Predicting acupuncture efficacy for functional dyspepsia based on functional brain network features: a machine learning study.

Acupuncture is effective in treating functional dyspepsia (FD), while its efficacy varies significantly from different patients. Predicting the responsiveness of different patients to acupuncture treatment based on the objective biomarkers would assist physicians to identify the candidates for acupuncture therapy. One hundred FD patients were enrolled, and their clinical characteristics and functional brain MRI data were collected before and after treatment. Taking the pre-treatment functional brain network as features, we constructed the support vector machine models to predict the responsiveness of FD patients to acupuncture treatment. These features contributing critically to the accurate prediction were identified, and the longitudinal analyses of these features were performed on acupuncture responders and non-responders. Results demonstrated that prediction models achieved an accuracy of 0.76 ± 0.03 in predicting acupuncture responders and non-responders, and a R2 of 0.24 ± 0.02 in predicting dyspeptic symptoms relief. Thirty-eight functional brain network features associated with the orbitofrontal cortex, caudate, hippocampus, and anterior insula were identified as the critical predictive features. Changes in these predictive features were more pronounced in responders than in non-responders. In conclusion, this study provided a promising approach to predicting acupuncture efficacy for FD patients and is expected to facilitate the optimization of personalized acupuncture treatment plans for FD.

Abnormal functional connectivity of the reward circuit associated with early satiety in patients with postprandial distress syndrome.

Postprandial distress syndrome (PDS) is the most common functional dyspepsia (FD) subtype. Early satiety is one of the cardinal symptoms of the PDS subtype in FD patients. The heterogeneity of symptoms in FD patients hampered therapy for patients based on specific symptoms, necessitating a symptom-based understanding of the pathophysiology of FD. To investigate the correlation between reward circuit and symptom severity of PDS patients, seed (Nucleus accumbens, NAc, a key node in the reward circuit) based resting-state functional connectivity (FC) was applied in the neuroimaging data analysis. The results demonstrated that the patients with PDS manifested strengthened FC between NAc and the caudate, putamen, pallidum, amygdala, hippocampus, thalamus, anterior cingulate cortex (ACC), and insula. Moreover, the FC between NAc and ACC, insula, thalamus, and hippocampus exhibited significant positive associations with symptom severity. More importantly, the strengthened FC between NAc and the ACC, insula, amygdala, and hippocampus were found associated with the early satiety symptom of patients with PDS. This study indicated that the altered FC of reward circuit regions may play a role in the pathophysiology of patients with PDS, and some of the aberrant NAc-based FC within the reward circuit were more related to the early satiety of patients with PDS. These findings improve our symptom-based understanding of the central pathophysiology of FD, lay the groundwork for an objective diagnosis of FD, and shed light on the precise prescription for treating FD based on symptoms.

Clinical-functional brain connectivity signature predicts longitudinal symptom improvement after acupuncture treatment in patients with functional dyspepsia.

Whilst acupuncture has been shown to be an effective treatment for functional dyspepsia (FD), its efficacy varies significantly among patients. Knowing beforehand how each patient responds to acupuncture treatment will facilitate the ability to produce personalized prescriptions, therefore, improving acupuncture efficacy. The objective of this study was to construct the prediction model, based on the clinical-neuroimaging signature, to forecast the individual symptom improvement of FD patients following a 4-week acupuncture treatment and to identify the critical predictive features that could potentially serve as biomarkers for predicting the efficacy of acupuncture for FD. Clinical-functional brain connectivity signatures were extracted from samples in the training-test set (100 FD patients) and independent validation set (60 FD patients). Based on these signatures and support vector machine algorithms, prediction models were developed in the training test set, followed by model performance evaluation and predictive features extraction. Subsequently, the external robustness of the extracted predictive features in predicting acupuncture efficacy was evaluated by the independent validation set. The developed prediction models possessed an accuracy of 88% in predicting acupuncture responders, as well as an R2 of 0.453 in forecasting symptom relief. Factors that contributed significantly to stronger responsiveness of patients to acupuncture therapy included higher resting-state functional connectivity associated with the orbitofrontal gyrus, caudate, hippocampus, and anterior insula, as well as higher baseline scores of the Symptom Index of Dyspepsia and shorter durations of the condition. Furthermore, the robustness of these features in predicting the efficacy of acupuncture for FD was verified through various machine learning algorithms and independent samples and remained stable in univariate and multivariate analyses. These findings suggest that it is both feasible and reliable to predict the efficacy of acupuncture for FD based on the pre-treatment clinical-neuroimaging signature. The established prediction framework will promote the identification of suitable candidates for acupuncture treatment, thereby improving the efficacy and reducing the cost of acupuncture for FD.

