Privacy-aware Data Trading

The growing threat of personal data breach in data trading pinpoints an urgent need to develop countermeasures for preserving individual privacy. The state-of-the-art work either endows the data collector with the responsibility of data privacy or reports only a privacy-preserving version of the data. The basic assumption of the former approach that the data collector is trustworthy does not always hold true in reality, whereas the latter approach reduces the value of data. In this paper, we investigate the privacy leakage issue from the root source. Specifically, we take a fresh look to reverse the inferior position of the data provider by making her dominate the game with the collector to solve the dilemma in data trading. To that aim, we propose the noisy-sequentially zero-determinant (NSZD) strategies by tailoring the classical zero-determinant strategies, originally designed for the simultaneous-move game, to adapt to the noisy sequential game. NSZD strategies can empower the data provider to unilaterally set the expected payoff of the data collector or enforce a positive relationship between her and the data collector's expected payoffs. Both strategies can stimulate a rational data collector to behave honestly, boosting a healthy data trading market. Numerical simulations are used to examine the impacts of key parameters and the feasible region where the data provider can be an NSZD player. Finally, we prove that the data collector cannot employ NSZD to further dominate the data market for deteriorating privacy leakage.Comment: 10 pages, 11 figure

Proof of User Similarity: the Spatial Measurer of Blockchain

Although proof of work (PoW) consensus dominates the current blockchain-based systems mostly, it has always been criticized for the uneconomic brute-force calculation. As alternatives, energy-conservation and energy-recycling mechanisms heaved in sight. In this paper, we propose proof of user similarity (PoUS), a distinct energy-recycling consensus mechanism, harnessing the valuable computing power to calculate the similarities of users, and enact the calculation results into the packing rule. However, the expensive calculation required in PoUS challenges miners in participating, and may induce plagiarism and lying risks. To resolve these issues, PoUS embraces the best-effort schema by allowing miners to compute partially. Besides, a voting mechanism based on the two-parties computation and Bayesian truth serum is proposed to guarantee privacy-preserved voting and truthful reports. Noticeably, PoUS distinguishes itself in recycling the computing power back to blockchain since it turns the resource wastage to facilitate refined cohort analysis of users, serving as the spatial measurer and enabling a searchable blockchain. We build a prototype of PoUS and compare its performance with PoW. The results show that PoUS outperforms PoW in achieving an average TPS improvement of 24.01% and an average confirmation latency reduction of 43.64%. Besides, PoUS functions well in mirroring the spatial information of users, with negligible computation time and communication cost.Comment: 12 pages,10 figure

SECF: Improving SPARQL Querying Performance with Proactive Fetching and Caching

Querying on SPARQL endpoints may be unsatisfactory due to high latency of connections to the endpoints. Caching is an important way to accelerate the query response speed. In this paper, we propose SPARQL Endpoint Caching Framework (SECF), a client-side caching framework for this purpose. In particular, we prefetch and cache the results of similar queries to recently cached query aiming to improve the overall querying performance. The similarity between queries are calculated via an improved Graph Edit Distance (GED) function. We also adapt a smoothing method to implement the cache replacement. The empirical evaluations on real world queries show that our approach has great potential to enhance the cache hit rate and accelerate the querying speed on SPARQL endpoints

Panoptic Scene Graph Generation with Semantics-prototype Learning

Panoptic Scene Graph Generation (PSG) parses objects and predicts their relationships (predicate) to connect human language and visual scenes. However, different language preferences of annotators and semantic overlaps between predicates lead to biased predicate annotations in the dataset, i.e. different predicates for same object pairs. Biased predicate annotations make PSG models struggle in constructing a clear decision plane among predicates, which greatly hinders the real application of PSG models. To address the intrinsic bias above, we propose a novel framework named ADTrans to adaptively transfer biased predicate annotations to informative and unified ones. To promise consistency and accuracy during the transfer process, we propose to measure the invariance of representations in each predicate class, and learn unbiased prototypes of predicates with different intensities. Meanwhile, we continuously measure the distribution changes between each presentation and its prototype, and constantly screen potential biased data. Finally, with the unbiased predicate-prototype representation embedding space, biased annotations are easily identified. Experiments show that ADTrans significantly improves the performance of benchmark models, achieving a new state-of-the-art performance, and shows great generalization and effectiveness on multiple datasets

