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Endwall film cooling protects vane endwall by coolant coverage, especially at the leading edge (LE) region and vane-pressure side (PS) junction region. Strong flow impingement and complex vortexaa structures on the vane endwall cause difficulties for coolant flows to cover properly. This work aims at a full-scale arrangement of film cooling holes on the endwall which improves coolant efficiency in the LE region and vane-PS junction region.

The endwall film holes are grouped in four-holes constructal patterns. Three ways of arranging the groups are studied: based on the pressure field, the streamlines or the heat transfer field. The computational analysis is done with the k-ω SST model after validating the turbulence model properly.

By clustering the film cooling holes in four-holes patterns, the ejection of the coolant flow is stronger. The four-holes constructal patterns also improve the local coolant coverage in the “tough” regions, such as the junction region of the PS and the endwall. The arrangement based on streamlines distribution can effectively improve the coolant coverage and the arrangement based on the heat transfer distribution (HTD) has benefits by reducing high-temperature regions on the endwall.

A full-scale endwall film cooling design is presented considering interactions of different film cooling holes. A comprehensive model validation and mesh independence study are provided. The cooling holes pattern on the endwall is designed as four-holes constructal patterns combined with several arrangement choices, i.e. by pressure, by heat transfer and by streamline distributions.

This paper employs the theoretical foundations for subjective well-being to examine the impacts of two underlying dimensions of subjective well-being (psychological well-being and social well-being) on pro-environmental consumption behaviors (PECBs). In this research, the moderating role of exposure to positive environmental messages on media in the relationship between subjective well-being and PECBs is also examined.

This research uses a quantitative research method with data collected from an online survey questionnaire posted in Facebook groups related to PECBs in Vietnam.

Psychological well-being and social well-being are found to be separate significant predictors of PECBs. More importantly, exposure to positive environmental messages on media was found to reinforce the impacts of psychological well-being on PECB but not moderate the relationship between social well-being and PECB.

This research offers a new insight for encouraging PECB from the perspective of subjective well-being. Different from the extant perspectives, which usually examine subjective well-being as a unidimensional antecedent of PECB, the authors highlight that subjective well-being can influence PECB in two separate dimensions. Moreover, this research extends existing literature by accentuating the role of exposure to environmental messages in the association between different types of social well-being and PECB.

For policymakers and participants of financial markets, predictions of trading volumes of financial indices are important issues. This study aims to address such a prediction problem based on the CSI300 nearby futures by using high-frequency data recorded each minute from the launch date of the futures to roughly two years after constituent stocks of the futures all becoming shortable, a time period witnessing significantly increased trading activities.

In order to answer questions as follows, this study adopts the neural network for modeling the irregular trading volume series of the CSI300 nearby futures: are the research able to utilize the lags of the trading volume series to make predictions; if this is the case, how far can the predictions go and how accurate can the predictions be; can this research use predictive information from trading volumes of the CSI300 spot and first distant futures for improving prediction accuracy and what is the corresponding magnitude; how sophisticated is the model; and how robust are its predictions?

The results of this study show that a simple neural network model could be constructed with 10 hidden neurons to robustly predict the trading volume of the CSI300 nearby futures using 1–20 min ahead trading volume data. The model leads to the root mean square error of about 955 contracts. Utilizing additional predictive information from trading volumes of the CSI300 spot and first distant futures could further benefit prediction accuracy and the magnitude of improvements is about 1–2%. This benefit is particularly significant when the trading volume of the CSI300 nearby futures is close to be zero. Another benefit, at the cost of the model becoming slightly more sophisticated with more hidden neurons, is that predictions could be generated through 1–30 min ahead trading volume data.

The results of this study could be used for multiple purposes, including designing financial index trading systems and platforms, monitoring systematic financial risks and building financial index price forecasting.

The purpose of this study is to identify major themes and potential research opportunities in online and offline consumer search.

