Self-cleaning, superhydrophobic cotton fabrics with excellent washing durability, solvent resistance and chemical stability prepared from an SU-8 derived surface coating

Superhydrophobic cotton fabrics with a very low contact angle hysteresis were prepared using a single-pot coating solution comprising SU-8 (a negative photoresist), a fluorinated alkyl silane and silica nanoparticles. The fabric was treated using a dip-coating technique and subsequently cured under UV light. The coated fabric showed excellent superhydrophobicity with a water contact angle as high as 163° and a sliding angle as low as 2°. The coating was durable enough to withstand 100 laundry cycles. It also had excellent stability against long immersion times in organic solvents, and acid and base solutions.

The Christmas effect-special dividend announcements

This paper examines the Halloween effect in special dividend announcements. We find that firms are more likely to announce special dividends at the end of a year, especially in the months of November and December. There is a Halloween effect in the announcements, but more importantly, there is a Christmas effect in the propensity and abnormal returns of special dividends. This paper provides initial evidence on the Christmas effect of special dividend payments. It links monthly effects in stock returns and corporate events to explain the likelihood of the occurrence of special dividend announcements. The results of this paper shed light on why corporate events are more likely to occur in some periods, but less likely to occur in others.

A sword with two edges: propagation studies on both positive and negative information in online social networks

Online social networks (OSN) have become one of the major platforms for people to exchange information. Both positive information (e.g., ideas, news and opinions) and negative information (e.g., rumors and gossips) spreading in social media can greatly influence our lives. Previously, researchers have proposed models to understand their propagation dynamics. However, those were merely simulations in nature and only focused on the spread of one type of information. Due to the human-related factors involved, simultaneous spread of negative and positive information cannot be thought of the superposition of two independent propagations. In order to fix these deficiencies, we propose an analytical model which is built stochastically from a node level up. It can present the temporal dynamics of spread such as the time people check newly arrived messages or forward them. Moreover, it is capable of capturing people's behavioral differences in preferring what to believe or disbelieve. We studied the social parameters impact on propagation using this model. We found that some factors such as people's preference and the injection time of the opposing information are critical to the propagation but some others such as the hearsay forwarding intention have little impact on it. The extensive simulations conducted on the real topologies confirm the high accuracy of our model.

Environmental migration and capital mobility

Based on utility equalization, this paper considers a developing economy with labor migration. Pollution and capital taxes are imposed on producers in the polluted sector. The optimal policy combinations of capital taxes and pollution taxes for the host economy are examined. A zero capital tax is required for increasing mobility of capital to raise real GDP, while a larger than Pigovian pollution tax is needed for enhancing environmental amenities. The impacts on those two optimal tax rates are examined theoretically and numerically if foreign countries adopt higher environmental standards or if foreign countries impose tax credits on foreign investments.

Another explanation of the mutual fund fee puzzle

This paper demonstrates that investor sentiment explains the recent puzzle of the negative relation between fees and before-fee performance of equity mutual funds. Using a composite proxy for investor sentiment, the puzzle can be explained stronger by investor sentiment, compared to the strategic fee-setting explanation discussed in the literature. More-sentiment driven investors would like to select more skilled fund managers, leading to a better future performance in short run. Additionally, when sentiment is high (low), it results in lower (higher) fees. Our results highlight the use of investor sentiment approach in determining mutual fund fees and performance.

Cross-border travellers and parallel trade: implications for Asian economies

This paper explores the impact of parallel trade in an export market by cross-border travellers on welfare of the home country in a model with heterogeneous consumers' perceptions. We show that such parallel trade when it is organised trading always hurts the home-country welfare. However, when parallel trade is unorganised trading, it might benefit the home-country welfare provided that the size of the export market is relatively small. Along these lines, we suggest optimal policy responses in the home country to parallel trade by cross-border travellers. The results of the paper yield insightful policy implications for Asian economies.

Enhanced mechanical response of an ultrafine grained Ti-6Al-4V alloy produced through warm symmetric and asymmetric rolling

An equiaxed ultrafine-grained (UFG) microstructure was successfully produced in a Ti-6Al-4V alloy with an average grain size of 110-230. nm through symmetric and asymmetric warm rolling of a martensitic starting microstructure. The UFG material displayed a combination of ultrahigh strength and ductility at room temperature. Compared with the conventional symmetric rolling, the asymmetric rolling process led to a more pronounced effect of microstructure refinement and a higher tensile ductility. The optimum mechanical response was obtained though the asymmetric rolling at 70% reduction, offering an ultimate tensile strength of 1365. MPa and a total elongation of ~23%. Apart from the magnitude of grain refinement, the inclination of basal texture component from the normal towards the rolling direction during asymmetric rolling and possible strain induced β to martensite transformation may concurrently contribute to a remarkable tensile strength-ductility balance.

State-owned enterprises, competition and product quality

We consider a general oligopoly model with consumer surplus moderated quantity competition among state-owned enterprises (SOEs), where the SOEs employ workers who are members of the state-owned worker union and produce differentiated products. We show that increasing the number of SOEs would lead to an outcome in which these enterprises choose a lower level of product quality and this, in turn, results in welfare losses for the society, depending on the degree of substitutability. Our findings are consistent with the evidence from China and uncovers important linkages that exist between worker union, product quality and competition, and that have mostly been ignored in the industrial organisation, trade and development literature.

