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Creators/Authors contains: "Zhang, Han"

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  1. Abstract Purpose

    Specialized robotic and surgical tools are increasing the complexity of operating rooms (ORs), requiring elaborate preparation especially when techniques or devices are to be used for the first time. Spatial planning can improve efficiency and identify procedural obstacles ahead of time, but real ORs offer little availability to optimize space utilization. Methods for creating reconstructions of physical setups, i.e., digital twins, are needed to enable immersive spatial planning of such complex environments in virtual reality.

    Methods

    We present a neural rendering-based method to create immersive digital twins of complex medical environments and devices from casual video capture that enables spatial planning of surgical scenarios. To evaluate our approach we recreate two operating rooms and ten objects through neural reconstruction, then conduct a user study with 21 graduate students carrying out planning tasks in the resulting virtual environment. We analyze task load, presence, perceived utility, plus exploration and interaction behavior compared to low visual complexity versions of the same environments.

    Results

    Results show significantly increased perceived utility and presence using the neural reconstruction-based environments, combined with higher perceived workload and exploratory behavior. There’s no significant difference in interactivity.

    Conclusion

    We explore the feasibility of using modern reconstruction techniques to create digital twins of complex medical environments and objects. Without requiring expert knowledge or specialized hardware, users can create, explore and interact with objects in virtual environments. Results indicate benefits like high perceived utility while being technically approachable, which may indicate promise of this approach for spatial planning and beyond.

     
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  2. Markostamou, Ioanna (Ed.)
    People differ substantially in their vulnerability to distraction. Yet, many types of distractions exist, from external stimulation to internal thoughts. How should we characterize individual differences in their distractibility? Two samples of adult participants (total N = 1220) completed a large battery of questionnaires assessing different facets of real-world distractibility. Latent modeling revealed that these measures could be explained by three correlated-yet-distinct factors: external distraction, unwanted intrusive thoughts, and mind-wandering. Importantly, about 80% of the total variance in these three factors could be explained by a single higher-order factor (d) that could be construed in terms of a person’s general distractibility, and this general distractibility model was replicated across the two samples. We then applied the general distractibility model to understand the nature of ADHD symptomatology and hyperfocus (an intense state of long-lasting and highly focused attention). d was substantially associated with self-reported ADHD symptoms. Interestingly, d was also positively associated with hyperfocus, suggesting that hyperfocus may, to some degree, reflect attention problems. These results also show marked consistencies across the two samples. Overall, the study provides an important step toward a comprehensive understanding of individual differences in distractibility and related constructs. 
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    Free, publicly-accessible full text available October 25, 2024
  3. Free, publicly-accessible full text available December 27, 2024
  4. Conventional Multi-Agent Path Finding (MAPF) problems aim to compute an ensemble of collision-free paths for multiple agents from their respective starting locations to pre-allocated destinations. This work considers a generalized version of MAPF called Multi-Agent Combinatorial Path Finding (MCPF) where agents must collectively visit a large number of intermediate target locations along their paths before arriving at destinations. This problem involves not only planning collision-free paths for multiple agents but also assigning targets and specifying the visiting order for each agent (i.e., target sequencing). To solve the problem, we leverage Conflict-Based Search (CBS) for MAPF and propose a novel approach called Conflict-Based Steiner Search (CBSS). CBSS interleaves (1) the collision resolution strategy in CBS to bypass the curse of dimensionality in MAPF and (2) multiple traveling salesman algorithms to handle the combinatorics in target sequencing, to compute optimal or bounded sub-optimal paths for agents while visiting all the targets. We also develop two variants of CBSS that trade off runtime against solution optimality. Our test results verify the advantage of CBSS over the baselines in terms of computing cheaper paths and improving success rates within a runtime limit for up to 20 agents and 50 targets. Finally, we run both Gazebo simulation and physical robot tests to validate that the planned paths are executable. 
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  5. Abstract

