QUAK: A Synthetic Quality Estimation Dataset for Korean-English Neural Machine Translation

With the recent advance in neural machine translation demonstrating its importance, research on quality estimation (QE) has been steadily progressing. QE aims to automatically predict the quality of machine translation (MT) output without reference sentences. Despite its high utility in the real world, there remain several limitations concerning manual QE data creation: inevitably incurred non-trivial costs due to the need for translation experts, and issues with data scaling and language expansion. To tackle these limitations, we present QUAK, a Korean-English synthetic QE dataset generated in a fully automatic manner. This consists of three sub-QUAK datasets QUAK-M, QUAK-P, and QUAK-H, produced through three strategies that are relatively free from language constraints. Since each strategy requires no human effort, which facilitates scalability, we scale our data up to 1.58M for QUAK-P, H and 6.58M for QUAK-M. As an experiment, we quantitatively analyze word-level QE results in various ways while performing statistical analysis. Moreover, we show that datasets scaled in an efficient way also contribute to performance improvements by observing meaningful performance gains in QUAK-M, P when adding data up to 1.58M

Clonal hematopoiesis is associated with risk of severe Covid-19.

Acquired somatic mutations in hematopoietic stem and progenitor cells (clonal hematopoiesis or CH) are associated with advanced age, increased risk of cardiovascular and malignant diseases, and decreased overall survival. These adverse sequelae may be mediated by altered inflammatory profiles observed in patients with CH. A pro-inflammatory immunologic profile is also associated with worse outcomes of certain infections, including SARS-CoV-2 and its associated disease Covid-19. Whether CH predisposes to severe Covid-19 or other infections is unknown. Among 525 individuals with Covid-19 from Memorial Sloan Kettering (MSK) and the Korean Clonal Hematopoiesis (KoCH) consortia, we show that CH is associated with severe Covid-19 outcomes (OR = 1.85, 95%=1.15-2.99, p = 0.01), in particular CH characterized by non-cancer driver mutations (OR = 2.01, 95% CI = 1.15-3.50, p = 0.01). We further explore the relationship between CH and risk of other infections in 14,211 solid tumor patients at MSK. CH is significantly associated with risk of Clostridium Difficile (HR = 2.01, 95% CI: 1.22-3.30, p = 6×10-3) and Streptococcus/Enterococcus infections (HR = 1.56, 95% CI = 1.15-2.13, p = 5×10-3). These findings suggest a relationship between CH and risk of severe infections that warrants further investigation

Synthesis of polyfunctional amines as curing agents and its effect on mechanical property of epoxy polymers

A curing agent is required to cure an epoxy resin, but a few curing agents also improve the mechanical properties of the resin. In addition, it is rare to find hardeners containing multiple amines, which can be used to form high crosslink densities. In this study, two different curing agents with six amine functional groups each were synthesized via a two-step reaction. In the first step, isophorone diamine (IPDI) was reacted with two equivalents of pentaerythritol triacrylate (PETA). The resulting IPDI-PETA2 was reacted with ethylene diamine and 4,4 '-diaminodiphenyl sulfone to form two amine curers with six amines each-IPDI-PETA2-ED (ED) and IPDI-PETA2-DDS (DDS). Both amines were added in varying amounts to an epoxy composition consisting of dicyandiamide and 2-methylimidazole to improve the mechanical properties compared with a reference epoxy composition. Mechanical studies showed that an epoxy composition containing 5% IPDI-PETA2-DDS improved the flexural strength by 34% and impact strength by 36.7%. Furthermore, adding 5% IPDI-PETA2-ED to the epoxy composition increased the flexural strength by 39.7%, to 197 MPa and the impact strength by 38.8% to 68 J/m. These results highlight the potential of curing agents containing multiple amines for improving the mechanical properties of epoxy resins

Effect of Sulfuric Acid Baking and Caustic Digestion on Enhancing the Recovery of Rare Earth Elements from a Refractory Ore

To improve the recovery of rare earth elements (REEs) from a refractory ore, this study investigated two different chemical decomposition methods, namely sulfuric acid baking and caustic digestion, with their respective leaching processes. The studied lateritic ore contained goethite (FeOOH) as a major constituent with REEs scattered around and forming submicron grains of phosphate minerals, such as apatite and monazite. Therefore, despite the substantially high content of REEs (3.4% total rare earth oxide), the normal acidic leaching efficiency of REEs reached only 60–70%. By introducing sulfuric acid baking and caustic digestion, the REE-leaching efficiency was significantly improved. After sulfuric acid baking at 2.0 acid/solid ratio and 200 °C for 2 h, the leaching efficiency reached 97–100% in the subsequent water-leaching. When the ore was digested with a solid/liquid ratio of 100 g/L in a 30 wt% NaOH solution at 115 °C and 300 rpm for 3 h, the REE-leaching efficiency of 99–100% was attained at 80 °C using a 3.0 M HCl solution. The correlation between the REE and the Fe-leaching was determined. The improvements in REE-leaching in both methods were mostly attributed to the mineral phase and crystallinity changes of Fe-bearing minerals due to the ore pretreatments. Such findings were also supported by X-ray diffraction and scanning electron microscopy analyses

