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Abstract Purpose Despite the efforts of countless researchers to develop glioma treatment strategies, the current therapeutic effect of glioma is still not ideal, and it is necessary to further explore the mechanism to guide treatment. Thus, this study aims to introduce a novel approach for predicting patient prognosis and guiding further treatment interventions. Methods Initially, we conducted a differential gene expression analysis to identify Hippo pathway-associated genes overexpressed in tumors and determined genes correlated with prognosis. Subsequently, employing cluster analysis, we categorized samples into two groups and performed further analyses including prediction, immune cell infiltration abundance, and drug response rates. We utilized weighted gene co-expression analysis to reveal gene sets with high co-variation, delineate inter-sample gene correlation patterns, and conduct enrichment analysis. Prognostic models were built using ten machine learning algorithms combined in 101 different combinations, followed by evaluation and validation. Immune infiltration analysis, differential expression analysis of depleted T cell-related markers, drug sensitivity analysis, and exploration of pathway dysregulation were performed for different risk groups. Quality control and batch integration were performed, and single-cell data were analyzed using dimensionality reduction clustering algorithms and annotation tools to evaluate the activity of the prognostic model in malignant cells. Results We conducted data filtering to identify genes overexpressed in tumors, intersecting these genes with Hippo pathway-related genes, identifying 62 genes correlated with prognosis, and performing cluster analysis to divide tumor tissues into two groups. Cluster 2 exhibited a poorer prognosis and demonstrated differences in immune cell infiltration. Utilizing weighted gene co-expression analysis on Cluster 2, we identified gene modules, conducted functional enrichment analysis, and delineated pathways. Employing a combined model based on ten machine learning algorithm combinations, we selected the optimal prognostic model system and validated the model’s predictive ability within the dataset. Through immune-related analysis and drug sensitivity analysis, we uncovered differences in immune infiltration and varying sensitivities to chemotherapy drugs. Additionally, the enrichment analysis of gene set revealed discrepancies in upregulation within relevant pathways between the high and low-risk groups. Finally, annotation and evaluation of malignant cells via single-cell analysis showed increased activity of the prognostic model and variations in distribution across different prognostic levels in malignant cells. Conclusion This study introduces a novel approach utilizing the Hippo pathway and associated genes for glioma prognosis research, demonstrating the potential and significance of this method in evaluating the outcome for patients with glioma. These findings hold substantial clinical significance in guiding therapy and predicting outcomes for individuals diagnosed with glioma, offering significant clinical utility.

Abstract Disruption of ciliary homeostasis in vascular endothelial cells has been implicated in the development of atherosclerosis. However, the molecular basis for the regulation of endothelial cilia during atherosclerosis remains poorly understood. Herein, we provide evidence in male mice that the accumulation of lipid droplets in vascular endothelial cells induces ciliary loss and contributes to atherosclerosis. Triglyceride accumulation in vascular endothelial cells differentially affects the abundance of free fatty acid species in the cytosol, leading to stimulated lipid droplet formation and suppressed protein S-palmitoylation. Reduced S-palmitoylation of ciliary proteins, including ADP ribosylation factor like GTPase 13B, results in the loss of cilia. Restoring palmitic acid availability, either through pharmacological inhibition of stearoyl-CoA desaturase 1 or a palmitic acid-enriched diet, significantly restores endothelial cilia and mitigates the progression of atherosclerosis. These findings thus uncover a previously unrecognized role of lipid droplets in regulating ciliary homeostasis and provide a feasible intervention strategy for preventing and treating atherosclerosis.

This paper investigated the opportunities and challenges of integrating ports into hydrogen (H2) supply chains in the context of Australia and Japan because they are leading countries in the field and are potential leaders in the upcoming large-scale H2 trade. Qualitative interviews were conducted in the two countries to identify opportunities for H2 ports, necessary infrastructure and facilities, key factors for operations, and challenges associated with the ports’ development, followed by an online survey investigating the readiness levels of H2 export and import ports. The findings reveal that there are significant opportunities for both countries’ H2 ports and their respective regions, which encompass business transition processes and decarbonisation. However, the ports face challenges in areas including infrastructure, training, standards, and social licence, and the sufficiency and readiness levels of port infrastructure and other critical factors are low. Recommendations were proposed to address the challenges and barriers encountered by H2 ports. To optimise logistics operations within H2 ports and facilitate effective integration of H2 applications, this paper developed a user-oriented working process framework to provide guidance to ports seeking to engage in the H2 economy. Its findings and recommendations contribute to filling the existing knowledge gap pertaining to H2 ports.

