Bare-metal stents versus drug-eluting stents in large (≥3.5mm) single coronary artery: Angiographic and clinical outcomes at 6 months

SummaryBackgroundAlthough drug-eluting stents (DES) have been shown to dramatically reduce restenosis and improve the rate of event-free survival in large randomized trials, the benefit of DES appears to be limited to restenosis. In large arteries, it is not clear which type of stent is more superior in angiographic and clinical outcomes between DES and bare-metal stents (BMS). We compared the angiographic and clinical outcomes of DES versus BMS in large arteries (≥3.5mm).MethodTwo hundred and forty patients from March 2002 to March 2007 received stents; 196 patients were treated with DES (44.9% sirolimus-eluting stents; 43.9% paclitaxel-eluting stents; 11.2% zotarolimus-eluting stents) and 44 with cobalt–chromium BMS for single de novo lesions in a large vessel. All subjects received aspirin, clopidogrel, and/or cilostazol as the standard antiplatelet regimen. The angiographic and clinical outcomes were evaluated at 6 months.ResultsFor the baseline characteristics, there were no significant differences between the DES and BMS groups. In addition, for the initially implanted stent there was no difference in the length, stent diameter, and lesion site between the two groups. After 6 months, the follow-up angiogram showed that in-stent diameter restenosis and late loss was more common with BMS than DES (39±21% vs. 19±17%, p=0.007; 1.44±0.83mm vs. 0.62±0.58mm, p=0.009, respectively). However, the target-lesion revascularization/target-vessel revascularization, and total major adverse cardiac events showed no significant differences between the groups (5.3% vs. 3.6%, p=0.62; 5.3% vs. 4.6%, p=0.86, respectively).ConclusionThe DES and cobalt–chromium BMS placed in large coronary arteries showed equally favorable 6-month clinical outcomes, although the 6-month angiographic results appeared more favorable in the DES group than in the BMS group

Nanostructured Spinel Oxides as Bi-functional Electrocatalysts for Rechargeable Metal-Air Batteries

