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Jiaojiang sag in the East China Sea Basin is at the earlier exploration stage, where characterizing hydrocarbon generation of source rocks is important to understand oil-gas exploration potential. Utilizing geochemical and basin modeling analysis, hydrocarbon generation capacity and process of the Paleocene E 1 y , E 1 l and E 1 m formations were investigated. Results show that E 1 y and E 1 l mudstones are high-quality source rocks with Type II kerogen, which is dominated by both aquatic organisms and terrestrial higher plants deposited in sub-reduced environment. E 1 m mudstone interbedded with thin carbonaceous mudstone and coal is poor-quality source rock with Type III kerogen, whose organic matter was originated from terrestrial higher plants under oxidized environment. Controlled by burial and maturity histories, E 1 y and E 1 l source rocks experienced two hydrocarbon generation stages, which took place in the Late Paleocene and in the Middle to Late Eocene, respectively, and had high hydrocarbon generation capacity with cumulative hydrocarbon volume of 363 and 328 mg/g, respectively. E 1 m source rock only had one hydrocarbon generation process in the Late Eocene, which had low hydrocarbon generation capacity with cumulative hydrocarbon volume of only 24 mg/g. The future oil-gas exploration in the Jiaojiang sag should focus on hydrocarbon generation center and select targets in the central uplift formed before the Miocene with high-quality traps.

To study the adaptation of the current automobile design load of highway bridges in China in case of separation of passenger cars and trucks, a statistical method is proposed in this paper to study the load data of special lanes for trucks. Four typical truck-based lanes were selected as the study object, from which information of continuous truck fleet was selected as the study of truck-specific lane load flow samples, and technical parameters of truck vehicles were determined. Finally, the load flow was introduced into simply supported bridges and continuous bridges of different spans, and the load effect at the control section was calculated and compared with the effect of the design load at the control section according to the current code. The results show that under the operation mode of “passenger car and truck separation,” when the truck fleet passes through the simple support beam, the load effect at the control section generally does not exceed the effect of the vehicle load calculated according to the code design load. When the truck fleet passes through the continuous beam, the midspan bending moment of the continuous beam side span and the midspan bending moment of the middle span do not exceed the effect of the vehicle load calculated according to the code design load. However, the bending moment effect of the continuous beam support section exceeds the effect of the vehicle load calculated according to the design load of the code. To ensure the safety and durability of the bridge structure, the proposed lane load standard value is increased by 1.1 times and rounded up from the current Highway Bridge and Culvert Design Code.

Medium-depth geothermal energy mainly consists of two types, hydrothermal and dry-heat rock. With huge resource reserves, its exploration and development are of great significance to the transformation of China’s energy structure and the realization of the goal of “Double-Carbon”. From the differences in the electrical characteristics between hydrothermal and hot dry rock geothermal resources, this project uses the numerical modeling of the wide field electromagnetic (WFEM) method as a tool to design a model of typical geothermal resources. Then, we summarize and analyze the detection capability of the WFEM by calculating the WFEM response under the conditions of different depths, resistivity values, thickness-to-depth ratios and other parameters. Moreover, aiming at the key problems faced by the WFEM in real applications, we discuss the factors affecting the detection accuracy and give solutions to improve the reliability of the detection results. Finally, the medium-depth geothermal energy detection in the Jiyang Depression of Shandong is presented as an example, showing how the WFEM detection technique was used with the inversion result profile obtained. By comparing the results of geomagnetic and seismic detection on the same survey line, it is demonstrated that the WFEM method has great potential in the exploration of medium-depth geothermal energy and can be the preferred method.

BackgroundMinimal hepatic encephalopathy (MHE) is a complication of cirrhosis that affects patients’ cognitive function and quality of life (QOL). The psychometric hepatic encephalopathy score (PHES) is recommended for MHE diagnosis. Herein, we aimed to normalize the PHES based on a healthy Chinese population and investigate the prevalence and impact of MHE in patients with cirrhosis.MethodsThis prospective, multicenter study screened 1,728 healthy controls and 1,879 patients with cirrhosis from 40 hospitals in China. The PHES was first normalized by multivariate linear regression using the results of healthy controls and then used to diagnose MHE in patients with cirrhosis and linked with the QOL using the EuroQol 5-D (EQ-5D) questionnaire.ResultsAfter the screening, 1,428 healthy controls and 1,442 patients with cirrhosis were analyzed (IDDF2023-ABS-0075 Figure 1. Flow chart of the study population). The PHES norms were established using control results adjusted for age, sex, and education. MHE was diagnosed with a PHES score of <-4, which was noted in 24.2% of patients with cirrhosis. Further MHE prevalence analyses revealed that patients with decompensated cirrhosis (30.9%) vs. compensated cirrhosis (15.6%), patients with Child-Pugh grades B (29.4%) and C (29.9%) vs. Child-Pugh grade A (18.1%), and patients with high-risk varices (31.4%) vs. without high-risk varices (19.2%) all have significant differences (p < 0.05, for all) (IDDF2023-ABS-0075 Figure 2. Prevalence of minimal hepatic encephalopathy in different groups of patients with cirrhosis). The EQ-5D score revealed that MHE was associated with a significantly reduced QOL (p < 0.001) (IDDF2023-ABS-0075 Figure 3. Quality of life scores in patients with and without minimal hepatic encephalopathy).ConclusionsIn this largest study of MHE across rural and urban China, we found that a quarter of the subjects tested had MHE. MHE is associated with QOL decline and showed higher prevalence in patients with worse liver function and high-risk varices.Abstract IDDF2023-ABS-0075 Figure 1Flow chart of the study populationAbstract IDDF2023-ABS-0075 Figure 2Prevalence of minimal hepatic encephalopathy in different groups of patients with cirrhosisAbstract IDDF2023-ABS-0075 Figure 3Quality of life scores in patients with and without minimal hepatic encephalopathy

