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Urban traffic accidents impose a significant threat to public safety because of its frequent occurrence and potential for severe injuries and fatalities. Hence, an effective analysis of accident patterns is crucial for designing accident prevention strategies. Recent advancement in data analytics have provided opportunities to improve the pattern of urban traffic accidents. However, the existing works face several challenges in adapting the complex dynamics, and heterogeneity of the accident data. To overcome these challenges, we proposed an innovative solution by combining the K-means clustering and Support Vector Machine to precisely predict the traffic accident patterns. By leveraging the efficiencies of clustering technique and machine learning, this work intends to identify the intricate patterns within the traffic database. Initially, a traffic accident database was collected and fed into the system. The collected database was pre-processed to improve and standardize the raw dataset. Further, cluster analysis is employed to identify distinct patterns within the dataset and group similar accidents into clusters. This clustering enables the system to recognize common accident scenarios and identify recent accident trends. Subsequently, a Support Vector Machine is deployed to classify accidents into distinct categories through intensive training with identified clusters. The combination enables the system to understand the complex relationships among diverse accident variables, making it an effective framework for real-time pattern recognition. The proposed strategy is implemented in Python and validated using the publicly available traffic accident database. The experimental results manifest that the proposed method achieved 99.65% accuracy, 99.53% precision, 99.62% recall, and 99.57% f-measure. Finally, the comparison with the existing techniques shows that the developed strategy offers improved accuracy, precision, recall, and f-measure compared to existing ones. shows that the developed strategy offers improved accuracy, precision, recall, and f-measure compared to existing ones. [ABSTRACT FROM AUTHOR]

Cysteine thiols are susceptible to various oxidative posttranslational modifications (PTMs) due to their high chemical reactivity. Thiol‐based PTMs play a crucial role in regulating protein functions and are key contributors to cellular redox signaling. Although reversible thiol‐based PTMs, such as disulfide bond formation, S‐nitrosylation, and S‐glutathionylation, have been extensively studied for their roles in redox regulation, thiol sulfinic acid (–SO2H) modification is often perceived as irreversible and of marginal significance in redox signaling. Here, we revisit this narrow perspective and shed light on the redox regulatory roles of –SO2H in plant stress signaling. We provide an overview of protein sulfinylation in plants, delving into the roles of hydrogen peroxide‐mediated and plant cysteine oxidase‐catalyzed formation of –SO2H, highlighting the involvement of –SO2H in specific regulatory signaling pathways. Additionally, we compile the existing knowledge of the –SO2H reducing enzyme, sulfiredoxin, offering insights into its molecular mechanisms and biological relevance. We further summarize current proteomic techniques for detecting –SO2H and furnish a list of experimentally validated cysteine –SO2H sites across various species, discussing their functional consequences. This review aims to spark new insights and discussions that lead to further investigations into the functional significance of protein –SO2H‐based redox signaling in plants. [ABSTRACT FROM AUTHOR]

Four trinucleotides 5′-ATA-3′ (I), 5′-ATC-3′ (II), 5′-CTA-3′ (III) and 5′-CTC-3′ (IV) were introduced to interact with a diazido-based photoactivatable anticancer prodrug trans,trans,trans-[PtIV(N3)2(OH)2(py)2] (py = pyridine; 1) upon light irradiation. Using electrospray ionization mass spectrometry (ESI-MS), we aimed to investigate the possibility of 1,3-intrastrand crosslinks at adenine and/or cytosine in the trinucleotides via the bi-functional trans-[PtII(py)2]2+ species generated by photodecomposition of complex 1. The primary mass spectrometry results showed that although mono- and di-platinated trinucleotides bound by mono-functional trans-[PtII(N3)(py)2]+ species were the major platinated adducts, comparable amounts of bifunctional trans-[PtII(py)2]2+-bound trinucleotides were also observed. Further tandem mass spectrometry of the trans-[PtII(py)2]2+-bound trinucleotides showed the formation of 1,3-crosslinks between adenine–adenine, adenine–cytosine and cytosine–cytosine bases in the trinucleotides. The formation of such unique structures is not only distinct from the action modes of cisplatin with DNA but also an important complement to the acknowledged 1,3-GNG intrastrand crosslink by trans-Pt species, which may support the promising and distinct anticancer activities of such photoactivatable diazido Pt(IV) anticancer prodrugs and deserve further studies. [ABSTRACT FROM AUTHOR]

Summary: The binding sites between zinc chelating peptide (ZCP) and zinc have not been clearly understood at the quantum chemistry level. Ala‐Ser‐His (ASH), a new ZCP located in the cruciferin precursor, was identified from in vitro digestion hydrolysate of rapeseed (Brassica napus) protein. Also, ASH exerted the concentration value of 114.09 ± 0.98 mM showing 50% zinc chelating activity. The prepared ASH–Zn (ZCP‐zinc chelate), displayed varying characteristics from ASH on surface microstructures, X‐ray photon energies, and infrared spectrum. The geometric structure of ASH–Zn with minimum free energy was obtained using density functional theory, producing a bridge bond of O21–Zn41–O32 between Ser and His residues. Based on the basic set of 6–311++G (d, p), O21–Zn 41 and O32–Zn41, respectively, had bond lengths of 1.96503 Å and 1.94515 Å, while O21–Zn41–O32 displayed a bond angle of 136.41069°. These findings further promote research on rapeseed proteins providing new possibilities for studying peptide‐metal chelates. [ABSTRACT FROM AUTHOR]

An accurate measurement of greenhouse gas emissions serves as foundation for creation of adequate mitigation measures. In this context, a significant prerequisite is the development of protocols for measuring emissions and methods for data analysis that can extrapolate precise annual emission values. Quantifying the emissions of greenhouse gases (GHGs) from irrigated paddy fields is crucial for combating climate change. We present an electro-optic hardware platform for optical neural networks' nonlinear activation functions. With no slowdown in processing speed, the optical-to-optical nonlinearity works by transforming a small amount of the input optical signal into an analogue electric signal, which is then utilised to intensity-modulate the original optical signal. Using machine learning methods, this study proposes a novel method for detecting anthropogenic greenhouse gases from food products and managing carbon footprints. Multilayer kernel vector expectile regression (MKVEx) is utilized to examine presence of anthropogenic greenhouse gases in this food product as an input. After that, quadrature convolutional genetic neural networks (QCGNN) are used to developed explicitly for use on unstructured data like carbon footprints and cut down on energy and carbon emissions. In terms of sensitivity, positive predictive value, negative predictive value, training accuracy, and precision, various food product greenhouse gas datasets have been the subject of experimental analysis. The proposed technique attained sensitivity of 65%, positive predictive value of 59%, negative predictive value of 59%, training accuracy of 98%, precision of 95%. [ABSTRACT FROM AUTHOR]

