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Depression is a polygenic and highly complex psychiatric disorder that is currently a major burden on society. Depression is highly heterogeneous in presentation and frequently exhibits high co-morbidity with other psychiatric and somatic deficits. Commonly used treatments, such as selective serotonin reuptake inhibitors (SSRIs), are not ideal since only a subset of patients achieve remission. In addition, the reason why some individuals respond to SSRIs while others don’t are unknown. Here we begin to ask what the basis of treatment-resistance is, and propose new strategies to model this phenomenon in animals. We focus specifically on animal models that offer the appropriate framework to study treatment resistance with face, construct and predictive validity.

Abstract-Consensus protocols are distributed algorithms in networked multi-agent systems. Based on the local information, agents automatically converge to a common consensus state and the convergence speed is determined by the algebraic connectivity of the communication network. In order to achieve a fast consensus seeking, we propose the multi-hop relay protocols, where each agent can expand its knowledge by employing multi-hop paths in the network. We demonstrate that multi-hop relay protocols can enlarge the algebraic connectivity without physically changing the network topology. Moreover, communication delays are discussed and a tradeoff is identified between the convergence speed and the time delay sensitivity.Index Terms-Networked multi-agent systems, consensus protocol, multi-hop relay protocol, distributed algorithms, convergence speed, time delay.

For state estimation over a communication network, efficiency and reliability of the network are critical issues. The presence of packet dropping and communication delay can greatly impair our ability to measure and predict states. In this paper, multiple description (MD) codes, a type of network source codes, are used to compensate for this effect on Kalman filtering. We consider two packet dropping models: in one model, packet dropping occurs according to an independent and identically distributed (i.i.d.) Bernoulli random process and in the other model, packet dropping is bursty and occurs according to a Markov chain. We show that MD codes greatly improve the statistical stability and performance of Kalman filter over a large set of packet loss scenarios in both cases. Our conclusions are verified by simulation results.

Depth camera such as Microsoft Kinect, is much cheaper than conventional 3D scanning devices, and thus it can be acquired for everyday users easily. However, the depth data captured by Kinect over a certain distance is of extreme low quality. In this paper, we present a novel scanning system for capturing 3D full human body models by using multiple Kinects. To avoid the interference phenomena, we use two Kinects to capture the upper part and lower part of a human body respectively without overlapping region. A third Kinect is used to capture the middle part of the human body from the opposite direction. We propose a practical approach for registering the various body parts of different views under non-rigid deformation. First, a rough mesh template is constructed and used to deform successive frames pairwisely. Second, global alignment is performed to distribute errors in the deformation space, which can solve the loop closure problem efficiently. Misalignment caused by complex occlusion can also be handled reasonably by our global alignment algorithm. The experimental results have shown the efficiency and applicability of our system. Our system obtains impressive results in a few minutes with low price devices, thus is practically useful for generating personalized avatars for everyday users. Our system has been used for 3D human animation and virtual try on, and can further facilitate a range of home–oriented virtual reality (VR) applications.

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