Subcortical-cortical functional connectivity as a potential biomarker for identifying patients with functional dyspepsia.

The diagnosis of functional dyspepsia (FD) presently relies on the self-reported symptoms. This study aimed to determine the potential of functional brain network features as biomarkers for the identification of FD patients. Firstly, the functional brain Magnetic Resonance Imaging data were collected from 100 FD patients and 100 healthy subjects, and the functional brain network features were extracted by the independent component analysis. Then, a support vector machine classifier was established based on these functional brain network features to discriminate FD patients from healthy subjects. Features that contributed substantially to the classification were finally identified as the classifying features. The results demonstrated that the classifier performed pretty well in discriminating FD patients. Namely, the accuracy of classification was 0.84 ± 0.03 in cross-validation set and 0.80 ± 0.07 in independent test set, respectively. A total of 15 connections between the subcortical nucleus (the thalamus and caudate) and sensorimotor cortex, parahippocampus, orbitofrontal cortex were finally determined as the classifying features. Furthermore, the results of cross-brain atlas validation showed that these classifying features were quite robust in the identification of FD patients. In summary, the current findings suggested the potential of using machine learning method and functional brain network biomarkers to identify FD patients.

Aberrant functional brain network dynamics in patients with functional constipation.

The aberrant static functional connectivity of brain network has been widely investigated in patients with functional constipation (FCon). However, the dynamics of brain functional connectivity in FCon patients remained unknown. This study aimed to detect the brain dynamics of functional connectivity states and network topological organizations of FCon patients and investigate the correlations of the aberrant brain dynamics with symptom severity. Eighty-three FCon patients and 80 healthy subjects (HS) were included in data analysis. The spatial group independent component analysis, sliding-window approach, k-means clustering, and graph-theoretic analysis were applied to investigate the dynamic temporal properties and coupling patterns of functional connectivity states, as well as the time-variation of network topological organizations in FCon patients. Four reoccurring functional connectivity states were identified in k-means clustering analysis. Compared to HS, FCon patients manifested the lower occurrence rate and mean dwell time in the state with a complex connection between default mode network and cognitive control network, as well as the aberrant anterior insula-cortical coupling patterns in this state, which were significantly correlated with the symptom severity. The graph-theoretic analysis demonstrated that FCon patients had higher sample entropy at the nodal efficiency of anterior insula than HS. The current findings provided dynamic perspectives for understanding the brain connectome of FCon and laid the foundation for the potential treatment of FCon based on brain connectomics.

Ultrasound assisted Fenton-like degradation of dyes using copper doped graphitic carbon nitride.