Abstract Introduction Glioma, particularly glioblastoma (GBM), is a highly malignant brain tumor with poor prognosis despite current therapeutic approaches. The tumor microenvironment (TME), plays a crucial role in glioma progression by promoting invasion and drug resistance. Angiogenesis, the formation of new blood vessels, is a tightly regulated process involving endothelial cell activation, proliferation, and migration. In cancer, angiogenesis becomes dysregulated, leading to excessive blood vessel formation. Methods We enrolled bulk data of TCGA-LGG/GBM, CGGA-693, and CGGA-325 cohorts, scRNA data of GSE162631, GSE84465, and GSE138794 cohorts. Identification of malignant cells was conducted by “copycat” R package. The “AUCell” R package scored the activity of target gene set of each single cell. Consensus clustering was applied using the “ConsensusClusterPlus” R package, while tumor-infiltrating immune cells were determined using “IOBR” R package. To construct a prognostic model, we used LASSO and multiCOX algorithms based on the expression levels of the 15 hub genes, the efficacy of which was verified by KM and ROC analysis. Results We identified 4 different malignant cell subclusters in glioma and disclosed their distinct gene expression patterns and interactions within TME. We identified differentially expressed immune-related genes (DE-ARGs) in glioma and found 15 genes that were specifically expressed in the malignant glioma cell populations. Glioma cells with higher expression of these DE-ARGs were associated with gliogenesis, glial cell development, and vasculature development. We found that tumor-infiltrating monocytes were the main interacting cell type within glioma TME. Using the expression patterns of the 15 screened DE-ARGs, we categorized glioma samples into 2 molecular clusters with distinct immune features, suggesting a possible relationship between angiogenesis and immune activation and recruitment. We constructed a prognostic model based on the expression levels of the 15 DE-ARGs and evaluated its predictive ability for glioma patient outcomes, which displayed exceedingly high efficacy. Conclusion We characterized different malignant cell subclusters in glioma and investigate their gene expression patterns and interactions within TME. We constructed a prognostic model based on the expression levels of the 15 DE-ARGs and evaluated its predictive ability for glioma patient outcomes, which displayed exceedingly high efficacy.

Liquified natural gas (LNG) bunkering simultaneous operations (SIMOPs) refers to the operations (such as cargo operations, port activities and ship maintenance) occurring around LNG bunkering. SIMOPs pose new risks to LNG bunkering, because the operations are dynamically interlocked in which the occurrence probabilities of potential consequences change at different times due to commencement or completion of specific SIMOP events. However, traditional static risk assessment approaches are not able to take the dynamic nature of these new risks into account. This article proposes a dynamic quantitative risk assessment (DQRA) methodology based on the Bayesian network (BN) to develop better understanding of dynamic risks of LNG bunkering SIMOPs. The methodology is demonstrated and evaluated through a truck-to-ship LNG bunkering case study. The results and discussion of the case study validate the utility of the proposed methodology and demonstrate that BNs are efficient in performing the probability calculations and are flexible in conducting causal diagnosis. The main innovation of this work is realizing the quantification of risks at different times, which reflects the most essential time-changing characteristics of risks associated with LNG bunkering SIMOPs.

Abstract Objective Our research was designed to figure out the influence and mechanism of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitor on the improvement of elderly essential hypertension-induced vascular endothelial function impairment based on the JAK/STAT pathway. Methods Eighty-six elderly patients with essential hypertension were randomized into a control group (oral Amlodipine Besylate Tablets) and an observation group (oral Amlodipine Besylate Tablets + HMG-CoA reductase inhibitor atorvastatin calcium). Patients in both groups were treated with the drug for 12 weeks. Blood pressure, serum levels of inflammatory factors, and vascular endothelial function indicators, and levels of blood lipids were measured. The modeled rats were treated with atorvastatin calcium and a JAK/STAT pathway inhibitor (AG490), and the levels of cardiac function-related indices, left ventricular mass index, lipid levels, serum inflammatory factors and vascular endothelial function-related indices were detected in each group. Results HMG-CoA reductase inhibitor improved blood pressure levels, lipid levels, serum inflammatory factor levels and cardiac function in elderly patients with essential hypertension. Both HMG-CoA reductase inhibitor and AG490 improved blood pressure levels, lipid levels, serum inflammatory factor levels and cardiac function in SHR rats. Both HMG-CoA reductase inhibitor and AG490 decreased p-JAK2/JAK2 and p-STAT3/STAT3 expression levels. Conclusion Our study demonstrates that HMG-CoA reductase inhibitor improves elderly essential hypertension-induced vascular endothelial function impairment by blocking the JAK/STAT pathway.

