Performance-based design prodedure for a novel semi-active cladding connection applied to blast mitigation

ABSTRACT Cladding systems are conventionally designed to provide buildings with environmental protection against wind, temperature, humidity, moisture, etc. Recently, researchers have proposed to leverage these systems to provide additional protection against manmade (e.g., bombs) and natural (e.g., earthquakes, hurricanes) hazards. This can be achieved, for example, by redesigning the connection cladding-structure to provide energy dissipation capabilities. While promising, these strategies are typically effective against single types of hazards. Here, we propose to utilize a novel semi-active damping system connecting cladding to the structure. This system is based on a variable friction mechanism. By varying the normal force applied on the friction plates through a system of moving toggles, it is possible to mitigate vibrations over a wide frequency range, therefore making it useful to mitigate different types of hazards, or multi-hazards. In a passive mode, i.e. unactuated, the device is designed to provide very high stiffness and friction resistance to provide blast mitigation capabilities. The objective of this thesis is to enable a holistic integration of such device within the structural design process by developing performance-based design procedures. The study will focus on the passive mode of the device, which will provide a stepping stone for the development of performance-based design procedures for its semi-active, i.e. actuated, capabilities. The proposed performance-based design procedure consists of: 1) determining the design performance criteria, including the blast properties and allowable distance cladding-structure; 2) selecting design properties for the cladding connection, including stiffness and damping; and 3) designing the impact rubber located between the structure and the cladding in order to prevent the cladding from impacting the structure. In this work, we first describe the novel semi-active device in the context of cladding systems designed for blast resistance. It is followed by a description of the proposed performance-based design procedure, which includes the derivation of different models to simply the derivation of key equations. These equations are then used to provide design guidance. The proposed design procedures are verified and validated on a single degree-of-freedom model, on a two degree-of-freedoms model, and on a realistic four stories structure. Results show that the design methodology can be applied for the semi-active connection utilized in a passive mode against blast load

The double contravariant powerset monad in the Goguen category of fuzzy sets

A monad is constructed in the Goguen category of fuzzy sets valued in a unital quantale, which is an analog of the double contravariant powerset monad in the category of sets. With help of this monad it is proved that the Goguen category of fuzzy sets is dually monadic over itself.Comment: 21 page

Label-Free Optical Imaging of Chromophores and Genome Analysis at the Single Cell Level

Since the emergence of biology as a quantitative science in the past century, a lot of biological discoveries have been driven by milestone technical advances such as X-ray crystallography, fluorescence microscopy and high-throughput sequencing. Fluorescence microscopy is widely used to explore the nanoscale cellular world because of its superb sensitivity and spatial resolution. However, many species (e.g. lipids, small proteins) are non-fluorescent and are difficult to label without disturbing their native functions. In the first part of the dissertation, we explore using three different contrast mechanisms for label-free imaging of these species – absorption and stimulated emission (Chapter 2), heat generation and diffusion (Chapter 3) and nonlinear scattering (Chapter 4). We demonstrate label-free imaging of blood vessels, cytochromes, drugs for photodynamic therapy, and muscle and brain tissues with three dimensional optical sectioning capability. With the rapid development of high throughput genotyping techniques, genome analysis is currently routinely done genome-wide with single nucleotide resolution. However, a large amount of starting materials are often required for whole genome analysis. The dynamic changes in DNA molecules generate intra-sample heterogeneity. Even with the same genome content, different cells often have very different transcriptome profiles in a functional organism. Such intra-sample heterogeneities in the genome and transcriptome are often masked by ensemble analysis. In this second part of the dissertation, we first introduce a whole genome amplification method with high coverage in sequencing single human cells (Chapter 6). We then use the technique to study meiotic recombinations in sperm cells from an individual (Chapter 7). We further develop a technique that enables digital counting of genome fragments and whole genome haplotyping in single cells (Chapter 8). And we introduce our ongoing efforts on single cell transcriptome analysis (Chapter 9). In the end, we introduce our initial effort in exploring the genome accessibility at the single cell level (Chapter 9). Through the development of techniques probing the single cell genome, transcriptome and possibly epigenome, we hope to provide a toolbox for studying biological processes with genome-wide and single cell resolution.Chemistry and Chemical Biolog

