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The performance of gas blown in side walls of a single strand tundish is numerically simulated. Three cases are studied, i.e. tundish without gas blown, tundish with gas blown from the right side wall, and from the front wall. The vortex circulating flow is the main flow structure in tundish without gas blown. The gas blown from the right side wall of tundish will significantly change the flow field. The short-circuit flow that the tracer flow along the bottom of tundish to the outlet is becoming the main flow pattern. The RTD curve shows a rapid increase tendency. An anticlockwise flow near the top surface is formed. The mixing of tracer in the tundish is delayed and the dead volume fraction is increased when compared with the tundish without gas blown case. In contrast, the gas blown from the front wall of tundish will divide the tundish into two parts. The strong circulation flow in two parts is formed. Besides, the mixing of tracer is faster and the dead volume fraction is lower than that of the case without gas blown. This case may be an optimized gas blown technology in tundish.

Mesoporous silica nanoparticles (MSNs) are widely used in many biomedical applications and clinical fields. However, the applications of MSNs are limited by their severe toxicity. Apigenin (AG) has demonstrated pharmacological effects with low toxicity. The aim of this study was to clarify the role of AG in the progression of MSNs-induced renal injury. BALB/c mice and NRK-52E cells were exposed to MSNs with or without AG. AG protected mice and NRK-52E cells from the MSNs-induced pathological variations in renal tissues and decreased cell viability. AG significantly reduced the levels of serum blood urea nitrogen (BUN) and serum creatinine (Scr), upregulated the levels of superoxide dismutase (SOD), glutathione (GSH) and catalase (CAT), and improved the pathological changes of the kidney in MSNs-treated mice. The protective effects of AG were associated with its ability to increase the levels of antioxidants, reduce the accumulation of ROS, and inhibit the expression of the inflammatory mediators (TNF-α, IL-6). In addition, AG treatment upregulated the activity of FOXO3a, increased the level of IkBα, and reduced the nuclear translocation of NF-κB, which ultimately alleviated MSNs-induced inflammation. Nuclear FOXO3a translocation also triggered antioxidant gene transcription and protected nephrocyte from oxidative damage. However, knockdown of FOXO3a significantly blocked the protective effects of AG. These findings suggested that AG could be a promising therapeutic strategy for MSNs-induced nephrotoxicity, and this protective effect might be related to the suppression of oxidative stress and inflammation via the FOXO3a/NF-κB pathway.

We investigate the effect of institutional investor attention and the public information about asset value on the financial market by studying a strategic trading problem, where the strategic trader is subject to an information-processing constraint and the asset value follows a mean-reverting process. We show that the limited institutional investor attention endogenously generates a private signal for the strategic trader, precluding a fully revealed price. In contrast, the transparency of the asset value improves the market efficiency. Furthermore, the trading aggressiveness, expected payoff, and informativeness of price increase with institutional investor attention, while market liquidity decreases with this attention. On the other hand, the effect of the public information about asset value is uncertain and depends on the remaining of the strategic trader's information advantage. This feature explains different empirical findings pertaining to the relationship between public news and market liquidity.

The radiation hardness of passive CMOS pixel sensors fabricated in 150 nm LFoundry technology is investigated. CMOS process lines are especially of interest for large-scale silicon detectors as they offer high production throughput at comparatively low cost. Moreover, several features like poly-silicon resistors, MIM-capacitors and several metal layers are available which can help enhance the sensor design. The performance of a 100 $\mathrm{\mu}$m thin passive CMOS sensor with a pixel pitch of 50 $\mathrm{\mu}$m at different irradiation levels, 5 $\times$ 10$^{15}$n$_{\mathrm{eq}}$cm$^{-2}$ and 1 $\times$ 10$^{16}$n$_{\mathrm{eq}}$cm$^{-2}$, is presented. The sensor was bump-bonded and read out using the RD53A readout chip. After the highest fluence a hit-detection efficiency larger than 99% is measured for minimum ionising particles. The measured equivalent noise charge is comparable to conventional planar pixel sensors. Passive CMOS sensors are thus an attractive option for silicon detectors operating in radiation harsh environments like the upgrades for the LHC experiments., Comment: 18 pages, 10 figures

