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ENHANCED MOIRÉ TECHNIQUE FOR REMOTE SENSING OF GROUND MOTION INTEGRATING ACTIVE CONVOLVED ILLUMINATION AND DEEP LEARNING
No full textImaging through noisy media is inherently challenging, particularly when the noise stems from dynamic and stochastic environments such as atmospheric turbulence. However, these noisy media are not merely obstacles. If imaging can be achieved effectively under such conditions, it opens the door to transformative applications in remote sensing and free-space optical communication. One domain where this potential is especially critical is the remote sensing of seismic and geophysical activity. Traditional approaches rely on in situ sensors that are often difficult or dangerous to deploy in volatile or inaccessible terrains, such as active volcanic regions. Atmospheric turbulence further complicates long-distance optical imaging, introducing phase and amplitude distortions that degrade measurement fidelity. This dissertation presents a novel Moiré-based remote sensing framework, enhanced with Active Convolved Illumination (ACI) and deep learning techniques, to overcome the challenges posed by atmospheric turbulence in optical propagation. ACI is an optical method that actively mitigates turbulence-induced distortions. When combined with learning-based post-processing, this approach enables high-resolution imaging in remote sensing scenarios. The Moiré-based apparatus, designed specifically for remote ground motion measurement, leverages these techniques to achieve high-fidelity displacement detection over long distances, without the need for physical contact or on-site instrumentation. The proposed methodology provides a robust, scalable, and non-invasive solution for geophysical monitoring in complex and hazardous environments, significantly advancing the capabilities of optical remote sensing under turbulent atmospheric conditions
Coastal Environments: LiDAR Mapping of Copper Tailings Impacts, Particle Retention of Copper, Leaching, and Toxicity
Get PDFTailings generated by mining account for the largest world-wide waste from industrial activities. As an element, copper is relatively uncommon, with low concentrations in sediments and waters, yet is very elevated around mining operations. On the Keweenaw Peninsula of Michigan, USA, jutting out into Lake Superior, 140 mines extracted native copper from the Portage Lake Volcanic Series, part of an intercontinental rift system. Between 1901 and 1932, two mills at Gay (Mohawk, Wolverine) sluiced 22.7 million metric tonnes (MMT) of copper-rich tailings (stamp sands) into Grand (Big) Traverse Bay. About 10 MMT formed a beach that has migrated 7 km from the original Gay pile to the Traverse River Seawall. Another 11 MMT are moving underwater along the coastal shelf, threatening Buffalo Reef, an important lake trout and whitefish breeding ground. Here we use remote sensing techniques to document geospatial environmental impacts and initial phases of remediation. Aerial photos, multiple ALS (crewed aeroplane) LiDAR/MSS surveys, and recent UAS (uncrewed aircraft system) overflights aid comprehensive mapping efforts. Because natural beach quartz and basalt stamp sands are silicates of similar size and density, percentage stamp sand determinations utilise microscopic procedures. Studies show that stamp sand beaches contrast greatly with natural sand beaches in physical, chemical, and biological characteristics. Dispersed stamp sand particles retain copper, and release toxic levels of dissolved concentrations. Moreover, copper leaching is elevated by exposure to high DOC and low pH waters, characteristic of riparian environments. Lab and field toxicity experiments, plus benthic sampling, all confirm serious impacts of tailings on aquatic organisms, supporting stamp sand removal. Not only should mining companies end coastal discharges, we advocate that they should adopt the UNEP “Global Tailings Management Standard for the Mining Industry”
Affinity of MoP (001) and MoP (010) Surfaces toward Nucleobases: A DFT Outlook
No full textThe work presents density functional study of the adsorption of nucleobases, adenine (A), guanine (G), cytosine (C), thymine (T) and uracil (U) on the MoP (001) and (010) surfaces. The results indicate that nucleobases (i.e., G, A, C, T, and U) chemisorb onto the metallic MoP (001) and (010) surfaces with high binding energies. The oxygen-mediated interactions lead to cytosine being strongly chemisorbed on both surfaces. The variation in the structural and electronic properties after the nucleobase adsorption has been assessed in terms of charge transfer, charge density difference, energy band structures, quantum conductance, current-voltage curves, and total density of states plots. While the surfaces retain their metallic character, there is a decrease in quantum conductance as the number of energy bands crossing the Fermi level decreases following nucleobase adsorption. Both pristine and chemisorbed surfaces display ohmic-like conduction in the current-voltage curves; the MoP (010) surface exhibits considerably higher sensitivity for adenine. The findings divulge the promising potential of the MoP (001) and (010) surfaces as biochemical adsorbents for DNA/RNA nucleobases
Revealing the nature of the second branch point in the catalytic mechanism of the Fe(ii)/2OG-dependent ethylene forming enzyme