The orchestration of cellular metabolism and redox balance is a complex, multifaceted process crucial for maintaining cellular homeostasis. Lipid droplets (LDs), once considered inert storage depots for neutral lipids, are now recognized as dynamic organelles critical in lipid metabolism and energy regulation. Mitochondria, the powerhouses of the cell, play a central role in energy production, metabolic pathways, and redox signaling. The physical and functional contacts between LDs and mitochondria facilitate a direct transfer of lipids, primarily fatty acids, which are crucial for mitochondrial β-oxidation, thus influencing energy homeostasis and cellular health. This review highlights recent advances in understanding the mechanisms governing LD–mitochondria interactions and their regulation, drawing attention to proteins and pathways that mediate these contacts. We discuss the physiological relevance of these interactions, emphasizing their role in maintaining energy and redox balance within cells, and how these processes are critical in response to metabolic demands and stress conditions. Furthermore, we explore the pathological implications of dysregulated LD–mitochondria interactions, particularly in the context of metabolic diseases such as obesity, diabetes, and non-alcoholic fatty liver disease, and their potential links to cardiovascular and neurodegenerative diseases. Conclusively, this review provides a comprehensive overview of the current understanding of LD–mitochondria interactions, underscoring their significance in cellular metabolism and suggesting future research directions that could unveil novel therapeutic targets for metabolic and degenerative diseases.

Abstract C−C bond forming reaction by alkylation of aryl rings is a main pillar of chemistry in the production of broad portfolios of chemical products. The dominant mechanism proceeds via electrophilic substitution of secondary and tertiary carbocations over acid catalysts, forming multiple aryl alkylation products non-selectively through all secondary and tertiary carbons in the alkyl chains but producing little α-C alkylation products because primary carbocations are poorly stable. Herein, we report that anatase TiO2 (TiO2-A) catalyzes nucleophilic α-C alkylation of phenols with alcohols in high selectivity to simply linear alkylphenols. Experimental and computational studies reveal the formation of Ti=C− bond with the α-carbon of the alkyl group at oxygen vacancies of the TiO2-A surface. The subsequent α-C alkylation by selective substitution of phenol ortho-C−H bond is verified by deuterium exchanged substrate and DFT calculations.

BackgroundPatients with intraventricular hemorrhage (IVH) are at a higher risk of developing hydrocephalus and often require external ventricular drainage or long-term ventriculoperitoneal shunt surgery.ObjectiveTo investigate whether cerebrospinal fluid drainage in patients with IVH due to aneurysmal subarachnoid hemorrhage (aSAH) reduces the incidence of chronic hydrocephalus.MethodA retrospective analysis was conducted on patients with aSAH treated at our hospital between January 2020 and December 2022. The first analysis compared patients with and without IVH, while the second analysis compared IVH patients with and without chronic hydrocephalus. The third analysis compared IVH patients who underwent in different drainage methods which is lumbar drainage (LD) or external ventricular drainage (EVD). The primary outcome measure was the incidence of chronic hydrocephalus.ResultOf the 296 patients hospitalized with aSAH, 108 (36.5%) had IVH, which was associated with a significantly higher incidence of chronic hydrocephalus compared to patients without IVH (49.1% vs. 16.5%, p

The purpose of this study was to explore the fermentation state and bacterial community structure of fermented grains during the stacking fermentation of Maotai-flavor Baijiu. The ''FD technology'' was applied to the stacking fermentation in second round of fermented grains production, and the changes of physicochemical factors and bacterial community in fermented grains during stacking fermentation were studied. Results showed that, compared with stacking fermentation of traditional fermented grains, the acidity of fermented grains of ''FD technology'' decreased by 1.72 mmol/10 g and the moisture content was kept to ±0.8%. The ''FD technology'' could effectively promote starch transformation (increased by 0.76%), and the reducing sugar content was increased by 0.46%. The Shannon, Sobs and Ace index of bacterial community in fermented grains increased significantly (P

Fractures of multi-scales and multi-origins are primary storage space and effective seepage channels for metamorphic buried-hill reservoirs. They not only allow communication between various pores to enhance storage and seepage capacity, but also are essential for high yields. Fracture development and controlling factors at metamorphic buried-hill reservoirs of Bozhong 19-6 Gas Field were investigated based on imaging log, core data, experiments, e.g., thin sections and scanning electron microscope, and outcrop description. Results show that structural fractures, weathering fractures and dissolution fractures were developed in the metamorphic buried-hill reservoirs in the study area, among which structural fractures and weathering fractures are the most popular ones. However, fracture types varied obviously among different structure positions. Lithology, fault, weathering crust and ancient landform are primary factors affecting fracture distribution. Fractures were prone to be developed at lithology with high bright mineral contents. Faults were characterized by a dual structure including fault core and damage zone. Fracture density followed a decreasing trend with increasing distance from faults. Damage zone could be identified when fracture density was consistent with regional fracture density. The width of the damage zone was determined by factors such as fault scale and structure location. Well-connected weathering fractures were popular at the leached unit, with structural fractures of secondary importance. The unweathered unit was dominated by structural fractures with low density.