Background: With the coming of the aging society, the incidence of elderly nasopharyngeal carcinoma (NPC) has been increasing which may result in considerable disease burden; however, the optimal treatment strategy for elderly patients is still debatable. Methods and Results: Clinical data on 294 elderly NPC patients aged ≥70 treated between 2009 and 2019 was analyzed. Kaplan–Meier method was used to estimate overall survival (OS) and cancer‐specific survival (CSS) rates. With a median follow‐up of 53.25 months, the 5‐year estimated OS and CSS for the entire group were 59.5% and 69.8%, respectively. 146 patients died within the follow‐up period, of which recurrence + metastasis (48%) and internal medical disease unrelated to NPC (32%) are the primary causes of death. On univariable analysis, (IMRT vs. 3D‐CRT) (p = 0.001; p = 0.000), T stage (p = 0.001; p = 0.000), N stage (p = 0.013; p = 0.000) and clinical stage (p = 0.000; p = 0.000) were associated with OS and CSS; Charlson Comorbidity Index (CCI) (p = 0.016) was associated with OS. The addition of chemotherapy (CT) correlated with better CSS (p = 0.039), but did not improve OS (p = 0.056) for stage III–IV subgroup. On multivariate analysis, advanced clinical stage independently predicted poorer OS (p = 0.002) and CSS (p = 0.000). In addition, the application of IMRT was an independent protective factor on both OS (p = 0.028) and CSS (p = 0.030). Conclusion: IMRT is a reasonable treatment strategy to improve survival for elderly NPC patients aged over 70 years; consideration of adding chemotherapy for elderly population should be weighed carefully. [ABSTRACT FROM AUTHOR]

With the development of industrial and agricultural, a large amount of nitrate is produced, which not only disrupts the natural nitrogen cycle, but also endangers public health. Among the commonly used nitrate treatment techniques, the electrochemical nitrate reduction reaction (eNRR) has attracted extensive attention due to its mild conditions, pollution‐free nature, and other advantages. An in‐depth understanding of the eNRR mechanism is the prerequisite for designing highly efficient electrocatalysts. However, some traditional characterization tools cannot comprehensively and deeply study the reaction process. It is necessary to develop in situ and operando techniques to reveal the reaction mechanism at the time‐resolved and atomic level. This review discusses the eNRR mechanism and summarizes the possible in situ techniques used in eNRR. A detailed introduction of various in situ techniques and their help in understanding the reaction mechanism is provided. Finally, the current challenges and future opportunities in this research area are discussed and highlighted. [ABSTRACT FROM AUTHOR]

Significance: Hydrogen sulfide (H2S) is a multitasking potent regulator that facilitates plant growth, development, and responses to environmental stimuli. Recent Advances: The important beneficial effects of H2S in various aspects of plant physiology aroused the interest of this chemical for agriculture. Protein cysteine persulfidation has been recognized as the main reduction–oxidation (redox) regulatory mechanism of H2S signaling. An increasing number of studies, including large-scale proteomic analyses and functional characterizations, have revealed that H2S-mediated persulfidations directly regulate protein functions, altering downstream signaling in plants. To date, the importance of H2S-mediated persulfidation in several abscisic acid signaling-controlling key proteins has been assessed as well as their role in stomatal movements, largely contributing to the understanding of the plant H2S-regulatory mechanism. Critical Issues: The molecular mechanisms of the H2S sensing and transduction in plants remain elusive. The correlations of H2S-mediated persulfidation with other oxidative post-translational modifications of cysteines are still to be explored. Future Directions: Implementation of advanced detection approaches for the spatiotemporal monitoring of H2S levels in cells and the current proteomic profiling strategies for the identification and quantification of the cysteine site-specific persulfidation will provide insight into the H2S signaling in plants. Antioxid. Redox Signal. 39, 40–58. [ABSTRACT FROM AUTHOR]

Background: The target population for women's sexual health services in China was unclear. To identify high-risk individuals with psychological barriers to sexual health-seeking behaviors and those at high risk of hypoactive sexual desire disorder (HSDD), we investigated correlates of Chinese women's unwillingness to communicate sexual health, the shame of sexual health-related disorders, sexual distress, and HSDD. Methods: An online survey was conducted from April to July 2020. Results: We received 3443 valid responses online (effective rate 82.6%). Participants were mainly Chinese urban women of childbearing age (median 26 years old, Q1-Q3 23–30). Women who knew little about sexual health knowledge (aOR 0.42, 95%CI 0.28–0.63) and were ashamed (aOR 0.32–0.57) of sexual health-related disorders were less willing to communicate sexual health. Age (aOR 4.29, 95%CI 2.26–8.17), low income (aOR 1.52–2.11), family burden (aOR 1.34–1.43), and living with friends (aOR 1.39, 95%CI 1.02–1.91) were independent correlates of women's shame about sexual health-related disorders while living with a spouse (aOR 0.66, 95%CI 0.51–0.86) or children (aOR 0.77, 95%CI 0.62–0.96) were correlated with less shame. Age (aOR 0.98, 95%CI 0.96–0.99) and a postgraduate degree (aOR 0.45, 95%CI 0.28–0.71) were linked with less sexual distress of low sexual desire while having children (aOR 1.38–2.10), intense work pressure (aOR 1.32, 95%CI 1.10–1.60) and heavy family burden (aOR 1.43, 95%CI 1.07–1.92) increased women's odds of having distress. Women with a postgraduate degree (aOR 0.42, 95%CI 0.19–0.90), more knowledge about sexual health (aOR 0.53–0.67), and decreased sexual desire caused by pregnancy, recent childbirth, or menopausal symptoms (aOR 0.60, 95%CI 0.41–0.85) were less likely to have HSDD, while they were more likely to have HSDD when their decreased sexual desire was due to other sexual issues (aOR 2.56, 95%CI 1.84–3.57) and partners' sexual problems (aOR 1.72, 95%CI 1.23–2.39). Conclusion: Sexual health education and related services need to focus on psychological barriers of women with older age, insufficient knowledge of sexual health, intense work pressure, and poor economic conditions. The medical staff need to pay attention to the sexual health of women with intense work or life pressure and a history of gynecological disease. Low sexual desire is not equal to the sexual desire problem, which should be noticed in the future. [ABSTRACT FROM AUTHOR]

Reactive electrophilic species are ubiquitous in plant cells, where they contribute to specific redox-regulated signaling events. Redox signaling is known to modulate gene expression during diverse biological processes, including plant growth, development, and environmental stress responses. Emerging data demonstrates that transcription factors (TFs) are a main target of cysteine thiol-based oxidative post-translational modifications (OxiPTMs), which can alter their transcriptional activity and thereby convey redox information to the nucleus. Here, we review the significant progress that has been made in characterizing cysteine thiol-based OxiPTMs, their biochemical properties, and their functional effects on plant TFs. We discuss the underlying mechanism of redox regulation and its contribution to various physiological processes as well as still outstanding challenges in redox regulation of plant gene expression. Reactive electrophilic species, including reactive oxygen, nitrogen, and sulfur species (ROS/RNS/RSS), actively contribute to redox signal transduction in diverse signaling processes. Hydrogen peroxide (H 2 O 2), nitric oxide (NO), and hydrogen sulfide (H 2 S) are the most studied ROS/RNS/RSS, respectively. The biological function of H 2 O 2 /NO/H 2 S is largely governed through oxidative post-translational modifications (OxiPTMs) of proteins that impact protein function. An expanding list of transcription factors undergoes OxiPTMs and has been found to contribute to redox signaling–regulated transcription reprogramming in plant development and stress responses. OxiPTMs can alter the DNA binding ability, subcellular localization, protein stability, phase separation, and/or protein–protein interactions of transcription factors. [ABSTRACT FROM AUTHOR]