Developing an Adaptive Pathway to Mitigate Air Pollution Risk for Vulnerable Groups in South Korea

Air pollution is one of the most significant environmental hazards. The elderly, young, and poor are more vulnerable to air pollution. The risk of air pollution was assessed based on the risk framework published by the Intergovernmental Panel on Climate Change (IPCC) in terms of three aspects: hazard, exposure, and vulnerability. This study determined the concentrations of hazardous pollutants using satellite images from 2015 at 1 km2 spatial resolution. In addition, the study identified vulnerable groups who are exposed to hazardous air pollutants. The study highlighted the degree of vulnerability based on environmental sensitivity and institutional abilities, such as mitigation and social adaption policies, using statistical data. Based on the results, Seoul City and Gyeonggi Province have low air pollution risk owing to good institutional abilities, while the western coastal area has the highest air pollution risk. Three adaption pathway scenarios were assessed in terms of the effect of increases in the budget for social adaptation policies on the level of risk. The study found that the risk can be reduced when the social adaptation budget of 2015 base level is increased by 20% in Gyeonggi Province and by 30% in the western coastal area. In conclusion, this risk assessment can support policy-making to target more vulnerable groups based on scientific evidence and to ensure environmental justice at the national level

TLR7 activation by miR-21 promotes renal fibrosis by activating the pro-inflammatory signaling pathway in tubule epithelial cells

Abstract Background Toll-like receptor 7 (TLR7) is an endosomal TLR activated by single-stranded RNA, including endogenous microRNAs. Although TLR7 is known to promote inflammatory responses in pathophysiological conditions, its role in renal fibrosis has not been investigated. Here, we aim to investigate the inflammatory roles of TLR7 in kidney inflammation and fibrosis. Methods TLR7 knockout mice (Tlr7 −/−) subjected to AD-induced kidney injury were utilized to examine the role of TLR7 in kidney fibrosis. To elucidate the role of TLR7 in renal epithelial cells, NRK52E rat renal tubule epithelial cells were employed. Results Under fibrotic conditions induced by an adenine diet (AD), TLR7 was significantly increased in damaged tubule epithelial cells, where macrophages were highly infiltrated. TLR7 deficiency protected against AD-induced tubular damage, inflammation, and renal fibrosis. Under in vitro conditions, TLR7 activation increased NF-κB activity and induced chemokine expression, whereas TLR7 inhibition effectively blocked NF-κB activation. Furthermore, among the known TLR7 endogenous ligands, miR-21 was significantly upregulated in the tubular epithelial regions. In NRK52E cells, miR-21 treatment induced pro-inflammatory responses, which could be blocked by a TLR7 inhibitor. When the TLR7 inhibitor, M5049, was administered to the AD-induced renal fibrosis model, TLR7 inhibition significantly attenuated AD-induced renal inflammation and fibrosis. Conclusions Overall, activation of TLR7 by endogenous miR-21 in renal epithelial cells contributes to inflammatory responses in a renal fibrosis model, suggesting a possible therapeutic target for the treatment of renal fibrosis. Video Abstrac

Advanced Electron Paramagnetic Resonance Studies of a Ternary Complex of Copper, Amyloid-beta, and a Chemical Regulator

Although there has been extensive effort to develop chemical regulators, progress has been static, in part because of these regulators??? unclear mechanisms. Here, we report using advanced electron paramagnetic resonance (EPR) spectroscopy to obtain the first molecular-level structural information regarding a ternary complex of CuII-amyloid-?? (A??) with a chemical regulator that can specifically modulate Cu-induced A?? aggregation. Our advanced EPR spectroscopic results revealed that a chemical regulator (1) for CuII-A??1-16 disrupted the coordination environment of CuII in A??, resulting in the detachment of the primary amine at the N-terminal and a carbonyl group between Asp1 and Ala2 from the CuII center and the subsequent formation of a ternary complex, chemical regulator-CuII-A??1-16. Therefore, our results demonstrate how a chemical regulator interacts with metal-A?? at the molecular level. These findings provide novel insight into working mechanisms and thereby contribute to the establishment of a rational design for chemical regulators of metal-A?? complexes

