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Developing covalent organic frameworks (COFs) with good electrical conductivity is essential to widen their range of practical applications. Thermal annealing is known to be a facile approach for enhancing conductivity. However, at higher temperatures, most COFs undergo amorphization and/or thermal degradation because of the lack of linker rigidity and physicochemical stability. Here, we report the synthesis of a conductive benzoxazole-linked COF/carbon hybrid material (BCOF-600C) by simple thermal annealing. The fused-aromatic benzoxazole and biphenyl building units endow the resulting COF with excellent physicochemical stability against high temperatures and strong acids/bases. This allows heat treatment to further enhance electrical conductivity with minimal structural alteration. The robust crystalline structure with periodically incorporated nitrogen atoms allowed platinum (Pt) atoms to be atomically integrated into the channel walls of BCOF-600C. The resulting electrocatalyst with well-defined active sites exhibited superior catalytic performance toward hydrogen evolution in acidic media.

SummaryDue to the enhanced labeling capability of maleimide-based fluorescent probes, lysine-cysteine-lysine (KCK) tags are frequently added to proteins for visualization. In this study, we employedin vitrosingle-molecule DNA flow-stretching assay as a sensitive way to assess the impact of the KCK-tag on the property of DNA-binding proteins. UsingBacillus subtilisParB as an example, we show that, although no noticeable changes were detected byin vivofluorescence imaging and chromatin immunoprecipitation (ChIP) assays, the KCK-tag substantially altered ParB’s DNA compaction rates, its response to nucleotide binding and to the presence of the specific sequence (parS) on the DNA. While it is typically assumed that short peptide tags minimally perturb protein function, our results urge researchers to carefully validate the use of tags for protein labeling. Our comprehensive analysis can be expanded and used as a guide to assess the impacts of other tags on DNA-binding proteins in single-molecule assays.MotivationSingle-molecule fluorescence microscopy has been extensively used in modern biology to define the molecular action of proteins. Appending short peptide tags is a common strategy to enhance fluorescence labeling. In this Resources article, we evaluate the impact of a commonly used tag, the lysine-cysteine-lysine (KCK) tag, on protein behavior in single-molecule DNA flow-stretching assay, which is a sensitive and versatile method to understand the action of DNA-binding proteins. Our motivation is to provide researchers with an experimental framework to validate the fluorescently labeled DNA-binding proteins in single-molecule methods.

Multispectral pedestrian detection has been actively studied as a promising multi-modality solution to handle illumination and weather changes. Most multi-modality approaches carry the assumption that all inputs are fully-overlapped. However, these kinds of data pairs are not common in practical applications due to the complexity of the existing sensor configuration. In this letter, we tackle multispectral pedestrian detection, where all input data are not paired. To this end, we propose a novel single-stage detection framework that leverages multi-label learning to learn input state-aware features by assigning a separate label according to the given state of the input image pair. We also present a novel augmentation strategy by applying geometric transformations to synthesize the unpaired multispectral images. In extensive experiments, we demonstrate the efficacy of the proposed method under various real-world conditions, such as fully-overlapped images and partially-overlapped images, in stereo-vision. Code and a demonstration video are available at https://github.com/sejong-rcv/MLPD-Multi-Label-Pedestrian-Detection .

This study focuses on the applicability of single-atom Mo-doped graphitic carbon nitride (GCN) nanosheets which are specifically engineered with high surface area (exfoliated GCN), NH

In this paper, multispectral pedestrian detection is mainly discussed, which can contribute to assigning human-aware properties to automated forklifts to prevent accidents, such as collisions, at an early stage. Since there was no multispectral pedestrian detection dataset in an intralogistics domain, we collected a dataset; the dataset employs a method that aligns image pairs with different domains, i.e. RGB and thermal, without the use of a cumbersome device such as a beam splitter, but rather by exploiting the disparity between RGB sensors and camera geometry. In addition, we propose a multispectral pedestrian detector called SSD 2.5D that can not only detect pedestrians but also estimate the distance between an automated forklift and workers. In extensive experiments, the performance of detection and centroid localization is validated with respect to evaluation metrics used in the driving car domain but with distinct categories, such as hazardous zone and warning zone, to make it more applicable to the intralogistics domain.

Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects movement. The nonreceptor tyrosine kinase c-Abl has shown a potential role in the progression of PD. As such, c-Abl inhibition is a promising candidate for neuroprotection in PD and α-synucleinopathies. Compound 5 is a newly synthesized blood-brain barrier penetrant c-Abl inhibitor with higher efficacy than existing inhibitors. The objective of the current study was to demonstrate the neuroprotective effects of compound 5 on the α-synuclein preformed fibril (α-syn PFF) mouse model of PD. Compound 5 significantly reduced neurotoxicity, activation of c-Abl, and Lewy body pathology caused by α-syn PFF in cortical neurons. Additionally, compound 5 markedly ameliorated the loss of dopaminergic neurons, c-Abl activation, Lewy body pathology, neuroinflammatory responses, and behavioral deficits induced by α-syn PFF injection in vivo. Taken together, these results suggest that compound 5 could be a pharmaceutical agent to prevent the progression of PD and α-synucleinopathies.