A systematic review was conducted based on 118 articles identified from prevalent journal databases. Keywords frequency analysis was carried out to identify the major themes. An inductive thematic analysis was carried out to verify the generated themes.

Results show that uncertainty, knowledge, perceived risk, price, experience and involvement are the major themes associated with consumer information search. Uncertainty, one of the major themes of offline search, has not been studied in the online search context. Similarly, the previous experience needs to be explored in the context of the offline search. Finally, potential research opportunities for future research has been summarized based on the retrieved themes.

The systematic review provides an in-depth understanding on the current research on information search literature with future research directions.

This study helps retailers to understand the key elements that motivate consumers to perform external information searches from online and offline sources and to curate targeted information provision strategies to influence purchase decisions.

Consumers with limited internet availability may access channels prior to decision-making. The themes identified in this study can aid policymakers to design affordable access to these channels.

This study adds to the sparse literature on systematic reviews on consumer search for online and offline channels.

Data service (DS) is a special software service that enables data access in cloud environment and provides a unified data model for cross-origination data integration and data sharing. The purpose of the work is to automatically compose DSs and quickly generate data view to satisfy users' various data requirements (DRs).

The paper proposes an automatic DS composition and view generation approach. DSs are organized into DS dependence graph (DSDG) based on their inherent dependences, and DSs can be automatically composed using the DSDG according to user's DRs. Then, data view will be generated by interpreting the composed DS.

Experimental results with real cross-origination data sets show the proposed approaches have high efficiency and good quality for DS composition and view generation.

The authors propose a DS composition algorithm and a data view generation algorithm according to users' DRs.

This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.

Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.

Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.

The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.

Building on the theory of brand psychological ownership, this paper aims to explore the mediating role of brand psychological ownership in the relationship between brand personality (innocence/coolness) and consumers’ preferences, as well as identify the boundary conditions of this relationship.

To test the hypotheses, a series of four experiments were conducted in Wuhan, a city in southern China, using questionnaires administered at two universities and two supermarkets. Hypotheses were tested using PLS-SEM in SmartPLS 4.

The results indicate that brand personality, specifically the dimensions of innocence and coolness, has a significant impact on consumers’ brand preferences. Brands with a cool personality are preferred over those with an innocent personality. Moreover, the relationship between brand personality and consumers’ brand preferences is moderated by power motivation and identity centrality.

This study contributes to the literature by differentiating between brand personality of innocence and coolness as two separate constructs and proposing brand psychological ownership as a mechanism through which brand personality affects brand preferences. The study’s samples were drawn from universities and supermarkets in southern China, providing evidence for the significant moderating effects of power motivation and identity centrality on consumers’ brand preferences.

This paper undertakes a structured literature review to analyse the literature on performance management and measurement (PMM) in universities over the last four decades. Over that time, PMM has emerged as an influential force in universities that impacts their operations and redefines their identity.

A structured literature review approach was used to analyse a sample of articles on PMM research from a broad range of disciplines over four decades. This was undertaken to understand the impacts of PMM practices on universities, highlight changes over time and point to avenues for future research.

The analysis highlights the fact that research on PMM in universities has grown significantly over the 40 years studied. We provide an overview of published articles over four decades regarding content, themes, theories, methods and impacts. We provide an empirical basis for discussing past, present and future university PMM research. The future research avenues offer multiple provocations for scholars and policymakers, for instance, PMM implementation strategies and relationships with various government programs and external evaluation and the role of different actors, particularly academics, in shaping PMM systems.

Unlike a traditional literature review, the structured literature review method can develop insights into how the field has changed over time and highlight possible future research. The sample for this literature review differs from previous reviews in covering a broad range of disciplines, including accounting.

The purpose of this study is to examine the different results and the level of success obtained with advertising campaigns developed on Facebook to promote postgraduate programs to create awareness and engagement.