Get PDFEthylene-forming enzyme (EFE) has economic importance due to its ability to catalyze the formation of ethylene and 3-hydroxypropionate (3HP). Understanding the catalytic mechanism of EFE is essential for optimizing the biological production of these important industrial chemicals. In this study, we implemented molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) to elucidate the pathways leading to ethylene and 3HP formation. Our results suggest that ethylene formation occurs from the propion-3-yl radical intermediate rather than the (2-carboxyethyl)carbonato-Fe(ii) (EFIV) intermediate, which conclusively acts as a precursor for 3HP formation. The results also explain the role of the hydrophobic environment surrounding the 2OG binding site in stabilizing the propion-3-yl radical, which defines their conversion to either ethylene or 3HP. Our simulations on the A198L EFE variant, which produces more 3HP than wild-type (WT) EFE based on experimental observations, predict that the formation of the EFIV intermediate was more favored than WT. Also, MD simulations on the EFIV intermediate in both WT and A198L EFE predicted that the water molecules approach the Fe center, which suggests the role of water molecules in the breakdown of the EFIV intermediate. QM/MM simulations on the EFIV intermediate of WT and A198L EFE predicted that the Fe-bound water molecule could provide a proton for the 3HP formation from EFIV. The study underscores the critical influence of the enzyme\u27s hydrophobic environment and second coordination sphere residues in determining product distribution between ethylene and 3HP. These mechanistic insights lay a foundation for targeted enzyme engineering, aiming to improve the selectivity and catalytic efficiency of EFE in biological ethylene and 3HP production
Flipping out: Role of arginine in hydrophobic interactions and biological formulation design
Get PDFArginine has been a mainstay in biological formulation development for decades. To date, the way arginine modulates protein stability has been widely studied and debated. Here, we employed a hydrophobic polymer to decouple hydrophobic effects from other interactions relevant to protein folding. While existing hypotheses for the effects of arginine can generally be categorized as either direct or indirect, our results indicate that direct and indirect mechanisms of arginine co-exist and oppose each other. At low concentrations, arginine was observed to stabilize hydrophobic polymer folding via a sidechain-dominated direct mechanism, while at high concentrations, arginine stabilized polymer folding via a backbone-dominated indirect mechanism. Upon introducing partially charged polymer sites, arginine destabilized polymer folding. Further, we found arginine-induced destabilization of a model virus similar to direct-mechanism destabilization of the charged polymer and concentration-dependent stabilization of a model protein similar to the indirect mechanism of hydrophobic polymer stabilization. These findings highlight the modular nature of the widely used additive arginine, with relevance in the information-driven design of stable biological formulations
Advances in Prediction of Posttranslational Modification Sites Known to Localize in Protein Supersecondary Structures
No full textPosttranslational modifications (PTMs) play a crucial role in modulating the structure, function, localization, and interactions of proteins, with many PTMs being localized within supersecondary structures, such as helical pairs. These modifications can significantly influence the conformation and stability of these structures. For instance, phosphorylation introduces negative charges that alter electrostatic interactions, while acetylation or methylation of lysine residues affects the stability and interactions of alpha helices or beta strands. Given the pivotal role of supersecondary structures in the overall protein architecture, their modulation by PTMs is essential for protein functionality. This chapter explores the latest advancements in predicting sites for the five PTMs (phosphorylation, acetylation, glycosylation, methylation, and ubiquitination) known to be localized within supersecondary structures. The chapter highlights the recent advances in the prediction of these PTM sites, including the use of global contextualized embeddings from protein language models, integration of structural information, utilization of reliable positive and negative sites, and application of contrastive learning. These methodologies and emerging trends offer a roadmap for novel innovations in addressing PTM prediction challenges, particularly those linked to supersecondary structures
Biomedically vibrant and cost-effective biocomposite bone plate – development and testing