MXenes have shown great potential application in new electronic devices owing to the unique surface properties and 2D structure, especially in the popular memory storage. In this work, Ti 3 C 2 T x , one of the MXenes, is partially oxidized and used as the resistance layer to fabricate memristors with resistance switching characteristics and synapse characteristics. The device exhibits excellent bipolar resistance switching property based on the gradual formation and annihilation of the conductive filaments of oxygen vacancy cation, including enough on/off ratio (≈102), long cyclic endurance (>103 cycles) and retention time (>104 s). Furthermore, since oxygen vacancy cation migration is similar to the Ca2+ ion dynamics of biological synapses, the device successfully mimics biological synaptic functions such as paired-pulse facilitation (PPF), long-term potentiation (LTP) and long-term depression (LTD). This work provides the experimental and theoretical foundation for MXenes in memristor and artificial synapse filed, pushes the development of MXenes in neurocomputing application. A novel nonvolatile memory device based on oxidized Ti 3 C 2 T x MXene with threshold resistance switching characteristics and synapse characteristics is demonstrated to realize the function of computing in memory in neurocomputing application. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper, we mainly use recurrence plot, recurrence quantification analysis and cross recurrence plot to investigate the potential nonlinear dynamical characteristics of the stock market. In addition, we introduce and analyze the capital asset pricing model (CAPM), which can analyze the correlation between returns and risks of stock price data. In particular, we selected the large-cap stocks represented by SSE 50 index and the small-cap stocks represented by CSI 500 index as our research objects. Through the recurrence plot analysis of the time series of β factor of CAPM and the time series of the stock market, we can find the advantages of large-cap stocks, such as stronger stationarity and long-term certainty, the disadvantages of small-cap stocks, such as greater risk and information, and nonlinear cross recurrence with the stock market. [ABSTRACT FROM AUTHOR]

Deep learning algorithms such as AlphaFold2 predict three-dimensional protein structure with high confidence. The recent release of more than 200 million structural models provides an unprecedented resource for functional protein annotation. Here, we used AlphaFold2 predicted structures of fifteen plant proteomes to functionally and evolutionary analyze cysteine residues in the plant kingdom. In addition to identification of metal ligands coordinated by cysteine residues, we systematically analyzed cysteine disulfides present in these structural predictions. Our analysis demonstrates most of these predicted disulfides are trustworthy due their high agreement (∼96%) with those present in X-ray and NMR protein structures, their characteristic disulfide stereochemistry, the biased subcellular distribution of their proteins and a higher degree of oxidation of their respective cysteines as measured by proteomics. Adopting an evolutionary perspective, zinc binding sites are increasingly present at the expense of iron-sulfur clusters in plants. Interestingly, disulfide formation is increased in secreted proteins of land plants, likely promoting sequence evolution to adapt to changing environments encountered by plants. In summary, Alphafold2 predicted structural models are a rich source of information for studying the role of cysteines residues in proteins of interest and for protein redox biology in general. [Display omitted] • AlphaFold2 predictions enable proteome-wide structural annotation of cysteines forming disulfides or binding metal ligands. • Disulfide formation is highly compartmentalized and in line with the subcellular redox environment. • Zinc binding sites are increasingly present throughout plant evolution, at the expense of iron-sulfur clusters. • Secreted proteins in land plants are richer in disulfides, likely facilitating adaptations to terrestrial habitats. • Protein structure predictions can hint towards intermolecular disulfides and cysteine-bound cofactors such as heme. [ABSTRACT FROM AUTHOR]

Salt stress is a critical limiting factor for rice growth and production. Although numerous salt-tolerant genes have been identified, the mechanism underlying salt stress tolerance in rice remains unclear. This study reports the need for an uncharacterized WRKY transcription factor OsWRKY54 for rice salt-tolerance. Salt stress resulted in a rapid induction of OsWRKY54 expression in roots. Immunostaining analysis showed that it was mainly expressed in the stele. The loss of OsWRKY54 resulted in greater Na accumulation in shoots and enhanced sensitivity of rice plants to salt stress. The real-time quantitative PCR (qRT-PCR) and transcriptome analysis revealed that OsWRKY54 regulated the expression of some essential genes related to salt tolerance, such as OsNHX4 and OsHKT1;5. Furthermore, OsWRKY54 was found to regulate OsHKT1;5 expression by directly binding to the W-box motif in its promoter. Thus, these results indicated that OsWRKY54 was a critical regulatory factor in salt tolerance in rice. [ABSTRACT FROM AUTHOR]

In recent years, robust performance of the system has been broadly studied as a trending topic among a vast array of scholars. This paper discusses the robustness of control laws for complex dynamic networks (CDNs) with a deviation argument. We design two categories of control laws (linear control law and nonlinear control law) for the undisturbed CDNs to achieve exponential synchronization. It is intractable to ascertain the range of the deviation function exactly. Hence, some corresponding sufficient criteria are put forward to ensure exponential synchronization of CDNs with deviation argument when control laws are not changed. By adopting the Gronwall–Bellman lemma and solving the transcendental equation, we can obtain the admissible upper limits of the deviating function, to keep the corresponding control laws. In comparison with previous research findings, robustness, deviating argument, and control laws are all considered in this study, which enhances the previous findings. Finally, two emulation examples verify the validity of the analysis. [ABSTRACT FROM AUTHOR]

Identification of embedding dimension is helpful to the reconstruction of phase space. However, it is difficult to calculate the proper embedding dimension for the financial time series of dynamics. By this Letter, we suggest a new method based on Manhattan distance and recurrence quantification analysis for determining the embedding dimension. By the advantages of the above two tools, the new method can calculate the proper embedding dimension with the feature of stability, accuracy and rigor. Besides, it also has a good performance on the chaotic time series which has a high-dimensional attractors. [ABSTRACT FROM AUTHOR]

• MDD has substantial changes in the structure and function of gut microbiota. • MDD exhibited decreased amino acids and bile acids and increased lipids in blood. • The changes of blood immune cell subtypes of MDD tend to promote inflammation. • MDD could be divided into two immune subtypes, and one is correlated with relapse. • We revealed integrative discriminative signatures for distinguishing MDD from HC. Major depressive disorder (MDD) involves systemic changes in peripheral blood and gut microbiota, but the current understanding is incomplete. Herein, we conducted a multi-omics analysis of fecal and blood samples obtained from an observational cohort including MDD patients (n = 99) and healthy control (HC, n = 50). 16S rRNA sequencing of gut microbiota showed structural alterations in MDD, as characterized by increased Enterococcus. Metagenomics sequencing of gut microbiota showed substantial functional alterations including upregulation in the superpathway of the glyoxylate cycle and fatty acid degradation and downregulation in various metabolic pathways in MDD. Plasma metabolomics revealed decreased amino acids and bile acids, together with increased sphingolipids and cholesterol esters in MDD. Notably, metabolites involved in arginine and proline metabolism were decreased while sphingolipid metabolic pathway were increased. Mass cytometry analysis of blood immune cell subtypes showed rises in proinflammatory immune subsets and declines in anti-inflammatory immune subsets in MDD. Furthermore, our findings revealed disease severity-related factors of MDD. Interestingly, we classified MDD into two immune subtypes that were highly correlated with disease relapse. Moreover, we established discriminative signatures that differentiate MDD from HC. These findings contribute to a comprehensive understanding of the MDD pathogenesis and provide valuable resources for the discovery of biomarkers. [ABSTRACT FROM AUTHOR]