Electrochemical CO2 reduction reaction (CO2RR) is the key part of clean energy generation and utilization, which has great potential to help the world to reach the carbon-neutral energy cycle in the future. In line with the development of metal-organic frameworks (MOFs) with the large specific area and considerable porosity in the past two decades, some of the MOF-based electrocatalysts have shown superior ability to accelerate CO2RR. However, regarding such a significant CO2RR process, some critical disadvantages, including inferior robustness, low yield and selectivity, and idealistic working environment, are still required to be concentrated on. Herein, a comprehensive outline of the reaction mechanism of CO2 conversion and rational synthesis of the state-of-the-art pristine MOFs is given. Further, recent progress of pristine MOF-based electrocatalysts in CO2RR is systematically summarized. Lastly, the major limitations and future opportunities in MOF electrocatalysis for CO2RR are presented.

3D scene shape retrieval is a brand new but important research direction in content-based 3D shape retrieval. To promote this research area, two Shape Retrieval Contest (SHREC) tracks on 2D scene sketch-based and image-based 3D scene model retrieval have been organized by us in 2018 and 2019, respectively. In 2018, we built the first benchmark for each track which contains 2D and 3D scene data for ten (10) categories, while they share the same 3D scene target dataset. Four and five distinct 3D scene shape retrieval methods have competed with each other in these two contests, respectively. In 2019, to measure and compare the scalability performance of the participating and other promising Query-by-Sketch or Query-by-Image 3D scene shape retrieval methods, we built a much larger extended benchmark for each type of retrieval which has thirty (30) classes and organized two extended tracks. Again, two and three different 3D scene shape retrieval methods have contended in these two tracks, separately. To solicit state-of-the-art approaches, we perform a comprehensive comparison of all the above methods and an additional new retrieval methods by evaluating them on the two benchmarks. The benchmarks, evaluation results and tools are publicly available at our track websites (Yuan et al., 2019 [1]; Abdul-Rashid et al., 2019 [2]; Yuan et al., 2019 [3]; Abdul-Rashid et al., 2019 [4]), while code for the evaluated methods are also available: http://github.com/3DSceneRetrieval .

Background Until recently, synthetic fiber conjunctival granuloma (SFCG) is rarely reported and has been poorly understood. Our study was to explore the clinical features, histopathologic characteristics, surgical outcomes, and prognosis of SFCG after surgical excision. Methods Retrospective review of clinical findings, histopathological and immunohistochemical studies identified 18 cases of SFCG. Specimens were routinely processed and stained with H&E. Immunohistochemical stains for GMS, PAS, CD68 and CK-pan were also performed. Results Eighteen patients with an average age of 9.3 ± 6.6 years had a tender white to red mass on the conjunctiva. All the lesions were completely removed, and none of the patients relapsed. Histologically, all of the specimens revealed inflammatory granulation tissues with a large number of inflammatory cells infiltration and the presence of synthetic fibers. Immunohistochemical stains were positive for CD68, CK, GMS and PAS. Conclusions Synthetic fiber conjunctival granuloma is an uncommon lesion with foreign body sensation caused by inoculation of synthetic exogenous materials. These lesions are mostly unilateral and occur in the inferior conjunctival fornix. SFCGs are characterized by a large number of inflammatory cells infiltration and the presence of synthetic fibers. Surgical excision followed by topical corticosteroids has been clinically proven to be effective.