Natural fractures are regarded as important reservoir spaces and effective seepage channels at metamorphic buried hills. Continuous networks associated with multi-scale fractures with good connectivity is critical for high-quality reservoirs as well as high and stable production in the tight metamorphic rocks. The multi-scale fractures in Bozhong 19–6 metamorphic buried hills were well characterized through integrating image logs, cores, thin-sections, and scanning electron microscope, etc. After that, power-law distribution of multi-scale fractures was established to understand contribution of fractures to reservoir quality and figure out structure models of fracture networks as well as their impact on production. Results show that parameters of fracture systems vary regularly with fracture scales. Fracture development degree, e.g., cumulative areal density, increases as a power law function with decreasing fracture size from macro to micro (e.g., aperture and/or length), where storage space associated with micro fractures is also increased. Reversely, fracture connectivity and permeability follow a significant decreasing trend. Five structure models of fracture network were established based on combination pattern of multi-scale fractures: multi-scale fracture network with high-density and multi-sets, large-scale fracture network with medium-density and multi-sets, small-scale fracture network with high-density and multi-sets, large-scale fracture network with low-density and multi-sets, and small-scale fracture network with low-density and single-set. The former two fracture networks can be widely developed into high-quality reservoirs, contributing greatly to high and stable yields. Fracturing is required for the third and the fourth fracture networks to obtain stable production, while it is difficult for the fifth fracture network to obtain industrial oil and gas flow.

Adopting proton exchange membrane fuel cells fuelled by hydrogen presents a promising solution for the shipping industry’s deep decarbonisation. However, the potential safety risks associated with hydrogen leakage pose a significant challenge to the development of hydrogen-powered ships. This study examines the safe design principles and leakage risks of the hydrogen gas supply system of China’s first newbuilt hydrogen-powered ship. This study utilises the computational fluid dynamics tool FLACS to analyse the hydrogen dispersion behaviour and concentration distributions in the hydrogen fuel cell room based on the ship’s parameters. This study predicts the flammable gas cloud and time points when gas monitoring points first reach the hydrogen volume concentrations of 0.8% and 1.6% in various leakage scenarios, including four different diameters (1, 3, 5, and 10 mm) and five different directions. This study’s findings indicate that smaller hydrogen pipeline diameters contribute to increased hydrogen safety. Specifically, in the hydrogen fuel cell room, a single-point leakage in a hydrogen pipeline with an inner diameter not exceeding 3 mm eliminates the possibility of flammable gas cloud explosions. Following a 10 mm leakage diameter, the hydrogen concentration in nearly all room positions reaches 4.0% within 6 s of leakage. While the leakage diameter does not impact the location of the monitoring point that first activates the hydrogen leak alarm and triggers an emergency hydrogen supply shutdown, the presence of obstructions near hydrogen detectors and the leakage direction can affect it. These insights provide guidance on the optimal locations for hydrogen detectors in the fuel cell room and the pipeline diameters on hydrogen gas supply systems, which can facilitate the safe design of hydrogen-powered ships.

ABSTRACT Importance There is a high incidence of iron deficiency in children worldwide. Notably, however, while iron deficiency is the most common cause of anemia, little is known about the prevalence and different types of iron deficiency in neuroblastoma patients. Objective The aim of the present study was to investigate the prevalence of iron deficiency in patients newly diagnosed with neuroblastoma. Methods A total of 195 newly diagnosed neuroblastoma patients from November 2015 to January 2018 were analyzed retrospectively. The survival analysis was estimated by the Kaplan‐Meier method. Results Of the 195 neuroblastoma patients included in the study, 121 (62.1%) had iron deficiency, 55 (28.2%) had absolute iron deficiency, and 66 (33.9%) had functional iron deficiency. Being aged ≥ 18 months, tumor originating in the abdomen, International Neuroblastoma Risk Group Staging System M, high‐risk neuroblastoma, lactate dehydrogenase ≥ 1500 U/L, neuron‐specific enolase ≥ 100 U/L, unfavorable histologic category, MYCN amplification, chromosome 1p loss, and bone marrow metastasis were associated with significantly higher rates of functional iron deficiency (P < 0.05). Interpretation Functional iron deficiency at the time of initial neuroblastoma diagnosis predicted lower event‐free survival. Long‐term effects of iron supplementation in neuroblastoma patients with different types of iron deficiency need to be further studied.