A novel copper doped graphitic carbon nitride (Cu-C3N4) was successfully synthesized and used as an effective Fenton-like catalyst. Cu-C3N4 was characterized by scanning electron microscopy, surface area analyzer, Fourier transform infrared spectroscopy, X-ray diffractometer, and X-ray photoelectron spectroscopy. Effect of process parameters including catalyst dosage, hydrogen peroxide (H2O2) concentration, solution pH, and initial methylene blue (MB) concentration was investigated to evaluate catalytic performance. The pseudo first-order kinetic model was used to describe the catalytic process. The enhancement of MB degradation is observed assisted by ultrasound. MB degradation of 96% is obtained within 30 min in Cu-C3N4/H2O2/ultrasound system, and the corresponding rate constant is 0.099 min-1. Effective MB degradation is obtained over a broad pH range (3.3-9.9). The catalytic mechanism is examined by ultraviolet-visible spectra, quenching test, and electron spin resonance determination. The dominant mechanism of MB degradation is ascribed to the ultrasonic H2O2 activation by Cu-C3N4 for hydroxyl radical generation. Cu-C3N4 has good reusability and is effective to degrade rhodamine B and acid orange 7. This work not only contributes to the field of wastewater treatment, but also provides insights into the synthesis of Fenton-like catalysts. The results manifest that Cu-C3N4 is a promising Fenton-like catalyst for dye degradation in the field of environmental pollution remediation.

Translocation kinetics and structural dynamics of ribosomes are modulated by the conformational plasticity of downstream pseudoknots.

Downstream stable mRNA secondary structures can stall elongating ribosomes by impeding the concerted movements of tRNAs and mRNA on the ribosome during translocation. The addition of a downstream mRNA structure, such as a stem-loop or a pseudoknot, is essential to induce -1 programmed ribosomal frameshifting (-1 PRF). Interestingly, previous studies revealed that -1 PRF efficiencies correlate with conformational plasticity of pseudoknots, defined as their propensity to form incompletely folded structures, rather than with the mechanical properties of pseudoknots. To elucidate the detailed molecular mechanisms of translocation and -1 PRF, we applied several smFRET assays to systematically examine how translocation rates and conformational dynamics of ribosomes were affected by different pseudoknots. Our results show that initial pseudoknot-unwinding significantly inhibits late-stage translocation and modulates conformational dynamics of ribosomal post-translocation complexes. The effects of pseudoknots on the structural dynamics of ribosomes strongly correlate with their abilities to induce -1 PRF. Our results lead us to propose a kinetic scheme for translocation which includes an initial power-stroke step and a following thermal-ratcheting step. This scheme provides mechanistic insights on how selective modulation of late-stage translocation by pseudoknots affects -1 PRF. Overall our findings advance current understanding of translocation and ribosome-induced mRNA structure unwinding.

Machine Learning in Neuroimaging: A New Approach to Understand Acupuncture for Neuroplasticity.

The effects of acupuncture facilitating neural plasticity for treating diseases have been identified by clinical and experimental studies. In the last two decades, the application of neuroimaging techniques in acupuncture research provided visualized evidence for acupuncture promoting neuroplasticity. Recently, the integration of machine learning (ML) and neuroimaging techniques becomes a focus in neuroscience and brings a new and promising approach to understand the facilitation of acupuncture on neuroplasticity at the individual level. This review is aimed at providing an overview of this rapidly growing field by introducing the commonly used ML algorithms in neuroimaging studies briefly and analyzing the characteristics of the acupuncture studies based on ML and neuroimaging, so as to provide references for future research.

Concurrent brain structural and functional alterations in patients with migraine without aura: an fMRI study.

OBJECTIVES: To explore the possible concurrent brain functional and structural alterations in patients with migraine without aura (MwoA) patients compared to healthy subjects (HS). METHODS: Seventy-two MwoA patients and forty-six HS were recruited. 3D-T1 and resting state fMRI data were collected during the interictal period for MwoA and HS. Voxel-based morphometry (VBM) for structure analysis and regional homogeneity (Reho) for fMRI analysis were applied. The VBM and Reho maps were overlapped to determine a possible brain region with concurrent functional and structural alteration in MwoA patients. Further analysis of resting state functional connectivity (FC) alteration was applied with this brain region as the seed. RESULTS: Compared with HS, MwoA patients showed decreased volume in the bilateral superior and inferior colliculus, periaqueductal gray matter (PAG), locus ceruleus, median raphe nuclei (MRN) and dorsal pons medulla junction. MwoA patients showed decreased Reho values in the middle occipital gyrus and inferior occipital gyrus, and increased Reho values in the MRN. Only a region in the MRN showed both structural and functional alteration in MwoA patients. Pearson correlation analysis showed that there was no association between volume or Reho values of the MRN and headache frequency, headache intensity, disease duration, self-rating anxiety scale or self-rating depression scale in MwoA patients. Resting state functional connectivity (FC) with the MRN as the seed showed that MwoA patients had increased FC between the MRN and PAG. CONCLUSIONS: MRN are involved in the pathophysiology of migraine during the interictal period. This study may help to better understand the migraine symptoms. TRIAL REGISTRATION: NCT01152632 . Registered 27 June 2010.