Image generation from sketch is a popular and well-studied computer vision problem. However, the inverse problem image-to-sketch (I2S) synthesis still remains open and challenging, let alone image-to-scene sketch (I2S2) synthesis, especially when full-scene sketch generations are highly desired. In this paper, we propose a framework for generating full-scene sketch representations from natural scene images, aiming to generate outputs that approximate hand-drawn scene sketches. Specifically, we exploit generative adversarial models to produce full-scene sketches given arbitrary input images that are actually conditions which are incorporated to guide the distribution mapping in the context of adversarial learning. To advance the use of such conditions, we further investigate edge detection solutions and propose to utilize Holistically-nested Edge Detection (HED) maps to condition the generative model. We conduct extensive experiments to validate the proposed framework and provide detailed quantitative and qualitative evaluations to demonstrate its effectiveness. In addition, we also demonstrate the flexibility of the proposed framework by using different conditional inputs, such as the Canny edge detector.

Increased utilization of platinum ions in chemicals and drugs escalates environmental pollution and toxicity associated with Pt ions. However, current analysis and detection strategies of Pt ions display limited sensitivity due to the similar inert metal nature of platinum to gold. Herein, a photoinduced charge-separated molecule (MTPA)2Ab was synthesized as a probe for enhanced sensitive selection of Pt ions. Long-lived charge-separated states generated upon exposure to 365 nm light lead to a stable complex between (MTPA)2Ab and PtCl2/PtCl4 with highly-selectivity via sequential photoinduced electron transfers. Owing to the linear relationship of complex characteristic absorption and fluorescence emission intensities to Pt2+/Pt4+ concentrations, ultrasensitive spectrum analysis of Pt ions is achieved with a detection limit of 14.2 nM (2.8 ppb) for Pt2+ and 12.6 nM (2.5 ppb) for Pt4+ by an absorption spectrometer and 9.8 nM (1.9 ppb) for Pt ions (Pt2+/Pt4+) by a fluorescence spectrometer, far less than the reported values. Furthermore, a portable test box is developed based on (MTPA)2Ab test strips due to distinguishable color change with Pt2+/Pt4+ concentrations for rapid colorimetric detection of Pt ions. The results highlight the promise of photoinduced charge-separated molecular probe in ultrasensitive and rapid detection of Pt ions to overcome current limitations of detection strategies.

The contact welding failure of general-purposed relay closely relates to alternating current (AC) arc erosion. In this paper, AC arc behavior is investigated by a general-purpose relay firstly. The typical waveforms of arc voltage and current during contact making and breaking are presented, then the effects of point-on-wave (POW) at break on arc energy is analyzed explicitly. Based on the degradation processes of contact opening time and making heat occurred in the electrical endurance experiment, the possible physical mechanism of contact welding failure for general-purposed relay is proposed.

3D scene recognition is important for many applications including robotics, autonomous driving cars, augmented reality (AR), virtual reality (VR), 3D movie and game production. A lot of semantic information (i.e. objects, object parts and object groups) is existing in 3D scene models. To significantly improve 3D scene recognition accuracy, we incorporate such semantic information into the recognition process by building a semantic scene tree and propose a deep random field (DRF) model-based semantic 3D scene recognition approach. Experiments demonstrate that the semantic approach can effectively capture semantic information of 3D scene models, accurately measure their similarities, and therefore greatly enhance the recognition performance. Code, data and experimental results can be found on the project homepage.

Ultraviolet B (UVB) exposure is a core factor that leads to skin disease or carcinogenesis through the insufficient repair of DNA lesions. UVB-induced DNA lesions are mainly removed by the nucleotide excision repair (NER) mechanism. The expression of histone deacetylase 4 (HDAC4) is altered in the skin upon UVB exposure, indicating its possible implication in UVB-induced DNA lesions repair. Here, we investigated the role of HDAC4 in the NER removal of the main classes of UVB-induced DNA lesions consisting of cyclobutane pyrimidine dimers and pyrimidine (6-4) pyrimidone photoproducts (6-4PPs). We found that UVB irradiation increased HDAC4 expression at both the mRNA and protein levels. HDAC4 interacted with NER factor XPC, which played an important role in effectively removing the UVB-induced DNA lesions. This study provides an understanding of the HDAC4 function in DNA repair, which will allow the development of efficient strategies to protect the skin from UVR-induced diseases.