Ensuring interfacial stability of Si-containing anodes and Ni-rich cathodes is the key to achieving high-energy lithium-ion cells. Herein, we present 4-(allyloxy)phenyl fluorosulfate (APFS), a multi-functional electrolyte additive that forms a mechanical strain-adaptive solid electrolyte interphase (SEI) composed of LiF and polymeric species, and a thermally stable cathode–electrolyte interface containing S–O and S–F species. Radical copolymerization of vinylene carbonate (VC) with APFS via electrochemical initiation creates a spatially deformable polymeric SEI on the Si/C-graphite (SiG-C) anode with large volume changes during cycling. Here we show that APFS-promoted interfacial layers reduce Ni dissolution and deposition and that APFS deactivates Lewis acidic PF5, inhibiting the hydrolysis that produces unwanted HF. These results show that the combined use of VC and APFS allows capacity retention of 72.5% with a high capacity of 143.5 mAh g− 1 after 300 cycles at 45°C.

We examine whether corporate bankruptcy predictions can be improved by utilizing the recurrent neural network (RNN) and long short-term memory (LSTM) algorithms, which can process sequential data. Employing the RNN and LSTM methodologies improves bankruptcy prediction performance relative to using other classification techniques, such as logistic regression, support vector machine, and random forest methods. Because performance indicators, such as sensitivity and specificity, differ depending on the methodology, selecting a model that suits the purpose of the bankruptcy predictions is necessary. Our ensemble model, a synthesis of all methodologies, exhibits the best forecasting performance. In the test sample for the ensemble model, none of the observations with a default probability of less than 10% defaults within one year.

The patterning of poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) hydrogels with excellent electrical property and spatial resolution is a challenge for bioelectronic applications. However, most PEDOT:PSS hydrogels are fabricated by conventional manufacturing processes such as photolithography, inkjet printing, and screen printing with complex fabrication steps or low spatial resolution. Moreover, the additives used for fabricating PEDOT:PSS hydrogels are mostly cytotoxic, thus requiring days of detoxification. Here, we developed a previously unexplored ultrafast and biocompatible digital patterning process for PEDOT:PSS hydrogel via phase separation induced by a laser. We enhanced the electrical properties and aqueous stability of PEDOT:PSS by selective laser scanning, which allowed the transformation of PEDOT:PSS into water-stable hydrogels. PEDOT:PSS hydrogels showed high electrical conductivity of 670 S/cm with 6-μm resolution in water. Furthermore, electrochemical properties were maintained even after 6 months in a physiological environment. We further demonstrated stable neural signal recording and stimulation with hydrogel electrodes fabricated by laser.

The shortcomings of current anti-human cytomegalovirus (HCMV) drugs has stimulated a search for anti-HCMV compounds with novel targets. We screened collections of bioactive compounds and identified a range of compounds with the potential to inhibit HCMV replication. Of these compounds, we selected bisbenzimide compound RO-90-7501 for further study. We generated analogues of RO-90-7501 and found that one compound, MRT00210423, had increased anti-HCMV activity compared to RO-90-7501. Using a combination of compound analogues, microscopy and biochemical assays we found RO-90-7501 and MRT00210423 interacted with DNA. In single molecule microscopy experiments we found RO-90-7501, but not MRT00210423, was able to compact DNA, suggesting that compaction of DNA was non-obligatory for anti-HCMV effects. Using bioinformatics analysis, we found that there were many putative bisbenzimide binding sites in the HCMV DNA genome. However, using western blotting, quantitative PCR and electron microscopy, we found that at a concentration able to inhibit HCMV replication our compounds had little or no effect on production of certain HCMV proteins or DNA synthesis, but did have a notable inhibitory effect on HCMV capsid production. We reasoned that these effects may have involved binding of our compounds to the HCMV genome and/or host cell chromatin. Therefore, our data expand our understanding of compounds with anti-HCMV activity and suggest targeting of DNA with bisbenzimide compounds may be a useful anti-HCMV strategy.

Due to the advantage that a thermal camera robustly works in various illumination conditions, it has become a crucial sensor in real-world applications, such as self-driving, advanced driver assistance as well as a surveillance system. However, unlike RGB images with color information, thermal images do not contain abundant information. This disadvantage makes it users difficult to recognize thermal scenes. In this paper, we aim to make pseudo-RGB that can be used at day and night by receiving thermal images as inputs and to show the necessity of pseudo-RGB research through colorization that synthesizes chromaticity of RGB in thermal images. Furthermore, we evaluate models to see whether the produced colorized image can be interpreted by perceptual models for tasks, such as pedestrian detection and depth estimation by feeding colorized images to the models that are trained with original RGB images. These experiments explicitly show the limitation and possibility of thermal colorization.