Temporal-spatial distribution and diastereoisomer pattern of hexabromocyclododecane in the vicinity of a chemical plant.

Hexabromocyclododecane (HBCD) is an effective brominated flame-retardant additive, which is mainly produced in the coastal area of China. This study collected soil samples from a HBCD production plant and its surrounding area in Weifang, Shandong Province, China, and analyzed the temporal-spatial distribution of HBCD and its diastereoisomers in soil. The analysis results showed that the concentration of HBCD in soil near the plant was much higher than normal values, with an annual average concentration reaching 5405 ng/g. Soils 1, 2 and 4 km away from the plant were also analyzed, showing that the concentration of HBCD in soil decreased accordingly with the distance from the pollution sources. In order to investigate the effect of the season on HBCD content, the soil samples were collected in all four seasons of the year 2017-2018. According to variations in the wind direction, the concentration of HBCD in soil was also changed. The distribution trend showed that the concentration of HBCD in soil in the downwind direction of the prevailing wind was higher than that in the upwind direction. In addition, this work analyzed the distribution of HBCD in vertical soil sections. It was found that the concentration of HBCD decreased with depth in the soil vertical profile. Finally, the various diastereoisomer patterns in the soil compartments were examined, finding that α-HBCD and γ-HBCD were the predominant diastereoisomers in the soil of the study area.

The Dysfunction of the Cerebellum and Its Cerebellum-Reward-Sensorimotor Loops in Chronic Spontaneous Urticaria.

Chronic spontaneous urticaria (CSU) is a common itchy skin disease. Despite its prevalence, the neuropathology of CSU is uncertain. In this study, we explored resting state functional connectivity (rs-FC) changes in CSU, as well as how the symptom changes following intervention can modulate rs-FC. Forty patients and 40 healthy controls (HCs) were recruited. Following an intervention, 32 patients participated in a second scan approximately 6 weeks after the first scan. Compared with healthy controls, CSU subjects exhibited higher regional homogeneity (ReHo) values in the cerebellum, which were positively associated with urticaria activity scores over 7 days (UAS7) at baseline. After an intervention accompanied with clinical improvement, we found that ReHo values decreased at the cerebellum and increased at the bilateral primary somatosensory cortex (SI)/primary motor cortex (MI)/supplementary motor area (SMA). Using the cerebellum as a seed, CSU subjects exhibited increased rs-FC with reward regions when compared with HCs and exhibited decreased rs-FC at the right orbitofrontal cortex and right sensorimotor region following the intervention. The improvement rate values were positively associated with reduced rs-FC values in the two regions. Using the cluster of SI/MI/SMA as a seed, CSU patients exhibited decreased rs-FC with the left putamen, caudate, accumbens, and thalamus following the intervention. These results demonstrate the altered cerebellar activity and cerebellum-reward-sensorimotor loops in CSU.

FlrA Represses Transcription of the Biofilm-Associated bpfA Operon in Shewanella putrefaciens.