Generally, in-depth learning has been extensively employed in numerous industries to enhance the growth of economic globalization since the dawn of the big data age. At the same time, the demand for foreign language talent has risen dramatically, and more and more businesses are steadily raising their English proficiency standards. International interactions, as well as scientific and technical exchanges, are influenced by English communicating competence. As a result, colleges and universities place a high value on students studying English. However, English learning is also a compulsory course in Colleges and universities, which is different from other courses. Therefore, in setting teaching objectives, arranging teaching activities, and compiling teaching contents, we should highlight students' personalized needs and formulate learning plans in combination with the individual requirements of each student. Aiming at this problem, this paper adopts the deep learning method to study the personalized learning of College English. Deep learning algorithm utilization in the development of college students' English learning reduces teachers' workload and focuses more on students' personalized needs, which is beneficial to teachers' teaching and students' learning. By analyzing the deep learning neural network model, the process of English speech recognition is described, and the characteristic parameters of English speech are extracted. Then compare and explain the characteristics of deep learning and shallow learning, analyze the relationship between them, and clarify the route of deep learning. Finally, the effect of College Students' personalized learning is analyzed by random sampling, and the effect of College English personalized learning based on deep learning is explained from two aspects: listening effect and reading practice. [ABSTRACT FROM AUTHOR]

In this paper, the influence of Nano-silica (NS) and Polyvinyl alcohol (PVA) fibers on the corrosion behavior of steel rebar embedded in high-volume fly ash cement mortars under accelerated chloride attack was studied by using an impressed voltage technique. The PVA fibers used were 1.0 vol.%, and two mass fractions of cement (50 and 60 wt.%) were replaced by fly ash. Four NS mass fractions (0, 0.5, 1.0, and 1.5 wt.%) were utilized in this paper. In addition, the mono and hybrid effects of NS and PVA on the mechanical properties and water absorption of mortar were also studied. The results showed that the incorporation of PVA and nano-SiO2 can improve the flexural and compressive strengths of high-volume fly ash mortar. Generally, the flexural and compressive strengths increased with the increase of nano-SiO2 content. Moreover, the incorporation NS can also reduce the capillary water–absorption rate of cement mortar. The impressed voltage corrosion test indicated that the composite incorporation of nano-SiO2 and PVA can significantly delay the deterioration process of steel bars in mortar, effectively reducing the steel rebar's corrosion level and increasing the exposure time of the surface crack. With hybrid-incorporation 1.0 vol.% PVA and 1.0 wt.% nano-SiO2, the steel rebar had the lowest corrosion degree, which exhibited a mass loss of 49% and increased the broken time by 71% as compared to the control mortar. [ABSTRACT FROM AUTHOR]

In the era of artificial intelligence, the traditional English teaching methods cannot meet the increasing demand of course learning at this stage. Therefore, in this paper, a brand-new English teaching model based on strategic reasoning mechanism is designed by analyzing the problems faced by construction of network curriculum in universities. By introducing the idea of artificial intelligence, the student model and teacher model are designed, and the separation of teaching content and teaching strategy is realized. The development of the system adopts B/S structure and relies on lightweight J2EE multitier framework. At the same time, the overall architecture, functions, and processes of the teaching system are analyzed and designed. The system is convenient to transplant and expand, which has certain practical value and can provide reference for the design of various teaching systems and the innovation of teaching modes. [ABSTRACT FROM AUTHOR]

Background: Levels of inflammatory markers are elevated in patients with psychological disorders. However, anti-psychological drugs have an effect on proinflammatory cytokine production and disturb their relationship. Limited evidence focuses on the inflammatory marker profile of psychological status before treatment. This study aimed to investigate the inflammatory biomarker profiles of psychological treatment-naive individuals.Methods: We included 790 psychological treatment-naive individuals from a longitudinal cohort study of Midlife in the United States (MIDUS). Symptoms of depression, anxiety, and stress were assessed by the Center for Epidemiologic Studies Depression Scale (CES-D) subscales, the Social Anxiety Scale (STAI), and Liebowitz Social Anxiety Scale (LSAS), the Perceived Stress Scale (PSS), respectively.Results: Spearman correlation analysis showed that a higher CESD total score was correlated with higher CRP (p=0.009), IL-6 (p=0.007), fibrinogen (p=0.036), E-selectin (p=0.018), ICAM-1 (p=0.013), and IL-8 (p=0.05) levels. Multivariate linear regression analysis showed that the CESD total score was positively associated with the levels of IL-6 (p=0.024) after adjustments. Moreover, the perceived stress score (PSS) was negatively associated with the levels of IL-8 (p=0.025). However, these associations were not significant after multiple testing (p=0.088, 0.091, respectively).Limitations: The casual relationship cannot be drawn due to the cross-sectional design CONCLUSION: Overall, our results suggested IL-6 and IL-8 might play a important role in the pathogenesis of psychological disorder. Larger and longitude studies are needed to confirm our results. [ABSTRACT FROM AUTHOR]

Background: The aerial organs of most terrestrial plants are covered by cuticular waxes, which impart plants a glaucous appearance and play important roles in protecting against various biotic and abiotic stresses. Despite many glossy green (wax-defective) mutants being well characterized in model plants, little is known about the genetic basis of glossy green mutant in broccoli. Results: B156 is a spontaneous broccoli mutant showing a glossy green phenotype. Detection by scanning electron microscopy (SEM) and chromatography-mass spectrometry (GC-MS) revealed that B156 is a cuticular wax-defective mutant, lacking waxes mostly longer than C28. Inheritance analysis revealed that this trait was controlled by a single recessive gene, BoGL5. Whole-genome InDel markers were developed, and a segregating F2 population was constructed to map BoGL5. Ultimately, BoGL5 was mapped to a 94.1 kb interval on C01. The BoCER2 gene, which is homologous to the Arabidopsis CER2 gene, was identified as a candidate of BoGL5 from the target interval. Sequence analyses revealed that Bocer2 in B156 harbored a G-to-T SNP mutation at the 485th nucleotide of the CDS, resulting in a W-to-L transition at the 162nd amino acid, a conserved site adjacent to an HXXXD motif of the deduced protein sequence. Expression analysis revealed that BoCER2 was significantly down-regulated in the leaves, stems, and siliques of B156 mutant than that of B3. Last, ectopic expression of BoCER2 in A. thaliana could, whereas Bocer2 could not, rescue the phenotype of cer2 mutant. Conclusions: Overall, this study mapped the locus determining glossy phenotype of B156 and proved BoCER2 is functional gene involved in cuticular wax biosynthesis which would promotes the utilization of BoCER2 to enhance plant resistance to biotic and abiotic stresses, and breeding of B. oleracea cultivars with glossy traits. [ABSTRACT FROM AUTHOR]

GTPase-activating protein (GAP) is a negative regulator of GTPase protein that is thought to promote the conversion of the active GTPase-GTP form to the GTPase-GDP form. Based on its ability to regulate GTPase proteins and other domains, GAPs are directly or indirectly involved in various cell requirement processes. We reviewed the existing evidence of GAPs regulating regulated cell death (RCD), mainly apoptosis and autophagy, as well as some novel RCDs, with particular attention to their association in diseases, especially cancer. We also considered that GAPs could affect tumor immunity and attempted to link GAPs, RCD and tumor immunity. A deeper understanding of the GAPs for regulating these processes could lead to the discovery of new therapeutic targets to avoid pathologic cell loss or to mediate cancer cell death. [ABSTRACT FROM AUTHOR]

