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Since infancy, humans acquire motor skills, behavioral priors, and objectives by learning from their caregivers. Similarly, as we create humanoids in our own image, we aspire for them to learn from us and develop universal physical and cognitive capabilities that are comparable to, or even surpass, our own. In this thesis, we explore how to equip humanoids with the mobility, dexterity, and environmental awareness necessary to perform meaningful tasks. Unlike previous efforts that focus on learning a narrow set of tasks, such as traversing terrains, imitating a few human motion clips, or playing a single game, we emphasize scaling humanoid control tasks by leveraging large-scale human data (e.g., motion, videos). We show that scaling brings numerous benefits, gradually moving us closer to achieving truly \"universal\" capabilities.Our key idea centers around scaling up humanoid motion tracking and forming a foundational humanoid control prior that can be used to speed up task learning. Just like young animals are born with the instinct to walk, run, and grasp, we wish to equip humanoids with motor control priors that lead to human-like movement. We begin by scaling the reinforcement learning based motion tracking framework, enabling humanoids to imitate large-scale kinematic human motion datasets. This motion imitator forms the basis for acquiring motor skills: given a kinematic reference motion, the imitator can robustly control the humanoid to execute everyday activities and more complex, dynamic movements. Such a motion imitator can be used for human pose estimation, teleoperation, and controlling simulated avatars using first-person and third-person cameras.Equipped with such a motion tracker, we distill behaviors from the tracker into a compact, physics-based control latent space and form a general-purpose humanoid control prior. This prior enables the reuse of previously learned motor skills from a large-scale dataset. Randomly sampling from this latent space leads to human-like behaviors from the humanoid. Leveraging this latent representation in hierarchical reinforcement learning significantly improves sample efficiency and produces human-like motion. A critical aspect of this framework is ensuring that the latent space faithfully encapsulates the full range of motor skills present in the source dataset—a property we verify empirically.Building upon such a humanoid control prior, we study simulated humanoids equipped with dexterous hands, touch sensors, and vision to interact with their environments and manipulate objects. We find that our control prior significantly simplifies the training process for manipulation tasks, and we can learn policies that generalize across diverse sets of objects and scenes. Along the way, we solve practical problems involved in humanoid dexterous manipulation and perception-int-the-loop control.Finally, we take a step toward real-world deployment by transferring this framework to physical humanoids. As a first milestone, we train a universal humanoid motion tracker that runs in real time and can be used for humanoid teleoperation. This real-world deployment highlights the practicality of our approach and sets the stage for future work in learning universal controllers for real humanoids.

A model-based optimal dispatch framework was proposed to optimize operation of residential flexible loads considering their real-life operating characteristics, energy-related occupant behavior, and the benefits of different stakeholders. A pilot test was conducted for a typical household. According to the monitored appliance-level data, operating characteristics of flexible loads were identified and the models of these flexible loads were developed using multiple linear regression and K-means clustering methods. Moreover, a data-mining approach was developed to extract the occupant energy usage behavior of various flexible loads from the monitored data. Occupant behavior of appliance usage, such as daily turn-on times, turn-on moment, duration of each operation, preference of temperature setting, and flexibility window, were determined by the developed data-mining approach. Based on the established flexible load models and the identified occupant energy usage behavior, a many-objective nonlinear optimal dispatch model was developed aiming at minimizing daily electricity costs, occupants’ dissatisfaction, CO 2 emissions, and the average ramping index of household power profiles. The model was solved with the assistance of the NSGA-III and TOPSIS methods. Results indicate that the proposed framework can effectively optimize the operation of household flexible loads. Compared with the benchmark, the daily electricity costs, CO 2 emissions, and average ramping index of household power profiles of the optimal plan were reduced by 7.3%, 6.5%, and 14.4%, respectively, under the TOU tariff, while those were decreased by 9.5%, 8.8%, and 23.8%, respectively, under the dynamic price tariff. The outputs of this work can offer guidance for the day-ahead optimal scheduling of household flexible loads in practice.

Vessel behaviour analysis plays an important role in maritime situational awareness. However, available technology still provides only limited approaches to vessel behaviour analysis. In this paper, we propose a visual analytics framework to interactively explore the characteristics of vessel behaviour by means of integrating visualisation with data mining and a human-computer interaction controlling model, which combines human insight with the enormous storage and processing capacities of computers to gain insight into vessel behaviour. In addition, we provide multiple views for visually analysing vessel trajectories, densities and speeds. Case studies with 15 days' AIS data collected from the middle Hankou channel to Yangluo channel in the Yangtze River demonstrate the effectiveness of our approach.

