Influencing Factors Of Online Advertising Towards Consumer Purchase Intention

The present study attempts to explore the relationship between the personal beliefs, namely product information, social image, enjoyment and falsity (no sense) ·and purchase intention, whilest attitude towards online advertising is included as a mediator. Percubaan kajian digunakan untuk meneroka hubungan antara kepercayaan peribadi, maklumat produk, imej sosial, keseronokan, kepalsuan (tanpa perasaan) dan niat pembelian

Elaboration and characterization of nanoplate structured alpha-Fe2O3 films by Ag3PO4

A new strategy for surface treatment of hematite nanoplates for efficient photoelectrochemical (PEC) performances is proposed. Silver orthophosphate (Ag₃PO₄) has been adopted to mediate the formation of α-Fe₂O₃ films. Phosphate ions in Ag₃PO₄ is found to cause a significant morphology change during annealing process, from β-FeOOH nanorod arrays to hematite nanoplates. Meanwhile, Ag ions is doped into α-Fe₂O₃ film. The obtained nanoplate structured Fe₂O₃ –Ag–P films demonstrate much higher photoelectrochemical performance as photoanodes than the bare Fe₂O₃ nanorod thin films. The effects of phosphate and silver ions on the morphology, surface characteristics and the PEC properties of the photoanodes are investigated

Management's perceptions of factors that influence firm performance : Chinese international subsidiaries in South Africa

Thesis (M.M. (Entrepreneurship and New Venture Creation))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Graduate School of Business Administration, 2014.Firm performance and its determinants in emerging markets have generated much attention in recent years. This study examined the perceived performance of Chinese international subsidiaries in South Africa and the influence of four factors, namely, host country institutions, financial capital, human resource management, and entrepreneurial orientation. Questionnaires were distributed to 46 Chinese subsidiaries operating in South Africa. The analysis of the results used the Spearman's rho to test the relationship of the four factors with the performance of the Chinese subsidiaries. The findings showed a positive relationship between entrepreneurial orientation and perceived performance of Chinese international subsidiaries. A negative relationship was revealed between sufficient initial capital investment and the perceived performance of Chinese international subsidiaries. The remaining two factors did not show any significant influence on the perceived performance of Chinese international subsidiaries. This study provided empirical evidence to support the existing performance theories in the context of emerging economies. This research examines the performance of Chinese foreign direct investment in South Africa. Both countries involved are developing countries, which in itself was an unusual research setting. Furthermore, this paper could provide guidance for those Chinese international companies that are already operating, or are about to set up business, in South Africa. The findings of this research indicated that Chinese international subsidiaries could adopt EO as a firm strategy to improve performance. The South African government could help firms to achieve better performance by creating a social climate to encourage innovation, protect innovative products and develop its institutions to give every firm fair access to information that is key when predicting market trends

Sulfuric Acid and Ammonia Generation by Bipolar Membranes Electrodialysis: Transport Rate Model for Ion and Water through Anion Exchange Membrane

Regeneration of sulfuric acid and ammonia from ammonium sulfate by bipolar membrane electrodialysis (BMED) coupling with stripping ammonia by air-blowing was studied. The result showed that it was feasible to regenerate sulfuric acid and ammonia from ammonium sulfate solution using this method. Empirical models to describe the ion and water transport behaviors through anion exchange membrane for BMED system were successfully developed. The models were valid to evaluate water transport rate and ion transport behavior for anion exchange membrane under similar operation conditions. Comparison of calculated values with experimental data indicated that the models were reliable to describe the water and ion transport behavior through anion exchange membrane for BMED system and also be used to predict the water transport and ion transport behaviors for other current density under similar operation condition

Unbiased Pairwise Learning from Implicit Feedback for Recommender Systems without Biased Variance Control