Background Previously, we have investigated the therapeutic mechanism of Qingzao Jiufei Decoction (QZJFD), a Chinese classic prescription, on acute lung injury (ALI), however, which remained to be further clarified together with the underlying efficacy related compounds for quality markers (Q-markers). Hypothesis/Purpose To explore Q-markers of QZJFD on ALI by integrating a stepwise multi-system with ‘network pharmacology-metabolomics- pharmacokinetic (PK)/ pharmacodynamic (PD) modeling’. Methods First, based on in vitro and in vivo component analysis, a network pharmacology strategy was developed to identify active components and potential action mechanism of QZJFD on ALI. Next, studies of poly-pharmacology and non-targeted metabolomics were used to elaborate efficacy and verify network pharmacology results. Then, a comparative PK study on active components in network pharmacology was developed to profile their dynamic laws in vivo under ALI, suggesting Q-marker candidates. Next, quantified analytes with marked PK variations after modeling were fitted with characteristic endogenous metabolites along drug concentration-efficacy-time curve in a PK-PD modeling to verify and select primary effective compounds. Finally, Q-markers were further chosen based on representativeness among analytes through validity analysis of PK quantitation of primary effective compounds. Results In virtue of 121 and 33 compounds identified in vitro and in vivo, respectively, 33 absorbed prototype compounds were selected to construct a ternary network of ‘20 components-47 targets-113 pathways’ related to anti-ALI of QZJFD. Predicted mechanism (leukocytes infiltration, cytokines, endogenous metabolism) were successively verified by poly-pharmacology and metabolomics. Next, 18 measurable components were retained from 20 analytes by PK comparison under ALI. Then, 15 primary effective compounds from 18 PK markers were further selected by PK-PD analysis. Finally, 9 representative Q-markers from 15 primary effective compounds attributed to principal (chlorogenic acid), ministerial (methylophiopogonanone A, methylophiopogonanone B), adjuvant (sesamin, ursolic acid, amygdalin), conductant drugs (liquiritin apioside, liquiritigenin and isoliquiritin) in QZJFD, were recognized by substitutability and relevance of plasmatic concentration at various time points. Conclusion 9 Q-markers for QZJFD on ALI were identified by a stepwise integration strategy, moreover, which was a powerful tool for screening Q-makers involved with the therapeutic action of traditional Chinese medicine (TCM) prescription and promoting the process of TCM modernization and scientification.

International audience; The monolithic CMOS pixel sensor for charged particle tracking has already become a mainstream technology in high energy particle physics (HEP) experiments. During the last decade, progressive improvements have been made for CMOS pixels to deal with the high-radiation and high-rate environments expected, for example, at the future High Luminosity LHC. One of the key ingredients of these improvements is to achieve a fully depleted sensitive layer, where the charge collection is guided by strong drift field lines. CMOS sensors incorporating such charge collection property, often referred to as DMAPS (Depleted Monolithic Active Pixel Sensor), have been recently demonstrated in several large-scale monolithic prototypes with integrated fast readout architectures. This contribution summarizes the recent progress made on the large-scale DMPAS development, focusing on two demonstrator chips designed in the LFoundry 150 nm and the TowerJazz 150 nm CMOS processes, namely LF-Monopix1 and TJ-Monopix1.

Comparing the amplitude and phase modulations of the gear meshing vibration can help detecting the weak gear local defects such as fatigue cracks. As for a planet gear operating in a wind turbine (WT) planetary gearbox, however, the vibration from the stage of the fixed-axis gearbox will act as a strong interruption towards the crack fault detection in both time and frequency domain. As such, a new algorithm based on the principles of the meshing resonance (MR) demodulation is proposed to address this issue. This method consists of four main steps: (a) signal decomposing via arborescent filter-bank—this together with the meshing index lead to the MRgram with prominent planet gear MR frequency area, (b) determination of the optimal planet gear MR frequency band from the MRgram and the raw spectrum using a bilateral expansion method, (c) highlighting of the planet gear related vibration via the optimal planet gear MR frequency band based bandpass filtering and the time synchronous averaging (TSA), (d) identification of the planet gear tooth root crack by comparing the corresponding amplitude and phase modulations. The effectiveness and superiority of the proposed algorithm are validated by the experimental vibration data from a WT planetary gearbox test rig.