This study combined the data envelopment analysis technique to measure advertising efficiency with multidimensional scaling (MDS) representation, thus offering alternatives for practitioners and organizations on how to evaluate social advertising performance.

Investments on social paid advertising are an affordable and effective way both to promote postgraduate programs and create engagement with prospective students. Facebook advertisements maximize visibility, which improves social and online positioning and encourages student recruitment.

Higher education institutions can efficiently promote their programs with a minimal social investment contributing to dissemination and engagement. Compared to other forms of traditional or digital advertising, social media ads can be efficient and affordable with wider segmentation and targeting options. Moreover, results are immediate and measurable and campaigns can be instantly modified to better suit the audience’s requirements.

This study is unique as it offers a new, alternative way of measuring efficiency, in addition to the classic ratios of payment models in digital advertising that combine clicks and impressions, on a sector where there are few empirical studies. Moreover, it can be easily applied to many other sectors in public and private organizations.

El objetivo de esta investigación es examinar los diferentes resultados y el nivel de éxito obtenido con las campañas publicitarias desarrolladas en Facebook para promover programas de postgrado que aumenten la notoriedad y la participación de los mismos.

Combinamos la técnica de análisis de envolvente de datos (DEA) para medir la eficiencia de la publicidad con la representación de escalado multidimensional (MDS), ofreciendo alternativas tanto a profesionales como a organizaciones sobre cómo evaluar el rendimiento de la publicidad social.

Las inversiones en publicidad social pagada son una forma asequible y efectiva tanto para promover programas de postgrado como para crear un compromiso con los posibles estudiantes. Los anuncios en Facebook maximizan la visibilidad, lo que también mejora el posicionamiento social y en línea, fomentando la captación de estudiantes.

Las instituciones de educación superior pueden promover eficazmente sus programas con una inversión social mínima que contribuya a la difusión y el engagement. En comparación con otras formas de publicidad tradicional o digital, los anuncios de los medios sociales pueden ser eficientes y asequibles, con una segmentación y opciones de orientación más amplias. Además, los resultados son inmediatos y cuantificables y las campañas pueden modificarse instantáneamente para adaptarse mejor a las necesidades del público objetivo.

Esta investigación es única ya que ofrece una nueva y alternativa forma de medir la eficiencia, además de los ratios clásicos de los modelos de pago en la publicidad digital que combinan clics e impresiones, en un sector en el que hay pocos estudios empíricos. Además, puede aplicarse fácilmente a muchos otros sectores en organizaciones públicas y privadas.

This paper investigates whether democracy plays a mediating role in the relationship between foreign direct investment (FDI) and inequality in Sub-Saharan Africa (SSA).

The empirical analysis is conducted using fixed effects and system GMM (Generalised Method of Moments) on a panel of 38 Sub-Saharan African countries covering the period of 1990–2018.

The results find that FDI has no direct effect on inequality whereas democracy reduces inequality directly in both the short run and the long run. The sensitivity analyses find that democracy improves equality regardless of the magnitude of FDI, resource endowment or democratic deepening whereas FDI only reduces inequality once a moderate level of democracy has been achieved.

The results discussed above thus have four policy implications. First, these results show that although democracy has inequality reducing benefits, SSA is unlikely to significantly reduce inequality unless the region purposefully diversifies its trade and FDI away from natural resources. Second, the region should continue to expand credit access to reduce inequality and attract FDI. Third, policymakers should undertake reforms that will reduce youth inequality. Lastly, the region should focus on long-run democratic reforms rather than on short-run democratization to improve governance and investor confidence.

Although there are existing studies that examine the association between FDI and inequality, FDI and democracy and democracy and inequality, this is the first study to explicitly examine the effect of democracy on the association between FDI and inequality in SSA, and the first study to separately consider the possible varied effects of contemporaneous democratization versus the long-run accumulation of democratic capital. In addition, rather than measure inequality by income alone, this study uses the more appropriate Human Development Index to account for SSA's sociological, education and income disparities.