Secure Pick Up: Implicit Authentication When You Start Using the Smartphone

We propose Secure Pick Up (SPU), a convenient, lightweight, in-device, non-intrusive and automatic-learning system for smartphone user authentication. Operating in the background, our system implicitly observes users' phone pick-up movements, the way they bend their arms when they pick up a smartphone to interact with the device, to authenticate the users. Our SPU outperforms the state-of-the-art implicit authentication mechanisms in three main aspects: 1) SPU automatically learns the user's behavioral pattern without requiring a large amount of training data (especially those of other users) as previous methods did, making it more deployable. Towards this end, we propose a weighted multi-dimensional Dynamic Time Warping (DTW) algorithm to effectively quantify similarities between users' pick-up movements; 2) SPU does not rely on a remote server for providing further computational power, making SPU efficient and usable even without network access; and 3) our system can adaptively update a user's authentication model to accommodate user's behavioral drift over time with negligible overhead. Through extensive experiments on real world datasets, we demonstrate that SPU can achieve authentication accuracy up to 96.3% with a very low latency of 2.4 milliseconds. It reduces the number of times a user has to do explicit authentication by 32.9%, while effectively defending against various attacks.Comment: Published on ACM Symposium on Access Control Models and Technologies (SACMAT) 201

How and Why Are Cancers Acidic? Carbonic Anhydrase IX and the Homeostatic Control of Tumour Extracellular pH.

The acidic tumour microenvironment is now recognized as a tumour phenotype that drives cancer somatic evolution and disease progression, causing cancer cells to become more invasive and to metastasise. This property of solid tumours reflects a complex interplay between cellular carbon metabolism and acid removal that is mediated by cell membrane carbonic anhydrases and various transport proteins, interstitial fluid buffering, and abnormal tumour-associated vessels. In the past two decades, a convergence of advances in the experimental and mathematical modelling of human cancers, as well as non-invasive pH-imaging techniques, has yielded new insights into the physiological mechanisms that govern tumour extracellular pH (pHe). In this review, we examine the mechanisms by which solid tumours maintain a low pHe, with a focus on carbonic anhydrase IX (CAIX), a cancer-associated cell surface enzyme. We also review the accumulating evidence that suggest a role for CAIX as a biological pH-stat by which solid tumours stabilize their pHe. Finally, we highlight the prospects for the clinical translation of CAIX-targeted therapies in oncology

GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning

Automatic transistor sizing is a challenging problem in circuit design due to the large design space, complex performance trade-offs, and fast technological advancements. Although there has been plenty of work on transistor sizing targeting on one circuit, limited research has been done on transferring the knowledge from one circuit to another to reduce the re-design overhead. In this paper, we present GCN-RL Circuit Designer, leveraging reinforcement learning (RL) to transfer the knowledge between different technology nodes and topologies. Moreover, inspired by the simple fact that circuit is a graph, we learn on the circuit topology representation with graph convolutional neural networks (GCN). The GCN-RL agent extracts features of the topology graph whose vertices are transistors, edges are wires. Our learning-based optimization consistently achieves the highest Figures of Merit (FoM) on four different circuits compared with conventional black-box optimization methods (Bayesian Optimization, Evolutionary Algorithms), random search, and human expert designs. Experiments on transfer learning between five technology nodes and two circuit topologies demonstrate that RL with transfer learning can achieve much higher FoMs than methods without knowledge transfer. Our transferable optimization method makes transistor sizing and design porting more effective and efficient.Comment: Accepted to the 57th Design Automation Conference (DAC 2020); 6 pages, 8 figure

HIF-1-Independent Mechanisms Regulating Metabolic Adaptation in Hypoxic Cancer Cells.

In solid tumours, cancer cells exist within hypoxic microenvironments, and their metabolic adaptation to this hypoxia is driven by HIF-1 transcription factor, which is overexpressed in a broad range of human cancers. HIF inhibitors are under pre-clinical investigation and clinical trials, but there is evidence that hypoxic cancer cells can adapt metabolically to HIF-1 inhibition, which would provide a potential route for drug resistance. Here, we review accumulating evidence of such adaptions in carbohydrate and creatine metabolism and other HIF-1-independent mechanisms that might allow cancers to survive hypoxia despite anti-HIF-1 therapy. These include pathways in glucose, glutamine, and lipid metabolism; epigenetic mechanisms; post-translational protein modifications; spatial reorganization of enzymes; signalling pathways such as Myc, PI3K-Akt, 2-hyxdroxyglutarate and AMP-activated protein kinase (AMPK); and activation of the HIF-2 pathway. All of these should be investigated in future work on hypoxia bypass mechanisms in anti-HIF-1 cancer therapy. In principle, agents targeted toward HIF-1β rather than HIF-1α might be advantageous, as both HIF-1 and HIF-2 require HIF-1β for activation. However, HIF-1β is also the aryl hydrocarbon nuclear transporter (ARNT), which has functions in many tissues, so off-target effects should be expected. In general, cancer therapy by HIF inhibition will need careful attention to potential resistance mechanisms

Hybrid High-order Functional Connectivity Networks Using Resting-state Functional MRI for Mild Cognitive Impairment Diagnosis