Intelligent line segment perception with cortex-like mechanisms

This paper proposes a novel general framework for line segment perception, which is motivated by a biological visual cortex, and requires no parameter tuning. In this framework, we design a model to approximate receptive fields of simple cells. More importantly, the structure of biological orientation columns is imitated by organizing artificial complex and hypercomplex cells with the same orientation into independent arrays. Besides, an interaction mechanism is implemented by a set of self-organization rules. Enlightened by the visual topological theory, the outputs of these artificial cells are integrated to generate line segments that can describe nonlocal structural information of images. Each line segment is evaluated quantitatively by its significance. The computation complexity is also analyzed. The proposed method is tested and compared to state-of-the-art algorithms on real images with complex scenes and strong noises. The experiments demonstrate that our method outperforms the existing methods in the balance between conciseness and completeness.

Actual intervention and verbal intervention in the Chinese RMB exchange rate

Central bank communication has become a more and more important instrument for the monetary authorization to intervene its exchange rate. This paper investigates the impact of both verbal and actual intervention on the exchange rate of China's currency, which has become the second-used currency in international trade settlement. The empirical evidence indicates that the central bank communication can influence the exchange rate, but the efficient is quite weak. Moreover, the effect of verbal intervention on the exchange rate of the RMB is weaker than that of actual intervention. One possible explanation is that most of the statements made by the governor of central bank on the RMB exchange rate are neutral in China. Overall, this study identifies the difference between the actual and verbal intervention in exchange rate in China, the largest emerging economy in the world.

ANGEL: agent-based scheduling for real-time tasks in virtualized clouds

The success of cloud computing makes an increasing number of real-time applications such as signal processing and weather forecasting run in the cloud. Meanwhile, scheduling for real-time tasks is playing an essential role for a cloud provider to maintain its quality of service and enhance the system's performance. In this paper, we devise a novel agent-based scheduling mechanism in cloud computing environment to allocate real-time tasks and dynamically provision resources. In contrast to traditional contract net protocols, we employ a bidirectional announcement-bidding mechanism and the collaborative process consists of three phases, i.e., basic matching phase, forward announcement-bidding phase and backward announcement-bidding phase. Moreover, the elasticity is sufficiently considered while scheduling by dynamically adding virtual machines to improve schedulability. Furthermore, we design calculation rules of the bidding values in both forward and backward announcement-bidding phases and two heuristics for selecting contractors. On the basis of the bidirectional announcement-bidding mechanism, we propose an agent-based dynamic scheduling algorithm named ANGEL for real-time, independent and aperiodic tasks in clouds. Extensive experiments are conducted on CloudSim platform by injecting random synthetic workloads and the workloads from the last version of the Google cloud tracelogs to evaluate the performance of our ANGEL. The experimental results indicate that ANGEL can efficiently solve the real-time task scheduling problem in virtualized clouds.

6 million spam tweets: a large ground truth for timely Twitter spam detection

Twitter has changed the way of communication and getting news for people's daily life in recent years. Meanwhile, due to the popularity of Twitter, it also becomes a main target for spamming activities. In order to stop spammers, Twitter is using Google SafeBrowsing to detect and block spam links. Despite that blacklists can block malicious URLs embedded in tweets, their lagging time hinders the ability to protect users in real-time. Thus, researchers begin to apply different machine learning algorithms to detect Twitter spam. However, there is no comprehensive evaluation on each algorithms' performance for real-time Twitter spam detection due to the lack of large groundtruth. To carry out a thorough evaluation, we collected a large dataset of over 600 million public tweets. We further labelled around 6.5 million spam tweets and extracted 12 light-weight features, which can be used for online detection. In addition, we have conducted a number of experiments on six machine learning algorithms under various conditions to better understand their effectiveness and weakness for timely Twitter spam detection. We will make our labelled dataset for researchers who are interested in validating or extending our work.

Another January effect—evidence from stock split announcements

This paper examines whether there is a January effect in the propensity and abnormal returns of stock split announcements. It provides primary evidence in the investigation of using monthly effects to explain the patterns of stock splits. The results show that the January effect exists in the likelihood of the occurrence of share splits and in the associated short-term abnormal returns. We also find that another monthly effect—the Halloween effect—exists in stock split announcements. However, the January effect has a much larger and considerably more significant impact on the probability and returns of these announcements. The results of this paper shed light on why we observe patterns in the announcement of corporate events.

Asymmetric self-learning for tackling Twitter spam drift

Spam has become a critical problem on Twitter. In order to stop spammers, security companies apply blacklisting services to filter spam links. However, over 90% victims will visit a new malicious link before it is blocked by blacklists. To eliminate the limitation of blacklists, researchers have proposed a number of statistical features based mechanisms, and applied machine learning techniques to detect Twitter spam. In our labelled large dataset, we observe that the statistical properties of spam tweets vary over time, and thus the performance of existing ML based classifiers are poor. This phenomenon is referred as 'Twitter Spam Drift'. In order to tackle this problem, we carry out deep analysis of 1 million spam tweets and 1 million non-spam tweets, and propose an asymmetric self-learning (ASL) approach. The proposed ASL can discover new information of changed tweeter spam and incorporate it into classifier training process. A number of experiments are performed to evaluate the ASL approach. The results show that the ASL approach can be used to significantly improve the spam detection accuracy of using traditional ML algorithms.