Quantum difference equation for the affine type AA quiver varieties I: General Construction

In this article we use the philosophy in [OS22] to construct the quantum difference equation of affine type $A$ quiver varieties in terms of the quantum toroidal algebra $U_{q,t}(\hat{\hat{\mathfrak{sl}}}_{r})$. In the construction, and we define the set of wall for each quiver varieties by the action of the universal $R$-matrix, which is shown to be almost equivalent to that of the $K$-theoretic stable envelope on each interval in $H^2(X,\mathbb{Q})$. We also give the examples of the instanton moduli space $M(n,r)$ and the Hilbert scheme $\text{Hilb}_{n}(\widehat{\mathbb{C}^2/\mathbb{Z}_{r}})$ to show the explicit form of the quantum difference operator.Comment: 59 page

Differential privacy and its application

 While the thesis reports our research in extending the theory of differential privacy to real world application, many interesting and promising issues remain unexplored. This thesis can be a starting point for new challenges because they precisely demonstrate how differential privacy can be extended in real-world scenarios

Regulation of embryo development in Norway spruce by WOX transcription factors

In seed plants, the apical-basal axis of the plant body is established during early embryogenesis. Major regulatory genes of the apical-basal axis formation belong to the WUSCHEL-RELATED HOMEOBOX (WOX) gene family of transcription factors. The spatiotemporal expression pattern and the molecular role of the WOX genes has mainly been studied in the angiosperm model plant Arabidopsis (Arabidopsis thaliana). Similar information in conifers is limited. The aim of my thesis has been to characterize WOX genes in Norway spruce (Picea abies) and to elucidate the function of WOX genes expressed during embryo development. We cloned 11 WOX homologs from Norway spruce and examined their phylogenetic relationship to WOX genes from other species. The phylogenetic analyses showed that the major diversification within the WOX gene family took place before the gymnosperm-angiosperm split. PaWOX8/9, PaWOX2 and PaWOX3, which are expressed in embryos, were selected for further studies. PaWOX8/9 and PaWOX2 are highly expressed in early and late embryos, and PaWOX3 is highly expressed in mature embryos. Functional studies were performed in RNAi lines where the genes were down-regulated. Embryos in PaWOX8/9 RNAi lines showed a disturbed apical-basal patterning caused by abnormal orientation of the cell division plane at the basal part of the embryonal mass. In PaWOX2 RNAi lines, vacuolated cells differentiated on the surface of the embryonal mass and the embryos failed to form a proper protoderm. Down-regulation of PaWOX3 disturbed lateral margin outgrowth in cotyledons and needles. Taken together, our results indicate that WOX8/9, WOX2 and WOX3 exert evolutionarily conserved functions during embryo development. We can therefore conclude that the regulatory networks of embryo development are at least partly conserved between angiosperms and gymnosperms

SaaS: A situational awareness and analysis system for massive android malware detection

A large amount of mobile applications (Apps) are uploaded, distributed and updated in various Android markets, e.g., Google Play and Huawei AppGallery every day. One of the ongoing challenges is to detect malicious Apps (also known as malware) among those massive newcomers accurately and efficiently in the daily security management of Android App markets. Customers rely on those detection results in the selection of Apps upon downloading, and undetected malware may result in great damages. In this paper, we propose a cloud-based malware detection system called SaaS by leveraging and marrying multiple approaches from diverse domains such as natural language processing (n-gram), image processing (GLCM), cryptography (fuzzy hash), machine learning (random forest) and complex networks. We firstly extract n-gram features and GLCM features from an App's smali code and DEX file, respectively. We next feed those features into training data set, to create a machine learning detect model. The model is further enhanced by fuzzy hash to detect whether inspected App is repackaged or not. Extensive experiments (involving 1495 samples) demonstrates that the detecting accuracy is more than 98.5%, and support a large-scale detecting and monitoring. Besides, our proposed system can be deployed as a service in clouds and customers can access cloud services on demand

Privacy Intelligence: A Survey on Image Sharing on Online Social Networks

Image sharing on online social networks (OSNs) has become an indispensable part of daily social activities, but it has also led to an increased risk of privacy invasion. The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharing images on OSNs. However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection. As a result, an more intelligent environment for privacy-friendly OSN image sharing is in demand. To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing. Specifically, we present a high-level analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field. The framework is divided into three main stages: local management, online management and social experience. At each stage, we identify typical sharing-related user behaviors, the privacy issues generated by those behaviors, and review representative intelligent solutions. The resulting analysis describes an intelligent privacy-enhancing chain for closed-loop privacy management. We also discuss the challenges and future directions existing at each stage, as well as in publicly available datasets.Comment: 32 pages, 9 figures. Under revie

Towards Robust GAN-generated Image Detection: a Multi-view Completion Representation

GAN-generated image detection now becomes the first line of defense against the malicious uses of machine-synthesized image manipulations such as deepfakes. Although some existing detectors work well in detecting clean, known GAN samples, their success is largely attributable to overfitting unstable features such as frequency artifacts, which will cause failures when facing unknown GANs or perturbation attacks. To overcome the issue, we propose a robust detection framework based on a novel multi-view image completion representation. The framework first learns various view-to-image tasks to model the diverse distributions of genuine images. Frequency-irrelevant features can be represented from the distributional discrepancies characterized by the completion models, which are stable, generalized, and robust for detecting unknown fake patterns. Then, a multi-view classification is devised with elaborated intra- and inter-view learning strategies to enhance view-specific feature representation and cross-view feature aggregation, respectively. We evaluated the generalization ability of our framework across six popular GANs at different resolutions and its robustness against a broad range of perturbation attacks. The results confirm our method's improved effectiveness, generalization, and robustness over various baselines.Comment: Accepted to IJCAI 202

Docetaxel-loaded M1 macrophage-derived exosomes for a safe and efficient chemoimmunotherapy of breast cancer

The conversion of tumor-promoting M2 macrophage phenotype to tumor-suppressing M1 macrophages is a promising therapeutic approach for cancer treatment. However, the tumor normally provides an abundance of M2 macrophage stimuli, which creates an M2 macrophage-dominant immunosuppressive microenvironment. In our study, docetaxel (DTX) as chemotherapeutic modularity was loaded into M1 macrophage-derived exosomes (M1-Exo) with M1 proinflammatory nature to establish DTX-M1-Exo drug delivery system. We found that DTX-M1-Exo induced naïve M0 macrophages to polarize to M1 phenotype, while failed to repolarize to M2 macrophages upon Interleukin 4 restimulation due to impaired mitochondrial function. This suggests that DTX-M1-Exo can achieve long-term robust M1 activation in immunosuppressive tumor microenvironment. The in vivo results further confirmed that DTX-M1-Exo has a beneficial effect on macrophage infiltration and activation in the tumor tissues. Thus, DTX-M1-Exo is a novel macrophage polarization strategy via combined chemotherapy and immunotherapy to achieve great antitumor therapeutic efficacy