Reliability Analysis of Correlated Competitive and Dependent Components Considering Random Isolation Times

Funding Information: Funding Statement: This work was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 62172058) and the Hunan Provincial Natural Science Foundation of China (Grant Nos. 2022JJ10052, 2022JJ30624). Publisher Copyright: © 2023 Tech Science Press. All rights reserved.Peer reviewedPublisher PD

Photodegradation of RhB over YVO4/g-C3N4 composites under visible light irradiation

National Natural Science Foundation of China [21003109, 51108424]; Opening-foundation of State Key Laboratory Physical Chemistry and Solid Surfaces, Xiamen University, China [201311]; Science Foundation of Zhejiang Normal University [KJ20120028]A series of novel YVO4/g-C3N4 photocatalysts were prepared by a facile mixing and calcination method. The obtained composites were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, transmission electron microscopy, ultraviolet visible diffuse reflection spectroscopy, X-ray photoelectron spectroscopy, photoluminescence spectroscopy, and a photocurrent-time experiment. The rhodamine B dye was selected as a model pollutant to evaluate the photocatalytic activity of the as-prepared YVO4/g-C3N4 composite. It shows that the photocatalytic activity of g-C3N4 can be largely improved by the doping of YVO4. The optimal YVO4 content is determined to be 25.8 wt%; and the corresponding degradation rate is 2.34 h(-1), about 2.75 folds that of pure g-C3N4. A possible mechanism of YVO4 on the enhancement of visible light performance is proposed. It suggests that YVO4 plays a key role, which may lead to efficiently suppressing the recombination of photogenerated charge carriers, consequently, improving the visible light photoactivity

Amorphous alloy : a potential electrocatalyst in water splitting

Catalytic water splitting to produce hydrogen gas driven by renewable electricity is regarded as one of the most promising methods for the sustainable energy conversion, but its efficiency is greatly restricted due to the high overpotential required for the anodic water oxidation half reaction. To accelerate the sluggish four-electron transfer kinetics for the oxygen evolution reaction (OER), it has attracted numerous attention on developing earth-abundant materials as efficient electrocatalysts. Amorphous catalysts are reported to have better activities of water oxidation than their crystalline counterparts, but little is known about the underlying origin, which retards the development of high-performance amorphous oxygen evolution reaction (OER) catalysts. In the first work, to gain an in-depth understanding of the structure-performance relationship for OER on amorphous alloy catalysts, we present a room temperature wet-chemical technique to prepare an amorphous nickel-iron alloy catalyst for water oxidation. And crystalline nickel-iron alloy catalysts without changing composition can be obtained via thermal annealing of amorphous catalyst in N2 atmosphere. Through theoretical analysis including cyclic voltammetry and electrochemical impedance spectroscopy studies, and following by experimental methods of isotope (18O) labeling studies and in situ X-ray absorption spectroscopy (XAS) on both amorphous and crystalline nickel-iron alloy catalysts, it was demonstrated that the amorphous nickel-iron alloy catalyst could be electrochemically activated to expose active sites by applying a positive anodic potential because of the short-range ordering of the amorphous structure. This process greatly increased the number of active sites and thus significantly improved the water oxidation activity. Additionally, the amorphous nickel-iron alloy catalyst with Ni to Fe atomic ratio of 3:1 could reach a water oxidization current density of 10 mA/cm2 at an overpotential of 265 mV (iR corrected) on a glassy carbon electrode, which is 100 mV smaller as compared to the crystalline counterpart. Additionally, by coating the as-prepared amorphous nickel-iron alloy catalyst onto a nickel foam, long term OER stability in 1 M KOH at 80 oC and 500 mA/cm2 could be achieved, rendering the amorphous nickel-iron alloy catalyst practically feasible for high performance water electrolysis. To gain an in-depth understanding of the electronic-performance relationship for OER on amorphous alloy catalysts, we develop the amorphous multimetal alloy catalyst with different electronic structures toward oxygen evolution reaction. In the second work, we provide a room temperature solution technique to synthesis the homogeneously dispersed, amorphous multimetal alloy catalysts. Based on analysis of HAADF-STEM, XPS valence band, electrochemical simulation, and using methanol as a probing molecule to measure binding energy, we success to modulate the 3d electronic structure of amorphous multimetal alloy and thus tune the adsorption energies for oxygenated intermediates. It is demonstrated that near optimal adsorption energy is achieved for oxygenated intermediates by adding high-valence metal (molybdenum) resulting in significantly improved water oxidation activity. Additionally, the amorphous nickel-iron-molybdenum alloy catalyst could reach a water oxidization current density of 10 mA/cm2 at an overpotential of 220 mV on a glassy carbon electrode, which is the best OER catalyst as compared to recently reported works. Additionally, by coating the as-prepared amorphous nickel-iron-molybdenum alloy catalyst onto nickel foam as anode coupled with a crystalline nickel boron catalyst as the hydrogen-evolving cathode, long term OER stability at 80 oC in 6 M KOH and 500 mA/cm2 could be achieved with input voltage around 1.48 V (1.63 V in 1 M KOH at room temperature), making the amorphous nickel-iron-molybdenum alloy catalyst practically feasible for high performance water electrolysis. In this thesis, we revealed the mechanism of amorphous catalyst outperforming much better OER performance than the crystalline counterpart using both in situ and ex situ measurements, demonstrating that the amorphous nickel iron alloy catalyst could be electrochemically activated to expose active sites under an anodic potential due to the short-range ordering structure. And we further successfully designed the OER catalyst, which showed the highest activity over the world, based on the deep comprehension of electronic-performance relationship for OER on the amorphous alloy.Doctor of Philosoph