Abstract Background Neuroblastoma is the most common extracranial solid tumor of childhood. The high rate of recurrence is associated with a low survival rate for patients with high-risk neuroblastoma. There is thus an urgent need to identify effective predictive biomarkers of disease recurrence. Methods A total of 116 patients with high-risk neuroblastoma were recruited at Beijing Children’s Hospital between February 2015 and December 2017. All patients received multidisciplinary treatment, were evaluated for the therapeutic response, and then initiated on maintenance treatment. Blood samples were collected at the beginning of maintenance treatment, every 3 months thereafter, and at the time of disease recurrence. Plasma levels of cell-free DNA (cfDNA) were quantified by qPCR. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the ability of plasma cfDNA concentration to predict recurrence. Results Of the 116 patients, 36 (31.0%) developed recurrence during maintenance treatment. The median time to recurrence was 19.00, 9.00, and 8.00 months for patients who had achieved complete response (n = 6), partial response (n = 25), and stable disease (n = 5), respectively, after multidisciplinary treatment. The median plasma cfDNA concentration at the time of recurrence was significantly higher than the concentration in recurrence-free patients throughout maintenance treatment (29.34 ng/mL vs 10.32 ng/mL). Patients recorded a plasma cfDNA level ≥ 29 ng/mL an average of 0.55 months before diagnosis of disease recurrence. ROC analysis of the power of plasma cfDNA to distinguish between patients with or without recurrence yielded an area under the curve of 0.825, with optimal sensitivity and specificity of 80.6 and 71.3%, respectively, at a cfDNA level of 12.93 ng/mL. Conclusions High plasma cfDNA concentration is a potential molecular marker to signal disease recurrence in patients with high-risk neuroblastoma.

The median grain size of rock is the main basis for the identification of sedimentary facies, and the variation of the median grain size of rock can be used to obtain the stratum sedimentary rhythm and thus to classify the flow unit. Therefore, the median grain size of rock is an extremely important parameter for reservoir evaluation. However, there is no petrophysical method that can directly evaluate the median grain size of rock in the logging data. The predecessors used natural gamma logging data to calculate the median rock grain size (Md) based on linear and statistical analysis for medium-high porosity and permeability sandstone reservoirs work. However, for low-permeability sandstone reservoirs, the error in the fitted median grain size of rock using linear multiple regression methods is too large for the calculated results to be applied. Therefore, the calculation of the median grain size of low-permeability sandstone reservoirs is a difficult problem to be solved. In this paper, the sensitivity logging parameters of median rock grain size are optimized for low permeability sandstone reservoirs using principal component analysis obtained the grain size direction correlation curves (DEN, CNL,GR, and RD) in the study area, and the corresponding loss and activation functions are selected based on the learning characteristics of the nonlinear mapping of the logging data and the BP neural network to ensure that overfitting occurs. The best model was obtained by using decision tree, support vector machine, shallow and deep neural networks to model the median rock grain size and predict neighboring wells, and a comparative analysis showed that for the problem of predicting the median rock grain size in low-permeability sandstone reservoirs, the deep neural network improved significantly over the shallow one and was much stronger than other machine learning methods. The best model obtained a coefficient of determination (R2) of 0.9831. Machine learning of median grain size from conventional logging data was systematically carried out through conventional logging sensitivity curve optimization, algorithm modeling, network parameter optimization, median grain size prediction, and validation, and the relative error in its quantitative prediction met application requirements. This method takes into account the nonlinear mapping relationship between the logging data and the fitting of small sample data and provides a systematic way of thinking for the logging curve to predict the grain size of low-permeability sandstone.

The identification of the “sweet spot” of low-permeability sandstone reservoirs is a basic research topic in the exploration and development of oil and gas fields. Lithology identification, reservoir classification based on the pore structure and physical properties, and petrophysical facies classification are common methods for low-permeability reservoir classification, but their classification effect needs to be improved. The low-permeability reservoir is characterized by low rock physical properties, small porosity and permeability distribution range, and strong heterogeneity between layers. The seepage capacity and productivity of the reservoir vary considerably. Moreover, the logging response characteristics and resistivity value are similar for low-permeability reservoirs. In addition to physical properties and oil bearing, they are also affected by factors such as complex lithology, pore structure, and other factors, making it difficult for division of reservoir petrophysical facies and “sweet spot” identification. In this study, the logging values between low-porosity and -permeability reservoirs in the Paleozoic Es3 reservoir in the M field of the Bohai Sea, and between natural gamma rays and triple porosity reservoirs are similar. Resistivity is strongly influenced by physical properties, oil content, pore structure, and clay content, and the productivity difference is obvious. In order to improve the identification accuracy of “sweet spot,” a semi-supervised learning model for petrophysical facies division is proposed. The influence of lithology and physical properties on resistivity was removed by using an artificial neural network to predict resistivity R0 saturated with pure water. Based on the logging data, the automatic clustering MRGC algorithm was used to optimize the sensitive parameters and divide the logging facies to establish the unsupervised clustering model. Then using the divided results of mercury injection data, core cast thin layers, and logging faces, the characteristics of diagenetic types, pore structure, and logging response were integrated to identify rock petrophysical facies and establish a supervised identification model. A semi-supervised learning model based on the combination of “unsupervised supervised” was extended to the whole region training prediction for “sweet spot” identification, and the prediction results of the model were in good agreement with the actual results.