The high-frequency resonant dc transformer (DCT) becomes popular in hybrid ac/dc microgrids, thanks to its good bidirectional power transmission (PT) ability and high power density. However, its application is limited by either the complex systematic control or the complicated parameter design. To solve this problem, in this article, a multitime scale frequency regulation approach is put forward for a general CLLC-DCT (GCLLC-DCT). By establishing the general model of the resonant DCT, the relationship between the transmitted power and the resonant frequency is derived at first. Afterward, the power trigger mechanism is introduced to assist the implementation of the proposed approach. If the long-time scale control is triggered, only once calculation based on the PT requirement will be introduced to avoid redundant computations. If the short-time scale control is triggered, the frequency regulation based on the voltage conversion gain feature of GCLLC-DCT will be executed till it reaches a new steady state, which is beneficial to ensure the real-time control precision. The cooperation of the short-time and long-time scale control is also presented to make the proposed approach easily implement at hybrid ac/dc microgrids. The lab-scale prototype of GCLLC-DCT has been set up based on a hybrid ac/dc microgrid to verify the superiority of the proposed approach. [ABSTRACT FROM AUTHOR]

Background: Major depressive disorder is the second leading cause of years lost to disability worldwide. Anyu Peibo Capsule has been shown to be effective and safe in phase II trials.Methods: This clinical study is a multi-center, randomized, double-blinded, placebo-controlled, parallel-group, phase III trial of Anyu Peibo Capsule in China. The aim is to test whether the administration of Anyu Peibo Capsule compared to placebo improves clinical outcomes in adults (aged 18 to 65 years) with MDD. Patients will receive an 8-week treatment of Anyu Peibo Capsule 1.6 g per day or placebo. The primary outcome will be the change from baseline in the total score for the Montgomery-Asberg Depression Rating Scale at the end of the 8-week treatment.Discussion: The trial aims to provide pivotal evidence for the efficacy and safety of Anyu Peibo Capsule in patients with major depressive disorder.Trial Registration: ClinicalTrials.gov NCT04210973 . Registered on December 26, 2019. [ABSTRACT FROM AUTHOR]

Deep eutectic solvents (DESs), as a new type of eco‐friendly solvent, have attracted increasing attention on the extraction and separation of flavonoid compounds from various samples, owing to their excellent properties such as biodegradability and ease of handling with very low toxicity. This article provides a status review of the applications of DESs in the extraction of flavonoids, including the introduction of flavonoid compounds, the properties and superiority of DESs, and extraction methods (ultrasonic‐assisted extraction, heating reflux extraction, matrix solid‐phase dispersion, and solid‐phase extraction). Finally, prospects and challenges in the application of DESs on extraction and separation are extensively elucidated and critically reviewed. [ABSTRACT FROM AUTHOR]

Purpose: To explore the feasibility of automatic detection based on air flow and blood oxygen in patients with sleep disordered breathing. Methods: This study proposes a new automated detection method for sleep disordered breathing based on overnight airflow and blood oxygen saturation (SaO2). In this regard, local range (LR) of the airflow was adopted to detect apnea events and the SaO2 sudden drops were used to help determine hypopnea events. Pearson correlation index was used to evaluate the relationship between the two automated methods (this study vs. Remlogic software) and the manual reports. Error and mean absolute error (MAE) were used to assess the two automated methods. Results: For all patients, the apnea–hypopnea index (AHI), apnea index (AI) and hypopnea index (HI) for our automated scoring and manual reports were highly correlated (the Pearson correlation index were 0.996, 0.995 and 0.928, respectively, P < 0.001). However, HI for Remlogic automated scoring and clinical manual reports was poorly correlated (r = 0.316, P < 0.001). Compared with the manual reports, mean absolute error of AHI, AI and HI between the two automated methods (this study vs. Remlogic software) were statistically significant (P < 0.0001). Furthermore, among the three subgroups (group 1, AHI < 15/h, group 2, 15/h ≤ AHI < 30/h and group 3, AHI ≥ 30/h), the mean error and MAE of AHI between the two automated methods were also statistically significant (P < 0.01). Conclusions: Generally, good agreements were shown between our automated detection and clinical reports. This procedure is robust and effective, which would significantly shorten the analysis time. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a gastrointestinal malignancy originating from either the colon or the rectum. A growing number of researches prove that the unfolded protein response (UPR) is closely related to the occurrence and progression of colorectal cancer. The UPR has three canonical endoplasmic reticulum (ER) transmembrane protein sensors: inositol requiring kinase 1 (IRE1), pancreatic ER eIF2α kinase (PERK), and activating transcription factor 6 (ATF6). Each of the three pathways is closely associated with CRC development. The three pathways are relatively independent as well as interrelated. Under ER stress, the activated UPR boosts the protein folding capacity to maximize cell adaptation and survival, whereas sustained or excessive ER triggers cell apoptosis conversely. The UPR involves different stages of CRC pathogenesis, promotes or hinders the progression of CRC, and will pave the way for novel therapeutic and diagnostic approaches. Meanwhile, the correlation between different signal branches in UPR and the switch between the adaptation and apoptosis pathways still need to be further investigated in the future. [ABSTRACT FROM AUTHOR]

In this letter, an event-triggered model predictive control (ET-MPC) method for power converters is presented. In the proposed method, the model predictive control (MPC) scheme is triggered only when the state of the converter exceeds a preset threshold; otherwise, the MPC scheme is suspended and the control signal is held as constant. Therefore, compared with the conventional MPC with finite control set (FCS-MPC), the ET-MPC method has the advantages of less computational burden and less switching actions, which contribute to lower switching losses, while ensuring satisfactory regulation performance. A buck converter prototype is adopted to validate the performance of ET-MPC. The results from the comparison with FCS-MPC demonstrate the effectiveness of the proposed ET-MPC method. [ABSTRACT FROM AUTHOR]

Objectives: To assess the agreement and reliability of DECT (dual-energy CT)-derived vBMD (volumetric bone mineral density) measurements from excised human femoral heads and to compare DECT-derived BMD with that measured by DXA (dual-energy X-ray absorptiometry) and QCT (quantitative CT) to determine its accuracy. Methods: Twenty patients that underwent total hip arthroplasty were enrolled to this study. Femoral heads were excised to rectangles without cortical bones for scanning. A dual-source DECT scanner generated images under 80/Sn140 kVp and 100/Sn140 kVp scanning conditions. Specimens were subsequently scanned by QCT and DXA to produce QCT-derived vBMD (mg/cm3) and DXA-derived BMM (bone mineral mass, g). DECT images were loaded to a post-processing workstation to calculate DECT-derived vBMD and BMM. Results: Higher DECT-derived vBMD and BMM were found under 80/Sn140 and 100/Sn140 kVp compared with those for QCT and DXA (p = 0.005). DECT-derived vBMD was highly correlated with QCT-derived vBMD (r = 0.961 ~ 0.993, p < 0.05). Similarly, DECT-derived BMM was strongly correlated with DXA-derived BMM (r = 0.927 ~ 0.943, p < 0.05). Agreement of the inter- and intra-observation of DECT-derived vBMD was excellent. Linear regression was carried out to calibrate DECT-derived vBMD of 80/Sn140 kVp (14 + 0.7 × DECT-derived vBMD) and 100/Sn140 kVp (74 + 0.4 × DECT-derived vBMD) with the reference of QCT-derived vBMD. After calibration, excellent agreement was found for vBMD and BMM within various imaging modalities. Conclusions: Our study showed that DECT-derived vBMD exhibited high agreement and reliability features, and after calibration, it also displayed a high degree of accuracy. However, in vivo studies are needed to extend its potential utility in clinical settings. Key Points: • Measurements of DECT-derived vBMD had high intra- and inter-observer agreement and reliability. • Measurements of DECT-derived vBMD and BMM had a high correlation with those derived from QCT and DXA. • DECT-derived vBMD and BMM were accurate after calibration compared with QCT and DXA. [ABSTRACT FROM AUTHOR]