Manipulation of biofilm formation in Shewanella is beneficial for application to industrial and environmental biotechnology. BpfA is an adhesin largely responsible for biofilm formation in many Shewanella species. However, the mechanism underlying BpfA production and the resulting biofilm remains vaguely understood. We previously described the finding that BpfA expression is enhanced by DosD, an oxygen-stimulated diguanylate cyclase, under aerobic growth. In the present work, we identify FlrA as a critical transcription regulator of the bpfA operon in Shewanella putrefaciens CN32 by transposon mutagenesis. FlrA acted as a repressor of the operon promoter by binding to two boxes overlapping the -10 and -35 sites recognized by σ70 DosD regulation of the expression of the bpfA operon was mediated by FlrA, and cyclic diguanylic acid (c-di-GMP) abolished FlrA binding to the operon promoter. We also demonstrate that FlhG, an accessory protein for flagellum synthesis, antagonized FlrA repression of the expression of the bpfA operon. Collectively, this work demonstrates that FlrA acts as a central mediator in the signaling pathway from c-di-GMP to BpfA-associated biofilm formation in S. putrefaciens CN32. IMPORTANCE: Motility and biofilm are mutually exclusive lifestyles, shifts between which are under the strict regulation of bacteria attempting to adapt to the fluctuation of diverse environmental conditions. The FlrA protein in many bacteria is known to control motility as a master regulator of flagellum synthesis. This work elucidates its effect on biofilm formation by controlling the expression of the adhesin BpfA in S. putrefaciens CN32 in response to c-di-GMP. Therefore, FlrA plays a dual role in controlling motility and biofilm formation in S. putrefaciens CN32. The cooccurrence of flrA, bpfA, and the FlrA box in the promoter region of the bpfA operon in diverse Shewanella strains suggests that bpfA is a common mechanism that controls biofilm formation in this bacterial species.

Single-Molecule Photoactivation FRET: A General and Easy-To-Implement Approach To Break the Concentration Barrier.

Single-molecule fluorescence resonance energy transfer (sm-FRET) has become a widely used tool to reveal dynamic processes and molecule mechanisms hidden under ensemble measurements. However, the upper limit of fluorescent species used in sm-FRET is still orders of magnitude lower than the association affinity of many biological processes under physiological conditions. Herein, we introduce single-molecule photoactivation FRET (sm-PAFRET), a general approach to break the concentration barrier by using photoactivatable fluorophores as donors. We demonstrate sm-PAFRET by capturing transient FRET states and revealing new reaction pathways during translation using µm fluorophore labeled species, which is 2-3 orders of magnitude higher than commonly used in sm-FRET measurements. sm-PAFRET serves as an easy-to-implement tool to lift the concentration barrier and discover new molecular dynamic processes and mechanisms under physiological concentrations.

Expression of a fungal manganese peroxidase in Escherichia coli: a comparison between the soluble and refolded enzymes.

BACKGROUND: Manganese peroxidase (MnP) from Irpex lacteus F17 has been shown to have a strong ability to degrade recalcitrant aromatic pollutants. In this study, a recombinant MnP from I. lacteus F17 was expressed in Escherichia coli Rosetta (DE3) in the form of inclusion bodies, which were refolded to achieve an active enzyme. Further, we optimized the in vitro refolding conditions to increase the recovery yield of the recombinant protein production. Additionally, we attempted to express recombinant MnP in soluble form in E. coli, and compared its activity with that of refolded MnP. RESULTS: Refolded MnP was obtained by optimizing the in vitro refolding conditions, and soluble MnP was produced in the presence of four additives, TritonX-100, Tween-80, ethanol, and glycerol, through incubation at 16 °C. Hemin and Ca2+ supplementation was crucial for the activity of the recombinant protein. Compared with refolded MnP, soluble MnP showed low catalytic efficiencies for Mn2+ and H2O2 substrates, but the two enzymes had an identical, broad range substrate specificity, and the ability to decolorize azo dyes. Furthermore, their enzymatic spectral characteristics were analysed by circular dichroism (CD), electronic absorption spectrum (UV-VIS), fluorescence and Raman spectra, indicating the differences in protein conformation between soluble and refolded MnP. Subsequently, size exclusion chromatography (SEC) and dynamic light scattering (DLS) analyses demonstrated that refolded MnP was a good monomer in solution, while soluble MnP predominantly existed in the oligomeric status. CONCLUSIONS: Our results showed that two forms of recombinant MnP could be expressed in E. coli by varying the culture conditions during protein expression.