Additional file 1 Descriptions of Method 1 and Method 2.

Additional file 1. Clinical photographs of 18 patients with synthetic fiber conjunctival granuloma (only for review).

Additional file 4 Yearly new infections, undiagnosed prevalence, and diagnosis probabilities from 1990 to 2017 (estimated by method 1).

Additional file 2 Comparisons between real data and model predictions obtained by method 1.

Journal of Instrumentation 15(02), P02005 (2020). doi:10.1088/1748-0221/15/02/P02005, Depleted Monolithic Active Pixel Sensor (DMAPS) prototypes developed in the TowerJazz 180 nm CMOS imaging process have been designed in the context of the ATLAS upgrade Phase-II at the HL-LHC. The pixel sensors are characterized by a small collection electrode (3 μm) to minimize capacitance, a small pixel size (36.4× 36.4 μm$^2$), and are produced on high resistivity epitaxial p-type silicon. The design targets a radiation hardness of 1×10$^{15}$ 1 MeV n$_{eq}$/cm$^2$, compatible with the outermost layer of the ATLAS ITK Pixel detector. This paper presents the results from characterization in particle beam tests of the Mini-MALTA prototype that implements a mask change or an additional implant to address the inefficiencies on the pixel edges. Results show full efficiency after a dose of 1×10$^{15}$ 1 MeV n$_{eq}$/cm$^2$., Published by Inst. of Physics, London

Additional file 3 Comparisons between real data and model predictions obtained by method 2.

Motivated by the complex dynamics between the oil and stock markets, this study develops a dynamic Markov regime switching-copula-extreme value theory (MRS-copula-EVT) model to quantitatively investigate financial contagion and its characteristics between these two markets. The proposed model, which characterizes the complex dynamics in lower tail dependence, is applied to daily returns on the crude oil price and major stock indices in both the United States and China's markets over a series of major extreme downside risk events, including the most recent 2020 oil and stock market crashes after the outbreak of COVID-19 pandemic. The proposed model outperforms the alternative model in detecting financial contagion, showing that such contagion is shorter but stronger in the United States than in China; moreover, financial contagion is more susceptible to extreme downside shocks between the oil and stock markets in the United States than in China. In addition, the COVID-19 crisis shows the largest financial contagion compared with previous crises. Our results remain consistent following extensive robustness tests. These findings shed new light on our understanding of financial contagion and provide important insights and guidance for asset allocation and risk management.

The effect of total calcium, sodium concentration and bacteria growth history was investigated on biofilm formation of Geobacillus stearothermophilus in milk formulations. Biofilm cell numbers of three G. stearothermophilus strains were compared in two milk formulations (MF1 and MF2) over 18 h. MF1 and MF2 had similar compositions but MF2 had relatively high sodium and low calcium concentrations. Biofilm formation of all three strains was lower (P m calcium increased (P

Rotational energy harvesting for powering low-power electronic devices and wireless sensors has attracted increasing attention in recent years. This paper proposes an energy harvester to scavenge rotational energy from rotating machines by installing an arc-shaped piezoelectric sheet between the outer race of rolling bearing and bearing pedestal. The proposed piezoelectric energy harvester cannot only supply power to sensors but also has the capability of bearing fault detection. The structural design and working principle are initially demonstrated, where an electromechanical coupling model is developed to explain the working principle of energy harvester. Then, a prototype of the energy harvester is fabricated and mounted on a rotor test rig, on which experiments are carried out to evaluate the output performance of energy harvester. The effects of rotating speed, rotor weight, shaft span and matched resistances on energy harvester performance are comprehensively evaluated. It is revealed that a single piezoelectric section of the energy harvester can generate RMS voltage of 25 V, and RMS power of 60–131 μW under the rotating speed range from 600 to 1200 r/min. Finally, the applications of the proposed energy harvester for bearing fault detection and self-powered wireless sensing are demonstrated to manifest its capability of bearing condition monitoring.