    Overcoming barriers on the use of multi-center data for medical analytics is challenging due to privacy protection and data heterogeneity in the healthcare system. In this study, we propose the Distributed Synthetic Learning (DSL) architecture to learn across multiple medical centers and ensure the protection of sensitive personal information. DSL enables the building of a homogeneous dataset with entirely synthetic medical images via a form of GAN-based synthetic learning. The proposed DSL architecture has the following key functionalities: multi-modality learning, missing modality completion learning, and continual learning. We systematically evaluate the performance of DSL on different medical applications using cardiac computed tomography angiography (CTA), brain tumor MRI, and histopathology nuclei datasets. Extensive experiments demonstrate the superior performance of DSL as a high-quality synthetic medical image provider by the use of an ideal synthetic quality metric called Dist-FID. We show that DSL can be adapted to heterogeneous data and remarkably outperforms the real misaligned modalities segmentation model by 55% and the temporal datasets segmentation model by 8%.

     
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  6. Free, publicly-accessible full text available June 13, 2024
  7. Abstract We present 0.″4 resolution imaging polarimetry at 8.7, 10.3, and 12.5 μ m, obtained with CanariCam at the Gran Telescopio Canarias, of the central 0.11 pc × 0.28 pc (4.″2 × 10.″8) region of W51 IRS2. The polarization, as high as ∼14%, arises from silicate particles aligned by the interstellar magnetic field ( B -field). We separate, or unfold, the polarization of each sightline into emission and absorption components, from which we infer the morphologies of the corresponding projected B -fields that thread the emitting- and foreground-absorbing regions. We conclude that the projected B -field in the foreground material is part of the larger-scale ambient field. The morphology of the projected B -field in the mid-infrared (mid-IR) emitting region spanning the cometary H ii region W51 IRS2W is similar to that in the absorbing region. Elsewhere, the two B -fields differ significantly with no clear relationship between them. The B -field across the W51 IRS2W cometary core appears to be an integral part of a champagne outflow of gas originating in the core and dominating the energetics there. The bipolar outflow, W51north jet, that appears to originate at or near SMA1/N1 coincides almost exactly with a clearly demarcated north–south swath of lower polarization. While speculative, comparison of mid-IR and submillimeter polarimetry on two different scales may support a picture in which SMA1/N1 plays a major role in the B -field structure across W51 IRS2. 
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  8. Centromeres are long, often repetitive regions of genomes that bind kinetochore proteins and ensure normal chromosome segregation. Engineering centromeres that function in vivo has proven to be difficult. Here we describe a tethering approach that activates functional maize centromeres at synthetic sequence arrays. A LexA-CENH3 fusion protein was used to recruit native Centromeric Histone H3 (CENH3) to long arrays of LexO repeats on a chromosome arm. Newly recruited CENH3 was sufficient to organize functional kinetochores that caused chromosome breakage, releasing chromosome fragments that were passed through meiosis and into progeny. Several fragments formed independent neochromosomes with centromeres localized over the LexO repeat arrays. The new centromeres were self-sustaining and transmitted neochromosomes to subsequent generations in the absence of the LexA-CENH3 activator. Our results demonstrate the feasibility of using synthetic centromeres for karyotype engineering applications. 
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  9. As Internet-of-Things (IoT) devices rapidly gain popularity, they raise significant privacy concerns given the breadth of sensitive data they can capture. These concerns are amplified by the fact that in many situations, IoT devices collect data about people other than their owner or administrator, and these stakeholders have no say in how that data is managed, used, or shared. To address this, we propose a new model of ownership, IoT Ephemeral Ownership (TEO). TEO allows stakeholders to quickly register with an IoT device for a limited period, and thus claim co-ownership over the sensitive data that the device generates. Device admins retain the ability to decide who may become an ephemeral owner, but no longer have access or control to the private data generated by the device. The encrypted data in TEO is accessible only by entities after seeking explicit permission from the different co-owners of that data. We verify the key security properties of our protocol underpinning TEO in the symbolic model using ProVerif. We also implement a cross-platform prototype of TEO for mobile phones and embedded devices, and integrate it into three real-world application case studies. Our evaluation shows that the latency and battery impact of TEO is typically small, adding ≤ 187 ms onto one-time operations, and introducing limited (<25%) overhead on recurring operations like private data storage. 
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