In order to reveal the reasons for the differences in initial water production characteristics of gas wells in different regions of the East China Sea Basin and to screen favorable targets for low-permeability reservoir reconstruction, a calculation method of initial production water–gas ratios at different gas column heights was established by combining gas-water two-phase capillary pressure with J function definition, power function relative permeability model and fractional flow equation. Then based on the experimental data of standard capillary pressure and standard relative permeability in the gas province of the East China Sea, an evaluation chart on initial production water–gas ratio of the East China Sea at different gas column heights was calculated and established. Finally, the evaluation chart was validated by using the data of the tested or commissioned gas wells in the gas reservoirs of the East China Sea, and the physical property conditions suitable for reservoir reconstruction of low-permeability gas reservoirs in the East China Sea were determined according to the evaluation chart. The following research results were obtained. First, the evaluation chart established in this paper reflects that the correlation between the parameters is similar to the actual production law and matches well with the actual data, which verifies the correctness and reliability of the chart establishment method and the key parameter calculation method. Second, with the production water–gas ratio less than 1 m3/104 m3 as the screening condition, for the permeability of the low-permeability gas reservoirs (with gas column height of about 50 m) in the west sub-sag, the central uplift belt and the periphery suitable for reservoir reconstruction shall be greater than 0.65 mD, and that of the large low-permeability gas reservoirs (with a gas column height of more than 100 m) in the north of central uplift belt shall be greater than 0.26 mD. Third, there is no gas–water contact in gas reservoirs under the hydrocarbon accumulation conditions of in-situ reservoirs, so the method and the evaluation chart proposed in this paper are not applicable. It is concluded that the method of establishing the initial water production evaluation chart and the method of calculating the key parameters proposed in this paper can provide meaningful reference for the development and evaluation of other gas fields in China. Keywords: China, East China Sea Basin, Gas reservoir, Capillary pressure, Relative permeability model, Water–gas ratio, Evaluation chart, Reservoir reconstruction, Parameter calculation

The International Maritime Organization (IMO) has set decarbonisation goals for the shipping industry. As a result, shipowners and operators are preparing to use low- or zero-carbon alternative fuels. The greenhouse gas (GHG) emission performances are fundamental for choosing suitable marine fuels. However, the current regulations adopt tank-to-wake (TTW) emission assessment methods that could misrepresent the total climate impacts of fuels. To better understand the well-to-wake (WTW) GHG emission performances, this work applied the life cycle assessment (LCA) method to a very large crude carrier (VLCC) sailing between the Middle East and China to investigate the emissions. The life cycle GHG emission impacts of using alternative fuels, including liquified natural gas (LNG), methanol, and ammonia, were evaluated and compared with using marine gas oil (MGO). The bunkering site of the VLCC was in Zhoushan port, China. The MGO and LNG were imported from overseas, while methanol and ammonia were produced in China. Four production pathways for methanol and three production pathways for ammonia were examined. The results showed that, compared with MGO, using fossil energy-based methanol and ammonia has no positive effect in terms of annual WTW GHG emissions. The emission reduction effects of fuels ranking from highest to lowest were full solar and battery-based methanol, full solar and battery-based ammonia, and LNG. Because marine ammonia-fuelled engines have not been commercialised, laboratory data were used to evaluate the nitrous oxide (N2O) emissions. The GHG emission reduction potential of ammonia can be exploited more effectively if the N2O emitted from engines is captured and disposed of through after-treatment technologies. This paper discussed three scenarios of N2O emission abatement ratios of 30%, 50%, and 90%. The resulting emission reduction effects showed that using full solar and battery-based ammonia with 90% N2O abatement performs better than using full solar and battery-based methanol. The main innovation of this work is realising the LCA GHG emission assessment for a deep-sea ship.

New international regulations aimed at decarbonizing maritime transportation are positively contributing to attention being paid to the use of liquefied natural gas (LNG) as a ship fuel. Scaling up LNG-fueled ships is highly dependent on safe bunkering operations, particularly during simultaneous operations (SIMOPs); therefore, performing a quantitative risk assessment (QRA) is either mandated or highly recommended, and a dynamic quantitative risk assessment (DQRA) has been developed to make up for the deficiencies of the traditional QRA. The QRA and DQRA are both data-driven processes, and so far, the data of occurrence rates (ORs) of basic events (BEs) in LNG bunkering SIMOPs are unavailable. To fill this gap, this study identified a total of 41 BEs and employed the online questionnaire method, the fuzzy set theory, and the Onisawa function to the investigation of the fuzzy ORs for the identified BEs. Purposive sampling was applied when selecting experts in the process of online data collection. The closed-ended structured questionnaire garnered responses from 137 experts from the industry and academia. The questionnaire, the raw data and obtained ORs, and the process of data analysis are presented in this data descriptor. The obtained data can be used directly in QRAs and DQRAs. This dataset is first of its kind and could be expanded further for research in the field of risk assessment of LNG bunkering.

