348 research outputs found
Modeling Dengue Virus-Hepatic Cell Interactions Using Human Pluripotent Stem Cell-Derived Hepatocyte-like Cells
No full textSummaryThe development of dengue antivirals and vaccine has been hampered by the incomplete understanding of molecular mechanisms of dengue virus (DENV) infection and pathology, partly due to the limited suitable cell culture or animal models that can capture the comprehensive cellular changes induced by DENV. In this study, we differentiated human pluripotent stem cells (hPSCs) into hepatocytes, one of the target cells of DENV, to investigate various aspects of DENV-hepatocyte interaction. hPSC-derived hepatocyte-like cells (HLCs) supported persistent and productive DENV infection. The activation of interferon pathways by DENV protected bystander cells from infection and protected the infected cells from massive apoptosis. Furthermore, DENV infection activated the NF-κB pathway, which led to production of proinflammatory cytokines and downregulated many liver-specific genes such as albumin and coagulation factor V. Our study demonstrates the utility of hPSC-derived hepatocytes as an in vitro model for DENV infection and reveals important aspects of DENV-host interactions
Crustal and upper-most mantle seismic structure beneath the Middle-east using surface-wave tomography
No full textWe have constructed a 3-D shear-wave velocity model for the crust and upper most mantle beneath the Middle-East by analysis of Rayleigh wave records obtained from ambient-noise correlation and regional earthquakes. We combined one decade of data collected from more than 850 permanent and temporary broadband stations in the region in order to calculate group velocity dispersion curves. We have in total >60000 ray paths giving reliable group velocity measurements for periods between 5 and 100 seconds.
The group velocities calculated at different periods along individual ray paths were inverted for 2-D group-velocity maps. Due to the heterogeneous ray coverage, we pursue an adaptive parametrization for the group velocity tomography inversion.
We then inverted the dispersion curves extracted at grid points of the 2-D group-velocity maps for 1-D shear-wave velocity profiles beneath each grid.
The S-wave velocity model shows regions of low-velocities at shallow depths (5-10 km) beneath the Mesopotamian foredeep, south Caspian basin, eastern Mediterranean and Black Sea. These low velocity regions coincide with the thick sedimentary basins. Shallow high-velocity anomalies are observed in the regions with magmatic outcrops such as the Arabian Shield and NW Iran.
In the upper crustal depth range (10-20 km), we clearly observe a band of high-velocity anomalies (> 4.0 km/s) along the Red Sea, indicating the presence of the upper mantle rocks in this depth range. Low velocity regions are observed beneath the Mesopotamian foredeep and Zagros implying the effect of thick sedimentary rocks comprising the upper crust.
Our 3-D velocity model exhibits high velocities in the depth range 25-40 km beneath the western Arabia, south Caspian basin, eastern Mediterranean and Black Sea indicating a relatively thin crust beneath these regions, whereas the Zagros, NW Iran, the easternmost Anatolian plateau and Lesser Caucasus are characterized by low velocities at these depths. At least some of these anomalies may be related to thick crustal roots that support the high topography of these regions.
In the upper mantle depth range, high-velocity anomalies are obtained beneath the Arabian Platform, southern Zagros and eastern Mediterranean and low velocities beneath Red Sea, Arabian Shield, Afar depression, Central Iran and eastern Turkey
Object segmentation in neural radiance field
No full textFirst, we present one of the first learning-based 3D instance segmentation pipelines in Neural Radiance Field (NeRF), dubbed as Instance-NeRF. Taking a NeRF pretrained from multi-view RGB images as input, Instance-NeRF can learn 3D instance segmentation of a given scene, represented as an instance field component of the NeRF model. To this end, we adopt a 3D proposal-based mask prediction network on the sampled volumetric features from NeRF, which generates discrete 3D instance masks. The coarse 3D mask prediction is then projected to image space to match 2D segmentation masks from different views generated by existing panoptic segmentation models, which are used to supervise the training of the instance field. Notably, beyond generating consistent 2D segmentation maps from novel views, Instance-NeRF can query instance information at any 3D point, which greatly enhances NeRF object segmentation and manipulation. Next, we introduce the Segment Anything for NeRF in High Quality (SANeRF-HQ) to achieve high-quality 3D segmentation of any target object in a given scene. SANeRF-HQ utilizes Segment Anything Model (SAM) for open-world object segmentation guided by user-supplied prompts, while leveraging NeRF to aggregate information from different viewpoints. To overcome the aforementioned challenges, we employ density field and RGB similarity to enhance the accuracy of segmentation boundary during the aggregation. Emphasizing on segmentation accuracy, we evaluate our method on multiple NeRF datasets where high-quality ground-truths are available or manually annotated. SANeRF-HQ shows a significant quality improvement over state-of-the-art methods in NeRF object segmentation, provides higher flexibility for object localization, and enables more consistent object segmentation across multiple views.</p
