Changes in Fire Weather Climatology Under 1.5 ◦C and 2.0 ◦C Warming

The 2015 Paris Agreement led to a number of studies that assessed the impact of the 1.5 ◦C and 2.0 ◦C increases in global temperature over preindustrial levels. However, those assessments have not actively investigated the impact of these levels of warming on fire weather. In view of a recent series of high-profile wildfire events worldwide, we access fire weather sensitivity based on a set of multi-model large ensemble climate simulations for these low-emission scenarios. The results indicate that the half degree difference between these two thresholds may lead to a significantly increased hazard of wildfire in certain parts of the world, particularly the Amazon, African savanna and Mediterranean. Although further experiments focused on human land use are needed to depict future fire activity, considering that rising temperatures are the most influential factor in augmenting the danger of fire weather, limiting global warming to 1.5 ◦C would alleviate some risk in these parts of the world

A Case of Right Sided Aortic Arch Combined with Atrial Septal Defect

Right sided aortic arch is an uncommon congenital anomaly. It can be classified into three types, depending on the left aortic arch's degenerating pattern and the branching pattern of the great vessels. It can be associated with major congenital heart disease, depending on the type of right sided aortic arch. We report a case of an 18-years-old female who has right sided aortic arch with atrial septal defect (ASD). In our case, the patient had a right sided aortic arch and aberrant left subclavian artery, also she had ASD (ostium secundum) and moderate tricuspid regurgitation with pulmonary hypertension. The patient was successfully performed patch closure of ASD and tricuspid valve annuloplasty via midline sternotomy. The patient had uneventful postoperative course

Genetic variations in HMGCR and PCSK9 and kidney function: a Mendelian randomization study

Background The genetically predicted lipid-lowering effect of HMGCR or PCSK9 variant can be used to assess drug proxy effects on kidney function. Methods Mendelian randomization (MR) analysis-identified HMGCR and PCSK9 genetic variants were used to predict the low-density lipoprotein (LDL) cholesterol-lowering effects of medications targeting related molecules. Primary summary-level outcome data for log-estimated glomerular filtration rate (eGFR; creatinine) were provided by the CKDGen Consortium (n = 1,004,040 European) from a meta-analysis of CKDGen and UK Biobank data. We also conducted a separate investigation of summary-level data from CKDGen (n = 567,460, log-eGFR [creatinine]) and UK Biobank (n = 436,581, log-eGFR [cystatin C]) samples. Summary-level MRs using an inverse variance weighted method and pleiotropy-robust methods were performed. Results Summary-level MR analysis indicated that the LDL-lowering effect predicted genetically by HMGCR variants (50-mg/dL decrease) was significantly associated with a decrease in eGFR (–1.67%; 95% confidence interval [CI], –2.20% to –1.13%). Similar significance was found in results from the pleiotropy-robust MR methods when the CKDGen and UK Biobank data were analyzed separately. However, the LDL-lowering effect predicted genetically by PCSK9 variants was significantly associated with an increase in eGFR (+1.17%; 95% CI, 0.10%–2.25%). The results were similarly supported by the weighted median method and in each CKDGen and UK Biobank dataset, but the significance obtained by MR-Egger regression was attenuated. Conclusion Genetically predicted HMG-CoA reductase inhibition was associated with low eGFR, while genetically predicted PCSK9 inhibition was associated with high eGFR. Clinicians should consider that the direct effect of different types of lipid-lowering medication on kidney function can vary

Prevalence of Anti-Ganglioside Antibodies and Their Clinical Correlates with Guillain-Barre Syndrome in Korea: A Nationwide Multicenter Study