The reservoir heterogeneity of Q oilfield is more severe after long-term water injection development, and water flooding is ineffective. In this study, the combined technologies of profile control, profile control and flooding, and oil displacement were proposed to improve the water flooding development effect. Then, the influence of the well pattern type on the remaining oil distribution, after development, was investigated. Cr3+ polymer gel, which has an optimal gel-forming effect, was used as the profile control agent. Moreover, the entire molecular structure had a “network” structure. A polymer microsphere was used as a profile control and flooding agent, which showed a good hydration expansion capacity. The initial particle size distribution had a range of 7.2–11.1 μm, and the expansion multiple was 4.35–5.64 after 7 days. The surfactant was an oil displacement agent, and the interfacial tension was approximately 5.08–5.11 × 10−1 mN/m. After the “profile control + profile control and flooding + oil displacement” technologies, the horizontal well pattern had a large seepage area. The effect of expanding the sweep volume was significant, and the remaining oil saturation in each stage was lower than those of the vertical and horizontal–vertical combined well patterns. Compared with the first water flooding stage, the remaining oil saturation values of the three permeable layers changed by 11.9%, 17.3%, and 19.8% during the subsequent water flooding stage.

Liquified natural gas (LNG) as a marine fuel has gained momentum as the maritime industry moves towards a sustainable future. Since unwanted LNG release may lead to severe consequences, performing quantitative risk assessment (QRA) for LNG bunkering operations has become mandatory according to some regulations. Human error is a main contributor to the risks, and the human error probabilities (HEPs) are essential for inclusion in a QRA. However, HEPs data are unavailable in the LNG bunkering industry so far. Therefore, this study attempts to infer HEPs through on-site safety philosophical factors (SPFs). The cognitive reliability and error analysis method (CREAM) was adopted as a basic model and modified to make it suitable for HEP assessment in LNG bunkering. Nine common performance condition (CPC) indicators were identified based on the fuzzy ranking of 23 SPF indicators (SPFIs). A Bayesian network (BN) was built to simulate the occurrence probabilities of different contextual control modes (COCOMs), and a conditional probability table (CPT) for the COCOM node with 19,683 possible combinations in the BN was developed according to the CREAM’s COCOM matrix. The prior probabilities of CPCs were evaluated using the fuzzy set theory (FST) based on data acquired from an online questionnaire survey. The results showed that the prior HEP for LNG bunkering is 0.009841. This value can be updated based on the re-evaluation of on-site SPFIs for a specific LNG bunkering project to capture the dynamics of HEP. The main innovation of this work is realizing the efficient quantification of HEP for LNG bunkering operations by using the proposed fuzzy BN-CREAM model.

LNG bunkering pontoons are presented to solve the fueling difficulty of LNG ships on inland waterways with a great variation of water height and channel width by seasonal change. First, the background of this concept was analyzed as well as the demand of LNG bunkering pontoons, and the involved idea of levels management. Then, from the safety barrier perspective, safety design principles were discussed, the safety principles and implement measures of LNG storage were provided, LNG tanks for the pontoon were analyzed in detail in terms of their types, design pressure, material selection and leakage protection principles. Also, the safety concerns of LNG supply and bunkering process were raised, and an improved handy bunkering arm & hose, lighter and more flexible than ever before, was introduced. Berthing and unberthing are related to the survival of the pontoon so that the key points of such design were highlighted. It is concluded that (1) based on the levels management, the pontoon equipped with IMO Type C tanks, with reasonable berthing/unberthing and safety designs adopted, is proved to be safe and reliable by practices; (2) by 2025, nearly 30 such improved LNG bunkering pontoons with a fueling capacity of 500 m3 each will be required on Yangtze and Pearl Rivers; and (3) the pontoon's safety and reliability has been verified by practices and its fourth generation has been developed. Keywords: LNG bunkering pontoon, Floating fueling station, LNG fuel, Storage, IMO type C tanks, Bunkering arm & hose, Technical security, Levels management

