Touching 3D data:interactive visualization of cosmological simulations

Visualisatie richt zich op het aanvullen van de zintuigen en het voorstellingsvermogen van wetenschappers zodat ze hun gegevens beter kunnen begrijpen. Dit is een interactief en iteratief proces waar informatierepresentatie, interactieve verkenning en het nemen van beslissingen een grote rol spelen. Het doel is om door middel van dit iteratieve proces inzicht te verkrijgen in het probleem en de onderliggende gegevens totdat er voldoende begrip is. Bij deze visuele verkenning is een hoge mate van interactiviteit essentieel voor het op eem efficiënte manier behalen van dit doel omdat het de gebruiker dan de mogelijkheid geeft om nieuwe ideëen uit te proberen, terugkoppeling te verkrijgen en de verkenning op basis daarvan bij te sturen. In dit proefschrift rapporteren we over ons onderzoek naar de uitdagingen voor natuurlijke interactie en de verkenning van gegevens die gerepresenteerd worden in drie dimensies. In dit proefschrift hebben we de visualisatie van astronomische gegevens als centraal voorbeeld genomen van een toepassingsdomein waarin de nadruk ligt op op drie-dimensionale puntwolkgegevens van numerieke simulaties, zoals simulaties van galactische dynamica of hoog-dimensionale informatie uit deeltjessystemen. We introduceren twee intuïtieve en efficiënte interactie-technieken voor de verkenning van gegevens in drie dimensies. De eerste techniek helpt gebruikers te navigeren in drie dimensies en de tweede techniek geeft gebruikers de mogelijkheid om eenvoudig een subset van deeltjes te selecteren. Daarnaast integreren we deze twee technieken in een visueel-analytische computerapplicatie om zo wetenschappers te helpen nuttige informatie te extraheren en inzicht te verkrijgen

Traceability of Water Pollution: An Inversion Scheme Via Dynamic Complex Geometrical Optics Solutions

We investigate the identification of the time-dependent source term in the diffusion equation using boundary measurements. This facilitates tracing back the origins of environmental pollutants. Employing the concept of dynamic complex geometrical optics (CGO) solutions, a variational formulation of the inverse source problem is analyzed, leading to a proof of uniqueness result. Our proposed two-step reconstruction algorithm first determines the point source locations and subsequently reconstructs the Fourier components of the emission concentration functions. Numerical experiments on simulated data are conducted. The results demonstrate that the proposed two-step reconstruction algorithm can reliably reconstruct multiple point sources and accurately reconstruct the emission concentration functions. Additionally, by partitioning the algorithm into online and offline computations, and concentrating computational demand offline, real-time pollutant traceability becomes feasible. This method, applicable in various fields - especially those related to water pollution, can identify the source of a contaminant in the environment, thus serving as a valuable tool in environmental protection

Flow Measurement: An Inverse Problem Formulation

This paper proposes a new mathematical formulation for flow measurement based on the inverse source problem for wave equations with partial boundary measurement. Inspired by the design of acoustic Doppler current profilers (ADCPs), we formulate an inverse source problem that can recover the flow field from the observation data on a few boundary receivers. To our knowledge, this is the first mathematical model of flow measurement using partial differential equations. This model is proved well-posed, and the corresponding algorithm is derived to compute the velocity field efficiently. Extensive numerical simulations are performed to demonstrate the accuracy and robustness of our model. Our formulation is capable of simulating a variety of practical measurement scenarios

Co-skeletons:Consistent curve skeletons for shape families

We present co-skeletons, a new method that computes consistent curve skeletons for 3D shapes from a given family. We compute co-skeletons in terms of sampling density and semantic relevance, while preserving the desired characteristics of traditional, per-shape curve skeletonization approaches. We take the curve skeletons extracted by traditional approaches for all shapes from a family as input, and compute semantic correlation information of individual skeleton branches to guide an edge-pruning process via skeleton-based descriptors, clustering, and a voting algorithm. Our approach achieves more concise and family-consistent skeletons when compared to traditional per-shape methods. We show the utility of our method by using co-skeletons for shape segmentation and shape blending on real-world data

The diversity and dynamics of tumor-associated macrophages in recurrent glioblastoma

Despite tremendous efforts to exploit effective therapeutic strategies, most glioblastoma (GBM) inevitably relapse and become resistant to therapies, including radiotherapy and immunotherapy. The tumor microenvironment (TME) of recurrent GBM (rGBM) is highly immunosuppressive, dominated by tumor-associated macrophages (TAMs). TAMs consist of tissue-resident microglia and monocyte-derived macrophages (MDMs), which are essential for favoring tumor growth, invasion, angiogenesis, immune suppression, and therapeutic resistance; however, restricted by the absence of potent methods, the heterogeneity and plasticity of TAMs in rGBM remain incompletely investigated. Recent application of single-cell technologies, such as single-cell RNA-sequencing has enabled us to decipher the unforeseen diversity and dynamics of TAMs and to identify new subsets of TAMs which regulate anti-tumor immunity. Here, we first review hallmarks of the TME, progress and challenges of immunotherapy, and the biology of TAMs in the context of rGBM, including their origins, categories, and functions. Next, from a single-cell perspective, we highlight recent findings regarding the distinctions between tissue-resident microglia and MDMs, the identification and characterization of specific TAM subsets, and the dynamic alterations of TAMs during tumor progression and treatment. Last, we briefly discuss the potential of TAM-targeted strategies for combination immunotherapy in rGBM. We anticipate the comprehensive understanding of the diversity and dynamics of TAMs in rGBM will shed light on further improvement of immunotherapeutic efficacy in rGBM