Minimal hepatic encephalopathy (MHE) has a substantial impact on the clinical outcomes and quality of life (QOL) of patients with cirrhosis. However, timely diagnosis and intervention are challenging due to sophisticated diagnostic methods. In this study, 673 healthy controls and 905 patients with cirrhosis were screened, and 660 healthy controls and 757 patients with cirrhosis, divided into the test (292 patients) and validation (465 patients) cohort, were analyzed after screening. A diagnostic model of the Stroop test (Stroop‐CN) was constructed by multivariate linear regression based on the results of healthy controls. The prevalence of MHE and the comparison results with psychometric hepatic encephalopathy score through the Stroop‐CN model were stable in the test and validation cohorts. Moreover, the prevalence of MHE remained significantly higher in patients with worse disease conditions marked as high Child–Pugh grades and the Model for End‐stage Liver Disease and Sodium (MELD‐Na) scores in the test and validation cohort. The EuroQol 5‐D questionnaire revealed that patients with MHE had a worse QOL than those without MHE both in the test and validation cohort. In conclusion, an easy and practical Stroop‐CN model for MHE diagnosis based on the EncephalApp is established. It is found that a considerable number of Chinese patients with cirrhosis experience MHE, which significantly impacts their QOL. The Stroop‐CN model was developed based on health control results and was used to identify MHE patients among cirrhotic patients. This subset of MHE patients had significantly lower quality of life than non‐MHE patients.

To develop and validate a machine learning prediction model for 28-day all-cause mortality in patients with alcoholic cirrhosis using data from the MIMIC-IV database. The data of 2134 patients diagnosed with alcoholic cirrhosis (AC) were obtained from Medical Information Mart for Intensive Care IV database. Machine learning algorithms, including decision trees, random forests, extreme gradient boosting, Logistic Regression and support vector machines were employed to develop the prediction model. The model was trained on 70% of the data and validated on the remaining 30% randomly. Performance was assessed using the area under the receiver operating characteristic curve, calibration curves and decision curve analysis (DCA). SHAP analysis was used to assess the marginal effects of each independent variable. The mean age was 56.2 years, and 69.5% were male. The primary factors associated with 28-day mortality included Age, SOFA score, ASPIII score, OASIS score, LODS score, Temperature, Chloride, Lactate, Total bilirubin (Tbil), international normalized ratio (INR), Activated partial thromboplastin time (Aptt), Stroke, Malignancy, Congenital coagulation defect (Ccd). The machine learning model demonstrated good predictive performance in the training and validation group, higher than traditional MELD score. Our machine learning prediction model effectively identifies patients with alcoholic cirrhosis at high risk of 28-day mortality. This model could assist clinicians in early risk stratification and guide clinical decision-making. Further validation in external cohorts is warranted to confirm its generalizability.

