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"Yuan, Feng"
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On wall pressure fluctuations in conical shock wave/turbulent boundary layer interaction
The structure and the frequency spectra of wall pressure fluctuations beneath a planar turbulent boundary layer interacting with a conical shock wave at Mach number $M_\\infty =2.05$ and Reynolds number $\\textit {Re}_\\theta \\approx 630$ (based on the upstream boundary layer momentum thickness) are examined to elucidate the effects of pressure gradient and flow separation on the characteristics of the wall pressure fluctuations, by exploiting a direct numerical simulation database. Upstream of the interaction, in the zero pressure gradient region, wall pressure statistics compare well with canonical compressible boundary layers in terms of fluctuation intensities and frequency spectra. Across the main interaction zone (APG1), the root-mean-square of wall pressure fluctuations becomes very large (corresponding to approximately 173.3 dB), with maximum increase approximately 12.7 dB from the incoming level. In the second adverse pressure gradient zone (APG2), the root-mean-square of wall pressure fluctuations attains a second peak (corresponding to $164.7$ dB), with an increase of 8.4 dB from the upstream level. Both the APG1 and APG2 regions feature a substantial fraction of flow reversal events, which are, however, scattered and interspersed with regions of attached flow. The wall pressure power spectral density exhibits a broadband and energetic low-frequency component associated with the global unsteadiness of the separation bubble/conical shock system. Analysis of the two-point correlations and wavenumber/frequency spectra of wall pressure fluctuations further suggests that the typical eddies become more elongated along the spanwise direction, as the flow in the separated region tends to escape the centreline, and the convection velocity is significantly reduced.
Journal Article
Bank Green Credit Risk Assessment and Management by Mobile Computing and Machine Learning Neural Network under the Efficient Wireless Communication
The study is aimed at assessing and managing the green credit risk of banks, reduces the systemic risk in the financial industry, and improves the efficiency of the use of bank funds. With the development and evolution of efficient wireless data communication and transmission technology, the study combines theoretical and empirical green credit analysis to analyze listed companies in different industries quantitatively. The index system of credit risk assessment is established through wireless data transmission technology combined with mobile computing and machine learning neural networks. A back-propagation neural network (BPNN) model is confirmed by principal component analysis and factor analysis, and the performance of the model is verified with example data. The results show that the BPNN-based credit risk assessment model can provide 95% accuracy. In addition, 99% of the sample companies have low risk and no green credit risk. However, most companies in the coal industry are at greater risk. Overall, medium and high-risk companies accounted for 11.5%. Compared with other state-of-the-art models, the machine learning neural network adopted here has better data fitting and prediction accuracy, higher learning efficiency, and higher accuracy. The model established inefficient wireless communication is suitable for bank credit risk assessment and has good reference value and practical significance for bank credit risk assessment and management in different industries.
Journal Article
Fragile Phases as Affine Monoids: Classification and Material Examples
Topological phases in electronic structures contain a new type of topology, called fragile, which can arise, for example, when an elementary band representation (atomic limit band) splits into a particular set of bands. For the first time, we obtain a complete classification of the fragile topological phases, which can be diagnosed by symmetry eigenvalues, to find an incredibly rich structure that far surpasses that of stable or strong topological states. We find and enumerate hundreds of thousands of different fragile topological phases diagnosed by symmetry eigenvalues, and we link the mathematical structure of these phases to that of affine monoids in mathematics. Furthermore, for the first time, we predict and calculate (hundreds of realistic) materials where fragile topological bands appear, and we showcase the very best ones.
Journal Article
Internet-Based Cognitive Behavioral Therapy for Insomnia (ICBT-i) Improves Comorbid Anxiety and Depression—A Meta-Analysis of Randomized Controlled Trials
As the internet has become popularized in recent years, cognitive behavioral therapy for insomnia (CBT-i) has shifted from a face-to-face approach to delivery via the internet (internet-based CBT-i, ICBT-i). Several studies have investigated the effects of ICBT-i on comorbid anxiety and depression; however, the results remain inconclusive. Thus, a meta-analysis was conducted to determine the effects of ICBT-i on anxiety and depression. Electronic databases, including PubMed, EMBASE, PsycINFO and the Cochrane Library (throughout May 28, 2015), were systematically searched for randomized controlled trials (RCTs) of ICBT-i. Data were extracted from the qualified studies and pooled together. The standardized mean difference (SMD) and 95% confidence interval (95% CI) were calculated to assess the effects of ICBT-i on comorbid anxiety and depression. Nine records that included ten studies were ultimately qualified. The effect sizes (ESs) were -0.35 [-0.46, -0.25] for anxiety and -0.36 [-0.47, -0.26] for depression, which were stable using a between-group or within-group comparison and suggest positive effects of ICBT-i on both comorbid disorders. Although positive results were identified in this meta-analysis, additional high-quality studies with larger sample sizes are needed in the future.
Journal Article
Epidemiology and diagnosis technologies of human metapneumovirus in China: a mini review
Human metapneumovirus (HMPV) is a newly identified pathogen causing acute respiratory tract infections in young infants worldwide. Since the initial document of HMPV infection in China in 2003, Chinese scientists have made lots of efforts to prevent and control this disease, including developing diagnosis methods, vaccines and antiviral agents against HMPV, as well as conducting epidemiological investigations. However, effective vaccines or special antiviral agents against HMPV are currently not approved, thus developing early diagnosis methods and knowing its epidemiological characteristics will be beneficial for HMPV control. Here, we summarized current research focused on the epidemiological characteristics of HMPV in China and its available detection methods, which will be beneficial to increase the public awareness and disease control in the future.