How Team Building Influences Team Outcomes
No full textTeam building activities can be found everywhere. Sometimes, people would question that such simple or even silly games are not effective at all. In order to justify the effectiveness of team building activities, the present study tried to find out the real impact of team building on team outcomes. Several theories were discussed in the present study, but only the input-mediator-outcome (IMO) model was selected as the major framework. Within the framework of emergent stages, the present study focused on investigating in the impact of team building on social preferences which would finally influence personal decision makings and individuals’ affect. By specifying team outcomes as team performance and members’ affect, the present study conducted two sets of experiments. First experiment recruited 108 participants via Mturk and asked participants to finish several questionnaires and investigated in the relationship between team building experiences and either team production behaviors or job satisfaction. Second experiment recruited 64 participants from the College of Wooster and the Capital University of Economics and Business in China. Participants were asked to play three rounds of public goods games or two rounds of public goods games plus one team building game. The results from two experiments showed no significant relationship between team building and team outcomes. However, the results suggested that team building activities reinforced team learning behaviors
Design and evaluation of trajectory-based tasks in a thin-seam perspective-corrected cubic display
No full textThis thesis describes the design and evaluation of wire-tracing task in pCubee, an improved version of hand-held perspective-corrected display that allows the user to observe and interact with 3D content visualized inside the cubic system. In order to overcome visual discontinuity issues identified from previous works, we redesigned pCubee system using OLED panels and FPGA-based display controller to achieve reduced seam size and compact form-factor. We investigated user performance with the new system using a trajectory-based wire-tracing task where users were asked to move a ring along wires. Experiments were conducted to evaluate the impact of ring radius, wire length and curvature. Analysis of results revealed that a linear model similar to the steering law for 2D tunnel task applies to 3D trajectory-based task in pCubee as well, exhibiting an increase of task completion time when smaller ring or longer wire is used. Our study complemented the theory that 3D interaction in virtual reality system follows existing principle for 2D tasks, and also identified a potential method to evaluate interaction designs for geometric displays. This work could help motivate future development of pCubee and guide interaction design for similar systems.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat
Raw Data for "On-demand cell-autonomous gene therapy for brain circuit disorders", Qiu et al. 2022 Science
No full textRaw Data for Qui et al. 2022 10.1126/science.abq6656
On-demand cell-autonomous gene therapy for brain circuit disorders
Yichen Qiu, Nathanael O’Neill, Benito Maffei, Clara Zourray, Amanda Almacellas Barbanoj, Jenna C. Carpenter,Steffan P. Jones, Marco Leite, Thomas J. Turner, Francisco C. Moreira, Albert Snowball, Tawfeeq Shekh-Ahmad, Vincent Magloire, Serena Barral, Manju A. Kurian, Matthew C. Walker, Stephanie Schorge, Dimitri M. Kullmann, Gabriele Lignani
Content:
EEG
MEA
Immuno
Patch Clamp Electrophysiology
All data are in a open source format. MEA files can be analysed using the MATLAB-based developed by Prof Michela Chiappalone and requests should be direct to:
Michela Chiappalone [email protected]
Ilaria Colombi [email protected]
EEG files are .zip with different transmitters. See EEG_Keys.xlxs for whcih virus was used in each animal.
MEA files are divided in 2 separate .zip: 1. Fig2 and Fig S3 and S7. 2. Fig S6.
Immuno: all the raw images are in the .zip file seprated by Figure #
Patch Clamp Electrophysiology: all the raw .abf files are in the .zip file separated by Figure #
For more info or to request materials please contact the corrsponding author Gabriele Lignani [email protected]
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What Is an Author's Role in the AI Era? Demystifying the Black Box of Human-AI Collaborative Creation Through an "Aesthetic Judgment" Study of the novel Solid Reference Frame Manuscript
No full textThis project repository establishes a permanent timestamp for a study that rethinks Roland Barthes' proclamation of the "death of the author" for the AI era. It engages with Michel Foucault's concept of "author-function" to propose "Aesthetic Judgment" as a new theoretical framework for human-AI collaborative creation. This framework reconceptualizes AI as a "critical partner"—a source of provocation and challenge. The human author, in turn, exercises decisive curatorial power through four key operations: 1) The Right to Question, 2) The Right to Select, 3) The Right to Arbitrate, and 4) The Right to Integrate.
