Assentication: User Deauthentication and Lunchtime Attack Mitigation with Seated Posture Biometric

Biometric techniques are often used as an extra security factor in authenticating human users. Numerous biometrics have been proposed and evaluated, each with its own set of benefits and pitfalls. Static biometrics (such as fingerprints) are geared for discrete operation, to identify users, which typically involves some user burden. Meanwhile, behavioral biometrics (such as keystroke dynamics) are well suited for continuous, and sometimes more unobtrusive, operation. One important application domain for biometrics is deauthentication, a means of quickly detecting absence of a previously authenticated user and immediately terminating that user's active secure sessions. Deauthentication is crucial for mitigating so called Lunchtime Attacks, whereby an insider adversary takes over (before any inactivity timeout kicks in) authenticated state of a careless user who walks away from her computer. Motivated primarily by the need for an unobtrusive and continuous biometric to support effective deauthentication, we introduce PoPa, a new hybrid biometric based on a human user's seated posture pattern. PoPa captures a unique combination of physiological and behavioral traits. We describe a low cost fully functioning prototype that involves an office chair instrumented with 16 tiny pressure sensors. We also explore (via user experiments) how PoPa can be used in a typical workplace to provide continuous authentication (and deauthentication) of users. We experimentally assess viability of PoPa in terms of uniqueness by collecting and evaluating posture patterns of a cohort of users. Results show that PoPa exhibits very low false positive, and even lower false negative, rates. In particular, users can be identified with, on average, 91.0% accuracy. Finally, we compare pros and cons of PoPa with those of several prominent biometric based deauthentication techniques

Housing Bubbles: A Tale of Two Cities

postprin

12-year follow-up student of mortality due to suicide among first-episode psychosis cohort: Is the early intervention program more effective in reducing excess mortality due to suicide in psychosis

Oral Presentation: O10. Treatment and clinical service: no. O10.8published_or_final_versio

Web-Based Psychoeducation Program for Caregivers of First-Episode of Psychosis: An Experience of Chinese Population in Hong Kong

published_or_final_versio

High-Resolution Electrochemical Transistors Defined by Mold-Guided Drying of PEDOT:PSS Liquid Suspension.

Ion-sensitive transistors with nanoscale or microscale dimensions are promising for high-resolution electrophysiological recording and sensing. Technology that can pattern polymer functional materials directly from a solution can effectively avoid any chemical damage induced by conventional lithography techniques. The application of a mold-guided drying technique to pattern PEDOT:PSS-based transistors with high resolution directly from the water-based suspension is presented in this paper. Gold electrodes with short channels were first defined by creating high-resolution polymer lines with mold-guided drying followed by pattern transfer through a lift-off process. Then, PEDOT:PSS lines were subsequently created through an identical mold-guided drying process on the predefined electrodes. Small-scale transistor devices with both shortened channel length and width exhibited a good high-frequency response because of the weak capacitive effect. This is particularly advantageous for electrochemical transistors since the use of conventional fabrication techniques is extremely challenging in this case. In addition, modified polymer chain alignment of the assembled PEDOT:PSS lines during the drying process was observed by optical and electrical measurement. The mold-guided drying technique has been proven to be a promising method to fabricate small-scale devices, especially for biological applications

Perorally active nanomicellar formulation of quercetin in the treatment of lung cancer

10.2147/IJN.S26538International Journal of Nanomedicine7651-66

Directed differentiation of human bone marrow stromal cells to fate-committed Schwann cells

Transplantation of oligodendrocyte precursors represents a potential therapy for myelin disorders but requires a safe and accessible cell source. Here we report the directed differentiation of neural progenitors derived from adult bone marrow stromal cells (BMSCs) into oligodendrocyte precursors for cell therapy purpose. Neural progenitors among BMSCs could be culture expanded in non-adherent sphere-forming conditions and directed to differentiate along the oligodendrocyte lineage. BMSC-derived oligodendrocyte precursors (BM-OPs) differentiated into myelin basic protein (MBP)-positive oligodendrocyte when co-cultured with purified dorsal root ganglion (DRG) neurons. Injection of BM-OPs into the brain of myelin deficient Shiverer mice resulted in the generation of MBP-positive oligodendrocyte and compact myelin. Our results provided pointers to adult BMSCs as a readily accessible source of OPs towards cell therapy for myelin disorders.published_or_final_versio

The Effect of Paternal Age on Relapse in First-Episode Schizophrenia

published_or_final_versio

Fast Distributed Approximation for Max-Cut

Finding a maximum cut is a fundamental task in many computational settings. Surprisingly, it has been insufficiently studied in the classic distributed settings, where vertices communicate by synchronously sending messages to their neighbors according to the underlying graph, known as the $\mathcal{LOCAL}$ or $\mathcal{CONGEST}$ models. We amend this by obtaining almost optimal algorithms for Max-Cut on a wide class of graphs in these models. In particular, for any $\epsilon > 0$, we develop randomized approximation algorithms achieving a ratio of $(1-\epsilon)$ to the optimum for Max-Cut on bipartite graphs in the $\mathcal{CONGEST}$ model, and on general graphs in the $\mathcal{LOCAL}$ model. We further present efficient deterministic algorithms, including a $1/3$-approximation for Max-Dicut in our models, thus improving the best known (randomized) ratio of $1/4$. Our algorithms make non-trivial use of the greedy approach of Buchbinder et al. (SIAM Journal on Computing, 2015) for maximizing an unconstrained (non-monotone) submodular function, which may be of independent interest