MoEController: Instruction-based Arbitrary Image Manipulation with Mixture-of-Expert Controllers

Diffusion-model-based text-guided image generation has recently made astounding progress, producing fascinating results in open-domain image manipulation tasks. Few models, however, currently have complete zero-shot capabilities for both global and local image editing due to the complexity and diversity of image manipulation tasks. In this work, we propose a method with a mixture-of-expert (MOE) controllers to align the text-guided capacity of diffusion models with different kinds of human instructions, enabling our model to handle various open-domain image manipulation tasks with natural language instructions. First, we use large language models (ChatGPT) and conditional image synthesis models (ControlNet) to generate a large number of global image transfer dataset in addition to the instruction-based local image editing dataset. Then, using an MOE technique and task-specific adaptation training on a large-scale dataset, our conditional diffusion model can edit images globally and locally. Extensive experiments demonstrate that our approach performs surprisingly well on various image manipulation tasks when dealing with open-domain images and arbitrary human instructions. Please refer to our project page: [https://oppo-mente-lab.github.io/moe_controller/]Comment: 5 pages,6 figure

GIS-based Economic Cost Estimation of Traffic Accidents in St. Louis, Missouri

AbstractThe economic loss due to total traffic accidents in St. Louis remains high every year. This paper presents an effective approach to spatially identifying potential casualty areas and their economic losses. In this study, five years of traffic accident data, from 2007 to 2011, collected in the City of St. Louis and the adjacent counties, is used. Using Geographic Information System (GIS)-based techniques, e.g. Kernel Density Estimation (KDE), two maps are generated and compared: 1) traffic accident rate map based on the number of traffic accidents per year and 2) the economic costs map. The locations with high economic costs but with low accident rates are identified and shown in a 3-D visualization format. The results can be used as a foundation for the traffic accident cost estimation related research and serves as a guideline for practitioners to investigate the areas with high traffic accident severity levels

Pharmaceutical approaches for COVID-19: An update on current therapeutic opportunities

SARS-CoV-2, a newly discovered coronavirus, has been linked to the COVID-19 pandemic and is currently an important public health issue. Despite all the work done to date around the world, there is still no viable treatment for COVID-19. This study examined the most recent evidence on the efficacy and safety of several therapeutic options available including natural substances, synthetic drugs and vaccines in the treatment of COVID-19. Various natural compounds such as sarsapogenin, lycorine, biscoclaurine, vitamin B12, glycyrrhizic acid, riboflavin, resveratrol and kaempferol, various vaccines and drugs such as AZD1222, mRNA-1273, BNT162b2, Sputnik V, and remdesivir, lopinavir, favipiravir, darunavir, oseltamivir, and umifenovir, resp., have been discussed comprehensively. We attempted to provide exhaustive information regarding the various prospective therapeutic approaches available in order to assist researchers and physicians in treating COVID-19 patients

Coherent Nonlinear Optical Imaging: Beyond Fluorescence Microscopy

The quest for ultrahigh detection sensitivity with spectroscopic contrasts other than fluorescence has led to various novel approaches to optical microscopy of biological systems. Coherent nonlinear optical imaging, especially the recently developed nonlinear dissipation microscopy (including stimulated Raman scattering and two-photon absorption) and pump-probe microscopy (including excited-state absorption, stimulated emission, and ground-state depletion), provides new image contrasts for nonfluorescent species. Thanks to the high-frequency modulation transfer scheme, these imaging techniques exhibit superb detection sensitivity. By directly interrogating vibrational and/or electronic energy levels of molecules, they offer high molecular specificity. Here we review the underlying principles and excitation and detection schemes, as well as exemplary biomedical applications of this emerging class of molecular imaging techniques.Chemistry and Chemical Biolog