Employing a "Process-Tracing" methodology, the research analyzes the complete manuscript of the novel Solid Reference Frame to demystify the creative "black box." This empirical study aims to demonstrate how the human author's role is transformed from a solitary genius into a systemic architect of meaning, thereby asserting a new, viable author-function for the digital age
Tailored family adaptation to living in a zero-energy house: Occupant’s crises and conflicts with a heat pump-based system
No full textBackgroundThis project belongs to the IEBB project, which advocates for the renovation of ‘zero energy houses’ (ZEH) that synergize insulation and heat pump systems for energy conservation. The ZEH’s energy-saving efficiency depends on user behaviour. From a systems perspective, improper human interactions hinder energy saving, while occupants may find system responses that conflict with their preferences. This study delves into these conflicts and crises, highlighting the variance in post-occupancy adaptation influenced by individual perceptions and familial interplay. The project’s zenith aim is to tailor adaptation, ensuring co-performance between the heat pumpsystem and households. Key InsightIn researching residents’ responses to the ‘routine crisis’ introduced by a new system, I discovered that these ‘crises’ could be productive, stimulating household engagement and fostering harmonious interactions with ZEH systems. This insight gave rise to the concept of the ‘enacted interface’ - a distinctive bridge between residents and their automated homes that supports the adaptation process. Through analysis, I identified elements that amplify residents’ engagement with ‘crises’ and observed the influence of family diversity on individual perceptions and responses to them. The results are manifested in two interrelated frameworks: one describing the ubiquity of ‘crises’ and another characterising the classification and impact of different elements.DesignThis design aims to make households curious about ‘crises’ and guide them towards tailored adaptations to new tech. The ‘Clock’ thermostat provides a consistent interface for temperature adjustments, while the ‘Feeling Message Board’ suggests lifestyle tips based on the user’s emotional input and changing scenarios. Both reinforce the system’s ability to communicate contextual and real-time status, motivating users to actively engage with its functions. Additionally, the design stimulates family discussions about the indoor environment and promotes collaborative responses to ‘crises’. Through co-performance of the system’s dynamic feedback and the household’s proactive exploration, the aim is to facilitate tailored adaptation.IEBB projectIntegrated Product Desig
Genetic Algorithm–Assisted Design of Redistribution Layer Vias for a Fan-Out Panel-Level SiC MOSFET Power Module Packaging
No full textA fan-out panel-level packaging (FOPLP) with an embedded redistribution layer (RDL) via interconnection reduces the size, thermal resistance, and parasitic inductance of power module packaging. In this study, the effect of the RDL via size on the reliability of a FOPLP SiC MOSFET power module was investigated. To improve the thermal management and thermal cycling reliability of the designed SiC module, genetic algorithm (GA)–assisted optimization methods were proposed to optimize the RDL via size. First, the heat dissipation and the plastic work density of the SiC MOSFET module with various via diameters and depths were simulated using finite element simulations. Next, both the ant colony optimization-backpropagation neural network (ACOBPNN) with finite element simulation and the nondominated sorting genetic algorithm (NSGA-II) with theoretical model were developed to optimize the RDL via size. The results revealed that: (1) smaller via depth and size reduce the heat dissipation and thermal cycling reliability of the RDL via; (2) through both the ACO-BPNN and NSGA-II, the same optimal heat dissipation and plastic work density can be achieved in the designed module. (3) ACO-BPNN with assist of finite element simulation can provide a more effective optimization in complex packaging structure.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Electronic Components, Technology and Material
The assessment model of online vocal music teaching quality under the optimized DL model
No full textIn recent years, art disciplines have flourished in response to the requirements of the times, and online vocal music courses have been offered by major colleges and universities. The quality of education in colleges and universities is a key indicator of the quality of a school's talents, and improving its quality is the most important part of modernizing education. In this study, a new education index system is constructed to address the problems of traditional online vocal teaching quality evaluation methods, and a vocal teaching quality evaluation model based on an adaptive variant Genetic Algorithm improved Back Propagation neural network is proposed. The model is combined with the established new index system and used in the evaluation of vocal music teaching quality. Comparing the performance between the model and the model constructed by the traditional algorithm, the experimental results showed that the convergence speed of the optimized model was improved by 79.32%. The model adaptation reached convergence in the 19th time, and the adaptation value was stabilized at 1.34, which can be seen that the improved model has a stronger adaptive ability and a faster convergence speed. In summary, the results predicted by the model basically coincide with the trend of the actual evaluation results, and the existence of the error is small, indicating that the model can achieve a more comprehensive and scientific evaluation of education quality
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