Dysbiosis of the gut microbiome in elderly patients with hepatocellular carcinoma

Abstract Fecal samples from participants aged 60–80 were collected and sequenced by a high-throughput second-generation sequencer to explore the structural composition of gut microbiota in elderly patients with hepatocellular carcinoma(HCC). Comparison of gut microbiota between patients with hepatocellular carcinoma and healthy controls, α diversity and β diversity were statistically different. At the genus level, compared with the normal group, the abundance of A Blautia , Fusicatenibacter , Anaerostipes, Lachnospiraceae_ND3007_group, CAG-56, Eggerthella, Lachnospiraceae_FCS020_group and Olsenella were decreased significantly in the LC group. In contrast, the abundance of Escherichia-Shigella, Fusobacterium, Megasphaera , Veillonella, Tyzzerella_4, Prevotella_2 and Cronobacter increased significantly. The KEGG and COG pathway analyses showed that the dysbiosis of gut bacteria in primary liver carcinoma is associated with several pathways, including amino acid metabolism, replication and repair, nucleotide metabolism, cell motility, cell growth and death, and transcription. Age is negatively associated with the abundance of Bifidobacterium. Lachnospiraceae_ ND3007_ group, [Eubacterium]_hallii_group, Blautia, Fuscatenibacter and Anaerostipes are negatively correlated with ALT, AST and GGT levels (p < 0.05), respectively. Alpha-fetoprotein (AFP) is positively associated with the abundance of Erysipelatoclostridium, Magasphaera, Prevotella 2, Escherichia-Shigella, Streptococcus and [Eubacterium]_eligens_group (p < 0.05), respectively. A random forest model showed that the genera Eggerthella, Anaerostipes, and Lachnospiraceae_ ND3007_ group demonstrated the best predictive capacity. The area under the Receiver Operating Characteristic Curve of Eggerthella, Anaerostipes and Lachnospiraceae_ ND3007_ group are 0.791, 0.766 and 0.730, respectively. These data are derived from the first known gut microbiome study in elderly patients with hepatocellular carcinoma. Potentially, specific microbiota can be used as a characteristic index for screening, diagnosis, and prognosis of gut microbiota changes in elderly patients with hepatocellular carcinoma and even as a therapeutic clinical target