Data-driven fault diagnosis methods have become a research hotspot recently. However, the following two problems are still barring them from the application: (1) Most of the existing models rely deeply on sufficient labeled samples and neglect the high cost of labeled data collection in reality; (2) The existing models usually focus on the single-level attribute of the sample and ignore the latent hierarchical fault attributes. To address these issues, a novel semi-supervised multi-layer non-negative matrix factorization (SMNMF) method is proposed in this study. The fault pattern and severity identification problems are converted into a hierarchical fault attribute representation task, which can reduce the complexity of the classification task and improve the fault diagnosis accuracy. The hierarchical attribute representations of different fault locations and sizes are learned from the time-frequency distribution (TFD) of signals by a newly constructed two-layer non-negative matrix factorization model. The graph-based semi-supervised learning method is adopted to lead the attributes of the hierarchy structure and carry out label propagation from labeled samples to unlabeled samples for more accurate fault diagnosis. The fault diagnosis experiments executed in the aeroengine bearings and a diesel engine demonstrated the feasibility and superiority of the proposed method.

A series of charge-separated (CS) sensitizers with various donor modules and pyrimidine as acceptor were synthesized and employed to explore the effect of donor structure engineering on the properties of CS sensitizers and photovoltaic performances of dye-sensitized solar cells (DSSCs). Using previously reported CS sensitizer MTPA-Pyc or YD-Pyc as the model molecule, cyano group or benzotriazole were incorporated into the donor module and the electrochemical, spectral and photophysical properties were investigated. Incorporating electron-withdrawing structures enhances the intramolecular charge transfer (ICT) and conjugation of the donor module which leads to not only remarkably red-shifted absorption spectra, but also elongated lifetime of CS state of the sensitizers, thus resulting in an over 30% increase of power conversion efficiency (PCE) of the DSSCs. Combination of an electron-withdrawing benzotriazole with a strong electron-donating indoline moiety in the donor module produces the best PCE of 7.41% for DSSC based on YDBT-Pyc. Our results provide not only the rational design principles for CS sensitizers, but also insight into the feasibility of CS sensitizers for high performance photovoltaic applications.

Identifying the bearing fault-induced impulsive components in the frequency domain is a key step in the corresponding fault detection. However, gearbox vibration signals often significant interrupt the rolling bearing fault diagnosis, particularly in the detection of planet bearing faults under the background noise of the planetary gearbox. Except in the case of a high amplitude, a gear meshing-related vibration may also affect the identification of the planet bearing fault-induced resonance frequency band. To solve this problem, a meshing frequency modulation index (indexMFM)-based kurtogram utilizing a particular gearbox related phenomenon is proposed. The underlying mechanism is such that although the gear meshing-related spectral components are always more prominent in relatively higher-frequency band than the planet bearing-induced resonance frequency band in impulsiveness, the gear meshing-related impulsive components modulate the gear meshing frequency, yet the faulty bearing-induced one does not. Exploiting this difference, the planet bearing fault-induced impulsive components can be directly identified from the strong gear vibration interruption by determining the bearing fault-related resonance frequency band in the indexMFM-based kurtogram. The effectiveness of the proposed method is separately verified using simulated and experimental data.

Understanding potential evapotranspiration (PET) changes under climate change is of great importance for hydrological research. The trends of PET changes and their driving forces were investigated in the Lancang (LRB) and Yarlung Zangbo (YRB) river basins, southwest China, using diagnosis graphs and the Mann-Kendall test. Analysis of variance was applied to examine the contribution of different climatic variables to PET. The results show that: (i) there was a statistically significant increase in PET in the period of 1957–2015 in the LRB, while it showed a markedly decreasing trend in the YRB; (ii) PET in both basins is fairly sensitive to wind speed, relative humidity, solar radiation and maximum air temperature, and the interactions between wind speed and relative humidity are also important; and (iii) the increase in PET in the LRB is due mainly to the increase in maximum air temperature and decrease in relative humidity, while declines in wind speed and solar radiation are the main reasons for the decrease in PET in the YRB.