[Diagnostic value and influencing factors for amplitude-integrated EEG in brain injury in preterm infants].

OBJECTIVE: To study the diagnostic value and influencing factors for amplitude-integrated EEG (aEEG) in brain injury in preterm infants. METHODS: One hundred and sixteen preterm infants with a gestational age (GA) between 27 weeks and 36(+6) weeks were enrolled as subjects. The aEEG scores of all preterm infants were obtained within 6 hours after birth. According to the diagnostic results, the 116 preterm infants were divided into two groups: brain injury (n=63) and non-brain injury (n=53). The risk factors for brain injury were evaluated using logistic regression analysis. According to the aEEG results, the 116 preterm infants were divided into two groups: normal aEEG (n=58) and abnormal aEEG (n=58). The influencing factors for aEEG results in preterm infants were determined using univariate analysis. RESULTS: The brain injury group had a significantly higher rate of abnormal aEEG than the non-brain injury group (83% vs 11%; P<0.05). The infants in the brain injury group from two different GA subgroups (27-33(+6) weeks and 34-36(+6) weeks) had significantly lower aEEG scores than the non-brain injury group from corresponding GA subgroups (P<0.01). Logistic regression analysis showed that low GA (<32 weeks), low birth weight (<1 500 g), abnormal placenta, fetal membranes, and umbilical cord, and hypertension during pregnancy were high-risk factors for brain injury (P<0.05). There were significant differences in GA, birth weight, abnormal placenta, fetal membranes, and umbilical cord, and hypertension during pregnancy between the normal and abnormal aEEG groups (P<0.05). CONCLUSIONS: The risk factors for brain injury are consistent with the influencing factors for aEEG results in preterm infants, suggesting that aEEG contributes to the early diagnosis of brain injury.

Prognostic value of blood GRHL2 in patients with non-small-cell lung cancer after radiotherapy and chemotherapy.

Aim: We aimed to investigate the predictive value of the Grainyhead-like 2 (GRHL2) expression from circulating blood for recurrence, metastasis and overall death on patients with non-small-cell lung cancer (NSCLC).Materials & Methods: We collected blood samples from 122 patients who were admitted to our hospital for NSCLC.Results: Multivariable Cox proportional-hazards analysis in adjusted Model II showed that compared with GRHL2-negative expression, positive expression in patients with NSCLC was associated with increased death risk (HR = 7.0, 95% CI: 2.1-20.9, p = 0.03) and risk for composite end point (HR = 8.2, 95% CI: 4.0-27.1, p <0.01).Conclusion: This study supported that elevated circulating GRHL2 expression might be considered as a candidate prognostic biomarker for poor prognosis among these NSCLC patients.

[Box: see text].

Implications of Pretreatment Serum Carcinoembryonic Antigen Levels and Perineural Invasion with Staging, Prognosis, and Management in Stage I-III Colon Cancer after Surgery: A Retrospective Cohort Study in the SEER Database.

BACKGROUND: Pretreatment levels of serum carcinoembryonic antigen (CEA) and perineural invasion (PNI) are related to poor prognosis in colon cancer. We analyzed the CEA and PNI (defined as incorporation of carcinoembryonic antigen and perineural invasion (CP)-stage), which are included in the Tumor-Node-Metastasis (TNM) staging system of the American Joint Committee on Cancer (AJCC), and evaluated the survival prognosis of patients treated with surgery in I-III stage colon carcinoma. MATERIALS AND METHODS: We employed a retrospective study for eligible colon carcinoma patients obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Kaplan-Meier curve and Multivariate Cox regression analysis were used to analyze different TNM-CP stages for the cancer-specific survival (CSS) probabilities in colon cancer. RESULT: In our study, CEA levels and PNI were significant prognostic factors (p < 0.05), and the newly proposed CP-stage was an independent prognostic index in stage I-III colon carcinoma after surgery. Multivariate Cox regression analyses indicated that CP1-stage was related to a 63.9% increased risk of cancer-specific mortality (hazard ratio (HR): 1.639, 95% confidence interval (CI): 1.544-1.739, p < 0.001), compared with CP0-stage in colon cancer. In respective TNM stages, the CP0-stage had an advantage over the CP1-stage for CSS (p < 0.001). Moreover, CP1-stage patients with node-negative colon cancer were contacted with similar or worse survival in comparison to CP0-stage patients with node-positive. CONCLUSION: For postoperative patients with stage I-III colon cancer, our study indicated that the CP stage is a significant prognostic factor for CSS, which deserves more clinical attention. It's worth noting that including the CP stage in the AJCC TNM staging system of colon carcinoma is beneficial to the survival prediction and clinical treatment.