Due to continuously increasing energy demands, particularly with the emergence of electric vehicles (EV), smart energy grids, and portable electronics, advanced energy conversion and storage systems such as fuel-cells and metal-air batteries have drawn tremendous research and industrial attention. Even though the lithium-ion battery technology is the most developed and widely distributed energy device for a wide range of applications, some researchers view its energy density insufficient for fulfilling the ultimate requirements of highly energy intensive applications such as EVs. Recently, zinc-air batteries have re-gained research attention since the initial development in the 1970s due to their remarkably highly energy density and the potential to be electrically rechargeable. However, some technological hurdles such as low charge/discharge energy efficiency, and insufficient cycle stability have hampered commercialization and introduction of rechargeable zinc-air batteries to the market. The mentioned hurdles are currently the main challenges of rechargeable zinc-air battery developed, and they stem from the fact that the reaction kinetics of the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are intrinsically very sluggish. The two are the main electrochemical reactions that govern the charge and discharge processes of a rechargeable metal-air battery at the air electrode, and these oxygen reactions must be facilitated by active electrocatalysts in order to progress them at practically viable and stable rates. Currently, the best known catalysts for ORR and OER are carbon supported platinum (Pt/C) and iridium (Ir/C), respectively. However, the use of these precious metal based catalysts for large scale applications like EVs and energy storage systems is prohibitively expensive. Additionally, the durability of these catalysts have been reported to be insufficient for long-term usage under normal device operating conditions. Perhaps most importantly, the precious metal based catalysts are strongly active towards only one of the two oxygen reactions required for rechargeable applications. For example, Pt/C is a strong ORR active catalyst, while Ir/C is a strong OER active catalyst. Recently in the literature, a simple physical mixture of these two catalysts have been used to render bi-functionality, but this method is very rudimentary and still requires two separate syntheses for each catalyst. This suggests that future bi-functionally active catalysts must not only be non-precious (inexpensive), but also a single active material capable of catalyzing both ORR and OER over the same active surface. Having said above, non-precious catalyst research, specifically for bi-functional ORR and OER electrocatalyses, has increased dramatically beginning in the 90’s with a very popular and positive belief in the energy community that rechargeable lithium-air batteries could potentially replace lithium-ion batteries. This wave of interest has also picked up research in rechargeable zinc-air batteries since the electrochemical oxygen reactions that take place at the air electrodes are fundamentally very similar. Additionally, the use of zinc metal as the anode, which is one of Earth’s most abundant elements, and the water-based (aqueous) solutions as the electrolyte (as opposed to organic ones) made the rechargeable zinc-air battery development very attractive and seemingly easy to scale-up. Moreover, primary (non-rechargeable) zinc-air batteries have already been commercialized and are available in the market as hearing aid batteries, leading many researchers to believe that a simple tuning of the current technology would lead to a successful secondary (rechargeable) zinc-air battery development. However, there are a set of technical difficulties specific to rechargeable zinc-air batteries that have slowed the development for the past few decades. Therefore, the work presented in this thesis aims to address the challenges of rechargeable zinc-air batteries particularly from the active bi-functional electrocatalyst standpoint to make them as commercially viable as possible. In the first study, a facile hydrothermal materials synthesis technique has been employed to synthesize a non-precious metal cobalt oxide bi-functional catalyst. Microscopic characterizations have revealed the morphology of this material to be mesoporous hexagonal nanodisks, a high surface area catalyst compared to simple granular nanoparticles which enhances active site exposure and transport of reactants during the electrochemical reactions. This unique nanostructure has been made possible with the addition of surface-active agents that played a role of capping agent, binding to specific crystal faces and allowing growth of cobalt oxide only in certain directions. Additionally, the adsorbed capping agent has been found to leave mesopores on the nanodisks as it decomposes during the heat treatment following the hydrothermal process. Compared to randomly shaped nanoparticle catalyst of the same atomic composition, the mesoporous nanodisks greatly outperformed in terms of both charge and discharge performance of a rechargeable zinc-air battery. In the second study, the bi-functional capabilities of the cobalt oxide catalyst towards the ORR and OER in the first study have been improved by introducing nickel metal substituents into the spinel crystal lattice, as well as adapting a highly conductive nano-structured carbon support. The bi-functional activity enhancements have been attributed to an increase in electrical conductivity of spinel cobalt oxide with the insertion of nickel atoms into specific interstitial sites of the spinel lattice, as well as the high surface area nano-carbon support which helped to disperse the active spinel oxide catalyst and facilitate charge transfer during the electrochemical reactions. In the third study, the effect of nickel and manganese insertion into the spinel cobalt oxide lattice on the bi-functional catalytic activity has been studied more in detail. Spinel oxide catalysts with different atomic compositions, including cobalt oxide (un-doped), nickel cobalt oxide, and manganese cobalt oxide, have been synthesized as nanocrystals that self-assembled into high surface area porous spheres. Based on the electrochemical evaluation, the best overall bi-functional catalytic activity has been observed with nickel-substituted cobalt oxide, while the least has been observed with manganese cobalt oxide, with pristine cobalt oxide in the middle. Interestingly, computational modelling of these catalysts has resulted in the same activity trend, confirming the importance of choosing an appropriate metal substituent depending on the level of bi-functional activity required. In the last study, the knowledge gained from the high surface area nanostructured spinel oxide catalysts has been transferred to the fabrication of active catalyst/current collector assemblies. Specifically, cobalt oxide nanowire array has been directly grown on stainless steel mesh, a typical current collector used for zinc-air batteries. This unique active electrode assembly design greatly simplified battery architecture and the preparation steps required to produce a rechargeable air electrode, which usually involve physical deposition techniques such as spray-coating to deposit as-synthesized catalysts on gas diffusion layers. During this step, catalyst is mixed with ancillary materials such as carbon black and polymer ionomer, which corrode during battery charging. The direct coupling of active cobalt oxide catalyst onto the current collector completely eliminated the use of any additional material, and a gas diffusion layer was simply attached to the active assembly to form a rechargeable air electrode. Without any corrosion, the advanced electrode has demonstrated a remarkable durability during rechargeable zinc-air battery testing, lasting over 600 hours of operation, which has never been reported in the literature. There are still a plenty of opportunities to further leverage the knowledge and experience gained from this thesis work to improve the performance of electrically rechargeable zinc-air batteries. For example, the cobalt oxide nanowire arrays can be doped with other metals such as nickel and manganese to precisely tune the bi-functional catalytic activity depending on specific requirements for the battery application. Also, the idea of high surface area nano-carbon support can be used to fabricate an interfacial layer between the cobalt oxide array and stainless steel mesh to improve charge transfer during the reactions. Graphitized carbon, such as graphene nanosheets and carbon nanotubes, that are stable in rechargeable zinc-air battery conditions are great candidates for this purpose and is likely to significantly improve both the activities of ORR and OER