Journal Article
Different regulatory mechanisms of plant hormones in the ripening of climacteric and non-climacteric fruits: a review
Key messageThis review contains the regulatory mechanisms of plant hormones in the ripening process of climacteric and non-climacteric fruits, interactions between plant hormones and future research directions.The fruit ripening process involves physiological and biochemical changes such as pigment accumulation, softening, aroma and flavor formation. There is a great difference in the ripening process between climacteric fruits and non-climacteric fruits. The ripening of these two types of fruits is affected by endogenous signals and exogenous environments. Endogenous signaling plant hormones play an important regulatory role in fruit ripening. This paper systematically reviews recent progress in the regulation of plant hormones in fruit ripening, including ethylene, abscisic acid, auxin, jasmonic acid (JA), gibberellin, brassinosteroid (BR), salicylic acid (SA) and melatonin. The role of plant hormones in both climacteric and non-climacteric fruits is discussed, with emphasis on the interaction between ethylene and other adjustment factors. Specifically, the research progress and future research directions of JA, SA and BR in fruit ripening are discussed, and the regulatory network between JA and other signaling molecules remains to be further revealed. This study is meant to expand the understanding of the importance of plant hormones, clarify the hormonal regulation network and provide a basis for targeted manipulation of fruit ripening.
Journal Article
Characterization of Free, Conjugated, and Bound Phenolic Acids in Seven Commonly Consumed Vegetables
Phenolic acids are thought to be beneficial for human health and responsible for vegetables’ health-promoting properties. Free, conjugated, and bound phenolic acids of seven commonly consumed vegetables, including kidney bean, cow pea, snow pea, hyacinth bean, green soy bean, soybean sprouts and daylily, from the regions of Beijing, Hangzhou, and Guangzhou, were identified and quantified by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Three vegetables, namely green soy bean, soybean sprouts, and daylily (Hemerocallis fulva L.), from the Beijing region contained higher concentrations of total phenolic acids than those from the Hangzhou and Guangzhou regions. The results indicated that the phenolic acid content in the seven vegetables appeared to be species-dependent. The highest content of phenolic acids was found in daylily, followed by green soy bean, while the least amounts were identified in kidney bean and hyacinth bean. Typically, phenolic acids are predominantly found in conjugated forms. Principle component analysis (PCA) revealed some key compounds that differentiated the seven vegetables. Green soy bean, compared to the other six vegetables, was characterized by higher levels of syringic acid, ferulic acid, vanillic acid, and sinapic acid. Other compounds, particularly p-coumaric acid, neochlorogenic acid, and caffeic acid, exhibited significantly higher concentrations in daylily. In addition, p-coumaric acid was the characteristic substance in cow pea. Results from this study can contribute to the development of vegetables with specific phytochemicals and health benefits.
Journal Article
The associations between depressive symptoms, functional impairment, and quality of life, in patients with major depression: undirected and Bayesian network analyses
Depressive symptoms, functional impairment, and decreased quality of life (QOL) are three important domains of major depressive disorder (MDD). However, the possible causal relationship between these factors has yet to be elucidated. Moreover, it is not known whether certain symptoms of MDD are more impairing than others. The network approach is a promising solution to these shortfalls.
The baseline data of a multicenter prospective project conducted in 11 governances of China were analyzed. In total, 1385 patients with MDD were included. Depressive symptoms, functioning disability, and QOL were evaluated by the 17-item Hamilton Depression Rating Scale (HAMD-17), the Sheehan Disability Scale (SDS), and the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF). The network was estimated through the graphical Least Absolute Shrinkage and Selection Operator (LASSO) technique in combination with the directed acyclic graph.
Three centrality metrics of the graphical LASSO showed that social life dysfunction, QOL, and late insomnia exhibited the highest strength centrality. The network accuracy and stability were estimated to be robust and stable. The Bayesian network indicated that some depressive symptoms were directly associated with QOL, while other depressive symptoms showed an indirect association with QOL mediated by impaired function. Depressed mood was positioned at the highest level in the model and predicted the activation of functional impairment and anxiety.
Functional disability mediated the relationship between depressive symptoms and QOL. Family functionality and suicidal symptoms were directly related to QOL. Depressed mood played the predominant role in activating both anxiety symptom and functional impairment.
Journal Article
Decoding endosperm endophytes in Pinus armandi: a crucial indicator for host response to climate change
Background
Plant-associated microorganisms significantly contribute to plant survival in diverse environments. However, limited information is available regarding the involvement of endophytes in responding to climate change and their potential to enhance host plants’ adaptation to future environmental shifts.
Pinus armandi
, endemic to China and widely distributed in climate-sensitive regions, serves as an ideal subject for investigating microbiome interactions that assist host plants in climate change response. Despite this, a comprehensive understanding of the diversity, community composition, and factors influencing endosperm endophytes in
P. armandi
, as well as the response of these endophytes to climate change, remains elusive.
Results
In this study, transcriptome data from 55
P. armandi
samples from 13 populations were analyzed to evaluate the composition and diversity of active endosperm endophytes and predict their response to future climate change. The results revealed variations in community composition, phylogenetic diversity, and interaction network between the northern and southern groups. Temperature and precipitation correlated with endosperm endophytic species richness and diversity. Under projected future climate conditions, the northern group exhibits greater genomic vulnerability and anticipates increased threats, reflecting a corresponding trend in endosperm endophytes, particularly within the Ascomycota community.
Conclusion
The consistent threat trend from climate change impacting both hosts and endophytes emphasizes the potential importance of host-related fungi as crucial indicators for predicting future climate impacts. Meanwhile, this study establishes an initial framework for exploring host-microbial interactions within the context of climate warming and provides valuable insights for studies related to plant protection.
Journal Article