The frequency threshold (FTH) is vital for the switching frequency regulation (SFR) of resonant dc–dc converters to restrain the fluctuation range of the output dc voltage and eliminate the low-voltage and overvoltage issues. Therefore, a step-by-step FTH design method is proposed in this article for a generalized resonant dc–dc converter. The mathematical model of the normalized voltage gain is established to reveal the function of the FTH in the SFR scheme. After then, combining the resonant circuit feature and the permitted fluctuation range of the output dc voltage, the specific upper and lower values of the FTH are derived within three steps. A design example is also detailedly presented to facilitate the proposed design. Experimental results verify the performance of the proposed step-by-step FTH design using a resonant converter prototype. [ABSTRACT FROM AUTHOR]

The multiwavelet scale multidimensional recurrence quantification analysis (MWMRQA) method is proposed in this paper, which is a combination of multidimensional recurrence quantification analysis and wavelet packet decomposition. It allows us to quantify the recurrence properties of a single multidimensional time series under different wavelet scales. We apply the MWMRQA method to the Lorenz system and the Chinese stock market, respectively, and show the feasibility of this method as well as the dynamic variation of the Lorenz system and the Chinese stock market under different wavelet scales. This provides another perspective for other disciplines that need to study the recurrence properties of different scales in the future. [ABSTRACT FROM AUTHOR]

In hybrid ac/dc microgrids, a bus converter system involving the use of a high-frequency dc transformer (DCT) plays a vital role to transmit power between dc and ac subgrids. However, the multiple control tasks and power transfer mode switching of bidirectional dc/ac converter create big challenges for the systematic controller design of DCT. To address this concern, a comprehensive coordinated frequency control (CCFC) is put forward in this article for the symmetrical CLLC-DCT to adapt the complicated hybrid ac/dc microgrid operation. By establishing the mathematical model on the voltage conversion gain (VCG) and active power transmission ratio (APTR), four operation modes are proposed based on power transfer conditions. The corresponding operators are derived based on the circuit feature to avoid the redundant manipulations. Frequency threshold is determined to avoid both overvoltage and low-voltage issues based on the known allowable range of VCG. The proposed CCFC scheme is detailedly realized by combining both the open-loop and closed-loop schemes to facilitate the design procedure. The prototype DCT demonstrates the proposed CCFC scheme can achieve a peak efficiency of 98.2% and satisfied performances on both VCG and APTR. [ABSTRACT FROM AUTHOR]

Background and aims: Tree species can produce litter with large variation in nitrogen to phosphorus (N:P) ratios. Here we examined how litter N:P ratios affected decomposer community composition and nutrient release for two contrasting tree species in the Qinling Mountains, China. Methods: Two-year-old Quercus aliena var. acuteserrata and Pinus tabulaeformis seedlings were fertilized using nutrient solutions with varying N:P ratios for four months. The obtained litters with contrasting N:P stoichiometry were left to decompose on nutrient-free quartz sand for 12 weeks with microbial inoculum. Then, the post-decomposition microbial community composition was determined using a phospholipid fatty acid (PLFA) analysis. Results: The Q. aliena litter stoichiometry was more homeostatic than P. tabulaeformis litter. Litter N:P ratio was significantly related to litter nutrient loss and mass loss for P. tabulaeformis but not always for Q. aliena. The soil microbial community compositions showed larger fungal to bacterial (F:B) ratios with increasing litter N:P ratios for Q. aliena but not P. tabulaeformis. Conclusion: Litter N:P ratio, as determined by species-specific homeostasis, showed an interspecific difference to affect the patterns of litter decomposition dynamics, as well as related soil microbial community composition. The less variation in the soil microbial community composition than plant litter stoichiometric characteristics during decomposition is likely an important mechanism that regulates the balance of biogeochemical cycles in the Qinling Mountains. [ABSTRACT FROM AUTHOR]

We used the multifractal detrended cross-correlation analysis (MFDCCA) method based on ensemble empirical mode decomposition (EEMD) to study the 5-min high-frequency data of two Chinese stocks and two US stocks. Using EEMD method to decompose the original high-frequency stock data can effectively reduce the interference of noise on the series, which helps to reveal the internal characteristics of the stock system and extract more accurate and rich information. We first conducted a cross-correlation test and cross-correlation coefficient analysis on the reconstructed stock data of two groups, and found that there is a cross-correlations between them. Then we used the EEMD-based MFDCCA method to analyze the cross-correlation between the data and found that there are significant cross-correlations between DJI and NASDAQ and between SSEC and SZSE. The cross-correlation of the two Chinese stocks is stronger than that of the two US stocks. The MFDCCA results of the comparison of the original series with the reconstructed series after decomposition by the EEMD method show that the reconstructed series can display more internal details of the multifractal cross-correlation metrics compared with the original series. [ABSTRACT FROM AUTHOR]

• MEC with FW as substrate can obtain high H 2 recovery under negative pressure. • MEC combined with AD enables a hydrogen production rate of 3.48 L/L/d. • MEC reactor for continuous hydrogen production by increasing acid conversion. • MEC can successfully increase the degree of solid reduction. Increased generation of food waste (FW) poses significant risks to the social environment, and therefore it is critical that efficient technology be developed for effective waste valorization. This study used an integrated reactor to combine single-chamber microbial electrolysis cell (MEC) treatment and anaerobic digestion (AD) to achieve efficient hydrogen recovery using FW as substrate. Hydrogen production during continuous AD-MEC operation (511.02 ml H 2 g−1 VS) was higher than that achieved by AD (49.39 ml H 2 g−1 VS). The hydrogen recovery and electrical energy recovery in AD-MEC were as high as 96% and 238.7 ± 5.8%, respectively. To explore the mechanism of hydrogen production increase, the main components of FW [lipids, volatile fatty acids (VFAs), carbohydrates, and protein] were analyzed to investigate the utilization of organic matter. Compared with AD treatment, the removal rates of carbohydrates and proteins in the soluble phase in AD-MEC were increased by 4 times and 2.3 times, respectively. The removal of VFAs by AD-MEC was increased by 4.7 times, which indicated that the AD reactor coupled with MEC technology improved the utilization of the main organic components and thus increased hydrogen production. This study demonstrates the possibilities of reducing FW quantities along with the production of bio-hydrogen. [ABSTRACT FROM AUTHOR]

For hybrid ac–dc microgrids, the widely applied high-frequency dc transformer (DCT) is usually scheduled to operate at resonant frequency with 50% duty-cycle-based semiregulated control to ensure the power transmission (PT), improve its power-density, and simplify the system-level control. However, for a real DCT, it may exist more than one resonant frequency that exhibit totally different features, which may seriously degrade the PT ability if the inappropriate switching frequency is selected. Meanwhile, the actual values of the DCT inductances and capacitances are also changing with the power, temperature, etc., which may lead to the practical resonant frequency's variation. Thus, how to select the suitable switching frequency to guarantee the PT ability against the parameter variation becomes a challenge. In this paper, three-step switching frequency selection criteria (SFSC) are proposed. A generalized CLLC-type DCT (GCLLC-DCT) model is extracted to make the proposed approach available for the LLC-, CLL-, symmetric CLLC-, and asymmetric CLLC-type topologies. For convenience, the definition of the active power transmission ratio (APTR) is introduced to help evaluate the PT ability. First, the number, value, and impact variables of the resonant frequency are derived and analyzed in Step I as the preliminary. Afterward, the optimum resonant frequency is confirmed for the GCLLC-DCT as the criterion based on the APTR in Step II. At last, the criterion in Step III is given to finally determine the switching frequency against the parameter variations. The proposed SFSC method is also validated by the experiments. [ABSTRACT FROM AUTHOR]