BlindHarmony: "Blind" Harmonization for MR Images via Flow model

In MRI, images of the same contrast (e.g., T$_1$) from the same subject can exhibit noticeable differences when acquired using different hardware, sequences, or scan parameters. These differences in images create a domain gap that needs to be bridged by a step called image harmonization, to process the images successfully using conventional or deep learning-based image analysis (e.g., segmentation). Several methods, including deep learning-based approaches, have been proposed to achieve image harmonization. However, they often require datasets from multiple domains for deep learning training and may still be unsuccessful when applied to images from unseen domains. To address this limitation, we propose a novel concept called `Blind Harmonization', which utilizes only target domain data for training but still has the capability to harmonize images from unseen domains. For the implementation of blind harmonization, we developed BlindHarmony using an unconditional flow model trained on target domain data. The harmonized image is optimized to have a correlation with the input source domain image while ensuring that the latent vector of the flow model is close to the center of the Gaussian distribution. BlindHarmony was evaluated on both simulated and real datasets and compared to conventional methods. BlindHarmony demonstrated noticeable performance on both datasets, highlighting its potential for future use in clinical settings. The source code is available at: https://github.com/SNU-LIST/BlindHarmonyComment: ICCV 2023 accepted. 9 pages and 5 Figures for manuscipt, supplementary include

Dynamic biospeckle analysis, a new tool for the fast screening of plant nematicide selectivity

Background: Plant feeding, free-living nematodes cause extensive damage to plant roots by direct feeding and, in the case of some trichodorid and longidorid species, through the transmission of viruses. Developing more environmentally friendly, target-specific nematicides is currently impeded by slow and laborious methods of toxicity testing. Here, we developed a bioactivity assay based on the dynamics of light 'speckle' generated by living cells and we demonstrate its application by assessing chemicals' toxicity to different nematode trophic groups.Results: Free-living nematode populations extracted from soil were exposed to methanol and phenyl isothiocyanate (PEITC). Biospeckle analysis revealed differing behavioural responses as a function of nematode feeding groups. Trichodorus nematodes were less sensitive than were bacterial feeding nematodes or non-trichodorid plant feeding nematodes. Following 24 h of exposure to PEITC, bioactivity significantly decreased for plant and bacterial feeders but not for Trichodorus nematodes. Decreases in movement for plant and bacterial feeders in the presence of PEITC also led to measurable changes to the morphology of biospeckle patterns.Conclusions: Biospeckle analysis can be used to accelerate the screening of nematode bioactivity, thereby providing a fast way of testing the specificity of potential nematicidal compounds. With nematodes' distinctive movement and activity levels being visible in the biospeckle pattern, the technique has potential to screen the behavioural responses of diverse trophic nematode communities. The method discriminates both behavioural responses, morphological traits and activity levels and hence could be used to assess the specificity of nematicidal compounds.</p

BeyondScene: Higher-Resolution Human-Centric Scene Generation With Pretrained Diffusion

Generating higher-resolution human-centric scenes with details and controls remains a challenge for existing text-to-image diffusion models. This challenge stems from limited training image size, text encoder capacity (limited tokens), and the inherent difficulty of generating complex scenes involving multiple humans. While current methods attempted to address training size limit only, they often yielded human-centric scenes with severe artifacts. We propose BeyondScene, a novel framework that overcomes prior limitations, generating exquisite higher-resolution (over 8K) human-centric scenes with exceptional text-image correspondence and naturalness using existing pretrained diffusion models. BeyondScene employs a staged and hierarchical approach to initially generate a detailed base image focusing on crucial elements in instance creation for multiple humans and detailed descriptions beyond token limit of diffusion model, and then to seamlessly convert the base image to a higher-resolution output, exceeding training image size and incorporating details aware of text and instances via our novel instance-aware hierarchical enlargement process that consists of our proposed high-frequency injected forward diffusion and adaptive joint diffusion. BeyondScene surpasses existing methods in terms of correspondence with detailed text descriptions and naturalness, paving the way for advanced applications in higher-resolution human-centric scene creation beyond the capacity of pretrained diffusion models without costly retraining. Project page: https://janeyeon.github.io/beyond-scene.Comment: Project page: https://janeyeon.github.io/beyond-scen

