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  • Cytokinesis is an essential event in canonical cell division. In multicellular organisms, cells must divide in the context of neighboring cells in intact tissues. Recent studies have shown that tissue architecture can regulate the dynamics of and molecular requirements for cytokinesis. On the other hand, regulated cytokinesis failure occurs in, and is required for the proper function of, certain cell types and tissues including cardiomyocytes, hepatocytes, and germ lines. One way to build our understanding of cytokinesis in diverse cell types is to visualize cytokinesis in intact tissues. The nematode Caenorhabditis elegans is a powerful system for such inquiries due to the well-characterized, invariant lineage of each of its cells, the ease of genomic modifications including tagging proteins, and many more advantages. The clear cuticle of C. elegans allows for live imaging of intact tissues; however, the worm's motility can confound imaging. Here we introduce two C. elegans tissues, an epithelial tissue and the germ line, both excellent systems for the study of cytokinesis in the context of an intact animal. Additionally, we present three protocols for overcoming the challenges of live imaging in C. elegans.
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  • Polyploidy, the state of having greater than a diploid DNA content (tetraploid, octoploid, etc.) is a characteristic feature of mammalian hepatocytes and accompanies late fetal development and postnatal maturation of the liver. During the weaning period, diploid hepatocytes can engage either into normal cell division cycle giving rise to two diploid hepatocytes or follow a scheduled division program characterized by incomplete cytokinesis. In that case, diploid hepatocytes undergo mitosis, but do not form a contractile ring. Indeed, cleavage-plane specification is never established, because of the deficiencies of actin cytoskeleton reorganization. Furthermore, microtubules fail both to contact the cortex and to deliver their molecular signal, preventing localization and activation of RhoA. Therefore, cytokinesis aborts and a binucleate tetraploid liver cell is generated, which subsequently plays a pivotal role in liver progressive polyploidization. In this chapter, we describe detailed protocols to monitor hepatocyte proliferation and cytokinesis process by in situ and dynamic ex vivo approaches.
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  • Spinal ependymomas are predominantly slow-growing lesions constituting approximately 30–88% of primary spinal intramedullary tumors. They usually present as circumscribed lesions, with regular margins and a clear surgical plane. Gross-total resection is often feasible and potentially curative but neurosurgeons should keep in mind that the ultimate goal of surgery is the preservation of spinal cord function. We present the surgical technique to safely resect an intramedullary ependymoma using a posterior median sulcus approach. A brief description of current management of this pathology is also presented.
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  • Check dams are transversal structures built across morphologically-active streams in mountainous regions. These structures have been used widely in torrent-hazard mitigation for over 150years. Thousands of them are regularly maintained by stream managers and torrent-control services. The stabilization role of these structures is well known, i.e. they durably constrain the stream-bed through the creation of vertical and planar fixed points. What is not yet clear is to what extent check dams influence bed-load transport: How do peak solid discharge or flood-transported volume change when check dams are added to a reach? To address these questions, long-lasting small-scale experiments were conducted in a 4.8-m-long flume with either one, three or no structures. The results show that the addition of structures creates independent compartments in the bed level, which have a strong influence on bed surface armouring and stream morphodynamics: the consequence is that instantaneous transport intensities are unchanged, but peak solid discharge occur more often and for shorter duration. This results in the same total transported volume over the long term, but reduced volume for a single transport event. It reaffirms the observation of pioneering authors of the mid-19th and early 20th century who conceptualized the possible sediment transport regulation function of check dams: in addition to stabilizing the stream-bed, check dams influence bed-load transport through a buffering effect, releasing frequently and in small doses what, in their absence, would be transported abruptly en masse during rare extreme events.