Nuclear calcium levels affect gene expression, but little is known about how they are regulated. The authors show that large-conductance calcium-activated potassium (BK) channels are present on the nuclear envelope in rodent hippocampal neurons. Blockade of nuclear BK channels revealed that they regulate nucleoplasmic Ca 2+ , gene expression and dendritic arborization. Ion channels are essential for the regulation of neuronal functions. The significance of plasma membrane, mitochondrial, endoplasmic reticulum and lysosomal ion channels in the regulation of Ca 2+ is well established. In contrast, surprisingly little is known about the function of ion channels on the nuclear envelope (NE). Here we demonstrate the presence of functional large-conductance, calcium-activated potassium channels (BK channels) on the NE of rodent hippocampal neurons. Functionally, blockade of nuclear BK channels (nBK channels) induces NE-derived Ca 2+ release, nucleoplasmic Ca 2+ elevation and cyclic AMP response element binding protein (CREB)-dependent transcription. More importantly, blockade of nBK channels regulates nuclear Ca 2+ –sensitive gene expression and promotes dendritic arborization in a nuclear Ca 2+ –dependent manner. These results suggest that the nBK channel functions as a molecular link between neuronal activity and nuclear Ca 2+ to convey signals from synapse to nucleus and is a new modulator, operating at the NE, of synaptic activity–dependent neuronal functions.

This study describes the synaptogenic function of an ErbB2-interacting protein called Erbin, particularly its function in the formation of excitatory synapses on interneurons and its regulation of AMPA-type glutamate receptors through its interaction with the auxiliary AMPA receptor protein TARP γ-2. Inhibitory neurons control the firing of glutamatergic neurons and synchronize brain activity. However, little is known about mechanisms of excitatory synapse formation in inhibitory neurons. Here we demonstrate that Erbin is specifically expressed in cortical inhibitory neurons. It localizes at excitatory synapses and regulates AMPA receptor (AMPAR) surface expression. Erbin mutation reduced mEPSCs and AMPAR currents specifically in parvalbumin (PV)-positive interneurons but not in pyramidal neurons. We found that the AMPAR auxiliary protein TARP γ-2 was specifically expressed in cortical interneurons. Erbin interacts with TARP γ-2 and is crucial for its stability. Deletion of the γ-2–interacting domain in Erbin attenuated surface AMPAR and excitatory transmission in PV-positive interneurons. Furthermore, we observed behavioral deficits in Erbin-null mice and in mice expressing an Erbin truncation mutant that is unable to interact with TARP γ-2. These observations demonstrate a crucial function for Erbin in AMPAR surface expression in cortical PV-positive interneurons and may contribute to a better understanding of psychiatric disorders.

4-aminopyridine (4-AP), a voltage-gated potassium channel blocker, was revealed to possess pro-apoptotic properties in various types of cancer cells. The present study aimed to explore the effect of 4-AP on a cisplatin (DDP) resistant lung cancer cell line A549/CDDP and the underlying mechanism by which it had an effect. In the present study, an MTT assay and cell cycle analysis were used to determine that 4-AP inhibited cell growth in vitro and a tumorigenesis assay in nude mice determined that 4-AP also inhibited cell growth in vivo. 4-AP induced cell apoptosis of A549/CDDP cells observed by electron microscopy and Annexin V-APC/7-ADD analysis. In addition, 4-AP enhanced the sensitivity of A549/CDDP cells to DDP as revealed by an MTT assay. Mechanistically, 4-AP upregulated the phosphatase and tensin homolog (PTEN) and modulated the phosphoinositide 3-kinase/protein kinase B signaling pathway and its downstream cell cycle factors, including cyclin D1, cyclin-dependent kinase 4 and p21, as well as apoptosis-associated proteins B-cell lymphoma 2, pro-caspase 9, pro-caspase 3, cleaved caspase 9 and cleaved caspase 3. The effects of 4-AP on cell growth and apoptosis were reversed by PTEN silencing. In conclusion, the results indicated that 4-AP inhibited cell growth, induced apoptosis and sensitized A549/CDDP cells to DDP via the upregulation of PTEN. 4-AP may be a potential therapeutic agent for patients with DDP resistance.

Nat. Neurosci. 17, 1055–1063 (2014); published online 22 June 2014; corrected after print 5 September 2014 In the version of this article initially published, item (ii) in the third paragraph of the Discussion read, “The ability to obtain high-resistance gigaohm seals during patch clamping in the nucleus-attached mode, when dozens of NPCs may be encompassed by the patch pipette, suggests that NPCs can exist in a closed state that restricts ion flow39.