Novel OTEC Cycle Using Efficiency Enhancer

The ocean thermal energy conversion (OTEC) plant is designed to improve the efficiency of the existing plants. Various researches are being conducted to increase the plant’s efficiency and output with the use of an enhancer, and studies for performance improvement are also in progress from the Kalina and Uehara cycles to ejector pump OTEC (EP-OTEC). Their performance can be improved by increasing the evaporation pressure using an unused heat source and reducing the heat consumption using a reheating system and a regenerator. In the case of EP-OTEC, an ejector is installed near the turbine-exit to reduce the pressure and therefore increase the power output. In simulations and experiments conducted in this study, EP-OTEC showed 38% efficiency improvement from the basic cycle, which is due to the power output volume increase. The optimum ratio was derived by adjusting the pressure ratio. The demonstration plant to be developed in the future is expected to be applied to the high-efficiency OTEC demonstration plant with improved performance, and new technologies will be continuously developed considering economics and commercial viability

Addressing Negative Transfer in Diffusion Models

Diffusion-based generative models have achieved remarkable success in various domains. It trains a model on denoising tasks that encompass different noise levels simultaneously, representing a form of multi-task learning (MTL). However, analyzing and improving diffusion models from an MTL perspective remains under-explored. In particular, MTL can sometimes lead to the well-known phenomenon of $\textit{negative transfer}$, which results in the performance degradation of certain tasks due to conflicts between tasks. In this paper, we aim to analyze diffusion training from an MTL standpoint, presenting two key observations: $\textbf{(O1)}$ the task affinity between denoising tasks diminishes as the gap between noise levels widens, and $\textbf{(O2)}$ negative transfer can arise even in the context of diffusion training. Building upon these observations, our objective is to enhance diffusion training by mitigating negative transfer. To achieve this, we propose leveraging existing MTL methods, but the presence of a huge number of denoising tasks makes this computationally expensive to calculate the necessary per-task loss or gradient. To address this challenge, we propose clustering the denoising tasks into small task clusters and applying MTL methods to them. Specifically, based on $\textbf{(O2)}$, we employ interval clustering to enforce temporal proximity among denoising tasks within clusters. We show that interval clustering can be solved with dynamic programming and utilize signal-to-noise ratio, timestep, and task affinity for clustering objectives. Through this, our approach addresses the issue of negative transfer in diffusion models by allowing for efficient computation of MTL methods. We validate the proposed clustering and its integration with MTL methods through various experiments, demonstrating improved sample quality of diffusion models.Comment: 22 pages, 12 figures, under revie

Towards Practical Plug-and-Play Diffusion Models

Diffusion-based generative models have achieved remarkable success in image generation. Their guidance formulation allows an external model to plug-and-play control the generation process for various tasks without fine-tuning the diffusion model. However, the direct use of publicly available off-the-shelf models for guidance fails due to their poor performance on noisy inputs. For that, the existing practice is to fine-tune the guidance models with labeled data corrupted with noises. In this paper, we argue that this practice has limitations in two aspects: (1) performing on inputs with extremely various noises is too hard for a single model; (2) collecting labeled datasets hinders scaling up for various tasks. To tackle the limitations, we propose a novel strategy that leverages multiple experts where each expert is specialized in a particular noise range and guides the reverse process at its corresponding timesteps. However, as it is infeasible to manage multiple networks and utilize labeled data, we present a practical guidance framework termed Practical Plug-And-Play (PPAP), which leverages parameter-efficient fine-tuning and data-free knowledge transfer. We exhaustively conduct ImageNet class conditional generation experiments to show that our method can successfully guide diffusion with small trainable parameters and no labeled data. Finally, we show that image classifiers, depth estimators, and semantic segmentation models can guide publicly available GLIDE through our framework in a plug-and-play manner

Monitoring daily evapotranspiration in Northeast Asia using MODIS and a regional Land Data Assimilation System

