoding conventional insecticide targets [voltage-sensitive sodium channel α-subunit (VSSC) and acetylcholinesterase (AChE)] were annotated and characterized following the analysis of whole transcriptomes of adults and larvae. A single VSSC gene was identified but no apparent mutations associated with pyrethroid resistance were detected. Genes encoding two AChEs (AtAChE1 and AtAChE2) were identified from the SHB transcriptome. AtAChE1 was determined to be the main catalytic enzyme, thereby being a toxicologically more relevant target. No apparent mutations associated with resistance to organophosphorus and carbamate insecticides was identified in the AtAChE1 gene, whereas the S238G mutation, originally identified from the Colorado potato beetle, was detected in the AtAChE2 gene.

K+ channels are key components of the primary and secondary basolateral Cl- pump systems, which are important for secretion from the salivary glands. Paroxetine is a selective serotonin reuptake inhibitor (SSRI) for psychiatric disorders that can induce QT prolongation, which may lead to torsades de pointes. We studied the effects of paroxetine on a human K+ channel, human ether-a-go-go-related gene (hERG), expressed in Xenopus oocytes and on action potential in guinea pig ventricular myocytes. The hERG encodes the pore-forming subunits of the rapidly-activating delayed rectifier K+ channel (IKr) in the heart. Mutations in hERG reduce IKr and cause type 2 long QT syndrome (LQT2), a disorder that predisposes individuals to lifethreatening arrhythmias. Paroxetine induced concentrationdependent decreases in the current amplitude at the end of the voltage steps and hERG tail currents. The inhibition was concentration-dependent and time-dependent, but voltageindependent during each voltage pulse. In guinea pig ventricular myocytes held at 36℃, treatment with 0.4 μM paroxetine for 5 min decreased the action potential duration at 90% of repolarization (APD90) by 4.3%. Our results suggest that paroxetine is a blocker of the hERG channels, providing a molecular mechanism for the arrhythmogenic side effects of clinical administration of paroxetine.

Increased intracellular levels of Ca2+ are generally thought to negatively regulate lipolysis in mature adipocytes, whereas store-operated Ca2+ entry was recently reported to facilitate lipolysis and attenuate lipotoxicity by inducing lipophagy. Transient receptor potential mucolipin1 (TRPML1), a Ca2+-permeable non-selective cation channel, is mainly expressed on the lysosomal membrane and plays key roles in lysosomal homeostasis and membrane trafficking. However, the roles of TRPML1 in lipolysis remains unclear. In this study, we examined whether the channel function of TRPML1 induces lipolysis in mature adipocytes. We found that treatment of mature adipocytes with ML-SA1, a specific agonist of TRPML1, solely upregulated extracellular glycerol release, but not to the same extent as isoproterenol. In addition, knockdown of TRPML1 in mature adipocytes significantly reduced autophagic flux, regardless of ML-SA1 treatment. Our findings demonstrate that the channel function of TRPML1 partially contributes to lipid metabolism and autophagic membrane trafficking, suggesting that TRPML1, particularly the channel function of TRPML1, is as therapeutic target molecule for treating obesity.

As fashion and distribution companies have increasingly turned to implementing marketing activities that use omni-channel strategies, it is imperative to explore consumer-oriented evaluations of omni-channel shopping for fashion products. Through contributing to the growing research flow of consumer behavior within omni-channel contexts, the current study explores consumer motivations for omni-channel fashion shopping and their impacts on the decision-making stages of fashion products. The authors first performed in-depth interviews with six Korean consumers and confirmed the four types of consumer motivation for omni-channel shopping, and how decision- making processes react to fashion companies’ omni- channel marketing strategies. These findings were used to set survey items for the main study. Based on the results and findings of previous literature, an online survey was conducted with 300 participants who had actual experience with omni-channel shopping for fashion products. The statistic results from the survey revealed the following: First, the in-depth interviews allowed the authors to confirm four factors of omni-channel shopping motivation (ubiquity, efficiency, convenience, and impulsiveness). Second, the survey showed the authors that among the four factors of omni-channel shopping orientation, impulsiveness had the greatest effect on consumer behaviors at the preand on-purchase stages, while the ubiquity factor had the greatest effect at the post-purchase stage. As such, the study empirically tested the omni-channel-specific factors of shopping orientation and motivation. In addition, it showed the effect of omni-channel marketing on various stages of the decision- making process and the study’s limitations and implications were discussed.

The most time consuming job in the sheet metal forming process is compensating for springback. Factors such as uneven material properties and process conditions generate noise, which in turn create springback. The springback is very sensitive to the process and noise conditions, and the main effects of the design variables cannot be obtained from mean analysis. Therefore, to achieve minimal springback, an effective design countermeasure must be put in place to reduce noise effects. In this study, two robust design methods to achieve minimal springback in U-channel forming, including compensation process, are proposed. The effectiveness of the proposed methods is shown with an example of the sidewall curl springback. The proposed methods consistently outperform our previous work, indicating that the complex method is more preferable to the mean analysis, if there is no evidence of additivity of effects.

The distribution and marketing has faced a new business environment with the advent of mobile distribution channels. Due to the prevalence of smartphones and SNS, distribution structures in the market are changing naturally from multi-channel to omni-channel. Recently, omni-channel strategies have been established and implemented in many domestic distributors. This paper has proceeded with a preliminary study on how the change of the distribution structure to the omni-channel affects the supply chain management. To do this, we first looked at the cases of omni-channel strategy. Based on the systematic classification of the strategies implemented in the cases, strategies for strengthening the omni-channel were derived from statistical testing of hypotheses and research models.