Conventional functional connectivity (FC), referred to as low-order FC, estimates temporal correlation of the resting-state functional magnetic resonance imaging (rs-fMRI) time series between any pair of brain regions, simply ignoring the potentially high-level relationship among these brain regions. A high-order FC based on "correlation's correlation" has emerged as a new approach for abnormality detection of brain disease. However, separate construction of the low- and high-order FC networks overlooks information exchange between the two FC levels. Such a higher-level relationship could be more important for brain diseases study. In this paper, we propose a novel framework, namely "hybrid high-order FC networks" by exploiting the higher-level dynamic interaction among brain regions for early mild cognitive impairment (eMCI) diagnosis. For each sliding window-based rs-fMRI sub-series, we construct a whole-brain associated high-order network, by estimating the correlations between the topographical information of the high-order FC sub-network from one brain region and that of the low-order FC sub-network from another brain region. With multi-kernel learning, complementary features from multiple time-varying FC networks constructed at different levels are fused for eMCI classification. Compared with other state-of-the-art methods, the proposed framework achieves superior diagnosis accuracy, and hence could be promising for understanding pathological changes of brain connectome

Coherent Time-Varying Graph Drawing with Multifocus+Context Interaction

Abstract—We present a new approach for time-varying graph drawing that achieves both spatiotemporal coherence and multifocus+context visualization in a single framework. Our approach utilizes existing graph layout algorithms to produce the initial graph layout, and formulates the problem of generating coherent time-varying graph visualization with the focus+context capability as a specially-tailored deformation optimization problem. We adopt the concept of the super graph to maintain spatiotemporal coherence and further balance the needs for aesthetic quality and dynamic stability when interacting with time-varying graphs through focus+context visualization. Our method is particularly useful for multifocus+context visualization of time-varying graphs where we can preserve the mental map by preventing nodes in the focus from undergoing abrupt changes in size and location in the time sequence. Experiments demonstrate that our method strikes a good balance between maintaining spatiotemporal coherence and accentuating visual foci, thus providing a more engaging viewing experience for the users. Index Terms—Graph drawing, time-varying graphs, spatiotemporal coherence, focus+context visualization

The Nematic Energy Scale and the Missing Electron Pocket in FeSe

Superconductivity emerges in proximity to a nematic phase in most iron-based superconductors. It is therefore important to understand the impact of nematicity on the electronic structure. Orbital assignment and tracking across the nematic phase transition prove to be challenging due to the multiband nature of iron-based superconductors and twinning effects. Here, we report a detailed study of the electronic structure of fully detwinned FeSe across the nematic phase transition using angle-resolved photoemission spectroscopy. We clearly observe a nematicity-driven band reconstruction involving dxz, dyz, and dxy orbitals. The nematic energy scale between dxz and dyz bands reaches a maximum of 50 meV at the Brillouin zone corner. We are also able to track the dxz electron pocket across the nematic transition and explain its absence in the nematic state. Our comprehensive data of the electronic structure provide an accurate basis for theoretical models of the superconducting pairing in FeSe

D-wave superconductivity in doped Mott insulators

The effect of proximity to a Mott insulating phase on the charge transport properties of a superconductor is determined. An action describing the low energy physics is formulated and different scenarios for the approach to the Mott phase are distinguished by different variation with doping of the parameters in the action. A crucial issue is found to be the doping dependence of the quasiparticle charge which is defined here and which controls the temperature and field dependence of the electromagnetic response functions. Presently available data on high-T$_{c}$ superconductors are analysed. The data, while neither complete nor entirely consistent, suggest that neither the quasiparticle velocity nor the quasiparticle charge vanish as the Mott phase is approached, in contradiction to the predictions of several widely studied theories of lightly doped Mott insulators. Implications of the results for the structure of vortices in high-T$_{c}$ superconductors are determined. The numerical coefficients in the field-dependent specific heat are given for square and triangular vortex lattices.Comment: 12 pages. No figures. Submitted to JPCS (Proceedings of Chicago SNS conference

Evidence suggesting that di-n-butyl phthalate has anti-androgenic effects in fish

This article is the pre-print version of the full and final published article.Phthalate ester plasticizers are anti-androgenic in mammals. High doses of certain phthalates consistently interfere with the normal development of male offspring exposed in utero, causing disrupted sperm production, abnormal development of the genitalia, and in some cases infertility. In the environment, phthalates are considered ubiquitous and are commonly measured in aquatic ecosystems at low ng to mu g per litre concentrations. Given the similarity between mammalian and teleost endocrine systems, phthalate esters may be able to cause anti-androgenic endocrine disruption in fish in the wild. In the present study, adult male three-spined sticklebacks (Gasterosteus aculetaus) (n = 8) were exposed to di-n-butyl phthalate (DBP) (0, 15, and 35 mu g DBP/L) for 22 d and analyzed for changes in nesting behavior, plasma androgen concentrations, spiggin concentrations, and steroidogenic gene expression. Plasma testosterone concentrations were significantly higher in males from the 35 mu g DBP/L group compared with the solvent control, whereas plasma 11-ketotestosterone concentrations were not significantly affected. Expression of steroid acute regulatory protein and 3 beta-hydroxysteroid dehydrogenase remained unchanged. Spiggin concentrations were significantly lower in the males exposed to 35 mu g DBP/L. Nest building appeared to be slower in some males exposed to DBP, but this was not statistically significant. These results suggest that DBP has anti-androgenic effects in fish. However, further research is required to firmly establish the consequences of chronic DBP exposure in fish