Asymmetrical CLLC-type dc transformers (ACLLC-type DCTs) are becoming more and more popular in the renewable energy system, thanks to the bidirectional power transmission (PT), high power density, and low-cost sensorless open-loop control. Nevertheless, the resonant frequency is not constant due to variations of the operation power and temperature in practice, which may make DCT lose its required voltage conversion gain and deteriorate the PT ability. This poses a challenge on the design of circuit parameters, especially when the open-loop scheme is usually recommended for the ACLLC-type DCT in the renewable energy system. Therefore, a semi-artificial intelligence (semi-AI)-based simplified parameter design approach is put forward in this paper for ACLLC-type DCT. It replaces all unknown parameters with two intermediate parameters through certain manipulations, and then utilizes a very simple computer-assisted procedure to optimally design the parameters of the ACLLC-type DCT. In addition, a detailed design example with a special planar transformer is presented via the aid of ANSYS Maxwell to achieve the desired resonant parameters of the ACLLC-type DCT. Finally, the proposed semi-AI-based method is experimentally demonstrated in a real renewable energy system prototype. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to develop a population pharmacokinetic (PPK) model to investigate the impact of GSTA1, GSTP1, and GSTM1 genotypes on busulfan pharmacokinetic (PK) variability in Chinese adult patients.Methods: Forty-three and 19 adult patients who underwent hematopoietic stem cell transplantation (HSCT) were enrolled for modeling group and validation group, respectively. All patients received twice-daily intravenous busulfan as part of conditioning regimen before HSCT. The PPK model was developed by nonlinear mixed-effect modeling. Covariates investigated were age, sex, actual body weight, body surface area, diagnoses, hepatic function markers, GST genotypes and conditioning regimen.Results: A total of 488 busulfan concentrations from 43 patients were obtained for the PPK model. The PK of intravenous busulfan was described by one-compartment model with first-order elimination with estimated clearance (CL) of 14.2 L/h and volume of distribution of 64.1 L. Inclusion of GSTA1 genotype as a covariate accounted for 1.1% of the inter-individual variability of busulfan CL (from 17.8% in the basic model to 16.7% in the final model). The accuracy and applicability of the final model were externally validated in the independent group. The difference of busulfan PK between Chinese patients and Caucasian patients existed because of the rarity of haplotype *B in Chinese population.Conclusions: Although the GSTA1 genotype-based PPK model of intravenous busulfan was successfully developed and externally validated, the GSTA1 genotype was not considered to be clinically relevant to busulfan CL. We did not suggest the guidance of GSTA1 genotype on initial busulfan dose in Chinese adult patients. [ABSTRACT FROM AUTHOR]

The myofibrillar protein (MP) extracted from Ctenopharyngodon idellus was used as a novel shell material for microencapsulation of tuna oil by using the complex coacervation method in the presence of κ- or λ-carrageenan. The optimum conditions for the complex coacervation process were found to be pH 5.0 and a 4:1 ratio of MP to carrageenan (κ- or λ-carrageenan). The occurrence of complexation between the biopolymers (liquid microcapsules) was compared to the final emulsion of individual MP and confirmed by confocal laser scanning microscopy (CSLM). After spray-drying, the obtained microcapsules were analyzed in terms of morphology, size, encapsulation efficiency (EE), surface oil (SO), encapsulation yield (EY), payload (PL), moisture content, hygroscopicity, wettability, solubility, flowability, color and oxidative stability. CSLM confirmed the occurrence of complexation between the biopolymers. The morphology of the resultant microcapsules was influenced by polymer type. The average size of all microcapsules was no more than 6.0 μm with EE, SO, EY and PL ranging from 91.11 to 98.65%, 0.01–0.07%, 82.67–99%, and 41.33–49.5%, respectively. When compared to the individual MP microcapsules, the complex coacervate microcapsules were lower in hygroscopicity and wettability, but higher in moisture content and solubility. The λ-carrageenan improved the solubility of microcapsules greatly, followed by κ-carrageenan. The optimal complex coacervate microcapsules performed better in protection against oxidative deterioration during storage. This research reveals MP as a promising microencapsulating agent for microencapsulation and protection of bioactive compounds, especially with κ- or λ-carrageenan as complex coacervates. Image 1 • Ctenopharyngodon idellus MP was used as wall material to produce microcapsules. • Physiochemical properties of microencapsulated powders were investigated. • λ-carrageenan and κ-carrageenan greatly improved microcapsule solubility. • Optimal pH and ratio of MP to κ- or λ-carrageenan were pH 5 and 4:1 (w/w). • Complex coacervate microcapsules enhanced tuna oil oxidative stability. [ABSTRACT FROM AUTHOR]

In a hybrid ac/dc microgrid, the symmetrical CLLC-type dc transformer (CLLC-DCT) generally operates at the resonant frequency with the simple and low-cost semi-regulated open-loop scheme to ensure the power transmission (PT). However, more than one resonant frequency may exist, and they feature different characteristics for DCT. Meanwhile, the practical resonant frequencies are varying with temperature and power, which will degrade the PT ability if the switching frequency selection is not considered. Therefore, a switching frequency selection criteria (SFSC) approach is put forward for the symmetrical CLLC-DCT. For convenience, the active PT ratio (APTR) is employed as evaluation index of SFSC. First of all, the number and accurate values of resonant frequency are achieved in Step I. Then, in Step II, the optimal resonant frequency is determined as APTR-based criterion. In Step III, the parameter-variation-based criterion is presented to determine switching frequency. Finally, the experimental results verify that the semiregulated DCT based on the proposed approach not only improves efficiency, but also achieves the approximate PT ability with the relatively high-cost closed-loop controlled DCT. [ABSTRACT FROM AUTHOR]

In order to obtain richer information on the cross-correlation properties between two time series, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). This method is based on the Hurst surface and can be used to study the non-linear relationship between two time series. By sweeping through all the scale ranges of the multifractal structure of the complex system, it can present more information than the multifractal detrended cross-correlation analysis (MF-DCCA). In this paper, we use the MM-DCCA method to study the cross-correlations between two sets of artificial data and two sets of 5 min high-frequency stock data from home and abroad. They are SZSE and SSEC in the Chinese market, and DJI and NASDAQ in the US market. We use Hurst surface and Hurst exponential distribution histogram to analyze the research objects and find that SSEC, SZSE and DJI, NASDAQ all show multifractal properties and long-range cross-correlations. We find that the fluctuation of the Hurst surface is related to the positive and negative of q , the change of scale range, the difference of national system, and the length of time series. The results show that the MM-DCCA method can give more abundant information and more detailed dynamic processes. [ABSTRACT FROM AUTHOR]

MXene basal planes are generally considered catalytically inert, due to the passivation by inactive surface groups. However, theoretical calculation predicates that MXene basal planes can become active by tuning its terminal groups. The above understandings are ambiguous on whether the MXene basal planes are indeed electrocatalytically active, and in turn what are the true active sites on MXene. Herein, we functionalized Ti 3 C 2 MXene by introducing terminal oxygen groups to reveal the active sites and probe the reaction mechanism for electrocatalytic nitrate reduction reaction (eNO 3 -RR). On the basis of the data presented, the in situ transformed surface hydroxyl groups were identified as a new active site for nitrate reduction. A novel reaction mechanism involving hydrogen-bonding (H-bonding) between nitrate and the -OH groups on the Ti 3 C 2 MXene basal plane was proposed, which adequately explained the high applied potentials and low selectivity for HER on the OH-terminated Ti 3 C 2 MXene during eNO 3 -RR. This hydrogen-bonding-mediated process is likely applicable to a wide range of other materials and reactions. [Display omitted] • In situ transformed surface hydroxyl groups were identified as a new active site for nitrate reduction. • Reaction mechanism involving hydrogen bonding on the Ti 3 C 2 MXene basal plane was proposed. • Hydrogen bonding-mediated process is likely applicable to a wide range of materials and reactions. [ABSTRACT FROM AUTHOR]