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  • In this study, we present a framework that infers human activities from observations using semantic representations. The proposed framework can be utilized to address the difficult and challenging problem of transferring tasks and skills to humanoid robots. We propose a method that allows robots to obtain and determine a higher-level understanding of a demonstrator's behavior via semantic representations. This abstraction from observations captures the “essence” of the activity, thereby indicating which aspect of the demonstrator's actions should be executed in order to accomplish the required activity. Thus, a meaningful semantic description is obtained in terms of human motions and object properties. In addition, we validated the semantic rules obtained in different conditions, i.e., three different and complex kitchen activities: 1) making a pancake; 2) making a sandwich; and 3) setting the table. We present quantitative and qualitative results, which demonstrate that without any further training, our system can deal with time restrictions, different execution styles of the same task by several participants, and different labeling strategies. This means, the rules obtained from one scenario are still valid even for new situations, which demonstrates that the inferred representations do not depend on the task performed. The results show that our system correctly recognized human behaviors in real-time in around 87.44% of cases, which was even better than a random participant recognizing the behaviors of another human (about 76.68%). In particular, the semantic rules acquired can be used to effectively improve the dynamic growth of the ontology-based knowledge representation. Hence, this method can be used flexibly across different demonstrations and constraints to infer and achieve a similar goal to that observed. Furthermore, the inference capability introduced in this study was integrated into a joint space control loop for a humanoid robot, an iCub, for achieving similar goals to the human demonstrator online.
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  • Winter navigation is a complex but common operation in the Northern Baltic Sea areas. In Finnish waters, the safety of the wintertime maritime transportation system is managed through the Finnish–Swedish winter navigation system. This system results in different operational modes of ship navigation, with vessels either navigating independently or under icebreaker assistance. A recent risk analysis indicates that during icebreaker assistance, convoys operations are among the most hazardous, with convoy collisions the most important risk events. While the accident likelihood per exposure time is rather low, accidents occur almost every winter. Even though these typically lead to less serious consequences, accidents leading to ship loss and oil pollution have occurred and may occur in the future. One aspect of ship convoy navigation in ice conditions is the distance kept between the icebreaker and the ships in the convoy, a form of the well-known ship domain concept. While operational experience naturally is a valuable source of information for decision making about the distance of navigation in convoys, systematic analyses are lacking. The aim of this paper is to investigate selected operational aspects of convoy navigation in ice conditions in the Finnish waters of the Gulf of Finland, based on data of the Automatic Identification System and sea ice hindcast data. Focus is on obtaining qualitative and quantitative knowledge concerning distances between vessels in escort and convoy operations and the respective transit speeds, conditional to ice conditions. Such empirical knowledge can support operational decision making, contributing to wintertime maritime safety.
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  • Cargo-bearing unmanned aerial vehicles (UAVs) have tremendous potential to assist humans by delivering food, medicine, and other supplies. For time-critical cargo delivery tasks, UAVs need to be able to quickly navigate their environments and deliver suspended payloads with bounded load displacement. As a constraint balancing task for joint UAV-suspended load system dynamics, this task poses a challenge. This article presents a reinforcement learning approach for aerial cargo delivery tasks in environments with static obstacles. We first learn a minimal residual oscillations task policy in obstacle-free environments using a specifically designed feature vector for value function approximation that allows generalization beyond the training domain. The method works in continuous state and discrete action spaces. Since planning for aerial cargo requires very large action space (over 106 actions) that is impractical for learning, we define formal conditions for a class of robotics problems where learning can occur in a simplified problem space and successfully transfer to a broader problem space. Exploiting these guarantees and relying on the discrete action space, we learn the swing-free policy in a subspace several orders of magnitude smaller, and later develop a method for swing-free trajectory planning along a path. As an extension to tasks in environments with static obstacles where the load displacement needs to be bounded throughout the trajectory, sampling-based motion planning generates collision-free paths. Next, a reinforcement learning agent transforms these paths into trajectories that maintain the bound on the load displacement while following the collision-free path in a timely manner. We verify the approach both in simulation and in experiments on a quadrotor with suspended load and verify the method's safety and feasibility through a demonstration where a quadrotor delivers an open container of liquid to a human subject. The contributions of this work are two-fold. First, this article presents a solution to a challenging, and vital problem of planning a constraint-balancing task for an inherently unstable non-linear system in the presence of obstacles. Second, AI and robotics researchers can both benefit from the provided theoretical guarantees of system stability on a class of constraint-balancing tasks that occur in very large action spaces.
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