Numerical study of the dynamic processes in volcanic eruptions: Bubble dynamics and volatiles diffusion

Volcanic eruption releases gases and aerosols (e.g., sulfur compounds) to the atmosphere, impacting climate for up to several years. While most research efforts of volcanologists to date have been devoted to unraveling the eruptive activity and formation of volcanoes, the understanding of volatiles diffusion during volcanic eruption is still preliminary, largely due to the lack of robust computational tools for magma dynamics during volcanic eruption at the necessary time and length scales. On the other hand, magmatic processes, from the production of melts in the upper mantle to their crystallization or eruption at the surface, are dominated by dynamic processes in deep Earth that are not directly observable, limiting the direct measurement of these processes through geological fieldwork. This dissertation includes three main parts: (i) a non-equilibrium bubble growth models are developed to assess the role of bubble dynamics and volatile kinetics in "excess sulfur" problem (Chap. 2) and the implication of the volatile diffusion profile after eruptions on magma ascent history (Chap. 3); (ii) a new bubble dynamics model that accounts for hydrodynamical interactions (deformation, coalescence) between bubbles are established (Chap. 4); (iii) the dynamical response of saturated porous media to transient stresses is studied using the lattice Boltzmann method with four different porous media topologies (Chap. 5). It is anticipated that the findings in this dissertation will improve physical understanding of volatile degassing, bubble dynamics, and saturated porous media in response to transient changes of stresses.Ph.D

Efficient Cavity Searching for Gene Network of Influenza A Virus

High order structures (cavities and cliques) of the gene network of influenza A virus reveal tight associations among viruses during evolution and are key signals that indicate viral cross-species infection and cause pandemics. As indicators for sensing the dynamic changes of viral genes, these higher order structures have been the focus of attention in the field of virology. However, the size of the viral gene network is usually huge, and searching these structures in the networks introduces unacceptable delay. To mitigate this issue, in this paper, we propose a simple-yet-effective model named HyperSearch based on deep learning to search cavities in a computable complex network for influenza virus genetics. Extensive experiments conducted on a public influenza virus dataset demonstrate the effectiveness of HyperSearch over other advanced deep-learning methods without any elaborated model crafting. Moreover, HyperSearch can finish the search works in minutes while 0-1 programming takes days. Since the proposed method is simple and easy to be transferred to other complex networks, HyperSearch has the potential to facilitate the monitoring of dynamic changes in viral genes and help humans keep up with the pace of virus mutations.Comment: work in progres

Nanostructured Oxygen Sensor - Using Micelles to Incorporate a Hydrophobic Platinum Porphyrin

Hydrophobic platinum(II)-5,10,15,20-tetrakis-(2,3,4,5,6-pentafluorophenyl)-porphyrin (PtTFPP) was physically incorporated into micelles formed from poly(ε-caprolactone)-block-poly(ethylene glycol) to enable the application of PtTFPP in aqueous solution. Micelles were characterized using dynamic light scattering (DLS) and atomic force microscopy (AFM) to show an average diameter of about 140 nm. PtTFPP showed higher quantum efficiency in micellar solution than in tetrahydrofuran (THF) and dichloromethane (CH2Cl2). PtTFPP in micelles also exhibited higher photostability than that of PtTFPP suspended in water. PtTFPP in micelles exhibited good oxygen sensitivity and response time. This study provided an efficient approach to enable the application of hydrophobic oxygen sensors in a biological environment

NetMoST: A network-based machine learning approach for subtyping schizophrenia using polygenic SNP allele biomarkers

Subtyping neuropsychiatric disorders like schizophrenia is essential for improving the diagnosis and treatment of complex diseases. Subtyping schizophrenia is challenging because it is polygenic and genetically heterogeneous, rendering the standard symptom-based diagnosis often unreliable and unrepeatable. We developed a novel network-based machine-learning approach, netMoST, to subtyping psychiatric disorders. NetMoST identifies polygenic risk SNP-allele modules from genome-wide genotyping data as polygenic haplotype biomarkers (PHBs) for disease subtyping. We applied netMoST to subtype a cohort of schizophrenia subjects into three distinct biotypes with differentiable genetic, neuroimaging and functional characteristics. The PHBs of the first biotype (36.9% of all patients) were related to neurodevelopment and cognition, the PHBs of the second biotype (28.4%) were enriched for neuroimmune functions, and the PHBs of the third biotype (34.7%) were associated with the transport of calcium ions and neurotransmitters. Neuroimaging patterns provided additional support to the new biotypes, with unique regional homogeneity (ReHo) patterns observed in the brains of each biotype compared with healthy controls. Our findings demonstrated netMoST's capability for uncovering novel biotypes of complex diseases such as schizophrenia. The results also showed the power of exploring polygenic allelic patterns that transcend the conventional GWAS approaches.Comment: 21 pages,4 figure