Effects of Ginsenoside Biopolymer Nanoparticles on the Malignant Behavior of Non-Small-Cell Lung Cancer

Objective. To explore the effects and mechanism of ginsenoside Rg3 nanoparticles on the malignant behavior of non-small-cell lung cancer. Methods. The nanoparticle carriers were prepared by using an electrostatic system, and the coverage of ginsenoside Rg3 was determined by HPLC after coating the nanoparticle carriers with the ginsenoside Rg3 monomer. The proliferation of H125 cells was measured using MTT assay, and the Transwell assay was used to detect the invasiveness of H125 cells. Cell scratch test was used to determine the migration ability of H125 cells, and Western blotting was used to measure the expression level of PTEN in H125 cells; the expression level of miR-192 in H125 cells was measured via RT-qPCR, and the apoptosis level of H125 cells was detected by Tunel assay. Results. Firstly, gelatin nanoparticles and hyaluronic acid nanoparticles were uniformly distributed, uniform in size and spherical in shape, and after coating ginsenoside Rg3, the sizes of the nanoparticles were significantly increased. Secondly, the expression level of miR-192 was upregulated in H125 cells, which could be effectively inhibited by the treatment of Rg3 monomer and HA-Rg3 nanoparticles. Thirdly, the knockdown of miR-192 significantly inhibited H125 cell proliferation, invasion, and migration and also enhanced H125 cell apoptosis. In addition, PTEN was demonstrated as a target gene of miR-192. Finally, by inhibiting the expression level of miR-192 in H125 cells, the Rg3 monomer and HA-Rg3 nanoparticles upregulated the expression of PTEN and thus exerted its antitumor effect; the effects of HA-Rg3 were comparatively more significant than those of the Rg3 monomer. Conclusions. The Rg3 monomer and HA-Rg3 nanoparticles mitigated the malignant behavior of human non-small-cell lung cancer H125 cells through the miR-192/PTEN molecular axis, and HA-Rg3 nanoparticles showed better antitumor effects

In situ/operando characterization techniques to probe the electrochemical reactions for energy conversion

The water‐splitting reaction, including the hydrogen and oxygen evolution reactions, as well as the electrochemical oxygen and CO2 reduction reactions offer promising solutions to address the global energy scarcity and the associated environmental issues. However, the lack of deep insight into the reaction mechanisms and clear identification of the catalytic active sites hinder any breakthrough for the development of efficient electrocatalysts with high performance and durability. Operando characterization techniques allowing in situ monitoring the surface oxidation state and local atomic‐structure transformation are capable of probing the active sites and promoting the fundamental understanding of the reaction mechanism in these systems. Herein, the recent applications of various operando characterization techniques in identifying the active sites and capturing the geometric structure, oxidation state, and local atomic‐structure evolution of the catalysts during water electrolysis and O2/CO2 electroreduction are thoroughly summarized. The challenges and outlook in developing operando techniques to further extend the understanding of the underlying mechanism during electrochemical energy‐conversion reactions are discussed

CBGRU: A Detection Method of Smart Contract Vulnerability Based on a Hybrid Model

In the context of the rapid development of blockchain technology, smart contracts have also been widely used in the Internet of Things, finance, healthcare, and other fields. There has been an explosion in the number of smart contracts, and at the same time, the security of smart contracts has received widespread attention because of the financial losses caused by smart contract vulnerabilities. Existing analysis tools can detect many smart contract security vulnerabilities, but because they rely too heavily on hard rules defined by experts when detecting smart contract vulnerabilities, the time to perform the detection increases significantly as the complexity of the smart contract increases. In the present study, we propose a novel hybrid deep learning model named CBGRU that strategically combines different word embedding (Word2Vec, FastText) with different deep learning methods (LSTM, GRU, BiLSTM, CNN, BiGRU). The model extracts features through different deep learning models and combine these features for smart contract vulnerability detection. On the currently publicly available dataset SmartBugs Dataset-Wild, we demonstrate that the CBGRU hybrid model has great smart contract vulnerability detection performance through a series of experiments. By comparing the performance of the proposed model with that of past studies, the CBGRU model has better smart contract vulnerability detection performance