Generally speaking, the model training for recommender systems can be based on two types of data, namely explicit feedback and implicit feedback. Moreover, because of its general availability, we see wide adoption of implicit feedback data, such as click signal. There are mainly two challenges for the application of implicit feedback. First, implicit data just includes positive feedback. Therefore, we are not sure whether the non-interacted items are really negative or positive but not displayed to the corresponding user. Moreover, the relevance of rare items is usually underestimated since much fewer positive feedback of rare items is collected compared with popular ones. To tackle such difficulties, both pointwise and pairwise solutions are proposed before for unbiased relevance learning. As pairwise learning suits well for the ranking tasks, the previously proposed unbiased pairwise learning algorithm already achieves state-of-the-art performance. Nonetheless, the existing unbiased pairwise learning method suffers from high variance. To get satisfactory performance, non-negative estimator is utilized for practical variance control but introduces additional bias. In this work, we propose an unbiased pairwise learning method, named UPL, with much lower variance to learn a truly unbiased recommender model. Extensive offline experiments on real world datasets and online A/B testing demonstrate the superior performance of our proposed method.Comment: 5 page

Wuxi – a Chinese City on its Way to a Low Carbon Future

Urbanization and climate change are amongst the greatest challenges of the 21st century. In the “Low Carbon Future Cities” project (LCFC), three important problem dimensions are analysed: current and future GHG emissions and their mitigation (up to 2050), resource use and material flows and vulnerability to climate change. The industrial city of Wuxi has been the Chinese pilot city of the project. To establish the pathway for a low carbon future, it is crucial to understand the current situation and possible future developments. The paper presents the key results of the status quo analysis and the future scenario analysis carried out for Wuxi. Two scenarios are outlined. The Current Policy Scenario (CPS) shows the current most likely development in the area of energy demand and GHG emissions until 2050. Whereas the extra low carbon scenario (ELCS) assumes a significantly more ambitious implementation, it combines a market introduction of best available technologies with substantial behavioural change. All scenarios are composed of sub-scenarios for the selected key sectors. Looking at the per capita emissions in Wuxi, the current levels are already high at around 12 tonnes CO2 per capita compared to Western European cities. Although Wuxi has developed a low carbon plan, the projected results under current policies (CPS) show that the total emissions would increase to 23.6 tonnes CO2 per capita by 2050. If the ELCS pathway was to be adopted, these CO2 emission levels could be reduced to 6.4 tonnes per capita by 2050. However, this is not a problem unique to Wuxi or China. A comprehensive rethink at global level on how to increase energy and resource efficiency and sustainability is required

Assessment of Night-Time Lighting for Global Terrestrial Protected and Wilderness Areas

Protected areas (PAs) play an important role in biodiversity conservation and ecosystem integrity. However, human development has threatened and affected the function and effectiveness of PAs. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) night-time stable light (NTL) data have proven to be an effective indicator of the intensity and change of human-induced urban development over a long time span and at a larger spatial scale. We used the NTL data from 1992 to 2013 to characterize the human-induced urban development and studied the spatial and temporal variation of the NTL of global terrestrial PAs. We selected seven types of PAs defined by the International Union for Conversation of Nature (IUCN), including strict nature reserve (Ia), wilderness area (Ib), national park (II), natural monument or feature (III), habitat/species management area (IV), protected landscape/seascape (V), and protected area with sustainable use of natural resources (VI). We evaluated the NTL digital number (DN) in PAs and their surrounding buffer zones, i.e., 0–1 km, 1–5 km, 5–10 km, 10–25 km, 25–50 km, and 50–100 km. The results revealed the level, growth rate, trend, and distribution pattern of NTL in PAs. Within PAs, areas of types V and Ib had the highest and lowest NTL levels, respectively. In the surrounding 1–100 km buffer zones, type V PAs also had the highest NTL level, but type VI PAs had the lowest NTL level. The NTL level in the areas surrounding PAs was higher than that within PAs. Types Ia and III PAs showed the highest and lowest NTL growth rate from 1992 to 2013, respectively, both inside and outside of PAs. The NTL distributions surrounding the Ib and VI PAs were different from other types. The areas close to Ib and VI boundaries, i.e., in the 0–25 km buffer zones, showed lower NTL levels, for which the highest NTL level was observed within the 25–100 km buffer zone. However, other types of PAs showed the opposite NTL patterns. The NTL level was lower in the distant buffer zones, and the lowest night light was within the 1–25 km buffer zones. Globally, 6.9% of PAs are being affected by NTL. Conditions of wilderness areas, e.g., high latitude regions, Tibetan Plateau, Amazon, and Caribbean, are the least affected by NTL. The PAs in Europe, Asia, and North America are more affected by NTL than South America, Africa, and Oceania

Effective detection of seismic events by non-classical receptive field visual cognitive modelling.