The local defect in rotating machine always gives rise to repetitive transients in the collected vibration signal. However, the transient signature is prone to be contaminated by strong background noises, thus it is a challenging task to detect the weak transients for machine fault diagnosis. In this paper, a novel adaptive tunable Q-factor wavelet transform (TQWT) filter based feature extraction method is proposed to detect repetitive transients. The emerging TQWT possesses distinct advantages over the classical constant-Q wavelet transforms, whose Q-factor can be tuned to match the oscillatory behavior of different signals, but the parameter selection for TQWT heavily relies on prior knowledge. Within our adaptive TQWT filter algorithm, the automatic optimization techniques for three TQWT parameters are implemented to achieve an optimal TQWT basis that matches the transient components. Specifically, the decomposition level is selected according to a center frequency ratio based stopping criterion, and the Q-factor and redundancy are optimized based on the minimum energy-weighted normalized wavelet entropy. Then, the adaptive TQWT decomposition can be achieved in a sparse way and result in subband signals at various wavelet scales. Further, the optimum subband signal which carries transient feature information, is identified using a normalized energy to bandwidth ratio index. Finally, the single branch reconstruction signal from the optimum subband is obtained with transient signatures via inverse TQWT, and the frequency of repetitive transients is detected using Hilbert envelope demodulation. It has been verified via numerical simulation that the proposed adaptive TQWT filter based feature extraction method can adaptively select TQWT parameters and the optimum subband for repetitive transient detection without prior knowledge. The proposed method is also applied to faulty bearing vibration signals and its effectiveness is validated.

In this study, we applied a novel, mild, and convenient synthetic method involving the oxidative cyclization of 1-(pyrazin-2-yl)guanidine derivatives to produce [1,2,4]triazolo[4,3-a]pyrazin-3-amines. We optimized the reaction procedure to easily obtain 5-chloro-[1,2,4]triazolo[4,3-a]pyrazin-3-amine. Various types of halogenated pyrazines can successfully undergo this process. We synthesized a series of 1-(pyrazin-2-yl)guanidines and [1,2,4]triazolo[4,3-a]pyrazin-3-amines, and then elucidated their structures based on their 1H-NMR, 13C-NMR, ESI-HRMS, and nuclear Overhauser effect spectra.

A thioester-functionalized triphenylamine hole-transporting molecule (TPD-SAc) was synthesized and self-assembled to form a monolayer on an ultra-thin Au film supported on indium-tin oxide glass. The modified surface was characterized by aqueous contact angle, ellipsometer, atomic force microscopy, X-ray photoelectron spectroscopy, and ultraviolet photoelectron spectrometer to substantiate the formation of compact and pinhole-free monolayers. The modified organic light emitting diode device [indium-tin oxide/Au (5 nm)/self-assembled monolayers (SAM)/TPD (50 nm)/Alq3 (40 nm)/TPBI (15 nm)/LiF (1 nm)/Al (100 nm)] showed a luminance of 7303.90 cd/m2 and a current efficiency of 8.49 cd/A with 1.78 and 2.29-fold increase, respectively, compared to the control device without SAM. The improvements were attributed to the enhanced compatibility of the organic–inorganic interface, matched energy level by introduction of an energy mediating step and superior hole-injection property of SAM molecules.

This paper proposes a variant application of the Merton distance-to-default model by employing implied volatility and implied cost of capital to predict defaults. The proposed model’s results are compared with predictions obtained from three popular models in different setups. We find that our “best” model, which contains forward-looking proxies of returns and volatility outperform other models, carries a default prediction accuracy rate of 89%. Additional analysis using a discrete-time hazard model indicates the pseudo-R2 values from regression models that include the two forward-looking measures are as high as 51%. Overall, our results establish the informational relevance of implied cost of capital and implied volatility in predicting defaults.