Weak Magnetic Field Accelerates Chromate Removal by Zero-Valent Iron

Weak magnetic field (WMF) was employed to improve the removal of Cr(VI) by zero-valent iron (ZVI) for the first time. The removal rate of Cr(VI) was elevated by a factor of 1.12-5.89 due to the application of a WMF, and the WMF-induced improvement was more remarkable at higher Cr(VI) concentration and higher pH. Fe2+ was not detected until Cr(VI) was exhausted, and there was a positive correlation between the WMF-induced promotion factor of Cr(VI) removal rate and that of Fe2+ release rate in the absence of Cr(VI) at pH 4.0-5.5. These phenomena imply that ZVI corrosion with Fe2+ release was the limiting step in the process of Cr(VI) removal. The superimposed WMF had negligible influence on the apparent activation energy of Cr(VI) removal by ZVI, indicating that WMF accelerated Cr(VI) removal by ZVI but did not change the mechanism. The passive layer formed with WMF was much more porous than without WMF, thereby facilitating mass transport. Therefore, WMF could accelerate ZVI corrosion and alleviate the detrimental effects of the passive layer, resulting in more rapid removal of Cr(VI) by ZVI. Exploiting the magnetic memory of ZVI, a two-stage process consisting of a small reactor with WMF for ZVI magnetization and a large reactor for removing contaminants by magnetized ZVI can be employed as a new method of ZVI-mediated remediation

Physical Activity, Screen Time, and Emotional Well-Being during the 2019 Novel Coronavirus Outbreak in China

We aimed to evaluate the effects of the COVID-19 lock down on lifestyle in China during the initial stage of the pandemic. A questionnaire was distributed to Chinese adults living in 31 provinces of China via the internet using a snowball sampling strategy. Information on 7-day physical activity recall, screen time, and emotional state were collected between January 24 and February 2, 2020. ANOVA, χ² test, and Spearman's correlation coefficients were used for statistical analysis. 12,107 participants aged 18-80 years were included. During the initial phase of the COVID-19 outbreak, nearly 60% of Chinese adults had inadequate physical activity (95% CI 56.6%-58.3%), which was more than twice the global prevalence (27.5%, 25.0%-32.2%). Their mean screen time was more than 4 hours per day while staying at home (261.3 ± 189.8 min per day), and the longest screen time was found in young adults (305.6 ± 217.5 min per day). We found a positive and significant correlation between provincial proportions of confirmed COVID-19 cases and negative affect scores (r = 0.501, p = 0.004). Individuals with vigorous physical activity appeared to have a better emotional state and less screen time than those with light physical activity. During this nationwide lockdown, more than half of Chinese adults temporarily adopted a sedentary lifestyle with insufficient physical activity, more screen time, and poor emotional state, which may carry considerable health risks. Promotion of home-based self-exercise can potentially help improve health and wellness.This study was funded by the National Key Technology R&D Program of China (2019YFF0301600),and the National Natural Science Foundation of China (11775059 and 31900845)

NUMB regulates the endocytosis and activity of the anaplastic lymphoma kinase in an isoform-specific manner

NUMB is an evolutionarily conserved protein that plays an important role in cell adhesion, migration, polarity, and cell fate determination. It has also been shown to play a role in the pathogenesis of certain cancers, although it remains controversial whether NUMB functions as an oncoprotein or tumor suppressor. Here, we show that NUMB binds to anaplastic lymphoma kinase (ALK), a receptor tyrosine kinase aberrantly activated in several forms of cancer, and this interaction regulates the endocytosis and activity of ALK. Intriguingly, the function of the NUMB-ALK interaction is isoform-dependent. While both p66-NUMB and p72-NUMB isoforms are capable of mediating the endocytosis of ALK, the former directs ALK to the lysosomal degradation pathway, thus decreasing the overall ALK level and the downstream MAP kinase signal. In contrast, the p72-NUMB isoform promotes ALK recycling back to the plasma membrane, thereby maintaining the kinase in its active state. Our work sheds light on the controversial role of different isoforms of NUMB in tumorigenesis and provides mechanistic insight into ALK regulation