Advancements in second-line treatment research for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, characterized by high incidence and mortality rates. Due to its insidious onset, most patients are diagnosed at an advanced stage, often missing the opportunity for surgical resection. Consequently, systemic treatments play a pivotal role. In recent years, an increasing number of drugs have been approved for first-line systemic treatment of HCC. However, their efficacy is limited, and some patients develop drug resistance after a period of treatment. For such patients, there is currently a lack of standard second-line systemic treatment options. This review summarizes the latest advancements in second-line systemic treatment research for HCC patients who have developed resistance to various first-line systemic treatments, aiming to provide more rational and personalized second-line treatment strategies.

Integration method of compressed sensing with variational mode decomposition based on gray wolf optimization and its denoising effect in mud pulse signal.

The continuous wave mud pulse transmission holds great promise for the future of downhole data communication. However, significant noise interference during the transmission process poses a formidable challenge for decoding. In particular, effectively eliminating random noise with a substantial amplitude that overlaps with the pulse signal spectrum has long been a complex issue. To address this, an enhanced integration algorithm that merges variational mode decomposition (VMD) and compressed sensing (CS) to suppress high-intensity random noise is proposed in this paper. In response to the inadequacy of manually preset parameters in VMD, which often leads to suboptimal decomposition outcomes, the gray wolf optimization algorithm is designed to obtain the optimal penalty factor and decomposition mode number in VMD. Subsequently, the optimized parameter combination decomposes the signal into a series of intrinsic modes. The mode exhibiting a stronger correlation with the original signal is retained to enhance signal sparsity, thereby fulfilling the prerequisite for compressed sensing. The signal is then observed and reconstructed using the compressed sensing method to yield the final signal. The proposed algorithm has been compared with VMD, CS, and CEEMD; the results demonstrate that the method can enhance the signal-noise ratio by up to ∼20.55 dB. Furthermore, it yields higher correlation coefficients and smaller mean square errors. Moreover, the experimental results using real field data show that the useful pulse waveforms can be recognized effectively, assisting surface workers in acquiring precise downhole information, enhancing drilling efficiency, and significantly reducing the risk of engineering accidents.

Failure probability analysis of high fill levee considering multiple uncertainties and correlated failure modes.

Such complex causative factors in current failure probability models are represented by simply random uncertainty and completely independent or correlation of failure modes, which can often limit the model utility. In this study, we developed a methodology to construct failure probability models for high fill levees, incorporating the identification of uncertainties and an analysis of failure modes. Based on quantification of stochastic-grey-fuzzy uncertainties, probability analysis involved with overtopping, instability and seepage failure modes was implemented combined with probability and non-probability methods. Given that the interaction among failure modes typically exhibits nonlinear behavior, rather than linear correlation or complete independence, a simple methodology for the binary Copula function was established and implemented in MATLAB. This methodology was applied to the high fill segments of a long-distance water transfer project characterized by high population density. It shows that the failure probability of a single failure mode is overestimated when uncertainties are not considered, because of the randomness and fuzziness of some parameters and the greyness of information. Meanwhile, it is found that the magnitude of failure probability related to levee breach is overestimated without respect to failure modes correlation, especially when the probabilities of seepage and instability are both significant and closely aligned.