In this paper, an electrostatic vibration energy harvester is proposed and fabricated with both broad bandwidth and high normalized power density (NPD, harvested power/volume/acceleration2). The device is made up of two parts, top movable plate and bottom fixed plate, both of which are fabricated from silicon wafers using advanced micro-electro-mechanical system (MEMS) technology. A CYTOP polymer layer is spray coated for an electret material as well as an adhesive layer for low temperature wafer bonding. The air damping effect in energy harvesting has been investigated. At a low pressure of 3 Pa in a vacuum chamber, maximum power output of 4.95 μW has been harvested at low vibration amplitude of 0.09 g, resulting in a bandwidth of 12 Hz and NPD of 3 mW/cm3/g2, which outperforms most of the previous harvesters. A high harvester effectiveness of 67.9% is therefore achieved. The response on random vibrations is also tested. An average output power of 2.22 μW is harvested when random vibration is applied at a frequency range of 160 ± 12.5 Hz with RMS acceleration of 10.5 m/s2. The excellent overall performance gives promising application for energy harvesting from random sources and multi-device stack for wireless sensor networks.

The aim of this study is to develop and validate a rapid, high-selective and sensitive supercritical fluid chromatography/tandem mass spectrometry (SFC–MS/MS) with a multiple reactions monitoring (MRM) mode method for the detection of ezetimibe in dog plasma. Several conditions were optimized systematically as follows: lipid–lipid extraction (LLE) performances were used to extract analytes from dog plasma; an ACQUITY HSS C18 SB (1.8 μm, 3.0 × 100 mm) column was employed to separate the target compounds; the triple-quadrupole mass spectrometry equipped with electrospray ionization (ESI) source was applied to detect ezetimibe. The method, which required a relatively small volume of plasma (100 μL), was obtained at concentration ranging from 1.0 to 100 ng/mL(r2 > 0.99). The lower limit of quantification (LLOQ)for ezetimibe was found to be as low as 1.0 ng/mL. In addition, the validations of the methodology including sensitivity, recovery, matrix effect, intra- and inter-day precision, accuracy and stability were all within acceptable limits. The Cmax, AUC0–inf and Tmax values obtained in our study were 52.2 ± 6.3, 820.6 ± 4.3 and 1.25 ± 0.35 for reference formulation; 61.8 ± 12.6, 924.2 ± 4.7 and 2.00 ± 0 for test formulation. In conclusion, the method developed in this study can be successfully applied to pharmacokinetic studies after oral administration of ezetimibe in dogs.

Due to environmental pollution and the increasing shortage of fossil fuels, sustainable hybrid electrode materials must be developed to improve the performance of semiconductor-based supercapacitors, thus allowing for the realization of alternative energy storage systems. An ordered mesoporous (OM) NiO/ZnO p-n heterojunction electrochemical electrode was prepared by using a soft-template method and facile hydrothermal technique. The p-type NiO was successfully assembled on the ordered mesoporous n-type ZnO matrix, thus forming p-n heterojunction artifacts with hierarchical porous structures. The capacitive performance and mechanism were systemically investigated. The prepared p-n heterojunction OM-NiO/ZnO supercapacitor exhibited excellent capacitive performances with a significantly higher specific capacity of 1394 C g − 1 (1 A g − 1), high rate capability of 560 C g − 1 at 20 A g − 1, stable cycling property (constant at 538 C g − 1 after 2000 cycles at 5 A g − 1), and wide potential window of 0.6 V. These high supercapacitor performances can be mainly attributed to the synergistic effects of the nanoscale ordered mesoporous structure, loose 3D- networks, and p-n heterojunction formed by two phases of ZnO and NiO, which provide abundant active sites and charge transfer pathways for the diffusion of ions and electron transfer, respectively. The results show that this novel approach involving the p-n heterojunction with a hierarchical mesoporous structure allows for the development of energy materials.