A two-dimensional angular-resolved proton spectrometer

We present a novel design of two-dimensional (2D) angular-resolved spectrometer for full beam characterization of ultrashort intense laser driven proton sources. A rotated 2D pinhole array was employed, as selective entrance before a pair of parallel permanent magnets, to sample the full proton beam into discrete beamlets. The proton beamlets are subsequently dispersed without overlapping onto a planar detector. Representative experimental result of protons generated from femtosecond intense laser interaction with thin foil target is presented

An image cryptography method by highly error-prone DNA storage channel

Introduction: Rapid development in synthetic technologies has boosted DNA as a potential medium for large-scale data storage. Meanwhile, how to implement data security in the DNA storage system is still an unsolved problem.Methods: In this article, we propose an image encryption method based on the modulation-based storage architecture. The key idea is to take advantage of the unpredictable modulation signals to encrypt images in highly error-prone DNA storage channels.Results and Discussion: Numerical results have demonstrated that our image encryption method is feasible and effective with excellent security against various attacks (statistical, differential, noise, and data loss). When compared with other methods such as the hybridization reactions of DNA molecules, the proposed method is more reliable and feasible for large-scale applications

A flexible, on-line magnetic spectrometer for ultra-intense laser produced fast electron measurement

We have developed an on-line magnetic spectrometer to measure energy distributions of fast electrons generated from ultra-intense laser-solid interactions. The spectrometer consists of a sheet of plastic scintillator, a bundle of non-scintillating plastic fibers, and an sCMOS camera recording system. The design advantages include on-line capturing ability, versatility of detection arrangement, and resistance to harsh in-chamber environment. The validity of the instrument was tested experimentally. This spectrometer can be applied to the characterization of fast electron source for understanding fundamental laser-plasma interaction physics and to the optimization of high-repetition-rate laser-driven applications

Immunological Changes in Monocyte Subsets and Their Association With Foxp3+ Regulatory T Cells in HIV-1-Infected Individuals With Syphilis: A Brief Research Report

The incidence of syphilis has increased dramatically in men who have sex with men (MSM), especially those with HIV-1 infection. Treponema pallidum and HIV-1 are bidirectionally synergistic, accelerating disease progression reciprocally in co-infected individuals. We have shown that monocytes have different effects on T helper cells at different stages of HIV-1 infection. However, the immunological changes in the three monocyte subsets and in regulatory T cells (Tregs), and the associations between these cell types during syphilis infection among HIV-1-infected MSM remain unclear. Herein, we used cell staining methods to explore changes in monocyte subsets and Tregs and any associations between these cells. We found that the frequency of classical monocytes was higher in the rapid plasma reagin (RPR+) group than in the healthy controls (HCs) and the chronic HIV-1 infection (CHI) plus RPR+ (CHI&RPR+) group. The frequencies of Foxp3+CD25+CD45RA+ and Foxp3+Helios+CD45RA+ Tregs were significantly higher in the RPR+, CHI, and CHI&RPR+ groups than in HCs, whereas the frequency of CD45RA+ Tregs was lower in the CHI&RPR+ group than in CHI group. The frequencies of Foxp3+CD25+CD45RO+ and Foxp3+Helios+CD45RO+ Tregs were lower in the RPR+, CHI, and CHI&RPR+ groups than in HCs. The frequency of intermediate monocytes was inversely correlated with the frequency of CD45RA+ Tregs and positively correlated with the frequency of CD45RO+ Tregs. These results demonstrate for the first time that intermediate monocytes control the differentiation of Treg subsets in Treponema pallidum/HIV-1 co-infections. These findings provide new insights into an immunological mechanism involving monocytes/Tregs in HIV-infected individuals with syphilis

Micelles as Delivery Vehicles for Oligofluorene for Bioimaging

With the successful development of organic/polymeric light emitting diodes, many organic and polymeric fluorophores with high quantum efficiencies and optical stability were synthesized. However, most of these materials which have excellent optical properties are insoluble in water, limiting their applications in biological fields. Herein, we used micelles formed from an amino-group-containing poly(ε-caprolactone)-block-poly(ethylene glycol) (PCL-b-PEG-NH2) to incorporate a hydrophobic blue emitter oligofluorene (OF) to enable its application in biological conditions. Although OF is completely insoluble in water, it was successfully transferred into aqueous solutions with a good retention of its photophysical properties. OF exhibited a high quantum efficiency of 0.84 in a typical organic solvent of tetrahydrofuran (THF). In addition, OF also showed a good quantum efficiency of 0.46 after being encapsulated into micelles. Two cells lines, human glioblastoma (U87MG) and esophagus premalignant (CP-A), were used to study the cellular internalization of the OF incorporated micelles. Results showed that the hydrophobic OF was located in the cytoplasm, which was confirmed by co-staining the cells with nucleic acid specific SYTO 9, lysosome specific LysoTracker Red®, and mitochondria specific MitoTracker Red. MTT assay indicated non-toxicity of the OF-incorporated micelles. This study will broaden the application of hydrophobic functional organic compounds, oligomers, and polymers with good optical properties to enable their applications in biological research fields