We applied an approach for daily estimation and monitoring of evapotranspiration (ET) over the Northeast Asia monsoon region using satellite remote sensing observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Frequent cloud cover results in a substantial loss of remote sensing information, limiting the capability of continuous ET monitoring for the monsoon region. Accordingly, we applied and evaluated a stand-alone MODIS ET algorithm for representative regional ecosystem types and an alternative algorithm to facilitate continuous regional ET estimates using surface meteorological inputs from the Korea Land Data Assimilation System (KLDAS) in addition to MODIS land products. The resulting ET calculations showed generally favorable agreement (root-mean-square error  \u3c 1.3 mm d−1) with respect to in situ measurements from eight regional flux tower sites. The estimated mean annual ET for 3 years (2006 to 2008) was approximately 362.0 ± 161.5 mm yr−1 over the Northeast Asia domain. In general, the MODIS and KLDAS-based ET (MODIS-KLDAS ET) results showed favorable performance when compared to tower observations, though the results were overestimated for a forest site by approximately 39.5% and underestimated for a cropland site in South Korea by 0.8%. The MODIS-KLDAS ET data were generally underestimated relative to the MODIS (MOD16) operational global terrestrial ET product for various biome types, excluding cropland; however, MODIS-KLDAS ET showed better agreement than MOD16 ET for forest and cropland sites in South Korea. Our results indicate that MODIS ET estimates are feasible but are limited by satellite optical-infrared remote sensing constraints over cloudy regions, whereas alternative ET estimates using continuous meteorological inputs from operational regional climate systems (e.g., KLDAS) provide accurate ET results and continuous monitoring capability under all-sky conditions

Hepatitis C Virus Induces E6AP-Dependent Degradation of the Retinoblastoma Protein

Hepatitis C virus (HCV) is a positive-strand RNA virus that frequently causes persistent infections and is uniquely associated with the development of hepatocellular carcinoma. While the mechanism(s) by which the virus promotes cancer are poorly defined, previous studies indicate that the HCV RNA-dependent RNA polymerase, nonstructural protein 5B (NS5B), forms a complex with the retinoblastoma tumor suppressor protein (pRb), targeting it for degradation, activating E2F-responsive promoters, and stimulating cellular proliferation. Here, we describe the mechanism underlying pRb regulation by HCV and its relevance to HCV infection. We show that the abundance of pRb is strongly downregulated, and its normal nuclear localization altered to include a major cytoplasmic component, following infection of cultured hepatoma cells with either genotype 1a or 2a HCV. We further demonstrate that this is due to NS5B-dependent ubiquitination of pRb and its subsequent degradation via the proteasome. The NS5B-dependent ubiquitination of pRb requires the ubiquitin ligase activity of E6-associated protein (E6AP), as pRb abundance was restored by siRNA knockdown of E6AP or overexpression of a dominant-negative E6AP mutant in cells containing HCV RNA replicons. E6AP also forms a complex with pRb in an NS5B-dependent manner. These findings suggest a novel mechanism for the regulation of pRb in which the HCV NS5B protein traps pRb in the cytoplasm, and subsequently recruits E6AP to this complex in a process that leads to the ubiquitination of pRb. The disruption of pRb/E2F regulatory pathways in cells infected with HCV is likely to promote hepatocellular proliferation and chromosomal instability, factors important for the development of liver cancer

Ketoamide Resistance and Hepatitis C Virus Fitness in Val55 Variants of the NS3 Serine Protease

ABSTRACT Drug-resistant viral variants are a major issue in the use of direct-acting antiviral agents in chronic hepatitis C. Ketoamides are potent inhibitors of the NS3 protease, with V55A identified as mutation associated with resistance to boceprevir. Underlying molecular mechanisms are only partially understood. We applied a comprehensive sequence analysis to characterize the natural variability at Val55 within dominant worldwide patient strains. A residue-interaction network and molecular dynamics simulation were applied to identify mechanisms for ketoamide resistance and viral fitness in Val55 variants. An infectious H77S.3 cell culture system was used for variant phenotype characterization. We measured antiviral 50% effective concentration (EC 50 ) and fold changes, as well as RNA replication and infectious virus yields from viral RNAs containing variants. Val55 was found highly conserved throughout all hepatitis C virus (HCV) genotypes. The conservative V55A and V55I variants were identified from HCV genotype 1a strains with no variants in genotype 1b. Topology measures from a residue-interaction network of the protease structure suggest a potential Val55 key role for modulation of molecular changes in the protease ligand-binding site. Molecular dynamics showed variants with constricted binding pockets and a loss of H-bonded interactions upon boceprevir binding to the variant proteases. These effects might explain low-level boceprevir resistance in the V55A variant, as well as the Val55 variant, reduced RNA replication capacity. Higher structural flexibility was found in the wild-type protease, whereas variants showed lower flexibility. Reduced structural flexibility could impact the Val55 variant's ability to adapt for NS3 domain-domain interaction and might explain the virus yield drop observed in variant strains

Next-generation sequencing analysis of hepatitis C virus resistance–associated substitutions in direct-acting antiviral failure in South Korea