Background and Purpose No previous studies have investigated the relationship between various anti-ganglioside antibodies and the clinical characteristics of Guillain-Barre syndrome (GBS) in Korea. The aim of this study was to determine the prevalence and types of anti-ganglioside antibodies in Korean GBS patients, and to identify their clinical significance. Methods Serum was collected from patients during the acute phase of GBS at 20 university-based hospitals in Korea. The clinical and laboratory findings were reviewed and compared with the detected types of anti-ganglioside antibody. Results Among 119 patients, 60 were positive for immunoglobulin G (IgG) or immunoglobulin M antibodies against any type of ganglioside (50%). The most frequent type was IgG anti-GM1 antibody (47%), followed by IgG anti-GT1a (38%), IgG anti-GD1a (25%), and IgG anti-GQ1b (8%) antibodies. Anti-GM1-antibody positivity was strongly correlated with the presence of preceding gastrointestinal infection, absence of sensory symptoms or signs, and absence of cranial nerve involvement. Patients with anti-GD1a antibody were younger, predominantly male, and had more facial nerve involvement than the antibody-negative group. Anti-GT1a-antibody positivity was more frequently associated with bulbar weakness and was highly associated with ophthalmoplegia when coupled with the coexisting anti-GQ1b antibody. Despite the presence of clinical features of acute motor axonal neuropathy (AMAN), 68% of anti-GM1- or anti-GD1a-antibody-positive cases of GBS were diagnosed with acute inflammatory demyelinating polyradiculoneuropathy (AMP) by a single electrophysiological study. Conclusions Anti-ganglioside antibodies were frequently found in the serum of Korean GBS patients, and each antibody was correlated strongly with the various clinical manifestations. Nevertheless, without an anti-ganglioside antibody assay, in Korea AMAN is frequently misdiagnosed as AIDP by single electrophysiological studies.OAIID:oai:osos.snu.ac.kr:snu2014-01/102/0000004487/14SEQ:14PERF_CD:SNU2014-01EVAL_ITEM_CD:102USER_ID:0000004487ADJUST_YN:YEMP_ID:A075641DEPT_CD:801CITE_RATE:1.807FILENAME:kimjk-anti ganlioside ab-gbs-j clin neurol-2014-10(2)94.pdfDEPT_NM:의학과SCOPUS_YN:YCONFIRM:

Aerial Imaging-Based Fuel Information Acquisition for Wildfire Research in Northeastern South Korea

Tree detection and fuel amount and distribution estimation are crucial for the investigation and risk assessment of wildfires. The demand for risk assessment is increasing due to the escalating severity of wildfires. A quick and cost-effective method is required to mitigate foreseeable disasters. In this study, a method for tree detection and fuel amount and distribution prediction using aerial images was proposed for a low-cost and efficient acquisition of fuel information. Three-dimensional (3D) fuel information (height) from light detection and ranging (LiDAR) was matched to two-dimensional (2D) fuel information (crown width) from aerial photographs to establish a statistical prediction model in northeastern South Korea. Quantile regression for 0.05, 0.5, and 0.95 quantiles was performed. Subsequently, an allometric tree model was used to predict the diameter at the breast height. The performance of the prediction model was validated using physically measured data by laser distance meter triangulation and direct measurement from a field survey. The predicted quantile, 0.5, was adequately matched to the measured quantile, 0.5, and most of the measured values lied within the predicted quantiles, 0.05 and 0.95. Therefore, in the developed prediction model, only 2D images were required to predict a few of the 3D fuel details. The proposed method can significantly reduce the cost and duration of data acquisition for the investigation and risk assessment of wildfires

Optofluidic in situ maskless lithography of charge selective nanoporous hydrogel for DNA preconcentration

An optofluidic maskless photopolymerization process was developed for in situ negatively charged nanoporous hydrogel [poly-AMPS (2-acrylamido-2-methyl-1-propanesulfonic acid)] fabrication. The optofluidic maskless lithography system, which combines a high power UV source and digital mirror device, enables fast polymerization of arbitrary shaped hydrogels in a microfluidic device. The poly-AMPS hydrogel structures were positioned near the intersections of two microchannels, and were used as a cation-selective filter for biological sample preconcentration. Preconcentration dynamics as well as the fabricated polymer shape were analyzed in three-dimensions using fluorescein sample and a confocal microscope. Finally, single-stranded DNA preconcentration was demonstrated for polymerase chain reaction-free signal enhancement