Aims Minimal hepatic encephalopathy (MHE) significantly affects the prognosis of patients with cirrhosis. This study was performed to determine whether there is a difference in the prevalence of MHE among patients with cirrhosis of different etiologies and whether the etiology directly influences the occurrence of MHE. Methods This multicenter, cross‐sectional study enrolled 1879 patients with confirmed cirrhosis at 40 hospitals from October 25, 2021, to January 10, 2023 (Trial registration: https://clinicaltrials.gov/[NCT05140837]). The patients' demographics, etiologies of cirrhosis, and laboratory test results were collected. The psychometric hepatic encephalopathy score (PHES) was determined in all patients to screen for MHE. Multivariate logistic analyses were performed to identify the risk factors for MHE. Results In total, 736 patients with cirrhosis were analyzed. The prevalence of MHE was 42.0% (n = 309). The primary etiology among all patients was hepatitis B virus (HBV)‐related cirrhosis (71.9% [529/736]). The prevalence of MHE was significantly higher in patients with alcoholic cirrhosis (57.1% [40/70]) than in those with HBV‐related cirrhosis (40.6% [215/529], p = 0.009) or hepatitis C virus (HCV)‐related cirrhosis (38.2% [26/68], p = 0.026). Age (odds ratio [OR], 1.042; 95% confidence interval [CI], 1.024–1.059; p < 0.001), duration of education (OR, 0.935; 95% CI, 0.899–0.971; p = 0.001), etiology (OR, 1.740; 95% CI, 1.028–2.945; p = 0.039), and high MELD‐Na scores (OR, 1.038; 95% CI, 1.009–1.067; p = 0.009) were independent risk factors for MHE. When patients with cirrhosis of different etiologies were analyzed separately, the results showed that age (OR, 1.035; 95% CI, 1.014–1.057; p = 0.001) and duration of education (OR, 0.924; 95% CI, 0.883–0.966; p = 0.001) were risk factors for MHE among patients with HBV‐related cirrhosis, whereas age (OR, 1.138; 95% CI, 1.033–1.254; p = 0.009) and creatinine concentration (OR, 16.487; 95% CI, 1.113–244.160; p = 0.042) were risk factors for MHE in patients with HCV‐related cirrhosis. No risk factors for MHE were found in patients with autoimmune cirrhosis. For patients with alcoholic cirrhosis, the platelet count (OR, 1.014; 95% CI, 1.000–1.027; p = 0.045) was a risk factor for MHE. The PHES subtest results were inconsistent among patients who had MHE with cirrhosis of different etiologies. Patients with HBV‐related cirrhosis performed better on Number Connection Test B and the serial dotting test than those with alcoholic cirrhosis (p = 0.007 and p < 0.001), better on Number Connection Test B than those with HCV‐related cirrhosis (p = 0.020), and better on the line tracing test than those with autoimmune cirrhosis (p = 0.037). Conclusion The etiology of cirrhosis affected the prevalence of MHE and risk factors for MHE. The domains of major cognitive impairment varied among patients with cirrhosis of different etiologies. Further studies are required to verify these findings. In this study, patients with cirrhosis of four etiologies underwent screening for minimal hepatic encephalopathy (MHE) using the psychometric hepatic encephalopathy score. The results showed that the etiology of cirrhosis affects the prevalence of MHE and that patients with different etiologies have different risk factors for MHE. The major areas of cognitive impairment varied among patients with cirrhosis of different etiologies, necessitating further research. Key points Significant findings of the study The etiology of cirrhosis affected the occurrence of minimal hepatic encephalopathy (MHE). Risk factors for MHE varied among patients with different etiologies. The domains of major cognitive impairment showed discrepancies among patients who had MHE with cirrhosis of different etiologies. What this study adds Etiology should be considered when performing routine clinical screening and monitoring of patients with cirrhosis. The domains of major cognitive impairment varied among patients with cirrhosis of different etiologies, warranting further studies.

To solve the true stress strain of Cr8 steel, a method of cone inversion is used to deal with the high temperature tensile data. Based on the precise determination and description of sample size, the test data is analyzed in the SSC(Stress strain calculator) software developed on MATLAB, and the true stress strain curve of Cr8 is drew. The true stress strain curve calculated by this method is smooth and continuous, and more identical to the principle of metal elastic-plastic deformation process, which shows a good promotion value.

A Newton iteration-based interval uncertainty analysis method （NI-IUAM） is proposed to analyze the propagating effect of interval uncertainty in multidisciplinary systems. NI-IUAM decomposes one multidisciplinary system into single disciplines and utilizes a Newton iteration equation to obtain the upper and lower bounds of coupled state variables at each iterative step. NI-IUAM only needs to determine the bounds of uncertain parameters and does not require specific distribution formats. In this way, NI-IUAM may greatly reduce the necessity for raw data. In addition, NI-IUAM can accelerate the convergence process as a result of the super-linear convergence of Newton iteration. The applicability of the proposed method is discussed, in particular that solutions obtained in each discipline must be compatible in multidisciplinary systems. The validity and efficiency of NI-IUAM is demonstrated by both numerical and engineering examples.

Aims::Minimal hepatic encephalopathy (MHE) significantly affects the prognosis of patients with cirrhosis. This study was performed to determine whether there is a difference in the prevalence of MHE among patients with cirrhosis of different etiologies and whether the etiology directly influences the occurrence of MHE.Methods::This multicenter, cross-sectional study enrolled 1879 patients with confirmed cirrhosis at 40 hospitals from October 25, 2021, to January 10, 2023 (Trial registration: https://clinicaltrials.gov/[NCT05140837]). The patients' demographics, etiologies of cirrhosis, and laboratory test results were collected. The psychometric hepatic encephalopathy score (PHES) was determined in all patients to screen for MHE. Multivariate logistic analyses were performed to identify the risk factors for MHE.Results::In total, 736 patients with cirrhosis were analyzed. The prevalence of MHE was 42.0% ( n = 309). The primary etiology among all patients was hepatitis B virus (HBV)-related cirrhosis (71.9% [