The detection and up-picking of the seismic events are critical for seismic data analysis and interpretation. Events picking can be used for sequence stratigraphic analysis, reservoir feature extraction, the determining of the subsequent reflection interface, the improving of the SNR and the storage prediction. The research of the events picking is very significant for the seismic exploration. In order to overcome the existing events picking methods have the same sensitivity to noise, we propose a non-classical receptive field visual cognitive method for the events picking UP. Vision is an important functional organ for human beings to observe and recognize the world. About 80% of the information obtained by human beings from the outside world comes from the visual system, which fully shows that visual information is huge_ and also shows that human beings have a high utilization rate of visual information. How to transfer some typical information processing mechanism and target recognition function of human vision to machine is one of the most important and urgent tasks in the field of computer vision and artificial intelligence. The introduction of computer vision technology into geophysical prospecting is still in its infancy in the field of seismic exploration, our research fill the blank of this field, where the use of visual features to improve the seismic data processing and rapid realization of oil and gas exploration, will become the vane of the future direction of research and development. As a basic research work in the crossing field, this paper has made a breakthrough in the research methods and ideas, and the research content can be summarized as the following four aspects: 1. The proposed method implements the function of environmental suppression and spatial enhancement of the bio-visual primary visual cortex, which is applies to the ore-stack seismic data, as ore-stack seismic data contains abundant information such as amplitude and frequency to reflect tiny structures of the formation. 2. The seismic data is preprocessed to obtain the wavelet fusion of the envelope peak instantaneous frequency (EPIF) and the slant stack peak amplitude (SSPA), which can maximum the limit to provide optimal quality data. 3. An adaptive Gabor filter direction selection method is proposed to provide a reliable angle range and improve the recognition rate of filter decomposition. In addition. by adopting an anisotropic environmental suppression method, our method can detect edge variability more accurately than the isotropic method. 4. With the enhanced contour aggregation, cocircular constraint is adopted and combined with the characteristics of low curvature and continuous changing curvature, which is unique to the seismic events, to establish a consistent spatial structure perception model. The events picked by our method is more continuous and accurate than the existing methods, and doesn't require human interaction, which is beneficial for subsequent seismic interpretation and reservoir prediction

CVT: A Crowdsourcing Video Transcoding Scheme Based on Blockchain Smart Contracts

Streaming media has been largely used by millions of users every day. The number of customers and programs, e.g., TV series, movies, and various shows, are still growing fast. However, the demand for video transcoding for various personal terminal devices results in the shortage of computing resources and the prolongation of processing delay in centralized video transcoding systems. To solve this issue, we propose a blockchain, especially, smart contract based scheme that can achieve decentralized and on-demand crowdsourcing for video transcoding, which remarkably mitigates the transcoding overhead. Specifically, our scheme consists of four key components such as employers, workers, task allocation, and payment. An employer initializes the smart contract, releases the task, and initiates the smart contract. Workers bid for the task, and the successful bidder will obtain the task and execute the task. The task allocation mechanism and the payment mechanism can guarantee the profits of both and encourage both as well. Moreover, the smart contract consists of the bidding contract and the task execution contract. The extensive analysis of our proposed scheme justified the feasibility, security for defending against typical threats, applicability in realistic situations, and portability for most multimedia such as videos and audios

GFI1 downregulation promotes inflammation-linked metastasis of colorectal cancer.

Inflammation is frequently associated with initiation, progression, and metastasis of colorectal cancer (CRC). Here, we unveil a CRC-specific metastatic programme that is triggered via the transcriptional repressor, GFI1. Using data from a large cohort of clinical samples including inflammatory bowel disease and CRC, and a cellular model of CRC progression mediated by cross-talk between the cancer cell and the inflammatory microenvironment, we identified GFI1 as a gating regulator responsible for a constitutively activated signalling circuit that renders CRC cells competent for metastatic spread. Further analysis of mouse models with metastatic CRC and human clinical specimens reinforced the influence of GFI1 downregulation in promoting CRC metastatic spread. The novel role of GFI1 is uncovered for the first time in a human solid tumour such as CRC. Our results imply that GFI1 is a potential therapeutic target for interfering with inflammation-induced CRC progression and spread