Background/Aims We used next-generation sequencing (NGS) to analyze resistance-associated substitutions (RASs) and retreatment outcomes in patients with chronic hepatitis C virus (HCV) infection who failed direct-acting antiviral agent (DAA) treatment in South Korea. Methods Using prospectively collected data from the Korean HCV cohort study, we recruited 36 patients who failed DAA treatment in 10 centers between 2007 and 2020; 29 blood samples were available from 24 patients. RASs were analyzed using NGS. Results RASs were analyzed for 13 patients with genotype 1b, 10 with genotype 2, and one with genotype 3a. The unsuccessful DAA regimens were daclatasvir+asunaprevir (n=11), sofosbuvir+ribavirin (n=9), ledipasvir/sofosbuvir (n=3), and glecaprevir/pibrentasvir (n=1). In the patients with genotype 1b, NS3, NS5A, and NS5B RASs were detected in eight, seven, and seven of 10 patients at baseline and in four, six, and two of six patients after DAA failure, respectively. Among the 10 patients with genotype 2, the only baseline RAS was NS3 Y56F, which was detected in one patient. NS5A F28C was detected after DAA failure in a patient with genotype 2 infection who was erroneously treated with daclatasvir+asunaprevir. After retreatment, 16 patients had a 100% sustained virological response rate. Conclusions NS3 and NS5A RASs were commonly present at baseline, and there was an increasing trend of NS5A RASs after failed DAA treatment in genotype 1b. However, RASs were rarely present in patients with genotype 2 who were treated with sofosbuvir+ribavirin. Despite baseline or treatment-emergent RASs, retreatment with pan-genotypic DAA was highly successful in Korea, so we encourage active retreatment after unsuccessful DAA treatment

Loss of immune escape mutations during persistent HCV infection in pregnancy enhances replication of vertically transmitted viruses

Globally, about 1% of pregnant women are persistently infected with the hepatitis C virus (HCV)1. Vertical transmission occurs in 3–5% of cases2 and accounts for most new childhood HCV infections1,3. HCV-specific CD8+ cytotoxic T-lymphocytes (CTLs) play a vital role in the clearance of acute infections4–6, but in the 60–80% of infections that persist these cells become functionally exhausted or select mutant viruses that escape T-cell recognition7–9. Increased HCV replication during pregnancy10,11 suggests that maternofetal immune tolerance mechanisms12 may further impair HCV-specific CTLs, limiting their selection pressure on persistent viruses. To assess this possibility, we characterized the circulating viral quasispecies during and after consecutive pregnancies. This revealed a loss of some escape mutations in class I epitopes in pregnancy associated with emergence of more fit viruses13. CTL selection pressure was reimposed after childbirth, when escape mutations in these epitopes again predominated in the quasispecies and viral load dropped sharply14. Importantly, viruses transmitted perinatally were those with enhanced fitness due to reversion of escape mutations. Our findings indicate that immunoregulatory changes of pregnancy reduce CTL selection pressure on HCV class I epitopes, thereby facilitating vertical transmission of viruses with optimized replicative fitness

The value of diffusion-weighted imaging in assessing the ADC changes of tissues adjacent to breast carcinoma

<p>Abstract</p> <p>Background</p> <p>To define a threshold value of apparent diffusion coefficient (ADC) with which malignant breast lesions can be distinguished from benign lesions, and to evaluate the ADC change of peri-tumor tissue in breast carcinoma by echo planar-diffusion weighted imaging (EPI-DWI).</p> <p>Methods</p> <p>57 breast lesions were scanned by routine MRI and EPI-DWI. The ADC values were compared between malignant and benign lesions. The sensitivity and specificity of EPI-DWI and the threshold ADC value were evaluated by Receiver Operating Characteristic curve (ROC). The ADC values of malignant lesion and layered peri-tumor tissues (from innermost layer 1 to outermost layer 4 with 5 mm every layer) in different directions were compared and the ADC values among different layers were compared.</p> <p>Results</p> <p>The ADC value of 35 malignant lesions was statistically lower than that of 22 benign lesions (P < 0.05). In ROC curve, the threshold value was 1.24 +/- 0.25*10E-3 mm²/s (b = 500) or 1.20 +/- 0.25*10E-3 mm²/s (b = 1000). The ADC value of malignant lesions was statistically lower than that of peri-tumor tissues in different directions (P < 0.05). For peri-tumor tissues, the ADC values increased gradually from layer 1 to layer 4 and there was a significant difference between the ADC values of layer 1 and layer 2 (P < 0.05); while from layer 2 outwards, there was no statistical difference among different layers.</p> <p>Conclusion</p> <p>ADC value was a sensitive and specific parameter that could help to differentiate benign and malignant breast lesions. ADC changes in tissues adjacent to breast carcinoma could be detected by EPI-DWI, which made EPI-DWI a promising method for helping to determine surgical scope of breast carcinoma.</p