This study examines the time‐series momentum in China's commodity futures market. We find that a time‐series momentum strategy outperforms classical passive long and cross‐sectional momentum strategies in terms of the Sharpe ratio, risk‐adjusted excess returns, and cumulative returns. The time‐series momentum strategy with a 1‐month look‐back period and a 1‐month holding period exhibits the best performance. We observe clear time‐series momentum patterns and find that the time‐series momentum strategy is effective in the Chinese commodity futures market. However, the momentum lasts for less time in China than in the United States because China's futures market seems to have a greater number of speculative investors.

A construction surety bond helps a development project to proceed smoothly. This financial product has supported the rapid economic growth of several emerging markets, including the Republic of Korea. In this study, by using a unique and high-quality dataset, the authors analyze construction surety bonds to estimate their default probabilities. The results have several empirical implications. First, firm characteristics, such as firm size and leverage ratio, influence the surety bond default risk; the safety and liquidity measure are especially robust indicators. The result also confirms that account receivables can increase the default risk. Second, endogenous variables of the surety bond are also robust indicators of default. Because a construction surety bond itself has additional information about a company starting a new construction project, those variables can contribute to indicating default risk. Finally, default forecasting based on this model has much greater forecasting power than models based on the credit rating. TOPICS:Project finance, statistical methods, credit risk management, emerging markets

Despite their simple formulations, advection upstream splitting method (AUSM)-type flux schemes treat linear and nonlinear waves of complex flow fields in a robust and accurate manner. This paper presents the progress of AUSM-type fluxes augmented with pressure-based weight functions introduced by the authors and their colleagues. Starting from a flux designed for single-phase gas dynamics (AUSMPW+), its extensions to capture multi-phase flow physics with phase transition (AUSMPW+_N) have been carried out. The accuracy of the computed results by the AUSMPW+_N scheme for multi-phase flows is then further improved by introducing a simple phase interface-sharpening procedure, which scales the volume fraction in a mass-conserving manner. Various all-speed compressible tests ranging from interactions between a shock and phase interfaces, two- and three-dimensional interface-only problems, to a cryogenic three-component flow with phase change are computed to demonstrate the effectiveness of the proposed method.

Although shipping was not included in the final text of the Paris Agreement in 2015, IMO (International Maritime Organization) adopted the EEDI (Energy Efficiency Design Index) and the EEOI (Energy Efficiency Operational Indicator) to control climate change and also to reduce gas emission from ships. Accurate prediction of added resistance in waves is essential to evaluate the minimum fuel consumption of a ship in a real sea state. In this paper, the added resistance and motions of a KCS (KRISO Container Ship) with rudder were calculated using a commercial CFD program, STAR-CCM+. Wave forcing was used to generate the waves in the numerical domain, in which no extra wave generation and damping zones were produced. DFBI (Dynamic Fluid Body Interaction) was used for the motions of the KCS with rudder. In this study, five (5) regular head waves from a short wavelength to a long wavelength based on the LPP were considered. Finally, added resistance and the heave and pitch motions of the simulation were compared with experimental data. Simulation and experimental data were in qualitatively and quantitatively good agreement.

Following the Basel II convention, consumer credit default is commonly defined as delinquency beyond a period of 90 days. In this study, rather than considering default as a binary variable, we dissect delinquency states further to investigate default behavior in greater detail. As such, we define three states—no delinquency, delinquency and serious delinquency—and estimate the probabilities of the transitions between states using extensive panel data from Korea, covering a wide range of behavioral information. Our findings have several economic implications. First, the factors that affect delinquency risk can differ from those that affect the transition from delinquency to serious delinquency. Second, the recent increase in the number of seriously delinquent accounts can be attributed to changes in the borrower age distribution. Third, macroeconomic conditions, especially differences in gross domestic product and consumption growth, have led to the recent increase in delinquent accounts. Fourth, the debt-to-income (DTI) ratio has a profound effect on transitions between delinquency states and thus affects both recovery and delinquency. Furthermore, this result is robust to controls for demographic and macroeconomic factors.

Computations of all-speed multiphase real fluid flows for aerospace launch vehicles are known to be very demanding, owing to several issues that include robust capturing of two-phase shock/phase di...

This paper focuses on the limitations of single-phase computations which have been widely applied to the numerical simulations of flow fields around thermal vapor compressors (TVCs), and provides computational improvements through multi-phase flow modeling and analysis. In order to capture the multi-phase flow physics accurately and provide reliable results, several numerical methods and models, including the shock-stable multi-phase AUSMPW+ scheme, phase-changing models, cell-by-cell adaptive mesh refinement technique, and the IAPWS-97 equation of states, are combined into a numerical solver. We then simulate various TVC systems and compare the computed system performance and local flow physics between the single- and multi-phase computations. Based on the computational results and comparisons, we examine phase-changing process and its influence on two major local physical features, namely shock-train region and shear layer.