Potentiometric Multichannel Cytometer Microchip for High-throughput Microdispersion Analysis

The parallelization of microfluidic cytometry is expected to lead to considerably enhanced throughput enabling point-of-care diagnosis. In this article, the development of a microfluidic potentiometric multichannel cytometer is presented. Parallelized microfluidic channels sharing a fluid path inevitably suffer from interchannel signal crosstalk that results from electrical coupling within the microfluidic channel network. By employing three planar electrodes within a single detection channel, we electrically decoupled each channel unit, thereby enabling parallel analysis by using a single cytometer microchip with multiple microfluidic channels. The triple-electrode configuration is validated by analyzing the size and concentration of polystyrene microbeads (diameters: 1.99, 2.58, 3, and 3.68 μm; concentration range: ∼2 × 10⁵ mL^–1 to ∼1 × 10⁷ mL^–1) and bacterial microdispersion samples (<i>Bacillus subtilis</i>, concentration range: ∼4 × 10⁵ CFU mL^–1 to ∼3 × 10⁶ CFU mL^–1). Crosstalk-free parallelized analysis is then demonstrated using a 16-channel potentiometric cytometer (maximum cross-correlation coefficients |<i>r</i>|: < 0.13 in all channel combinations). A detection throughput of ∼48 000 s^–1 was achieved; the throughout can be easily increased with the degree of parallelism of a single microchip without additional technical complexities. Therefore, this methodology should enable high-throughput and low-cost cytometry

Development of a Prediction Model of Fuel Moisture Changes in a Deciduous Forest of Yeongdong Region in Korea

Understanding how fuel moisture changes after a rainfall is important to predict forest fire risk, and knowing such change in advance can greatly assist in fire risk monitoring. To better understand the fuel moisture dynamics after a rainfall, we investigated how fuel moisture level changes across four different fuel layers (fall leaves, humus, top soil layer (<5 cm depth), and lower soil layer (5–10 cm depth)) under three different stand density levels (high, medium and low) after a significant rainfall event (>5 mm) during spring season. We measured variables including effective humidity, solar irradiation, wind speed, and days after rainfall. These variables were incorporated into developing a fuel moisture prediction regression model. Variables were measured daily for 6 days after a rainfall, for a total of 4 rainfall events in the spring of 2008 for model development, and one event in the spring of 2009 for model validation. Results show that in a low density stand, fuel moisture of the fallen leaves layer reached a dangerously dry level of 17% only after 3 days since rainfall, while at the medium and high density stands, fuel moisture level remained at 19–20% after 6 days since rainfall. Fuel moisture at the humus level was highest among all fuel layers, and remained at greater than 57% even after 6 days since rainfall. Top and lower soil layers both showed small to no changes in fuel moisture content throughout the sampling period. The prediction regression model showed a reasonable performance (R^2=0.56–0.90, p–value <0.001) and validated well against an independent set of measurements

Progress in the Development of Active-Matrix Quantum-Dot Light-Emitting Diodes Driven by Non-Si Thin-Film Transistors

This paper aims to discuss the key accomplishments and further prospects of active-matrix (AM) quantum-dot (QD) light-emitting diodes (QLEDs) display. We present an overview and state-of-the-art of QLEDs as a frontplane and non-Si-based thin-film transistors (TFTs) as a backplane to meet the requirements for the next-generation displays, such as flexibility, transparency, low power consumption, fast response, high efficiency, and operational reliability. After a brief introduction, we first review the research on non-Si-based TFTs using metal oxides, transition metal dichalcogenides, and semiconducting carbon nanotubes as the driving unit of display devices. Next, QLED technologies are analyzed in terms of the device structure, device engineering, and QD patterning technique to realize high-performance, full-color AM-QLEDs. Lastly, recent research on the monolithic integration of TFT–QLED is examined, which proposes a new perspective on the integrated device. We anticipate that this review will help the readership understand the fundamentals, current state, and issues on TFTs and QLEDs for future AM-QLED displays