Design of hierarchical, three‐dimensional free‐standing single‐atom electrode for H2O2 production in acidic media

Abstract Electrochemical reduction of molecular O2 to hydrogen peroxide (H2O2) offers a promising solution for water purification and environmental remediation. Here, we design a hierarchical free‐standing single‐Co‐atom (with Co–N4 coordination) electrode for oxygen reduction reaction (ORR) via a two‐electron pathway to make H2O2 in acidic media. The current density of the single‐Co‐atom electrode reached 51 mA/cm2 at 0.1 V vs reversible hydrogen electrode, lasting for more than 10 hours of continuous operation with H2O2 selectivity greater than 80%. Toward practical application, the single‐Co‐atom electrode was directly used to assemble an electrochemical cell to produce H2O2 at a rate of 676 mol/kgcat/h with a cell voltage of about 1.6 V

SPCBIG-EC: A Robust Serial Hybrid Model for Smart Contract Vulnerability Detection

With countless devices connected to the Internet of Things, trust mechanisms are especially important. IoT devices are more deeply embedded in the privacy of people&rsquo;s lives, and their security issues cannot be ignored. Smart contracts backed by blockchain technology have the potential to solve these problems. Therefore, the security of smart contracts cannot be ignored. We propose a flexible and systematic hybrid model, which we call the Serial-Parallel Convolutional Bidirectional Gated Recurrent Network Model incorporating Ensemble Classifiers (SPCBIG-EC). The model showed excellent performance benefits in smart contract vulnerability detection. In addition, we propose a serial-parallel convolution (SPCNN) suitable for our hybrid model. It can extract features from the input sequence for multivariate combinations while retaining temporal structure and location information. The Ensemble Classifier is used in the classification phase of the model to enhance its robustness. In addition, we focused on six typical smart contract vulnerabilities and constructed two datasets, CESC and UCESC, for multi-task vulnerability detection in our experiments. Numerous experiments showed that SPCBIG-EC is better than most existing methods. It is worth mentioning that SPCBIG-EC can achieve F1-scores of 96.74%, 91.62%, and 95.00% for reentrancy, timestamp dependency, and infinite loop vulnerability detection

Identifying active sites of nitrogen-doped carbon materials for the CO2 reduction reaction

Nitrogen-doped carbon materials are proposed as promising electrocatalysts for the carbon dioxide reduction reaction (CRR), which is essential for renewable energy conversion and environmental remediation. Unfortunately, the unclear cognition on the CRR active site (or sites) hinders further development of high-performance electrocatalysts. Herein, a series of 3D nitrogen-doped graphene nanoribbon networks (N-GRW) with tunable nitrogen dopants are designed to unravel the site-dependent CRR activity/selectivity. The N-GRW catalyst exhibits superior CO2 electrochemical reduction activity, reaching a specific current of 15.4 A gcatalyst−1 with CO Faradaic efficiency of 87.6% at a mild overpotential of 0.49 V. Based on X-ray photoelectron spectroscopy measurements, it is experimentally demonstrated that the pyridinic N site in N-GRW serves as the active site for CRR. In addition, the Gibbs free energy calculated by density functional theory further illustrates the pyridinic N as a more favorable site for the CO2 adsorption, *COOH formation, and *CO removal in CO2 reduction.NRF (Natl Research Foundation, S’pore)ASTAR (Agency for Sci., Tech. and Research, S’pore)MOE (Min. of Education, S’pore