Detailed Human-Centric Text Description-Driven Large Scene Synthesis

Text-driven large scene image synthesis has made significant progress with diffusion models, but controlling it is challenging. While using additional spatial controls with corresponding texts has improved the controllability of large scene synthesis, it is still challenging to faithfully reflect detailed text descriptions without user-provided controls. Here, we propose DetText2Scene, a novel text-driven large-scale image synthesis with high faithfulness, controllability, and naturalness in a global context for the detailed human-centric text description. Our DetText2Scene consists of 1) hierarchical keypoint-box layout generation from the detailed description by leveraging large language model (LLM), 2) view-wise conditioned joint diffusion process to synthesize a large scene from the given detailed text with LLM-generated grounded keypoint-box layout and 3) pixel perturbation-based pyramidal interpolation to progressively refine the large scene for global coherence. Our DetText2Scene significantly outperforms prior arts in text-to-large scene synthesis qualitatively and quantitatively, demonstrating strong faithfulness with detailed descriptions, superior controllability, and excellent naturalness in a global context

Characterization of Magnetron Sputtered BiTe-Based Thermoelectric Thin Films

Thermoelectric (TE) technology attracts much attention due to the fact it can convert thermal energy into electricity and vice versa. Thin-film TE materials can be synthesized on different kinds of substrates, which offer the possibility of the control of microstructure and composition to higher TE power, as well as the development of novel TE devices meeting flexible and miniature requirements. In this work, we use magnetron sputtering to deposit N-type and P-type BiTe-based thin films on silicon, glass, and Kapton HN polyimide foil. Their morphology, microstructure, and phase constituents are studied by SEM/EDX, XRD, and TEM. The electrical conductivity, thermal conductivity, and Seebeck coefficient of the thin film are measured by a special in-plane advanced test system. The output of electrical power (open-circuit voltage and electric current) of the thin film is measured by an in-house apparatus at different temperature gradient. The impact of deposition parameters and the thickness, width, and length of the thin film on the power output are also investigated for optimizing the thin-film flexible TE device to harvest thermal energy

Prediction model of intention to use digital fitness services for health promotion during the COVID-19 pandemic: a gender-based multi-group analysis

As the number of people infected with COVID-19 in Korea is increasing, several measures have been implemented to gradually restrict outdoor activities and indoor gatherings while promoting a non-face-to-face social culture. In this study, we performed a gender-based multi-group analysis using a technology acceptance model (TAM) as an external variable for COVID-19 risk perception to verify the model’s predictive ability to increase participation behavior toward digital fitness services. We analyzed the data of 433 Koreans using an online survey consisting of 23 items. A structural equation model was used to verify the perceived ease of use (PEOU), perceived usefulness (PU), intention to use and exercise participation behavior of the TAM with COVID-19 risk perception as an external variable. First, our results showed that COVID-19 risk perception had a statistically higher significant and positive effect on PEOU (β = 0.170, t = 3.296, p < 0.001) than on PU (β = 0.130, t = 2.848, p = 0.004) of digital fitness services. Second, the PEOU of the digital fitness service was found to have a statistically higher significant positive effect on PU (β = 0.512, t = 9.728, p < 0.001) than on intention to use (β = 0.130, t = −2.774, p = 0.006). Third, the PU of digital fitness services was found to have a statistically significant positive effect on the intention to use (β = 0.684, t = 12.909, p < 0.001). Fourth, the intention to use the digital fitness service was found to have a statistically significant positive effect on exercise participation behavior (β = 0.796, t = 16.248, p < 0.001). Lastly, we observed a significant difference between men and women in COVID-19 risk perception and PEOU among the six paths established. Digital environments that encourage participation in exercises could promote health during a pandemic. This study highlighted the need to consider digital environments that encourage exercise participation in creating physical exercise contents as there was no significant difference in the intention to use digital fitness services between men and women

A note on comonotonicity and positivity of the control components of decoupled quadratic FBSDE

In this small note we are concerned with the solution of Forward-Backward Stochastic Differential Equations (FBSDE) with drivers that grow quadratically in the control component (quadratic growth FBSDE or qgFBSDE). The main theorem is a comparison result that allows comparing componentwise the signs of the control processes of two different qgFBSDE. As a byproduct one obtains conditions that allow establishing the positivity of the control process.Comment: accepted for publicatio