Development of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan

Drought is a natural disaster that occurs globally and is a main trigger of secondary environmental and socio-economic damages, such as food insecurity, land degradation, and sand-dust storms. As climate change is being accelerated by human activities and environmental changes, both the severity and uncertainties of drought are increasing. In this study, a diagnostic drought prediction model (DDPM) was developed to reduce the uncertainties caused by environmental diversity at the regional level in Kyrgyzstan, by predicting drought with meteorological forecasts and satellite image diagnosis. The DDPM starts with applying a prognostic drought prediction model (PDPM) to 1) estimate future agricultural drought by explaining its relationship with the standardized precipitation index (SPI), an accumulated precipitation anomaly, and 2) compensate for regional variances, which were not reflected sufficiently in the PDPM, by taking advantage of preciseness in the time-series vegetation condition index (VCI), a satellite-based index representing land surface conditions. Comparing the prediction results with the monitored VCI from June to August, it was found that the DDPM outperformed the PDPM, which exploits only meteorological data, in both spatiotemporal and spatial accuracy. In particular, for June to August, respectively, the results of the DDPM (coefficient of determination [R2] = 0.27, 0.36, and 0.4; root mean squared error [RMSE] = 0.16, 0.13, and 0.13) were more effective in explaining the spatial details of drought severity on a regional scale than those of the PDPM (R2 = 0.09, 0.10, and 0.11; RMSE = 0.17, 0.15, and 0.16). The DDPM revealed the possibility of advanced drought assessment by integrating the earth observation big data comprising meteorological and satellite data. In particular, the advantage of data fusion is expected to be maximized in areas with high land surface heterogeneity or sparse weather stations by providing observational feedback to the PDPM. This research is anticipated to support policymakers and technical officials in establishing effective policies, action plans, and disaster early warning systems to reduce disaster risk and prevent environmental and socio-economic damage

Repurposing a peptide antibiotic as a catalyst: a multicopper–daptomycin complex as a cooperative O–O bond formation and activation catalyst

A peptide antibiotic, daptomycin, was repurposed to a multicopper catalyst presenting cooperative rate enhancement in O–O bond formation and activation reactions. In naturally occurring metalloenzymes, cooperative multimetallic sites activate, cleave, and form dioxygen bonds. Thus, molecular scaffolds providing multimetallic sites are increasingly being exploited to develop cooperative redox catalysts. Herein, we report a multicopper complex based on a peptide antibiotic, daptomycin (dap), which mediates O-O bond formation and activation reactions. In alkaline media, UV-vis and electron paramagnetic resonance (EPR) spectroscopy showed that dap stabilized up to four Cu(ii) ions (Cun-dap, n = 1-4) in a square planar Cu-N4 geometry, with an axially bound H2O or OH ligand. Cooperative rate enhancement was observed for the O2 activation, H2O2 disproportionation, and O2 evolution reactions, only in the presence of the multimetallic Cu complex. In situ Raman spectroscopy was used to study the intermediate species involved in the electrochemical O2 evolution reaction and understand the catalytic mechanism behind the O-O bond formation. The observed Cu-O species related to the Cu2O2 core suggested a possible radical coupling pathway for the O-O bond formation. This study provides a strategy to repurpose natural calcium-binding peptide antibiotics as ligands, to create multimetallic sites for cooperative catalysis. © 2022 The Royal Society of Chemistry.11Nsciescopu

Synergistically enhanced photocatalytic activity of graphitic carbon nitride and WO3 nanohybrids mediated by photo-Fenton reaction and H2O2

The development of solar energy conversion in the production of fuels, water splitting and water purification systems, has become an important sidestep for traditional fossil energy. Herein we have investigated the coupling effect of a Photo-Fenton system on a conventional photocatalytic reaction with a novel Fe-doped C3N4/WO3 hybrid structure. The decomposition of p-nitrophenol was selected as a model reaction in the context of the degradation of organic pollutants. Heterojunction nanocomposites consisting of g-C3N4 nanosheets and WO3 nanoparticles were shown to facilitate the separation of photo-induced electron and hole pairs. The photocatalytic activity was further maximized as a result of a synergism of the ‘Photo-Fenton cycle’ with Fe(II) or Fe(III)-doping in the presence of H2O2 to generate additional hydroxyl radicals. As a result, after 4 h under visible light the degradation of p-nitrophenol could be remarkably enhanced from 10 to 90% compared to the g-C3N4 reference. To the best of our knowledge, this is the first time such a striking increase is reported with a Photo-Fenton system applied in the present photocatalytic system. The significance of the presence of hydroxyl radicals in the photo-Fenton performance of Fe-doped C3N4/WO3 was assessed by scavenger and fluorescence tests. Additional light was shed into the reaction mechanism via spin trapping enabled by in-situ electron paramagnetic resonance