On-line multi-gas component measurement in the mud logging process based on Raman spectroscopy combined with a CNN-LSTM-AM hybrid model.

The qualitative and quantitative analysis of gas components extracted from drilling fluids during mud logging is essential for identifying drilling anomalies, reservoir characteristics, and hydrocarbon properties during oilfield recovery. Gas chromatography (GC) and gas mass spectrometers (GMS) are currently used for the online analysis of gases throughout the mud logging process. Nevertheless, these methods have limitations, including expensive equipment, high maintenance costs, and lengthy detection periods. Raman spectroscopy can be applied to the online quantification of gases at mud logging sites due to its in-situ analysis, high resolution, and rapid detection. However, laser power fluctuations, field vibrations, and the overlapping of characteristic peaks of different gases in the existing online detection system of Raman spectroscopy can affect the quantitative accuracy of the model. For these reasons, a gas Raman spectroscopy system with a high reliability, low detection limits, and increased sensitivity has been designed and applied to the online quantification of gases in the mud logging process. The near-concentric cavity structure is used to improve the signal acquisition module in the gas Raman spectroscopic system, thus enhancing the Raman spectral signal of the gases. One-dimensional convolutional neural networks (1D-CNN) combined with long- and short-term memory networks (LSTM) are applied to construct quantitative models based on the continuous acquisition of Raman spectra of gas mixtures. In addition, the attention mechanism is used to futher improve the quantitative model performance. The results indicated that our proposed method has the capability to continuously on-line detect 10 hydrocarbon and non-hydrocarbon gases in the mud logging process. The limitation of detection (LOD) for different gas components based on the proposed method are in the range of 0.0035%-0.0223%. Based on the proposed CNN-LSTM-AM model, the average detection errors of different gas components range from 0.899% to 3.521%, and their maximum detection errors range from 2.532% to 11.922%. These results demonstrate that our proposed method has a high accuracy, low deviation, and good stability and can be applied to the on-line gas analysis process in the mud logging field.

Clinical cure induced by pegylated interferon α-2b in the advantaged population of chronic hepatitis B virus infection: a retrospective cohort study.

Background: Among the advantaged population with clinical cure of chronic hepatitis B, chronic inactive hepatitis B virus carriers (IHCs) and nucleoside analog-experienced patients have similar serological manifestations. This study established non-interferon-treated groups as controls to compare the efficacy of pegylated interferon α-2b (Peg-IFNα-2b) in achieving clinical cure between IHCs and nucleoside analog (NA)-experienced patients. Method: A total of 270 patients were enrolled in this observational study. The IHC cohort comprised 55 patients who received Peg-IFNα-2b (Peg-IFN group), and the other 70 patients did not receive any antiviral treatment (untreated group). Patients treated with NAs were divided into two groups: one group (70 patients) receiving NA add-on Peg-IFNα-2b therapy regimen (NA add-on Peg-IFN group) and another group (75 patients) receiving continuous NA monotherapy (NA group). The primary endpoints were hepatitis B surface antigen (HBsAg) clearance and HBsAg seroconversion at 48 weeks and 72 weeks. Results: At 48 weeks, 65.5% (36/55) and 52.9% (37/70) patients achieved HBsAg clearance in the Peg-IFN group and NA add-on Peg-IFN group, respectively (p = 0.156). HBsAg seroconversion was achieved in 47.3% (26/55) of the Peg-IFN group and 34.3% (24/70) of the NA add-on Peg-IFN group (p = 0.141). At the follow-up of 72 weeks, 36 patients in the Peg-IFN group achieved HBsAg loss (65.5%, 36/55), and 33 patients in the NA add-on Peg-IFN group achieved HBsAg clearance (47.1%, 33/70), which were significantly higher than in the Peg-IFN group (p = 0.041). The HBsAg seroconversion rates in the Peg-IFN group and NA add-on Peg-IFN group at 72 weeks were 45.5% (25/55) and 32.9% (23/70), respectively (p = 0.151). No patient achieved HBsAg clearance or seroconversion in the NA group and untreated group. Furthermore, the receiver operating characteristic curve showed baseline HBsAg< 72 IU/mL, and the decline of HBsAg of more than 80% and 98% from baseline to 12 and 24 weeks provided good predictions for HBsAg clearance. Meanwhile, 77% of patients with baseline HBsAg< 100 IU/mL achieved a clinical cure at 48 weeks. Conclusion: Peg-IFNα-2b results in a high rate of HBsAg clearance and seroconversion in both IHCs and NA-experienced patients, especially for those patients who have HBsAg below 100 IU/mL.

Myeloarchitectonic Asymmetries of Language Regions in the Human Brain.

One prominent theory in neuroscience and psychology assumes that cortical regions for language are left hemisphere lateralized in the human brain. In the current study, we used a novel technique, quantitative magnetic resonance imaging (qMRI), to examine interhemispheric asymmetries in language regions in terms of macromolecular tissue volume (MTV) and quantitative longitudinal relaxation time (T1) maps in the living human brain. These two measures are known to reflect cortical myeloarchitecture from the microstructural perspective. One hundred and fifteen adults (55 male, 60 female) were examined for their myeloarchitectonic asymmetries of language regions. We found that the cortical myeloarchitecture of inferior frontal areas including the pars opercularis, pars triangularis, and pars orbitalis is left lateralized, while that of the middle temporal gyrus, Heschl's gyrus, and planum temporale is right lateralized. Moreover, the leftward lateralization of myelination structure is significantly correlated with language skills measured by phonemic and speech tone awareness. This study reveals for the first time a mixed pattern of myeloarchitectonic asymmetries, which calls for a general theory to accommodate the full complexity of principles underlying human hemispheric specialization.

Acupoint-brain (acubrain) mapping: Common and distinct cortical language regions activated by focused ultrasound stimulation on two language-relevant acupoints.

Acupuncture, taking the advantage of modality-specific neural pathways, has shown promising results in the treatment of brain disorders that affect different modalities such as pain and vision. However, the precise underlying mechanisms of within-modality neuromodulation of acupoints on human high-order cognition remain largely unknown. In the present study, we used a non-invasive and easy-operating method, focused ultrasound, to stimulate two language-relevant acupoints, namely GB39 (Xuanzhong) and SJ8 (Sanyangluo), of thirty healthy adults. The effect of focused ultrasound stimulation (FUS) on brain activation was examined by functional magnetic resonance imaging (fMRI). We found that stimulating GB39 and SJ8 by FUS evoked overlapping but distinct brain activation patterns. Our findings provide a major step toward within-modality (in this case, language) acupoint-brain (acubrain) mapping and shed light on to the potential use of FUS as a personalized treatment option for brain disorders that affect high-level cognitive functions.