Get PDFBone fracture treatment requires a supportive structure called, bone plate for a specific period required to heal the fractured bone. Titanium, stainless steel, tantalum etc. are widely used as bone plates. However, these metallic bone plates lead to some major problems namely, stress shielding, bone atrophy, high cost etc. because of their very high strength compared to bones. In addition, the metallic bone plates need secondary surgery to remove it from the body. This research aims to develop a sustainable composite bone plate that is biocompatible, bio-functional, and biodegradable in the human body. Firstly, different composite samples were fabricated using locally available low-cost natural fibers like jute, silk, kenaf, etc. reinforced in epoxy, polypropylene, etc. The materials used are known to be fully/partially biodegradable and environmentally friendly. The hybrid fabrication process like the combination of hand lay-up and compression method was used to fabricate the composite samples. Several tests, e.g. mechanical tests (tensile, flexural, and compression test), cytotoxicity tests, microstructure analysis, moisture absorbability, and biodegradability in simulated body fluid, were performed to investigate the properties of the fabricated composites. The tests were performed following respective ASTM standards. The computational analysis on mechanical properties was also performed by Ansys\u27s finite element analysis module and compared/validated the experimental results. The results revealed that that the kenaf/epoxy composite was non-cytotoxic, bio-functional and partially biodegradable, which could be suitable for bone plate application. Overall, the composite bone plate developed from local resources demonstrates biomedical vibrancy and cost-effectiveness. However, it requires further in-vivo evaluation for clinical trials, which is in the plan for the next study
Unfitted finite element method for the quad-curl interface problem
No full textIn this paper, we introduce a novel unfitted finite element method to solve the quad-curl interface problem. We adapt Nitsche’s method for curlcurl-conforming elements and double the degrees of freedom on interface elements. To ensure stability, we incorporate ghost penalty terms and a discrete divergence-free term. We establish the well-posedness of our method and demonstrate an optimal error bound in the discrete energy norm. We also analyze the stiffness matrix’s condition number. Our numerical tests back up our theory on convergence rates and condition numbers
In-situ electrochemical synthesis of Ni/Ni(OH)2/molecularly imprinted polymer nanocomposite for high-performance glucose detection
No full textThis study presents a novel non-enzymatic glucose sensor that synergistically combines the high catalytic activity of nickel hydroxide (Ni(OH)2) with the selective recognition of molecularly imprinted polymers (MIPs). The sensors were fabricated through an entirely in-situ synthesis directly on the electrode, comprising electrodeposition and oxidation of Ni/Ni(OH)2 nanoparticles and electropolymerization of a glucose-imprinted MIP layer using pyrrole and 3-aminophenyl boronic acid. The integrated MIP layer significantly enhanced selectivity against common interferents while amplifying glucose sensitivity. The resulting sensor demonstrated a high sensitivity of 1802 μA mM−1 cm−2 with a linear range from 0.04 to 2.6 mM. Notably, the sensor exhibited remarkable stability, retaining 97.2 % of its original sensitivity after 6 months of room-temperature storage. To extend the linear range, Nafion coatings at two concentrations were applied, achieving ranges up to 0.04–11.6 mM with adjusted sensitivities. This innovative approach, leveraging MIPs to provide selectivity to electrocatalytic nanomaterials, offers a promising strategy for developing high-performance non-enzymatic sensors for glucose and other biomolecules in diabetes monitoring and beyond
Understanding the Influence of Image Enhancement on Underwater Object Detection: A Quantitative and Qualitative Study
Get PDFUnderwater image enhancement is often perceived as a disadvantageous process to object detection. We propose a novel analysis of the interactions between enhancement and detection, elaborating on the potential of enhancement to improve detection. In particular, we evaluate object detection performance for each individual image rather than across the entire set to allow a direct performance comparison of each image before and after enhancement. This approach enables the generation of unique queries to identify the outperforming and underperforming enhanced images compared to the original images. To accomplish this, we first produce enhanced image sets of the original images using recent image enhancement models. Each enhanced set is then divided into two groups: (1) images that outperform or match the performance of the original images and (2) images that underperform. Subsequently, we create mixed original-enhanced sets by replacing underperforming enhanced images with their corresponding original images. Next, we conduct a detailed analysis by evaluating all generated groups for quality and detection performance attributes. Finally, we perform an overlap analysis between the generated enhanced sets to identify cases where the enhanced images of different enhancement algorithms unanimously outperform, equally perform, or underperform the original images. Our analysis reveals that, when evaluated individually, most enhanced images achieve equal or superior performance compared to their original counterparts. The proposed method uncovers variations in detection performance that are not apparent in a whole set as opposed to a per-image evaluation because the latter reveals that only a small percentage of enhanced images cause an overall negative impact on detection. We also find that over-enhancement may lead to deteriorated object detection performance. Lastly, we note that enhanced images reveal hidden objects that were not annotated due to the low visibility of the original images