This study aimed to predict the area under the curve (AUC) of the initial busulfan dose using a test dose with the sparse sampling scheme in adult patients who underwent hematopoietic cell transplant. A test dose of 0.8 mg/kg busulfan was used 2 days before twice‐daily intravenous busulfan‐based conditioning regimens were administered. The AUC and the clearance (CL) were calculated for both the test dose and the first dose (AUCT, CLT, AUC1, and CL1) by noncompartmental analysis. The sparse sampling schemes of the test dose were developed by Bayesian method based on the population pharmacokinetic model. The optimal sparse sampling schemes were determined by evaluating the mean prediction error, the root mean square error, the absolute mean prediction error, and Bland‐Altman plot. The mean AUC1 was 7.20 ± 1.48 mg • h/L, which ranged from 4.70 to 9.46 mg • h/L. The AUC1 was below the therapeutic concentration of 7.38 mg • h/L in 45% (9 of 20) of the patients. The CLT of 3.05 ± 0.56 mL/min/kg was not significantly different with the CL1 of 3.03 ± 0.69 mL/min/kg (P =.901). A sampling scheme at 2 and 6 hours after the test dose was developed to predict the AUCT (mean prediction error of 1.64%, root mean square error of 6.17%, and absolute mean prediction error of 4.94%). Additionally, the Bland‐Altman plot showed that the 2‐sampling scheme provided an acceptably accurate prediction of the AUC1. A test dose with a 2‐sampling scheme was sufficient to personalize the initial busulfan dosing in hematopoietic cell transplant recipients. [ABSTRACT FROM AUTHOR]

Abstract We use multifractal detrended fluctuation analysis (MF-DFA) method to investigate the multifractal behavior of Shenzhen Component Index (SZSE) 5-minute high-frequency stock data from 2017.6.15 - 2018.4.11. We determine generalized Hurst exponent and singularity spectrum and find that these fluctuations have multifractal nature. In order to maintain the long-term memory of the stock , all 9696 data are divided into 6 units. According to the multifractal spectrum, the main parameters of the six units are obtained. Comparing the MF-DFA results for the original SZSE high-frequency time series with those for shuffled series, we conclude that the origin of multifractality is due to both the broadness of probability density function and long-range correlation. The generalized Hurst exponent obviously depend on the order of fluctuation function and change with it. The curve of scaling function clearly departs from a straight line, i.e. it shows clearly nonlinear property, and the multifractal spectrum displays the commonly observed bell shape. This will provide an important and theoretical foundation for researching the forecasting of finance markets. Highlights • Use MF-DFA to investigate the multifractal behavior of high-frequency SZSE. • Determine generalized Hurst exponent and singularity spectrum of SZSE. • All data are divided into 6 units and their main parameters are obtained. • Compare the MF-DFA results for the original SZSE with shuffled series. [ABSTRACT FROM AUTHOR]

Highlights • Boric acid compound was applied as complexing reagent to promote reservation of three vitamin Bs on the SPE column. • The SPE adsorbents were conductive polymer Polypyrrole (Ppy) electrospun nanofiber. • Rapid operation, high sensitivity and accuracy of this method were demonstrated. • The method was successfully applied in the determination of three urinary vitamin Bs. Abstract This paper put forward a prospective pre-cleanup method of packed-fiber solid phase extraction by using Polypyrrole (Ppy) electrospun nanofibers as the sorbent to simultaneously extract three water-soluble vitamins (i.e., folic acid, cyanocobalamin and riboflavin) in human urine. Primary extraction of target analytes was carried out by loading samples onto the column along with diphenylboronic acid 2-aminoethylester (DPBA) reagent, and then the column should be rinsed with DPBA solution for three times before eluting. The DPBA was innovatively applied as complexing reagent to retain as much of three analytes as possible on the column based on the multi interaction between three vitamins and the boronate affinity reagent, thus improving hydrophobicity of targets and adsorption efficiency through loading and rinsing steps. Under optimized conditions, sample concentration factor was five times with small amount of organic solvent consumed and recoveries between 84.9% to 125.4%, and the lowest detection limit (LOD) between 0.020 to 0.041 μg/mL were achieved. Finally, the urine samples from a group of healthy children were processed with the optimized method. It proved that the proposed method is applicable in the determination of urinary B-vitamins in big samples of people. [ABSTRACT FROM AUTHOR]

CLLC-type dc transformer (CLLC-DCT) is very popular in the hybrid ac–dc microgrid thanks to its high-power density advantage and good bidirectional power transfer capacity. In the hybrid ac/dc microgrid, the open-loop control is always utilized by the CLLC-DCT to cooperate with the bidirectional interlinking converter to realize the power and voltage conversion between the ac and dc bus. This paper first studies the circuit parameters design of the open-loop controlled CLLC-DCT with consideration of such a realistic problem: The real inductors/capacitors values are actually different with their theoretically designed values due to the operation power and temperature variation. To solve this problem, a robust circuit parameters design scheme is proposed for the CLLC-DCT in this paper. With the proposed scheme, the designed CLLC-DCT exhibits good power transmission and voltage regulation ability in the hybrid ac/dc microgrid even when its actual inductors/capacitors values vary with the practical power and temperature. The robust design method is experimentally verified in a hybrid ac/dc microgrid prototype. [ABSTRACT FROM AUTHOR]

Highlights • Gelation of myofibrillar protein-Na 4 P 2 O 7 ·10H 2 O or Na 5 P 3 O 10 (MP-SPP or STP) was studied. • Phosphate weakened MP network as instantaneous and retarded compliance rose at 4 and 40 °C. • MP changed from weak gel into concentrated sol as 280 mg/kg SPP or 440 mg/kg STP added. • Phosphate contributed to smaller pore size and finer structure for MP gel network. • Phosphate more tightly trapped immobile water into smaller-sized pores of MP network. Abstract Effect of phosphates on the heat-induced gel characteristics of myofibrillar protein (MP) from grass carp was investigated. Both heating and phosphates exerted significant influences. Heating induced more elastic, water-holding and less flowing gel. But phosphates had diverse effects at different temperatures. At 4 °C and 40 °C, phosphate as a dominant factor reduced the gel elasticity and resistance and increased flowability with increasing levels of phosphates. Furthermore, 280 mg/kg sodium pyrophosphate (SPP) or 440 mg/kg sodium triphosphates (STP) transformed MP from weak gel into concentrated solution. It clarified phosphates disentangled MP macromolecules and inhibited their aggregation and pre-gelation at low temperature. At 80 °C, heating accompanied with phosphates governed MP gelation. The appropriate level of phosphates (SPP superior to STP) endowed MP-phosphate gels with the lowest flowability and greatest elasticity, textural properties as well as finest microstructures. Besides, phosphates entrapped a portion of weak immobile water more tightly into smaller-sized pores of protein network. [ABSTRACT FROM AUTHOR]