Ship-source air pollutants, especially sulphur oxides (SOx), have a major impact on human health, the marine environment and the natural resources. Therefore, control of SOx emissions has become a main concern in the maritime industry. The International Maritime Organization (IMO) has set a global limit on sulphur content of 0.50% m/m (mass by mass) in marine fuels which has entered into effect on 1 January 2020.To comply with the sulphur limits, ship owners are facing the need to select suitable abatement solutions. The choice of a suitable solution is a compromise among many issues, but the economic performance offers the basis for which ones are attractive to ship owners. Currently, there are three technologically feasible SOx abatement solutions that could be used by ships, namely, liquified natural gas (LNG) as a fuel (Solution A), scrubbers (Solution B) and low-sulphur fuel oil (LSFO) (Solution C). To compare the economic performances of the mentioned three solutions for a newbuilding very large crude carrier (VLCC), this paper proposes a voyage expenses-based method (VEM). It was found that, within the initial target payback period of 6 years, Solution A and C are more expensive than Solution B, while Solution C is more competitive than Solution A. Five scenarios of target payback years were assumed to compare the trends of the three proposed solutions. The results show that Solution B maintains its comparative advantage. As the assumed target payback years becomes longer, the economy of Solution A gradually improves and the economics of Solution B and C gradually decline. A comparison between Solution A and C shows 6.5 years is a turning point. The advantage of Solution A is prominent after this payback period. In addition, the performance of a certain solution in terms of adaptability to the IMO greenhouse gas (GHG) emissions regulations is also a factor that ship owner need to consider when making decisions. In conclusion, when the IMO air pollutant regulations and GHG regulations are considered simultaneously, the advantages of using LNG are obvious.

Fluvial reservoirs of the lower member of the Neogene Minghuazhen Formation in Q33-1 Oilfield, Bohai Bay Basin, are studied as examples to determine the distribution and characteristics of marginal reservoirs and develop offshore marginal oilfields effectively. Based on seismic, geological and logging data, three key technologies for the fluvial reservoir characterization of marginal reservoirs are proposed. The geometry and heterogeneity of fluvial sandbodies were studied through well-seismic calibration, 3D seismic interpretation and boundaries characterization. The geological knowledge database of fluvial reservoirs was established by the methods of width prediction outside wells and variogram analysis based on the high resolution 3D seismic data. Three types of well correlation modes of vertical facies changes, stacking sandbodies, incised channels, were constructed by integrating the analogous data from the oilfield with dense well pattern. According to the above three techniques of reservoir characterization, the most likely mode of reservoir distribution was established, based on which the oil field development plan was made and economic benefits have been gained. Key words: marginal oilfield, reservoir characterization, fluvial facies reservoir, 3D seismic, geological knowledge database, reservoir correlation mode

Background: Patients with intraventricular hemorrhage (IVH) are at a higher risk of developing hydrocephalus and often require external ventricular drainage or long-term ventriculoperitoneal shunt surgery. Objective: To investigate whether cerebrospinal fluid drainage in patients with IVH due to aneurysmal subarachnoid hemorrhage (aSAH) reduces the incidence of chronic hydrocephalus. Method: A retrospective analysis was conducted on patients with aSAH treated at our hospital between January 2020 and December 2022. The first analysis compared patients with and without IVH, while the second analysis compared IVH patients with and without chronic hydrocephalus. The third analysis compared IVH patients who underwent in different drainage methods which is lumbar drainage (LD) or external ventricular drainage (EVD). The primary outcome measure was the incidence of chronic hydrocephalus. Result: Of the 296 patients hospitalized with aSAH, 108 (36.5%) had IVH, which was associated with a significantly higher incidence of chronic hydrocephalus compared to patients without IVH (49.1% vs. 16.5%, p < 0.001). Multivariate logistic regression analysis showed that IVH was independently associated with the formation of chronic hydrocephalus (OR: 3.530, 95% CI: 1.958-6.362, p < 0.001). Among the 108 IVH patients, 53 (49.1%) developed chronic hydrocephalus. Multivariate logistic regression analysis revealed that the Hunt Hess grade at admission (OR: 3.362, 95% CI: 1.146-9.863, p = 0.027) and postoperative cerebrospinal fluid drainage (OR: 0.110, 95% CI: 0.036-0.336, p < 0.001) were independent risk factors for the development of chronic hydrocephalus in IVH patients. Among all IVH patients who underwent cerebrospinal fluid drainage, 45 (75%) received continuous lumbar puncture drainage, and 15 (25%) received external ventricular drainage. Univariate analysis did not show a statistically significant difference between the two groups in terms of postoperative chronic hydrocephalus (p = 0.283). However, multivariate logistic regression analysis suggested that the drainage methods of LD and EVD might be associated with the development of chronic hydrocephalus. Conclusion: The presence of IVH increases the risk of chronic hydrocephalus in patients with aSAH, and postoperative cerebrospinal fluid drainage appears to reduce this risk. The specific effects of lumbar puncture drainage and ventricular drainage on the incidence of chronic hydrocephalus require further investigation. [ABSTRACT FROM AUTHOR]